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Precision oncology trials based on cancer biomarkers have the potential to improve outcomes by guiding the optimal choice of therapies for patients. For this to be truly achieved, computational methods such as virtual molecular tumor boards, dynamic precision medicine and digital twins are needed to support cohort selection and trial enrollment at scale.

The interaction among a group of musicians before, during, and after the performance of a jazz standard is analyzed to show the interdependence of jazz aesthetics and jazz ethics. The authors argue that what makes jazz distinct from other kinds of musical traditions is not just the ubiquity of improvisation in the genre but the vulnerability that jazz improvisation always generates—a vulnerability that is due to the genre’s reliance on both shared conventions and partly unpredictable individual choices. Analyzing video recordings of a university course on jazz organized to reproduce the setting of a jam session, the authors examine in detail the interactional assumptions and consequences of choices made by band members during the performance of “Softly, as in a Morning Sunrise.” The authors’ analysis shows how musicians position themselves to be responsive to one another as the song progresses, starting from an improvised “introduction” that sets the tempo, rhythm, and style of the song and continuing with smooth transitions from one solo to the next. Drawing from Erving Goffman’s ideas about the presentation of self and the phenomenology of Emmanuel Levinas, the authors examine the ethical implications of a musical “vacuum” that was created by one musician’s decision to wait to take his solo. In the interaction, the other musicians responded to the vacuum by assuming responsibility for the group’s performance and, more broadly, the performance of the jazz tradition, and this chapter uses their actions to illustrate how “jazz etiquette” operates as a practice that includes aesthetic, ethical, and practical concerns.

Management of metastatic radioiodine refractory differentiated thyroid cancer (DTC) can be a therapeutic challenge. Generally, little is known about the paired molecular profile of the primary tumor and the metastases and whether they harbor the same genetic abnormalities. The present study compared the molecular profile of paired tumor specimens (primary tumor/metastatic sites) from patients with radioiodine refractory DTC in order to gain insight into a possible basis for resistance to radioiodine. Twelve patients with radioiodine refractory metastases were studied; median age at diagnosis of 61 years (range, 25–82). Nine patients had papillary TC (PTC), one had follicular TC (FTC), and two had Hürthle cell TC (HTC). Distant metastases were present in the lungs (n = 10), bones (n = 4), and liver (n = 1). The molecular profiling of paired tumors was performed with a panel of 592 genes for Next Generation Sequencing, RNA-sequencing, and immunohistochemistry. Digital microfluidic PCR was used to investigateTERTpromoter mutations. The genetic landscape of all paired sites comprisedBRAF,NRAS,HRAS,TP53,ATM,MUTYH,POLE, andNTRKgenes, includingBRAFandNTRKfusions.BRAFV600E was the most common point mutation in the paired specimens (5/12).TERTpromoter mutation C228T was detected in one case. PD-L1 expression at metastatic sites was highly positive (95%) for one patient with HTC. All specimens were stable for microsatellite instability testing, and the tumor mutation burden was low to intermediate. Therefore, the molecular profile of DTC primary and metastatic lesions can show heterogeneity, which may help explain some altered responses to therapeutic intervention.

DNA sequence accounts for the majority of disease heritability, including cancer. Yet, not all familial cancer cases can be explained by genetic factors. There is mounting evidence that environmentally-induced epigenetic inheritance occurs and that the progeny’s traits can be shaped by parental environmental experiences. In humans, epidemiologic studies have implicated endocrine disruptors and environmental toxicants such as the pesticide DDT in intergenerational cancer development, including breast and childhood tumors. Using a mouse model, we investigated whether paternal DDT exposure may result in an intergenerational increase in breast cancer development. We also investigated the effects of DDT on the paternal germline and the mechanisms underlying intergenerational transmission. Male mice (c57bl/6) were exposed to DDT or to a control-vehicle (CO) solution and used for sperm collection or mating with unexposed females to produce the DDT or CO daughters. In another experiment, normal mouse embryos (zygote stage) were injected with RNA purified from sperm of DDT or CO males or miRNA mimic. Resulting zygotes were implanted into surrogate mothers to produce offspring. DDT daughters or RNA injected females were used to study breast cancer development (carcinogen-induced or orthotopic models). We found that the female progeny of males exposed to DDT in the pre-conception period have higher susceptibility of developing aggressive tumors in two different mouse models of breast cancer. Sperm of DDT-exposed males exhibited distinct patterns of small non-coding RNAs, with an increase in miRNAs and a specific surge in miRNA-10b levels. Remarkably, embryonic injection of the entire sperm RNA load of DDT-exposed males or synthetic miRNA-10b recapitulated the tumor phenotypes observed in DDT daughters. We also found that E3.5 embryos injected with miR-10b have altered transcriptional profile compared to controls. Our findings reveal a causal role for sperm RNAs in the inheritance of cancer predisposition and could explain some of the “missing heritability” of breast and other malignancies, if confirmed in humans. Citation Format: Raquel Santana Da Cruz, Odalys Dominguez, Apsra Nasir, Alexandra K. Gonsiewski, Maria Idalia Cruz, Lu Jin, Matthew McCoy, Sonia de Assis. DDT induces intergenerational epigenetic inheritance of cancer predisposition in a mouse model [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1429.

Human Antigen R (HuR/ELAVL1) is known to regulate stability of mRNAs involved in pancreatic ductal adenocarcinoma (PDAC) cell survival. Although several HuR targets are established, it is likely that many remain currently unknown. Here, we identified BARD1 mRNA as a novel target of HuR. Silencing HuR caused a >70% decrease in homologous recombination repair (HRR) efficiency as measured by the double-strand break repair (pDR-GFP reporter) assay. HuR-bound mRNAs extracted from RNP-immunoprecipitation and probed on a microarray, revealed a subset of HRR genes as putative HuR targets, including the BRCA1-Associated-Ring-Domain-1 (BARD1) (p < 0.005). BARD1 genetic alterations are infrequent in PDAC, and its context-dependent upregulation is poorly understood. Genetic silencing (siRNA and CRISPR knock-out) and pharmacological targeting of HuR inhibited both full length (FL) BARD1 and its functional isoforms (α, δ, Φ). Silencing BARD1 sensitized cells to olaparib and oxaliplatin; caused G2-M cell cycle arrest; and increased DNA-damage while decreasing HRR efficiency in cells. Exogenous overexpression of BARD1 in HuR-deficient cells partially rescued the HRR dysfunction, independent of an HuR pro-oncogenic function. Collectively, our findings demonstrate for the first time that BARD1 is a bona fide HuR target, which serves as an important regulatory point of the transient DNA-repair response in PDAC cells.

Management of metastatic radioiodine refractory differentiated thyroid cancer (DTC) can be a therapeutic challenge. Generally, little is known about the paired molecular profile of the primary tumor and the metastases and whether they harbor the same genetic abnormalities. The present study compared the molecular profile of paired tumor specimens (primary tumor/metastatic sites) from patients with radioiodine refractory DTC in order to gain insight into a possible basis for resistance to radioiodine. Twelve patients with radioiodine refractory metastases were studied; median age at diagnosis of 61 years (range, 25–82). Nine patients had papillary TC (PTC), one had follicular TC (FTC), and two had Hürthle cell TC (HTC). Distant metastases were present in the lungs (n = 10), bones (n = 4), and liver (n = 1). The molecular profiling of paired tumors was performed with a panel of 592 genes for Next Generation Sequencing, RNA-sequencing, and immunohistochemistry. Digital microfluidic PCR was used to investigate TERT promoter mutations. The genetic landscape of all paired sites comprised BRAF, NRAS, HRAS, TP53, ATM, MUTYH, POLE, and NTRK genes, including BRAF and NTRK fusions. BRAF V600E was the most common point mutation in the paired specimens (5/12). TERT promoter mutation C228T was detected in one case. PD-L1 expression at metastatic sites was highly positive (95%) for one patient with HTC. All specimens were stable for microsatellite instability testing, and the tumor mutation burden was low to intermediate. Therefore, the molecular profile of DTC primary and metastatic lesions can show heterogeneity, which may help explain some altered responses to therapeutic intervention.

Precision medicine (PM) matches patients to therapies, utilizing traditional biomarker classifiers. Dynamic precision medicine (DPM) is an evolutionarily directed approach which adapts every six weeks, plans ahead for future resistance development, incorporates multiple therapeutic agents, and may improve survival (simulated hazard ratio DPM:PM, HR-DPM/PM, 0.52). We developed an evolutionary classifier (EC) to select patients who benefit from DPM. Subclonal prevalence and growth, mutation, and drug sensitivity parameters determine each DPM recommended adaptation (move). In simulations, if the first two moves are identical for DPM and PM, patients will not benefit (90% negative predictive value). The first two moves provide nearly the benefit of 40 moves. Patients benefiting equally between 2 and 40 moves have extraordinary predicted benefit (HR-DPM/PM 0.04). This EC development paradigm may apply to other dynamic cancer models despite different underlying assumptions. It may reduce the duration and frequency of required monitoring, and also enable “window” clinical trials.STATEMENT OF SIGNIFICANCEBiomarker classifiers match patients to therapies. Dynamic precision medicine (DPM) directs therapeutic sequence and timing using evolutionary dynamics. We present an evolutionary classifier (EC) for predicting patient benefit from DPM, discovering that many require only briefly, thereby improving cost-effectiveness. This approach may generalize to other evolutionarily directed strategies.

Oncogenic mutations in the kinase domain of the B-Raf protein have long been associated with cancers involving the RAF-MEK-ERK pathway. One constitutive ERK activating mutation in B-Raf, the V600E (valine to glutamate) replacement occurring adjacent to a site of threonine phosphorylation (T599) occurs in many types of cancer, and in a large percentage of certain cancers, such as melanoma. Because natural ATP binding activity and the V600E mutation are both known to alter the physical behavior of the activation loop in the ATP binding domain, this system is especially amenable to comparative functional analyses using molecular dynamics of drug classes and genetic variants at all-atom resolution. Here, we employ machine learning enabled identification of functionally conserved protein dynamics to compare how disease pertinent molecular variations impact conserved loop dynamics during the binding of four ATP competitive B-Raf inhibitors (sorafenib, vemurafenib, dabrafenib, and PLX7904) that differ in their effectiveness in preventing cancer recurrence. We demonstrate that drug development targeting B-Raf has progressively moved towards ATP competitive inhibitors that demonstrate less tendency to mimic the functional dynamic shifts associated with ATP binding in this domain. We argue this functional dynamic mimicry in first generation B-Raf inhibitors increases the side effect of hyperactivation (i.e. inducing MAPK activation in non-tumorous cells in the absence of secondary mutation). Within the context of the binding interaction of each inhibitor, we compare the functional dynamic impacts of V600E and other sensitizing and drug resistance causing mutations in the activation and P-loops, confirming sites of low mutational tolerance in these two functional regions. Lastly, we investigate V600E sensitivity of B-Raf loop dynamics in an evolutionary context, demonstrating that while it probably shares partial origin with its early evolution in primitive eukaryotes, the functional sensitivity to V600E was secondarily increased during early jawed vertebrate evolution. Author Summary Our lab has recently developed a combined simulation-based and machine learning method and user-friendly software for identifying dynamic motions in proteins that are preserved over evolutionary time scales (i.e. are functionally conserved). Our method also can assess how genetic or chemical variation affects these functionally conserved motions. Here, we utilize this approach to computationally demonstrate how one of the most common mutations that arise in tumors, the V600E B-Raf protein mutation, disrupts the functioning of protein loop dynamics responsible for normal regulation of the oncogenic B-Raf protein and its growth signaling pathway. We demonstrate that cancer recurrence in the absence of new mutations may be caused by drug interactions impacting these dynamics. We propose that mimicry of the functional dynamics of natural chemical activators (i.e. agonists) by many cancer targeting drugs may be a potent causal factor in recurrence of cancer in the absence of secondary mutation. By combining comparative modeling of molecular dynamics and analyses of molecular evolution, we also demonstrate that the unusual sensitivity of B-Raf protein regulatory loop dynamics to this mutation has an ancient evolutionary origin.

Pancreatic ductal adenocarcinoma (PDAC) is a lethal aggressive cancer, in part due to elements of the microenvironment (hypoxia, hypoglycemia) that cause metabolic network alterations. The FDA-approved antihelminthic pyrvinium pamoate (PP) has previously been shown to cause PDAC cell death, although the mechanism has not been fully determined. We demonstrated that PP effectively inhibited PDAC cell viability with nanomolar IC50 values (9–93 nmol/L) against a panel of PDAC, patient-derived, and murine organoid cell lines. In vivo, we demonstrated that PP inhibited PDAC xenograft tumor growth with both intraperitoneal (IP; P < 0.0001) and oral administration (PO; P = 0.0023) of human-grade drug. Metabolomic and phosphoproteomic data identified that PP potently inhibited PDAC mitochondrial pathways including oxidative phosphorylation and fatty acid metabolism. As PP treatment reduced oxidative phosphorylation (P < 0.001), leading to an increase in glycolysis (P < 0.001), PP was 16.2-fold more effective in hypoglycemic conditions similar to those seen in PDAC tumors. RNA sequencing demonstrated that PP caused a decrease in mitochondrial RNA expression, an effect that was not observed with established mitochondrial inhibitors rotenone and oligomycin. Mechanistically, we determined that PP selectively bound mitochondrial G-quadruplexes and inhibited mitochondrial RNA transcription in a G-quadruplex–dependent manner. This subsequently led to a 90% reduction in mitochondrial encoded gene expression. We are preparing to evaluate the efficacy of PP in PDAC in an IRB-approved window-of-opportunity trial (IND:144822).

PURPOSE The cancer research community is constantly evolving to better understand tumor biology, disease etiology, risk stratification, and pathways to novel treatments. Yet the clinical cancer genomics field has been hindered by redundant efforts to meaningfully collect and interpret disparate data types from multiple high-throughput modalities and integrate into clinical care processes. Bespoke data models, knowledgebases, and one-off customized resources for data analysis often lack adequate governance and quality control needed for these resources to be clinical grade. Many informatics efforts focused on genomic interpretation resources for neoplasms are underway to support data collection, deposition, curation, harmonization, integration, and analytics to support case review and treatment planning. METHODS In this review, we evaluate and summarize the landscape of available tools, resources, and evidence used in the evaluation of somatic and germline tumor variants within the context of molecular tumor boards. RESULTS Molecular tumor boards (MTBs) are collaborative efforts of multidisciplinary cancer experts equipped with genomic interpretation resources to aid in the delivery of accurate and timely clinical interpretations of complex genomic results for each patient, within an institution or hospital network. Virtual MTBs (VMTBs) provide an online forum for collaborative governance, provenance, and information sharing between experts outside a given hospital network with the potential to enhance MTB discussions. Knowledge sharing in VMTBs and communication with guideline-developing organizations can lead to progress evidenced by data harmonization across resources, crowd-sourced and expert-curated genomic assertions, and a more informed and explainable usage of artificial intelligence. CONCLUSION Advances in cancer genomics interpretation aid in better patient and disease classification, more streamlined identification of relevant literature, and a more thorough review of available treatments and predicted patient outcomes.

Cannabis has been cultivated for millennia for medicinal, industrial and recreational uses. Our long-term goal is to compare the transcriptomes of cultivars with different cannabinoid profiles for therapeutic purposes. Here we describe the de novo assembly, annotation and initial analysis of two cultivars of Cannabis, a high THC variety and a CBD plus THC variety. Cultivars were grown under different lighting conditions; flower buds were sampled over 71 days. Cannabinoid profiles were determined by ESI-LC/MS. RNA samples were sequenced using the HiSeq4000 platform. Transcriptomes were assembled using the DRAP pipeline and annotated using the BLAST2GO pipeline and other tools. Each transcriptome contained over twenty thousand protein encoding transcripts with ORFs and flanking sequence. Identification of transcripts for cannabinoid pathway and related enzymes showed full-length ORFs that align with the draft genomes of the Purple Kush and Finola cultivars. Two transcripts were found for olivetolic acid cyclase (OAC) that mapped to distinct locations on the Purple Kush genome suggesting multiple genes for OAC are expressed in some cultivars. The ability to make high quality annotated reference transcriptomes in Cannabis or other plants can promote rapid comparative analysis between cultivars and growth conditions in Cannabis and other organisms without annotated genome assemblies.

Harmonization of cancer variant representation, efficient communication, and free distribution of clinical variant‐associated knowledge are central problems that arise with increased usage of clinical next‐generation sequencing. The Clinical Genome Resource (ClinGen) Somatic Working Group (WG) developed a minimal variant level data (MVLD) representation of cancer variants, and has an ongoing collaboration with Clinical Interpretations of Variants in Cancer (CIViC), an open‐source platform supporting crowdsourced and expert‐moderated cancer variant curation. Harmonization between MVLD and CIViC variant formats was assessed by formal field‐by‐field analysis. Adjustments to the CIViC format were made to harmonize with MVLD and support ClinGen Somatic WG curation activities, including four new features in CIViC: (1) introduction of an assertions feature for clinical variant assessment following the Association of Molecular Pathologists (AMP) guidelines, (2) group‐level curation tracking for organizations, enabling member transparency, and curation effort summaries, (3) introduction of ClinGen Allele Registry IDs to CIViC, and (4) mapping of CIViC assertions into ClinVar submission with automated submissions. A generalizable workflow utilizing MVLD and new CIViC features is outlined for use by ClinGen Somatic WG task teams for curation and submission to ClinVar, and provides a model for promoting harmonization of cancer variant representation and efficient distribution of this information.

Purpose: Publicly available databases, for example, The Cancer Genome Atlas (TCGA), containing clinical and molecular data from many patients are useful in validating the contribution of particular genes to disease mechanisms and in forming novel hypotheses relating to clinical outcomes. Experimental Design: The impact of key drivers of cancer progression can be assessed by segregating a patient cohort by certain molecular features and constructing survival plots using the associated clinical data. However, conclusions drawn from this straightforward analysis are highly dependent on the quality and source of tissue samples, as demonstrated through the pancreatic ductal adenocarcinoma (PDAC) subset of TCGA. Results: Analyses of the PDAC-TCGA database, which contains mainly resectable cancer samples from patients in stage IIB, reveal a difference from widely known historic median and 5-year survival rates of PDAC. A similar discrepancy was observed in lung, stomach, and liver cancer subsets of TCGA. The whole transcriptome expression patterns of PDAC-TCGA revealed a cluster of samples derived from neuroendocrine tumors, which have a distinctive biology and better disease prognosis than PDAC. Furthermore, PDAC-TCGA contains numerous pseudo-normal samples, as well as those that arose from tumors not classified as PDAC. Conclusions: Inclusion of misclassified samples in the bioinformatic analyses distorts the association of molecular biomarkers with clinical outcomes, altering multiple published conclusions used to support and motivate experimental research. Hence, the stringent scrutiny of type and origin of samples included in the bioinformatic analyses by researchers, databases, and web-tool developers is of crucial importance for generating accurate conclusions. Clin Cancer Res; 24(16); 3813–9. ©2018 AACR.

Clinical significance of somatic gene variants needs to be comprehensively characterized for their diagnostic, prognostic and/or therapeutic actionability in patient management. However, challenges remain due to discrepancies in interpretation and reporting of these somatic variants among different testing labs. Therefore, standardized curation, clinical interpretation and reporting of somatic variants in hematologic cancers is critical. To address this issue, the Hematologic Cancer Taskforce (HCT), composed of 52 multi-disciplinary experts including oncologists, molecular pathologists, lab directors, genomic scientists and biocurators, was formed in January 2020 within the ClinGen Somatic Cancer Clinical Domain Working Group (CDWG) with a goal to undertake systematic curation and evidence-based clinical interpretation of genes/somatic variants associated with hematologic malignancies. In collaboration with the Clinical Interpretation of Variants in Cancer (CIViC) (civicdb.org) knowledgebase, HCT members curate, edit, and verify Evidence Items for each variant extracted from peer-reviewed publications. Monthly discussions based on these Evidence Items lead to the preparation of variant Assertions, which summarize the state of the field consensus variant interpretation and include tiering based on the AMP/ASCO/CAP guidelines (PMID: 27993330). FMS-like tyrosine kinase 3 (FLT3) encodes a class III receptor tyrosine kinase expressed in hematopoietic cells. FLT3 mutations, including both internal tandem duplication (ITD) and mutations in the tyrosine kinase domain (TKD), are the most common mutations in acute myeloid leukemia (AML), occurring in approximately 30% of all AML cases. Implementing FLT3 tyrosine kinase inhibitors (TKIs) in different treatment regimens for FLT3 mutated AML patients has led to significantly improved overall survival. Type I FLT3 inhibitors, including midostaurin, gilteritinib, sunitinib, lestaurtinib, and crenolanib, bind to the ATP-binding site when the receptor is in active conformation. Type II FLT3 inhibitors, including sorafenib, ponatinib, and quizartinib, interact with a hydrophobic region directly adjacent to the ATP-binding domain that is only accessible when the receptor is inactive, which prevents receptor activation. Generally in AML cells, type I FLT3 inhibitors prevent activity for both ITD and TKD mutations, while Type II inhibitors target ITD but lack efficiency against TKD mutations. The development of TKD mutations in AML cells with ITD have proved to be a mechanism of acquired, or secondary resistance to Type II FLT3 inhibitors. The HCT is piloting curation assessments of FLT3 alterations, including ITD, TKD and non-TKD variants, in AML. So far, the HCT has curated 75 evidence items for FLT3 somatic variants. FLT3-ITD, as well as D835 and I836 were asserted as tier 1 level A variants based on the prediction of response to gilteritinib in relapsed/refractory AML (PMIDs: 27993330, 31665578, 28645776, 28516360, 27908881). Recent curation activities are focused on FLT3 D839G and N676K, as clinical trials using large AML patient cohorts are lacking in their ability to validate drug response/resistance associations of these two TKD variants due to their low frequency. Functional studies showed both variants result in increased proliferation and protection from apoptosis, supporting the oncogenic potential of these two variants (PMIDs: 26891877, 2468088). FLT3 D839G combined with ITD confers resistance to pexidartinib and ponatinib, both Type II FLT3 inhibitors (PMIDs: 25847190, 23430109). FLT3 N676K predicts response to the Type I FLT3 inhibitor, gilteritinib, when N676K is present alone or in combination with ITD. Interestingly, FLT3 N676K in the absence of ITD predicts response to sorafenib, a Type II FLT3 inhibitor (PMIDs: 32040554, 32984009). However, these results are mostly derived from in vitro studies. Two separate Tier II, Level D Assertions have been submitted for FLT3-ITD&D839G for its response to pexidartinib and ponatinib, and more evidence is being collected to form an Assertion for FLT3 N676K. The complexity of the prediction of response/resistance associated with FLT3 D839G and N676K supports the importance of evidence-based curation and collection for these variants in the context of the overall mutation profile, disease context and specific FLT3 TKIs to clearly define their clinical impact. Disclosures Pullarkat: Stemline Therapeutics: Honoraria.

Venetoclax is an oral, highly selective, BCL2 inhibitor approved by the FDA for use in chronic lymphocytic leukemia/small lymphocytic lymphoma and acute myeloid leukemia. Despite favorable responses, multiple biological mechanisms lead to treatment resistance. One such mechanism includes somatic mutations in the BCL2 gene. Multiple lines of evidence suggest that hot-spot mutations in BCL2 such as Gly101Val induce treatment resistance by disrupting the binding of BCL2 to the BCL2 inhibitors such as venetoclax. Further, widespread use of high-throughput NGS technologies has identified multiple BCL2 mutations and additional concurrent molecular alterations at various variant allele frequencies in patients with progression while undergoing venetoclax therapy. In order to understand and determine the clinical significance of each of these mutations, careful expert curation and integration into somatic variant annotation AMP/ASCO/CAP guidelines is needed. Further, curation of those somatic variants that may not have sufficient functional evidence in literature may benefit from additional tools such as in silico analysis. To address these issues, we have undertaken an effort to integrate the contributions of a multidisciplinary expert panel (clinical laboratory diagnosticians, oncologists, biomedical informaticians and lab-based researchers) for curation of BCL2 variants in hematological malignancies under the umbrella of ClinGen, an NIH/NHGRI funded consortium to establish standards and centralized resources for assessing the clinical significance of gene variants. Within the ClinGen Somatic Cancer Clinical Domain Working Group (CDWG) ((https://www.clinicalgenome.org/working-groups/somatic/), the somatic hematological malignancy taskforce has identified 56 peer-reviewed publications on BCL2 inhibitors (Jan 2014 to June 2020). The functional evidence contained within these publications was curated using CIViC (Clinical Interpretation of Variants in Cancer, civicdb.org), an open access, crowdsourced aggregation of expert curated evidence. Only a fraction of the somatic variants identified in BCL2 has established functional evidence on variant induced disruption to Venetoclax inhibition. Curation of these remaining variants of unknown significance (VUS) only have in silico functional assays to provide evidence on their potential resistance to Venetoclax. The current curation guidelines do not consider in silico prediction as a strong line of evidence for the interpretation of somatic sequence variants, however this recommendation is meant to interpret generalized in silico predictors and not robust computational models of specific protein function. The latter are more comparable to an experimental functional assay, and provide curators with more trustworthy computational assessments of disruption to protein specific functions. In order to assess their potential to integrate and supplement experimental evidence, the interaction of Ventoclax with several drug resistant BCL2 variants was simulated using AutoDock Vina (J Comput Chem. 2010;31(2):455-61). Facilitated by the SNP2SIM workflow (BMC Bioinformatics. 2019;20(1):171), the relative impact on binding energy was compared to the wildtype system. The in silico binding assay accurately predicted resistance (Fig 1), and demonstrates the utility of applying these methods to the large number of VUS in BCL2. In conclusion, the evidence-based expert curation of BCL2 variants provides a standardized approach for reporting and interpretation across all labs. For those variants (Tier 3) with limited published evidence, computational models that can predict specific changes to functional protein interactions can provide additional tools to the expert curators. Development and incorporation of these tools into curation guidelines requires the refinement of the predictive models through focused validation studies. Disclosures No relevant conflicts of interest to declare.

Immune checkpoint therapies have shown tremendous promise in cancer therapy. However, tools to assess their target engagement, and hence the ability to predict their efficacy, have been lacking. Here, we show that target engagement and tumor-residence kinetics of antibody therapeutics targeting programmed death ligand-1 (PD-L1) can be quantified noninvasively. In computational docking studies, we observed that PD-L1–targeted monoclonal antibodies (atezolizumab, avelumab, and durvalumab) and a high-affinity PD-L1–binding peptide, WL12, have common interaction sites on PD-L1. Using the peptide radiotracer [((64))Cu]WL12 in vivo, we employed positron emission tomography (PET) imaging and biodistribution studies in multiple xenograft models and demonstrated that variable PD-L1 expression and its saturation by atezolizumab, avelumab, and durvalumab can be quantified independently of biophysical properties and pharmacokinetics of antibodies. Next, we used [((64))Cu]WL12 to evaluate the impact of time and dose on the unoccupied fraction of tumor PD-L1 during treatment. These quantitative measures enabled, by mathematical modeling, prediction of antibody doses needed to achieve therapeutically effective occupancy (defined as >90%). Thus, we show that peptide-based PET is a promising tool for optimizing dose and therapeutic regimens employing PD-L1 checkpoint antibodies, and can be used for improving therapeutic efficacy.

BACKGROUND & AIMS: Pancreatic ductal adenocarcinomas (PDAC) are characterized by fibrosis and an abundance of cancer-associated fibroblasts (CAFs). We investigated strategies to disrupt interactions among CAFs, the immune system, and cancer cells, focusing on adhesion molecule cadherin 11 (CDH11), which has been associated with other fibrotic disorders and is expressed by activated fibroblasts. METHODS: We compared levels of CDH11 mRNA in human pancreatitis and pancreatic cancer tissues and cells, compared with normal pancreas, and measured levels of CDH11 protein in human and mouse pancreatic lesions and normal tissues. We crossed p48-Cre;LSL-Kras(G12D/+);LSL-Trp53(R172H/+) (KPC) mice with CDH11-knockout mice and measured survival times of offspring. Pancreata were collected and analyzed by histology, immunohistochemistry, and (single-cell) RNA sequencing; RNA and proteins were identified by imaging mass cytometry. Some mice were given injections of PD1 antibody or gemcitabine and survival was monitored. Pancreatic cancer cells from KPC mice were subcutaneously injected into Cdh11(+/+) and Cdh11(−/−) mice and tumor growth was monitored. Pancreatic cancer cells (mT3) from KPC mice (C57BL/6), were subcutaneously injected into Cdh11(+/+) (C57BL/6J) mice and mice were given injections of antibody against CDH11, gemcitabine, or small molecule inhibitor of CDH11 (SD133) and tumor growth was monitored. RESULTS: Levels of CDH11 mRNA and protein were significantly higher in CAFs than in pancreatic cancer epithelial cells, human or mouse pancreatic cancer cell lines, or immune cells. KPC/Cdh11(+/−) and KPC/Cdh11(−/−) mice survived significantly longer than KPC/Cdh11(+/+) mice. Markers of stromal activation entirely surrounded pancreatic intraepithelial neoplasias in KPC/Cdh11(+/+) mice and incompletely in KPC/Cdh11(+/−) and KPC/Cdh11(−/−) mice, whose lesions also contained fewer FOXP3(+) cells in the tumor center. Compared with pancreatic tumors in KPC/Cdh11(+/+) mice, tumors of KPC/Cdh11(+/−) mice had increased markers of antigen processing and presentation; more lymphocytes and associated cytokines; decreased extracellular matrix components; and reductions in markers and cytokines associated with immunosuppression. Administration of the PD1 antibody did not prolong survival of KPC mice with 0, 1, or 2 alleles of Cdh11. Gemcitabine extended survival only of KPC/Cdh11(+/−) and KPC/Cdh11(−/−) mice or reduced subcutaneous tumor growth in mT3 engrafted Cdh11(+/+) mice given in combination with the CDH11 antibody. A small molecule inhibitor of CDH11 reduced growth of pre-established mT3 subcutaneous tumors only if T and B cells were present in mice. CONCLUSIONS: Knockout or inhibition of CDH11, which is expressed by CAFs in the pancreatic tumor stroma, reduces growth of pancreatic tumors, increases their response to gemcitabine, and significantly extends survival of mice. CDH11 promotes immunosuppression and extracellular matrix deposition, and might be developed as a therapeutic target for pancreatic cancer.

Hematological malignancies comprise a genetically heterogeneous spectrum of diseases caused by abnormal proliferation or maturation of a variety of hematological cell lineages. Genomic abnormalities including chromosomal translocations, copy number variations and sequence level gene mutations underlie the pathogenesis of these disorders and frequently serve as important diagnostic, prognostic and/or therapeutic markers. However, the substantial discrepancy in interpretation and reporting of these genomic abnormalities among testing labs creates challenges for patient management. Therefore, standardizing the curation, clinical interpretation and reporting of somatic alterations within the context of their diagnostic, prognostic and therapeutic significance in hematological cancers is critical. In January 2020, the ClinGen Somatic Cancer Clinical Domain working group formed the Hematological Cancer Taskforce (HCT) with a goal to undertake systematic curation and evidence-based clinical interpretation of genes/somatic variants associated with hematological malignancies. The HCT has recruited 32 multi-disciplinary experts including oncologists, molecular pathologists, clinical lab directors, genomic scientists and biocurators with expertise in hematological malignancies. In collaboration with the Clinical Interpretation of Variants in Cancer (CIViC) (civicdb.org) knowledgebase, variants from peer-reviewed publications are curated with editor review for clinical utility as evidence items. Monthly discussions based on these evidence items lead to the creation of summary variant assertions using the AMP/ASCO/CAP guidelines (Li M, et al., Journal of Molecular Diagnostics, 2017). The HCT is currently focused on expert curation and clinical interpretation of somatic variants in FLT3 (internal tandem duplication, tyrosine kinase domain and non tyrosine kinase domain variants) in acute myeloid leukemia (AML). Expert curation of gene fusions in Philadelphia chromosome-like acute lymphoblastic leukemia (Ph-like ALL) in collaboration with the ClinGen somatic pediatric cancer taskforce is currently underway. To date, the HCT has curated 45 evidence items from clinical and pre-clinical studies on the aforementioned genes/variants. In addition, three AMP Tier I, level A variant assertions of FLT3-ITD, D835 and I836, which predict response to Gilteritinib, an FDA-approved drug for relapsed or refractory AML, have been curated. In the future, the HCT plans to extend its focus on curation of BCR-ABL1 kinase domain mutations in chronic myeloid leukemia (CML). Based on the initial pilot curation phase, the HCT will develop gene-specific recommendations to standardize the reporting and interpretation of somatic variants to better assist clinical decisions and apply to become official ClinGen Somatic Expert Panels in each of these gene-disease domains. Disclosures Blombery: Novartis: Consultancy; Invivoscribe: Honoraria; Amgen: Consultancy; Janssen: Honoraria.

The Clinical Genome (ClinGen) Resource is a US National Human Genome Research Institute (NHGRI)-funded program dedicated to building an expert curated and freely available central resource that defines the clinical relevance of genes and variants for use in precision medicine. Teams of experts in various clinical domains come together as working groups within ClinGen to facilitate the interpretation, annotation and utilization of genes-variants for clinical application. Somatic Cancer is one such ClinGen Clinical Domain Working Group (CDWG) that consists of over 90 members worldwide, including clinicians, clinical laboratory diagnosticians, genomic scientists and bioinformaticians. Members of this CDWG identify high priority somatic variants in different cancer types that require expert curation and consensus in their clinical interpretation. In order to accurately implement practice guidelines/standards for variant interpretation, the Somatic Cancer CDWG recently established a somatic Variant Curation Expert Panel (VCEP) approval process. Based on their interest and clinical domain expertise, a subset of the CDWG members formed somatic VCEPs to perform authoritative curation on the shortlisted genes-somatic variants within the context of a disease, therapeutic indication or biological pathway. Expert curation within these VCEPs is performed by utilizing guidelines such as those recommended by AMP/ASCO/CAP (Li et al. 2017) and the Somatic Cancer CDWG (Ritter et al. 2016). Wherever necessary, the somatic VCEPs will develop: 1) gene- and disease-specific modifications to address gaps in existing variant assessment guidelines, 2) quantitative approaches for variant interpretation, and 3) implement standardized protocols for annotating somatic variants in genes for a specific disease, drug or biological pathway. Furthermore, ClinGen recently formed the Cancer Variant Interpretation (CVI) committee to provide support, review and feedback on the provisional somatic variant interpretation proposals developed by the VCEPs. The CVI provides somatic VCEPs with a preliminary approval before the final approval by the ClinGen CDWG oversight committee and ultimately ‘expert panel' status in ClinVar, an NCBI-maintained database of clinically relevant gene variants. NTRK fusions in cancer is the first Somatic VCEP going through the ClinGen Somatic Expert Panel approval process. Alterations in the FGFR pathway in GU cancers is the second somatic VCEP under consideration. The Somatic CDWG uses the CIViC (Clinical Interpretation of Variants in Cancer) platform for curation of somatic variants. To date, the CDWG has curated 268 evidence items relating to cancer variants in CIViC, 6 assertions, and 33 evidence source suggestions. The ultimate goal of the Somatic CDWG is to enhance the usability, dissemination and implementation of cancer somatic changes in the ClinGen resource and other cancer variant knowledgebases. Citation Format: Shruti Rao, Deborah Ritter, Arpad Danos, Gordana Raca, Angshumoy Roy, Kilannin Krysiak, Wan-Hsin Lin, Erica Barnell, Matthew McCoy, Beth Pitel, Dmitriy Sonkin, Jue Wang, Seyed Ali Hosseini, Shamini Selvarajah, Ian King, Rashmi Kanagal-Shamana, Xinjie Xu, Jeremy L. Warner, Funda Meric-Bernstam, Jason D. Merker, Marilyn Li, Alex H. Wagner, Malachi Griffith, Obi L. Griffith, Shashikant Kulkarni, Subha Madhavan. ClinGen somatic cancer working group: Disseminating standardized cancer molecular diagnostic data and evidence through global collaboration and expert curation [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3215.

In the last 3-5 years, there has been a rapid increase in clinical use of next generation sequencing (NGS) based cancer molecular diagnostic (MolDx) testing to develop better treatment plans with targeted therapies. To truly achieve precision oncology, it is critical to catalog cancer sequence variants from MolDx testing for their clinical relevance along with treatment information and patient outcomes, and to do so in a way that supports large-scale data aggregation and new hypothesis generation. Through the NIH-funded Clinical Genome Resource (ClinGen), in collaboration with NLM’s ClinVar database and >50 academic and industry based cancer research organizations, a Minimal Variant Level Data (MVLD) framework to standardize reporting and interpretation of drug associated alterations was developed. Methodological and technology development to standardize and map MolDx data to the MVLD standard are presented here. Also described is a novel community engagement effort through disease-focused taskforces to provide usecases for technology development.

A growing number of academic and community clinics are conducting genomic testing to inform treatment decisions for cancer patients (1). In the last 3–5 years, there has been a rapid increase in clinical use of next generation sequencing (NGS) based cancer molecular diagnostic (MolDx) testing (2). The increasing availability and decreasing cost of tumor genomic profiling means that physicians can now make treatment decisions armed with patient-specific genetic information. Accumulating research in the cancer biology field indicates that there is significant potential to improve cancer patient outcomes by effectively leveraging this rich source of genomic data in treatment planning (3). To achieve truly personalized medicine in oncology, it is critical to catalog cancer sequence variants from MolDx testing for their clinical relevance along with treatment information and patient outcomes, and to do so in a way that supports large-scale data aggregation and new hypothesis generation. One critical challenge to encoding variant data is adopting a standard of annotation of those variants that are clinically actionable. Through the NIH-funded Clinical Genome Resource (ClinGen) (4), in collaboration with NLM’s ClinVar database and >50 academic and industry based cancer research organizations, we developed the Minimal Variant Level Data (MVLD) framework to standardize reporting and interpretation of drug associated alterations (5). We are currently involved in collaborative efforts to align the MVLD framework with parallel, complementary sequence variants interpretation clinical guidelines from the Association of Molecular Pathologists (AMP) for clinical labs (6). In order to truly democratize access to MolDx data for care and research needs, these standards must be harmonized to support sharing of clinical cancer variants. Here we describe the processes and methods developed within the ClinGen’s Somatic WG in collaboration with over 60 cancer care and research organizations as well as CLIA-certified, CAP-accredited clinical testing labs to develop standards for cancer variant interpretation and sharing.

Pancreatic ductal adenocarcinoma (PDAC) is the 3rd leading cause of cancer related deaths in the U.S. Recent advances in understanding RNA biology in PDAC have shed light on post-transcriptional regulation of genes and pathways through RNA binding proteins (RBP). Our lab has demonstrated that HuR, an RBP, is overexpressed in PDAC cells and stabilizes pro-survival mRNAs. Additionally, our work and others have demonstrated that this level of gene regulation can support drug resistance in PDAC cells. A synthetic lethal strategy employing Poly-ADP ribose polymerase inhibitors (PARPi) in a subset of patients with DNA repair deficient pancreatic cancers has been gaining interest. However, the success of PARPi is often hindered by the emergence of drug resistance in patients who initially respond. We have published that short-term PARPi treatment of PDAC cells causes activation of HuR where it stabilizes a DNA repair enzyme, PAR-glycohydrolase, and mediates acute PARPi resistance. In this study, we generated olaparib acquired resistant pancreatic cancer cells in vitro and acquired pancreatic patient derived xenograft cell lines (pre- and post PARPi) to understand acute versus acquired resistant mechanism(s). In characterising the acquired resistant model of PARPi resistance, we found that these cells are >20 fold more resistant to olaparib and platinums and >5 fold resistant to other PARPi like rucaparib and veliparib, compared to parental cells. No cross resistance was seen with other chemotherapeutics like gemcitabine. Additionally, we also found acquired resistant cells lost PARP-1 protein expression compared to parental cells. Bioinformatic analyses on HuR-RNA immunoprecipitation-microarray (RIP-microarray) data from acutely treated olaparib cells show enrichment of pro-survival mRNAs. Interestingly, these mRNAs are significantly downregulated in acquired resistant cells compared to control cells (i.e., negative log2 fold changes, p Citation Format: Aditi Jain, Matthew McCoy, Lebaron A. Agostini, Yuriy Gusev, Subha Madhavan, Michael Pishvaian, Sankar Addya, Eric Londin, Maria R. Gurevich, Chani Stossel, Talia Golan, Charles J. Yeo, Jonathan R. Brody. A global transcriptome analysis of pancreatic cancer cells distinguishes between acute and acquired PARP inhibitor resistance mechanisms [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4764.

Objective: This study investigates the impact of isometric contraction of anterior cervical muscles on cervical lordosis. Methods: 29 volunteers were randomly assigned to an anterior head translation (n=15) or anterior head flexion (n=14) group. Resting neutral lateral cervical x-rays were compared to x-rays of sustained isometric contraction of the anterior cervical muscles producing anterior head translation or anterior head flexion. Results: Paired sample t-tests indicate no significant difference between pre and post anterior head translation or anterior head flexion. Analysis of variance suggests that gender and peak force were not associated with change in cervical lordosis. Chamberlain's to atlas plane line angle difference was significantly associated with cervical lordosis difference during anterior head translation (p=0.01). Conclusion: This study shows no evidence that hypertonicity, as seen in muscle spasms, of the muscles responsible for anterior head translation and anterior head flexion have a significant impact on cervical lordosis.

The objective of this study was to determine whether a standardized, commercial wellness protocol (Creating Wellness) that focuses on diet, exercise, vitamin supplementation, and one-on-one coaching improves anthropometric and physiologic function and reduces health risk factors.Using a retrospective analysis of subject data collected through a central data repository, several measures of anthropometric and physiologic function were analyzed for changes in outcome.There were 197 private chiropractic clinics in the United States utilizing the Creating Wellness protocol in 2007. A total of 178 subjects completed an 18-week protocol and had initial and final assessments. All anthropometric and physiologic measures showed improvement following the intervention; therefore, this standardized wellness protocol was shown to improve weight, heart rate, blood pressure, strength, body-mass index, and forced vital capacity. Paired sample t tests and significance testing for the entire sample, and for both genders separately, determined that these changes were statistically significant.The Creating Wellness protocol leads to improved health risk factor outcomes based on improvement in anthropometric and physiologic measures in this study population. The results of these tests are generally accepted measures of risk for cardiovascular events, diabetes, metabolic syndrome, and cancer. There are little evaluative data on health outcomes related to programs designed to reduce risk of lifestyle-related diseases. For those clients utilizing the program evaluated in this study, there appears to be evidence suggesting improved health risk factor outcomes from participation in this specific protocol. The results of this study have implications related to a broad number of public health issues related to management of chronic lifestyle diseases.