Chenyang Yu

MicroRNA sequence polymorphisms and the risk of different types of cancer

MicroRNAs (miRNAs) participate in diverse biological pathways and may act as oncogenes or tumor suppressors. Single nucleotide polymorphisms (SNPs) in miRNAs (MirSNPs) might promote carcinogenesis by affecting miRNA function and/or maturation; however, the association between MirSNPs reported and cancer risk remain inconsistent. Here, we investigated the association between nine common MirSNPs and cancer risk using data from large scale case-control studies. Eight precursor-miRNA (pre-miRNA) SNPs (rs2043556/miR-605, rs3746444/miR-499a/b, rs4919510/miR-608, rs2910164/miR-146a, rs11614913/miR-196a2, rs895819/miR-27a, rs2292832/miR-149, rs6505162/miR-423) and one primary-miRNA (pri-miRNA) SNP (rs1834306/miR-100) were analyzed in 16399 cases and 21779 controls from seven published studies in eight common cancers. With a novel statistic, Cross phenotype meta-analysis (CPMA) of the association of MirSNPs with multiple phenotypes indicated rs2910164 C (P = 1.11E-03), rs2043556 C (P = 0.0165), rs6505162 C (P = 2.05E-03) and rs895819 (P = 0.0284) were associated with a significant overall risk of cancer. In conclusion, MirSNPs might affect an individuals susceptibility to various types of cancer.

Genetic variants in the inositol phosphate metabolism pathway and risk of different types of cancer.

Members of the inositol phosphate metabolism pathway regulate cell proliferation, migration and phosphatidylinositol-3-kinase (PI3K)/Akt signaling, and are frequently dysregulated in cancer. Whether germline genetic variants in inositol phosphate metabolism pathway are associated with cancer risk remains to be clarified. We examined the association between inositol phosphate metabolism pathway genes and risk of eight types of cancer using data from genome-wide association studies. Logistic regression models were applied to evaluate SNP-level associations. Gene- and pathway-based associations were tested using the permutation-based adaptive rank-truncated product method. The overall inositol phosphate metabolism pathway was significantly associated with risk of lung cancer (P = 2.00 × 10−4), esophageal squamous cell carcinoma (P = 5.70 × 10−3), gastric cancer (P = 3.03 × 10−2) and renal cell carcinoma (P = 1.26 × 10−2), but not with pancreatic cancer (P = 1.40 × 10−1), breast cancer (P = 3.03 × 10−1), prostate cancer (P = 4.51 × 10−1), and bladder cancer (P = 6.30 × 10−1). Our results provide a link between inherited variation in the overall inositol phosphate metabolism pathway and several individual genes and cancer. Further studies will be needed to validate these positive findings, and to explore its mechanisms.

Increased risk of hemorrhage in metastatic colorectal cancer patients treated with bevacizumab: An updated meta-analysis of 12 randomized controlled trials.

Background:As an important antivascular endothelial growth factor monoclonal antibody, bevacizumab has been administrated for the treatment of cancer patients. Hemorrhage, one of the common adverse events of angiogenesis inhibitors, sometimes is also fatal and life-threatening. We aimed at determining the incidence and risk of hemorrhage associated with bevacizumab in patients with metastatic colorectal cancer (mCRC). Methods:We searched PubMed, EMBASE, and the Web of Science databases for relevant randomized controlled trials (RCTs). The overall incidence, overall relative risk (RR), and 95% confidence interval (CI) were calculated by using a random-effects or fixed-effects model based on the heterogeneity of selected trials. Results:A total of 10,555 mCRC patients from 12 RCTs were included in our study. The overall incidence of hemorrhage was 5.8% (95% CI 3.9%–7.8%). Bevacizumab significantly increased the overall risk of hemorrhage with an RR of 1.96 (95% CI 1.27–3.02). The RR of all-grade hemorrhage was 2.39 (95% CI 1.09–5.24) and 1.41 (95% CI 1.01–1.97) for high-grade hemorrhage. The risk of hemorrhage associated with bevacizumab was dose-dependent with an RR of 1.73 (95% CI 1.15–2.61) for 2.5 mg/kg/wk and 4.67 (95% CI 2.36–9.23) for 5 mg/kg/wk. More importantly, the RR of hemorrhage for treatment duration (<= 6 months and > 6 months) based on subgroup analysis was 4.13 (95% CI 2.58–6.61) and 1.43 (95% CI 0.96–2.14), respectively. Conclusion:The addition of bevacizumab to concurrent antineoplastic in patients with mCRC significantly increased the risk of hemorrhage. The dose of bevacizumab may contribute to the risk of hemorrhage. And the 1st 6 months of treatment may be a crucial period when hemorrhagic events occur.

Differentially Expressed lncRNAs in Gastric Cancer Patients: A Potential Biomarker for Gastric Cancer Prognosis

Current studies indicate that long non-coding RNAs (lncRNAs) are frequently aberrantly expressed in cancers and implicated with prognosis in gastric cancer (GC). We intended to generate a multi-lncRNA signature to improve prognostic prediction of GC. By analyzing ten paired GC and adjacent normal mucosa tissues, 339 differentially expressed lncRNAs were identified as the candidate prognostic biomarkers in GC. Then we used LASSO Cox regression method to build a 12-lncRNA signature and validated it in another independent GEO dataset. An innovative 12-lncRNA signature was established, and it was significantly associated with the disease free survival (DFS) in the training dataset. By applying the 12-lncRNA signature, the training cohort patients could be categorized into high-risk or low-risk subgroup with significantly different DFS (HR = 4.52, 95%CI= 2.49-8.20, P < 0.0001). Similar results were obtained in another independent GEO dataset (HR=1.58, 95%CI=1.05 - 2.38, P=0.0270). Further analysis showed that the prognostic value of this 12-lncRNA signature was independent of AJCC stage and postoperative chemotherapy. Receiver operating characteristic (ROC) analysis showed that the area under receiver operating characteristic curve (AUC) of combined model reached 0.869. Additionally, a well-performed nomogram was constructed for clinicians. Moreover, single-sample gene-set enrichment analysis (ssGSEA) showed that a group of pathways related to drug resistance and cancer metastasis significantly enriched in the high risk patients. A useful innovative 12-lncRNA signature was established for prognostic evaluation of GC. It might complement clinicopathological features and facilitate personalized management of GC.

Recurrence-associated gene signature optimizes recurrence free survival prediction of colorectal cancer

High throughput gene expression profiling has showed great promise in providing insight into molecular mechanisms. Metastasis‐related mRNAs may potentially enrich genes with the ability to predict cancer recurrence, therefore we attempted to build a recurrence‐associated gene signature to improve prognostic prediction of colorectal cancer (CRC). We identified 2848 differentially expressed mRNAs by analyzing CRC tissues with or without metastasis. For the selection of prognostic genes, a LASSO Cox regression model (least absolute shrinkage and selection operator method) was employed. Using this method, a 13‐mRNA signature was identified and then validated in two independent Gene Expression Omnibus cohorts. This classifier could successfully discriminate the high‐risk patients in discovery cohort [hazard ratio (HR) = 5.27, 95% confidence interval (CI) 2.30–12.08, P < 0.0001). Analysis in two independent cohorts yielded consistent results (GSE14333: HR = 4.55, 95% CI 2.18–9.508, P < 0.0001; GSE33113: HR = 3.26, 95% CI 2.16–9.16, P = 0.0176). Further analysis revealed that the prognostic value of this signature was independent of tumor stage, postoperative chemotherapy and somatic mutation. Receiver operating characteristic (ROC) analysis showed that the area under ROC curve of this signature was 0.8861 and 0.8157 in the discovery and validation cohort, respectively. A nomogram was constructed for clinicians, and did well in the calibration plots. Furthermore, this 13‐mRNA signature outperformed other known gene signatures, including oncotypeDX colon cancer assay. Single‐sample gene‐set enrichment analysis revealed that a group of pathways related to drug resistance, cancer metastasis and stemness were significantly enriched in the high‐risk patients. In conclusion, this 13‐mRNA signature may be a useful tool for prognostic evaluation and will facilitate personalized management of CRC patients.

GeneExpressScore Signature: a robust prognostic and predictive classifier in gastric cancer

Although several prognostic signatures have been developed for gastric cancer (GC), the utility of these tools is limited in clinical practice due to lack of validation with large and multiple independent cohorts, or lack of a statistical test to determine the robustness of the predictive models. Here, a prognostic signature was constructed using a least absolute shrinkage and selection operator (LASSO) Cox regression model and a training dataset with 300 GC patients. The signature was verified in three independent datasets with a total of 658 tumors across multiplatforms. A nomogram based on the signature was built to predict disease‐free survival (DFS). Based on the LASSO model, we created a GeneExpressScore signature (GESGC) classifier comprised of eight mRNA. With this classifier patients could be divided into two subgroups with distinctive prognoses [hazard ratio (HR) = 4.00, 95% confidence interval (CI) = 2.41–6.66, P < 0.0001]. The prognostic value was consistently validated in three independent datasets. Interestingly, the high‐GESGC group was associated with invasion, microsatellite stable/epithelial–mesenchymal transition (MSS/EMT), and genomically stable (GS) subtypes. The predictive accuracy of GESGC also outperformed five previously published signatures. Finally, a well‐performed nomogram integrating the GESGC and four clinicopathological factors was generated to predict 3‐ and 5‐year DFS. In summary, we describe an eight‐mRNA‐based signature, GESGC, as a predictive model for disease progression in GC. The robustness of this signature was validated across patient series, populations, and multiplatform datasets.

TEAD4 promotes colorectal tumorigenesis via transcriptionally targeting YAP1

ABSTRACT TEAD4 (TEA domain family member 4) was recently revealed as an oncogenic character in tumorigenesis. However, its role remains unclear in colorectal tumorigenesis. Here, we firstly found that the expression level of TEAD4 was significantly elevated in clinical samples of colorectal adenomas (CRA) and correlated with the size and histological type of CRA. Moreover, patients with higher TEAD4 expression in normal colon mucosa are more prone to be recurrent after polypectomy. TEAD4 knockdown significantly inhibited colorectal cell proliferation in vitro and suppressed tumor growth in vivo. RNA-seq and GSEA analysis reveals TEAD4 can probably regulate Hippo pathway and further experiment confirm the downstream target gene YAP1. The subsequent ChIP-qPCR and luciferase report assay indicated that TEAD4 regulated YAP1 by direct binding and transcriptional activation. In summary, our study reveals that TEAD4 plays an important tumor-promoting role in colorectal cancer by directly targeting the YAP1, thus we suggests TEAD4 may be used as a novel biomarker in colorectal tumorigenesis and provides TEAD4/YAP1 axis as a potential therapeutic option for colorectal cancer.