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Supplementary Figure 1 depicts copy number alterations in the described cohort

Supplementary Table 2

Supplementary Methods

Supplementary Table 3

Supplementary Figures and Legends

Supplementary Table 1 shows point mutations found in DSRCT samples

Supplementary Figure 3 provides a breakdown of the structural variant types found via whole genome sequencing in DSRCT samples

Supplementary Figure 2 depicts whole genome sequencing findings

Supplementary Table 5

Desmoplastic small round cell tumor (DSRCT) is characterized by the EWSR1–WT1 t(11;22) (p13:q12) translocation. Few additional putative drivers have been identified, and research has suffered from a lack of model systems. Next-generation sequencing (NGS) data from 68 matched tumor-normal samples, whole-genome sequencing data from 10 samples, transcriptomic and affymetrix array data, and a bank of DSRCT patient-derived xenograft (PDX) are presented. EWSR1–WT1 fusions were noted to be simple, balanced events. Recurrent mutations were uncommon, but were noted in TERT (3%), ARID1A (6%), HRAS (5%), and TP53 (3%), and recurrent loss of heterozygosity (LOH) at 11p, 11q, and 16q was identified in 18%, 22%, and 34% of samples, respectively. Comparison of tumor-normal matched versus unmatched analysis suggests overcalling of somatic mutations in prior publications of DSRCT NGS data. Alterations in fibroblast growth factor receptor 4 (FGFR4) were identified in 5 of 68 (7%) of tumor samples, whereas differential overexpression of FGFR4 was confirmed orthogonally using 2 platforms. PDX models harbored the pathognomic EWSR1–WT1 fusion and were highly representative of corresponding tumors. Our analyses confirm DSRCT as a genomically quiet cancer defined by the balanced translocation, t(11;22)(p13:q12), characterized by a paucity of secondary mutations but a significant number of copy number alterations. Against this genomically quiet background, recurrent activating alterations of FGFR4 stood out, and suggest that this receptor tyrosine kinase, also noted to be highly expressed in DSRCT, should be further investigated. Future studies of DSRCT biology and preclinical therapeutic strategies should benefit from the PDX models characterized in this study.Implications:These data describe the general quiescence of the desmoplastic small round cell tumor (DSRCT) genome, present the first available bank of DSRCT model systems, and nominate FGFR4 as a key receptor tyrosine kinase in DSRCT, based on high expression, recurrent amplification, and recurrent activating mutations.

Supplementary Figure 4 shows data related to FGFR4 inhibition in DSRCT and control models

Supplementary Table 4

Supplementary Table 2 shows the raw data further described in Figure 3

Supplementary Table 1

Supplementary Data from Bone Marrow Surveillance of Pediatric Cancer Survivors Identifies Clones that Predict Therapy-Related Leukemia

Supplementary Figure from Bone Marrow Surveillance of Pediatric Cancer Survivors Identifies Clones that Predict Therapy-Related Leukemia

Genomic profiling at diagnosis of B-cell precursor Acute Lymphoblastic Leukemia (BCP-ALL) in adults is used to guide disease classification, risk stratification and treatment decisions. Patients for which diagnostic screening fails to identify disease defining or risk stratifying lesions are classified as B-other ALL. We screened a cohort of 652 BCP-ALL cases enrolled in UKALL14 to identify and perform whole genome sequencing (WGS) on paired tumor-normal samples. For 52 B-other patients we compared WGS findings to data from clinical and research cytogenetics. WGS identifies a cancer associated event in 51/52 cases, this includes an established subtype defining genetic alteration in 5/52 that were previously missed by standard-of-care genetics. Of the 47 true B-other ALL we identified a recurrent driver in 87% (41). Complex karyotype by cytogenetics emerges as a heterogeneous group, including distinct genetic alterations associated with either favorable (DUX4-r) or poor outcomes (MEF2D-r, IGK::BCL2). For a subset of 31 cases, we integrate findings from RNA-sequencing (RNA-seq) analysis to include fusion gene detection, and classification by gene expression. Compared to RNA-seq, WGS was sufficient to detect and resolve recurrent genetic subtypes, however RNA-seq can provide orthogonal validation of findings. In conclusion, we demonstrate that WGS can identify clinically relevant genetic abnormalities missed by standard-of-care testing and identify leukemia driver events in virtually all cases of B-other ALL.

Multiple large-scale tumor genomic profiling efforts have been undertaken in osteosarcoma, however, little is known about the spatial and temporal intratumor heterogeneity and how it may drive treatment resistance. We performed whole-genome sequencing of 37 tumor samples from eight patients with relapsed or refractory osteosarcoma. Each patient had at least one sample from a primary site and a metastatic or relapse site. We identified subclonal copy number alterations in all but one patient. We observed that in five patients, a subclonal copy number clone from the primary tumor emerged and dominated at subsequent relapses.MYCgain/amplification was enriched in the treatment-resistant clone in 6 out of 7 patients with more than one clone. Amplifications in other potential driver genes, such asCCNE1,RAD21,VEGFA, andIGF1R, were also observed in the resistant copy number clones. Our study sheds light on intratumor heterogeneity and the potential drivers of treatment resistance in osteosarcoma.SignificanceSubclonal copy number clones emerged and dominated in relapsed osteosarcoma, withMYCgain/amplification being the defining characteristic in our cohort. Selective pressure from neoadjuvant chemotherapy revealed this clone at the time of primary resection, highlighting that genomic profiling at this time may identify clones that are selected for, or determine innate resistance to primary chemotherapy.

High-risk neuroblastoma is generally metastatic and often lethal. Using genomic profiling of 470 sequential and spatially separated samples from 283 patients, we characterize subtype-specific genetic evolutionary trajectories from diagnosis, through progression and end-stage metastatic disease. Clonal tracing timed disease initiation to embryogenesis. Continuous acquisition of structural variants at disease defining loci (MYCN, TERT, MDM2-CDK4) followed by convergent evolution of mutations targeting shared pathways emerged as the predominant feature of progression. At diagnosis metastatic clones were already established at distant sites where they could stay dormant, only to cause relapses years later and spread via metastasis-to-metastasis and polyclonal seeding after therapy.

Desmoplastic small round cell tumor (DSRCT) is characterized by the EWSR1–WT1 t(11;22) (p13:q12) translocation. Few additional putative drivers have been identified, and research has suffered from a lack of model systems. Next-generation sequencing (NGS) data from 68 matched tumor-normal samples, whole-genome sequencing data from 10 samples, transcriptomic and affymetrix array data, and a bank of DSRCT patient-derived xenograft (PDX) are presented. EWSR1–WT1 fusions were noted to be simple, balanced events. Recurrent mutations were uncommon, but were noted in TERT (3%), ARID1A (6%), HRAS (5%), and TP53 (3%), and recurrent loss of heterozygosity (LOH) at 11p, 11q, and 16q was identified in 18%, 22%, and 34% of samples, respectively. Comparison of tumor-normal matched versus unmatched analysis suggests overcalling of somatic mutations in prior publications of DSRCT NGS data. Alterations in fibroblast growth factor receptor 4 (FGFR4) were identified in 5 of 68 (7%) of tumor samples, whereas differential overexpression of FGFR4 was confirmed orthogonally using 2 platforms. PDX models harbored the pathognomic EWSR1–WT1 fusion and were highly representative of corresponding tumors. Our analyses confirm DSRCT as a genomically quiet cancer defined by the balanced translocation, t(11;22)(p13:q12), characterized by a paucity of secondary mutations but a significant number of copy number alterations. Against this genomically quiet background, recurrent activating alterations of FGFR4 stood out, and suggest that this receptor tyrosine kinase, also noted to be highly expressed in DSRCT, should be further investigated. Future studies of DSRCT biology and preclinical therapeutic strategies should benefit from the PDX models characterized in this study.Implications:These data describe the general quiescence of the desmoplastic small round cell tumor (DSRCT) genome, present the first available bank of DSRCT model systems, and nominate FGFR4 as a key receptor tyrosine kinase in DSRCT, based on high expression, recurrent amplification, and recurrent activating mutations.

Whole genome sequencing (WGS) enables the identification of all cancer associated biomarkers in a patient’s tumor genome. Whilst fresh frozen (FF) derived WGS data provides optimal data quality, the majority of clinical biospecimens are from formalin fixed paraffin embedded (FFPE) tissue which results in DNA damage and an increase in artifactual mutation calls. Development of analytical frameworks tailored to FFPE derived WGS data can unlock the potential of genome profiling in clinical oncology. We performed comprehensive WGS analysis on 58 matched FF/FFPE specimens derived from 3 cancer centers. Consensus calling detected high-confidence somatic mutations across variant classes including: single nucleotide variants (SNVs), insertions/deletions (indels), structural variants (SVs) and copy number aberrations (CNAs). For each sample, genome-wide mutational patterns including tumor mutational burden (TMB), SNV/indel signatures, and homologous recombination deficiency (HRD) scores were estimated. We developed a random forest based framework using 33 features to learn mutation patterns associated with FFPE artifacts and implemented a filtration strategy for FFPE derived WGS data within a clinical prototype analytical workflow. We identified a high degree of concordance (~91%, n=192/210) for oncogenic variants between FF/FFPE WGS data. Comparison of small mutation calls presented an average 2-fold increase in FFPE samples with a range up to 152x for SNVs and 43x for indels. However, this was not the case for SVs: -0.4x (range -0.8-1.4). We demonstrate that genome-wide mutation patterns were significantly affected, impacting estimates for TMB, HRD and signature contributions. On average, TMB was overestimated in FFPE (median=10.3, range: 1.4-94) versus FF (median=3.4, range:0.04-29.6). For 7 patients with evidence of HRD in FF, HRD scores did not reach statistical significance in FFPE. Mutational signatures in FFPE were enriched for COSMIC signatures 37 and 5. Our artifact classification model achieved ROC AUC of 97.5% and precision-recall of 98.9%. Post artifact filtration, precision in SNV/indel calling was increased from 49.3% to 93.4% and 61.8% to 82.7% respectively with no effect on driver alterations. This increased global signal concordance drastically, with comparable TMB scores (median 2.4; range .03-26.1) and improved cosine similarity for SNV/indel signatures (median 0.98; range 0.40-1). HRD was successfully detected in 7/7 patients from FFPE derived data post filtering with probability scores ranging from 0.76-1. We demonstrate that FFPE specimens harbor a variable increase in artifactual mutation burden in SNV/indels but not in SVs. We propose an effective filtering procedure which successfully removes FFPE related artifacts enabling accurate profiling of clinically relevant driver mutations and genome-wide mutation patterns from readily available FFPE-derived tumor specimens. Citation Format: Dylan Domenico, Gunes Gundem, Max F. Levine, Juanes E. Arango-Ossa, Pauline Robbe, Georgios Asimomitis, Cassidy Cobbs, Emily Stockfisch, Janine Senz, Dawn Cochrane, Neeman Mohibullah, Neerav Shukla, Sohrab P. Shah, Andrew McPherson, Anna Schuh, Andrew L. Kung, Elli Papaemmanuil. Enabling whole genome sequencing analysis from FFPE specimens in clinical oncology [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3142.

Homologous recombination deficiency (HRd) is a DNA repair defect prevalent in but not exclusive to breast and ovarian cancer most commonly associated with BRCA1 or BRCA2 alterations. HRd results in accumulation of small and large scale genetic alterations across the genome, including allele specific copy number alterations (aCNAs), small nucleotide variants (SNVs), deletions, and structural variants (SVs). Detection of HRd in tumors predicts response to genotoxic drugs such as PARP inhibitors and platinum. Genome wide aCNAs such as large state transitions (LST), loss of heterozygosity (LOH), and telomeric allelic imbalances (TAI) in conjunction with BRCA1/2 mutation detection have been implemented in routine diagnostic testing to identify HRd in tumors. However, these features represent a subset of the genetic signatures predictive of HRd, and we hypothesize that a significant portion of tumors with HRd are missed using these existing assays. Whole genome sequencing (WGS) enables the detection of the full spectrum of genetic lesions that arise in an HRd tumor in a single assay. To demonstrate the added value of WGS to identify HRd, we trained and validated a pan-cancer classifier of HRd. A tumor/normal matched cohort of 321 cancer patients sequenced by WGS was assembled and analyzed as part of a retrospective study, representing 62 tumor types. An unbiased analysis of HRd associated SV signatures revealed the top quartile of samples harboring tandem duplications (Dups) and deletions (Dels) in the size range of 1-10kbp were enriched with BRCA1, BRCA2, and RAD51C/D alterations. Through curating Dels, Dups, HRd SNV/InDel signatures, and alteration of HRd associated genes, 37 unique patients were found to have high confidence HRd, out of which 13% had no alterations in BRCA1, BRCA2, or other HRd genes. We then trained a random forest classifier to identify HRd tumors. The most important predictive features were WGS-specific, namely small deletions with microhomology, SV Dels, and SV Dups. The HRd classifier was validated using an independent cohort of 556 samples from the Pan-Cancer Analysis of Whole Genomes (PCAWG) study. Of 46 samples with biallelic BRCA1/2 alterations, the classifier achieved high areas under receiver-operator characteristic (AUROC, 0.99) and precision recall curves (AUPRC, 0.96). The aCNA score, the number of segments harboring LST, LOH, and TAI, had similar AUROC (0.96) but lower AUPRC (0.87). There were 11 BRCA1/2 non-altered cases predicted to be HRd with the classifier which were not identified by CNA scores, in which 10 had at least 1 alteration in an HRd gene, including RAD51C, CHEK2 biallelic alterations and SVs in PALB2, Fanconi pathway genes, and ATM/ATR. We conclude that a classifier incorporating the additional mutational features which can only be detected using WGS can achieve superior precision in identifying HRd tumors and, in the future, uncover additional patients for therapeutic options. Citation Format: Kevin Hadi, Gunes Gundem, Max F. Levine, Aditya Deshpande, Minal Patel, Stan Skzrypczak, Majd Al Assaad, Juan Miguel Mosquera, Olivier Elemento, Andrew L. Kung, Juan S. Medina-Martínez, Elli Papaemmanuil. A whole genome sequencing classifier of homologous recombination deficiency [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2149.

Objective: The osteosarcoma genome is characterized by high levels of genomic instability, however whether there is pervasive ongoing genomic instability, or instability introduced by an early catastrophic event, is still unsettled. Methods: We performed 30-80x whole genome sequencing (WGS) of 37 tumor samples from 8 patients with relapsed or refractory osteosarcoma. Each patient had at least one sample from a primary site and one sample from a metastatic or relapse site. A set of high confidence single nucleotide variants (SNV), copy number alterations (CNA), structural variations (SV) were called for each sample using our pediatric expanded genomics pipeline and an analysis focused on markers of genomic instability was performed using a custom pipeline of computational tools. Results: Of the 8 patients in our cohort, 4 had localized disease at diagnosis (OSCE4, OSCE5, OSCE6, OSCE9) and 4 had metastatic disease at diagnosis (OSCE1, OSCE2, OSCE3, OSCE10). There were 17 samples from primary sites, 7 pretreatment biopsies, 10 on therapy primary resections, 20 metastatic sites, 15 of which were from lung metastases. We have previously reported on the clonal evolution regarding SNVs and CNAs within this cohort. TP53 structural variants involving intron 1/2 were seen in 6/8 patients (OSCE2, OSCE3, OSCE4, OSCE6, OSCE9, OSCE10). No new structural variants in consensus driver genes emerged in metastatic or relapse samples. Comparing the earliest sample to most recent sample in each patient, only OSCE1, OSCE9, and OSCE10 demonstrated an increase of ≥100 structural variants at the final timepoint. In OSCE2, OSCE5, and OSCE6, there were less structural variants identified at the final timepoint when compared to the earliest timepoint. Homologous recombination deficiency (HRD) scores were calculated for each sample. Only 4/8 patients (OSCE3, OSCE4, OSCE9, OSCE10) had an HRD score in the most recently acquired sample higher than the score from the primary site. Regions of hypermutation consistent with kataegis were identified for each sample, with the number of kataegis events remaining unchanged or decreasing in some instances. Kataegis events co-localized with rearrangement events a majority of the time (range 50-100%, Avg= 72.6%). Complex rearrangements such as chromothripsis and chromoplexy were assesed. In 6 patients there were > 9 chromosomal arms involved in complex rearrangements that were shared between primary sites and metastatic/recurrent sites, while ≤ 4 chromosomal arms were involved with new complex rearrangements unique to the metastatic sites. Conclusion: The patterns observed in our cohort reveal that osteosarcoma is relatively stable from diagnosis through subsequent relapses, supporting the model that an early catastrophic event accounts for the genomic instability observed in osteosarcoma. Citation Format: Michael David Kinnaman, Simone Zaccaria, Alvin Makohon-Moore, Gunes Gundem, Juan E. Arango Ossa, Filemon S. Dela Cruz, Paul A. Meyers, Meera Hameed, William D. Tap, Julia Lynne Glade Bender, Elli Papaemmanuil, Andrew Kung, Christine Iacobuzio Donahue. Assessing patterns of genomic instability in recurrent osteosarcoma. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3556.

Whole genome sequencing (WGS) has emerged as a tool to characterize the entire genomic landscape of cancer and capture potential new targets and predictive biomarkers. Using state-of-the-art whole-genome and transcriptome sequencing (WGTS) analysis we interrogated a pan cancer cohort to nominate new treatment options. WGS was performed on 414 tumor/germline pairs from our pan cancer cohort of 355 patients, of which 103 had results of other commercial NGS assays. RNAseq data was available in 96 samples. We employed the Isabl GxT analytic platform and manually curated single base substitution (COSMIC v3) mutational signatures and structural variants (SVs). WGTS results were correlated with available clinico-pathologic data. High throughput drug screening that included PARP inhibitors and functional validation were performed in 61 matched patient-derived tumor organoids (PDTO). We found 5,129 SVs affecting at least one cancer gene in 88% of cases. High-confidence homologous recombination deficiency (HRD), determined by curation of mutational signatures and mutations/SVs affecting oncogenes and tumor suppressor genes, was detected in 8.3% of solid tumors (e.g., prostate, pancreas, ovarian, uterine, breast, gallbladder, and stomach carcinomas). HRD status included tumors with BRCA1/2 wildtype and SVs impacting BRCA1/2, RAD51, ATM and other HRD genes. CDK12-loss associated genomic instability was detected in 7 cases including 3 cases of prostate adenocarcinoma. 93 gene fusions involving cancer genes were detected including known and novel fusions of potential significance (e.g., SLC45A3::ALK in metastatic prostate adenocarcinoma, TMEM106A::BRCA1 in serious ovarian carcinoma, ESR1::EP300 in metastatic breast cancer). Some tumor cohorts demonstrated enrichment of drivers e.g., FGFR1 amplification in male breast cancer, rearrangements at the TERT locus in adrenocortical carcinoma, enrichment for repeat-mediated deletion attributed to mismatch repair (MMR) in gynecological carcinosarcoma, and SVs affecting FHIT in gastric adenocarcinoma. Drug screening of PDTO and functional testing with RAD51 immunofluorescence assay validated high-confidence HRD annotation. One example is a BRCA1/2 wildtype pancreatic adenocarcinoma with increased tandem duplications and SV (inversion) impacting BRCA2, and high-confidence HRD by our novel WGS classifier. Drug screening of the corresponding PDTO showed an enhanced response to Olaparib, in contrast to cases without HRD that did not. We have used state-of-the-art analysis of WGTS to improve the detection of targets and significant biomarkers in a pan cancer cohort, including HRD, CDK12-type genomic instability, pathogenic germline mutations and potential targetable novel fusions. A robust and clinically relevant ex vivo preclinical model allowed us to validate a WGS-based classifier that detects HRD even in cancers with wildtype BRCA1/2. Citation Format: Majd Al Assaad, Hui-Hsuan Kuo, Jones Nauseef, Max F. Levine, Gunes Gundem, Juan S. Medina-Martínez, Jyothi Manohar, Michael Sigouros, Ahmed Elsaeed, David Wilkes, Elli Papaemmanuil, Eloise Chapman, Scott T. Tagawa, Allyson Ocean, Cora N. Sternberg, Eleni Andreopoulou, Manish Shah, Andrea Sboner, Kevin Holcomb, David Nanus, Laura Martin, Olivier Elemento, Juan Miguel Mosquera. Whole genome and transcriptome sequencing of a pan cancer cohort unearths novel therapeutic avenues [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3437.

Background The widespread adoption of high throughput technologies has democratized data generation. However, data processing in accordance with best practices remains challenging and the data capital often becomes siloed. This presents an opportunity to consolidate data assets into digital biobanks—ecosystems of readily accessible, structured, and annotated datasets that can be dynamically queried and analysed. Results We present Isabl, a customizable plug-and-play platform for the processing of multimodal patient-centric data. Isabl's architecture consists of a relational database (Isabl DB), a command line client (Isabl CLI), a RESTful API (Isabl API) and a frontend web application (Isabl Web). Isabl supports automated deployment of user-validated pipelines across the entire data capital. A full audit trail is maintained to secure data provenance, governance and ensuring reproducibility of findings. Conclusions As a digital biobank, Isabl supports continuous data utilization and automated meta analyses at scale, and serves as a catalyst for research innovation, new discoveries, and clinical translation.

To describe the unique clinical features, determine the genomics, and investigate the metabolic derangement of an extremely rare form of a hereditary lethal kidney cancer syndrome.Three patients with lethal kidney cancer (age 19, 20, and 37 years) exhibiting persistent (1 to 3 months) extremely high levels of blood lactate (5 mM) despite normal oxygen perfusion, highly avid tumors on [All three patients with kidney cancer were initially given various diagnoses as a result of diverse tumor histopathology and atypical clinical presentations. The correct diagnoses of theseSDHB-deficient metastatic renal cell carcinoma is a rare, aggressive form of kidney cancer that manifests with clinical evidence of a severe Warburg effect, and genomic studies demonstrated two genetic hits at

225 Background: Metastatic, castration-resistant prostate cancer (mCRPC) is commonly the deadly form of PC. Among these, a subset of tumors are androgen-indifferent with the most aggressive often manifesting variant histology, including neuroendocrine or small cell changes. Neuroendocrine PC can be de novo (NEPC) or develop in response to therapy as treatment emergent (CRPC-NE). Currently effective durable treatments for NEPC are lacking. Hence, we sought to identify additional targets in CRPC/NEPC using an integrative platform of whole genome (WGS) and transcriptome sequencing (RNAseq). Methods: WGS was performed on55 tumor/normal pairs (CRPC-Ad, n= 32; CRPC-NE, n=13; de novo NEPC, n=7; metastatic hormone naïve, PC n=3) from 48 patients. RNAseq data was available in a subset of 21 samples. We employed the Isabl GxT analytic platform and manually curated single base substitution (SBS, COSMIC v3) molecular signatures and structural variants (SV) that involved tumor suppressor genes and oncogenes. Results: We observed 184 events in cancer-associated genes and targets in 38 cases. Non-canonical ETS fusions were identified in 2 CRPC-Ad patients ( MSMB-ERG and YWHAE-ETV4). Other rare events included SVs affecting ALK ( SLC45A3-ALK) and FGFR1 amplification in 1 patient each. Pathogenic germline alterations in 15% of patients with equal frequency in each clinicopathological state. These variants included genes such as BRCA1, BRCA2, and ATM, and other genes of uncertain relevance for prostate cancer ( e.g., PPM1D and MUTYH). SBS genomic signatures associated with homologous recombination deficiency (HRD) were observed in 15% of the patients (7 cases): 3 harbored germline BRCA1/2mutations, 2 with somatic BRCA2 mutations, and 2 without alteration in BRCA1/2 (1 of these CRPC-Ad had a complex SV disrupting RAD51B) without apparent enrichment for any histology, and a majority of both histologies were enriched in Mismatch repair (MMR)-associated SBS. One subject CRPC-NE and amphicrine character, which displayed a complete response to immune checkpoint blockade, harbored driver mutations in AR and CTNNB1, and homozygous loss of MSH2/6. Further, molecular signatures of potential clinical relevance were detected at varying contributions and included CDK12-type genomic instability (CRPC-Ad, n=2) (4%) and MMR deficiency with POLD1 proofreading (CRPC-Ad) who also experienced a durable response to pembrolizumab. Conclusions: WGS/RNAseq in CRPC and NEPC elucidates genomic signatures associated with HRD and MMR, complex SVs in oncogenes, and non-canonical ETS fusions. Expansion of our analysis is underway with enhanced integration of clinical metadata and RNAseq for rational trial design for aggressive variant CRPC and NEPC.

Very rarely, vasoactive intestinal peptide-related diarrhea (VIP-D) is observed in patients with high-risk neuroblastoma (HR-NB) where the associated fluid and electrolyte abnormalities can pose a major clinical challenge for administering the required aggressive multimodality treatment. Two patients with HR-NB developed VIP-D during induction and were found to have a somatic BRAF V600E mutation. Serum VIP levels and diarrhea promptly resolved in both patients after initiating treatment with BRAF and MEK inhibitors. This illustrates an association of VIP-D with BRAF V600E mutations and demonstrates a therapeutic strategy in the specific context of VIP-D and BRAF V600E mutations in HR-NB patients. The addition of BRAF and MEK inhibitors allows continued conventional tumor-directed treatment by decreasing the severity of symptoms caused by this life-threatening complication.

11533 Background: Multiple large-scale tumor genomic profiling efforts have been undertaken in osteosarcoma, however little is known about the spatial and temporal intratumor heterogeneity and how it may drive treatment resistance. Methods: We performed 30-80x whole genome sequencing (WGS) of 37 tumor samples from 8 patients with relapsed or refractory osteosarcoma. A set of high confidence single nucleotide variants (SNV), copy number alterations (CNA), structural variations (SV) were called for each sample using our pediatric expanded genomics pipeline and an evolutionary analysis was performed using a custom pipeline of computational tools. Results: Of the 8 patients in our cohort, 4 had localized disease at diagnosis (OSCE4, OSCE5, OSCE6, OSCE9) and 4 had metastatic disease at diagnosis (OSCE1, OSCE2, OSCE3, OSCE10). There were 17 samples from primary sites, 7 were pretreatment biopsies, 10 from on therapy primary resections. 20 samples came from metastatic sites, 15 of which were from lung metastases. Driver gene SNV’s were identified in 5 of 8 patients, including TP53 (OSCE1), ATRX (OSCE3, OSCE10), RB1 (OSCE4), and CDKN2A (OSCE9). No new driver SNV’s emerged post-therapy in any patient. HATCHet, an algorithm which infers clone specific copy number alterations, identified subclonal CNAs in all but one patient (OSCE2). In the 7 patients with subclonal CNAs, 6 had two copy number clones identified, and 1 patient (OSCE10) had three copy number clones identified. In 5 patients (OSCE1, OSCE4, OSCE5, OSCE6, OSCE10) there is a copy number clone that is subclonal in the primary tumor which emerges and dominates at subsequent relapses. The resistant clone in each of these cases had either MYC gain/amplification. Amplifications in CCNE1 (OSCE1), RAD21 (OSCE4, OSCE5, OSCE10), VEGFA (OSCE1, OSCE9), IGF1R (OSCE6) were also identified as potential drivers in the resistant copy number clones. In two of these patients (OSCE1, OSCE6), the treatment resistant subclone becomes the dominant copy number clone by the time of primary resection. SNV based phylogenies revealed monoclonal and polyclonal seeding of metastases and monophyletic and polyphyletic modes of dissemination. Over half the new mutations acquired in recurrent disease were attributed to HRD or cisplatin mutational signatures. Conclusions: Subclonal copy number clones emerge and dominate in relapsed osteosarcoma, with MYC gain/amplification a defining characteristic in our cohort. Selective pressure from neoadjuvant chemotherapy reveals this clone at the time of primary resection, implying genomic profiling at this timepoint may be more reflective of its metastatic potential. [Table: see text]

Multiple myeloma (MM) progression is characterized by the seeding of cancer cells in different anatomic sites. To characterize this evolutionary process, we interrogated, by whole genome sequencing, 25 samples collected at autopsy from 4 patients with relapsed MM and an additional set of 125 whole exomes collected from 51 patients. Mutational signatures analysis showed how cytotoxic agents introduce hundreds of unique mutations in each surviving cancer cell, detectable by bulk sequencing only in cases of clonal expansion of a single cancer cell bearing the mutational signature. Thus, a unique, single-cell genomic barcode can link chemotherapy exposure to a discrete time window in a patient's life. We leveraged this concept to show that MM systemic seeding is accelerated at relapse and appears to be driven by the survival and subsequent expansion of a single myeloma cell following treatment with high-dose melphalan therapy and autologous stem cell transplant.

The evolutionary progression from primary to metastatic prostate cancer is largely uncharted, and the implications for liquid biopsy are unexplored. We infer detailed reconstructions of tumor phylogenies in ten prostate cancer patients with fatal disease, and investigate them in conjunction with histopathology and tumor DNA extracted from blood and cerebrospinal fluid. Substantial evolution occurs within the prostate, resulting in branching into multiple spatially intermixed lineages. One dominant lineage emerges that initiates and drives systemic metastasis, where polyclonal seeding between sites is common. Routes to metastasis differ between patients, and likely genetic drivers of metastasis distinguish the metastatic lineage from the lineage that remains confined to the prostate within each patient. Body fluids capture features of the dominant lineage, and subclonal expansions that occur in the metastatic phase are non-uniformly represented. Cerebrospinal fluid analysis reveals lineages not detected in blood-borne DNA, suggesting possible clinical utility., The evolutionary progression from primary to metastatic prostate cancer is largely uncharted, and the implications for liquid biopsy are unexplored. Here, the authors use deep genomic sequencing and histopathological information to trace tumor evolution both within the prostate and during metastasis in ten men.

Tumor protein p53 (TP53) is the most frequently mutated gene in cancer1,2. In patients with myelodysplastic syndromes (MDS), TP53 mutations are associated with high-risk disease3,4, rapid transformation to acute myeloid leukemia (AML)5, resistance to conventional therapies6–8 and dismal outcomes9. Consistent with the tumor-suppressive role of TP53, patients harbor both mono- and biallelic mutations10. However, the biological and clinical implications of TP53 allelic state have not been fully investigated in MDS or any other cancer type. We analyzed 3,324 patients with MDS for TP53 mutations and allelic imbalances and delineated two subsets of patients with distinct phenotypes and outcomes. One-third of TP53-mutated patients had monoallelic mutations whereas two-thirds had multiple hits (multi-hit) consistent with biallelic targeting. Established associations with complex karyotype, few co-occurring mutations, high-risk presentation and poor outcomes were specific to multi-hit patients only. TP53 multi-hit state predicted risk of death and leukemic transformation independently of the Revised International Prognostic Scoring System (IPSS-R)11. Surprisingly, monoallelic patients did not differ from TP53 wild-type patients in outcomes and response to therapy. This study shows that consideration of TP53 allelic state is critical for diagnostic and prognostic precision in MDS as well as in future correlative studies of treatment response. Clinical sequencing across a large prospective cohort of patients with myelodysplasic syndrome uncovers distinct associations between the mono- and biallelic states of TP53 and clinical presentation

In the Supplementary Information of this Article, some errors were made in compiling the Supplementary Data file called ‘Supplementary Variant Lists’. In the first worksheet (entitled ‘subs’) the clusters to which some single nucleotide variants (SNVs) were assigned were not reported and were replaced with ‘NA’ for ‘not available’. The correct cluster numbers have now been inserted. Three mutations occurring in tumour A32 were incorrectly assigned to cluster 3 and have now been correctly assigned to cluster 2. Duplicate entries were present for some mutations in A32. These duplicate entries have now been removed. In the fourth worksheet (entitled ‘copy_number’) incorrect copy number information was reported for sample A31-c. The previous information, implying that A31-c was primarily diploid, has now been replaced with the copy number call used within the Article, which indicates that A31-c is primarily tetraploid. The Supplementary Information to this Amendment contains the corrected Excel file ‘Supplementary Variant Lists’. These corrections do not change the authors’ interpretation of the findings. The original Article has not been corrected.

Acquired mutations are pervasive across normal tissues. However, understanding of the processes that drive transformation of certain clones to cancer is limited. Here we study this phenomenon in the context of clonal hematopoiesis (CH) and the development of therapy-related myeloid neoplasms (tMNs). We find that mutations are selected differentially based on exposures. Mutations in ASXL1 are enriched in current or former smokers, whereas cancer therapy with radiation, platinum and topoisomerase II inhibitors preferentially selects for mutations in DNA damage response genes (TP53, PPM1D, CHEK2). Sequential sampling provides definitive evidence that DNA damage response clones outcompete other clones when exposed to certain therapies. Among cases in which CH was previously detected, the CH mutation was present at tMN diagnosis. We identify the molecular characteristics of CH that increase risk of tMN. The increasing implementation of clinical sequencing at diagnosis provides an opportunity to identify patients at risk of tMN for prevention strategies. Environmental exposures shape patterns of selection for mutations in clonal hematopoiesis. Cancer therapies promote the growth of clones with mutations that are strongly enriched in treatment-related myeloid neoplasms.

Additional file 1. Supplementary figures and notes related to this manuscript.

MC3 Working Group: Rehan Akbani21, Pavana Anur22, Matthew H. Bailey1,2,3, Alex Buchanan9, Kami Chiotti9, Kyle Covington12,23, Allison Creason9, Li Ding1,2,3,20, Kyle Ellrott9, Yu Fan21, Steven Foltz1,2, Gad Getz8,14,15,16, Walker Hale12, David Haussler24,25, Julian M. Hess8,26, Carolyn M. Hutter27, Cyriac Kandoth28, Katayoon Kasaian29,30, Melpomeni Kasapi27, Dave Larson1 , Ignaty Leshchiner8, John Letaw31, Singer Ma32, Michael D. McLellan1,3,20, Yifei Men32, Gordon B. Mills33,34, Beifang Niu35, Myron Peto22, Amie Radenbaugh24, Sheila M. Reynolds36, Gordon Saksena8, Heidi Sofia27, Chip Stewart8, Adam J. Struck31, Joshua M. Stuart24,37, Wenyi Wang21, John N. Weinstein38, David A. Wheeler12,13, Christopher K. Wong24,39, Liu Xi12 & Kai Ye40,41 21Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. 22Molecular and Medical Genetics, OHSU Knight Cancer Institute, Oregon Health and Science University, Portland, OR 97239, USA. 23Castle Biosciences Inc, Friendswood, TX 77546, USA. 24UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA. 25Howard Hughes Medical Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA. 26Massachusetts General Hospital Center for Cancer Research, Charlestown, MA 02114, USA. 27National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20894, USA. 28Marie-Josée and Henry R. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA. 29Ontario Institute for Cancer Research, Toronto, ON M5G 0A3, Canada. 30Canada’s Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, BC V5Z 4S6, Canada. 31Computational Biology Program, School of Medicine, Oregon Health and Science University, Portland, OR 97239, USA. 32DNAnexus Inc, Mountain View, CA 94040, USA. 33Department of Systems Biology, UT MD Anderson Cancer Center, Houston, TX 77030, USA. 34Precision Oncology, OHSU Knight Cancer Institute, Oregon Health and Science University, Portland, OR 97239, USA. 35Computer Network Information Center, Chinese Academy of Sciences, Beijing, China. 36Institute for Systems Biology, Seattle, WA 98109, USA. 37Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA. 38Department of Bioinformatics and Computational Biology and Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. 39Biomolecular Engineering Department, University of California Santa Cruz, Santa Cruz, CA 95064, USA. 40School of Elect, PCAWG novel somatic mutation calling methods working group: Matthew H. Bailey1,2,3, Beifang Niu35, Matthias Bieg42,43, Paul C. Boutros6,44,45,46, Ivo Buchhalter43,47,48, Adam P. Butler49, Ken Chen50, Zechen Chong51, Li Ding1,2,3,20, Oliver Drechsel52,53, Lewis Jonathan Dursi6,7, Roland Eils47,48,54,55, Kyle Ellrott9, Shadrielle M. G. Espiritu6, Yu Fan21, Robert S. Fulton1,3,20, Shengjie Gao56, Josep L. l. Gelpi57,58, Mark B. Gerstein5,18,19, Gad Getz8,14,15,16, Santiago Gonzalez59,60, Ivo G. Gut52,61, Faraz Hach62,63, Michael C. Heinold47,48, Julian M. Hess8,26, Jonathan Hinton49, Taobo Hu64, Vincent Huang6, Yi Huang65,66, Barbara Hutter43,67,68, David R. Jones49, Jongsun Jung69, Natalie Jäger47, Hyung-Lae Kim70, Kortine Kleinheinz47,48, Sushant Kumar5,19, Yogesh Kumar64, Christopher M. Lalansingh6, Ignaty Leshchiner8, Ivica Letunic71, Dimitri Livitz8, Eric Z. Ma64, Yosef E. Maruvka8,26,72, R. Jay Mashl1,2, Michael D. McLellan1,3,20, Andrew Menzies49, Ana Milovanovic57, Morten Muhlig Nielsen73, Stephan Ossowski52,53,74, Nagarajan Paramasivam43,47, Jakob Skou Pedersen73,75, Marc D. Perry76,77, Montserrat Puiggròs57, Keiran M. Raine49, Esther Rheinbay8,14,72, Romina Royo57, S. Cenk Sahinalp62,78,79, Gordon Saksena8, Iman Sarrafi62,78, Matthias Schlesner47,80, Jared T. Simpson6,17, Lucy Stebbings49, Chip Stewart8, Miranda D. Stobbe52,61, Jon W. Teague49, Grace Tiao8, David Torrents57,81, Jeremiah A. Wala8,14,82, Jiayin Wang1,40,66, Wenyi Wang21, Sebastian M. Waszak60, Joachim Weischenfeldt60,83,84, Michael C. Wendl1,10,11, Johannes Werner47,85, Zhenggang Wu64, Hong Xue64, Sergei Yakneen60, Takafumi N. Yamaguchi6, Kai Ye40,41, Venkata D. Yellapantula20,86, Christina K. Yung76 & Junjun Zhang76, PCAWG Consortium: Lauri A. Aaltonen87, Federico Abascal49, Adam Abeshouse88, Hiroyuki Aburatani89, David J. Adams49, Nishant Agrawal90, Keun Soo Ahn91, Sung-Min Ahn92, Hiroshi Aikata93, Rehan Akbani21, Kadir C. Akdemir50, Hikmat Al-Ahmadie88, Sultan T. Al-Sedairy94, Fatima Al-Shahrour95, Malik Alawi96,97, Monique Albert98, Kenneth Aldape99,100, Ludmil B. Alexandrov49,101,102, Adrian Ally30, Kathryn Alsop103, Eva G. Alvarez104,105,106, Fernanda Amary107, Samirkumar B. Amin108,109,110, Brice Aminou76, Ole Ammerpohl111,112, Matthew J. Anderson113, Yeng Ang114, Davide Antonello115, Pavana Anur22, Samuel Aparicio116, Elizabeth L. Appelbaum1,117, Yasuhito Arai118, Axel Aretz119, Koji Arihiro93, Shun-ichi Ariizumi120, Joshua Armenia121, Laurent Arnould122, Sylvia Asa123,124, Yassen Assenov125, Gurnit Atwal6,126,127, Sietse Aukema112,128, J. Todd Auman129, Miriam R. Aure130, Philip Awadalla6,126, Marta Aymerich131, Gary D. Bader126, Adrian Baez-Ortega132, Matthew H. Bailey1,2,3, Peter J. Bailey133, Miruna Balasundaram30, Saianand Balu134, Pratiti Bandopadhayay8,135,136, Rosamonde E. Banks137, Stefano Barbi138, Andrew P. Barbour139,140, Jonathan Barenboim6, Jill Barnholtz-Sloan141,142, Hugh Barr143, Elisabet Barrera59, John Bartlett98,144, Javier Bartolome57, Claudio Bassi115, Oliver F. Bathe145,146, Daniel Baumhoer147, Prashant Bavi148, Stephen B. Baylin149,150, Wojciech Bazant59, Duncan Beardsmore151, Timothy A. Beck152,153, Sam Behjati49, Andreas Behren154, Beifang Niu35, Cindy Bell155, Sergi Beltran52,61, Christopher Benz156, Andrew Berchuck157, Anke K. Bergmann158, Erik N. Bergstrom101,102, Benjamin P. Berman159,160,161, Daniel M. Berney162, Stephan H. Bernhart163,164,165, Rameen Beroukhim8,14,82, Mario Berrios166, Samantha Bersani167, Johanna Bertl73,168, Miguel Betancourt169, Vinayak Bhandari6,44, Shriram G. Bhosle49, Andrew V. Biankin133,170,171,172, Matthias Bieg42,43, Darell Bigner173, Hans Binder163,164, Ewan Birney59, Michael Birrer72, Nidhan K. Biswas174, Bodil Bjerkehagen147,175, Tom Bodenheimer134, Lori Boice176, Giada Bonizzato177, Johann S. De Bono178, Arnoud Boot179,180, Moiz S. Bootwalla166, Ake Borg181, Arndt Borkhardt182, Keith A. Boroevich183,184, Ivan Borozan6, Christoph Borst185, Marcus Bosenberg186, Mattia Bosio52,53,57, Jacqueline Boultwood187, Guillaume Bourque188,189, Paul C. Boutros6,44,45,46, G. Steven Bova190, David T. Bowen49,191, Reanne Bowlby30, David D. L. Bowtell103, Sandrine Boyault192, Rich Boyce59, Jeffrey Boyd193, Alvis Brazma59, Paul Brennan194, Daniel S. Brewer195,196, Arie B. Brinkman197, Robert G. Bristow44,198,199,200,201, Russell R. Broaddus99, Jane E. Brock202, Malcolm Brock203, Annegien Broeks204, Angela N. Brooks8,24,37,82, Denise Brooks30, Benedikt Brors67,205,206, Søren Brunak207,208, Timothy J. C. Bruxner113,209, Alicia L. Bruzos104,105,106, Alex Buchanan9, Ivo Buchhalter43,47,48, Christiane Buchholz210, Susan Bullman8,82, Hazel Burke211, Birgit Burkhardt212, Kathleen H. Burns213,214, John Busanovich8,215, Carlos D. Bustamante216,217, Adam P. Butler49, Atul J. Butte218, Niall J. Byrne76, Anne-Lise Børresen-Dale130,219, Samantha J. Caesar-Johnson220, Andy Cafferkey59, Declan Cahill221, Claudia Calabrese59,60, Carlos Caldas222,223, Fabien Calvo224, Niedzica Camacho178, Peter J. Campbell49,225, Elias Campo226,227, Cinzia Cantù177, Shaolong Cao21, Thomas E. Carey228, Joana Carlevaro-Fita229,230,231, Rebecca Carlsen30, Ivana Cataldo167,177, Mario Cazzola232, Jonathan Cebon154, Robert Cerfolio233, Dianne E. Chadwick234, Dimple Chakravarty235, Don Chalmers236, Calvin Wing Yiu Chan47,237, Kin Chan238, Michelle Chan-Seng-Yue148, Vishal S. Chandan239, David K. Chang133,170, Stephen J. Chanock240, Lorraine A. Chantrill170,241, Aurélien Chateigner76,242, Nilanjan Chatterjee149,243, Kazuaki Chayama93, Hsiao-Wei Chen114,121, Jieming Chen218, Ken Chen50, Yiwen Chen21, Zhaohong Chen244, Andrew D. Cherniack8,82, Jeremy Chien245, Yoke-Eng Chiew246,247, Suet-Feung Chin222,223, Juok Cho8, Sunghoon Cho248, Jung Kyoon Choi249, Wan Choi250, Christine Chomienne251, Zechen Chong51, Su Pin Choo252, Angela Chou170,246, Angelika N. Christ113, Elizabeth L. Christie103, Eric Chuah30, Carrie Cibulskis8, Kristian Cibulskis8, Sara Cingarlini253, Peter Clapham49, Alexander Claviez254, Sean Cleary148,255, Nicole Cloonan256, Marek Cmero257,258,259, Colin C. Collins62, Ashton A. Connor255,260, Susanna L. Cooke133, Colin S. Cooper178,196,261, Leslie Cope149, Vincenzo Corbo138,177, Matthew G. Cordes1,262, Stephen M. Cordner263, Isidro Cortés-Ciriano264,265,266, Kyle Covington12,23, Prue A. Cowin267, Brian Craft24, David Craft8,268, Chad J. Creighton269, Yupeng Cun270, Erin Curley271, Ioana Cutcutache179,180, Karolina Czajka272, Bogdan Czerniak99,273, Rebecca A. Dagg274, Ludmila Danilova149, Maria Vittoria Davi275, Natalie R. Davidson276,277,278,279,280, Helen Davies49,281,282, Ian J. Davis283, Brandi N. Davis-Dusenbery284, Kevin J. Dawson49, Francisco M. De La Vega216,217,285, Ricardo De Paoli-Iseppi211, Timothy Defreitas8, Angelo P. Dei Tos286, Olivier Delaneau287,288,289, John A. Demchok220, Jonas Demeulemeester290,291, German M. Demidov52,53,74, Deniz Demircioğlu292,293, Nening M. Dennis221, Robert E. Denroche148, Stefan C. Dentro49,290,294, Nikita Desai76, Vikram Deshpande72, Amit G. Deshwar295, Christine Desmedt296,297, Jordi Deu-Pons298,299, Noreen Dhalla30, Neesha C. Dhani300, Priyanka Dhingra301,302, Rajiv Dhir303, Anthony DiBiase304, Klev Diamanti305, Li Ding1,2,3,20, Shuai Ding306, Huy Q. Dinh159, Luc Dirix307, HarshaVardhan Doddapaneni12, Nilgun Donmez62,78, Michelle T. Dow244, Ronny Drapkin308, Oliver Drechsel52,53, Ruben M. Drews223, Serge Serge49, Tim Dudderidge150,221, Ana Dueso-Barroso57, Andrew J. Dunford8, Michael Dunn309, Lewis Jonathan Dursi6,7, Fraser R. Duthie133,310, Ken Dutton-Regester311, Jenna Eagles272, Douglas F. Easton312,313, Stuart Edmonds314, Paul A. Edwards223,315, Sandra E. Edwards178, Rosalind A. Eeles178,221, Anna Ehinger316, Juergen Eils54,55, Roland Eils47,48,54,55, Adel El-Naggar99,273, Matthew Eldridge223, Kyle Ellrott9, Serap Erkek60, Georgia Escaramis53,317,318, Shadrielle M. G. Espiritu6, Xavier Estivill53,319, Dariush Etemadmoghadam103, Jorunn E. Eyfjord320, Bishoy M. Faltas280, Daiming Fan321, Yu Fan21, William C. Faquin72, Claudiu Farcas244, Matteo Fassan322, Aquila Fatima323, Francesco Favero324, Nodirjon Fayzullaev76, Ina Felau220, Sian Fereday103, Martin L. Ferguson325, Vincent Ferretti76,326, Lars Feuerbach205, Matthew A. Field327, J. Lynn Fink57,113, Gaetano Finocchiaro328, Cyril Fisher221, Matthew W. Fittall290, Anna Fitzgerald329, Rebecca C. Fitzgerald282, Adrienne M. Flanagan330, Neil E. Fleshner331, Paul Flicek59, John A. Foekens332, Kwun M. Fong333, Nuno A. Fonseca59,334, Christopher S. Foster335,336, Natalie S. Fox6, Michael Fraser6, Scott Frazer8, Milana Frenkel-Morgenstern337, William Friedman338, Joan Frigola298, Catrina C. Fronick1,262, Akihiro Fujimoto184, Masashi Fujita184, Masashi Fukayama339, Lucinda A. Fulton1 , Robert S. Fulton1,3,20, Mayuko Furuta184, P. Andrew Futreal340, Anja Füllgrabe59, Stacey B. Gabriel8, Steven Gallinger148,255,260, Carlo Gambacorti-Passerini341, Jianjiong Gao121, Shengjie Gao56, Levi Garraway82, Øystein Garred342, Erik Garrison49, Dale W. Garsed103, Nils Gehlenborg8,343, Josep L. l. Gelpi57,58, Joshy George110, Daniela S. Gerhard344, Clarissa Gerhauser345, Jeffrey E. Gershenwald346,347, Mark B. Gerstein5,18,19, Moritz Gerstung59,60, Gad Getz8,14,15,16, Mohammed Ghori49, Ronald Ghossein348, Nasra H. Giama349, Richard A. Gibbs12, Anthony J. Gill170,350, Pelvender Gill351, Dilip D. Giri348, Dominik Glodzik49, Vincent J. Gnanapragasam352,353, Maria Elisabeth Goebler354, Mary J. Goldman24, Carmen Gomez355, Santiago Gonzalez59,60, Abel Gonzalez-Perez298,299,356, Dmitry A. Gordenin357, James Gossage358, Kunihito Gotoh359, Ramaswamy Govindan3, Dorthe Grabau360, Janet S. Graham133,361, Robert C. Grant148,260, Anthony R. Green315, Eric Green27, Liliana Greger59, Nicola Grehan282, Sonia Grimaldi177, Sean M. Grimmond362, Robert L. Grossman363, Adam Grundhoff97,364, Gunes Gundem88, Qianyun Guo75, Manaswi Gupta8, Shailja Gupta365, Ivo G. Gut52,61, Marta Gut52,61, Jonathan Göke292,366, Gavin Ha8, Andrea Haake111, David Haan37, Siegfried Haas185, Kerstin Haase290, James E. Haber367, Nina Habermann60, Faraz Hach62,63, Syed Haider6, Natsuko Hama118, Freddie C. Hamdy351, Anne Hamilton267, Mark P. Hamilton368, Leng Han369, George B. Hanna370, Martin Hansmann371, Nicholas J. Haradhvala8,72, Olivier Harismendy102,372, Ivon Harliwong113, Arif O. Harmanci5,373, Eoghan Harrington374, Takanori Hasegawa375, David Haussler24,25, Steve Hawkins223, Shinya Hayami376, Shuto Hayashi375, D. Neil Hayes134,377,378, Stephen J. Hayes379,380, Nicholas K. Hayward211,311, Steven Hazell221, Yao He381, Allison P. Heath382, Simon C. Heath52,61, David Hedley300, Apurva M. Hegde38, David I. Heiman8, Michael C. Heinold47,48, Zachary Heins88, Lawrence E. Heisler152, Eva Hellstrom-Lindberg383, Mohamed Helmy384, Seong Gu Heo385, Austin J. Hepperla134, José María Heredia-Genestar386, Carl Herrmann47,48,387, Peter Hersey211, Julian M. Hess8,26, Holmfridur Hilmarsdottir320, Jonathan Hinton49, Satoshi Hirano388, Nobuyoshi Hiraoka389, Katherine A. Hoadley134,390, Asger Hobolth75,168, Ermin Hodzic78, Jessica I. Hoell182, Steve Hoffmann163,164,165,391, Oliver Hofmann392, Andrea Holbrook166, Aliaksei Z. Holik53, Michael A. Hollingsworth393, Oliver Holmes209,311, Robert A. Holt30, Chen Hong205,237, Eun Pyo Hong385, Jongwhi H. Hong394, Gerrit K. Hooijer395, Henrik Hornshøj73, Fumie Hosoda118, Yong Hou56,396, Volker Hovestadt397, William Howat352, Alan P. Hoyle134, Ralph H. Hruban149, Jianhong Hu12, Taobo Hu64, Xing Hua240, Kuan-lin Huang1,398, Mei Huang176, Mi Ni Huang179,180, Vincent Huang6, Yi Huang65,66, Wolfgang Huber60, Thomas J. Hudson272,399, Michael Hummel400, Jillian A. Hung246,247, David Huntsman401, Ted R. Hupp402, Jason Huse88, Matthew R. Huska403, Barbara Hutter43,67,68, Carolyn M. Hutter27, Daniel Hübschmann48,54,404,405,406, Christine A. Iacobuzio-Donahue348, Charles David Imbusch205, Marcin Imielinski407,408, Seiya Imoto375, William B. Isaacs409, Keren Isaev6,44, Shumpei Ishikawa410, Murat Iskar397, S. M. Ashiqul Islam244, Michael Ittmann411,412,413, Sinisa Ivkovic284, Jose M. G. Izarzugaza414, Jocelyne Jacquemier415, Valerie Jakrot211, Nigel B. Jamieson133,172,416, Gun Ho Jang148, Se Jin Jang417, Joy C. Jayaseelan12, Reyka Jayasinghe1 , Stuart R. Jefferys134, Karine Jegalian418, Jennifer L. Jennings419, Seung-Hyup Jeon250, Lara Jerman60,420, Yuan Ji421,422, Wei Jiao6, Peter A. Johansson311, Amber L. Johns170, Jeremy Johns272, Rory Johnson230,423, Todd A. Johnson183, Clemency Jolly290, Yann Joly424, Jon G. Jonasson320, Corbin D. Jones425, David R. Jones49, David T. W. Jones426,427, Nic Jones428, Steven J. M. Jones30, Jos Jonkers204, Young Seok Ju49,249, Hartmut Juhl429, Jongsun Jung69, Malene Juul73, Randi Istrup Juul73, Sissel Juul374, Natalie Jäger47, Rolf Kabbe47, Andre Kahles276,277,278,279,430, Abdullah Kahraman431,432,433, Vera B. Kaiser434, Hojabr Kakavand211, Sangeetha Kalimuthu148, Christof von Kalle405, Koo Jeong Kang91, Katalin Karaszi351, Beth Karlan435, Rosa Karlić436, Dennis Karsch437, Katayoon Kasaian29,30, Karin S. Kassahn113,438, Hitoshi Katai439, Mamoru Kato440, Hiroto Katoh410, Yoshiiku Kawakami93, Jonathan D. Kay117, Stephen H. Kazakoff209,311, Marat D. Kazanov441,442,443, Maria Keays59, Electron Kebebew444,445, Richard F. Kefford446, Manolis Kellis8,447, James G. Kench170,350,448, Catherine J. Kennedy246,247, Jules N. A. Kerssemakers47, David Khoo273, Vincent Khoo221, Narong Khuntikeo115,449, Ekta Khurana301,302,450,451, Helena Kilpinen117, Hark Kyun Kim452, Hyung-Lae Kim70, Hyung-Yong Kim415, Hyunghwan Kim250, Jaegil Kim8, Jihoon Kim453, Jong K. Kim454, Youngwook Kim455,456, Tari A. King457,458,459, Wolfram Klapper128, Kortine Kleinheinz47,48, Leszek J. Klimczak460, Stian Knappskog49,461, Michael Kneba437, Bartha M. Knoppers424, Youngil Koh462,463, Jan Komorowski305,464, Daisuke Komura410, Mitsuhiro Komura375, Gu Kong415, Marcel Kool426,465, Jan O. Korbel59,60, Viktoriya Korchina12, Andrey Korshunov465, Michael Koscher465, Roelof Koster466, Zsofia Kote-Jarai178, Antonios Koures244, Milena Kovacevic284, Barbara Kremeyer49, Helene Kretzmer164,165, Markus Kreuz467, Savitri Krishnamurthy99,468, Dieter Kube469, Kiran Kumar8, Pardeep Kumar221, Sushant Kumar5,19, Yogesh Kumar64, Ritika Kundra114,121, Kirsten Kübler8,14,72, Ralf Küppers470, Jesper Lagergren383,471, Phillip H. Lai166, Peter W. Laird472, Sunil R. Lakhani473, Christopher M. Lalansingh6, Emilie Lalonde6, Fabien C. Lamaze6, Adam Lambert351, Eric Lander8, Pablo Landgraf474,475, Luca Landoni115, Anita Langerød130, Andrés Lanzós230,231,423, Denis Larsimont476, Erik Larsson477, Mark Lathrop189, Loretta M. S. Lau478, Chris Lawerenz55, Rita T. Lawlor177, Michael S. Lawrence8,72,183, Alexander J. Lazar99,108, Xuan Le479, Darlene Lee30, Donghoon Lee5, Eunjung Alice Lee480, Hee Jin Lee417, Jake June-Koo Lee264,266, Jeong-Yeon Lee481, Juhee Lee482, Ming Ta Michael Lee340, Henry Lee-Six49, Kjong-Van Lehmann276,277,278,279,430, Hans Lehrach483, Dido Lenze400, Conrad R. Leonard209,311, Daniel A. Leongamornlert49,178, Ignaty Leshchiner8, Louis Letourneau484, Ivica Letunic71, Douglas A. Levine88,485, Lora Lewis12, Tim Ley486, Chang Li56,396, Constance H. Li6,44, Haiyan Irene Li30, Jun Li21, Lin Li56, Shantao Li5, Siliang Li56,396, Xiaobo Li56,396, Xiaotong Li5, Xinyue Li56, Yilong Li49, Han Liang21, Sheng-Ben Liang234, Peter Lichter68,397, Pei Lin8, Ziao Lin8,487, W. M. Linehan488, Ole Christian Lingjærde489, Dongbing Liu56,396, Eric Minwei Liu88,301,302, Fei-Fei Liu201,490, Fenglin Liu381,491, Jia Liu492, Xingmin Liu56,396, Julie Livingstone6, Dimitri Livitz8, Naomi Livni221, Lucas Lochovsky5,19,110, Markus Loeffler467, Georgina V. Long211, Armando Lopez-Guillermo493, Shaoke Lou5,19, David N. Louis72, Laurence B. Lovat117, Yiling Lu38, Yong-Jie Lu162,494, Youyong Lu495,496,497, Claudio Luchini167, Ilinca Lungu144,148, Xuemei Luo152, Hayley J. Luxton117, Andy G. Lynch223,315,498, Lisa Lype36, Cristina López111,112, Carlos López-Otín499, Eric Z. Ma64, Yussanne Ma30, Gaetan MacGrogan500, Shona MacRae501, Geoff Macintyre223, Tobias Madsen73, Kazuhiro Maejima184, Andrea Mafficini177, Dennis T. Maglinte166,502, Arindam Maitra174, Partha P. Majumder174, Luca Malcovati232, Salem Malikic62,78, Giuseppe Malleo115, Graham J. Mann211,246,503, Luisa Mantovani-Löffler504, Kathleen Marchal505,506, Giovanni Marchegiani115, Elaine R. Mardis1,193,507, Adam A. Margolin31, Maximillian G. Marin37, Florian Markowetz223,315, Julia Markowski403, Jeffrey Marks508, Tomas Marques-Bonet61,81,386,509, Marco A. Marra30, Luke Marsden351, John W. M. Martens332, Sancha Martin49,510, Jose I. Martin-Subero81,511, Iñigo Martincorena49, Alexander Martinez-Fundichely301,302,451 Yosef E. Maruvka8,26,72, R. Jay Mashl1,2, Charlie E. Massie223, Thomas J. Matthew37, Lucy Matthews178, Erik Mayer221,512, Simon Mayes513, Michael Mayo30, Faridah Mbabaali272, Karen McCune514, Ultan McDermott49, Patrick D. McGillivray19, Michael D. McLellan1,3,20, John D. McPherson148,272,515, John R. McPherson179,180, Treasa A. McPherson260, Samuel R. Meier8, Alice Meng516, Shaowu Meng134, Andrew Menzies49, Neil D. Merrett115,517, Sue Merson178, Matthew Meyerson8,14,82, William U. Meyerson4,5, Piotr A. Mieczkowski518, George L. Mihaiescu76, Sanja Mijalkovic284, Ana Mijalkovic Mijalkovic-Lazic284, Tom Mikkelsen519, Michele Milella253, Linda Mileshkin103, Christopher A. Miller1 , David K. Miller113,170, Jessica K. Miller272, Gordon B. Mills33,34, Ana Milovanovic57, Sarah Minner520, Marco Miotto115, Gisela Mir Arnau267, Lisa Mirabello240, Chris Mitchell103, Thomas J. Mitchell49,315,352, Satoru Miyano375, Naoki Miyoshi375, Shinichi Mizuno521, Fruzsina Molnár-Gábor522, Malcolm J. Moore300, Richard A. Moore30, Sandro Morganella49, Quaid D. Morris127,490, Carl Morrison523,524, Lisle E. Mose134, Catherine D. Moser349, Ferran Muiños298,299, Loris Mularoni298,299, Andrew J. Mungall30, Karen Mungall30, Elizabeth A. Musgrove133, Ville Mustonen525,526,527, David Mutch528, Francesc Muyas52,53,74, Donna M. Muzny12, Alfonso Muñoz59, Jerome Myers529, Ola Myklebost461, Peter Möller530, Genta Nagae89, Adnan M. Nagrial170, Hardeep K. Nahal-Bose76, Hitoshi Nakagama531, Hidewaki Nakagawa184, Hiromi Nakamura118, Toru Nakamura388, Kaoru Nakano184, Tannistha Nandi532, Jyoti Nangalia49, Mia Nastic284, Arcadi Navarro61,81,386, Fabio C. P. Navarro19, David E. Neal223,352, Gerd Nettekoven533, Felicity Newell209,311, Steven J. Newhouse59, Yulia Newton37, Alvin Wei Tian Ng534, Anthony Ng535, Jonathan Nicholson49, David Nicol221, Yongzhan Nie321,536, G. Petur Nielsen72, Morten Muhlig Nielsen73, Serena Nik-Zainal49,281,282,537, Michael S. Noble8, Katia Nones209,311, Paul A. Northcott538, Faiyaz Notta148,539, Brian D. O’Connor76,540, Peter O’Donnell541, Maria O’Donovan282, Sarah O’Meara49, Brian Patrick O’Neill542, J. Robert O’Neill543, David Ocana59, Angelica Ochoa88, Layla Oesper544, Christopher Ogden221, Hideki Ohdan93, Kazuhiro Ohi375, Lucila Ohno-Machado244, Karin A. Oien523,545, Akinyemi I. Ojesina546,547,548, Hidenori Ojima549, Takuji Okusaka550, Larsson Omberg551, Choon Kiat Ong552, Stephan Ossowski52,53,74, German Ott553, B. F. Francis Ouellette76,554, Christine P’ng6, Marta Paczkowska6, Salvatore Paiella115, Chawalit Pairojkul523, Marina Pajic170, Qiang Pan-Hammarström56,555, Elli Papaemmanuil49, Irene Papatheodorou59, Nagarajan Paramasivam43,47, Ji Wan Park385, Joong-Won Park556, Keunchil Park557,558, Kiejung Park559, Peter J. Park264,266, Joel S. Parker518, Simon L. Parsons124, Harvey Pass560, Danielle Pasternack272, Alessandro Pastore276, Ann-Marie Patch209,311, Iris Pauporté251, Antonio Pea115, John V. Pearson209,311, Chandra Sekhar Pedamallu8,14,82, Jakob Skou Pedersen73,75, Paolo Pederzoli115, Martin Peifer270, Nathan A. Pennell561, Charles M. Perou129,518, Marc D. Perry76,77, Gloria M. Petersen562, Myron Peto22, Nicholas Petrelli563, Robert Petryszak59, Stefan M. Pfister426,465,564, Mark Phillips424, Oriol Pich298,299, Hilda A. Pickett478, Todd D. Pihl565, Nischalan Pillay566, Sarah Pinder567, Mark Pinese170, Andreia V. Pinho568, Esa Pitkänen60, Xavier Pivot569, Elena Piñeiro-Yáñez95, Laura Planko533, Christoph Plass345, Paz Polak8,14,15, Tirso Pons570, Irinel Popescu571, Olga Potapova572, Aparna Prasad52, Shaun R. Preston573, Manuel Prinz47, Antonia L. Pritchard311, Stephenie D. Prokopec6, Elena Provenzano574, Xose S. Puente499, Sonia Puig176, Montserrat Puiggròs57, Sergio Pulido-Tamayo505,506, Gulietta M. Pupo246, Colin A. Purdie575, Michael C. Quinn209,311, Raquel Rabionet52,53,576, Janet S. Rader577, Bernhard Radlwimmer397, Petar Radovic284, Benjamin Raeder60, Keiran M. Raine49, Manasa Ramakrishna49, Kamna Ramakrishnan49, Suresh Ramalingam578, Benjamin J. Raphael579, W. Kimryn Rathmell580, Tobias Rausch60, Guido Reifenberger475, Jüri Reimand6,44, Jorge Reis-Filho348, Victor Reuter348, Iker Reyes-Salazar298, Matthew A. Reyna579, Sheila M. Reynolds36, Esther Rheinbay8,14,72, Yasser Riazalhosseini189, Andrea L. Richardson323, Julia Richter111,128, Matthew Ringel581, Markus Ringnér181, Yasushi Rino582, Karsten Rippe405, Jeffrey Roach583, Lewis R. Roberts349, Nicola D. Roberts49, Steven A. Roberts584, A. Gordon Robertson30, Alan J. Robertson113, Javier Bartolomé Rodriguez57, Bernardo Rodriguez-Martin104,105,106, F. Germán Rodríguez-González83,332, Michael H. A. Roehrl44,123,148,234,585,586, Marius Rohde587, Hirofumi Rokutan440, Gilles Romieu588, Ilse Rooman170, Tom Roques262, Daniel Rosebrock8, Mara Rosenberg8,72, Philip C. Rosenstiel589, Andreas Rosenwald590, Edward W. Rowe221,591, Romina Royo57, Steven G. Rozen179,180,592, Yulia Rubanova17,127, Mark A. Rubin423,593,594,595,596, Carlota Rubio-Perez298,299,597, Vasilisa A. Rudneva60, Borislav C. Rusev177, Andrea Ruzzenente598, Gunnar Rätsch276,277,278,279,280,430, Radhakrishnan Sabarinathan298,299,599, Veronica Y. Sabelnykova6, Sara Sadeghi30, S. Cenk Sahinalp62,78,79, Natalie Saini357, Mihoko Saito-Adachi440, Gordon Saksena8, Adriana Salcedo6, Roberto Salgado600, Leonidas Salichos5,19, Richard Sallari8, Charles Saller601, Roberto Salvia115, Michelle Sam272, Jaswinder S. Samra115,602, Francisco Sanchez-Vega114,121, Chris Sander276,603,604, Grant Sanders134, Rajiv Sarin605, Iman Sarrafi62,78, Aya Sasaki-Oku184, Torill Sauer489, Guido Sauter520, Robyn P. M. Saw211, Maria Scardoni167, Christopher J. Scarlett170,606, Aldo Scarpa177, Ghislaine Scelo194, Dirk Schadendorf68,607, Jacqueline E. Schein30, Markus B. Schilhabel589, Matthias Schlesner47,80, Thorsten Schlomm84,608, Heather K. Schmidt1 , Sarah-Jane Schramm246, Stefan Schreiber609, Nikolaus Schultz121, Steven E. Schumacher8,323, Roland F. Schwarz59,403,405,610, Richard A. Scolyer211,448,602, David Scott428, Ralph Scully611, Raja Seethala612, Ayellet V. Segre8,613, Iris Selander260, Colin A. Semple434, Yasin Senbabaoglu276, Subhajit Sengupta614, Elisabetta Sereni115, Stefano Serra585, Dennis C. Sgroi72, Mark Shackleton103, Nimish C. Shah352, Sagedeh Shahabi234, Catherine A. Shang329, Ping Shang211, Ofer Shapira8,323, Troy Shelton271, Ciyue Shen603,604, Hui Shen615, Rebecca Shepherd49, Ruian Shi490, Yan Shi134, Yu-Jia Shiah6, Tatsuhiro Shibata118,616, Juliann Shih8,82, Eigo Shimizu375, Kiyo Shimizu617, Seung Jun Shin618, Yuichi Shiraishi375, Tal Shmaya285, Ilya Shmulevich36, Solomon I. Shorser6, Charles Short59, Raunak Shrestha62, Suyash S. Shringarpure217, Craig Shriver619, Shimin Shuai6,126, Nikos Sidiropoulos83, Reiner Siebert112,620, Anieta M. Sieuwerts332, Lina Sieverling205,237, Sabina Signoretti202,621, Katarzyna O. Sikora177, Michele Simbolo138, Ronald Simon520, Janae V. Simons134, Jared T. Simpson6,17, Peter T. Simpson473, Samuel Singer115,458, Nasa Sinnott-Armstrong8,217, Payal Sipahimalani30, Tara J. Skelly390, Marcel Smid332, Jaclyn Smith622, Karen Smith-McCune514, Nicholas D. Socci276, Heidi J. Sofia27, Matthew G. Soloway134, Lei Song240, Anil K. Sood623,624,625, Sharmila Sothi626, Christos Sotiriou244, Cameron M. Soulette37, Paul N. Span627, Paul T. Spellman22, Nicola Sperandio177, Andrew J. Spillane211, Oliver Spiro8, Jonathan Spring628, Johan Staaf181, Peter F. Stadler163,164,165, Peter Staib629, Stefan G. Stark277,279,618,630, Lucy Stebbings49, Ólafur Andri Stefánsson631, Oliver Stegle59,60,632, Lincoln D. Stein6,126, Alasdair Stenhouse633, Chip Stewart8, Stephan Stilgenbauer634, Miranda D. Stobbe52,61, Michael R. Stratton49, Jonathan R. Stretch211, Adam J. Struck31, Joshua M. Stuart24,37, Henk G. Stunnenberg396,635, Hong Su56,396, Xiaoping Su99, Ren X. Sun6, Stephanie Sungalee60, Hana Susak52,53, Akihiro Suzuki89,636, Fred Sweep637, Monika Szczepanowski128, Holger Sültmann67,638, Takashi Yugawa617, Angela Tam30, David Tamborero298,299, Benita Kiat Tee Tan639, Donghui Tan518, Patrick Tan180,532,592,640, Hiroko Tanaka375, Hirokazu Taniguchi616, Tomas J. Tanskanen641, Maxime Tarabichi49,290, Roy Tarnuzzer220, Patrick Tarpey642, Morgan L. Taschuk152, Kenji Tatsuno89, Simon Tavaré223,643, Darrin F. Taylor113, Amaro Taylor-Weiner8, Jon W. Teague49, Bin Tean Teh180,592,640,644,645, Varsha Tembe246, Javier Temes104,105, Kevin Thai76, Sarah P. Thayer393, Nina Thiessen30, Gilles Thomas646, Sarah Thomas221, Alan Thompson221, Alastair M. Thompson633, John F. Thompson211, R. Houston Thompson647, Heather Thorne103, Leigh B. Thorne176, Adrian Thorogood424, Grace Tiao8, Nebojsa Tijanic284, Lee E. Timms272, Roberto Tirabosco648, Marta Tojo106, Stefania Tommasi649, Christopher W. Toon170, Umut H. Toprak48,650, David Torrents57,81, Giampaolo Tortora651,652, Jörg Tost653, Yasushi Totoki118, David Townend654, Nadia Traficante103, Isabelle Treilleux655,656, Jean-Rémi Trotta61, Lorenz H. P. Trümper469, Ming Tsao124,539, Tatsuhiko Tsunoda183,657,658,659, Jose M. C. Tubio104,105,106, Olga Tucker660, Richard Turkington661, Daniel J. Turner513, Andrew Tutt323, Masaki Ueno376, Naoto T. Ueno662, Christopher Umbricht151,213,663, Husen M. Umer305,664, Timothy J. Underwood665, Lara Urban59,60, Tomoko Urushidate616, Tetsuo Ushiku339, Liis Uusküla-Reimand666,667, Alfonso Valencia57,81, David J. Van Den Berg166, Steven Van Laere307, Peter Van Loo290,291, Erwin G. Van Meir668, Gert G. Van den Eynden307, Theodorus Van der Kwast123, Naveen Vasudev137, Miguel Vazquez57,669, Ravikiran Vedururu267, Umadevi Veluvolu518, Shankar Vembu490,670, Lieven P. C. Verbeke506,671, Peter Vermeulen307, Clare Verrill351,672, Alain Viari177, David Vicente57, Caterina Vicentini177, K. Vijay Raghavan365, Juris Viksna673, Ricardo E. Vilain674, Izar Villasante57, Anne Vincent-Salomon635, Tapio Visakorpi190, Douglas Voet8, Paresh Vyas311,351, Ignacio Vázquez-García49,86,675,676, Nick M. Waddell209, Nicola Waddell209,311, Claes Wadelius677, Lina Wadi6, Rabea Wagener111,112, Jeremiah A. Wala8,14,82, Jian Wang56, Jiayin Wang1,40,66, Linghua Wang12, Qi Wang465, Wenyi Wang21, Yumeng Wang21, Zhining Wang220, Paul M. Waring523, Hans-Jörg Warnatz483, Jonathan Warrell5,19, Anne Y. Warren352,678, Sebastian M. Waszak60, David C. Wedge49,294,679, Dieter Weichenhan345, Paul Weinberger680, John N. Weinstein38, Joachim Weischenfeldt60,83,84, Daniel J. Weisenberger166, Ian Welch681, Michael C. Wendl1,10,11, Johannes Werner47,85, Justin P. Whalley61,682, David A. Wheeler12,13, Hayley C. Whitaker117, Dennis Wigle683, Matthew D. Wilkerson518, Ashley Williams244, James S. Wilmott211, Gavin W. Wilson6,148, Julie M. Wilson148, Richard K. Wilson1,684, Boris Winterhoff685, Jeffrey A. Wintersinger17,127,384, Maciej Wiznerowicz686,687, Stephan Wolf688, Bernice H. Wong689, Tina Wong1,30, Winghing Wong690, Youngchoon Woo250, Scott Wood209,311, Bradly G. Wouters44, Adam J. Wright6, Derek W. Wright133,691, Mark H. Wright217, Chin-Lee Wu72, Dai-Ying Wu285, Guanming Wu692, Jianmin Wu170, Kui Wu56,396, Yang Wu179,180, Zhenggang Wu64, Liu Xi12, Tian Xia693, Qian Xiang76, Xiao Xiao66, Rui Xing497, Heng Xiong56,396, Qinying Xu209,311, Yanxun Xu694, Hong Xue64, Shinichi Yachida118,695, Sergei Yakneen60, Rui Yamaguchi375, Takafumi N. Yamaguchi6, Masakazu Yamamoto120, Shogo Yamamoto89, Hiroki Yamaue376, Fan Yang490, Huanming Yang56, Jean Y. Yang696, Liming Yang220, Lixing Yang697, Shanlin Yang306, Tsun-Po Yang270, Yang Yang369, Xiaotong Yao408,698, Marie-Laure Yaspo483, Lucy Yates49, Christina Yau156, Chen Ye56,396, Kai Ye40,41, Venkata D. Yellapantula20,86, Christopher J. Yoon249, Sung-Soo Yoon463, Fouad Yousif6, Jun Yu699, Kaixian Yu700, Willie Yu701, Yingyan Yu702, Ke Yuan223,510,703, Yuan Yuan21, Denis Yuen6, Takashi Yugawa617, Christina K. Yung76, Olga Zaikova704, Jorge Zamora49,104,105,106, Marc Zapatka397, Jean C. Zenklusen220, Thorsten Zenz67, Nikolajs Zeps705,706, Cheng-Zhong Zhang8,707, Fan Zhang381, Hailei Zhang8, Hongwei Zhang494, Hongxin Zhang121, Jiashan Zhang220, Jing Zhang5, Junjun Zhang76, Xiuqing Zhang56, Xuanping Zhang66,369, Yan Zhang5,708,709, Zemin Zhang381,710, Zhongming Zhao711, Liangtao Zheng381, Xiuqing Zheng381, Wanding Zhou615, Yong Zhou56, Bin Zhu240, Hongtu Zhu700,712, Jingchun Zhu24, Shida Zhu56,396, Lihua Zou713, Xueqing Zou49, Anna deFazio246,247,714, Nicholas van As221, Carolien H. M. van Deurzen715, Marc J. van de Vijver523, L. van’t Veer716 & Christian von Mering433,717, The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts.

SummaryThe landscape of structural variants (SVs) in multiple myeloma remains poorly understood. Here, we performed comprehensive classification and analysis of SVs in multiple myeloma, interrogating a large cohort of 762 patients with whole genome and RNA sequencing. We identified 100 SV hotspots involving 31 new candidate driver genes, including drug targets BCMA (TNFRSF17) and SLAMF7. Complex SVs, including chromothripsis and templated insertions, were present in 61 % of patients and frequently resulted in the simultaneous acquisition of multiple drivers. After accounting for all recurrent events, 63 % of SVs remained unexplained. Intriguingly, these rare SVs were associated with up to 7-fold enrichment for outlier gene expression, indicating that many rare driver SVs remain unrecognized and are likely important in the biology of individual tumors.

Purpose To describe the unique clinical features, determine the genomics, and investigate the metabolic derangement of an extremely rare form of a hereditary lethal kidney cancer syndrome. Patients and Methods Three patients with lethal kidney cancer (age 19, 20, and 37 years) exhibiting persistent (1 to 3 months) extremely high levels of blood lactate (> 5 mM) despite normal oxygen perfusion, highly avid tumors on [18F]fluorodeoxyglucose positron emission tomography (PET), and pleomorphic histopathologic features were identified and treated in a single institute. Integrated studies including whole-genome sequencing (WGS), targeted sequencing, immunohistochemistry, cell-based assays, and 18F-glutamine PET imaging were performed to investigate this rare kidney cancer syndrome. Results All three patients with kidney cancer were initially given various diagnoses as a result of diverse tumor histopathology and atypical clinical presentations. The correct diagnoses of these SDHB-mutated renal cell carcinomas were first made based on cancer genomics. Genomic studies of the blood and tumors of these patients identified three different kinds of germline loss-of-function mutations in the SDHB gene and the common loss of heterozygosity in the remaining SDHB allele thorough somatic chromosome 1p deletion. In one patient, WGS revealed that a germline mutation of SDHB coupled with loss of heterozygosity was the sole genetic event. Cancer evolution analysis of SDHB tumors based on WGS demonstrated that SDHB in kidney epithelium fulfills the Knudson two-hit criteria as a major tumor suppressor gene. SDHB−/− tumor cells displayed increase in glucose uptake and lactate production, alteration in mitochondrial architecture, and defect in oxidative respiration. 18F-Glutamine PET imaging studies demonstrated increased glutamine metabolism. Conclusion SDHB-deficient metastatic renal cell carcinoma is a rare, aggressive form of kidney cancer that manifests with clinical evidence of a severe Warburg effect, and genomic studies demonstrated two genetic hits at SDHB genes during kidney tumorigenesis.