Background To investigate the prognostic value of six lymph nodes (LNs) staging systems: TNM pN stage, 2018 Federation International of Gynecology and Obstetrics (FIGO) stage, number of positive LNs (PLN), number of negative LNs (NLN), metastatic LN ratio (LNR), and log odds of positive LNs (LODDS) in cervical squamous cell carcinoma (CSCC) patients following radical surgery. Methods The records of 3,732 CSCC patients who underwent radical surgery between 2006 and 2014 were retrospectively reviewed. We divided variables into different groups by applying tree-based recursive partitioning. Survival curves were compared by the log-rank test, and prognostic factors were identified through Cox regression analysis. The six staging systems underwent assessment for their relative discriminative abilities by way of Harrell's concordance index (C-index) and the Akaike's Information Criterion (AIC). Results All of the six staging systems had a significant influence on patients' progression-free survival (PFS) and overall survival (OS), with univariate analysis showing all of the staging systems to have the significant prognostic ability in relation to PFS and OS (P<0.001 for each). Multivariate analysis demonstrated five of the staging methods to be independent prognostic factors, but that NLN classification was not. PLN was noted to have somewhat the best prognostic performance for both PFS (C-index: 0.634; AIC: 33,343.83) and OS (C-index: 0.675; AIC: 34,223.11). Conclusions The pN, 2018 FIGO stage, PLN, LNR, and LODDS appeared to predict better survival than the NLN in CSCC patients. Moreover, PLN appeared to be the most valuable and predictive LN staging system.

https://atm.amegroups.com/article/download/38863/pdf

Validation of the prognostic value of various lymph node staging systems for cervical squamous cell carcinoma following radical surgery: a single‐center analysis of 3,732 patients

Esophageal squamous cell carcinoma (ESCC) is a prevalent aggressive malignant tumor with poor prognosis. Investigations into the molecular changes that occur as a result of the disease, as well as identification of novel biomarkers for its diagnosis and prognosis, are urgently required. Long non-coding RNAs (lncRNAs) have been reported to play a critical role in tumor progression. The present study performed data mining analyses for ESCC via an integrated study of accumulated datasets and identification of the differentially expressed lncRNAs from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. The identified intersection of differentially expressed genes (lncRNAs, miRNAs and mRNAs) in ESCC tissues between the GEO and TCGA datasets was investigated. Based on these intersected lncRNAs, the present study constructed a competitive endogenous RNA (ceRNA) network of lncRNAs in ESCC. A total of 81 intersection lncRNAs were identified; 67 of these were included in the ceRNA network. Functional analyses revealed that these 67 key lncRNAs primarily dominated cellular biological processes. The present study then analyzed the associations between the expression levels of these 67 key lncRNAs and the clinicopathological characteristics of the ESCC patients, as well as their survival time using TCGA. The results revealed that 31 of these lncRNAs were associated with tumor grade, tumor-node-metastasis (TNM) stage and lymphatic metastasis status (P<0.05). In addition, 15 key lncRNAs were demonstrated to be associated with survival time (P<0.05). Finally, 5 key lncRNAs were selected for validation of their expression levels in 30 patients newly diagnosed with ESCC via reverse transcription-quantitative PCR (RT-qPCR). The results suggested that the fold changes in the trends of up- and downregulation between GEO, TCGA and RT-qPCR were consistent. In addition, it was also demonstrated that a select few of these 5 key lncRNAs were significantly associated with TNM stage and lymph node metastasis (P<0.05). The results of the clinically relevant analysis and the aforementioned bioinformatics were similar, hence proving that the bioinformatics analysis used in the present study is credible. Overall, the results from the present study may provide further insight into the functional characteristics of lncRNAs in ESCC through bioinformatics integrative analysis of the GEO and TCGA datasets, and reveal potential diagnostic and prognostic biomarkers for ESCC.

/pdf/integrated-analysis-highlights-multiple-long-non-coding-rnas-53rq2y2kp4.pdf

Integrated analysis highlights multiple long non‑coding RNAs and their potential roles in the progression of human esophageal squamous cell carcinoma

Neuroblastoma (NBL) is the most frequently encountered extracranial solid neoplasm and impacts significantly on the survival of patients, especially in cases of advanced tumor stage or relapse. A long noncoding RNA (lncRNA) signature to predict the survival of patients with NBL is proposed in this paper. Differentially expressed lncRNA (DElncRNA) was selected using the Limma plus Voom package in R based on the RNA-sequencing data downloaded from the Therapeutically Applicable Research To Generate Effective Treatments database and Genotype-Tissue Expression database. Univariate cox regression analysis, least absolute shrinkage and selection operator regression analysis, and multivariate cox regression analysis were conducted to identify candidate DElncRNAs for the risk signature. Consequently, 10 DElncRNAs were designated as candidate DElncRNAs for the risk signature. Time-dependent receiver operating characteristic curves and Kapan-Meier survival curves confirmed the efficacy of the risk signature in predicting the survival of patients with NBL (area under the curve = 0.941; p ≤ .001). One of the DElncRNA constituent subparts (LINC01010) was significantly associated with the survival outcome of patients with NBL in GSE62564 (p = .004). Thus, a risk signature comprising 10 DElncRNAs was identified as effective for individual risk stratification and the survival prediction outcomes of patients with NBL.

A novel risk signature that combines 10 long noncoding RNAs to predict neuroblastoma prognosis.

Prognostic implications of ENE and LODDS in relation to lymph node-positive colorectal cancer location.

FUNDC1-mediated mitophagy in bovine papillomavirus-infected urothelial cells.

Background ceRNAs have emerged as pivotal players in the regulation of gene expression and play a crucial role in the physiology and development of various cancers. Nevertheless, the function and underlying mechanisms of ceRNAs in esophageal cancer (EC) are still largely unknown. Methods In this study, profiles of DEmRNAs, DElncRNAs, and DEmiRNAs between normal and EC tumor tissue samples were obtained from the Cancer Genome Atlas database using the DESeq package in R by setting the adjusted P 2 as the cutoff. The ceRNA network (ceRNet) was initially constructed to reveal the interaction of these ceRNAs during carcinogenesis based on the bioinformatics of miRcode, miRDB, miRTarBase, and TargetScan. Then, independent microarray data of GSE6188, GSE89102, and GSE92396 and correlation analysis were used to validate molecular biomarkers in the initial ceRNet. Finally, a least absolute shrinkage and selection operator logistic regression model was built using an oncogenic ceRNet to diagnose EC more accurately. Results We successfully constructed an oncogenic ceRNet of EC, crosstalk of hsa-miR372-centered CADM2-ADAMTS9-AS2 and hsa-miR145-centered SERPINE1-PVT1. In addition, the risk-score model -0.0053*log2(CADM2)+0.0168*log2(SERPINE1)-0.0073*log2(ADAMTS9-AS2)+0.0905*log2(PVT1)+0.0047*log2(hsa-miR372)-0.0193*log2(hsa-miR145), (log2[gene count]) could improve diagnosis of EC with an AUC of 0.988. Conclusion We identified two novel pairs of ceRNAs in EC and its role of diagnosis. The pairs of hsa-miR372-centered CADM2-ADAMTS9-AS2 and hsa-miR145-centered SERPINE1-PVT1 were likely potential carcinogenic mechanisms of EC, and their joint detection could improve diagnostic accuracy.

/pdf/robust-analysis-of-novel-mrna-lncrna-cross-talk-based-on-4ibbywxiow.pdf

Robust analysis of novel mRNA-lncRNA cross talk based on ceRNA hypothesis uncovers carcinogenic mechanism and promotes diagnostic accuracy in esophageal cancer.

Comparison of three lymph node staging schemes for predicting the outcome in patients with small bowel adenocarcinoma: A population-based cohort and international multicentre cohort study.

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Robust analysis of novel mRNA-lncRNA cross talk based on ceRNA hypothesis uncovers carcinogenic mechanism and promotes diagnostic accuracy in esophageal cancer.

Comparison of three lymph node staging schemes for predicting the outcome in patients with small bowel adenocarcinoma: A population-based cohort and international multicentre cohort study.