Potential Driver Mutations Research Articles

1020 – HEMATOPOIETIC STEM CELL CLONAL TRACKING BY WHOLE GENOME SEQUENCING IDENTIFIES MULTIPLE INDEPENDENT SOMATIC GENETIC RESCUE MECHANISMS IN BONE MARROW FAILURE DISORDERS.

The congenital bone marrow failure syndrome Shwachman-Diamond Syndrome (SDS) is characterized by defective ribosome biogenesis, with a significant risk of developing a severe myelodysplastic syndrome or leukemia. The most common causal germ line mutations are in the SBDS gene. It remains unclear how the germline ribosomal dysfunction/stress affects individual hematopoietic stem cells and contributes to the aberrant population dynamics that drive specific clonal expansions and eventual leukemic transformation. To address this, we adopted a clonal tracking approach using whole genome sequencing of single hematopoietic stem and progenitor cell (HSPC)-derived colonies followed by phylogenetic tree construction to assess clonal relatedness in 9 SDS patients. The mean mutation burden in SDS HSPCs increased linearly with age and the majority of mutations were C >T variants, consistent with mutational signatures in ageing. Single nucleotide variants in annotated genes across patients were found in known drivers <i>TP53, EIF6</i> and other ribosomal proteins: all of which were mutually exclusive in different HSPC clones. Distinct mutations in the same genes were found within the same patients, demonstrating that individual clones must acquire independent genetic rescue mechanisms. Whole genome sequencing permitted us to uncover a high degree of intra-patient heterogeneity, charting multiple independent paths that individual cells can take to combat defective ribosome deficiency caused by SBDS loss. This study sets the stage for functional analysis of potential leukemia driver mutations and longitudinal tracking of clonal dynamics throughout disease progression and re-enforces the value of using whole genome sequencing to track individual stem cell clones in disease.

Analysis of mutation detection of POLD1/pole in pan-cancer.

3142 Background: Previous studies proved that mutation of POLD1 and POLE elevates base-substitution mutations and lead to the elevation of tumor mutation burden (TMB). Other signature needs to explore to identify driver mutations in these two genes. Methods: Using gene-panel target-capture next generation sequencing, we analyzed the TMB and POLD1/POLE mutation in 17383 tumor tissue or plasma ctDNA samples from different patients. Results: Tumor mutation burdens were calculated of all the 17383 samples. According to the present research and our panel, we use 10 and 100 Mut/Mb to define hypermutation and ultra-hypermutation. Samples with hypermutation possessed 18.8% (n = 3268) and ultra-hypermutation possessed 0.3% (n = 58). In unselected, hypermutation and ultra-hypermutation group, POLD1 or/and POLE mutations were identified in 3.5% (n = 625), 56.1% (n = 32) and 87.9%(n = 372) samples. There were 0.5% (n = 81), 17.0% (n = 73) and 87.7%(n = 51) identified more than one mutation. These results showed that POLD1 or/and POLE mutations were enriched in samples with high TMB. We screened every known POLE and POLD1 driver mutations. There were 22 ultra-hypermutation samples identified these mutations, including A456P(3), P286R(10), V411L(6), M444K(1), S459F(1) in POLE and R1016H(1) in POLD1. Interestingly, all of them were identified in microsatellite stable (MSS) samples, which suggest that driver mutation may enriched in MSS samples. These already known driver mutation was not detect in 24 high-level microsatellite instability (MSI-H) and ultra-hypermutation samples. We further analyzed 10 POLD1/POLE mutations in other 5 MSS and ultra-hypermutation samples. POLE L424V was a pathogenic germline mutation but not defined as a driver mutation clearly before. POLE P286C had not been biochemically characterized but had different residue with P286R in the same position. Others had not been biochemically characterized (R232H, A234T, V945M, S1064I, Y467H in POLD1, D462N and R749Q, E1956D in POLE). These mutations were potential driver mutations and further research need to be support. Conclusions: We found that not only POLD1 or/and POLE mutations were enriched in samples with high TMB, but also driver mutations were enriched in microsatellite stable tumors. Further researches need to continue to identify more driver mutations of POLD1 and POLE.

Whole-genome sequencing of 508 patients identifies key molecular features associated with poor prognosis in esophageal squamous cell carcinoma.

Esophageal squamous cell carcinoma (ESCC) is a poor-prognosis cancer type with limited understanding of its molecular etiology. Using 508 ESCC genomes, we identified five novel significantly mutated genes and uncovered mutational signature clusters associated with metastasis and patients’ outcomes. Several functional assays implicated that NFE2L2 may act as a tumor suppressor in ESCC and that mutations in NFE2L2 probably impaired its tumor-suppressive function, or even conferred oncogenic activities. Additionally, we found that the NFE2L2 mutations were significantly associated with worse prognosis of ESCC. We also identified potential noncoding driver mutations including hotspot mutations in the promoter region of SLC35E2 that were correlated with worse survival. Approximately 5.9% and 15.2% of patients had high tumor mutation burden or actionable mutations, respectively, and may benefit from immunotherapy or targeted therapies. We found clinically relevant coding and noncoding genomic alterations and revealed three major subtypes that robustly predicted patients’ outcomes. Collectively, we report the largest dataset of genomic profiling of ESCC useful for developing ESCC-specific biomarkers for diagnosis and treatment.

Molecular subtypes in canine hemangiosarcoma reveal similarities with human angiosarcoma.

Angiosarcoma (AS) is a rare neoplasm with limited treatment options and a poor survival rate. Development of effective therapies is hindered by the rarity of this disease. Dogs spontaneously develop hemangiosarcoma (HSA), a common, histologically similar neoplasm. Metastatic disease occurs rapidly and despite chemotherapy, most dogs die several months after diagnosis. These features suggest that HSA might provide a tractable model to test experimental therapies in clinical trials. We previously reported whole exome sequencing of 20 HSA cases. Here we report development of a NGS targeted resequencing panel to detect driver mutations in HSA and other canine tumors. We validated the panel by resequencing the original 20 cases and sequenced 30 additional cases. Overall, we identified potential driver mutations in over 90% of the cases, including well-documented (in human cancers) oncogenic mutations in PIK3CA (46%), PTEN (6%), PLCG1(4%), and TP53 (66%), as well as previously undetected recurrent activating mutations in NRAS (24%). The driver role of these mutations is further demonstrated by augmented downstream signaling crucial to tumor growth. The recurrent, mutually exclusive mutation patterns suggest distinct molecular subtypes of HSA. Driver mutations in some subtypes closely resemble those seen in some AS cases, including NRAS, PLCG1, PIK3CA and TP53. Furthermore, activation of the MAPK and PI3K pathways appear to be key oncogenic mechanisms in both species. Together, these observations suggest that dogs with spontaneous HSA could serve as a useful model for testing the efficacy of targeted therapies, some of which could potentially be of therapeutic value in AS.

Identifying multi-hit carcinogenic gene combinations: Scaling up a weighted set cover algorithm using compressed binary matrix representation on a GPU

Despite decades of research, effective treatments for most cancers remain elusive. One reason is that different instances of cancer result from different combinations of multiple genetic mutations (hits). Therefore, treatments that may be effective in some cases are not effective in others. We previously developed an algorithm for identifying combinations of carcinogenic genes with mutations (multi-hit combinations), which could suggest a likely cause for individual instances of cancer. Most cancers are estimated to require three or more hits. However, the computational complexity of the algorithm scales exponentially with the number of hits, making it impractical for identifying combinations of more than two hits. To identify combinations of greater than two hits, we used a compressed binary matrix representation, and optimized the algorithm for parallel execution on an NVIDIA V100 graphics processing unit (GPU). With these enhancements, the optimized GPU implementation was on average an estimated 12,144 times faster than the original integer matrix based CPU implementation, for the 3-hit algorithm, allowing us to identify 3-hit combinations. The 3-hit combinations identified using a training set were able to differentiate between tumor and normal samples in a separate test set with 90% overall sensitivity and 93% overall specificity. We illustrate how the distribution of mutations in tumor and normal samples in the multi-hit gene combinations can suggest potential driver mutations for further investigation. With experimental validation, these combinations may provide insight into the etiology of cancer and a rational basis for targeted combination therapy.

Gene mutations distinguishing gastric from colorectal and esophageal adenocarcinomas.

Genetic analysis of gastrointestinal malignancies shows a great number of mutations. Most mutations found in gastric tumors are also found in colorectal and esophageal tumors. The challenge remains to identify mutations that distinguish gastric from colorectal and esophageal cancers. Using open-access cancer genomics data, we sought to identify mutations that accounted for the unique phenotypic features of gastric tumors. Thirteen cancer genomics datasets with demographic, clinical, and genetic variables were analyzed. Pathologic stage and histology were compared between subjects with and without a specific mutated gene using two-sample t-tests, adjusted for multiple gene testing. Sequence convergence and functional impact of genetic mutations were analyzed using permutation test and PolyPhen-2 score. Analysis included 1,915 subjects with valid pathologic stage and histology. Mean age was 68 years (SD =10). About 54% were female. The most common race was Caucasian (37%) while minorities were rare with high rates of missing data (44%). Pathologic stage: 20% stage I, 35% stage II, 31% stage III, and 14% stage IV. Anatomical location: 30% gastric, 59% colorectal, and 11% esophageal. Histology of gastric cancer: 61% intestinal, 23% diffuse, 15% mixed, and 1% missing. Two mutated genes-CDH1, RHOA-distinguished gastric from colorectal and esophageal tumors. These mutations were highly specific to diffuse histology and advanced stages of gastric tumors and recurrent in transcribed regions known to impact protein functions. CDH1 and RHOA regulate cell-cell adhesion which is vital to cell growth and proliferation. Identification of these potential driver mutations is critical to better define therapeutic vulnerabilities for the rational design of gastric cancer therapies.

Identification of Altered Genes in Gallbladder Cancer as Potential Driver Mutations for Diagnostic and Prognostic Purposes: A Computational Approach.

Prognostic markers for cancer can assist in the evaluation of survival probability of patients and help clinicians to assess the available treatment modalities. Gallbladder cancer (GBC) is a rare tumor that causes 165 087 deaths in the world annually. It is the most common cancer of the biliary tract and has a particularly high incidence in Chile, Japan, and northern India. Currently, there is no accurate diagnosis test or effective molecular markers for GBC identification. Several studies have focused on the discovery of genetic alterations in important genes associated with GBC to propose novel diagnosis pathways and to create prognostic profiles. To achieve this, we performed data-mining of GBC in public repositories, harboring 133 samples of GBC, allowing us to describe relevant somatic mutations in important genes and to propose a genetic alteration atlas for GBC. In our results, we reported the 14 most altered genes in GBC: arid1a, arid2, atm, ctnnb1, erbb2, erbb3, kmt2c, kmt2d, kras, pik3ca, smad4, tert, tp53, and znf521 in samples from Japan, the United States, Chile, and China. Missense mutations are common among these genes. The annotations of many mutations revealed their importance in cancer development. The observed annotations mentioned that several mutations found in this repository are probably oncogenic, with a putative loss-of-function. In addition, they are hotspot mutations and are probably linked to poor prognosis in other cancers. We identified another 11 genes, which presented a copy number alteration in gallbladder database samples, which are ccnd1, ccnd3, ccne1, cdk12, cdkn2a, cdkn2b, erbb2, erbb3, kras, mdm2, and myc. The findings reported here can help to detect GBC cancer through the development of systems based on genetic alterations, for example, the development of a mutation panel specifically for GBC diagnosis, as well as the creation of prognostic profiles to accomplish the development of GBC and its prevalence.

The mutational footprints of cancer therapies.

Some cancer therapies damage DNA and cause mutations both in cancer and healthy cells of the patient. Therapy-induced mutations may underlie some of the long-term and late side effects of treatments, such as mental disabilities, organ toxicities and secondary neoplasms. Currently we ignore the mutation burden caused by different cancer treatments. Here we identify mutational signatures, or footprints of six widely-used anti-cancer therapies across more than 3,500 metastatic tumors originating from different organs. These include previously known and new mutational signatures generated by platinum-based drugs, and a novel signature of nucleoside metabolic inhibitors. Exploiting these mutational footprints, we estimate the contribution of different treatments to the mutation burden of tumors and their risk of contributing coding and potential driver mutations in the genome. The mutational footprints identified here allow for precisely assessing the mutational risk of different cancer therapies to understand their long-term side effects.

Outcomes of Patients with Acute Myeloid Leukemia with Myelodysplastic Are Dependent on Diagnostic Criteria and Therapy

Outcomes of Patients with Acute Myeloid Leukemia with Myelodysplastic Are Dependent on Diagnostic Criteria and Therapy

Transcriptomic Analysis Implicates Necroptosis in Disease Progression and Prognosis in Myelodysplastic Syndromes

INTRODUCTION: Myelodysplastic syndromes (MDS) are characterized by ineffective hematopoiesis and cytopenias due to uncontrolled programmed cell death. The presence of pro-inflammatory cytokines and constitutive activation of innate immunity signals in MDS cells suggest inflammatory cell death, such as necroptosis, may be responsible for disease phenotype. There is no data evaluating the association of RIPK1, RIPK3 and MLKL with response and prognosis in MDS. METHODS: We evaluated 64 bone marrow samples from 55 patients with MDS or chronic myelomonocytic leukemia (CMML) obtained prior to (n=46) or after (n=18) therapy with hypomethylating agents (HMAs). RNA from sorted bone marrow CD34+ cells was isolated and subject to amplification and RNA-seq. Gene co-expression was evaluated using Spearman correlation. Pathway enrichment analysis was performed using gene set enrichment analysis, with the fgsea library in R. Sequencing data was obtained by use of a 81-gene targeted PCR-based next generation sequencing (NGS) platform. Previously described somatic mutations registered at the Catalogue of Somatic Mutations in Cancer (COSMIC: http://cancer.sanger.ac.uk/cosmic) were considered as potential driver mutations. RESULTS: Compared to healthy controls, MLKL (CMML vs controls: 2.09 log2FC, p=0.0013; MDS vs control: 1.89 log2FC, p=0.003), but not RIPK1 or RIPK3, were significantly upregulated in patients with MDS and CMML (Figure 1A-C). No differences in the level of expression of RIPK1, MLKL or RIPK3 were observed based on the mutation context or burden. No significant difference in RIPK1, RIPK3 or MLKL expression levels was observed based on presence of cytogenetic abnormalities (RIPK1: 0.10 log2FC, p=0.6; RIPK3: -0.39 log2FC, p=0.40; MLKL: 0.34 log2FC, p=0.30). Higher expression levels of MLKL were associated with lower hemoglobin levels at the time of diagnosis (-0.19 log2FC per 1g/dL increase of Hgb, p=0.03) (Figure 1D). Exposure to HMA therapy was associated with a trend to decreased expression of MLKL (-0.52 log2FC, p=0.08) when all post-HMA therapy samples were evaluated. Among patient matched samples, significant reduction in MLKL levels was observed after HMA therapy (-1.06 log2FC, p=0.05). The degree of reduction in expression levels was greater among non-responders (-2.89 log2FC, p=0.06) compared to responders (-0.78, log2FC, p=0.06). Expression levels of RIPK1 at the time of diagnosis predicted for shorter survival for patients with high RIPK1 levels, defined as a log expression higher than median mRNA expression values, (median OS 10.7 vs 24.2 months, HR 1.92, 95% CI 1.00-3.67, p=0.049 by Cox proportional hazards) (Figure 1E). A multivariate analysis for overall survival using both IPSS-R risk and RIPK1 expression levels demonstrated that high RIPK1 expression was an independent adverse prognostic factor in MDS patients (HR 6.83, 95% CI 1.74-26.8, p=0.006). A total of 359 genes were significantly correlated with RIPK1 levels in MDS CD34+ cells (Spearman's method q&lt;0.2). Among these, 21 genes were positively correlated with RIPK1 expression, while 17 genes were negative correlated (Spearman's correlation, q&lt;0.1). Gene set enrichment analysis identified 373 gene sets that significantly correlated with RIPK1 expression. Upregulated genes were associated with molecular signals associated with innate immunity and inflammatory signaling including TNF-α signaling via NFkB, NFkB signaling, the IFN-g pathway, and RIG-I-like receptor (RLRs) signaling genes (Figure 1F). CONCLUSIONS: This data provides further support for a role of necroptosis in MDS, and potentially response to HMAs and prognosis. This data also indicates that RIPK1/RIPK3/MLKL are potential therapeutic targets in MDS. Figure 1 Disclosures Sasaki: Otsuka: Honoraria; Pfizer: Consultancy. Bueso-Ramos:Incyte: Consultancy. Kantarjian:Cyclacel: Research Funding; Jazz Pharma: Research Funding; AbbVie: Honoraria, Research Funding; Astex: Research Funding; Amgen: Honoraria, Research Funding; Actinium: Honoraria, Membership on an entity's Board of Directors or advisory committees; BMS: Research Funding; Immunogen: Research Funding; Daiichi-Sankyo: Research Funding; Pfizer: Honoraria, Research Funding; Novartis: Research Funding; Ariad: Research Funding; Agios: Honoraria, Research Funding; Takeda: Honoraria. Garcia-Manero:Amphivena: Consultancy, Research Funding; Helsinn: Research Funding; Novartis: Research Funding; AbbVie: Research Funding; Celgene: Consultancy, Research Funding; Astex: Consultancy, Research Funding; Onconova: Research Funding; H3 Biomedicine: Research Funding; Merck: Research Funding.

Outcomes in Molecular Subgroups and Resistance Patterns with Ten-Day Decitabine and Venetoclax (DEC10-VEN) in Acute Myeloid Leukemia

Outcomes in Molecular Subgroups and Resistance Patterns with Ten-Day Decitabine and Venetoclax (DEC10-VEN) in Acute Myeloid Leukemia

The U1 Spliceosomal RNA: A Novel Non-Coding Hotspot Driver Mutation Independently Associated with Clinical Outcome in Chronic Lymphocytic Leukemia

Introduction: Genomic studies of chronic lymphocytic leukemia (CLL) have uncovered &amp;gt;80 potential driver mutations. The vast majority of these mutations affect coding regions, and just two potential drivers have been identified in non-coding elements. Aim: To describe the biological and clinical impact of a recurrent A&amp;gt;C mutation at the third base of the small nuclear RNA U1, the non-coding component of the spliceosome involved in the recognition of the 5' splice site (5'SS). Methods: Whole-genome sequencing (WGS) and RNA-seq from 318 CLL patients were used to identify and characterize a highly recurrent A&amp;gt;C point mutation occurring at position 3 of the U1 snRNA gene (g.3A&amp;gt;C mutation). The U1 wild-type and mutant forms were introduced into three CLL cell lines (JVM3, HG3, MEC1) to validate in vitro the predicted effect of this alteration. We screened two independent cohorts including a total of 1,314 CLL patients for the presence of the mutation using the rhAmp SNP genotyping assay, and integrated the U1 mutational status with well-known driver alterations, IGHV and epigenetic subgroups, and clinical parameters. Results: The U1 mutation was found in 8/78 (10.3%) CLL cases analyzed by WGS. Given its role in 5'SS recognition by base-pairing, we reasoned that this mutation was likely to alter the splicing and expression patterns of CLL. We were able to confirm widespread specific alterations in the transcriptome by comparing RNA-seq data between wild-type and g.3A&amp;gt;C mutated samples. Applying this knowledge to an algorithm aimed to infer the U1 mutational status from expression data, we were able to identify 4 mutated cases among 240 additional cases that had RNA-seq but no WGS. In total, 12/318 (3.8%) CLL patients analyzed by WGS and/or RNA-seq harbored this mutation. This g.3A&amp;gt;C U1 mutation changes the preferential A-U base-pairing between U1 and 5'SS to C-G base-pairing, creating novel splice junctions and altering the splicing pattern of 3,193 introns in 1,519 genes. In addition to altered splicing, 869 genes were differentially expressed between mutated and wild-type cases. We identified specific cancer genes (e.g. MSI2, POLD1, or CD44) and pathways (B-cell receptor signaling, promotion of apoptosis, telomere maintenance, among others) altered by the U1 mutation. To confirm a causal link between this mutation and splicing changes, we introduced exogenous U1 genes with or without the mutation into three cell lines. Subsequent RNA-seq of these cell lines recapitulated the altered splicing and expression patterns observed in CLL patients. We next screened for the presence of the U1 mutation 1,057 patients (cohort 1) using the rhAmp assay and it was found in 30 (2.8%) cases. The distribution of the mutation was similar in Binet stages and CLL vs monoclonal B-cell lymphocytosis. However, the U1 mutation was almost always found in IGHV unmutated CLL (29/30, p=9.0e-11) and within the naïve-like CLL epigenetic subgroup (p=3.7e-7). None of the U1 mutated cases had mutations in the SF3B1 splicing factor. Considering only pre-treatment CLL samples, U1 mutation was associated with a shorter time to first treatment independently of the Binet stage, IGHV mutational status, epigenetic subgroups, and mutations in the well-known CLL drivers SF3B1, NOTCH1, ATMor TP53. In cohort 2 (n=257), this mutation was found in 13 (5.1%) patients, confirming its enrichment in IGHV unmutated cases, naïve-like epigenetic subgroup, and splicing modulation. Despite the relatively small number of pre-treatment samples carrying the U1 mutation (7/178) and short follow-up of the patients (median 2.6 years), the effect of this mutation on time to first treatment in cohort 2 was compatible with the one observed in cohort 1. Finally, we screened for the U1 mutation a cohort of diffuse large B-cell lymphoma (n=108), mantle cell lymphoma (n=101), follicular lymphoma (n=87), splenic marginal zone lymphoma (n=12), acute myeloid leukemia (n=52), and myelodysplastic syndrome (n=67). The mutation was not present in any of the samples analyzed. Conclusions: Here we have reported that the third base of the small nuclear RNA U1 is recurrently mutated in CLL, proved its effect in splicing and gene expression, and shown that this mutation is independently associated with faster disease progression. The g.3A&amp;gt;C U1 mutation represents a novel non-coding driver alteration in CLL with potential clinical and therapeutic implications. Disclosures Ramirez Payer: GILEAD SCIENCES: Research Funding. Terol:Astra Zeneca: Consultancy; Gilead: Research Funding; Abbvie: Consultancy; Janssen: Consultancy, Research Funding; Roche: Consultancy. Lopez-Guillermo:Celgene: Consultancy, Research Funding; Janssen: Research Funding; Roche: Consultancy, Research Funding; Gilead: Consultancy, Research Funding.

Temporal dissection of altered pathways during the evolution of cancer

Abstract Background Cancer arise as normal cells acquire insults to the genome through both mutations and gross copy number alterations. Our current understanding of the molecular makeup of cancer is based on a snap-shot, a biopsy taken at a single time point. Large-scale studies have shown an abundance of genomic alterations, but few are shared across samples which makes interpretation of effect difficult, particularly as different processes may be dominant at different time points in the development of cancer. Here, we have performed pathway analysis on timed mutational driver events to investigate if specific pathways are preferentially affected at different time points during the life-history of cancer. Methods We analyzed mutation data and copy number information from bladder cancer acquired from The Cancer Genome Atlas, to time the mutations as early and late relative to copy number events affecting the same genomic location (McGranahan et al., 2015). The mutations were annotated to genes and potential driver mutations were annotated (Jamal-Hanjani et al., 2017). Timed driver events across each cohort were combined into early and late, and subjected to pathway analysis using Reactome (Fabregat et al., 2017). Results Focusing on bladder cancer, 28% of the timed mutations are early and 72% are late. The most frequent early driver mutations are TP53 (12%), MUC4 (8%), and PIK3CA (5%), while in late they are PABPC1 (21%), KMT2C (16%), HLA-A (9%). Pathway analysis on early drivers showed how events that affects cell cycle and proliferation dominates, while late drivers are particularly enriched in pathways associated with the immune system. Conclusions Our results demonstrate a clear time-separated preference for specific events. These indicates that selection in early cancer development may be primarily focused on genomic alterations that increase proliferation. Conversely, late cancer development enriches in events targeting pathways associated with the immune response, consistent with increased immune pressure as the cancer develops. These results show how timing of events may provide novel insights into how cancer develops, and may help determine the evolutionary developmental stage of cancer with potential implications for improved prognostics and differential therapy. Legal entity responsible for the study The authors. Funding The Lundbeck Foundation. Disclosure All authors have declared no conflicts of interest.

RHOA G17V mutation in angioimmunoblastic T-cell lymphoma: A potential biomarker for cytological assessment

BackgroundThe World Health Organization, in a 2016 revision, introduced recurrent genetic abnormalities for classifying mature T- and NK-cell neoplasms. However, the role of genetic analyses from lymph node aspiration cytology is still not elucidated. We hypothesize that the use of genetic analyses may increase the accuracy of diagnosis from cytological preparations. MethodsFifty-seven formalin-fixed paraffin-embedded (FFPE) samples were collected for next-generation sequencing (NGS) targeting potential driver mutations including TET2, DMN3TA, IDH2, RHOA, STAT3, and STAT5B. Competitive allele-specific TaqMan polymerase chain reaction (cast-PCR) was performed to validate the mutation status by using FFPE and preoperative fine needle aspiration cytology (FNAC) samples. ResultsAmong these six candidate genes, only IDH2 and RHOA mutations were significantly more frequent in nodal subtypes, angioimmunoblastic T-cell lymphoma (AITL) and peripheral T-cell lymphoma, not otherwise specified (PTCL, NOS) (P = .002 and <0.001, respectively). All genes exhibited different mutation patterns except RHOA with a hotspot mutation involving the Gly17 residue. The RHOA G17V mutation was found in 15 (75%) of 20 AITL and two (22%) of nine PTCL, NOS. Cast-PCR using FFPE samples showed 100% concordance with NGS. Among 12 lymph node aspirates, the preliminary diagnoses were suspicious for lymphoma (3, 25%), atypical lymphoid cells (3, 25%) and benign/negative (6, 50%). Cast-PCR detected the RHOA G17V mutation in six (75%) of eight RHOA-mutated aspirates and revealed negative results in all (100%) of four wild-type aspirates, with an 83.3% (10/12) concordance comparing to FFPE samples. ConclusionsThe RHOA G17V mutation serves as a useful biomarker for cytological assessment in AITL. The use of cast-PCR is valuable in the diagnosis of malignant lymphomas from cytological preparations, and thus avoiding the potential risks of invasive procedures.

Understanding the impacts of missense mutations on structures and functions of human cancer-related genes: A preliminary computational analysis of the COSMIC Cancer Gene Census.

Genomics and genome screening are proving central to the study of cancer. However, a good appreciation of the protein structures coded by cancer genes is also invaluable, especially for the understanding of functions, for assessing ligandability of potential targets, and for designing new drugs. To complement the wealth of information on the genetics of cancer in COSMIC, the most comprehensive database for cancer somatic mutations available, structural information obtained experimentally has been brought together recently in COSMIC-3D. Even where structural information is available for a gene in the Cancer Gene Census, a list of genes in COSMIC with substantial evidence supporting their impacts in cancer, this information is quite often for a single domain in a larger protein or for a single protomer in a multiprotein assembly. Here, we show that over 60% of the genes included in the Cancer Gene Census are predicted to possess multiple domains. Many are also multicomponent and membrane-associated molecular assemblies, with mutations recorded in COSMIC affecting such assemblies. However, only 469 of the gene products have a structure represented in the PDB, and of these only 87 structures have 90–100% coverage over the sequence and 69 have less than 10% coverage. As a first step to bridging gaps in our knowledge in the many cases where individual protein structures and domains are lacking, we discuss our attempts of protein structure modelling using our pipeline and investigating the effects of mutations using two of our in-house methods (SDM2 and mCSM) and identifying potential driver mutations. This allows us to begin to understand the effects of mutations not only on protein stability but also on protein-protein, protein-ligand and protein-nucleic acid interactions. In addition, we consider ways to combine the structural information with the wealth of mutation data available in COSMIC. We discuss the impacts of COSMIC missense mutations on protein structure in order to identify and assess the molecular consequences of cancer-driving mutations.

Abstract 4699: Enriching tumor purity using a unique flow-sorting approach to elucidate clonal evolution in matched samples of squamous cell carcinoma of the lung

Abstract Background:All carcinomas contain a variable proportion of benign stromal and immune cells, limiting the sensitivity in the identification of somatic genetic alterations. The average tumor purity of squamous cell carcinomas (SCC) of the lung is only around 50%. Low tumor content in tumor samples represents a challenge in studying intratumoral genomic heterogeneity in cancer research. Here, we applied flow-sorting to enrich for tumor cell nuclei to investigate the clonal relationship of primary SCC and matched metastases. Methods:Tumor tissues from 16 patients with primary SCC of the lung and matched metastases were used. We implemented a flow-sorting based approach to enrich for tumor nuclei as followed: after extraction of nuclei from snap-frozen or FFPE tissue, they were flow-sorted by DNA content (ploidy) and cytokeratin expression of the adherent cytoplasm, using a pan-cytokeratin (pCK) antibody. Isolated diploid and aneuploid pCK-positive tumor cell populations were subjected to whole exome sequencing (WES). DNA from diploid pCK-negative populations was used as germline control. Mutational profile and copy number aberrations (CNA) were determined to infer the clonal relationship and evolution between the primary tumors and their metastases. Results:Our flow-sorting based approach was able to enrich tumor content from 20%-50% to more than 80%-90% and to distinguish between aneuploid and diploid tumor cell populations from bulk tumor tissues. It enabled the identification of somatic mutations and CNA in both, aneuploid and diploid tumor cell populations, including potential subclonal driver mutations in ARID1A and KDM6A at low allelic frequencies. Shared and private mutations were observed in matched longitudinal tumor samples of individual patients and in synchronous distant metastases. Ploidy did not change significantly between primary tumors and relapse or distant metastases. Conclusion:We present a flow-sorting based method to enrich for tumor cell nuclei to facilitate genomic analysis, which also enabled separate analysis of aneuploid and diploid tumor populations. Our results show that the enrichment approach can be used to decode the clonal evolutionary relationship between primary tumors and their matched metastases, even in samples with low tumor cell content. Citation Format: Arthur Krause, Maria R. De Filippo, Thomas Lorber, Tanja Dietsche, Valeria Perrina, Christian Ruiz, Michael T. Barrett, Salvatore Piscuoglio, Charlotte K. Ng, Lukas Bubendorf. Enriching tumor purity using a unique flow-sorting approach to elucidate clonal evolution in matched samples of squamous cell carcinoma of the lung [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 4699.

Identification of a Novel Fusion Gene, FAM174A-WWC1, in Early-Onset Colorectal Cancer: Establishment and Characterization of Four Human Cancer Cell Lines from Early-Onset Colorectal Cancers

Colorectal cancer (CRC) is the third most common cancer diagnosed worldwide and represents the second most common cause of all cancer-related deaths in Korea. Although epidemiological data indicate a sharp increase in the incidence of CRC among individuals older than 50 years, more than 10% of CRCs occur before reaching 50. These are known as early-onset CRCs (EOCRCs) and are likely to be suggestive of hereditary predisposition. However, known familial CRC syndromes account for only 20% of genetic aberrations of EOCRC, and the remaining 80% are still in question. Therefore, we aimed to establish reproducible biological resources and contribute to expand the mutation database of EOCRC. Four cell lines derived from the original tumor mass of CRC patients diagnosed under age 30 years were established, and next-generation sequencing technique was used to identify the genetic features of EOCRC. We have identified one novel fusion gene, FAM174A-WWC1, and analyzed its functional role. The induction of FAM174A-WWC1 to normal fibroblast caused alternations in cellular morphology as well as intercellular expression of E-cadherin and N-cadherin. Moreover, WWC1 carrying the fused FAM174A domain not only abrogated the membrane expression of YAP1 but also significantly increased the levels of nucleic YAP1. As a result, the FAM174A-WWC1 expression increased the oncogenic capacity and invasiveness of normal fibroblasts, which suggests its role as a potential driver mutation of EOCRC.

Somatic Mutations Profile of a Young Patient With Metastatic Urothelial Carcinoma Reveals Mutations in Genes Involved in Ion Channels

Background: Urothelial carcinoma is the most common malignancy of the bladder and is primarily considered as a disease of the elderly. Studies that address bladder tumor occurrence in young age groups are rare.Case Presentation: A 19-year-old male presented with a gross total painless hematuria. A histology after biopsy revealed a high-grade transitional cell carcinoma with lymph node metastasis. The patient succumbed to the disease on day 72 of the treatment. Here, we used whole-exome sequencing of a paired tumor-normal sample to identify the somatic mutations and the possible targets of treatment.Result: We predicted eight potential driver mutations (TP53 p.V157L, RB1 c.1498+1G>T, MED23 p.L1127P, CTNND1 p.S713C, NSD1 p.P2212A, MED17 p.G556V, DPYD p.Q814K, and SPEN p.S1078*). In addition, we predicted deleterious mutations in genes involved in the ion channels (CACNA1S p.E1581K, CACNG1 p.P71T, CACNG8 p.G404W, GRIN2B p.A1096T, KCNC1 p.G16V, KCNH4 p.E874K, KCNK9 p.R131S, P2RX7 p.A296D, and SCN8A p.R558H).Conclusions: Most likely, mutations in genes involved in ion channels may be responsible for the aggressive behavior of a tumor. Ion channels are the second largest class of drug targets, and may thus serve as a putative potential therapeutic target in advanced stage urothelial carcinoma.

Somatic mutational profile of Merkel cell carcinoma treated with immune checkpoint blockade: Preliminary results from a planned multiplatform analysis.

e21064 Background: Merkel cell carcinoma (MCC) is an immunogenic neuroendocrine malignancy with promising responses to immune checkpoint blockade (ICB). Although ICB is standard of care in advanced MCC patients, approximately 50% of patients are resistant to ICB. Thus, it is crucial to identify biomarkers predictive of response. Methods: To understand the genomic landscape of MCC, we performed exome capture sequencing on 27 tumor and matched normal samples from 25 patients with MCC treated at Memorial Sloan Kettering. Herein, we report the analysis of 16 paired samples from 14 patients. Nonsynonymous, high-confidence somatic mutations were identified and tumor reads aligned to the Merkel cell polyoma virus (MCPyV) were quantified. Results: Tumor and matched normal samples were sequenced to a median target coverage depth of 53x and 79x reads, respectively. One sample was not analyzed due to inadequate coverage. The MCPyV genome was detected in 12 of 13 patients (92%). The median somatic mutation burden among analyzed samples was 19 nonsynonymous variants per exome (range: 8 - 120). No recurrent driver mutations were identified in any sample. Four samples lacked potential driver mutations and, among the remaining 11 samples, 36 putatively oncogenic mutations were detected in 33 genes (variant allele frequency: 0.08 – 1), including genes involved in the cell cycle checkpoint ( TP53, RB1), DNA damage repair ( ERCC4, FANCA, FANCD2), PI3K-AKT-mTOR ( PIK3CA, PIK3CG), and Notch ( NOTCH1, NOTCH2) pathways. One sample with undetected MCPyV DNA demonstrated loss of heterozygosity of both TP53 and RB1. Four samples contained strand coordinated clusters of mutations in more than 20 distinct gene regions, suggesting an APOBEC-high mutagenesis signature. Conclusions: The MCPyV genome was detected in most tumors analyzed and tumor mutation burden was low in such tumors, consistent with published literature. Analysis of an additional 11 sample pairs is ongoing, along with personalized neoantigen binding predictions on all samples. Immunohistochemistry (IHC) for PDL1 and CD8 expression is in progress. Associations between the aforementioned and response to ICB will be reported.

Comparison of the genomic background of MET-altered carcinomas of the lung: biological differences and analogies

Although non-small-cell lung cancer is a leading cause of cancer-related deaths, the molecular characterization and classification of its genetic alterations has drastically changed treatment options and overall survival within the last few decades. In particular, tyrosine kinase inhibitors targeting specific molecular alterations, among other MET, have greatly improved the prognosis of non-small-cell lung cancer patients. Here, we compare the genomic background of a subset of non-small-cell lung cancer cases harboring either a MET high-level amplification (n = 24) or a MET exon 14 skipping mutation (n = 26), using next-generatison sequencing, fluorescence in situ hybridization, immunohistochemistry, and Nanostring nCounter® technology. We demonstrate that the MET-amplified cohort shows a higher genetic instability, compared with the mutant cohort (p < 0.001). Furthermore, MET mutations occur at high allele frequency and in the presence of co-occurring TP53 mutations (n = 7), as well as MDM2 (n = 7), CDK4 (n = 6), and HMGA2 (n = 5) co-amplifications. No other potential driver mutation has been detected. Conversely, in the MET-amplified group, we identify co-occurring pathogenic NRAS and KRAS mutations (n = 5) and a significantly higher number of TP53 mutations, compared with the MET-mutant cohort (p = 0.048). Of note, MET amplifications occur more frequently as subclonal events. Interestingly, despite the significantly (p = 0.00103) older age at diagnosis of stage IIIb/IV of MET-mutant patients (median 77 years), compared with MET high-level amplified patients (median 69 years), MET-mutant patients with advanced-stage tumors showed a significantly better prognosis at 12 months (p = 0.04). In conclusion, the two groups of MET genetic alterations differ, both clinically and genetically: our data strongly suggest that MET exon 14 skipping mutations represent an early driver mutation. In opposition, MET amplifications occur usually in the background of other strong genetic events and therefore MET amplifications should be interpreted in the context of each tumor's genetic background, rather than as an isolated driver event, especially when considering MET-specific treatment options.