Risk score based on ten lncRNA-mRNA expression predicts the survival of stage II-III colorectal carcinoma.
Ontology highlight
ABSTRACT:
SUBMITTER: Diao R
PROVIDER: S-EPMC5552098 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:BackgroundColorectal cancer is the second-leading cause of cancer-related mortality in the United States and a leading cause of cancer-related mortality worldwide. Loss of SMAD4, a critical tumor suppressor and the central node of the transforming growth factor-beta superfamily, is associated with worse outcomes for colorectal cancer patients; however, it is unknown whether an RNA-based profile associated with SMAD4 expression could be used to better identify high-risk colorectal cancer patients.AimIdentify a gene expression-based SMAD4-modulated profile and test its association with patient outcome.Methods and resultsUsing a discovery dataset of 250 colorectal cancer patients, we analyzed expression of BMP/Wnt target genes for association with SMAD4 expression. Promoters of the BMP/Wnt genes were interrogated for SMAD-binding elements. Fifteen genes were implicated and three tested for modulation by SMAD4 in patient-derived colorectal cancer tumoroids. Expression of the 15 genes was used for unsupervised hierarchical clustering of a training dataset and two resulting clusters modeled in a centroid model. This model was applied to an independent validation dataset of stage II and III patients. Disease-free survival was analyzed by the Kaplan-Meier method. In vitro analysis of three genes identified in the SMAD4-modulated profile (JAG1, TCF7, and MYC) revealed modulation by SMAD4 consistent with the trend observed in the profile. In the training dataset (n = 553), the profile was not associated with outcome. However, among stage II and III patients (n = 461), distinct clusters were identified by unsupervised hierarchical clustering that were associated with disease-free survival (p = .02, log-rank test). The main model was applied to a validation dataset of stage II/III CRC patients (n = 257) which confirmed the association of clustering with disease-free survival (p = .013, log-rank test).ConclusionsA SMAD4-modulated gene expression profile identified high-risk stage II and III colorectal cancer patients, can predict disease-free survival, and has prognostic potential for stage II and III colorectal cancer patients.
| S-EPMC8789617 | biostudies-literature
Project description:Loss of SMAD4 is associated with worse outcomes for colorectal cancer patients. We used gene ontology and data driven approach to identify a SMAD4-modulated profile and test its association with patient outcome. Using a discovery dataset of 250 colorectal cancer patients, we analyzed expression of BMP/Wnt target genes for association with SMAD4 expression. Promoters of the BMP/Wnt genes were interrogated for SMAD-binding elements. 15 genes were implicated and three tested for modulation by SMAD4 in patient-derived colorectal cancer tumoroids. Expression of the 15 genes was used for unsupervised hierarchical clustering of a training dataset and two resulting clusters modeled in a centroid model.
2020-11-11 | GSE161158 | GEO
Project description:BackgroundProfound heterogeneity in prognosis has been observed in colorectal cancer (CRC) patients with intermediate levels of disease (stage II-III), advocating the identification of valuable biomarkers that could improve the prognostic stratification. This study aims to develop a deep learning-based pipeline for fully automatic quantification of immune infiltration within the stroma region on immunohistochemical (IHC) whole-slide images (WSIs) and further analyze its prognostic value in CRC.MethodsPatients from two independent cohorts were divided into three groups: the development group (N = 200), the internal (N = 134), and the external validation group (N = 90). We trained a convolutional neural network for tissue classification of CD3 and CD8 stained WSIs. A scoring system, named stroma-immune score, was established by quantifying the density of CD3+ and CD8+ T-cells infiltration in the stroma region.ResultsPatients with higher stroma-immune scores had much longer survival. In the development group, 5-year survival rates of the low and high scores were 55.7% and 80.8% (hazard ratio [HR] for high vs. low 0.39, 95% confidence interval [CI] 0.24-0.63, P < 0.001). These results were confirmed in the internal and external validation groups with 5-year survival rates of low and high scores were 57.1% and 78.8%, 63.9% and 88.9%, respectively (internal: HR for high vs. low 0.49, 95% CI 0.28-0.88, P = 0.017; external: HR for high vs. low 0.35, 95% CI 0.15-0.83, P = 0.018). The combination of stroma-immune score and tumor-node-metastasis (TNM) stage showed better discrimination ability for survival prediction than using the TNM stage alone.ConclusionsWe proposed a stroma-immune score via a deep learning-based pipeline to quantify CD3+ and CD8+ T-cells densities within the stroma region on WSIs of CRC and further predict survival.
| S-EPMC8557607 | biostudies-literature
Project description:PurposeThe overall survival (OS) of patients diagnosed with stage II-III colorectal cancer (CRC) can vary greatly, even between patients with the same tumor stage. We aimed to design a nomogram to predict OS in resected, stage II-III CRC and stratify patients with CRC into different risk groups.Patients and methodsBased on data from 873 patients with CRC, we used univariate Cox regression analysis to select the significant prognostic features, which were subjected to the least absolute shrinkage and selection operator (LASSO) regression algorithm for feature selection. Cross-validation was used to confirm suitable tuning parameters (λ) for LASSO logistic regression. Then, the nomogram was used to estimate 3- and 5-year OS based on the multivariable Cox regression model. The survival curves of the two groups were produced using the Kaplan-Meier method. Risk group stratification was performed to assess the predictive capacity of the nomogram.ResultsPreoperative mean platelet volume, preoperative platelet distribution width, monocytes, and postoperative adjuvant chemotherapy were identified as independent prognostic factors by LASSO regression and integrated for the construction of the nomogram. The nomogram provided good discrimination, with C-indices of 0.67 and 0.69 for the training and validation sets, respectively. Calibration plots illustrated excellent agreement between the nomogram predictions and actual observations for 3- and 5-year OS. Moreover, a significant difference in OS was shown between patients stratified into different risk groups (P < .001).ConclusionWe constructed and validated an original predictive nomogram for OS in patients with CRC after surgery, facilitating physicians to appraise the individual survival of postoperative patients accurately and identify high-risk patients who need more aggressive treatment and follow-up strategies.
| S-EPMC7131840 | biostudies-literature
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. Total of 111 microarray datasets (77 for LCM samples, and 17 pairs for homogenized samples from tumor and adjacent tissues) were normalized using robust multi-array average (RMA) method under R 2.6.2 statistical software together with BioConductor package, as described previously. Then, the gene expression levels were log2-transformed, and 62 control probe sets were removed for further analysis. In order to identify a set of genes associated with development of metastatic recurrence, we performed Wilcoxon rank-sum test for gene expression differences of 54,613 probe sets between recurrence and non-recurrence groups. Similarly, Wilcoxon singed-rank test was conducted to select genes which showed significant expression difference between tumor and adjacent tissue. Then, we selected a set of genes that satisfied both of above two criteria.
2010-03-05 | E-GEOD-18105 | biostudies-arrayexpress
Project description:Dysregulation of mRNAs and long non-coding RNAs (lncRNAs) is one of the most important features of carcinogenesis and cancer development. However, studies integrating the expression of mRNAs and lncRNAs to predict the survival of head and neck squamous cell carcinoma (HNSC) are still limited, hitherto. In current work, we identified survival related mRNAs and lncRNAs in three datasets (TCGA dataset, E-TABM-302, GSE41613). By random forest, seven gene signatures (six mRNAs and lncRNA) were further selected to develop the risk score model. The risk score was significantly associated with survival in both training and testing datasets (E-TABM-302, GSE41613, and E-MTAB-1324). Furthermore, correlation analyses showed that the risk score is independent from clinicopathological features. According to Cox multivariable hazard model and nomogram, the risk score contributes the most to survival than the other clinical information, including gender, age, histologic grade, and alcohol taking. The Gene Set Enrichment Analysis (GSEA) indicates that the risk score is associated with cancer related pathways. In summary, the lncRNA-mRNA based risk score model we developed successfully predicts the survival of 755 HNSC samples in five datasets and two platforms. It is independent from clinical information and performs better than clinical information for prognosis.
| S-EPMC5428014 | biostudies-literature
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
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: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:BackgroundPatients with high-risk stage II/III resected melanoma commonly develop distant metastases. At present, we cannot differentiate between patients who will recur or those who are cured by surgery. We investigated if circulating tumor DNA (ctDNA) can predict relapse and survival in patients with resected melanoma.Patients and methodsWe carried out droplet digital polymerase chain reaction to detect BRAF and NRAS mutations in plasma taken after surgery from 161 stage II/III high-risk melanoma patients enrolled in the AVAST-M adjuvant trial.ResultsMutant BRAF or NRAS ctDNA was detected (?1 copy of mutant ctDNA) in 15/132 (11%) BRAF mutant patient samples and 4/29 (14%) NRAS mutant patient samples. Patients with detectable ctDNA had a decreased disease-free interval [DFI; hazard ratio (HR) 3.12; 95% confidence interval (CI) 1.79-5.47; P?<?0.0001] and distant metastasis-free interval (DMFI; HR 3.22; 95% CI 1.80-5.79; P?<?0.0001) versus those with undetectable ctDNA. Detectable ctDNA remained a significant predictor after adjustment for performance status and disease stage (DFI: HR 3.26, 95% CI 1.83-5.83, P?<?0.0001; DMFI: HR 3.45, 95% CI 1.88-6.34, P?<?0.0001). Five-year overall survival rate for patients with detectable ctDNA was 33% (95% CI 14%-55%) versus 65% (95% CI 56%-72%) for those with undetectable ctDNA. Overall survival was significantly worse for patients with detectable ctDNA (HR 2.63; 95% CI 1.40-4.96); P?=?0.003) and remained significant after adjustment for performance status (HR 2.50, 95% CI 1.32-4.74, P?=?0.005).ConclusionctDNA predicts for relapse and survival in high-risk resected melanoma and could aid selection of patients for adjuvant therapy.Clinical trial numberISRCTN 81261306.
| S-EPMC5834029 | biostudies-literature