Identification of the Functions and Prognostic Values of RNA Binding Proteins in Bladder Cancer

Identification and validation of a 9-RBPs-related gene signature associated with prognosis and immune infiltration in bladder cancer based on bioinformatics analysis and machine learning

Background

Bladder cancer (BLCA) is the most common type of malignancy affecting the urinary tract, characterized by high recurrence rates, propensity for progression, metastatic potential, and multidrug resistance, all of which ultimately contribute to an unfavorable prognosis. RNA-binding proteins (RBPs) play a critical role in cancer development and have been associated with the progression and prognosis of the disease. However, comprehensive investigations into the biological functions and molecular mechanisms of RBPs in BLCA remain limited. The study aims to explore the relationship between RBPs and prognosis in BLCA, and to develop and validate an RBPs-based prognostic signature, providing new insights for the diagnosis and treatment of BLCA.

Methods

Clinical data and RBPs expression profiles of BLCA patients were sourced from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). A systematic bioinformatics analysis was conducted to identify differentially expressed RBPs and assess their prognostic significance. The optimal predictive model was selected by integrating multiple machine learning algorithms, enabling the identification of hub genes associated with BLCA prognosis and developing an RBP-related gene signature. To evaluate the prognostic signature's efficacy, survival curves and receiver operating characteristic (ROC) curves were generated. A nomogram was constructed and validated to predict the survival of BLCA patients at 1, 3, and 5 years. Furthermore, analyses of immune infiltration and gene set enrichment analysis (GSEA) were conducted to explore the roles of RBPs in immune cell interactions and elucidate underlying biological pathways.

Results

A prognostic signature was effectively developed using nine RBPs (OAS1, MTG1, DUS4L, IGF2BP3, NOL12, PABPC1L, ZC3HAV1L, TRMT2A and TRMU), represented as risk score, through the integration of 13 combinatorial machine learning algorithms. Kaplan-Meier analysis revealed that the high-risk group exhibited a significantly poorer overall survival (OS) probability compared to the low-risk group. The areas under the ROC curves for the risk score model at 1, 3, and 5 years were 0.661, 0.655, and 0.676, respectively. The nomogram, which integrated clinical characteristics and risk scores, demonstrated robust prognostic accuracy. Furthermore, single-sample gene set enrichment analysis (ssGSEA) demonstrated significant correlations between both the risk score model and hub RBPs with the immune status of BLCA patients. GSEA indicated that major signaling pathways enriched in the high-risk group included extracellular matrix (ECM) components and interaction, as well as cytokine and receptor interaction.

Conclusions

This study successfully identified and developed a prognostic signature based on nine RBPs, accompanied by a nomogram for predicting survival probability in BLCA patients. Our findings demonstrate that these nine RBPs function as significant biomarkers for forecasting the prognosis and immune status in BLCA, suggesting their potential as therapeutic targets for BLCA.

Identification of RNA-binding protein RBMS3 as a potential biomarker for immunotherapy in bladder cancer

RNA-binding protein (RBP) plays pivotal roles in the malignant progression of cancer by regulating gene expression. In this paper, we aimed to develop RBP-based prognostic signature and identify critical hub RBPs in bladder cancer (BLCA). Firstly, a risk model based on differentially expressed RBP gens (DERBPs) between normal and tumor tissues was successfully established, which can predict the tumor stromal score and drug sensitivity. Then two another RBP risk models based on miRNA-correlated RBPs or lncRNA-correlated RBPs were also established, and RBMS3 was identified as the overlapping gene in the three models. Data from multiple bioinformatics databases revealed that RBMS3 was an independent prognostic factor for overall survival (OS), and was associated with an immunosuppressive tumor microenvironment (TME) in BLCA. Further, Single-cell RNA-Seq (scRNA-Seq) data and the human protein altas (HPA) database showed that RBMS3 expression (both mRNA and protein) were up-regulated in BLCA tumor and tumor stromal cells. Finally, RBMS3 was shown to be associated with worse response to BLCA immunotherapy. Overall, RBMS3 is a key prognostic RBP with TME remodeling function and may serve as a target for BLCA immunotherapy.

Single-cell RNA-binding protein pattern-mediated molecular subtypes depict the hallmarks of the tumor microenvironment in bladder urothelial carcinoma

Objectives

Bladder carcinoma (BC) is a common malignancy of the urinary tract. As a new hallmark of cancer for drug therapy, RNA-binding proteins (RBPs) are key regulatory factors in alternative splicing events. This work is to uncover the relationship between BC and RBP in order to find drug targets in BC.

Methods

In this work, data from single-cell RNA-seq GSE1355337, PRJNA662018, and the TCGA-Bladder urothelial carcinoma (BLCA) cohorts are integrated to identify their relationships. A scoring system is constructed according to RBPs gene expression and patients’ survival. A network is constructed to analyze the alternative splicing events and RBP genes.

Results

A scoring system identified 321 RBPs significantly associated with the prognosis of patients. Subsequent typing of these RBP genes in two single-cell datasets demonstrated that most of the RBP genes had variable copy numbers. Three RBP clusters were identified. Using RBP genes as a signature in BC epithelial cells allows for differentiation between different grades of BC samples. The novel RBP genes-based subtype system reflects BC clinical staging. Notably, CellChat analysis revealed that the RBP genes-associated cell subtypes of T cells had extensive interactions with epithelial cells. Further analysis showed that the ligand-receptor pair MIF-CXCR4 mediated the communication between RBP-associated subtypes of BC epithelial cells and T cells.

Conclusions

Taken together, RBP genes are associated with BC progress and offer new indicators for precision medicine in BC.

m6A reader IGF2BP2 promotes M2 macrophage polarization and malignant biological behavior of bladder cancer by stabilizing NRP1 mRNA expression

BACKGROUND

Insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2) has been confirmed to play oncogenic role in many cancers. However, the role and mechanism of IGF2BP2 in bladder cancer (BCa) still deserves to be further revealed.

METHODS

The mRNA and protein levels of IGF2BP2 and neuronilin-1 (NRP1) were detected by real-time quantitative PCR (RT-qPCR) and western blot. Cell proliferation, apoptosis, migration and invasion were determined using colony formation assay, EdU assay, CCK8 assay, flow cytometry and transwell assay. Xenograft tumor model was conducted to evaluate the role of IGF2BP2 in vivo. THP-1-M0 macrophages were co-cultured with the condition medium (CM) of BCa cells to induce polarization. M2 macrophage polarization was assessed by detecting the mRNA levels of M2 macrophage markers using RT-qPCR and measuring the proportion of M2 macrophage markers using flow cytometry. Moreover, MeRIP and RIP assay were performed to assess m6A level and the interaction between IGF2BP2 and NRP1.

RESULTS

IGF2BP2 and NRP1 were upregulated in BCa tissues and cells. IGF2BP2 knockdown suppressed BCa cell growth and metastasis, as well as inhibited BCa tumor growth. After THP-1-M0 macrophages were co-cultured with the CM of BCa cells, the levels of M2 macrophage markers were markedly enhanced, while this effect was abolished by IGF2BP2 knockdown. IGF2BP2 level was positively correlated with NRP1 level, and it could increase NRP1 mRNA stability. NRP1 overexpression reversed the suppressive effect of IGF2BP2 knockdown on M2 macrophage polarization and BCa cell progression.

CONCLUSION

m6A-reader IGF2BP2 enhanced M2 macrophage polarization and BCa cell progression by promoting NRP1 mRNA stability.

Prognostic biomarker DARS2 correlated with immune infiltrates in bladder tumor

Background

DARS2 is a pivotal member of the Aminoacyl-tRNA synthetases family that is critical for regulating protein translation. However, the biological role of DARS2 in bladder cancer remains elusive.

Methods

We analyzed the correlation between DARS2 expression and prognosis, tumor stage, and immune infiltration in bladder cancer using The Cancer Genome Atlas (TCGA) database. We validated findings in clinical samples from The First Affiliated Hospital of Nanchang University and explored the biological functions of DARS2 using cell and animal models.

Results

We found DARS2 to be upregulated in bladder cancer, associated with tumor progression and poor prognosis. Immune infiltration analysis suggested that DARS2 may facilitate immune evasion by modulating PD-L1. Cell and animal experiments validated that DARS2 knockdown and overexpress can inhibit or increase cancer cell proliferation, metastasis, tumorigenesis, immune escape, and PD-L1 levels.

Conclusions

Our study reveals DARS2 as a potential prognostic biomarker and immunotherapy target in BLCA.

Susceptibility Genes Associated with Multiple Primary Cancers

With advancements in treatment and screening techniques, we have been witnessing an era where more cancer survivors harbor multiple primary cancers (MPCs), affecting approximately one in six patients. Identifying MPCs is crucial for tumor staging and subsequent treatment choices. However, the current clinicopathological criteria for clinical application are limited and insufficient, making it challenging to differentiate them from recurrences or metastases. The emergence of next-generation sequencing (NGS) technology has provided a genetic perspective for defining multiple primary cancers. Researchers have found that, when considering multiple tumor pairs, it is crucial not only to examine well-known essential mutations like MLH1/MSH2, EGFR, PTEN, BRCA1/2, CHEK2, and TP53 mutations but also to explore certain pleiotropic loci. Moreover, specific deleterious mutations may serve as regulatory factors in second cancer development following treatment. This review aims to discuss these susceptibility genes and provide an explanation of their functions based on the signaling pathway background. Additionally, the association network between genetic signatures and different tumor pairs will be summarized.

Cancer metastasis under the magnifying glass of epigenetics and epitranscriptomics

Most of the cancer-associated mortality and morbidity can be attributed to metastasis. The role of epigenetic and epitranscriptomic alterations in cancer origin and progression has been extensively demonstrated during the last years. Both regulations share similar mechanisms driven by DNA or RNA modifiers, namely writers, readers, and erasers; enzymes responsible of respectively introducing, recognizing, or removing the epigenetic or epitranscriptomic modifications. Epigenetic regulation is achieved by DNA methylation, histone modifications, non-coding RNAs, chromatin accessibility, and enhancer reprogramming. In parallel, regulation at RNA level, named epitranscriptomic, is driven by a wide diversity of chemical modifications in mostly all RNA molecules. These two-layer regulatory mechanisms are finely controlled in normal tissue, and dysregulations are associated with every hallmark of human cancer. In this review, we provide an overview of the current state of knowledge regarding epigenetic and epitranscriptomic alterations governing tumor metastasis, and compare pathways regulated at DNA or RNA levels to shed light on a possible epi-crosstalk in cancer metastasis. A deeper understanding on these mechanisms could have important clinical implications for the prevention of advanced malignancies and the management of the disseminated diseases. Additionally, as these epi-alterations can potentially be reversed by small molecules or inhibitors against epi-modifiers, novel therapeutic alternatives could be envisioned.

DARS2 overexpression is associated with PET/CT metabolic parameters and affects glycolytic activity in lung adenocarcinoma

BACKGROUND

This study investigated the correlation between the expression of DARS2 and metabolic parameters of 18F-FDG PET/CT, and explored the potential mechanisms of DARS2 affecting the proliferation and glycolysis of lung adenocarcinoma (LUAD) cells.

METHODS

This study used genomics and proteomics to analyze the difference in DARS2 expression between LUAD samples and control samples. An analysis of 62 patients with LUAD who underwent 18F-FDG PET/CT examinations before surgery was conducted retrospectively. The correlation between DARS2 expression and PET/CT metabolic parameters, including SUVmax, SUVmean, MTV, and TLG, was examined by Spearman correlation analysis. In addition, the molecular mechanism of interfering with DARS2 expression in inhibiting LUAD cell proliferation and glycolysis was analyzed through in vitro cell experiments.

RESULTS

DARS2 expression was significantly higher in LUAD samples than in control samples (p < 0.001). DARS2 has high specificity (98.4%) and sensitivity (95.2%) in the diagnosis of LUAD. DARS2 expression was positively correlated with SUVmax, SUVmean, and TLG (p < 0.001). At the same time, the sensitivity and specificity of SUVmax in predicting DARS2 overexpression in LUAD were 88.9% and 65.9%, respectively. In vitro cell experiments have shown that interfering with DARS2 expression can inhibit the proliferation and migration of LUAD cells, promote cell apoptosis, and inhibit the glycolytic activity of tumor cells by inhibiting the expression of glycolytic related genes SLC2A1, GPI, ALDOA, and PGAM1.

CONCLUSIONS

Overexpression of DARS2 is associated with metabolic parameters on 18F-FDG PET/CT, which can improve LUAD diagnosis accuracy. DARS2 may be a useful biomarker to diagnose, prognosis, and target treatment of LUAD patients.

Cisplatin-induced increase in heregulin 1 and its attenuation by the monoclonal ErbB3 antibody seribantumab in bladder cancer

Cisplatin-based combination chemotherapy is the foundation for treatment of advanced bladder cancer (BlCa), but many patients develop chemoresistance mediated by increased Akt and ERK phosphorylation. However, the mechanism by which cisplatin induces this increase has not been elucidated. Among six patient-derived xenograft (PDX) models of BlCa, we observed that the cisplatin-resistant BL0269 express high epidermal growth factor receptor, ErbB2/HER2 and ErbB3/HER3. Cisplatin treatment transiently increased phospho-ErbB3 (Y1328), phospho-ERK (T202/Y204) and phospho-Akt (S473), and analysis of radical cystectomy tissues from patients with BlCa showed correlation between ErbB3 and ERK phosphorylation, likely due to the activation of ERK via the ErbB3 pathway. In vitro analysis revealed a role for the ErbB3 ligand heregulin1-β1 (HRG1/NRG1), which is higher in chemoresistant lines compared to cisplatin-sensitive cells. Additionally, cisplatin treatment, both in PDX and cell models, increased HRG1 levels. The monoclonal antibody seribantumab, that obstructs ErbB3 ligand-binding, suppressed HRG1-induced ErbB3, Akt and ERK phosphorylation. Seribantumab also prevented tumor growth in both the chemosensitive BL0440 and chemoresistant BL0269 models. Our data demonstrate that cisplatin-associated increases in Akt and ERK phosphorylation is mediated by an elevation in HRG1, suggesting that inhibition of ErbB3 phosphorylation may be a useful therapeutic strategy in BlCa with high phospho-ErbB3 and HRG1 levels.

The emerging roles and mechanism of N6-methyladenosine (m6A) modifications in urologic tumours progression

Prostate cancer (PCa), bladder cancer (BC), and renal cell cancer (RCC) are the most common urologic tumours in males. N6-methyladenosine (m⁶A), adenosine N6 methylation, is the most prevalent RNA modification in mammals. Increasing evidence suggests that m⁶A plays a crucial role in cancer development. In this review, we comprehensively analyzed the influence of m⁶A methylation on Prostate cancer, bladder cancer, and renal cell cancer and the relationship between the expression of relevant regulatory factors and their development and occurrence, which provides new insights and approaches for the early clinical diagnosis and targeted therapy of urologic malignancies.

Comprehensive research into prognostic and immune signatures of transcription factor family in breast cancer

BACKGROUND

Breast cancer (BRCA) is the most common malignancy with high morbidity and mortality in women, and transcription factor (TF) is closely related to the occurrence and development of BRCA. This study was designed to identify a prognostic gene signature based on TF family to reveal immune characteristics and prognostic survival of BRCA.

METHODS

In this study, RNA-sequence with corresponding clinical data were obtained from The Cancer Genome Atlas (TCGA) and GSE42568. Prognostic differentially expressed transcription factor family genes (TFDEGs) were screened to construct a risk score model, after which BRCA patients were stratified into low-risk and high-risk groups based on their corresponding risk scores. Kaplan-Meier (KM) analysis was applied to evaluate the prognostic implication of risk score model, and a nomogram model was developed and validated with the TCGA and GSE20685. Furthermore, the GSEA revealed pathological processes and signaling pathways enriched in the low-risk and high-risk groups. Finally, analyses regarding levels of immune infiltration, immune checkpoints and chemotactic factors were all completed to investigate the correlation between the risk score and tumor immune microenvironment (TIME).

RESULTS

A prognostic 9-gene signature based on TFDEGs was selected to establish a risk score model. According to KM analyses, high-risk group witnessed a significantly worse overall survival (OS) than low-risk group in both TCGA-BRCA and GSE20685. Furthermore, the nomogram model proved great possibility in predicting the OS of BRCA patients. As indicted in GSEA analysis, tumor-associated pathological processes and pathways were relatively enriched in high-risk group, and the risk score was negatively correlated with ESTIMATE score, infiltration levels of CD4+ and CD8+T cells, as well as expression levels of immune checkpoints and chemotactic factors.

CONCLUSIONS

The prognostic model based on TFDEGs could distinguish as a novel biomarker for predicting prognosis of BRCA patients; in addition, it may also be utilized to identify potential benefit population from immunotherapy in different TIME and predict potential drug targets.

Comprehensive analysis of ZNF family genes in prognosis, immunity, and treatment of esophageal cancer

BACKGROUND

As a common malignant tumor, esophageal carcinoma (ESCA) has a low early diagnosis rate and poor prognosis. This study aimed to construct the prognostic features composed of ZNF family genes to effectively predict the prognosis of ESCA patients.

METHODS

The mRNA expression matrix and clinical data were downloaded from TCGA and GEO database. Using univariate Cox analysis, lasso regression and multivariate Cox analysis, we screened six prognosis-related ZNF family genes to construct the prognostic model. We then used Kaplan-Meier plot, time-dependent receiver operating characteristic (ROC), multivariable Cox regression analysis of clinical information, and nomogram to evaluate the prognostic value within and across sets, separately and combined. We also validated the prognostic value of the six-gene signature using GSE53624 dataset. The different immune status was observed in the single sample Gene Set Enrichment Analysis (ssGSEA). Finally, real-time quantitative PCR was used to detect the expression of six prognostic ZNF genes in twelve pairs of ESCA and adjacent normal tissues.

RESULTS

A six prognosis-related ZNF family genes model consisted of ZNF91, ZNF586, ZNF502, ZNF865, ZNF106 and ZNF225 was identified. Multivariable Cox regression analysis revealed that six prognosis-related ZNF family genes were independent prognostic factors for overall survival of ESCA patients in TCGA and GSE53624. Further, a prognostic nomogram including the riskScore, age, gender, T, stage was constructed, and TCGA/GSE53624-based calibration plots indicated its excellent predictive performance. Drug Sensitivity and ssGSEA analysis showed that the six genes model was closely related to immune cells infiltration and could be used as a potential predictor of chemotherapy sensitivity.

CONCLUSION

We identified six prognosis-related ZNF family genes model of ESCA, which provide evidence for individualized prevention and treatment.

Telomere maintenance-related genes are important for survival prediction and subtype identification in bladder cancer

Background: Bladder cancer ranks among the top three in the urology field for both morbidity and mortality. Telomere maintenance-related genes are closely related to the development and progression of bladder cancer, and approximately 60%-80% of mutated telomere maintenance genes can usually be found in patients with bladder cancer. Methods: Telomere maintenance-related gene expression profiles were obtained through limma R packages. Of the 359 differential genes screened, 17 prognostically relevant ones were obtained by univariate independent prognostic analysis, and then analysed by LASSO regression. The best result was selected to output the model formula, and 11 model-related genes were obtained. The TCGA cohort was used as the internal group and the GEO dataset as the external group, to externally validate the model. Then, the HPA database was used to query the immunohistochemistry of the 11 model genes. Integrating model scoring with clinical information, we drew a nomogram. Concomitantly, we conducted an in-depth analysis of the immune profile and drug sensitivity of the bladder cancer. Referring to the matrix heatmap, delta area plot, consistency cumulative distribution function plot, and tracking plot, we further divided the sample into two subtypes and delved into both. Results: Using bioinformatics, we obtained a prognostic model of telomere maintenance-related genes. Through verification with the internal and the external groups, we believe that the model can steadily predict the survival of patients with bladder cancer. Through the HPA database, we found that three genes, namely ABCC9, AHNAK, and DIP2C, had low expression in patients with tumours, and eight other genes-PLOD1, SLC3A2, RUNX2, RAD9A, CHMP4C, DARS2, CLIC3, and POU5F1-were highly expressed in patients with tumours. The model had accurate predictive power for populations with different clinicopathological features. Through the nomogram, we could easily assess the survival rate of patients. Clinicians can formulate targeted diagnosis and treatment plans for patients based on the prediction results of patient survival, immunoassays, and drug susceptibility analysis. Different subtypes help to further subdivide patients for better treatment purposes. Conclusion: According to the results obtained by the nomogram in this study, combined with the results of patient immune-analysis and drug susceptibility analysis, clinicians can formulate diagnosis and personalized treatment plans for patients. Different subtypes can be used to further subdivide the patient for a more precise treatment plan.

Identification and validation of the mitochondrial function related hub genes by unsupervised machine learning and multi-omics analyses in lung adenocarcinoma

Background

The mitochondrion and its associated genes were heavily implicated in developing and therapy tumors as the primary cellular organelle in charge of metabolic reprogramming and ferroptosis. Our work focuses on discovering new potential targets while analyzing the multi-omics data of mitochondria-related genes in lung adenocarcinoma (LUAD).

Methods

The Cancer Genome Atlas (TCGA) database provided multi-omics data for LUAD patients. Based on the expression profile of the genes associated with mitochondria, the patients were grouped by the unsupervised clustering method. R was used to explore the differential expressed protein-code gene, miRNA, and lncRNA, as well as their enriched functions and ceRNA networks. Additionally, the discrepancy between immune infiltration and genetic variation was comprehensively characterized. Our clinical samples and in vitro experiments investigated the hub gene determined by LASSO and batch analysis.

Results

Two clusters are distinguished using unsupervised consensus clustering based on mitochondrial heterogeneity. The integrated analysis emphasized that patients in cluster B had a worse prognosis, higher mutation frequencies, and less immune cell infiltration. The hub genes DARS2 and COX5B are identified by further analysis using LASSO penalization. In vitro experiments indicated that DARS2 and COX5B knockdown inhibited tumor cell proliferation. The specimen of our hospital cohort conducted the immunohistochemistry analysis and validated that DARS2 and COX5B's expression was significantly higher in the tumor than in adjacent normal tissue and correlated to LUAD patients' prognosis.

Conclusion

Our observations implied that LUAD patients' tumors had distinct mitochondrial function heterogeneity with different clinical and molecular characteristics. DARS2 and COX5B might be critical genes involved in mitochondrial alterations and potential therapeutic targets.

Prognostic values of the immune microenvironment-related non-coding RNA IGF2BP2-AS1 in bladder cancer

Bladder cancer can range from noninvasive to invasive tumors. When non-muscle invasive bladder cancer (NMIBC) recurs, patients could endure long-term invasive malignancies with a high disease-specific death rate. Immune escape frequently results in tumor development, metastases, unfavorable prognosis, and failure of immunotherapy. Based on the median immune score, this study used ESTIMATE scores to evaluate 411 bladder cancer cases from TCGA-BLCA. Two hundred two ncRNAs were differentially expressed in two groups, where 29 candidates appeared to be associated with the overall survival of bladder cancer patients. LASSO algorithm was performed to establish the risk score model of 13-ncRNA. Risk scores were computed for cases in the training set, validation set, and TCGA-BLCA set; Poor prognosis in cases with higher risk scores was based on the training set, validating set, and TCGA-BLCA set. Among the 13 ncRNAs, IGF2BP2-AS1, MAGF-AS1, ARHGAP5-AS1, and LINC00942 were significantly correlated with the overall survival of bladder cancer patients. Pearson's correlation analysis based on TCGA-BLCA identified 2093, 3107, 386, and 936 mRNAs co-expressed with IGF2BP2-AS1, MAGF-AS1, ARHGAP5-AS1, and LINC00942, respectively. Conclusively, the 13 ncRNA signature exhibited a feasible predictive prognostic value for bladder cancer patients. IGF2BP2-AS1 expression was higher in bladder cancer tissues and significantly correlated to immune-related factors, suggesting that IGF2BP2-AS1 represents a promising immune-related target for treating bladder cancer patients.

Assessment of genetic susceptibility to multiple primary cancers through whole-exome sequencing in two large multi-ancestry studies

BACKGROUND

Up to one of every six individuals diagnosed with one cancer will be diagnosed with a second primary cancer in their lifetime. Genetic factors contributing to the development of multiple primary cancers, beyond known cancer syndromes, have been underexplored.

METHODS

To characterize genetic susceptibility to multiple cancers, we conducted a pan-cancer, whole-exome sequencing study of individuals drawn from two large multi-ancestry populations (6429 cases, 165,853 controls). We created two groupings of individuals diagnosed with multiple primary cancers: (1) an overall combined set with at least two cancers across any of 36 organ sites and (2) cancer-specific sets defined by an index cancer at one of 16 organ sites with at least 50 cases from each study population. We then investigated whether variants identified from exome sequencing were associated with these sets of multiple cancer cases in comparison to individuals with one and, separately, no cancers.

RESULTS

We identified 22 variant-phenotype associations, 10 of which have not been previously discovered and were significantly overrepresented among individuals with multiple cancers, compared to those with a single cancer.

CONCLUSIONS

Overall, we describe variants and genes that may play a fundamental role in the development of multiple primary cancers and improve our understanding of shared mechanisms underlying carcinogenesis.

Role of RBMS3 Novel Potential Regulator of the EMT Phenomenon in Physiological and Pathological Processes

RNA-binding protein 3 (RBMS3) plays a significant role in embryonic development and the pathogenesis of many diseases, especially cancer initiation and progression. The multiple roles of RBMS3 are conditioned by its numerous alternative expression products. It has been proven that the main form of RBMS3 influences the regulation of microRNA expression or stabilization. The absence of RBMS3 activates the Wnt/β-catenin pathway. The expression of c-Myc, another target of the Wnt/β-catenin pathway, is correlated with the RBMS3 expression. Numerous studies have focused solely on the interaction of RBMS3 with the epithelial-mesenchymal transition (EMT) protein machinery. EMT plays a vital role in cancer progression, in which RBMS3 is a new potential regulator. It is also significant that RBMS3 may act as a prognostic factor of overall survival (OS) in different types of cancer. This review presents the current state of knowledge about the role of RBMS3 in physiological and pathological processes, with particular emphasis on carcinogenesis. The molecular mechanisms underlying the role of RBMS3 are not fully understood; hence, a broader explanation and understanding is still needed.

Integrated Analysis and Identification of Critical RNA-Binding Proteins in Bladder Cancer

RBPs in the development and progression of BC remains unclear. Here, we elucidated the role of RBPs in predicting the survival of patients with BC. Clinical information and RNA sequencing data of the training and validation cohorts were downloaded from the Cancer Genome Atlas and Gene Expression Omnibus databases, respectively. Survival-related differentially expressed RBPs were identified using Cox regression analyses. A total of 113 upregulated and 54 downregulated RBPs were observed, with six showing prognostic values (AHNAK, MAP1B, LAMA2, P4HB, FASN, and GSDMB). In both the GSE32548 and GSE31684 datasets, patients with low-risk scores in survival-related six RBPs-based prognostic model showed longer overall survival than those with high-risk scores. AHNAK, MAP1B, P4HB, and FASN expression were significantly upregulated in both BC tissues and cell lines. BC tissues from high-risk group showed higher proportions of naive CD4+ T cells, M0 and M2 macrophages, and neutrophils and lower proportions of plasma cells, CD8+ T cells, and T-cell follicular helper compared to low-risk group. AHNAK knockdown significantly inhibited the proliferation, invasion, and migration of BC cells in vitro and inhibited the growth of subcutaneous tumors in vivo. We thus developed and functionally validated a novel six RBPs-based prognostic model for BC.

The role of Insulin-like growth factor 2 mRNA-binding proteins (IGF2BPs) as m6A readers in cancer

RNA can be modified by over 170 types of distinct chemical modifications, and the most abundant internal modification of mRNA in eukaryotes is N6-methyladenosine (m6A). The m6A modification accelerates mRNA process, including mRNA splicing, translation, transcript stability, export and decay. m6A RNA modification is installed by methyltransferase-like proteins (writers), and potentially removed by demethylases (erasers), and this process is recognized by m6A-binding proteins (readers). Notably, alterations of m6A-modified proteins (writers, erasers and readers) are involved in the tumorigenesis, progression and metastasis. Importantly, the fate of m6A-methylated mRNA is mediated mostly through m6A readers, and among these readers, insulin-like growth factor 2 mRNA-binding proteins (IGF2BPs) are unique RNA-binding proteins (RBPs) that stabilize their targets mRNA via m6A modification. In this review, we update the writers, erasers and readers, and their cross-talks in m6A modification, and briefly discuss the oncogenic role of IGF2BPs in cancer. Most importantly, we mainly review the up-to-date knowledges of IGF2BPs (IGF2BP1/2/3) as m6A readers in an m6A-modified manner in cancer progression.

RNA-binding Protein MBNL2 regulates Cancer Cell Metastasis through MiR-182-MBNL2-AKT Pathway

The aberrant expression of RNA-binding proteins (RBPs) plays important roles in the occurrence and progression of cancer. MBNL2 is a member of the RNA binding protein MBNL family that is widely expressed in mammalian cells. We report here that MBNL2 is downregulated in breast, lung and liver cancer tissues, the promoter methylation levels of MBNL2 are higher in cancer tissues than normal tissues. The enrichment analysis of MBNL2 correlated genes indicates the potential function of MBNL2 on cancer progression. MBNL2 regulates cancer cell migration and invasion by modulating PI3K/AKT-mediated epithelial-mesenchymal transition. PI3K/AKT inhibitor overcomes the promotive effect of shMBNL2 on metastasis. The expression of MBNL2 is directly targeted by miR-182. miR-182 is upregulated in breast, lung and liver cancers and has good potential for cancer diagnosis. miR-182 promotes cancer cell migration and invasion by inhibiting the expression of MBNL2. Re-introduction of exogenous MBNL2 reverses the promotive effect of miR-182 on metastasis. Collectively, these findings suggest that MBNL2 plays a tumor suppressive function through miR-182-MBNL2-AKT-EMT signaling pathways.