Prognostic lncRNAs, miRNAs, and mRNAs Form a Competing Endogenous RNA Network in Colon Cancer

Downregulation of SMOC1 is associated with progression of colorectal traditional serrated adenomas

BACKGROUND

Aberrant DNA methylation is prevalent in colorectal serrated lesions. We previously reported that the CpG island of SMOC1 is frequently methylated in traditional serrated adenomas (TSAs) and colorectal cancers (CRCs) but is rarely methylated in sessile serrated lesions (SSLs). In the present study, we aimed to further characterize the expression of SMOC1 in early colorectal lesions.

METHODS

SMOC1 expression was analyzed immunohistochemically in a series of colorectal tumors (n = 199) and adjacent normal colonic tissues (n = 112).

RESULTS

SMOC1 was abundantly expressed in normal colon and SSLs while it was significantly downregulated in TSAs, advanced adenomas and cancers. Mean immunohistochemistry scores were as follows: normal colon, 24.2; hyperplastic polyp (HP), 18.9; SSL, 23.8; SSL with dysplasia (SSLD)/SSL with early invasive cancer (EIC), 15.8; TSA, 5.4; TSA with high grade dysplasia (HGD)/EIC, 4.7; non-advanced adenoma, 21.4; advanced adenoma, 11.9; EIC, 10.9. Higher levels SMOC1 expression correlated positively with proximal colon locations and flat tumoral morphology, reflecting its abundant expression in SSLs. Among TSAs that contained both flat and protruding components, levels of SMOC1 expression were significantly lower in the protruding components.

CONCLUSION

Our results suggest that reduced expression of SMOC1 is associated with progression of TSAs and conventional adenomas and that SMOC1 expression may be a biomarker for diagnosis of serrated lesions and risk prediction in colorectal tumors.

Transcription Factor Sox9 Exacerbates Kidney Injury through Inhibition of MicroRNA-96-5p and Activation of the Trib3/IL-6 Axis

INTRODUCTION

Our study investigated the possible mechanisms of the role of the transcription factor Sox9 in the development and progression of kidney injury through regulation of the miR-96-5p/Trib3/IL-6 axis.

METHODS

Bioinformatics analysis was performed to identify differentially expressed genes in kidney injury and normal tissues. An in vivo animal model of kidney injury and an in vitro cellular model of kidney injury were constructed using LPS induction in 8-week-old female C57BL/6 mice and human normal renal tubular epithelial cells HK-2 for studying the possible roles of Sox9, miR-96-5p, Trib3, and IL-6 in kidney injury.

RESULTS

Sox9 was highly expressed in both mouse and cellular models of kidney injury. Sox9 was significantly enriched in the promoter region of miR-96-5p and repressed miR-96-5p expression. Trib3 was highly expressed in both mouse and cellular models of kidney injury and promoted inflammatory responses and kidney injury. In addition, Trib3 promoted IL-6 expression, which was highly expressed in kidney injury, and promoted the inflammatory response and extent of injury in kidney tissue. In vivo and in vitro experiments confirmed that the knockdown of Sox9 improved the inflammatory response and fibrosis of mouse kidney tissues and HK-2 cells, while the ameliorative effect of silencing Sox9 was inhibited by overexpression of IL-6.

CONCLUSION

Collectively, Sox9 up-regulates miR-96-5p-mediated Trib3 and activates the IL-6 signaling pathway to exacerbate the inflammatory response, ultimately promoting the development and progression of kidney injury.

Rebound increase in microRNA levels at the end of 5-FU-based therapy in colorectal cancer patients

Treatment with 5-fluorouracil (5-FU) based therapy is still used for colorectal cancer (CRC). Epigenetics has become a focus of study in cancer because of its reversibility besides its known regulatory functions. In this study, we will monitor the change in microRNAs (miRNAs) levels with 5-FU-based therapy at baseline and after 3 and 6 months of treatment to be correlated with their prognostic potential. The expression levels of 5 miRNAs, namely miRNA223-3p, miRNA20a-5p, miRNA17-5p, miRNA19a-3p, and miRNA7-5p, were measured in the peripheral blood of 77 CRC patients, along with the expression of 3 proteins PTEN, ERK, and EGFR. At baseline, CRC patients had significantly higher levels of circulating miRNAs than healthy controls. This level was reduced after 3 months of 5-FU-based therapy, then increased after 6 months significantly in responder patients compared to non-responders. MiRNA19a-3p showed that significant pattern of change in the subgroups of patients with high ERK, EGFR, and PTEN protein levels, and its 6 months level after 5-FU-based therapy showed significance for the hazard of increased risk of disease recurrence and progression.

A cuproptosis-related lncRNA signature to predict prognosis and immune microenvironment of colon adenocarcinoma

Cuproptosis is a novel cell death modality but its regulatory role in the colon cancer remains obscure. This study is committed to establishing a cuproptosis-related lncRNA (CRL) signature to forecast the prognosis for colon adenocarcinoma (COAD). The Cancer Genome Atlas (TCGA) samples were randomly divided into training and validation cohorts. LASSO-COX analysis was performed to construct a prognostic signature consisting of five CRLs (AC015712.2, ZEB1-AS1, SNHG26, AP001619.1, and ZKSCAN2-DT). We found the patients with high-risk scores suffered from poor prognosis in training cohort (p < 0.001) and validation cohort (p = 0.004). Nomogram was created based on the 5-CRL signature. Calibration curves, receiver operating characteristic (ROC) curves, and decision curve analysis (DCA) demonstrated the nomogram performed well in 1‑, 3‑, and 5‑year overall survival (OS). Subsequently, we observed increased infiltration of multiple immune cells and upregulated expression of immune checkpoints and RNA methylation modification genes in high-risk patients. Additionally, gene set enrichment analysis (GSEA) revealed two tumor-related pathways, including MAPK and Wnt signaling pathways. Finally, we found AKT inhibitors, all-trans retinoic acid (ATRA), camptothecin, and thapsigargin had more sensitivity to antitumor therapy in high-risk patients. Collectively, this CRL signature is promising for the prognostic prediction and precise therapy of COAD.

Comprehensive analysis of cuproptosis-related long noncoding RNA for predicting prognostic and diagnostic value and immune landscape in colorectal adenocarcinoma

BACKGROUND

Cuproptosis, as a copper-induced mitochondrial cell death, has attracted extensive attention recently, especially in cancer. Although some key regulatory genes have been identified in cuproptosis, the related lncRNAs have not been further studied. Exploring the prognostic and diagnostic value of cuproptosis-related lncRNAs (CRLs) in colon adenocarcinoma and providing guidance for individualized immunotherapy for patients are of great significance.

RESULTS

A total of 2003 lncRNAs were correlated with cuproptosis genes and considered as CRLs. We screened 33 survival-associated CRLs and established a prognostic signature base on 7 CRLs in the training group. The patients in the low-risk group had better outcomes in both training group (P < 0.001) and test group (P = 0.016). More exciting, our model showed good prognosis prediction in both stage I-II (P = 0.020) and stage III-IV (P = 0.001). The nomogram model could further improve the accuracy of prognosis prediction. Interestingly, glucose-related metabolic pathways, which were closely related to cuproptosis, were enriched in the low-risk group. Meanwhile, the immune infiltration scores were lower in the high-risk group. The high-risk group was more sensitive to OSI.906 and ABT.888, while low-risk group was more sensitive to Sorafenib. Three lncRNAs, FALEC, AC083967.1 and AC010997.4, were highly expressed in serum of COAD patients, and the AUC was 0.772, 0.726 and 0.714, respectively, indicating their valuable diagnostic value.

CONCLUSIONS

Our research constructed a prognostic signature based on 7 CRLs and found three promising diagnostic markers for COAD patients. Our results provided a reference to the personalized immunotherapy strategies.

LINC02875 Upregulation Contributed to Poor Prognosis for the Hepatocellular Carcinoma and Progression for the Cancerous Cells

The prognostic implications and physiological effect of LINC02875 are unknown in hepatocellular carcinoma (HCC). We sought to examine the prognostic value of LINC02875 in HCC and assessed its role in HCC cellular function. LINC02875 expression was evaluated by RT-qPCR in HCC specimens and cell lines. LINC02875 expression was subjected to assess the correlation with clinical parameters by Chi-squared test and overall survival by Kaplan - Meier curve and Cox regression analysis. The effects of LINC02875 on the biological characteristics of HCC cells were studied by MTS and Transwell assay. LINC02875 was high-expressed in HCC, and this was associated with unfavorable clinical features and poor prognosis of HCC, especially HBV-related HCC. Knockdown of LINC02875 inhibited the proliferation, migration, and invasion of HCC cells. miR-485-5p was a downstream microRNA of LINC02875. LINC02875 affects the prognosis of HCC patients, especially HBV-related ones. LINC02875 represents a suitable therapeutic target for HCC.

Ferroptosis-Related Long Noncoding RNAs Have Excellent Predictive Ability for Multiomic Characteristics of Bladder Cancer

Background

The role of ferroptosis-related long non-coding RNAs (lncRNAs) in bladder cancer remains elusive. This study is aimed at examining the prognostic role of ferroptosis-related lncRNAs in bladder cancer.

Materials and Methods

The transcriptomic matrix and clinical information of patients with bladder cancer were obtained from The Cancer Genome Atlas (TCGA) database. A ferroptosis-related lncRNA signature was developed via the least absolute shrinkage and selection operator (LASSO) analysis using data from the training cohort, and the signature was further validated using data from the test cohort. The role of AC006160.1, the most significant lncRNA in the risk signature, was examined in various cell lines including SV-HUC-1, BIU-87, HT-1376, T24, RT4, RT-112, 5637, and UMUC3. The pcDNA3.1-AC006160.1 plasmid was constructed and transfected into the bladder cancer cell lines T24 and BIU-87. In addition, cell proliferation, colony formation, transwell, and wound healing assays were performed to examine the biological function of AC006160.1 in T24 and BIU-87 cell lines.

Results

Two clusters were identified through consensus clustering based on prognostic ferroptosis-related lncRNAs. A 5-lncRNA risk signature was successfully constructed using data from the training cohort and validated using data from the test cohort. The risk signature had excellent ability to predict survival outcomes, clinical stages, pathological grades, expression of immune checkpoints, and immunotherapeutic responses in bladder cancer samples. Furthermore, AC006160.1 expression was found to be lower in the cancer cell lines BIU-87, T24, RT4, RT-112, and 5637 than in the normal control cell line SV-HUC-1. Cell proliferation, colony formation, transwell migration, and wound healing assays validated that overexpression of AC006160.1 significantly inhibited the proliferation and invasion abilities of both T24 and BIU-87 cells. Drug sensitivity analysis revealed that patients with high expression of AC006160.1 were sensitive to metformin and methotrexate, and the results were further validated via in vitro drug experiments.

Conclusions

Ferroptosis-related lncRNAs play a vital role in predicting the multiomic characteristics of bladder cancer. The lncRNA AC006160.1 serves as a protective factor for the development of bladder cancer.

Construction and validation of a cuproptosis-related lncRNA signature as a novel and robust prognostic model for colon adenocarcinoma

Background

Cuproptosis, a newly identified form of programmed cell death, is thought to play a role in tumorigenesis. Long non-coding RNAs (lncRNAs) are reported to be associated with tumor progression and prognosis in colon adenocarcinoma (COAD). However, the role and prognostic value of cuproptosis-related lncRNAs in COAD remains unknown. This study is devoted to constructing and validating a cuproptosis-related lncRNA signature that can predict COAD patient outcomes using bioinformatics methods.

Methods

The COAD mRNA and lncRNA expression profiles and corresponding clinical data were downloaded from The Cancer Genome Atlas (TCGA) database and 2,567 cuproptosis-related lncRNAs were obtained. A 10 cuproptosis-related-lncRNA prognostic signature was then constructed using the least absolute shrinkage and selection operator (LASSO) algorithm and Cox regression model and patients were divided into high- and low-risk groups. Kaplan-Meier analysis, receiver operating characteristic (ROC) curve, and a nomogram were employed to evaluate the predictive power of the signature. The immune characteristics and drug sensitivity were also investigated based on the signature. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) was performed to verify the risk model. In vitro experiments were conducted to validate the expression of the ten lncRNAs during cuproptosis.

Results

The high-risk group was associated with shorter overall survival (OS) time in COAD patients (p&lt;0.001). Multivariate Cox regression indicated that a high-risk score was an independent risk factor for poor prognosis (p&lt;0.001). ROC curve analysis was performed to confirm the validity of the signature (area under the curve (AUC) at 3 years: 0.879). Gene Ontology (GO) enrichment analysis revealed that the signature was highly correlated with the immune response in biological processes. The immune function, the score of the immune cells, and the expression of immune checkpoints were significantly different between the two risk groups. Three drugs, LAQ824, FH535, YM155, were found to be more sensitive in the high-risk group. Finally, the expression levels of the ten lncRNAs comprising the signature were tested by qRT-PCR.

Conclusion

A ten-cuproptosis-related lncRNA signature was constructed that provided promising insights into personalized prognosis and drug selection among COAD patients.

N7-methylguanosine-related lncRNAs: Predicting the prognosis and diagnosis of colorectal cancer in the cold and hot tumors

Background: 7-Methylguanosine(m7G) contributes greatly to its pathogenesis and progression in colorectal cancer. We proposed building a prognostic model of m7G-related LncRNAs. Our prognostic model was used to identify differences between hot and cold tumors.

Methods: The study included 647 colorectal cancer patients (51 cancer-free patients and 647 cancer patients) from The Cancer Genome Atlas (TCGA). We identified m7G-related prognostic lncRNAs by employing the univariate Cox regression method. Assessments were conducted using univariate Cox regression, multivariate Cox regression, receiver operating characteristics (ROC), nomogram, calibration curves, and Kaplan-Meier analysis. All of these procedures were used with the aim of confirming the validity and stability of the model. Besides these two analyses, we also conducted half-maximal inhibitory concentration (IC50), immune analysis, principal component analysis (PCA), and gene set enrichment analysis (GSEA). The entire set of m7G-related (lncRNAs) with respect to cold and hot tumors has been divided into two clusters for further discussion of immunotherapy.

Results: The risk model was constructed with 17 m7G-related lncRNAs. A good correlation was found between the calibration plots and the prognosis prediction in the model. By assessing IC50 in a significant way across risk groups, systemic treatment can be guided. By using clusters, it may be possible to distinguish hot and cold tumors effectively and to aid in specific therapeutic interventions. Cluster 1 was identified as having the highest response to immunotherapy drugs and thus was identified as the hot tumor.

Conclusion: This study shows that 17 m7G-related lncRNA can be used in clinical settings to predict prognosis and use them to determine whether a tumor is cold or hot in colorectal cancer and improve the individualization of treatment.

HOXA1, a breast cancer oncogene

More than 25 years ago, the first literature records mentioned HOXA1 expression in human breast cancer. A few years later, HOXA1 was confirmed as a proper oncogene in mammary tissue. In the following two decades, molecular data about the mode of action of the HOXA1 protein, the factors contributing to activate and maintain HOXA1 gene expression and the identity of its target genes have accumulated and provide a wider view on the association of this transcription factor to breast oncogenesis. Large-scale transcriptomic data gathered from wide cohorts of patients further allowed refining the relationship between breast cancer type and HOXA1 expression. Several recent reports have reviewed the connection between cancer hallmarks and the biology of HOX genes in general. Here we take HOXA1 as a paradigm and propose an extensive overview of the molecular data centered on this oncoprotein, from what its expression modulators, to the interactors contributing to its oncogenic activities, and to the pathways and genes it controls. The data converge to an intricate picture that answers questions on the multi-modality of its oncogene activities, point towards better understanding of breast cancer aetiology and thereby provides an appraisal for treatment opportunities.

Comprehensive Analyses of Stromal-Immune Score-Related Competing Endogenous RNA Networks In Colon Adenocarcinoma

Although recent clinical investigations emphasize the roles of myriad diversities of RNAs in stromal and immune components in the tumor microenvironment, especially in colon adenocarcinoma, however, analyses of “competing endogenous RNAs (ceRNA)” network in association with stromal and immune scores have yet to be determined. This study was conducted to explore the regulatory mechanisms of a stromal-immune score-based ceRNA network in colon adenocarcinoma. Stromal and immune scores of colon adenocarcinoma tumor samples were calculated by using the ESTIMATE algorithm. Differential expression analysis between samples with high/low stromal and immune scores was performed, followed by functional annotation for the overlapping DEmRNAs. The ceRNA network was constructed by differential expression analysis, prediction of RNA-RNA interaction, and correlation with clinicopathological parameters of the patients, which were further verified by external datasets and experiments. Colon adenocarcinoma patients having higher immune scores exhibited prolonged overall survival. RNA dataset analyses from TCGA revealed aberrant expressions of a total of 2052 mRNAs, 108 lncRNAs, and 70 miRNAs between high and low stromal/immune groups. Functional annotation mapped the differentially overexpressed mRNAs for immune-associated GO terms. To construct the ceRNA network, a total of 48 lncRNAs, 40 miRNAs, and 199 mRNAs were sorted out. A dysregulated ceRNA network consisting of 6 lncRNAs, 11 miRNAs, and 39 mRNAs was constructed by comparing RNA expressions between cancer as well as adjacent normal tissues. The ceRNA regulatory axis “MIAT/miR-532-3p/STC1” was regarded as a potential hit by the comprehensive analysis. The RT-qPCR assay showed upregulation of MIAT and STC1 while downregulation of hsa-miR-532-3p expression in cancer. Thus, our study highlights the potential role of a stromal-immune score-based ceRNA network in the colon adenocarcinoma microenvironment. The ceRNA axis MIAT/miR-532-3p/STC1 could serve as a promising therapeutic target for colon adenocarcinoma.

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.

The functions and roles of sestrins in regulating human diseases

Sestrins (Sesns), highly conserved stress-inducible metabolic proteins, are known to protect organisms against various noxious stimuli including DNA damage, oxidative stress, starvation, endoplasmic reticulum (ER) stress, and hypoxia. Sesns regulate metabolism mainly through activation of the key energy sensor AMP-dependent protein kinase (AMPK) and inhibition of mammalian target of rapamycin complex 1 (mTORC1). Sesns also play pivotal roles in autophagy activation and apoptosis inhibition in normal cells, while conversely promoting apoptosis in cancer cells. The functions of Sesns in diseases such as metabolic disorders, neurodegenerative diseases, cardiovascular diseases, and cancer have been broadly investigated in the past decades. However, there is a limited number of reviews that have summarized the functions of Sesns in the pathophysiological processes of human diseases, especially musculoskeletal system diseases. One aim of this review is to discuss the biological functions of Sesns in the pathophysiological process and phenotype of diseases. More significantly, we include some new evidence about the musculoskeletal system. Another purpose is to explore whether Sesns could be potential biomarkers or targets in the future diagnostic and therapeutic process.

Prognostic Potential of Secreted Modular Calcium-Binding Protein 1 in Low-Grade Glioma

Background: Secreted modular calcium-binding protein 1 (SMOC1) belongs to a family of matricellular proteins; it was involved in embryo development, endothelial cell proliferation, angiogenesis, integrin–matrix interactions, cell adhesion, and regulation of glucose metabolism. Previous studies showed that the expression of SMOC1 was increased in some tumors. However, the prognostic value and the biological function of SMOC1 in tumor remain unclear.

Methods: In this study, we explored the expression profile and prognostic value of SMOC1 in pan-cancers, especially glioma, via multiple databases, including Oncomine, Gene Expression Profiling Interactive 2, PrognoScan, Kaplan–Meier plotter, and the Chinese Glioma Genome Atlas database. Furthermore, LinkedOmics was used to identify the genes coexpressed with SMOC1 and to perform Kyoto Encyclopedia of Genes and Genomes pathways and Gene Ontology analysis in low-grade glioma (LGG). Also, the Cancer Single-Cell State Atlas database was used to evaluate the correlation between SMOC1 expression and functional state activities in glioma cells. In addition, the Tumor Immune Estimation Resource and TISIDB databases were used to evaluate the correlations between SMOC1 expression and tumor-infiltrating immune cells in the tumor microenvironment.

Results: Compared with normal brain tissues, the expression of SMOC1 was increased in LGG tissues. The higher expression of SMOC1 was significantly correlated with better survival of LGG patients. Additionally, functional analyses showed that the SMOC1 coexpressed genes were inhibited in processes such as response to type I interferon and interferon-gamma, lymphocyte-mediated immunity, leukocyte migration, adaptive immune response, neutrophil-mediated immunity, T cell activation, and pathways including EMC–receptor interaction, Th17 cell differentiation, and leukocyte trans-endothelial migration in LGG. Moreover, the expression of SMOC1 was correlated with stemness, hypoxia, EMT, and metastasis of glioma cells. Additionally, the expression of SMOC1 expression was negatively correlated with levels of infiltrating B cells, CD8⁺ T cells, CD4⁺ T cells, macrophages, neutrophils and dendritic cells, and gene markers of most immune cells in LGG.

Conclusion: Our results suggest that SMOC1 could be a potential biomarker to determine prognosis and might play a specific role in the tumor microenvironment of glioma, thereby influencing the development and progression of glioma. These findings provide some new insights for further investigation.

Using BioPAX-Parser (BiP) to enrich lists of genes or proteins with pathway data

BACKGROUND

Pathway enrichment analysis (PEA) is a well-established methodology for interpreting a list of genes and proteins of interest related to a condition under investigation. This paper aims to extend our previous work in which we introduced a preliminary comparative analysis of pathway enrichment analysis tools. We extended the earlier work by providing more case studies, comparing BiP enrichment performance with other well-known PEA software tools.

METHODS

PEA uses pathway information to discover connections between a list of genes and proteins as well as biological mechanisms, helping researchers to overcome the problem of explaining biological entity lists of interest disconnected from the biological context.

RESULTS

We compared the results of BiP with some existing pathway enrichment analysis tools comprising Centrality-based Pathway Enrichment, pathDIP, and Signaling Pathway Impact Analysis, considering three cancer types (colorectal, endometrial, and thyroid), for a total of six datasets (that is, two datasets per cancer type) obtained from the The Cancer Genome Atlas and Gene Expression Omnibus databases. We measured the similarities between the overlap of the enrichment results obtained using each couple of cancer datasets related to the same cancer.

CONCLUSION

As a result, BiP identified some well-known pathways related to the investigated cancer type, validated by the available literature. We also used the Jaccard and meet-min indices to evaluate the stability and the similarity between the enrichment results obtained from each couple of cancer datasets. The obtained results show that BiP provides more stable enrichment results than other tools.

Construction and Analysis of a Colorectal Cancer Prognostic Model Based on N6-Methyladenosine-Related lncRNAs

Given the relatively poor understanding of the expression and functional effects of the N6-methyladenosine (m6A) RNA methylation on colorectal cancer (CRC), we attempted to measure its prognostic value and clinical significance. We comprehensively screened 37 m6A-related prognostic long non-coding RNAs (lncRNAs) with significant differences in expression based on 21 acknowledged regulators of m6A modification and data on 473 colorectal cancer tissues and 41 para-cancer tissues obtained from the TCGA database. Accordingly, we classified 473 CRC patients into two clusters by consensus clustering on the basis of significantly different survival outcomes. We also found a potential correlation between m6A-related prognostic lncRNAs and BRAF-KRAS expression, as well as immune cell infiltration. Then, we established a prognostic model by selecting 16 m6A-related prognostic lncRNAs via LASSO Cox analysis and grouped the CRC patients into low- and high-risk groups to calculate risk scores. Then, we performed stratified sampling to validate and confirm our model by categorising the 473 samples into a training group (N = 208) and a testing group (N = 205) in a 1:1 ratio. The survival curve showed a distinct clinical outcome in the low- and high-risk subgroups. We reconfirmed the reliability and independence of the prognostic model through various measures: risk curve, heat map and univariate and multivariate Cox analyses. To ensure that the outcomes were applicable to clinical settings, we performed stratified analyses on different clinical features, such as age, lymph node status and clinical stage. CRC patients with downregulated m6A-related gene expression, lower immune score, distant metastasis, lymph node metastasis or more advanced clinical staging had higher risk scores, indicating less-desirable outcomes. Moreover, we explored the immunology of colorectal cancer cells. The risk score showed positive correlations with eosinophils, M2 macrophages and neutrophils. In summary, our effort revealed the significance of m6A RNA methylation regulators in colorectal cancer, and the prognostic model we constructed may be used as an essential reference for predicting the outcome of CRC patients.

Secreted modular calcium-binding protein 1 binds and activates thrombin to account for platelet hyperreactivity in diabetes

Secreted modular calcium-binding protein 1 (SMOC1) is an osteonectin/SPARC-related matricellular protein, whose expression is regulated by microRNA-223 (miR-223). Given that platelets are rich in miR-223, this study investigated the expression of SMOC1 and its contribution to platelet function. Human and murine platelets expressed SMOC1, whereas platelets from SMOC1+/- mice did not present detectable mature SMOC1 protein. Platelets from SMOC1+/- mice demonstrated attenuated responsiveness to thrombin (platelet neutrophil aggregate formation, aggregation, clot formation, Ca2+ increase, and β3 integrin phosphorylation), whereas responses to other platelet agonists were unaffected. SMOC1 has been implicated in transforming growth factor-β signaling, but no link to this pathway was detected in platelets. Rather, the SMOC1 Kazal domain directly bound thrombin to potentiate its activity in vitro, as well as its actions on isolated platelets. The latter effects were prevented by monoclonal antibodies against SMOC1. Platelets from miR-223-deficient mice expressed high levels of SMOC1 and exhibited hyperreactivity to thrombin that was also reversed by preincubation with monoclonal antibodies against SMOC1. Similarly, SMOC1 levels were markedly upregulated in platelets from individuals with type 2 diabetes, and the SMOC1 antibody abrogated platelet hyperresponsiveness to thrombin. Taken together, we have identified SMOC1 as a novel thrombin-activating protein that makes a significant contribution to the pathophysiological changes in platelet function associated with type 2 diabetes. Thus, strategies that target SMOC1 or its interaction with thrombin may be attractive therapeutic approaches to normalize platelet function in diabetes.

Competing Endogenous RNA in Colorectal Cancer: An Analysis for Colon, Rectum, and Rectosigmoid Junction

BACKGROUND

Colorectal cancer (CRC) is a heterogeneous cancer. Its treatment depends on its anatomical site and distinguishes between colon, rectum, and rectosigmoid junction cancer. This study aimed to identify diagnostic and prognostic biomarkers using networks of CRC-associated transcripts that can be built based on competing endogenous RNAs (ceRNA).

METHODS

RNA expression and clinical information data of patients with colon, rectum, and rectosigmoid junction cancer were obtained from The Cancer Genome Atlas (TCGA). The RNA expression profiles were assessed through bioinformatics analysis, and a ceRNA was constructed for each CRC site. A functional enrichment analysis was performed to assess the functional roles of the ceRNA networks in the prognosis of colon, rectum, and rectosigmoid junction cancer. Finally, to verify the ceRNA impact on prognosis, an overall survival analysis was performed.

RESULTS

The study identified various CRC site-specific prognosis biomarkers: hsa-miR-1271-5p, NRG1, hsa-miR-130a-3p, SNHG16, and hsa-miR-495-3p in the colon; E2F8 in the rectum and DMD and hsa-miR-130b-3p in the rectosigmoid junction. We also identified different biological pathways that highlight differences in CRC behavior at different anatomical sites, thus reinforcing the importance of correctly identifying the tumor site.

CONCLUSIONS

Several potential prognostic markers for colon, rectum, and rectosigmoid junction cancer were found. CeRNA networks could provide better understanding of the differences between, and common factors in, prognosis of colon, rectum, and rectosigmoid junction cancer.

Tribbles Pseudokinases in Colorectal Cancer

The Tribbles family of pseudokinases controls a wide number of processes during cancer on-set and progression. However, the exact contribution of each of the three family members is still to be defined. Their function appears to be context-dependent as they can act as oncogenes or tumor suppressor genes. They act as scaffolds modulating the activity of several signaling pathways involved in different cellular processes. In this review, we discuss the state-of-knowledge for TRIB1, TRIB2 and TRIB3 in the development and progression of colorectal cancer. We take a perspective look at the role of Tribbles proteins as potential biomarkers and therapeutic targets. Specifically, we chronologically systematized all available articles since 2003 until 2020, for which Tribbles were associated with colorectal cancer human samples or cell lines. Herein, we discuss: (1) Tribbles amplification and overexpression; (2) the clinical significance of Tribbles overexpression; (3) upstream Tribbles gene and protein expression regulation; (4) Tribbles pharmacological modulation; (5) genetic modulation of Tribbles; and (6) downstream mechanisms regulated by Tribbles; establishing a comprehensive timeline, essential to better consolidate the current knowledge of Tribbles' role in colorectal cancer.

Identification prognosis-associated immune genes in colon adenocarcinoma

Colon adenocarcinoma (COAD) is one of the most prevalent malignant tumors worldwide. Immune genes (IGs) have a considerable correlation with tumor initiation and prognosis. The present paper aims to identify the prognosis value of IGs in COAD and conduct a prognosis model for clinical utility. Gene expression data of COAD were downloaded from The Cancer Genome Atlas (TCGA), screening and analyzing differentially expressed IGs by bioinformatics. Core genes were screened by univariate and multivariate Cox regression analyses. Survival analysis was appraised by the Kaplan–Meier method and the log-rank test. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Gene Set Enrichment Analysis (GSEA) were used to identify IGs’ relevant signal pathways. We predicted the overall survival (OS) by nomogram. Finally, a prognosis model was conducted based on 12 IGs (SLC10A2, CXCL3, NOX4, FABP4, ADIPOQ, IGKV1-33, IGLV6-57, INHBA, UCN, VIP, NGFR, and TRDC). The risk score was an independent prognostic factor, and a nomogram could accurately predict the OS of individual COAD patients. These results were validated in GSE39582, GSE12945, and GSE103479 cohorts. Functional enrichment analysis demonstrated that these IGs are mainly enriched in hormone secretion, hormone transport, lipid transport, cytokine–cytokine receptor interaction, and peroxisome proliferators-activated receptor signaling pathway. In summary, the risk score is an independent prognostic biomarker. We also excavated several IGs related to COAD’s survival and maybe potential biomarkers for COAD diagnosis and treatment.

Comprehensive analyses of correlation and survival reveal informative lncRNA prognostic signatures in colon cancer

BACKGROUND

Colon cancer is a commonly worldwide cancer with high morbidity and mortality. Long non-coding RNAs (lncRNAs) are involved in many biological processes and are closely related to the occurrence of colon cancer. Identification of the prognostic signatures of lncRNAs in colon cancer has great significance for its treatment.

METHODS

We first identified the colon cancer-related mRNAs and lncRNAs according to the differential analysis methods using the expression data in TCGA. Then, we performed correlation analysis between the identified mRNAs and lncRNAs by integrating their expression values and secondary structure information to estimate the co-regulatory relationships between the cancer-related mRNAs and lncRNAs. Besides, the competing endogenous RNA regulation network based on co-regulatory relationships was constructed to reveal cancer-related regulatory patterns. Meanwhile, we used traditional regression analysis (univariate Cox analysis, random survival forest analysis, and lasso regression analysis) to screen the cancer-related lncRNAs. Finally, by combining the identified colon cancer-related lncRNAs according to the above analyses, we constructed a risk prognosis model for colon cancer through multivariate Cox analysis and also validated the model in the colon cancer dataset in TCGA cohorts.

RESULTS

Six lncRNAs were found highly correlated with the overall survival of colon cancer patients, and a risk prognosis model based on them was constructed to predict the overall survival of colon cancer patients. In particular, EVX1-AS, ZNF667-AS1, CTC-428G20.6, and CTC-297N7.9 were first reported to be related to colon cancer by using our model, among which EVX1-AS and ZNF667-AS1 have been predicted to be related to colon cancer in LncRNADisease database.

CONCLUSIONS

This study identified the potential regulatory relationships between lncRNAs and mRNAs by integrating their expression values and secondary structure information and presented a significant 6-lncRNA risk prognosis model to predict the overall survival of colon cancer patients.

LncRNA LINC00467 acted as an oncogene in esophageal squamous cell carcinoma by accelerating cell proliferation and preventing cell apoptosis via the miR-485-5p/DPAGT1 axis

BACKGROUND AND AIM

Esophageal carcinoma has been regarded as one of the top 10 common malignancies globally. Esophageal squamous cell carcinoma (ESCC) is an important subtype of esophageal carcinoma with approximately 20% survival rate. Long noncoding RNAs were documented to regulate the occurrence or progression of several tumors. However, neither the biological role nor the molecular mechanism of LINC00467 has been explored. This research is aimed to investigating the regulatory mechanism of LINC00467 in ESCC.

METHODS

In this study, a series of experiments including reverse transcription-quantitative polymerase chain reaction, Cell Counting Kit-8, luciferase reporter, western blot, and RNA immunoprecipitation were designed and conducted to explore the potential function and mechanism of LINC00467 in ESCC.

RESULTS

According to experimental results, we found out upregulated LINC00467 improved cell proliferation, but hindered cell apoptosis. In mechanism, miR-485-5p was predicted, screened out, and validated to combine with LINC00467, which displayed lower expression in ESCC. Additionally, miR-485-5p negatively regulated and directly targeted DPAGT1. Rescue assays suggested that DPAGT1 amplification was able to recover the influence of LINC00467 deficiency on cell proliferation and apoptosis. Furthermore, knockdown of LINC00467 suppressed tumor growth in vivo.

CONCLUSION

We proved that LINC00467 acted as an oncogene in ESCC by accelerating cell proliferation and preventing cell apoptosis via miR-485-5p/DPAGT1 axis. This may provide a potential diagnostic marker for ESCC treatment.

Construction and Analysis of Survival-Associated Competing Endogenous RNA Network in Lung Adenocarcinoma

Increasing evidence has shown that noncoding RNAs play significant roles in the initiation, progression, and metastasis of tumours via participating in competing endogenous RNA (ceRNA) networks. However, the survival-associated ceRNA in lung adenocarcinoma (LUAD) remains poorly understood. In this study, we aimed to investigate the regulatory mechanisms underlying ceRNA in LUAD to identify novel prognostic factors. mRNA, lncRNA, and miRNA sequencing data obtained from the GDC data portal were utilized to identify differentially expressed (DE) RNAs. Survival-related RNAs were recognized using univariate Kaplan-Meier survival analysis. We performed functional enrichment analysis of survival-related mRNAs using the clusterProfiler package of R and STRING. lncRNA-miRNA and miRNA-mRNA interactions were predicted based on miRcode, Starbase, and miRanda. Subsequently, the survival-associated ceRNA network was constructed for LUAD. Multivariate Cox regression analysis was used to identify prognostic factors. Finally, we acquired 15 DE miRNAs, 49 DE lncRNAs, and 843 DE mRNAs associated with significant overall survival. Functional enrichment analysis indicated that survival-related DE mRNAs were enriched in cell cycle. The survival-associated lncRNA-miRNA-mRNA ceRNA network was constructed using five miRNAs, 49 mRNAs, and 21 lncRNAs. Furthermore, seven hub RNAs (LINC01936, miR-20a-5p, miR-31-5p, TNS1, TGFBR2, SMAD7, and NEDD4L) were identified based on the ceRNA network. LINC01936 and miR-31-5p were found to be significant using the multifactorial Cox regression model. In conclusion, we successfully constructed a survival-related lncRNA-miRNA-mRNA ceRNA regulatory network in LUAD and identified seven hub RNAs, which provide novel insights into the regulatory molecular mechanisms associated with survival of LUAD, and identified two independent prognostic predictors for LUAD.

A prognostic gene expression signature for oropharyngeal squamous cell carcinoma

BACKGROUND

Robust prognostic stratification of patients with oropharyngeal squamous cell carcinoma (OPSCC) is important for developing individualized treatment plans. This study was conducted to develop and validate a clinically feasible prognostic classifier based on transcriptome-wide gene expression profiles.

METHODS

Tumor tissues were collected from 208 OPSCC patients treated at Washington University in St. Louis and 130 OPSCC patients treated at Vanderbilt University, used for model training and validation, respectively. OPSCC patients (n = 70) from the TCGA cohort were also included for independent validation. Based on RNA-seq profiling data, Cox proportional hazards regression analysis was performed to identify genes associated with disease outcomes. Then, Lasso-penalized multivariate survival models were constructed to identify biomarker genes for developing a prognostic gene signature.

FINDINGS

A 60-gene signature was identified by RNA-seq profiling analysis. Computed risk score of the gene signature was significantly predictive of 5-year overall survival of the training cohort (Hazard ratio (HR) 28·32, P = 4·3E-41). Subgroup analysis stratified by HPV status revealed that the signature was prognostic in HPV-positive OPSCC patients (HR 30·55, P = 7·0E-37) and was independent of clinical features. Importantly, the gene signature was validated in two independent patient cohorts, including the TCGA cohort (HR 3·94, P = 0·0018) and the Vanderbilt cohort (HR 8·50, P = 5·7E-09) for overall survival.

INTERPRETATION

The prognostic gene signature is a robust tool for risk stratification of OPSCC patients. The signature remains prognostic among HPV-positive OPSCC patients.

FUNDING

National Institutes of Health.

Comprehensive analysis of competitive endogenous RNAs network reveals potential prognostic lncRNAs in gastric cancer

Long non-coding RNAs (lncRNAs) are key regulators of a range of human diseases, including various cancers, with multiple previous studies having explored lncRNA dysregulation in the context of gastric cancer (GC). The present study sought to expand upon these previous results by downloading lncRNA, mRNA, and microRNA (miRNA) expression profiles derived from 180 GC tissues and 24 normal control tissues within the Cancer Genome Atlas (TCGA) database. These datasets were then interrogated to identify GC-related differentially expressed (DE) RNAs (|fold change| ≥ 2, FDR< 0.01), leading to the identification of 1946 DE lncRNAs, 123 DE miRNAs, and 3159 DE mRNAs. These results were then used to generate a putative GC-related competitive endogenous RNA (ceRNA) network composed of 131 lncRNAs, 9 miRNAs, and 78 mRNAs. Subsequent survival analyses based upon this network revealed 17 of these lncRNAs to be significantly associated with GC patient survival (P < 0.05). Further multivariable Cox regression and lasso analyses allowed for the construction of an 8-lncRNA risk score that was able to effectively predict GC patient survival with good discriminative ability. The Kaplan-Meier Plotter database further confirmed that network hub genes that were related to these 8 lncRNAs were associated with GC patient prognosis (P < 0.05). As the ceRNA network in the present study was constructed with a focus on both disease stage and differential gene expression, it represents a key resource that will offer valuable insights into the mechanistic roles of ceRNA pathways in GC development and progression.

A novel prognostic model based on multi-omics features predicts the prognosis of colon cancer patients

Background

As a common malignant tumor in the colon, colon cancer (CC) has high incidence and recurrence rates. This study is designed to build a prognostic model for CC.

Methods

The gene expression dataset, microRNA‐seq dataset, copy number variation (CNV) dataset, DNA methylation dataset, and transcription factor (TF) dataset of CC were downloaded from UCSC Xena database. Using limma package, the differentially methylated genes (DMGs), and differentially expressed genes (DEGs) and miRNAs (DEMs) were identified. Based on random forest method, prognostic model for each omics dataset were constructed. After the omics features related to prognosis were selected using logrank test, the prognostic model based on multi‐omics features was built. Finally, the clinical phenotypes correlated with prognosis were screened using Kaplan–Meier survival analysis, and the nomogram model was established.

Results

There were 1625 DEGs, 268 DEMs, and 386 DMGs between the tumor and normal samples. A total of 105, 29, 159, five, and six genes/sites significantly correlated with prognosis were identified in the gene expression dataset (GABRD), miRNA‐seq dataset (miR‐1271), CNV dataset (RN7SKP247), DNA methylation dataset (cg09170112 methylation site [located in SFSWAP]), and TF dataset (SIX5), respectively. The prognostic model based on multi‐omics features was more effective than those based on single omics dataset. The number of lymph nodes, pathologic_M stage, and pathologic_T stage were the clinical phenotypes correlated with prognosis, based on which the nomogram model was constructed.

Conclusion

The prognostic model based on multi‐omics features and the nomogram model might be valuable for the prognostic prediction of CC.

MicroRNAs Associated With Colon Cancer: New Potential Prognostic Markers and Targets for Therapy

MicroRNAs (miRNAs) are a kind of non-coding RNA (ncRNA) that regulate the expression of target genes and play a role in the occurrence and development of cancers. Colon cancer (COAD) is the second most common cause of cancer-related mortality. However, the prognostic value of miRNAs in COAD is still confusing. In this study, we obtain miRNAs and messenger RNAs (mRNAs) expression profiles of COAD from the Cancer Genome Atlas (TCGA) database. After preliminary data screening and preprocessing, we acquire the expression data of 894 miRNAs and 17,019 mRNAs. Then, compared with the normal samples, 39 upregulated miRNAs and 54 downregulated miRNAs are identified by differential expression analysis. Furthermore, we obtain 1,487 upregulated mRNAs and 2,847 downregulated mRNAs. We confirm nine key miRNAs related to the survival rate of COAD patients. Moreover, by using bioinformatics methods, we get 461 common genes from both the target genes of these nine key miRNAs and differentially expressed mRNAs. Through analyzing the protein-protein interaction (PPI) network of these 461 common genes and survival analysis, we confirm five hub genes as promising biomarkers for COAD prognosis. It is worth mentioning that no previous reports have found that PGR and KCNB1 are related to COAD. We expect these key miRNAs and hub genes will provide a new way for the study of COAD.

Data Mining and Expression Analysis of Differential lncRNA ADAMTS9-AS1 in Prostate Cancer

Long noncoding RNAs (lncRNAs) play important roles in the regulation of gene expression by acting as competing endogenous RNAs (ceRNAs). However, the roles of lncRNA-associated ceRNAs in oncogenesis are not fully understood. The present study aims to determine whether a ceRNA network can serve as a prognostic marker in human prostate cancer (PCa). In order to identify a ceRNA network and the key lncRNAs in PCa, we constructed a differentially expressed lncRNAs (DELs)-differentially expressed miRNAs (DEMis)-differentially expressed mRNAs (DEMs) regulatory network based on the ceRNA theory using data from the Cancer Genome Atlas (TCGA). We found that the DELs-DEMis-DEMs network was composed of 27 DELs nodes, seven DEMis nodes, and three DEMs nodes. The 27 DELs were further analyzed with several public databases to provide meaningful information for understanding the functional roles of lncRNAs in regulatory networks in PCa. We selected ADAMTS9-AS1 to determine its role in PCa and found that ADAMTS9-AS1 significantly influences tumor cell growth and proliferation, suggesting that it plays a tumor suppressive role. In addition, ADAMTS9-AS1 functioned as ceRNA, effectively becoming a sponge for hsa-mir-96 and modulating the expression of PRDM16. These results suggest that ceRNAs could accelerate biomarker discovery and therapeutic strategies for PCa.

Long Noncoding RNA SNHG7, a Molecular Sponge for microRNA-485, Promotes the Aggressive Behavior of Cervical Cancer by Regulating PAK4

Purpose

A long noncoding RNA called small nucleolar RNA host gene 7 (SNHG7) is known to be a key regulator of biological processes in multiple human cancer types. In this study, our aims were to determine the expression status of SNHG7 in cervical cancer, to figure out the detailed roles of SNHG7 in cervical cancer cells, and to identify the mechanism underlying the activity of SNHG7 in cervical cancer.

Methods

Reverse-transcription quantitative PCR was performed to measure SNHG7 expression in cervical cancer. A Cell Counting Kit-8 assay, flow-cytometric analysis, cell migration and invasion assays, and a tumor xenograft experiment were conducted to respectively determine the effects of SNHG7 on cervical cancer cell proliferation, apoptosis, migration, and invasion in vitro and tumor growth in vivo.

Results

SNHG7 was found to be markedly upregulated in cervical cancer tissues and cell lines. Higher SNHG7 expression significantly correlated with FIGO stage, lymph node metastasis, the depth of cervical invasion, and shorter overall survival in patients with cervical cancer. Functional experiments indicated that a SNHG7 knockdown attenuated proliferation, migration, and invasiveness and promoted apoptosis of cervical cancer cells in vitro. The SNHG7 knockdown also slowed tumor growth in vivo. Further investigation showed that SNHG7 acts as a competing endogenous RNA for microRNA-485 (miR-485) in cervical cancer cells, and the inhibitory actions of the SNHG7 knockdown on the malignant phenotype were reversed by miR-485 inhibition. P21-activated kinase 4 (PAK4) was identified as a direct target gene of miR-485 in cervical cancer, and PAK4 expression was promoted by SNHG7.

Conclusion

SNHG7 functions as an oncogenic RNA in cervical cancer, competitively binds to miR-485, and thereby upregulates PAK4. This SNHG7–miR-485–PAK4 regulatory network may provide insights into the pathogenesis of cervical cancer, and can help in the identification of novel diagnostic and therapeutic approaches for cervical cancer.

Function and mechanisms of microRNA-20a in colorectal cancer

Colorectal cancer (CRC) is the third most common malignancy and the second leading cause of cancer-associated mortality worldwide. CRC currently has no specific biomarkers to promote its diagnosis and treatment and the underlying mechanisms regulating its pathogenesis have not yet been determined. MicroRNAs (miRs) are small, non-coding RNAs that exhibit regulatory functions and have been demonstrated to serve a crucial role in the post-transcriptional regulatory processes of gene expression that is associated with cell physiology and disease progression. Recently, abnormal miR-20a expression has been identified in a number of cancers types and this has become a novel focus within cancer research. High levels of miR-20a expression have been identified in CRC tissues, serum and plasma. In a recent study, miR-20a was indicated to be present in feces and to exhibit a high sensitivity to CRC. Therefore, miR-20a may be used as a marker for CRC and an indicator that can prevent the invasive examination of patients with this disease. Changes in the expression of miR-20a during chemotherapy can be used as a biomarker for monitoring resistance to treatment. In conclusion, miR-20a exhibits the potential for clinical application as a novel diagnostic biomarker and therapeutic target for use in patients with CRC. The present study focused on the role and mechanisms of miR-20a in CRC.

A Circulating miRNA-Based Scoring System Established by WGCNA to Predict Colon Cancer

Introduction

Circulation microRNAs (miRNAs) perform as potential diagnostic biomarkers of many kinds of cancers. This study is aimed at identifying circulation miRNAs as diagnostic biomarkers in colon cancer.

Methods

We conducted a weighted gene coexpression network analysis (WGCNA) in miRNAs to find out the expression pattern among circulation miRNAs by using a “WGCNA” package in R. Correlation analysis was performed to find cancer-related modules. Differentially expressed miRNAs (DEmiRs) in colon cancer were identified by a “limma” package in R. Hub gene analysis was conducted for these DEmiRs in the cancer-related modules by the “closeness” method in cytoscape software. Then, logistic regression was performed to identify the independent risk factors, and a scoring system was constructed based on these independent risk factors. Then, we use data from the GEO database to confirm the reliability of this scoring system.

Results

A total of 9 independent coexpression modules were constructed based on the expression levels of 848 miRNAs by WGCNA. After correlation analysis, green (cor = 0.77, p = 3 × 10^‐25) and yellow (cor = 0.65, p = 6 × 10^‐16) modules were strongly correlated with cancer development. 20 hub genes were found after hub gene analysis in these DEmiRs by cytoscape. Among all these hub genes, hsa-miR-23a-3p (OR = 2.6391, p = 6.23 × 10^‐5) and hsa-miR-663a (OR = 1.4220, p = 0.0069) were identified as an independent risk factor of colon cancer by multivariate regression. Furthermore, a scoring system was built to predict the probability of colon cancer based on both of these miRNAs, the area under the curve (AUC) of which was 0.828. Data from GSE106817 and GSE112264 was used to confirm this scoring system. And the AUC of them was 0.980 and 0.917, respectively.

Conclusion

We built a scoring system based on circulation hub miRNAs found by WGCNA to predict the development of colon cancer.