Transcriptomic analysis of pretreated rectal cancer biopsies and association to the tumor regression score.
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA549937 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:To determine a preditcive marker of treatment resistance for rectal cancer, we have employed a microarray gene profiling analysis on pretreated rectal biopsies and compared with their response to therapy as defined by the American Joint Commission on Cancer (AJCC) and the American College of Pathologists.
2019-11-26 | GSE133057 | GEO
Project description:Understanding transcriptional changes in locally advanced rectal cancer which are therapy-related and dependent upon tumour regression will drive stratified medicine in the rectal cancer paradigm
2018-11-01 | GSE94104 | GEO
Project description:Although preoperative chemoradiotherapy (CRT) and surgical mesorectal resection is the standard of care for locally advanced rectal carcinomas, it is still difficult to predict which patients will respond to treatment. We explored how differential stromal transcriptomic profiles from microdissected pretreatment rectal biopsies can be used to define an immunohistochemical score based on two CAF-specific proteins for predicting neoadjuvant treatment response. The analysis of differentially expressed genes (DEGs) of stroma and tumour glands from responder and non-responder patients shows that most changes were associated with the stromal compartment. Gene ontology analysis revealed that the DEGs codify mainly for extracellular matrix and ribosomal components. We built a CAF-specific classifier with genes showing monotonic changes in expression according to the tumour regression grade (coefficient >1; FN1, COL3A1, COL1A1, MMP2 and IGFBP5). These are the genes that display the biggest a priori differences in expression between non-responder and responder stroma. We translated these five genes at the protein level by means of immunohistochemical staining in a cohort of 38 patients. For predictive purposes we used a leave-one-out cross-validated (LOOCV) model with a positive predictive value (PPV) of 80%. Classifier optimisation with Random Forest identified FN1 and COL3A1 as the best predictors. Rebuilding the LOOCV regression model improved the classification performance with a PPV of 89.5% and a negative predictive value (NPV) of 73.7%. An independent cohort of 36 patients was used to validate the classifier performance, which had a PPV of 84.2% and an NPV of 70.6%. In a multivariate analysis the two-protein classifier proved to be the only independent predictor of response (HR=2.58; P=0.003). We also explored a pharmacogenomic approach to gather information about possible therapeutic strategies for non-responder patients. In conclusion, we developed a two-protein immunohistochemical classifier that performs well at predicting the absence of response to neoadjuvant treatment in rectal cancer.
2017-01-11 | GSE93375 | GEO
Project description:RNA was isolated from rectal biopsies from 190 pediatric patients undergoing diagnostic colonoscopy for inflammatory bowel diseases, including Crohn's disease and ulcerative colitis. Single-end, 75-bp sequencing was performed, and raw reads aligned to the human genome using Gencode v 24 as reference. We included 14085 protein-coding mRNA genes in downstream analyses, where cutoffs of fold change>1.5 and FDR<0.05 were considered significant.
2018-11-27 | GSE117993 | GEO
Project description:Importance: Neoadjuvant chemoradiotherapy (CRT) is the standard of care for advanced rectal cancer. Yet, predicting response to CRT remains an unmet clinical challenge. Objective: To investigate the transcriptomic determinants to predict response to neoadjuvant CRT and survival in patients with advanced rectal cancer. Design: A single-center, retrospective, cohort study. Setting: A comprehensive cancer center. Participants: Pre-treatment biopsies from 298 patients with rectal cancer, who were later treated with neoadjuvant CRT between 2004 and 2020, were analyzed by RNA sequencing. Main measures and outcomes: Transcriptional subtyping was performed by consensus molecular subtype (CMS) classification. Immune cell infiltration was assessed using MCP-counter scores and single-sample gene set enrichment analysis (ssGSEA). Patients with surgical specimens of tumor regression grade (TRG) 3-4 or who were managed by the watch-and-wait approach for more than 3 years were defined as good responders. Results: Patients classified as CMS1 (6.4%) had a significantly higher rate of good responders; albeit survival was comparable among the four subtypes. Good responders exhibited an enrichment in various immune-related pathways (IFNg and a responses, allograft rejection, IL6 STAT3 signaling during acute phase response, and inflammation), as determined by ssGSEA. MCP-counter scores for cytotoxic lymphocytes were significantly higher for good responders than non-responders (p = 0.0003), and significantly higher for responders than non-responders in GSE109057 (p = 0.0137), GSE87211 (p = 0.0092), and GSE45404 (p = 0.0327) datasets. Cytotoxic lymphocyte MCP-counter score was thus considered an independent predictor of response to CRT, as determined in the multivariable Cox analysis (OR 3.810 [95% CI 1.820-7.970]; p = 0.0004). Multivariable Cox analysis, including post-operative pathological factors, revealed cytotoxic lymphocyte MCP-counter score to be independently associated with recurrence-free survival (HR 0.382 [95% CI 0.158-0.923]; p = 0.0325) and overall survival (HR 0.157 [95% CI 0.030-0.827]; p = 0.0290). ssGSEA showed significantly higher levels of four subpopulations of cytotoxic cells (effector memory CD8 T, natural killer T, natural killer, and activated CD8 T cells) among good responders than non-responders. Conclusions and Relevance: Cytotoxic lymphocyte score, as computed by RNA sequencing, could be a useful marker for predicting response to CRT and survival among patients with rectal cancer.
2023-01-25 | GSE216616 | GEO
Project description:Background: Neoadjuvant chemoradiotherapy (NCRT) is the treatment of choice in advanced rectal cancer, even though there are many patients who will not benefit from it. There are still no effective methods for predicting which patients will respond or not. The present study aimed to define the genomic profile of rectal tumors and to identify alterations that are predictive of response in order to optimize therapeutic strategies. Methods: Forty-eight candidates for NCRT were recruited and their pretherapy biopsies analyzed by array Comparative Genomic Hybridization (aCGH). Pathologic response was evaluated by tumor regression grade (TRG).Results: Both Smoothing and Hidden Markov Model (HMM) approaches identified similar alterations, with a prevalence of DNA gains. Non responsive patients had a different alteration profile from responsive ones, with a higher number of genome changes mainly located on 2q21, 7q21, 7q36, 13q12, 13q32-34, 16p13, 17p12 chromosomal regions. Conclusion: This exploratory study suggests that an in depth characterization of chromosomal alterations by aCGH would provide useful predictive information about response to NCRT and help to optimize therapy in rectal cancer patients.
2011-11-17 | GSE25885 | GEO
Project description:Transcriptomics and proteomics analyses were carried out on rectal mucosal biopsies from 22 healthy adults with either optimal (n=11, mean plasma Se =1.43μmol/l, s.e.m ±0.06) or sub-optimal (n=11, mean plasma Se = 0.86umol/l, s.e.m ± 0.01) plasma Se status. Plasma Se status was associated with altered expression of 254 genes implicated in cancer, immune function and inflammatory response, cell growth and proliferation, cellular movement and cell death; 69 out of 254 genes had their expression significantly correlated with Se status, including two selenoprotein genes (SEPW1 and SELK). Proteomics identified 26 proteins differentially expressed between the two Se groups, including cytoskeletal proteins and factors involved in immune and inflammatory response and cancer pathways. Results from proteomics and transcriptomics support each other and integration of the two datasets was consistent with a reduced inflammatory and immune responses and a cytoskeleton remodelling in the rectal mucosa of individuals with sub-optimal Se status.
2015-12-31 | GSE70550 | GEO
Project description:Mucosal transcriptome of rectal biopsies in treatment-naïve, pediatric ulcerative colitits patients
| PRJNA429769 | ENA
Project description:Emerging evidence suggests that an increased density of pre-treatment CD8+ tumor-infiltrating lymphocytes (TILs) is associated with good response to chemoradiotherapy (CRT) in patients with locally advanced rectal cancer. However, the significance of T-cell complexity in the clinical setting remains unknown. High-throughput T-cell receptor (TCR) β sequencing was applied to quantify the TCR repertoire of pre-treatment biopsies from 67 patients with advanced rectal cancer receiving preoperative CRT. Changes in TCR repertoire before and after CRT were also analysed in 23 patients.
2022-11-22 | GSE218181 | GEO
Project description:Gene expression profiles were recorded from rectal suction specimens of Cystic Fibrosis (CF) patients, carrying the CF-specific D508 mutated CFTR-allele. These profiles were compared with gene expression profiles from rectal suction specimens of non-CF subjects (control). We used Affymetrix GeneChip HG-U133A microarrays to record the gene expression profile of 16 CF and 13 non-CF individuals. Rectal suction specimens representing rectal mucosal epithelia were collected from CF patients and non-CF individuals. Biopsies were analyzed for residual function using ICM and total RNA was isolation immediately using the Qiagen RNeasy protocol with on column DNA digestion. About 1-5 µg RNA were obtained from each individual. Integrity of total RNA samples was monitored by gel-electrophoresis before cDNA synthesis. Labeled cRNA synthesis and hybridization was performed following standard protocols.
2013-11-28 | E-GEOD-15568 | biostudies-arrayexpress