Large Number Of Somatic Mutations Research Articles

Impact of Molecular Risk on Efficacy of Blood and Marrow Transplantation for Pediatric Acute Myeloid Leukemia: A Report from the Children's Oncology Group

Outcomes for children and adolescents with newly diagnosed acute myeloid leukemia (AML) have only shown modest improvement over the past three decades. Additionally, outcomes for relapsed disease continue to be poor. As a result, there is a pressing need to optimize consolidation therapy to ensure deep and persistent remissions and prevent future relapse. In particular, the utility of bone and marrow transplant (BMT) for consolidation in pediatric AML has been debated for decades. A prior Children's Oncology Group (COG) study risk-stratified patients on the basis of cytogenetic alterations and demonstrated that consolidative BMT performed in first complete remission (CR1) improved long-term outcomes specifically in patients diagnosed with intermediate-risk disease, but found no survival benefit in patients with either low- or high-risk disease. Since then, whole genome and transcriptome sequencing have uncovered a large number of somatic mutations and cryptic fusions that carry prognostic significance in pediatric AML. Combining these molecular features with traditional cytogenetic risk stratification results in the re-classification of a significant number of patients. While this cytomolecular risk stratification is now being used in contemporary clinical trials (e.g., AAML1831/NCT04293562), the merits of consolidative BMT have not been rigorously re-assessed using these newly defined risk strata. To address this gap, we analyzed clinical and biological data from patients enrolled on COG phase 3 clinical trials AAML0531/NCT00372593 and AAML1031/NCT01371981. We filtered the resulting 2,024 patients to include those who had sufficient diagnostic data to ascertain their cytomolecular risk stratification. Additional inclusion criteria were achieving CR1; completing induction I, induction II, and intensification I; and undergoing BMT after intensification I, which was the recommended time point for BMT on both protocols. Our final analysis included 1,004 patients who met all inclusion criteria. BMT versus chemotherapy alone in CR1 was recommended based on indications provided by AAML0531 or AAML1031, which differ from one another (e.g., AAML1031 incorporated measurable residual disease). Clinical outcomes were assessed using Kaplan-Meier analysis and differences between groups were determined using log-rank testing. Clinical outcomes were superior for patients in the cytomolecular high-risk cohort who underwent BMT in CR1 relative to those who received chemotherapy alone. Specifically, high-risk patients who underwent BMT had a significantly improved five-year OS of 60.8 ± 9.3% (versus 41.3 ± 7.7%; p = 0.002) ( Fig. 1A) and DFS of 55.9 ± 9.4% (versus 30.6 ± 7.2%; p < 0.001) (data not shown). We also observed a decreased incidence of relapse in high-risk patients who received BMT, with a RR of 31.8 ± 8.8% relative to 64.5 ± 7.5% for patients in the chemotherapy only group (p < 0.001) ( Fig. 1B). Conversely, there was no difference in any of these outcome measures for patients in the low- and intermediate-risk groups who underwent BMT in CR1 versus receiving chemotherapy alone. Subsequent and ongoing analysis preliminarily indicates that while a subset of high-risk cytomolecular subtypes benefit from BMT in CR1, others do not. Increased availability of high-throughput sequencing has facilitated the identification of numerous molecular features that have prognostic importance in pediatric AML, leading to more accurate risk stratification and opportunities to better allocate patients to appropriate risk-adapted therapy. In this study, we demonstrate that incorporation of these molecular features into the traditional risk stratification schema significantly impacts the clinical indications for BMT as consolidation therapy in pediatric AML. Whereas BMT was previously found to benefit only those patients with intermediate-risk disease, our data suggest that patients with contemporary high-risk cytomolecular alterations benefit significantly from consolidative BMT. Notably, our current analysis does not yet address the potential bias that patients who reach BMT systematically differ from those patients who did not reach BMT (e.g., toxicity that precludes BMT), which we will address with multivariable analysis using BMT as a time varying exposure. These findings support the need for further prospective studies evaluating the role of BMT in high-risk pediatric AML.

Mutations observed in somatic evolution reveal underlying gene mechanisms

Highly sensitive DNA sequencing techniques have allowed the discovery of large numbers of somatic mutations in normal tissues. Some mutations confer a competitive advantage over wild-type cells, generating expanding clones that spread through the tissue. Competition between mutant clones leads to selection. This process can be considered a large scale, in vivo screen for mutations increasing cell fitness. It follows that somatic missense mutations may offer new insights into the relationship between protein structure, function and cell fitness. We present a flexible statistical method for exploring the selection of structural features in data sets of somatic mutants. We show how this approach can evidence selection of specific structural features in key drivers in aged tissues. Finally, we show how drivers may be classified as fitness-enhancing and fitness-suppressing through different patterns of mutation enrichment. This method offers a route to understanding the mechanism of protein function through in vivo mutant selection.

The landscape of somatic mutations in lymphoblastoid cell lines

Somatic mutations have important biological ramifications while exerting substantial rate, type, and genomic location heterogeneity. Yet, their sporadic occurrence makes them difficult to study at scale and across individuals. Lymphoblastoid cell lines (LCLs), a model system for human population and functional genomics, harbor large numbers of somatic mutations and have been extensively genotyped. By comparing 1,662 LCLs, we report that the mutational landscape of the genome varies across individuals in terms of the number of mutations, their genomic locations, and their spectra; this variation may itself be modulated by somatic trans-acting mutations. Mutations attributed to the translesion DNA polymerase η follow two different modes of formation, with one mode accounting for the hypermutability of the inactive X chromosome. Nonetheless, the distribution of mutations along the inactive X chromosome appears to follow an epigenetic memory of the active form.

Bias and inconsistency in the estimation of tumour mutation burden

BackgroundTumour mutation burden (TMB), defined as the number of somatic mutations per megabase within the sequenced region in the tumour sample, has been used as a biomarker for predicting response to immune therapy. Several studies have been conducted to assess the utility of TMB for various cancer types; however, methods to measure TMB have not been adequately evaluated. In this study, we identified two sources of bias in current methods to calculate TMB.MethodsWe used simulated data to quantify the two sources of bias and their effect on TMB calculation, we down-sampled sequencing reads from exome sequencing datasets from TCGA to evaluate the consistency in TMB estimation across different sequencing depths. We analyzed data from ten cancer cohorts to investigate the relationship between inferred TMB and sequencing depth.ResultsWe found that TMB, estimated by counting the number of somatic mutations above a threshold frequency (typically 0.05), is not robust to sequencing depth. Furthermore, we show that, because only mutations with an observed frequency greater than the threshold are considered, the observed mutant allele frequency provides a biased estimate of the true frequency. This can result in substantial over-estimation of the TMB, when the cancer sample includes a large number of somatic mutations at low frequencies, and exacerbates the lack of robustness of TMB to variation in sequencing depth and tumour purity.ConclusionOur results demonstrate that care needs to be taken in the estimation of TMB to ensure that results are unbiased and consistent across studies and we suggest that accurate and robust estimation of TMB could be achieved using statistical models that estimate the full mutant allele frequency spectrum.

Abstract P111: Therapeutic KRASG12C inhibition alleviates KRAS-driven immunosuppression

Abstract Therapeutic KRASG12C inhibitors may substantially improve KRAS-mutant cancer patient care, considering the encouraging clinical data emerging from ongoing clinical trials. Since oncogene-targeting therapies often lead to resistance, the development of combinatorial therapies will be of utmost importance to achieve long-lasting tumour control. Given the known immunosuppressive role of KRAS, clinical trials investigating the combination of KRASG12C inhibitors with immune checkpoint blockade are currently underway for NSCLC patients. Here, we show that KRASG12C inhibition using MRTX1257 alleviates KRAS-driven immune suppression, through a myriad of mechanisms including the augmentation of tumour cell-intrinsic interferon responses. Despite harbouring a large number of somatic mutations, orthotopic 3LL (KRASG12CDNRAS) tumours are able to evade anti-tumour immune responses. Combining multicolour flow cytometry, RNA sequencing and imaging mass cytometry, we observed significantly increased T cell activation and infiltration after MRTX1257 treatment in addition to enhanced antigen presentation cells and gene sets, and reduced myeloid cells, creating an immune permissive microenvironment in these lung tumours. Despite these profound changes, combination of KRASG12C inhibitors and anti-PD-(L)1 antibodies fail to show synergism in our model, in contrast with Amgen’s published data using an immunogenic model of colorectal cancer. This data suggests that a pre-existing anti-tumour immunity may be crucial for clinical responses to KRAS inhibitors and immune checkpoint blockade combinations. Henceforth, ongoing clinical trials investigating this approach will likely only benefit a subset of patients and further research will be needed to examine novel therapeutic approaches and combinations for refractory patients. Citation Format: Edurne Mugarza, Febe Van Maldegem, Jesse Boumelha, Chris Moore, Sareena Rana, Miriam Llorian Sopena, Phil East, Miriam Molina Arcas, Julian Downward. Therapeutic KRASG12C inhibition alleviates KRAS-driven immunosuppression [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2021 Oct 7-10. Philadelphia (PA): AACR; Mol Cancer Ther 2021;20(12 Suppl):Abstract nr P111.

Potential Immune Biomarker Candidates and Immune Subtypes of Lung Adenocarcinoma for Developing mRNA Vaccines.

mRNA vaccines against cancer have advantages in safety, improved therapeutic efficacy, and large-scale production. Therefore, our purpose is to identify immune biomarkers and to analyze immune status for developing mRNA vaccines and selecting appropriate patients for vaccination. We downloaded clinical information and RNA-seq data of 494 LUAD patients from TCGA. LUAD mutational information was hierarchically clustered by NMF package (Version 0.23.0). DeconstructSigs package (Version 1.8.0) and NMF consistency clustering were used to identify mutation signatures. Maftools package (Version 2.6.05) was used to select LUAD-related immune biomarkers. TIMER was used to discuss the correlation between genetic mutations and cellular components. Unsupervised clustering Pam method was used to identify LUAD immune subtypes. Log-rank test and univariate/multivariate cox regression were used to predict the prognosis of immune subtypes. Dimensionality reduction analysis was dedicated to the description of LUAD immune landscape. LUAD patients are classified into four signatures: T >C, APOBEC mutation, age, and tobacco. Then, GPRIN1, MYRF, PLXNB2, SLC9A4, TRIM29, UBA6, and XDH are potential LUAD-related immune biomarker candidates to activate the immune response. Next, we clustered five LUAD-related immune subtypes (IS1–IS5) by prognostic prediction. IS3 showed prolonged survival. The reliability of our five immune subtypes was validated by Thorsson’s results. IS2 and IS4 patients had high tumor mutation burden and large number of somatic mutations. Besides, we identified that immune subtypes of cold immunity (patients with IS2 and IS4) are ideal mRNA vaccination recipients. Finally, LUAD immune landscape revealed immune cells and prognostic conditions, which provides important information to select patients for vaccination. GPRIN1, MYRF, PLXNB2, SLC9A4, TRIM29, UBA6, and XDH are potential LUAD-related immune biomarker candidates to activate the immune response. Patients with IS2 and IS4 might potentially be immunization-sensitive patients for vaccination.

Identification of a Somatic Mutation-Derived Long Non-Coding RNA Signatures of Genomic Instability in Renal Cell Carcinoma.

BackgroundRenal cell carcinoma (RCC) is a malignant tumor with high morbidity and mortality. It is characterized by a large number of somatic mutations and genomic instability. Long non-coding RNAs (lncRNAs) are widely involved in the expression of genomic instability in renal cell carcinoma. But no studies have identified the genome instability-related lncRNAs (GInLncRNAs) and their clinical significances in RCC.MethodsClinical data, gene expression data and mutation data of 943 RCC patients were downloaded from The Cancer Genome Atlas (TCGA) database. Based on the mutation data and lncRNA expression data, GInLncRNAs were screened out. Co-expression analysis, Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were conducted to explore their potential functions and related signaling pathways. A prognosis model was further constructed based on genome instability-related lncRNAs signature (GInLncSig). And the efficiency of the model was verified by receiver operating characteristic (ROC) curve. The relationships between the model and clinical information, prognosis, mutation number and gene expression were analyzed using correlation prognostic analysis. Finally, the prognostic model was verified in clinical stratification according to TCGA dataset.ResultsA total of 45 GInLncRNAs were screened out. Functional analysis showed that the functional genes of these GInLncRNAs were mainly enriched in chromosome and nucleoplasmic components, DNA binding in molecular function, transcription and complex anabolism in biological processes. Univariate and Multivariate Cox analyses further screened out 11 GInLncSig to construct a prognostic model (AL031123.1, AC114803.1, AC103563.7, AL031710.1, LINC00460, AC156455.1, AC015977.2, ‘PRDM16-dt’, AL139351.1, AL035661.1 and LINC01606), and the coefficient of each GInLncSig in the model was calculated. The area under the curve (AUC) value of the ROC curve was 0.770. Independent analysis of the model showed that the GInLncSig model was significantly correlated with the RCC patients’ overall survival. Furthermore, the GInLncSig model still had prognostic value in different subgroups of RCC patients.ConclusionOur study preliminarily explored the relationship between genomic instability, lncRNA and clinical characteristics of RCC patients, and constructed a GInLncSig model consisted of 11 GInLncSig to predict the prognosis of patients with RCC. At the same time, our study provided theoretical support for the exploration of the formation and development of RCC.

RepairSig: Deconvolution of DNA damage and repair contributions to the mutational landscape of cancer.

Cancer genomes accumulate a large number of somatic mutations resulting from a combination of stochastic errors in DNA processing, cancer-related aberrations of the DNA repair machinery, or carcinogenic exposures; each mutagenic process leaves a characteristic mutational signature. A key challenge is understanding the interactions between signatures, particularly as DNA repair deficiencies often modify the effects of other mutagens. Here, we introduce RepairSig, a computational method that explicitly models additive primary mutagenic processes; non-additive secondary processes, which interact with the primary processes; and a mutation opportunity, that is, the distribution of sites across the genome that are vulnerable to damage or preferentially repaired. We demonstrate that RepairSig accurately recapitulates experimentally identified signatures, identifies autonomous signatures of deficient DNA repair processes, and explains mismatch repair deficiency in breast cancer by de novo inference of both primary and secondary signatures from patient data. RepairSig is freely available for download at https://github.com/ncbi/RepairSig.

Pollen-Specific CRISPR/Cas9 System to Increase Heritable Gene Mutations in Maize

The CRISPR/Cas9 system has been widely utilized in plant biotechnology as a gene editing tool. However, a conventional design with ubiquitously expressed CRISPR/Cas9 was observed to cause large numbers of somatic mutations that complicated the identification of heritable mutations. We constructed a pollen-specific CRISPR/Cas9 (PSC) system using pollen-specific promoters of maize Profilin 1 and Profilin 3 (pZmPRO1 and pZmPRO3) to drive Cas9 expression, and the bZIP transcription factor Opaque2 (O2) was employed as the target gene. The maize ubiquitin promoter (pZmUbi)-driven CRISPR/Cas9 (UC) system was employed as a control. We generated transgenic plants for the PSC and UC systems and analyzed three independent events for each system. We found that the pZmPRO1 PSC system generated no target gene mutations in the T0 generation but successfully generated 0–90% target gene mutations in the T1 generation. A total of 31 of 33 mutations in the T1 generation could be inherited in the T2 generation. In addition, 88.9–97.3% of T2 mutations were from the T1 generation. The UC system generated mutations in the T0 generation, and 0%, 50% and 92.9% of T1 mutations were from the T0 generation. Our results demonstrate that the PSC system provided stable, heritable mutants in the next generation, and this approach might also be applied in other crops using germinal cell-specific CRISPR/Cas9 systems to facilitate plant breeding.

Rapid selection of HIV envelopes that bind to neutralizing antibody B cell lineage members with functional improbable mutations.

SUMMARYElicitation of broadly neutralizing antibodies (bnAbs) by an HIV vaccine will involve priming the immune system to activate antibody precursors, followed by boosting immunizations to select for antibodies with functional features required for neutralization breadth. The higher the number of acquired mutations necessary for function, the more convoluted are the antibody developmental pathways. HIV bnAbs acquire a large number of somatic mutations, but not all mutations are functionally important. In this study, we identify a minimal subset of mutations sufficient for the function of the naturally occurring V3-glycan bnAb DH270.6. Using antibody library screening, candidate envelope immunogens that interact with DH270.6-like antibodies containing this set of key mutations are identified and selected in vitro. Our results demonstrate that less complex B cell evolutionary pathways than those naturally observed exist for the induction of HIV bnAbs by vaccination, and they establish rational approaches to identify boosting candidate immunogens.

­­­­Rapid Selection of HIV Envelopes that Bind to Neutralizing Antibody B Cell Lineage Members with Functional Improbable Mutations

Elicitation of broadly neutralizing antibodies (bnAbs) by an HIV vaccine will involve priming the immune system to activate antibody precursors, followed by boosting immunizations to select for antibodies with functional features required for neutralization breadth. The higher the number of acquired mutations necessary for function, the more convoluted are the antibody developmental pathways. HIV bnAbs acquire a large number of somatic mutations, but not all mutations are functionally important. Here we identified a minimal subset of mutations sufficient for the function of the naturally occurring V3-glycan bnAb DH270.6. Using antibody library screening, candidate envelope immunogens that interacted with DH270.6-like antibodies containing this set of key mutations were identified and selected in vitro. Our results demonstrate that less complex B cell evolutionary pathways than those naturally observed exist for the induction of HIV bnAbs by vaccination, and establish rational approaches to identify boosting sequential envelope candidate immunogens.

MP16-17 GENOMIC LANDSCAPE OF METASTATIC HORMONE- NAÏVE PROSTATE CANCER

You have accessJournal of UrologyProstate Cancer: Basic Research & Pathophysiology I (MP16)1 Apr 2020MP16-17 GENOMIC LANDSCAPE OF METASTATIC HORMONE- NAÏVE PROSTATE CANCER Kei Mizuno*, Shusuke Akamatsu, Takayuki Sumiyoshi, Takayuki Goto, Takashi Kobayashi, Toshinari Yamasaki, Takahiro Inoue, Akihiro Fujimoto, and Osamu Ogawa Kei Mizuno*Kei Mizuno* More articles by this author , Shusuke AkamatsuShusuke Akamatsu More articles by this author , Takayuki SumiyoshiTakayuki Sumiyoshi More articles by this author , Takayuki GotoTakayuki Goto More articles by this author , Takashi KobayashiTakashi Kobayashi More articles by this author , Toshinari YamasakiToshinari Yamasaki More articles by this author , Takahiro InoueTakahiro Inoue More articles by this author , Akihiro FujimotoAkihiro Fujimoto More articles by this author , and Osamu OgawaOsamu Ogawa More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000000841.017AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Multiple studies have demonstrated recurrent genomic alterations in advanced prostate cancer in recent years. However, genomic characterization of metastatic hormone-naïve prostate cancer (mHNPC) has been limited. Recently, we identified clinical parameters associated with prognosis in mHNPC, and it would be helpful to characterize genomic alterations in mHNPC for developing a more accurate prognostic model. In this study, we performed whole-exome sequencing (WES) of mHNPC and aimed to detect somatic genomic alterations and discover the relevance between the findings and clinical course. METHODS: Prostate biopsies were performed in 19 mHNPC patients and the specimens were halved. One section from each was used for pathological analysis, while the other was stored for DNA extraction. We extracted DNA from the stored section when the paired one had cancer cells, and matched germline DNA was isolated from blood. We then performed WES of DNA from tumor tissue and lymphocytes, and the following criteria were applied for variant calling: 1) variant allele frequency (VAF) of ≥ 5% after removing base calls with base quality or mapping quality of < 20; 2) the P-value of Fisher’s exact test comparing VAF in tumor to that in matched germline of < 0.001; 3) single nucleotide polymorphisms that were registered in databases were excluded. The relevance between genomic alterations and clinicopathological features were assessed. RESULTS: Of the 19 samples, five samples exhibited an exceptionally large number of somatic mutations, and the average tumor mutational burden (TMB) was 14.9 per megabase. The average TMB of the rest of 14 samples was 2.5 per megabase, which was about half that of castration-resistant prostate cancer. Of the five samples with high TMB, four had aberrations in DNA repair genes such as CDK12, ATM and ERCC2. Recurrently mutated genes were SPOP, FOXA1, KMT2C and ZMYM3, and all were mutated in five samples each. There was no relationship between TMB and clinicopathological features such as PSA progression-free survival, overall survival, PSA value and Gleason score. No specific mutation correlated with survival in this cohort. CONCLUSIONS: SPOP and FOXA1, which are key genes in AR signaling, were most frequently mutated in mHNPC. Patients with DNA repair genes mutations had higher TMB, which was not associated with worse survival in this study. Source of Funding: This study was supported by a research grant provided by Astellas Pharma. © 2020 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 203Issue Supplement 4April 2020Page: e222-e222 Advertisement Copyright & Permissions© 2020 by American Urological Association Education and Research, Inc.MetricsAuthor Information Kei Mizuno* More articles by this author Shusuke Akamatsu More articles by this author Takayuki Sumiyoshi More articles by this author Takayuki Goto More articles by this author Takashi Kobayashi More articles by this author Toshinari Yamasaki More articles by this author Takahiro Inoue More articles by this author Akihiro Fujimoto More articles by this author Osamu Ogawa More articles by this author Expand All Advertisement PDF downloadLoading ...

Identification of cancer driver genes based on nucleotide context.

Cancer genomes contain large numbers of somatic mutations, but few of these mutations drive tumor development. Current approaches identify driver genes based on mutational recurrence, or they approximate the functional consequences of nonsynonymous mutations using bioinformatic scores. While passenger mutations are enriched in characteristic nucleotide contexts, driver mutations occur in functional positions, which are not necessarily surrounded by a particular nucleotide context. We observed that mutations in contexts that deviate from the characteristic contexts around passenger mutations provide a signal in favor of driver genes. We therefore developed a method that combines this feature with the signals traditionally used for driver gene identification. We applied our method to whole-exome sequencing data from 11,873 tumor-normal pairs and identified 460 driver genes that clustered into 21 cancer-related pathways. Our study provides a resource of driver genes across 28 tumor types with additional driver genes identified based on mutations in unusual nucleotide contexts.

Identifying Driver Interfaces Enriched for Somatic Missense Mutations in Tumors.

Human cancers often harbor large numbers of somatic mutations. However, only a small proportion of these mutations are expected to contribute to tumor growth and progression. Therefore, determining causal driver mutations and the genes they target is becoming an important challenge in cancer genomics. Here we describe an approach for mapping somatic mutations onto 3D structures of human proteins in complex to identify "driver interfaces." Our strategy relies on identifying protein-interaction interfaces that are unexpectedly biased toward nonsynonymous mutations, which suggests that these interfaces are subject to positive selection during tumorigenesis, implicating the interacting proteins as candidate drivers.

Detecting presence of mutational signatures in cancer with confidence

Cancers arise as the result of somatically acquired changes in the DNA of cancer cells. However, in addition to the mutations that confer a growth advantage, cancer genomes accumulate a large number of somatic mutations resulting from normal DNA damage and repair processes as well as carcinogenic exposures or cancer related aberrations of DNA maintenance machinery. These mutagenic processes often produce characteristic mutational patterns called mutational signatures. The decomposition of a cancer genome's mutation catalog into mutations consistent with such signatures can provide valuable information about cancer etiology. However, the results from different decomposition methods are not always consistent. Hence, one needs to be able to not only decompose a patient's mutational profile into signatures but also establish the accuracy of such decomposition. We proposed two complementary ways of measuring confidence and stability of decomposition results and applied them to analyze mutational signatures in breast cancer genomes. We identified both very stable and highly unstable signatures, as well as signatures that previously have not been associated with breast cancer. We also provided additional support for the novel signatures. Our results emphasize the importance of assessing the confidence and stability of inferred signature contributions. All tools developed in this paper have been implemented in an R package, called SignatureEstimation, which is available from https://www.ncbi.nlm.nih.gov/CBBresearch/Przytycka/index.cgi\#signatureestimation. Supplementary data are available at Bioinformatics online.

Integrating genomic alterations in diffuse large B-cell lymphoma identifies new relevant pathways and potential therapeutic targets

Genome studies of diffuse large B-cell lymphoma (DLBCL) have revealed a large number of somatic mutations and structural alterations. However, the clinical significance of these alterations is still not well defined. In this study, we have integrated the analysis of targeted next-generation sequencing of 106 genes and genomic copy number alterations (CNA) in 150 DLBCL. The clinically significant findings were validated in an independent cohort of 111 patients. Germinal center B-cell and activated B-cell DLBCL had a differential profile of mutations, altered pathogenic pathways and CNA. Mutations in genes of the NOTCH pathway and tumor suppressor genes (TP53/CDKN2A), but not individual genes, conferred an unfavorable prognosis, confirmed in the independent validation cohort. A gene expression profiling analysis showed that tumors with NOTCH pathway mutations had a significant modulation of downstream target genes, emphasizing the relevance of this pathway in DLBCL. An in silico drug discovery analysis recognized 69 (46%) cases carrying at least one genomic alteration considered a potential target of drug response according to early clinical trials or preclinical assays in DLBCL or other lymphomas. In conclusion, this study identifies relevant pathways and mutated genes in DLBCL and recognizes potential targets for new intervention strategies.

Abstract 3579: A novel algorithm to identify TCR-binding somatic mutations from human cancers

Abstract A large number of pre-clinical and clinical studies have strongly implicated that combining cancer-derived neo-antigen vaccines with checkpoint control inhibitors will enhance priming and expansion of tumor-specific naïve and memory T-cells resulting in superior efficacy and durability of response. The neo-antigens, derived from somatic mutations are prime candidates for cancer vaccines, not subjected to host’s central and peripheral tolerance. Identifying potential T-cell engaging neo-epitopes among a large number of somatic mutations is like finding a specific needle in a stack of needles. Currently, the available T-cell neo-epitope prioritization pipelines rely primarily on two attributes - the class-I HLA-binding affinity of the mutant peptide compared to the wild-type counterpart, and the level of expression of the mutated gene in tumor cells. The higher the binding differential, and higher the expression level of the mutant allele, the greater is the likelihood for the peptide to be presented on antigen-presenting cells. These approaches however fall short of predicting whether the HLA-bound peptide will engage T-cells by binding to T-cell receptors (TCRs). We have developed a novel algorithm to predict the binding of HLA-peptide complexes to TCRs by analyzing the physico-chemical composition of the amino acids and their positional biases in the 9-mers from crystal structures of HLA-peptide-TCR complex. We applied machine learning approach to build a classification model that can predict whether a given 9-mer peptide is a TCR-binder or not by identifying whether an amino acid at a given position carries key features that will facilitate interaction with the TCR. We applied this approach to positive and negative TCR interactions selected from Immune Epitope data base (IEDB). We tested multiple classification approaches and found that Random Forest and ClassificationviaRegression methods provided the best performance. We achieved more than 99% accuracy at 10-fold cross validation on both training and unseen test datasets. We further validated our model using positive and negative peptides curated from published papers reporting clinical trial results of checkpoint control inhibitors. The performance of the two classification models was evaluated on two different TCR-binding assays - dextramer binding and IFN-γ release. The ClassificationviaRegression method showed a higher positive predictive value for the dextramer-binding assay, whereas the Random Forest method showed a higher positive predictive value for the IFN-γ ELISPOT assay, suggesting subtle differences between the two classification methods. The inclusion of the TCR binding step to our T-cell neo-epitope prioritization pipeline increased accuracy of prediction, reduced false positives and selected potential neo-epitopes to a manageable number for testing in cell-based assays. Citation Format: Priyanka Shah, Kiran V. Paul, Malini Manoharan, Amitabha Chaudhuri, Ravi Gupta. A novel algorithm to identify TCR-binding somatic mutations from human cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3579. doi:10.1158/1538-7445.AM2017-3579

Abstract 628: Neoantigens predicted by clonal mutation analysis in lung adenocarcinoma patients

Abstract Mutant peptides presented in cancer are superior vaccine candidates than self peptides. The efficacy of mutant K-Ras, P53 and EFGR peptides have been tested as cancer vaccines in pancreatic cancer, colorectal cancer, and lung adenocarcinoma. However, the occurrence of these mutations in cancer is limited. Further more, these mutant peptides can only be presented by certain MHC alleles. Neoantigens expressed by passenger mutations which are not involved in common proliferative molecular pathways are potential candidates for personalized vaccine design. Such passenger mutations have drawn attention by the recent clinical data that colorectal cancer with a large number of somatic mutations due to mismatch-repair defects are more susceptible to immune checkpoint blockade by PD1 antibody therapy. In this study, we analyzed the next generation sequencing data of 147 lung adenocarcinoma patients from The Cancer Genome Atlas and predicted neoantigens presented by MHC Class I and Class II molecules. We found 18175 expressed clonal somatic mutations, with an average of 124 per patient. Based on such somatic mutations, we predicted 8731 neo-peptides, among which 3888 strong-binders and 4843 weak-binders to MHC Class I molecules were found by NetMHCPan. For HLA-A*02:01, 778 strong binding and 822 weak binding neo-peptides were found. In average, 11 neo-antigen peptides of mutations were predicted per individual patient with HLA-A*02:01 allele. Smokers expressed 5.73 fold higher mutant neo-antigen peptides than non-smokers. The 20 most commonly mutated genes with predicted neo-antigens are TTN, RYR2, MUC16, KRAS, ZFHX4, TP53, USH2A, NAV3, KEAP1, ANK2, DNAH9, ADAMTS12, CSMD1, CSMD3, SPTA1, FAT3, ZNF804A, PAPPA2, PCLO, EGFR. As a positive control, the frequency of known proliferation-related mutations (KRAS, P53, and EGFR) were determined in 147 patients, which are consistent with previously next generation sequencing studies of lung adenocarcinoma. Mutation hotspots were found in proliferation-related mutations (KRAS), but not in passenger mutations. 6950 neo-peptides, including 259 strong binders and 6691 weak binders were found for HLA DRB1, an MHC Class II molecule. INDEL mutation type of neo-epitopes were found in 119 of 147 patients, with an average of 4.34 INDEL mutations presented by MHC Class I and 0.86 INDEL mutations presented by MHC Class II molecule HLA DRB1 in every patient. Our results support the feasibility of discovering individualized mutant peptides as candidates for immunodiagnosis and immunotherapy of lung adenocarcinoma. Neo-epitopes which can be presented by both MHC Class I and MHC Class II molecules are attractive targets for designing long-peptide vaccines. Note: This abstract was not presented at the meeting. Citation Format: Dapeng Zhou, Weijing Cai, Deng Pan, Tan Wen Ling, Jiaqian Wang, Caichun Zhou, Yanyan Lou. Neoantigens predicted by clonal mutation analysis in lung adenocarcinoma patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 628. doi:10.1158/1538-7445.AM2017-628

Comprehensive molecular profiling of multi-focal prostate cancer and concomitant lymph node metastasis: Implications for tissue-based prognostic biomarkers.

5061 Background: Current tissue-based prognostic biomarker assays claim that assessment of a single biopsy focus is sufficient to predict disease behavior. We analyzed and compared the genetic profiles of multifocal prostate cancer (PCa) with concordant lymph node metastasis (LNM) to determine if expression-based prognostic tests are robust to multifocality. Methods: This IRB-approved study comprised patients who underwent radical prostatectomy and lymph node dissection that revealed N1 or discordant multifocal (low- and high-grade foci) disease. DNA and RNA were co-isolated from each tumor focus pre-identified on formalin fixed paraffin embedded specimens. High depth, targeted DNA and RNA next generation sequencing was performed to characterize the molecular profile of each sample, using the Oncomine Comprehensive (11 patients) or Comprehensive Cancer (DNA, 3 patients) Panels and a custom targeted RNAseq panel comprising genes for deriving prognostic signatures. Results: A total of 67 primary tumor and 17 LNM foci from 14 patients were analyzed. We observed significant intra- and inter-patient molecular heterogeneity. For example, in patient #1, while all 4 regions of high-grade primary tumor showed TP53 somatic mutations and some copy number alterations (CNAs) with two samples from the LNM, tumor areas near the positive margin showed more complete concordance than intraprostatic regions. Critically, a low-grade primary tumor focus in this case showed no somatic mutation or CNA overlap with the high-grade or LNM samples. In patient #4, all tumor and LNM foci shared a large number of somatic mutations, including a frameshift mutation in PTEN, with no high level CNA, consistent with a hypermutated genotype. By targeted RNAseq, low- and high-grade tumors from the same patient showed distinct expression profiles using genes included in prognostic signatures. Conclusions: Our results challenge the claim that expression-based prognostic tests are robust to multifocality. Further studies are needed to better characterize the biologically dominant lesion in multifocal PCa and hold promise for the development of improved prognostic biomarkers.

PD07-12 MOLECULAR PROFILING OF MULTI-FOCAL PROSTATE CANCER AND CONCOMITANT LYMPH NODE METASTASIS: IMPLICATIONS FOR TISSUE-BASED PROGNOSTIC BIOMARKERS

You have accessJournal of UrologyProstate Cancer: Detection & Screening II1 Apr 2017PD07-12 MOLECULAR PROFILING OF MULTI-FOCAL PROSTATE CANCER AND CONCOMITANT LYMPH NODE METASTASIS: IMPLICATIONS FOR TISSUE-BASED PROGNOSTIC BIOMARKERS Simpa Salami, Daniel Hovelson, Romain Mathieu, Jeremy Kaplan, Martin Susani, Christopher Russell, Nathalie Rioux-Leclercq, Shahrokh Shariat, Scott Tomlins, and Ganesh Palapattu Simpa SalamiSimpa Salami More articles by this author , Daniel HovelsonDaniel Hovelson More articles by this author , Romain MathieuRomain Mathieu More articles by this author , Jeremy KaplanJeremy Kaplan More articles by this author , Martin SusaniMartin Susani More articles by this author , Christopher RussellChristopher Russell More articles by this author , Nathalie Rioux-LeclercqNathalie Rioux-Leclercq More articles by this author , Shahrokh ShariatShahrokh Shariat More articles by this author , Scott TomlinsScott Tomlins More articles by this author , and Ganesh PalapattuGanesh Palapattu More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2017.02.387AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Current tissue-based prognostic biomarker assays claim that genetic assessment of a single focus is sufficient to predict disease behavior. We analyzed and compared the genetic profiles of multifocal prostate cancer (PCa) with concordant lymph node metastasis (LNM) to determine if expression based prognostic tests are robust to multifocality. METHODS This IRB-approved study comprised patients who underwent radical prostatectomy and lymph node dissection that revealed N1 disease or discordant multifocal disease (low- and high-grade foci). DNA and RNA were co-isolated from each tumor focus pre-identified on formalin fixed paraffin embedded specimens. High depth, targeted DNA and RNA next generation sequencing was performed to characterize the genetic and transcriptional signature of each sample, using the Oncomine Comprehensive (11 patients) or Comprehensive Cancer (DNA, 3 patients) Panels and a custom targeted RNAseq panel comprising genes for deriving prognostic signatures. RESULTS A total of 67 primary tumor and 17 LMN foci (with control tissue when available) from 14 patients were analyzed. We observed significant intra- and inter-patient molecular heterogeneity. For example, in patient #1, while all four regions of high-grade primary tumor showed TP53 somatic mutations and some broad copy number alterations (CNAs) with two samples from the LNM, tumor areas near the positive margin showed more complete concordance than intraprostatic regions. Critically, a low-grade primary tumor focus in this case showed no somatic mutation or CNA overlap with the high-grade or LNM samples. In patient #4, all tumor and LNM foci shared a large number of somatic mutations, including a frameshift mutation in PTEN, with no high level CNA identified, consistent with a hypermutated genotype. By targeted RNAseq, low-grade and high-grade tumors from the same patient showed distinct expression profiles using genes included in available prognostic signatures (Figure 1). CONCLUSIONS Our results challenge the claim that expression based prognostic tests are robust to multifocality. Additional molecular studies are needed to better characterize the biologically dominant lesion in multi-focal PCa and hold promise for the development of improved prognostic biomarkers. © 2017FiguresReferencesRelatedDetails Volume 197Issue 4SApril 2017Page: e132-e133 Advertisement Copyright & Permissions© 2017MetricsAuthor Information Simpa Salami More articles by this author Daniel Hovelson More articles by this author Romain Mathieu More articles by this author Jeremy Kaplan More articles by this author Martin Susani More articles by this author Christopher Russell More articles by this author Nathalie Rioux-Leclercq More articles by this author Shahrokh Shariat More articles by this author Scott Tomlins More articles by this author Ganesh Palapattu More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...