Beyond cancer genes: colorectal cancer as robust intrinsic states formed by molecular interactions.
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ABSTRACT:
SUBMITTER: Yuan R
PROVIDER: S-EPMC5717345 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Colorectal cancer (CRC) biopsies underpin accurate diagnosis, but are also relevant for patient stratification in molecularly-guided clinical trials. The consensus molecular subtypes (CMSs) and colorectal cancer intrinsic subtypes (CRISs) transcriptional signatures have potential clinical utility for improving prognostic/predictive patient assignment. However, their ability to provide robust classification, particularly in pretreatment biopsies from multiple regions or at different time points, remains untested. In this study, we undertook a comprehensive assessment of the robustness of CRC transcriptional signatures, including CRIS and CMS, using a range of tumour sampling methodologies currently employed in clinical and translational research. These include analyses using (i) laser-capture microdissected CRC tissue, (ii) eight publically available rectal cancer biopsy data sets (n = 543), (iii) serial biopsies (from AXEBeam trial, NCT00828672; n = 10), (iv) multi-regional biopsies from colon tumours (n = 29 biopsies, n = 7 tumours), and (v) pretreatment biopsies from the phase II rectal cancer trial COPERNCIUS (NCT01263171; n = 44). Compared to previous results obtained using CRC resection material, we demonstrate that CMS classification in biopsy tissue is significantly less capable of reliably classifying patient subtype (43% unknown in biopsy versus 13% unknown in resections, p = 0.0001). In contrast, there was no significant difference in classification rate between biopsies and resections when using the CRIS classifier. Additionally, we demonstrated that CRIS provides significantly better spatially- and temporally- robust classification of molecular subtypes in CRC primary tumour tissue compared to CMS (p = 0.003 and p = 0.02, respectively). These findings have potential to inform ongoing biopsy-based patient stratification in CRC, enabling robust and stable assignment of patients into clinically-informative arms of prospective multi-arm, multi-stage clinical trials. © 2018 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.
| S-EPMC5947827 | biostudies-literature
Project description:ObjectiveTo systematically analyze the expression of cuproptosis and ferroptosis genes and their impact on the development, prognosis, tumor microenvironment (TME), and treatment response in colorectal cancer (CRC) patients.MethodsWe systematically evaluated 33 cuproptosis and ferroptosis-related genes and comprehensively identified the correlations between cuproptosis and ferroptosis-related genes and transcriptional patterns, prognosis, and clinical features. Three distinct subgroups were identified in CRC using the TCGA database and the GEO database. We next assessed the relationship between the molecular features, prognostic significance, and clinical indicators of the prognostic genes in the cuproptosis and ferroptosis-related gene clusters. In addition, a PAC_score, which accurately predicted the prognosis of CRC patients and the efficacy of immunomodulatory mAbs, was obtained.ResultsPatients in the low expression group (low expression of cuproptosis and ferroptosis-related genes) had a longer survival compared to the high expression group. We identified two distinct prognosis-associated molecular subtypes and observed an association between clinical information and prognosis. The enrichment analysis of differential genes associated with prognosis showed that the main enrichment was related to biological processes such as metastasis and metabolism. Next, the PCA_score for predicting overall survival (OS) was established and its reliable predictive value in CRC patients was confirmed. Furthermore, highly reliable nomogram was created to facilitate the clinical feasibility of the PCA_score. It was found that the immunomodulatory mAbs, PD-L1 and CTLA4 were highly expressed in the low PCA_score score group with statistically significance.ConclusionOverall, the PCA scores of prognostic differential genes in the cuproptosis and ferroptosis-related gene clusters were strongly associated with clinical characteristics, prognosis, and immunotherapy in CRC patients. This data may promote further exploration of more effective immunotherapy strategies for CRC.
| S-EPMC9483209 | biostudies-literature
Project description:Colorectal cancer (CRC) transcriptional subtypes have been recently identified by gene expression profiling. Here we describe an analytical pipeline, microRNA master regulator analysis (MMRA), developed to search for microRNAs potentially driving CRC subtypes. Starting from a microRNA-mRNA tumour expression data set, MMRA identifies candidate regulator microRNAs by assessing their subtype-specific expression, target enrichment in subtype mRNA signatures and network analysis-based contribution to subtype gene expression. When applied to a CRC data set of 450 samples, assigned to subtypes by 3 different transcriptional classifiers, MMRA identifies 24 candidate microRNAs, in most cases downregulated in the stem/serrated/mesenchymal (SSM) poor prognosis subtype. Functional validation in CRC cell lines confirms downregulation of the SSM subtype by miR-194, miR-200b, miR-203 and miR-429, which share target genes and pathways mediating this effect. These results show that, by combining statistical tests, target prediction and network analysis, MMRA effectively identifies microRNAs functionally associated to cancer subtypes.
| S-EPMC4660217 | biostudies-literature
Project description:Colorectal cancer (CRC) is the third most diagnosed malignancy and a major leading cause of cancer-related deaths worldwide. Despite advances in therapeutic regimens, the number of patients presenting with metastatic CRC (mCRC) is increasing due to resistance to therapy, conferred by a small population of cancer cells, known as cancer stem cells. Targeted therapies have been highly successful in prolonging the overall survival of patients with mCRC. Agents are being developed to target key molecules involved in drug-resistance and metastasis of CRC, and these include vascular endothelial growth factor, epidermal growth factor receptor, human epidermal growth factor receptor-2, mitogen-activated extracellular signal-regulated kinase, in addition to immune checkpoints. Currently, there are several ongoing clinical trials of newly developed targeted agents, which have shown considerable clinical efficacy and have improved the prognosis of patients who do not benefit from conventional chemotherapy. In this review, we highlight recent developments in the use of existing and novel targeted agents against drug-resistant CRC and mCRC. Furthermore, we discuss limitations and challenges associated with targeted therapy and strategies to combat intrinsic and acquired resistance to these therapies, in addition to the importance of implementing better preclinical models and the application of personalized therapy based on predictive biomarkers for treatment selection.
| S-EPMC10044855 | biostudies-literature
Project description:It is urgent to diagnose colorectal cancer in the early stage. Some feature genes which are important to colorectal cancer development have been identified. However, for the early stage of colorectal cancer, less is known about the identity of specific cancer genes that are associated with advanced clinical stage. In this paper, we conducted a feature extraction method named Optimal Mean based Block Robust Feature Extraction method (OMBRFE) to identify feature genes associated with advanced colorectal cancer in clinical stage by using the integrated colorectal cancer data. Firstly, based on the optimal mean and L 2,1-norm, a novel feature extraction method called Optimal Mean based Robust Feature Extraction method (OMRFE) is proposed to identify feature genes. Then the OMBRFE method which introduces the block ideology into OMRFE method is put forward to process the colorectal cancer integrated data which includes multiple genomic data: copy number alterations, somatic mutations, methylation expression alteration, as well as gene expression changes. Experimental results demonstrate that the OMBRFE is more effective than previous methods in identifying the feature genes. Moreover, genes identified by OMBRFE are verified to be closely associated with advanced colorectal cancer in clinical stage.
| S-EPMC5561268 | biostudies-literature
Project description:Colorectal cancer is an endemic disease in the western world. Search for molecular signatures present in primary tumors that predict tumor metastasis potential has been proposed and in particular, a 17-gene molecular signature is associated with poor survival in breast cancer, prostate cancer, meduloblastoma and lymphoma in a recent study. Using quantitative real-time PCR assay (qPCR), our study observed tumor-normal differential RNA expression in 15 of these 17 genes in a cohort of 52 stage III colorectal cancer patients (all p<0.05), which signified the importance of these 17 signature genes in colorectal cancer. Although no significant correlation was found between tumor RNA levels of these 17 genes and some of clinical features (age, gender, and location, all p>0.05), two distinct groups among these genes were observed with Spearman correlation scores>0.6 (p<0.01), suggesting co-expression/interaction within these genes. Of the 37 patients for whom complete follow-up data was available, 12 patients had recurrence and 25 had no recurrence. There was no significant difference in tumor RNA levels between recurrence and non-recurrence groups for the 17 genes (all p>0.05), but the recurrence group had more patients with mucinous tumors (9/12 vs. 7/25, p<0.05) and more lymph node involvement (median 7.2 vs. 2.5, p<0.05) compared to the non-recurrence group. Moreover, survival analysis revealed a significant difference in patient overall survival time between low and high tumor RNA levels for 1 of the 17 genes (PTTG1, p=0.024). Our qPCR validation study confirms the importance of most 17-gene molecular signature genes with differential RNA expression and suggests the relevance of PTTG1 for survival in colorectal cancers.
| S-EPMC3954856 | biostudies-literature
Project description:MotivationThe PAM50 signature/method is widely used for intrinsic subtyping of breast cancer samples. However, depending on the number and composition of the samples included in a cohort, the method may assign different subtypes to the same sample. This lack of robustness is mainly due to the fact that PAM50 subtracts a reference profile, which is computed using all samples in the cohort, from each sample before classification. In this paper we propose modifications to PAM50 to develop a simple and robust single-sample classifier, called MPAM50, for intrinsic subtyping of breast cancer. Like PAM50, the modified method uses a nearest centroid approach for classification, but the centroids are computed differently, and the distances to the centroids are determined using an alternative method. Additionally, MPAM50 uses unnormalized expression values for classification and does not subtract a reference profile from the samples. In other words, MPAM50 classifies each sample independently, and so avoids the previously mentioned robustness issue.ResultsA training set was employed to find the new MPAM50 centroids. MPAM50 was then tested on 19 independent datasets (obtained using various expression profiling technologies) containing 9637 samples. Overall good agreement was observed between the PAM50- and MPAM50-assigned subtypes with a median accuracy of 0.792, which (we show) is comparable with the median concordance between various implementations of PAM50. Additionally, MPAM50- and PAM50-assigned intrinsic subtypes were found to agree comparably with the reported clinical subtypes. Also, survival analyses indicated that MPAM50 preserves the prognostic value of the intrinsic subtypes. These observations demonstrate that MPAM50 can replace PAM50 without loss of performance. On the other hand, MPAM50 was compared with 2 previously published single-sample classifiers, and with 3 alternative modified PAM50 approaches. The results indicated a superior performance by MPAM50.ConclusionsMPAM50 is a robust, simple, and accurate single-sample classifier of intrinsic subtypes of breast cancer.
| S-EPMC10052604 | biostudies-literature
Project description:INTRODUCTION:We examined expression of genes in the p53-signaling pathway. We determine if genes that have significantly different expression in carcinoma tissue compared to normal mucosa also have significantly differentially expressed miRNAs. We utilize a sample of 217 CRC cases. METHODS:We focused on fold change (FC) > 1.50 or <0.67 for genes and miRNAs, that were statistically significant after adjustment for multiple comparisons. We evaluated the linear association between the differential expression of miRNA and mRNA. miRNA:mRNA seed-region matches also were determined. RESULTS:Eleven dysregulated genes were associated with 37 dysregulated miRNAs; all were down-stream from the TP53 gene. MiR-150-5p (HR = 0.82) and miR-196b-5p (HR 0.73) significantly reduced the likelihood of dying from CRC when miRNA expression increased in rectal tumors. CONCLUSIONS:Our data suggest that activation of p53 from cellular stress, could target downstream genes that in turn could influence cell cycle arrest, apoptosis, and angiogenesis through mRNA:miRNA interactions.
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Project description:Autophagy is a common name for a number of catabolic processes, which keep the cellular homeostasis by removing damaged and dysfunctional intracellular components. Impairment or misbalance of autophagy can lead to various diseases, such as neurodegeneration, infection diseases, and cancer. A central axis of autophagy is formed along the interactions of autophagy modifiers (Atg8-family proteins) with a variety of their cellular counter partners. Besides autophagy, Atg8-proteins participate in many other pathways, among which membrane trafficking and neuronal signaling are the most known. Despite the fact that autophagy modifiers are well-studied, as the small globular proteins show similarity to ubiquitin on a structural level, the mechanism of their interactions are still not completely understood. A thorough analysis and classification of all known mechanisms of Atg8-protein interactions could shed light on their functioning and connect the pathways involving Atg8-proteins. In this review, we present our views of the key features of the Atg8-proteins and describe the basic principles of their recognition and binding by interaction partners. We discuss affinity and selectivity of their interactions as well as provide perspectives for discovery of new Atg8-interacting proteins and therapeutic approaches to tackle major human diseases.
| S-EPMC7564214 | biostudies-literature
Project description:Colorectal cancer (CRC) is the most common cancer of the digestive system. The aim of the present study was to identify the potential biomarkers and uncover the underlying mechanisms. The gene and miRNA expression profiles were obtained from GEO database. The differentially expressed genes (DEGs) and miRNAs (DE miRNAs) were identified by GEO2R. The gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed by KOBAS 3.0. The protein-protein interaction (PPI) network and miRNA-gene network were constructed by Cytoscape software. Then, the identified genes were verified by quantitative real-time PCR in both CRC tissue samples and cell lines. A total of 600 upregulated DEGs, 283 downregulated DEGs, 13 upregulated DE miRNAs and 7 downregulated DE miRNAs were identified. GO analysis results showed that upregulated DEGs were significantly enriched in binding, organelle and cellular process. Downregulated DEGs were enriched in binding, extracellular region and chemical homeostasis. KEGG analysis showed that the DEGs were mostly enriched in cell cycle and pathways in cancer. A total of eight genes were identified as biomarkers, including CAD, ITGA2, E2F3, BCL2, PRKACB, IGF1, SGK1 and NR3C1. Experimental validation showed that seven of the eight identified genes had the same expression trend as predicted, except for ITGA2. Besides, hsa-miR-552 and hsa‑miR-30a were identified as key miRNAs. the present study provides a series of biomarkers and mechanisms for the diagnosis and therapy of CRC. We also prove that although bioinformatics analysis is a wonderful approach, experiment validation is necessary.
| S-EPMC5652954 | biostudies-literature