Identification of Biomarkers Correlated with the TNM Staging and Overall Survival of Patients with Bladder Cancer

Yuan

J Cellular Molecular Medi

et al. 2019

Self Cite

The precision evaluation of prognosis is crucial for clinical treatment decision of bladder cancer (BCa). Therefore, establishing an effective prognostic model for BCa has significant clinical implications. We performed WGCNA and DEG screening to initially identify the candidate genes. The candidate genes were applied to construct a LASSO Cox regression analysis model. The effectiveness and accuracy of the prognostic model were tested by internal/external validation and pan-cancer validation and time-dependent ROC. Additionally, a nomogram based on the parameter selected from univariate and multivariate cox regression analysis was constructed.Eight genes were eventually screened out as progression-related differentially expressed candidates in BCa. LASSO Cox regression analysis identified 3 genes to build up the outcome model in E-MTAB-4321 and the outcome model had good performance in predicting patient progress free survival of BCa patients in discovery and test set. Subsequently, another three datasets also have a good predictive value for BCa patients' OS and DFS. Time-dependent ROC indicated an ideal predictive accuracy of the outcome model. Meanwhile, the nomogram showed a good performance and clinical utility. In addition, the prognostic model also exhibits good performance in pan-cancer patients. Our outcome model was the first prognosis model for human bladder cancer progression prediction via integrative bioinformatics analysis, which may aid in clinical decision-making. K E Y W O R D S bladder cancer, Gene Expression Omnibus (GEO), LASSO, prognosis, WGCNA S U PP O RTI N G I N FO R M ATI O N Additional supporting information may be found online in the Supporting Information section. How to cite this article: Xiong Y, Yuan L, Xiong J, et al. An outcome model for human bladder cancer: A comprehensive study based on weighted gene co-expression network analysis.

Section: Discussionmentioning

confidence: 55%

An outcome model for human bladder cancer: A comprehensive study based on weighted gene co‐expression network analysis

Yuan

J Cellular Molecular Medi

et al. 2019

Self Cite

“…Consistently, profiling the age‐related stomach adenocarcinoma in young and old subjects also reveals altered genes in cell cycle and muscle system . Recent studies also show genes involved in apical junction might also play role in cancer development . Collectively, these common oncogenic pathways and uncharacterized pathways might together contribute to the invasive feature of cancer in elder patients.…”

Section: Resultsmentioning

confidence: 72%

“…16 Recent studies also show genes involved in apical junction might also play role in cancer development. 17 Collectively, these common oncogenic pathways and uncharacterized pathways might together contribute to the invasive feature of cancer in elder patients. These pathways might collectively contribute resistance to current cancer therapies and make the elder cancer patients response poorly.…”

Section: Aging Widely Impacts Specific Pathways Across Cancersmentioning

confidence: 99%

Comprehensive transcriptome profiling in elderly cancer patients reveals aging‐altered immune cells and immune checkpoints

Wei

Chen

et al. 2018

Intl Journal of Cancer

Aging is the single most significant risk factor for cancer development. However, the potential impact of aging on cancer microenvironment remains poorly understood. Here, we performed a pan-cancer transcriptome analysis to identify aging-specific molecular patterns across 18 cancer types. Strikingly, aging-specific molecular features define human cancers into two types, including the strong and weak aging-effect groups. Significant aging associated molecular signature was observed in 16 cancer types (strong aging-effect group) such as breast invasive carcinoma and acute myeloid leukemia. In such 16 cancer types, old patients showed obvious poor survival compared to young patients, but this observation was not found in the weak aging-effect cancers. Aging-associated cancer-relevant molecules significantly enriched in 23 pathways including EMT and KRAS signaling. More interestingly, in cancer microenvironment, aging significantly restrains adaptive immunity, but strikingly, increases the number of infiltrated innate immune cells. Further analysis shows that the expression of immune checkpoints including PD-1, PD-L1, PD-L2, and CTLA-4 are mostly correlated with age. In general, cancer cells in elderly patients show a more aggressive phenotype and their surrounding microenvironment is under a more immune suppression status compared with young patients. Our study provides a systematic understanding of aging-associated molecular features in pan-cancer and indicates a clinical requirement to develop aging-specific therapeutic strategies in a majority of cancer types. Furthermore, aging-altered immune cells and immune checkpoints should be considered in cancer immunotherapy. This article is protected by copyright. All rights reserved.

J of Cellular Biochemistry

“…The remaining three genes turn out to have a positive impact on patients’ survival time. Among the five risk genes, CDCA8 was found to be correlated with bladder cancer and was abundantly expressed in bladder cancer samples . And the high expression of CDCA8 was regarded as an adverse predictor of survival time for patients with bladder cancer.…”

Section: Discussionmentioning

confidence: 98%

The discovery of a novel eight‐mRNA‐lncRNA signature predicting survival of hepatocellular carcinoma patients

Shi

Lin

et al. 2018

Increasing evidence indicates that the expressions of messenger RNAs (mRNAs) and long non‐coding RNAs (lncRNAs) undergo a frequent and aberrant change in carcinogenesis and cancer development. But some research was carried out on mRNA‐lncRNA signatures for prediction of hepatocellular carcinoma (HCC) prognosis. We aimed to establish an mRNA‐lncRNA signature to improve the ability to predict HCC patients’ survival. The subjects from the cancer genome atlas (TCGA) data set were randomly divided into two parts: training data set (n = 246) and testing data set (n = 124). Using computational methods, we selected eight gene signatures (five mRNAs and three lncRNAs) to generate the risk score model, which were significantly correlated with overall survival of patients with HCC in both training and testing data set. The signature had the ability to classify the patients in training data set into a high‐risk group and low‐risk group with significantly different overall survival (hazard ratio = 4.157, 95% confidence interval = 2.648‐6.526, P < 0.001). The prognostic value was further validated in testing data set and the entire data set. Further analysis revealed that this signature was independent of tumor stage. In addition, Gene Set Enrichment Analysis suggested that high risk score group was associated with cell proliferation and division related pathways. Finally, we developed a well‐performed nomogram integrating the prognostic signature and other clinical information to predict 3‐ and 5‐year overall survival. In conclusion, the prognostic mRNAs and lncRNAs identified in our study indicate their potential role in HCC biogenesis. The risk score model based on the mRNA‐lncRNA may be an efficient classification tool to evaluate the prognosis of patients’ with HCC.