Comprehensive Characterization of Cancer Driver Genes and Mutations.

Identifying molecular cancer drivers is critical for precision oncology. Multiple advanced algorithms to identify drivers now exist, but systematic attempts to combine and optimize them on large datasets are few. We report a PanCancer and PanSoftware analysis spanning 9,423 tumor exomes (comprising all 33 of The Cancer Genome Atlas projects) and using 26 computational tools to catalog driver genes and mutations. We identify 299 driver genes with implications regarding their anatomical sites and cancer/cell types. Sequence- and structure-based analyses identified >3,400 putative missense driver mutations supported by multiple lines of evidence. Experimental validation confirmed 60%-85% of predicted mutations as likely drivers. We found that >300 MSI tumors are associated with high PD-1/PD-L1, and 57% of tumors analyzed harbor putative clinically actionable events. Our study represents the most comprehensive discovery of cancer genes and mutations to date and will serve as a blueprint for future biological and clinical endeavors.

GenomeVIP: a cloud platform for genomic variant discovery and interpretation.

Identifying genomic variants is a fundamental first step toward the understanding of the role of inherited and acquired variation in disease. The accelerating growth in the corpus of sequencing data that underpins such analysis is making the data-download bottleneck more evident, placing substantial burdens on the research community to keep pace. As a result, the search for alternative approaches to the traditional "download and analyze" paradigm on local computing resources has led to a rapidly growing demand for cloud-computing solutions for genomics analysis. Here, we introduce the Genome Variant Investigation Platform (GenomeVIP), an open-source framework for performing genomics variant discovery and annotation using cloud- or local high-performance computing infrastructure. GenomeVIP orchestrates the analysis of whole-genome and exome sequence data using a set of robust and popular task-specific tools, including VarScan, GATK, Pindel, BreakDancer, Strelka, and Genome STRiP, through a web interface. GenomeVIP has been used for genomic analysis in large-data projects such as the TCGA PanCanAtlas and in other projects, such as the ICGC Pilots, CPTAC, ICGC-TCGA DREAM Challenges, and the 1000 Genomes SV Project. Here, we demonstrate GenomeVIP's ability to provide high-confidence annotated somatic, germline, and de novo variants of potential biological significance using publicly available data sets.

Stability and uniqueness of clonal immunoglobulin CDR3 sequences for MRD tracking in multiple myeloma.

Minimal residual disease (MRD) tracking, by next generation sequencing of immunoglobulin sequences, is moving towards clinical implementation in multiple myeloma. However, there is only sparse information available to address whether clonal sequences remain stable for tracking over time, and to what extent light chain sequences are sufficiently unique for tracking. Here, we analyzed immunoglobulin repertoires from 905 plasma cell myeloma and healthy control samples, focusing on the third complementarity determining region (CDR3). Clonal heavy and/or light chain expression was identified in all patients at baseline, with one or more subclones related to the main clone in 3.2%. In 45 patients with 101 sequential samples, the dominant clonal CDR3 sequences remained identical over time, despite differential clonal evolution by whole exome sequencing in 49% of patients. The low frequency of subclonal CDR3 variants, and absence of evolution over time in active multiple myeloma, indicates that tumor cells at this stage are not under selective pressure to undergo antibody affinity maturation. Next, we establish somatic hypermutation and non-templated insertions as the most important determinants of light chain clonal uniqueness, identifying a potentially trackable sequence in the majority of patients. Taken together, we show that dominant clonal sequences identified at baseline are reliable biomarkers for long-term tracking of the malignant clone, including both IGH and the majority of light chain clones.

Molecular Evolution of Classic Hodgkin Lymphoma Revealed Through Whole-Genome Sequencing of Hodgkin and Reed Sternberg Cells.

The rarity of malignant Hodgkin and Reed Sternberg (HRS) cells in classic Hodgkin lymphoma (cHL) limits the ability to study the genomics of cHL. To circumvent this, our group has previously optimized fluorescence-activated cell sorting to purify HRS cells. Using this approach, we now report the whole-genome sequencing landscape of HRS cells and reconstruct the chronology and likely etiology of pathogenic events leading to cHL. We identified alterations in driver genes not previously described in cHL, APOBEC mutational activity, and the presence of complex structural variants including chromothripsis. We found that high ploidy in cHL is often acquired through multiple, independent chromosomal gains events including whole-genome duplication. Evolutionary timing analyses revealed that structural variants enriched for RAG motifs, driver mutations in B2M, BCL7A, GNA13, and PTPN1, and the onset of AID-driven mutagenesis usually preceded large chromosomal gains. This study provides a temporal reconstruction of cHL pathogenesis. SIGNIFICANCE: Previous studies in cHL were limited to coding sequences and therefore not able to comprehensively decipher the tumor complexity. Here, leveraging cHL whole-genome characterization, we identify driver events and reconstruct the tumor evolution, finding that structural variants, driver mutations, and AID mutagenesis precede chromosomal gains. This article is highlighted in the In This Issue feature, p. 171.

Initial Whole-Genome Sequencing of Plasma Cell Neoplasms in First Responders and Recovery Workers Exposed to the World Trade Center Attack of September 11, 2001.

PURPOSE: The World Trade Center (WTC) attack of September 11, 2001 created an unprecedented environmental exposure to known and suspected carcinogens. High incidence of multiple myeloma and precursor conditions has been reported among first responders to the WTC disaster. To expand on our prior screening studies, and to characterize the genomic impact of the exposure to known and potential carcinogens in the WTC debris, we were motivated to perform whole-genome sequencing (WGS) of WTC first responders and recovery workers who developed a plasma cell disorder after the attack. EXPERIMENTAL DESIGN: We performed WGS of nine CD138-positive bone marrow mononuclear samples from patients who were diagnosed with plasma cell disorders after the WTC disaster. RESULTS: No significant differences were observed in comparing the post-WTC driver and mutational signature landscapes with 110 previously published WGSs from 56 patients with multiple myeloma and the CoMMpass WGS cohort (n = 752). Leveraging constant activity of the single-base substitution mutational signatures 1 and 5 over time, we estimated that tumor-initiating chromosomal gains were windowed to both pre- and post-WTC exposure. CONCLUSIONS: Although limitations in sample size preclude any definitive conclusions, our findings suggest that the observed increased incidence of plasma cell neoplasms in this population is due to complex and heterogeneous effects of the WTC exposure that may have initiated or contributed to progression of malignancy.

Revealing the impact of structural variants in multiple myeloma.

The landscape of structural variants (SVs) in multiple myeloma remains poorly understood. Here, we performed comprehensive analysis of SVs in a large cohort of 752 multiple myeloma patients by low coverage long-insert whole genome sequencing. We identified 68 SV hotspots involving 17 new candidate driver genes, including the therapeutic targets BCMA (TNFRSF17), SLAMF and MCL1. Catastrophic complex rearrangements termed chromothripsis were present in 24% of patients and independently associated with poor clinical outcomes. Templated insertions were the second most frequent complex event (19%), mostly involved in super-enhancer hijacking and activation of oncogenes such as CCND1 and MYC. Importantly, in 31% of patients two or more seemingly independent putative driver events were caused by a single structural event, demonstrating that the complex genomic landscape of multiple myeloma can be acquired through few key events during tumor evolutionary history. Overall, this study reveals the critical role of SVs in multiple myeloma pathogenesis.

Baseline identification of clonal V(D)J sequences for DNA-based minimal residual disease detection in multiple myeloma.

Tracking of clonal immunoglobulin V(D)J rearrangement sequences by next generation sequencing is highly sensitive for minimal residual disease in multiple myeloma. However, previous studies have found variable rates of V(D)J sequence identification at baseline, which could limit tracking. Here, we aimed to define the factors influencing the identification of clonal V(D)J sequences. Bone marrow mononuclear cells from 177 myeloma patients underwent V(D)J sequencing by the LymphoTrack assays (Invivoscribe). As a molecular control for tumor cell content, we sequenced the samples using our in-house myeloma panel myTYPE. V(D)J sequence clonality was identified in 81% of samples overall, as compared with 95% in samples where tumor-derived DNA was detectable by myTYPE. Clonality was detected more frequently in patients with lambda-restricted disease, mainly because of increased detection of kappa gene rearrangements. Finally, we describe how the tumor cell content of bone marrow aspirates decrease gradually in sequential pulls because of hemodilution: From the initial pull used for aspirate smear, to the final pull that is commonly used for research. In conclusion, baseline clonality detection rates of 95% or higher are feasible in multiple myeloma. Optimal performance depends on the use of good quality aspirates and/or subsequent tumor cell enrichment.

Patient-Driven Discovery, Therapeutic Targeting, and Post-Clinical Validation of a Novel AKT1 Fusion-Driven Cancer.

Despite the important role of the PI3K/AKT/mTOR axis in the pathogenesis of cancer, to date there have been few functional oncogenic fusions identified involving the AKT genes. A 12-year-old female with a histopathologically indeterminate epithelioid neoplasm was found to harbor a novel fusion between the LAMTOR1 and AKT1 genes. Through expanded use access, she became the first pediatric patient to be treated with the oral ATP-competitive pan-AKT inhibitor ipatasertib. Treatment resulted in dramatic tumor regression, demonstrating through patient-driven discovery that the fusion resulted in activation of AKT1, was an oncogenic driver, and could be therapeutically targeted with clinical benefit. Post-clinical validation using patient-derived model systems corroborated these findings, confirmed a membrane-bound and constitutively active fusion protein, and identified potential mechanisms of resistance to single-agent treatment with ipatasertib. SIGNIFICANCE: This study describes the patient-driven discovery of the first AKT1 fusion-driven cancer and its treatment with the AKT inhibitor ipatasertib. Patient-derived in vitro and in vivo model systems are used to confirm the LAMTOR1-AKT1 fusion as a tumorigenic driver and identify potential mechanisms of resistance to AKT inhibition.This article is highlighted in the In This Issue feature, p. 565.