495 results for "cancer rna-seq"

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• A Phase 2 Study of Lamivudine in Patients with p53 Mutant Metastatic Colorectal Cancer

  This was an open-label, single-arm Phase II study of lamivudine in patients who had progressed on systemic therapy for advanced colorectal cancer with TP53 mutations. The phase II study had a two-stage design, with a target accrual of 20 evaluable patients for the first stage and a total of 32 patients for the whole study. The first 9 patients were treated with lamivudine at 150 mg PO bid continuously for 28-day cycles. Subsequent patients (10-32) received a higher dose of 600 mg PO bid continuously for 28-day cycles. Tumor assessments were performed every 8 weeks until documented disease progression by Response Evaluation Criteria in Solid Tumors (RECIST) or drug intolerance. Whole genome sequencing (WGS) and total RNA-seq were performed on pre- and post- treatment biopsies on this trial.

  Study phs002833

• RNA-seq TPMs quantification for baseline tumor samples originating from IMpower150, and relevant clinical metadata

  This dataset includes full tumor transcriptomes from 558 advanced NSCLC tumors. These data originate from pre-treatment samples from a clinical trial for first-line non-small cell lung cancer (IMpower150). The patients in this trial were treated with the PD-L1 inhibitor atezolizumab +bevacizumab + chemotherapy or bevacizumab + chemotherapy or atezolizumab + chemotherapy.

  Dataset EGAD50000001814

• Processed RNA-seq data for clinical efficacy and biomarker analysis of neoadjuvant atezolizumab in operable urothelial carcinoma in the ABACUS trial

  ABACUS is a single arm phase 2 study that investigated 2 cycles of atezolizumab (1200mg Q3) prior to cystectomy in 95 patients with muscle invasive transitional cell cancer (T2-4N0M0). Pathological complete response (pCR) occurring in ≥20% of patients was the primary endpoint. Biomarker analysis on sequential tissue was a co-primary endpoint. This dataset includes the TPM and raw counts tables.

  Dataset EGAD00001006199

• ScRNA-seq of 6 human FL

  Follicular lymphoma (FL) is an indolent cancer of mature B-cells but carries increased risk of transformation to a more aggressive histology over time. We present here comprehensive profiling both tumor and immune compartments in 6 diagnostic FL biopsies by single-cell RNA sequencing. This confirmed results from 155 FL tumors characterized by mass cytometry (CyTOF) which revealed two distinct evolutionary trajectories with disparate risk of transformation and alternate biologies.

  Dataset EGAD00001007691

• Processed bam files for the whole exome sequencing of primary lung adenocarcinoma samples

  We performed single cell RNA sequencing (scRNA-seq) for 208,506 cells derived from 58 lung adenocarcinomas from 44 patients, which covers primary tumour, lymph node and brain metastases, and pleural effusion in addition to normal lung tissues and lymph nodes. The extensive single cell profiles depicted a complex cellular atlas and dynamics during lung adenocarcinoma progression which includes cancer, stromal, and immune cells in the surrounding tumor microenvironments.

  Dataset EGAD00001010320

• Genomic and Immune Profiling of Breast Cancer Brain Metastases

  Previous work has shown that breast cancer brain metastases (BCBrM) can have unique molecular profiles compared to extracranial tumors (ECTs), resulting in some patients demonstrating subtype switching between primary/extracranial tumors and brain metastases. Description of the biology of BCBrM and associations between biological features and clinical outcomes, particularly between molecular intrinsic subtypes, will facilitate the design of rational therapies for patients with BCBrM. To better characterize the molecular profiles of BCBrM, we conducted whole exome sequencing (WES) and total RNA sequencing (RNA-Seq) on BCBrM tissues, regardless of clinical or molecular subtype, obtained from a cohort of 42 patients from Duke University Medical Center. This cohort adds valuable patient samples to the field and enables strengthened investigation of somatic mutations, copy number alterations, gene expression profiles, and immune populations within and between BCBrM patients and other similar cohorts. The Duke BCBrM cohort includes clinical and molecular annotation of the 42 patient specimens and their associated WES and RNA-Seq data. Clinical and molecular (PAM50) intrinsic subtypes in ECTs and brain metastases were largely concordant within patients. There were observed differences in intrinsic subtype calls between frozen and FFPE specimens of the same tissue, with discordance mostly observed with LumB calls. Copy number alterations in chromosomal regions included clinically relevant genes, and somatic alterations were largely conserved within patients across matched samples, with few genes, including TP53, being recurrently altered in the majority of patient specimens. In matched FFPE brain metastasis and ECT samples, we observed differentially expressed genes and pathways that had increased or decreased expression in brain metastasis, including in oxidative phosphorylation and DNA repair. Survival outcomes for patients differed by intrinsic molecular subtypes, with some association between expression of select gene pathways and survival. Data available through dbGaP will be the sequencing data and sample attributes from BCBrM tissues obtained from 42 patients from Duke University Medical Center.

  Study phs003673

• Probabilistic cell type assignment of single-cell transcriptomic data reveals spatiotemporal microenvironment dynamics in human cancers

  Single-cell RNA sequencing (scRNA-seq) has transformed biomedical research, enabling decomposition of complex tissues into disaggregated, functionally distinct cell types. For many applications, investigators wish to identify cell types with known marker genes. Typically, such cell type assignments are performed through unsupervised clustering followed by manual annotation based on these marker genes, or via "mapping" procedures to existing data. However, the manual interpretation required in the former case scales poorly to large datasets, which are also often prone to batch effects, while existing data for purified cell types must be available for the latter. Furthermore, unsupervised clustering can be error-prone, leading to under- and over- clustering of the cell types of interest. To overcome these issues we present CellAssign, a probabilistic model that leverages prior knowledge of cell type marker genes to annotate scRNA-seq data into pre-defined and de novo cell types. CellAssign automates the process of assigning cells in a highly scalable manner across large datasets while simultaneously controlling for batch and patient effects. We demonstrate the analytical advantages of CellAssign through extensive simulations and exemplify real-world utility to profile the spatial dynamics of high-grade serous ovarian cancer and the temporal dynamics of follicular lymphoma. Our analysis reveals subclonal malignant phenotypes and points towards an evolutionary interplay between immune and cancer cell populations with cancer cells escaping immune recognition.

  Study EGAS00001003452

• Exploring_the_heterogeneity_of_sarcoma_using_single_cell_sequencing_

  Multi region samples are collected from patients, with consent, immediately after resection of the tumour. Samples are digested and sorted using FACS as single cells into lysis buffer. Cells are then stored until further processing for G&T-seq. After sequencing, we will explore intra-tumour heterogeneity using computational approaches to integrate RNA and DNA data onto the tumour phylogeny This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001002866

• Transcriptional Profiling of Macrophages In Situ in Metastatic Melanoma Reveals Localization-Dependent Phenotypes and Function

  Therapeutic interventions modulating immune function at the tumor site could improve outcomes in cancer. Here we analyzed metastatic melanoma, a tumor type highly responsive to T-cell based therapies, and found that the tumor-infiltrating T cells are localized closely to CD14+ monocytes/macrophages rather than to melanoma cells. Using novel immunofluorescence-guided laser capture micro-dissection, we analyzed transcriptomes of CD3+ T cells, CD14+ monocytes/macrophages and melanoma cells in non-dissociated tissue. CD14+ cells localized in tumors beds displayed specific transcriptional signatures distinct from CD14+ cells that were localized in tumor stroma.The 8 distinct metastatic melanoma samples are from the Cooperative Human Tissue Network (CHTN). 64 RNA-seq files are available from 16 intraCD14+, 16 stromaCD14+, 16 cancer cells, 8 intraCD3+ and 8 stromaCD3+ cells. 2 LCM harvests were completed for the CD14+ and cancer cells on two sections of the samples. One harvest was done for the CD3+ samples.The processed data (TPM/raw counts tables) are available on GEO under GSE180124. 

  Study phs002564

• Development of the prevention and therapy of CRC using patient derived culture tissues.

  Tumor tissues consist of functionally heterogeneous cells including those with high clonogenic potential called cancer stem cells (CSCs) which produce differentiated non-tumorigenic progenies. Transplantation assays have been performed to identify cell surface markers in solid tumors including colorectal cancers, which identified several CSC markers such as CD133 and CD44. In addition to the transplantation, the lineage tracing of genetically labelling cells in animal models of cancer qhas been employed to explore the cellular heterogeneity of tumors by identifying the CSCs and its progenies. This approach is particularly useful to investigate solid tumors, where cellular proliferation and differentiation are controlled by niche factors and cell-cell contact with adjacent cells. Lineage tracing of mouse model of cancer unravel the mode of growth of autochthonous tumor in their native environment. In this study, we used patient derived organoids (PDO) established from surgically resected CRC patients to identify the CSC. Single cell RNA-seq analysis identified potential CRC markers, which may exhibit self-renewal activity and produce progenitors

  Study JGAS000139

• Dissecting intratumor heterogeneity of nodal B cell lymphoma on the transcriptional, genetic, and drug response level

  Tumor heterogeneity encompasses both the malignant cells and their microenvironment. While heterogeneity between individual patients is well-known to affect the efficacy of anti-cancer, most personalized treatment approaches do not account for intratumor heterogeneity. We addressed this issue by studying the heterogeneity of lymph node-derived B cell non-Hodgkin lymphoma (B-NHL) by single cell RNA-sequencing (scRNA-seq) and transcriptome-informed flow cytometry. We identified transcriptionally distinct malignant subclones and compared their drug response and genomic profiles. Malignant subclones of the same patient responded strikingly different to anti-cancer drugs ex vivo, which recapitulated subclone-specific drug sensitivity during in vivo treatment. Tumor infiltrating T cells represented the majority of non-malignant cells, whose gene expression signatures were similar across all donors, whereas the frequencies of T cell subsets varied significantly between the donors. Our data provide new insights into the heterogeneity of B-NHL and highlight the relevance of intratumor heterogeneity for personalized cancer therapies.

  Study EGAS00001004335

• Epigenome and transcriptome profiling of chronic lymphocytic leukemia patients

  Chronic lymphocytic leukemia (CLL) is characterized by substantial clinical heterogeneity, despite relatively few genetic alterations. To provide a basis for studying epigenome deregulation in CLL, we established genome-wide chromatin accessibility maps for 88 CLL samples from 55 patients using the ATAC-seq assay, and we also performed ChIPmentation and RNA-seq profiling for ten representative samples. Based on the resulting dataset, we devised and applied a bioinformatic method that links chromatin profiles to clinical annotations. Our analysis identified sample-specific variation on top of a shared core of CLL regulatory regions. IGHV mutation status – which distinguishes the two major subtypes of CLL – was accurately predicted by the chromatin profiles, and gene regulatory networks inferred for IGHV-mutated vs. IGHV-unmutated samples identified characteristic differences between these two disease subtypes. In summary, we discovered widespread heterogeneity in the chromatin landscape of CLL, established a community resource for studying epigenome deregulation in leukemia, and demonstrated the feasibility of chromatin accessibility mapping in cancer cohorts and clinical research.

  Study EGAS00001001821

• single cell RNA-seq of small cell lung cancer circulating tumor cells

  This study investigated the transcriptomic profile of circulating tumor cells from three small cell lung cancer patients. CTCs were enriched from the blood of three SCLC patients using the CTC-iChip followed by magnetic depletion of RBCs. The enriched samples were processed with the 10x Genomics Chromium platform (Chromium GEM-X Single Cell 3' Kit v4) and sequenced on a NextSeq 2000 system.

  Study EGAS50000001401

• Inferring expressed genes by whole-genome sequencing of plasma DNA

  The analysis of cell-free DNA (cfDNA) in plasma represents a rapidly advancing field in medicine. cfDNA consists predominantly of nucleosome-protected DNA shed into the bloodstream by cells undergoing apoptosis. We performed whole-genome sequencing (WGS) of plasma DNA and identified two discrete regions at transcription start sites (TSS) where the nucleosome occupancy results in different read-depth coverage patterns in expressed and silent genes. By employing machine learning for gene classification we found that the plasma DNA read depth patterns from healthy donors reflected the expression signature of hematopoietic cells. In cancer patients with metastatic disease, we were able to classify expressed cancer driver genes in regions with somatic copy number gains with high accuracy. We could even determine the expressed isoform of genes with several TSSs as confirmed by RNA-Seq of the matching primary tumor. Our analyses provide functional information about the cells releasing their DNA into the circulation.

  Study EGAS00001001754

• Case Report: Pre-Clinical Combination Targeting VEGF and PI3K in a Rare, Aggressive Mixed Endometrial Carcinoma

  We report a rare case of a young patient (VENUS 167) initially diagnosed with grade 1 endometrioid endometrial cancer, which, following endocrine treatment, presented with mixed aggressive carcinoma with three distinct histologic patterns: grade 1 endometrioid, large cell neuroendocrine, and undifferentiated carcinoma. The surgical specimen at the time of disease progression was used to establish OPTO.85, a patient-derived organoid (PDO), followed by a corresponding organoid-derived xenograft (ODX). Multi-omic analyses confirmed that OPTO.85 accurately reflected the patient’s tumor characteristics. WES analysis identified oncogenic alterations in PIK3CA, ARID1A, and CTNNB1. Further RNA-seq and ATAC-seq analyses revealed enrichment in VEGF and Wnt signaling pathways, suggesting therapeutic vulnerabilities. A high-throughput drug screen was conducted using ApexBio-Approved and Epigenetic Drug Libraries, along with Kinase Inhibitor and Tool Compound Libraries developed at the Ontario Institute of Cancer Research. The OPTO.85 PDO exhibited sensitivity to PI3K inhibitors and responsiveness to VEGF inhibition. Cediranib demonstrated synergy with BKM120, significantly reducing organoid growth. This combination also showed in vivo efficacy in the ODX model, where dual inhibitors significantly suppressed tumor growth compared to single compounds. This case exemplifies the impact of genomic profiling and patient-derived models in identifying actionable molecular changes in rare cancers with limited therapeutic options and poor prognosis. It highlights that high-throughput sequencing for individual patient tumors and generation of patient-derived models are feasible in endometrial cancer. This preclinical model may assist clinical decision and personalized therapy requiring validation in prospective studies.

  Study EGAS50000001665

• Human Pilocytic Astrocytoma Single Cell RNA Sequencing

  Pilocytic astrocytoma (PA), the most common childhood brain tumor, is a low-grade glioma with a single driver BRAF rearrangement. Here, we perform scRNAseq in six PAs using methods that enabled detection of the rearrangement. When compared to higher-grade gliomas, a strikingly higher proportion of the PA cancer cells exhibit a differentiated, astrocyte-like phenotype. A smaller proportion of cells exhibit a progenitor-like phenotype with evidence of proliferation. These express a mitogen-activated protein kinase (MAPK) program that was absent from higher-grade gliomas. Immune cells, especially microglia, comprise 40% of all cells in the PAs and account for differences in bulk expression profiles between tumor locations and subtypes. These data indicate that MAPK signaling is restricted to relatively undifferentiated cancer cells in PA, with implications for investigational therapies directed at this pathway. Note that 931 out of 1234 samples in the Sequence Read Archive (SRA) passed QC and have transcript count data available from the Broad Institute Single Cell Portal. The transcript count data can be found at https://singlecell.broadinstitute.org/single_cell/study/SCP271/pilocytic-astrocytoma-single-cell-rna-seq#study-download

  Study phs001854

• Integrative analysis reveals a macrophage-predominant, immunosuppressive immune microenvironment and subtype-specific therapeutic vulnerabilities in advanced salivary gland cancer

  Background Salivary gland cancers (SGC) are rare and heterogeneous malignant tumors. Advanced SGC lack established treatment options and show poor response to immunotherapy. Here, an integrative multi-omics analysis in a large cohort of advanced SGC revealed insights into the tumor immune microenvironment (TIM) and distinct mechanisms of immune evasion. Methods A total of 104 patients with recurrent/metastatic SGC from the DKTK MASTER program were included in this study. Whole-exome or whole-genome sequencing and RNA-sequencing was performed on fresh frozen tumor tissue. The tumor immune microenvironment was analyzed using CIBERSORT deconvolution analysis and immune gene expression scores in bulk RNA-sequencing data. Single-nuclei sequencing and immunohistochemistry analyses were performed in selected samples. Results were validated in bulk RNA-sequencing data of a previously published independent dataset. Results Bulk transcriptome analysis revealed an immune-deserted TIM in the majority of advanced SGC samples. Immune exclusion was most prominent in adenoid cystic carcinoma (ACC) subgroup 1 exhibiting a downregulation of the antigen processing machinery. Only a small subset of advanced SGC, including few adenoid cystic carcinoma, exhibited T-cell inflammation, which was correlated with tumor mutational burden in Non-ACC samples. Subtype specific expression of immune checkpoints as well as cancer testis antigens were identified with prominent expression of VTCN1 in luminal cells within ACC. Single-cell RNA-sequencing and bulk RNA-seq deconvolution analysis validated immune cell exclusion and revealed a TIM that was dominated by M2 macrophages across SGC subtypes. Among evaluable patients treated with immune checkpoint inhibitors, a high T-cell to macrophage ratio was associated with clinical benefit. Conclusions These data support biomarker-based development of immune-checkpoint inhibition and the development of novel immune-checkpoint inhibitors and cellular therapies in SGC.

  Study EGAS50000000809

• International Cancer Proteogenome Consortium (ICPC): Proteogenomics of Oral Squamous Cell Carcinoma in Taiwan

  Oral cavity squamous cell carcinoma (OSCC) is the major subtype (~90%) of oral cancer, which is leading cancer with high mortality worldwide. The environmental risk factors associated with OSCC are quite different in Taiwan as compared to other populations. In most non-Taiwanese populations, OSCC is often associated with tobacco chewing, cigarette smoking, alcohol drinking, or human papillomavirus (HPV) infection. In Taiwan, in contrast, the OSCC occurs mainly in males aged 30 years or older who have habitual betel nut chewing, cigarette smoking, and alcohol drinking. To uncover molecular mechanisms and identify new therapeutic strategies of oral squamous cell carcinoma, this study recruited 112 treatment-naïve OSCC patients and generated multi-omics data, including WES, RNA-Seq, TMT-labeled proteomes, and phosphoproteomes from paired normal/tumor tissues. We have investigated our multi-omics data, covering molecular characterizations such as mutation signatures, impacts of mutations on RNA/protein/phosphoprotein, RNA-protein correlation, somatic copy number alteration, and the relationship with RNA & protein, proteome, and phosphoproteome analysis (T vs NAT), novel peptides (somatic variants, neoantigens, CT antigens, T cell receptors, etc.), as well as molecular subtyping (& pathway analysis). Notably, we have discovered a higher frequency of APOBEC3B deletion polymorphism in the Taiwanese population, and APOBEC3A is a potential prognostic biomarker. Our proteogenomic data enable us to further stratify patients into four groups based on APOBE3A expression level, which is found inversely correlated with EGFR expression. Therefore, the patients with high EGFR and low APOBEC3A expression may benefit from anti-EGFR therapy, while those with low EGFR and high APOBEC3A expression may benefit from immunotherapy. To clarify if there is an interaction between genetic polymorphisms and betel nut chewing habit in Taiwanese OSCC, we plan to concurrently evaluate the effect of habitual betel nut chewing on the gene mutation pattern, the dysregulated protein/phosphoproteins as novel biomarkers and/or therapeutic targets, and the molecular subtyping of patients for effective treatments. 

  Study phs002580

• High-coverage whole exome sequence in non-TRU-type lung adenocarcinomas

  In order to elucidate the key genetic events in non-TRU-type lung cancer, we selected 43 non-TRU-type lung adenocarcinomas and performed a whole exome sequence and RNA-seq analysis using a next-generation sequencer. The results of the analysis identified mutations in TP53, KRAS and NKX2-1 as the top three significantly mutated genes, while the EGFR mutation was rare in this cohort. Eight NKX2-1 mutations (5 frameshift, 2 nonsense, and one missense) were identified, with one case harboring two distinct NKX2-1 mutations (missense and frameshift). All NKX2-1 mutants were transcriptionally inactive in reporter assays. Histologically, invasive mucinous adenocarcinomas accounted for most of the NKX2-1 mutations (5 cases), while 1 enteric and 1 acinar adenocarcinoma harbored the NKX2-1 mutation.

  Study JGAS000105

• Arriba: accurate and efficient detection of gene fusions from RNA-Seq (H021)

  The identification of gene fusions from RNA sequencing data is a routine task in cancer research and precision oncology. However, despite the availability of many computational tools, fusion detection remains challenging. Existing methods suffer from poor prediction accuracy and are computationally demanding. We developed Arriba, a novel fusion detection algorithm with high sensitivity and short runtime. When applied to a large collection of published pancreatic cancer samples (n=803), Arriba identified a variety of driver fusions, many of which affected druggable proteins, including ALK, BRAF, FGFR2, NRG1, NTRK1, NTRK3, RET, and ROS1. The fusions were significantly associated with KRAS wild-type tumors and involved proteins stimulating the MAPK signaling pathway, suggesting that they substitute for activating mutations in KRAS. In addition, we confirmed the transforming potential of two novel fusions, RRBP1-RAF1 and RASGRP1-ATP1A1, in cellular assays. These results demonstrate Arriba’s utility in both basic cancer research and clinical translation.

  Study EGAS00001003554

• Breast Cancer FRT RNA seq

  We propose to definitively characterise the somatic genetics of ER+ve, HER2-ve breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Dataset EGAD00001000338

• Data Access Committee for the DNA sequencing data included in the study "Multifocal cohort analysis unveils cell types associated with regional lymph node seeding in prostate cancer".

  A data transfer agreement (DTA), based on the example DTA provided by UZ Gent, is to be filled out by the requester and Multifocal RNA-seq and tNGS data from primary and metastatic tissues of locally advanced and de novo metastatic cohorts - Data Access Committee. https://www.uzgent.be/nl/over-uz-gent/organisatie/data-access-comite/wat-zijn-de-opdrachten-van-het-data-access-comite Coordinator: Muriel Fouquet E-mail: dataaccesscommittee@uzgent.be

  Dac EGAC50000000930

• Comprehensive single cell study of lung adenocarcinoma from early to metastatic stages

  We performed single cell RNA sequencing (scRNA-seq) for 208,506 cells derived from 58 lung adenocarcinomas from 44 patients, which covers primary tumour, lymph node and brain metastases, and pleural effusion in addition to normal lung tissues and lymph nodes. The extensive single cell profiles depicted a complex cellular atlas and dynamics during lung adenocarcinoma progression which includes cancer, stromal, and immune cells in the surrounding tumor microenvironments.

  Dataset EGAD00001005054

• Translation of non-canonical open reading frames as a cancer cell survival mechanism in childhood medulloblastoma - Ribo-Seq

  This study aims to investigate the dysregulation of RNA translation and identify functional non-canonical open reading frames (ORFs) as potential targets for medulloblastoma treatment. The study involves ribosome profiling and RNAseq of medulloblastoma tissues and cell lines to observe the translation of non-canonical ORFs. Multiple CRISPR-Cas9 screens will be used to identify functional non-canonical ORFs implicated in medulloblastoma cell survival.

  Dataset EGAD00001011193

• Childhood Cancer Data Initiative (CCDI): Pediatric In Vivo Testing Program –Sarcoma, Kidney, and Liver Cancers

  The goal was to complete whole exome sequencing (WES) and RNA sequencing (RNA-Seq) on patient derived xenograft samples. Cancer in children is rare with approximately 15,700 new cases diagnosed annually in children 21 years or younger in the U.S. Through use of multimodality therapy (surgery, radiation therapy, and aggressive chemotherapy), 70% of patients will be 'cured' of their disease, and 5-year Event-Free Survival (EFS) exceeds 80%. Consequently, the number of patients that can be enrolled in phase I/II clinical trials is small, and most patients will have been extensively treated, hence drug/radiation resistant. Thus, preclinical studies that accurately translate into effective clinical therapy are an essential component of pediatric drug development. Our group has contributed to studies in the Pediatric Preclinical Testing Program (PPTP) and Pediatric Preclinical Testing Consortium (PPTC) that have led to clinical studies through Children's Oncology Group (COG). Of importance, we have developed and characterized over 330 Patient Derived Xenografts (PDX), developed from tumors both at diagnosis and relapse, that can be used to facilitate pediatric drug development as directed by FDA under the Research to Accelerate Cures and Equity for Children Act (RACE for Children Act).

  Study phs003160