A consensus molecular subtypes classification strategy for clinical colorectal cancer tissues
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE267010 | GEO | 2024/05/22
REPOSITORIES: GEO
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Project description:Gene expression profile from 193 formalin-fixed and paraffin embedded primary tumor samples.
2018-05-08 | GSE104645 | GEO
Project description:The Colorectal Cancer Subtyping Consortium established four Consensus Molecular Subtypes (CMS) in colorectal cancer: CMS1 (microsatellite-instability [MSI], Immune), CMS2 (Canonical, epithelial), CMS3 (Metabolic), and CMS4 (Mesenchymal). However, in the clinical practice only patients with MSI tumors have experienced a change in the management of their disease. Proteomics has experimented significant technical advances with the implementation of data-independent acquisition (DIA) as the gold-standard for the analysis of large cohort of patients, providing a dynamic framework of the disease and direct information about the effectors of the biological processes. The aim of this study is the characterization of the proteome of colon cancer CMS by DIA–based proteomics and expand the utility of CMS in the clinical practice. CMS were assigned and differences in the protein profiles between CMS were defined and evaluated using a Systems Biology approach. One hundred fifty-eight paraffin samples from colon cancer patients with stage II-III disease treated with adjuvant chemotherapy were analyzed. After applying quality criteria, 1,940 identified and quantified proteins were used for the analyses. CMS1 had an overexpression of proteins related to immune system, specifically neutrophils, phagocytosis and antimicrobial response, and a glycolytic profile. CMS3 had an overexpression of proteins related to metabolic pathways, while CMS2 showed an intermediate protein profile between CMS1-3, but with a characteristic profile regarding translation, adhesion, and mitochondria and metabolism biological processes. Two proteomics subtypes within CMS2 with different protein characteristics and prognosis were identified. CMS4 was the most different group with an overexpression of proteins related to angiogenesis, extracellular matrix, focal adhesion, and complement activation. In conclusion, DIA LC-MS/MS proteomics characterization of CRC CMS established new features for each CMS, such as a higher mitochondrial activity in CMS2 or an overexpression of proteins related to phagocytosis in CMS1, but also confirmed previous findings established using transcriptomics such as an overexpression of proteins related to angiogenesis in CMS4. In this CMS4 subtype, several adhesion-related proteins suggested a high metastatic profile and a possible chemoresistance that may explain the worse prognosis of this subtype. CMS1 was characterized as immune and glycolitic-active subtype, being the combination of immunotherapy and glycolytic inhibitors a possible therapeutic strategy. Additionally, two different CMS2 proteomics-based subtypes with different prognosis and possible therapeutic targets were identified. These proccesses could be used as therapeutic targets in the future.
2024-09-30 | PXD044935 | Pride
Project description:Purpose: To validate the novel ColoType assay for computing consensus molecular subtypes of colon cancer tumor samples Method: Whole-genome RNA-sequencing of colon cancer samples from formalin-fixed paraffin-embedded (FFPE) provided data for consensus molecular subtyping samples using multiple independent methods, including the novel ColoType method. A custom Illumina AmpliSeq library was also used to implement ColoType on these samples by targeted RNA-sequencing. Results: Multiple independent methods for computing CMS subtypes for FFPE colon cancer samples have widespread agreement with ColoType assay.
2020-07-27 | GSE152430 | GEO
Project description:Purpose: Celiac disease (CD) is a risk factor for developing Small Bowel Carcinoma (SBC) with a 14 folds higher risk than that of the general population. As SBCs associated with CD (CD-SBCs) are extremely rare, very few molecular data are currently available about their pathogenesis and information about CD-SBC transcriptomic profiling is completely lacking. Patients and Methods: We generated RNA-seq data on 13 CD-SBCs selected from the largest and well-characterized series of CD-SBCs published so far that was collected by the Small Bowel Cancer Italian Consortium. In all cases we compared the CD-SBC transcriptional signatures with the four consensus molecular subtypes (CMS) of colorectal carcinoma (CRC) applying the ‘CMS classifier’. CpG Island Methylator Phenotype (CIMP+) was evaluated in all cases using methylation-sensitive multiple ligation-dependent probe amplification. Results: RNA-based signatures of CD-SBCs exhibited strong similarities with CRCs. Twelve of 13 CD-SBCs (92%) fell within the two main subtypes exhibiting high immune and inflammatory signatures, i.e. CMS1 and CMS4. CMS1 CD-SBCs (62% of cases) were commonly MSI/CIMP+ tumors and showed increased expression of genes associated with a diffuse TH1 and cytotoxic T immune infiltrate, up-regulation of apoptosis, cell cycle progression and proteasome pathways. CMS4 CD-SBCs (31% of cases) showed prominent TGF-β activation and were characterized by complement-associated inflammation, matrix remodeling, stromal invasion and angiogenesis Conclusions: RNA-based signatures of CD-SBCs strongly recapitulate CMS classification of CRC, give a promising tool to improve our knowledge of this rare entity and provide clinically useful information using the wealth of data available for CRC.
2020-03-01 | E-MTAB-7760 | biostudies-arrayexpress
Project description:Consensus Molecular Subtype (CMS) classification of colorectal cancer (CRC) tissues is complicated by RNA degradation upon formalin-fixed paraffin-embedded (FFPE) preservation. Here, we present an FFPE-curated CMS classifier. The CMSFFPE classifier was developed using genes with a high transcript integrity in FFPE-derived RNA. We evaluated the classification accuracy in two FFPE-RNA datasets with matched fresh-frozen (FF) RNA data, and an FF-derived RNA set. An FFPE-RNA application cohort of metastatic CRC patients was established, partly treated with anti-EGFR therapy. Key characteristics per CMS were assessed. Cross-referenced with matched benchmark FF CMS calls, the CMSFFPE classifier strongly improved classification accuracy in two FFPE datasets compared with the original CMSClassifier (63.6% versus 40.9% and 83.3% versus 66.7%, respectively). We recovered CMS-specific recurrence-free survival patterns (CMS4 versus CMS2: hazard ratio 1.75, 95% CI 1.24-2.46). Key molecular and clinical associations of the CMSs were confirmed. In particular, we demonstrated the predictive value of CMS2 and CMS3 for anti-EGFR therapy response (CMS2&3: odds ratio 5.48, 95% CI 1.10-27.27). The CMSFFPE classifier is an optimized FFPE-curated research tool for CMS classification of clinical CRC samples.
| S-EPMC11116811 | biostudies-literature
Project description:INTRODUCTION. Consensus molecular subtypes (CMSs) can guide precision treatment of colorectal cancer (CRC). Currently available dedicated assays can identify CMS1 and CMS4 cases very well while a dedicated test to distinguish CMS2 and 3 is lacking. This study aimed to identify a panel of methylation markers to distinguish between CMS2 and 3 in patients with CRC. METHODS. Fresh-frozen tumor tissue of 239 patients with stage I-III CRC who underwent surgery between 2007 and 2014 was included. CMS classification was performed on RNA-seq data using the single-sample prediction parameter from the “CMSclassifier” package. Methylation profiles were gathered/obtained using the Infinium HumanMethylation450 BeadChip for 146 samples (124 CMS2 and 22 CMS3) . We performed adaptive group-regularised logistic ridge regression with post-hoc group-weighted elastic net marker selection to build prediction models for classification of CMS2 and CMS3 based on 15, 10 or 5 methylation markers. Data from the Cancer Genome Atlas project was used for independent validation of our obtained models. RESULTS. Overall methylation profiles differed between CMS2 and CMS3 tumors. Group-regularisation of the methylation probes was done based on their location either relative to a CpG island or relative to a gene present in the CMS classifier. This resulted in two different prediction models and subsequently different marker panels. For both panels, even when using only 5 markers, the sensitivity, specificity, and accuracy were >90%. Independent validation of the fixed models in TCGA data showed comparable performances. CONCLUSION. Our highly sensitive and specific methylation marker panel can be used to distinguish CMS2 and 3. This enables future development of a qPCR DNA methylation assay in patients with CRC to provide a specific and non-invasive classification tool.
2021-12-08 | GSE164811 | GEO
Project description:Infinium® HumanMethylation450 BeadChip and EPIC arrays were run with the aim of using the methylation profiles (n=986 in total) for sarcoma subtype classification (Paper: Lyskjær et al, 2021, DNA methylation-based profiling of bone and soft tissue tumours: a validation study of the ‘DKFZ sarcoma Classifier’ ). 500ng of DNA from fresh frozen (FT) or formalin-fixed paraffin-embedded (FFPE) tumour samples were bisulfite converted using the Zymo EZ DNA methylation Gold kit (Zymo Research Corp. Irvine, USA) before hybridisation to the Infinium HumanMethylation450 or EPIC beadchip arrays (Illumina, San Diego, CA) by UCL Genomics. All bisulfite-converted FFPE samples were restored with the Infinium FFPE DNA Restore kit (Illumina).
2021-05-01 | E-MTAB-9875 | biostudies-arrayexpress
Project description:Formalin-fixed, paraffin-embedded (FFPE) samples of varying grade (II-IV) malignant gliomas were measured by Illumina cDNA-mediated Annealing, Selection, extension and ligration (DASL) platform. DASL platform was selected for its specialized design for partially degraded RNA.
2014-02-13 | GSE54004 | GEO
Project description:Gene expression profiling was carried out for RNA extracted from Formalin-fixed, paraffin embedded (FFPE) biopsies for 76 patients using the Illumina DASL version 3 platform. The patients were then classified into BL and DLBCL by moleclar classifier proposed in the article.
2015-09-30 | GSE69049 | GEO
Project description:A consensus molecular subtypes classification strategy for clinical colorectal cancer tissues
| PRJNA1109343 | ENA