Gene Expression Profiles in Stage II and III Colon Cancer. Application of a 128-gene signature
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE31595 | GEO | 2011/09/01
SECONDARY ACCESSION(S): PRJNA145569
REPOSITORIES: GEO
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Project description:Purpose: The present study aimed to develop a classification model to predict recurrence in stage II and III colon cancer, using a previously published 128-gene signature on external and independent material. Experimental Design: Microarray gene expression data from 148 patients (37 Danish patients and 111 patients retrieved from the Gene Expression Omnibus, GSE17536) with stage II and III colon cancer were analyzed using Affymetrix Arrays (Affymetrix, Santa Clara, USA). Based on a known 128-gene signature, a classification model was created with the random forest method, using a training set consisting of stage I colon cancers (with localized disease and a good prognosis) and stage IV colon cancers (with metastasis and a poor prognosis). The classifier were built to predict stage II and III colon cancers as either stage I-like (good prognosis) or stage IV-like (poor prognosis). Results: The 3-year relapse-free survival probability (RFS) of stage III patients predicted to have a good prognosis was 79% compared to 55% of patients with a poor prognosis (P = 0.177, log-rank test). The classification model could not stratify stage II colon cancer. The complete dataset representing: (1) the 37 Danish patients (2) the 111 patients retrieved from Series GSE17536 (re-used data), is linked below as a supplementary file. Tumor samples were obtained from 37 patients with stage II and III colon cancer, who underwent colon resection at the Department of Surgery, Roskilde Hospital, Denmark and the Department of Surgery, Bispebjerg Hospital, Denmark between 2001 and 2008. Purified tumor RNA was reverse-transcribed, labelled and hybridized to Affymetrix Human Genome U133 Plus 2.0 GeneChip Array (Affymetrix, Santa Clara, USA) according to the manufacturers instructions and scanned at the RH Microarray Center, Rigshospitalet, University of Copenhagen.
2011-08-31 | E-GEOD-31595 | biostudies-arrayexpress
Project description:We obtained fibroblast cultures from fresh surgical specimen ressected from patients with primary colorectal carcinoma: normal colonic fibroblasts (NCF=9) from the normal colonic mucosa at least 5-10cm from the surgical margin, carcinoma-associated fibroblasts from the primary tumor (CAF-PT=14) and carcinoma-associated fibroblasts (CAF-LM=11) from fresh surgical specimens of liver metastases. We identified 277 probes, in common between the three types of fibroblasts, whose expression level is sequentially deregulated according to cancer progression (NCF→CAF-PT→CAF-LM; fold change Log2 normalized expression>1.5 in each step). Prediction Analysis of Microarrays was applied to obtain a 25-gene signature that better characterizes each fibroblast class. The signature is able to classify patients carrying primary tumors according to prognosis. This fact was exploited to obtain a 19-gene signature (from the 277 deregulated probes) predicting recurrence with high accuracy in stage II/III colorectal cancer patients. Signature validation has been carried out in two independent datasets and in a meta-cohort of 336 stage II/III patients. Since the 25-gene signature was obtained regardless of gene expression data of tumor specimens or patient’s clinical data, the prognostic power of this signature provides strong evidence of the link between the tumor stroma and cancer progression. Furthermore, the 19-gene signature was able to identify low-risk patients with very high accuracy, especially relevant for those high-risk stage-II patients.
2013-05-10 | GSE46824 | GEO
Project description:We obtained fibroblast cultures from fresh surgical specimen ressected from patients with primary colorectal carcinoma: normal colonic fibroblasts (NCF=9) from the normal colonic mucosa at least 5-10cm from the surgical margin, carcinoma-associated fibroblasts from the primary tumor (CAF-PT=14) and carcinoma-associated fibroblasts (CAF-LM=11) from fresh surgical specimens of liver metastases. We identified 277 probes, in common between the three types of fibroblasts, whose expression level is sequentially deregulated according to cancer progression (NCF→CAF-PT→CAF-LM; fold change Log2 normalized expression>1.5 in each step). Prediction Analysis of Microarrays was applied to obtain a 25-gene signature that better characterizes each fibroblast class. The signature is able to classify patients carrying primary tumors according to prognosis. This fact was exploited to obtain a 19-gene signature (from the 277 deregulated probes) predicting recurrence with high accuracy in stage II/III colorectal cancer patients. Signature validation has been carried out in two independent datasets and in a meta-cohort of 336 stage II/III patients. Since the 25-gene signature was obtained regardless of gene expression data of tumor specimens or patient’s clinical data, the prognostic power of this signature provides strong evidence of the link between the tumor stroma and cancer progression. Furthermore, the 19-gene signature was able to identify low-risk patients with very high accuracy, especially relevant for those high-risk stage-II patients. We hybridised fibroblast RNA in Affymetrix GeneChip 1.0 st arrays
2013-05-10 | E-GEOD-46824 | biostudies-arrayexpress
Project description:One of the main problems in managing desmoids tumors is their locoregional aggressiveness and their high ability to recur after initial treatment. In our work, with the goal to identify molecular markers that can predict Progression-Free Survival, gene-expression screening was conducted on 128 available independent untreated primary desmoid tumors using cDNA microarray. By analyzing expression profiles, we have identified, for the first time, a gene expression signature that is able to predict Progression-Free Survival. This molecular signature identified two groups with clearly distinct Progression-Free Survival in the two sets of subjects. Patients in good prognostic group had achieved a progression-free 2-year survival rate of 86% while patients in poor prognostic group had a progression-free 2-year survival rate of 44%. 128 available independent untreated primary desmoid tumors
2015-05-13 | E-GEOD-58697 | biostudies-arrayexpress
Project description:Colorectal cancer (CRC) has one of the highest worldwide incidences and mortality rates. Compared to surgery alone, adjuvant 5-Fluorouracil (5FU)-based chemotherapy improves 5-year overall survival (OS) in only 3-4% of stage II and 15-20% of stage III patients in unselected populations. Significant advances have been made in the molecular stratification of CRC, with the emerging Consensus Molecular Subtype (CMS) and Colorectal Cancer Intrinsic Signature (CRIS) transcriptomics-based classification systems; however, the therapeutic impact of molecular stratification has so far been limited. In an effort to identify subgroups of patients benefitting from chemotherapy, we assessed which CMS and CRIS subgroups of stage II and III CRC benefitted from adjuvant 5FU-based chemotherapy using in-house and published datasets.
2017-12-31 | GSE103479 | GEO
Project description:Background & Aims. The current staging system for colorectal cancer (CRC) based on TNM classification allows prediction of potential recurrence. However, it does not necessarily make reliable personalized prediction of prognosis. In this paper we describe combination of clinicopathological data and gene signature of dissected tumor specimen with stage II and III CRC patients would improve the situation.. Methods. A total of 1978 CRC were collected over 5 years, and then 371 stage II and 322 stage III of them with more than 45.9 months records were subjected to clinicopathological feature analyses. Out of this collection, 129 stage II and III CRC cases were selected for analyses of gene expression profiles with resected specimen. The gene signatures were analyzed by repeated random divisions of the samples into training and test sets to extract discriminator genes. After testing the applicability of this discriminator set, it was subjected to validation using a newly obtained set of 69 samples. Results. The pathological factors in solo or in combinations could not make personalized recurrence prediction, except for partial success with stage II patients. The gene signature, on the other hand, was capable of producing a set of discriminator genes, though the accuracy was yet to be improved. We observed that the best result was obtained when discriminators were selected from stage II CRC samples and used for prognosis of stage II CRC. When stage III cases were included in the process of discriminator extraction or in the process to validate samples, the results were poorer. Finally, we examined 31 independent stage II samples with a set of 30 such discriminators and were able to obtain results with 78 % accuracy, 90 % negative predictive value (NPV), and 55% positive predictive value (PPV). Conclusions. Independent clinicopathological variables were not able to predict prognosis of individual patient, unless the factors are combined. On the other hand, gene signatures allowed accurate prediction of prognosis for individuals, especially with stage II CRC, suggesting its potential use for selection of best treatment option for individual patients. The accuracy of discriminator prediction will be further improved when we take the evolution of CRC into consideration.
2009-07-02 | GSE12032 | GEO
Project description:Background & Aims. The current staging system for colorectal cancer (CRC) based on TNM classification allows prediction of potential recurrence. However, it does not necessarily make reliable personalized prediction of prognosis. In this paper we describe combination of clinicopathological data and gene signature of dissected tumor specimen with stage II and III CRC patients would improve the situation.. Methods. A total of 1978 CRC were collected over 5 years, and then 371 stage II and 322 stage III of them with more than 45.9 months records were subjected to clinicopathological feature analyses. Out of this collection, 129 stage II and III CRC cases were selected for analyses of gene expression profiles with resected specimen. The gene signatures were analyzed by repeated random divisions of the samples into training and test sets to extract discriminator genes. After testing the applicability of this discriminator set, it was subjected to validation using a newly obtained set of 69 samples. Results. The pathological factors in solo or in combinations could not make personalized recurrence prediction, except for partial success with stage II patients. The gene signature, on the other hand, was capable of producing a set of discriminator genes, though the accuracy was yet to be improved. We observed that the best result was obtained when discriminators were selected from stage II CRC samples and used for prognosis of stage II CRC. When stage III cases were included in the process of discriminator extraction or in the process to validate samples, the results were poorer. Finally, we examined 31 independent stage II samples with a set of 30 such discriminators and were able to obtain results with 78 % accuracy, 90 % negative predictive value (NPV), and 55% positive predictive value (PPV). Conclusions. Independent clinicopathological variables were not able to predict prognosis of individual patient, unless the factors are combined. On the other hand, gene signatures allowed accurate prediction of prognosis for individuals, especially with stage II CRC, suggesting its potential use for selection of best treatment option for individual patients. The accuracy of discriminator prediction will be further improved when we take the evolution of CRC into consideration. Of 198 samples, 129 represented the discovery phase and 69 represented the validation phase.
2009-07-02 | E-GEOD-12032 | biostudies-arrayexpress
Project description:The aim of our study was to identify a microRNA signature to predict the recurrence in stage II & III CRC patients who were treated with FOLFOX-based adjuvant chemotherapy after curative resection of tumors. We performed small RNA sequencing in 71 FFPE surgical specimens, and discovered differentially expressed microRNAs in patients who developed recurrence. Thereafter, selected microRNA biomarkers were validated in independent cohort using qRT-PCR assay.
2022-11-16 | GSE217978 | GEO
Project description:One of the main problems in managing desmoids tumors is their locoregional aggressiveness and their high ability to recur after initial treatment. In our work, with the goal to identify molecular markers that can predict Progression-Free Survival, gene-expression screening was conducted on 128 available independent untreated primary desmoid tumors using cDNA microarray. By analyzing expression profiles, we have identified, for the first time, a gene expression signature that is able to predict Progression-Free Survival. This molecular signature identified two groups with clearly distinct Progression-Free Survival in the two sets of subjects. Patients in good prognostic group had achieved a progression-free 2-year survival rate of 86% while patients in poor prognostic group had a progression-free 2-year survival rate of 44%.
2015-05-13 | GSE58697 | GEO
Project description:Distant metastasis is the major causes of death in colorectal cancer (CRC) patients. In order to identify genes influencing the prognosis of patients with CRC, we compared gene expression in primary tumors with and without distant metastasis using an oligonucleotide microarray. We also examined the expression of the candidate gene in 100 CRC patients by quantitative real-time reverse transcription PCR and studied the relationship between its expression and the prognosis of patients with CRC. As a result, we identified MUC12 as a candidate gene involved in metastasis processes by microarray analysis. Quantitative real-time reverse transcription PCR showed that MUC12 expression was significantly lower in cancer tissues than in adjacent normal tissues (P < 0.001). In stage II and stage III CRC, patients with low expression showed worse disease-free survival (P = 0.038). Multivariate analysis disclosed that MUC12 expression status was an independent prognostic factor in stage II and stage III CRC (relative risk, 9.532; 95% confidence interval, 2.303-41.905; P = 0.002). This study revealed the prognostic value of MUC12 expression in CRC patients. Moreover, our result suggests MUC12 expression is a possible candidate gene for assessing postoperative adjuvant therapy for CRC patients.
2010-02-04 | GSE18105 | GEO