Integrated analysis of RNA-binding proteins in human colorectal cancer

Anti-Th/To Antibodies in Scleroderma: Good Prognosis or Serious Concern?

Systemic sclerosis (SSc) represents a rare and intricate autoimmune connective tissue disease, the pathophysiology of which has not been fully understood. Its key features include progressive fibrosis of the skin and internal organs, vasculopathy and aberrant immune activation. While various anti-nuclear antibodies can serve as biomarkers for the classification and prognosis of SSc, their direct role in organ dysfunction remains unclear. Anti-Th/To antibodies are present in approximately 5% of SSc patients, and are particularly prevalent among those with the limited subtype of the disease. Although the presence of these autoantibodies is associated with a mild course of the disease, there is a strong connection between them and severe clinical manifestations of SSc, including interstitial lung disease, pulmonary arterial hypertension and gastrointestinal involvement. Also, the additional clinical correlations, particularly with malignancies, need further research. Moreover, the disease's course seems to be influenced by antibodies, specific serum cytokines and TLR signaling pathways. Understanding the relationships between presence of anti-Th/To, its molecular aspects and response to treatment options is crucial for the development of novel, personalized therapeutic techniques and should undergo profound analysis in future studies.

Targeting the "tumor microenvironment": RNA-binding proteins in the spotlight in colorectal cancer therapy

Colorectal cancer (CRC) is the third most common cancer and has the second highest mortality rate among cancers. The development of CRC involves both genetic and epigenetic abnormalities, and recent research has focused on exploring the ex-transcriptome, particularly post-transcriptional modifications. RNA-binding proteins (RBPs) are emerging epigenetic regulators that play crucial roles in post-transcriptional events. Dysregulation of RBPs can result in aberrant expression of downstream target genes, thereby affecting the progression of colorectal tumors and the prognosis of patients. Recent studies have shown that RBPs can influence CRC pathogenesis and progression by regulating various components of the tumor microenvironment (TME). Although previous research on RBPs has primarily focused on their direct regulation of colorectal tumor development, their involvement in the remodeling of the TME has not been systematically reported. This review aims to highlight the significant role of RBPs in the intricate interactions within the CRC tumor microenvironment, including tumor immune microenvironment, inflammatory microenvironment, extracellular matrix, tumor vasculature, and CRC cancer stem cells. We also highlight several compounds under investigation for RBP-TME-based treatment of CRC, including small molecule inhibitors such as antisense oligonucleotides (ASOs), siRNAs, agonists, gene manipulation, and tumor vaccines. The insights gained from this review may lead to the development of RBP-based targeted novel therapeutic strategies aimed at modulating the TME, potentially inhibiting the progression and metastasis of CRC.

Development and validation of an RBP gene signature for prognosis prediction in colorectal cancer based on WGCNA

BACKGROUND

RNA binding proteins (RBPs) have been implicated in oncogenesis and progression in various cancers. However, the potential value of RBPs as prognostic indicators and therapeutic targets in colorectal cancer (CRC) requires further investigation.

METHODS

Four thousand eighty two RBPs were collected from literature. The weighted gene co-expression network analysis (WGCNA) was performed to identify prognosis-related RBP gene modules based on the data attained from the TCGA cohorts. LASSO algorithm was conducted to establish a prognostic risk model, and the validity of the proposed model was confirmed by an independent GEO dataset. Functional enrichment analysis was performed to reveal the potential biological functions and pathways of the signature and to estimate tumor immune infiltration. Potential therapeutic compounds were inferred utilizing CMap database. Expressions of hub genes were further verified through the Human Protein Atlas (HPA) database and RT-qPCR.

RESULTS

One thousand seven hundred thirty four RBPs were differently expressed in CRC samples and 4 gene modules remarkably linked to the prognosis were identified, based on which a 12-gene signature was established for prognosis prediction. Multivariate Cox analysis suggested this signature was an independent predicting factor of overall survival (P < 0.001; HR:3.682; CI:2.377-5.705) and ROC curves indicated it has an effective predictive performance (1-year AUC: 0.653; 3-year AUC:0.673; 5-year AUC: 0.777). GSEA indicated that high risk score was correlated with several cancer-related pathways, including cytokine-cytokine receptor cross talk, ECM receptor cross talk, HEDGEHOG signaling cascade and JAK/STAT signaling cascade. ssGSEA analysis exhibited a significant correlation between immune status and the risk signature. Noscapine and clofazimine were screened as potential drugs for CRC patients with high-risk scores. TDRD5 and GPC1 were identified as hub genes and their expression were validated in 15 pairs of surgically resected CRC tissues.

CONCLUSION

Our research provides a depth insight of RBPs' role in CRC and the proposed signature are helpful to the personalized treatment and prognostic judgement.

Integrated analysis of multi-omics data for the discovery of biomarkers and therapeutic targets for colorectal cancer

The considerable burden of colorectal cancer and the rising trend in young adults emphasize the necessity of understanding its underlying mechanisms, providing new diagnostic and prognostic markers, and improving therapeutic approaches. Precision medicine is a new trend all over the world and identification of novel biomarkers and therapeutic targets is a step forward towards this trend. In this context, multi-omics data and integrated analysis are being investigated to develop personalized medicine in the management of colorectal cancer. Given the large amount of data from multi-omics approach, data integration and analysis is a great challenge. In this Review, we summarize how statistical and machine learning techniques are applied to analyze multi-omics data and how it contributes to the discovery of useful diagnostic and prognostic biomarkers and therapeutic targets. Moreover, we discuss the importance of these biomarkers and therapeutic targets in the clinical management of colorectal cancer in the future. Taken together, integrated analysis of multi-omics data has great potential for finding novel diagnostic and prognostic biomarkers and therapeutic targets, however, there are still challenges to overcome in future studies.

Identification and validation of a pyroptosis-related prognostic model for colorectal cancer

In this study, we explored the pyroptosis-related biomarkers and signatures of colorectal cancer (CRC). Gene expression profiles were downloaded from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA)-COADREAD and were analyzed for differentially expressed genes (DEGs). DEGs in CRC‒pyroptosis-related genes (CRC‒PRGs) were obtained by intersecting DEGs associated with CRC and PRGs. The CRC‒PRGs were verified; functional enrichment analysis was performed with Gene Ontology (GO) followed by cluster analysis. Cox analyses and LASSO regression were used in TCGA dataset to construct a prognostic model for patients with CRC. A prognostic risk assessment model was constructed and efficacy was evaluated. Decision curve analysis was utilized to assess the role of the Lasso-Cox regression prognostic model for clinical utility at 1, 3, and 5 years. Twelve CRC‒PRGs were identified as prognostic pyroptosis-related DEGs. CXCL8, IL13RA2, MELK, and POP1 were selected as prognostic genes to construct features with a good prognostic performance in GEO and TCGA. Functional enrichment indicated that the 4-gene signature might be involved in CRC tumorigenesis and development through various pathways by playing a prognostic role in CRC. Furthermore, the results of the immune landscape analysis showed that the expression of CXCL8 and IL13RA2 in TCGA-COADREAD dataset was positively correlated with significant differential enrichment of most immune cells. A novel prognostic model consisting of four key genes, CXCL8, IL13RA2, MELK, and POP1, can accurately predict the survival of patients with CRC. This finding may provide a new perspective for the treatment of pyroptosis-related CRC.

Identification of Prognostic Gene Signatures by Developing a scRNA-Seq-Based Integration Approach to Predict Recurrence and Chemotherapy Benefit in Stage II–III Colorectal Cancer

Prospective identification of robust biomarkers related to prognosis and adjuvant chemotherapy has become a necessary and critical step to predict the benefits of adjuvant therapy for patients with stage II–III colorectal cancer (CRC) before clinical treatment. We proposed a single-cell-based prognostic biomarker recognition approach to identify and construct CRC up- and down-regulated prognostic signatures (CUPsig and CDPsig) by integrating scRNA-seq and bulk datasets. We found that most genes in CUPsig and CDPsig were known disease genes, and they had good prognostic abilities in CRC validation datasets. Multivariate analysis confirmed that they were two independent prognostic factors of disease-free survival (DFS). Significantly, CUPsig and CDPsig could effectively predict adjuvant chemotherapy benefits in drug-treated validation datasets. Additionally, they also performed well in patients with CMS4 subtype. Subsequent analysis of drug sensitivity showed that expressions of these two signatures were significantly associated with the sensitivities of CRC cell lines to multiple drugs. In summary, we proposed a novel prognostic biomarker identification approach, which could be used to identify novel prognostic markers for stage II–III CRC patients who will undergo adjuvant chemotherapy and facilitate their further personalized treatments.

The protein biosynthesis inhibitor vioprolide A evokes anti-angiogenic and pro-survival actions by targeting NOP14 and decreasing VEGF receptor 2- and TAZ-signaling

Angiogenesis contributes to the progression of several diseases including cancer or age-related macular degeneration and is crucially driven by pathologically hyperactive endothelial cells (ECs). Targeting angiogenic processes in ECs thus represents a promising strategy to treat these conditions. Vioprolide A (vioA) is a myxobacterial cyclic depsipeptide that targets the nucleolar protein 14 (NOP14) and possesses strong anti-cancer and anti-inflammatory actions. Here, we present evidence that vioA promotes anti-angiogenic actions in vivo and in ECs in vitro. VioA reduced the choroidal neovascularization after laser-induced photocoagulation in mice in vivo, the sprouting of choroidal explant cultures ex vivo and key angiogenic features of ECs in vitro. Mechanistically, vioA decreased VEGFR2 protein levels and phosphorylation leading to impaired downstream pro-angiogenic signaling. Concurrently, vioA influenced TAZ signaling by diminishing its nuclear translocation and protein level, resulting in a reduced expression of pro-angiogenic target genes and dynamic cytoskeletal remodeling. Surprisingly, vioA induced pro-survival signaling in ECs by activating Akt and inhibiting p53-dependent apoptosis. Knockdown of the cellular target NOP14 further revealed a partial involvement in the anti-angiogenic and pro-survival actions of vioA. Taken together, our study introduces vioA as an interesting anti-angiogenic compound that warrants further investigations in preclinical studies.

Potential of Mitochondrial Ribosomal Genes as Cancer Biomarkers Demonstrated by Bioinformatics Results

Next-generation sequencing and bioinformatics analyses have clearly revealed the roles of mitochondrial ribosomal genes in cancer development. Mitochondrial ribosomes are composed of three RNA components encoded by mitochondrial DNA and 82 specific protein components encoded by nuclear DNA. They synthesize mitochondrial inner membrane oxidative phosphorylation (OXPHOS)-related proteins and participate in various biological activities via the regulation of energy metabolism and apoptosis. Mitochondrial ribosomal genes are strongly associated with clinical features such as prognosis and foci metastasis in patients with cancer. Accordingly, mitochondrial ribosomes have become an important focus of cancer research. We review recent advances in bioinformatics research that have explored the link between mitochondrial ribosomes and cancer, with a focus on the potential of mitochondrial ribosomal genes as biomarkers in cancer.

Inferring Potential Cancer Driving Synonymous Variants

Synonymous single nucleotide variants (sSNVs) are often considered functionally silent, but a few cases of cancer-causing sSNVs have been reported. From available databases, we collected four categories of sSNVs: germline, somatic in normal tissues, somatic in cancerous tissues, and putative cancer drivers. We found that screening sSNVs for recurrence among patients, conservation of the affected genomic position, and synVep prediction (synVep is a machine learning-based sSNV effect predictor) recovers cancer driver variants (termed proposed drivers) and previously unknown putative cancer genes. Of the 2.9 million somatic sSNVs found in the COSMIC database, we identified 2111 proposed cancer driver sSNVs. Of these, 326 sSNVs could be further tagged for possible RNA splicing effects, RNA structural changes, and affected RBP motifs. This list of proposed cancer driver sSNVs provides computational guidance in prioritizing the experimental evaluation of synonymous mutations found in cancers. Furthermore, our list of novel potential cancer genes, galvanized by synonymous mutations, may highlight yet unexplored cancer mechanisms.

Increased expression of NOP14 is associated with improved prognosis due to immune regulation in colorectal cancer

Background

Colorectal cancer (CRC) is the third most common of cancer-related deaths. Nucleolar protein 14 (NOP14) is known to play different roles in diverse types of cancers. However, little is known about its roles in CRC. Here, we assessed the prognostic value and functions of NOP14 in CRC using the data from The Cancer Genome Atlas (TCGA) and validated them based on the data from Gene Expression Omnibus (GEO).

Methods

NOP14 mRNA and protein data in CRC was obtained from the TCGA, GEO, human protein atlas (HPA), and UALCAN databases. Survival and Cox regression analysis was performed to assess the prognostic value of NOP14 in CRC patients. Next, to evaluate the potential functions of NOP14, a protein–protein interaction (PPI) network was constructed and gene set enrichment analysis (GSEA) of differential expression genes (DEGs) associated with dysregulated NOP14 was performed. Finally, to investigate the immune response associated with NOP14 expression in CRC, we analyzed the correlations between immune cells infiltration and NOP14 expression level. Additionally, the correlations between immune molecule expression levels with NOP14 expression level were analyzed.

Results

High NOP14 mRNA expression was observed in CRC tissues based on the data from TCGA and GEO datasets. Similarly, high NOP14 protein levels were found in CRC tissues according to the immunohistochemical images from HPA. Interestingly, high NOP14 expression level was associated with an improved prognosis in CRC patients. Univariate and multivariate Cox regression analysis indicated that high NOP14 expression level was an independent protective factor for CRC patients. With the support of PPI network analysis, we found several risk genes interacted with NOP14. GSEA revealed that high NOP14 expression inhibited several signal pathways involved in tumor formation and development. Additionally, high NOP14 expression was positively associated with most kinds of immune cell infiltrations and the expression levels of some molecules related to immune activation.

Conclusion

Altogether, these results indicated that high NOP14 expression leads to improved prognosis in CRC patients by inhibiting the signaling pathways involved in tumor growth and promoting the immune responses.

Significant co-expression of putative cancer stem cell markers, EpCAM and CD166, correlates with tumor stage and invasive behavior in colorectal cancer

BACKGROUND

The crucial oncogenic role of cancer stem cells (CSCs) in tumor maintenance, progression, drug resistance, and relapse has been clarified in different cancers, particularly in colorectal cancer (CRC). The current study was conducted to evaluate the co-expression pattern and clinical significance of epithelial cell adhesion molecules (EpCAM) and activated leukocyte cell adhesion (CD166 or ALCAM) in CRC patients.

METHODS

This study was carried out on 458 paraffin-embedded CRC specimens by immunohistochemistry on tissue microarray (TMA) slides.

RESULTS

Elevated expression of EpCAM and CD166 was observed in 61.5% (246/427) and 40.5% (164/405) of CRC cases. Our analysis showed a significant positive association of EpCAM expression with tumor size (P = 0.02), tumor stage (P = 0.007), tumor differentiate (P = 0.005), vascular (P = 0.01), neural (P = 0.01), and lymph node (P = 0.001) invasion. There were no significant differences between CD166 expression and clinicopathological parameters. Moreover, the combined analysis demonstrated a reciprocal significant correlation between EpCAM and CD166 expression (P = 0.02). Interestingly, there was a significant positive correlation between EpCAM/CD166 phenotypes expression and tumor stage (P = 0.03), tumor differentiation (P = 0.05), neural, and lymph node invasion (P =0.01).

CONCLUSIONS

The significant correlation of EpCAM and CD166 expression and their association with tumor progression and aggressive behavior is the reason for the suggestion of these two CSC markers as promising targets to promote novel effective targeted-therapy strategies for cancer treatment in the present study.

Expression profile of RNA binding protein in cervical cancer using bioinformatics approach

BACKGROUND

It has been demonstrated by studies globally that RNA binding proteins (RBPs) took part in the development of cervical cancer (CC). Few studies concentrated on the correlation between RBPs and overall survival of CC patients. We retrieved significant DEGs (differently expressed genes, RNA binding proteins) correlated to the process of cervical cancer development.

METHODS

Expressions level of genes in cervical cancer and normal tissue samples were obtained from GTEx and TCGA database. Differently expressed RNA binding proteins (DEGs) were retrieved by Wilcoxon sum-rank test. ClusterProfiler package worked in R software was used to perform GO and KEGG enrichment analyses. Univariate proportional hazard cox regression and multivariate proportional hazard cox regressions were applied to identify DEGs equipped with prognostic value and other clinical independent risk factors. ROC curve was drawn for comparing the survival predict feasibility of risk score with other risk factors in CC patients. Nomogram was drawn to exhibit the prediction model and validated by C-index and calibration curve. Correlations between differentially expressed RNA binding proteins (DEGs) and other clinical features were investigated by t test or Cruskal Wallis analysis. Correlation between Immune and DEGs in cervical cancer was investigated by ssGSEA.

RESULTS

347 differentially expressed RBPs (DEGs) were retrieved from cervical cancer tissue and normal tissue samples. GO enrichment analysis showed that these DEGs involved in RNA splicing, catabolic process and metabolism. Cox regression model showed that there were ten DEGs significantly associated with overall survival of cervical cancer patients. WDR43 (HR = 0.423, P = 0.008), RBM38 (HR = 0.533, P < 0.001), RNASEH2A (HR = 0.474, P = 0.002) and HENMT1 (HR = 0.720, P = 0.071) played protective roles in survival among these ten genes. Stage (Stage IV vs Stage I HR = 3.434, P < 0.001) and risk score (HR = 1.214, P < 0.001) were sorted as independent prognostic risk factors based on multivariate cox regression. ROC curve validated that risk score was preferable to predict survival of CC patients than other risk factors. Additionally, we found some of these ten predictor DEGs were correlated significantly in statistic with tumor grade or stage, clinical T stage, clinical N stage, pathology or risk score (all P < 0.05). Part of immune cells and immune functions showed a lower activity in high risk group than low risk group which is stratified by median risk score.

CONCLUSION

Our discovery showed that many RNA binding proteins involved in the progress of cervical cancer, which could probably serve as prognostic biomarkers and accelerate the discovery of treatment targets for CC patients.

CELF Family Proteins in Cancer: Highlights on the RNA-Binding Protein/Noncoding RNA Regulatory Axis

Post-transcriptional modifications to coding and non-coding RNAs are unquestionably a pivotal way in which human mRNA and protein diversity can influence the different phases of a transcript's life cycle. CELF (CUGBP Elav-like family) proteins are RBPs (RNA-binding proteins) with pleiotropic capabilities in RNA processing. Their responsibilities extend from alternative splicing and transcript editing in the nucleus to mRNA stability, and translation into the cytoplasm. In this way, CELF family members have been connected to global alterations in cancer proliferation and invasion, leading to their identification as potential tumor suppressors or even oncogenes. Notably, genetic variants, alternative splicing, phosphorylation, acetylation, subcellular distribution, competition with other RBPs, and ultimately lncRNAs, miRNAs, and circRNAs all impact CELF regulation. Discoveries have emerged about the control of CELF functions, particularly via noncoding RNAs, and CELF proteins have been identified as competing, antagonizing, and regulating agents of noncoding RNA biogenesis. On the other hand, CELFs are an intriguing example through which to broaden our understanding of the RBP/noncoding RNA regulatory axis. Balancing these complex pathways in cancer is undeniably pivotal and deserves further research. This review outlines some mechanisms of CELF protein regulation and their functional consequences in cancer physiology.

Circ_0026416 downregulation blocks the development of colorectal cancer through depleting MYO6 expression by enriching miR-545-3p

Background

Emerging evidence reveals that the initiation and development of human cancers, including colorectal cancer (CRC), are associated with the deregulation of circular RNAs (circRNAs). Our study intended to disclose the role of circ_0026416 in the malignant behaviors of CRC.

Methods

The detection for circ_0026416 expression, miR-545-3p expression, and myosin VI (MYO6) mRNA expression was performed using quantitative real-time PCR (qPCR). CCK-8 assay, colony formation assay, transwell assay, and flow cytometry assay were applied for functional analysis to monitor cell proliferation, migration, invasion, and apoptosis. The protein levels of MYO6 and epithelial mesenchymal-transition (EMT) markers were detected by western blot. Mouse models were used to determine the role of circ_0026416 in vivo. The potential relationship between miR-545-3p and circ_0026416 or MYO6 was verified by dual-luciferase reporter assay and RIP assay.

Results

The expression of circ_0026416 was increased in CRC tumor tissues and cell lines. Circ_0026416 downregulation inhibited CRC cell proliferation, colony formation, migration, invasion, and EMT but induced cell apoptosis in vitro, and circ_0026416 knockdown also blocked tumor growth in vivo. MiR-545-3p was a target of circ_0026416, and rescue experiments indicated that circ_0026416 knockdown blocked CRC development by enriching miR-545-3p. In addition, miR-545-3p targeted MYO6 and inhibited MYO6 expression. MiR-545-3p enrichment suppressed CRC cell malignant behaviors by sequestering MYO6. Importantly, circ_0026416 knockdown depleted MYO6 expression by enriching miR-545-3p.

Conclusion

Circ_0026416 downregulation blocked the development of CRC through depleting MYO6 expression by enriching miR-545-3p.

Highlights

Circ_0026416 downregulation inhibits CRC development in vitro and in vivo.

Circ_0026416 regulates the expression of MYO6 by targeting miR-545-3p.

Circ_0026416 governs the miR-545-3p/MYO6 axis to regulate CRC progression.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12957-021-02407-y.

Development of an Interferon Gamma Response-Related Signature for Prediction of Survival in Clear Cell Renal Cell Carcinoma

Background

Interferon plays a crucial role in the pathogenesis and progression of tumors. Clear cell renal cell carcinoma (ccRCC) represents a prevalent malignant urinary system tumor. An effective predictive model is required to evaluate the prognosis of patients to optimize treatment.

Materials and Methods

RNA-sequencing data and clinicopathological data from TCGA were involved in this retrospective study. The IFN-γ response genes with significantly different gene expression were screened out. Univariate Cox regression, LASSO regression and multivariate Cox regression were used to establish a new prognostic scoring model for the training group. Survival curves and ROC curves were drawn, and nomogram was constructed. At the same time, we conducted subgroup analysis and experimental verification using our own samples. Finally, we evaluated the relatedness between the prognostic signature and immune infiltration landscapes. In addition, the sensitivity of different risk groups to six drugs and immune checkpoint inhibitors was calculated.

Results

The IFN-γ response-related signature included 7 genes: C1S, IFI44, ST3GAL5, NUP93, TDRD7, DDX60, and ST8SIA4. The survival curves of the training and testing groups showed the model's effectiveness (P = 4.372e-11 and P = 1.08e-08, respectively), the ROC curves showed that the signature was stable, and subgroup analyses showed the wide applicability of the model (P<0.001). Multivariate Cox regression analysis showed that the risk model was an independent prognostic factor of ccRCC. A high-risk score may represent an immunosuppressive microenvironment, while the high-risk group exhibited poor sensitivity to drugs.

Conclusion

Our findings strongly indicate that the IFN-γ response-related signature can be used as an effective prognostic indicator of ccRCC.

LINC01224 promotes colorectal cancer progression through targeting miR-485-5p/MYO6 axis

Background

Long noncoding RNAs (lncRNAs) are related to colorectal cancer (CRC) development. However, the role and mechanism of lncRNA LINC01224 in CRC development are largely unknown.

Methods

LINC01224, Yin Yang 1 (YY1), microRNA (miR)-485-5p, and myosins of class VI (MYO6) levels were examined using quantitative reverse transcription polymerase chain reaction and western blotting. Functional analyses were processed through CCK-8, colony formation, flow cytometry, transwell, and xenograft analyses. Dual-luciferase reporter, chromatin immunoprecipitation (ChIP), RNA immunoprecipitation, and pull-down assays were conducted to analyze the binding interaction.

Results

LINC01224 abundance was elevated in CRC tissue samples and cell lines. Elevated LINC01224 might indicate the lower 5-year overall survival in 52 CRC patients. LINC01224 was upregulated via the transcription factor YY1. LINC01224 knockdown restrained CRC cell proliferation, migration, and invasion and increased apoptosis. MiR-485-5p was sponged by LINC01224, and miR-485-5p downregulation relieved the influence of LINC01224 interference on CRC progression. MYO6 was targeted via miR-485-5p and regulated via LINC01224/miR-485-5p axis. MiR-485-5p overexpression suppressed CRC cell proliferation, migration, and invasion and facilitated apoptosis. MYO6 upregulation mitigated the role of miR-485-5p. LINC01224 knockdown decreased xenograft tumor growth.

Conclusion

YY1-induced LINC01224 regulates CRC development via modulating miR-485-5p/MYO6 axis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12957-021-02389-x.

Importance of Circ0009910 in colorectal cancer pathogenesis as a possible regulator of miR-145 and PEAK1

Introduction

Colorectal cancer (CRC) is one of the most frequent neoplasms in the world. Based on the emerging role of noncoding RNAs, particularly circular RNAs in pathogenesis of cancers, we designed this study to inspect the expression levels of a circ0009910-mediated regulatory pathway in colorectal cancer.

Methods

After bioinformatics analyses and construction of putative circ0009910/ miR-145-5p/PEAK1 pathway, the expression levels of these components were evaluated in 50 CRC tissues and adjacent specimens by quantitative real-time PCR. Moreover, we appraised the correlation coefficients between these transcripts and calculated the correlation between circ0009910 expression levels with clinicopathological features of patients.

Results

Circ0009910 and PEAK1 were significantly upregulated, while miR-145-5p was decreased in CRC samples compared with adjacent tissues (p < 0.05). Moreover, statistically significant correlations were observed between expression levels of circ0009910, miR-145-5p, and PEAK1. We also reported considerable correlations between circ0009910 expression and clinicopathological parameters including sex and perineural invasion. Finally, ROC curve analysis showed circ0009910 level as a discriminative biomarker for CRC.

Conclusion

For the first time, we could introduce circ0009910 as an important biomarker in CRC. Collectively, this investigation helped us to identify a newly diagnosed pathway in CRC that can be a potential axis for designing effective drugs for treatment of CRC patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12957-021-02378-0.

The RNA-Binding Protein ESRP1 Modulates the Expression of RAC1b in Colorectal Cancer Cells

Simple Summary

Colorectal cancer (CRC) ranks third for incidence and second for number of deaths among cancer types worldwide. Poor patient survival due to inadequate response to currently available treatment regimens points to the urgent requirement for personalized therapy in CRC patients. Our aim was to provide mechanistic insights into the pro-tumorigenic role of the RNA-binding protein ESRP1, which is highly expressed in a subset of CRC patients. We show that, in CRC cells, ESRP1 binds to and has the same trend in expression as RAC1b, a well-known tumor promoter. Thus, RAC1b may be a potential therapeutic target in ESRP1-overexpressing CRC.

Abstract

RNA binding proteins are well recognized as critical regulators of tumorigenic processes through their capacity to modulate RNA biogenesis, including alternative splicing, RNA stability and mRNA translation. The RNA binding protein Epithelial Splicing Regulatory Protein 1 (ESRP1) can act as a tumor suppressor or promoter in a cell type- and disease context-dependent manner. We have previously shown that elevated expression of ESRP1 in colorectal cancer cells can drive tumor progression. To gain further insights into the pro-tumorigenic mechanism of action of ESRP1, we performed cDNA microarray analysis on two colorectal cells lines modulated for ESRP1 expression. Intriguingly, RAC1b was highly expressed, both at mRNA and protein levels, in ESRP1-overexpressing cells, while the opposite trend was observed in ESRP1-silenced CRC cells. Moreover, RAC1 and RAC1b mRNA co-immunoprecipitate with ESRP1 protein. Silencing of RAC1b expression significantly reduced the number of soft agar colonies formed by ESRP1-overexpressing cells, suggesting that ESRP1 acted, at least partially, through RAC1b in its tumor-promoting activities in CRC cells. Thus, our data provide molecular cues on targetable candidates in CRC cases with high ESRP1 expression.

Identification of a Three-RNA Binding Proteins (RBPs) Signature Predicting Prognosis for Breast Cancer

BACKGROUND

To date, breast cancer remains the primary cause of tumor-related death among women, even though some leap-type developments of oncology have been done to slash the mortality. Considering the tumor heterogeneity and individual variation, the more reliable biomarkers are required to be identified for supporting the development of precision medicine in breast cancer.

METHODS

Based on the TCGA-BRCA and METABRIC databases, the differently expressed RNA binding proteins (RBPs) between tumor and normal tissues were investigated. In this study, we focused on the communal differently expressed RBPs in four subtypes of breast cancer. Lasso-penalized Cox analysis, Stepwise-multivariate Cox analysis and Kaplan-Meier survival curve were performed to identify the hub RBP-coding genes in predicting prognosis of breast cancer, and a prognostic model was established. The efficiency of this model was further validated in other independent GSE20685, GSE4922 and FUSCC-TNBC cohorts by calculating the risk score and performing survival analysis, ROC and nomogram. Moreover, pathologic functions of the candidate RBPs in breast cancer were explored using some routine experiments in vitro, and the potential compounds targeting these RBPs were predicted by reviewing the Comparative Toxicogenomics Database.

RESULTS

Here, we identified 62 RBPs which were differently expressed between the tumor and normal tissues. Thereinto, three RBPs (MRPL12, MRPL13 and POP1) acted as independent risk factors, and their expression pattern also correlated with poor prognosis of patients. A prognostic model, built with these 3-RBPs, possessed statistical significance to predict the survival probability of patients with breast cancer. Furthermore, experimental validations showed that down-regulating the expression of endogenous MRPL12, MRPL13 or POP1 could dramatically suppress the cellular viability and migration of breast cancer cells in vitro. Besides, some compounds (such as the Acetaminophen, Urethane and Tunicamycin) were predicted for curing breast cancer via targeting MRPL12, MRPL13 and POP1 simultaneously.

CONCLUSION

This study identified and established a 3-RBPs-based signature and nomogram for predicting the survival probability of patients with breast cancer. MRPL12, MRPL13 and POP1 might act as oncogenes in maintaining cellular viability and accelerating metastasis of breast cancer cells, implying the possibility of which to be designed as biomarkers and/or therapeutic targets for breast cancer.

Construction and validation of an RNA-binding protein-associated prognostic model for colorectal cancer

Colorectal cancer (CRC) is one of the most prevalent and fatal malignancies, and novel biomarkers for the diagnosis and prognosis of CRC must be identified. RNA-binding proteins (RBPs) are essential modulators of transcription and translation. They are frequently dysregulated in various cancers and are related to tumorigenesis and development. The mechanisms by which RBPs regulate CRC progression are poorly understood and no clinical prognostic model using RBPs has been reported in CRC. We sought to identify the hub prognosis-related RBPs and to construct a prognostic model for clinical use. mRNA sequencing and clinical data for CRC were obtained from The Cancer Genome Atlas database (TCGA). Gene expression profiles were analyzed to identify differentially expressed RBPs using R and Perl software. Hub RBPs were filtered out using univariate Cox and multivariate Cox regression analysis. We used functional enrichment analysis, including Gene Ontology and Gene Set Enrichment Analysis, to perform the function and mechanisms of the identified RBPs. The nomogram predicted overall survival (OS). Calibration curves were used to evaluate the consistency between the predicted and actual survival rate, the consistency index (c-index) was calculated, and the prognostic effect of the model was evaluated. Finally, we identified 178 differently expressed RBPs, including 121 up-regulated and 57 down-regulated proteins. Our prognostic model was based on nine RBPs (PNLDC1, RRS1, HEXIM1, PPARGC1A, PPARGC1B, BRCA1, CELF4, AEN and NOVA1). Survival analysis showed that patients in the high-risk subgroup had a worse OS than those in the low-risk subgroup. The area under the curve value of the receiver operating characteristic curve of the prognostic model is 0.712 in the TCGA cohort and 0.638 in the GEO cohort. These results show that the model has a moderate diagnostic ability. The c-index of the nomogram is 0.77 in the TCGA cohort and 0.73 in the GEO cohort. We showed that the risk score is an independent prognostic biomarker and that some RBPs may be potential biomarkers for the diagnosis and prognosis of CRC.