Bulk RNA sequencing of colorectal tumors for molecular subtyping
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB34752 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:We have performed bulk RNA sequencing on colorectal tumors in order to determine their transcriptome-based molecular subtypes. RNA was isolated from fresh frozen human colorectal tumor specimens with Trizol extraction. RNA library preparation was performed with KAPA stranded mRNA sequencing kit, during which mRNA selection was performed with polyT capture beads. Sequencing was performed on Illumina HiSeq4000 as single-end 51 bp reads. File names include dataset name (KUL3), patient code(SCXXX), sample region (core or border) and sample code (EXTXXX): DATASETNAME_PATIENTCODE_SAMPLEREGION_rSAMPLE_CODE_...fastq.gz
2020-04-05 | E-MTAB-8412 | biostudies-arrayexpress
Project description:Colorectal Adenomas and Consensus Molecular Subtyping
| PRJNA423096 | ENA
Project description:Consensus molecular subtyping in adenomatous and serrated polyps
2018-12-19 | GSE108317 | GEO
Project description:Gene-expression molecular subtyping of triple-negative breast cancer tumors
| PRJNA400182 | ENA
Project description:Breast cancer was one of the first cancer types where molecular subtyping led to explanation of interpersonal heterogeneity and resulted in improvement of treatment regimen. Several multigene classifiers have been developed and in particular those defining molecular signatures of early breast cancers possess significant prognostic information. Hence since 2014, molecular subtyping of primary breast cancers was implemented as a part of routine diagnostics with direct impact of therapy assignment. In this study, we evaluate direct and potential benefits of molecular subtyping in low-risk breast cancers as well as present the advantages of a robust molecular signature in regard to patient work-up among high-risk breast cancers.
2017-12-01 | E-MTAB-5724 | biostudies-arrayexpress
Project description:Molecular subtyping of “double negative” MIBC
| PRJNA816119 | ENA
Project description:Purpose: Molecular subtyping for pancreatic cancer has made substantial progress in recent years, facilitating the optimization of existing therapeutic approaches to improve clinical outcomes in pancreatic cancer. With advances in treatment combinations and choices, it is becoming increasingly important to determine ways to place patients on the best therapies upfront. Although various molecular subtyping systems for pancreatic cancer have been proposed, consensus regarding proposed subtypes, as well as their relative clinical utility, remains largely unknown and presents a natural barrier to wider clinical adoption. Methods: We assess three major subtype classification schemas in the context of results from two clinical trials and by meta-analysis of publicly available expression data to assess statistical criteria of subtype robustness and overall clinical relevance. We then developed a single-sample classifier (SSC) using penalized logistic regression based on the most robust and replicable schema. Results: We demonstrate that a tumor-intrinsic two-subtype schema is most robust, replicable, and clinically relevant. We developed Purity Independent Subtyping of Tumors (PurIST), a SSC with robust and highly replicable performance on a wide range of platforms and sample types. We show that PurIST subtypes have meaningful associations with patient prognosis and have significant implications for treatment response to FOLIFIRNOX. Conclusions: The flexibility and utility of PurIST on low-input samples such as tumor biopsies allows it to be used at the time of diagnosis to facilitate the choice of effective therapies for patients with pancreatic ductal adenocarcinoma and should be considered in the context of future clinical trials.
2019-12-10 | GSE131050 | GEO
Project description:The GUSTO clinical trial (Gene expression subtypes of Urothelial carcinoma: Stratified Treatment and Oncological outcomes) uses molecular subtypes to guide neoadjuvant therapies in participants with muscle-invasive bladder cancer (MIBC). Before commencing the GUSTO trial, we needed to determine the reliability of a commercial subtyping platform (Decipher Bladder; Veracyte) when performed in an external trial laboratory as this has not been done previously. Here we report our pre-trial verification of the TCGA molecular subtyping model using gene expression profiling. Formalin fixed paraffin embedded tissue blocks of MIBC were used for gene expression subtyping by gene expression microarrays. Intra- and inter-laboratory technical reproducibility, together with quality control of laboratory and bioinformatics processes were assessed. Eighteen samples underwent analysis. RNA of sufficient quality and quantity was successfully extracted from all samples. All subtypes were represented in the cohort. Each sample was subtyped twice in our laboratory and once in a separate reference laboratory. No clinically significant discordance in subtype occurred between intra- or inter-laboratory replicates. Examination of sample histopathology showed variability of morphological appearances within and between subtypes. Overall, these results show that molecular subtyping by gene expression profiling is reproducible, robust, and suitable for use in the GUSTO clinical trial.
2024-01-18 | GSE253531 | GEO
Project description:Molecular stratification using gene-level transcriptional data has identified subtypes with distinctive genotypic and phenotypic traits, as exemplified by the consensus molecular subtypes (CMS) in colorectal cancer (CRC). Here, rather than gene-level data, we make use of gene ontology and biological activation state information for initial molecular class discovery. In doing so, we defined three pathway-derived subtypes (PDS) in CRC; PDS1 tumours are canonical/LGR5+ stem-rich, highly proliferative and display good prognosis. PDS2 which is regenerative/ANXA1+ stem-rich, with elevated stromal/immune tumour microenvironmental lineages. PDS3 tumours represent a previously overlooked slow-cycling subset of tumours within CMS2, with reduced stem populations and increased differentiated lineages, particularly enterocytes and enteroendocrine cells, yet display the worst prognosis in locally advanced disease. These PDS3 phenotypic traits are evident across numerous bulk and single-cell datasets, and demark a series of subtle biological states that are under-represented in pre-clinical models currently and are not identified using existing subtyping classifiers Mutations: https://www.s-cort.org/sites/default/files/exports/scort_spinal_focus_paper/ws4_spinal_mutations.txt, CNA per gene : https://www.s-cort.org/sites/default/files/exports/scort_spinal_focus_paper/ws4_spinal_cna_gene_subselection_for_paper.txt, CNA segments SPINAL https://www.s-cort.org/sites/default/files/exports/scort_spinal_focus_paper/ws4_spinal_cna.zip, CNA segments FOCUS https://www.s-cort.org/sites/default/files/exports/scort_spinal_focus_paper/ws2.focus_cna.zip
2023-12-12 | GSE248381 | GEO
Project description:Five molecular subtypes have been identified according to intrinsic genes transcription. Microarrays have been adopted for molecular subtyping in addition to the original NanoString nCounter assay. This study aimed to evaluate subtyping consistency among Taiwanese breast cancers. Our study showed that fundamental discrepancy exists between distinct gene expression measuring approaches, and cross platform equivalence should not be overemphasized with too much extrapolation.
2021-09-01 | GSE162228 | GEO