Live Notes, Real Time Conference Coverage AACR 2020: Tuesday June 23, 2020 Noon-2:45 Educational Sessions
Reporter: Stephen J. Williams, PhD
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Presidential Address
Elaine R Mardis, William N Hait
DETAILS
Welcome and introduction
William N Hait
Improving diagnostic yield in pediatric cancer precision medicine
Elaine R Mardis
- Advent of genomics have revolutionized how we diagnose and treat lung cancer
- We are currently needing to understand the driver mutations and variants where we can personalize therapy
- PD-L1 and other checkpoint therapy have not really been used in pediatric cancers even though CAR-T have been successful
- The incidence rates and mortality rates of pediatric cancers are rising
- Large scale study of over 700 pediatric cancers show cancers driven by epigenetic drivers or fusion proteins. Need for transcriptomics. Also study demonstrated that we have underestimated germ line mutations and hereditary factors.
- They put together a database to nominate patients on their IGM Cancer protocol. Involves genetic counseling and obtaining germ line samples to determine hereditary factors. RNA and protein are evaluated as well as exome sequencing. RNASeq and Archer Dx test to identify driver fusions
- PECAN curated database from St. Jude used to determine driver mutations. They use multiple databases and overlap within these databases and knowledge base to determine or weed out false positives
- They have used these studies to understand the immune infiltrate into recurrent cancers (CytoCure)
- They found 40 germline cancer predisposition genes, 47 driver somatic fusion proteins, 81 potential actionable targets, 106 CNV, 196 meaningful somatic driver mutations
Tuesday, June 23
12:00 PM – 12:30 PM EDT
Awards and Lectures
NCI Director’s Address
Norman E Sharpless, Elaine R Mardis
DETAILS
Introduction: Elaine Mardis
NCI Director Address: Norman E Sharpless
- They are functioning well at NCI with respect to grant reviews, research, and general functions in spite of the COVID pandemic and the massive demonstrations on also focusing on the disparities which occur in cancer research field and cancer care
- There are ongoing efforts at NCI to make a positive difference in racial injustice, diversity in the cancer workforce, and for patients as well
- Need a diverse workforce across the cancer research and care spectrum
- Data show that areas where the clinicians are successful in putting African Americans on clinical trials are areas (geographic and site specific) where health disparities are narrowing
- Grants through NCI new SeroNet for COVID-19 serologic testing funded by two RFAs through NIAD (RFA-CA-30-038 and RFA-CA-20-039) and will close on July 22, 2020
Tuesday, June 23
12:45 PM – 1:46 PM EDT
Virtual Educational Session
Immunology, Tumor Biology, Experimental and Molecular Therapeutics, Molecular and Cellular Biology/Genetics
Tumor Immunology and Immunotherapy for Nonimmunologists: Innovation and Discovery in Immune-Oncology
This educational session will update cancer researchers and clinicians about the latest developments in the detailed understanding of the types and roles of immune cells in tumors. It will summarize current knowledge about the types of T cells, natural killer cells, B cells, and myeloid cells in tumors and discuss current knowledge about the roles these cells play in the antitumor immune response. The session will feature some of the most promising up-and-coming cancer immunologists who will inform about their latest strategies to harness the immune system to promote more effective therapies.
Judith A Varner, Yuliya Pylayeva-Gupta
Introduction
Judith A Varner
New techniques reveal critical roles of myeloid cells in tumor development and progression
- Different type of cells are becoming targets for immune checkpoint like myeloid cells
- In T cell excluded or desert tumors T cells are held at periphery so myeloid cells can infiltrate though so macrophages might be effective in these immune t cell naïve tumors, macrophages are most abundant types of immune cells in tumors
- CXCLs are potential targets
- PI3K delta inhibitors,
- Reduce the infiltrate of myeloid tumor suppressor cells like macrophages
- When should we give myeloid or T cell therapy is the issue
Judith A Varner
Novel strategies to harness T-cell biology for cancer therapy
Positive and negative roles of B cells in cancer
Yuliya Pylayeva-Gupta
New approaches in cancer immunotherapy: Programming bacteria to induce systemic antitumor immunity
Tuesday, June 23
12:45 PM – 1:46 PM EDT
Virtual Educational Session
Cancer Chemistry
Chemistry to the Clinic: Part 2: Irreversible Inhibitors as Potential Anticancer Agents
There are numerous examples of highly successful covalent drugs such as aspirin and penicillin that have been in use for a long period of time. Despite historical success, there was a period of reluctance among many to purse covalent drugs based on concerns about toxicity. With advances in understanding features of a well-designed covalent drug, new techniques to discover and characterize covalent inhibitors, and clinical success of new covalent cancer drugs in recent years, there is renewed interest in covalent compounds. This session will provide a broad look at covalent probe compounds and drug development, including a historical perspective, examination of warheads and electrophilic amino acids, the role of chemoproteomics, and case studies.
Benjamin F Cravatt, Richard A. Ward, Sara J Buhrlage
Discovering and optimizing covalent small-molecule ligands by chemical proteomics
Benjamin F Cravatt
- Multiple approaches are being investigated to find new covalent inhibitors such as: 1) cysteine reactivity mapping, 2) mapping cysteine ligandability, 3) and functional screening in phenotypic assays for electrophilic compounds
- Using fluorescent activity probes in proteomic screens; have broad useability in the proteome but can be specific
- They screened quiescent versus stimulated T cells to determine reactive cysteines in a phenotypic screen and analyzed by MS proteomics (cysteine reactivity profiling); can quantitate 15000 to 20,000 reactive cysteines
- Isocitrate dehydrogenase 1 and adapter protein LCP-1 are two examples of changes in reactive cysteines they have seen using this method
- They use scout molecules to target ligands or proteins with reactive cysteines
- For phenotypic screens they first use a cytotoxic assay to screen out toxic compounds which just kill cells without causing T cell activation (like IL10 secretion)
- INTERESTINGLY coupling these MS reactive cysteine screens with phenotypic screens you can find NONCANONICAL mechanisms of many of these target proteins (many of the compounds found targets which were not predicted or known)
Electrophilic warheads and nucleophilic amino acids: A chemical and computational perspective on covalent modifier
The covalent targeting of cysteine residues in drug discovery and its application to the discovery of Osimertinib
Richard A. Ward
- Cysteine activation: thiolate form of cysteine is a strong nucleophile
- Thiolate form preferred in polar environment
- Activation can be assisted by neighboring residues; pKA will have an effect on deprotonation
- pKas of cysteine vary in EGFR
- cysteine that are too reactive give toxicity while not reactive enough are ineffective
Accelerating drug discovery with lysine-targeted covalent probes
Tuesday, June 23
12:45 PM – 2:15 PM EDT
Virtual Educational Session
Molecular and Cellular Biology/Genetics
Virtual Educational Session
Tumor Biology, Immunology
Metabolism and Tumor Microenvironment
This Educational Session aims to guide discussion on the heterogeneous cells and metabolism in the tumor microenvironment. It is now clear that the diversity of cells in tumors each require distinct metabolic programs to survive and proliferate. Tumors, however, are genetically programmed for high rates of metabolism and can present a metabolically hostile environment in which nutrient competition and hypoxia can limit antitumor immunity.
Jeffrey C Rathmell, Lydia Lynch, Mara H Sherman, Greg M Delgoffe
T-cell metabolism and metabolic reprogramming antitumor immunity
Jeffrey C Rathmell
Introduction
Jeffrey C Rathmell
Metabolic functions of cancer-associated fibroblasts
Mara H Sherman
Tumor microenvironment metabolism and its effects on antitumor immunity and immunotherapeutic response
Greg M Delgoffe
- Multiple metabolites, reactive oxygen species within the tumor microenvironment; is there heterogeneity within the TME metabolome which can predict their ability to be immunosensitive
- Took melanoma cells and looked at metabolism using Seahorse (glycolysis): and there was vast heterogeneity in melanoma tumor cells; some just do oxphos and no glycolytic metabolism (inverse Warburg)
- As they profiled whole tumors they could separate out the metabolism of each cell type within the tumor and could look at T cells versus stromal CAFs or tumor cells and characterized cells as indolent or metabolic
- T cells from hyerglycolytic tumors were fine but from high glycolysis the T cells were more indolent
- When knock down glucose transporter the cells become more glycolytic
- If patient had high oxidative metabolism had low PDL1 sensitivity
- Showed this result in head and neck cancer as well
- Metformin a complex 1 inhibitor which is not as toxic as most mito oxphos inhibitors the T cells have less hypoxia and can remodel the TME and stimulate the immune response
- Metformin now in clinical trials
- T cells though seem metabolically restricted; T cells that infiltrate tumors are low mitochondrial phosph cells
- T cells from tumors have defective mitochondria or little respiratory capacity
- They have some preliminary findings that metabolic inhibitors may help with CAR-T therapy
Obesity, lipids and suppression of anti-tumor immunity
Lydia Lynch
- Hypothesis: obesity causes issues with anti tumor immunity
- Less NK cells in obese people; also produce less IFN gamma
- RNASeq on NOD mice; granzymes and perforins at top of list of obese downregulated
- Upregulated genes that were upregulated involved in lipid metabolism
- All were PPAR target genes
- NK cells from obese patients takes up palmitate and this reduces their glycolysis but OXPHOS also reduced; they think increased FFA basically overloads mitochondria
- PPAR alpha gamma activation mimics obesity
Tuesday, June 23
12:45 PM – 2:45 PM EDT
Virtual Educational Session
Clinical Research Excluding Trials
The Evolving Role of the Pathologist in Cancer Research
Long recognized for their role in cancer diagnosis and prognostication, pathologists are beginning to leverage a variety of digital imaging technologies and computational tools to improve both clinical practice and cancer research. Remarkably, the emergence of artificial intelligence (AI) and machine learning algorithms for analyzing pathology specimens is poised to not only augment the resolution and accuracy of clinical diagnosis, but also fundamentally transform the role of the pathologist in cancer science and precision oncology. This session will discuss what pathologists are currently able to achieve with these new technologies, present their challenges and barriers, and overview their future possibilities in cancer diagnosis and research. The session will also include discussions of what is practical and doable in the clinic for diagnostic and clinical oncology in comparison to technologies and approaches primarily utilized to accelerate cancer research.
Jorge S Reis-Filho, Thomas J Fuchs, David L Rimm, Jayanta Debnath
DETAILS
Tuesday, June 23
12:45 PM – 2:45 PM EDT
High-dimensional imaging technologies in cancer research
David L Rimm
- Using old methods and new methods; so cell counting you use to find the cells then phenotype; with quantification like with Aqua use densitometry of positive signal to determine a threshold to determine presence of a cell for counting
- Hiplex versus multiplex imaging where you have ten channels to measure by cycling of flour on antibody (can get up to 20plex)
- Hiplex can be coupled with Mass spectrometry (Imaging Mass spectrometry, based on heavy metal tags on mAbs)
- However it will still take a trained pathologist to define regions of interest or field of desired view
Introduction
Jayanta Debnath
Challenges and barriers of implementing AI tools for cancer diagnostics
Jorge S Reis-Filho
Implementing robust digital pathology workflows into clinical practice and cancer research
Jayanta Debnath
Invited Speaker
Thomas J Fuchs
- Founder of spinout of Memorial Sloan Kettering
- Separates AI from computational algothimic
- Dealing with not just machines but integrating human intelligence
- Making decision for the patients must involve human decision making as well
- How do we get experts to do these decisions faster
- AI in pathology: what is difficult? =è sandbox scenarios where machines are great,; curated datasets; human decision support systems or maps; or try to predict nature
- 1) learn rules made by humans; human to human scenario 2)constrained nature 3)unconstrained nature like images and or behavior 4) predict nature response to nature response to itself
- In sandbox scenario the rules are set in stone and machines are great like chess playing
- In second scenario can train computer to predict what a human would predict
- So third scenario is like driving cars
- System on constrained nature or constrained dataset will take a long time for commuter to get to decision
- Fourth category is long term data collection project
- He is finding it is still finding it is still is difficult to predict nature so going from clinical finding to prognosis still does not have good predictability with AI alone; need for human involvement
- End to end partnering (EPL) is a new way where humans can get more involved with the algorithm and assist with the problem of constrained data
- An example of a workflow for pathology would be as follows from Campanella et al 2019 Nature Medicine: obtain digital images (they digitized a million slides), train a massive data set with highthroughput computing (needed a lot of time and big software developing effort), and then train it using input be the best expert pathologists (nature to human and unconstrained because no data curation done)
- Led to first clinically grade machine learning system (Camelyon16 was the challenge for detecting metastatic cells in lymph tissue; tested on 12,000 patients from 45 countries)
- The first big hurdle was moving from manually annotated slides (which was a big bottleneck) to automatically extracted data from path reports).
- Now problem is in prediction: How can we bridge the gap from predicting humans to predicting nature?
- With an AI system pathologist drastically improved the ability to detect very small lesions
Virtual Educational Session
Epidemiology
Cancer Increases in Younger Populations: Where Are They Coming from?
Incidence rates of several cancers (e.g., colorectal, pancreatic, and breast cancers) are rising in younger populations, which contrasts with either declining or more slowly rising incidence in older populations. Early-onset cancers are also more aggressive and have different tumor characteristics than those in older populations. Evidence on risk factors and contributors to early-onset cancers is emerging. In this Educational Session, the trends and burden, potential causes, risk factors, and tumor characteristics of early-onset cancers will be covered. Presenters will focus on colorectal and breast cancer, which are among the most common causes of cancer deaths in younger people. Potential mechanisms of early-onset cancers and racial/ethnic differences will also be discussed.
Stacey A. Fedewa, Xavier Llor, Pepper Jo Schedin, Yin Cao
Cancers that are and are not increasing in younger populations
Stacey A. Fedewa
- Early onset cancers, pediatric cancers and colon cancers are increasing in younger adults
- Younger people are more likely to be uninsured and these are there most productive years so it is a horrible life event for a young adult to be diagnosed with cancer. They will have more financial hardship and most (70%) of the young adults with cancer have had financial difficulties. It is very hard for women as they are on their childbearing years so additional stress
- Types of early onset cancer varies by age as well as geographic locations. For example in 20s thyroid cancer is more common but in 30s it is breast cancer. Colorectal and testicular most common in US.
- SCC is decreasing by adenocarcinoma of the cervix is increasing in women’s 40s, potentially due to changing sexual behaviors
- Breast cancer is increasing in younger women: maybe etiologic distinct like triple negative and larger racial disparities in younger African American women
- Increased obesity among younger people is becoming a factor in this increasing incidence of early onset cancers
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