Category Archives: Genetics

Biotechnology xpert Jamie Metzl addresses realities of genetics revolution, Feb. 9 – Vail Daily News

Progressing at breakneck speed, genetic engineering has seen significant advancements since the first time Jamie Metzl addressed the topic at the Vail Symposium in 2015 to a sold-out audience. Metzl will return today, offering the latest update on the science and implications of this world-changing technology.

Metzl, an annual speaker at the Symposium, is a senior fellow of the Atlantic Council and an expert on Asian affairs and biotechnology policy. He previously served as executive vice president of the Asia Society, deputy staff director of the U.S. Senate Foreign Relations Committee, senior coordinator for International Public Information at the U.S. State Department, director for multilateral affairs on the National Security Council and as a human-rights officer for the United Nations in Cambodia.

Also a novelist, Metzl explores the challenging issues raised by new technologies and revolutionary science in his science fiction writing. His latest novel, Eternal Sonata, imagines a future global struggle to control the science of extreme human life extension. This world, according to Metzl, is not far off.

Jamie Metzl is a brilliant thinker and eloquent speaker who will be discussing a captivating subject based very much in reality, said Kris Sabel, Vail Symposium executive director. His background in biotechnology allows him to understand this complex science, his experience with international affairs lets him place science in a geopolitical context and his dynamic and creative mind can break it all down into digestible information for everyone

Here, Metzl elaborates on the progress of the genetics revolution, his new book, how this unique science fits into the landscape of technological breakthroughs and how the new administration may impact scientific progress.

VAIL SYMPOSIUM: What sort of progress has the genetics revolution made since you first addressed the issue in front of the Vail Symposium audience two years ago?

METZL: The genetics revolution is charging forward at a blistering, exponentially accelerating pace. Virtually every day, major progress is being made deciphering the genome; describing gene-editing tools to alter the genetic makeup of plants, animals or even humans; and outlining how gene drives can be used to push genetic changes across populations. Even if this rate of change slows, then its absolutely clear to me that these new technologies will transform health care in the short to medium term and alter our evolution as a species in the medium to long term.

VS: Despite your scholarly background on the topic, youve again chosen to use science fiction writing as a way to encompass real issues surrounding the progress in genetics science. How does your new book, Eternal Sonata, based in 2025, two years after the setting of your first genetics thriller, Genesis Code, reflect the true pace, opportunities and consequences of genetic science?

METZL: The genetic revolution is too important to be left only or even primarily to the experts. I write nonfiction articles and spend a lot of time with expert groups, but the general public must be an equal stakeholder in the dialogue about our genetic future. I aspire for my novels to be fun and exciting, but also to help people who might be a little afraid of science find a more accessible on-ramp to thinking about the many complex, challenging human issues associated with technological innovation.

I fully believe well be seeing significant growth in human health and lifespans throughout the coming decades, but this progress will also raise some thorny questions well need to address. Like Genesis Code, its based on real science and tries to explore what it will mean on a human level when new technologies begin to transform our understanding of our own mortality.

VS: How much weight should society put on concerns and opportunities of genetics science, or actually making conscious alterations to humans as a species?

METZL: Advances in genetic technologies will help us live longer, healthier, more robust lives, and we should all be very, very excited about that. Like all technologies, however, there will also be new opportunities for abuse. Thats why we need to have the broadest, most inclusive global dialogue possible to help us develop new norms and standards that can guide our actions going forward. The technologies are new, but the best values we will need to deploy to use them wisely are old.

VS: Has there, then, been any progress in policy to regulate genetics science or legal framework created to limit the radical changes this could have on society?

METZL: There is a real mismatch between the rapid pace of scientific advancement and the glacial pace of regulation. On the one hand, we dont want over-regulation killing this very promising field in its relative infancy. On the other, it is clear that all aspects of altering the human genome must be regulated. This challenge is all the greater because different countries have different belief systems and ethical traditions, so there is a deep need for a global norm-creation and then regulatory harmonization process.

VS: Do you have any insight on how changes in the administration will affect progress in this field of science?

METZL: Many people are worried about how the new administration will deal with these very complex scientific issues. Viewing genetic technologies in the context of the abortion debate would be a significant blow to this work in the United States. But the science is global, and even if the U.S. shuts down all of its labs for ideological or other reasons, then the science will advance elsewhere. Well lose our lead building the future as we wait forever for the coal mining and low-end manufacturing jobs to come back.

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Biotechnology xpert Jamie Metzl addresses realities of genetics revolution, Feb. 9 - Vail Daily News

Genetics of Height is Way Complex, It Turns Out – KQED

When scientists first read out the human genome 15 years ago, there were high hopes that wed soon understand how traits like height are inherited. It hasnt been easy. A huge effort to find height-related genes so far only explains a fraction of this trait.

Now scientists say theyve made some more headway. And the effort is not just useful for understanding how genes determine height, but how theyre involved in driving many other human traits.

At first, these problems didnt seem to be so complicated. The 19th-century monk Gregor Mendel discovered that traits in his garden peas, like smoothness and color, could be passed predictably from one generation to the next.

But Joel Hirschhorn, a geneticist at Boston Childrens Hospital and the Broad Institute, says it became evident that most stories of inheritance were not so simple. Height turns out to be a prime example.

Peoples height didnt behave like Mendels peas, Hirschhorn says. It wasnt like they you had two tall people and theyd either have a tall [child] or a short [child]. Often the child was partway between the parents.

Scientists explained this 100 years ago, when they realized that height was influenced by many genes, and each makes a small contribution.

So when the human genome was sequenced, scientists like Hirschhorn thought they could plumb that data to track all the height genes, and finally understand how height and in fact most other human traits are shaped by our genes.

That effort started slowly. But now, Hirschhorn says, For height there are about 700 variants known to affect height, each of them usually with a pretty small effect on height, usually like a millimeter or less.

That massive global effort has involved studying the genes of more than 700,000 volunteer subjects. Even so, the traits theyve found only explain about a quarter of the inherited height factors.

And, frustratingly, for most of those variants scientists have no idea what they actually do.

Mostly the variants crop up in mysterious bits of DNA between genes on our chromosomes. That makes it hard to figure out their roles.

So Hirschhorn and his army of colleagues, who reported on the effort last weekin the journal Nature, tried a new tack.

Their study focused only on variants that are directly in the genes themselves. By knowing that the genes do, they can understand better how variants might influence height. For example, one is in a gene that influences hormones that regulate growth.

The variants within genes are uncommon, but some have a remarkably large influence on height.

We found some that, if you carry them, you might actually be an inch taller or an inch shorter, as opposed to just a millimeter difference that we found with the previous variants, Hirschhorn says.

Scientists are still very far from identifying all the genes involved with stature, but these new findings do help them better understand the natural biochemistry that influences height.

So far most of our understanding of height has come from scientists who study children who have abnormal growth patterns, according to Constantine Stratakis, a pediatrician and scientific director of the National Institute of Child Health and Human Development.

There are rare experiments of nature that have told us these genes are involved in the regulation of growth, he says. In fact, he discovered one of those rare genes, linked to a trait called gigantism.

It leads to babies that double or triple their length in the first year of life, he says.

These natural experiments have been most useful for treating height disorders, but Stratakis hopes that eventually the genome-search methods will provide leads for future treatments.

The bigger lesson here is figuring out how the biology of a complex trait like height really works.

Rare variants can sometimes make a big difference, but most of the time its all about systems that interact that define how an organism behaves, or grows, or has a disease, develops a trait and so on, Stratakis says. And although its humbling to see the complexity, at this point its not unexpected.

Hirschhorn and his colleagues are expanding their already massive study of 700,000 subjects. That approach has drawn skepticism from some scientists, who think its a waste of effort.

David Goldstein, a professor of genetics at Columbia University, says an expanded effort could ultimately implicate every gene in existence, and that hardly helps scientists narrow down the biological factors that contribute to height.

Its likely scientists will never be able to figure out what these hundreds of common variants do to influence height, Goldstein says. Instead, a much better strategy is what Hirschhorn used in this latest study: looking for rare variants that pack a big punch.

Hirschhorn is undeterred.

We probably wont get all of the way to explaining 100 percent of the genetic factors, but in some sense thats not really our goal, Hirschhorn says. Our goal is to use the genetics to do our best at understanding the biology.

To that end, Hirschhorn and his colleagues are not just looking at height; theyre digging into traits that make people susceptible to diabetes and obesity.

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Genetics of Height is Way Complex, It Turns Out - KQED

Fulgent Genetics to Announce Fourth Quarter and Full Year 2016 Financial Results on February 27, 2017 – GlobeNewswire (press release)

February 08, 2017 08:00 ET | Source: Fulgent Genetics, Inc.

TEMPLE CITY, Calif., Feb. 08, 2017 (GLOBE NEWSWIRE) -- Fulgent Genetics, Inc. (Nasdaq:FLGT) (Fulgent Genetics or thecompany) today announced that its fourth quarter and full year 2016 financial results will be released after market close on Monday, February 27, 2017 . The companys Chairman and Chief Executive Officer Ming Hsieh, its Chief Science officer Dr. Harry Gao, and its Chief Financial Officer Paul Kim will host an investment community conference call the same day at 5:00 PM ET (2:00 PM PT) to discuss the results and answer questions.

The call can be accessed through a live audio webcast in the Investor section of the companys website, http://www.fulgentgenetics.com, and through a live conference call by calling 1-855-321-9535, passcode # 65226206. An audio replay will be available in the investors section of the companys website or by calling 1-855-859-2056 through March 6, 2017.

About Fulgent Genetics

Fulgent Genetics is a rapidly growing technology company with an initial focus on offering comprehensive genetic testing to provide physicians with clinically actionable diagnostic information they can use to improve the overall quality of patient care. The company has developed a proprietary technology platform that integrates sophisticated data comparison and suppression algorithms, adaptive learning software, advanced genetic diagnostics tools and integrated laboratory processes. This platform allows the company to offer a broad and flexible test menu while maintaining accessible pricing, high accuracy and competitive turnaround times. The company believes its current test menu, which includes more than 18,000 single-gene tests and more than 275 pre-established, multi-gene, disease-specific panels, offers more genes for testing than its competitors in todays market, which enables it to provide expansive options for test customization and clinically actionable results.

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Fulgent Genetics to Announce Fourth Quarter and Full Year 2016 Financial Results on February 27, 2017 - GlobeNewswire (press release)

Scientists Discover 83 Genetic Mutations That Help Determine Your Height – Huffington Post

Ever wonder how much of your height you inherited from your parents?

A large-scale genetic study published recently in the journal Natureis helping shed some light on the factors that determine whether a person grows to be 6-feet-1 or 5-feet-2.

While scientists already had a good idea of the most common genetic factors that contribute to height, the new findings uncover a number of rare genetic alterations that can play a surprisingly major role in human growth.

Using data from the Genetic Investigation of Anthropometric Traits consortium (a group also known as GIANT), scientists from the Broad Instituteat MIT and Harvard analyzed genetic information from more than 700,000 people, discovering 83 DNA changes that play a part in determining a persons height.

In their previous work, the same research team identified nearly 700 common genetic factors linked with height. Now, theyve identified a number of rare genetic variants for human growth that have an even larger effect than most common factors. For some people, these rare DNA changes may account for height differences of up to a full inch.

Overall, common variants still contribute more to height than rare variants, Dr. Joel Hirschhorn, the studys lead author and a professor of pediatrics and genetics at Boston Childrens Hospital and Harvard Medical School, told The Huffington Post. But, for the person who happens to carry one of the rare variants, the impact can be much greater than for common variants. For the variants we looked at, this was up to almost an inch... as opposed to a millimeter or less for the common variants.

Using a new technology called the ExomeChip, the researchers were able to scan the genomes of large populations to find rare markers that correlated with a particular height. They identified 51 uncommon variants found in less than 5 percent of people, and 32 rare variants found in less than 0.5 percent of the population.

With the addition of these uncommon variants, geneticists can now account for 27 percent of the genetics determining height up from 20 percent based on earlier studies.

Heritability is by far the largest factor contributing to individual height.

Today, in places where most people get enough nutrition in childhood to grow to their potential, about 80 percent or more of the variability in height is due to genetic factors that we inherit from our parents, Hirschhorn explained.

According to the studys authors, this method of testing rare genetic variants could be used to investigate uncommon DNA changes involved in other aspects of human health.

Looking at rare variants in genes was helpful in understanding the biology of human growth, Hirschhorn said. With a big enough study, similar approaches could be valuable in understanding the biology of many diseases, which could help guide better treatments.

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Scientists Discover 83 Genetic Mutations That Help Determine Your Height - Huffington Post

Greengro Technologies, Inc. Launches Cannabis Genetics Breeding Initiative – GlobeNewswire (press release)

February 07, 2017 01:02 ET | Source: Greengro Technologies

Creates New Division Called GenoBreeding to Improve Cannabis Strains

ANAHEIM, Calif., Feb. 07, 2017 (GLOBE NEWSWIRE) -- Greengro Technologies, Inc. (OTC:GRNH), a world-class provider of eco-friendly green technologies, today launched a new internal company division called GenoBreeding that will direct a Greengro initiative to bring to the market cutting edge cannabis varieties through the application of modern plant breeding technologies.

This initiative from Greengro is in keeping with the cannabis industrys increasing reliance on genetics heredity and the variation of inherited characteristic in plants to help growers create better, more powerful and sometimes personalized commercial cannabis strains that share desirable inherited characteristics.

This initiative includes the use of conventional and modern plant breeding techniques to develop high quality cannabis varieties for medical use, said Greengro CEO James Haas.

Greengro is working with a team of specialized plant scientists and geneticists to develop cannabis varieties that possess improved levels of key compositional traits (e.g., THC and CBD) by using innovative breeding technologies, according to Haas, who said that Greengro has had its cannabis genetics program in development for a number of years.

Greengros GenoBreeding group is focused on developing breeding tools such as molecular markers to enable breeding decisions and processes to achieve top-tier plant performance in a sustainable manner.

Our collaboration through this initiative with leading scientists enables us to utilize proven crop breeding techniques in the indoor production of cannabis, while at the same time modernizing Greengros existing efforts to produce original products for Californias cannabis market, said Haas, who indicated that the GenoBreeding division will eventually be spun off into its own company.

Were developing market leading elite cannabis genetics with innovative breeding solutions, explained Haas.

Greengros GenoBreeding initiative combines elite cannabis genetics with state-of-the-art plant breeding methods to maximize yields and expression of desired traits. Key elements in the breeding program include:

The goal of Greengros GenoBreeding initiative in using applied genetics in cannabis production is to promote stability and predictability in hybridized strains. Stability refers to minimizing variability and maximizing predictability found in the offspring of parent plant generations.

Genetics is helping growers create better, more powerful and sometimes personalized commercial cannabis strains.

This process involves the cannabis genome (the complete set of genes and genetic material present in the plant), genotype (the plant's complete heritable genetic identity), and phenotype (the set of a strains expressed, observable characteristics resulting from the interaction of its genotype with the environment).

Variability, a consequence of strain genetic instability, refers to the range of different phenotypes that will express when hybridizing two different plant strains. Desirable predictability refers to the expected distribution ratio of a plants different phenotypes expressed as a unique strain.

About Greengro Technologies Greengro Technologies is a national leader in both indoor and outdoor aquaponic and hydroponic systems and grow rooms, with specific domain expertise in agricultural science systems serving both the consumer and commercial farming markets. The company's customers include restaurants, community gardens, and small- and large-scale commercial clients. For more up to date info like our Facebook page athttps://www.facebook.com/GreengroTechnologiesInc?ref=hl.

Disclaimer:The Company relies upon the Safe Harbor Laws of 1933, 1934 and 1995 for all public news releases. Statements, which are not historical facts, are forward-looking statements. The company, through its management, makes forward-looking public statements concerning its expected future operations, performance and other developments. Such forward-looking statements are necessarily estimates reflecting the company's best judgment based upon current information and involve a number of risks and uncertainties, and there can be no assurance that other factors will not affect the accuracy of such forward-looking statements. It is impossible to identify all such factors. Factors which could cause actual results to differ materially from those estimated by the company include, but are not limited to, government regulation; managing and maintaining growth; the effect of adverse publicity; litigation; competition; and other factors which may be identified from time to time in the company's public announcements.

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Greengro Technologies, Inc. Launches Cannabis Genetics Breeding Initiative - GlobeNewswire (press release)

Studies reveal link between rotator cuff disease and genetics – News-Medical.net

A new study presented this week at the Association of Academic Physiatrists Annual Meeting in Las Vegas shows rotator cuff disease might be a heritable trait.

Rotator cuff disease is a common disorder that affects 30 to 50 percent of people over the age of 50. The disease often leads to shoulder pain and loss of function. While many think of this as a 'tear' due to an injury or sustained over/misuse, some studies suggest genetics might play a role.

"People are living longer and more active lives, but a large percentage of these people may suffer from rotator cuff disease," explains Lead Investigator in the study, Dominique Dabija, MS, a medical student at Vanderbilt University School of Medicine. "Identifying a genetic link can help early recognition of individuals at higher risk and could warrant application of prevention strategies for this specific population.

To assess if there could be a genetic or familial predisposition to rotator cuff disease, Dabija along with Chan Gao, MD, PhD; Todd L. Edwards, MS, PhD; John Kuhn, MD, MS; and Nitin B. Jain, MD, MSPH, also from Vanderbilt University Medical Center looked through two databases (PubMed and EMBASE) that hold thousands of medical research studies to identify those using the term "rotator cuff." They searched all studies in the databases through March 2016 and narrowed down 251 citations to seven studies that were relevant to their literature review.

"Different studies on similar topics may produce different results depending on the specific methods and populations looked at," explains Dabija. "Our literature review compiles all of these studies to look at the data on a larger scale, and this allows us to identify macro trends as well as research gaps that need to be filled."

Four of the seven studies reviewed by Dabija's team assess whether there is a familial predisposition to rotator cuff disease. One of these found if an individual has a sibling with a rotator cuff tear, he or she is twice as likely to also have a tear and nearly five times more likely to have associated pain and loss of function. This is in comparison to if that individual did not have a sibling with a tear.

Another study reviewed by Dabija's team showed that a significantly higher number of individuals with tears (32.3 percent) had family members with a history of tears or surgery on their rotator cuffs than those without tears (18.3 percent).

A third study found if an individual is diagnosed with a rotator cuff tear before the age of 40, there is a higher likelihood that any of his or her family members immediate or extended will also have a tear. In contrast, if an individual is diagnosed with a rotator cuff tear after the age of 40, only close family members parents, siblings, grandparents, aunts/uncles have a higher likelihood of having a tear. This difference may also be attributed to environmental factors.

The other three studies investigated whether there is a genetic predisposition to rotator cuff disease, and these noted certain patterns of genes were found more often in people with rotator cuff disease when compared to those without rotator cuff disease.

"Although there was a small number of studies in this literature review pointing to a need for more studies on this topic the consensus among all seven studies is rotator cuff disease is a heritable trait," says Dabija. "More large-scale studies need to be performed, and these results can assist in identifying individuals at higher risk of developing a tear and then help them before they have pain."

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Geisinger Genetics Research Offers Big Health, Economic Impact for Central Pennsylvania – State College News

As Geisinger Health Systems MyCode genetics research initiative grows to more than 132,000 participants, the community is seeing results in more ways than one.

And now the MyCode project is helping serve as a springboard to local participation in a federal initiative that could pump $40 million to $50 million of government funds and bring numerous jobs into central Pennsylvanias economy in the years ahead.

The DNA of the first participants in the study that began in 2007 has been read, and 148 people were found to have gene mutations that put them at greater risk for developing certain diseases or conditions such as cancer, heart disease or dangerously high cholesterol.

One finding of particular note: The research so far suggests that the incidence of familial hypercholesterolemia, a genetic disorder characterized by high cholesterol, is much higher than previously believed. While national data has shown about one in 500 people affected by FH, the Geisinger data is showing about one in 225 to 250, according to Andy Faucett, director of policy and education with Geisingers Genomic Medicine Institute in Danville.

Were starting to be able to provide results that will guide research around the world, Faucett noted.

Findings like this are significant because they can help improve health care by finding ways to diagnose medical conditions earlier or before they appear and also to help find new treatments or medications to manage these diseases, according to Geisinger.

INFORMATION EMPOWERING

For patients, the information can also be empowering, said Miranda Hallquist, genetic counselor with the Genomic Medicine Institute in State College.

Knowing it is related to genetics frequency empowers them to take steps, Hallquist said, adding that were changing peoples health care, giving them information they would not otherwise have gotten as quickly.

The MyCode initiative includes a biobank that stores blood and saliva samples from Geisinger patients who have agreed to participate. Geisinger has already far surpassed its initial goal of 100,000 participants and has set its next goal at 250,000.

Consenters at various Geisinger facilities approach patents to see if they want to participate in the program, and to answer questions they might have. Patients can also sign up at http://www.mygeisinger.org. Participation is relatively simple, generally involving donation of an extra 2 tablespoons of blood at the patients next blood draw. Participants also allow Geisinger to access information in their medical records.

About 90 percent of patients asked have agreed to participate, according to Geisinger.

It surprised me how altruistic people in central Pennsylvania are, Faucett said. He noted that while the program is open to all ages, many participants are older because that age group tends to go to the doctor more.

People are more concerned not so much about the information for themselves, but for their children and grandchildren, he said.

Currently Geisinger has between 1 million and 1.4 million active patients, so we have talked with about 10 percent of the patient population, Faucett said. His goal is that every patient have the opportunity to participate.

GENETIC MARKERS

Of those who provide samples, about 4 percent will hear back because they have genetic markers that make them susceptible to a certain disease. Other participants do not hear back because nothing of concern was found in their DNA.

For those who are found to be at increased risk, meetings are scheduled to discuss the results and appropriate next steps, Hallquist said.

We talk about what the result means for them and their family members, she said.

Part of that education process, Hallquist said, means helping patients sort through the genetics gobbledygook.

For the 96 percent of participants whose genetics dont show increased risks, their data is still imperative to the research project, Hallquist said.

The turnaround time from MyCode samples to results can take a year or more. Hallquist said that while that process should get faster as more staff are added, she emphasized that MyCode is not a substitute for clinical testing for those with health concerns.

PRECISION MEDICINE INITIATIVE

Geisingers experience with the MyCode project helped it become one of four new health care provider organizations selected to participate in the federal Precision Medicine Initiative Cohort Program to help build a nationwide million-person study.

The PMI was launched by then President Barack Obama in 2015 to bring us closer to curing diseases like cancer and diabetes, and to give all of us access to the personalized information we need to keep ourselves and our families healthier.

Ultimately depending on final funding from the National Institutes of Health, the program could bring $40 million to $50 million to Geisinger over the course of five years, Faucett said. These funds will be used to recruit participants, providing multiple jobs throughout the Geisinger footprint. NIH provides funding on a yearly basis, he said.

Participants in the MyCode initiative will be approached about joining the PMI study as well, but it will ask more of patients than MyCode does, Faucett and Hallquist said.

Central Pennsylvania is fertile ground for such studies.

It is a very stable community, with patients willing to participate, Faucett said.

Additionally Geisinger officials noted that its electronic health records system goes back to the late 1990s.

For many families, we have three generations of patient records, Hallquist said. This includes an average of 14 years of health information for MyCode participants.

MyCode has allowed Geisinger to recruit amazing scientists, Faucett said. The types of research we are doing is growing every day.

Faucett sees a future in which physicians will order a patients genetic profile and use it to help guide care over a lifetime.

It was the MyCode project that brought Hallquist to Geisinger.

Precision medicine is the future, she said, while noting that healthy lifestyle choices are still as important as ever. Being able to look at someones DNA to help determine what their risks are, its spectacular that its moving in that direction.

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Geisinger Genetics Research Offers Big Health, Economic Impact for Central Pennsylvania - State College News

Seattle Genetics, Inc. (NASDAQ:SGEN) earnings reaction history – The Independent Republic

Seattle Genetics, Inc. (NASDAQ:SGEN) is projected to declare fiscal fourth quarter financial results right after the stock markets official close on February 09, 2017. The stock added about 22.4 percent in price since last results when it was at $49.93 a share. Based on the most relevant past-periods data, there is an 60.71 percent probability for this firms share price to go down following next quarterly results. Earnings reaction history tells us that the equity price moved down 17 times out of last 28 reported quarters. It has beaten earnings-per-share estimates 66% of the time in its last 12 earnings reports. It fell short of earnings estimates on 4 occasions, and it has met expectations 0 time.

Heres how traders responded to SGEN earnings announcements over the past few quarters.

Seattle Genetics, Inc. (SGEN) Earnings Surprises & Reaction

Given its history, the average earnings announcement surprise was 2.19 percent over the past four quarters. Back on October 27, 2016, it posted earnings per-share earnings at $-0.23 which beat the consensus $-0.29 projection (positive surprise of20.69%. For the quarter, revenue came in at 106.32M versus consensus estimate of 101.74M. The stock gained 1.84 percent the session following the earnings reports were released, and on 7th day price change was 14.16 percent.

On July 26, 2016, it reported earnings at $-0.23 a share compared with the consensus estimate of $-0.33 per share (positive surprise of 30.3%). Revenue of 95.4M for that quarter was above the $94.13M analysts had expected. The stock climbed 9.62% the day following the earnings announcement, and on 7th day price change was 10.85%.

On April 28, 2016, it recorded $-0.15 a share in earnings which missed the consensus estimate of $-0.11 (negative surprise of -36.36%). Revenue for the quarter was $111.15M while analysts called for revenues to be $116.04M. The stock dropped -4.85% the day following the earnings data was made public, and on 7th day price change was -10.91%.

On February 9, 2016, it announced earnings per share at $-0.18 versus the consensus estimate of $-0.17 per share (negative surprise of -5.88%). That came on revenues of $93.48M for that period. Analysts had expected $88.28M in revenue.

Seattle Genetics, Inc. Earnings Estimates

As Q4 earnings announcement date approaches, Wall Street is expecting earnings per share of $-0.31. The analysts present consensus range is $-0.42-$-0.25 for EPS. The market consensus range for revenue is between $91.86M and $117.07M, with an average of $106.17M.

Seattle Genetics, Inc. (NASDAQ:SGEN) last ended at $61.11, sending the companys market cap near $8.65B. The consensus 12-month price target from analysts covering the stock is $58.79. The share price has declined -18.91% from its top level in 52 weeks and dropped 15.8% this year. It recently traded in a range of $59.57-$61.16 at a volume of 444485 shares. The recent trading ended with the price nearly 4.48 higher for the last 5 trading days, rebounding 134.86% from its 52-week low.

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Seattle Genetics, Inc. (NASDAQ:SGEN) earnings reaction history - The Independent Republic

Genetics of Breast and Gynecologic Cancers (PDQ)Health …

Executive Summary

This executive summary reviews the topics covered in this PDQ summary on the genetics of breast and gynecologic cancers, with hyperlinks to detailed sections below that describe the evidence on each topic.

Breast and ovarian cancer are present in several autosomal dominant cancer syndromes, although they are most strongly associated with highly penetrant germline pathogenic variants in BRCA1 and BRCA2. Other genes, such as PALB2, TP53 (associated with Li-Fraumeni syndrome), PTEN (associated with Cowden syndrome), CDH1 (associated with diffuse gastric and lobular breast cancer syndrome), and STK11 (associated with Peutz-Jeghers syndrome), confer a risk to either or both of these cancers with relatively high penetrance.

Inherited endometrial cancer is most commonly associated with LS, a condition caused by inherited pathogenic variants in the highly penetrant mismatch repair genes MLH1, MSH2, MSH6, PMS2, and EPCAM. Colorectal cancer (and, to a lesser extent, ovarian cancer and stomach cancer) is also associated with LS.

Additional genes, such as CHEK2, BRIP1, RAD51, and ATM, are associated with breast and/or gynecologic cancers with moderate penetrance. Genome-wide searches are showing promise in identifying common, low-penetrance susceptibility alleles for many complex diseases, including breast and gynecologic cancers, but the clinical utility of these findings remains uncertain.

Breast cancer screening strategies, including breast magnetic resonance imaging and mammography, are commonly performed in carriers of BRCA pathogenic variants and in individuals at increased risk of breast cancer. Initiation of screening is generally recommended at earlier ages and at more frequent intervals in individuals with an increased risk due to genetics and family history than in the general population. There is evidence to demonstrate that these strategies have utility in early detection of cancer. In contrast, there is currently no evidence to demonstrate that gynecologic cancer screening using cancer antigen 125 testing and transvaginal ultrasound leads to early detection of cancer.

Risk-reducing surgeries, including risk-reducing mastectomy (RRM) and risk-reducing salpingo-oophorectomy (RRSO), have been shown to significantly reduce the risk of developing breast and/or ovarian cancer and improve overall survival in carriers of BRCA1 and BRCA2 pathogenic variants. Chemoprevention strategies, including the use of tamoxifen and oral contraceptives, have also been examined in this population. Tamoxifen use has been shown to reduce the risk of contralateral breast cancer among carriers of BRCA1 and BRCA2 pathogenic variants after treatment for breast cancer, but there are limited data in the primary cancer prevention setting to suggest that it reduces the risk of breast cancer among healthy female carriers of BRCA2 pathogenic variants. The use of oral contraceptives has been associated with a protective effect on the risk of developing ovarian cancer, including in carriers of BRCA1 and BRCA2 pathogenic variants, with no association of increased risk of breast cancer when using formulations developed after 1975.

Psychosocial factors influence decisions about genetic testing for inherited cancer risk and risk-management strategies. Uptake of genetic testing varies widely across studies. Psychological factors that have been associated with testing uptake include cancer-specific distress and perceived risk of developing breast or ovarian cancer. Studies have shown low levels of distress after genetic testing for both carriers and noncarriers, particularly in the longer term. Uptake of RRM and RRSO also varies across studies, and may be influenced by factors such as cancer history, age, family history, recommendations of the health care provider, and pretreatment genetic education and counseling. Patients' communication with their family members about an inherited risk of breast and gynecologic cancer is complex; gender, age, and the degree of relatedness are some elements that affect disclosure of this information. Research is ongoing to better understand and address psychosocial and behavioral issues in high-risk families.

[Note: Many of the medical and scientific terms used in this summary are found in the NCI Dictionary of Genetics Terms. When a linked term is clicked, the definition will appear in a separate window.]

[Note: A concerted effort is being made within the genetics community to shift terminology used to describe genetic variation. The shift is to use the term variant rather than the term mutation to describe a genetic difference that exists between the person or group being studied and the reference sequence. Variants can then be further classified as benign (harmless), likely benign, of uncertain significance, likely pathogenic, or pathogenic (disease causing). Throughout this summary, we will use the term pathogenic variant to describe a disease-causing mutation. Refer to the Cancer Genetics Overview summary for more information about variant classification.]

[Note: Many of the genes and conditions described in this summary are found in the Online Mendelian Inheritance in Man (OMIM) database. When OMIM appears after a gene name or the name of a condition, click on OMIM for a link to more information.]

Among women, breast cancer is the most commonly diagnosed cancer after nonmelanoma skin cancer, and it is the second leading cause of cancer deaths after lung cancer. In 2016, an estimated 249,260 new cases will be diagnosed, and 40,890 deaths from breast cancer will occur.[1] The incidence of breast cancer, particularly for estrogen receptorpositive cancers occurring after age 50 years, is declining and has declined at a faster rate since 2003; this may be temporally related to a decrease in hormone replacement therapy (HRT) after early reports from the Womens Health Initiative (WHI).[2] An estimated 22,280 new cases of ovarian cancer are expected in 2016, with an estimated 14,240 deaths. Ovarian cancer is the fifth most deadly cancer in women.[1] An estimated 60,050 new cases of endometrial cancer are expected in 2016, with an estimated 10,470 deaths.[1] (Refer to the PDQ summaries on Breast Cancer Treatment; Ovarian Epithelial, Fallopian Tube, and Primary Peritoneal Cancer Treatment; and Endometrial Cancer Treatment for more information about breast, ovarian, and endometrial cancer rates, diagnosis, and management.)

A possible genetic contribution to both breast and ovarian cancer risk is indicated by the increased incidence of these cancers among women with a family history (refer to the Risk Factors for Breast Cancer, Risk Factors for Ovarian Cancer, and Risk Factors for Endometrial Cancer sections below for more information), and by the observation of some families in which multiple family members are affected with breast and/or ovarian cancer, in a pattern compatible with an inheritance of autosomal dominant cancer susceptibility. Formal studies of families (linkage analysis) have subsequently proven the existence of autosomal dominant predispositions to breast and ovarian cancer and have led to the identification of several highly penetrant genes as the cause of inherited cancer risk in many families. (Refer to the PDQ summary Cancer Genetics Overview for more information about linkage analysis.) Pathogenic variants in these genes are rare in the general population and are estimated to account for no more than 5% to 10% of breast and ovarian cancer cases overall. It is likely that other genetic factors contribute to the etiology of some of these cancers.

Refer to the PDQ summary on Breast Cancer Prevention for information about risk factors for breast cancer in the general population.

In cross-sectional studies of adult populations, 5% to 10% of women have a mother or sister with breast cancer, and about twice as many have either a first-degree relative (FDR) or a second-degree relative with breast cancer.[3-6] The risk conferred by a family history of breast cancer has been assessed in case-control and cohort studies, using volunteer and population-based samples, with generally consistent results.[7] In a pooled analysis of 38 studies, the relative risk (RR) of breast cancer conferred by an FDR with breast cancer was 2.1 (95% confidence interval [CI], 2.02.2).[7] Risk increases with the number of affected relatives, age at diagnosis, the occurrence of bilateral or multiple ipsilateral breast cancers in a family member, and the number of affected male relatives.[4,5,7-9] A large population-based study from the Swedish Family Cancer Database confirmed the finding of a significantly increased risk of breast cancer in women who had a mother or a sister with breast cancer. The hazard ratio (HR) for women with a single breast cancer in the family was 1.8 (95% CI, 1.81.9) and was 2.7 (95% CI, 2.62.9) for women with a family history of multiple breast cancers. For women who had multiple breast cancers in the family, with one occurring before age 40 years, the HR was 3.8 (95% CI, 3.14.8). However, the study also found a significant increase in breast cancer risk if the relative was aged 60 years or older, suggesting that breast cancer at any age in the family carries some increase in risk.[9] (Refer to the Penetrance of BRCA pathogenic variants section of this summary for a discussion of familial risk in women from families with BRCA1/BRCA2 pathogenic variants who themselves test negative for the family pathogenic variant.)

Cumulative risk of breast cancer increases with age, with most breast cancers occurring after age 50 years.[10] In women with a genetic susceptibility, breast cancer, and to a lesser degree, ovarian cancer, tends to occur at an earlier age than in sporadic cases.

In general, breast cancer risk increases with early menarche and late menopause and is reduced by early first full-term pregnancy. There may be an increased risk of breast cancer in carriers of BRCA1 and BRCA2 pathogenic variants with pregnancy at a younger age (before age 30 years), with a more significant effect seen for carriers of BRCA1 pathogenic variants.[11-13] Likewise, breast feeding can reduce breast cancer risk in carriers of BRCA1 (but not BRCA2) pathogenic variants.[14] Regarding the effect of pregnancy on breast cancer outcomes, neither diagnosis of breast cancer during pregnancy nor pregnancy after breast cancer seems to be associated with adverse survival outcomes in women who carry a BRCA1 or BRCA2 pathogenic variant.[15] Parity appears to be protective for carriers of BRCA1 and BRCA2 pathogenic variants, with an additional protective effect for live birth before age 40 years.[16]

Reproductive history can also affect the risk of ovarian cancer and endometrial cancer. (Refer to the Reproductive History sections in the Risk Factors for Ovarian Cancer and Risk Factors for Endometrial Cancer sections of this summary for more information.)

Oral contraceptives (OCs) may produce a slight increase in breast cancer risk among long-term users, but this appears to be a short-term effect. In a meta-analysis of data from 54 studies, the risk of breast cancer associated with OC use did not vary in relationship to a family history of breast cancer.[17]

OCs are sometimes recommended for ovarian cancer prevention in carriers of BRCA1 and BRCA2 pathogenic variants. (Refer to the Oral Contraceptives section in the Risk Factors for Ovarian Cancer section of this summary for more information.) Although the data are not entirely consistent, a meta-analysis concluded that there was no significant increased risk of breast cancer with OC use in carriers of BRCA1/BRCA2 pathogenic variants.[18] However, use of OCs formulated before 1975 was associated with an increased risk of breast cancer (summary relative risk [SRR], 1.47; 95% CI, 1.062.04).[18] (Refer to the Reproductive factors section in the Clinical Management of Carriers of BRCA Pathogenic Variants section of this summary for more information.)

Data exist from both observational and randomized clinical trials regarding the association between postmenopausal HRT and breast cancer. A meta-analysis of data from 51 observational studies indicated a RR of breast cancer of 1.35 (95% CI, 1.211.49) for women who had used HRT for 5 or more years after menopause.[19] The WHI (NCT00000611), a randomized controlled trial of about 160,000 postmenopausal women, investigated the risks and benefits of HRT. The estrogen-plus-progestin arm of the study, in which more than 16,000 women were randomly assigned to receive combined HRT or placebo, was halted early because health risks exceeded benefits.[20,21] Adverse outcomes prompting closure included significant increase in both total (245 vs. 185 cases) and invasive (199 vs. 150 cases) breast cancers (RR, 1.24; 95% CI, 1.021.5, P < . 001) and increased risks of coronary heart disease, stroke, and pulmonary embolism. Similar findings were seen in the estrogen-progestin arm of the prospective observational Million Womens Study in the United Kingdom.[22] The risk of breast cancer was not elevated, however, in women randomly assigned to estrogen-only versus placebo in the WHI study (RR, 0.77; 95% CI, 0.591.01). Eligibility for the estrogen-only arm of this study required hysterectomy, and 40% of these patients also had undergone oophorectomy, which potentially could have impacted breast cancer risk.[23]

The association between HRT and breast cancer risk among women with a family history of breast cancer has not been consistent; some studies suggest risk is particularly elevated among women with a family history, while others have not found evidence for an interaction between these factors.[24-28,19] The increased risk of breast cancer associated with HRT use in the large meta-analysis did not differ significantly between subjects with and without a family history.[28] The WHI study has not reported analyses stratified on breast cancer family history, and subjects have not been systematically tested for BRCA1/BRCA2 pathogenic variants.[21] Short-term use of hormones for treatment of menopausal symptoms appears to confer little or no breast cancer risk.[19,29] The effect of HRT on breast cancer risk among carriers of BRCA1 or BRCA2 pathogenic variants has been studied only in the context of bilateral risk-reducing oophorectomy, in which short-term replacement does not appear to reduce the protective effect of oophorectomy on breast cancer risk.[30] (Refer to the Hormone replacement therapy in carriers of BRCA1/BRCA2 pathogenic variants section of this summary for more information.)

Hormone use can also affect the risk of developing endometrial cancer. (Refer to the Hormones section in the Risk Factors for Endometrial Cancer section of this summary for more information.)

Observations in survivors of the atomic bombings of Hiroshima and Nagasaki and in women who have received therapeutic radiation treatments to the chest and upper body document increased breast cancer risk as a result of radiation exposure. The significance of this risk factor in women with a genetic susceptibility to breast cancer is unclear.

Preliminary data suggest that increased sensitivity to radiation could be a cause of cancer susceptibility in carriers of BRCA1 or BRCA2 pathogenic variants,[31-34] and in association with germline ATM and TP53 variants.[35,36]

The possibility that genetic susceptibility to breast cancer occurs via a mechanism of radiation sensitivity raises questions about radiation exposure. It is possible that diagnostic radiation exposure, including mammography, poses more risk in genetically susceptible women than in women of average risk. Therapeutic radiation could also pose carcinogenic risk. A cohort study of carriers of BRCA1 and BRCA2 pathogenic variants treated with breast-conserving therapy, however, showed no evidence of increased radiation sensitivity or sequelae in the breast, lung, or bone marrow of carriers.[37] Conversely, radiation sensitivity could make tumors in women with genetic susceptibility to breast cancer more responsive to radiation treatment. Studies examining the impact of radiation exposure, including, but not limited to, mammography, in carriers of BRCA1 and BRCA2 pathogenic variants have had conflicting results.[38-43] A large European study showed a dose-response relationship of increased risk with total radiation exposure, but this was primarily driven by nonmammographic radiation exposure before age 20 years.[42] Subsequently, no significant association was observed between prior mammography exposure and breast cancer risk in a prospective study of 1,844 BRCA1 carriers and 502 BRCA2 carriers without a breast cancer diagnosis at time of study entry; average follow-up time was 5.3 years.[43] (Refer to the Mammography section in the Clinical Management of Carriers of BRCA Pathogenic Variants section of this summary for more information about radiation.)

The risk of breast cancer increases by approximately 10% for each 10 g of daily alcohol intake (approximately one drink or less) in the general population.[44,45] Prior studies of carriers of BRCA1/BRCA2 pathogenic variants have found no increased risk associated with alcohol consumption.[46,47]

Weight gain and being overweight are commonly recognized risk factors for breast cancer. In general, overweight women are most commonly observed to be at increased risk of postmenopausal breast cancer and at reduced risk of premenopausal breast cancer. Sedentary lifestyle may also be a risk factor.[48] These factors have not been systematically evaluated in women with a positive family history of breast cancer or in carriers of cancer-predisposing pathogenic variants, but one study suggested a reduced risk of cancer associated with exercise among carriers of BRCA1 and BRCA2 pathogenic variants.[49]

Benign breast disease (BBD) is a risk factor for breast cancer, independent of the effects of other major risk factors for breast cancer (age, age at menarche, age at first live birth, and family history of breast cancer).[50] There may also be an association between BBD and family history of breast cancer.[51]

An increased risk of breast cancer has also been demonstrated for women who have increased density of breast tissue as assessed by mammogram,[50,52,53] and breast density is likely to have a genetic component in its etiology.[54-56]

Other risk factors, including those that are only weakly associated with breast cancer and those that have been inconsistently associated with the disease in epidemiologic studies (e.g., cigarette smoking), may be important in women who are in specific genotypically defined subgroups. One study [57] found a reduced risk of breast cancer among carriers of BRCA1/BRCA2 pathogenic variants who smoked, but an expanded follow-up study failed to find an association.[58]

Refer to the PDQ summary on Ovarian, Fallopian Tube, and Primary Peritoneal Cancer Prevention for information about risk factors for ovarian cancer in the general population.

Although reproductive, demographic, and lifestyle factors affect risk of ovarian cancer, the single greatest ovarian cancer risk factor is a family history of the disease. A large meta-analysis of 15 published studies estimated an odds ratio of 3.1 for the risk of ovarian cancer associated with at least one FDR with ovarian cancer.[59]

Ovarian cancer incidence rises in a linear fashion from age 30 years to age 50 years and continues to increase, though at a slower rate, thereafter. Before age 30 years, the risk of developing epithelial ovarian cancer is remote, even in hereditary cancer families.[60]

Nulliparity is consistently associated with an increased risk of ovarian cancer, including among carriers of BRCA/BRCA2 pathogenic variants, yet a meta-analysis could only identify risk-reduction in women with four or more live births.[13] Risk may also be increased among women who have used fertility drugs, especially those who remain nulligravid.[61,62] Several studies have reported a risk reduction in ovarian cancer after OC pill use in carriers of BRCA1/BRCA2 pathogenic variants;[63-65] a risk reduction has also been shown after tubal ligation in BRCA1 carriers, with a statistically significant decreased risk of 22% to 80% after the procedure.[65,66] On the other hand, evidence is growing that the use of menopausal HRT is associated with an increased risk of ovarian cancer, particularly in long-time users and users of sequential estrogen-progesterone schedules.[67-70]

Bilateral tubal ligation and hysterectomy are associated with reduced ovarian cancer risk,[61,71,72] including in carriers of BRCA1/BRCA2 pathogenic variants.[73] Ovarian cancer risk is reduced more than 90% in women with documented BRCA1 or BRCA2 pathogenic variants who chose risk-reducing salpingo-oophorectomy. In this same population, risk-reducing oophorectomy also resulted in a nearly 50% reduction in the risk of subsequent breast cancer.[74,75] (Refer to the Risk-reducing salpingo-oophorectomy section of this summary for more information about these studies.)

Use of OCs for 4 or more years is associated with an approximately 50% reduction in ovarian cancer risk in the general population.[61,76] A majority of, but not all, studies also support OCs being protective among carriers of BRCA1/BRCA2 pathogenic variants.[66,77-80] A meta-analysis of 18 studies including 13,627 carriers of BRCA pathogenic variants reported a significantly reduced risk of ovarian cancer (SRR, 0.50; 95% CI, 0.330.75) associated with OC use.[18] (Refer to the Oral contraceptives section in the Chemoprevention section of this summary for more information.)

Refer to the PDQ summary on Endometrial Cancer Prevention for information about risk factors for endometrial cancer in the general population.

Although the hyperestrogenic state is the most common predisposing factor for endometrial cancer, family history also plays a significant role in a womans risk for disease. Approximately 3% to 5% of uterine cancer cases are attributable to a hereditary cause,[81] with the main hereditary endometrial cancer syndrome being Lynch syndrome (LS), an autosomal dominant genetic condition with a population prevalence of 1 in 300 to 1 in 1,000 individuals.[82,83] (Refer to the LS section in the PDQ summary on Genetics of Colorectal Cancer for more information.)

Age is an important risk factor for endometrial cancer. Most women with endometrial cancer are diagnosed after menopause. Only 15% of women are diagnosed with endometrial cancer before age 50 years, and fewer than 5% are diagnosed before age 40 years.[84] Women with LS tend to develop endometrial cancer at an earlier age, with the median age at diagnosis of 48 years.[85]

Reproductive factors such as multiparity, late menarche, and early menopause decrease the risk of endometrial cancer because of the lower cumulative exposure to estrogen and the higher relative exposure to progesterone.[86,87]

Hormonal factors that increase the risk of type I endometrial cancer are better understood. All endometrial cancers share a predominance of estrogen relative to progesterone. Prolonged exposure to estrogen or unopposed estrogen increases the risk of endometrial cancer. Endogenous exposure to estrogen can result from obesity, polycystic ovary syndrome (PCOS), and nulliparity, while exogenous estrogen can result from taking unopposed estrogen or tamoxifen. Unopposed estrogen increases the risk of developing endometrial cancer by twofold to twentyfold, proportional to the duration of use.[88,89] Tamoxifen, a selective estrogen receptor modulator, acts as an estrogen agonist on the endometrium while acting as an estrogen antagonist in breast tissue, and increases the risk of endometrial cancer.[90] In contrast, oral contraceptives, the levonorgestrel-releasing intrauterine system, and combination estrogen-progesterone hormone replacement therapy all reduce the risk of endometrial cancer through the antiproliferative effect of progesterone acting on the endometrium.[91-94]

Autosomal dominant inheritance of breast and gynecologic cancers is characterized by transmission of cancer predisposition from generation to generation, through either the mothers or the fathers side of the family, with the following characteristics:

Breast and ovarian cancer are components of several autosomal dominant cancer syndromes. The syndromes most strongly associated with both cancers are the syndromes associated with BRCA1 or BRCA2 pathogenic variants. Breast cancer is also a common feature of Li-Fraumeni syndrome due to TP53 pathogenic variants and of Cowden syndrome due to PTEN pathogenic variants.[95] Other genetic syndromes that may include breast cancer as an associated feature include heterozygous carriers of the ataxia telangiectasia gene and Peutz-Jeghers syndrome. Ovarian cancer has also been associated with LS, basal cell nevus (Gorlin) syndrome (OMIM), and multiple endocrine neoplasia type 1 (OMIM).[95] LS is mainly associated with colorectal cancer and endometrial cancer, although several studies have demonstrated that patients with LS are also at risk of developing transitional cell carcinoma of the ureters and renal pelvis; cancers of the stomach, small intestine, liver and biliary tract, brain, breast, prostate, and adrenal cortex; and sebaceous skin tumors (Muir-Torre syndrome).[96-102]

Germline pathogenic variants in the genes responsible for these autosomal dominant cancer syndromes produce different clinical phenotypes of characteristic malignancies and, in some instances, associated nonmalignant abnormalities.

The family characteristics that suggest hereditary cancer predisposition include the following:

Figure 1 and Figure 2 depict some of the classic inheritance features of a BRCA1 and BRCA2 pathogenic variant, respectively. Figure 3 depicts a classic family with LS. (Refer to the Standard Pedigree Nomenclature figure in the PDQ summary on Cancer Genetics Risk Assessment and Counseling for definitions of the standard symbols used in these pedigrees.)

Figure 1. BRCA1 pedigree. This pedigree shows some of the classic features of a family with a BRCA1 pathogenic variant across three generations, including affected family members with breast cancer or ovarian cancer and a young age at onset. BRCA1 families may exhibit some or all of these features. As an autosomal dominant syndrome, a BRCA1 pathogenic variant can be transmitted through maternal or paternal lineages, as depicted in the figure.

Figure 2. BRCA2 pedigree. This pedigree shows some of the classic features of a family with a BRCA2 pathogenic variant across three generations, including affected family members with breast (including male breast cancer), ovarian, pancreatic, or prostate cancers and a relatively young age at onset. BRCA2 families may exhibit some or all of these features. As an autosomal dominant syndrome, a BRCA2 pathogenic variant can be transmitted through maternal or paternal lineages, as depicted in the figure.

Figure 3. Lynch syndrome pedigree. This pedigree shows some of the classic features of a family with Lynch syndrome, including affected family members with colon cancer or endometrial cancer and a younger age at onset in some individuals. Lynch syndrome families may exhibit some or all of these features. Lynch syndrome families may also include individuals with other gastrointestinal, gynecologic, and genitourinary cancers, or other extracolonic cancers. As an autosomal dominant syndrome, Lynch syndrome can be transmitted through maternal or paternal lineages, as depicted in the figure.

There are no pathognomonic features distinguishing breast and ovarian cancers occurring in carriers of BRCA1 or BRCA2 pathogenic variants from those occurring in noncarriers. Breast cancers occurring in carriers of BRCA1 pathogenic variants are more likely to be ER-negative, progesterone receptornegative, HER2/neu receptornegative (i.e., triple-negative breast cancers), and have a basal phenotype. BRCA1-associated ovarian cancers are more likely to be high-grade and of serous histopathology. (Refer to the Pathology of breast cancer and Pathology of ovarian cancer sections of this summary for more information.)

Some pathologic features distinguish carriers of LS-associated pathogenic variants from noncarriers. The hallmark feature of endometrial cancers occurring in LS is mismatch repair (MMR) defects, including the presence of microsatellite instability (MSI), and the absence of specific MMR proteins. In addition to these molecular changes, there are also histologic changes including tumor-infiltrating lymphocytes, peritumoral lymphocytes, undifferentiated tumor histology, lower uterine segment origin, and synchronous tumors.

The accuracy and completeness of family histories must be taken into account when they are used to assess risk. A reported family history may be erroneous, or a person may be unaware of relatives affected with cancer. In addition, small family sizes and premature deaths may limit the information obtained from a family history. Breast or ovarian cancer on the paternal side of the family usually involves more distant relatives than does breast or ovarian cancer on the maternal side, so information may be more difficult to obtain. When self-reported information is compared with independently verified cases, the sensitivity of a history of breast cancer is relatively high, at 83% to 97%, but lower for ovarian cancer, at 60%.[103,104] Additional limitations of relying on family histories include adoption; families with a small number of women; limited access to family history information; and incidental removal of the uterus, ovaries, and/or fallopian tubes for noncancer indications. Family histories will evolve, therefore it is important to update family histories from both parents over time. (Refer to the Accuracy of the family history section in the PDQ summary on Cancer Genetics Risk Assessment and Counseling for more information.)

Models to predict an individuals lifetime risk of developing breast and/or gynecologic cancer are available.[105-108] In addition, models exist to predict an individuals likelihood of having a pathogenic variant in BRCA1, BRCA2, or one of the MMR genes associated with LS. (Refer to the Models for prediction of the likelihood of a BRCA1 or BRCA2 pathogenic variant section of this summary for more information about some of these models.) Not all models can be appropriately applied to all patients. Each model is appropriate only when the patients characteristics and family history are similar to those of the study population on which the model was based. Different models may provide widely varying risk estimates for the same clinical scenario, and the validation of these estimates has not been performed for many models.[106,109,110]

In general, breast cancer risk assessment models are designed for two types of populations: 1) women without a pathogenic variant or strong family history of breast or ovarian cancer; and 2) women at higher risk because of a personal or family history of breast cancer or ovarian cancer.[110] Models designed for women of the first type (e.g., the Gail model, which is the basis for the Breast Cancer Risk Assessment Tool [BCRAT]) [111], and the Colditz and Rosner model [112]) require only limited information about family history (e.g., number of first-degree relatives with breast cancer). Models designed for women at higher risk require more detailed information about personal and family cancer history of breast and ovarian cancers, including ages at onset of cancer and/or carrier status of specific breast cancer-susceptibility alleles. The genetic factors used by the latter models differ, with some assuming one risk locus (e.g., the Claus model [113]), others assuming two loci (e.g., the International Breast Cancer Intervention Study [IBIS] model [114] and the BRCAPRO model [115]), and still others assuming an additional polygenic component in addition to multiple loci (e.g., the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm [BOADICEA] model [116-118]). The models also differ in whether they include information about nongenetic risk factors. Three models (Gail/BCRAT, Pfeiffer,[108] and IBIS) include nongenetic risk factors but differ in the risk factors they include (e.g., the Pfeiffer model includes alcohol consumption, whereas the Gail/BCRAT does not). These models have limited ability to discriminate between individuals who are affected and those who are unaffected with cancer; a model with high discrimination would be close to 1, and a model with little discrimination would be close to 0.5; the discrimination of the models currently ranges between 0.56 and 0.63).[119] The existing models generally are more accurate in prospective studies that have assessed how well they predict future cancers.[110,120-122]

In the United States, BRCAPRO, the Claus model,[113,123] and the Gail/BCRAT [111] are widely used in clinical counseling. Risk estimates derived from the models differ for an individual patient. Several other models that include more detailed family history information are also in use and are discussed below.

The Gail model is the basis for the BCRAT, a computer program available from the National Cancer Institute (NCI) by calling the Cancer Information Service at 1-800-4-CANCER (1-800-422-6237). This version of the Gail model estimates only the risk of invasive breast cancer. The Gail/BCRAT model has been found to be reasonably accurate at predicting breast cancer risk in large groups of white women who undergo annual screening mammography; however, reliability varies depending on the cohort studied.[124-129] Risk can be overestimated in the following populations:

The Gail/BCRAT model is valid for women aged 35 years and older. The model was primarily developed for white women.[128] Extensions of the Gail model for African American women have been subsequently developed to calibrate risk estimates using data from more than 1,600 African American women with invasive breast cancer and more than 1,600 controls.[130] Additionally, extensions of the Gail model have incorporated high-risk single nucleotide polymorphisms and pathogenic variants; however, no software exists to calculate risk in these extended models.[131,132] Other risk assessment models incorporating breast density have been developed but are not ready for clinical use.[133,134]

Generally, the Gail/BCRAT model should not be the sole model used for families with one or more of the following characteristics:

Commonly used models that incorporate family history include the IBIS, BOADICEA, and BRCAPRO models. The IBIS/Tyrer-Cuzick model incorporates both genetic and nongenetic factors.[114] A three-generation pedigree is used to estimate the likelihood that an individual carries either a BRCA1/BRCA2 pathogenic variant or a hypothetical low-penetrance gene. In addition, the model incorporates personal risk factors such as parity, body mass index (BMI); height; and age at menarche, first live birth, menopause, and HRT use. Both genetic and nongenetic factors are combined to develop a risk estimate. The BOADICEA model examines family history to estimate breast cancer risk and also incorporates both BRCA1/BRCA2 and non-BRCA1/BRCA2 genetic risk factors.[117] The most important difference between BOADICEA and the other models using information on BRCA1/BRCA2 is that BOADICEA assumes an additional polygenic component in addition to multiple loci,[116-118] which is more in line with what is known about the underlying genetics of breast cancer. However, the discrimination and calibration for these models differ significantly when compared in independent samples;[120] the IBIS and BOADICEA models are more comparable when estimating risk over a shorter fixed time horizon (e.g., 10 years),[120] than when estimating remaining lifetime risk. As all risk assessment models for cancers are typically validated over a shorter time horizon (e.g., 5 or 10 years), fixed time horizon estimates rather than remaining lifetime risk may be more accurate and useful measures to convey in a clinical setting.

In addition, readily available models that provide information about an individual womans risk in relation to the population-level risk depending on her risk factors may be useful in a clinical setting (e.g., Your Disease Risk). Although this tool was developed using information about average-risk women and does not calculate absolute risk estimates, it still may be useful when counseling women about prevention. Risk assessment models are being developed and validated in large cohorts to integrate genetic and nongenetic data, breast density, and other biomarkers.

Two risk predictions models have been developed for ovarian cancer.[107,108] The Rosner model [107] included age at menopause, age at menarche, oral contraception use, and tubal ligation; the concordance statistic was 0.60 (0.570.62). The Pfeiffer model [108] included oral contraceptive use, menopausal hormone therapy use, and family history of breast cancer or ovarian cancer, with a similar discriminatory power of 0.59 (0.560.62). Although both models were well calibrated, their modest discriminatory power limited their screening potential.

The Pfeiffer model has been used to predict endometrial cancer risk in the general population.[108] For endometrial cancer, the relative risk model included BMI, menopausal hormone therapy use, menopausal status, age at menopause, smoking status, and oral contraceptive pill use. The discriminatory power of the model was 0.68 (0.660.70); it overestimated observed endometrial cancers in most subgroups but underestimated disease in women with the highest BMI category, in premenopausal women, and in women taking menopausal hormone therapy for 10 years or more.

In contrast, MMRpredict, PREMM1,2,6, and MMRpro are three quantitative predictive models used to identify individuals who may potentially have LS.[135-137] MMRpredict incorporates only colorectal cancer patients but does include MSI and immunohistochemistry (IHC) tumor testing results. PREMM1,2,6 accounts for other LS-associated tumors but does not include tumor testing results. MMRpro incorporates tumor testing and germline testing results, but is more time intensive because it includes affected and unaffected individuals in the risk-quantification process. All three predictive models are comparable to the traditional Amsterdam and Bethesda criteria in identifying individuals with colorectal cancer who carry MMR gene pathogenic variants.[138] However, because these models were developed and validated in colorectal cancer patients, the discriminative abilities of these models to identify LS are lower among individuals with endometrial cancer than among those with colon cancer.[139] In fact, the sensitivity and specificity of MSI and IHC in identifying carriers of pathogenic variants are considerably higher than the prediction models and support the use of molecular tumor testing to screen for LS in women with endometrial cancer.

Table 1 summarizes salient aspects of breast and gynecologic cancer risk assessment models that are commonly used in the clinical setting. These models differ by the extent of family history included, whether nongenetic risk factors are included, and whether carrier status and polygenic risk are included (inputs to the models). The models also differ in the type of risk estimates that are generated (outputs of the models). These factors may be relevant in choosing the model that best applies to a particular individual.

The proportion of individuals carrying a pathogenic variant who will manifest a certain disease is referred to as penetrance. In general, common genetic variants that are associated with cancer susceptibility have a lower penetrance than rare genetic variants. This is depicted in Figure 4. For adult-onset diseases, penetrance is usually described by the individual carrier's age, sex, and organ site. For example, the penetrance for breast cancer in female carriers of BRCA1 pathogenic variants is often quoted by age 50 years and by age 70 years. Of the numerous methods for estimating penetrance, none are without potential biases, and determining an individual carrier's risk of cancer involves some level of imprecision.

Figure 4. Genetic architecture of cancer risk. This graph depicts the general finding of a low relative risk associated with common, low-penetrance genetic variants, such as single-nucleotide polymorphisms identified in genome-wide association studies, and a higher relative risk associated with rare, high-penetrance genetic variants, such as pathogenic variants in the BRCA1/BRCA2 genes associated with hereditary breast and ovarian cancer and the mismatch repair genes associated with Lynch syndrome.

Throughout this summary, we discuss studies that report on relative and absolute risks. These are two important but different concepts. Relative risk (RR) refers to an estimate of risk relative to another group (e.g., risk of an outcome like breast cancer for women who are exposed to a risk factor RELATIVE to the risk of breast cancer for women who are unexposed to the same risk factor). RR measures that are greater than 1 mean that the risk for those captured in the numerator (i.e., the exposed) is higher than the risk for those captured in the denominator (i.e., the unexposed). RR measures that are less than 1 mean that the risk for those captured in the numerator (i.e., the exposed) is lower than the risk for those captured in the denominator (i.e., the unexposed). Measures with similar relative interpretations include the odds ratio (OR), hazard ratio (HR), and risk ratio.

Absolute risk measures take into account the number of people who have a particular outcome, the number of people in a population who could have the outcome, and person-time (the period of time during which an individual was at risk of having the outcome), and reflect the absolute burden of an outcome in a population. Absolute measures include risks and rates and can be expressed over a specific time frame (e.g., 1 year, 5 years) or overall lifetime. Cumulative risk is a measure of risk that occurs over a defined time period. For example, overall lifetime risk is a type of cumulative risk that is usually calculated on the basis of a given life expectancy (e.g., 80 or 90 years). Cumulative risk can also be presented over other time frames (e.g., up to age 50 years).

Large relative risk measures do not mean that there will be large effects in the actual number of individuals at a population level because the disease outcome may be quite rare. For example, the relative risk for smoking is much higher for lung cancer than for heart disease, but the absolute difference between smokers and nonsmokers is greater for heart disease, the more-common outcome, than for lung cancer, the more-rare outcome.

Therefore, in evaluating the effect of exposures and biological markers on disease prevention across the continuum, it is important to recognize the differences between relative and absolute effects in weighing the overall impact of a given risk factor. For example, the magnitude is in the range of 30% (e.g., ORs or RRs of 1.3) for many breast cancer risk factors, which means that women with a risk factor (e.g., alcohol consumption, late age at first birth, oral contraceptive use, postmenopausal body size) have a 30% relative increase in breast cancer in comparison with what they would have if they did not have that risk factor. But the absolute increase in risk is based on the underlying absolute risk of disease. Figure 5 and Table 2 show the impact of a relative risk factor in the range of 1.3 on absolute risk. (Refer to the Standard Pedigree Nomenclature figure in the PDQ summary on Cancer Genetics Risk Assessment and Counseling for definitions of the standard symbols used in these pedigrees.) As shown, women with a family history of breast cancer have a much higher benefit from risk factor reduction on an absolute scale.[1]

Figure 5. These five pedigrees depict probands with varying degrees of family history. Table 2 accompanies this figure.

With the increasing use of multigene panel tests (see below), a framework for cancer risk management among individuals with pathogenic variants detected in novel genes has been described [2] that incorporates data on age-specific, lifetime, and absolute cancer risks. The framework suggests initiating screening in these individuals at the age when their 5-year cancer risk approaches that at which screening is routinely initiated for women in the general population (approximately 1% for breast cancer in the United States). As a result, the age at which to begin screening will vary depending on the gene.

Since the availability of next-generation sequencing and the Supreme Court of the United States ruling that human genes cannot be patented, several clinical laboratories now offer genetic testing through multigene panels at a cost comparable to single-gene testing. Even testing for BRCA1 and BRCA2 is a limited panel test of two genes. Approximately 25% of all ovarian/fallopian tube/peritoneal cancers are due to a heritable genetic condition. Of these, about one-quarter (6% of all ovarian/fallopian tube/peritoneal cancers) are caused by genes other than BRCA1 and BRCA2, including many genes associated with the Fanconi anemia pathway or otherwise involved with homologous recombination.[1] In a population of ovarian cancer patients who test negative for BRCA1 and BRCA2 pathogenic variants, multigene panel testing can reveal actionable pathogenic variants.[2,3] In an unselected population of breast cancer patients, the prevalence of BRCA1 and BRCA2 pathogenic variants was 6.1%, while the prevalence of pathogenic variants in other breast/ovarian cancerpredisposing genes was 4.6%.[4] A caveat is the possible finding of a variant of uncertain significance, where the clinical significance remains unknown. Many centers now offer a multigene panel test instead of just BRCA1 and BRCA2 testing if there is a concerning family history of syndromes other than hereditary breast and ovarian cancer, or more importantly, to gain as much genetic information as possible with one test, particularly if there may be insurance limitations.

(Refer to the Multigene [panel] testing section in the PDQ summary on Cancer Genetics Risk Assessment and Counseling for more information about multigene testing, including genetic education and counseling considerations and research examining the use of multigene testing.)

Epidemiologic studies have clearly established the role of family history as an important risk factor for both breast and ovarian cancer. After gender and age, a positive family history is the strongest known predictive risk factor for breast cancer. However, it has long been recognized that in some families, there is hereditary breast cancer, which is characterized by an early age of onset, bilaterality, and the presence of breast cancer in multiple generations in an apparent autosomal dominant pattern of transmission (through either the maternal or the paternal lineage), sometimes including tumors of other organs, particularly the ovary and prostate gland.[1,2] It is now known that some of these cancer families can be explained by specific pathogenic variants in single cancer susceptibility genes. The isolation of several of these genes, which when altered are associated with a significantly increased risk of breast/ovarian cancer, makes it possible to identify individuals at risk. Although such cancer susceptibility genes are very important, highly penetrant germline pathogenic variants are estimated to account for only 5% to 10% of breast cancers overall.

A 1988 study reported the first quantitative evidence that breast cancer segregated as an autosomal dominant trait in some families.[3] The search for genes associated with hereditary susceptibility to breast cancer has been facilitated by studies of large kindreds with multiple affected individuals and has led to the identification of several susceptibility genes, including BRCA1, BRCA2, TP53, PTEN/MMAC1, and STK11. Other genes, such as the mismatch repair genes MLH1, MSH2, MSH6, and PMS2, have been associated with an increased risk of ovarian cancer, but have not been consistently associated with breast cancer.

In 1990, a susceptibility gene for breast cancer was mapped by genetic linkage to the long arm of chromosome 17, in the interval 17q12-21.[4] The linkage between breast cancer and genetic markers on chromosome 17q was soon confirmed by others, and evidence for the coincident transmission of both breast and ovarian cancer susceptibility in linked families was observed.[5] The BRCA1 gene (OMIM) was subsequently identified by positional cloning methods and has been found to contain 24 exons that encode a protein of 1,863 amino acids. Germline pathogenic variants in BRCA1 are associated with early-onset breast cancer, ovarian cancer, and fallopian tube cancer. (Refer to the Penetrance of BRCA pathogenic variants section of this summary for more information.) Male breast cancer, pancreatic cancer, testicular cancer, and early-onset prostate cancer may also be associated with pathogenic variants in BRCA1;[6-9] however, male breast cancer, pancreatic cancer, and prostate cancer are more strongly associated with pathogenic variants in BRCA2.

A second breast cancer susceptibility gene, BRCA2, was localized to the long arm of chromosome 13 through linkage studies of 15 families with multiple cases of breast cancer that were not linked to BRCA1. Pathogenic variants in BRCA2 (OMIM) are associated with multiple cases of breast cancer in families, and are also associated with male breast cancer, ovarian cancer, prostate cancer, melanoma, and pancreatic cancer.[8-14] (Refer to the Penetrance of BRCA pathogenic variants section of this summary for more information.) BRCA2 is a large gene with 27 exons that encode a protein of 3,418 amino acids.[15] While not homologous genes, both BRCA1 and BRCA2 have an unusually large exon 11 and translational start sites in exon 2. Like BRCA1, BRCA2 appears to behave like a tumor suppressor gene. In tumors associated with both BRCA1 and BRCA2 pathogenic variants, there is often loss of the wild-type allele.

Pathogenic variants in BRCA1 and BRCA2 appear to be responsible for disease in 45% of families with multiple cases of breast cancer only and in up to 90% of families with both breast and ovarian cancer.[16]

Most BRCA1 and BRCA2 pathogenic variants are predicted to produce a truncated protein product, and thus loss of protein function, although some missense pathogenic variants cause loss of function without truncation. Because inherited breast/ovarian cancer is an autosomal dominant condition, persons with a BRCA1 or BRCA2 pathogenic variant on one copy of chromosome 17 or 13 also carry a normal allele on the other paired chromosome. In most breast and ovarian cancers that have been studied from carriers of pathogenic variants, deletion of the normal allele results in loss of all function, leading to the classification of BRCA1 and BRCA2 as tumor suppressor genes. In addition to, and as part of, their roles as tumor suppressor genes, BRCA1 and BRCA2 are involved in myriad functions within cells, including homologous DNA repair, genomic stability, transcriptional regulation, protein ubiquitination, chromatin remodeling, and cell cycle control.[17,18]

Nearly 2,000 distinct variants and sequence variations in BRCA1 and BRCA2 have already been described.[19] Approximately 1 in 400 to 800 individuals in the general population may carry a germline pathogenic variant in BRCA1 or BRCA2.[20,21] The variants that have been associated with increased risk of cancer result in missing or nonfunctional proteins, supporting the hypothesis that BRCA1 and BRCA2 are tumor suppressor genes. While a small number of these pathogenic variants have been found repeatedly in unrelated families, most have not been reported in more than a few families.

Variant-screening methods vary in their sensitivity. Methods widely used in research laboratories, such as single-stranded conformational polymorphism analysis and conformation-sensitive gel electrophoresis, miss nearly a third of the variants that are detected by DNA sequencing.[22] In addition, large genomic alterations such as translocations, inversions, or large deletions or insertions are missed by most of the techniques, including direct DNA sequencing, but testing for these is commercially available. Such rearrangements are believed to be responsible for 12% to 18% of BRCA1 inactivating variants but are less frequently seen in BRCA2 and in individuals of Ashkenazi Jewish (AJ) descent.[23-29] Furthermore, studies have suggested that these rearrangements may be more frequently seen in Hispanic and Caribbean populations.[27,29,30]

Germline pathogenic variants in the BRCA1/BRCA2 genes are associated with an approximately 60% lifetime risk of breast cancer and a 15% to 40% lifetime risk of ovarian cancer. There are no definitive functional tests for BRCA1 or BRCA2; therefore, the classification of nucleotide changes to predict their functional impact as deleterious or benign relies on imperfect data. The majority of accepted pathogenic variants result in protein truncation and/or loss of important functional domains. However, 10% to 15% of all individuals undergoing genetic testing with full sequencing of BRCA1 and BRCA2 will not have a clearly pathogenic variant detected but will have a variant of uncertain (or unknown) significance (VUS). VUS may cause substantial challenges in counseling, particularly in terms of cancer risk estimates and risk management. Clinical management of such patients needs to be highly individualized and must take into consideration factors such as the patients personal and family cancer history, in addition to sources of information to help characterize the VUS as benign or deleterious. Thus an improved classification and reporting system may be of clinical utility.[31]

A comprehensive analysis of 7,461 consecutive full gene sequence analyses performed by Myriad Genetic Laboratories, Inc., described the frequency of VUS over a 3-year period.[32] Among subjects who had no clearly pathogenic variant, 13% had VUS defined as missense mutations and mutations that occur in analyzed intronic regions whose clinical significance has not yet been determined, chain-terminating mutations that truncate BRCA1 and BRCA2 distal to amino acid positions 1853 and 3308, respectively, and mutations that eliminate the normal stop codons for these proteins. The classification of a sequence variant as a VUS is a moving target. An additional 6.8% of subjects with no clear pathogenic variants had sequence alterations that were once considered VUS but were reclassified as a polymorphism, or occasionally as a pathogenic variant.

The frequency of VUS varies by ethnicity within the U.S. population. African Americans appear to have the highest rate of VUS.[33] In a 2009 study of data from Myriad, 16.5% of individuals of African ancestry had VUS, the highest rate among all ethnicities. The frequency of VUS in Asian, Middle Eastern, and Hispanic populations clusters between 10% and 14%, although these numbers are based on limited sample sizes. Over time, the rate of changes classified as VUS has decreased in all ethnicities, largely the result of improved variant classification algorithms.[34] VUS continue to be reclassified as additional information is curated and interpreted.[35,36] Such information may impact the continuing care of affected individuals.

A number of methods for discriminating deleterious from neutral VUS exist and others are in development [37-40] including integrated methods (see below).[41] Interpretation of VUS is greatly aided by efforts to track VUS in the family to determine if there is cosegregation of the VUS with the cancer in the family. In general, a VUS observed in individuals who also have a pathogenic variant, especially when the same VUS has been identified in conjunction with different pathogenic variants, is less likely to be in itself deleterious, although there are rare exceptions. As an adjunct to the clinical information, models to interpret VUS have been developed, based on sequence conservation, biochemical properties of amino acid changes,[37,42-46] incorporation of information on pathologic characteristics of BRCA1- and BRCA2-related tumors (e.g., BRCA1-related breast cancers are usually estrogen receptor [ER]negative),[47] and functional studies to measure the influence of specific sequence variations on the activity of BRCA1 or BRCA2 proteins.[48,49] When attempting to interpret a VUS, all available information should be examined.

Statistics regarding the percentage of individuals found to be carriers of BRCA pathogenic variants among samples of women and men with a variety of personal cancer histories regardless of family history are provided below. These data can help determine who might best benefit from a referral for cancer genetic counseling and consideration of genetic testing but cannot replace a personalized risk assessment, which might indicate a higher or lower pathogenic variant likelihood based on additional personal and family history characteristics.

In some cases, the same pathogenic variant has been found in multiple apparently unrelated families. This observation is consistent with a founder effect, wherein a pathogenic variant identified in a contemporary population can be traced to a small group of founders isolated by geographic, cultural, or other factors. Most notably, two specific BRCA1 pathogenic variants (185delAG and 5382insC) and a BRCA2 pathogenic variant (6174delT) have been reported to be common in AJs. However, other founder pathogenic variants have been identified in African Americans and Hispanics.[30,50,51] The presence of these founder pathogenic variants has practical implications for genetic testing. Many laboratories offer directed testing specifically for ethnic-specific alleles. This greatly simplifies the technical aspects of the test but is not without limitations. For example, it is estimated that up to 15% of BRCA1 and BRCA2 pathogenic variants that occur among Ashkenazim are nonfounder pathogenic variants.[32]

Among the general population, the likelihood of having any BRCA variant is as follows:

Among AJ individuals, the likelihood of having any BRCA variant is as follows:

Two large U.S. population-based studies of breast cancer patients younger than age 65 years examined the prevalence of BRCA1 [55,70] and BRCA2 [55] pathogenic variants in various ethnic groups. The prevalence of BRCA1 pathogenic variants in breast cancer patients by ethnic group was 3.5% in Hispanics, 1.3% to 1.4% in African Americans, 0.5% in Asian Americans, 2.2% to 2.9% in non-AJ whites, and 8.3% to 10.2% in AJ individuals.[55,70] The prevalence of BRCA2 pathogenic variants by ethnic group was 2.6% in African Americans and 2.1% in whites.[55]

A study of Hispanic patients with a personal or family history of breast cancer and/or ovarian cancer, who were enrolled through multiple clinics in the southwestern United States, examined the prevalence of BRCA1 and BRCA2 pathogenic variants. BRCA pathogenic variants were identified in 189 of 746 patients (25%) (124 BRCA1, 65 BRCA2);[71] 21 of the 189 (11%) BRCA pathogenic variants identified were large rearrangements, of which 13 (62%) were the BRCA1 exon 912 deletion. An unselected cohort of 810 women of Mexican ancestry with breast cancer were tested; 4.3% had a BRCA pathogenic variant. Eight of the 35 pathogenic variants identified also were the BRCA1 exon 912 deletion.[72] In another population-based cohort of 492 Hispanic women with breast cancer, the BRCA1 exon 912 deletion was found in three patients, suggesting that this variant may be a Mexican founder pathogenic variant and may represent 10% to 12% of all BRCA1 pathogenic variants in similar clinic- and population-based cohorts in the United States. Within the clinic-based cohort, there were nine recurrent pathogenic variants, which accounted for 53% of all variants observed in this cohort, suggesting the existence of additional founder pathogenic variants in this population.

A retrospective review of 29 AJ patients with primary fallopian tube tumors identified germline BRCA pathogenic variants in 17%.[69] Another study of 108 women with fallopian tube cancer identified pathogenic variants in 55.6% of the Jewish women and 26.4% of non-Jewish women (30.6% overall).[73] Estimates of the frequency of fallopian tube cancer in carriers of BRCA pathogenic variants are limited by the lack of precision in the assignment of site of origin for high-grade, metastatic, serous carcinomas at initial presentation.[6,69,73,74]

Population screening has identified carriers in a number of AJ populations who would not have met criteria for family-based testing.[62,75-77] This could potentially expand the number of individuals who could benefit from preventive strategies. Because the detection rate is highly dependent on the prevalence of pathogenic variants in a population, it is not clear how applicable this approach would be for other populations, including other founder pathogenic variant populations. Another unanswered question is whether adequate genetic counseling can be provided for whole populations.

Several studies have assessed the frequency of BRCA1 or BRCA2 pathogenic variants in women with breast or ovarian cancer.[55,56,70,78-86] Personal characteristics associated with an increased likelihood of a BRCA1 and/or BRCA2 pathogenic variant include the following:

Family history characteristics associated with an increased likelihood of carrying a BRCA1 and/or BRCA2 pathogenic variant include the following:

Several professional organizations and expert panels, including the American Society of Clinical Oncology,[91] the National Comprehensive Cancer Network (NCCN),[92] the American Society of Human Genetics,[93] the American College of Medical Genetics and Genomics,[94] the National Society of Genetic Counselors,[94] the U.S. Preventive Services Task Force,[95] and the Society of Gynecologic Oncologists,[96] have developed clinical criteria and practice guidelines that can be helpful to health care providers in identifying individuals who may have a BRCA1 or BRCA2 pathogenic variant.

Many models have been developed to predict the probability of identifying germline BRCA1/BRCA2 pathogenic variants in individuals or families. These models include those using logistic regression,[32,78,79,81,84,97,98] genetic models using Bayesian analysis (BRCAPRO and Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm [BOADICEA]),[84,99] and empiric observations,[52,55,58,100-102] including the Myriad prevalence tables.

In addition to BOADICEA, BRCAPRO is commonly used for genetic counseling in the clinical setting. BRCAPRO and BOADICEA predict the probability of being a carrier and produce estimates of breast cancer risk (see Table 3). The discrimination and accuracy (factors used to evaluate the performance of prediction models) of these models are much higher for these models' ability to report on carrier status than for their ability to predict fixed or remaining lifetime risk.

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The Department of Obstetrics and Gynecology at the Medical College of Georgia at Augusta University is a comprehensive clinical service and educational department, specializing in the healthcare of women both on a primary and referral basis. We provide quality clinical services in following areas: General Obstetrics and Gynecology, Gynecologic Oncology, Maternal-Fetal Medicine, Reproductive Endocrinology, Infertility, and Genetics, and Urogynecology and Pelvic Surgery.

General Obstetrics and Gynecology provides a full range of general obstetrical and gynecological services ranging from outpatient care to surgery, and from routine visits to complicated consultations. In addition to normal obstetrical and gynecological services, our specialized research and interest areas include urodynamics, dysmenorrhea, menorrhagia, pelvic pain, menopause, and others.

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