Dataset Information

A network-based predictive gene-expression signature for adjuvant chemotherapy benefit in stage II colorectal cancer.

ABSTRACT: The clinical benefit of adjuvant chemotherapy for stage II colorectal cancer (CRC) is controversial. This study aimed to explore novel gene signature to predict outcome benefit of postoperative 5-Fu-based therapy in stage II CRC.Gene-expression profiles of stage II CRCs from two datasets with 5-Fu-based adjuvant chemotherapy (training dataset, n?=?212; validation dataset, n?=?85) were analyzed to identify the indicator. A systemic approach by integrating gene-expression and protein-protein interaction (PPI) network was implemented to develop the predictive signature. Kaplan-Meier curves and Cox proportional hazards model were used to determine the survival benefit of adjuvant chemotherapy. Experiments with shRNA knock-down were carried out to confirm the signature identified in this study.In the training dataset, we identified 44 PPI sub-modules, by which we separate patients into two clusters (1 and 2) having different chemotherapeutic benefit. A predictor of 11 PPI sub-modules (11-PPI-Mod) was established to discriminate the two sub-groups, with an overall accuracy of 90.1%. This signature was independently validated in an external validation dataset. Kaplan-Meier curves showed an improved outcome for patients who received adjuvant chemotherapy in Cluster 1 sub-group, but even worse survival for those in Cluster 2 sub-group. Similar results were found in both the training and the validation dataset. Multivariate Cox regression revealed an interaction effect between 11-PPI-Mod signature and adjuvant therapy treatment in the training dataset (RFS, p?=?0.007; OS, p?=?0.006) and the validation dataset (RFS, p?=?0.002). From the signature, we found that PTGES gene was up-regulated in CRC cells which were more resistant to 5-Fu. Knock-down of PTGES indicated a growth inhibition and up-regulation of apoptotic markers induced by 5-Fu in CRC cells.Only a small proportion of stage II CRC patients could benefit from adjuvant therapy. The 11-PPI-Mod as a potential predictor could be helpful to distinguish this sub-group with favorable outcome.

SUBMITTER: Cao B

PROVIDER: S-EPMC5729289 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

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A network-based predictive gene-expression signature for adjuvant chemotherapy benefit in stage II colorectal cancer.

Cao Bangrong B Luo Liping L Feng Lin L Ma Shiqi S Chen Tingqing T Ren Yuan Y Zha Xiao X Cheng Shujun S Zhang Kaitai K Chen Changmin C

BMC cancer 20171213 1

<h4>Background</h4>The clinical benefit of adjuvant chemotherapy for stage II colorectal cancer (CRC) is controversial. This study aimed to explore novel gene signature to predict outcome benefit of postoperative 5-Fu-based therapy in stage II CRC.<h4>Methods</h4>Gene-expression profiles of stage II CRCs from two datasets with 5-Fu-based adjuvant chemotherapy (training dataset, n = 212; validation dataset, n = 85) were analyzed to identify the indicator. A systemic approach by integrating gene-e ...[more]

PMID: 29237416

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Project description:The current criteria for defining the recurrence risks of stage II colorectal cancer (CRC) are not robust; therefore, we aimed to explore novel gene signatures to predict recurrence risks and to reveal the underlying mechanisms of stage II CRC. First, the gene expression profiles of 124 patients with stage II CRC from The Cancer Genome Atlas (TCGA) database were obtained to screen differentially expressed genes (DEGs). A total of 202 DEGs, including 128 upregulated and 74 downregulated, were identified in the recurrence group (n = 24) compared to the nonrecurrence group (n = 100). Furthermore, the top 5 DEGs (ZNF561, WFS1, SLC2A1, MFI2, and PTGR1) were identified by random forest variable hunting, and four (ZNF561, WFS1, SLC2A1, and PTGR1) were selected to create a four-gene recurrent model (GRM), with an area under the curve (AUC) of 0.882 according to the receiver operating characteristic curve, and the robust diagnostic effectiveness of the GRM was further validated with another gene expression profiling dataset (GSE12032), with an AUC of 0.943. The diagnostic effectiveness of the GRM regarding recurrence was associated with poor disease-free survival in all stages of CRC. In addition, gene ontology functional annotation and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses revealed 18 enriched functions and 6 enriched pathways. Four genes, ABCG2, CACNA1F, CYP19A1, and TF, were identified as hub genes by the protein-protein interaction network, which further validated that these genes were correlated with a poor pathologic stage and overall survival in all stages of CRC. In conclusion, the GRM can effectively classify stage II CRC into groups of high and low risks of recurrence, thereby making up for the prognostic value of the traditional clinicopathological risk factors defined by the National Comprehensive Cancer Network guidelines. The hub genes may be useful therapeutic targets for recurrence. Thus, the GRM and hub genes could offer clinical value in directing individualized and precision therapeutic regimens for stage II CRC patients.

Project description:BackgroundWe developed and validated a prognostic and predictive computational pathology risk score (CoRiS) using H&E stained tissue images from patients with early-stage non-small cell lung cancer (ES-NSCLC).Methods1330 patients with ES-NSCLC were acquired from 3 independent sources and divided into four cohorts D1-4. D1 comprised 100 surgery treated patients and was used to identify prognostic features via an elastic-net Cox model to predict overall and disease-free survival. CoRiS was constructed using the Cox model coefficients for the top features. The prognostic performance of CoRiS was evaluated on D2 (N=331), D3 (N=657) and D4 (N=242). Patients from D2 and D3 which comprised surgery + chemotherapy were used to validate CoRiS as predictive of added benefit to adjuvant chemotherapy (ACT) by comparing survival between different CoRiS defined risk groups.FindingsCoRiS was found to be prognostic on univariable analysis, D2 (hazard ratio (HR) = 1.41, adjusted (adj.) P = .01) and D3 (HR = 1.35, adj. P < .001). Multivariable analysis showed CoRiS was independently prognostic, D2 (HR = 1.41, adj. P < .001) and D3 (HR = 1.35, adj. P < .001), after adjusting for clinico-pathologic factors. CoRiS was also able to identify high-risk patients who derived survival benefit from ACT D2 (HR = 0.42, adj. P = .006) and D3 (HR = 0.46, adj. P = .08).InterpretationCoRiS is a tissue non-destructive, quantitative and low-cost tool that could potentially help guide management of ES-NSCLC patients.FundingData collection, anlaysis, and computation resources of the research reported in this publication was supported by the National Cancer Institute of the National Institutes of Health under award numbers: 1U24CA199374-01, R01CA202752-01A1, R01CA208236-01A1, R01 CA216579-01A1, R01 CA220581-01A1, 1U01 CA239055-01. National Center for Research Resources under award number 1 C06 RR12463-01. VA Merit Review Award IBX004121A from the United States Department of Veterans Affairs Biomedical Laboratory Research and Development Service, the DOD Prostate Cancer Idea Development Award (W81XWH-15-1-0558), the DOD Lung Cancer Investigator-Initiated Translational Research Award (W81XWH-18-1-0440), the DOD Peer Reviewed Cancer Research Program (W81XWH-16-1-0329), the Ohio Third Frontier Technology Validation Fund, the Wallace H. Coulter Foundation Program in the Department of Biomedical Engineering and the Clinical and Translational Science Award Program (CTSA) at Case Western Reserve University.

Project description:BackgroundDebates exist on the treatment decision of the stage II/III colorectal cancer (CRC) due to the insufficiency of the current TNM stage-based risk stratification system. Epithelial-mesenchymal transition (EMT) and tumor microenvironment (TME) have both been linked to CRC progression in recent studies. We propose to improve the prognosis prediction of CRC by integrating TME and EMT.MethodsIn total, 2382 CRC patients from seven datasets and one in-house cohort were collected, and 1640 stage II/III CRC patients with complete survival information and gene expression profiles were retained and divided into a training cohort and three independent validation cohorts. Integrated analysis of 398 immune, stroma, and epithelial-mesenchymal transition (ISE)-related genes identified an ISE signature independently associated with the recurrence of CRC. The underlying biological mechanism of the ISE signature and its influence on adjuvant chemotherapy was further explored.ResultsWe constructed a 26-gene signature which was significantly associated with poor outcome in Training cohort (p < 0.001, HR [95%CI] = 4.42 [3.25-6.01]) and three independent validation cohorts (Validation cohort-1: p < 0.01, HR [95%CI] = 1.70 [1.15-2.51]; Validation cohort-2: p < 0.001, HR [95% CI] = 2.30 [1.67-3.16]; Validation cohort-3: p < 0.01, HR [95% CI] = 2.42 [1.25-4.70]). After adjusting for known clinicopathological factors, multivariate cox analysis confirmed the ISE signature's independent prognostic value. Subgroup analysis found that stage III patients with low ISE score might benefit from adjuvant chemotherapy (p < 0.001, HR [95%CI] = 0.15 [0.04-0.55]). Hypergeometric test and enrichment analysis revealed that low-risk group was enriched in thr immune pathway while high-risk group was associated with the EMT pathway and CMS4 subtype.ConclusionWe proposed an ISE signature for robustly predicting the recurrence of stage II/III CRC and help treatment decision by identifying patients who will not benefit from current standard treatment.

Project description:BackgroundFor stage II colorectal cancer (CRC), the efficacy of adjuvant chemotherapy remains controversial. Consensus molecular subtype (CMS) has been validated to be a prognostic tool for CRCs. In this study, CMS status was investigated as a prognostic biomarker for the efficacy of adjuvant chemotherapy for stage II colorectal cancer.Materials and methodsThe tissue microarray was retrospectively constructed of 165 nonconsecutive, primary, and sporadic stage II CRCs. CMS status was determined by immunohistochemistry staining of CDX2, HTR2B, FRMD6, and ZEB1, combining with microsatellite instability testing. The prognostic for adjuvant chemotherapy efficacy of CMS status was calculated by Kaplan-Meier curves and Cox regression analysis. Subgroup analyses were conducted according to tumor location.ResultsKaplan-Meier curves indicated that CMS was associated with overall survival (OS) and disease-free survival for stage II CRCs. Cox regression analysis showed that CMS was an independent risk factor for OS. Among high-risk clinicopathological factors, patients with CMS2/3 (hazard ratio [HR]: 0.445, 95% confidence interval [CI]: 0.227-0.875), left-sided tumors (HR: 0.488, 95% CI: 0.247-0.968), or fewer than 12 lymph nodes examined (HR: 0.307, 95% CI: 0.097-0.974) had survival benefit from adjuvant chemotherapy. Subgroup analysis showed that adjuvant chemotherapy only improved OS for patients with left-sided tumors of CMS2/3 subtype. Regardless of CMS, right-sided tumors had no benefit from adjuvant chemotherapy.ConclusionCMS is a better prognostic factor for adjuvant chemotherapy for stage II CRCs. Together with tumor location, CMS classification will aid in personalized treatment for stage II CRCs.Implications for practiceFor stage II colorectal cancer (CRC), the efficacy of adjuvant chemotherapy remains controversial, in that its minimal benefit (no more than 5% on average) is considered not worth the toxic effects of the drugs. There are still no effective prognostic and predictive biomarkers. This study showed that consensus molecular subtype (CMS) status is a predictive marker for adjuvant chemotherapy efficacy. Patients with left-sided tumors of CMS2/3 subtype have survival benefit by receiving adjuvant chemotherapy, which will aid in personalized treatment for stage II CRCs. Moreover, this test of CMS based on immunohistochemistry is cheap, not time consuming, and easily conducted in the laboratories of most hospitals.

Dataset Information

A network-based predictive gene-expression signature for adjuvant chemotherapy benefit in stage II colorectal cancer.

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A network-based predictive gene-expression signature for adjuvant chemotherapy benefit in stage II colorectal cancer.

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