9338 results for "cancer rna-seq"

in 67.05 milliseconds.

• Genomic Correlates of Response and Resistance to Immune Checkpoint Blockade in Solid Tumors

  Immune checkpoint inhibitors yield clinical benefit in many cancer types, but molecular predictors of response have not yet been robustly characterized. In this study, we pursued whole exome sequencing (WES) of pre-treatment tumors from patients treated with immune checkpoint therapies - including monoclonal antibodies targeting programmed cell death-1 (PD-1) and cytotoxic T-lymphocyte-associated protein-4 (CTLA-4). Using these data, we aim to apply computational pipelines for mutation-calling, neoantigen prediction, and other analyses to validate pre-existing hypotheses regarding response to immune checkpoint therapies and discover new relationships with greater power. Further, by pursuing genomic characterization of tumors from patients with a variety of cancer types, we hope to describe molecular features of intrinsically sensitive or resistant tumors that are both context-specific and shared across cancer types.

  Study phs001565

• Whole-genome sequencing in 14 cases and whole-exome sequencing in 90 cases of Chinese ESCC

  Esophageal cancer is one of the most aggressive cancers and the sixth leading cause of cancer death worldwide1. Approximately 70% of the global esophageal cancers occur in China and over 90% histopathological forms of this disease are esophageal squamous cell carcinoma (ESCC)2-3. Currently, there are limited clinical approaches for early diagnosis and treatment for ESCC, resulting in a 10% 5-year survival rate for the patients. Meanwhile, the full repertoire of genomic events leading to the pathogenesis of ESCC remains unclear. Here we show a comprehensive genomic analysis in 158 ESCC cases, as part of the International Cancer Genome Consortium (ICGC) Research Projects (http://icgc.org/icgc/cgp/72/371/1001734). We conducted whole-genome sequencing in 14 ESCC cases and whole-exome sequencing in 90 cases.

  Study EGAS00001001487

• Genomic DNA of tumor tissues, adjacent normal tissues, and peripheral blood were extracted using QIAamp DNA mini Kit (QIAGEN, cat. #51306)

  Although genomic instability, epigenetic abnormality, and gene expression dysregulation are hallmarks of colorectal cancer, these features have not been simultaneously analyzed at single cell resolution. Using optimized single cell multiomics sequencing together with multiregional sampling of the primary tumor, lymphatic and distant metastases, we provide insights beyond intratumoral heterogeneity. Genome wide DNA methylation levels were relatively consistent within a single genetic sublineage. The genome-wide DNA demethylation patterns of cancer cells were consistent in all 10 sequenced patients. The cancer cells’ DNA demethylation degrees clearly correlated with the densities of the heterochromatin-associated histone modification H3K9me3 of normal tissue, and those of repetitive element Long Interspersed Nuclear Element 1. Our work demonstrates the feasibility of reconstructing genetic lineages, and tracing their epigenomic and transcriptomic dynamics with single cell multiomics sequencing.

  Study EGAS00001003242

• Characterization and clinical relevance of the genomic alterations defining invasive lobular breast cancer

  Background: Invasive lobular breast cancer (ILBC) is the second most common histological subtype after ductal breast cancer (IDBC). In spite of significant clinical and pathological differences, ILBC is still treated as IDBC. Here, we aimed at identifying recurrent genomic alterations in ILBC with potential clinical implications.Methods: Starting from 630 ILBC primary tumors with a median follow up of 10 years, we interrogated oncogenic substitutions and indels of 360 cancer genes and genome-wide copy number alterations in 413 and 170 ILBC samples, respectively, and correlated those findings with clinical, pathological, and outcome features. The Cancer Genome Atlas database was used for comparison of frequency estimates.Results: Besides the high mutation frequency of CDH1 in 65% of the tumors, alterations in one of the three key genes of the PI3K pathway, PIK3CA, PTEN and AKT1, were present in more than half of the cases. ERBB2 and ERBB3 were mutated in 5.1 and 3.6% of the tumors. FOXA1 mutations and ESR1 copy number gains were detected in 9% and 25% of the samples. All these alterations were more frequent in ILBC than IDBC. The histological diversity of ILBC was associated with specific genomic alterations, such as enrichment for ERBB2 mutations in the mixed, non-classic subtype, and for ARID1A mutations and ESR1 gains in the solid subtype. Finally, ERBB2 and AKT1 mutations were associated with short-term risk of relapse, and chromosome 1q and 11p gain with increased and decreased breast cancer free survival, respectively.Conclusion: ERBB2, ERBB3 and AKT1 mutations represent high prevalence therapeutic targets in ILBC. FOXA1 mutations and ESR1 gains urgently deserve dedicated clinical investigation, especially in the context of endocrine treatment.

  Dataset EGAD00001001395

• Asian lung cancer genome data

  Dac EGAC00001000248

• MDACC-Yale-breast-cancer

  Dac EGAC00001000298

• DAC Barretos Cancer Hospital

  Dac EGAC00001001077

• SMC Colon cancer team

  Dac EGAC00001001277

• Charbonneau Cancer Institute DAC

  Dac EGAC00001001280

• Cancer Data Access Commitee

  Dac EGAC00001001436

• Gene expression and Cancer

  Dac EGAC00001001727

• bladder cancer data access commitee

  Dac EGAC00001002016

• Lung cancer cfDNA dataset DAC

  Dac EGAC00001002388

• Lung cancer cfDNA dataset DAC

  Dac EGAC00001002387

• Cancer Team Data Access Committee

  Dac EGAC00001002449

• Cancer Sequencing Data Access Committee

  Dac EGAC00001002457

• Lung cancer cfDNA dataset DAC

  Dac EGAC00001002608

• Cancer Team Data Access Committee

  Dac EGAC00001002891

• Pancreatic cancer PDOs/CAFs DAC

  Dac EGAC00001002897

• Pan Cancer Plasma cfRNA DAC

  Dac EGAC00001002956

• Sequencing of Breast Cancer

  Study EGAS00001007490

• Sequencing of Ovarian Cancer

  Study EGAS00001007489

• Leukemia sequencing study

  Study EGAS00001006901

• EAC Genomic data

  Study EGAS00001004887

• ID1 in glioblastoma

  Study EGAS00001003711