A Five-microRNA Signature as Prognostic Biomarker in Colorectal Cancer by Bioinformatics Analysis

Circulating miRNA Signature Predicts Cancer Incidence in Lynch Syndrome-A Pilot Study

Lynch syndrome (LS) is the most common autosomal dominant cancer syndrome and is characterized by high genetic cancer risk modified by lifestyle factors. This study explored whether a circulating miRNA (c-miR) signature predicts LS cancer incidence within a 4-year prospective surveillance period. To gain insight how lifestyle behavior could affect LS cancer risk, we investigated whether the cancer-predicting c-miR signature correlates with known risk-reducing factors such as physical activity, body mass index (BMI), dietary fiber, or NSAID usage. The study included 110 c-miR samples from LS carriers, 18 of whom were diagnosed with cancer during a 4-year prospective surveillance period. Lasso regression was utilized to find c-miRs associated with cancer risk. Individual risk sum derived from the chosen c-miRs was used to develop a model to predict LS cancer incidence. This model was validated using 5-fold cross-validation. Correlation and pathway analyses were applied to inspect biological functions of c-miRs. Pearson correlation was used to examine the associations of c-miR risk sum and lifestyle factors. hsa-miR-10b-5p, hsa-miR-125b-5p, hsa-miR-200a-3p, hsa-miR-3613-5p, and hsa-miR-3615 were identified as cancer predictors by Lasso, and their risk sum score associated with higher likelihood of cancer incidence (HR 2.72, 95% confidence interval: 1.64-4.52, C-index = 0.72). In cross-validation, the model indicated good concordance with the average C-index of 0.75 (0.6-1.0). Coregulated hsa-miR-10b-5p, hsa-miR-125b-5p, and hsa-miR-200a-3p targeted genes involved in cancer-associated biological pathways. The c-miR risk sum score correlated with BMI (r = 0.23, P < 0.01). In summary, BMI-associated c-miRs predict LS cancer incidence within 4 years, although further validation is required.

PREVENTION RELEVANCE

The development of cancer risk prediction models is key to improving the survival of patients with LS. This pilot study describes a serum miRNA signature-based risk prediction model that predicts LS cancer incidence within 4 years, although further validation is required.

An Updated Review on Molecular Biomarkers in Diagnosis and Therapy of Colorectal Cancer

Colorectal cancer is one of the most common cancer types worldwide. Since colorectal cancer takes time to develop, its incidence and mortality can be treated effectively if it is detected in its early stages. As a result, non-invasive or invasive biomarkers play an essential role in the early diagnosis of colorectal cancer. Many experimental studies have been carried out to assess genetic, epigenetic, or protein markers in feces, serum, and tissue. It may be possible to find biomarkers that will help with the diagnosis of colorectal cancer by identifying the genes, RNAs, and/or proteins indicative of cancer growth. Recent advancements in the molecular subtypes of colorectal cancer, DNA methylation, microRNAs, long noncoding RNAs, exosomes, and their involvement in colorectal cancer have led to the discovery of novel biomarkers. In small-scale investigations, most biomarkers appear promising. However, large-scale clinical trials are required to validate their effectiveness before routine clinical implementation. Hence, this review focuses on small-scale investigations and results of big data analysis that may provide an overview of the biomarkers for the diagnosis, therapy, and prognosis of colorectal cancer.

MicroRNA-183 cluster: a promising biomarker and therapeutic target in gastrointestinal malignancies

Small non-coding RNAs (microRNA, miR), powerful epigenetic regulators, were found involved in the regulation of most biological functions via post-translational inhibition of protein expression. Increased expression of pro-oncogenic miRs (known as miR cancer biomarkers) and inhibition of pro-apoptotic miR expression have been demonstrated in different tumors. The recently identified miR-183 was found implicated in gastrointestinal tumor metabolism regulation. Elevated miR-183 expression and cancer-promoting effects were reported in esophageal and colorectal cancers, which was partially contradicted by controversial data observed in gastric cancers. Anti-cancer effect of miR-183 in gastric cancer cells was associated with the Bim-1 and Ezrin genes regulation. Many studies indicated that miR-183 can inhibit tumor suppressor genes in most cell lines, promoting tumor cell proliferation and migration. Increased miR-183 level results in the downregulation of FOXO1, PDCD4, and other tumor suppressor genes in gastrointestinal tumor cells. MiR-183 also influences the signaling of PI3K/AKT/mTOR, Wnt/β-catenin, and Bcl-2/p53 signaling pathways. Mir-183 inhibits apoptosis and autophagy, and promotes epithelial-to-mesenchymal transition, cancer cell proliferation, and migration. Accordingly, gastrointestinal cancer occurrence, development of chemoradiotherapy resistance, recurrence/metastasis, and prognosis were associated with miR-183 expression. The current study assessed reported miR-183 functions and signaling, providing new insights for the diagnosis and treatment of gastrointestinal malignancies.

A nine-gene signature as prognostic biomarker in gastric cancer by bioinformatics analysis

PURPOSE

The prognosis of advanced gastric cancer (GC) remains poor. It is urgent and necessary to find suitable prognostic markers. miR-619-5p is highly expressed in GC. However, the value of miR-619-5p and its target genes as prognostic biomarkers of GC is unclear.

METHODS

RT-PCR was performed to verify the expression of miR-619-5p in GC cell lines and their exosomes. Western blotting and transmission electron microscope were used to identify exosomes. The target genes of miR-619-5p were predicted by RNA22 and TargetScan. The differentially expressed genes (DEGs) and prognosis-related genes (PRGs) were obtained using The Cancer Genome Atlas (TCGA) database. The DAVID database was used to analyse pathway enrichment and functional annotation of common target genes. The STRING database and Cytoscape software were used to screen key genes and visualize their functional modules. The survival analysis was conducted using TCGA and Kaplan-Meier Plotter (KMP) databases. Finally, a prognostic model was constructed on the foundation of the key genes to assess the reliability of the screening process.

RESULTS

The expression of miR-619-5p in GC cells and their exosomes was proved to be significantly higher than that in normal cell lines. There are 129 common target genes involved in 3 pathways and 28 functional annotations. Finally, nine key target genes of GC (BRCA1, RAD51, KIF11, ERCC6L, BRIP1, TIMELESS, CDC25A, CLSPN and NCAPG2) were identified, and a prognostic model was successfully constructed with a good predictive ability.

CONCLUSIONS

The model of 9-gene signature could effectively predict the prognosis of GC, and have great potential to be novel prognostic factors and therapeutic targets for patients with GC.

A novel miRNA-based signature as predictive tool of survival outcome of colorectal cancer patients

It is great significance of identifying valuable biomarkers for early diagnosis and prognostic prediction of colorectal cancer (CRC) patients. This study aimed at developing and validating a miRNAs-based signature as prognostic tool for CRC patients. The miRNA expression profile of 624 CRC samples (613 tumor tissues and 11 normal tissues) was analyzed, and 523 differentially expressed miRNAs (DEmiRNAs) were identified, in which 191 were downregulated and 332 were upregulated. All patients were randomly divided into a training cohort (N = 308) and an internal validation cohort (N = 200). Using the least absolute shrinkage and selection operator (LASSO) and Cox regression model, a prognostic signature of 10 miRNAs (hsa-miR-149-5p, hsa-miR-193b-5p, hsa-miR-193a-3p, hsa-miR-3677-3p, hsa-miR-29a-3p, hsa-miR-200c-5p, hsa-miR-200a-5p, hsa-miR-6854-5p, hsa-miR-216a-5p and hsa-miR-891a-5p) was developed in the training cohort. The risk score was calculated by the product of the expression level and the coefficients of each miRNA. The prognostic value of 10 miRNAs-based signature for CRC patients was tested and validated. Survival analysis indicated that high-risk patients (> 1.10) had a worse overall survival (OS) than low-risk (≤ 1.10) patients (5-year OS rate for training cohort: 59.3% vs. 78.9%, p < .001; validation cohort: 48.3% vs. 69.3%, p = .011). The miRNA-based signature was an independent prognostic factor for CRC patients (HR for training cohort:2.476, 95% CI:1.202-5.098, p = .014; HR for validation cohort:2.050, 95% CI:1.087-3.869, p = .027). The AUC values for 3-year and 5-year OS prediction were 0.718 and 0.784 in the training cohort, 0.659 and 0.614 in the validation cohort, respectively. The 10 miRNAs-based signature provided a proper prognostic stratification for CRC patients, and it might be a promising tool for survival prediction.

Prognosis-related metabolic genes in the development of colorectal cancer progress and perspective

Colorectal cancer (CRC) is one of the most commonplace malignant tumors in the world. The occurrence and development of CRC are involved in numerous events. Metabolic reprogramming is one of the hallmarks of cancer and is convoluted and associated with carcinogenesis. Lots of metabolic genes are involved in the occurrence and progression of CRC. Study methods combining tumor genomics and metabolomics are more likely to explore this field in depth. In this mini-review, we make the latest progress and future prospects into the different molecular mechanisms of seven prognosis-related metabolic genes, we screened out in previous research, involved in the occurrence and development of CRC.

Common Genetic Factors and Pathways in Alzheimer's Disease and Ischemic Stroke: Evidences from GWAS

Alzheimer's disease (AD) and ischemic stroke (IS) are common neurological disorders, and the comorbidity of these two brain diseases is often seen. Although AD and IS were regarded as two distinct disease entities, in terms of different etiologies and clinical presentation, recent genome-wide association studies (GWASs) revealed that there were common risk genes between AD and IS, indicating common molecular pathways and their common pathophysiology. In this review, we summarize AD and IS risk single nucleotide polymorphisms (SNPs) and their representative genes from the GWAS Catalog database, and find thirteen common risk genes, but no common risk SNPs. Furthermore, the common molecular pathways associated with these risk gene products are summarized from the GeneCards database and clustered into inflammation and immunity, G protein-coupled receptor, and signal transduction. At least seven of these thirteen genes can be regulated by 23 microRNAs identified from the TargetScan database. Taken together, the imbalance of these molecular pathways may give rise to these two common brain disorders. This review sheds light on the pathogenesis of comorbidity of AD and IS, and provides molecular targets for disease prevention, manipulation, and brain health maintenance.

Identification of neoplasm-specific signatures of miRNA interactions by employing a systems biology approach

MicroRNAs represent major regulatory components of the disease epigenome and they constitute powerful biomarkers for the accurate diagnosis and prognosis of various diseases, including cancers. The advent of high-throughput technologies facilitated the generation of a vast amount of miRNA-cancer association data. Computational approaches have been utilized widely to effectively analyze and interpret these data towards the identification of miRNA signatures for diverse types of cancers. Herein, a novel computational workflow was applied to discover core sets of miRNA interactions for the major groups of neoplastic diseases by employing network-based methods. To this end, miRNA-cancer association data from four comprehensive publicly available resources were utilized for constructing miRNA-centered networks for each major group of neoplasms. The corresponding miRNA-miRNA interactions were inferred based on shared functionally related target genes. The topological attributes of the generated networks were investigated in order to detect clusters of highly interconnected miRNAs that form core modules in each network. Those modules that exhibited the highest degree of mutual exclusivity were selected from each graph. In this way, neoplasm-specific miRNA modules were identified that could represent potential signatures for the corresponding diseases.

Membrane-associated RING-CH protein (MARCH8) is a novel glycolysis repressor targeted by miR-32 in colorectal cancer

BACKGROUND

Colorectal cancer (CRC) is the third most common cancer and leading cause of cancer-related deaths worldwide. Aberrant cellular metabolism is a hallmark of cancer cells, and disturbed metabolism showed clinical significance in CRC. The membrane-associated RING-CH 8 (MARCH8) protein, the first MARCH E3 ligase, plays an oncogenic role and serves as a prognostic marker in multiple cancers, however, the role of MARCH8 in CRC is unclear. In the present study, we aimed to investigate the biomarkers and their underlying mechanism for CRC.

METHOD

In this study, we first examined the function of MARCH8 in CRC by analysing public database. Besides, we performing gene silencing studies and generating cellular overexpression and xenograft models. Then its protein substrate was identified and validated. In addition, the expression of MARCH8 was investigated in tissue samples from CRC patients, and the molecular basis for decreased expression was analysed.

RESULTS

Systematic analysis reveals that MARCH8 is a beneficial prognostic marker in CRC. In CRC, MARCH8 exhibited tumor-suppressive activity both in vivo and in vitro. Furthermore, we found that MARCH8 is negatively correlated with hexokinase 2 (HK2) protein in CRC patients. MARCH8 regulates glycolysis and promotes ubiquitination-mediated proteasome degradation to reduces HK2 protein levels. Then HK2 inhibitor partially rescues the effect of MARCH8 knockdown in CRC. Poised chromatin and elevated miR-32 repressed MARCH8 expression.

CONCLUSION

In summary, we propose that in CRC, poised chromatin and miR-32 decrease the expression of MARCH8, further bind and add ubiquitin, induce HK2 degradation, and finally repress glycolysis to promote tumor suppressors in CRC.

Transcriptomic signature associated with RNA-binding proteins for survival stratification of laryngeal cancer

RNA-binding proteins (RBPs) have been suggested as important prognostic indicators in different human cancers. This study was designed to search the prognostic value of RBPs of laryngeal squamous cell carcinoma (LSCC). Differentially expressed RBPs (DERBPs) were screened via The Cancer Genome Atlas (TCGA). Bioinformatics methods were used to identify prognostic DERBPs. Expression profiling of training cohort were calculated to develop a transcriptomic signature, which was validated by three independent cohorts (TCGA cohort, GSE65858 cohort and GSE27020 cohort). We identified DERBPs and a set of signatures (GTPBP3, KHDRBS3 and RBM38) were confirmed as prognosis-related hub DERBPs in LSCC, which was also tested and verified by bioinformatics method and molecular biology experiment. The role of immune cell infiltration and drug resistance between subgroups was explored. Furthermore, the risk score based on transcriptomic signature was turned out to be an independent prognostic indicator for LSCC. Finally, a nomogram for further clinical application was established. Our study demonstrated that the transcriptomic signature we constructed could serve as a novel therapeutic target and biomarker for LSCC from the perspective of RBPs.

A Ferroptosis-Related Gene Signature for Predicting Survival and Immunotherapy Effect in Renal Cancer

Background

Most recently, no efficient prognostic indictor is present for kidney cancer. Thus, we aimed to build and validate a new prognostic gene signature for renal cancer patients using the Cancer Genomic Atlas (TCGA).

Methods

A “time-dependent receiver operating characteristic (tROC)” curve was generated, and a log-rank test was performed to assess the performance of the biomarker in training and validation. A “ferroptosis-related gene signature” was developed. In different training and validations sets, tROC and log-rank test were used to validate the biomarker's performance.

Results

In the training set with a P value less than 0.01 and the validation set, the “gene signature” was significantly correlated with survival. Eventually, it was found that the ferroptosis-related gene signature was directly correlated with immune score and the score of tumor mutation, suggesting its role in predicting response to immunotherapy.

Conclusion

We developed and validated a “ferroptosis-related gene signature” that can be sued for patients with kidney cancer. It can also assist in facilitating the plan for treatment and risk stratification.

High Levels of Tumor miR-187-3p—A Potential Tumor-Suppressor microRNA—Are Correlated with Poor Prognosis in Colorectal Cancer

Background: The microRNA miR-187-3p plays antitumor roles in a variety of cancers. We and others have previously identified miR-187-3p as a potential tumor suppressor in colorectal cancer (CRC), but there are also reports revealing that high miR-187-3p levels are associated with poor prognosis among CRC patients. This study further investigated the clinicopathological significance of miR-187-3p in CRC. Methods: MiR-187-3p levels in paired polyp/CRC/normal specimens or primary CRC/liver metastasis specimens were determined by qPCR, and correlated with the patient’s clinicopathological and postoperative survival data. The clinical findings were validated using our validation cohort and data obtained from the TCGA or GEO databases. The functional effects of miR-187-3p were investigated through its overexpression in CRC cell lines. Results: MiR-187-3p was significantly repressed in colorectal polyps and CRC when compared to adjacent normal tissue. Overexpression of miR-187-3p in CRC cell lines impaired colony formation, cell migration, and invasion, and induced chemosensitivity. Clinical analysis revealed that despite miR-187-3p being repressed in CRC, high tumor miR-187-3p levels were positively correlated with tumor stage and disease recurrence. Further analysis showed that miR-187-3p levels were lower in metastatic specimens when compared to paired primary CRC, suggesting that high tumor miR-187-3p levels resulted from the dissemination of metastatic tumor cells. Tumor miR-187-3p levels were positively correlated with peripheral inflammation-related blood markers. Finally, SPRY1 was identified as a novel target gene of miR-187-3p, and was involved in miR-187-3p-impaired CRC metastasis. Conclusions: This study demonstrated that in spite of its repression and role as a tumor suppressor in CRC, high levels of miR-187-3p in tumors were correlated with poor prognosis and higher levels of peripheral inflammation-related blood markers.

Identifying potential prognosis markers in hepatocellular carcinoma via integrated bioinformatics analysis and biological experiments

Background: Hepatocellular carcinoma is one kind of clinical common malignant tumor with a poor prognosis, and its pathogenesis remains to be clarified urgently. This study was performed to elucidate key genes involving HCC by bioinformatics analysis and experimental evaluation.

Methods: We identified common differentially expressed genes (DEGs) based on gene expression profile data of GSE60502 and GSE84402 from the Gene Expression Omnibus (GEO) database. Gene Ontology enrichment analysis (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, REACTOME pathway enrichment analysis, and Gene Set Enrichment Analysis (GSEA) were used to analyze functions of these genes. The protein-protein interaction (PPI) network was constructed using Cytoscape software based on the STRING database, and Molecular Complex Detection (MCODE) was used to pick out two significant modules. Hub genes, screened by the CytoHubba plug-in, were validated by Gene Expression Profiling Interactive Analysis (GEPIA) and the Human Protein Atlas (HPA) database. Then, the correlation between hub genes expression and immune cell infiltration was evaluated by Tumor IMmune Estimation Resource (TIMER) database, and the prognostic values were analyzed by Kaplan-Meier plotter. Finally, biological experiments were performed to illustrate the functions of RRM2.

Results: Through integrated bioinformatics analysis, we found that the upregulated DEGs were related to cell cycle and cell division, while the downregulated DEGs were associated with various metabolic processes and complement cascade. RRM2, MAD2L1, MELK, NCAPG, and ASPM, selected as hub genes, were all correlated with poor overall prognosis in HCC. The novel RRM2 inhibitor osalmid had anti-tumor activity, including inhibiting proliferation and migration, promoting cell apoptosis, blocking cell cycle, and inducing DNA damage of HCC cells.

Conclusion: The critical pathways and hub genes in HCC progression were screened out, and targeting RRM2 contributed to developing new therapeutic strategies for HCC.

Development of an Accessible Gene Expression Bioinformatics Pipeline to Study Driver Mutations of Colorectal Cancer

Colorectal cancer (CRC) is a global cause of cancer-related mortality driven by genetic and environmental factors which influence therapeutic outcomes. The emergence of next-generation sequencing technologies enables the rapid and extensive collection and curation of genetic data for each cancer type into clinical gene expression biobanks. We report the application of bioinformatics tools for investigating the expression patterns and prognostic significance of three genes that are commonly dysregulated in colon cancer: adenomatous polyposis coli (APC); B-Raf proto-oncogene (BRAF); and Kirsten rat sarcoma viral oncogene homologue (KRAS). Through the use of bioinformatics tools, we show the patterns of APC, BRAF and KRAS genetic alterations and their role in patient prognosis. Our results show mutation types, the frequency of mutations, tumour anatomical location and differential expression patterns for APC, BRAF and KRAS for colorectal tumour and matched healthy tissue. The prognostic value of APC, BRAF and KRAS genetic alterations was investigated as a function of their expression levels in CRC. In the era of precision medicine, with significant advancements in biobanking and data curation, there is significant scope to use existing clinical data sets for evaluating the role of mutational drivers in carcinogenesis. This approach offers the potential for studying combinations of less well-known genes and the discovery of novel biomarkers, or for studying the association between various effector proteins and pathways.

Alterations of RNA Modification in Mouse Germ Cell-2 Spermatids Under Hypoxic Stress

Hypoxia is a known stress factor in mammals and has been shown to potentially impair male fertility, which manifests as spermatogenic dysfunction and decreased semen quality. Studies have shown that RNA modifications, the novel post-transcriptional regulators, are involved in spermatogenesis, and hypoxia-induced alterations in RNA modification in testes and sperm cells may be associated with impaired spermatogenesis in mice. However, the molecular mechanisms via which RNA modifications influence spermatogenesis under hypoxic stress conditions are unclear. In this study, we generated a mouse Germ Cell-2 spermatid (GC-2spd) hypoxia model by culturing cells in a 1% O2 incubator for 48 h or treating them with CoCl2 for 24 h. The hypoxia treatment significantly inhibited proliferation and induced apoptosis in GC-2spd cells. The RNA modification signatures of total RNAs (2 types) and differentially sized RNA fragments (7 types of approximately 80 nt-sized tRNAs; 9 types of 17–50 nt-sized sncRNAs) were altered, and tRNA stability was partially affected. Moreover, the expression profiles of sncRNAs, such as microRNAs, tsRNAs, rsRNAs, and ysRNAs, were significantly regulated, and this might be related to the alterations in RNA modification and subsequent transcriptomic changes. We comprehensively analyzed alterations in RNA modification signatures in total RNAs, tRNAs (approximately 80 nt), and small RNAs (17–50 nt) as well as the expression profiles of sncRNAs and transcriptomes in hypoxia-treated GC-2spd cells; our data suggested that RNA modifications may be involved in cellular responses under hypoxic stress conditions and could provide a basis for a better understanding of the molecular mechanisms underlying male infertility.

The LINC01929/miR-6875-5p/ADAMTS12 Axis in the ceRNA Network Regulates the Development of Advanced Bladder Cancer

Considering its speedy development and extremely low 5-year overall survival rate worldwide, bladder cancer (BCa) is one of the most common and highly malignant tumors. Increasing evidence suggests that protein-coding mRNAs and non-coding RNAs, including long non-coding RNAs (lncRNAs) and micro RNAs (miRNAs), play an essential role in regulating the biological processes of cancer. To investigate the molecular regulation associated with poor prognosis during advanced BCa development, we constructed a competitive endogenous RNA (ceRNA) network. Using transcriptome profiles from The Cancer Genome Atlas and Gene Expression Omnibus databases, we performed differential expression (DE) analysis, weighted gene co-expression network analysis, functional enrichment analysis, survival analysis, prediction of miRNA targeting, and Pearson correlation analysis. Through layers of selection, 8 lncRNAs-28 mRNAs and 8 miRNAs-28 mRNAs pairs shared similar expression patterns, constituting a core ceRNA regulatory network related to the invasion, progression, and metastasis of advanced clinical stage (ACS) BCa. Subsequently, we conducted real time qPCR, western blotting, and immunohistochemistry to validate expression trend bioinformatics analysis on 3, 2, and 3 differentially expressed mRNAs, lncRNAs, and miRNAs, respectively. The most significantly differentially expressed LINC01929, miR-6875-5p and ADAMTS12 were selected for in vitro experiments to assess the functional role of the LINC01929/miR-6875-5p/ADAMTS12 axis. RNA pull-down, luciferase assays, and rescue assays were performed to examine the binding of LINC01929 and miR-6875-5p. Increasing trends in COL6A1, CDH11, ADAMTS12, LINC01705, and LINC01929 expression variation were verified as consistent with previous DE analysis results in ACS-BCa, compared with low clinical stage (LCS) BCa. Expression trends in parts of these RNAs, such as hsa-miR-6875-5p, hsa-miR-6784-5p, COL6A1, and CDH11, were measured in accordance with DE analysis in LCS-BCa, compared with normal bladder urothelium. Through experimental validation, the cancer-promoting molecule ADAMST12 was found to play a key role in the development of advanced BCa. Functionally, ADAMTS12 knockdown inhibited the progression of bladder cancer. Overexpression of LINC01929 promoted bladder cancer development, while overexpression of miR-6785-5p inhibited bladder cancer development. Mechanistically, LINC01929 acted as a sponge for miR-6785-5p and partially reversed the role of miR-6785-5p. Our findings provide an elucidation of the molecular mechanism by which advanced bladder cancer highly expressed LINC01929 upregulates ADAMTS12 expression through competitive adsorption of miR-6875-5p. It provides a new target for the prognosis and diagnosis of advanced bladder cancer.

ExhauFS: exhaustive search-based feature selection for classification and survival regression

Feature selection is one of the main techniques used to prevent overfitting in machine learning applications. The most straightforward approach for feature selection is an exhaustive search: one can go over all possible feature combinations and pick up the model with the highest accuracy. This method together with its optimizations were actively used in biomedical research, however, publicly available implementation is missing. We present ExhauFS-the user-friendly command-line implementation of the exhaustive search approach for classification and survival regression. Aside from tool description, we included three application examples in the manuscript to comprehensively review the implemented functionality. First, we executed ExhauFS on a toy cervical cancer dataset to illustrate basic concepts. Then, multi-cohort microarray breast cancer datasets were used to construct gene signatures for 5-year recurrence classification. The vast majority of signatures constructed by ExhauFS passed 0.65 threshold of sensitivity and specificity on all datasets, including the validation one. Moreover, a number of gene signatures demonstrated reliable performance on independent RNA-seq dataset without any coefficient re-tuning, i.e., turned out to be cross-platform. Finally, Cox survival regression models were used to fit isomiR signatures for overall survival prediction for patients with colorectal cancer. Similarly to the previous example, the major part of models passed the pre-defined concordance index threshold 0.65 on all datasets. In both real-world scenarios (breast and colorectal cancer datasets), ExhauFS was benchmarked against state-of-the-art feature selection models, including L₁-regularized sparse models. In case of breast cancer, we were unable to construct reliable cross-platform classifiers using alternative feature selection approaches. In case of colorectal cancer not a single model passed the same 0.65 threshold. Source codes and documentation of ExhauFS are available on GitHub: https://github.com/s-a-nersisyan/ExhauFS.

Non-coding RNAs as emerging regulators and biomarkers in colorectal cancer

CRC is the third most common cancer occurring worldwide and the second leading cause of cancer deaths. In the year 2020, 1,931,590 new cases of CRC and 935,173 deaths were reported. The last two decades have witnessed an intensive study of noncoding RNAs and their implications in various pathological conditions including cancer. Noncoding RNAs such as miRNAs, tsRNAs, piRNAs, lncRNAs, pseudogenes, and circRNAs have emerged as promising prognostic and diagnostic biomarkers in preclinical studies of cancer. Some of these noncoding RNAs have also been shown as promising therapeutic targets for cancer treatment. In this review, we have discussed the emerging roles of various types of noncoding RNAs in CRC and their future implications in colorectal cancer management and research.

A Potential Nine-lncRNAs Signature Identification and Nomogram Diagnostic Model Establishment for Papillary Thyroid Cancer

The purpose of our current study was to establish a long non-coding RNA(lncRNA) signature and assess its prognostic and diagnostic power in papillary thyroid cancer (PTC). LncRNA expression profiles were obtained from the Cancer Genome Atlas (TCGA). The key module and hub lncRNAs related to PTC were determined by weighted gene co-expression network analysis (WGCNA) and LASSO Cox regression analyses, respectively. Functional enrichment analyses, including Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene set enrichment analysis were implemented to analyze the possible biological processes and signaling pathways of hub lncRNAs. Associations between key lncRNA expressions and tumor-infiltrating immune cells were identified using the TIMER website, and proportions of immune cells in high/low risk score groups were compared. Kaplan-Meier Plotter was used to evaluate the prognostic significance of hub genes in PTC. A diagnostic model was conducted with logistic regression analysis, and its diagnostic performance was assessed by calibration/receiver operating characteristic curves and principal component analysis. A nine-lncRNAs signature (SLC12A5-AS1, LINC02028, KIZ-AS1, LINC02019, LINC01877, LINC01444, LINC01176, LINC01290, and LINC00581) was established in PTC, which has significant diagnostic and prognostic power. Functional enrichment analyses elucidated the regulatory mechanism of the nine-lncRNAs signature in the development of PTC. This signature and expressions of nine hub lncRNAs were correlated with the distributions of tumor infiltrating immune cells. A diagnostic nomogram was also established for PTC. By comparing with the published models with less than or equal to nine lncRNAs, our signature showed a preferable performace for prognosis prediction. In conclusion, our present research established an innovative nine-lncRNAs signature and a six-lncRNAs nomogram that might act as a potential indicator for PTC prognosis and diagnosis, which could be conducive to the PTC treatment.

MicroRNAs and 'Sponging' Competitive Endogenous RNAs Dysregulated in Colorectal Cancer: Potential as Noninvasive Biomarkers and Therapeutic Targets

The gastrointestinal (GI) tract in mammals is comprised of dozens of cell types with varied functions, structures, and histological locations that respond in a myriad of ways to epigenetic and genetic factors, environmental cues, diet, and microbiota. The homeostatic functioning of these cells contained within this complex organ system has been shown to be highly regulated by the effect of microRNAs (miRNA). Multiple efforts have uncovered that these miRNAs are often tightly influential in either the suppression or overexpression of inflammatory, apoptotic, and differentiation-related genes and proteins in a variety of cell types in colorectal cancer (CRC). The early detection of CRC and other GI cancers can be difficult, attributable to the invasive nature of prophylactic colonoscopies. Additionally, the levels of miRNAs associated with CRC in biofluids can be contradictory and, therefore, must be considered in the context of other inhibiting competitive endogenous RNAs (ceRNA) such as lncRNAs and circRNAs. There is now a high demand for disease treatments and noninvasive screenings such as testing for bloodborne or fecal miRNAs and their inhibitors/targets. The breadth of this review encompasses current literature on well-established CRC-related miRNAs and the possibilities for their use as biomarkers in the diagnoses of this potentially fatal GI cancer.

WGCNA-Based Identification of Hub Genes and Key Pathways Involved in Nonalcoholic Fatty Liver Disease

Background

The morbidity of nonalcoholic fatty liver disease (NAFLD) has been rising, but the pathogenesis of NAFLD is still elusive. This study is aimed at determining NAFLD-related hub genes based on weighted gene coexpression network analysis (WGCNA).

Methods

GSE126848 dataset based construction of coexpression networks was performed based on WGCNA. Database for Annotation, Visualization, and Integrated Discovery (DAVID) was utilized for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Hub genes were identified and validated in independent datasets and mouse model.

Results

We found that the steelblue module was most significantly correlated with NAFLD. Total 15 hub genes (NDUFA9, UQCRQ, NDUFB8, COPS5, RPS17, UBL5, PSMA3, PSMA1, SF3B5, MRPL27, RPL26, PDCD5, PFDN6, SNRPD2, PSMB3) were derived from both the coexpression and PPI networks and considered “true” hub genes. Functional enrichment analysis showed that the hub genes were related to NAFLD pathway and oxidative phosphorylation. Independent dataset-based analysis and the establishment of NAFLD mouse model confirmed the involvement of two hub genes NDUFA9 and UQCRQ in the pathogenesis of NAFLD.

Conclusions

Oxidative phosphorylation and NAFLD pathway may be crucially involved in the pathogenesis of NAFLD, and two hub genes NDUFA9 and UQCRQ might be diagnostic biomarkers and therapeutic targets for NAFLD.

Identification of a detection panel for post-transplant virus infection through integrated analysis of non-coding RNAs in peripheral blood

Viral infection seriously affects the survival and life quality of transplanted patients without an accurate diagnosis during the early stage. Herein, we aimed to develop a novel diagnostic method based on non-coding RNAs expression in peripheral blood. An immunosuppressive mouse model of viral infection after transplantation was established. Differentially expressed non-coding RNAs were distinguished by microarray analyses in the virus-infected group. After homology analysis, 46 miRNAs and 24 lncRNAs were further verified by qRT-PCR in the peripheral blood samples of transplanted patients. Compared with normal transplanted patients, miR-29b, miR-185, and NR_073415.2 were significantly downregulated in the PBMC of post-transplant patients with viral infection. Based on the expression of the above three RNAs, principal component analysis (PCA) identified a slight overlap between the two groups. A 3-non-coding-RNA detection panel was constructed by the support vector machine analysis (SVM), whose loss rate was 14.71%. The area under the curve of it was 0.909. With the optimal cut-off value (Y = 0.328), the sensitivity was 0.929 and the specificity was 0.781. Therefore, based on non-coding RNAs expressions, a detection panel for viral infection after organ transplantation was formed with high diagnostic specificity and sensitivity.

Construction of a Ferroptosis-Related Long Non-coding RNA Prognostic Signature and Competing Endogenous RNA Network in Lung Adenocarcinoma

Ferroptosis-related genes play an important role in the progression of lung adenocarcinoma (LUAD). However, the potential function of ferroptosis-related lncRNAs in LUAD has not been fully elucidated. Thus, to explore the potential role of ferroptosis-related lncRNAs in LUAD, the transcriptome RNA-seq data and corresponding clinical data of LUAD were downloaded from the TCGA dataset. Pearson correlation was used to mine ferroptosis-related lncRNAs. Differential expression and univariate Cox analysis were performed to screen prognosis related lncRNAs. A ferroptosis-related lncRNA prognostic signature (FLPS), which included six ferroptosis-related lncRNAs, was constructed by the least absolute shrinkage and selection operator (LASSO) Cox regression. Patients were divided into a high risk-score group and low risk-score group by the median risk score. Receiver operating characteristic (ROC) curves, principal component analysis (PCA), and univariate and multivariate Cox regression were performed to confirm the validity of FLPS. Enrichment analysis showed that the biological processes, pathways and markers associated with malignant tumors were more common in high-risk subgroups. There were significant differences in immune microenvironment and immune cells between high- and low-risk groups. Then, a nomogram was constructed. We further investigated the relationship between six ferroptosis-related lncRNAs and tumor microenvironment and tumor stemness. A competing endogenous RNA (ceRNA) network was established based on the six ferroptosis-related lncRNAs. Finally, we detected the expression levels of ferroptosis-related lncRNAs in clinical samples through quantitative real-time polymerase chain reaction assay (qRT-PCR). In conclusion, we identified the prognostic ferroptosis-related lncRNAs in LUAD and constructed a prognostic signature which provided a new strategy for the evaluation and prediction of prognosis in LUAD.

The dual role of microRNA-9 in gastrointestinal cancers: oncomiR or tumor suppressor?

microRNA are noncoding endogenous RNAs of ∼ 25-nucleotide, involved in RNA silencing and controlling of cell function. Recent evidence has highlighted the important role of various in the biology of human cancers. miR-9 is a highly conserved microRNA and abnormal regulation of miR-9 expression has various impacts on disease pathology. miR-9 may play a dual tumor-suppressive or oncomiR activity in several cancers. There have been conflicting reports concerning the role of miR-9 in gastrointestinal cancers. Several signaling pathways including PDK/AKT, Hippo, Wnt/β-catenin and PDGFRB axes are affected by miR-9 in suppressing proliferation, invasion and metastasis of tumor cells. Oncogenic miR-9 triggers migration, metastasis and clinic-pathological characteristics of patients with gastrointestinal malignancy by targeting various enzymes and transcription factors such as E-cadherin, HK2, LMX1A, and CDX2. On the other hand, long non-coding RNAs and circular RNAs can modulate miR-9 expression in human cancers. In this review, we aimed to summarize recent findings about the potential value of miR-9 in gastrointestinal tumors, that include: screening, prognostic and treatment.

miR-142-3p Regulates Tumor Cell Autophagy and Promotes Colon Cancer Progression by Targeting TP53INP2

OBJECTIVES

Colon cancer (CC) is the third largest cancer worldwide. Investigation of the molecular mechanism of CC progression helps to explore novel therapeutic targets. We attempted to understand the modulatory mechanism of miR-142-3p in CC cell autophagy and CC progression, which will lay a theoretical groundwork for seeking potential diagnostic and therapeutic targets for CC.

METHODS

Through bioinformatics methods, miRNA expression data were subjected to differential analysis for identification of target miRNA. Downstream target mRNAs were predicted and gene set enrichment analysis (GSEA) was completed. qRT-PCR assessed gene expression in cells. Cell Counting Kit-8, cell doubling time calculation, colony formation, and flow cytometry were used to assess cellular biological functions. Dual-luciferase assay was used for targeting relationship validation of the target miRNA and mRNA. Western blot was performed to evaluate expression of proteins related to HEDGEHOG signaling pathway and autophagy.

RESULTS

miR-142-3p was markedly highly expressed in CC, and high miR-142-3p expression in CC patients was implicated with relatively poor prognosis. Over-expressing miR-142-3p facilitated proliferation and inhibited apoptosis of CC cells, whereas silencing it produced an opposite result. miR-142-3p targeted and decreased TP53INP2 level. TP53INP2 over-expression suppressed the HEDGEHOG signaling pathway and induced the activation of CC cell autophagy. Rescue experiments revealed that influence of miR-142-3p inhibitor on CC cell proliferation and apoptosis could be reversed by silencing TP53INP2.

CONCLUSION

miR-142-3p hampered tumor cell autophagy and promoted CC progression via targeting TP53INP2, which will offer a fresh research orientation for the diagnosis of CC.

Robust Glycogene-Based Prognostic Signature for Proficient Mismatch Repair Colorectal Adenocarcinoma

Background

Proficient mismatch repair (pMMR) colorectal adenocarcinoma (CRAC) metastasizes to a greater extent than MMR-deficient CRAC. Prognostic biomarkers are preferred in clinical practice. However, traditional biomarkers screened directly from sequencing are often not robust and thus cannot be confidently utilized.

Methods

To circumvent the drawbacks of blind screening, we established a new strategy to identify prognostic biomarkers in the conserved and specific oncogenic pathway and its regulatory RNA network. We performed RNA sequencing (RNA-seq) for messenger RNA (mRNA) and noncoding RNA in six pMMR CRAC patients and constructed a glycosylation-related RNA regulatory network. Biomarkers were selected based on the network and their correlation with the clinicopathologic information and were validated in multiple centers (n = 775).

Results

We constructed a competing endogenous RNA (ceRNA) regulatory network using RNA-seq. Genes associated with glycosylation pathways were embedded within this scale-free network. Moreover, we further developed and validated a seven-glycogene prognosis signature, GlycoSig (B3GNT6, GALNT3, GALNT8, ALG8, STT3B, SRD5A3, and ALG6) that prognosticate poor-prognostic subtype for pMMR CRAC patients. This biomarker set was validated in multicenter datasets, demonstrating its robustness and wide applicability. We constructed a simple-to-use nomogram that integrated the risk score of GlycoSig and clinicopathological features of pMMR CRAC patients.

Conclusions

The seven-glycogene signature served as a novel and robust prognostic biomarker set for pMMR CRAC, highlighting the role of a dysregulated glycosylation network in poor prognosis.

A seven-gene prognostic signature predicts overall survival of patients with lung adenocarcinoma (LUAD)

Background

Lung adenocarcinoma (LUAD) is one of the most common types in the world with a high mortality rate. Despite advances in treatment strategies, the overall survival (OS) remains short. Our study aims to establish a reliable prognostic signature closely related to the survival of LUAD patients that can better predict prognosis and possibly help with individual monitoring of LUAD patients.

Methods

Raw RNA-sequencing data were obtained from Fudan University and used as a training group. Differentially expressed genes (DEGs) for the training group were screened. The univariate, least absolute shrinkage and selection operator (LASSO), and multivariate cox regression analysis were conducted to identify the candidate prognostic genes and construct the risk score model. Kaplan–Meier analysis, time-dependent receiver operating characteristic (ROC) curve were used to evaluate the prognostic power and performance of the signature. Moreover, The Cancer Genome Atlas (TCGA-LUAD) dataset was further used to validate the predictive ability of prognostic signature.

Results

A prognostic signature consisting of seven prognostic-related genes was constructed using the training group. The 7-gene prognostic signature significantly grouped patients in high and low-risk groups in terms of overall survival in the training cohort [hazard ratio, HR = 8.94, 95% confidence interval (95% CI)] [2.041–39.2]; P = 0.0004), and in the validation cohort (HR = 2.41, 95% CI [1.779–3.276]; P < 0.0001). Cox regression analysis (univariate and multivariate) demonstrated that the seven-gene signature is an independent prognostic biomarker for predicting the survival of LUAD patients. ROC curves revealed that the 7-gene prognostic signature achieved a good performance in training and validation groups (AUC = 0.91, AUC = 0.7 respectively) in predicting OS for LUAD patients. Furthermore, the stratified analysis of the signature showed another classification to predict the prognosis.

Conclusion

Our study suggested a new and reliable prognostic signature that has a significant implication in predicting overall survival for LUAD patients and may help with early diagnosis and making effective clinical decisions regarding potential individual treatment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-01975-z.

Comprehensive evaluation of microRNA-10b in digestive system cancers reveals prognostic implication and signaling pathways associated with tumor progression

Background: Digestive system cancers (DSCs) have been recognized to be linked with high morbidity and mortality. Recent studies have reported that microRNA-10b (miR-10b) is abnormally expressed in DSCs and associated with prognosis. However, the inconclusive results and unknown underlying mechanisms promoted us to perform this study. Methods: We systematic searched several databases for eligible studies and conducted quantitative analysis for evidence regarding the associations between miR-10b and survival outcome of DSCs. We also performed a series of bioinformatics analyses to uncover the potential mechanisms. Results: A total of 32 eligible studies with 3392 patients were included. Increased miR-10b expression was linked with unfavorable overall survival (OS) in DSCs (HR=1.72; 95% CI: 1.30-2.27; P <0.001). When stratified by tumor type, the impact of miR-10b overexpression on poor prognosis was observed in colorectal cancer, gastric cancer, hepatocellular carcinoma, and esophageal carcinoma, but not in pancreatic cancer. Subsequently, we predicted the targets of miR-10b and conducted functional enrichment analyses. The results disclosed that miR-10b targets were predominantly enriched in some vital biological terms and pivotal signaling pathways associated with tumor progression including cell cycle, FoxO, proteoglycans, central carbon metabolism, p53, Notch, HIF-1, focal adhesion, AMPK, and pancreatic cancer. Moreover, a protein-protein interaction (PPI) network was also constructed to identify the top ten hub genes and significant modules and demonstrated the underlying interactions among them. Conclusion: Our results indicated that miR-10b could act as a significant biomarker in the prognosis DSCs. However, more research should be performed to test these findings.

The Ambivalent Role of miRNAs in Carcinogenesis: Involvement in Renal Cell Carcinoma and Their Clinical Applications

The analysis of microRNA (miRNAs), small, non-coding endogenous RNA, plays a crucial role in oncology. These short regulatory sequences, acting on thousands of messenger RNAs (mRNAs), modulate gene expression at the transcriptional and post-transcriptional level leading to translational repression or degradation of target molecules. Although their function is required for several physiological processes, such as proliferation, apoptosis and cell differentiation, miRNAs are also responsible for development and/or progression of several cancers, since they may interact with classical tumor pathways. In this review, we highlight recent advances in deregulated miRNAs in cancer focusing on renal cell carcinoma (RCC) and provide an overview of the potential use of miRNA in their clinical settings, such as diagnostic and prognostic markers.

Construction of Competitive Endogenous RNA Network and Verification of 3-Key LncRNA Signature Associated With Distant Metastasis and Poor Prognosis in Patients With Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is a common malignancy with high distant metastasis rate. Long non-coding RNAs (LncRNAs) are reported to be upregulated or downregulated in multiple cancers and play a crucial role in the metastasis of tumors or prognosis. Therefore, the purpose of our study is to construct a prognostic signature for ccRCC based on distant metastasis-related lncRNAs and explore the involved potential competitive endogenous RNA (ceRNA) network. The differentially expressed genes (DEGs) screened from the database of the cancer genome atlas (TCGA) were used to construct a co-expression network and identify the distant metastasis-related module by weighted gene co-expression network analysis (WGCNA). Key genes with metastatic and prognostic significance were identified through rigorous screening, including survival analysis, correlation analysis, and expression analyses in stage, grade, and distant metastasis, and were verified in the data set of gene expression omnibus (GEO) and the database from gene expression profiling interactive analysis (GEPIA). The potential upstream miRNAs and lncRNAs were predicted via five online databases and LncBase. Here, we constructed a ceRNA network of key genes that are significantly associated with the distant metastasis and prognosis of patients with ccRCC. The distant metastasis-related lncRNAs were used to construct a risk score model through the univariate, least absolute shrinkage selection operator (LASSO), and multivariate Cox regression analyses, and the patients were divided into high- and low-risk groups according to the median of the risk score. The Kaplan–Meier survival analysis demonstrated that mortality was significantly higher in the high-risk group than in the low-risk group. Considering the other clinical phenotype, the Cox regression analyses indicated that the lncRNAs model could function as an independent prognostic factor. Quantitative real-time (qRT)-PCR in the tissues and cells of ccRCC verified the high-expression level of three lncRNAs. Gene set enrichment analysis (GSEA) revealed that the lncRNA prognostic signature was mainly enriched in autophagy- and immune-related pathways, indicating that the autophagy and immune functions may play an important role in the distant metastasis of ccRCC. In summary, the constructed distant metastasis-related lncRNA signature could independently predict prognosis in patients with ccRCC, and the related ceRNA network provided a new sight on the potential mechanism of distant metastasis and a promising therapeutic target for ccRCC.

The clinical relevance of gene expression based prognostic signatures in colorectal cancer

Colorectal cancer (CRC) is one of the most prevalent cancers, with more than one million new cases every year. In the last few decades, several advancements in therapeutic and preventative levels have reduced the mortality rate, but new biomarkers are required for improved prognosis. The alterations at the genetic and epigenetic level have been recognized as major players in tumorigenesis. The products of gene expression in the form of mRNA, microRNA, and long-noncoding RNA, have started to emerge as important regulatory molecules, playing an important role in cancer. Gene-expression based prognostic risk scores, which quantify and compare their expression, have emerged as promising biomarkers with enormous clinical value. These composite multi-gene models in which more than one gene is used to predict prognosis have been shown to be significantly effective in identifying patients with multiple clinico-pathological risks like overall mortality, response to chemotherapy, risk of metastasis, etc. The advent of microarray and advanced sequencing technologies have led to the generation of large datasets like TCGA (The Cancer Genome Atlas) and GEO (Gene Expression Omnibus), which have fueled the search for new biomarkers. Continuous evaluation of these candidate biomarkers in clinical settings is promising to improve the management of CRC. These composite gene signatures provide potential in identifying high-risk patients, which might help clinicians to better manage these patients and design appropriate personalized therapeutic interventions. In this review, we emphasize on composite prognostic scores from diverse resources with clinical utility in CRC.

Construction of an mRNA-miRNA-lncRNA network prognostic for triple-negative breast cancer

The aim of this study was to establish a novel competing endogenous RNA (ceRNA) network able to predict prognosis in patients with triple-negative breast cancer (TNBC). Differential gene expression analysis was performed using the GEO2R tool. Enrichr and STRING were used to conduct protein-protein interaction and pathway enrichment analyses, respectively. Upstream lncRNAs and miRNAs were identified using miRNet and mirTarBase, respectively. Prognostic values, expression, and correlational relationships of mRNAs, lncRNAs, and miRNAs were examined using GEPIA, starBase, and Kaplan-Meier plotter. It total, 860 upregulated and 622 downregulated differentially expressed mRNAs were identified in TNBC. Ten overexpressed and two underexpressed hub genes were screened. Next, 10 key miRNAs upstream of these key hub genes were predicted, of which six upregulated miRNAs were significantly associated with poor prognosis and four downregulated miRNAs were associated with good prognosis in TNBC. NEAT1 and MAL2 were selected as key lncRNAs. An mRNA-miRNA-lncRNA network in TNBC was constructed. Thus, we successfully established a novel mRNA-miRNA-lncRNA regulatory network, each component of which is prognostic for TNBC.

Specific MiRNAs in naïve T cells associated with Hepatitis C Virus-induced Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the fifth most common type of cancer and the second leading cause of cancer-associated mortality worldwide. Hepatitis C virus (HCV) infection is the primary cause of hepatic fibrosis and cirrhosis, which in turn, notably increase the risk of developing HCC. The systematic immune response plays a vital role in protecting eukaryotic cells from exogenous antigens. In the present study, to determine the association between T cells and miRNAs in HCV-induced HCC (HCV-HCC), bulk mRNA and miRNA sequencing data from HCV-HCC tissues were combined, along with single-cell RNA sequencing (RNA-seq) data from T cells. Deconvoluted bulk RNA-seq data and miRNA profiles enabled the identification of naive CD4+ T cell-associated miRNAs, which may help to elucidate the underlying mechanism of the anti-HCV immune response. Using bulk RNA-seq data, the current analysis presents a feasible method for assessing the relationship between miRNAs and cell components, providing valuable insights into the effects of T cell-associated miRNAs in HCV-HCC.

CircRNA hsa_circRNA_104348 promotes hepatocellular carcinoma progression through modulating miR-187-3p/RTKN2 axis and activating Wnt/β-catenin pathway

Circular RNAs (circRNAs) have confirmed to participate in diverse biological functions in cancer. However, the expression patterns of circRNAs on hepatocellular carcinoma (HCC) remains unclear. In the present study, we clarified that hsa_circRNA_104348 was dramatically upregulated in HCC tissues and cells. Patients with HCC displaying high hsa_circRNA_104348 level possessed poor prognosis. Has_circ_104348 facilitated proliferation, migration, and invasion, meanwhile suppressed apoptosis of HCC cell. Furthermore, hsa_circRNA_104348 directly targeted miR-187-3p, could regulate miR-187-3p to affect proliferation, migration, invasion, and apoptosis of HCC cells, and may have effect on Wnt/β-catenin signaling pathway. Moreover, RTKN2 could be a direct target of miR-187-3p. In addition, knockdown of hsa_circRNA_104348 attenuated HCC tumorigenesis and lung metastasis in vivo. Taken together, these findings indicated that circular RNA hsa_circRNA_104348 might function as a competing endogenous RNA (ceRNA) to promotes HCC progression by targeting miR-187-3p/RTKN2 axis and activating Wnt/β-catenin pathway.

Identification and Validation of MSX1 as a Key Candidate for Progestin Resistance in Endometrial Cancer

Purpose

Progestin resistance is a critical obstacle for endometrial conservative therapy. Therefore, studies to acquire a more comprehensive understanding of the mechanisms are urgent. However, the pivotal molecules are still unexplored.

Materials and Methods

We downloaded GSE121367 from the GEO database. The “limma” R language package was applied to identify differentially expressed genes (DEGs). We conducted Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA). Protein–protein interaction was constructed by STRING and visualized in Cytoscape. The tumor immune microenvironment was explored by the TISIDB database. Methylation validation and overall survival analysis were conducted by the TCGA database. In addition, the upstream modulators of hub genes were predicted by miRTarBase and Network Analyst databases. The expression levels of candidate genes were validated by quantitative real-time PCR (qRT-PCR), Western blot, and immunohistochemical assay (IHC). Cell growth, clone formation, migration, invasion, and wound healing assays were studied to explore the role of MSX1 in progestin resistance in vitro.

Results

A total of 3,282 DEGs were identified and they were mostly enriched in the cell adhesion pathway. We screened out ten hub genes whose genomic alteration rates were low based on the current endometrial carcinoma sample sets. Has-miR-335-5p, has-miR-124-3p, MAZ, and TFDP1 were the most prominent upstream regulators. The methylation status of CDH1, JAG1, EPCAM, and MSX1 was decreased, corresponding to their high protein expression, which also predicted better overall survival. The homeobox protein of MSX1 showed significant tissue specificity and better prognostic value and its knockdown inhibited epithelial–mesenchymal transitions (EMT) and enhanced progesterone efficacy.

Conclusion

Our study identified that the gene of MSX1 promised to be the specific indicator and therapeutic target for progestin resistance. This would shed new light on the underlying biological mechanism to overcome progestin resistance of endometrial cancer.

Screening and identification of biomarkers associated with the diagnosis and prognosis of lung adenocarcinoma

BACKGROUND

In this study, we aimed to identify the pathogenesis and prognostic biomarkers of lung adenocarcinoma (LUAD).

METHODS

Differentially expressed mRNAs (DEmRNAs) and single nucleotide polymorphism (SNP) mutant genes were screened. In addition, enrichment and protein-protein interaction (PPI) network analyses of the SNP-mutated genes were performed. Thereafter, the correlation between gene mutation and expression was analyzed. Finally, the mutated genes associated with LUAD prognosis were validated on the basis of The Cancer Genome Atlas (TCGA) database.

RESULTS

A total of 2502 DEmRNAs were initially screened in this study. We identified 756 SNP-mutated genes from more than 30 cases. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that the mutated genes involved in LUAD were mainly associated with the ECM-receptor interaction, focal adhesion, and calcium signaling pathways. Tumor protein p53 (TP53) and neurexin 1 (NRXN1) with the higher degree were chosen as the hub genes in the PPI network. In addition, the correlation analysis revealed six genes, including assembly factor for spindle microtubules (ASPM), centromere protein F (CENPF), contactin 3 (CNTN3), catenin delta 2 (CTNND2), PKHD1 like 1 (PKHD1L1), and semaphorin 6D (SEMA6D), and three SNP mutations at ASPM rs368020495, CENPF rs762653487, and PKHD1L1 rs768349010 sites that were found to be associated with LUAD prognosis. Further validation showed that among the aforementioned six mutated genes, CENPF was upregulated and SEMA6D was downregulated.

CONCLUSION

CENPF, SEMA6D, TP53, and NRXN1 were found to be closely associated with the development of LUAD.

miRNAs-Based Molecular Signature for KRAS Mutated and Wild Type Colorectal Cancer: An Explorative Study

microRNAs (miRNAs) have been proposed as promising molecular biomarkers for diagnosis, prognosis, and responsive therapeutic targets in different types of cancer, including colorectal cancer (CRC). In this study, we evaluated the expression levels of 84 cancer-associated miRNAs in a cohort of 39 human samples comprising 13 peritumoral and 26 tumoral tissues from surgical specimens of CRC patients. KRAS mutations were detected in 11 tumoral samples. In a first analysis, we found 5 miRNAs (miR-215-5p, miR-9-5p, miR-138-5p, miR378a-3p, and miR-150-5p) that were significantly downregulated and one upregulated (miR-135b-5p) in tumoral tissues compared with the peritumoral tissues. Furthermore, by comparing miRNA profile between KRAS mutated CRC tissues respect to wild type CRC tissues, we found 7 miRNA (miR-27b-3p, miR-191-5p, miR-let7d-5p, miR-15b-5p, miR-98-5p, miR-10a-5p, and miR-149-5p) downregulated in KRAS mutated condition. In conclusion, we have identified a panel of miRNAs that specifically distinguish CRC tissues from peritumoral tissue and a different set of miRNAs specific for CRC with KRAS mutations. These findings may contribute to the discovering of new molecular biomarkers with clinic relevance and might shed light on novel molecular aspects of CRC.

Identification of Prognostic miRNA Signature and Lymph Node Metastasis-Related Key Genes in Cervical Cancer

Background

miRNAs and genes can serve as biomarkers for the prognosis and therapy of cervical tumors whose metastasis into lymph nodes is closely associated with disease progression and poor prognosis.

Methods

R software and Bioconductor packages were employed to identify differentially expressed miRNAs (DEMs) from The Cancer Genome Atlas (TCGA) database. GEO2R detected differentially expressed genes (DEGs) in the GSE7410 dataset originating from the Gene Expression Omnibus (GEO). A Cox proportional hazard regression model was established to select prognostic miRNA biomarkers. Online tools such as TargetScan and miRDB predicted target genes, and overlapping DEGs and target genes were defined as consensus genes. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment and Gene Ontology (GO) function annotations were performed to discern the potential functions of consensus genes. STRING and Cytoscape screened key genes and constructed a regulatory network.

Results

A combination of four miRNAs (down-regulated miR-502 and miR-145, up-regulated miR-142 and miR-33b) was identified as an independent prognostic signature of cervical cancer. A total of 94 consensus genes were significantly enriched in 7 KEGG pathways and 19 GO function annotations including the cAMP signaling pathway, the plasma membrane, integral components of the plasma membrane, cell adhesion, etc. The module analysis suggested that CXCL12, IGF1, PTPRC CDH5, RAD51B, REV3L, and WDHD1 are key genes that significantly correlate with cervical cancer lymph node metastasis.

Conclusions

This study demonstrates that a four-miRNA signature can be a prognostic biomarker, and seven key genes are significantly associated with lymph node metastasis in cervical cancer patients. These miRNAs and key genes have the potential to be therapeutic targets for cervical cancer. Among them, two miRNAs (miR-502 and miR-33b) and two key genes (PTPRC and CDH5) were first reported to be potential novel biomarkers for cervical cancer. The current study further characterizes the progression of lymph node metastasis and mechanism of cervical tumors; therefore, it provides a novel diagnostic indicator and therapeutic targets for future clinical treatments.

Evaluation of the Prognostic Value of STEAP1 in Lung Adenocarcinoma and Insights Into Its Potential Molecular Pathways via Bioinformatic Analysis

Background

Upregulation of the six-transmembrane epithelial antigen of prostate-1 (STEAP1) is closely associated with prognosis of numerous malignant cancers. However, its role in lung adenocarcinoma (LUAD), the most common type of lung cancer, remains unknown. This study aimed to investigate the role of STEAP1 in the occurrence and progression of LUAD and the potential mechanisms underlying its regulatory effects.

Methods

STEAP1 mRNA and protein expression were analyzed in 40 LUAD patients via real-time PCR and western blotting, respectively. We accessed the clinical data of 522 LUAD patients from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) to investigate the expression and prognostic role of STEAP1 in LUAD. Further, we performed gene ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, and gene set enrichment analysis (GSEA) to elucidate the potential mechanism underlying the role of STEAP1 in LUAD. The protein-protein interaction (PPI) network of STEAP1 was analyzed using the Search Tool for the Retrieval of Interacting Genes (STRING) database, and hub genes with significant positive and negative associations with STEAP1 were identified and their role in LUAD prognosis was predicted.

Results

STEAP1 was significantly upregulated in LUAD patients and associated with LUAD prognosis. Further, TCGA data indicated that STEAP1 upregulation is correlated with the clinical prognosis of LUAD. GO and KEGG analysis revealed that the genes co-expressed with STEAP1 were primarily involved in cell division, DNA replication, cell cycle, apoptosis, cytokine signaling, NF-kB signaling, and TNF signaling. GSEA revealed that homologous recombination, p53 signaling pathway, cell cycle, DNA replication, apoptosis, and toll-like receptor signaling were highly enriched upon STEAP1 upregulation. Gene Expression Profiling Interactive Analysis (GEPIA) analysis revealed that the top 10 hub genes associated with STEAP1 expression were also associated with the LUAD prognosis.

Conclusion

STEAP1 upregulation potentially influences the occurrence and progression of LUAD and its co-expressed genes via regulation of homologous recombination, p53 signaling, cell cycle, DNA replication, and apoptosis. STEAP1 is a potential prognostic biomarker for LUAD.

Prognostic implications of metabolism-associated gene signatures in colorectal cancer

Colorectal cancer (CRC) is one of the most common and deadly malignancies. Novel biomarkers for the diagnosis and prognosis of this disease must be identified. Besides, metabolism plays an essential role in the occurrence and development of CRC. This article aims to identify some critical prognosis-related metabolic genes (PRMGs) and construct a prognosis model of CRC patients for clinical use. We obtained the expression profiles of CRC from The Cancer Genome Atlas database (TCGA), then identified differentially expressed PRMGs by R and Perl software. Hub genes were filtered out by univariate Cox analysis and least absolute shrinkage and selection operator Cox analysis. We used functional enrichment analysis methods, such as Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Gene Set Enrichment Analysis, to identify involved signaling pathways of PRMGs. The nomogram predicted overall survival (OS). Calibration traces were used to evaluate the consistency between the actual and the predicted survival rate. Finally, a prognostic model was constructed based on six metabolic genes (NAT2, XDH, GPX3, AKR1C4, SPHK1, and ADCY5), and the risk score was an independent prognostic prognosticator. Genetic expression and risk score were significantly correlated with clinicopathologic characteristics of CRC. A nomogram based on the clinicopathological feature of CRC and risk score accurately predicted the OS of individual CRC cancer patients. We also validated the results in the independent colorectal cancer cohorts GSE39582 and GSE87211. Our study demonstrates that the risk score is an independent prognostic biomarker and is closely correlated with the malignant clinicopathological characteristics of CRC patients. We also determined some metabolic genes associated with the survival and clinical stage of CRC as potential biomarkers for CRC diagnosis and treatment.