Identification of Novel Diagnostic Biomarkers in Prostate Adenocarcinoma Based on the Stromal-Immune Score and Analysis of the WGCNA and ceRNA Network

Prostate cancer is still a significant global health burden in the coming decade. Novel biomarkers for detection and prognosis are needed to improve the survival of distant and advanced stage prostate cancer patients. The tumor microenvironment is an important driving factor for tumor biological functions. To investigate RNA prognostic biomarkers for prostate cancer in the tumor microenvironment, we obtained relevant data from The Cancer Genome Atlas (TCGA) database. We used the bioinformatics tools Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data (ESTIMATE) algorithm and weighted coexpression network analysis (WGCNA) to construct tumor microenvironment stromal-immune score-based competitive endogenous RNA (ceRNA) networks. Then, the Cox regression model was performed to screen RNAs associated with prostate cancer survival. The differentially expressed gene profile in tumor stroma was significantly enriched in microenvironment functions, like immune response, cancer-related pathways, and cell adhesion-related pathways. Based on these differentially expressed genes, we constructed three ceRNA networks with 152 RNAs associated with the prostate cancer tumor microenvironment. Cox regression analysis screened 31 RNAs as the potential prognostic biomarkers for prostate cancer. The most interesting 8 prognostic biomarkers for prostate cancer included lncRNA LINC01082, miRNA hsa-miR-133a-3p, and genes TTLL12, PTGDS, GAS6, CYP27A1, PKP3, and ZG16B. In this systematic study for ceRNA networks in the tumor environment, we screened out potential biomarkers to predict prognosis for prostate cancer. Our findings might apply a valuable tool to improve prostate cancer clinical management and the new target for mechanism study and therapy.

Identifying changes in immune cells and constructing prognostic models using immune-related genes in post-burn immunosuppression

Background Burn patients are prone to infection as well as immunosuppression, which is a significant cause of death. Currently, there is a lack of prognostic biomarkers for immunosuppression in burn patients. This study was conducted to identify immune-related genes that are prognosis biomarkers in post-burn immunosuppression and potential targets for immunotherapy. Methods We downloaded the gene expression profiles and clinical data of 213 burn patients and 79 healthy samples from the Gene Expression Omnibus (GEO) database. Immune infiltration analysis was used to identify the proportion of circulating immune cells. Functional enrichment analyses were carried out to identify immune-related genes that were used to build miRNA-mRNA networks to screen key genes. Next, we carried out correlation analysis between immune cells and key genes that were then used to construct logistic regression models in GSE77791 and were validated in GSE19743. Finally, we determined the expression of key genes in burn patients using quantitative reverse transcription polymerase chain reaction (qRT-PCR). Results A total of 745 differently expressed genes were screened out: 299 were up-regulated and 446 were down-regulated. The number of Th-cells (CD4+) decreased while neutrophils increased in burn patients. The enrichment analysis showed that down-regulated genes were enriched in the T-cell activation pathway, while up-regulated genes were enriched in neutrophil activation response in burn patients. We screened out key genes (NFATC2, RORA, and CAMK4) that could be regulated by miRNA. The expression of key genes was related to the proportion of Th-cells (CD4+) and survival, and was an excellent predictor of prognosis in burns with an area under the curve (AUC) value of 0.945. Finally, we determined that NFATC2, RORA, and CAMK4 were down-regulated in burn patients. Conclusion We found that NFATC2, RORA, and CAMK4 were likely prognostic biomarkers in post-burn immunosuppression and potential immunotherapeutic targets to convert Th-cell dysfunction.

MicroRNAs as biomarkers for prostate cancer prognosis: a systematic review and a systematic reanalysis of public data

Background Reliable prognostic biomarkers to distinguish indolent from aggressive prostate cancer (PCa) are lacking. Many studies investigated microRNAs (miRs) as PCa prognostic biomarkers, often reporting inconsistent findings. We present a systematic review of these; also systematic reanalysis of public miR-profile datasets to identify tissue-derived miRs prognostic of biochemical recurrence (BCR) in patients undergoing radical prostatectomy. Methods Independent PubMed searches were performed for relevant articles from January 2007 to December 2019. For the review, 128 studies were included. Pooled-hazard-ratios (HRs) for miRs in multiple studies were calculated using a random-effects model (REM). For the reanalysis, five studies were included and Cox proportional-hazard models, testing miR association with BCR, performed for miRs profiled in all. Results Systematic review identified 120 miRs as prognostic. Five (let-7b-5p, miR-145-5p, miR152-3p, miR-195-5p, miR-224-5p) were consistently associated with progression in multiple cohorts/studies. In the reanalysis, ten (let-7a-5p, miR-148a-3p, miR-203a-3p, miR-26b-5p, miR30a-3p, miR-30c-5p, miR-30e-3p, miR-374a-5p, miR-425-3p, miR-582-5p) were significantly prognostic of BCR. Of these, miR-148a-3p (HR = 0.80/95% CI = 0.68-0.94) and miR-582-5p (HR = 0.73/95% CI = 0.61-0.87) were also reported in prior publication(s) in the review. Conclusions Fifteen miRs were consistently associated with disease progression in multiple publications or datasets. Further research into their biological roles is warranted to support investigations into their performance as prognostic PCa biomarkers.

Preoperative Neutrophil-to-Lymphocyte Ratio, Platelet-to-Lymphocyte Ratio, and CEA as the Potential Prognostic Biomarkers for Colorectal Cancer

Background. This study was to evaluate the prognostic value of the preoperative neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and carcinoembryonic antigen (CEA) in colorectal cancer (CRC) patients and to identify the potential and easily accessible prognostic biomarkers for CRC. Methods. We retrospectively reviewed altogether the records of 330 CRC patients according to inclusion criteria. The clinical characteristics include age at diagnosis, body mass index (BMI), preoperative CEA level, neutrophil , lymphocyte, and platelet count, tumor primary site and size, clinical pathological TNM stage, and survival status were recorded through the review of medical records. The overall survival (OS) was calculated using the Kaplan–Meier method. The Cox proportional hazards model was used for the univariate and multivariate analysis to evaluate the prognostic factors of CRC. Results. A total of 330 patients were finally included in the current study. The mean follow-up duration was 32.8 ± 19.1 months (range, 0.1–67.7). Compared with the median OS, preoperative high NLR, PLR, and CEA, and low BMI had lower median OS. The NLR and PLR value rise indicates lower median OS in stage I-II CRC; however, the NLR value and CEA level rise indicates lower median OS in stage III-IV CRC. Preoperative high NLR, PLR, and CEA level and low BMI have poorer OS by univariate analysis. By multivariate analysis, the age, sex, N, M stage, and BMI demonstrated independently influence the OS of CRC. NLR was an independent predictor of stage I-II CRC, and the CEA level was an independent predictor of stage III-IV CRC. Conclusions. Our results show that preoperative high NLR, PLR, CEA, and low BMI had poorer OS, NLR was an independent predictor of stage I-II CRC, and the CEA level was an independent predictor of stage III-IV CRC.