Which genetic alterations drive tumorigenesis and how they evolve over the course of disease and therapy are central questions in cancer biology. Here we identify 44 recurrently mutated genes and 11 ...recurrent somatic copy number variations through whole-exome sequencing of 538 chronic lymphocytic leukaemia (CLL) and matched germline DNA samples, 278 of which were collected in a prospective clinical trial. These include previously unrecognized putative cancer drivers (RPS15, IKZF3), and collectively identify RNA processing and export, MYC activity, and MAPK signalling as central pathways involved in CLL. Clonality analysis of this large data set further enabled reconstruction of temporal relationships between driver events. Direct comparison between matched pre-treatment and relapse samples from 59 patients demonstrated highly frequent clonal evolution. Thus, large sequencing data sets of clinically informative samples enable the discovery of novel genes associated with cancer, the network of relationships between the driver events, and their impact on disease relapse and clinical outcome.
Cancer genomes contain large numbers of somatic mutations but few of these mutations drive tumor development. Current approaches either identify driver genes on the basis of mutational recurrence or ...approximate the functional consequences of nonsynonymous mutations by using bioinformatic scores. Passenger mutations are enriched in characteristic nucleotide contexts, whereas 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 according to mutations in unusual nucleotide contexts.
Abstract Background & Aims Early-onset gastric cancer, which develops in younger patients than most gastric cancers, is usually detected at advanced stages, has diffuse histologic features, and ...occurs more frequently in women. We investigated somatic genomic alterations associated with the unique characteristics of sporadic diffuse gastric cancers (DGCs) from younger patients. Methods We conducted whole exome and RNA sequence analyses of 80 resected DGC samples from patients 45 years old or younger in Korea. Patients with pathogenic germline mutations in CDH1 , TP53 , and ATM were excluded from the onset of this analysis, given our focus on somatic alterations. We used MutSig2CV to evaluate the significance of mutated genes. We recruited 29 additional early-onset Korean DGC samples and performed SNP6.0 array and targeted sequencing analyses of these 109 early-onset DGC samples (54.1% female, median age of 38 years). We compared the SNP6.0 array and targeted sequencing data of the 109 early-onset DGC samples with those from diffuse-type stomach tumor samples collected from 115 patients in Korea who were 46 years or older (late-onset) at the time of diagnosis (controls; 29.6% female, median age of 67 years). We compared patient survival times among tumors from different subgroups and with different somatic mutations. We performed gene silencing of RHOA or CDH1 in DGC cells with small interfering RNAs for cell-based assays. Results We identified somatic mutations in the following genes in a significant number of early-onset DGCs: the cadherin 1 gene ( CDH1 ), TP53, ARID1A, KRAS, PIK3CA, ERBB3, TGFBR1, FBXW7, RHOA, and MAP2K1 . None of 109 early-onset DGC cases had pathogenic germline CDH1 mutations. A higher proportion of early-onset DGCs had mutations in CDH1 (42.2%) or TGFBR1 (7.3%) compared with control DGCs (17.4% and 0.9%, respectively) (P<0.001 and 0.014 for CDH1 and TGFBR1 , respectively). In contrast, a smaller proportion of early-onset DGCs contained mutations in RHOA (9.2%) than control DGCs (19.1%) (P=0.033). Late-onset DGCs in the Cancer Genome Atlas also contained less frequent mutations in CDH1 and TGFBR1 and more frequent RHOA mutations, compared with early-onset DGCs. Early-onset DGCs from women contained significantly more mutations in CDH1 or TGFBR1 than early-onset DGCs from men. CDH1 alterations, but not RHOA mutations, were associated with shorter survival times of patients with early-onset DGCs (hazard ratio, 3.4 (95% CI, 1.5–7.7)). RHOA activity was reduced by an R5W substitution—the RHOA mutation most frequently detected in early-onset DGCs. Silencing of CDH1 , but not RHOA , increased migratory activity of DGC cells. Conclusions In an integrative genomic analysis, we found higher proportions of early-onset DGCs to contain somatic mutations in CDH1 or TGFBR1 compared with late-onset DGCs. However, a smaller proportion of early-onset DGCs contained somatic mutations in RHOA than late-onset DGCs. CDH1 alterations, but not RHOA mutations, were associated with shorter survival times of patients, which might account for the aggressive clinical course of early-onset gastric cancer. Female predominance in early-onset gastric cancer may be related to relatively high rates of somatic CDH1 and TGFBR1 mutations in this population.
Traumatic brain injury (TBI) is a major risk factor for developing pharmaco-resistant epilepsy. Although disruptions in brain circuitry are associated with TBI, the precise mechanisms by which brain ...injury leads to epileptiform network activity is unknown. Using controlled cortical impact (CCI) as a model of TBI, we examined how cortical excitability and glutamatergic signaling was altered following injury. We optically mapped cortical glutamate signaling using FRET-based glutamate biosensors, while simultaneously recording cortical field potentials in acute brain slices 2-4 weeks following CCI. Cortical electrical stimulation evoked polyphasic, epileptiform field potentials and disrupted the input-output relationship in deep layers of CCI-injured cortex. High-speed glutamate biosensor imaging showed that glutamate signaling was significantly increased in the injured cortex. Elevated glutamate responses correlated with epileptiform activity, were highest directly adjacent to the injury, and spread via deep cortical layers. Immunoreactivity for markers of GABAergic interneurons were significantly decreased throughout CCI cortex. Lastly, spontaneous inhibitory postsynaptic current frequency decreased and spontaneous excitatory postsynaptic current increased after CCI injury. Our results suggest that specific cortical neuronal microcircuits may initiate and facilitate the spread of epileptiform activity following TBI. Increased glutamatergic signaling due to loss of GABAergic control may provide a mechanism by which TBI can give rise to post-traumatic epilepsy.
Juvenile myelomonocytic leukemia (JMML) is an aggressive myeloproliferative neoplasm of childhood associated with a poor prognosis. Recently, massively parallel sequencing has identified recurrent ...mutations in the SKI domain of SETBP1 in a variety of myeloid disorders. These lesions were detected in nearly 10% of patients with JMML and have been characterized as secondary events. We hypothesized that rare subclones with SETBP1 mutations are present at diagnosis in a large portion of patients who relapse, but are below the limits of detection for conventional deep sequencing platforms. Using droplet digital polymerase chain reaction, we identified SETBP1 mutations in 17/56 (30%) of patients who were treated in the Children's Oncology Group sponsored clinical trial, AAML0122. Five-year event-free survival in patients with SETBP1 mutations was 18% ± 9% compared with 51% ± 8% for those without mutations (P = .006).
•Mutations in SETBP1 can be detected using droplet digital polymerase chain reaction in at least 30% of patients with JMML and are associated with a dismal prognosis.•Patients harboring rare cells with mutant SETBP1 at diagnosis should be considered candidates for swift hematopoietic stem cell transplant.
Current genomics methods are designed to handle tens to thousands of samples but will need to scale to millions to match the pace of data and hypothesis generation in biomedical science. Here, we ...show that high efficiency at low cost can be achieved by leveraging general-purpose libraries for computing using graphics processing units (GPUs), such as PyTorch and TensorFlow. We demonstrate > 200-fold decreases in runtime and ~ 5-10-fold reductions in cost relative to CPUs. We anticipate that the accessibility of these libraries will lead to a widespread adoption of GPUs in computational genomics.
Computational methods have made substantial progress in improving the accuracy and throughput of pathology workflows for diagnostic, prognostic, and genomic prediction. Still, lack of ...interpretability remains a significant barrier to clinical integration. We present an approach for predicting clinically-relevant molecular phenotypes from whole-slide histopathology images using human-interpretable image features (HIFs). Our method leverages >1.6 million annotations from board-certified pathologists across >5700 samples to train deep learning models for cell and tissue classification that can exhaustively map whole-slide images at two and four micron-resolution. Cell- and tissue-type model outputs are combined into 607 HIFs that quantify specific and biologically-relevant characteristics across five cancer types. We demonstrate that these HIFs correlate with well-known markers of the tumor microenvironment and can predict diverse molecular signatures (AUROC 0.601-0.864), including expression of four immune checkpoint proteins and homologous recombination deficiency, with performance comparable to 'black-box' methods. Our HIF-based approach provides a comprehensive, quantitative, and interpretable window into the composition and spatial architecture of the tumor microenvironment.
Barrett's esophagus is thought to progress to esophageal adenocarcinoma (EAC) through a stepwise progression with loss of CDKN2A followed by TP53 inactivation and aneuploidy. Here we present ...whole-exome sequencing from 25 pairs of EAC and Barrett's esophagus and from 5 patients whose Barrett's esophagus and tumor were extensively sampled. Our analysis showed that oncogene amplification typically occurred as a late event and that TP53 mutations often occurred early in Barrett's esophagus progression, including in non-dysplastic epithelium. Reanalysis of additional EAC exome data showed that the majority (62.5%) of EACs emerged following genome doubling and that tumors with genomic doubling had different patterns of genomic alterations, with more frequent oncogenic amplification and less frequent inactivation of tumor suppressors, including CDKN2A. These data suggest that many EACs emerge not through the gradual accumulation of tumor-suppressor alterations but rather through a more direct path whereby a TP53-mutant cell undergoes genome doubling, followed by the acquisition of oncogenic amplifications.
Everolimus, an inhibitor of the mammalian target of rapamycin (mTOR), is effective in treating tumors harboring alterations in the mTOR pathway. Mechanisms of resistance to everolimus remain ...undefined. Resistance developed in a patient with metastatic anaplastic thyroid carcinoma after an extraordinary 18-month response. Whole-exome sequencing of pretreatment and drug-resistant tumors revealed a nonsense mutation in TSC2, a negative regulator of mTOR, suggesting a mechanism for exquisite sensitivity to everolimus. The resistant tumor also harbored a mutation in MTOR that confers resistance to allosteric mTOR inhibition. The mutation remains sensitive to mTOR kinase inhibitors.
Small cell lung carcinoma (SCLC) is a highly lethal, smoking-associated cancer with few known targetable genetic alterations. Using genome sequencing, we characterized the somatic evolution of a ...genetically engineered mouse model (GEMM) of SCLC initiated by loss of Trp53 and Rb1. We identified alterations in DNA copy number and complex genomic rearrangements and demonstrated a low somatic point mutation frequency in the absence of tobacco mutagens. Alterations targeting the tumor suppressor Pten occurred in the majority of murine SCLC studied, and engineered Pten deletion accelerated murine SCLC and abrogated loss of Chr19 in Trp53; Rb1; Pten compound mutant tumors. Finally, we found evidence for polyclonal and sequential metastatic spread of murine SCLC by comparative sequencing of families of related primary tumors and metastases. We propose a temporal model of SCLC tumorigenesis with implications for human SCLC therapeutics and the nature of cancer-genome evolution in GEMMs.
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•Murine SCLCs acquire few point mutations in the absence of tobacco mutagens•Pten is recurrently mutated, and engineered deletion accelerates tumor progression•Mycl1 amplifications play an early, central role in mSCLC tumorigenesis•Analysis of related primary and metastatic mSCLC suggests complex clonal evolution
Comprehensive genomic analysis in a mouse model of small-cell lung carcinoma delineates metastatic progression in this tumor type, showing that selection for specific cancer mutations can drive large genomic rearrangements and that distant metastases likely arise from a common metastatic seeding step involving the lymph nodes.
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