BIOL Notes for Exam #3 PDF

Slide 15- Personal Genome Services, Genetic Ownership & Privacy What are personal genome services? - Informs that directly provide to users their genetic data (without doctor or prescription) - General interpretation of data - Often called Direct to Consumer (DTC) services (interchangeable)...

Slide 15- Personal Genome Services, Genetic Ownership & Privacy What are personal genome services? - Informs that directly provide to users their genetic data (without doctor or prescription) - General interpretation of data - Often called Direct to Consumer (DTC) services (interchangeable) - When 23andMe takes your saliva, they use Single Nucleotide Polymorphism (SNP) genotyper, NOT the same as Whole Genome Sequencing - Only counts SNPs - After machine detects SNPs, it gives a predictive measure of how these SNPs may arise phenotypically - Correlational studies (e.g. GWAS) are used for predictions - that’s why GWAS does not need entire genome - Risky: GWAS/correlational studies are not perfect predictors; thinking so is genetic determinism What is privacy? - Privacy of Choice: Freedom to make life choices - Physical Privacy: Right to be left alone - Proprietary Privacy: Ability to use/exploit one’s unique qualities - Privacy of Information: Safeguarding one’s uniquely personal information through preventing collection or disclosure What is special about genetic privacy? - Genes give information about your medical future and relatives - Genetic data can be stored permanently, widely distributed, and difficulty to remain anonymous - Use of genetic info is broad - Open ethical, legal, and scientific question to use of genetic info and tech in the future 23andMe process - Customers: - Set up account - Receive kit in the mail - Fill out health survey + privacy agreement - Return the saliva kit to 23andMe (kind of) - Sample handling and genotyping is contracted out to LabCorp - 23andMe keeps data and email addresses - LapCorp has liquid handling robots preparing DNA - After PCR amplification step, samples are transferred to SNP genotyping chip - Chips designed in advance to detect nucleotides at around 900K sites of interest - Not DNA sequencing, less likely whole genome sequencing (WGS) About Doug’s data  - Services obtain SNPs (not genome sequences) - His data had 96,000 SNPs but 23andMe promised 900,000 - Risk assessments are estimated from known correlations between SNP genotypes → genes or phenotype - 23andMe used data of associated genome regions with phenotypes to create new findings of disease risk and phenotype prediction - More predictions (i.e. caffeine consumption: likely to consume more) - Reports are phenotypic scores/prediction - Concerns of accuracy are not new - This is for entertainment 23andMe’s relationship with FDA - 23andMe marketed FDA approval but in 2014, the FDA ordered 23andMe to stop selling DNA kits - FDA claims 23andMe: - Diagnosing/practicing medicine (without medical approval) - False positives could result in people doing unnecessary surgeries/other bad things - Did not reach out to them yet marketing approval - FDA also warned other DTC companies about genetic testing (not just 23andMe) - In response to FDA’s order to stop selling, 23andMe reported only ancestry while seeing FDA approval for one report at a time - Diversified into drug and development and personalized health care - Risks are seen when 23andMe makes medical predictions that create false positives (causes unnecessary anxiety and treatment) - Anonymity is another major concern: - Personal genome services sell data to health companies and have major data breaches - Golden State Killer never released genetic data but family members did - That’s how he was arrested - No one is truly anonymous - Very easy to connect someone with a crime using genetic data that only somewhat resembles yours Regulation of Personalized Genome Services - Regulatory arms of federal government believe reports from genetic data should be filtered through medically verified results/claims - 23andMe made medical interpretations of your results proprietary - Yet they are packaging publicly available data (you should already have access to your data) - Nothing stopping you from looking yourself up on SNPedia, Promethease, and Genotation that collect all known associations between SNPs and phenotypes - SNPedia was bought by MyHeritage.com → inadvertently shared data  - Importantly, medical relevance of SNPs is public knowledge – these platforms communicate publicly available info - Boils down to whether you should be allowed to conduct your own medical tests on yourself - Arizona law allows patients to order their own genetic tests – should this be allowed? - If you can take your own blood pressure, should you be allowed to order an MRI? - Who interprets the results? Especially if you order your genome info? - Data from personalized genome services are permanent, easy to distribute, and inherently non-anonymous and therefore carry many privacy risks Warning signs about 23andMe - 23andMe and Ancestry are laying off workers with declining interests in DNA tests - Market saturation - DNA market came to point where most early adopted already used it - Privacy - Companies can sell your data to third parties (including Silicon Valley startups and pharmaceutical giants - Also DNA sharing is governed by companies’ often dense privacy policies - Utility - DNA tests aren’t as accurate as we’ve hoped (perceived usefulness is limited) - Doug’s opinion: 23andMe spent millions to get integrated into healthcare (e.g. integrating genomic data with personalized medicine) - The hope was that genetic testing services for entertainment would end up being a quaint start for a much larger business - Monetization of genetic data for drug development continues → Drugmakers set to pay 23andMe millions to have non-exclusive access to consumer DNA - Doug’s opinion: 23andMe is not about selling DNA kits to consumers → trying to be a healthcare company but is currently a data broker - Doug’s further opinion: 23andMe SNP data are just not as valuable as they once were - GeneDX has leading exome and genome tests to accelerate diagnosis to improve outcomes for pediatric patients - Test revenue grew to $60 million, an increase of 77% year-over-year - Exome and genome tests translate “complex genetic data into clinical answers that unlock personalized health plans, accelerate drug discovery, and improve health system efficiencies” What’s up with competitors (such as Ancestry.com)? - Ancestry combines DNA and genealogy data (family tree) - For entertainment but data is also powerful Combining genomic data with other forms of data (metadata) is uniquely powerful - 15 year old tracked down anonymous sperm donor biological father - Submitted saliva sample to FamilyTree.com (could have been any related site) - Father never used this site…  - Teen contacted two men who did not know each other but had same Y chromosome as him - Two men shared surnames albeit spelled slightly differently - His mother also knew the father’s approximate date and place of birth - Teen turned to another internet service (Omnitrace.com) and bought info on people born in same place and same time as his father - One man matched surname → teen contacted him 10 days later - Now have an amicable relationship Implications on adoption - Finding sperm donors is becoming mainstream - Anonymity cannot be guaranteed for sperm donations - Concept of closed vs open adoptions is obsolete - Applies to same-sex couples and child custody - Activists are trying to end secrecy for sperm and egg donors – this campaign that troubles some LGBTQ families - You are not anonymous De-Anonymization / Concerns about anonymity are real - Yaniv Ehrlich cross referenced Y chromosome data with publicly available information - Anonymously listed people in genetic studies could be easily identified - When Erlich published the results of his work, he didn’t revealed research participants’ names - He didn’t spell out all the steps he had taken to find their identities - “There is an obvious tension, because as a scientist you want to tell everything about how you did the work. On the other hand, you can’t do that, because it will expose people’s identities to the world” - Some researchers believe genetic data should be deposited to central data-hosting agencies → in other words, data would be off-limits to the public - Alternatively, scientists should be more transparent about the difficulty of guaranteeing anonymity - May be difficult for someone signing up for a research study to understand all the ways their data might be used in the future (and weigh the risks when even researchers do not necessarily know them) - Take home message: Despiterules and regulations about privacy, there may not ever be true anonymity when it comes to your genome The Golden State Killer - Sadistic rapes/murders in 1970s and 1980s that remained unsolved - At one point, occurred twice a month - Solved when investigators identified Mr. DeAngelo then matched his DNA to two unsolved murders in Ventura County, CA - Investigation by a crime writer rekindled interest in this case - Details not published but not very difficult to outline - Used DNA in crime scene to construct genetic profile (like using Doug’s raw data in 23andMe) - Data used to make a profile, using a site to take raw data from other sources (in this case, GEDMatch)  - Identify relatives (genealogy), find who they are, and with a little luck, identify the suspect - Surveil the suspect, obtain discarded DNA samples (e.g. from the trash) - Test for match with the crime scene - Geneticists studied the implications of this case: DNA can narrow identity to one in 20 people from a database of 1.3 million - EVEN IF THE PERSON’S DNA IS NOT IN THE DATABASE - This could identify 60% of white Americans even if they have never submitted their DNA into a database - GEDMatch had 1 million records (0.5% of the population) - If just 2% of the population is sampled, the odds of being found jump to 90% - Genealogy allows you to identify unsampled individuals when combined with other data - See Cook/Van Cuylenborg Double Homicide Cold Case - Datasets are much larger now - Illustrates lack of genetic privacy, especially when combined with other metadata (age, geographic location, genealogy) - Recall the 15 year old boy who tracked down sperm donor father? - Genetic database in this case was GEDMatch: collects DNA from many users across services, accepting a raw data format - Far more extensive genealogical data than just using DNA data alone (forms connections in the network of families) - Authorities did not need to use de-anonymization algorithms in this case - Other criminal suspects were identified since this case broke in April 2018 What does the future hold for databases and genealogical networks? - They will grow, as will our ability to identify/learn about genomes not represented in database - Most individuals are already identifiable using these methods - 6000 relatives spanning seven generations (world’s largest family tree with Kevin Bacon) - Growth in DTC Genetic testing: - Small growth for Powerof1Million, then stopped - Small growth for 23andMePress, slightly growing - Big growth for AncestryDNA Press, exponentially growing State laws of personal genomics, privacy, and law enforcement - According to the New York Times on 5/21, two new laws restrict police use of DNA search method:  - New laws in Maryland and Montana are the first in the U.S. to restrict law’s enforcement’s use of genetic genealogy (DNA matching technique that identified the Golden State Killer in 2018) - Effort to ensure the genetic privacy of the accused and their relatives - According to The Center Square on 7/21, Florida on Wednesday became the nation’s first state to enact a DNA privacy law - prohibiting life, disability, and long-term care insurance companies from using genetic tests for coverage purposes - “Given the continued rise in popularity of DNA testing kids,” Sprowls said Tuesday, “it was imperative we take action to protect Floridians’ DNA data from falling into the hands of an insurer who could potentially weaponize that information against…policyholders” - Since 2021, there have been 29 bills introduced across 16 states that relate to genetics and insurance underwriting - Privacy regulations help, but security breaches happen - Nearly ⅔ of GEDmatch’s users opt out of helping law enforcement - 23andMe lay off 100 people as DNA test sales decline (CEO was “surprised” to see market turn) - Security breach exposed more than one million DNA profiles on a major genealogy database Should you be worried about your DNA privacy? - 23andMe said it will not share your information with any public databases, insurance companies, or employers, but it may be shared with “service providers” - won’t violate federal law but is a databroker - There are precautions and reassurances: “DNA data in encrypted databases ensure restricted access, and all DNA data is encrypted at rest and in transit” - Despite all these precautions, 23andMe include a disclaimer about data breaches in its privacy policy: “In the event of a data breach, it is possible that your data could be associated with your identity, which could be used against your interests” - Data security seems to be at the top of their mind for these companies, and they do store genetic and personal info separately - Yet, at the end of the day, no company is 100% safe from data breaches, so the only way to guarantee your security is to not give out your info in the first place Major 23andMe data breach - 23andMe confirmed that data from its users have been compromised - Systems were not breached; attached gathered the data by guessing the login credentials of a group of users (i.e. all your data is not all over the internet, but login data is) - Full picture is unclear of why data was stolen, how much more attackers have, and whether it was focused on Ashkenazim Jews - Hundreds of thousands of Chinese customers were also targeted - Doug’s opinion: doesn’t matter whether the logins were stolen or data was stolen. The issue is quite clear to the informed consumer that their data is not perfectly safe What can you do? - Choose unique, impossible-to-guess passwords - Doug believes everyone needs a password manager  - Request to delete your data - If you haven’t already, think twice before sharing genetic information - Doug believes all true best practices for any online info - Consumers are not particularly informed or responsible when it comes to privacy - Given current practices from data brokers, informed consent is unrealistic The Delete Act - By Jan 2026, the California Privacy Protection Agency must create a way for people to make data brokers delete their data with a single request - This agency has the ability to ensure data brokers are deleting info when required + register when required to register - Doubles the fine for non-registration and increases amount of info brokers have to provide every year when they register with agency, includes auditing requirements - The Delete Act - Current framework: when you initiate your California Consumer Privacy Act request, it can take up to 90 days to fulfill for every single broker (600 registered ones) - Once you exercise your privacy rights, there’s nothing to stop that broker from turning around and then immediately collecting info again → selling it from some other third party - The Delete Act wants to require data brokers registered with the Attorney General (privacy enforcer) to move to the California Privacy Protection Agency - Create a way for any of us to go to the agency’s website and delete all personal info within a few mins, for free for anyone with disabilities - Brokers must delete their info every 45 days and stop selling - You can choose when to share your info for all time in the future - The Delete Act Take home messages - 23andMe.com and ancestry.com were the industry leaders, but many DTC services out there - Services used SNP data to trace ancestry and correlate genetic background with phenotypic traits - FDA attempted to regulate genetic testing (since it regulates for any medical device or test) - 23andMe moved into formal genetic testing, research, and drug development - Finally as a data broker - Although personalized genomics and personalized medicine will become a significant factor in health care, SNP based firms are not keeping up - Ancestry.com leveraged its large genealogical database and combined it with genetics - Large genetic databases combined with other data present opportunities for law enforcement - Serious challenge to privacy - Using relatives to get info will be an exponentially powerful tool (one that requires legislative action) - Other genetic privacy issues abound - Genetic data is not anonymous - These concerns overlap broadly with privacy in other disciplines  - Not easy to opt out Slide 16 - Personalized Genomics, Polygenic Risk Scores The Next Step for Direct to Consumer (DTC) Genetic testing - Starting to predict phenotypes and make business from it - Exponentially growing industry - Could be first way to encounter genetic data What can polygenic risk scoring do? - Identity people at high risk for disease if other warning signs are absent - Potential use in lab - 23andMe thinks polygenic risk scores are ready for the masses - Experts aren’t so sure Polygenic Risk Scores and Personalized Medicine - Personalized medicine: promise to use genomic data to understand and eventually change health outcomes for individuals - Immense global effort - GWAS can correlate phenotypic variation with SNP variation of population (e.g. humans) - Now, this data generates polygenic risk score for individual - We are supposed to convince ourselves that 23andMe and GWAS are essentially the same thing - Post-GWAS era may involve more than SNPs (including genetic variation that is KNOWN to influence phenotypes) - BUT we are NOT there yet - Reported by telling you the number of possible risk variants are alleles and how many you have that are associated with higher risk - Gives you a percentile for risk Risk Scores for Coronary Artery Disease - At some level, we can translate genomic data into future risk categories for this disease - Could save or extend thousands of lives in a public health setting What do risk scores not consider? - Plots of quantiles of risk score do not consider environmental variation - For example, relative risk of heart attack is determined by combination of genetics and lifestyle - Important picture on slideshow 16, slide 6 - High lifestyle risk + high genetic risk = high overall risk - High risk of either genetic or lifestyle doesn’t matter too much - Cannot choose your genetics but you can choose your lifestyle - that is what REALLY matters - Important for discussion of heritability or genetic risk  - Genetic variation does not predetermine outcomes (genetic essentialism) - Important distinction: Genetic essentialism is more about perception of fixed identity based on genes/stereotypical judgements while genetic determinism is about genes that completely determine outcomes What racial group do polygenic risk scores work best for? - Europeans, because data from Europeans were used to calculate disease risk - American accuracy falls between 0.40 to 0.95 - South Asian accuracy falls between 0.30 to 1.00 - East Asian accuracy falls between 0.10 to 0.80 - African accuracy falls between 0.20 to 0.50 Update about educational attainment with polygenic risk scores - Around 3 million individuals with 3,952 genome-wide-significant SNPs - Massive size from 23andMe - Explains 12-16% of educational attainment variance (increased from 11-13% in previous study of 1 million individuals) - Doug thinks this looks like an incremental advance (at best) given that we know genetic correlations with educational attainment can be misinterpreted - For college completion, the polygenic risk scores graph shows that the genetic risk and completing college are dramatically different - However, it doesn’t factor environmental effects (noise) - similar to coronary artery disease - Different levels of educational attainment are highly variable genetically and do not form distinct groups (statistical fit to the data with groups is poor) - Variability makes it dangerous to make predictions about individual outcomes - Statistical differences may be useful in public health context (which groups should be more regularly screened for heart disease) - BUT NEVER PREDICT ONE’S FUTURE BASED ON RISK GROUP - Not okay, basis of discrimination Health lifestyle mitigating risks - Lessons from coronary artery applies to other traits → early death - Individuals were assigned apolygenetic risk scores based on genes correlated with human lifespan - Genetics put you at greater risk for early death but healthy lifestyle could mitigate risk by about 62% - Regardless of genetic risks, participants were 78% more likely to die early with unhealthy lifestyle / die later with healthy lifestyle - Social/policy intervention are effective for traits that are heritable (i.e. IQ and Educational attainment) - Similar to increased awareness for autism link to low empathy What’s the deal with Orchid? - “Have healthy babies - safely and naturally, protect your baby from diseases that run in your family”  - “Identify your healthiest embryo - mitigate your family’s genetic predispositions with advanced genetic screening for your embryos - Calculate risk scores of parents estimating likelihood of encountering common illnesses (i.e. heart disease, diabetes, schizophrenia) - Then calculate likelihood of passing risks to offspring - Parents can use IVF and Orchid’s embryo screening package - First (mostly likely not the last) consumer-driven model of human reproduction - Marketing strategy encourages regular use of IVF for customers who can afford it - Geneticist says methods are not ready for prime time - Ethicists expressed severe concerns Genetic screening of embryos for IQ - Heliospect Genomics, US-based biotech startup, is promising prospective parents smarter children through genetically screening embryos (controversial and expensive) - Business model borrowed from the plot of Gattaca - Charging up to $50,000 to test 100 embryos for genetic markers linked to higher intelligence - Claims it can increase a child's IQ by at least six points (how would they know?) - By late 2023, five couples used Heliospect’s prediction algorithm - Company assures users it follows all US laws and regulations / service is legal Slideshow 16’s Take Home Messages - Personalized genomics involve some kind of polygenic risk score (i.e. attempting to predict phenotype from genotype - Polygenic risk scores can be calculated from GWAS data and personal genome services (e.g. 23andMe) - The simplest polygenic risk scores add up the effects of each individuals’ genotype (each SNP throughout the genome → on the phenotype) - Polygenic risk scores are typically vaulted using data from Europeans → prediction of genetic risk is less accurate for underrepresented communities - Problem being addressed but new problems will emerge - Polygenic risk score often overstates degree of genetic essentialism, so people should be cautious about individual healthcare decisions from them - Public health decisions based on statistics is a different story - Applying statistical association from population to judge individual’s qualities or outcomes sounds like bigotry - Cautionary notes about GWAS apply here - are we really studying genes for educational attainment? - Combining genomics with reproductive technologies have significant ethical concerns - Personalized genomics and polygenic risk will become significant factor in healthcare as we move towards personalized/precision medicine Slide 17 - Genetic Privacy and Ownership: Healthcare and Research Healthcare and Insurance - Concept of insurance is based on mutual uncertainty - Insurance companies can raise/lower rates depending on gender, marriage status, grade, type of car - Risk categories (placing bets on risk outcome → make more money with less risk) - Males are involved in more risky behaviors - Marriage shows more “stability” - Smart kids tend to be safer - Sport cars are more reckless - If you know your medical future, Doug would advise you to only buy insurance if you will be unhealthy - Young healthy people don’t buy health insurance, while old sick people do - If insurance knows your medical future, they will only sell you insurance if you’re going to healthy - Or else they will charge you a lot of money - Hence the individual mandate in the ACA - Insurance companies are placing bets on health outcomes - Average person pays in more than they get out - The fact that they make so many bets means they will always make money - Casino analogy? - Individuals place only one bet - Pay a premium cost to avoid costly events they could not afford - Risk factors that predict risk can be small to us individuals - Companies can make money when this risk is aggregated (e.g. insurance companies) - Useful indicators of future health is therefore extremely valuable (i.e. your genetic makeup) What is GINA? - Genetic Information Non-Discrimination Act of 2008 - Title I: Prohibition of Genetic Discrimination in Health Insurance - Title II: Prohibition of Employment Discrimination on the basis of genetic info - Amended existing federal law: ERISA and various Federal Employment Discrimination statutes - Strengthened protections from the ADA (Americans with Disabilities Act) and HIPAA (The Health Insurance Portability and Accountability Act of 1996) - Prior to GINA, most states (except MS, PA, WA) prohibited genetic discrimination in health insurance - 45 states prohibited the use of genetic info in determining insurability - 42 states prohibited the use of genetic info in risk classification or pricing - 27 states prohibited the mandatory acquisition of genetic info - This was a means to provide uniform standards - Federal laws often do that Why GINA? - Health Insurers in the Individual Market Shall Not (102(b)) - The launch of the Human Genome Project in 1990 provided impetus (motivation) for seeking state federal protection against genetic discrimination, supposedly  - “Congress has a compelling interest in relieving the fear of discrimination and in prohibiting its actual practice in employment and health insurance” - GINA was not in response to a wave of discrimination: RESPONSE TO POTENTIAL FEAR - According to section 2(5) of GINA, federal legislation “is necessary to fully protect the public from discrimination and allay their concerns about the potential for discrimination, thereby allowing individuals to take advantage of genetic testing, technologies, research, and new therapies” - Require an individual or family member to undergo a genetic test - Establish rules for eligibility to enroll on the basis of genetic info - Adjust premiums or contribution amounts based on genetic info - Impose preexisting condition excursions based on genetic info - Request, require, purchase genetic tests or info for underwriting purposes What GINA doesn’t do - GINA’s employment discrimination provisions do not apply to employers with fewer than 15 employees - GINA does not separate genetic info from standard medical records - Combination of genetic testing, health records, and wearable devices that track health data (metadata) can blur the lines between genetic testing and pre existing conditions - It is still okay to use family history to adjust premiums - a mixture of genetics and environmental generalizations applied to an individual - Doug is not sure this is okay - GINA does not cover life/disability insurance at all GINA - life insurance conundrum - GINA does nothing to prohibit discrimination in life insurance, disability insurance, long-term care insurance, mortgages, commercial transactions, or any of the other possible uses of genetic info - These carve outs and exemptions exist because of effective lobbying - Insurance lobbyists note a tense relationship with these carve outs; use of genetic info is rare but may be a legislative target if it becomes common What genetic testing means for life insurers - Life insurers could test each applicant’s genetics and write their own policy - Not taking place, but there is a path leading towards it - Regulations/legislation would need to follow if it takes place - Highly controversial for insurance companies to have access to genetic profiles, but it may be necessary - If evolution of genetic testing continues and government prevents life insurance companies from obtaining genetic profiles, this could cause asymmetric info - A case in which one party to a transaction (consumers) have better information than the other party (insurers) - Yet there are rising concerns and reports of genetic discrimination in life insurance The Affordable Care Act (ACA) of 2010  - The ACA prohibits issuers of health insurance from discriminating against patients with genetic diseases by refusing coverage because of “pre-existing conditions” - Is your genome the ultimate pre-existing condition? - Certain genetic tests cannot be used (e.g. gender tests) - The ACA provides protections for patients with genetic diseases by establishing that certain health insurance issuers may only vary premiums based on a few specified factors, such as age or geographic area → prohibits the adjustment of premiums because of all medical conditions - GINA said certain genetic tests could not be used as a basis for rate adjustments - Only means of rate adjustments specified by the ACA are allowed - ACA strengthened GINA Bottom line of insurance - All insurance depends on mutual uncertainty - If you know you’re going to get sick, you are more likely to want to buy insurance → companies are less likely to want to sell it to you - If life insurance companies know your genetic predispositions, they may raise premiums (sounds unfair) - Is it fair if you have a right to test your genetic predispositions but do not have to report your findings to a potential insurer? - Does it make sense to ban genetic discrimination to protect consumers but not insurance underwriters? - The extent of this potential problem depends on genetic determinism…how much does our genetic info tell us about future health outcomes? - Information about BRCA1, BRCA2, and APOE4 is extremely valuable! - How would we resolve this? - Protect individual genetic privacy (e.g. consumers over insurance underwriters)? - Mandatory sharing of your genetic info? - Less reliance on the insurance model for health care (e.g. a public option)? - We can see how science may influence (or should influence) policy Insurance Take Home Messages - Concept of insurance depends on mutual uncertainty - We are willing participants in a casino that must profit, or there is no health care system - We do not know how certain/uncertain genetic info will be in the future - Insurance companies value info that predict health outcomes - Individuals also value that info and do not want to share it - Insurance companies are wary of an asymmetry of knowledge - States had varied protections: Insurance companies operate across state boundaries so federal legislation was needed - GINA: filled gaps from prior Federal and State laws that wanted to separate genetic info from insurance companies when assessing risks / not use - Employers are restricted from genetic testing and discrimination  - Life/disability insurance are not covered under GINA - could be addressed if companies misbehave - ACA refines this coverage (i.e. premiums only based on specific conditions, not all) but gaps remain. Consumers should know this (e.g. life insurance) Ethics, privacy, and ownership in medical research - Institutional Review Board (IRBs) must approve all research involving human subjects - Derived from the Nuremberg Code, which requires voluntary consent from human subjects - Capacity to consent - Freedom from coercion - Minimization of risk and harm - Favorable risk/benefit ratio - Qualified investigators using proper research designs - Freedom for the subject to withdraw from study at any time - Standards influence our expectations outside of the research field - 1050s: Thalidomide - Prescribed for nausea during pregnancy - Caused significant birth defects - Incomplete drug safety review - 1964: Declaration of Helsinki - Established ethical principles r.e. human experimentation - Addresses religious concerns - Not binding itself, just driven legislation worldwide - Right to self-determination, informed decisions - Individual welfare over benefits to society (cannot sacrifice one’s health for good of others) - Ethical considerations more important than law - Constantly runs into conflict: - Africa didn’t believe in birth control so 6 mill people died from no sexual protection - Constantly revised (latest 2013) - 1996: Henry Beecher - New England Journal of Medicine - Highlighted widespread studies where therapies had no therapeutic effects and were done without patient consent - Led to US legislation - Ethical problems motivated Legislative advances, albeit slowly Tuskegee Syphilis Study (1932-1972) - Before Nuremberg code - 1932: 600 African American men (rural sharecroppers) were recruited - 399 had syphilis - Initially a short-term project: subjects had free medical care, food, burial - Treatments at the time were ineffective  - After funds were lost, the study continued as a long-term observational trial - 1947: Penicillin was accepted as an effective treatment for syphilis - Yet none of the subject were informed they had syphilis or were treated - 1964: Study was not revisited after the Declaration of Helsinki - 1965 (Irwin Schatz) and 1966 (Peter Buxtun): Concerns from physicians were raised, read the work and questioned the ethics - CDC supported continuing the study - Buxtun went to the press → 1972 NYT times story which prompted congressional hearings - Led to the termination of the study and the 1974 passage of the National Research Act - 1972: 28 had died from syphilis, 100 dead from related complications, 40 wives and 19 children infected - 1974: Survivors and families settled out of court - 1979: The Belmont Report led to Federal Policy for the Protection of Human Subjects - What is now the “Common Rule” - basis for IRBs - Institutional Review Boards (IRBs) include laypeople - established in scientific research groups and hospitals to review study protocols and protect patient interests - Ensures participants are fully informed - 1994: Conference at UVA led to a committee recommending a formal apology “What was done cannot be undone. But we can end the silence. We can stop turning our heads away. We cnan look at you in the eye and finally say on behalf of the American people, what the US government did was shameful, and I am sorry…To our African American citizens, I am sorry that your federal government orchestrated a study so clearly racist” - Bill Clinton, 1997 Modern Institutional Review Boards (IRBs) - Emphasis on confidentiality/privacy/anonymity in the use of tissues/cells/genomes - Research should not collect unnecessary info about its subjects - Identifiers should be removed, and experiments designed to preserve anonymity - Destroy identifying genes (e.g. hair color) - Participant must be taken in a poll where their traits are broad enough to be unidentifiable - Only the investigators and research team can identity the responses of individual subjects - Two options for anonymity of information collected: either the project does not collect identifying info of individual subjects (i.e. name, address, email address) or the project cannot link individual responses with participants’ identities - Issues with IRBs and the Common Rule: - Ownership: Tissues from millions of Americans are used in research without their knowledge - You no longer own your own DNA if chain of custody is broken - The Case of Henrietta Lacks: - Born in 1920 from Southwest Virginia - 1951: Lived in Baltimore and went to Johns’ Hopkins’ reporting a “knot” in her womb - Diagnosed with malignant adenocarcinoma of the cervix and died later that year  - Samples taken without her knowledge or consent were cultured - this was customary at the time - Become the HeLa cell line, commercialized and widely used in biomedical research - 1980s: Family medical records released without permission - 2013: German researchers published her genome without family permission - Lacks’ family is now involved with the NIH regarding decisions to use her cells and genome - Other medical institutes (HHMI) have accepted donations for reparations to the family - Read the award-winning book by Rebecca Skloot - Even if Ms. Lacks gave consent, could she have seen what she was giving consent to? - 1990 in the California Supreme Court: Moore v. Regents of the University of California - John Moore was a leukemia patient at UCLA in 1976 - His consent to surgery noted that physicians could dispose of severed tissue by cremation - 1983: Moore was asked to sign an agreement granting “the University of California all rights I, or my heirs, may have in any cell line or any other potential product which might be developed from the blood and/or bone marrow obtained from me” - Later, Moore’s attorney discovered a patent on his cell line (“Mo”) and his physician was receiving more than $300k + stock shares - Moore sued for a share, lost, and appealed up to the CA supreme court (lost again) - Court did find the physicians should have revealed his financial interests - Moore could sue for any damages resulting from that lack of disclosure - More signed a contract, but two things: - Did he really provide consent? - Did he understand what he provided consent for? - Similar to Facebook - do you consent to have them know so much about you? - “Clinical biospecimens” are leftovers from blood tests, biopsies, and surgeries - Common Rule doesn’t require consent for “non-identifiable” samples - Incidentalomas: Patients cannot be informed of conditions discovered that fall outside of research objectives - Important questions to consider: - Who determines what is deemed important to someone’s medical care? - What if there are incidental findings not pertinent to their present condition but are important to know? - Wide range of opinions on handling these types of findings  - Should we ask beforehand if patients would like to be informed when unexpected results arise? - THAT WOULD VIOLATE CURRENT IRBS - What happens when there are new research findings? - How do patients grant informed consent when even the researchers are uncertain of what will be found and the implications of genetic data on future health outcomes? - Same issues arise in all forms of personalized genomics - would you talk to your family before or after signing up for 23andMe? - In 2020, NIH’s All of Us Research returns first genetic results to participants who have donated biosamples - Program is committed to ensuring participants have access to their own info - Developed a robust informed consent process to give participants info and choice: - Whether or not to receive results - Which results they want to receive - Provides access to genetic counselors to answer questions from participants and health care providers - Should people who volunteer for genomic studies be told about unrelated disease mutations in sequence data? - Researchers (often physicians) view incidental findings are an opportunity to boost the health of millions - Bioethicists respect hesitance about receiving potentially genetic discrimination or unwelcome info - In this study, participants could opt-out (2% did so) - half of this 2% changed their minds later on - Opt in default is more powerful because it’s easy to get in than get out - Black participants were more likely to opt-out and less likely to change their minds - Based on this fact, it’s odd how NIH does not recommend to give genetic info unless they have direct consent - What would the data look like if this was an opt-in? CHECKBOXES OVERSIMPLIFY CONSENT - American College of Medical Genetics and Genomics (ACMG) generated a list of actionable genes that should be reported at all (i.e. BRCA1, BRCA2, APOE4) - Out of tens of millions who have been genotyped/sequenced for research, only a tiny fraction had findings returned for their potential medical benefit - Doctors believe genomics that if genomics give valuable info, they should collect it and tell patients - Similar to how taking blood pressure is a default practice - We don’t have as much agency as we think - Anonymity: Anonymity of genetic data is a myth (as we have discussed)  - Difficult to guarantee - De-anonymization algorithms could thwart privacy protects in medical research Take home messages of Privacy and Medical Research - Rules don’t solve problems because practices are slow to implement - We don’t really know anything about privacy until we’re put to the test - Ethics of medical research practices have evolved - from Nuremberg code to the Declaration of Helsinki - Lessons learned from unethical conduct over the years - egregiously the Tuskegee Syphilis experiment that prompted legislation and ethical/privacy protections in medical research - Modern IRBs (aka The Common Rule) strive to protect confidentiality and privacy but problems arise, especially when inherently personal genomic data is stored indefinitely - and we don’t know important this info is or will be - Anonymity in medical research can mean that individuals may be denied ownership of their own info - Anonymity can mean that researchers cannot report ‘incidentalomas’ to patients - Anonymity of genomic data is very likely a myth - Some seek IRB revisions (i.e. more openness between research and subjects, sharing research agendas/outcomes) - If privacy were lost, they need to build trust that the info is properly used Slide 18 - Genetic Ownership in Law - Patents Thomas Jefferson’s analogy - Candle aflame transfers to another with the same flame intensity - Ideas shared cannot be extinguished Early Patent History - Ancient Greece - evidence of rights to “creators” being protected for ~1 year - 1300s: Britain had “letters patent” - monopolies and political patronage granted as gifts from the king - 1421: First invention patent traced to Florence - 1474: First patent law in Venice - Laws established a process to grant exclusive rights for 10 years in the territory controlled by Venice in return for public disclosure - 1624: English Parliament passed the Statute of Monopolies - Not to create a new right → to rein in the king’s power to grant monopolies as a source of income and political patronage - Invention patents were intended to promote the collective good, replacing monarchic whim with a principled rule of law - US constitution promoted “the progress of science and useful arts, by securing for limited times to authors and inventors the exclusive right to their respective writings and discoveries: - Congress passed a patent statute based on this authorization with Thomas Jefferson as the first Commissioner of Patents Modern Patents - Patents are compromises that grant monopolies but protect intellectual property, allowing those those to reap the benefits of innovation - Regulate around market failures for common good - Tech companies don’t invest in long term benefit companies - All patents are anti-competitive - innovations are not open to the free market until the period is over - Issue is inherently gray, trying to promote innovation without suppressing competitive spirit - For example, drug costs are often high because it takes many years to develop drugs + profits need to be made then - In 2014, the cost of drug development was 2.6 billion (number has high variance) - Nobody is going to produce drugs if their intellectual property immediately becomes a public good - Drug companies are reluctant to develop drugs targeted for a rare disease - When they do, the drugs are expensive - Once the “torch” expires, it becomes public property What is patentable? What are patents for? - An invention must be a patentable subject matter - U.S. definition: “Any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof” - Invention must also meet three criteria for patentability: a) novelty, b) nonobviousness, and c) utility - Must describe an invention in sufficient detail that a “person having ordinary skill in the art” will be able to make and use of it without “undue experimentation” - Very important patent process in the U.S.:Patent office subsidizes at university - Helps professors get patent → university makes profit History of genetic patents - June 1980: Diamond v. Chakrabarty - The U.S. patent office denied General Electric’s patent application for a bacterium selectively bred to metabolize petrochemicals - designed to digest oil spills - Argument: you cannot patent a life form - Supreme Court determined this was an invention eligible for patent protection - Case was decided amid a very public national discussion about recombinant DNA and fears of biohazards arising from splicing genes into living organisms - There were also successes in gene cloning to show the promise of biotechnology - Supreme Court decision was nonetheless interpreted as a strong sign that products and organisms from recombinant DNA technology / genetically modified living organisms were patentable  - Weeks after U.S. Supreme Court decision, the General Secretaries of the three largest U.S. religious denominations jointly signed a letter to President Jimmy Carter raising questions and concerns - Who shall determine how human good is best served when new life forms are being engineered? - Who shall control genetic experimentation and its results which could have untold implications for human survival? - Who will benefit and who will bear any adverse consequences, directly or indirectly? - These are not only scientific but moral, ethical, and religious questions - Deal with the fundamental nature of human life and the dignity/worth of the individual human being - Many (all?) questions are still worth asking - As students interested in genetics, we seek to be informed of the scientific aspects of these questions Erythropoietin (Epo) is a poster child of a valuable gene patent - Hormone produced in the kidney that protects red blood cells against destruction and stimulates stem cells of the bone marrow, increasing their production - Epo is useful in treating anemia associated with kidney disease, diabetes, and some cancers - Epo shows how good attorneys and these patent cases can change the history of drug development (and involve big bucks!) - Epo is a multibillion-dollar therapeutic protein that was central to the rise of Amgen - Synthetic Epo is manufactured using recombinant DNA technology, licensed to Amgen - Amgen was founded on a business model of sequencing genes encoding protein therapeutics - First gained notoriety by having E. coli produce Indigo dye, published in Science - Result from their Epo research was a drug named EPOGEN, where human Epo is produced by Chinese Hamster Ovary (CHO) cells grown in culture - Generated revenues of ~$660mil/year, totaling more than $25 billion worldwide between 1987-2011 - This case highlights the high stakes of these patents and legal wrangling over patents - In 1987, “The Genetics Institute” was issued a patent on the protein itself, a means of isolating it - NOT A MEANS OF PRODUCING IT - Amgen had a similar patent approved months later, effectively simultaneous - Amgen patented the DNA sequence and a means of producing it commercially - Thus, neither company could proceed without infringing on the other patent - After 8 years, the courts upheld Amgen’s patent and fined “The Genetics Institute” for infringement - Amgen’s stock went up 12% in one day - Subsequent modifications to the protein itself and methods of producing it are constantly honing in on Amgen’s turf; the courts decide whether something is a violation of the patent or something really new - Amgen survived these patent challenges! - Patent on the recombinant Epo protein expired in 2015 The Venter Patents - Back to genomics: Prior to large scale DNA sequencing, identifying and sequencing genes was difficult and costly - Automated sequencers changed things - Craig Venter (NIH researcher who founded Celera) sequenced coding sequences (ESTs) and identified potential drug targets rather isolating genes of interest then sequencing them - Wanted to patent human genes and sell subscriptions to pharmacies - Venter’s Celera was funded by drug companies looking for early access to human genes that might point to targets of drug development - The NIH was not willing to fund the research at the time, and no private companies would fund the collection of genetic info if the fruits of that research did not advance their business - Went private sector - Patent law argues that nefarious intentions were necessary for innovation to occur - Would this funding have been available without patents? - Next generation sequencing changed things further - Identification of gene sequences is now trivial - We learned from the HGP that innovation is shared Myriad Genetics CEO Claims He Owns Your Genes - BRCA is the poster child for debates on the issue of genetic patents - Mary Claire King (scientist and Human Rights Activist) found a linkage between BRCA1 (on chromosome 17) that is associated with 5-10% of bread cancer cases - She also later mapped BRCA2 - Race was on to clone and sequence the gene, a race that was essentially won by Myriad Genomics - Lots of litigation resulted in Myriad being the sole source for BRCA testing in the US - Health organizations challenged to end genetic patents - Myriad Genetics became the only commercial BRCA testing laboratory in the US - This meant if you wanted to know your own genotype at this locus (and couldn’t do it on your own), you had to pay Myriad - Through 2013, Myriad performed over one million BRCA tests and generated over $2.8 billion in revenues - Health professional organizations and the ACLU challenged these patents - ACLU carefully selected Myriad and BRCA as a test case of genetic patents based on the high profile nature of this disease and gene - Intention was for the case to act as a precedent for other future applications to genes - Supreme Court ruled unanimously that one cannot patent DNA sequence, though one can patent analytical techniques for studying it - 40% of genes have been patented at some point → private sector challenges one at a time  - One can patent synthetic DNA, as long as they are modified in a way that changes the way they operate compared to its natural state - Opinion specifically states that you cannot patent naturally occurring DNA sequence simply because it is difficulty to study - This is quite the reversal - It’s interesting to contemplate how the growth of the field of genetics and genomics might have been affected if this decision was issued in 1970 - Doug’s interpretation: Back in the day, it was a big deal to isolate and identify genes. It was a major research enterprise and the resources put in were more deserving of patent protection. Therefore, patent protection was more necessary before than it is today - Scientific changes: We can isolate human genes in everyone for little cost or effort - What changed legally? CRISPR-Cas9 dispute - Dates back to 2012 when researchers reprogrammed Cas9 to cut strands of DNA at specific sites - Jennifer Doudna (UC Berkeley) and Emmanuelle Charpentier (Max Planck Institute, Berlin) filed a patent application in March 2013 - Feng Zhang (Broad Institute, MIT) filed a patent application for the CRISPR-Cas9 technique in October 2013 under a special expedited review program - Granted in April 2014…Zhang was awarded additional patents on the technology while the Doudna patent was pending - April 2015: The Berkeley team began an interference proceeding to determine which team was the first to invent the technique - Both sides presented evidence culled from publications and laboratory notebooks - Zhang’s group clearly used Doudna/Charpentier’s innovations as references/guides for their experiments - Argument boiled down to whether CRISPR application to human cells was an invention under patent law - Did Dr. Zheng advance the field beyond an “ordinary skill in the art”? - Broad - MIT won! MIT innovated from Doudna’s discovery! (contested for over a decade) - Two European CRISPR patents belonging to Nobel Laureates (Doudna and Charpentier) are set to be revoked - The European Patent Office (EPO) stated that two key patents do not explain CRISPR-Cas9 well enough for other researchers to use it – so they do not qualify as inventions - EPO noted that patents fail to mention the short DNA sequences needed to cut the target DNA sequence - Nobelists’ lawyers asserted these motifs are common knowledge and “even undergraduate students” would know its CRISPR function - but patents are supposed to be applicable to an ordinary person, so they shouldn’t have excluded this  - Stakeholders: The patents are opposed by strange bedfellows, environmental advocates who oppose genetic engineering, competing pharmaceutical firms and lawyers representing undisclosed clients, and defended by ERS Genomics - company set up by Charpentier to license her CRISPR patents - Tactical retreat: Broad patents remaining in the EU; losing these two patents could have repercussions in other patent courts, even in the U.S> - “Doudna and Charpentier’s lawyers don’t want anything negative out of the EPO” - The EPO’s highly respected views could have “played through to the US” - CRISPR-Cas9 patent ownership differs in Europe and the US - In Europe, the Doudna and Charpentier patents dominate - In the US, patents from Feng Zhang of the Broad Institute prevail - These two parties and, and others, have been contesting CRISPR-Cas9 ownership for over a decade - Last year, South Korea-based ToolGen claimed it invented CRISPR-Cas9 editing before Zheng or Doudna and Charpentier - The patent and licensing situation was already complicated, but these latest developments make it more so - Although CRISPR is being overtaken by new gene-editing tools, patents including Cas9 remain valuable - Ex. Base editing, prime editing, and technologies underlying large sequence insertions require a Cas9 component - Cas9’s patent outcomes will affect new-generation gene technologies - Gene editing is also an exponentially growing field Take Home Messages - Genetic Ownership, Patents - Patents have become a mechanism to protect investments in product development and intellectual property rights, ensuring that creators of new products and methods reap the rewards of their investments - Patents are anti-competitive, but this is balanced by the public good motivation incentivizing motivation - Balance can be struck by decisions involving breadth of patents and their duration - In 1980, the Supreme Court established that organisms could be patented - Implied that genes could too - Finding genes of interest, patenting them, and developing drugs (often using recombinant DNA methods) fueled the rise of the pharmaceutical industry - Were gene patents a good thing? - Genomics caused human genes to be patented at an alarming pace (e.g. The Venter Patents) - Would Celera have existed without the promise to commercialize patent human genes? - probably not, since Venter Patents had to target certain parts of human genome to develop drugs - Myriad Genetics won the race to identify BRCA genes and patent them - 2013: The U.S. Supreme Court ruled (unanimously) that unmodified genes occurring in nature cannot be patented  - Was this a shift in legal thinking, or a logical consequence that finding genes is now so easy that it’s not worth a patent - I would say the latter, since it’s no longer an original finding and would cause mass conflicts among genomic researchers - CRISPR is a high stakes patent fight - but not an anomaly when attempting to determine the “ownership” of scientific discovery - Genome editing is another exponentially growing DNA revolution Slideshow 19: Careers in Genomics/Guest Panel Notes Relevance of Genomics has Changed - Used to be biomedical researchers, healthcare professionals, and the healthcare ecosystem - Now there are nurses, research scientists, research technicians, diagnostic technicians, genetic counselors, physicians, science historians, forensic scientists, data scientists, pharmacists, engineers, science writers, lawyers, medical illustrators, business analysts, policymakers, teachers, bioethicists - Might your future career “touch” genomics in some meaningful way? - Even if not, you will encounter genomics in your lives (via healthcare and as a citizen) - In many cases, you’ll have interactions with professionals who “touch” genomics as part of their jobs - This class prepared you for the previous two bullets - There are 27 institutes and centers in the National Institutes of Health - One of them is the National Human Genome Research Institute (NHGRI) - Established in 1989 - Now at around $660 million/year and ~700 staff Eric Green - Many career opportunities in genomics (i.e. nurse, business analyst, lawyer) - 27 institutes/centers part of the NIH - Difficult to stop the spread of misinformation about health/genomic topics - Will continue with incoming change of the cabinet - Trust and trustworthiness play a part in how information is shared - “Infectious disease”: some fear that vaccine research will be shut down with Trump administration Vence Bonham - Started as an educator → Lawyer in healthcare - Benefits of 23andMe: sickle cell anemia research - Risks: Selling data? - There are issues with GINA - Uses legal background in work he does - Provided a way to interpret and analyze data - Attended the Hong Kong meeting where Dr. H announced germline editing of twins  - Integration of genomics in sickle cell disease clinical care was used to study doctors in their use of genomic clinical care - Don’t use race as a biological basis Sarah Bates - science journalist Sarah Hull - “How did her ethics change after being involved in genomic work?” - Answer: She had to look at how earlier work “excluded the participation of people who are underrepresented and undercounted in their date” - Tribal Research Office in the NIH: Built trust and relationships with tribal communities before proceeding with research - Believes it is important for researchers to slow down and concentrate on how minoritized communities feel - Believes there is bias in data that exists Beth Tuck - Education director - Mentioned equity and access - “Who gets to be part of science?” - Implementing genomic literacy in K-12 can be seen as finding connections where genomics and genetics can be added to the curriculum - Genomic info to rural and urban areas Sheethal Jose - Strict data sharing policies - Had difficulty translating research and presenting it to policymakers - Genes don’t determine your fate (genetic determinism) Slide 20 - Cancer Genomics What is cancer? - Collection of diseases where cells divide without stopping - Somatic mutation causing cell proliferation into surrounding tissues - Some factors can be carried through germline - Mutations allow cells to “go rogue” or “become selfish” - Cancers are named for the tissues where they originate as well as its histology - what the cell looks like under the microscope - Cancer cells exhibit unregulated growth, no contact inhibition, etc. often forming tumors - Normal functions:  - Divide at limited rate - Use only its fair share of resources - Eventually die - Some mutations overrides pathways that force cells to behave → - Contact inhibition: cell restricts growth in contact with like cell - In cancer, instead of meeting in the middle, it will grow - Keeps dividing at expense of other cells - Not nerves, not blood = differentiated cells - Cells so small = undetectable by technology - Detecting cancer through cell-free DNA in non-invasive prenatal treatment (remember this?) - Benign tumors grow slowly, are usually less likely to invade other tissues, less likely to grow back when surgically removed - Even benign tumors can reach considerable size and cause serious issues if left untreated - Most cancers are NOT inherited (occur due to somatic mutations accumulated over time) (e.g. sun damage) - Pre-programmed cell death - In cancer, cells are immortal - Hayflick limit: point where cell stops dividing - Angiogenesis = recruit blood vessels in tumor formation to proliferate, become malignant - Tumor says “feed me” with own circulatory system because they were starving most of their lives - Metastasis: metastatic cell from primary tumor invades into blood vessel (blood and lympathic system) and can travel → form new cells in another tissue - Too much metastasis = cannot remove surgically - Around 600k people die of cancer every year in the US History of Cancer (last 5000 years) - Edwin Smith Surgical Papyrus (around 3000 BC) Papyrus records documented cancer (existed as long as medical care) - Cases were incurable if skin felt cold to the touch, bulging, and spreading all over the breast - Greece, 1st century AD: Leonidas of Alexandria described detailed surgical procedures, including leaving a wide margin of excision of tumors - Greek surgical traditions were revived in the Islamic world, where Greek science/philosophy/math were also preserved - European Renaissance (16th - 18th century) increased understanding of our own anatomy, led to resurgence of surgical approaches - 19th and 20th centuries: surgeries started becoming more aggressive and disfiguring - Outcomes not measured statistically Cancer Treatment History (20th century AD) - WWII research related to the development of mustard gas as a weapon and the origins of chemotherapy - Nitrogen mustard alleviate symptoms of lymphoma - Blood, skin, and hair cells grow rapidly → chemotherapy blocks any rapidly dividing cells - Sidney Farber fed chemotaxins (Aminopterin, predecessor of methotrexate, which blocks DNA replication) to children with leukemia → didn’t have much time to live, so they became experimental subjects (CONTROVERSIAL) - Other compounds blocked parts of cell growth and replication: logic was that these chemicals destroyed rapidly growing cells - Led to many experimentations with chemotherapy, including a combination of drugs (combination chemotherapy) at increasingly aggressive doses - Started to combine chemotherapy and surgery (radiation used to reduce local tumors) to control tumor growth - Also used for metastatic tumors that cannot be treated surgically - Designed cancer drugs to attack tumor cells specifically/certain tissues to reduce side effects (Gleevec) - Cancer mortalities have slowly declined and recovery rates in certain forms are high, others not - Every president (since Truman or Eisenhower) has promised to cure cancer Cancer’s relation to genomics - Explicitly a genomic disease - Leukemia, BCR-ABL, and drug development occurred during the growth of molecular genetics - 1911: Peyton Rous discovered that cell free extracts of chicken tumors could transfer to another chicken - Cause was a virus, later named the Rous Sarcoma Virus (RSV) - Other viruses cause cancerous mutations (e.g. HPV) - Led to decades of debate if cancer is caused by infectious agents/transmissible - Led to finding transmissible cancers in humans (largely failed, not one found) - Only found in mice, dogs, and tasmanian devils - Environmental influences are causing mutations (i.e. smoking, living by chemical plants) = not direct cause - Studying RSV led to the discovery of oncogenes What is Src? - oncogene, center of signal, constantly turned on to proliferate - Normal gene (c-src) that regulates cell growth, exists in mammals, birds, humans etc - When mutated cells are deregulated = cancer (Hanafusa discovered this) - Mutated = oncogene called v-src - Rous Sarcoma Virus became incorporated into the v-src gene, causing cancer when transmitted - Work of Bishop and Varmus - Normal (has potential to mutate) = proto-oncogene - Mutated = oncogene What is abl? - center of signal, constantly turned on to proliferate - 1970s: Herbert Abelson (pediatrician) discovered transmissible leukemia gene in mice → Led to discovery of abl, another oncogene - Src and abl are tyrosine kinases = propagating signals in cells to regulate many parts of cell growth/proliferation, stimulated external of cell - Regulation of these kinases are essential for normal restraints on cell proliferation - Add phosphate, cascades and finds way into nucleus - De-regulate these kinases → de-regulate cell growth = cancer - When abl is fused with bcr, it is cancerous (BCR/ABL) Chronic Myeloid Leukemia (CML) - Rare, affects around 8,000 Americans/year - Slowly developing - Phase I: explosive proliferation of normal white blood cells in bone marrow - Can last months or years and the patient is often alerted by a routine blood test - As disease progresses, white blood cells become increasingly abnormal - Proliferates from stem cells in bone marrow, myeloid cells  - Proliferating white blood cells burst capillaries and suffocate tissues by crowding oxygen carrying red blood cells - Used to be invariably fatal, most patients died within five years - Cause: genomic changes - The more we understand genomics, the more treatments can be produced - CML was observed under a microscope, not technology - Strange translocation on “Philadelphia” chromosome - discovered in Philly (no surprise) - Abl moves to philly chromosome and forms BCR-ABL (mutation) - Two proteins next to each other, abl is turned on and BCR mutant makes cells go wild - In bcr-abl fusion cells, tyrosine kinase is constitutively expressed (expressed all the time) and white cell proliferation is de-regulated - Happens in the mouse sarcoma - this is how the fundamental research in chicken and mice translated into cancer treatments Brian Druker’s development of Gleevec to treat CML - Druker was qualified to run clinical trials because he got his Ph.D. after his MD - Druker recognized that inhibitors of Tyrosine Kinase offered promise as cancer drugs - If we stop src and abl = stop proliferation of cancer - Druker identified drug companies that had compounds that might attack these kinases - Nick Lydon (chemist) developed chemical combos that would inhibit bcr-abl activity, not abl - KEY POINT: DRUG ONLY AFFECTS ABNORMAL PROTEINS - Company he worked for (Ciba-Geigy → Novartis) sent several of these compounds to Druker in a blind test - Druker knew and saw that the treatment eliminated the disease in mice, despite being blind to the identity of treatment and controls - Novartis said no to production because not enough people had CML - Druker suspects the real reason was that drug development (esp. Clinical trials) were too costly and unlikely to generate profits for rare diseases - Lydon showed evidence from mice → FDA approved - Hard to figure out dosage (can’t overdose people) - Never sign up for Phase I trials - you’re not gonna get better! - Phase II trials: double blind with control and experimental (but experiment wasn’t really double blind), used statistics - Results showed they were onto something - Increased dosages found that 30 out of 31 patients had white blood cells returned to normal within a month  - Billions of dollars for Novartis - Gleevec treated so many! How does gleevec work? - Kinases are like switches; they go around the cell adding phosphate groups to molecules to turn them off/on - Leukemia process: ATP donates phosphate, delivered to target substrate protein - Changes shape, causes leukemia growth - Kinase affected by bcr/abl mutation continuously turns on growth factors without checkpoints - Causes dramatic blood cell increase in CML - Gleevec substitutes ATP, preventing phosphate delivery to target substrate protein - No leukemia growth - However, cancers can form resistance - Not genomic correction/getting rid of mutations causing cancer (not fixing abl-bcr) - Power to move past chemotherapy and provide specific cancer treatment - Attacks mutant cells/cells that express abnormal proteins from cancerous mutation, leaves normal cells intact - Genomics will identify cancers more accurately → future vaccines designed to attack YOUR personal cancer - Challenge for financing cancer in healthcare - Also: compare genome sequence of normal cell and tumor cell - Find ASSOCIATIONS with cancer, not causes - Cancer genomes are extremely complicated Take Home Messages - Cancer History and Genetics - Cancer has long history of unsuccessful treatment - Concept of clinical trials applied to surgical outcomes was not a thing until the mid-20th century - Chemotherapy was developed from chemical warfare research (e.g. alkylating agents that bind DNA) - Early chemotherapy on children was controversial but ultimately influential - Chemotherapy evolved with higher doses and combination chemotherapy - Side effects remained severe - Combined treatments reducing morbidity of childhood cancer throughout the 20th century (e.g. surgery and chemotherapy) - Meanwhile, molecular genetics was discovering the molecular basis of certain cancers - Knowledge led to the development of targeted drugs that were more effective and reduced side effects, since they only attacked abnormal cells/proteins - Gleevec is the poster child for this type of drug development to reduce mortality and side effects Genomics of Cancer - Although rational drug design saves lives and reduces compilations, cancer is complicated - Understanding and treating will involve genomic AND personalized approaches - “Optional” readings  - How cancer genomics is transforming diagnosis - Pan-Cancer Analysis of Whole Genome - 2013 study sequenced around 20,000 genes in 3,300 tumors, Identified 300,000 mutations associated with cancer - Many more discovered since - Complicated = not all cause cancer - Some cancers have many mutations, others don’t - Pediatric cancers have fewer mutations, but seen ones are very important - Adult cancers have a larger number of mutations because body is accumulating somatic mutations as they age - not all mutations cause cancer (noncancerous) - Tumors involving mutagens (e.g. lung cancer) have a large number of mutations, hence “mut” - Typically, not just ONE mutation causes cancer → cancer progression involves sequences of mutations in key pathways for cell growth/proliferation - At each stage, there are different pathways doing different things - influence differentiation - Mutated pathways = situation becomes worse - We now have a cancer atlas - Pan-Cancer analysis of whole genomes: collection of research from ICGC/TCGA on whole-genome sequencing and analysis of cancer - Increasingly used to identify cancers unique to diverse populations - Ex. 10,478 cancer genomes identify driver genes, opportunities for precision oncology - Ex. African-ancestry associated genomic differences in cancer Drivers and passenger mutations - Somatic cells accumulate mutations as we age - Some of these are passenger mutations (occurs in thousands of cells) = associated with cancer because of driver BUT are irrelevant - These cells increase as you grow older (fertilized egg → adulthood) - Cells differentiate as you grow older - All this happens as lifestyle changes (e.g. smoking) - However, driver mutations (occur in 1-10 cells) = affects cell growth, proliferation, etc. - Carries along all passenger cells (driver could pick up mutations from legs, arms, etc) - Many drivers are DNA repair genes → when mutated, bad!  - Generally, aggressive drivers have more drivers - At the very end, forms chemotherapy resistant cells Generalities allow us to study or screen for cancer related mutations - 99.9% of all these cancer associated mutations are immaterial passengers - Driver mutations are only in 138 genes in only 12 major biochemical pathways - Can be difficult to separate which mutations are drivers vs passengers, but it can be done - Cell Fate: Cancer cells are less likely to differentiate - Cell Survival: Cancer cells can proliferate under limited nutrient conditions - Genome maintenance: de-regulates checkpoints during mitosis/replication - Increase in mutation rate increases the likelihood of acquiring new driver mutations - Around of newly discovered driver genes encode proteins that directly regulate chromatin through modification of histones - Affects gene expression, DNA replication, and DNA repair - These few pathways overlap and combine to make cells cancerous Cancer treatments - Surgical methods are rarely effective in the long-term - makes sense because it can just come back - This was just the only treatment until radiation/chemotherapy became available - Chemotherapy targets all rapidly dividing cells, including healthy cells (e.g. hair) - How is a cancer atlas actionable? - Diagnosis - Treatment (could be using genome editing such as T-cell immunotherapy) - Ex. genetically alter patient’s T-cells to recognize and attack tumor cells specifically by removing from patient, alter genes → re-introduce genetically modified T-cells to selectively destroy tumor cells - Somatic gene editing, not editing the cancerous mutation itself, just giving the body a method to attack cancerous cells with odd surface proteins - Tumor cells often have 30-60 unique mutations (often passenger mutations) - Tumor cells have altered surface proteins - Diagnoses with more detail will become important - No two tumors are identical to each other, but they form helpful patterns  - Use unique aspects of tumor (whether driver or passenger) to build immunotherapy for your cancer - Better solution: mRNA cancer vaccine (similar to mRNA COVID vaccines) - Cancer vaccines were business model for BioNtech before COVID came - Personalized mRNA cancer vaccines would reduce the need to modify and reintroduce engineered cells - Train your OWN immune system to attack your OWN tumors - Relevant articles: - First patient dosed in BioNTech Phase II trial of mRNA cancer vaccine - Maybe the coronavirus was lower-hanging fruit - Cancer vaccine trials give reasons for optimism - Cancer cells make proteins not found in body - Existing vaccines made for t-cells to target certain cancers (i.e. lung cancer, leukemia) - Some haven’t worked - Making personalized vaccines by extracting patient’s mRNA and reading genome - Predicts neoantigens, selected and injected into body - Shows promise for treating melanoma and pancreatic cancers - Another personalized vaccine without sequencing: ex vivo - Proteins from cancer cell taken out, exposed to dendritic cells in petri dish - Dendritic cells reintroduced in body to stimulate t cells, recognizing and attacking cancer - Cons of personalized vaccines: too expensive and time-consuming - Another off the shelf treatment: vaccine occurring entirely in body, given drugs or radiotherapy - Important note: although cancer is genomic, most treatments do not directly target genomic mutations that cause it; most target other characteristics (i.e. abnormal rate of division, abnormal proteins) Cancer’s complex genomic rearrangements - Latest sequencing technologies involve assembly of many cancer genomes - These genomes have a lot of rearrangements - Can get complicated when multiple rearrangements happen at once - Oncogenes are on circular extrachromosomal fragments and amplify their copies - Process is associated with many cancers - Learning about no cases of transmissible cancers help us understand oncogenes CRISPR’s technique for treating most common and deadly brain cancer - Cancer is not simple nucleotide changes - Regions of genome are deleted or amplified to make cancer cells proliferate - COMPLEX - CRISPR could change nucleotides at sites related to cancer and tamp down repetitive regions in cancer genomes  - Concept is simple but not easy - Need to FIND those genomic regions amplified in tumors - Need to develop CRISPR tools to cut those specific sequences, shredding oncogenes that are amplified - Far from FDA approval - Ongoing arms race between complexities of cancer and exponential growth in technologies and capabilities - Genomics provide promise for radical transformations Cancer Genomics - Take Home Messages - Cancer is a genomic disease - Cancer tumors vary in number and types of associated mutations - Mutations accumulate with age - Pediatric cancers associated with fewer somatic mutations - Tumor progression is generally the sequential accumulation of mutations - Selective advantage to cancer cells - Genomic approaches have been useful to separate passenger mutations from drivers - Hundreds of thousands of identified mutations boil down to 138 genes in 12 types of biochemical pathways (so far) - Genomic rearrangements pose a special challenge to cancer scientists - Personalized cancer vaccines are on the horizon Slide 21 - The Story of Human Genomics and Genomic Medicine (Eric’s Version) Genetics (1907) and Genomics (1987) - Two scientific fields launched last century - Changing medicine this century - For reference: DNA’s double helix shape discovery was in 1953 (in between) Prologue: Molecular Biology Revolution - Developed tools for comprehensively exploring genomes - DNA cloning (1970s) - DNA sequencing (1977) - Polymerase Chain Reaction (1983) - 1989: Human Genome Project was about to be born Chapter 1: Human Genome Project - Can we map and sequence the human genome? - 1990-2003 - Highlights:  - Generation of first human genome sequence - Ethos of data sharing - Early integration of bioethics into genomics (aka ELSI) Chapter 2: Expansion and Maturation of Genomics - “Cool” applications of genomics - Agriculture, ancestry, biodiversity, infectious agents, forensics, bioenergy, microbiome, evolution, population history - Health, disease, and medicine (myriad applications) - Can we use genomics to advance knowledge about health and disease? - Genomic medicine (circa 2003): emerging medical discipline that uses an individual’s genomic info in their clinical care - E.g. diagnostic or therapeutic decision-making/other implications - Related (but not identical) terms: - Personalized medicine - Individualized medicine - Precision medicine - Went from over a quadrillion dollars to a thousand dollars to sequence human genome - Census of variants in average human genome sequence: - Average human genome has ~6 billion nucleotides - Contains ~5.6 million variants → affects ~26 million nucleotides (~0.4% of total genome) - Any two people would have ~99.6% identical genome sequences and ~0.4% differences - Most known to least known: - Gene function (around 20,000) - Epigenomics - RNA structure and function - Transcriptional regulation - Proteomics - Current knowledge of functional nuances of the human genome are only the tip of the iceberg of future discoveries - Highlights: New technologies for DNA sequencing - Emerging catalog of genomic variants in human population - Progress in identifying functional elements (8.2%) - Around 90%+ is “junk” DNA Chapter 3: En Route to Genomic Medicine - Can we demonstrate effective uses of genomics in medicine? - Some genomic variants influence genome function → impact traits (i.e. phenotypes) - But which ones? And how? - Continuum of Genetic Diseases: - Rare genetic diseases - one gene involved (monogenic)  - Progress: Causative (mutated) gene for nearly 6,000 diseases now known - Common Genetic Diseases - multiple genes involved (multigenic) - Progress: Around 400,000 associations between genomic variants and health-related traits - Rare diseases have more genomic underpinnings than common diseases - How genome sequencing in medicine works: - Compare patient’s genome sequence to reference genome sequence - Generate list of genomic variants - Implement genomic medicine Genomic Medicine Implementations - Cancer genomics: - Cancer is a disease of the genome - takes multiple mutations to make a call malignant - Routine Cancer Diagnostic Tools: - Cancer Histopathology used in morphology - Cancer Genome Sequencing used in genomic signature - Paradigm change: Genomic signature of a tumor often (almost always) provides more valuable clinical info than the tissue of origin - Liquid biopsy for detecting cancer - Standard biopsies of human tissues are invasive and can be dangerous - Tumor cells frequently die and release DNA into bloodstream - Highly sensitive DNA-sequencing methods can detect and analyze cell-free tumor DNA - Taken through simple blood draw - Rare Genetic Disease Diagnostics: - Genome sequencing is becoming a standard diagnostic tool in medicine - Yields a diagnosis for a rare genetic disease in ~30-50% of cases (this will increase over time!) - Rapid genome sequencing helps sick newborns - In 44 studies of children in ICUs with unknown diseases, 37% received genetic diagnosis, 26% had consequent changes in management, and net healthcare costs were reduced by $14,265 per child tested - This sequencing is a first-tier, standard of care test - In past five years, there is potential for infant and childhood mortality in the US and UK to be reduced by several percent - Noninvasive Prenatal Genomic Testing - Mother and fetus release cell-free DNA from dying cells into blood - Alternative to invasive procedure: sequencing of cell-free DNA in maternal plasma is used to screen for aneuploidy - #1 genomic medicine test worldwide  - Pharmacogenomic Testing - People respond differently to medicine - Prescribing medications is imprecise - One size does NOT fit all - Stratify patents based on detected genomic variants - Use genomics to get the “right drug to the right patient with the right dose” - Bottom line: pharmacogenomic testing is appropriate for a small portion of prescription medication, but that portion is expected to grow in the future - Efforts to increase clinical usage are ongoing - Genomics-based Prevention - Still exploring common diseases seen from polygenic risk scores - Preventive genomics clinic is mostly for rare diseases now - Highlights: - Compelling examples of genomic medicine emerged - Major progress in unraveling genomic bases of rare diseases - Used as a framework for studying genomic bases of common diseases - What was achieved in progression from Human Genome Project to Genomic Medicine - Cost of sequencing a human genome reduced over 1 million fold - Millions of human genomes sequenced - Profound advances in understanding human genome functions - Significant advances in unraveling genomic bases of human disease - Vivid examples of genomic medicine now emerging Genomics still face big challenges - Clinical understanding of patient’s genome sequence remains difficult - Challenges of analyzing patient’s genome sequence - Comparing reference genome sequence to patient, finding genomic variants, and implementing genomic medicine is an INTENTIONAL OVERSIMPLIFICATION - Number of variants in person’s genome sequence (becomes less and less through filtering and prioritizing) - ~3-5 million - 10,000s - 1000s - 100s - 10-20 - Requirements for Accurate and Equitable Analyses of patient’s genome sequences - Appropriately matched human genome reference sequence - or a human pangenome reference - Reference population database (with aggregated genomic variant info) for matching ancestral populations  - Robust knowledge base of curated info about likely pathogenicity of genomic variants - Developed by expert panels - Genomics is becoming profoundly relevant in society - Societal challenges with genomic medicine (e.g. genomic literacy) - Many, many other challenges Chapter 4: Making Genomics Mainstream in Medicine - Can we deploy genomics broadly and equitably in medicine? - 2020 NHGRI strategic vision for improving human health at the forefront of genomics - 10 bold predictions for human genomics by 2030 Cumulative Prep Take home messages - 02: Human Genome Project - Completed ahead of schedule (13 years) and under-budget - Accomplished a high quality sequence for >90% of human genome/92% (“near complete” or “essentially complete”) - Remaining ~8% was “junk” but it was important for structural (centromeres and telomeres) and medical reasons - Costed $1 billion - Race between HGP and Venter/Celera melted after announcing draft human genome in 2000 - Initial concerns about HGP melted away - HGP set genomics into widespread dissemination across biology, medicine, and society - Several new “revolutionary methods of sequencing have been developed over the last ~20 years - Generated a complete sequence of (female) human genome in 2022, then men in 2023 (“telomere-to-telomere”) - Lasted from 1990-2003 - Used a map-first, sequence-second strategy to study human genome - Used Sanger DNA sequencing - NOT revolutionary new DNA sequencing method - Sequencing human genome was difficult because of its large size, complexity, extensive amounts of repetitive regions - Venter/Celera used whole-genome sequencing strategy to sequence human genome + compete with HGP, built business but efforts never fully succeeded Take home messages - 03: The Scale of the Human Genome - DNA is composed of a backbone of sugars (deoxyribose) and phosphate groups, with nitrogen bases - DNA info is contained in sequence of base pairs/nucleotides - Genome sequence is the sequence of all nucleotides, in order - Human genome has ~3 billion base pairs - DNA is tightly packed into nuclei of cells - Genome carries tremendous amount of info in a small package - DNA sequences vary among individuals - but vast majority of our genomes are identical in sequence Take home messages - 04: How to Build an Organism - Central dogma represents most basic notion about genes and their products - one gene, one RNA, one protein - Does not apply to viruses - Gene expression is highly complex, regulated by transcriptional, translational, post-translational mechanisms - Epigenetics refers to chemical modification of DNA - affects expression directly through modification of histones and chromatin - do not change sequence of DNA; add chemical tags to DNA to change how cell reads and interprets genetic info - Environment can influence gene expression, even in utero - Appropriate timing and spatial location of gene expression is important for generating morphology - Ex. Hox genes illustrate the divergence in limb morphology in vertebrates, result of underlying changes in gene expression - Diversity of morphology is from divergence in gene copy number and patterns of expression - Small genetic changes (mutations) can have large effects - Hard to understand the translation of 3 billion base pairs into phenotypes, limbs, flight, disease, cancer, creativity, etc Take home messages - 05: Genome Structure - Genomes vary in size and content, no matter the complexity of the organism - Vast majority of genome is “non-coding” - Some parts of the genome are actively parasitic (along with functional, junk, e