A four-microRNA classifier as a novel prognostic marker for tumor recurrence in stage II colon cancer

miR-5100 Overexpression Inhibits Prostate Cancer Progression by Inducing Cell Cycle Arrest and Targeting E2F7

Despite advances in treatment, prostate cancer remains a leading cause of cancer-related deaths among men, highlighting the urgent need for innovative therapeutic strategies. MicroRNAs (miRNAs) have emerged as key regulatory molecules in cancer biology. In this research, we investigated the tumor-suppressive role of miR-5100 in PCa and its underlying molecular mechanism. By using RT-qPCR, we observed lower miR-5100 expression in PCa cell lines than in benign prostate cells. Functional assays demonstrated that miR-5100 overexpression significantly suppressed PCa cell proliferation, migration, and invasion. By using RNA-sequencing, we identified 446 down-regulated and 806 upregulated candidate miR-5100 target genes overrepresenting cell cycle terms. Mechanistically, E2F7 was confirmed as a direct target of miR-5100 using the reporter gene assay and RIP assay. By conducting flow cytometry analysis, cell cycle progression was blocked at the S phase. E2F7 overexpression partially mitigated the suppressive impact of miR-5100 in PCa cells. In conclusion, miR-5100 is a tumor suppressor in PCa by blocking cell cycle and targeting E2F7.

An evolutionary learning-based method for identifying a circulating miRNA signature for breast cancer diagnosis prediction

Breast cancer (BC) is one of the most commonly diagnosed cancers worldwide. As key regulatory molecules in several biological processes, microRNAs (miRNAs) are potential biomarkers for cancer. Understanding the miRNA markers that can detect BC may improve survival rates and develop new targeted therapeutic strategies. To identify a circulating miRNA signature for diagnostic prediction in patients with BC, we developed an evolutionary learning-based method called BSig. BSig established a compact set of miRNAs as potential markers from 1280 patients with BC and 2686 healthy controls retrieved from the serum miRNA expression profiles for the diagnostic prediction. BSig demonstrated outstanding prediction performance, with an independent test accuracy and area under the receiver operating characteristic curve were 99.90% and 0.99, respectively. We identified 12 miRNAs, including hsa-miR-3185, hsa-miR-3648, hsa-miR-4530, hsa-miR-4763-5p, hsa-miR-5100, hsa-miR-5698, hsa-miR-6124, hsa-miR-6768-5p, hsa-miR-6800-5p, hsa-miR-6807-5p, hsa-miR-642a-3p, and hsa-miR-6836-3p, which significantly contributed towards diagnostic prediction in BC. Moreover, through bioinformatics analysis, this study identified 65 miRNA-target genes specific to BC cell lines. A comprehensive gene-set enrichment analysis was also performed to understand the underlying mechanisms of these target genes. BSig, a tool capable of BC detection and facilitating therapeutic selection, is publicly available at https://github.com/mingjutsai/BSig.

Role of miR50103p in predicting the prognosis of hepatocellular carcinoma

OBJECTIVES

Numerous miRNAs have been found to be abnormally expressed in hepatocellular carcinoma (HCC). However, clinical significance of miR-5010-3p in HCC is not elucidated. This study aims to explore the prognostic value and role of miR-5010-3p in HCC.

METHODS

The differential gene expression analysis of miR-5010-3p in HCC was performed based on the Cancer Genome Atlas (TCGA) database. The receiver operating characteristic (ROC) curve was used to evaluate the predictive value of miR-5010-3p expression level for HCC prognosis. The Kaplan-Meier, Cox univariate, and Cox multivariate analysis were used to predict its role in the prognosis of HCC. The downstream target genes were predicted. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed to predict the potential functional pathways they may participate in. Finally, methyl thiazolyl tetrazolium (MTT) assay and 5-ethyl-2'-deoxyuridine (EDU) incorporation experiment were carried out to prove its effect on proliferation.

RESULTS

The expression of miR-5010-3p was associated with histological grade (P=0.019), vascular invasion degree (P=0.049), TP53 level (P=0.004), and alpha fetoprotein (AFP) level (P=0.012). A moderate ability to distinguish between tumor and paracancerous tissues of miR-5010-3p in HCC was perceived by ROC curve (AUC: 0.712, 95% CI 0.649 to 0.776). High expression of miR-5010-3p was associated with shorter overall survival (OS) (P=0.003). The results of functional enrichment analysis showed that miR-5010-3p was related to the tumorigenesis process. In vitro experiments verified that miR-5010-3p promoted the proliferation of hepatocellular carcinoma cells.

CONCLUSIONS

MiR-5010-3p promotes the proliferation of liver cancer cells, and its high expression is associated with poor prognosis, which may be a potential prognostic marker.

MicroRNAs as Targets for Cancer Diagnosis: Interests and Limitations

MicroRNAs are small RNAs with ability to attach to the large number of RNA that regulate gene expression on post-transcriptional level via inhibition or degradation of specific mRNAs. MiRNAs in cells are the primary regulators of functions such as cell growth, differentiation, and apoptosis and considerably influence cell function. The expression levels of microRNAs change in human diseases, including cancer. These changes highlight their essential role in cancer pathogenesis. Ubiquitous irregular expression profiles of miRNAs have been detected in various human cancers using genome-wide identification techniques, which are emerging as novel diagnostic and prognostic cancer biomarkers of high specificity and sensitivity. The measurable miRNAs with enhanced stability in blood, tissues, and other body fluids provide a comprehensive source of miRNA-dependent biomarkers for human cancers. The leading role of miRNAs as potential biomarkers in human cancers is discussed in this article. In addition, the interests and difficulties of miRNAs as biomarkers have been explored.

Identification of a Twelve-microRNA Signature with Prognostic Value in Stage II Microsatellite Stable Colon Cancer

We aimed to identify and validate a set of miRNAs that could serve as a prognostic signature useful to determine the recurrence risk for patients with COAD. Small RNAs from tumors of 100 stage II, untreated, MSS colon cancer patients were sequenced for the discovery step. For this purpose, we built an miRNA score using an elastic net Cox regression model based on the disease-free survival status. Patients were grouped into high or low recurrence risk categories based on the median value of the score. We then validated these results in an independent sample of stage II microsatellite stable tumor tissues, with a hazard ratio of 3.24, (CI_95% = 1.05-10.0) and a 10-year area under the receiver operating characteristic curve of 0.67. Functional analysis of the miRNAs present in the signature identified key pathways in cancer progression. In conclusion, the proposed signature of 12 miRNAs can contribute to improving the prediction of disease relapse in patients with stage II MSS colorectal cancer, and might be useful in deciding which patients may benefit from adjuvant chemotherapy.

State of the Art of Chemosensors in a Biomedical Context

Healthcare is undergoing large transformations, and it is imperative to leverage new technologies to support the advent of personalized medicine and disease prevention. It is now well accepted that the levels of certain biological molecules found in blood and other bodily fluids, as well as in exhaled breath, are an indication of the onset of many human diseases and reflect the health status of the person. Blood, urine, sweat, or saliva biomarkers can therefore serve in early diagnosis of diseases such as cancer, but also in monitoring disease progression, detecting metabolic disfunctions, and predicting response to a given therapy. For most point-of-care sensors, the requirement that patients themselves can use and apply them is crucial not only regarding the diagnostic part, but also at the sample collection level. This has stimulated the development of such diagnostic approaches for the non-invasive analysis of disease-relevant analytes. Considering these timely efforts, this review article focuses on novel, sensitive, and selective sensing systems for the detection of different endogenous target biomarkers in bodily fluids as well as in exhaled breath, which are associated with human diseases.

Copy-number intratumor heterogeneity increases the risk of relapse in chemotherapy-naive stage II colon cancer

Optimal selection of high-risk patients with stage II colon cancer is crucial to ensure clinical benefit of adjuvant chemotherapy. Here, we investigated the prognostic value of genomic intratumor heterogeneity and aneuploidy for disease recurrence. We combined targeted sequencing, SNP arrays, fluorescence in situ hybridization, and immunohistochemistry on a retrospective cohort of 84 untreated stage II colon cancer patients. We assessed the clonality of copy-number alterations (CNAs) and mutations, CD8⁺ lymphocyte infiltration, and their association with time to recurrence. Prognostic factors were included in machine learning analysis to evaluate their ability to predict individual relapse risk. Tumors from recurrent patients displayed a greater proportion of CNAs compared with non-recurrent (mean 31.3% versus 23%, respectively; p = 0.014). Furthermore, patients with elevated tumor CNA load exhibited a higher risk of recurrence compared with those with low levels [p = 0.038; hazard ratio (HR) 2.46], which was confirmed in an independent cohort (p = 0.004; HR 3.82). Candidate chromosome-specific aberrations frequently observed in recurrent cases included gain of the chromosome arm 13q (p = 0.02; HR 2.67) and loss of heterozygosity at 17q22-q24.3 (p = 0.05; HR 2.69). CNA load positively correlated with intratumor heterogeneity (R = 0.52; p < 0.0001). Consistently, incremental subclonal CNAs were associated with an elevated risk of relapse (p = 0.028; HR 2.20), which we did not observe for subclonal single-nucleotide variants and small insertions and deletions. The clinico-genomic model rated an area under the curve of 0.83, achieving a 10% incremental gain compared with clinicopathological markers (p = 0.047). In conclusion, tumor aneuploidy and copy-number intratumor heterogeneity were predictive of poor outcome and improved discriminative performance in early-stage colon cancer. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

MicroRNA-656-3p inhibits colorectal cancer cell migration, invasion, and chemo-resistance by targeting sphingosine-1-phosphate phosphatase 1

Colorectal cancer presents high rates of recurrence and metastasis, and the occurrence and progression and mechanism of its invasion and metastasis are not fully understood. The expression of miR-656-3p in patient samples and 10 cell lines were measured. Bioinformatic databases were used to predict miRNAs. Protein expressions were examined using Western blot. Transwell assay was used to measure cell migration and invasion. Transplanted tumor model in nude mice was established. Removal of the miR-656-3p by specific knocking-down of this gene promoted the chemo-resistance of colorectal cancer cells. Critically, we identified sphingosine-1-phosphate phosphatase 1 (SGPP1) as a downsteam target of the miR-656-3p, which we first obtained from 199 potential target genes from Targetscan, 200 genes from miRDB and 200 genes from DIANA, respectively. Then, we identified the interaction between SGPP1 and the miR-656-3p on 3’ UTR of SGPP1 gene. Knockdown of SGPP1 greatly suppressed the tumor growth in vivo and epithelial mesenchymal transition process. miR-656-3p could regulate cell proliferation and chemoresistance in the colorectal cancer that associate to downstream target with SGPP1. Along with its downstream molecule, we would like to predict that the SGPP1 associated miR-656-3p could be used to develop early for early diagnostics for CRC oncogenesis.

Two Novel Ceramide-Like Molecules and miR-5100 Levels as Biomarkers Improve Prediction of Prostate Cancer in Gray-Zone PSA

Reliable liquid biopsy-based tools able to accurately discriminate prostate cancer (PCa) from benign prostatic hyperplasia (BPH), when PSA is within the “gray zone” (PSA 4–10), are still urgent. We analyzed plasma samples from a cohort of 102 consecutively recruited patients with PSA levels between 4 and 16 ng/ml, using the SANIST-Cloud Ion Mobility Metabolomic Mass Spectrometry platform, combined with the analysis of a panel of circulating microRNAs (miR). By coupling CIMS ion mobility technology with SANIST, we were able to reveal three new structures among the most differentially expressed metabolites in PCa vs. BPH. In particular, two were classified as polyunsaturated ceramide ester-like and one as polysaturated glycerol ester-like. Penalized logistic regression was applied to build a model to predict PCa, using six circulating miR, seven circulating metabolites, and demographic/clinical variables, as covariates. Four circulating metabolites, miR-5100, and age were selected by the model, and the corresponding prediction score gave an AUC of 0.76 (C.I. = 0.66–0.85). At a specified cut-off, no high-risk tumor was misclassified, and 22 out of 53 BPH were correctly identified, reducing by 40% the false positives of PSA. We developed and applied a novel, minimally invasive, liquid biopsy-based powerful tool to characterize novel metabolites and identified new potential non-invasive biomarkers to better predict PCa, when PSA is uninformative as a tool for precision medicine in genitourinary cancers.

Molecular Markers to Predict Prognosis and Treatment Response in Uterine Cervical Cancer

Uterine cervical cancer is one of the leading causes of cancer-related mortality in women worldwide. Each year, over half a million new cases are estimated, resulting in more than 300,000 deaths. While less-invasive, fertility-preserving surgical procedures can be offered to women in early stages, treatment for locally advanced disease may include radical hysterectomy, primary chemoradiotherapy (CRT) or a combination of these modalities. Concurrent platinum-based chemoradiotherapy regimens remain the first-line treatments for locally advanced cervical cancer. Despite achievements such as the introduction of angiogenesis inhibitors, and more recently immunotherapies, the overall survival of women with persistent, recurrent or metastatic disease has not been extended significantly in the last decades. Furthermore, a broad spectrum of molecular markers to predict therapy response and survival and to identify patients with high- and low-risk constellations is missing. Implementation of these markers, however, may help to further improve treatment and to develop new targeted therapies. This review aims to provide comprehensive insights into the complex mechanisms of cervical cancer pathogenesis within the context of molecular markers for predicting treatment response and prognosis.

Overview of microRNAs as liquid biopsy biomarkers for colorectal cancer sub-type profiling and chemoresistance

Colorectal cancer (CRC) is the third most common cancer worldwide. It has also been demonstrated that over the last ten years the incidence of CRC among younger people below the age of 50 is also increasing. Screening for colorectal cancer is of utmost importance; the rationale behind screening is to target the malignancy and reduce the incidence and mortality of the disease. Diagnostic methods to screen for incidence or relapse are therefore a requisite to detect cancer as early as possible. Scientific findings demonstrate that many deaths are due to lack of screening and therefore early identification will lead to greater survivability. In colorectal cancer, diagnostic tests include liquid biopsy biomarkers. Since the discovery of microRNAs (miRNAs), many studies have demonstrated the relationship between miRNAs and the various sub-types of CRC. Several miRNAs have been identified after analysing serum or plasma samples in patients, and such miRNAs were found to be significantly dysregulated. Such findings place the possibility of miRNAs to be at the epicentre of novel diagnostic techniques for CRC identification and sub-type stratification, including other characteristics associated with CRC development such as patient prognosis. The following review serves to underline the latest findings for miRNAs with such potential for routine diagnostic employment in CRC diagnostics and treatments.

Computational prediction of CRISPR-impaired non-coding regulatory regions

Genome-wide CRISPR screens are becoming more widespread and allow the simultaneous interrogation of thousands of genomic regions. Although recent progress has been made in the analysis of CRISPR screens, it is still an open problem how to interpret CRISPR mutations in non-coding regions of the genome. Most of the tools concentrate on the interpretation of mutations introduced in gene coding regions. We introduce a computational pipeline that uses epigenomic information about regulatory elements for the interpretation of CRISPR mutations in non-coding regions. We illustrate our analysis protocol on the analysis of a genome-wide CRISPR screen in hTERT-RPE1 cells and reveal novel regulatory elements that mediate chemoresistance against doxorubicin in these cells. We infer links to established and to novel chemoresistance genes. Our analysis protocol is general and can be applied on any cell type and with different CRISPR enzymes.

A novel miRNA-based classification model of risks and stages for clear cell renal cell carcinoma patients

Background

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal carcinoma and patients at advanced stage showed poor survival rate. Despite microRNAs (miRNAs) are used as potential biomarkers in many cancers, miRNA biomarkers for predicting the tumor stage of ccRCC are still limitedly identified. Therefore, we proposed a new integrated machine learning (ML) strategy to identify a novel miRNA signature related to tumor stage and prognosis of ccRCC patients using miRNA expression profiles. A multivariate Cox regression model with three hybrid penalties including Least absolute shrinkage and selection operator (Lasso), Adaptive lasso and Elastic net algorithms was used to screen relevant prognostic related miRNAs. The best subset regression (BSR) model was used to identify optimal prognostic model. Five ML algorithms were used to develop stage classification models. The biological significance of the miRNA signature was analyzed by utilizing DIANA-mirPath.

Results

A four-miRNA signature associated with survival was identified and the expression of this signature was strongly correlated with high risk patients. The high risk patients had unfavorable overall survival compared with the low risk group (HR = 4.523, P-value = 2.86e−08). Univariate and multivariate analyses confirmed independent and translational value of this predictive model. A combined ML algorithm identified six miRNA signatures for cancer staging prediction. After using the data balancing algorithm SMOTE, the Support Vector Machine (SVM) algorithm achieved the best classification performance (accuracy = 0.923, sensitivity = 0.927, specificity = 0.919, MCC = 0.843) when compared with other classifiers. Furthermore, enrichment analysis indicated that the identified miRNA signature involved in cancer-associated pathways.

Conclusions

A novel miRNA classification model using the identified prognostic and tumor stage associated miRNA signature will be useful for risk and stage stratification for clinical practice, and the identified miRNA signature can provide promising insight to understand the progression mechanism of ccRCC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04189-2.

Circular RNA in Chemonaive Lymph Node Negative Colon Cancer Patients

Circular RNAs (circRNAs) appear important in tumor progression of colon cancer (CC). We identified an extensive catalog of circRNAs in 181 chemonaive stage I/II colon tumors, who underwent curative surgery between 2007 and 2014. We identified circRNAs from RNAseq data, investigated common biology related to circRNA expression, and studied the association between circRNAs and relapse status, tumor stage, consensus molecular subtypes (CMS), tumor localization and microsatellite instability (MSI). We identified 2606 unique circRNAs. 277 circRNAs (derived from 260 genes) were repeatedly occurring in at least 20 patients of which 153 showed a poor or even negative (R < 0.3) correlation with the expression level of their linear gene. The circular junctions for circSATB2, circFGD6, circKMT2C and circPLEKHM3 were validated by Sanger sequencing. Multiple correspondence analysis showed that circRNAs were often co-expressed and that high diversity in circRNAs was associated with favorable disease-free survival (DFS), which was confirmed by Cox regression analysis (Hazard Ratio (HR) 0.60, 95% CI 0.38-0.97, p = 0.036). Considering individual circRNAs, absence of circMGA was significantly associated with relapse, whereas circSATB2, circNAB1, and circCEP192 were associated with both MSI and CMS. This study represents a showcase of the potential clinical utility of circRNAs for prognostic stratification in patients with stage I-II colon cancer and demonstrated that high diversity in circRNAs is associated with favorable DFS.

Identifying the Signatures and Rules of Circulating Extracellular MicroRNA for Distinguishing Cancer Subtypes

Cancer is one of the most threatening diseases to humans. It can invade multiple significant organs, including lung, liver, stomach, pancreas, and even brain. The identification of cancer biomarkers is one of the most significant components of cancer studies as the foundation of clinical cancer diagnosis and related drug development. During the large-scale screening for cancer prevention and early diagnosis, obtaining cancer-related tissues is impossible. Thus, the identification of cancer-associated circulating biomarkers from liquid biopsy targeting has been proposed and has become the most important direction for research on clinical cancer diagnosis. Here, we analyzed pan-cancer extracellular microRNA profiles by using multiple machine-learning models. The extracellular microRNA profiles on 11 cancer types and non-cancer were first analyzed by Boruta to extract important microRNAs. Selected microRNAs were then evaluated by the Max-Relevance and Min-Redundancy feature selection method, resulting in a feature list, which were fed into the incremental feature selection method to identify candidate circulating extracellular microRNA for cancer recognition and classification. A series of quantitative classification rules was also established for such cancer classification, thereby providing a solid research foundation for further biomarker exploration and functional analyses of tumorigenesis at the level of circulating extracellular microRNA.

Prognostic Value of MicroRNAs in Stage II Colorectal Cancer Patients: A Systematic Review and Meta-Analysis

BACKGROUND

We performed a systematic review and meta-analysis to identify and underline multiple microRNAs (miRNAs) as biomarkers of disease prognosis in stage II colorectal cancer (CRC) patients.

METHODS AND ANALYSIS

This systematic review and meta-analysis study was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The required articles were collected from online bibliographic databases from January 2011 to November 2019 with multiple permutation keywords. Quantitative data synthesis was based on a meta-analysis with pooled data to observe and analyse the outcome measures and effect estimates by using the random effect model. The subgroup analysis was performed from demographic characteristics and the available data.

RESULTS

Eighteen articles were included in this study, 16 of which were incorporated for meta-analysis to examine the stage II CRC prognosis with up- and downregulated miRNA expressions. The pooled hazard ratio (HR) for death in stage II CRC patients was 1.90 (95% confidence interval 1.63-2.211), with a significant p value. A subgroup analysis based on up- or downregulated miRNA expression individually and any deregulated miRNA was also associated with a worse prognosis. The subgroup analysis included parameters such as age, gender, stage II and III combined patients' survival and the repetitive miRNAs (miR21, miR215, miR143-5p, miR106a and miR145) individually.

CONCLUSION

MicroRNAs play a significant role in determining prognosis in stage II CRC patients, with upregulation of miR21, miR215, miR143-5p and miR106a, in particular, portending a worse prognosis. These miRNAs could be considered for further evaluation as biomarkers of prognosis and to guide the decision to administer adjuvant chemotherapy.

Circulating microRNA Panel as a Potential Novel Biomarker for Oral Squamous Cell Carcinoma Diagnosis

Simple Summary

Although early detection of oral squamous cell carcinoma (OSCC) is considered vital, classical biomarkers have shown poor sensitivity and specificity for early detection and monitoring of OSCC. Therefore, identification of reliable and sensitive biomarkers allowing for early detection and monitoring of OSCC is of the utmost importance. In this study, we successfully identified significantly upregulated or downregulated microRNAs in OSCC patients, and reported that a combination of six microRNAs could distinguish between OSCC and the control group with a higher degree of accuracy. Furthermore, compared with serum squamous cell carcinoma (SCC) antigen, the miRNA panel reflected the presence of OSCC accurately. The present results suggest that the combined microRNA panel based on serum microRNA levels shows potential as a novel diagnostic biomarker of OSCC.

Abstract

A lack of reliable biomarkers for oral squamous cell carcinoma (OSCC) poses a major clinical issue. The sensitivity and specificity of classical serum tumor markers, such as the squamous cell carcinoma antigen (SCC-Ag), are quite poor, especially for early detection. This study aimed to identify specific serum miRNAs potentially serving as OSCC biomarkers. The expression levels of candidate miRNAs in serum samples from 40 OSCC patients and 40 healthy controls were quantitatively analyzed via microarray and reverse transcription PCR (RT-PCR) analyses. To enhance the accuracy of detection, we used Fisher’s linear discriminant analysis to establish a diagnostic model that incorporated a combination of selected miRNAs. Consequently, miR-19a and miR-20a were significantly upregulated in the patient group (p = 0.014 and 0.036, respectively), whereas miR-5100 was downregulated (p = 0.001). We found that a combination of six miRNAs (miR-24, miR-20a, miR-122, miR-150, miR-4419a, and miR-5100) could distinguish between OSCC and the control group with a higher degree of accuracy (Area Under the Curve, AUC: 0.844, sensitivity: 55%, and specificity: 92.5%). Furthermore, compared to serum SCC antigen, the 6-miRNA panel could accurately detect the presence of OSCC. The present specific miRNAs panel may serve as a novel candidate biomarker of oral cancer.

Circulating microRNAs: Biomarkers of disease

MicroRNAs are a class of endogenous noncoding single-stranded RNA molecules with approximately 20-24 nucleotides and are associated with a broad range of biological processes. Researchers found that microRNAs are abundant in tissues, and more importantly, there are also trace circulating microRNAs that exist in biological fluids. In recent years, circulating microRNAs had emerged as promising diagnostic and prognostic biomarkers for the noninvasive detection of diseases with high specificity and sensitivity. More importantly, specific microRNA expression signatures reflect not only the existence of early-stage diseases but also the dynamic development of advanced-stage diseases, disease prognosis prediction, and drug resistance. To date, an increasing number of potential miRNA biomarkers have been reported, but their practical application prospects are still unclear. Therefore, microRNAs, as potential diagnostic and prognostic biomarkers in a variety of diseases, need to be updated, as they are of great importance in the diagnosis, prognosis and prediction of therapeutic responses. In this review, we summary our current understanding of microRNAs as potential biomarkers in the major diseases (e.g., cancers and cardio-cerebrovascular diseases), which provide the basis for the design of diagnosis and treatment plan and the improvement of the cure rate.

Construction and validation of a novel prognostic signature of microRNAs in lung adenocarcinoma

MicroRNA (miRNA, miR) has been reported to be highly implicated in a wide range of biological processes in lung cancer (LC), and identification of differentially expressed miRNAs between normal and LC samples has been widely used in the discovery of prognostic factors for overall survival (OS) and response to therapy. The present study was designed to develop and evaluate a miRNA-based signature with prognostic value for the OS of lung adenocarcinoma (LUAD), a common histologic subtype of LC. In brief, the miRNA expression profiles and clinicopathological factors of 499 LUAD patients were collected from The Cancer Genome Atlas (TCGA) database. Kaplan-Meier (K-M) survival analysis showed significant correlations between differentially expressed miRNAs and LUAD survival outcomes. Afterward, 1,000 resample LUAD training matrices based on the training set was applied to identify the potential prognostic miRNAs. The least absolute shrinkage and selection operator (LASSO) cox regression analysis was used to constructed a six-miRNA based prognostic signature for LUAD patients. Samples with different risk scores displayed distinct OS in K-M analysis, indicating considerable predictive accuracy of this signature in both training and validation sets. Furthermore, time-dependent receiver operating characteristic (ROC) analysis demonstrated the nomogram achieved higher predictive accuracy than any other clinical variables after incorporating the clinical information (age, sex, stage, and recurrence). In the stratification analysis, the prognostic value of this classifier in LUAD patients was validated to be independent of other clinicopathological variables, such as age, gender, tumor recurrence, and early stage. Gene set annotation analyses were also conducted through the Hallmark gene set and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, indicating target genes of the six miRNAs were positively related to various molecular pathways of cancer, such as hallmark UV response, Wnt signaling pathway and mTOR signaling pathway. In addition, fresh cancer tissue samples and matched adjacent tissue samples from 12 LUAD patients were collected to verify the expression of miR-582's target genes in the model, further revealing the potential relationship between SOX9, RASA1, CEP55, MAP4K4 and LUAD tumorigenesis, and validating the predictive value of the model. Taken together, the present study identified a robust signature for the OS prediction of LUAD patients, which could potentially aid in the individualized selection of therapeutic approaches for LUAD patients.

Identification of an alternative splicing signature as an independent factor in colon cancer

BACKGROUND

Colon cancer is a common malignant tumor with a poor prognosis. Abnormal alternative splicing (AS) events played a part in the occurrence and metastasis of the tumor. We aimed to develop a survival-associated AS signature in colon cancer.

METHODS

The Percent Spliced In values of AS events were available in The Cancer Genome Atlas (TCGA) SpliceSeq database. Univariate Cox analysis was carried out to detect the prognosis-related AS events. We created a predictive model on account of the survival-associated AS events, which was further validated with a training-testing group design. Kaplan-Meier analysis was applied to assess patient survival. The area under curve (AUC) of receiver operating characteristic (ROC) was performed to evaluate the predictive values of this model. Meanwhile, the clinical relevance of the signature and its regulatory relationship with splicing factors (SFs) were also evaluated.

RESULTS

In total, 2132 survival-related AS events were identified from colon cancer samples. We developed an eleven-AS signature, in which the 5-year AUC value was 0.911. Meanwhile, the AUC values at five years were 0.782 and 0.855 in the testing and entire cohort, respectively. Multivariate Cox regression displayed that the T category and the risk score of the signature were independent risk factors of colon cancer survival. Also, we constructed an SFs-AS network based on 11 SFs and 48 AS events.

CONCLUSIONS

We identified an eleven-AS signature of colon cancer. This signature could be treated as an independent prognostic factor.

lncRNA SNHG8 promotes aggressive behaviors of nasopharyngeal carcinoma via regulating miR-656-3p/SATB1 axis

BACKGROUND

Long non-coding RNA (lncRNA) has been proposed to regulate tumorigenesis, however, the role of small nucleolar RNA host gene 8 (SNHG8) in nasopharyngeal carcinoma (NPC) remains unclear.

METHODS

Levels of SNHG8 in NPC tissues and cells were analyzed with real-time quantitative PCR method. Cell counting kit-8 assay, colony formation assay, wound-healing assay, and transwell invasion assay were performed to detect cell viability, migration, and invasion. Luciferase activity assay and RIP assay were performed to explore relationships among SNHG8, microRNA-656-3p (miR-656-3p), and special AT-rich sequence-binding protein 1 (SATB1).

RESULTS

We found SNHG8 level was increased expression in NPC tissues and cells.In vitro assays revealed that SNHG8 stimulates NPC cell proliferation, colony formation, cell migration, and cell invasion. In vivo assay confirmed knockdown of SNHG8 could hamper tumor growth. Furthermore, we showed SNHG8 serves as a sponge for miR-656-3p to regulate SATB1 expression, and participated in NPC progression.

CONCLUSIONS

In summary, our work indicated the importance of SNHG8 in NPC progression, which provided novel treatment methods for NPC.

A seven-gene signature model predicts overall survival in kidney renal clear cell carcinoma

Background

Kidney renal clear cell carcinoma (KIRC) is a potentially fatal urogenital disease. It is a major cause of renal cell carcinoma and is often associated with late diagnosis and poor treatment outcomes. More evidence is emerging that genetic models can be used to predict the prognosis of KIRC. This study aimed to develop a model for predicting the overall survival of KIRC patients.

Results

We identified 333 differentially expressed genes (DEGs) between KIRC and normal tissues from the Gene Expression Omnibus (GEO) database. We randomly divided 591 cases from The Cancer Genome Atlas (TCGA) into training and internal testing sets. In the training set, we used univariate Cox regression analysis to retrieve the survival-related DEGs and futher used multivariate Cox regression with the LASSO penalty to identify potential prognostic genes. A seven-gene signature was identified that included APOLD1, C9orf66, G6PC, PPP1R1A, CNN1G, TIMP1, and TUBB2B. The seven-gene signature was evaluated in the training set, internal testing set, and external validation using data from the ICGC database. The Kaplan-Meier analysis showed that the high risk group had a significantly shorter overall survival time than the low risk group in the training, testing, and ICGC datasets. ROC analysis showed that the model had a high performance with an AUC of 0.738 in the training set, 0.706 in the internal testing set, and 0.656 in the ICGC external validation set.

Conclusion

Our findings show that a seven-gene signature can serve as an independent biomarker for predicting prognosis in KIRC patients.

Protective effects of dexmedetomidine on hypoxia/reoxygenation injury in cardiomyocytes by regulating the CHOP signaling pathway

Hypoxia/reoxygenation (H/R) injury in myocardial cells occurs frequently during cardiac surgery and affects the prognosis of patients. The present study aimed to investigate the protective effects of dexmedetomidine (Dex) on H/R injury and its association with the C/EBP-homologous protein (CHOP) signaling pathway. An H/R model was constructed in H9C2 cells to investigate the effects of Dex on H/R injury. Cell viability, apoptosis and lactate dehydrogenase (LDH) levels were determined by MTT, flow cytometry and 2,4-dinitrophenylhydrazine colorimetric assays, respectively. The expression levels of inflammatory factors were measured by reverse transcription-quantitative PCR (RT-qPCR), and CHOP and glucose-regulated protein-78 (Grp78) expression levels were detected by RT-qPCR and western blotting. CHOP was overexpressed or knocked down to detect the cell viability, apoptosis, LDH level and the expression levels of inflammatory factors and Grp78. The results demonstrated that in the H/R group, cell viability was lower and apoptosis was higher, and that higher levels of LDH and inflammatory factors were present compared with those in the Dex+H/R group. Silencing of CHOP significantly reversed the H/R-reduced cell viability, high apoptotic rate and LDH levels, as well as the elevated expression levels of inflammatory factors and Grp78 caused by H/R injury, whereas the overexpression of CHOP inhibited cell viability and promoted apoptosis, elevated LDH level and expression of inflammatory factors and Grp78 compared with the negative control. Additionally, pretreatment with Dex significantly alleviated the H/R injury; thus, Dex may protect H9C2 cells against H/R induced cell injury, possibly by suppressing the CHOP signaling pathway.

The Construction and Comprehensive Prognostic Analysis of the LncRNA-Associated Competitive Endogenous RNAs Network in Colorectal Cancer

Competing endogenous RNAs (ceRNAs) are a newly proposed RNA interaction mechanism that has been associated with the tumorigenesis, metastasis, diagnosis, and predicting survival of various cancers. In this study, we constructed a ceRNA network in colorectal cancer (CRC). Then, we sought to develop and validate a composite clinicopathologic–genomic nomogram using The Cancer Genome Atlas (TCGA) database. To construct the ceRNA network in CRC, we analyzed the mRNAseq, miRNAseq data, and clinical information from TCGA database. LncRNA, miRNA, and mRNA signatures were identified to construct risk score as independent indicators of the prognostic value in CRC patients. A composite clinicopathologic–genomic nomogram was developed to predict the overall survival (OS). One hundred sixty-one CRC-specific lncRNAs, 97 miRNAs, and 161 mRNAs were identified to construct the ceRNA network. Multivariate Cox proportional hazards regression analysis indicated that nine-lncRNA signatures, eight-miRNA signatures, and five-mRNA signatures showed a significant prognostic value for CRC. Furthermore, a clinicopathologic–genomic nomogram was constructed in the primary cohort, which performed well in both the primary and validation sets. This study presents a nomogram that incorporates the CRC-specific ceRNA expression profile, clinical features, and pathological factors, which demonstrate its excellent differentiation and risk stratification in predicting OS in CRC patients.

MicroRNAs in Colon and Rectal Cancer - Novel Biomarkers from Diagnosis to Therapy

Colorectal cancer (CRC) is one of the most common cancers and a significant cause of tumor- related deaths worldwide. Traditional biomarkers, such as CEA and CA199, are not sensitive enough to provide useful information for early diagnosis and treatment and are rather used to track the clinical progression of the disease. There is growing evidence that microRNAs (miRNA) are potentially superior to traditional biomarkers as promising non-invasive biomarkers for the timely diagnosis and prediction of prognosis or treatment response in the management of CRC. In this review, the latest studies on the dysregulation of miRNAs expression in CRC and the potential for miRNAs to serve as biomarkers were collected. Given the limitations of miRNA, as discussed in this paper, its clinical applications as a diagnostic biomarker should be limited to use in combination with other biomarkers. Further research is necessary to elucidate the clinical applications of miRNA in therapy for CRC.

Mir-5100 Mediates Proliferation, Migration and Invasion of Oral Squamous Cell Carcinoma Cells Via Targeting SCAI

PURPOSE

We aimed to investigate the role of microRNA-5100 (miRNA-5100) in oral squamous cell carcinoma (OSCC) and its underlying mechanisms.Material/Methods: The expression of miR-5100 and suppressor of cancer cell invasion (SCAI) in OSCC cell lines were examined. A luciferase reporter assay was applied to confirm the combination between miR-5100 and SCAI. Then, miR-5100 inhibitor or small hairpin RNA (shRNA)-SCAI were transfected into cells. Cell Counting Kit-8 assay was executed for testing cell proliferation ability. Flow cytometry assay was exploited for measuring cell cycle. Invasion and migration of OSCC cells were assessed using Transwell assay and wound healing assay. The expression of proteins were detected using western blotting.

RESULTS

The results demonstrated that the level of miR-5100 was upregulated while SCAI was downregulated in OSCC cells. SCAI was verified as a direct target of miR-5100. MiR-5100 silencing suppressed proliferation of OSCC cells, increased cells in the G1 and G2 phases, and reduced those in the S phase, which was reversed after transfection with shRNA-SCAI. Moreover, miR-5100 inhibitor downregulated the expression of cyclin-dependent kinase-2 (CDK-2) and cyclinD1, accompanied by upregulation in p27 expression, whereas SCAI silencing had the opposite results. The invasion and migration abilities of OSCC cells were reduced after treatment with miR-5100 inhibitor, whereas SCAI silencing suppressed the effects of miR-5100 inhibitor on OSCC cell behaviors.

CONCLUSION

These findings suggested that miR-5100 silencing inhibit proliferation, invasion and migration of OSCC cells via upregulating the expression of SCAI, which provides theoretical basis and treatment strategies for the treatment of OSCC.

Identification of a novel microRNA recurrence-related signature and risk stratification system in breast cancer

Increasing evidence has revealed that microRNAs (miRNAs) play vital roles in breast cancer (BC) prognosis. Thus, we aimed to identify recurrence-related miRNAs and establish accurate risk stratification system in BC patients. A total of 381 differentially expressed miRNAs were confirmed by analyzing 1044 BC tissues and 102 adjacent normal samples from The Cancer Genome Atlas (TCGA). Then, based on the association between each miRNAs and disease-free survival (DFS), we identified miRNA recurrence-related signature to construct a novel prognostic nomogram using Cox regression model. Target genes of the four miRNAs were analyzed via Gene Ontology and KEGG pathway analyses. Time-dependent receiver operating characteristic analysis indicated that a combination of the miRNA signature and tumor-node-metastasis (TNM) stage had better predictive performance than that of TNM stage (0.710 vs 0.616, P<0.0001). Furthermore, risk stratification analysis suggested that the miRNA-based model could significantly classify patients into the high- and low-risk groups in the two cohorts (all P<0.0001), and was independent of other clinical features. Functional enrichment analysis demonstrated that the 46 target genes mainly enrichment in important cell biological processes, protein binding and cancer-related pathways. The miRNA-based prognostic model may facilitate individualized treatment decisions for BC patients.

Serum miR-626 and miR-5100 are Promising Prognosis Predictors for Oral Squamous Cell Carcinoma

Although serum microRNAs (miRNAs) are currently being considered as promising noninvasive biomarkers for cancers, their role in the prognosis of oral squamous cell carcinoma (OSCC) has not been elucidated. Here we aimed to identify serum miRNA biomarkers that could be used as prognosis predictors of OSCC.

Methods: A cohort of 260 serum miRNA samples was assessed in a three-step approach that included a screening stage, a training stage, and a testing stage. The correlation between prognosis of OSCC and the miRNAs expression was comprehensively analyzed.

Results: A two-miRNA signature involving miR-626 and miR-5100 has been developed. Patients defined to be high-risk group by the two-miRNA signature had significantly shortened median survival time compared with the low-risk group. In multivariate analysis, this two-miRNA signature was independently predictive of survival, and achieved a superior predictive value compared with that of traditional clinicopathologic factors such as pathology grade as well as tumor and node metastasis (TNM) stage. An integrated prognostic model combining the TNM stage and miRNA signature displayed the highest prognostic performance (AUC value: 0.787, specificity: 0.884, sensitivity: 0.573) compared to the TNM stage-alone (AUC value: 0.630, specificity: 0.526, sensitivity: 0.733) or miRNA signature-alone model (AUC value: 0.771, specificity: 0.768, sensitivity: 0.773). In addition, we found that OSCC tumor cells not only expressed a high level of these two miRNAs, but also secreted certain miRNAs into the extracellular environment, suggesting these miRNAs may originate from tumor cells.

Conclusion: In our study, we established a two-miRNA signature that was strongly and independently associated with prognosis in OSCC, and may serve as a promising prognosis predictor.

Systematic Analysis of Survival-Associated Alternative Splicing Signatures in Gastrointestinal Pan-Adenocarcinomas

BACKGROUND

Gastrointestinal pan-adenocarcinomas, which mainly include adenocarcinomas of the esophagus, stomach, colon, and rectum, place a heavy burden on society owing to their poor prognoses. Since aberrant alternative splicing (AS) are starting to be considered as efficacious signatures for tumor prognosis predicting and therapeutic targets, systematic analysis of AS events is urgent.

METHODS

Prognosis-related AS events were selected by using univariate COX regression analysis. Gene functional enrichment analysis revealed the pathways enriched by prognosis-related AS. Then, prognostic signatures based on AS events were developed for prognosis prediction. Potential mechanism to regulate splicing events by splicing factors was analyzed via Pearson correlation and regulatory networks were constructed.

FINDINGS

A total of 967, 918, 674, and 406 AS events were identified as prognosis-related AS events in esophagus, stomach, colon, and rectum adenocarcinomas, respectively. Survival-associated AS events were distinguishing in the four subtypes of adenocarcinoma. Furthermore, computational algorithm results indicated that perturbation of ribosome and ubiquitin-mediated proteolysis pathways were the potential molecular mechanisms corresponding to inferior prognoses. Most notably, several prognostic signatures based on AS events displayed moderate performance in prognosis predicting. The area under curve values of the time-dependent receiver operating characteristic were 0.961, 0.871, 0.870, and 0.890 in esophagus, stomach, colon, and rectum adenocarcinomas. Survival-associated splicing factors were submitted to construct the AS regulatory network, which could be an underlying mechanism of AS events.

INTERPRETATION

AS may could be ideal indiactors in the prognosis of gastrointestinal pan-adenocarcinomas. Exploring interesting splicing regulatory networks is conducive to solve the puzzles of AS.