RNA-binding protein CELF1 enhances cell migration, invasion, and chemoresistance by targeting ETS2 in colorectal cancer

CELF6 as an Oncogene in Colorectal Cancer: Targeting Stem-Cell-Like Properties Through Modulation of HOXA5 mRNA Stability

BACKGROUND

Emerging evidence indicates the essential role of cancer stem cells (CSCs) in the development and progression of various cancers, including colorectal cancer (CRC). CELF6, a member of the cytosine-uridine-guanine-binding protein (CUG-BP), Elav-like family (CELF), has been reported to be downregulated in CRC tissues. This study aims to elucidate the role and underlying mechanisms of CELF6 in CRC progression.

METHODS

The expression levels and prognostic significance of CELF6, along with its association with homeobox A5 (HOXA5), were analyzed using University of Alabama at Birmingham Cancer Data Analysis Portal (UALCAN), PrognoScan, and Tumor Immune Estimation Resource (TIMER) databases. The expression of CELF6 was further assessed through quantitative real-time polymerase chain reaction (qRT-PCR), immunoblotting, and immunohistochemistry. Both in vitro and in vivo experiments were conducted to investigate the effects of CELF6 on CRC cell proliferation, stemness and tumorigenesis, and to elucidate the molecular mechanisms.

RESULTS

CELF6 was found to be downregulated in CRC and was associated with poor prognosis. Functional studies revealed that overexpression of CELF6 resulted in decreased CRC cell proliferation and stemness in vitro, reduced tumor growth in vivo, and induced G1 phase cell cycle arrest. Mechanistically, CELF6 regulated the expression of HOXA5 by modulating its mRNA stability. Furthermore, the knockdown of HOXA5 reversed the inhibitory effects of CELF6 on CRC cell proliferation and stemness, demonstrating that silencing HOXA5 counteracted the suppressive effects of CELF6.

CONCLUSIONS

This study is the first to identify CELF6 as a suppressor of stemness and a modulator of CRC progression. These findings provide new insights into the role of CELF6 in CRC and highlight its potential as a novel therapeutic target.

MicroRNA-382 as a tumor suppressor during tumor progression

Despite the recent progresses in therapeutic and diagnostic methods, there is still a significantly high rate of mortality among cancer patients. One of the main reasons for the high mortality rate in cancer patients is late diagnosis, which leads to the failure of therapeutic strategies. Therefore, investigation of cancer biology can lead to the introduction of early diagnostic markers in these patients. MicroRNAs (miRNAs) play an important role in regulation of cellular processes associated with tumor progression. Due to the high stability of miRNAs in body fluids, these factors can be considered as the non-invasive tumor markers. Deregulation of miR-382 has been widely reported in different cancers. Therefore, in this review, we investigated the role of miR-382 during tumor development. It has shown that miR-382 has mainly a tumor suppressive, which inhibits the growth of tumor cells through the regulation of signaling pathways, RNA-binding proteins, and transcription factors. Therefore, miR-382 can be suggested as a diagnostic and therapeutic marker in cancer patients.

RNA Binding Proteins as Potential Therapeutic Targets in Colorectal Cancer

RNA-binding proteins (RBPs) play critical roles in regulating post-transcriptional gene expression, managing processes such as mRNA splicing, stability, and translation. In normal intestine, RBPs maintain the tissue homeostasis, but when dysregulated, they can drive colorectal cancer (CRC) development and progression. Understanding the molecular mechanisms behind CRC is vital for developing novel therapeutic strategies, and RBPs are emerging as key players in this area. This review highlights the roles of several RBPs, including LIN28, IGF2BP1-3, Musashi, HuR, and CELF1, in CRC. These RBPs regulate key oncogenes and tumor suppressor genes by influencing mRNA stability and translation. While targeting RBPs poses challenges due to their complex interactions with mRNAs, recent advances in drug discovery have identified small molecule inhibitors that disrupt these interactions. These inhibitors, which target LIN28, IGF2BPs, Musashi, CELF1, and HuR, have shown promising results in preclinical studies. Their ability to modulate RBP activity presents a new therapeutic avenue for treating CRC. In conclusion, RBPs offer significant potential as therapeutic targets in CRC. Although technical challenges remain, ongoing research into the molecular mechanisms of RBPs and the development of selective, potent, and bioavailable inhibitors should lead to more effective treatments and improved outcomes in CRC.

PKC-mediated phosphorylation governs the stability and function of CELF1 as a driver of EMT in breast epithelial cells

Epithelial to mesenchymal transition (EMT) is believed to be a principal factor contributing to cancer metastasis. The post-transcriptional and post-translational mechanisms underlying EMT are comparatively underexplored. We previously demonstrated that the CELF1 RNA binding protein is necessary and sufficient to drive the EMT of breast epithelial cells, and that the relative protein expression of CELF1 in this context was dictated at the post-translational level. Here, we elucidate the mechanism of this regulation. Mass spectrometric analysis of CELF1 isolated from mesenchymal MCF-10A cells identified multiple sites of serine and threonine phosphorylation on the protein, correlating with the increased stability of this protein in this cellular state. Analysis of phosphomimetic and serine/threonine-to-alanine phosphomutant variants of CELF1 revealed that these phosphorylation sites indeed dictate CELF1 stability, ubiquitination state, and function in vitro. Via co-immunoprecipitation and in vitro kinase assays, we identified the protein kinase C alpha and epsilon isozymes as the kinases responsible for CELF1 phosphorylation in a breast cell line. Genetic epistasis experiments confirmed that these PKCs function upstream of CELF1 in this EMT program, and CELF1 phosphorylation impacts tumor metastasis in a xenograft model. This work is the first to formally establish the mechanisms underlying post-translational control of CELF1 expression and function during EMT of breast epithelial cells. Given the broad dysregulation of CELF1 expression in human breast cancer, our results may ultimately provide knowledge that may be leveraged for novel therapeutic interventions in this context.

Comprehensive analysis of the functions, prognostic and diagnostic values of RNA binding proteins in head and neck squamous cell carcinoma

BACKGROUND

Accumulating evidence has suggested that RNA binding protein (RBP) dysregulation plays an essential role during tumorigenesis. Here, we sought to explore the potential biological functions and clinical significance of RBP and develop diagnostic and prognostic signatures based on RBP in patients with head and neck squamous cell carcinoma (HNSCC).

METHODS

The differently expressed RBPs between HNSCC samples and their normal counterparts were identified using the Limma package. The immunohistochemistry (IHC) images of several RBPs were collected from the Human Protein Atlas database. The diagnostic signature based on RBP was built by LASSO-logistic regression and random forest. The prognostic signature based on RBP was constructed by LASSO and stepwise Cox regression analysis in the training cohort and validated in the validation cohort.

RESULTS

Eighty-four aberrantly expressed RBPs were obtained, comprising 41 up-regulated and 43 down-regulated RBPs. Seven RBP genes (CPEB3, PDCD4, ENDOU, PARP12, DNMT3B, IGF2BP1, EXO1) were identified as diagnostic-related hub genes. They were used to establish a diagnostic RBP signature risk score (DRBPS) model by the coefficients in least absolute shrinkage and selection operator (LASSO)-logistic regression analysis and showed high specificity and sensitivity in the training (area under the receiver operating characteristic curve (AUC) = 0.998), and in all validation cohorts (AUC > 0.95 for all). Similarly, seven RBP genes (MKRN3, ZC3H12D, EIF5A2, AFF3, SIDT1, RBM24, and NR0B1) were identified as prognosis-associated hub genes by LASSO and stepwise multiple Cox regression analyses and were used to construct the prognostic model named as PRBPS. The AUC of the time-dependent receiver operator characteristic curve of the prognostic model was 0.664 at 3 years and 0.635 at 5 years in the training cohort and 0.720, 0.777 in the validation cohort, showing a favorable predictive efficacy for prognosis in HNSCC.

CONCLUSIONS

Our results demonstrate the value of consideration of RBP in the diagnosis and prognosis for HNSCC and provide a novel insight into understanding the potential role of dysregulated RBP in HNSCC.

Biomarker discovery with quantum neural networks: a case-study in CTLA4-activation pathways

BACKGROUND

Biomarker discovery is a challenging task due to the massive search space. Quantum computing and quantum Artificial Intelligence (quantum AI) can be used to address the computational problem of biomarker discovery from genetic data.

METHOD

We propose a Quantum Neural Networks architecture to discover genetic biomarkers for input activation pathways. The Maximum Relevance-Minimum Redundancy criteria score biomarker candidate sets. Our proposed model is economical since the neural solution can be delivered on constrained hardware.

RESULTS

We demonstrate the proof of concept on four activation pathways associated with CTLA4, including (1) CTLA4-activation stand-alone, (2) CTLA4-CD8A-CD8B co-activation, (3) CTLA4-CD2 co-activation, and (4) CTLA4-CD2-CD48-CD53-CD58-CD84 co-activation.

CONCLUSION

The model indicates new genetic biomarkers associated with the mutational activation of CLTA4-associated pathways, including 20 genes: CLIC4, CPE, ETS2, FAM107A, GPR116, HYOU1, LCN2, MACF1, MT1G, NAPA, NDUFS5, PAK1, PFN1, PGAP3, PPM1G, PSMD8, RNF213, SLC25A3, UBA1, and WLS. We open source the implementation at: https://github.com/namnguyen0510/Biomarker-Discovery-with-Quantum-Neural-Networks .

Curriculum vitae of CUG binding protein 1 (CELF1) in homeostasis and diseases: a systematic review

RNA-binding proteins (RBPs) are kinds of proteins with either singular or multiple RNA-binding domains (RBDs), and they can assembly into ribonucleic acid-protein complexes, which mediate transportation, editing, splicing, stabilization, translational efficiency, or epigenetic modifications of their binding RNA partners, and thereby modulate various physiological and pathological processes. CUG-BP, Elav-like family 1 (CELF1) is a member of the CELF family of RBPs with high affinity to the GU-rich elements in mRNA, and thus exerting control over critical processes including mRNA splicing, translation, and decay. Mounting studies support that CELF1 is correlated with occurrence, genesis and development and represents a potential therapeutical target for these malignant diseases. Herein, we present the structure and function of CELF1, outline its role and regulatory mechanisms in varieties of homeostasis and diseases, summarize the identified CELF1 regulators and their structure-activity relationships, and prospect the current challenges and their solutions during studies on CELF1 functions and corresponding drug discovery, which will facilitate the establishment of a targeted regulatory network for CELF1 in diseases and advance CELF1 as a potential drug target for disease therapy.

ETV7 promotes colorectal cancer progression through upregulation of IFIT3

Members of the E26 transformation-specific (ETS) variant transcription factor family act as either tumor suppressors or oncogenic factors in numerous types of cancer. ETS variant transcription factor 7 (ETV7) participates in the development of malignant tumors, whereas its involvement in colorectal cancer (CRC) is less clear. In this study, The Cancer Genome Atlas (TCGA) and immunochemistry staining were applied to check the clinical relevance of ETV7 and interferon-induced protein with tetratricopeptide repeats 3 (IFIT3) in CRC patients. Overexpression and knockdown of ETV7 and IFIT3 were conducted by transfecting the cells with pCDNA3.1 plasmids and siRNAs, respectively. Western blotting was used to detect the protein expression of ETV7 in CRC cells. Cell Counting Kit-8, cell colony formation, and Transwell assays, as well as flow cytometry, were used to evaluate the proliferation, migration, cell cycle, and apoptosis of CRC cells. Furthermore, western blotting, RT-qPCR, and luciferase assay were used to explore the regulation of ETV7 on IFIT3. Rescue assay was used to investigate the significance of ETV7/IFIT3 axis on CRC progression. We found that ETV7 was upregulated in CRC tissues and cells. Overexpression of ETV7 stimulated the proliferation, migration, and cell cycle amplification, and reduced the apoptosis of CRC cells. Downregulation of ETV7 exerted the opposite effect on CRC cell progression. Moreover, we demonstrated that ETV7 stimulated the transcription activity, the mRNA and protein expression of IFIT3 in CRC cells. There was a positive correlation between ETV7 and IFIT3 in CRC patients. IFIT3 knockdown reversed the promotive effect exerted by overexpression of ETV7 on the amplification and migration of CRC cells. By contrast, overexpression of IFIT3 blocked the inhibitory effect of ETV7-targeting siRNA. In summary, ETV7 induces progression of CRC by activating the transcriptional expression of IFIT3. The EVT7/IFIT3 axis may be a novel target for CRC therapy.

Integrating scRNA-seq and bulk RNA-seq to characterize infiltrating cells in the colorectal cancer tumor microenvironment and construct molecular risk models

Colorectal cancer (CRC) is a malignancy that is both highly lethal and heterogeneous. Although the correlation between intra-tumoral genetic and functional heterogeneity and cancer clinical prognosis is well-established, the underlying mechanism in CRC remains inadequately understood. Utilizing scRNA-seq data from GEO database, we re-isolated distinct subsets of cells, constructed a CRC tumor-related cell differentiation trajectory, and conducted cell-cell communication analysis to investigate potential interactions across cell clusters. A prognostic model was built by integrating scRNA-seq results with TCGA bulk RNA-seq data through univariate, LASSO, and multivariate Cox regression analyses. Eleven distinct cell types were identified, with Epithelial cells, Fibroblasts, and Mast cells exhibiting significant differences between CRC and healthy controls. T cells were observed to engage in extensive interactions with other cell types. Utilizing the 741 signature genes, prognostic risk score model was constructed. Patients with high-risk scores exhibited a significant correlation with unfavorable survival outcomes, high-stage tumors, metastasis, and low responsiveness to chemotherapy. The model demonstrated a strong predictive performance across five validation cohorts. Our investigation involved an analysis of the cellular composition and interactions of infiltrates within the microenvironment, and we developed a prognostic model. This model provides valuable insights into the prognosis and therapeutic evaluation of CRC.

Roles of miR-4442 in Colorectal Cancer: Predicting Early Recurrence and Regulating Epithelial-Mesenchymal Transition

Early recurrence in patients with colorectal cancer (CRC) is associated with a poor prognosis. We aimed to identify circulating microRNAs that are biomarkers of early CRC recurrence and elucidate their functions. We identified miR-4442 as a candidate biomarker by microRNA array analysis comparing preoperative and postoperative plasma levels in patients with CRC, with and without recurrence. The association between preoperative plasma miR-4442 levels, clinicopathological features, and recurrence-free survival was analyzed in 108 patients with CRC after curative surgery. Furthermore, cell-function analyses were performed, and the involvement of miR-4442 in regulating epithelial-mesenchymal transition (EMT) was examined. Preoperatively plasma miR-4442 levels were associated with CRC recurrence and exhibited an incremental increase with earlier recurrence dates. Moreover, miR-4442 demonstrated high sensitivity and specificity as a potential biomarker for early CRC recurrence. The expression of miR-4442 in cancer tissues of patients with metastatic liver cancer from CRC was higher than in normal liver, CRC, and normal colorectal tissues. The overexpression of miR-4442 promoted the proliferative, migratory, and invasive activities of CRC cells, decreased levels of RBMS1 and E-cadherin, and increased levels of N-cadherin and Snail1. Plasma miR-4442 is a clinically useful biomarker for predicting the early recurrence of CRC. Furthermore, miR-4442 regulates EMT in CRC by directly targeting the messenger RNA of RBMS1.

Phase separation of DDX21 promotes colorectal cancer metastasis via MCM5-dependent EMT pathway

RNA binding proteins (RBPs) contributes to cancer progression, but the underlying mechanism reminds unclear. Here, we find that DDX21, a representative RBP, is highly expressed in colorectal cancer (CRC), which leads to CRC cell migration and invasion in vitro, and CRC to liver metastasis and lung metastasis in vivo. This effect of DDX21 on CRC metastasis is correlated to the activation of Epithelial-mesenchymal transition (EMT) pathway. Moreover, we reveal that DDX21 protein is phase separated in vitro and in CRC cells, which controls CRC metastasis. Phase-separated DDX21 highly binds on MCM5 gene locus, which is markedly reduced when phase separation is disrupted by mutations on its intrinsically disordered region (IDR). The impaired metastatic ability of CRC upon DDX21 loss is restored by ectopic expression of MCM5, indicating MCM5 is a key downstream target of DDX21 for CRC metastasis. Furthermore, co-higher expressions of DDX21 and MCM5 is significantly correlated with poor survival outcomes of stage III and IV CRC patients, indicating the importance of this mechanism in CRC late and metastatic stage. Altogether, our results elucidate a new model of DDX21 in regulating CRC metastasis via phase separation.

Characterization of butyrate-metabolism in colorectal cancer to guide clinical treatment

Colorectal cancer (CRC) is the third most prevalent one in the world among the most common malignant tumors. Numerous studies have shown that butyrate has demonstrated promise as an antitumor agent in a variety of human cancer types. However, butyrate remains understudied in CRC tumorigenesis and progression. In this study, we explored therapeutic strategies to treat CRC by examining the role of butyrate metabolism. First, from the Molecular Signature Database (MSigDB), we identified 348 butyrate metabolism-related genes (BMRGs). Next, we downloaded 473 CRC and 41 standard colorectal tissue samples from The Cancer Genome Atlas (TCGA) database and the transcriptome data of GSE39582 dataset from Gene Expression Omnibus (GEO) database. Then we evaluated the expression patterns of butyrate metabolism-related genes with difference analysis in CRC. Through univariate Cox regression and least absolute shrinkage and selection operator (LASSO) analysis, a prognostic model was constructed based on differentially expressed BMRGs. In addition, we discovered an independent prognostic marker for CRC patients. According to the expression levels and coefficients of identified BMRGs, the risk scores of all CRC samples were calculated. Utilizing differentially expressed genes in the high- and low-risk groups, we also constructed a Protein-Protein Interaction (PPI) network to visualize the interactions between proteins. Through the results of PPI network, we screened out differentially expressed target butyrate metabolism-related genes from ten hub genes. Finally, we performed clinical correlation analysis, immune cell infiltration analysis, and mutation analysis for these target genes. One hundred and seventy three differentially expressed butyrate metabolism-related genes were screened out in all the CRC samples. The prognostic model was established with univariate Cox regression and LASSO regression analysis. CRC patients' overall survival was significantly lower in the high-risk group than in the low-risk group for both training and validation set. Among the ten hub genes identified from the PPI network, four target butyrate metabolism-related genes were identified containing FN1, SERPINE1, THBS2, and COMP, which might provide novel markers or targets for treating CRC patients. Eighteen butyrate metabolism-related genes were used to develop a risk prognostic model that could be helpful for doctors to predict CRC patients' survival rate. Using this model, it is beneficial to forecast the response of CRC patients to immunotherapy and chemotherapy, thus making it easier to custom tailor cancer chemotherapy and immunotherapy to the individual patient.

Targeting the "undruggable": RNA-binding proteins in the spotlight in cancer therapy

Tumors refractory to conventional therapy belong to specific subpopulations of cancer cells, which have acquired a higher number of mutations/epigenetic changes than the majority of cancer cells. This property provides them the ability to become resistant to therapy. Aberrant expression of certain RNA-binding proteins (RBPs) can regulate the sensitivity of tumor cells to chemotherapeutic drugs by binding to specific regions present in the 3´-UTR of certain mRNAs to promote or repress mRNA translation or by interacting with other proteins (including RBPs) and non-coding RNAs that are part of ribonucleoprotein complexes. In particular, an increasing interest in the RBPs involved in chemoresistance has recently emerged. In this review, we discuss how RBPs are not only affected by chemotherapeutic treatments, but also play an active role in therapeutic responses via the direct modulation of crucial cancer-related proteins. A special focus is being placed on the development of therapeutic strategies targeting these RBPs.

Long non-coding RNA and RNA-binding protein interactions in cancer: Experimental and machine learning approaches

Understanding the complex and specific roles played by non-coding RNAs (ncRNAs), which comprise the bulk of the genome, is important for understanding virtually every hallmark of cancer. This large group of molecules plays pivotal roles in key regulatory mechanisms in various cellular processes. Regulatory mechanisms, mediated by long non-coding RNA (lncRNA) and RNA-binding protein (RBP) interactions, are well documented in several types of cancer. Their effects are enabled through networks affecting lncRNA and RBP stability, RNA metabolism including N⁶-methyladenosine (m⁶A) and alternative splicing, subcellular localization, and numerous other mechanisms involved in cancer. In this review, we discuss the reciprocal interplay between lncRNAs and RBPs and their involvement in epigenetic regulation via histone modifications, as well as their key role in resistance to cancer therapy. Other aspects of RBPs including their structural domains, provide a deeper knowledge on how lncRNAs and RBPs interact and exert their biological functions. In addition, current state-of-the-art knowledge, facilitated by machine and deep learning approaches, unravels such interactions in better details to further enhance our understanding of the field, and the potential to harness RNA-based therapeutics as an alternative treatment modality for cancer are discussed.

Application of RNA processing factors for predicting clinical outcomes in colon cancer

Background: Colon cancer is the fifth most common cause of cancer-related death worldwide, and despite significant advances in related treatment, the prognosis of colon cancer patients remains poor.

Objective: This study performs systematic bioinformatics analysis of prognostic-associated RNA processing factor genes in colon cancer using the Cancer Related Genome Atlas database to explore their role in colon carcinogenesis and prognosis and excavate potential therapeutic targets.

Methods: Data sets of colon cancer patients were obtained from GEO and TCGA databases. Univariate cox analysis was performed on the GSE39582 training set to identify prognosis-associated RNA processing factor genes and constructed a muticox model. The predictive performance of the model was validated by Correlation curve analysis. Similar results were obtained for the test dataset. Functional analyses were performed to explore the underlying mechanisms of colon carcinogenesis and prognosis.

Results: A constructed muticox model consisting of βi and prognosis-related RNA processing factor gene expression levels (Expi) was established to evaluate the risk score of each patient. The subgroup with a higher risk score had lower overall survival (OS), higher risk factor, and mortality. We found that the risk score, age, gender, and TNM Stage were strongly associated with OS, and the 13-gene signature as an independent prognostic factor for colon cancer. The model has good accuracy in predicting patient survival and is superior to traditional pathological staging.

Conclusion: This study proposes 13 RNA processing factor genes as a prognostic factor for colon cancer patients, which can independently predict the clinical outcome by risk score. The gene expression profile in this model is closely related to the immune status and prognosis of colon cancer patients. The interaction of the 13 RNA processing factor genes with the immune system during colon carcinogenesis provides new ideas for the molecular mechanisms and targeted therapies for colon cancer.

Screening Gene Expression-Related Alternative Splicing Event Signature for Colon Cancer Prognostic Prediction

Colon cancer is a kind of common intestinal disease, and early diagnosis of colon cancer is crucial for patient's prognosis. RNA alternative splicing (AS) is an RNA modification that affects cancer occurrence. RNA AS detection is promising to improve the in-depth understanding of the pathological mechanisms in colon cancer. In this study, differential analysis was performed to determine colon cancer-related AS events and the corresponding parental genes. Subsequently, GO functional annotation analysis was carried out on the parental genes, which revealed that these AS events might affect cell adhesion and cell growth. Besides, protein-protein interaction (PPI) network was established with the parental genes, in which MCODE was utilized to identify major functional modules. Enrichment analysis for the major functional module was implemented again, which demonstrated that these genes were mainly concentrated in the ribosome, protein ubiquitination, cell adhesion molecule binding, and other relevant biological functions. Next, differentially expressed genes (DEGs) were screened from colon cancer and normal tissues and overlapped with the parental genes, by which 55 gene expression-associated AS and the corresponding 45 genes were obtained. Moreover, a correlation analysis between splicing factors (SFs) and AS was done to identify interactions. On this basis, an SF-AS network was constructed. The univariate Cox regression analysis was employed to screen prognostic AS signature and establish a risk model. To assess the model, K-M and ROC analyses were done for model assessment, indicating the effective prediction performance. Combined with common clinicopathological features, the multivariate Cox regression analysis was conducted to confirm whether the risk model could be considered as an independent prognostic indicator. Finally, the expression status of the parental genes for the prognostic AS was evaluated between normal and colon cancer cells using qRT-PCR. In summary, TCGA SpliceSeq data were comprehensively analyzed, and a 5-AS prognostic model was constructed for colon cancer.

DLX6-AS1 activated by H3K4me1 enhanced secondary cisplatin resistance of lung squamous cell carcinoma through modulating miR-181a-5p/miR-382-5p/CELF1 axis

Cisplatin (CDDP) based chemotherapy is widely used as the first-line strategy in treating non-small cell lung cancer (NSCLC), especially lung squamous cell carcinoma (LUSC). However, secondary cisplatin resistance majorly undermines the cisplatin efficacy leading to a worse prognosis. In this respect, we have identified the role of the DLX6-AS1/miR-181a-5p/miR-382-5p/CELF1 axis in regulating cisplatin resistance of LUSC. qRT-PCR and Western blot analysis were applied to detect gene expression. Transwell assay was used to evaluate the migration and invasion ability of LUSC cells. CCK-8 assay was used to investigate the IC50 of LUSC cells. Flow cytometry was used to test cell apoptosis rate. RNA pull-down and Dual luciferase reporter gene assay were performed to evaluate the crosstalk. DLX6-AS1 was aberrantly high expressed in LUSC tissues and cell lines, and negatively correlated with miR-181a-5p and miR-382-5p expression. DLX6-AS1 expression was enhanced by H3K4me1 in cisplatin resistant LUSC cells. Besides, DLX6-AS1 knockdown led to impaired IC50 of cisplatin resistant LUSC cells. Furthermore, DLX6-AS1 interacted with miR-181a-5p and miR-382-5p to regulate CELF1 expression and thereby mediated the cisplatin sensitivity of cisplatin resistant LUSC cells. DLX6-AS1 induced by H3K4me1 played an important role in promoting secondary cisplatin resistance of LUSC through regulating the miR-181a-5p/miR-382-5p/CELF1 axis. Therefore, targeting DLX6-AS1 might be a novel way of reversing secondary cisplatin resistance in LUSC.

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.

Comprehensive analysis of aberrant alternative splicing related to carcinogenesis and prognosis of papillary thyroid cancer

As a key mechanism, alternative splicing (AS) plays a role in the cancer initiation and development. However, in papillary thyroid cancer (PTC), data for the comprehensive AS event profile and its clinical implications are lacking. Herein, a genome-wide AS event profiling using RNA-Seq data and its correlation with matched clinical information was performed using a 389 PTC patient cohort from the project of The Cancer Genome Atlas (TCGA). We identified 1,925 cancer-associated AS events (CASEs) by comparing paired tumors and neighboring healthy tissues. Parent genes with CASEs remarkably enriched in the pathways were linked with carcinogenesis, such as P53, KRAS, IL6-JAK-STAT3, apoptosis, and MYC signaling. The regulatory networks of AS implied an obvious correlation between the expression of splicing factor and CASE. We identified eight CASEs as predictors for overall survival (OS) and disease-free survival (DFS). The established risk score model based on DFS-associated CASEs successfully predicted the prognosis of PTC patients. From the unsupervised clustering analysis results, it is found that different clusters based on AS correlated with prognosis, molecular features, and immune characteristics. Taken together, the comprehensive genome-wide AS landscape analysis in PTC showed new AS events linked with tumorigenesis and prognosis, which provide new insights for clinical monitoring and therapy for PTC.

Identification of Transcription Factor-Related Gene Signature and Risk Score Model for Colon Adenocarcinoma

The prognosis of colon adenocarcinoma (COAD) remains poor. However, the specific and sensitive biomarkers for diagnosis and prognosis of COAD are absent. Transcription factors (TFs) are involved in many biological processes in cells. As the molecule of the signal pathway of the terminal effectors, TFs play important roles in tumorigenesis and development. A growing body of research suggests that aberrant TFs contribute to the development of COAD, as well as to its clinicopathological features and prognosis. In consequence, a few studies have investigated the relationship between the TF-related risk model and the prognosis of COAD. Therefore, in this article, we hope to develop a prognostic risk model based on TFs to predict the prognosis of patients with COAD. The mRNA transcription data and corresponding clinical data were downloaded from TCGA and GEO. Then, 141 differentially expressed genes, validated by the GEPIA2 database, were identified by differential expression analysis between normal and tumor samples. Univariate, multivariate and Lasso Cox regression analysis were performed to identify seven prognostic genes (E2F3, ETS2, HLF, HSF4, KLF4, MEIS2, and TCF7L1). The Kaplan-Meier curve and the receiver operating characteristic curve (ROC, 1-year AUC: 0.723, 3-year AUC: 0.775, 5-year AUC: 0.786) showed that our model could be used to predict the prognosis of patients with COAD. Multivariate Cox analysis also reported that the risk model is an independent prognostic factor of COAD. The external cohort (GSE17536 and GSE39582) was used to validate our risk model, which indicated that our risk model may be a reliable predictive model for COAD patients. Finally, based on the model and the clinicopathological factors, we constructed a nomogram with a C-index of 0.802. In conclusion, we emphasize the clinical significance of TFs in COAD and construct a prognostic model of TFs, which could provide a novel and reliable model for the prognosis of COAD.

The E-Twenty-Six Family in Hepatocellular Carcinoma: Moving into the Spotlight

Hepatocellular carcinoma (HCC) is a major cause of morbidity and mortality worldwide. Although therapeutic strategies have recently advanced, tumor metastasis and drug resistance continue to pose challenges in the treatment of HCC. Therefore, new molecular targets are needed to develop novel therapeutic strategies for this cancer. E-twenty-six (ETS) transcription family has been implicated in human malignancies pathogenesis and progression, including leukemia, Ewing sarcoma, gastrointestinal stromal tumors. Recently, increasing studies have expanded its great potential as functional players in other cancers, including HCC. This review focuses primarily on the key functions and molecular mechanisms of ETS factors in HCC. Elucidating these molecular details may provide novel potential therapeutic strategies for cancers.

Identification of Two Novel Circular RNAs Deriving from BCL2L12 and Investigation of Their Potential Value as a Molecular Signature in Colorectal Cancer

The utility of circular RNAs (circRNAs) as molecular biomarkers has recently emerged. However, only a handful of them have already been studied in colorectal cancer (CRC). The purpose of this study was to identify new circRNAs deriving from BCL2L12, a member of the BCL2 apoptosis-related family, and investigate their potential as biomarkers in CRC. Total RNA extracts from CRC cell lines and tissue samples were reversely transcribed. By combining PCR with divergent primers and nested PCR followed by Sanger sequencing, we were able to discover two BCL2L12 circRNAs. Subsequently, bioinformatical tools were used to predict the interactions of these circRNAs with microRNAs (miRNAs) and RNA-binding proteins (RBPs). Following a PCR-based pre-amplification, real-time qPCR was carried out for the quantification of each circRNA in CRC samples and cell lines. Biostatistical analysis was used to assess their potential prognostic value in CRC. Both novel BCL2L12 circRNAs likely interact with particular miRNAs and RBPs. Interestingly, circ-BCL2L12-2 expression is inversely associated with TNM stage, while circ-BCL2L12-1 overexpression is associated with shorter overall survival in CRC, particularly among TNM stage II patients. Overall, we identified two novel BCL2L12 circRNAs, one of which can further stratify TNM stage II patients into two subgroups with substantially distinct prognosis.

Development and validation of a RNA binding protein gene pair-associated prognostic signature for prediction of overall survival in hepatocellular carcinoma

BACKGROUND

Increasing evidence has demonstrated the correlation between hepatocellular carcinoma (HCC) prognosis and RNA binding proteins (RBPs) dysregulation. Thus, we aimed to develop and validate a reliable prognostic signature that can estimate the prognosis for HCC.

METHODS

Gene expression profiling and clinical information of 374 HCC patients were derived from the TCGA data portal. The survival-related RBP pairs were determined using univariate cox-regression analysis and the signature was built based on LASSO analysis. All patients were divided patients into high-and low-risk groups according to the optimal cut off of the signature score determined by time-dependent receiver operating characteristic (ROC) curve analysis. The predictive value of the signature was further validated in an independent cohort.

RESULTS

A 37-RBP pairs signature consisting of 61 unique genes was constructed which was significantly associated with the survival. The RBP-related signature accurately predicted the prognosis of HCC patients, and patients in high-risk groups showed poor survival in two cohorts. The novel signature was an independent prognostic factor of HCC in two cohorts (all P < 0.001). Furthermore, the C-index of the prognostic model was 0.799, which was higher than that of many established risk models. Pathway and process enrichment analysis showed that the 61 unique genes were mainly enriched in translation, ncRNA metabolic process, RNA splicing, RNA modification, and translational termination.

CONCLUSION

The novel proposed RBP-related signature based on relative expression orderings could serve as a promising independent prognostic biomarker for patients with HCC, and could improve the individualized survival prediction in HCC.