7262 results for "canc*"

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• Genetic Factors associated with Conversion from Active Surveillance to Treatment for Prostate Cancer

  This is a genome-wide association study (GWAS) of conversion from active surveillance (AS) for prostate cancer (PC) to treatment. AS is the monitoring with screening tests and/or biopsies over time of men usually with low-risk, early-stage PC to avoid harmful side effects of PC treatment. "Conversion" refers to patients who withdraw from AS (switch to active treatment) due to changes in their cancer development, anxiety about delayed treatment, or other reasons. Patients who converted because of anxiety alone were censored in the GWAS analysis. The overall goal of this study is to develop an easily measurable, germline-based panel of genetic variants to aid in selecting PC patients appropriate for AS and/or the intensity of monitoring. In total, 6,324 PC patients from 28 collaborating institutions are included in this study. Patients are those with PC who are either on AS or who have previously converted from AS to treatment. In this study, 70% of all subjects were diagnosed with very low-risk, low-risk, or low-volume intermediate-risk PC (Kryvenko and Epstein, 2016; PMID: 26709152) and have been enrolled in an AS program. DNA was extracted from blood, saliva, or formalin-fixed, paraffin-embedded (FFPE) tissue collected from the study subjects at the participating sites. Genotyping, quality control processes, and imputation were performed at the Center for Inherited Disease Research (CIDR) at Johns Hopkins University. CIDR used the Illumina Infinium Multi-Ethnic Global Array (MEGA) version 1, which included genome-wide tag SNPs and 10,000 SNPs selected with custom content. Quality control and assurance (QC/QA) checks on genotyped data involved four domains: sample-level checks, batch effects, SNP-level checks, and preliminary association tests. Samples and SNPs passing the QC/QA checks were imputed to appropriate reference panels (HRC r1.1 for patients of European ancestry) using the Michigan Imputation Server (PMID: 27571263). Unmeasured genetic variants were imputed using the Trans-Omics for Precision Medicine (TOPMed) Imputation Server, with 97,256 reference samples and 308,107,085 SNPs. Variants with imputation quality (INFO) score < 0.3 were excluded, leaving a total of 22,691,641 SNPs successfully imputed. After QC steps, a total of 5,936 samples genotyped at CIDR remained for inclusion in the GWAS.

  Study phs002056

• National Cancer Institute - Population Structure and Natural Selection in the Epidemiology of Burkitt Lymphoma in East African Children and Minors (EMBLEM) study in Uganda

  A genome-wide analysis of genetic structure, gene flow, and natural selection was conducted in populations in the endemic Burkitt lymphoma (eBL) belt in Ghana and Northern Uganda, both subject to a high incidence of falciparum malaria and eBL. These populations have different ethnolinguistic ancestries and are located 2400 miles apart in sub-Saharan Africa. We characterized genetic composition of these populations in the context of 22 additional African populations and present evidence for gene flow events that occurred in the last 3000 years, possibly related to regional migrations in Western Africa and major migrations involving Nilotic, Cushitic, and Bantu groups. The Ugandan population was comprised of 758 children (mean age ~7 years) from 17 Western Nilo-Saharan tribes. The current dataset includes 561 healthy children and 197 children with eBL from northern Uganda.

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• Multimodal Genomic Features Predict Outcome of Immune Checkpoint Blockade in Non-small Cell Lung Cancer

  This study evaluates integrated genomic models of response to immune checkpoint blockade for lung cancer patients. A computationally adjusted tumor mutation burden was combined with HLA class I genetic variation, mutational smoking signature and activating mutations in receptor tyrosine kinase genes to generate a prognostic classifier that outperforms tumor mutation burden.

  Study phs001940

• Evolution of Core Archetypal Phenotypes in High-Grade Serous Ovarian Cancer (HGSOC)

  The evolution of resistance in high-grade serous ovarian cancer (HGSOC) cells in response to chemotherapy is only partially understood. To uncover phenotypic changes associated with chemotherapy resistance, we performed single-cell RNA-sequencing (scRNA-seq) or whole-genome sequencing of 23 total patients, with longitudinal samples collected from 9, treatment-naïve samples from 8 patients, and post-treatment samples from 6 patients. Our study revealed that the HGSOC transcriptome could be described using three core archetypal phenotypes, defined as oncogenic tasks that describe majority of the transcriptional data. We implemented a multi-task learning approach to identify the biological tasks of each archetype and identified metabolism and proliferation, cellular defense response, and DNA repair signaling. The “metabolism and proliferation” archetype evolved during treatment and was enriched in cancer cells from patients that received multiple-lines of treatment and had elevated tumor burden indicated by CA-125 levels. The emergence of archetypes was not consistently linked to specific whole-genome driver mutations. However, archetypes were closely associated with sub-clonal clusters at the single-cell level, indicating that cancer cell sub-populations specialize in particular biological tasks. Our study reveals a defining principle of ovarian tumor evolution using temporal scRNA-seq profiles, identifies the key phenotypic features across patients and links metabolic shifts with a response to chemotherapy.

  Study phs002294

• A prospective pilot study of genome-wide exome and transcriptome profiling in patients with small cell lung cancer progressing after first-line therapy

  In this prospective study, custom genome-wide exome and whole transcriptome sequencing (NGS) was used to identify genomic events and associated expression changes in advanced Small Cell Lung Cancer (SCLC) and attempt to prescribe systemic therapy based on the results. Tumor/normal pairs were sequenced from 12 patients with advanced SCLC for this study.

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• The Genomic Landscape of Endocrine Resistant Advanced Breast Cancers: Paired Pre- and Post-endocrine Therapy Samples.

  The genomic evolution of breast cancers exposed to systemic therapy and its effects on clinical outcome have not been broadly characterized. We integrated the genomic sequencing of 1918 breast cancers, including 1501 hormone receptor-positive tumors, with detailed clinical information and treatment outcomes. Functional mutations in ERBB2 and loss-of-function mutations in NF1 were more than twice as common in post-endocrine therapy tumors compared to treatment-naive tumors. Additional alterations in the MAPK pathway (EGFR, KRAS among others) and in estrogen receptor transcriptional regulators (MYC, CTCF, FOXA1 and TBX3) were also more common compared to hormonal therapy-naive tumors. To determine whether candidate genomic lesions in the MAPK pathway and estrogen receptor transcriptional regulators were present prior to therapy or whether such lesions arose under the selective pressure of therapy, we performed whole-exome sequencing in select patients who had adequate samples acquired prior to and after progression on endocrine therapy. In total, 95 specimens corresponding to 30 treatment-naive primary tumors, 35 post-treatment tumors, and 30 normal samples were sequenced from 30 patients with endocrine-resistant metastatic breast cancer.

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• Resistance studies in Lung Cancer

  The purpose of the study was to compare gene expression profiles from a cohort of crizotinib-resistant ALK-rearranged lung tumors and a cohort of treatment-naive ALK-rearranged lung tumors. Expression profiles were generated by RNA-seq. In parallel, gene expression profiles were obtained from ALK-rearranged lung cancer cell lines in the presence or absence of the ALK inhibitor TAE684. Gene expression profiles were also obtained from ALK-rearranged cells ectopically expressing genes associated with ALK inhibitor resistance that were identified from a functional genetic study.

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• Characterizing TP53 and PPM1D Mutations as Resistance Drivers to Radiation Therapy in Diffuse Intrinsic Pontine Gliomas

  Pediatric high-grade gliomas (pHGGs), encompassing diffuse midline gliomas (DMGs) and hemispheric tumors, represent the most common cause of cancer-related deaths in children age 0-14 years. Over the last decade, several landmark papers have revealed recurrent single nucleotide variants (SNVs) in the core histones H3.3 and H3.1, co-occurring with alterations in the TP53 signaling pathway and receptor tyrosine kinases (RTKs). However, the contribution of structural variants (SVs) to gliomagenesis has not been systematically explored. We performed a comprehensive analysis of whole genome sequencing (WGS) data on pediatric high-grade gliomas (pHGGs) from 179 children, including 61 hemispheric tumors and 118 diffuse midline gliomas, or DMGs, of which 61 are novel to this study. Among the DMGs, 84 (71%) were from pre-treatment biopsies including 33 obtained from the first multi-institutional North American clinical trial to incorporate diagnostic biopsies. This represents the largest cohort of pretreatment DMGs with whole genome sequencing to date. This large cohort of whole genome sequences provides an unparalleled opportunity to assess significantly recurrent structural variants in pHGG and their associations with driver SNVs and SCNAs. 

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• Identification of 22 Novel Loci Associated with Susceptibility to Testicular Germ Cell Tumors

  Testicular germ cell tumors (TGCT) are the most common cancers in young men of European ancestry aged 20 to 39 years. The Testicular Cancer Consortium (TECAC) has brought together the largest genome-wise association study (GWAS) study of TGCT to date. We conducted a GWAS of 5,602 cases and 5,006 controls aggregated from 12 locations in the US and Europe. Logistic regression models adjusted for study center and genomic ancestry. Genotypes were imputed against the Human Haplotype Reference Consortium. Meta-analysis was performed to combine GWAS results with summary statistics from five previously published TGCT studies, UK Biobank, deCODE Genetics, and an independent set of cases and controls, for a total of 10,156 cases and 179,683 controls. 22 novel and 45 previously reported loci associated with TGCT surpassed genome-wide significance (p < 5e-08).

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• National Cancer Institute (NCI) Non-Hodgkin Lymphoma Genome-wide Association Study (GWAS)

  Within the framework of the International Lymphoma Epidemiology Consortium (InterLymph) Consortium and NCI-sponsored Cohort Consortium, investigators from 22 studies came together to conduct a genome-wide association study (GWAS) of non-Hodgkin lymphoma (NHL). The goal of the study was to identify common genetic variants associated with the risk of NHL. As described previously (Berndt SI et al., Nature Genetics, 2013, PMID: 23770605 ), cases and controls from 22 studies, including nine prospective cohort studies, eight population-based case-control studies, and five clinic or hospital-based case-control studies were included in this effort. Cases of NHL were ascertained from cancer registries, clinics or hospitals, or through self-report verified by medical and pathology reports. The phenotype information for all NHL cases was reviewed centrally at the InterLymph Data Coordinating Center and harmonized according to the hierarchical classification proposed by the InterLymph Pathology Working Group based on the World Health Organization (WHO) classification (2008). Controls were frequency matched to cases on age and gender by study, and the study was limited to subjects of European ancestry. Participants were genotyped using the Illumina Omni Express. The NCI Non-Hodgkin Lymphoma GWAS is utilized in the following dbGaP sub-studies. To view genotypes and derived variables collected in these sub-studies, please click on the following sub-studies below or in the "Sub-studies" box located on the right hand side of this top-level study page phs000801 NCI Non-Hodgkin Lymphoma GWAS. phs000802 NCI Non-Hodgkin Lymphoma GWAS: CLL phs000818 NCI Non-Hodgkin Lymphoma GWAS: Controls phs000889 NCI Non-Hodgkin Lymphoma GWAS: DLBCL phs000890 NCI Non-Hodgkin Lymphoma GWAS: FL phs000891 NCI Non-Hodgkin Lymphoma GWAS: MZL

  Study phs000801

• The Genomics of Pilocytic Astrocytoma Formation in Neurofibromatosis Type 1

  Neurofibromatosis type 1 (NF1) inherited cancer predisposition syndrome is one of the most common autosomal dominant tumor predisposition syndromes in which affected individuals develop brain tumors. These low-grade glial neoplasms (pilocytic astrocytomas) typically arise in children younger than 7 years of age and are hypothesized to result from a combination of germline and acquired somatic NF1 tumor suppressor gene mutations. In this study, whole genome sequence analysis was performed on three NF1-associated pilocytic astrocytoma tumors (NF1-PA) and matched normal blood samples to establish the genomic landscape of NF1-PA. These data support the existence of multiple distinct mechanisms (mutation, LOH, and methylation) underlying somatic NF1 inactivation in NF1-PA tumors.

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• Stand Up 2 Cancer (SU2C) Genomics-Enabled Medicine for Melanoma (GEMM) Trial

  The goal of the GEMM Trial is to ascertain if comprehensive and systematic interrogation of a patient's tumor molecular profile improves outcomes compared to the current practice of physician's choice for metastatic melanoma patients who have progressed following first line therapy. The data shared here includes tumor/normal exome and tumor RNAseq data for the trial patients, as well as archival data for a subset of patients.

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• RNA Sequence-Based Analysis Used to Compare Breast Primary and Metastatic Tumor Pairs

  The goal of this study is to capture the transcriptome landscape of luminal and basal-like metastatic breast tumors. We will aim to show the importance of using the most up-to-date cancer biopsy for detecting cancer drivers that were often not present in the primary tumor.

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• Liquid Biopsy Versus Tissue Biopsy to Assess Acquired Resistance and Tumor Heterogeneity in Gastrointestinal Cancers

  Tumor heterogeneity can drive the evolution of multiple tumor subclones harboring unique molecular resistance alterations in different metastatic lesions in an individual patient, under the selective pressure of therapy1-3. Studies have suggested that liquid biopsy may better capture the heterogeneity of acquired resistance, but systematic, direct comparisons of post-progression liquid vs. standard single-lesion tumor biopsies are lacking. In a prospective cohort of 44 patients with molecularly-defined gastrointestinal cancers and acquired resistance to targeted therapy, direct comparison of post-progression liquid vs. tumor biopsy revealed that liquid biopsy more frequently identified clinically-relevant resistance alterations and multiple resistance mechanisms, detecting resistance alterations not detected in matched tumor biopsy in 78% of cases. Whole-exome sequencing of serial cell-free DNA, tumor biopsies and rapid autopsy specimens elucidated geographic and evolutionary characteristics of heterogeneity. Our data suggest that acquired resistance is frequently characterized by profound tumor heterogeneity and highlight the potential clinical utility of liquid biopsy. Burrell, R. A. & Swanton, C. Tumour heterogeneity and the evolution of polyclonal drug resistance. Molecular oncology 8, 1095-1111, doi:10.1016/j.molonc.2014.06.005 (2014). Misale, S. et al. Emergence of KRAS mutations and acquired resistance to anti-EGFR therapy in colorectal cancer. Nature 486, 532-536, doi:10.1038/nature11156 (2012). Ahronian, L. G. et al. Clinical Acquired Resistance to RAF Inhibitor Combinations in BRAF-Mutant Colorectal Cancer through MAPK Pathway Alterations. Cancer Disco 5, 358-367, doi:10.1158/2159-8290.Cd-14-1518 (2015).

  Study phs001853

• DNA Methylation Analysis of Prostate Cancer Cell Lines and Tissues Using Next Generation Sequencing

  Aberrant DNA methylation changes are known to occur during prostate cancer progression beginning with precursor lesions. Utilizing fifty nanograms of genomic DNA in Methylplex-Next Generation Sequencing (M-NGS) we mapped the global DNA methylation patterns in prostate tissues (n=17) and cells (n=2). Peaks were located from mapped reads obtained in each sequencing run using a Hidden Markov Model (HMM)-based algorithm previously used for Chip-Seq data analysis(http://www.sph.umich.edu/csg/qin/HPeak). The total methylation events in intergenic/intronic regions between benign adjacent and cancer tissues were comparable. Promoter CGI methylation gradually increased from -12.6% in benign samples to 19.3% and 21.8% in localized and metastatic cancer tissues and approximately 20% of all CpG islands (CGIs) (68,508) were methylated in tissues. We observed distinct patterns in promoter methylation around transcription start sites, where methylation occurred directly on the CGIs, flanking regions and on CGI sparse promoters. Among the 6,691 methylated promoters in prostate tissues, 2481 differentially methylated regions (DMRs) are cancer specific and several previously studied targets were among them. A novel cancer specific DMR in WFDC2 promoter showed 77% methylation in cancer (17/22), 100% methylation in transformed prostate cell lines (6/6), none in the benign tissues (0/10) and normal PrEC cells. Integration of LNCaP DNA methylation and H3K4me3 data suggested a role for DNA methylation in alternate transcription start site utilization. While methylated promoters containing CGIs had mutually exclusive H3K4me3 modification, the histone mark was absent in CGI sparse promoters. Finally, we observed difference in methylation of LINE-1 elements between transcription factor ERG positive and negative cancers. The comprehensive methylome map presented here will further our understanding of epigenetic regulation of the prostate cancer genome. Overall Design: We mapped the global DNA methylation patterns in prostate tissues (n=17) and cells (n=2) from fifty nanograms of genomic DNA using Methylplex-Next Generation Sequencing (M-NGS). For replicate analysis in cell lines, a total of 4 runs were completed for PrEC prostate normal cell line, and 5 runs were completed for LNCaP prostate cancer cell line. For tissue samples, 2 benign prostate samples were sequenced twice on Illumina next generation sequencing platform to access overall repeatability of M-NGS.

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• Genetic Determinants of Viral Clearance in HCV-Infected Populations

  The World Health Organization estimates there are 170 million persons with HCV infection worldwide, and an estimated 4 million persons are infected in the United States. Persistent HCV infection can cause cirrhosis and hepatocellular cancer. Long term disease consequences do not occur in persons who spontaneously recover. It is not known why 10-40% recover from hepatitis C (and are not at increased risk of cirrhosis and cancer), but that knowledge would contribute to efforts to treat and/or prevent HCV infection. The overall purpose of this study is to investigate the host genetic basis for recovery from hepatitis C virus (HCV) infection. There is strong evidence that host genetic differences determine HCV recovery. After accidental exposure to the same HCV inoculum, some persons recover while others develop persistent infection. Recovery from HCV infection is an outstanding phenotype for genetic studies since both viral exposure and viral recovery can be ascertained with high sensitivity and specificity and since there are no known viral or environmental determinants. The study group is comprised of an ethnically and geographically diverse international population. All cohorts comprising this study group of 3350 individuals are well characterized. This case-control study is comprised of approximately 40% clearance individuals who are matched by age and HIV status within their respective cohorts at a ratio of 1:1 or 1:2 with HCV chronically infected individuals.

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• National Cancer Institute (NCI) Study of Lung Cancer and Smoking Phenotypes in African-American Cases and Controls

  This is a two-stage case-control study designed to evaluate the association between common genetic variants and the risk of lung cancer. The stage 1 studies included 1737 cases and 3602 controls from the following studies: MD Anderson Lung Cancer Epidemiology Study, The Multiethnic Cohort Study (MEC), NCI-MD Lung Cancer-Case Control Study, Northern California Lung Cancer Study, Project CHURCH (Creating a Higher Understanding of Cancer Research δ Community Health), Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO), Southern Community Cohort Study (SCCS), and the Karmanos Cancer Institute at Wayne State University (KCI/WSU). The stage 2 studies included an independent set of 866 cases and 796 controls from the following studies: The Black Women's Health Study (BWHS), The Harvard-MGH Lung Cancer Susceptibility Study (HLCS), MD Anderson Lung Cancer Epidemiology Study, MD Anderson/LBJ Hospital Biorepository, NCI-MD Lung Cancer Case-Control Study, Northern California Lung Cancer Study, Philadelphia Lung Cancer Study on Gene Environment Interactions (Plus-Gene), Southern Community Cohort Study (SCCS), and KCI/WSU.

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• Defining T cell States Associated with Response to Checkpoint Immunotherapy in Melanoma

  Checkpoint blockade therapy using antibodies targeting CTLA4, PD1 or PDL1 have changed the way cancer patients with advanced disease are being treated, as evident by their FDA approval in a wide variety of malignancies, and their ability to induce high response rates when compared to conventional therapies (e.g. chemotherapy). However, even in melanoma, despite the high response rate, most patients are refractory to therapy or acquire resistance in 10-12 months. To identify key immunological elements coupled with response or resistance to checkpoint immunotherapy, we performed an unbiased analysis on 16,291 CD45+ immune cells from 32 patients (48 samples) treated with checkpoint therapy (anti-PD1=37; anti-PD1/CTLA4=11), using single cell transcriptomics. Initial unsupervised clustering of all CD45+ cells identified 11 clusters. When examining the association of these clusters with clinical outcome, we found that two clusters (B-cells, p=0.005; memory T-cells, p=0.03) were significantly enriched in responder lesions while 4 clusters (monocytes/macrophages, p=0.003; dendritic cells, p=0.015; exhausted CD8+ T-cells, p=0.005; and exhausted/cell-cycle lymphocytes, 1.3x10-5) are enriched in non-responder lesions. Next, by leveraging our unbiased single cell approach, we identified not only clusters but also specific markers associated with either responder lesions (PLAC8, LTB, LY9, SELL, TCF7, IGKC and CCR7) or non-responder ones (CCL3, CD38, HAVCR2, ENTPD1 and WARS), many of which were not previously reported to be associated with clinical outcome to checkpoint therapy. Due to the importance of CD8+ T-cells in controlling tumors, the significant association of T-cell states with clinical outcome, and their high abundance in melanoma tumors, we next focused our analysis on CD8+ T-cells and identified 2 main clusters CD8_G (with increased expression of genes linked to memory) and CD8_B (enriched for genes linked to cell dysfunction), that were significantly enriched in responder (CD8_G, p=1.4x10-6) and non-responder (CD8_B, p=0.005) lesions, respectively. Since cells with both states coexist in each of the responder and non-responder lesions, we decided to calculate the ratio between the number of cells in these 2 clusters and observed a significant separation between responders (CD8_G/CD8_B>1) and non-responders (CD8_G/CD8_B<1) when looking at all samples, baseline or post samples separately. Similar results were detected when looking at the expression of a single transcription factor, TCF7, in CD8 T-cells in an independent cohort (n=43) using a simple immunofluorescence assay. Additionally, we validated the identity and function of some of the newly identified cell states as well as their epigenetic landscape, and found that cells expressing the inhibitory molecules CD39 and TIM3, on top of being enriched in non-responder lesions, are likely to play a crucial role in T-cell exhaustion in melanoma. Collectively, our study provides extensive unbiased data in human tumors for discovery of predictors and therapeutic targets to checkpoint immunotherapy.

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• Improved T Cell Immunity Following Neoadjuvant Chemotherapy in Ovarian Cancer

  This study characterized the evolution of the peripheral immune cell function and composition across the course of standard of care platinum and taxane chemotherapy in ovarian cancer using bulk and single cell transcriptomic approaches. Serial blood samples were collected from ten patients with advanced high-grade serous ovarian cancer treated with chemotherapy. Single cell sequencing was performed on five patients' samples collected before the initiation of chemotherapy and after the third cycle of chemotherapy.

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• A National Translational Science Network of Precision-Based Immunotherapy for Primary Liver Cancer (PLC)

  The primary objective of the NCI-CLARITY study is to establish a biospecimen repository for genomic, genetic and epigenetic analysis to study the biology of primary liver cancer (PLC) development and progression. Secondary objectives include predicting overall and progression-free survival following immunotherapy. In the retrospective phase, anonymous archival tissue from PLC patients was obtained from five participating sites. Whole exome and transcriptome sequencing was generated and used to predict overall survival in response to immunotherapy.

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• Inhibition of CDK4/6 Promotes CD8 T Cell Memory

  Inhibitors of Cyclin-Dependent Kinase 4 and 6 (CDK4/6) have been recently deployed for the treatment of advanced breast cancer. Despite their success, the mechanism of action of these drugs is unclear. In mice, treatment with a CDK4/6 inhibitor improve T cell memory responses and protect mice against tumor rechallenge. We aimed to identify the correlates of this finding in human subjects. In this study, blood was collected from 5 breast cancer patients before and during treatment with the CDK4/6 inhibitors abemaciclib or palbociclib. Blood was also collected from 2 breast cancer patients who did not receive a CDK4/6 inhibitor. Recently activated CD8 T cells (CD45RO+ CD45RA+) were sorted and subjected to single-cell RNA sequencing.

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• Rearrangements of the MAST Kinase and Notch Gene Families in Breast Cancer

  Paired-end transcriptome sequencing was performed on a panel of breast cancer cell lines and tissues and a set of benign cell line and tissue controls. Analyses of the paired end sequences were performed and chimeric transcripts derived from gene rearrangement events were identified. Sequencing was performed on Illumina GAII and HiSeq 2000 platforms with read lengths from 40 to 100 bases.

  Study phs000513

• Estrogen Receptor Positive Breast Cancer: Aromatase Inhibitor Response Study

  Highly variable outcomes are observed in patients with estrogen receptor positive (ER+) breast cancer who undergo preoperative estrogen deprivation therapy with aromatase inhibitors (AI). In this study, 46 baseline tumor and normal genomes and 31 baseline tumor/normal exomes of participants selected from two clinical trials of neoadjuvant AI therapy on ER+ breast cancer were sequenced to identify somatic alterations that correlate with response to AI, to screen for therapeutic targets and to elucidate the genetic landscape of ER+ breast cancer. From the same set of patients we later performed deep genomic characterization of a subset of matched primary tumors after four months of AI therapy, generating comprehensive information about the range of changes that occur when ER+ breast cancers are subjected to estrogen deprivation. This data includes whole genome sequence and transcriptome data. To better understand tumor heterogeneity and the evolution of resistance to estrogen-deprivation therapy, a subset of these tumours, along with 38 additional cases were sequenced to greater depth using targeted capture with a gene panel.

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• Whole Exome Sequencing of Parathyroid Cancer Identifies Candidate Driver Mutations and Core Pathways

  Here we performed genomic characterization of twenty-nine sporadic parathyroid cancers using next generation whole exome sequencing. Thirty-three novel candidate driver genes for sporadic parathyroid cancer were proposed, in addition to previously known driver genes CDC73 and MEN1.

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• Foregut Microbiome and Risk of Gastric Intestinal Metaplasia, and Gastric Cancer Risk

  The study is composed of two sub-studies. The first study, conducted by NYU Grossman School of Medicine, is a case-control study of 89 cases with gastric intestinal metaplasia (IM) and 89 matched controls who underwent upper gastrointestinal endoscopy at three sites affiliated with NYU Langone Health. Shotgun metagenomic sequencing using oral wash samples from the 89 case-control pairs and antral mucosal brushing samples from 55 case-control pairs were conducted. The other study, conducted by Vanderbilt University Medical Center, is a prospective case-control study on the oral microbiome and gastric cancer risk, utilizing shotgun metagenomic sequencing data of pre-diagnostic buccal samples from 319 Asians, 118 African Americans and 51 European Americans. This study includes data from three population-based studies: the Southern Community Cohort Study (SCCS), the Shanghai Women's Health Study (SWHS), and the Shanghai Men's Health Study (SMHS). The SWHS and SMHS include 74,941 women aged 40-70 years and 61,480 men aged 40-74 years, respectively, who were permanent residents of Shanghai and recruited to the cohorts between 1997 and 2006. The SCCS is an ongoing prospective cohort study, including ~86,000 participants recruited during 2002 and 2009 from 12 Southeastern states. Nearly 67% of study participants are African Americans (AAs) and the remaining are European American (EA) subjects.

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