Feeds:
Posts

## Archive for the ‘REAL TIME Conference Coverage Twitter’s Hashtags and Handles per Presentation/session’ Category

### Will Web 3.0 Do Away With Science 2.0? Is Science Falling Behind?

Curator: Stephen J. Williams, Ph.D.

UPDATED 4/06/2022

A while back (actually many moons ago) I had put on two posts on this site:

Scientific Curation Fostering Expert Networks and Open Innovation: Lessons from Clive Thompson and others

Twitter is Becoming a Powerful Tool in Science and Medicine

Each of these posts were on the importance of scientific curation of findings within the realm of social media and the Web 2.0; a sub-environment known throughout the scientific communities as Science 2.0, in which expert networks collaborated together to produce massive new corpus of knowledge by sharing their views, insights on peer reviewed scientific findings. And through this new media, this process of curation would, in itself generate new ideas and new directions for research and discovery.

The platform sort of looked like the image below:

This system lied above a platform of the original Science 1.0, made up of all the scientific journals, books, and traditional literature:

Previous image source: PeerJ.com

To index the massive and voluminous research and papers beyond the old Dewey Decimal system, a process of curation was mandatory. The dissemination of this was a natural for the new social media however the cost had to be spread out among numerous players. Journals, faced with the high costs of subscriptions and their only way to access this new media as an outlet was to become Open Access, a movement first sparked by journals like PLOS and PeerJ but then begrudingly adopted throughout the landscape. But with any movement or new adoption one gets the Good the Bad and the Ugly (as described in my cited, above, Clive Thompson article). The bad side of Open Access Journals were

1. costs are still assumed by the individual researcher not by the journals
2. the arise of the numerous Predatory Journals

Even PeerJ, in their column celebrating an anniversary of a year’s worth of Open Access success stories, lamented the key issues still facing Open Access in practice

• which included the cost and the rise of predatory journals.

In essence, Open Access and Science 2.0 sprung full force BEFORE anyone thought of a way to defray the costs

### Can Web 3.0 Finally Offer a Way to Right the Issues Facing High Costs of Scientific Publishing?

What is Web 3.0?

From Wikipedia: https://en.wikipedia.org/wiki/Web3

Web 1.0 and Web 2.0 refer to eras in the history of the Internet as it evolved through various technologies and formats. Web 1.0 refers roughly to the period from 1991 to 2004, where most websites were static webpages, and the vast majority of users were consumers, not producers, of content.[6][7] Web 2.0 is based around the idea of “the web as platform”,[8] and centers on user-created content uploaded to social-networking services, blogs, and wikis, among other services.[9] Web 2.0 is generally considered to have begun around 2004, and continues to the current day.[8][10][4]

### Terminology

The term “Web3”, specifically “Web 3.0”, was coined by Ethereum co-founder Gavin Wood in 2014.[1] In 2020 and 2021, the idea of Web3 gained popularity[citation needed]. Particular interest spiked towards the end of 2021, largely due to interest from cryptocurrency enthusiasts and investments from high-profile technologists and companies.[4][5] Executives from venture capital firm Andreessen Horowitz travelled to Washington, D.C. in October 2021 to lobby for the idea as a potential solution to questions about Internet regulation with which policymakers have been grappling.[11]

Web3 is distinct from Tim Berners-Lee‘s 1999 concept for a semantic web, which has also been called “Web 3.0”.[12] Some writers referring to the decentralized concept usually known as “Web3” have used the terminology “Web 3.0”, leading to some confusion between the two concepts.[2][3] Furthermore, some visions of Web3 also incorporate ideas relating to the semantic web.[13][14]

## Concept

Web3 revolves around the idea of decentralization, which proponents often contrast with Web 2.0, wherein large amounts of the web’s data and content are centralized in the fairly small group of companies often referred to as Big Tech.[4]

Specific visions for Web3 differ, but all are heavily based in blockchain technologies, such as various cryptocurrencies and non-fungible tokens (NFTs).[4] Bloomberg described Web3 as an idea that “would build financial assets, in the form of tokens, into the inner workings of almost anything you do online”.[15] Some visions are based around the concepts of decentralized autonomous organizations (DAOs).[16] Decentralized finance (DeFi) is another key concept; in it, users exchange currency without bank or government involvement.[4] Self-sovereign identity allows users to identify themselves without relying on an authentication system such as OAuth, in which a trusted party has to be reached in order to assess identity.[17]

## Reception

Technologists and journalists have described Web3 as a possible solution to concerns about the over-centralization of the web in a few “Big Tech” companies.[4][11] Some have expressed the notion that Web3 could improve data securityscalability, and privacy beyond what is currently possible with Web 2.0 platforms.[14] Bloomberg states that sceptics say the idea “is a long way from proving its use beyond niche applications, many of them tools aimed at crypto traders”.[15] The New York Times reported that several investors are betting $27 billion that Web3 “is the future of the internet”.[18][19] Some companies, including Reddit and Discord, have explored incorporating Web3 technologies into their platforms in late 2021.[4][20] After heavy user backlash, Discord later announced they had no plans to integrate such technologies.[21] The company’s CEO, Jason Citron, tweeted a screenshot suggesting it might be exploring integrating Web3 into their platform. This led some to cancel their paid subscriptions over their distaste for NFTs, and others expressed concerns that such a change might increase the amount of scams and spam they had already experienced on crypto-related Discord servers.[20] Two days later, Citron tweeted that the company had no plans to integrate Web3 technologies into their platform, and said that it was an internal-only concept that had been developed in a company-wide hackathon.[21] Some legal scholars quoted by The Conversation have expressed concerns over the difficulty of regulating a decentralized web, which they reported might make it more difficult to prevent cybercrimeonline harassmenthate speech, and the dissemination of child abuse images.[13] But, the news website also states that, “[decentralized web] represents the cyber-libertarian views and hopes of the past that the internet can empower ordinary people by breaking down existing power structures.” Some other critics of Web3 see the concept as a part of a cryptocurrency bubble, or as an extension of blockchain-based trends that they see as overhyped or harmful, particularly NFTs.[20] Some critics have raised concerns about the environmental impact of cryptocurrencies and NFTs. Others have expressed beliefs that Web3 and the associated technologies are a pyramid scheme.[5] Kevin Werbach, author of The Blockchain and the New Architecture of Trust,[22] said that “many so-called ‘web3’ solutions are not as decentralized as they seem, while others have yet to show they are scalable, secure and accessible enough for the mass market”, adding that this “may change, but it’s not a given that all these limitations will be overcome”.[23] David Gerard, author of Attack of the 50 Foot Blockchain,[24] told The Register that “web3 is a marketing buzzword with no technical meaning. It’s a melange of cryptocurrencies, smart contracts with nigh-magical abilities, and NFTs just because they think they can sell some monkeys to morons”.[25] ##### Below is an article from MarketWatch.com Distributed Ledger series about the different forms and cryptocurrencies involved #### by Frances Yue, Editor of Distributed Ledger, Marketwatch.com Clayton Gardner, co-CEO of crypto investment management firm Titan, told Distributed Ledger that as crypto embraces broader adoption, he expects more institutions to bypass bitcoin and invest in other blockchains, such as Ethereum, Avalanche, and Terra in 2022. which all boast smart-contract features. Bitcoin traditionally did not support complex smart contracts, which are computer programs stored on blockchains, though a major upgrade in November might have unlocked more potential. “Bitcoin was originally seen as a macro speculative asset by many funds and for many it still is,” Gardner said. “If anything solidifies its use case, it’s a store of value. It’s not really used as originally intended, perhaps from a medium of exchange perspective.” For institutions that are looking for blockchains that can “produce utility and some intrinsic value over time,” they might consider some other smart contract blockchains that have been driving the growth of decentralized finance and web 3.0, the third generation of the Internet, according to Gardner. Bitcoin is still one of the most secure blockchains, but I think layer-one, layer-two blockchains beyond Bitcoin, will handle the majority of transactions and activities from NFT (nonfungible tokens) to DeFi,“ Gardner said. “So I think institutions see that and insofar as they want to put capital to work in the coming months, I think that could be where they just pump the capital.” ### Decentralized social media？ The price of Decentralized Social, or DeSo, a cryptocurrency powering a blockchain that supports decentralized social media applications, surged roughly 74% to about$164 from $94, after Deso was listed at Coinbase Pro on Monday, before it fell to about$95, according to CoinGecko.

In the eyes of Nader Al-Naji, head of the DeSo foundation, decentralized social media has the potential to be “a lot bigger” than decentralized finance.

“Today there are only a few companies that control most of what we see online,” Al-Naji told Distributed Ledger in an interview. But DeSo is “creating a lot of new ways for creators to make money,” Al-Naji said.

“If you find a creator when they’re small, or an influencer, you can invest in that, and then if they become bigger and more popular, you make money and they make and they get capital early on to produce their creative work,” according to AI-Naji.

BitClout, the first application that was created by AI-Naji and his team on the DeSo blockchain, had initially drawn controversy, as some found that they had profiles on the platform without their consent, while the application’s users were buying and selling tokens representing their identities. Such tokens are called “creator coins.”

AI-Naji responded to the controversy saying that DeSo now supports more than 200 social-media applications including Bitclout. “I think that if you don’t like those features, you now have the freedom to use any app you want. Some apps don’t have that functionality at all.”

But Before I get to the “selling monkeys to morons” quote,

THE GOOD, THE BAD, AND THE UGLY

#### THE GOOD

My foray into Science 2.0 and then pondering what the movement into a Science 3.0 led me to an article by Dr. Vladimir Teif, who studies gene regulation and the nucleosome, as well as creating a worldwide group of scientists who discuss matters on chromatin and gene regulation in a journal club type format.

Fragile Nucleosome is an international community of scientists interested in chromatin and gene regulation. Fragile Nucleosome is active in several spaces: one is the Discord server where several hundred scientists chat informally on scientific matters. You can join the Fragile Nucleosome Discord server. Another activity of the group is the organization of weekly virtual seminars on Zoom. Our webinars are usually conducted on Wednesdays 9am Pacific time (5pm UK, 6pm Central Europe). Most previous seminars have been recorded and can be viewed at our YouTube channel. The schedule of upcoming webinars is shown below. Our third activity is the organization of weekly journal clubs detailed at a separate page (Fragile Nucleosome Journal Club).

His lab site is at https://generegulation.org/ but had published a paper describing what he felt what the #science2_0 to #science3_0 transition would look like (see his blog page on this at https://generegulation.org/open-science/).

### This concept of science 3.0 he had coined back in 2009.  As Dr Teif had mentioned

So essentially I first introduced this word Science 3.0 in 2009, and since then we did a lot to implement this in practice. The Twitter account @generegulation is also one of examples

### This is curious as we still have an ill defined concept of what #science3_0 would look like but it is a good read nonetheless.

His paper,  entitled “Science 3.0: Corrections to the Science 2.0 paradigm” is on the Cornell preprint server at https://arxiv.org/abs/1301.2522

Abstract

### Science 3.0: Corrections to the Science 2.0 paradigm

The concept of Science 2.0 was introduced almost a decade ago to describe the new generation of online-based tools for researchers allowing easier data sharing, collaboration and publishing. Although technically sound, the concept still does not work as expected. Here we provide a systematic line of arguments to modify the concept of Science 2.0, making it more consistent with the spirit and traditions of science and Internet. Our first correction to the Science 2.0 paradigm concerns the open-access publication models charging fees to the authors. As discussed elsewhere, we show that the monopoly of such publishing models increases biases and inequalities in the representation of scientific ideas based on the author’s income. Our second correction concerns post-publication comments online, which are all essentially non-anonymous in the current Science 2.0 paradigm. We conclude that scientific post-publication discussions require special anonymization systems. We further analyze the reasons of the failure of the current post-publication peer-review models and suggest what needs to be changed in Science 3.0 to convert Internet into a large journal club. [bold face added]
In this paper it is important to note the transition of a science 1.0, which involved hard copy journal publications usually only accessible in libraries to a more digital 2.0 format where data, papers, and ideas could be easily shared among networks of scientists.
As Dr. Teif states, the term “Science 2.0” had been coined back in 2009, and several influential journals including Science, Nature and Scientific American endorsed this term and suggested scientists to move online and their discussions online.  However, even at present there are thousands on this science 2.0 platform, Dr Teif notes the number of scientists subscribed to many Science 2.0 networking groups such as on LinkedIn and ResearchGate have seemingly saturated over the years, with little new members in recent times.
The consensus is that science 2.0 networking is:
1. good because it multiplies the efforts of many scientists, including experts and adds to the scientific discourse unavailable on a 1.0 format
2. that online data sharing is good because it assists in the process of discovery (can see this evident with preprint servers, bio-curated databases, Github projects)
3. open-access publishing is beneficial because free access to professional articles and open-access will be the only publishing format in the future (although this is highly debatable as many journals are holding on to a type of “hybrid open access format” which is not truly open access
4. only sharing of unfinished works and critiques or opinions is good because it creates visibility for scientists where they can receive credit for their expert commentary

### A.  Science 3.0 Still Needs Peer Review

Peer review of scientific findings will always be an imperative in the dissemination of well-done, properly controlled scientific discovery.  As Science 2.0 relies on an army of scientific volunteers, the peer review process also involves an army of scientific experts who give their time to safeguard the credibility of science, by ensuring that findings are reliable and data is presented fairly and properly.  It has been very evident, in this time of pandemic and the rapid increase of volumes of preprint server papers on Sars-COV2, that peer review is critical.  Many of these papers on such preprint servers were later either retracted or failed a stringent peer review process.

Now many journals of the 1.0 format do not generally reward their peer reviewers other than the self credit that researchers use on their curriculum vitaes.  Some journals, like the MDPI journal family, do issues peer reviewer credits which can be used to defray the high publication costs of open access (one area that many scientists lament about the open access movement; where the burden of publication cost lies on the individual researcher).

An issue which is highlighted is the potential for INFORMATION NOISE regarding the ability to self publish on Science 2.0 platforms.

### The NEW BREED was born in 4/2012

An ongoing effort on this platform, https://pharmaceuticalintelligence.com/, is to establish a scientific methodology for curating scientific findings where one the goals is to assist to quell the information noise that can result from the massive amounts of new informatics and data occurring in the biomedical literature.

### B.  Open Access Publishing Model leads to biases and inequalities in the idea selection

#### Informatics tools for high-throughput analysis of cancer mutations

##### Rachel Karchin
• CRAVAT is a platform to determine, categorize, and curate cancer mutations and cancer related variants
• adding new tools used to be hard but having an open architecture allows for modular growth and easy integration of other tools
• so they are actively making an open network using social media

### Towards the FAIR principles

While LOD has had some uptake across the web, the number of databases using this protocol compared to the other technologies is still modest. But whether or not we use LOD, we do need to ensure that databases are designed specifically for the web and for reuse by humans and machines. To provide guidance for creating such databases independent of the technology used, the FAIR principles were issued through FORCE11: the Future of Research Communications and e-Scholarship. The FAIR principles put forth characteristics that contemporary data resources, tools, vocabularies and infrastructures should exhibit to assist discovery and reuse by third-parties through the web. Wilkinson et al.,2016. FAIR stands for: Findable, Accessible, Interoperable and Re-usable. The definition of FAIR is provided in Table 1:

Number Principle
F Findable
F1 (meta)data are assigned a globally unique and persistent identifier
F2 data are described with rich metadata
F3 metadata clearly and explicitly include the identifier of the data it describes
F4 (meta)data are registered or indexed in a searchable resource
A Accessible
A1 (meta)data are retrievable by their identifier using a standardized communications protocol
A1.1 the protocol is open, free, and universally implementable
A1.2 the protocol allows for an authentication and authorization procedure, where necessary
A2 metadata are accessible, even when the data are no longer available
I Interoperable
I1 (meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation.
I2 (meta)data use vocabularies that follow FAIR principles
I3 (meta)data include qualified references to other (meta)data
R Reusable
R1 meta(data) are richly described with a plurality of accurate and relevant attributes
R1.1 (meta)data are released with a clear and accessible data usage license
R1.2 (meta)data are associated with detailed provenance
R1.3 (meta)data meet domain-relevant community standards

A detailed explanation of each of these is included in the Wilkinson et al., 2016 article, and the Dutch Techcenter for Life Sciences has a set of excellent tutorials, so we won’t go into too much detail here.

• for outside vendors to access their data, vendors would need a signed Material Transfer Agreement but NCI had formulated a framework to facilitate sharing of data using a DIACOM standard for imaging data

Monday, June 22

1:30 PM – 3:01 PM EDT

Virtual Educational Session

Experimental and Molecular Therapeutics, Cancer Chemistry, Drug Development, Immunology

Engineering and Physical Sciences Approaches in Cancer Research, Diagnosis, and Therapy

The engineering and physical science disciplines have been increasingly involved in the development of new approaches to investigate, diagnose, and treat cancer. This session will address many of these efforts, including therapeutic methods such as improvements in drug delivery/targeting, new drugs and devices to effect immunomodulation and to synergize with immunotherapies, and intraoperative probes to improve surgical interventions. Imaging technologies and probes, sensors, and bioma

Claudia Fischbach, Ronit Satchi-Fainaro, Daniel A Heller

DETAILS

Monday, June 22

1:30 PM – 3:30 PM EDT

Virtual Educational Session

Survivorship

Exceptional Responders and Long-Term Survivors

How should we think about exceptional and super responders to cancer therapy? What biologic insights might ensue from considering these cases? What are ways in which considering super responders may lead to misleading conclusions? What are the pros and cons of the quest to locate exceptional and super responders?

Alice P Chen, Vinay K Prasad, Celeste Leigh Pearce

DETAILS

Monday, June 22

1:30 PM – 3:30 PM EDT

Virtual Educational Session

Tumor Biology, Immunology

Exploiting Metabolic Vulnerabilities in Cancer

The reprogramming of cellular metabolism is a hallmark feature observed across cancers. Contemporary research in this area has led to the discovery of tumor-specific metabolic mechanisms and illustrated ways that these can serve as selective, exploitable vulnerabilities. In this session, four international experts in tumor metabolism will discuss new findings concerning the rewiring of metabolic programs in cancer that support metabolic fitness, biosynthesis, redox balance, and the reg

Costas Andreas Lyssiotis, Gina M DeNicola, Ayelet Erez, Oliver Maddocks

DETAILS

Monday, June 22

1:30 PM – 3:30 PM EDT

Virtual Educational Session

## Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 28, 2020 Session on NCI Activities: COVID-19 and Cancer Research 5:20 PM

### Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 28, 2020 Session on NCI Activities: COVID-19 and Cancer Research 5:20 PM

Reporter: Stephen J. Williams, PhD

#### NCI Activities: COVID-19 and Cancer Research

Dinah S. Singer. NCI-DCB, Bethesda, MD @theNCI

• at the NCI they are pivoting some of their clinical trials to address COVID related issues like trials on tocilizumab and producing longitudinal cohorts of cancer patients and COVID for further analysis and studies
• vaccine and antibody efforts at NCI and they are asking all their cancer centers (Cancer COVID Consortium) collecting data
• Moonshot is collecting metadata but now COVID data from cellular therapy patients
• they are about to publish new grants related to COVID and adding option to investigators to use current funds to do COVID related options
• she says if at home take the time to think, write manuscripts, analyze data BE A REVIEWER FOR JOURNALS,
• SSMMART project from Moonshot is still active
• so far NCI and NIH grant process is ongoing although the peer review process is slower
• they have extended deadlines with NO justification required (extend 90 days)
• also allowing flexibility on use of grant money and allowing more early investigator rules and lax on those rules
• non competitive renewals (type 5) will allow restructuring of project; contact program administrator
• she and NCI heard rumors of institutions shutting down cancer research she is stressing to them not to do that
• non refundable travel costs may be charged to the grant
• NCI contemplating on extending the early investigator time
• for more information go to NIH and NCI COVID-19 pages which have more guidances updated regularly

@pharma_BI

@AACR

@CureCancerNow

@pharmanews

@BiotechWorld

@theNCI

#AACR20

## Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 28, 2020 Session on Novel Targets and Therapies 2:35 PM

### Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 28, 2020 Session on Novel Targets and Therapies 2:35 PM

Reporter: Stephen J. Williams, PhD

Updated on 07/08/2021

https://cancerdiscovery.aacrjournals.org/content/early/2021/07/01/2159-8290.CD-20-1741

#### Session VMS.ET04.01 – Novel Targets and Therapies

Targeting chromatin remodeling-associated genetic vulnerabilities in cancer: PBRM1 defects are synthetic lethal with PARP and ATR inhibitors

Presenter/AuthorsRoman Merial Chabanon, Daphné Morel, Léo Colmet-Daage, Thomas Eychenne, Nicolas Dorvault, Ilirjana Bajrami, Marlène Garrido, Suzanna Hopkins, Cornelia Meisenberg, Andrew Lamb, Theo Roumeliotis, Samuel Jouny, Clémence Astier, Asha Konde, Geneviève Almouzni, Jyoti Choudhary, Jean-Charles Soria, Jessica Downs, Christopher J. Lord, Sophie Postel-Vinay. Gustave Roussy, Villejuif, France, The Francis Crick Institute, London, United Kingdom, Institute of Cancer Research, London, United Kingdom, Sage Bionetworks, Seattle, WA, Institute of Cancer Research, London, United Kingdom, Institute of Cancer Research, London, United Kingdom, Institut Curie, Paris, France, Université Paris-Sud/Université Paris-Saclay, Le Kremlin-Bicêtre, France, Gustave Roussy Cancer Campus and U981 INSERM, ATIP-Avenir group, Villejuif, FranceDisclosures R.M. Chabanon: None. D. Morel: None. L. Colmet-Daage: None. T. Eychenne: None. N. Dorvault: None. I. Bajrami: None. M. Garrido: None. S. Hopkins: ; Fishawack Group of Companies. C. Meisenberg: None. A. Lamb: None. T. Roumeliotis: None. S. Jouny: None. C. Astier: None. A. Konde: None. G. Almouzni: None. J. Choudhary: None. J. Soria: ; Medimmune/AstraZeneca. ; Astex. ; Gritstone. ; Clovis. ; GSK. ; GamaMabs. ; Lilly. ; MSD. ; Mission Therapeutics. ; Merus. ; Pfizer. ; PharmaMar. ; Pierre Fabre. ; Roche/Genentech. ; Sanofi. ; Servier. ; Symphogen. ; Takeda. J. Downs: None. C.J. Lord: ; AstraZeneca. ; Merck KGaA. ; Artios. ; Tango. ; Sun Pharma. ; GLG. ; Vertex. ; Ono Pharma. ; Third Rock Ventures. S. Postel-Vinay: ; Merck KGaA. ; Principal investigator of clinical trials for Gustave Roussy.; Boehringer Ingelheim. ; Principal investigator of clinical trials for Gustave Roussy.; Roche. ; Principal investigator of clinical trials for Gustave Roussy. Benefited from reimbursement for attending symposia.; AstraZeneca. ; Principal investigator of clinical trials for Gustave Roussy.; Clovis. ; Principal investigator of clinical trials for Gustave Roussy.; Bristol-Myers Squibb. ; Principal investigator of clinical trials for Gustave Roussy.; Agios. ; Principal investigator of clinical trials for Gustave Roussy.; GSK.AbstractAim: Polybromo-1 (PBRM1), a specific subunit of the pBAF chromatin remodeling complex, is frequently inactivated in cancer. For example, 40% of clear cell Renal Cell Carcinoma (ccRCC) and 15% of cholangiocarcinoma present deleterious PBRM1 mutations. There is currently no precision medicine-based therapeutic approach that targets PBRM1 defects. To identify novel, targeted therapeutic strategies for PBRM1-defective cancers, we carried out high-throughput functional genomics and drug screenings followed by in vitro and in vivo validation studies.
Methods: High-throughput siRNA-drug sensitization and drug sensitivity screens evaluating > 150 cancer-relevant small molecules in dose-response were performed in Pbrm1 siRNA-transfected mouse embryonic stem cells (mES) and isogenic PBRM1-KO or -WT HAP1 cells, respectively. After identification of PBRM1-selective small molecules, revalidation was carried out in a series of in-house-generated isogenic models of PBRM1 deficiency – including 786-O (ccRCC), A498 (ccRCC), U2OS (osteosarcoma) and H1299 (non-small cell lung cancer) human cancer cell lines – and non-isogenic ccRCC models, using multiple clinical compounds. Mechanistic dissection was performed using immunofluorescence, RT-qPCR, western blotting, DNA fiber assay, transcriptomics, proteomics and DRIP-sequencing to evaluate markers of DNA damage response (DDR), replication stress and cell-autonomous innate immune signaling. Preclinical data were integrated with TCGA tumor data.
Results: Parallel high-throughput drug screens independently identified PARP inhibitors (PARPi) as being synthetic lethal with PBRM1 defects – a cell type-independent effect which was exacerbated by ATR inhibitors (ATRi) and which we revalidated in vitro in isogenic and non-isogenic systems and in vivo in a xenograft model. PBRM1 defects were associated with increased replication fork stress (higher γH2AX and RPA foci levels, decreased replication fork speed and increased ATM checkpoint activation), R-loop accumulation and enhanced genomic instability in vitro; these effects were exacerbated upon PARPi exposure. In patient tumor samples, we also found that PBRM1-mutant cancers possessed a higher mutational load. Finally, we found that ATRi selectively activated the cGAS/STING cytosolic DNA sensing pathway in PBRM1-deficient cells, resulting in increased expression of type I interferon genes.
Conclusion: PBRM1-defective cancer cells present increased replication fork stress, R-loop formation, genome instability and are selectively sensitive to PARPi and ATRi through a synthetic lethal mechanism that is cell type-independent. Our data provide the pre-clinical rationale for assessing PARPi as a monotherapy or in combination with ATRi or immune-modulating agents in molecularly-selected patients with PBRM1-defective cancers.

1057 – Targeting MTHFD2 using first-in-class inhibitors kills haematological and solid cancer through thymineless-induced replication stress

Presenter/AuthorsThomas Helleday. University of Sheffield, Sheffield, United KingdomDisclosures T. Helleday: None.AbstractSummary
Thymidine synthesis pathways are upregulated pathways in cancer. Since the 1940s, targeting nucleotide and folate metabolism to induce thymineless death has remained first-line anti-cancer treatment. Recent discoveries that showing cancer cells have rewired networks and exploit unique enzymes for proliferation, have renewed interest in metabolic pathways. The cancer-specific expression of MTHFD2 has gained wide-spread attention and here we describe an emerging role for MTHFD2 in the DNA damage response (DDR). The folate metabolism enzyme MTHFD2 is one of the most consistently overexpressed metabolic enzymes in cancer and an emerging anticancer target. We show a novel role for MTHFD2 being essential for DNA replication and genomic stability in cancer cells. We describe first-in-class nanomolar MTHFD2 inhibitors (MTHFD2i), with protein co-crystal structures demonstrating binding in the active site of MTHFD2 and engaging with the target in cells and tumours. We show MTHFD2i reduce replication fork speed and induce replication stress, followed by S phase arrest, apoptosis and killing of a range of haematological and solid cancer cells in vitro and in vivo, with a therapeutic window spanning up to four orders of magnitude compared to non-transformed cells. Mechanistically, MTHFD2i prevent thymidine production leading to mis-incorporation of uracil into DNA and replication stress. As MTHFD2 expression is cancer specific there is a potential of MTHFD2i to synergize with other treatments. Here, we show MTHFD2i synergize with dUTPase inhibitors as well as other DDR inhibitors and demonstrate the mechanism of action. These results demonstrate a new link between MTHFD2-dependent cancer metabolism and replication stress that can be exploited therapeutically.
Keywords
MTHFD2, one-carbon metabolism, folate metabolism, DNA replication, replication stress, synthetic lethal, thymineless death, small-molecule inhibitor, DNA damage response

#### 1060 – Genetic and pharmacologic inhibition of Skp2, an E3 ubiquitin ligase and RB1-target, has antitumor activity in RB1-deficient human and mouse small cell lung cancer (SCLC)

Presenter/Authors
Hongling ZhaoVineeth SukrithanNiloy IqbalCari NicholasYingjiao XueJoseph LockerJuntao ZouLiang ZhuEdward L. Schwartz. Albert Einstein College of Medicine, Bronx, NY, Albert Einstein College of Medicine, Bronx, NY, Albert Einstein College of Medicine, Bronx, NY, University of Pittsburgh Medical Center, Pittsburgh, PA, Albert Einstein College of Medicine, Bronx, NY
Disclosures
H. Zhao: None. V. Sukrithan: None. N. Iqbal: None. C. Nicholas: None. Y. Xue: None. J. Locker: None. J. Zou: None. L. Zhu: None. E.L. Schwartz: None.
Abstract
The identification of driver mutations and their corresponding targeted drugs has led to significant improvements in the treatment of non-small cell lung cancer (NSCLC) and other solid tumors; however, similar advances have not been made in the treatment of small cell lung cancer (SCLC). Due to their aggressive growth, frequent metastases, and resistance to chemotherapy, the five-year overall survival of SCLC is less than 5%. While SCLC tumors can be sensitive to first-line therapy of cisplatin and etoposide, most patients relapse, often in less than 3 months after initial therapy. Dozens of drugs have been tested clinically in SCLC, including more than 40 agents that have failed in phase III trials.
The near uniform bi-allelic inactivation of the tumor suppressor gene RB1 is a defining feature of SCLC. RB1 is mutated in highly aggressive tumors, including SCLC, where its functional loss, along with that of TP53, is both required and sufficient for tumorigenesis. While it is known that RB1 mutant cells fail to arrest at G1/S in response to checkpoint signals, this information has not led to effective strategies to treat RB1-deficient tumors, and it has been challenging to develop targeted drugs for tumors that are driven by the loss of gene function.
Our group previously identified Skp2, a substrate recruiting subunit of the SCF-Skp2 E3 ubiquitin ligase, as an early repression target of pRb whose knockout blocked tumorigenesis in Rb1-deficient prostate and pituitary tumors. Here we used genetic mouse models to demonstrate that deletion of Skp2 completely blocked the formation of SCLC in Rb1/p53-knockout mice (RP mice). Skp2 KO caused an increased accumulation of the Skp2-degradation target p27, a cyclin-dependent kinase inhibitor, and we confirmed this was the mechanism of protection in the RP-Skp2 KO mice by using the knock-in of a mutant p27 that was unable to bind to Skp2. Building on the observed synthetic lethality between Rb1 and Skp2, we found that small molecules that bind to and/or inhibit Skp2 induced apoptosis and inhibited SCLC cell growth. In a panel of SCLC cell lines, growth inhibition by a Skp2 inhibitor was not correlated with sensitivity/resistance to etoposide. Targeting Skp2 also had in vivo antitumor activity in mouse tumors and human patient-derived xenograft models of SCLC. Using the genetic and pharmacologic approaches, antitumor activity was seen in vivo in established SCLC primary lung tumors, in liver metastases, and in chemotherapy-resistant tumors. The identification and validation of an actionable target downstream of RB1 could have a broad impact on treatment of SCLC and other advanced tumors with mutant RB1, for which there are currently no targeted therapies available.

## Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 28, 2020 Session on COVID-19 and Cancer 9:00 AM

### Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 28, 2020 Session on COVID-19 and Cancer 9:00 AM

Reporter: Stephen J. Williams, PhD

#### Antoni Ribas UCLA Medical Center

• Almost 60,000 viewed the AACR 2020 Virtual meeting for the April 27 session
• The following speakers were the first cancer researchers treating patients at the epicenters of the pandemic even though nothing was known about the virus

The experience of treating patients with cancer during the COVID-19 pandemic in China
Li Zhang, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology

• reporting a retrospective study from three hospitals from Wuhan
• 2.2% of Wuhan cancer patients were COVID positive; most were lung cancers and most male; 35% were stage four
• most have hospital transmission of secondary infection; had severe events when admitted
• 74% were prescribed antivirals like ganciclovir and others; iv IgG was given to some
• mortailtiy rate of 26%; by April 4 54% were cured and discharged; median time of infection to severe event was 7 days; clinical presentation SARS sepsis, and shock
• by day 10 in lung cancer patients, see lung path but after supportive therapy improved
• cancer patients at stage four who did not receive therapy were at higher risk
• they followed up with cancer patients on I/O inhibitors;  it seemed there was only one patient that contracted COVID19 so there may not be as much risk with immune checkpoint inhibitors

TERAVOLT (Thoracic cancERs international coVid 19 cOLlaboraTion): First results of a global collaboration to address the impact of COVID-19 in patients with thoracic malignancies

Marina Chiara Garassino

@marinagarassino
Fondazione IRCCS Istituto Nazionale dei Tumori

Dr Marina Chiara Garassino is the Chief of the Thoracic Oncology Unit at Istituto Nazionale dei Tumori, Milan, Italy. She leads the strategy for clinical and translational research in advanced and locally advanced NSCLC, SCLC, mesothelioma and thymic malignancies. Istituto Nazionale dei Tumori in Milan is the most important comprehensive cancer in Italy and one of the most important in Europe. As a medical oncologist, she has done research in precision medicine and in immuno-oncology. Her main research interests have been mainly development of new drugs and therapeutical strategies and biomarkers. She has contributed to over 150 peer-reviewed publications, including publications as first or last author in the New England Journal of Medicine, Lancet Oncology, Journal of Clinical Oncology, Annals of Oncology. She has delivered many presentations at international congresses,  including  AACR, ASCO, ECCO, ESMO, WCLC. Her education includes a degree and further specialization in Medical Oncology at Università degli Studi in Milan. She achieved a Master Degree in Oncology management at University of Economics “Luigi Bocconi”. She completed her training with an ESMO Clinical fellowship in 2009 at Christie’s Hospital in Manchester (UK). She was a member of the EMA SAG (Scientific Advisory Group). She is serving as ESMO Council member as the Chair of the National Societies Committee. She was the ESMO National Representative for Italy for 5 years (2011-2017). She is serving on several ESMO Committees (Public Policy extended Committee, Press Committee, Women for Oncology Committee, Lung Cancer faculty, Membership Committee).She used to be an active member of the Young Oncologist Committee. She’s serving on both ESMO, WCLC and ASCO annual congress Lung Cancer Track (2019, and 2020), Chair of ESMO National Societies, from 2019. She is the founder and president of Women for Oncology Italy.

• 2 million confirmed cases but half of patients are asymptomatic and not tested; pooled prevalance of COVID in cancer patients in Italy was 2%; must take them as high risk patients
• they were not prepared for pandemic lasting for months instead of days; March 15 in middle of outbreak they started TERAVOLT registry; by March 26 had IRB approval; they are accruing 17 new patients per week; Ontario also joined in and has become worldwide (21 countries involved);  in registry they also included radiologic exams and COVID testing result
• most patients were males and many smokers; 75% had SCLC; 83% of cases had one comorbility like hypertension and one third had at least one comorbility; 73.9% of patients were on treatment (they see this in their clinic: 30% on chemo or TKI alone; other patients were just on folowup
• most of symptoms overlap with symptoms of lung cancer like pneumonia and pneumonitits and multi organ failure; most were hospitalized
• unexpected high mortality among lung cancer patients with COVID19; this mortality seems due to COVID and not to cancer;
• study had some limitations like short followup and some surgical cases so some bias may be present
• she stresses don’t go it alone and make your own registry JOIN A REGISTRY

Outcome of cancer patients infected with COVID-19, including toxicity of cancer treatments
Fabrice Barlesi @barlesi
Gustave Roussy Cancer Campus

Professor Fabrice Barlesi
As a specialist in lung cancer, precision medicine and cancer immunology, Prof. Fabrice Barlesi is a major contributor to research in the field of novel oncological therapies. He was apppointed General Director of Gustave Roussy in January 2020.
Fabrice Barlesi is Professor of Medicine at the University of Aix-Marseille. He has been head of the Multidisciplinary Oncology and Innovative Therapies Department of the Nord Hospital in Marseille (Marseille Public Hospitals) and the Marseille Centre for Early Trials in Oncology (CLIP2) which were established by him. He holds a doctorate in Sciences and Management with methods of analysis of health care systems, together with an ESSEC (international business school) master’s degree in general hospital management.
Professor Barlesi was also a co-founder of the Marseille Immunopôle French Immunology network, which aims to coordinate immunological expertise in the Aix-Marseille metropolitan area. In this context, he has organised PIONeeR (Investment in the future RHU 2017), the major international Hospital-University research project whose objective is to improve understanding of resistance to immunotherapy – anti-PD1(L1) – in lung cancer and help to prevent and overcome it. He was also vice-chair of the PACA (Provence, Alps and Côte d’Azur) Region Cancer Research Directorate.
Professor Barlesi is the author and co-author of some 300 articles in international journals and specialist publications. In 2018, the European Society of Medical Oncology (ESMO) and the International Association for the Study of Lung Cancer (IASLC) awarded him the prestigious Heine H. Hansen prize. He appears in the 2019 world list of most influential researchers (Highly cited researchers, Web of Science Group).
• March 14 started protective measures and at peak had increased commited beds at highest rate
• 12% of cancer patients tested positive for COVID; (by RTPCR); they curated data across different chemo regimens used
• they retrospectively collected data; primary endpoint was clinical worsening; median of disease 13 days;
• they actually had more breast cancer patients and other solid malignancies; 23% of covid cases no symptoms; 83% finally did have the symptoms after followup; diarhea actually in 10% of cases so clinics are seeing this as a symptom
• CT scan showed 66% cases had pneumonitits like display; 25% patients were managed as outpatient
• 24% patients worsened during treatment but 75% were able to go home (treated at home or well)
• I/O did not have negative outcome and you can use these drugs without increasing risk to COVID
• although many clinical trials have been hindered they are actively recruiting for COVID-cancer studies
• outcomes with respect to death and symptoms are comparable to worldwide stats

Adapting oncologic practice to COVID19 outbreak: From outpatient triage to risk assessment for specific treatment in Madrid, Spain
Carlos Gomez-Martin
Octubre University Hospital

• MOST slides were DO NOT POST so as requested data will not be shown; this study will be published soon
• Summary is that Spain is seeing statistics like other European countries and similar results
• Tocilizumab, the IL6 antagonists had been suggested as a treatment for cytokine storm and they are involved in a trial with this agent; results will be published

Experience in using oncology drugs in patients with COVID-19

Paolo A. Ascierto
Istituto Nazionale Tumori IRCCS Fondazione Pascale

• giving surgery only for patients at highest risk of cancer mortality so using neoadjuvant therapy more often
• telemedicine is a viable strategy for patient consult
• for metastatic melanoma they are given highest priority for treatment
• they are conducting a tocilizumab clinical trial and have accrued over 300 patients
• results are in press so please look for publication soon
• also can use TNF inhibitor, JAK inhibitor, IL1 inhibitor to treat cytokine storm

COVID-19 and cancer: Flattening the curve but widening disparities
Louis P. Voigt
Memorial Sloan Kettering Cancer Center

• Sloan has performed about 5000 COVID tests;  78 patients needed hospitilization; 15 died; 40% still in ICU
• they do see many African American patients
• mortality rates in US (published) have been around 50-60 % for cancer patients with COVID; Sloan prelim results are lower but still accruing data

Patients with cancer appear more vulnerable to SARS-COV-2: A multi-center study during the COVID-19 outbreak
Hongbing Cai
Zhongnan Hospital of Wuhan University

• metastatic cancer showed much higher risk than non cancer but non metastatic showed increased risk too
• main criteria of outcome was ICU admission
• patients need to be isolated and personalized treatment plans need to be made
• many comparisons were between non cancer and cancer which was clearest significance; had not looked at cancer types or stage grade or treatment
• it appears that there are more questions right now than answers so data collection is a priority

@pharma_BI

@AACR

@CureCancerNow

@pharmanews

@BiotechWorld

@HopkinsMedicine

#AACR20

#### For other Articles on the Online Open Access Journal on COVID19 and Cancer please see

https://pharmaceuticalintelligence.com/coronavirus-portal/

## Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 27, 2020 Minisymposium on AACR Project Genie & Bioinformatics 4:00 PM – 6:00 PM

### Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 27, 2020 Minisymposium on AACR Project Genie & Bioinformatics 4:00 PM – 6:00 PM

SESSION VMS.MD01.01 – Advancing Cancer Research through an International Cancer Registry: AACR Project GENIE Use Cases

Reporter: Stephen J. Williams, PhD

April 27, 2020, 4:00 PM – 6:00 PM
Virtual Meeting: All Session Times Are U.S. EDT

Session Type
Virtual Minisymposium
Track(s)
Bioinformatics and Systems Biology
17 Presentations
4:00 PM – 6:00 PM
– Chairperson Gregory J. Riely. Memorial Sloan Kettering Cancer Center, New York, NY

4:00 PM – 4:01 PM
– Introduction Gregory J. Riely. Memorial Sloan Kettering Cancer Center, New York, NY

Precision medicine requires an end-to-end learning healthcare system, wherein the treatment decisions for patients are informed by the prior experiences of similar patients. Oncology is currently leading the way in precision medicine because the genomic and other molecular characteristics of patients and their tumors are routinely collected at scale. A major challenge to realizing the promise of precision medicine is that no single institution is able to sequence and treat sufficient numbers of patients to improve clinical-decision making independently. To overcome this challenge, the AACR launched Project GENIE (Genomics Evidence Neoplasia Information Exchange).

AACR Project GENIE is a publicly accessible international cancer registry of real-world data assembled through data sharing between 19 of the leading cancer centers in the world. Through the efforts of strategic partners Sage Bionetworks (https://sagebionetworks.org) and cBioPortal (www.cbioportal.org), the registry aggregates, harmonizes, and links clinical-grade, next-generation cancer genomic sequencing data with clinical outcomes obtained during routine medical practice from cancer patients treated at these institutions. The consortium and its activities are driven by openness, transparency, and inclusion, ensuring that the project output remains accessible to the global cancer research community for the benefit of all patients.AACR Project GENIE fulfills an unmet need in oncology by providing the statistical power necessary to improve clinical decision-making, particularly in the case of rare cancers and rare variants in common cancers. Additionally, the registry can power novel clinical and translational research.

Because we collect data from nearly every patient sequenced at participating institutions and have committed to sharing only clinical-grade data, the GENIE registry contains enough high-quality data to power decision making on rare cancers or rare variants in common cancers. We see the GENIE data providing another knowledge turn in the virtuous cycle of research, accelerating the pace of drug discovery, improving the clinical trial design, and ultimately benefiting cancer patients globally.

The first set of cancer genomic data aggregated through AACR Project Genomics Evidence Neoplasia Information Exchange (GENIE) was available to the global community in January 2017.  The seventh data set, GENIE 7.0-public, was released in January 2020 adding more than 9,000 records to the database. The combined data set now includes nearly 80,000 de-identified genomic records collected from patients who were treated at each of the consortium’s participating institutions, making it among the largest fully public cancer genomic data sets released to date.  These data will be released to the public every six months. The public release of the eighth data set, GENIE 8.0-public, will take place in July 2020.

The combined data set now includes data for over 80 major cancer types, including data from greater than 12,500 patients with lung cancer, nearly 11,000 patients with breast cancer, and nearly 8,000 patients with colorectal cancer.

For more details about the data, analyses, and summaries of the data attributes from this release, GENIE 7.0-public, consult the data guide.

Users can access the data directly via cbioportal, or download the data directly from Sage Bionetworks. Users will need to create an account for either site and agree to the terms of access.

For frequently asked questions, visit our FAQ page.

• In fall of 2019 AACR announced the Bio Collaborative which collected pan cancer data in conjuction and collaboration and support by a host of big pharma and biotech companies
• they have a goal to expand to more than 6 cancer types and more than 50,000 records including smoking habits, lifestyle data etc
• They have started with NSCLC have have done mutational analysis on these
• included is tumor mutational burden and using cbioportal able to explore genomic data even further
• treatment data is included as well
• need to collect highly CURATED data with PRISM backbone to get more than outcome data, like progression data
• they might look to incorporate digital pathology but they are not there yet; will need good artificial intelligence systems

4:01 PM – 4:15 PM
– Invited Speaker Gregory J. Riely. Memorial Sloan Kettering Cancer Center, New York, NY

4:15 PM – 4:20 PM
– Discussion

4:20 PM – 4:30 PM
1092 – A systematic analysis of BRAF mutations and their sensitivity to different BRAF inhibitors: Zohar Barbash, Dikla Haham, Liat Hafzadi, Ron Zipor, Shaul Barth, Arie Aizenman, Lior Zimmerman, Gabi Tarcic. Novellusdx, Jerusalem, Israel

Abstract: The MAPK-ERK signaling cascade is among the most frequently mutated pathways in human cancer, with the BRAF V600 mutation being the most common alteration. FDA-approved BRAF inhibitors as well as combination therapies of BRAF and MEK inhibitors are available and provide survival benefits to patients with a BRAF V600 mutation in several indications. Yet non-V600 BRAF mutations are found in many cancers and are even more prevalent than V600 mutations in certain tumor types. As the use of NGS profiling in precision oncology is becoming more common, novel alterations in BRAF are being uncovered. This has led to the classification of BRAF mutations, which is dependent on its biochemical properties and affects it sensitivity to inhibitors. Therefore, annotation of these novel variants is crucial for assigning correct treatment. Using a high throughput method for functional annotation of MAPK activity, we profiled 151 different BRAF mutations identified in the AACR Project GENIE dataset, and their response to 4 different BRAF inhibitors- vemurafenib and 3 different exploratory 2nd generation inhibitors. The system is based on rapid synthesis of the mutations and expression of the mutated protein together with fluorescently labeled reporters in a cell-based assay. Our results show that from the 151 different BRAF mutations, ~25% were found to activate the MAPK pathway. All of the class 1 and 2 mutations tested were found to be active, providing positive validation for the method. Additionally, many novel activating mutations were identified, some outside of the known domains. When testing the response of the active mutations to different classes of BRAF inhibitors, we show that while vemurafenib efficiently inhibited V600 mutations, other types of mutations and specifically BRAF fusions were not inhibited by this drug. Alternatively, the second-generation experimental inhibitors were effective against both V600 as well as non-V600 mutations. Using this large-scale approach to characterize BRAF mutations, we were able to functionally annotate the largest number of BRAF mutations to date. Our results show that the number of activating variants is large and that they possess differential sensitivity to different types of direct inhibitors. This data can serve as a basis for rational drug design as well as more accurate treatment options for patients.

• Molecular profiling is becoming imperative for successful  targeted therapies
• 500 unique mutations in BRAF so need to use bioinformatic pipeline; start with NGS panels then cluster according to different subtypes or class specific patterns
• certain mutation like V600E mutations have distinct clustering in tumor types
• 25% of mutations occur with other mutations; mutations may not be functional; they used highthruput system to analyze other V600 braf mutations to determine if functional
• active yet uncharacterized BRAF mutations seen in a major proportion of human tumors
• using genomic drug data found that many inhibitors like verafanib are specific to a specific mutation but other inhibitors that are not specific to a cleft can inhibit other BRAF mutants
• 40% of 135 mutants were functionally active
• USE of Functional Profiling instead of just genomic profiling
• Q?: They have already used this platform and analysis for RTKs and other genes as well successfully
• Q? how do you deal with co reccuring mutations: platform is able to do RTK plus signaling protiens

4:30 PM – 4:35 PM
– Discussion

4:35 PM – 4:45 PM
1093 – Calibration Tool for Genomic Aggregates (CTGA): A deep learning framework for calibrating somatic mutation profiling data from conventional gene panel data. Jordan Anaya, Craig Cummings, Jocelyn Lee, Alexander Baras. Johns Hopkins Sidney Kimmel Comprehensive Cancer Center, MD, Genentech, Inc., CA, AACR, Philadelphia, PA

Abstract: It has been suggested that aggregate genomic measures such as mutational burden can be associated with response to immunotherapy. Arguably, the gold standard for deriving such aggregate genomic measures (AGMs) would be from exome level sequencing. While many clinical trials run exome level sequencing, the vast majority of routine genomic testing performed today, as seen in AACR Project GENIE, is targeted / gene-panel based sequencing.
Despite the smaller size of these gene panels focused on clinically targetable alterations, it has been shown they can estimate, to some degree, exomic mutational burden; usually by normalizing mutation count by the relevant size of the panels. These smaller gene panels exhibit significant variability both in terms of accuracy relative to exomic measures and in comparison to other gene panels. While many genes are common to the panels in AACR Project GENIE, hundreds are not. These differences in extent of coverage and genomic loci examined can result in biases that may negatively impact panel to panel comparability.
To address these issues we developed a deep learning framework to model exomic AGMs, such as mutational burden, from gene panel data as seen in AACR Project GENIE. This framework can leverage any available sample and variant level information, in which variants are featurized to effectively re-weight their importance when estimating a given AGM, such as mutational burden, through the use of multiple instance learning techniques in this form of weakly supervised data.
Using TCGA data in conjunction with AACR Project GENIE gene panel definitions, as a proof of concept, we first applied this framework to learn expected variant features such as codons and genomic position from mutational data (greater than 99.9% accuracy observed). Having established the validity of the approach, we then applied this framework to somatic mutation profiling data in which we show that data from gene panels can be calibrated to exomic TMB and thereby improve panel to panel compatibility. We observed approximately 25% improvements in mean squared error and R-squared metrics when using our framework over conventional approaches to estimate TMB from gene panel data across the 9 tumors types examined (spanning melanoma, lung cancer, colon cancer, and others). This work highlights the application of sophisticated machine learning approaches towards the development of needed calibration techniques across seemingly disparate gene panel assays used clinically today.

4:45 PM – 4:50 PM
– Discussion

4:50 PM – 5:00 PM
1094 – Genetic determinants of EGFR-driven lung cancer growth and therapeutic response in vivoGiorgia Foggetti, Chuan Li, Hongchen Cai, Wen-Yang Lin, Deborah Ayeni, Katherine Hastings, Laura Andrejka, Dylan Maghini, Robert Homer, Dmitri A. Petrov, Monte M. Winslow, Katerina Politi. Yale School of Medicine, New Haven, CT, Stanford University School of Medicine, Stanford, CA, Stanford University School of Medicine, Stanford, CA, Yale School of Medicine, New Haven, CT, Stanford University School of Medicine, Stanford, CA, Yale School of Medicine, New Haven, CT

5:00 PM – 5:05 PM
– Discussion

5:05 PM – 5:15 PM
1095 – Comprehensive pan-cancer analyses of RAS genomic diversityRobert Scharpf, Gregory Riely, Mark Awad, Michele Lenoue-Newton, Biagio Ricciuti, Julia Rudolph, Leon Raskin, Andrew Park, Jocelyn Lee, Christine Lovly, Valsamo Anagnostou. Johns Hopkins Sidney Kimmel Comprehensive Cancer Center, Baltimore, MD, Memorial Sloan Kettering Cancer Center, New York, NY, Dana-Farber Cancer Institute, Boston, MA, Vanderbilt-Ingram Cancer Center, Nashville, TN, Amgen, Inc., Thousand Oaks, CA, AACR, Philadelphia, PA

5:15 PM – 5:20 PM
– Discussion

5:20 PM – 5:30 PM
1096 – Harmonization standards from the Variant Interpretation for Cancer Consortium. Alex H. Wagner, Reece K. Hart, Larry Babb, Robert R. Freimuth, Adam Coffman, Yonghao Liang, Beth Pitel, Angshumoy Roy, Matthew Brush, Jennifer Lee, Anna Lu, Thomas Coard, Shruti Rao, Deborah Ritter, Brian Walsh, Susan Mockus, Peter Horak, Ian King, Dmitriy Sonkin, Subha Madhavan, Gordana Raca, Debyani Chakravarty, Malachi Griffith, Obi L. Griffith. Washington University School of Medicine, Saint Louis, MO, Reece Hart Consulting, CA, Broad Institute, Boston, MA, Mayo Clinic, Rochester, MN, Washington University School of Medicine, Saint Louis, MO, Washington University School of Medicine, Saint Louis, MO, Baylor College of Medicine, Houston, TX, Oregon Health and Science University, Portland, OR, National Cancer Institute, Bethesda, MD, Georgetown University, Washington, DC, The Jackson Laboratory for Genomic Medicine, Farmington, CT, National Center for Tumor Diseases, Heidelberg, Germany, University of Toronto, Toronto, ON, Canada, University of Southern California, Los Angeles, CA, Memorial Sloan Kettering Cancer Center, New York, NY

Abstract: The use of clinical gene sequencing is now commonplace, and genome analysts and molecular pathologists are often tasked with the labor-intensive process of interpreting the clinical significance of large numbers of tumor variants. Numerous independent knowledge bases have been constructed to alleviate this manual burden, however these knowledgebases are non-interoperable. As a result, the analyst is left with a difficult tradeoff: for each knowledgebase used the analyst must understand the nuances particular to that resource and integrate its evidence accordingly when generating the clinical report, but for each knowledgebase omitted there is increased potential for missed findings of clinical significance.The Variant Interpretation for Cancer Consortium (VICC; cancervariants.org) was formed as a driver project of the Global Alliance for Genomics and Health (GA4GH; ga4gh.org) to address this concern. VICC members include representatives from several major somatic interpretation knowledgebases including CIViC, OncoKB, Jax-CKB, the Weill Cornell PMKB, the IRB-Barcelona Cancer Biomarkers Database, and others. Previously, the VICC built and reported on a harmonized meta-knowledgebase of 19,551 biomarker associations of harmonized variants, diseases, drugs, and evidence across the constituent resources.In that study, we analyzed the frequency with which the tumor samples from the AACR Project GENIE cohort would match to harmonized associations. Variant matches increased dramatically from 57% to 86% when broader matching to regions describing categorical variants were allowed. Unlike precise sequence variants with specified alternate alleles, categorical variants describe a collection of potential variants with a common feature, such as “V600” (non-valine alleles at the 600 residue), “Exon 20 mutations” (all non-silent mutations in exon 20), or “Gain-of-function” (hypermorphic alterations that activate or amplify gene activity). However, matching observed sequence variants to categorical variants is challenging, as the latter are typically only described as unstructured text. Here we describe the expressive and computational GA4GH Variation Representation specification (vr-spec.readthedocs.io), which we co-developed as members of the GA4GH Genomic Knowledge Standards work stream. This specification provides a schema for common, precise forms of variation (e.g. SNVs and Indels) and the method for computing identifiers from these objects. We highlight key aspects of the specification and our work to apply it to the characterization of categorical variation, showcasing the variant terminology and classification tools developed by the VICC to support this effort. These standards and tools are free, open-source, and extensible, overcoming barriers to standardized variant knowledge sharing and search.

https://cancervariants.org/

• store information from different databases by curating them and classifying them then harmonizing them into values
• harmonize each variant across their knowledgebase; at any level of evidence
• had 29% of patients variants that matched when compare across many knowledgebase databases versus only 13% when using individual databases
• they are also trying to curate the database so a variant will have one code instead of various refseq codes or protein codes
• VIC is an open consortium

5:30 PM – 5:35 PM
– Discussion

5:35 PM – 5:45 PM
1097 – FGFR2 in-frame indels: A novel targetable alteration in intrahepatic cholangiocarcinoma. Yvonne Y. Li, James M. Cleary, Srivatsan Raghavan, Liam F. Spurr, Qibiao Wu, Lei Shi, Lauren K. Brais, Maureen Loftus, Lipika Goyal, Anuj K. Patel, Atul B. Shinagare, Thomas E. Clancy, Geoffrey Shapiro, Ethan Cerami, William R. Sellers, William C. Hahn, Matthew Meyerson, Nabeel Bardeesy, Andrew D. Cherniack, Brian M. Wolpin. Dana-Farber Cancer Institute, Boston, MA, Dana-Farber Cancer Institute, Boston, MA, Massachusetts General Hospital, Boston, MA, Brigham and Women’s Hospital, Boston, MA, Dana-Farber Cancer Institute, Boston, MA, Dana-Farber Cancer Institute, Boston, MA, Broad Institute of MIT and Harvard, Cambridge, MA, Massachusetts General Hospital, Boston, MA

5:45 PM – 5:50 PM
– Discussion

5:50 PM – 6:00 PM
– Closing RemarksGregory J. Riely. Memorial Sloan Kettering Cancer Center, New York, NY

@pharma_BI

@AACR

@CureCancerNow

@pharmanews

@BiotechWorld

@HopkinsMedicine

#AACR20

#AACR2020

#curecancernow

#pharmanews