Prognostic Value of a Four-miRNA Signature in Patients With Lymph Node Positive Locoregional Esophageal Squamous Cell Carcinoma Undergoing Complete Surgical Resection

Non‑coding RNA: A promising diagnostic biomarker and therapeutic target for esophageal squamous cell carcinoma (Review)

Esophageal cancer (EC) is a common form of malignant tumor in the digestive system that is classified into two types: Esophageal squamous cell carcinomas (ESCC) and esophageal adenocarcinoma. ESCC is known for its early onset of symptoms, which can be difficult to identify, as well as its rapid progression and tendency to develop drug resistance to chemotherapy and radiotherapy. These factors contribute to the high incidence of disease and low cure rate. Therefore, a diagnostic biomarker and therapeutic target need to be identified for ESCC. Non-coding RNAs (ncRNAs) are a class of molecules that are transcribed from DNA but do not encode proteins. Initially, ncRNAs were considered to be non-functional segments generated during transcription. However, with advancements in high-throughput sequencing technologies in recent years, ncRNAs have been associated with poor prognosis, drug resistance and progression of ESCC. The present study provides a comprehensive overview of the biogenesis, characteristics and functions of ncRNAs, particularly focusing on microRNA, long ncRNAs and circular RNAs. Furthermore, the ncRNAs that could potentially be used as diagnostic biomarkers and therapeutic targets for ESCC are summarized to highlight their application value and prospects in ESCC.

A novel microRNA panel exhibited significant potential in evaluating the progression of laryngeal squamous cell carcinoma

Background

Laryngeal squamous cell carcinoma (LSCC) is a common cancer of the head and neck in humans. The 5-years survival rate of patients with LSCC have declined in the past four decades. microRNAs (miRNAs) has been reported to be capable of predicting the prognosis outcomes of patients with different cancers. However, there are no reports on the usage of multi-miRNAs model as signature for the diagnosis or prognosis of LSCC.

Methods

To establish the miRNAs expression-associated model for diagnosis, prognosis prediction and aided therapy of patients with LSCC, the present study enrolled 107 patients with LSCC in clinic and obtained 117 LSCC samples data from TCGA database for evaluation, respectively. Next generation sequencing (NGS), raw data processing, the least absolute shrinkage and selection operator algorithm, Cox regression analysis, construction of nomogram and cell function assays (including proliferation, migration and invasion assays) were sequentially performed.

Results

There were massively dysregulated miRNAs in the LSCC compared to normal tissues. A six-miRNAs signature consists of miR-137-3p, miR-3934-5p, miR-1276, miR-129-5p, miR-7-5p and miR-105-5p was built for prognosis prediction of LSCC patients. The six-miRNAs signature is strongly associated with the poor overall survival (OS, p = 2.5e-05, HR: 4.30 [2.20-8.50]), progression free interval (PFI, p = 0.025, HR: 1.94 [1.08-3.46]) and disease specific survival (DSS, p = 1.1e-05, HR: 5.00 [2.50-10.00]). A nomogram for prediction of 2-, 3- and 5-years OS was also developed based on the six-miRNAs signature and clinical features. Furthermore, blocking the function of each of the six miRNAs inhibited proliferation, invasion and migration of LSCC cells.

Conclusions

The performance of six-miRNAs signature described in the current study demonstrated remarkable potential for progression assessment of LSCC. Moreover, the six-miRNAs signature may serve as predictive tool for prognosis and therapeutic targets of LSCC in clinic.

Multiple-model machine learning identifies potential functional genes in dilated cardiomyopathy

Introduction

Machine learning (ML) has gained intensive popularity in various fields, such as disease diagnosis in healthcare. However, it has limitation for single algorithm to explore the diagnosing value of dilated cardiomyopathy (DCM). We aim to develop a novel overall normalized sum weight of multiple-model MLs to assess the diagnosing value in DCM.

Methods

Gene expression data were selected from previously published databases (six sets of eligible microarrays, 386 samples) with eligible criteria. Two sets of microarrays were used as training; the others were studied in the testing sets (ratio 5:1). Totally, we identified 20 differently expressed genes (DEGs) between DCM and control individuals (7 upregulated and 13 down-regulated).

Results

We developed six classification ML methods to identify potential candidate genes based on their overall weights. Three genes, serine proteinase inhibitor A3 (SERPINA3), frizzled-related proteins (FRPs) 3 (FRZB), and ficolin 3 (FCN3) were finally identified as the receiver operating characteristic (ROC). Interestingly, we found all three genes correlated considerably with plasma cells. Importantly, not only in training sets but also testing sets, the areas under the curve (AUCs) for SERPINA3, FRZB, and FCN3 were greater than 0.88. The ROC of SERPINA3 was significantly high (0.940 in training and 0.918 in testing sets), indicating it is a potentially functional gene in DCM. Especially, the plasma levels in DCM patients of SERPINA3, FCN, and FRZB were significant compared with healthy control.

Discussion

SERPINA3, FRZB, and FCN3 might be potential diagnosis targets for DCM, Further verification work could be implemented.

Serum insulin-like growth factor binding protein-3 as a potential biomarker for diagnosis and prognosis of oesophageal squamous cell carcinoma

BACKGROUND

Insulin-like growth factor binding protein-3 (IGFBP3) has been reported to be related to the risk of some cancers. Here we focussed on serum IGFBP3 as a possible biomarker of diagnosis and prognosis for oesophageal squamous carcinoma (ESCC).

METHODS

Enzyme-linked immunosorbent assay (ELISA) was used to measure the serum IGFBP3 level in the training cohort including 136 ESCC patients and 119 normal controls and the validation cohort with 55 ESCC patients and 42 normal controls. The receiver operating characteristics curve (ROC) was used to assess the diagnosis value. Cox proportional hazards model was applied to select factors for survival nomogram construction.

RESULTS

Serum IGFBP3 levels were significantly lower in early-stage ESCC or ESCC patients than those in normal controls (p < .05). The specificity and sensitivity of serum IGFBP3 for the diagnosis of ESCC were 95.80% and 50.00%, respectively, with the area under the ROC curve (AUC) of 0.788 in the training cohort. Similar results were observed in the validation cohort (88.10%, 38.18%, and 0.710). Importantly, serum IGFBP3 could also differentiate early-stage ESCC from controls (95.80%, 52.54%, 0.777 and 88.10%, 36.36%, 0.695 in training and validation cohorts, respectively). Furthermore, Cox multivariate analysis revealed that serum IGFBP3 was an independent prognostic risk factor (HR = 2.599, p = .002). Lower serum IGFBP3 level was correlated with reduced overall survival (p < .05). Nomogram based on serum IGFBP3, TNM stage, and tumour size improved the prognostic prediction of ESCC with a concordance index of 0.715.

CONCLUSION

We demonstrated that serum IGFBP3 was a potential biomarker of diagnosis and prognosis for ESCC. Meanwhile, the nomogram might help predict the prognosis of ESCC. Key MessageSerum IGFBP3 showed early diagnostic value in oesophageal squamous cell carcinoma with independent cohort validation. Moreover, serum IGFBP3 was identified as an independent prognostic risk factor, which was used to construct a nomogram with improved prognosis ability in oesophageal squamous cell carcinoma.

Construction and Evaluation of a Risk Score Model for Lymph Node Metastasis-Associated Circadian Clock Genes in Esophageal Squamous Carcinoma

Background: Studies suggested that circadian clock genes (CCGs) in human esophageal squamous carcinoma (ESCC) samples are dysregulated. However, the relevance of CCGs to lymph node metastasis (LNM) and prognosis of ESCC remains unclear. Methods: The differentially expressed genes (DEGs) between normal and ESCC samples in The Cancer Genome Atlas database (TCGA) database were intersected with the genes associated with LNM (LNMGs) in ESCC samples and 300 CCGs to obtain the differentially expressed LNM-associated CCGs (DE-LNM-CCGs). The risk model was constructed by Cox regression analysis in the TCGA-ESCC training set, and the accuracy of the risk model was verified by risk profile and overall survival profile. Furthermore, differences of 23 immune cells, 13 immune functions, and immune checkpoint molecules between the high- and low-risk groups were assessed using the single-sample gene set enrichment analysis (ssGSEA) algorithm. Gene set enrichment analysis (GSEA) was conducted to investigate the functional differences between low- and high-risk groups. Finally, we validated the mRNA expression levels of prognostic model genes by quantitative real-time polymerase chain reaction (qRT-PCR). Results: A total of six DE-LNM-CCGs were identified in TCGA-ESCC. TP53 and NAGLU were selected by Cox regression analysis to construct the risk model. Risk profile plots, overall survival plots, and validation results of the risk model in the validation set indicated that the constructed risk model was reliable. The result of ssGSEA showed that the percentages of activated B cells, activated dendritic cells, effector memory CD8 T cells, immune function in neutrophils, plasmacytoid dendritic cells, T cell co-inhibition, and Type 17 T helper cells were different between the high- and low-risk groups. In addition, the expression of CD274, PDCD1, TNFRSF18, and TNFRSF9 was dysregulated between the high- and low-risk groups. GSEA revealed that the high-risk group was associated with cell differentiation, oxidative phosphorylation, and steroid biosynthesis pathways, while the low-risk group was associated with chromosome, ECM–receptor interaction, and other pathways. Finally, qRT-PCR results showed that the mRNA expression levels of two prognostic genes were consistent with TCGA. Conclusion: In conclusion, the risk model constructed based on TP53 and NAGLU could accurately predict the prognosis.

miR-375 suppresses the growth and metastasis of esophageal squamous cell carcinoma by targeting PRDX1

BACKGROUND

Esophageal cancer (EC) is one of the most lethal cancers. Esophageal squamous cell carcinoma (ESCC) is the most common histological subtype in Asian people. Diverse microRNAs, such as miR-375, have been confirmed to be involved in the process of tumorigenesis and metastasis. However, the underlying mechanism through which miR-375 acts in ESCC patients remains unknown.

METHODS

We used The Cancer Genome Atlas (TCGA) database to analyze the association between miR-375 and the survival rate in patients with esophageal squamous cell carcinoma. Real Time quantitative PCR (RT-qPCR) analysis was performed to evaluate the level of miR-375 in EC tissues and cells. A luciferase reporter assay was used to confirm the target gene of miR-375. A colony formation assay as well as flow cytometric and transwell invasion experiments were employed to examine the effects of miR-375 and peroxiredoxin 1 (PRDX1) on ESCC cells. A tumor xenograft mouse model was then used to investigate the role of miR-375 on tumor growth in vivo. Moreover, we performed rescue experiments to evaluate the effect of PRDX1 on ESCC progression.

RESULTS

miR-375 expression was significantly downregulated in both ESCC clinical tissues and serum, and the reduction of miR-375 was remarkably linked to a poor prognosis in ESCC. Further investigation illustrated that aberrant expression of miR-375 dampened the growth and infiltration of ESCC cells both in vitro and in vivo. Bioinformatics and luciferase reporter analysis verified that the transcript of PRDX1 is a direct target of miR-375 and its expression in ESCC cells was found to be inversely modulated by miR-375. Moreover, the tumor formation experiment in nude mice confirmed that miR-375 can effectively dampen tumor growth in xenograft tumor mice models. Notably, over-expression of PRDX1 effectively counteracted the tumor-suppressing capabilities of miR-375.

CONCLUSIONS

We demonstrated the antitumor effect of miR-375 on ESCC by targeting PRDX1 both in vitro and in vivo.

Development and validation of metabolic scoring to individually predict prognosis and monitor recurrence early in gastric cancer: A large-sample analysis

PURPOSE

To develop and validate a simple metabolic score (Metabolic score, MS) for use in evaluating the prognosis of gastric cancer (GC) patients and dynamically monitor for early recurrence.

METHODS

We retrospectively collected general clinicopathological data of patients who underwent radical gastrectomy for GC between September 2012 and December 2017 in the Department of Gastric Surgery of the Fujian Medical University Union Hospital. Using a random forest algorithm to screen preoperative blood indicators into the Least absolute shrinkage and selection operator (LASSO) model, we developed a novel MS to predict prognosis.

RESULTS

Data of 1974 patients were used to develop and validate the model. Total cholesterol (TCHO), bilirubin (TBIL), direct bilirubin (DBIL), and 15 other metabolic indicators had significant predictive value for the prognosis using the random forest algorithm. In the overall population, 533 patients (27.0%) had high and 1441 (73%) had low MS status. High MS status was related to tumor progression. The KM curves of 3-year OS and RFS for training set patients showed low MS had a better prognosis than high MS (OS: 79.4% vs 59.7%, P < 0.001; RFS: 76.0% vs 56.2%, P < 0.001).

CONCLUSIONS

We have developed and validated MS to predict the long-term survival of GC patients and allow early monitoring of recurrence. This will provide physicians with simple, economical, and dynamic tumor monitoring information.

GTF2E2 is a novel biomarker for recurrence after surgery and promotes progression of esophageal squamous cell carcinoma via miR-139-5p/GTF2E2/FUS axis

Esophageal squamous cell carcinoma (ESCC) is one of the most lethal gastrointestinal malignancies with high mortality. Recurrence develops within only a few years after curative resection and perioperative adjuvant therapy in 30-50% of these patients. Therefore, it is essential to identify postoperative recurrence biomarkers to facilitate selecting the following surveillance and therapeutic strategies. The general transcription factor IIE subunit beta (GTF2E2) is crucial for physiological and pathological functions, but its roles in the aggression and recurrence of ESCC remain ambiguous. In this study, we found that GTF2E2 was highly expressed in ESCC samples, and elevated GTF2E2 expression predicted early recurrence after surgery for ESCC patients. High expression of GTF2E2 associated with more aggressive clinic features and poor prognosis. GTF2E2 promoted the proliferation and mobility of ESCC cells in vitro and in vivo. We further revealed that miR-139-5p repressed GTF2E2 expression by downregulating its mRNA through binding with Argonaute 2 (Ago2). Rescue assays suggested that miR-139-5p affected GTF2E2-mediated ESCC progression. Moreover, GTF2E2 positively interacted with FUS promoter and regulated FUS expression, and the phenotype changes caused by GTF2E2 manipulation were recovered by rescuing FUS expression in ESCC cells. Additionally, we demonstrated that GTF2E2 promotes ESCC cells progression via activation of the AKT/ERK/mTOR pathway. In conclusion, GTF2E2 may serve as a novel biomarker for recurrence after surgery and a potential therapeutic target for ESCC patients, and it promotes ESCC progression via miR-139-5p/GTF2E2/FUS axis.

A Novel TCGA-Validated, MiRNA-Based Signature for Prediction of Breast Cancer Prognosis and Survival

Breast cancer (BC) is the most common cancer affecting women and the leading cause of cancer-related deaths worldwide. Compelling evidence indicates that microRNAs (miRNAs) are inextricably involved in the development of cancer. Here, we constructed a novel model, based on miRNA-seq and clinical data downloaded from The Cancer Genome Atlas (TCGA). Data from a total of 962 patients were included in this study, and the relationships among their clinicopathological features, survival, and miRNA-seq expression levels were analyzed. Hsa-miR-186 and hsa-miR-361 were identified as internal reference miRNAs and used to normalize miRNA expression data. A five-miRNA signature, constructed using univariate and multivariate Cox regression, was significantly associated with disease-specific survival (DSS) of patients with BC. Kaplan–Meier (KM) and receiver operating characteristic (ROC) analyses were conducted to confirm the clinical significance of the five-miRNA signature. Finally, a nomogram was constructed based on the five-miRNA signature to evaluate its clinical value. Cox regression analysis revealed that a five-miRNA signature was significantly associated with DSS of patients with BC. KM analysis demonstrated that the signature could efficiently distinguish high- and low-risk patients. Moreover, ROC analysis showed that the five-miRNA signature exhibited high sensitivity and specificity in predicting the prognosis of patients with BC. Patients in the high-risk subgroup who received adjuvant chemotherapy had a significantly lower incidence of mortality than those who did not. A nomogram constructed based on the five-miRNA signature was effective in predicting 5-year DSS. This study presents a novel five-miRNA signature as a reliable prognostic tool to predict DSS and provide theoretical reference significance for individualized clinical decisions for patients with BC.

MicroRNA-139-5p improves sepsis-induced lung injury by targeting Rho-kinase1

Sepsis-induced acute lung injury (ALI) is an inflammatory process that involves inflammatory cytokine production and cell apoptosis. In the present study, the regulatory role of microRNA (miR)-139-5p in sepsis-induced ALI was investigated using a murine model of cecal ligation puncture (CLP) and an in vitro model using lipopolysaccharide (LPS)-induced normal human bronchial epithelial cells (NHBEs). Sepsis-induced pathological changes in the lungs of ALI mice were detected using hematoxylin and eosin staining. Lung water content was determined, and the expression of proinflammatory cytokines in the bronchoalveolar lavage fluid and serum of sepsis-induced ALI mice were quantified using ELISA. The levels of oxidative stress in lung tissues were determined using commercial kits. The degree of apoptosis was determined using a TUNEL assay. The expression levels of miR-139-5p and Rho-kinase 1 (ROCK1) were determined using reverse transcription-quantitative PCR and western blot analyses. A dual-luciferase reporter assay was used to confirm the direct targeting of ROCK1 by miR-139-5p. NHBEs were co-transfected with vectors expressing ROCK1 (or empty vector) and miR-139-5p mimics or control mimics prior to LPS treatment. The transcriptional activity of caspase-3, the ratio of apoptotic cells, the expression levels of mucin 5AC, mucin 1, TNF-α, IL-1β, IL-6, NLR family pyrin domain containing 3, apoptosis-associated speck-like protein containing a CARD and caspase-1 were evaluated. Compared with the normal group, mice that underwent CLP exhibited abnormal lung morphology, enhanced production of TNF-α, IL-1β and IL-6, increased reactive oxygen species (ROS), malondialdehyde and lactate dehydrogenase levels, an increased proportion of apoptotic cells and increased ROCK1 expression. Superoxide dismutase, glutathione peroxidase and miR-139-5p levels were decreased following CLP. In the NHBEs, stimulation with LPS caused a marked increase in inflammatory cytokine levels and apoptosis compared with the untreated cells. Overexpression of miR-139-5p attenuated cell apoptosis and inflammation. Overexpression of ROCK1 in NHBEs restored the ROS levels and proinflammatory cytokine production inhibited by miR-139-5p. In conclusion, miR-139-5p alleviated sepsis-induced ALI via suppression of its downstream target, ROCK1, suggesting that miR-139-5p may hold promise in the treatment of sepsis-induced ALI.

Long non-coding RNA small nucleolar RNA host gene 7 facilitates the proliferation, migration, and invasion of esophageal cancer cells by regulating microRNA-625

Background

Esophageal cancer (EC) is a highly aggressive malignant tumor, of which esophageal squamous cell carcinoma (ESCC) constitutes the main subtype. Long non-coding RNA (lncRNA) small nucleolar RNA host gene 7 (SNHG7) has been extensively studied in many tumors and has been confirmed to be an oncogene; however, it has yet to be investigated in an ESCC study. Therefore, this study intended to uncover the role of SNHG7 in ESCC.

Methods

Quantitative real-time polymerase chain reaction was applied to measure the expression levels of SNHG7 and miR-625 in ESCC tumor tissues and cell lines. Cell Counting Kit-8 assay, 5-Ethynyl-2'-deoxyuridine assay, scratch assay, and Transwell assay were conducted to assess the proliferation, migration, and invasion ESCC cell. We verified the interaction between SNHG7 and miR-625 by performing the dual luciferase reporter gene experiment.

Results

Compared to that in adjacent normal tissues and HET1A cell lines, the expression level of SNHG7 in ESCC tumor tissues and ESCC cell lines was up-regulated, while the expression level of miR-625 was down-regulated. ESCC cell proliferation, migration, and invasion were significantly promoted by SNHG7 overexpression but inhibited by silencing of SNHG7. Further, luciferase reporter gene experiments confirmed that SNHG7 interacted with miR-625, and rescue experiments showed that SNHG7 promoted the malignant phenotype by inhibiting miR-625.

Conclusions

SNHG7 is up-regulated in ESCC tumor tissues and cell lines, while miR-625 is expressed at a low level. SNHG7 is able to facilitate the proliferation, migration, and invasion of ESCC cells by targeting miR-625.

Phenotypic profiling and prognostic significance of immune infiltrates in esophageal squamous cell carcinoma

The tumor microenvironment (TME) of esophageal squamous cell carcinoma (ESCC) impacts tumor progression but is poorly understood. We obtained tumor tissues from 279 patients after esophagectomy and characterized the TME in intraepithelial and stromal regions using multiplex fluorescent immunohistochemistry (mfIHC). A heterogeneous immune population infiltrating tumor and the uninvolved esophageal tissue were observed. The infiltration of intraepithelial programmed death ligand 1 (PD-L1)-positive tumor-associated macrophages (TAMs) and stromal granzyme B⁺ activated cytotoxic T cells (aCTLs) correlated with both prolonged overall survival (OS) and disease-free survival (DFS). The intraepithelial memory T cell infiltration predicted longer OS, while intraepithelial and stromal regulatory T cell (Treg) infiltration was associated with shortened OS and DFS, respectively. Multivariate models combining immune infiltrates and clinicopathological factors outperformed tumor-node-metastasis (TNM) stage in predicting OS and DFS at 3 and 5 years. The infiltration of Treg inversely correlated with that of the antitumor effectors including CTLs, aCTLs, and natural killer (NK) cells. Intraepithelial memory T cell infiltration also negatively correlated with PD-L1 expression. In spatial analysis, intraepithelial dendritic cell (DC)-memory T cell engagement increased in high PD-L1⁺ TAM infiltration group. The characterization of the TME revealed a complex interplay between immune populations and may be employed to stratify patient for prognosis prediction and immunotherapy.

The microRNA miR-29c-5p inhibits cell proliferation and migration by targeting TMEM98 in head and neck carcinoma

Head and neck squamous cell carcinoma (HNSCC), which occurs frequently worldwide, is characterized by high risk of metastasis. MicroRNAs (miRNAs) play crucial roles in tumorigenesis and cancer development. In this study, miR-29c-5p was identified using three high throughput microarrays. We measure miR-29c-5p expression in HNSCC tissues and cell lines. To determine the function of miR-29c-5p in HNSCC, we evaluated its effects in vitro on cell proliferation, the cell cycle, apoptosis, and cell migration. We employed a mouse tumor xenograft model to determine the effects of miR-29c-5p on tumors generated by HNSCC cell lines. The miR-29c-5p expression was lower in HNSCC tissues than in normal tissues. Upregulated miR-29c-5p expression in HNSCC cells inhibited migration and arrested cells in the G2/M phase of the cell cycle. Further, upregulated miR-29c-5p expression inhibited the proliferation of HNSCC cells in vivo and in vitro. In addition, transmembrane protein 98 (TMEM98) was identified as a direct target of miR-29c-5p by using a luciferase reporter assay. These findings provide new insights that link the regulation of miR-29c-5p expression to the malignant phenotype of HNSCC and suggest that employing miR-29c-5p may serve as a therapeutic strategy for managing patients with HNSCC.

Molecular characterization of breast cancer: a potential novel immune-related lncRNAs signature

Background

Accumulating evidence has demonstrated that immune-related lncRNAs (IRLs) are commonly aberrantly expressed in breast cancer (BC). Thus, we aimed to establish an IRL-based tool to improve prognosis prediction in BC patients.

Methods

We obtained IRL expression profiles in large BC cohorts (N = 911) from The Cancer Genome Atlas (TCGA) database. Then, in light of the correlation between each IRL and recurrence-free survival (RFS), we screened prognostic IRL signatures to construct a novel RFS nomogram via a Cox regression model. Subsequently, the performance of the IRL-based model was evaluated through discrimination, calibration ability, risk stratification ability and decision curve analysis (DCA).

Results

A total of 52 IRLs were obtained from TCGA. Based on multivariate Cox regression analyses, four IRLs (A1BG-AS1, AC004477.3, AC004585.1 and AC004854.2) and two risk parameters (tumor subtype and TNM stage) were utilized as independent indicators to develop a novel prognostic model. In terms of predictive accuracy, the IRL-based model was distinctly superior to the TNM staging system (AUC: 0.728 VS 0.673, P = 0.010). DCA indicated that our nomogram had favorable clinical practicability. In addition, risk stratification analysis showed that the IRL-based tool efficiently divided BC patients into high- and low-risk groups (P < 0.001).

Conclusions

A novel IRL-based model was constructed to predict the risk of 5-year RFS in BC. Our model can improve the predictive power of the TNM staging system and identify high-risk patients with tumor recurrence to implement more appropriate treatment strategies.

Diagnostic, prognostic, and therapeutic significance of miR-139-5p in cancers

miRNAs are a group of non-coding RNAs that have regulatory functions in post-transcriptional gene expression. These molecules play a fundamental role in cellular processes, for instance cell proliferation, apoptosis, migration, and invasion. Scientific investigations have previously established that miRNAs can either promote or suppress tumor development by mediating different signaling pathways. miR-139-5p, located on chromosome 11q13.4, has been examined extensively in cancers. Studies have demonstrated that miR-139-5p might be an attractive cancer biomarker. Herein, we will review how miR-139-5p acts in cancer diagnosis, prognosis, and therapy, as well as elucidating its major target genes and associated signaling pathways.

Genome-wide analysis of lncRNAs, miRNAs, and mRNAs forming a prognostic scoring system in esophageal squamous cell carcinoma

Background

Esophageal squamous cell carcinoma (ESCC) is the main subtype of esophageal carcinoma. Protein coding genes and non-coding RNAs can be powerful prognostic factors in multiple cancers, including ESCC. However, there is currently no model that integrates multiple types of RNA expression signatures to predict clinical outcomes.

Methods

The sequencing data (RNA-sequencing and miRNA-sequencing) and clinical data of ESCC patients were obtained from The Cancer Genome Atlas (TCGA) database, and Differential gene expression analysis, Cox regression analysis and Spearman correlation analysis were used to construct prognosis-related lncRNA-mRNA co-expression network and scoring system with multiple types of RNA. The potential molecular mechanisms of prognostic mRNAs were explored by functional enrichment analysis.

Results

A total of 62 prognostic lncRNAs, eight prognostic miRNAs and 66 prognostic mRNAs were identified in ESCC (P-value < 0.05) and a prognosis-related lncRNA-mRNA co-expression network was created. Five prognosis-related hub RNAs (CDCA2, MTBP, CENPE, PBK, AL033384.1) were identified. Biological process analysis revealed that mRNAs in prognosis-related co-expression RNA network were mainly enriched in cell cycle, mitotic cell cycle and nuclear division. Additionally, we constructed a prognostic scoring system for ESCC using ten signature RNAs (MLIP, TNFSF10, SIK2, LINC01068, LINC00601, TTTY14, AC084262.1, LINC01415, miR-5699-3p, miR-552-5p). Using this system, patients in the low-risk group had better long-term survival than those in the high-risk group (log-rank, P-value < 0.0001). The area under the ROC curve (AUCs) revealed that the accuracy of the prediction model was higher than the accuracy of single type of RNA prediction model.

Conclusion

In brief, we constructed a prognostic scoring system based on multiple types of RNA for ESCC that showed high predicting prognosis performance, and deeply understood the regulatory mechanism of prognosis-related lncRNA-mRNA co-expression network.

Prognostic significance of microRNA-135 in patients with digestive system cancers: a systematic review and meta-analysis

Background: MicroRNA-135 (miR-135) is a well-known non-coding RNA that has been demonstrated to participate in tumorigenesis and cancer development; however, the clinical prognostic value of miR-135 in digestive system cancers remains controversial. This meta-analysis aims to explore the potential value of miR-135 as a prognostic marker for digestive system cancers.

Methods: The PubMed, Embase, Cochrane Library, and Web of Science databases were searched for eligible articles published before 31 August 2019. Stata 12.0 software was used to analyze the overall survival (OS), disease-free survival (DFS), and recurrence-free survival (RFS) rates to access the prognostic value of miR-135 in digestive system cancers. We then used The Cancer Genome Atlas (TCGA) datasets to validate the meta-analysis results.

Results A total of 1470 patients from 17 studies were included in this meta-analysis. The pooled results showed that enhanced miR-135 expression was significantly associated with poor OR (hazard ratio (HR): 1.790; 95% confidence interval (95% CI): 1.577–2.031; P=0.000), DFS (HR: 1.482; 95% CI: 0.914–2.403; P=0.110), and RFS (HR: 3.994; 95% CI: 1.363–11.697; P=0.012) in digestive system cancers. A sensitivity analysis confirmed the reliability of our findings, and no significant publication bias was observed.

Conclusion: MiR-135 can be used as a novel biomarker for patients with digestive system cancers. We look forward to future large-scale clinical studies that will investigate the prognostic value of miR-135.