Passenger Mutations Research Articles

CanDriS: posterior profiling of cancer-driving sites based on two-component evolutionary model.

Current cancer genomics databases have accumulated millions of somatic mutations that remain to be further explored. Due to the over-excess mutations unrelated to cancer, the great challenge is to identify somatic mutations that are cancer-driven. Under the notion that carcinogenesis is a form of somatic-cell evolution, we developed a two-component mixture model: while the ground component corresponds to passenger mutations, the rapidly evolving component corresponds to driver mutations. Then, we implemented an empirical Bayesian procedure to calculate the posterior probability of a site being cancer-driven. Based on these, we developed a software CanDriS (Cancer Driver Sites) to profile the potential cancer-driving sites for thousands of tumor samples from the Cancer Genome Atlas and International Cancer Genome Consortium across tumor types and pan-cancer level. As a result, we identified that approximately 1% of the sites have posterior probabilities larger than 0.90 and listed potential cancer-wide and cancer-specific driver mutations. By comprehensively profiling all potential cancer-driving sites, CanDriS greatly enhances our ability to refine our knowledge of the genetic basis of cancer and might guide clinical medication in the upcoming era of precision medicine. The results were displayed in a database CandrisDB (http://biopharm.zju.edu.cn/candrisdb/).

A synDNA vaccine delivering neoAg collections controls heterogenous, multifocal murine lung and ovarian tumors via robust T cell generation

Neoantigens are tumor-specific antigens that arise due to somatic mutations in the DNA of tumor cells. They represent ideal targets for cancer immunotherapy since there is minimal risk for on-target, off-tumor toxicities. Additionally, these are foreign antigens that should be immunogenic due to lack of central immune tolerance. Tumor neoantigens are predominantly passenger mutations, which do not contribute to tumorigenesis. In cases of multi-focal or metastatic tumors, different foci can have significantly different mutation profiles. This suggests that it is important to target as many neoantigens as possible to better control tumors and target multi-focal tumors within the same patient. Herein, we report a study targeting up to 40 neoantigens using a single DNA plasmid. We observed significant plasticity in the epitope strings arranged in the vaccine with regard to immune induction and tumor control. Different vaccines elicited T cell responses against multiple epitopes on the vaccine string and controlled growth of multi-focal, heterogeneous tumors in a therapeutic tumor challenge. Additionally, the multi-epitope antigens induced long-term immunity and rejected a tumor re-challenge several weeks after the final vaccination. These data provide evidence that DNA-encoded long antigen strings can be an important tool for immunotherapeutic vaccination against neoantigens with implications for other in vivo-delivered antigen strings.

Bone phenotype of P2X4 receptor knockout mice: implication of a P2X7 receptor mutation?

Transgenic and knockout animal models are widely used to investigate the role of receptors, signaling pathways, and other peptides and proteins. Varying results are often published on the same model from different groups, and much effort has been put into understanding the underlying causes of these sometimes conflicting results. Recently, it has been shown that a P2X4R knockout model carries a so-called passenger mutation in the P2X7R gene, potentially affecting the interpretation of results from studies using this animal model. We therefore report this case to raise awareness about the potential pitfalls using genetically modified animal models, especially within P2 receptor research. Although purinergic signaling has been recognized as an important contributor to the regulation of bone remodeling, the process that maintains the bone quality during life, little is known about the role of the P2X4 receptor (P2X4R) in regulation of bone remodeling in health and disease. To address this, we analyzed the bone phenotype of P2rx4tm1Rass (C57BL/6J) knockout mice and corresponding wildtype using microCT and biomechanical testing. Overall, we found that the P2X4R knockout mice displayed improved bone microstructure and stronger bones in an age- and gender-dependent manner. While cortical BMD, trabecular BMD, and bone volume were higher in the 6-month-old females and 3-month-old males, this was not the case for the 3-month-old females and the 6-month-old males. Bone strength was only affected in the females. Moreover, we found that P2X4R KO mice carried the P2X7 receptor 451P wildtype allele, whereas the wildtype mice carried the 451L mutant allele. In conclusion, this study suggests that P2X4R could play a role in bone remodeling, but more importantly, it underlines the potential pitfalls when using knockout models and highlights the importance of interpreting results with great caution. Further studies are needed to verify any specific effects of P2X4R on bone metabolism.

The functional GRHL3-filaggrin axis maintains a tumor differentiation potential and influences drug sensitivity

Current therapies for treating heterogeneous cancers such as head and neck squamous cell carcinoma (HNSCC) are non-selective and are administered independent of response biomarkers. Therapy resistance subsequently emerges, resulting in increased cellular proliferation that is associated with loss of differentiation. Whether a cancer cell differentiation potential can dictate therapy responsiveness is still currently unknown. A multi-omic approach integrating whole-genome and whole-transcriptome sequencing with drug sensitivity was employed in a HNSCC mouse model, primary patients’ data, and human cell lines to assess the potential of functional differentiation in predicting therapy response. Interestingly, a subset of HNSCC with effective GRHL3-dependent differentiation was the most sensitive to inhibitors of PI3K/mTOR, c-Myc, and STAT3 signaling. Furthermore, we identified the GRHL3-differentiation target gene Filaggrin (FLG) as a response biomarker and more importantly, stratified HNSCC subsets as treatment resistant based on their FLG mutational profile. The loss of FLG in sensitive HNSCC resulted in a dramatic resistance to targeted therapies while the GRHL3-FLG signature predicted a favorable patient prognosis. This study provides evidence for a functional GRHL3-FLG tumor-specific differentiation axis that regulates targeted therapy response in HNSCC and establishes a rationale for clinical investigation of differentiation-paired targeted therapy in heterogeneous cancers.

Abstract PS5-04: Therapeutic considerations in microsatellite instability high (MSI- H) breast cancers (BC) identified by comprehensive genomic profiling (CGP)

Abstract Background: Non-colorectal MSI-H tumors are increasingly identified by CGP. Rare types such as MSI-H BC remain poorly defined with an evidence gap on how to optimally sequence or combine with standard of care treatment. MSI can be measured by either IHC, PCR, or CGP and can be caused by both sporadic and germline variants within different tumor types. Prior studies in BC have shown evidence of dMMR by IHC cases MSS based on PCR. This could be due to intra-tumor heterogeneity, specific microsatellite loci evaluated, or penetrance of germline, somatic, or epigenetic alterations. Published data suggests carriers of germline pathogenic MMR variants have a BC risk equivalent to the normal population and currently germline testing is recommended only for BRCA. Currently in advanced BC, standard tumor biomarker testing includes IHC, PCR, and FISH; however, with increasing use of CGP we demonstrate additional actionable biomarkers as well as potential germline variants in MSI-H BC. Methods: DNA was extracted and hybrid capture CGP was performed on 29,160 BC cases. TMB was determined on 0.8-1.2 Mb of DNA and MSI status on 95-114 loci. Genomic LOH was also evaluated. Comparative analysis was done with 101 MSI-H BC, 841 MSS BC and 4,988 non-breast MSI-H cancers. Histological subtype was obtained from the pathology along with orthogonal testing for ER/PR/HER2 status. Somatic-germline-zygosity (SGZ) status was predicted using a published research use algorithm. Select case reports with clinical outcomes will be presented. Results: We identified 101 (0.35% of total) MSI-H BC cases: 29 ER+/HER2-, 5 HER2+, 29 TNBC, and 28 unknown. Amongst BC cases with known subtype, TNBC was enriched for MSI-H vs MSS (53.4 vs 35.8%, p=0.005). The median TMB in MSI-H BC (26.1 mut/Mb, IQR 17.4;42.8) was significantly lower than that of MSI-H colon (46.1mut/MB) and higher than that of MSI-H uterine tumors (22.6mut/Mb) in our comparison group (p<0.001 for both, Kruskal-Wallis test). Pathogenic variants in an MMR gene were found in 61.4% of MSI-H BC with MLH1 loss being the most common (13.6%) and much higher vs. the non-breast MSI-H cohort (2.4%, p<0.0001). Germline mutations in MMR genes in BC are rare yet 5/52 MMR short variants identified in 101 MSI-H BCs were predicted to be germline, 34 somatic, and 13 could not be determined. We identified 21 MSI-H BC patients with a total of 25 pathogenic BRCA1/2 alterations of which 4 were likely germline, 10 were homozygous, and were enriched in TNBC. These were mainly frameshift mutations, including BRCA2 T3033fs* in 5/18 (28%) cases; however, 7/25 were deletions, rearrangements, or nonsense mutations. Median gLOH was significantly higher in BRCA altered (19.7%) compared to BRCA wild-type MSI-H BC cases (9.6%) (p=0.007, Wilcox test). Additional potentially targetable biomarkers included 26 CDx eligible PIK3CA mutations, 11 ERBB2 activating point mutations in the TKD or ECD domain, 1 FGFR2 rearrangement, and 6 AKT1 E17K mutations. Four cases also had concurrent (CD274) PD-L1 amplifications. Conclusion: MSI-H BC is rare but CGP can identify additional therapeutic options for rational combination with targeted therapies such as PI3K, PARP, and HER2 inhibitors. BRCA alterations may be of germline or somatic origin and they may be targetable, as demonstrated by gLOH, rather than passenger mutations. Further characterization of these tumors and comparison to both MSS BC and non-breast MSI-H tumor types, combined with treatment outcomes, can provide insights on rationale combinations and/or sequencing of therapeutic agents. Citation Format: Kimberly McGregor, Natalie Danzinger, Jeffrey S. Ross, Kyle Gowen, Alexa B. Schrock, Garrett M. Frampton, Dean C. Pavlick, Jan W. Davis, Carl R. Gray, Jeffrey M. Venstrom. Therapeutic considerations in microsatellite instability high (MSI- H) breast cancers (BC) identified by comprehensive genomic profiling (CGP) [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS5-04.

Abstract PD5-10: Mutational burden of the normal breast during age and pregnancy

Abstract Background: The potential for accumulation of somatic mutations in the healthy breast throughout life and pregnancy is poorly understood. In particular, the unique mutational landscape of both epithelial and stromal components of the mammary gland has not been investigated in depth. As cancer risk correlates with both age, age of first-time pregnancy and other factors including pregnancy itself, we wished to study mutational rate over time, using these landmarks. Methods: Here, using whole genome sequencing, we determined how the rate of mutations in both cancer drivers and passenger mutations are affected by both age and pregnancy. We aimed to describe for the first time how the mammary epithelium and stroma differ in their mutational burden. Results: Our analysis of epithelial and stromal laser-capture micro-dissected DNA from 25 normal breast samples of nulliparous and age-matched early- and late-parous women collected from Komen Tissue Bank, University of Indiana, shows that the mammary gland is characterised by known COSMIC signatures SBS1 and SBS5, both of which correlate with age (p<0.05). Using a non-negative matrix factorization approach, we identified a novel signature HB1 for a subset of samples which could not be fitted into the known signature database. Differences between the two cellular compartments were observed mostly in the enrichment pathway of mutated genes, notably a significant enrichment in mutations in the PI3K-Akt signalling pathway in the epithelium. We found that parous stroma is associated with a significant enrichment in mutations in the 3’UTR of genes, suggesting that regulation of the environment in the post-partum breast could preferably occur via these pathways. Alike other normal tissue, the mutational burden of the mammary gland significantly increases with age (P<0.05) and we observed parity-associated patterns of mutational burden, particularly evident in the epithelial compartment. The nulliparous epithelium is characterised by a significant increase of mutations (p<0.05), but mutated clones are maintained at a consistently small size. Conversely, the number of somatic mutations in the parous epithelium is not significantly affected by age, but age is positively correlated with bigger clone sizes (P<0.05) in this group. This trend suggests that possible cancer-associated mutations may have a lower probability of occurring but higher chance of expanding within the parous breast with age, compared to the nulliparous breast. To confirm this, we detected mutations in known driver genes in all the healthy samples, with some occurrence of known individual pathogenic variants.Conclusions: We show the mutational landscape of the healthy breast and highlight differences in the epithelial and stromal cellular compartments. We show how mutated cells, including mutations in driver genes for breast cancer, and genetic alterations change in the contest of pregnancy and age, provide a possible explanation for pregnancy-associated breast cancer risk. Citation Format: Biancastella Cereser, Neha Tabassum, Lisa Del Bel Belluz, Sladjana Zagorac, Angela Yiu, Philip Carter, Cristian Miere, Alicia R Jeffries-Jones, Justin Stebbing. Mutational burden of the normal breast during age and pregnancy [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PD5-10.

Abstract PO022: Somatic mutations in tumor infiltrating lymphocytes can affect the expression of immune system genes in the tumor microenvironment

Abstract Avoiding immune destruction is an emerging hallmark of cancer. It includes tumor cell mutations and epigenetic modifications that allow tumor cells to either evade detection by the immune system, or render the immune response ineffective. However, mutations in tumor infiltrating lymphocytes that inhibit immune response to tumor growth, have not been specifically identified as a hallmark of cancer. We have identified four distinct somatic mutations in tumor infiltrating lymphocytes that affect the expression of immune system genes in tumor samples, suggesting that these lymphocytic mutation may cause a deficient immune response, contributing to cancer progression. These rare mutations occurred frequently in specific cancer types. The T292Nfs*18 mutation in the FETUB gene, R216Gfs*20 in CCDC43, N377D in CLEC4M and V78Gfs*46 in RAB11FIP4 occurred in 13% of breast invasive carcinoma, 41% of colon adenocarcinoma, 12% of ovarian cystadenocarcinoma (OV) and 16% of OV samples respectively, compared to 0.002%, 0.003%, 0.014% and 0.001% in aggregated variant databases. These variants were found in 7-20% of DNA sequences in both tumor and matched normal blood samples, indicating that they originated in tumor infiltrating lymphocytes, rather than in the tumor cells. We argue that these mutations are unlikely to be passenger mutations since each of them occur in only 0-2% of normal tissue samples and in less than 2% of tumor samples from 24-32 of 32 cancer types other than the one noted above for each of the four mutations. The set of differentially expressed genes (FDR<0.05) in samples with each of the four variants, compared to samples without the variant, included 22-445 genes associated with the immune system pathway, suggesting a possible mechanism by which these mutations may affect tumor growth. Given the myriad of diverse mechanisms and genes implicated in cancer, it is not unexpected that mutations in tumor infiltrating lymphocytes could contribute to cancer progression. With further validation, genetic lesions in tumor infiltrating lymphocytes may represent a previously unstudied mechanism affecting tumor growth, and a new class of therapeutic targets. These mutations may also represent potential “somatic” risk markers that may present with age, supplementing traditional germline risk markers. Citation Format: Ramu Anandakrishnan, Robin T. Varghese, Nicholas A. Kinney, Harold R. Garner. Somatic mutations in tumor infiltrating lymphocytes can affect the expression of immune system genes in the tumor microenvironment [abstract]. In: Abstracts: AACR Virtual Special Conference: Tumor Immunology and Immunotherapy; 2020 Oct 19-20. Philadelphia (PA): AACR; Cancer Immunol Res 2021;9(2 Suppl):Abstract nr PO022.

Genetic Analysis of Multiple Myeloma Identifies Cytogenetic Alterations Implicated in Disease Complexity and Progression.

Simple SummaryMultiple myeloma (MM) is the second most common hematological neoplasia with a high incidence in elderly populations. The disease is characterized by a severe chaos of genomic abnormality. Comprehensive examinations of myeloma cytogenetics are needed for better understanding of MM and potential application to the development of novel therapeutic regiments. Here we utilized gene expression profiling and CytoScan HD genomic arrays to investigate molecular alterations in myeloma leading to disease progression and poor clinical outcomes. We demonstrates that genetic abnormalities within MM patients exhibit unique protein network signatures that can be exploited for implementation of existing therapies targeting key pathways and the development of novel therapeutics.Multiple myeloma (MM) is a genetically heterogeneous disease characterized by genomic chaos making it difficult to distinguish driver from passenger mutations. In this study, we integrated data from whole genome gene expression profiling (GEP) microarrays and CytoScan HD high-resolution genomic arrays to integrate GEP with copy number variations (CNV) to more precisely define molecular alterations in MM important for disease initiation, progression and poor clinical outcome. We utilized gene expression arrays from 351 MM samples and CytoScan HD arrays from 97 MM samples to identify eight CNV events that represent possible MM drivers. By integrating GEP and CNV data we divided the MM into eight unique subgroups and demonstrated that patients within one of the eight distinct subgroups exhibited common and unique protein network signatures that can be utilized to identify new therapeutic interventions based on pathway dysregulation. Data also point to the central role of 1q gains and the upregulated expression of ANP32E, DTL, IFI16, UBE2Q1, and UBE2T as potential drivers of MM aggressiveness. The data presented here utilized a novel approach to identify potential driver CNV events in MM, the creation of an improved definition of the molecular basis of MM and the identification of potential new points of therapeutic intervention.

Longitudinal tracking of 97 esophageal adenocarcinomas using liquid biopsy sampling

The incidence of esophageal adenocarcinoma (EAC) is rapidly rising and has a 5-year survival rate of <20%. Beyond TNM (tumor-node-metastasis) staging, no reliable risk stratification tools exist and no large-scale studies have profiled circulating tumor DNA (ctDNA) at relapse in EAC. Here we analyze the prognostic potential of ctDNA dynamics in EAC, taking into account clonal hematopoiesis with indeterminate potential (CHIP). A total of 245 samples from 97 patients treated with neoadjuvant chemotherapy and surgery were identified from the prospective national UK Oesophageal Cancer Clinical and Molecular Stratification (OCCAMS) consortium data set. A pan-cancer ctDNA panel comprising 77 genes was used. Plasma and peripheral blood cell samples were sequenced to a mean depth of 7082× (range 2196-28524) and ctDNA results correlated with survival. Characteristics of the 97 patients identified were as follows: 83/97 (86%) male, median age 68 years (SD 9.5 years), 100% cT3/T4, 75% cN+. EAC-specific drivers had higher variant allele fractions than passenger mutations. Using stringent quality criteria 16/79 (20%) were ctDNA positive following resection; recurrence was observed in 12/16 (75%) of these. As much as 78/97 (80%) had CHIP analyses that enabled filtering for CHIP variants, which were found in 18/78 (23%) of cases. When CHIP was excluded, 10/63 (16%) patients were ctDNA positive and 9/10 of these (90%) recurred. With correction for CHIP, median cancer-specific survival for ctDNA-positive patients was 10.0 months versus 29.9 months for ctDNA-negative patients (hazard ratio 5.55, 95% confidence interval 2.42-12.71; P= 0.0003). Similar outcomes were observed for disease-free survival. We demonstrate in a large, national, prospectively collected data set that ctDNA in plasma following surgery for EAC is prognostic for relapse. Inclusion of peripheral blood cell samples can reduce or eliminate false positives from CHIP. In future, post-operative ctDNA could be used to risk stratify patients into high- and low-risk groups for intensification or de-escalation of adjuvant chemotherapy.

Phosphorylation and Driver Mutations in PI3Kα and PTEN Autoinhibition.

PI3K and PTEN are the second and third most highly mutated proteins in cancer following only p53. Their actions oppose each other. PI3K phosphorylates signaling lipid PIP2 to PIP3 PTEN dephosphorylates it back. Driver mutations in both proteins accrue PIP3 PIP3 recruits AKT and PDK1 to the membrane, promoting cell-cycle progression. Here we review phosphorylation events and mutations in autoinhibition in PI3K and PTEN from the structural standpoint. Our purpose is to clarify how they control the autoinhibited states. In autoinhibition, a segment or a subunit of the protein occludes its functional site. Protein-protein interfaces are often only marginally stable, making them sensitive to changes in conditions in living cells. Phosphorylation can stabilize or destabilize the interfaces. Driver mutations commonly destabilize them. In analogy to "passenger mutations," we coin "passenger phosphorylation" to emphasize that the presence of a phosphorylation recognition sequence logo does not necessarily imply function. Rather, it may simply reflect a statistical occurrence. In both PI3K and PTEN, autoinhibiting phosphorylation events are observed in the occluding "piece." In PI3Kα, the "piece" is the p85α subunit. In PTEN, it is the C-terminal segment. In both enzymes the stabilized interface covers the domain that attaches to the membrane. Driver mutations that trigger rotation of the occluding piece or its deletion prompt activation. To date, both enzymes lack specific, potent drugs. We discuss the implications of detailed structural and mechanistic insight into oncogenic activation and how it can advance allosteric precision oncology.

Critical cancer vulnerabilities identified by unbiased CRISPR/Cas9 screens inform on efficient cancer Immunotherapy.

The mutational landscape of human cancers is highly complex. While next generation sequencing aims to comprehensively catalogue somatic alterations in tumor cells, it fails to delineate driver from passenger mutations. Functional genomic approaches, particularly CRISPR/Cas9, enable both gene discovery, and annotation of gene function. Indeed, recent CRISPR/Cas9 technologies have flourished with the development of more sophisticated and versatile platforms capable of gene knockouts to high throughput genome wide editing of a single nucleotide base. With new platforms constantly emerging, it can be challenging to navigate what CRISPR tools are available and how they can be effectively applied to understand cancer biology. This review provides an overview of current and emerging CRISPR technologies and their power to model cancer and identify novel treatments. Specifically, how CRISPR screening approaches have been exploited to enhance immunotherapies through the identification of tumor intrinsic and extrinsic mechanisms to escape immune recognition will be discussed.

A P2rx7 Passenger Mutation Affects the Vitality and Function of Tcells in Congenic Mice.

SummaryAmong laboratory mouse strains many genes are differentially expressed in the same cell population. As consequence, gene targeting in 129-derived embryonic stem cells (ESCs) and backcrossing the modified mice onto the C57BL/6 background can introduce passenger mutations in the close proximity of the targeted gene. Here, we demonstrate that several transgenic mice carry a P2rx7 passenger mutation that affects the function of T cells. By the example of P2rx4tm1Rass we demonstrate that P2X4ko T cells express higher levels of P2X7 and are more sensitive toward the P2X7 activators ATP and NAD+, rendering these cells more vulnerable toward NAD-induced cell death (NICD) compared with wild type (WT). The enhanced NICD sensitivity confounded functional assays e.g. cytokine production and cell migration. Our results need to be considered when working with P2rx4tm1Rass mice or other 129-based transgenic strains that target P2rx7 neighboring genes.

MEScan: a powerful statistical framework for genome-scale mutual exclusivity analysis of cancer mutations.

Cancer somatic driver mutations associated with genes within a pathway often show a mutually exclusive pattern across a cohort of patients. This mutually exclusive mutational signal has been frequently used to distinguish driver from passenger mutations and to investigate relationships among driver mutations. Current methods for de novo discovery of mutually exclusive mutational patterns are limited because the heterogeneity in background mutation rate can confound mutational patterns, and the presence of highly mutated genes can lead to spurious patterns. In addition, most methods only focus on a limited number of pre-selected genes and are unable to perform genome-wide analysis due to computational inefficiency. We introduce a statistical framework, MEScan, for accurate and efficient mutual exclusivity analysis at the genomic scale. Our framework contains a fast and powerful statistical test for mutual exclusivity with adjustment of the background mutation rate and impact of highly mutated genes, and a multi-step procedure for genome-wide screening with the control of false discovery rate. We demonstrate that MEScan more accurately identifies mutually exclusive gene sets than existing methods and is at least two orders of magnitude faster than most methods. By applying MEScan to data from four different cancer types and pan-cancer, we have identified several biologically meaningful mutually exclusive gene sets. MEScan is available as an R package at https://github.com/MarkeyBBSRF/MEScan. Supplementary data are available at Bioinformatics online.

Integrating Quantitative Assays with Biologically Based Mathematical Modeling for Predictive Oncology.

SummaryWe provide an overview on the use of biological assays to calibrate and initialize mechanism-based models of cancer phenomena. Although artificial intelligence methods currently dominate the landscape in computational oncology, mathematical models that seek to explicitly incorporate biological mechanisms into their formalism are of increasing interest. These models can guide experimental design and provide insights into the underlying mechanisms of cancer progression. Historically, these models have included a myriad of parameters that have been difficult to quantify in biologically relevant systems, limiting their practical insights. Recently, however, there has been much interest calibrating biologically based models with the quantitative measurements available from (for example) RNA sequencing, time-resolved microscopy, and in vivo imaging. In this contribution, we summarize how a variety of experimental methods quantify tumor characteristics from the molecular to tissue scales and describe how such data can be directly integrated with mechanism-based models to improve predictions of tumor growth and treatment response.

OncoVar: an integrated database and analysis platform for oncogenic driver variants in cancers.

The prevalence of neutral mutations in cancer cell population impedes the distinguishing of cancer-causing driver mutations from passenger mutations. To systematically prioritize the oncogenic ability of somatic mutations and cancer genes, we constructed a useful platform, OncoVar (https://oncovar.org/), which employed published bioinformatics algorithms and incorporated known driver events to identify driver mutations and driver genes. We identified 20 162 cancer driver mutations, 814 driver genes and 2360 pathogenic pathways with high-confidence by reanalyzing 10 769 exomes from 33 cancer types in The Cancer Genome Atlas (TCGA) and 1942 genomes from 18 cancer types in International Cancer Genome Consortium (ICGC). OncoVar provides four points of view, ‘Mutation’, ‘Gene’, ‘Pathway’ and ‘Cancer’, to help researchers to visualize the relationships between cancers and driver variants. Importantly, identification of actionable driver alterations provides promising druggable targets and repurposing opportunities of combinational therapies. OncoVar provides a user-friendly interface for browsing, searching and downloading somatic driver mutations, driver genes and pathogenic pathways in various cancer types. This platform will facilitate the identification of cancer drivers across individual cancer cohorts and helps to rank mutations or genes for better decision-making among clinical oncologists, cancer researchers and the broad scientific community interested in cancer precision medicine.

EPCO-22. IDENTIFYING NEOANTIGENS FOR A PERSONALIZED MUTATION-DERIVED GENOMIC VACCINE IN PATIENTS WITH NEWLY DIAGNOSED GLIOBLASTOMA

Abstract BACKGROUND Glioblastomas (GBM) are known for having a lower mutational burden than many other tumor types. Nevertheless, somatic variants that occur in GBM mutational processes may give rise to neoantigens, which can be targeted in a personalized genomic vaccine to elicit a patient-specific anti-tumor response. METHODS Normal and tumor DNA and tumor RNA are extracted from tumor specimens and PBMCs. Exome and RNA sequencing and HLA typing is performed for each patient. Neoantigens are identified using the OpenVax computational pipeline, which calls somatic variants in the DNA and prioritizes corresponding candidate neoantigens for vaccination based on tumor RNA expression and predicted MHC class I binding affinity for each of the patient’s HLA alleles. This work is the base for a phase I trial of personalized neoantigen vaccines in combination with Tumor Treating Fields for GBM (NCT03223103). RESULTS For each of the 9 patients enrolled in the trial, an average of 1005 somatic mutations were identified (range 299–2441), of which 118 were coding variants (range 52–198), 20 were coding and expressed in the tumor RNA (range 9–45), and 16 were coding, expressed and resulted in predicted MHC class I ligands (range 7–33). An average of 2.3% of all somatic variants identified in each tumor gave rise to predicted neoantigens. Sufficient numbers of neoantigens were identified in all tumor samples of the patients enrolled in the study. The overall somatic mutation landscape for the tumors revealed 4/9 PIK3R1 deletions, 2/9 IDH1 substitutions, as well as disruptions in PTEN, TP53, and ATRX, among others. CONCLUSIONS Identifying sufficient neoantigens for inclusion in the personalized genomic vaccine is computationally feasible despite a typically low GBM mutational burden. Driver and passenger mutations can be identified through the same computational pipeline utilized for other tumor types.

Opposing Evolutionary Pressures Drive Clonal Evolution and Health Outcomes in the Aging Blood System

The age-associated accumulation of somatic mutations and large-scale structural variants (SVs) in the early hematopoietic hierarchy have been linked to premalignant stages for cancer and cardiovascular disease (CVD). However, only a small proportion of individuals harboring these mutations progress to disease, and mechanisms driving the transformation to malignancy remains unclear. Hematopoietic evolution, and cancer evolution more broadly, has largely been studied through a lens of adaptive evolution and the contribution of functionally neutral or mildly damaging mutations to early disease-associated clonal expansions has not been well characterised despite comprising the majority of the mutational burden in healthy or tumoural tissues. Through combining deep learning with population genetics, we interrogate the hematopoietic system to capture signatures of selection acting in healthy and pre-cancerous blood populations. Here, we leverage high-coverage sequencing data from healthy and pre-cancerous individuals from the European Prospective Investigation into Cancer and Nutrition Study (n=477) and dense genotyping from the Canadian Partnership for Tomorrow's Health (n=5,000) to show that blood rejects the paradigm of strictly adaptive or neutral evolution and is subject to pervasive negative selection. We observe clear age associations across hematopoietic populations and the dominant class of selection driving evolutionary dynamics acting at an individual level. We find that both the location and ratio of passenger to driver mutations are critical in determining if positive selection acting on driver mutations is able to overwhelm regulated hematopoiesis and allow clones harbouring disease-predisposing mutations to rise to dominance. Certain genes are enriched for passenger mutations in healthy individuals fitting purifying models of evolution, suggesting that the presence of passenger mutations in a subset of genes might confer a protective role against disease-predisposing clonal expansions. Finally, we find that the density of gene disruption events with known pathogenic associations in somatic SVs impacts the frequency at which the SV segregates in the population with variants displaying higher gene disruption density segregating at lower frequencies. Understanding how blood evolves towards malignancy will allow us to capture cancer in its earliest stages and identify events initiating departures from healthy blood evolution. Further, as the majority of mutations are passengers, studying their contribution to tumorigenesis, will unveil novel therapeutic targets thus enabling us to better understand patterns of clonal evolution in order to diagnose and treat disease in its infancy. Disclosures Dick: Bristol-Myers Squibb/Celgene: Research Funding.

Robust Discovery of Candidate DNA Methylation Cancer Drivers

Robust Discovery of Candidate DNA Methylation Cancer Drivers

Molecular Profiling of Clear Cell Myoepithelial Carcinoma of Salivary Glands With EWSR1 Rearrangement Identifies Frequent PLAG1 Gene Fusions But No EWSR1 Fusion Transcripts.

Myoepithelial carcinoma of salivary glands is an underrecognized and challenging entity with a broad morphologic spectrum, including an EWSR1-rearranged clear cell variant. Myoepithelial carcinoma is generally aggressive with largely unknown genetic features. A retrospective review of Salivary Gland Tumor Registry in Pilsen searching for the key words "clear cell myoepithelial carcinoma," "hyalinizing clear cell," and "clear cell malignant myoepithelioma" yielded 94 clear cell myoepithelial carcinomas (CCMCs) for molecular analysis of EWSR1 rearrangement using fluorescence in situ hybridization (FISH). Tumors positive for EWSR1 gene rearrangement were tested by next-generation sequencing (NGS) using fusion-detecting panels. NGS results were confirmed by reverse-transcription polymerase chain reaction or by FISH. Twenty-six tumors originally diagnosed as CCMC (26/94, 27.6%) revealed split signals for EWSR1 by FISH. Six of these tumors (6/26, 23%) displayed amplification of the EWSR1 locus. Fifteen cases were analyzable by NGS, whereas 9 were not, and tissue was not available in 2 cases. None of the CCMCs with EWSR1 rearrangements detected by FISH had an EWSR1 fusion transcript. Fusion transcripts were detected in 6 cases (6/15, 40%), including LIFR-PLAG1 and CTNNB1-PLAG1, in 2 cases each, and CHCHD7-PLAG1 and EWSR1-ATF1 fusions were identified in 1 case each. Seven cases, including those with PLAG1 fusion, were positive for PLAG1 rearrangement by FISH, with notable exception of CHCHD7-PLAG1, which is an inversion not detectable by FISH. One single case with EWSR1-ATF1 fusion in NGS showed ATF1 gene rearrangement by FISH and was reclassified as clear cell carcinoma (CCC). In addition, another 4 cases revealed ATF1 rearrangement by FISH and were reclassified as CCC as well. Moreover, 12/68 (17%) CCMCs with intact EWSR1 gene were selected randomly and analyzed by NGS. PLAG1 fusions were found in 5 cases (5/12, 41.6%) with LIFR (2 cases), FGFR1 (2 cases), and CTNNB1 (1 case) as partner genes. Overall, PLAG1 gene rearrangements were detected in 10/38 (26%) tested cases. None of the tumors had SMARCB1 loss by immunohistochemistry as a possible explanation for the EWSR1 abnormalities in FISH. Novel findings in our NGS study suggest that EWSR1-FISH positive CCMC is a gene fusion-driven disease with frequent oncogenic PLAG1 fusions, including LIFR-PLAG1 and CTNNB1-PLAG1 in most cases. Productive EWSR1 fusions are found only in a minority of EWSR1-ATF1-rearranged cases, which were in part reclassifiable as CCCs. Detectable EWSR1-FISH abnormality in CCMCs without gene fusion perhaps represents a passenger mutation with minor or no oncologic effect.

Identifying Drug Sensitivity Subnetworks with NETPHIX

SummaryPhenotypic heterogeneity in cancer is often caused by different patterns of genetic alterations. Understanding such phenotype-genotype relationships is fundamental for the advance of personalized medicine. We develop a computational method, named NETPHIX (NETwork-to-PHenotype association with eXclusivity) to identify subnetworks of genes whose genetic alterations are associated with drug response or other continuous cancer phenotypes. Leveraging interaction information among genes and properties of cancer mutations such as mutual exclusivity, we formulate the problem as an integer linear program and solve it optimally to obtain a subnetwork of associated genes. Applied to a large-scale drug screening dataset, NETPHIX uncovered gene modules significantly associated with drug responses. Utilizing interaction information, NETPHIX modules are functionally coherent and can thus provide important insights into drug action. In addition, we show that modules identified by NETPHIX together with their association patterns can be leveraged to suggest drug combinations.