6129 results for "canc*"

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• Light at Night and Prostate Cancer in the Health Professionals Follow-Up Study

  The Health Professionals Follow-Up Study (HPFS) is a prospective cohort study of men designed to evaluate hypotheses about men's health related to diet and lifestyle to the incidence of serious illnesses, such as cancer, heart disease, and other vascular diseases. It consisted of 51,529 U.S. male health professionals who were 40-75 years old at baseline in 1986 and completed a mailed six-page baseline questionnaire. Information on age, height, weight, ancestry, medications, disease history, physical activity, lifestyle factors, and diet were gathered, with follow-up questionnaires sent biennially to update information and record health outcomes with every four years to update their diet. Light at Night and Prostate Cancer project uses HPFS participants to conduct research assessing the impact of light at night on prostate cancer incidence, with follow-up from baseline in 1986 to 2016. Average annual outdoor light at night (exposure) was derived from satellite imagery data from the US Defense Meteorological Satellite Program's Operational Linescan System (maintained by the National Oceanic and Atmospheric Administration's Earth Observation Group). Prostate cancer cases (outcome) were self-reported by study participants, and then confirmed by the HPFS team through medical record and pathology report review. The data for this project are arranged in a long format, meaning that there are multiple rows for each subject ID. The various rows correspond to different questionnaire periods. Because the exposure in this dataset, light at night, and several important covariates are time-varying variables, the format of this dataset captures the variation in exposure status by questionnaire period. The outcome variables are incidence of prostate cancer, including incidence of prostate cancer clinical subtypes, such as advanced, aggressive, high- and low-grade prostate cancer. For the published study, please see Chowdhury-Paulino et al.'s 2023 publication in Cancer Epidemiology Biomarkers and Prevention entitled, “Association between Outdoor Light at Night and Prostate Cancer in the Health Professionals Follow-up Study.” (PMID: 37462694).

  Study phs003538

• Phase 2 Study of Pembrolizumab in Combination with Gemcitabine and Cisplatin as Neoadjuvant Therapy

  The purpose of the clinical trial (NCT02690558) is to evaluate whether adding pembrolizumab (Keytruda) to the combination of gemcitabine and cisplatin will improve shrinkage of the tumor before having a cystectomy, for people with muscle-invasive bladder cancer (MIBC).

  Study phs003452

• Immune Responses in Checkpoint Myocarditis Across Heart, Blood, and Tumor

  Immune checkpoint inhibitors (ICIs) are widely used in anti-cancer therapies, but they can cause morbid and potentially fatal immune-related adverse events (irAEs), such as ICI-related myocarditis (irMyocarditis). The pathogenesis of irMyocarditis and its relationship to anti-tumor immunity remain poorly understood. We sought to define immune responses in heart, tumor, and blood in irMyocarditis patients and controls by leveraging single‐cell RNA sequencing (scRNA‐seq) coupled with T-cell Receptor Sequencing (TCR-Seq). Our analysis demonstrated increased frequencies of cytotoxic T cells, inflammatory mononuclear phagocytes (MNPs), conventional dendritic cells (cDCs), and inflammatory fibroblasts in irMyocarditis heart tissue. Additionally, we revealed decreased frequencies of plasmacytoid dendritic cells, cDCs, and B lineage cells but an increased frequency of MNPs in the blood of irMyocarditis patients. Raw data for heart and blood can be found in dbGaP. All processed data and raw TCRseq data from heart tissue and tumor samples for this study can be found in GEO (Accession number GSE228597).Subject IDs with the prefix "SIC" were collected by the Severe Immunotherapy Complications (SIC) service at MGH due to suspicion of immune-related adverse events. Subject IDs with the prefix "donor" were collected by the MGH Melanoma Biobank at scheduled timepoints; this biobank systematically collects samples from patients at MGH at clinically relevant timepoints.

  Study phs003413

• Common Deleterious Germline Variants Shape the Urothelial Cancer Genome

  Our study used whole-exome, whole-genome, and RNA sequencing to analyze samples from primary tumors, locally recurrent or metastatic urothelial tumors collected over time, and matched normal urothelium. We described the molecular landscape of mutational signatures and structural variants in chemotherapy-resistant urothelial cancer.

  Study phs001087

• Germline Mutations and Developmental Mosaicism Underlying EGFR-Mutant Lung Cancer

  We designed this study to examine the etiology of multiple lung tumors in EGFR-mutant non-small cell lung cancer patients who undergo surgical resection. Participants were 52-85 years old never or former smokers, who had at least 2 surgical lung tumor pathology specimens available in the Massachusetts General Hospital biobank, at least one of which had an EGFR mutation by routine clinical genotyping. 10 patients were selected, along with two patients from a family with an inherited EGFR-T790M mutation leading to multiple lung tumors. These patient tumor samples and matched normal lung samples were microdissected to collect DNA.In addition to obtaining clinical histories, we performed whole exome sequencing to evaluate the genetic profile of matched tumor and normal samples. The WES data are available on dbGaP. Our data showed increasing mutational burden and copy number alteration with increasing invasiveness, as compared to normal tissues, for the subset of samples that were assessed for tumor invasiveness. We also observed a range of numbers of shared mutations between tumors in a single patient, indicating different degrees of relatedness between lung tumors. We hope that this resource will help researchers understand non-small cell lung cancer presentations with multiple lung tumors. These data may aid in clinical decision making for such patients.

  Study phs003379

• Integrative Analysis for Multi-Omics Data in Non-Small-Cell Lung Cancer

  We conducted epigenetic and transcriptomic mapping of primary non-small cell lung tumors and non-neoplastic tissues. 20 non-neoplastic lung tissues and 18 non-small cell lung tumors were obtained from Biorepository and Tissue Technology Shared Resource at Moores Cancer Center, UC San Diego. All tumor samples were in pathological stages I and II. 8 pairs of samples were "matched", meaning that the tumor and normal tissues came from the same patient. Microfluidic oscillatory washing–based chromatin immunoprecipitation followed by sequencing (MOWChIP-seq) was used to profile the binding of H3K4me1, H3K4me3, H3K9me3, H3K27ac and H3K27me3. SmartSeq-2 was used to map mRNA expression. We identified a large number of differentially modified regions for both epigenetic and transcriptomic markers between tumors and normal tissues. Deep learning model showed extensive transcription factor network rewiring. Raw sequencing data of the ChIP-seq and RNA-seq libraries are available through this dbGaP submission.

  Study phs003113

• Childhood Cancer Data Initiative (CCDI): Identification and Targeting of Treatment Resistant Progenitor Populations in T-cell Acute Lymphoblastic Leukemia

  Our goal with this study was to identify the mechanisms of treatment resistance in T-cell acute lymphoblastic leukemia (ALL) using single-cell genomics. We profiled 40 T-ALL cases from the Children's Oncology Group AALL0434 clinical trial using CITE-seq/snATAC-seq, capturing a breadth of immunophenotypes, including early T-cell precursor (ETP) and near-ETP/non-ETP subtypes. By integrating analyses of T-ALL cells with the normal T-cell developmental trajectory, the study identified a specific subgroup of leukemia cells resembling bone marrow progenitors (BMP-like cells). These BMP-like cells were associated with treatment failure and poor overall survival in T-ALL patients. Overall, this study reveals comprehensive multiomic signatures for rapidly assessing risk and tailoring targeted treatment for high-risk T-ALL patients.

  Study phs003432

• Structure of the Mucosal and Stool Microbiome in Lynch Syndrome

  The gut microbiota has been associated with colorectal cancer (CRC), but causal alterations preceding CRC have not been elucidated. To prospectively assess microbiome changes prior to colorectal neoplasia, we investigated samples from 100 Lynch syndrome patients using 16S rRNA gene sequencing of colon biopsies, coupled with metagenomic and metatranscriptomic sequencing of feces. Colectomy and CRC history represented the largest effects on microbiome profiles. A subset of Clostridiaceae were depleted in stool corresponding with baseline adenomas, while Desulfovibrio was enriched in both stool and mucosal biopsies. A classifier leveraging stool metatranscriptomes resulted in modest power to predict interval development of preneoplastic colonic adenoma. Predictive transcripts corresponded with a shift in flagellin contributors and oxidative metabolic microenvironment, potentially factors in local CRC pathogenesis. This suggests that the effectiveness of prospective microbiome monitoring for adenomas may be limited but supports the potential causality of these consistent, early microbial changes in colonic neoplasia.

  Study phs002343

• Transcriptomic Profiling of Peripheral Immune Cells in a Trial of Ruxolitinib with Nivolumab for Anti-PD1 Non-Responsive cHL

  Treatment with checkpoint inhibitors is effective in multiple cancer types. However, even in cancers with high response rates such as Hodgkin lymphoma, some patients fail to respond or relapse following an initial response to checkpoint inhibitors. In this study, we examined patients enrolled in a clinical trial of ruxolitinib with nivolumab in relapsed or refractory Hodgkin lymphoma (NCT03681561). Patients relapsed or refractory to anti-PD1 therapy received ruxolitinib for 8 days followed by nivolumab every 4 weeks and continued ruxolitinib twice daily. For this transcriptomic study, peripheral blood mononuclear cells (PBMCs) were collected at baseline and 8 days of ruxolitinib therapy and analyzed by single-cell and bulk RNA-sequencing.

  Study phs003601

• Natural Killer Cell Therapies for Hematologic Malignancies

  The "Natural Killer Cell Therapies for Hematologic Malignancies" study is an umbrella repository for data pertaining to multiple related clinical trials that aim to assess NK cell therapies as part of treatment strategies for a range of hematologic malignancies. Here, data from two trials, NCT03068819 and NCT02782546, are presented.Cytokine Induced Memory-like NK Cell Adoptive Therapy for Relapsed AML after Allogeneic Hematopoietic Cell Transplant in Children and Adults (NCT03068819)Pediatric and young adult (YA) patients with acute myeloid leukemia (AML) who relapse after allogeneic hematopoietic cell transplantation (HCT) have extremely poor prognosis. Standard salvage chemotherapy and donor lymphocyte infusions (DLI) have little curative potential. Previous studies showed that natural killer (NK) cells can be stimulated ex vivo with interleukin-12 (IL-12), IL-15, and IL-18 to generate memory-like (ML) NK cells with enhanced anti-leukemia responses. We treated nine pediatric/YA patients with post-HCT relapsed AML with donor ML NK cells on a phase I trial. Patients received fludarabine, cytarabine, and filgrastim followed two weeks later by infusion of DLI and ML NK cells from the original HCT donor. ML NK cells were successfully generated from haploidentical, matched-related and matched-unrelated donors. Following infusion, donor-derived ML NK cells expanded and maintained ML multidimensional mass cytometry phenotype for over 3 months. Furthermore, ML NK cells exhibited persistent functional responses as evidenced by leukemia-triggered IFN-gamma production. Following DLI and ML NK cell adoptive transfer, 4 of 8 evaluable patients achieved complete remission at day 28. Two patients maintained a durable remission for over 3 months with one patient in remission for greater than two years. No significant toxicity was experienced. This study demonstrates that in a compatible immune environment post-HCT, donor ML NK cells robustly expand and persist with potent anti-leukemic activity in the absence of exogenous cytokines. ML NK cells in combination with DLI present a novel immunotherapy platform for AML that has relapsed after allogeneic HCT. This trial was registered at https://www.clinicaltrials.gov/study/NCT03068819.A Phase II Study of Cytokine Induced Memory-like NK Cell Adoptive Therapy after Haploidentical Donor Hematopoietic Cell Transplantation (NCT02782546)Natural killer (NK) cells are innate lymphoid cells that eliminate cancer cells, produce cytokines, and are being investigated as a nascent cellular immunotherapy. Impaired NK cell function, expansion, and persistence remain key challenges for optimal clinical translation. One promising strategy to overcome these challenges is cytokine-induced memory-like (ML) differentiation, whereby NK cells acquire enhanced anti-tumor function following stimulation with IL-12, IL-15, and IL-18. Here, reduced-intensity conditioning (RIC) for HLA-haploidentical hematopoietic cell transplantation (HCT) was augmented with same-donor ML NK cells on Day 7 and 3 weeks of N-803 (IL-15 superagonist) to treat patients with relapsed/refractory acute myeloid leukemia (AML) in the clinical trial (NCT02782546). In 15 patients, donor ML NK cells were well-tolerated and 87% of patients achieved a composite complete response at Day 28, which corresponded with clearing high-risk mutations, including TP53 variants. NK cells were the major blood lymphocytes for two months post-HCT with prolific expansion (1104-fold) over 1-2 weeks. Multidimensional mass cytometry and CITE-seq identified donor ML NK cells as distinct from conventional NK cells and persisting for over two months. ML NK cells expressed CD16, CD57, and high granzyme B and perforin, along with a unique transcription factor profile. ML NK cells differentiated in patients had enhanced ex vivo function compared to conventional NK cells from both patient and healthy donors. Overall, same-donor ML NK cell therapy with 3 weeks of N-803 support safely augmented RIC haplo-HCT for AML, with ML NK cells demonstrating enhanced in vivo persistence and functionality, overcoming barriers in the field.

  Study phs002681

• Genomic Characterization CS-MATCH-0007 Arm C1

  The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing and RNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm C1 is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with MET amplification are treated with Crizotinib. This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood.

  Study phs002177

• Genomic Characterization CS-MATCH-0007 Arm P

  The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing and RNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm P is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with PTEN loss by IHC are treated with the drug GSK2636771. This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood.

  Study phs002152

• Genomic Characterization CS-MATCH-0007 Arm Z1B

  The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing and RNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm Z1B is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with CCND1, CCND2, and/or CCND3 amplifications are treated with Palbociclib. This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood.

  Study phs002180

• Tumor detection by analysis of both symmetric- and hemi-methylation of plasma cell-free DNA

  Aberrant DNA methylation plays a critical role in tumorigenesis. While DNA methylation has been used for cancer detection and classification, DNA hemi-methylation, a novel epigenetic mark has not been analyzed extensively in cancer epigenomes. Here we report a strand-specific (ss) sequencing method (MeDIP-Seq) for plasma cell free (cf) DNA (sscf-MeDIP-Seq), which can analyze both symmetrically methylated DNA regions (DMRs) as well as hemi-methylated regions (DHMRs). Using the sscf-MeDIP-Seq method, we analyzed plasma cfDNA methylomes of 271 samples from subjects with liver cancer and brain cancer and from individuals without cancer (controls). Among them, 215 samples were chosen as the discovery cohort for the identification of DMRs and DHMRs specific in each subject group and for the training of machine learning models of multi-cancer detection (MCD) using DMRs, DHMRs and DMRs+DHMRs as inputs. These models were then used to predict the 56 samples in the validation cohort. We found that models trained with DMRs+DHMRs as inputs in general outperformed models trained with DMRs or DHMRs alone, with AUROC being 0.971, 0.981, and 0.99 in predicting control, liver and brain cancer samples in the validation cohort, respectively, by the DMR+DHMR-trained models.

  Study phs003462

• Childhood Cancer Data Initiative (CCDI): Molecular Characterization Initiative

  The National Cancer Institute's (NCI) Childhood Cancer Data Initiative (CCDI) focuses on the critical need to collect, analyze, and share data to address the burden of cancer in children, adolescents, and young adults (AYAs). The Molecular Characterization Initiative (MCI) will further the CCDI's goals by providing access to better diagnostic tests for pediatric and AYA patients. The molecular characterizations of solid tumors, soft tissue sarcomas, and rare diseases are performed in a CLIA-certified setting as results may be used to screen for and/or confirm clinical trial eligibility, direct treatment, or otherwise contribute to the conduct of the trial. The following molecular characterization assays were performed:Tumor/Normal Whole Exome sequencing Methylation arraysArcher fusion panel Deidentified clinical reportsNote: New data will be added periodically, please check the CCDI Hub Explore site for updates.

  Study phs002790

• Comprehensive Genomic Characterization of Translocation Renal Cell Carcinoma

  Xp11 translocation renal cell carcinoma (tRCC) is a rare, female-predominant cancer driven by a fusion between the TFE3 gene on chromosome Xp11.2 and a partner gene on either chrX or an autosome. It remains unknown what types of rearrangements underlie TFE3 fusions, whether fusions can arise from both the active (chrXa) and inactive X (chrXi) chromosomes, and whether TFE3 fusions from chrXi translocations account for the female predominance of tRCC. To address these questions, we performed haplotype-specific analyses of chrX rearrangements in tRCC whole genomes. We show that TFE3 fusions universally arise as reciprocal translocations and that oncogenic TFE3 fusions can arise from chrXi:autosomal translocations. Female-specific chrXi:autosomal translocations result in a 2:1 female-to-male ratio of TFE3 fusions involving autosomal partner genes and account for the female predominance of tRCC. Our results highlight how X chromosome genetics uniquely constrains somatic chrX alterations and underlies cancer sex differences.This version of the dbGaP study provides a comprehensive set of whole genome data and tables with clinical information collected for the 16 patients (15 pateints as tRCC and 1 patient as ccRCC) in the study cohort. The data also contains 12 RNA-seq samples used in the study and analyses. We anticipate that this data will considerably advance our molecular and genetic understanding of oncogenic translocations in TFE3-tRCC involving inactive chromosome X and its role in cancer sex bias.

  Study phs003008

• Aberrant Activation of Wound Healing Programs within the Metastatic Niche Facilitates Lung Colonization by Osteosarcoma Cells

  Lung metastasis is responsible for nearly all deaths caused by osteosarcoma, the most common pediatric bone tumor. How malignant bone cells coerce the lung microenvironment to support metastatic growth is unclear. This study delineates how osteosarcoma cells educate the lung microenvironment during metastatic progression.Using single-cell transcriptomics (scRNA-seq), we characterized genome– and tissue-wide molecular changes induced within lung tissues by disseminated osteosarcoma cells in both immunocompetent murine models of metastasis and patient samples. We confirmed transcriptomic findings at the protein level and determined spatial relationships with multi-parameter immunofluorescence. We evaluated the ability of nintedanib to impair metastatic colonization and prevent osteosarcoma-induced education of the lung microenvironment in both immunocompetent murine osteosarcoma and immunodeficient human xenograft models.Osteosarcoma cells induced acute alveolar epithelial injury upon lung dissemination. scRNA-seq demonstrated that the surrounding lung stroma adopts a chronic, non-resolving wound-healing phenotype similar to that seen in other models of lung injury. Accordingly, metastasis-associated lung demonstrated marked fibrosis, likely due to the accumulation of pathogenic, pro-fibrotic, partially-differentiated epithelial intermediates. Inhibition of fibrotic pathways with nintedanib prevented metastatic progression in multiple murine and human xenograft models. Our work demonstrates that osteosarcoma cells co-opt fibrosis to promote metastatic outgrowth. When harmonized with data from adult epithelial cancers, our results support a generalized model wherein aberrant mesenchymal-epithelial interactions are critical for promoting lung metastasis. Adult epithelial carcinomas induce fibrotic pathways in normal lung fibroblasts, whereas osteosarcoma, a pediatric mesenchymal tumor, exhibits fibrotic reprogramming in response to the aberrant wound-healing behaviors of an otherwise normal lung epithelium, which are induced by tumor cell interactions.

  Study phs003569

• Molecular Characterization of Prostate Cancer Specimens by Bulk and Single Cell Analysis

  Version 1: We performed single-cell RNA-sequencing (scRNA-seq) of fresh biopsies from metastatic castration resistant prostate cancer. Additionally, where available, we performed matched bulk whole exome sequencing (WXS; tumor and normal paired) and whole transcriptome sequencing for the same individuals. We also performed bulk whole exome (WXS) and RNA-sequencing (RNA-Seq) from FFPE pre-treatment biopsies from patients with clinically localized high-risk prostate cancer.Version 2: We added data from a randomized phase 2 trial of radium-223 with or without pembrolizumab in patients with Metastatic Castration-Resistant Prostate Cancer (mCRPC) to bone. After enrollment, study participants underwent bone biopsy and were randomized 2:1 to receive radium-223 at 55 kBq/kg every 4 weeks + pembrolizumab at 200 mg every 3 weeks (Arm A, R223+P) or radium-223 at 55 kBq/kg every 4 weeks alone (Arm B, R223). Stratification factors were alkaline phosphatase ≥220 vs. Data generated includes bulk whole exome sequencing (WXS), ultra-low pass whole genome sequencing (WGS) at 0.1X coverage, and targeted-capture sequencing. The ultra-low pass sequencing was used as part of the selection criteria for the target capture sequencing. Note: Two subjects in this study are linked to phs001577 and phs000915 respectively.

  Study phs001988

• Childhood Cancer Data Initiative (CCDI): Single-Cell Atlas of NF1 Nerve Sheath Tumors

  The worst outcome of NF1 is the development of the aggressive and highly metastatic malignant peripheral nerve sheath tumors (MPNST), which transform from benign plexiform neurofibroma (PN) and lack effective treatment. In this study, we performed single-cell RNA sequencing of 63 clinically annotated NF1-associated peripheral nerve sheath tumors, including 24 PN, 34 premalignant atypical neurofibromas, and 5 MPNSTs. These results improve the ability of identifying high-risk neurofibromas and provide a unique opportunity for early detection of MPNST.

  Study phs003519

• Single-Cell RNA-Sequencing of Human Prostatectomy Tissue

  The tissue microenvironment in prostate cancer is profoundly altered. How prostate cancer cells and their precursors mediate those changes is unclear, in part due to the inability to longitudinally study the disease evolution in human tissues. To overcome this limitation, we performed extensive single-cell RNA-sequencing (scRNA-seq) to assess the transcriptional profiles of the tissue microenvironment in prostate tissues from prostatectomies from men diagnosed with prostate cancer. For each subject, benign-enriched and tumor-enriched tissues were collected from the peripheral zone of the prostate. Our studies of human tissues revealed that cancer cell-intrinsic activation of MYC signaling was the top up-regulated pathway in human cancers, representing a common denominator across the well-known molecular and pathological heterogeneity of human prostate cancer. Numerous non-malignant cell states in the tumor microenvironment (TME), including non-cancerous epithelial, immune, and fibroblast cell compartments, were conserved across individuals, suggesting that these cell types may be a sequelae of the convergent MYC activation in the cancer cells.

  Study phs003480

• Basal-to-Inflammatory Transition Contributes to Basal Cell Carcinoma Therapy Resistance via Crosstalk with a Pro-Inflammatory Stromal Niche

  Overcoming tumor evolution and inducible resistance states remain the main challenge to creating successful anti-tumor therapies. The body's cancer-associated inflammatory response is a double-edged sword having ill-defined pro- and anti-tumor properties. Our group previously identified a basal cell carcinoma (BCC) tumor-intrinsic resistance pathway called basal to squamous cell carcinoma transition (BST). However, tumor resistance driven through the complex dynamics of tumor interactions with the inflammatory response remains poorly studied. Here, employing a multipronged approach combining human tumor single-cell transcriptomics, single-cell chromatin accessibility (scATAC-Seq) study, CODEX multiplexed imaging, spatial transcriptomic along with functional validation, we have identified a surprising inflammation-associated SMOi therapy enriched tumor epithelial cell state we term basal-to-inflammatory transition (BIT). Marked by CHI3L1, TAGLN, ITGAV, and VCAM1, BIT arises in spatially distinct neighborhoods from BST in a subset of naive BCCs. While BST tumor epithelium occurs within the central cores of tumor nodules, BIT tumor epithelium arises in a specialized inflammatory environment defined by a tumor associated TREM1 myeloid signature. IL1 and OSM secreted by TREM1 myeloid cells activate the inflammatory NF-kB family of transcription factors within the BIT tumor epithelium. Strikingly, IL1 and OSM ligands are sufficient not only in inducing the BIT tumor state in vitro and in vivo in a synergistic fashion but also in lowering the sensitivity of human BCC explant tumors to SMOi treatment. This work provides critical insights into the BIT-resistant state as a novel targetable tumor state driven by a specialized inflammatory microenvironment.

  Study phs003437

• Genetic Analysis of Skin Cells

  Cutaneous squamous cell carcinoma (cSCC) is a form of skin cancer originating from keratinocytes in the skin. They have high mutation burdens, primarily driven by UV-radiation-induced DNA damage. The order in which mutations undergo selection during the evolution of cSCC is not known. A subset of cSCCs grow out of benign neoplasms called actinic keratoses. To better understand the evolution of cSCC, we identified cases of cSCCs adjacent to actinic keratoses. From these cases, we separately microdissected the surrounding normal skin, the actinic keratosis, and the cSCC, and we performed targeted DNA-sequencing on the tissue from each area. We reconstructed tumor phylogenies and performed spatial transcriptomics on the 10X FFPE Visium platform on a subset of cases. Collectively, these studies revealed the mutational and gene expression changes that arise during the evolution of cSCC.

  Study phs003282

• Lung Cancer Genetic Study Among Asian Never Smokers

  The Lung Cancer Genetic Study Among Asian Never Smokers includes data from four population-based studies conducted among Asian women: the Shanghai Women's Health Study (SWHS), the Hwasun Cancer Epidemiology Study (HCES1 and HCES2), the Female Lung Cancer Consortium in Asia (FLCCA, including sFLCA), and the Guangzhou Lung Cancer Study (GLCS). Shanghai Women's Health Study (SWHS): The SWHS is a population-based prospective cohort study of approximately 75,000 adult women who were recruited between 1997 and 2000. The cohort has been followed by a combination of record linkage and active follow-ups. Lung cancer patients identified in the SWHS and non-cases were included in the current study.Hwasun Cancer Epidemiology Study-Lung Cancer (HCES1 and HCES2): The HCES is a hospital-based case-control study whose goal is to identify factors of the cancer development and clinical progression in a Korean population. Included in this project were 299 female lung cancer cases from HCES2, who were diagnosed between April 2004 and February 2013 at Chonnam National University Hwasun Hospital, a cancer specified hospital in Jeollanam-do province, South Korea. Controls were randomly selected from women with no previous cancer diagnosis at enrollment in the Namwon Study and the Dong-gu study, ongoing community-based cohort studies in South Korea. A total of 1,103 controls (273 from HCES1 and 830 from HCES2) were genotyped by MEGA. Guangzhou Lung Cancer Study (GLCS): The GLCS is a case-control study including never-smoking women lung cancer cases and controls from Guangzhou, China.In this study, the DNA samples of 1,195 subjects from SWHS and GLCS were genotyped using whole exome sequencing (WES), and the DNA samples of 7,174 subjects from SWHS, HCES1, HCES2, FLCCA, and sFLCA were genotyped using the Multi-Ethnic Global Array (MEGA).

  Study phs002366

• The Genetic Basis of Aggressive Prostate Cancer, The Role of Rare Variation

  In this study, we will apply a multi-staged approach to reveal genes harboring rare variants that are associated with aggressive PCa. Whole-exome sequencing (Aim 1a) of 2,774 aggressive cases and 2,776 non-aggressive cases of European ancestry will be conducted followed by rare variant analysis of single sites and gene burden testing to identify novel susceptibility loci/genes for aggressive disease. We will validate the most significantly associated genes (~500) through targeted sequencing in an additional 6,415 aggressive and 5,586 non-aggressive cases and 1,890 controls (Aim 1b). Next, we will investigate the clinical predictive utility of the genes/variants identified in 2,291 cases in the STHM3 trial who are undergoing biopsy based on PSA and genetic risk score stratification (Aim 2). Through this tiered approach we expect to significantly advance knowledge of aggressive PCa etiology and health disparities as well as guide the development of early detection and prognostic strategies for the subset of men who are most susceptible to this fatal form of disease. In this case-case study of aggressive vs non aggressive prostate cancer, aggressive cases are defined as prostate cancer as cause of death, (T4 disease or T3 disease) and Gleason 8+. Non-aggressive cases are men with T1/2 disease and Gleason ACKNOWLEDGMENTS and CONTRIBUTING SITES CAPS, PROCAP, STHM1, STHM2: Swedish Cancer Society (CAN 2016/818), Swedish Research Council (2014/2269).STHM3: Stockholm County Council (Stockholms Läns Landsting).MEC: Funding provided by the National Cancer Institute: Understanding Ethnic Differences in Cancer, 2U01CA164973 and The Genetic Basis of Aggressive Prostate Cancer, The Role of Rare Variation, 5R01CA196931-02.ATBC: The ATBC Study is supported by the Intramural Research Program of the U.S. National Cancer Institute, National Institutes of Health, and by U.S. Public Health Service contract HHSN261201500005C from the National Cancer Institute, Department of Health and Human Services.COSM: The Swedish Research Council/National Research Infrastructure Grant (VR 2014/6397; VR 2015/5997) The Swedish Cancer Foundation (CAN 2013/456; CAN 2016/727)CPSII: The authors express sincere appreciation to all Cancer Prevention Study II participants and to each member of the study and biospecimen management group. The American Cancer Society funds the creation, maintenance, and updating of the Cancer Prevention Study-II cohort.MCCS/APCS/PCFS: The Melbourne Collaborative Cohort Study (MCCS) recruitment was funded by VicHealth and Cancer Council Victoria and further supported by Australian National Health and Medical Research Council (NHMRC) grants 209057 and 396414. The Aggressive Prostate Cancer Case-Control Study (APCS) was funded by NHMRC grant 623204. The Prostate Cancer Family Study (PCFS) was fully funded by Cancer Council Victoria. Cancer Council Victoria funds the continuing maintenance and updating of the MCCS, APCS and PCFS. Cases and their vital status are ascertained and followed up through the Victorian Cancer Registry and the Australian Institute of Health and Welfare, including the National Death Index and the Australian Cancer Database.PLCO: The Prostate Lung Colorectal Ovarian Cancer Screening Trial (PLCO) was supported by the Intramural Research Program of the Division of Cancer Epidemiology and Genetics and by contracts from the Division of Cancer Prevention, National Cancer Institute, US National Institutes of Health, Department of Health and Human Services. EPIC: The coordination of EPIC is financially supported by International Agency for Research on Cancer (IARC) and also by the Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London which has additional infrastructure support provided by the NIHR Imperial Biomedical Research Centre (BRC). The national cohorts are supported by: Danish Cancer Society (Denmark); Ligue Contre le Cancer, Institut Gustave Roussy, Mutuelle Générale de l'Education Nationale, Institut National de la Santé et de la Recherche Médicale (INSERM) (France); German Cancer Aid, German Cancer Research Center (DKFZ), German Institute of Human Nutrition Potsdam- Rehbruecke (DIfE), Federal Ministry of Education and Research (BMBF) (Germany); Associazione Italiana per la Ricerca sul Cancro-AIRC-Italy, Compagnia di SanPaolo and National Research Council (Italy); Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF), Statistics Netherlands (The Netherlands); Health Research Fund (FIS) - Instituto de Salud Carlos III (ISCIII), Regional Governments of Andalucía, Asturias, Basque Country, Murcia and Navarra, and the Catalan Institute of Oncology - ICO (Spain); Swedish Cancer Society, Swedish Research Council and County Councils of Skåne and Västerbotten (Sweden); Cancer Research UK (14136 to EPIC-Norfolk; C8221/A19170 and C8221/A29017 to EPIC-Oxford), Medical Research Council (1000143 to EPIC-Norfolk; MR/M012190/1 to EPIC-Oxford). (United Kingdom). DFCI: Linda and Arthur Gelb and Rebecca and Nathan Milikowsky. HPFS and PHS: The Health Professionals Follow-up Study was supported by U01 167552 and P01 CA228696 from the National Cancer Institute, and with support from the Prostate Cancer Foundation. The Physicians' Health Study was supported by grants CA34944, CA40360, CA097193, HL26490 and HL34595.Northwestern: P50CA180995 (Catalona) 08/01/15 – 07/31/20 NIH/NCI SPORE in Prostate Cancer; The Urological Research FoundationPROMPT: MRC UK - Project reference G0500966, Cambridge BRC infrastructure funding, Cambridge Biomedical Research Campus (BRC-1215-20014), CRUK Cambridge Cancer Centre infrastructure funding (they are requesting this statement is written in blue for publications).ICR: This work was supported by the NIH R01 grant 5R01CA196931-02. The samples from the UK were from UKGPCS and PrompT. The UKGPCS study was supported by Cancer Research UK (grant numbers C5047/A7357, C1287/A10118, C1287/A5260, C5047/A3354, C5047/A10692, C16913/A6135 and C16913/A6835). We would like to acknowledge the NCRN nurses and Consultants for their work in the UKGPCS study. We thank all the patients who took part in this study. We also acknowledge The Institute of Cancer Research, The National Cancer Research Network UK, The National Cancer Research Institute (NCRI) UK for their ongoing support. We are grateful for support of NIHR funding to the NIHR Biomedical Research Centre at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust.Funding:CIDR grant X01HG008336

  Study phs001524

• The Cancer Dependency Map (DepMap)

  The Cancer Dependency Map (DepMap) aims to accelerate precision cancer medicine by creating a comprehensive map of tumor vulnerabilities. The DepMap project genomically profiles a wide range of cancer models and characterizes them for their sensitivity to genetic and compound perturbations. The data is computationally analyzed to create a systematic overview of the genetic dependencies and compound sensitivities of cancer types and the predictive biomarkers that point to patient populations most likely to benefit from targeting of these vulnerabilities. The DepMap public portal has become a comprehensive resource to identify cancer vulnerabilities by providing datasets at scale, cutting-edge computational tools, and sophisticated visualization tools that together have accelerated the discovery of novel targets and biomarkers. Please visit Depmap.org to access the public portal.

  Study phs003444

• Botensilimab, an Fc-enhanced Anti-CTLA-4 Antibody, is Effective Against Tumors Poorly Responsive to Conventional Immunotherapy

  This study explores the genomic landscape associated with a novel Fc-engineered anti-CTLA-4 antibody (botensilimab) in advanced solid tumors. We seek to understand if enhancing the Fc-region affinity of anti-CTLA-4 antibodies can improve anti-tumor efficacy and expand clinical benefit to tumors poorly responsive to conventional immunotherapy. As part of an ongoing open-label, Phase 1, multicenter study, we conducted an exploratory sub-analysis of genomics data. The primary study evaluates the safety, tolerability, pharmacokinetics, and pharmacodynamics of botensilimab monotherapy and in combination with an anti-PD-1 antibody (balstilimab) in participants with advanced solid tumors. RNA from formalin-fixed paraffin-embedded (FFPE) tumor biopsies and matched normal blood samples were isolated and subjected to RNA-sequencing using the Personalis ImmunoID NeXT Platform. We demonstrated that anti-CTLA-4 engineered for enhanced FcγR affinity leverages FcγR-dependent mechanisms to potentiate T cell responsiveness, reduce intratumoral Tregs, and enhance antigen presenting cell activation. This genomic analysis contributes to our understanding of the molecular mechanisms underlying patient responses to Fc-engineered anti-CTLA-4 therapy and may inform future strategies to expand the clinical benefit of immune checkpoint blockade in cancer immunotherapy.

  Study phs003704

• Molecular Analysis of Alliance A031201 Study

  This is the first study examining the relationship between clonal hematopoiesis and clinical outcomes in prostate cancer patients. We used a targeted gene sequencing panel to identify patients in the A031201 clinical trial with and without clonal hematopoiesis. We found that clonal hematopoiesis did not affect overall or progression free survival in A031201 but was associated more adverse cardiac events.

  Study phs003717

• The Somatic Mutational Landscape of Thyroid Cancer in Patients with Germline PTEN Mutations

  PTEN hamartoma tumor syndrome (PHTS) is associated with a high rate of thyroid cancer and benign thyroid disease, yet nothing is known of the genomic landscape of PHTS-associated thyroid tumors. In this study, exome sequencing was performed on 58 thyroid tumors (28 cancers, 30 benign nodules) from 19 patients with PHTS, sequenced in tumor-normal pairs. Somatic variant calling was utilized to determine the somatic mutational landscape of thyroid tumors in this population. This was then compared to the known mutational landscape of sporadic thyroid cancer in the general population using sequencing data from The Cancer Genome Atlas. The primary finding of the study was that PHTS-associated thyroid tumors had a unique genomic landscape, including a high frequency of second-hit somatic PTEN alterations compared to the sporadic thyroid tumors. Additionally, PHTS-associated thyroid cancers were found to have somatic alterations in BRAF, RAS family members, and genes associated with DNA double stranded break repair. Data available through dbGAP will include tumor BAM files for each tumor, normal BAM files for each patient, and MAF files for PHTS-associated thyroid cancer and PHTS associated benign thyroid nodules.

  Study phs003640

• A genotype-phenotype study of tumors from patients with inherited mutations in DNA repair genes

  This study investigated the genomic landscape of tumors from patients with inherited mutations in DNA repair genes. The aim of this study was to determine the relationship between locus-specific loss of heterozygosity (LOH) and genomic signatures of homologous recombination-based DNA repair (HR) deficiency in tumors associated with pathogenic germline variants in DNA repair genes. Cohorts of pathogenic germline variant (PGV) carriers with different cancer types were identified via a cancer genetics registry and clinical practice at Penn Medicine and through our collaborator network. Tumors were analyzed with next generation sequencing (whole exome and/or targeted panel sequencing) with or without transcriptomic analyses. Sub-study #1 "Non-breast/ovarian tumors in germline BRCA1/2 carriers". This study investigated primary non-breast/ovarian tumors that arise in individuals with BRCA1/BRCA2 pathogenic germline variants (PGVs). Whole exome sequencing (WES) using Agilent All-Exon Kit v7 hybrid capture probes was performed on matched tumor and blood germline normal DNA on an Illumina HiSeq. Individual WES data from DNA samples from tumor and normal are available. Sub-study #2: "Breast tumors in germline CHEK2 carriers". This study investigated primary breast tumors that arise in individuals with CHEK2 pathogenic germline variants (PGVs). Whole exome sequencing (WES) using Agilent All-Exon Kit v7 hybrid capture probes was performed on matched tumor and blood germline normal DNA on an Illumina HiSeq. Whole transcriptome RNAseq was performed on tumors. Individual WES data from DNA samples from tumor and normal and RNAseq data from tumor are available. Sub-study #3: "Breast tumors in germline TP53 carriers". This study investigated primary breast tumors that arise in individuals with TP53 pathogenic germline variants (PGVs). Whole genome sequencing (WGS) and/or custom panel targeted sequencing was performed on matched tumor and blood germline normal DNA on an Illumina HiSeq. Whole transcriptome RNAseq was performed on tumors and normal breast tissue. Individual WGS or targeted data from DNA samples from tumor and normal and RNASeq data from tumor and normal are available. Sub-study #4: "Prostate tumors in germline DNA repair carriers". This study investigated prostate tumors that arise in individuals with a variety of pathogenic germline variants (PGVs). Whole genome sequencing (WGS) and/or custom panel targeted sequencing was performed on matched tumor and blood germline normal DNA on an Illumina HiSeq. Whole transcriptome RNAseq was performed on tumors and normal prostate tissue. Individual WGS or targeted data from DNA samples from tumor and normal and RNASeq data from tumor and normal are available.

  Study phs003348

• Ipilimumab and Decitabine in Treating Patients With Relapsed or Refractory Myelodysplastic Syndrome or Acute Myeloid Leukemia

  The NCI Experimental Therapeutics Clinical Trials Network (ETCTN)/Cancer Therapy Evaluation Program (CTEP) 10026 study (NCT02890329) tested combined ipilimumab and decitabine treatment in two cohorts: Arm A consisted of patients with relapsed acute myeloid leukemia (AML) after allogeneic hematopoietic stem cell transplantation. Arm B consisted of patients with advanced myelodysplastic syndrome (MDS) or AML that did not previously undergo stem cell transplantation. During the study, peripheral blood and bone marrow samples were obtained from study participants at study entry (screening), following the first lead-in cycle of decitabine monotherapy, during combined treatment with decitabine and ipilimumab, and at the end of treatment.This study tested the combination of the CTLA-4 blocking antibody ipilimumab and the DNA methyltransferase inhibitor decitabine in advanced myeloid disease in the transplant-naive and post-transplant context. The samples were used for bulk and single cell RNA sequencing (scRNA-seq) as well as whole exome sequencing (WES).

  Study phs003015

• Exome Recapture and Sequencing of Prospectively Characterized Clinical Specimens From Cancer Patients

  The study cohort comprises samples from patients whose tumors have been prospectively characterized as part of their care at Memorial Sloan Kettering Cancer Center. This includes a variety of distinct tumor type and molecular subtypes.

  Study phs001783

• Single Cell RNA-Seq Reveals Malignant and Stromal Programs Associated with Metastasis in Head and Neck Cancer

  This study of head and neck cancer aimed to profile individual malignant, stromal, and immune cells in treatment-naive oral cavity squamous cell carcinoma, with or without matched metastatic cervical lymph nodes. Clinical and pathologic information was collected on all patients, in addition to a fresh biopsy sample from the primary tumor and/or metastatic lymph node at the time of initial surgery. Biopsy specimens were processed for single cell RNA-seq (scRNA-seq) and/or whole exome sequencing (WES). A total of ~6,000 single cells from 18 participants were included in the final dataset. Stromal and immune cells had consistent expression programs across patients. Conversely, malignant cells varied within and between tumors in their expression of signatures related to cell cycle, stress, hypoxia, epithelial differentiation, and partial epithelial-to-mesenchymal transition (p-EMT). One of the top scoring genes in this program was TGFβ-induced (TGFBI), implicating the classic EMT regulator TGFβ. Cells expressing the p-EMT program spatially localized to the leading edge of primary tumors. By integrating single-cell transcriptomes with bulk expression profiles for hundreds of tumors, we refined Head and Neck Squamous Cell Carcinoma (HNSCC) subtypes by their malignant and stromal composition, and established p-EMT as an independent predictor of nodal metastasis, grade, and adverse pathologic features. Our results provide insight into the HNSCC ecosystem and define stromal interactions and a p-EMT program associated with metastasis.

  Study phs001474

• Comprehensive Genomic Data Deposition for Pancreatic Cancer Precision Medicine Studies: Clinical Trials NCT02451982 and NCT02648282

  This submission includes specimens from 89 pancreatic cancer patients at Johns Hopkins Hospital, comprising 41 surgically resectable and 48 locally advanced pancreatic cancer (LAPC) cases. These samples originate from two clinical studies, NCT02451982 and NCT02648282, following the Johns Hopkins Medical Institution Institutional Review Board-approved registry protocol at the Pancreatic Cancer Precision Medicine Center of Excellence Program. Written consent for specimen use, obtained from participants in the original studies, covers additional research, including this one. Biopsy specimens collected through endoscopic ultrasound-guided fine needle core biopsies or surgically resected tumors are included. NCT02451982 is a platform trial evaluating immunotherapy combinations for surgically resectable pancreatic ductal adenocarcinoma in the neo-adjuvant and adjuvant settings. It investigates the GVAX pancreatic cancer vaccine with immune-boosting cyclophosphamide, exploring immune cell trafficking and the impact of PD-1 blocking. NCT02648282 focuses on the efficacy and safety of combining cyclophosphamide, pembrolizumab, GVAX, and stereotactic body radiotherapy (SBRT) in locally advanced pancreatic cancer, with an emphasis on anti-tumor activity. Both studies provide valuable insights into innovative pancreatic cancer treatment approaches.

  Study phs003600

• Analyzing Somatic Mutagenesis in Systemic Sclerosis

  The study was undertaken with the aim of estimating differences in the mutational burden in lung tissues from healthy vs systemic sclerosis (SSc) patients. SSc is an auto-immune disease, with patients often developing cancer. However, the etiology of this phenomenon is poorly understood. As such we sought to uncover potential molecular mechanisms prevalent within SSc tissues that might be potentiating cancer. Samples were randomly collected from individuals from two broad ethnic groups, European (EA) and African American (AA). In total, samples were obtained from 7 individuals belonging to the EA group and 4 individuals from the AA group. For this study, ethnicity was not included as a confounding variable, given that the data set has roughly comparable number of individuals from both ethnicities for the healthy and SSc cohorts. Study participants ranged in age from 37-63 years old. Median age (52 years old) of healthy individuals was comparable to the SSc cohort (~48 years old). Participants were self-described as current/former smokers or non-smokers. Lung tissues were obtained under a protocol approved by the University of Pittsburgh Institutional Review Board. Written informed consent statements were provided to the University of Pittsburgh IRB by the study participants/patients. Sample sizes were determined by the ability of bulk lung fibroblast tissues to stably propagate in culture until single cell clones could be obtained. Samples for which sufficient cell density could not be achieved for downstream high-depth sequencing analysis were excluded from the study and are not reported. Five or greater than 5 samples are collected from each cohort including healthy and SSc patients. Subjects were allocated to two basic cohorts based on diagnosis at the time of explant. Participants with no reported lung anomalies were allocated to the "healthy" cohort, whereas individuals with reported lung abnormalities, primarily SSc with pulmonary fibrosis and/or hypertension were allocated to the "SSc" cohort. All tissue samples were cultured, propagated and processed in identical fashion without requiring individual-specific protocols. Additionally, equivalent amounts of DNA were used for preparing sequencing libraries from both cohorts, and all samples were sequenced using Illumina whole genome sequencing (WGS) and analyzed using identical computational pipelines. Our study primarily discovered that there is a significantly higher burden of somatic mutations in SSc samples, compared to healthy samples. We observed an overall increase in a range of mutations in genomes of SSc patients, including single base substitutions, indels, structural variants and copy number alterations. Additionally, we uncovered a novel mutation signature associated with SSc samples, hinting at the activity of POLH in these samples, and highlighting the potential nexus between inflammation, DNA damage, and cancer.

  Study phs003700

• Pre-Existing Skin-Resident CD8 and γδ T Cell Circuits Mediate Immune Response in Merkel Cell Carcinoma and Predict Immunotherapy Efficacy

  Merkel cell carcinoma (MCC) is an aggressive neuroendocrine skin cancer with a ~50% response rate to immunotherapy. Here, we attempted to identify novel predictive biomarkers of response through extensive and deep multi-omics interrogation of 186 samples from 116 patients. We collectively integrated bulk RNAseq, single-cell RNAseq, multiplex immunofluorescence, and spatial transcriptomics. Importantly, we were also able to study 14 matched pairs of tissue samples from pre- and post-immunotherapy. In non-responders, tumors show evidence of increased tumor cell cycling, expression of neuronal stem cell markers, and IL-1α/β. Responders have evidence of increased type I/II interferon signatures and evidence of pre-existing tissue resident (Trm) CD8 or Vδ1 γδ T cells that functionally converge with overlapping antigen-specific transcriptional programs and clonal expansion of multiple T cell receptors. Spatial transcriptomics demonstrated higher co-localization of T cells with B and dendritic cells in responders, with evidence of expression of chemokines important for co-stimulation. Finally, immunotherapy increased clonal expansion or recruitment of Trm and Vδ1 cells in tumors in responders, further underscoring their therapeutic importance. These data identify potential novel actionable biomarkers and therapeutic targets for MCC.

  Study phs003629

• Radiation-Related Genomic Profile of Papillary Thyroid Cancer after the Chernobyl Accident

  The April 26, 1986 accident at the Chernobyl nuclear power plant in northern Ukraine resulted in the release of radioactive contaminants, which were deposited in the surrounding areas in Ukraine, Belarus, and Russia. The main radiation-related health effect resulting from these exposures is the increased occurrence of thyroid cancer among individuals who were children at the time of the accident or born shortly thereafter. The purpose of this study was to conduct a comprehensive genomic landscape analysis of papillary thyroid tumors arising in individuals who were exposed as children to radioactive iodine (I-131) from the Chernobyl nuclear power plant accident.

  Study phs001134

• UCSF Database for the Advancement of JMML - Integration of Metadata with Omic Data

  Juvenile myelomonocytic leukemia (JMML) is a rare and frequently fatal myeloproliferative/myelodysplastic disorder of early childhood with an estimated incidence of 1.2 cases per million. It is associated with a spectrum of diverse outcomes ranging from spontaneous resolution in rare patients to transformation to acute myeloid leukemia in others. The overwhelming majority of JMML patients (~95%) will harbor mutations in canonical Ras pathway genes, including NF1, NRAS, KRAS, PTPN11, and CBL. As Ras proteins are mutated in more than 30% of human cancers, the information gleaned from the study of JMML has provided insights into Ras signaling in cancer as well as a group of congenital diseases with tumor predispositions known as the “Rasopathies”. While oncogenic Ras is one of the most common mutations in human cancer, it remains one of the most vexing targets for efficacious therapy. To better understand this disease, a JMML tissue bank was established at UCSF that allows for consenting of subjects, biobanking of tissue and collection of follow up data from patients both locally and at other institutions. Through the collection and analysis of specimens, knowledge about the genetic, epigenetic, and biochemical basis of JMML has been gained. This integrated database will enable future JMML research, and importantly, additional Ras/MAPK pathway research by depositing linked, processed data to well annotated anonymized patients in an easily accessible online database

  Study phs002504

• Genomic Profiling of Pediatric B-cell Acute Lymphoblastic Leukemia

  Pediatric leukemia is the most common type of childhood cancer and, despite tremendous progress in treatment, remains the second leading cause of cancer deaths in children. B-cell acute lymphoblastic leukemia (B-ALL) is the most common type of pediatric leukemia. Recent studies using transcriptional profiling of large cohorts of pediatric B-ALL have shown that patients can be grouped into transcriptional subtypes that are often defined by specific driver mutations. Interestingly, many of these mutational subtypes are defined by gene fusions or rearrangements that drive altered expression of transcription factors (ETV6-RUNX1, PAX5, DUX4, TCF3-PBX1, ZNF384) or in chromatin regulatory machinery (KMT2A), suggesting that transcriptional dysregulation is a major driver of B-ALL. While the transcriptional distinctions are clear, the relationship between patients in terms of their chromatin regulatory landscape remains unclear. To address this, we profiled gene expression, open chromatin, and 3D genome folding in patient derived B-ALL samples. We identified that at the level of 3D genome organization, many chromatin interactions and looping events are shared across mutational subtypes, suggesting that shared transcriptional programs, in addition to group specific driver mutations, possibly regulate the chromatin landscape in B-ALL. Using RNA-seq and ATAC-seq data, we were able to identify "latent" signatures of expression related to non-mutant transcription factors (TFs) that also contribute to expression heterogeneity across TF subtypes. These are related to patient specific patterns of 3D genome folding, and in some cases, are predictive of disease outcomes. This study helps shed light on the chromatin landscape in B-ALL and furthers our understanding of the interactions between diverse mutant TFs that drive B-ALL and non-mutant TFs that help shape the B-ALL chromatin landscape.

  Study phs003226

• Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task (STARNET)

  STARNET is a genetics of RNA expression study of multiple disease-relevant tissues obtained from living patients with cardiovascular disease. Tissue samples are obtained from blood, atherosclerotic-lesion-free internal mammary artery (MAM) and atherosclerotic aortic root (AOR), subcutaneous fat (SF), visceral abdominal fat (VAF), skeletal muscle (SKLM), and liver (LIV) during open thorax surgery of 600 coronary artery disease (CAD) patients. All patients gave written informed consent. The inclusion criterion was eligibility for coronary artery by-pass graft (CABG) surgery. Patients with other severe systemic diseases, such as active systemic inflammatory disease or cancer, were excluded. The primary clinical end points were the SYNTAX score based on the extent of coronary atherosclerosis assessed from preoperative angiograms. The STARNET patients are Caucasians (31% females); 32% had diabetes, 75% had hypertension, and 67% had hyperlipidemia; and 33% had an MI before age 60. By New York Heart Association criteria, 45% were class I, 42% class II, 9% class III, and 1% class IV. TYPES AND RNA SEQUENCING: 566 DNA genotype and 3577 RNA-seq profiles from seven tissues from 600 STARNET CABG patients passed quality control (on average 511 RNA-seq profiles/tissue). DNA was genotyped with the OmniExpress Exome array (Illumina, ~900k SNPs) and imputed to a total of 14,098,063 DNA variant calls (6,245,505 with minor allele frequency >5%). The STARNET subjects mainly overlap with Caucasian of Northern European (Finnish) descent. RNA sequencing was performed using the HighSeq2000 platform, poly-A (LIV, SKLM, VAF, SF and blood) and ribo-zero (AOR, MAM) protocols with 50-100 bp read lengths, single end to 15-30 million read depth.

  Study phs001203

• Integrative genomic analyses reveal androgen-driven somatic alteration landscape in early-onset prostate cancer

  Early-onset prostate cancer (EO-PCA) represents the earliest clinical manifestation of prostate cancer. To compare the genomic alteration landscapes of EO-PCA with "classical" (elderly-onset) PCA, we performed deep sequencing-based genomics analyses in eleven tumors diagnosed at young age, and pursued comparative assessments with seven elderly-onset PCA genomes. Remarkable age-related differences in structural rearrangement (SR) formation became evident, suggesting distinct disease pathomechanisms. Whereas EO-PCAs harbored a prevalence of balanced SRs, with a specific abundance of androgen-regulated ETS gene fusions including TMPRSS2:ERG, elderly-onset PCAs displayed primarily non-androgen-associated SRs. Data from a validation cohort of >10,000 patients showed age-dependent androgen receptor levels and a prevalence of SRs affecting androgen-regulated genes, further substantiating the activity of a characteristic "androgen-type" pathomechanism in EO-PCA.

  Study EGAS00001000400

• Molecular determinants of response to PD-L1 blockade across tumor types

  Immune checkpoint inhibitors targeting the PD-1/PD-L1 axis lead to durable clinical responses in subsets of cancer patients across multiple indications, including non-small cell lung cancer (NSCLC), urothelial carcinoma (UC) and renal cell carcinoma (RCC). Herein, we complement PD-L1 immunohistochemistry (IHC) and tumor mutation burden (TMB) with RNA-seq in 366 patients to identify unifying and indication-specific molecular profiles that can predict response to checkpoint blockade across these tumor types. Multiple machine learning approaches failed to identify a baseline transcriptional signature highly predictive of response across these indications. Signatures described previously for immune checkpoint inhibitors also failed to validate. At the pathway level, significant heterogeneity was observed between indications, in particular within the PD-L1+ tumors. mUC and NSCLC were molecularly aligned, with cell cycle and DNA damage repair genes associated with response in PD-L1- tumors. At the gene level, the CDK4/6 inhibitor CDKN2A was identified as a significant transcriptional correlate of response, highlighting the association of non-immune pathways to the outcome of checkpoint blockade. This cross-indication analysis revealed molecular heterogeneity between mUC, NSCLC and RCC tumors, suggesting that indication-specific molecular approaches should be prioritized to formulate treatment strategies.

  Study EGAS00001004343

• Targeting TRIP13 in Wilms Tumor with Nuclear Export Inhibitors

  Wilms tumor (WT) is the most common renal malignancy of childhood. Despite improvements in the overall survival, relapse occurs in ~15% of patients with favorable histology WT (FHWT). Half of these patients will succumb to their disease. Identifying novel targeted therapies in a systematic manner remains challenging in part due to the lack of faithful preclinical in vitro models. We established ten short-term patient-derived WT cell lines and characterized these models using low-coverage whole genome sequencing, whole exome sequencing and RNA-sequencing, which demonstrated that these ex-vivo models faithfully recapitulate WT biology. We then performed targeted RNAi and CRISPR-Cas9 loss-of-function screens and identified the nuclear export genes (XPO1 and KPNB1) as strong vulnerabilities. We observed that these models are sensitive to nuclear export inhibition using the FDA approved therapeutic agent, selinexor (KPT-330). Selinexor treatment of FHWT suppressed TRIP13 expression, which was required for survival. We further identified in vitro and in vivo synergy between selinexor and doxorubicin, a chemotherapy used in high risk FHWT. Taken together, we identified XPO1 inhibition with selinexor as a potential therapeutic option to treat FHWTs and in combination with doxorubicin, leads to durable remissions in vivo.

  Study EGAS00001007389

• Smoking-dependent expression alterations in nasal epithelium reveal immune impairment linked to germline variation and lung cancer risk

  Study EGAS00001006137

• Genome and transcriptome sequence data from a infantile fibrosarcoma tumor patient

  Genome and transcriptome sequence data from a infantile fibrosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015263

• Genome and transcriptome sequence data from a neuroblastoma tumor patient

  Genome and transcriptome sequence data from a neuroblastoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015264

• Genome and transcriptome sequence data from a neuroblastoma tumor patient

  Genome and transcriptome sequence data from a neuroblastoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015265

• Genome and transcriptome sequence data from a neurofibromatosis type 1 (NF1) tumor patient

  Genome and transcriptome sequence data from a neurofibromatosis type 1 (NF1) patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015266

• Genome and transcriptome sequence data from a neuroblastoma tumor patient

  Genome and transcriptome sequence data from a neuroblastoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015267

• Genome and transcriptome sequence data from a CNS sarcoma tumor patient

  Genome and transcriptome sequence data from a CNS sarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015268

• Genome and transcriptome sequence data from a ocular melanoma tumor patient

  Genome and transcriptome sequence data from a ocular Melanoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015269

• Genome and transcriptome sequence data from a osteosarcoma tumor patient

  Genome and transcriptome sequence data from a osteosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015270

• Genome and transcriptome sequence data from a fibrovascular brain tumor tumor patient

  Genome and transcriptome sequence data from a fibrovascular brain tumor patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015271

• Genome and transcriptome sequence data from a angiosarcoma tumor patient

  Genome and transcriptome sequence data from a angiosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015272

• Genome and transcriptome sequence data from a craniopharyngioma tumor patient

  Genome and transcriptome sequence data from a craniopharyngioma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015273

• Genome and transcriptome sequence data from a NHL large B cell tumor patient

  Genome and transcriptome sequence data from a NHL large B Cell patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015274

• Genome and transcriptome sequence data from a malignant granular cell tumor tumor patient

  Genome and transcriptome sequence data from a malignant granular cell tumor patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015275

• Genome and transcriptome sequence data from a papillary thyroid carcinoma tumor patient

  Genome and transcriptome sequence data from a papillary thyroid carcinoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015276

• Genome and transcriptome sequence data from a neuroblastoma tumor patient

  Genome and transcriptome sequence data from a neuroblastoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015277

• Genome and transcriptome sequence data from a osteosarcoma tumor patient

  Genome and transcriptome sequence data from a osteosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015278

• Genome and transcriptome sequence data from a aggressive fibromatosis tumor patient

  Genome and transcriptome sequence data from a aggressive fibromatosis patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015279

• Genome and transcriptome sequence data from a pineoblastoma tumor patient

  Genome and transcriptome sequence data from a pineoblastoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015280

• Genome and transcriptome sequence data from a multifocal glioblastoma multiforme tumor patient

  Genome and transcriptome sequence data from a multifocal glioblastoma multiforme patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015281

• Genome and transcriptome sequence data from a progressive facial plexiform neurofibroma tumor patient

  Genome and transcriptome sequence data from a progressive facial plexiform neurofibroma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015282

• Genome and transcriptome sequence data from a plexiform neurofibroma tumor patient

  Genome and transcriptome sequence data from a plexiform neurofibroma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015283

• Genome and transcriptome sequence data from a diffuse intrinsic pontine glioma tumor patient

  Genome and transcriptome sequence data from a diffuse Intrinsic Pontine Glioma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015284

• Genome and transcriptome sequence data from a acute lymphoblastic leukemia tumor patient

  Genome and transcriptome sequence data from a acute lymphoblastic leukemia patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015285

• Genome and transcriptome sequence data from a ewing sarcoma tumor patient

  Genome and transcriptome sequence data from a ewing sarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015286

• Genome and transcriptome sequence data from a ependymoma tumor patient

  Genome and transcriptome sequence data from a ependymoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015287

• Genome and transcriptome sequence data from a glioblastoma tumor patient

  Genome and transcriptome sequence data from a glioblastoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015288

• Genome and transcriptome sequence data from a NUT midline carcinoma tumor patient

  Genome and transcriptome sequence data from a NUT midline carcinoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015289

• Genome and transcriptome sequence data from a angiosarcoma tumor patient

  Genome and transcriptome sequence data from a angiosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015290

• Genome and transcriptome sequence data from a pre-B all (2nd relapse in CNS) tumor patient

  Genome and transcriptome sequence data from a pre-B all (2nd relapse in CNS) patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015291

• Genome and transcriptome sequence data from a gliomatosis cerebri anaplastic astrocytoma tumor patient

  Genome and transcriptome sequence data from a gliomatosis cerebri anaplastic astrocytoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015292

• Genome and transcriptome sequence data from a osteosarcoma tumor patient

  Genome and transcriptome sequence data from a osteosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015293

• Genome and transcriptome sequence data from a neuroblastoma tumor patient

  Genome and transcriptome sequence data from a neuroblastoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015294

• Genome and transcriptome sequence data from a metastatic alveolar rhabdomyosarcoma tumor patient

  Genome and transcriptome sequence data from a metastatic alveolar rhabdomyosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015295

• Genome and transcriptome sequence data from a neuroblastoma tumor patient

  Genome and transcriptome sequence data from a neuroblastoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015296

• Genome and transcriptome sequence data from a minimally invasive adenocarcinoma tumor patient

  Genome and transcriptome sequence data from a minimally invasive adenocarcinoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015297

• Genome and transcriptome sequence data from a aggressive fibromatosis tumor patient

  Genome and transcriptome sequence data from a aggressive fibromatosis patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015298

• Genome and transcriptome sequence data from a aggressive fibromatosis tumor patient

  Genome and transcriptome sequence data from a aggressive fibromatosis patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015299

• Genome and transcriptome sequence data from a glioblastoma tumor patient

  Genome and transcriptome sequence data from a glioblastoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015300

• Genome and transcriptome sequence data from a neurofibromatosis type 1 tumor patient

  Genome and transcriptome sequence data from a neurofibromatosis type 1 patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015301

• Genome and transcriptome sequence data from a neuroblastoma tumor patient

  Genome and transcriptome sequence data from a neuroblastoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015302

• Genome and transcriptome sequence data from a papillary thyroid carcinoma tumor patient

  Genome and transcriptome sequence data from a papillary thyroid carcinoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015303

• Genome and transcriptome sequence data from a relapsed wilms tumor tumor patient

  Genome and transcriptome sequence data from a relapsed Wilms tumor patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015304

• Genome and transcriptome sequence data from a plexiform neurofibroma tumor patient

  Genome and transcriptome sequence data from a plexiform neurofibroma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015305

• Genome and transcriptome sequence data from a metastatic osteosarcoma tumor patient

  Genome and transcriptome sequence data from a metastatic osteosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015306

• Genome and transcriptome sequence data from a embryonal rhabdomyosarcoma of the nasopharynx tumor patient

  Genome and transcriptome sequence data from a embryonal rhabdomyosarcoma of the nasopharynx patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015307

• Genome and transcriptome sequence data from a diffuse aarge B-cell lymphoma (relapse) tumor patient

  Genome and transcriptome sequence data from a diffuse large B-cell lymphoma (relapse) patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015308

• Genome and transcriptome sequence data from a neuroblastoma tumor patient

  Genome and transcriptome sequence data from a neuroblastoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015309

• Genome and transcriptome sequence data from a malignant rhabdoid tumour tumor patient

  Genome and transcriptome sequence data from a malignant rhabdoid tumour patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015310

• Genome and transcriptome sequence data from a relapsed osteosarcoma tumor patient

  Genome and transcriptome sequence data from a relapsed osteosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015311

• Genome and transcriptome sequence data from a relapsed blastic plasmacytoid dendritic cell neoplasm tumor patient

  Genome and transcriptome sequence data from a relapsed blastic plasmacytoid dendritic cell neoplasm patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015312

• Genome and transcriptome sequence data from a synovial sarcoma tumor patient

  Genome and transcriptome sequence data from a synovial sarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015313

• Genome and transcriptome sequence data from a recurrence nasopharyngeal rhabdomyosarcoma tumor patient

  Genome and transcriptome sequence data from a recurrence nasopharyngeal rhabdomyosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015314

• Genome and transcriptome sequence data from a ewing sarcoma tumor patient

  Genome and transcriptome sequence data from a ewing sarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015315

• Genome and transcriptome sequence data from a osteosarcoma tumor patient

  Genome and transcriptome sequence data from a osteosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015316

• Genome and transcriptome sequence data from a pineal parenchymal tumor tumor patient

  Genome and transcriptome sequence data from a pineal parenchymal tumor patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015317

• Genome and transcriptome sequence data from a rhabdomyosarcoma, alveolar tumor patient

  Genome and transcriptome sequence data from a rhabdomyosarcoma, alveolar patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015318

• Genome and transcriptome sequence data from a anaplastic astrocytoma tumor patient

  Genome and transcriptome sequence data from a anaplastic astrocytoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015319