480 research outputs found

    The prognostic significance of low-frequency somatic mutations in metastatic cutaneous melanoma

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    Background: Little is known about the prognostic significance of somatically mutated genes in metastatic melanoma (MM). We have employed a combined clinical and bioinformatics approach on tumor samples from cutaneous melanoma (SKCM) as part of The Cancer Genome Atlas project (TCGA) to identify mutated genes with potential clinical relevance. Methods: After limiting our DNA sequencing analysis to MM samples (n = 356) and to the CANCER CENSUS gene list, we filtered out mutations with low functional significance (snpEFF). We performed Cox analysis on 53 genes that were mutated in ≥3% of samples, and had ≥50% difference in incidence of mutations in deceased subjects versus alive subjects. Results: Four genes were potentially prognostic [RAC1, FGFR1, CARD11, CIITA; false discovery rate (FDR) 75% of the samples that exhibited corresponding DNA mutations. The low frequency, UV signature type and RNA expression of the 22 genes in MM samples were confirmed in a separate multi-institution validation cohort (n = 413). An underpowered analysis within a subset of this validation cohort with available patient follow-up (n = 224) showed that somatic mutations in SPEN and RAC1 reached borderline prognostic significance [log-rank favorable (p = 0.09) and adverse (p = 0.07), respectively]. Somatic mutations in SPEN, and to a lesser extent RAC1, were not associated with definite gene copy number or RNA expression alterations. High (>2+) nuclear plus cytoplasmic expression intensity for SPEN was associated with longer melanoma-specific overall survival (OS) compared to lower (≤ 2+) nuclear intensity (p = 0.048). We conclude that expressed somatic mutations in infrequently mutated genes beyond the well-characterized ones (e.g., BRAF, RAS, CDKN2A, PTEN, TP53), such as RAC1 and SPEN, may have prognostic significance in MM

    Exceptional chemotherapy response in metastatic colorectal cancer associated with hyper-indel-hypermutated cancer genome and comutation of POLD1 and MLH1

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    Purpose A 73-year-old woman with metastatic colon cancer experienced a complete response to chemotherapy with dose-intensified irinotecan that has been durable for 5 years.Wesequenced her tumor and germ line DNA and looked for similar patterns in publicly available genomic data from patients with colorectal cancer. Patients and Methods Tumor DNA was obtained from a biopsy before therapy, and germ line DNA was obtained from blood. Tumor and germline DNA were sequenced using a commercial panel with approximately 250 genes. Whole-genome amplification and exome sequencing were performed for POLE and POLD1. A POLD1 mutation was confirmed by Sanger sequencing. The somatic mutation and clinical annotation data files from the colon (n = 461) and rectal (n = 171) adenocarcinoma data sets were downloaded from The Cancer Genome Atlas data portal and analyzed for patterns of mutations and clinical outcomes in patients withPOLE- and/orPOLD1- mutated tumors. Results The pattern of alterations included APC biallelic inactivation and microsatellite instability high (MSI-H) phenotype, with somatic inactivation of MLH1 and hypermutation (estimated mutation rate > 200 per megabase). The extremely high mutation rate led us to investigate additional mechanisms for hypermutation, including loss of function of POLE. POLE was unaltered, but a related gene not typically associated with somatic mutation in colon cancer, POLD1, had a somatic mutation c.2171G > A[p.Gly724Glu]. Additionally, we noted that the high mutation rate was largely composed of dinucleotide deletions. A similar pattern of hypermutation (dinucleotide deletions, POLD1 mutations, MSI-H) was found in tumors from The Cancer Genome Atlas. Conclusion POLD1 mutation with associated MSI-H and hyper-indel-hypermutated cancer genome characterizes a previously unrecognized variant of colon cancer that was found in this patient with an exceptional response to chemotherapy

    Comprehensive molecular characterization of urachal adenocarcinoma reveals commonalities with colorectal cancer, including a hypermutable phenotype

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    Purpose Urachal adenocarcinoma is a rare type of primary bladder adenocarcinoma that comprises less than 1% of all bladder cancers. The low incidence of urachal adenocarcinomas does not allow for an evidence-based approach to therapy. Transcriptome profiling of urachal adenocarcinomas has not been previously reported.Wehypothesized that an in-depth molecular understanding of urachal adenocarcinoma would uncover rational therapeutic strategies. Patients and Methods We performed targeted exon sequencing and global transcriptome profiling of 12 urachal tumors to generate a comprehensive molecular portrait of urachal adenocarcinoma. A single patient with an MSH6 mutation was treated with the anti-programmed death-ligand 1 antibody, atezolizumab. Results Urachal adenocarcinoma closely resembles colorectal cancer at the level of RNA expression, which extends previous observations that urachal tumors harbor genomic alterations that are found in colorectal adenocarcinoma. A subset of tumors was found to have alterations in genes that are associated with microsatellite instability (MSH2 and MSH6) and hypermutation (POLE).Apatient with anMSH6mutation was treated withimmunecheckpoint blockade, which resulted in stable disease. Conclusion Because clinical trials are next to impossible for patients with rare tumors, precision oncology may be an important adjunct for treatment decisions. Our findings demonstrate that urachal adenocarcinomas molecularly resemble colorectal adenocarcinomas at the level ofRNA expression, are the first report, to our knowledge, of MSH2andMSH6mutations in this disease, and support the consideration of immune checkpoint blockade as a rational therapeutic treatment of this exceedingly rare tumor

    Identification of clonal hematopoiesis mutations in solid tumor patients undergoing unpaired next-generation sequencing assays

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    Purpose: In this era of precision-based medicine, for optimal patient care, results reported from commercial next-generation sequencing (NGS) assays should adequately reflect the burden of somatic mutations in the tumor being sequenced. Here, we sought to determine the prevalence of clonal hematopoiesis leading to possible misattribution of tumor mutation calls on unpaired Foundation Medicine NGS assays. Experimental Design: This was a retrospective cohort study of individuals undergoing NGS of solid tumors from two large cancer centers. We identified and quantified mutations in genes known to be frequently altered in clonal hematopoiesis (DNMT3A, TET2, ASXL1, TP53, ATM, CHEK2, SF3B1, CBL, JAK2) that were returned to physicians on clinical Foundation Medicine reports. For a subset of patients, we explored the frequency of true clonal hematopoiesis by comparing mutations on Foundation Medicine reports with matched blood sequencing. Results: Mutations in genes that are frequently altered in clonal hematopoiesis were identified in 65% (1,139/1,757) of patients undergoing NGS. When excluding TP53, which is often mutated in solid tumors, these events were still seen in 35% (619/1,757) of patients. Utilizing paired blood specimens, we were able to confirm that 8% (18/226) of mutations reported in these genes were true clonal hematopoiesis events. The majority of DNMT3A mutations (64%, 7/11) and minority of TP53 mutations (4%, 2/50) were clonal hematopoiesis. Conclusions: Clonal hematopoiesis mutations are commonly reported on unpaired NGS testing. It is important to recognize clonal hematopoiesis as a possible cause of misattribution of mutation origin when applying NGS findings to a patient's care

    SCISSOR: a framework for identifying structural changes in RNA transcripts

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    High-throughput sequencing protocols such as RNA-seq have made it possible to interrogate the sequence, structure and abundance of RNA transcripts at higher resolution than previous microarray and other molecular techniques. While many computational tools have been proposed for identifying mRNA variation through differential splicing/alternative exon usage, challenges in its analysis remain. Here, we propose a framework for unbiased and robust discovery of aberrant RNA transcript structures using short read sequencing data based on shape changes in an RNA-seq coverage profile. Shape changes in selecting sample outliers in RNA-seq, SCISSOR, is a series of procedures for transforming and normalizing base-level RNA sequencing coverage data in a transcript independent manner, followed by a statistical framework for its analysis (https://github.com/hyochoi/SCISSOR). The resulting high dimensional object is amenable to unsupervised screening of structural alterations across RNA-seq cohorts with nearly no assumption on the mutational mechanisms underlying abnormalities. This enables SCISSOR to independently recapture known variants such as splice site mutations in tumor suppressor genes as well as novel variants that are previously unrecognized or difficult to identify by any existing methods including recurrent alternate transcription start sites and recurrent complex deletions in 3′ UTRs

    Enhancing Next-Generation Sequencing-Guided Cancer Care Through Cognitive Computing

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    Background: Using next-generation sequencing (NGS) to guide cancer therapy has created challenges in analyzing and reporting large volumes of genomic data to patients and caregivers. Specifically, providing current, accurate information on newly approved therapies and open clinical trials requires considerable manual curation performed mainly by human “molecular tumor boards” (MTBs). The purpose of this study was to determine the utility of cognitive computing as performed by Watson for Genomics (WfG) compared with a human MTB. Materials and Methods: One thousand eighteen patient cases that previously underwent targeted exon sequencing at the University of North Carolina (UNC) and subsequent analysis by the UNCseq informatics pipeline and the UNC MTB between November 7, 2011, and May 12, 2015, were analyzed with WfG, a cognitive computing technology for genomic analysis. Results: Using a WfG-curated actionable gene list, we identified additional genomic events of potential significance (not discovered by traditional MTB curation) in 323 (32%) patients. The majority of these additional genomic events were considered actionable based upon their ability to qualify patients for biomarker-selected clinical trials. Indeed, the opening of a relevant clinical trial within 1 month prior to WfG analysis provided the rationale for identification of a new actionable event in nearly a quarter of the 323 patients. This automated analysis took <3 minutes per case. Conclusion: These results demonstrate that the interpretation and actionability of somatic NGS results are evolving too rapidly to rely solely on human curation. Molecular tumor boards empowered by cognitive computing could potentially improve patient care by providing a rapid, comprehensive approach for data analysis and consideration of up-to-date availability of clinical trials. Implications for Practice: The results of this study demonstrate that the interpretation and actionability of somatic next-generation sequencing results are evolving too rapidly to rely solely on human curation. Molecular tumor boards empowered by cognitive computing can significantly improve patient care by providing a fast, cost-effective, and comprehensive approach for data analysis in the delivery of precision medicine. Patients and physicians who are considering enrollment in clinical trials may benefit from the support of such tools applied to genomic data

    Physical Characterization of an Unlensed, Dusty Star-forming Galaxy at z = 5.85

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    We present a physical characterization of MM J100026.36+021527.9 (a.k.a. "Mambo-9"), a dusty star-forming galaxy (DSFG) at z = 5.850 \ub1 0.001. This is the highest-redshift unlensed DSFG (and fourth most distant overall) found to date and is the first source identified in a new 2 mm blank-field map in the COSMOS field. Though identified in prior samples of DSFGs at 850 \u3bcm to 1.2 mm with unknown redshift, the detection at 2 mm prompted further follow-up as it indicated a much higher probability that the source was likely to sit at z &gt; 4. Deep observations from the Atacama Large Millimeter and submillimeter Array (ALMA) presented here confirm the redshift through the secure detection of 12CO(J = 6\u21925) and p-H2O (21,1 \u2192 20,2). Mambo-9 is composed of a pair of galaxies separated by 6 kpc with corresponding star formation rates of 590 M o\u2d9 yr-1 and 220 M o\u2d9 yr-1, total molecular hydrogen gas mass of (1.7 \ub1 0.4) 7 1011 M o\u2d9, dust mass of (1.3 \ub1 0.3) 7 109 M o\u2d9, and stellar mass of (3.2-1.5+1.0) 7 109 M o\u2d9. The total halo mass, (3.3 \ub1 0.8) 7 1012 M o\u2d9, is predicted to exceed 1015 M o\u2d9 by z = 0. The system is undergoing a merger-driven starburst that will increase the stellar mass of the system tenfold in \u3c4 depl = 40-80 Myr, converting its large molecular gas reservoir (gas fraction of 96-2+1) into stars. Mambo-9 evaded firm spectroscopic identification for a decade, following a pattern that has emerged for some of the highest-redshift DSFGs found. And yet, the systematic identification of unlensed DSFGs like Mambo-9 is key to measuring the global contribution of obscured star formation to the star formation rate density at z \u2a86 4, the formation of the first massive galaxies, and the formation of interstellar dust at early times ( 721 Gyr)

    UNMASC: Tumor-only variant calling with unmatched normal controls

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    Despite years of progress, mutation detection in cancer samples continues to require significant manual review as a final step. Expert review is particularly challenging in cases where tumors are sequenced without matched normal control DNA. Attempts have been made to call somatic point mutations without a matched normal sample by removing well-known germline variants, utilizing unmatched normal controls, and constructing decision rules to classify sequencing errors and private germline variants. With budgetary constraints related to computational and sequencing costs, finding the appropriate number of controls is a crucial step to identifying somatic variants. Our approach utilizes public databases for canonical somatic variants as well as germline variants and leverages information gathered about nearby positions in the normal controls. Drawing from our cohort of targeted capture panel sequencing of tumor and normal samples with varying tumortypes and demographics, these served as a benchmark for our tumor-only variant calling pipeline to observe the relationship between our ability to correctly classify variants against a number of unmatched normals. With our benchmarked samples, approximately ten normal controls were needed to maintain 94% sensitivity, 99% specificity and 76% positive predictive value, far outperforming comparable methods. Our approach, called UNMASC, also serves as a supplement to traditional tumor with matched normal variant calling workflows and can potentially extend to other concerns arising from analyzing next generation sequencing data
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