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Archive for the ‘Cancer – General’ Category


Noninvasive blood test can detect cancer 4 years before conventional diagnosis

Reporter : Irina Robu, PhD

Several international researchers at  Fudan University and at Singlera Genomics have developed a noninvasive blood test, PanSeer that can detect whether a patient with five common type of cancers such as stomach, esophageal, colorectal, lung and liver cancer; four years before the condition can be diagnosed by the current methods. Early detection is significant for the reason that the survival of cancer patients increases when the disease is identified at early stages, as the tumor can be surgically removed or treated with suitable drugs. Yet, only a partial number of early screening tests exist for a few cancer types.

The blood test detected cancer in 91 percent of samples from individuals who have been asymptomatic when the samples were collected, but only diagnosed with cancer one to four years later. It was found that the test can accurately detect cancer in 88 percent from samples of 113 patience who were diagnosed. The blood test also detects cancer free samples 95 percent of the time.

What is clear is that the study is unique, in that the scientists had access to blood samples from patients who were asymptomatic but not diagnosed yet. This permitted the researchers to design a test that can find a cancer marker much earlier than conventional diagnosis. The sample were collected as part of 10-year longitudinal study started in 2007 by Fudan University in China.

The researchers highlight that the PanSeer assay is improbable to predict which patients will later go on to develop cancer. As a substitute, it is most possible identifying patients who already have cancerous growths, but continue  to be asymptomatic for current detection methods. The team decided that further large-scale longitudinal studies are needed to confirm the potential of the test for the early detection of cancer in pre-diagnosis individuals.

SOURCE

https://www.universityofcalifornia.edu/news/non-invasive-blood-test-can-detect-cancer-4-years-conventional-diagnosis-methods?utm_source=fiat-lux

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Systems Biology analysis of Transcription Networks, Artificial Intelligence, and High-End Computing Coming to Fruition in Personalized Oncology

Curator: Stephen J. Williams, Ph.D.

In the June 2020 issue of the journal Science, writer Roxanne Khamsi has an interesting article “Computing Cancer’s Weak Spots; An algorithm to unmask tumors’ molecular linchpins is tested in patients”[1], describing some early successes in the incorporation of cancer genome sequencing in conjunction with artificial intelligence algorithms toward a personalized clinical treatment decision for various tumor types.  In 2016, oncologists Amy Tiersten collaborated with systems biologist Andrea Califano and cell biologist Jose Silva at Mount Sinai Hospital to develop a systems biology approach to determine that the drug ruxolitinib, a STAT3 inhibitor, would be effective for one of her patient’s aggressively recurring, Herceptin-resistant breast tumor.  Dr. Califano, instead of defining networks of driver mutations, focused on identifying a few transcription factors that act as ‘linchpins’ or master controllers of transcriptional networks withing tumor cells, and in doing so hoping to, in essence, ‘bottleneck’ the transcriptional machinery of potential oncogenic products. As Dr. Castilano states

“targeting those master regulators and you will stop cancer in its tracks, no matter what mutation initially caused it.”

It is important to note that this approach also relies on the ability to sequence tumors  by RNA-seq to determine the underlying mutations which alter which master regulators are pertinent in any one tumor.  And given the wide tumor heterogeneity in tumor samples, this sequencing effort may have to involve multiple biopsies (as discussed in earlier posts on tumor heterogeneity in renal cancer).

As stated in the article, Califano co-founded a company called Darwin-Health in 2015 to guide doctors by identifying the key transcription factors in a patient’s tumor and suggesting personalized therapeutics to those identified molecular targets (OncoTarget™).  He had collaborated with the Jackson Laboratory and most recently Columbia University to conduct a $15 million 3000 patient clinical trial.  This was a bit of a stretch from his initial training as a physicist and, in 1986, IBM hired him for some artificial intelligence projects.  He then landed in 2003 at Columbia and has been working on identifying these transcriptional nodes that govern cancer survival and tumorigenicity.  Dr. Califano had figured that the number of genetic mutations which potentially could be drivers were too vast:

A 2018 study which analyzed more than 9000 tumor samples reported over 1.5 million mutations[2]

and impossible to develop therapeutics against.  He reasoned that you would just have to identify the common connections between these pathways or transcriptional nodes and termed them master regulators.

A Pan-Cancer Analysis of Enhancer Expression in Nearly 9000 Patient Samples

Chen H, Li C, Peng X, et al. Cell. 2018;173(2):386-399.e12.

Abstract

The role of enhancers, a key class of non-coding regulatory DNA elements, in cancer development has increasingly been appreciated. Here, we present the detection and characterization of a large number of expressed enhancers in a genome-wide analysis of 8928 tumor samples across 33 cancer types using TCGA RNA-seq data. Compared with matched normal tissues, global enhancer activation was observed in most cancers. Across cancer types, global enhancer activity was positively associated with aneuploidy, but not mutation load, suggesting a hypothesis centered on “chromatin-state” to explain their interplay. Integrating eQTL, mRNA co-expression, and Hi-C data analysis, we developed a computational method to infer causal enhancer-gene interactions, revealing enhancers of clinically actionable genes. Having identified an enhancer ∼140 kb downstream of PD-L1, a major immunotherapy target, we validated it experimentally. This study provides a systematic view of enhancer activity in diverse tumor contexts and suggests the clinical implications of enhancers.

 

A diagram of how concentrating on these transcriptional linchpins or nodes may be more therapeutically advantageous as only one pharmacologic agent is needed versus multiple agents to inhibit the various upstream pathways:

 

 

From: Khamsi R: Computing cancer’s weak spots. Science 2020, 368(6496):1174-1177.

 

VIPER Algorithm (Virtual Inference of Protein activity by Enriched Regulon Analysis)

The algorithm that Califano and DarwinHealth developed is a systems biology approach using a tumor’s RNASeq data to determine controlling nodes of transcription.  They have recently used the VIPER algorithm to look at RNA-Seq data from more than 10,000 tumor samples from TCGA and identified 407 transcription factor genes that acted as these linchpins across all tumor types.  Only 20 to 25 of  them were implicated in just one tumor type so these potential nodes are common in many forms of cancer.

Other institutions like the Cold Spring Harbor Laboratories have been using VIPER in their patient tumor analysis.  Linchpins for other tumor types have been found.  For instance, VIPER identified transcription factors IKZF1 and IKF3 as linchpins in multiple myeloma.  But currently approved therapeutics are hard to come by for targets with are transcription factors, as most pharma has concentrated on inhibiting an easier target like kinases and their associated activity.  In general, developing transcription factor inhibitors in more difficult an undertaking for multiple reasons.

Network-based inference of protein activity helps functionalize the genetic landscape of cancer. Alvarez MJ, Shen Y, Giorgi FM, Lachmann A, Ding BB, Ye BH, Califano A:. Nature genetics 2016, 48(8):838-847 [3]

Abstract

Identifying the multiple dysregulated oncoproteins that contribute to tumorigenesis in a given patient is crucial for developing personalized treatment plans. However, accurate inference of aberrant protein activity in biological samples is still challenging as genetic alterations are only partially predictive and direct measurements of protein activity are generally not feasible. To address this problem we introduce and experimentally validate a new algorithm, VIPER (Virtual Inference of Protein-activity by Enriched Regulon analysis), for the accurate assessment of protein activity from gene expression data. We use VIPER to evaluate the functional relevance of genetic alterations in regulatory proteins across all TCGA samples. In addition to accurately inferring aberrant protein activity induced by established mutations, we also identify a significant fraction of tumors with aberrant activity of druggable oncoproteins—despite a lack of mutations, and vice-versa. In vitro assays confirmed that VIPER-inferred protein activity outperforms mutational analysis in predicting sensitivity to targeted inhibitors.

 

 

 

 

Figure 1 

Schematic overview of the VIPER algorithm From: Alvarez MJ, Shen Y, Giorgi FM, Lachmann A, Ding BB, Ye BH, Califano A: Functional characterization of somatic mutations in cancer using network-based inference of protein activity. Nature genetics 2016, 48(8):838-847.

(a) Molecular layers profiled by different technologies. Transcriptomics measures steady-state mRNA levels; Proteomics quantifies protein levels, including some defined post-translational isoforms; VIPER infers protein activity based on the protein’s regulon, reflecting the abundance of the active protein isoform, including post-translational modifications, proper subcellular localization and interaction with co-factors. (b) Representation of VIPER workflow. A regulatory model is generated from ARACNe-inferred context-specific interactome and Mode of Regulation computed from the correlation between regulator and target genes. Single-sample gene expression signatures are computed from genome-wide expression data, and transformed into regulatory protein activity profiles by the aREA algorithm. (c) Three possible scenarios for the aREA analysis, including increased, decreased or no change in protein activity. The gene expression signature and its absolute value (|GES|) are indicated by color scale bars, induced and repressed target genes according to the regulatory model are indicated by blue and red vertical lines. (d) Pleiotropy Correction is performed by evaluating whether the enrichment of a given regulon (R4) is driven by genes co-regulated by a second regulator (R4∩R1). (e) Benchmark results for VIPER analysis based on multiple-samples gene expression signatures (msVIPER) and single-sample gene expression signatures (VIPER). Boxplots show the accuracy (relative rank for the silenced protein), and the specificity (fraction of proteins inferred as differentially active at p < 0.05) for the 6 benchmark experiments (see Table 2). Different colors indicate different implementations of the aREA algorithm, including 2-tail (2T) and 3-tail (3T), Interaction Confidence (IC) and Pleiotropy Correction (PC).

 Other articles from Andrea Califano on VIPER algorithm in cancer include:

Resistance to neoadjuvant chemotherapy in triple-negative breast cancer mediated by a reversible drug-tolerant state.

Echeverria GV, Ge Z, Seth S, Zhang X, Jeter-Jones S, Zhou X, Cai S, Tu Y, McCoy A, Peoples M, Sun Y, Qiu H, Chang Q, Bristow C, Carugo A, Shao J, Ma X, Harris A, Mundi P, Lau R, Ramamoorthy V, Wu Y, Alvarez MJ, Califano A, Moulder SL, Symmans WF, Marszalek JR, Heffernan TP, Chang JT, Piwnica-Worms H.Sci Transl Med. 2019 Apr 17;11(488):eaav0936. doi: 10.1126/scitranslmed.aav0936.PMID: 30996079

An Integrated Systems Biology Approach Identifies TRIM25 as a Key Determinant of Breast Cancer Metastasis.

Walsh LA, Alvarez MJ, Sabio EY, Reyngold M, Makarov V, Mukherjee S, Lee KW, Desrichard A, Turcan Ş, Dalin MG, Rajasekhar VK, Chen S, Vahdat LT, Califano A, Chan TA.Cell Rep. 2017 Aug 15;20(7):1623-1640. doi: 10.1016/j.celrep.2017.07.052.PMID: 28813674

Inhibition of the autocrine IL-6-JAK2-STAT3-calprotectin axis as targeted therapy for HR-/HER2+ breast cancers.

Rodriguez-Barrueco R, Yu J, Saucedo-Cuevas LP, Olivan M, Llobet-Navas D, Putcha P, Castro V, Murga-Penas EM, Collazo-Lorduy A, Castillo-Martin M, Alvarez M, Cordon-Cardo C, Kalinsky K, Maurer M, Califano A, Silva JM.Genes Dev. 2015 Aug 1;29(15):1631-48. doi: 10.1101/gad.262642.115. Epub 2015 Jul 30.PMID: 26227964

Master regulators used as breast cancer metastasis classifier.

Lim WK, Lyashenko E, Califano A.Pac Symp Biocomput. 2009:504-15.PMID: 19209726 Free

 

Additional References

 

  1. Khamsi R: Computing cancer’s weak spots. Science 2020, 368(6496):1174-1177.
  2. Chen H, Li C, Peng X, Zhou Z, Weinstein JN, Liang H: A Pan-Cancer Analysis of Enhancer Expression in Nearly 9000 Patient Samples. Cell 2018, 173(2):386-399 e312.
  3. Alvarez MJ, Shen Y, Giorgi FM, Lachmann A, Ding BB, Ye BH, Califano A: Functional characterization of somatic mutations in cancer using network-based inference of protein activity. Nature genetics 2016, 48(8):838-847.

 

Other articles of Note on this Open Access Online Journal Include:

Issues in Personalized Medicine in Cancer: Intratumor Heterogeneity and Branched Evolution Revealed by Multiregion Sequencing

 

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National Cancer Institute Director Neil Sharpless says mortality from delays in cancer screenings due to COVID19 pandemic could result in tens of thousands of extra deaths in next decade

Reporter: Stephen J Williams, PhD

Source: https://cancerletter.com/articles/20200619_1/

NCI Director’s Report

Sharpless: COVID-19 expected to increase mortality by at least 10,000 deaths from breast and colorectal cancers over 10 years

By Matthew Bin Han Ong

This story is part of The Cancer Letter’s ongoing coverage of COVID-19’s impact on oncology. A full list of our coverage, as well as the latest meeting cancellations, is available here.

The COVID-19 pandemic will likely cause at least 10,000 excess deaths from breast cancer and colorectal cancer over the next 10 years in the United States.

Scenarios run by NCI and affiliated modeling groups predict that delays in screening for and diagnosis of breast and colorectal cancers will lead to a 1% increase in deaths through 2030. This translates into 10,000 additional deaths, on top of the expected one million deaths resulting from these two cancers.

“For both these cancer types, we believe the pandemic will influence cancer deaths for at least a decade,” NCI Director Ned Sharpless said in a virtual joint meeting of the Board of Scientific Advisors and the National Cancer Advisory Board June 15. “I find this worrisome as cancer mortality is common. Even a 1% increase every decade is a lot of cancer suffering.

“And this analysis, frankly, is pretty conservative. We do not consider cancers other than those of breast and colon, but there is every reason to believe the pandemic will affect other types of cancer, too. We did not account for the additional non-lethal morbidity from upstaging, but this could also be significant and burdensome.”

An editorial by Sharpless on this subject appears in the journal Science.

The early analyses, conducted by the institute’s Cancer Intervention and Surveillance Modeling Network, focused on breast and colorectal cancers, because these are common, with relatively high screening rates.

CISNET modelers created four scenarios to assess long-term increases in cancer mortality rates for these two diseases:

  1. The pandemic has no effect on cancer mortality

 

  1. Delayed screening—with 75% reduction in mammography and, colorectal screening and adenoma surveillance for six months

 

  1. Delayed diagnosis—with one-third of people delaying follow-up after a positive screening or diagnostic mammogram, positive FIT or clinical symptoms for six months during a six-month period

 

  1. Combination of scenarios two and three

 

Treatment scenarios after diagnosis were not included in the model. These would be: delays in treatment, cancellation of treatment, or modified treatment.

“What we did is show the impact of the number of excess deaths per year for 10 years for each year starting in 2020 for scenario four versus scenario one,” Eric “Rocky” Feuer, chief of the NCI’s Statistical Research and Applications Branch in the Surveillance Research Program, said to The Cancer Letter.

Feuer is the overall project scientist for CISNET, a collaborative group of investigators who use simulation modeling to guide public health research and priorities.

“The results for breast cancer were somewhat larger than for colorectal,” Feuer said. “And that’s because breast cancer has a longer preclinical natural history relative to colorectal cancer.”

Modelers in oncology are creating a global modeling consortium, COVID-19 and Cancer Taskforce, to “support decision-making in cancer control both during and after the crisis.” The consortium is supported by the Union for International Cancer Control, The International Agency for Research on Cancer, The International Cancer Screening Network, the Canadian Partnership Against Cancer, and Cancer Council NSW, Australia.

A spike in cancer mortality rates threatens to reverse or slow down—at least in the medium term—the steady trend of reduction of cancer deaths. On Jan. 8, the American Cancer Society published its annual estimates of new cancer cases and deaths, declaring that the latest data—from 2016 to 2017—show the “largest ever single-year drop in overall cancer mortality of 2.2%.” Experts say that innovation in lung cancer treatment and the success of smoking cessation programs are driving the sharp decrease (The Cancer LetterFeb. 7, 2020).

The pandemic is expected to have broader impact, including increases in mortality rates for other cancer types. Also, variations in severity of COVID-19 in different regions in the U.S. will influence mortality metrics.

“There’s some other cancers that might have delays in screening—for example cervical, prostate, and lung cancer, although lung cancer screening rates are still quite low and prostate cancer screening should only be conducted on those who determine that the benefits outweigh the harms,” Feuer said. “So, those are the major screening cancers, but impacts of delays in treatment, canceling treatment or alternative treatments—could impact a larger range of cancer sites.

“This model assumes a moderate disruption which resolves after six months, and doesn’t consider non-lethal morbidities associated with the delay. One thing I think probably is occurring is regional variation in these impacts,” Feuer said. “If you’re living in New York City where things were ground zero for some of the worst impact early on, probably delays were larger than other areas of the country. But now, as we’re seeing upticks in other areas of the country, there may be in impact in these areas as well”

How can health care providers mitigate some of these harms? For example, for people who delayed screening and diagnosis, are providers able to perform triage, so that those at highest risk are prioritized?

“From a strictly cancer control point of view, let’s get those people who delayed screening, or followup to a positive test, or treatment back on schedule as soon as possible,” Feuer said. “But it’s not a simple calculus, because in every situation, we have to weigh the harms and benefits. As we come out of the pandemic, it tips more and more to, ‘Let’s get back to business with respect to cancer control.’

“Telemedicine doesn’t completely substitute for seeing patients in person, but at least people could get the advice they need, and then are triaged through their health care providers to indicate if they really should prioritize coming in. That helps the individual and the health care provider  weigh the harms and benefits, and try to strategize about what’s best for any individual.”

If the pandemic continues to disrupt routine care, cancer-related mortality rates would rise beyond the predictions in this model.

“I think this analysis begins to help us understand the costs with regard to cancer outcomes of the pandemic,” Sharpless said. “Let’s all agree we will do everything in our power to minimize these adverse effects, to protect our patients from cancer suffering.”

 

For more Articles on COVID-19 please see our Coronavirus Portal at

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

 

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Live Notes, Real Time Conference Coverage AACR 2020 #AACR20: Tuesday June 23, 2020 Noon-2:45 Educational Sessions


Live Notes, Real Time Conference Coverage AACR 2020: Tuesday June 23, 2020 Noon-2:45 Educational Sessions

Reporter: Stephen J. Williams, PhD

Follow Live in Real Time using

#AACR20

@pharma_BI

@AACR

Register for FREE at https://www.aacr.org/

 

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

 

 

Other Articles on this Open Access  Online Journal on Cancer Conferences and Conference Coverage in Real Time Include

Press Coverage

Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 28, 2020 Symposium: New Drugs on the Horizon Part 3 12:30-1:25 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

Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 28, 2020 Session on Evaluating Cancer Genomics from Normal Tissues Through Metastatic Disease 3:50 PM

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

 

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Live Conference Coverage AACR 2020 in Real Time: Monday June 22, 2020 Mid Day Sessions

Reporter: Stephen J. Williams, PhD

This post will be UPDATED during the next two days with notes from recordings from other talks

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Register for FREE at https://www.aacr.org/

 

AACR VIRTUAL ANNUAL MEETING II

 

June 22-24: Free Registration for AACR Members, the Cancer Community, and the Public
This virtual meeting will feature more than 120 sessions and 4,000 e-posters, including sessions on cancer health disparities and the impact of COVID-19 on clinical trials

 

This Virtual Meeting is Part II of the AACR Annual Meeting.  Part I was held online in April and was centered only on clinical findings.  This Part II of the virtual meeting will contain all the Sessions and Abstracts pertaining to basic and translational cancer research as well as clinical trial findings.

 

REGISTER NOW

 

Pezcoller Foundation-AACR International Award for Extraordinary Achievement in Cancer Research

The prestigious Pezcoller Foundation-AACR International Award for Extraordinary Achievement in Cancer Research was established in 1997 to annually recognize a scientist of international renown who has made a major scientific discovery in basic cancer research OR who has made significant contributions to translational cancer research; who continues to be active in cancer research and has a record of recent, noteworthy publications; and whose ongoing work holds promise for continued substantive contributions to progress in the field of cancer. For more information regarding the 2020 award recipient go to aacr.org/awards.

John E. Dick, Enzo Galligioni, David A Tuveson

DETAILS

Awardee: John E. Dick
Princess Anne Margaret Cancer Center, Toronto, Ontario
For determining how stem cells contribute to normal and leukemic hematopoeisis
  • not every cancer cell equal in their Cancer Hallmarks
  • how do we monitor and measure clonal dynamics
  • Barnie Clarkson did pivotal work on this
  • most cancer cells are post mitotic but minor populations of cells were dormant and survive chemotherapy
  •  only one cell is 1 in a million can regenerate and transplantable in mice and experiments with flow cytometry resolved the question of potency and repopulation of only small percentage of cells and undergo long term clonal population
  • so instead of going to cell lines and using thousands of shRNA looked at clinical data and deconvoluted the genetic information (RNASeq data) to determine progenitor and mature populations (how much is stem and how much is mature populations)
  • in leukemic patients they have seen massive expansion of a single stem cell population so only need one cell in AML if the stem cells have the mutational hits early on in their development
  • finding the “seeds of relapse”: finding the small subpopulation of stem cells that will relapse
  • they looked in BALL;;  there are cells resistant to l-aspariginase, dexamethasone, and vincristine
  • a lot of OXPHOS related genes (in DRIs) that may be the genes involved in this resistance
  • it a wonderful note of acknowledgement he dedicated this award to all of his past and present trainees who were the ones, as he said, made this field into what it is and for taking it into directions none of them could forsee

Monday, June 22

1:30 PM – 3:30 PM EDT

Virtual Educational Session

Experimental and Molecular Therapeutics, Drug Development, Cancer Chemistry

Chemistry to the Clinic: Part 1: Lead Optimization Case Studies in Cancer Drug Discovery

How can one continue to deliver innovative medicines to patients when biological targets are becoming ever scarcer and less amenable to therapeutic intervention? Are there sound strategies in place that can clear the path to targets previously considered “undruggable”? Recent advances in lead finding methods and novel technologies such as covalent screening and targeted protein degradation have enriched the toolbox at the disposal of drug discovery scientists to expand the druggable ta

Stefan N Gradl, Elena S Koltun, Scott D Edmondson, Matthew A. Marx, Joachim Rudolph

DETAILS

Monday, June 22

1:30 PM – 3:30 PM EDT

Virtual Educational Session

Bioinformatics and Systems Biology, Molecular and Cellular Biology/Genetics

Informatics Technologies for Cancer Research

Cancer researchers are faced with a deluge of high-throughput data. Using these data to advance understanding of cancer biology and improve clinical outcomes increasingly requires effective use of computational and informatics tools. This session will introduce informatics resources that support the data management, analysis, visualization, and interpretation. The primary focus will be on high-throughput genomic data and imaging data. Participants will be introduced to fundamental concepts

Rachel Karchin, Daniel Marcus, Andriy Fedorov, Obi Lee Griffith

DETAILS

  • Variant analysis is the big bottleneck, especially interpretation of variants
  • CIVIC resource is a network for curation, interpretation of genetic variants
  • CIVIC curators go through multiple rounds of editors review
  • gene summaries, variant summaries
  • curation follows ACSME guidelines
  • evidences are accumulated, categories by various ontologies and is the heart of the reports
  • as this is a network of curators the knowledgebase expands
  • CIVIC is linked to multiple external informatic, clinical, and genetic databases
  • they have curated 7017 clinical interpretations, 2527 variants, using 2578 papers, and over 1000 curators
  • they are currently integrating with COSMIC ClinVar, and UniProt
  • they are partnering with ClinGen to expand network of curators and their curation effort
  • CIVIC uses a Python interface; available on website

https://civicdb.org/home

The Precision Medicine Revolution

Precision medicine refers to the use of prevention and treatment strategies that are tailored to the unique features of each individual and their disease. In the context of cancer this might involve the identification of specific mutations shown to predict response to a targeted therapy. The biomedical literature describing these associations is large and growing rapidly. Currently these interpretations exist largely in private or encumbered databases resulting in extensive repetition of effort.

CIViC’s Role in Precision Medicine

Realizing precision medicine will require this information to be centralized, debated and interpreted for application in the clinic. CIViC is an open access, open source, community-driven web resource for Clinical Interpretation of Variants in Cancer. Our goal is to enable precision medicine by providing an educational forum for dissemination of knowledge and active discussion of the clinical significance of cancer genome alterations. For more details refer to the 2017 CIViC publication in Nature Genetics.

U24 funding announced: We are excited to announce that the Informatics Technology for Cancer Research (ICTR) program of the National Cancer Institute (NCI) has awarded funding to the CIViC team! Starting this year, a five-year, $3.7 million U24 award (CA237719), will support CIViC to develop Standardized and Genome-Wide Clinical Interpretation of Complex Genotypes for Cancer Precision Medicine.

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 FAIR data in cancer imaging research

Andriy Fedorov, PhD

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

Other Articles on this Open Access  Online Journal on Cancer Conferences and Conference Coverage in Real Time Include

Press Coverage

Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 28, 2020 Symposium: New Drugs on the Horizon Part 3 12:30-1:25 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

Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 28, 2020 Session on Evaluating Cancer Genomics from Normal Tissues Through Metastatic Disease 3:50 PM

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

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Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 28, 2020 Symposium: New Drugs on the Horizon Part 3 12:30-1:25 PM

Reporter: Stephen J. Williams, PhD

New Drugs on the Horizon: Part 3
Introduction

Andrew J. Phillips, C4 Therapeutics

  • symposium brought by AACR CICR and had about 30 proposals for talks and chose three talks
  • unfortunately the networking event is not possible but hope to see you soon in good health

ABBV-184: A novel survivin specific T cell receptor/CD3 bispecific therapeutic that targets both solid tumor and hematological malignancies

Edward B Reilly
AbbVie Inc. @abbvie

  • T-cell receptors (TCR) can recognize the intracellular targets whereas antibodies only recognize the 25% of potential extracellular targets
  • survivin is expressed in multiple cancers and correlates with poor survival and prognosis
  • CD3 bispecific TCR to survivn (Ab to CD3 on T- cells and TCR to survivin on cancer cells presented in MHC Class A3)
  • ABBV184  effective in vivo in lung cancer models as single agent;
  • in humanized mouse tumor models CD3/survivin bispecific can recruit T cells into solid tumors; multiple immune cells CD4 and CD8 positive T cells were found to infiltrate into tumor
  • therapeutic window as measured by cytokine release assays in tumor vs. normal cells very wide (>25 fold)
  • ABBV184 does not bind platelets and has good in vivo safety profile
  • First- in human dose determination trial: used in vitro cancer cell assays to determine 1st human dose
  • looking at AML and lung cancer indications
  • phase 1 trial is underway for safety and efficacy and determine phase 2 dose
  • survivin has very few mutations so they are not worried about a changing epitope of their target TCR peptide of choice

The discovery of TNO155: A first in class SHP2 inhibitor

Matthew J. LaMarche
Novartis @Novartis

  • SHP2 is an intracellular phosphatase that is upstream of MEK ERK pathway; has an SH2 domain and PTP domain
  • knockdown of SHP2 inhibits tumor growth and colony formation in soft agar
  • 55 TKIs there are very little phosphatase inhibitors; difficult to target the active catalytic site; inhibitors can be oxidized at the active site; so they tried to target the two domains and developed an allosteric inhibitor at binding site where three domains come together and stabilize it
  • they produced a number of chemical scaffolds that would bind and stabilize this allosteric site
  • block the redox reaction by blocking the cysteine in the binding site
  • lead compound had phototoxicity; used SAR analysis to improve affinity and reduce phototox effects
  • was very difficult to balance efficacy, binding properties, and tox by adjusting stuctures
  • TNO155 is their lead into trials
  • SHP2 expressed in T cells and they find good combo with I/O with uptick of CD8 cells
  • TNO155 is very selective no SHP1 inhibition; SHP2 can autoinhibit itself when three domains come together and stabilize; no cross reactivity with other phosphatases
  • they screened 1.5 million compounds and got low hit rate so that is why they needed to chemically engineer and improve on the classes they found as near hits

Closing Remarks

 

Xiaojing Wang
Genentech, Inc. @genentech

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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

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Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 28, 2020 Session on Evaluating Cancer Genomics from Normal Tissues Through Metastatic Disease 3:50 PM

Reporter: Stephen J. Williams, PhD

 Minisymposium: Evaluating Cancer Genomics from Normal Tissues through Evolution to Metastatic Disease

Oncologic therapy shapes the fitness landscape of clonal hematopoiesis

April 28, 2020, 4:10 PM – 4:20 PM

Presenter/Authors
Kelly L. Bolton, Ryan N. Ptashkin, Teng Gao, Lior Braunstein, Sean M. Devlin, Minal Patel, Antonin Berthon, Aijazuddin Syed, Mariko Yabe, Catherine Coombs, Nicole M. Caltabellotta, Mike Walsh, Ken Offit, Zsofia Stadler, Choonsik Lee, Paul Pharoah, Konrad H. Stopsack, Barbara Spitzer, Simon Mantha, James Fagin, Laura Boucai, Christopher J. Gibson, Benjamin Ebert, Andrew L. Young, Todd Druley, Koichi Takahashi, Nancy Gillis, Markus Ball, Eric Padron, David Hyman, Jose Baselga, Larry Norton, Stuart Gardos, Virginia Klimek, Howard Scher, Dean Bajorin, Eder Paraiso, Ryma Benayed, Maria Arcilla, Marc Ladanyi, David Solit, Michael Berger, Martin Tallman, Montserrat Garcia-Closas, Nilanjan Chatterjee, Luis Diaz, Ross Levine, Lindsay Morton, Ahmet Zehir, Elli Papaemmanuil. Memorial Sloan Kettering Cancer Center, New York, NY, University of North Carolina at Chapel Hill, Chapel Hill, NC, University of Cambridge, Cambridge, United Kingdom, Dana-Farber Cancer Institute, Boston, MA, Washington University, St Louis, MO, The University of Texas MD Anderson Cancer Center, Houston, TX, Moffitt Cancer Center, Tampa, FL, National Cancer Institute, Bethesda, MD

Abstract
Recent studies among healthy individuals show evidence of somatic mutations in leukemia-associated genes, referred to as clonal hematopoiesis (CH). To determine the relationship between CH and oncologic therapy we collected sequential blood samples from 525 cancer patients (median sampling interval time = 23 months, range: 6-53 months) of whom 61% received cytotoxic therapy or external beam radiation therapy and 39% received either targeted/immunotherapy or were untreated. Samples were sequenced using deep targeted capture-based platforms. To determine whether CH mutational features were associated with tMN risk, we performed Cox proportional hazards regression on 9,549 cancer patients exposed to oncologic therapy of whom 75 cases developed tMN (median time to transformation=26 months). To further compare the genetic and clonal relationships between tMN and the proceeding CH, we analyzed 35 cases for which paired samples were available. We compared the growth rate of the variant allele fraction (VAF) of CH clones across treatment modalities and in untreated patients. A significant increase in the growth rate of CH mutations was seen in DDR genes among those receiving cytotoxic (p=0.03) or radiation therapy (p=0.02) during the follow-up period compared to patients who did not receive therapy. Similar growth rates among treated and untreated patients were seen for non-DDR CH genes such as DNMT3A. Increasing cumulative exposure to cytotoxic therapy (p=0.01) and external beam radiation therapy (2×10-8) resulted in higher growth rates for DDR CH mutations. Among 34 subjects with at least two CH mutations in which one mutation was in a DDR gene and one in a non-DDR gene, we studied competing clonal dynamics for multiple gene mutations within the same patient. The risk of tMN was positively associated with CH in a known myeloid neoplasm driver mutation (HR=6.9, p<10-6), and increased with the total number of mutations and clone size. The strongest associations were observed for mutations in TP53 and for CH with mutations in spliceosome genes (SRSF2, U2AF1 and SF3B1). Lower hemoglobin, lower platelet counts, lower neutrophil counts, higher red cell distribution width and higher mean corpuscular volume were all positively associated with increased tMN risk. Among 35 cases for which paired samples were available, in 19 patients (59%), we found evidence of at least one of these mutations at the time of pre-tMN sequencing and in 13 (41%), we identified two or more in the pre-tMN sample. In all cases the dominant clone at tMN transformation was defined by a mutation seen at CH Our serial sampling data provide clear evidence that oncologic therapy strongly selects for clones with mutations in the DDR genes and that these clones have limited competitive fitness, in the absence of cytotoxic or radiation therapy. We further validate the relevance of CH as a predictor and precursor of tMN in cancer patients. We show that CH mutations detected prior to tMN diagnosis were consistently part of the dominant clone at tMN diagnosis and demonstrate that oncologic therapy directly promotes clones with mutations in genes associated with chemo-resistant disease such as TP53.

  • therapy resulted also in clonal evolution and saw changes in splice variants and spliceosome
  • therapy promotes current DDR mutations
  • clonal hematopoeisis due to selective pressures
  • mutations, variants number all predictive of myeloid disease
  • deferring adjuvant therapy for breast cancer patients with patients in highest MDS risk group based on biomarkers, greatly reduced their risk for MDS

5704 – Pan-cancer genomic characterization of patient-matched primary, extracranial, and brain metastases

Presenter/AuthorsOlivia W. Lee, Akash Mitra, Won-Chul Lee, Kazutaka Fukumura, Hannah Beird, Miles Andrews, Grant Fischer, John N. Weinstein, Michael A. Davies, Jason Huse, P. Andrew Futreal. The University of Texas MD Anderson Cancer Center, TX, The University of Texas MD Anderson Cancer Center, TX, Olivia Newton-John Cancer Research Institute and School of Cancer Medicine, La Trobe University, AustraliaDisclosures O.W. Lee: None. A. Mitra: None. W. Lee: None. K. Fukumura: None. H. Beird: None. M. Andrews: ; Merck Sharp and Dohme. G. Fischer: None. J.N. Weinstein: None. M.A. Davies: ; Bristol-Myers Squibb. ; Novartis. ; Array BioPharma. ; Roche and Genentech. ; GlaxoSmithKline. ; Sanofi-Aventis. ; AstraZeneca. ; Myriad Genetics. ; Oncothyreon. J. Huse: None. P. Futreal: None.

Abstract: Brain metastases (BM) occur in 10-30% of patients with cancer. Approximately 200,000 new cases of brain metastases are diagnosed in the United States annually, with median survival after diagnosis ranging from 3 to 27 months. Recently, studies have identified significant genetic differences between BM and their corresponding primary tumors. It has been shown that BM harbor clinically actionable mutations that are distinct from those in the primary tumor samples. Additional genomic profiling of BM will provide deeper understanding of the pathogenesis of BM and suggest new therapeutic approaches.
We performed whole-exome sequencing of BM and matched tumors from 41 patients collected from renal cell carcinoma (RCC), breast cancer, lung cancer, and melanoma, which are known to be more likely to develop BM. We profiled total 126 fresh-frozen tumor samples and performed subsequent analyses of BM in comparison to paired primary tumor and extracranial metastases (ECM). We found that lung cancer shared the largest number of mutations between BM and matched tumors (83%), followed by melanoma (74%), RCC (51%), and Breast (26%), indicating that cancer type with high tumor mutational burden share more mutations with BM. Mutational signatures displayed limited differences, suggesting a lack of mutagenic processes specific to BM. However, point-mutation heterogeneity revealed that BM evolve separately into different subclones from their paired tumors regardless of cancer type, and some cancer driver genes were found in BM-specific subclones. These models and findings suggest that these driver genes may drive prometastatic subclones that lead to BM. 32 curated cancer gene mutations were detected and 71% of them were shared between BM and primary tumors or ECM. 29% of mutations were specific to BM, implying that BM often accumulate additional cancer gene mutations that are not present in primary tumors or ECM. Co-mutation analysis revealed a high frequency of TP53 nonsense mutation in BM, mostly in the DNA binding domain, suggesting TP53 nonsense mutation as a possible prerequisite for the development of BM. Copy number alteration analysis showed statistically significant differences between BM and their paired tumor samples in each cancer type (Wilcoxon test, p < 0.0385 for all). Both copy number gains and losses were consistently higher in BM for breast cancer (Wilcoxon test, p =1.307e-5) and lung cancer (Wilcoxon test, p =1.942e-5), implying greater genomic instability during the evolution of BM.
Our findings highlight that there are more unique mutations in BM, with significantly higher copy number alterations and tumor mutational burden. These genomic analyses could provide an opportunity for more reliable diagnostic decision-making, and these findings will be further tested with additional transcriptomic and epigenetic profiling for better characterization of BM-specific tumor microenvironments.

  • are there genomic signatures different in brain mets versus non metastatic or normal?
  • 32 genes from curated databases were different between brain mets and primary tumor
  • frequent nonsense mutations in TP53
  • divergent clonal evolution of drivers in BMets from primary
  • they were able to match BM with other mutational signatures like smokers and lung cancer signatures

5707 – A standard operating procedure for the interpretation of oncogenicity/pathogenicity of somatic mutations

Presenter/AuthorsPeter Horak, Malachi Griffith, Arpad Danos, Beth A. Pitel, Subha Madhavan, Xuelu Liu, Jennifer Lee, Gordana Raca, Shirley Li, Alex H. Wagner, Shashikant Kulkarni, Obi L. Griffith, Debyani Chakravarty, Dmitriy Sonkin. National Center for Tumor Diseases, Heidelberg, Germany, Washington University School of Medicine, St. Louis, MO, Mayo Clinic, Rochester, MN, Georgetown University Medical Center, Washington, DC, Dana-Farber Cancer Institute, Boston, MA, Frederick National Laboratory for Cancer Research, Rockville, MD, University of Southern California, Los Angeles, CA, Sunquest, Boston, MA, Baylor College of Medicine, Houston, TX, Memorial Sloan Kettering Cancer Center, New York, NY, National Cancer Institute, Rockville, MDDisclosures P. Horak: None. M. Griffith: None. A. Danos: None. B.A. Pitel: None. S. Madhavan: ; Perthera Inc. X. Liu: None. J. Lee: None. G. Raca: None. S. Li: ; Sunquest Information Systems, Inc. A.H. Wagner: None. S. Kulkarni: ; Baylor Genetics. O.L. Griffith: None. D. Chakravarty: None. D. Sonkin: None.AbstractSomatic variants in cancer-relevant genes are interpreted from multiple partially overlapping perspectives. When considered in discovery and translational research endeavors, it is important to determine if a particular variant observed in a gene of interest is oncogenic/pathogenic or not, as such knowledge provides the foundation on which targeted cancer treatment research is based. In contrast, clinical applications are dominated by diagnostic, prognostic, or therapeutic interpretations which in part also depends on underlying variant oncogenicity/pathogenicity. The Association for Molecular Pathology, the American Society of Clinical Oncology, and the College of American Pathologists (AMP/ASCO/CAP) have published structured somatic variant clinical interpretation guidelines which specifically address diagnostic, prognostic, and therapeutic implications. These guidelines have been well-received by the oncology community. Many variant knowledgebases, clinical laboratories/centers have adopted or are in the process of adopting these guidelines. The AMP/ASCO/CAP guidelines also describe different data types which are used to determine oncogenicity/pathogenicity of a variant, such as: population frequency, functional data, computational predictions, segregation, and somatic frequency. A second collaborative effort created the European Society for Medical Oncology (ESMO) Scale for Clinical Actionability of molecular Targets to provide a harmonized vocabulary that provides an evidence-based ranking system of molecular targets that supports their value as clinical targets. However, neither of these clinical guideline systems provide systematic and comprehensive procedures for aggregating population frequency, functional data, computational predictions, segregation, and somatic frequency to consistently interpret variant oncogenicity/pathogenicity, as has been published in the ACMG/AMP guidelines for interpretation of pathogenicity of germline variants. In order to address this unmet need for somatic variant oncogenicity/pathogenicity interpretation procedures, the Variant Interpretation for Cancer Consortium (VICC, a GA4GH driver project) Knowledge Curation and Interpretation Standards (KCIS) working group (WG) has developed a Standard Operating Procedure (SOP) with contributions from members of ClinGen Somatic Clinical Domain WG, and ClinGen Somatic/Germline variant curation WG using an approach similar to the ACMG/AMP germline pathogenicity guidelines to categorize evidence of oncogenicity/pathogenicity as very strong, strong, moderate or supporting. This SOP enables consistent and comprehensive assessment of oncogenicity/pathogenicity of somatic variants and latest version of an SOP can be found at https://cancervariants.org/wg/kcis/.

  • best to use this SOP for somatic mutations and not rearangements
  • variants based on oncogenicity as strong to weak
  • useful variant knowledge on pathogenicity curated from known databases
  • the recommendations would provide some guideline on curating unknown somatic variants versus known variants of hereditary diseases
  • they have not curated RB1 mutations or variants (or for other RBs like RB2? p130?)

 

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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

 

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.

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Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 28, 2020 Session on Early Detection and ctDNA 1:35 – 3:55 PM

Reporter: Stephen J. Williams, PhD

Introduction
Alberto Bardelli

  • circulating tumor DNA has been around but with NGS now we can have more specificity in analyzing ctDNA
  • interest lately in using liquid biopsy to gain insight on tumor heterogeneity versus single needle biopsy of the solid tumor
  • these talks will however be on ctDNA as a diagnostic and therapeutic monitoring modality

Prediction of cancer and tissue of origin in individuals with suspicion of cancer using a cell-free DNA multi-cancer early detection test
David Thiel 

@MayoClinic

  • test has a specificity over 90% and intended to used along with guideline
  • The Circulating  Cell-free Genome Atlas Study (clinical trial NCT02889978) (CCGA) study divided into three substudies: highest performing assay, refining assay, validation of assays
  • methylation based assays worked better than sequencing (bisulfite sequencing)
  • used a machine learning algorithm to help refine assay
  • prediction was >90%; subgroup for high clinical suspicion of cancer
  • HCS sensitivity was 100% and specificity very high; but sensitivity on training set was 40% and results may have been confounded by including kidney cancer
  • TOO tissue of origin was predicted in greater than 99% in both training and validation sets

A first-of-its-kind prospective study of a multi-cancer blood test to screen and manage 10,000 women with no history of cancer

  • DETECT-A study: prospective interventional study; can multi blood test be used prospectively and can lead to a personalized care; can the screen be used to complement current therapy?
  • 10,000 women aged 65-75;  these women could not have previous cancer and conducted through Geisinger Health Network; multi test detects DNA and protein and standard of care screening
  • the study focused on safety so a committee was consulted on each case, and used a diagnostic PET-CT
  • blood test alone not good but combined with protein and CT scans much higher (5 fold increase) detection for breast cancer

Nickolas Papadopoulos

@HopkinsMedicine

Discussant
David Huntsman

  • there are mutiple opportunities yet at same time there are still challenges to utilize these cell free tests in therapeutic monitoring, diagnostic, and screening however sensitivities for some cancers are still too low to use in large scale screening however can supplement current screening guidelines
  • we have to ask about false positive rate and need to concentrate on prospective studies
  • we must consider how tests will be used, population health studies will need to show improved survival

 

Phylogenetic tracking and minimal residual disease detection using ctDNA in early-stage NSCLC: A lung TRACERx study
Chris Abbosh @ucl

  • TRACERx study in collaboration with Charles Swanton.
  • multiplex PCR to track 200 SNVs: correlate tumor tissue biopsy with ctDNA
  • spike in assay shows very good sensitivity and specificity for SNVs variants tracked, did over 400 TRACERx libraries
  • sensitivity increases when tracking more variants but specificity does go down a bit
  • tracking variants can show evidence of subclonal dynamics and evolution and copy number deletion events;  they also show neoantigen editing or changing of their neoantigens
  • this assay can detect low variants in a reproducible manner

The TRACERx (TRAcking Cancer Evolution through therapy (Rx)) lung study is a multi-million pound research project taking place over nine years, which will transform our understanding of non-small cell lung cancer (NSCLC) and take a practical step towards an era of precision medicine. The study will uncover mechanisms of cancer evolution by analysing the intratumour heterogeneity in lung tumours from approximately 850 patients and tracking its evolutionary trajectory from diagnosis through to relapse. At £14 million, it’s the biggest single investment in lung cancer research by Cancer Research UK, and the start of a strategic UK-wide focus on the disease, aimed at making real progress for patients.

Led by Professor Charles Swanton at UCL, the study will bring together a network of experts from different disciplines to help integrate clinical and genomic data and identify patients who could benefit from trials of new, targeted treatments. In addition, it will use a whole suite of cutting edge analytical techniques on these patients’ tumour samples, giving unprecedented insight into the genomic landscape of primary and metastatic tumours and the impact of treatment upon this landscape.

In future, TRACERx will enable us to define how intratumour heterogeneity impacts upon cancer immunity throughout tumour evolution and therapy. Such studies will help define how the clinical evaluation of intratumour heterogeneity can inform patient stratification and the development of combinatorial therapies incorporating conventional, targeted and immune based therapeutics.

Intratumour heterogeneity is increasingly recognised as a major hurdle to achieve improvements in therapeutic outcome and biomarker validation. Intratumour genetic diversity provides a substrate for tumour adaptation and evolution. However, the evolutionary genomic landscape of non-small cell lung cancer (NSCLC) and how it changes through the disease course has not been studied in detail. TRACERx is a prospective observational study with the following objectives:

Primary Objectives

  • Define the relationship between intratumour heterogeneity and clinical outcome following surgery and adjuvant therapy (including relationships between intratumour heterogeneity and clinical disease stage and histological subtypes of NSCLC).
  • Establish the impact of adjuvant platinum-containing regimens upon intratumour heterogeneity in relapsed disease compared to primary resected tumour.

Key Secondary Objectives

  • Develop and validate an intratumour heterogeneity (ITH) ratio index as a prognostic and predictive biomarker in relation to disease-free survival and overall survival.
  • Infer a complete picture of NSCLC evolutionary dynamics – define drivers of genomic instability, metastatic progression and drug resistance by identifying and tracking the dynamics of somatic mutational heterogeneity, and chromosomal structural and numerical instability present in the primary tumour and at metastatic sites. Individual tumour phylogenetic tree analysis will:
    • Establish the order of somatic events in relation to genomic instability onset and metastatic progression
    • Decipher genetic “bottlenecking” events following metastasis and drug therapy
    • Establish dynamics of tumour evolution during the disease course from early to late stage NSCLC.
  • Initiate a longitudinal biobank of circulating tumour cells (CTCs) and circulating-free tumour DNA (cfDNA) to develop analytical methods for the early detection and monitoring of tumour evolution over time.
  • Develop a longitudinal tissue resource to serve as a platform to assess the relationship between genetic intratumour heterogeneity and the host immune response.
  • Define relationships between intratumour heterogeneity and targeted/cytotoxic therapeutic outcome.
  • Use a lung cancer specific gene panel in a certified Good Clinical Practice (GCP) laboratory environment to define clonally dominant disease drivers to address the role of clonal driver dominance in targeted therapeutic response and to guide stratification of lung cancer treatment and future clinical study inclusion (paired primary-metastatic site comparisons in at least 270 patients with relapsed disease).

 

 

Utility of longitudinal circulating tumor DNA (ctDNA) modeling to predict RECIST-defined progression in first-line patients with epidermal growth factor receptor mutation-positive (EGFRm) advanced non-small cell lung cancer (NSCLC)
Martin Johnson

 

Impact of the EML4-ALK fusion variant on the efficacy of lorlatinib in patients (pts) with ALK-positive advanced non-small cell lung cancer (NSCLC)
Todd Bauer

 

From an interview with Dr. Bauer at https://www.lungcancernews.org/2019/08/14/making-headway-with-lorlatinib/

Lorlatinib, a smallmolecule inhibitor of ALK and ROS1, was granted accelerated U.S. Food and Drug Administration approval in November 2018 for patients with ALK-positive metastatic NSCLC whose disease has progressed on crizotinib and at least one other ALK inhibitor or whose disease has progressed on alectinib or ceritinib as the first ALK inhibitor therapy for metastatic disease. Todd M. Bauer, MD, a medical oncologist and senior investigator at Sarah Cannon Research Institute/Tennessee Oncology, PLLC, in Nashville, has been very involved with the development of lorlatinib since the beginning. In the following interview, Dr. Bauer discusses some of lorlatinib’s unique toxicities, as well as his first-hand experiences with the drug.

For further reading: Solomon B, Besse B, Bauer T, et al. Lorlatinib in Patients with ALK-positive non-small-cell lung cancer: results from a global phase 2 study. Lancet. 2018;19(12):P1654-1667.

Abstract

BACKGROUND: Lorlatinib is a potent, brain-penetrant, third-generation inhibitor of ALK and ROS1 tyrosine kinases with broad coverage of ALK mutations. In a phase 1 study, activity was seen in patients with ALK-positive non-small-cell lung cancer, most of whom had CNS metastases and progression after ALK-directed therapy. We aimed to analyse the overall and intracranial antitumour activity of lorlatinib in patients with ALK-positive, advanced non-small-cell lung cancer.

METHODS: In this phase 2 study, patients with histologically or cytologically ALK-positive or ROS1-positive, advanced, non-small-cell lung cancer, with or without CNS metastases, with an Eastern Cooperative Oncology Group performance status of 0, 1, or 2, and adequate end-organ function were eligible. Patients were enrolled into six different expansion cohorts (EXP1-6) on the basis of ALK and ROS1 status and previous therapy, and were given lorlatinib 100 mg orally once daily continuously in 21-day cycles. The primary endpoint was overall and intracranial tumour response by independent central review, assessed in pooled subgroups of ALK-positive patients. Analyses of activity and safety were based on the safety analysis set (ie, all patients who received at least one dose of lorlatinib) as assessed by independent central review. Patients with measurable CNS metastases at baseline by independent central review were included in the intracranial activity analyses. In this report, we present lorlatinib activity data for the ALK-positive patients (EXP1-5 only), and safety data for all treated patients (EXP1-6). This study is ongoing and is registered with ClinicalTrials.gov, number NCT01970865.

FINDINGS: Between Sept 15, 2015, and Oct 3, 2016, 276 patients were enrolled: 30 who were ALK positive and treatment naive (EXP1); 59 who were ALK positive and received previous crizotinib without (n=27; EXP2) or with (n=32; EXP3A) previous chemotherapy; 28 who were ALK positive and received one previous non-crizotinib ALK tyrosine kinase inhibitor, with or without chemotherapy (EXP3B); 112 who were ALK positive with two (n=66; EXP4) or three (n=46; EXP5) previous ALK tyrosine kinase inhibitors with or without chemotherapy; and 47 who were ROS1 positive with any previous treatment (EXP6). One patient in EXP4 died before receiving lorlatinib and was excluded from the safety analysis set. In treatment-naive patients (EXP1), an objective response was achieved in 27 (90·0%; 95% CI 73·5-97·9) of 30 patients. Three patients in EXP1 had measurable baseline CNS lesions per independent central review, and objective intracranial responses were observed in two (66·7%; 95% CI 9·4-99·2). In ALK-positive patients with at least one previous ALK tyrosine kinase inhibitor (EXP2-5), objective responses were achieved in 93 (47·0%; 39·9-54·2) of 198 patients and objective intracranial response in those with measurable baseline CNS lesions in 51 (63·0%; 51·5-73·4) of 81 patients. Objective response was achieved in 41 (69·5%; 95% CI 56·1-80·8) of 59 patients who had only received previous crizotinib (EXP2-3A), nine (32·1%; 15·9-52·4) of 28 patients with one previous non-crizotinib ALK tyrosine kinase inhibitor (EXP3B), and 43 (38·7%; 29·6-48·5) of 111 patients with two or more previous ALK tyrosine kinase inhibitors (EXP4-5). Objective intracranial response was achieved in 20 (87·0%; 95% CI 66·4-97·2) of 23 patients with measurable baseline CNS lesions in EXP2-3A, five (55·6%; 21·2-86·3) of nine patients in EXP3B, and 26 (53·1%; 38·3-67·5) of 49 patients in EXP4-5. The most common treatment-related adverse events across all patients were hypercholesterolaemia (224 [81%] of 275 patients overall and 43 [16%] grade 3-4) and hypertriglyceridaemia (166 [60%] overall and 43 [16%] grade 3-4). Serious treatment-related adverse events occurred in 19 (7%) of 275 patients and seven patients (3%) permanently discontinued treatment because of treatment-related adverse events. No treatment-related deaths were reported.

INTERPRETATION: Consistent with its broad ALK mutational coverage and CNS penetration, lorlatinib showed substantial overall and intracranial activity both in treatment-naive patients with ALK-positive non-small-cell lung cancer, and in those who had progressed on crizotinib, second-generation ALK tyrosine kinase inhibitors, or after up to three previous ALK tyrosine kinase inhibitors. Thus, lorlatinib could represent an effective treatment option for patients with ALK-positive non-small-cell lung cancer in first-line or subsequent therapy.

  • loratinib could be used for crizotanib resistant tumors based on EML4-ALK variants present in ctDNA

Reference:
1. Updated efficacy and safety data from the global phase III ALEX study of alectinib (ALC) vs crizotinib (CZ) in untreated advanced ALK+ NSCLCJ Clin Oncol 36, 2018 (suppl; abstr 9043).

Discussion

Corey Langer

 

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