Molecular Characterization and Clinical Relevance of RNA Binding Proteins in Colorectal Cancer

Identification of New Prognostic Genes and Construction of a Prognostic Model for Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) is a rapidly progressive malignancy, and its mortality rate is very high. In this study, we aimed at finding novel prognosis-related genes and constructing a credible prognostic model to improve the prediction for LUAD patients. Differential gene expression, mutant subtype, and univariate Cox regression analyses were conducted with the dataset from the Cancer Genome Atlas (TCGA) database to screen for prognostic features. These features were employed in the following multivariate Cox regression analysis and the produced prognostic model included the stage and expression of SMCO2, SATB2, HAVCR1, GRIA1, and GALNT4, as well as mutation subtypes of TP53. The exactness of the model was confirmed by an overall survival (OS) analysis and disease-free survival (DFS) analysis, which indicated that patients in the high-risk group had a poorer prognosis compared to those in the low-risk group. The area under the receiver operating characteristic curve (AUC) was 0.793 in the training group and 0.779 in the testing group. The AUC of tumor recurrence was 0.778 in the training group and 0.815 in the testing group. In addition, the number of deceased patients increased as the risk scores raised. Furthermore, the knockdown of prognostic gene HAVCR1 suppressed the proliferation of A549 cells, which supports our prognostic model that the high expression of HAVCR1 predicts poor prognosis. Our work created a reliable prognostic risk score model for LUAD and provided potential prognostic biomarkers.

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.

Nonsense-Mediated mRNA Decay Factor Functions in Human Health and Disease

Nonsense-mediated mRNA decay (NMD) is a cellular surveillance mechanism that degrades mRNAs with a premature stop codon, avoiding the synthesis of C-terminally truncated proteins. In addition to faulty mRNAs, NMD recognises ~10% of endogenous transcripts in human cells and downregulates their expression. The up-frameshift proteins are core NMD factors and are conserved from yeast to human in structure and function. In mammals, NMD diversified into different pathways that target different mRNAs employing additional NMD factors. Here, we review our current understanding of molecular mechanisms and cellular roles of NMD pathways and the involvement of more specialised NMD factors. We describe the consequences of mutations in NMD factors leading to neurodevelopmental diseases, and the role of NMD in cancer. We highlight strategies of RNA viruses to evade recognition and decay by the NMD machinery.

A double-edged sword: role of apoptosis repressor with caspase recruitment domain (ARC) in tumorigenesis and ischaemia/reperfusion (I/R) injury

Apoptosis repressor with caspase recruitment domain (ARC) acts as a potent and multifunctional inhibitor of apoptosis, which is mainly expressed in postmitotic cells, including cardiomyocytes. ARC is special for its N-terminal caspase recruitment domain and caspase recruitment domain. Due to the powerful inhibition of apoptosis, ARC is mainly reported to act as a cardioprotective factor during ischaemia‒reperfusion (I/R) injury, preventing cardiomyocytes from being devastated by various catastrophes, including oxidative stress, calcium overload, and mitochondrial dysfunction in the circulatory system. However, recent studies have found that ARC also plays a potential regulatory role in tumorigenesis especially in colorectal cancer and renal cell carcinomas, through multiple apoptosis-associated pathways, which remains to be explored in further studies. Therefore, ARC regulates the body and maintains the balance of physiological activities with its interesting duplex. This review summarizes the current research progress of ARC in the field of tumorigenesis and ischaemia/reperfusion injury, to provide overall research status and new possibilities for researchers.

KLF16 promotes pancreatic adenocarcinoma cell proliferation and migration by positively regulating SMAD6

BACKGROUND

Pancreatic adenocarcinoma (PAAD) is a cancerous tumor with an extremely poor 5-year survival rate. The exploration of biomarkers for the diagnosis and treatment of PAAD is crucial in clinical practice. Krüppel-like factors (KLFs) are involved in a variety of biological functions in cells. According to multiple studies, KLF16 behave as an oncogene in prostate, breast and gastric cancers. However, no research has been done on the significance of KLF16 in PAAD.

AIM

To explore the molecular mechanisms of KLF16 in PAAD.

METHODS

KLF16 was identified in the tumor specimens and normal tissues by GEPIA database and verified by quantitative real-time PCR (qRT-PCR). Knockdown or exogenous expression of KLF16, combined with in vitro and in vivo assays, was performed to show the functional significance of KLF16. The molecular mechanism of KLF16 was demonstrated by qRT-PCR, western blotting, immunoprecipitation assay and flow cytometry.

RESULTS

We showed that KLF16 was highly expressed in PAAD patients based on the GEPIA database. KLF16 silencing suppressed while KLF16 overexpression promoted the malignant function of PAAD cells. Based on RNA sequencing, we discovered that KLF16 potentiated the expression of SMAD6 in PAAD cells. SMAD6 transcript abundance was increased and positively correlated with KLF16 expression in PAAD samples. In addition, inhibiting SMAD6 was able to mitigate the effects of KLF16 overexpression on PAAD cell processes, suggesting the importance of SMAD6 in the development of KLF16-triggered PAAD.

CONCLUSION

KLF16/SMAD6 axis might be explored as a therapeutic target for PAAD therapy.

RNA-binding proteins: Underestimated contributors in tumorigenesis

mRNA export, translation, splicing, cleavage or capping determine mRNA stability, which represents one of the primary aspects regulating gene expression and function. RNA-binding proteins (RBPs) bind to their target mRNAs to regulate multiple cell functions by increasing or reducing their stability. In recent decades, studies of the role of RBPs in tumorigenesis have revealed an increasing number of proteins impacting the prognosis, diagnosis and cancer treatment. Several RBPs have been identified based on their interactions with oncogenes or tumor suppressor genes in human cancers, which are involved in apoptosis, the epithelial-mesenchymal transition (EMT), DNA repair, autophagy, cell proliferation, immune response, metabolism, and the regulation of noncoding RNAs. In this review, we propose a model showing how RBP mutations influence tumorigenesis, and we update the current knowledge regarding the molecular mechanism by which RBPs regulate cancer. Special attention is being devoted to RBPs that represent prognostic and diagnostic factors in cancer patients.

RNA-binding proteins in ovarian cancer: a novel avenue of their roles in diagnosis and treatment

Ovarian cancer (OC), an important cause of cancer-related death in women worldwide, is one of the most malignant cancers and is characterized by a poor prognosis. RNA-binding proteins (RBPs), a class of endogenous proteins that can bind to mRNAs and modify (or even determine) the amount of protein they can generate, have attracted great attention in the context of various diseases, especially cancers. Compelling studies have suggested that RBPs are aberrantly expressed in different cancer tissues and cell types, including OC tissues and cells. More specifically, RBPs can regulate proliferation, apoptosis, invasion, metastasis, tumorigenesis and chemosensitivity and serve as potential therapeutic targets in OC. Herein, we summarize what is currently known about the biogenesis, molecular functions and potential roles of human RBPs in OC and their prospects for application in the clinical treatment of OC.

The Prognostic and Molecular Landscape of Autophagy-Related Long Noncoding RNA in Colorectal Cancer

Current evidence suggests that autophagy is closely correlated with the pathogenesis and development of malignant tumors. This study is aimed at assessing the potential prognostic significance of autophagy-related long noncoding RNA (ARlncRNA) in colorectal cancer (CRC). 3145 ARlncRNAs were obtained from autophagy-related genes (ARGs) by Pearson correlation analysis, and we established a competing endogenous RNA (ceRNA) network mediated by ARlncRNAs. A novel six-ARlncRNA prognostic signature was constructed based on TCGA samples used as the training group. Kaplan–Meier survival analysis and independent prognosis analysis were performed on the internal (training and test groups) and external validations (GEO datasets) to assess the accuracy and clinical practicability. Moreover, the nomogram combining the two independent prognostic factors (age and ARlncRNA-risk score (ARlncRNA-RS)) intuitively displayed overall survival. Gene set enrichment analysis (GSEA) conducted on the prognostic signature revealed that the gene set of the high-risk group was significantly enriched in the hallmark gene set “hypoxia” and the gene set of the low-risk group was enriched in KEGG pathways, including “peroxisome,” “the citrate cycle (TCA cycle),” and “other glycan degradation.” Assessment of antineoplastic therapy susceptibility and microsatellite instability (MSI) analysis were performed on CRC samples based on the prognostic signature. Moreover, Spearman correlation analysis was conducted on the expression of six ARlncRNAs of the prognostic signature and cancer stem cell (CSC) index as well as the tumor microenvironment (TME). In conclusion, this study established a six-ARlncRNA prognostic signature, which yielded favorable prognostic significance and demonstrated the correlation between ARlncRNAs and CRC progression.

Prognostic implications of ferroptosis-associated gene signature in colon adenocarcinoma

BACKGROUND

Colon adenocarcinoma (COAD) is one of the most common and fatal malignant tumors, which increases the difficulty of prognostic predictions. Thus, new biomarkers for the diagnosis and prognosis of COAD should be explored. Ferroptosis is a recently identified programmed cell death process that has the characteristics of iron-dependent lipid peroxide accumulation. However, the predictive value of ferroptosis-related genes (FRGs) for COAD still needs to be further clarified.

AIM

To identify some critical FRGs and construct a COAD patient prognostic signature for clinical utilization.

METHODS

The Cancer Genome Atlas database (TCGA) and Gene Expression Omnibus databases were the data sources for mRNA expression and corresponding COAD patient clinical information. Differentially expressed FRGs were recognized using R and Perl software. We constructed a multi-FRG signature of the TCGA-COAD cohort by performing a univariate Cox regression and least absolute shrinkage and selection operator Cox regression analysis. COAD patients from the Gene Expression Omnibus cohort were utilized for verification.

RESULTS

Our research showed that most of the FRGs (85%) were differentially expressed between the corresponding adjacent normal tissues and cancer tissues in the TCGA-COAD cohort. Seven FRGs were related to overall survival (OS) in the univariate Cox analysis (all P < 0.05). A model with five FRGs (AKR1C1, AKR1C3, ALOX12, CRYAB, and FDFT1) was constructed to divide patients into high- and low-risk groups. The OS of patients in the high-risk group was significantly lower than that of the low-risk group (all P < 0.01 in the TCGA and Gene Expression Omnibus cohorts). The risk score was an independent prognosticator of OS in the multivariate Cox analysis (hazard ratio > 1, P < 0.01). The predictive capacity of the model was verified by a receiver operating characteristic curve analysis. In addition, a nomogram based on the expression of five hub FRGs and risk score can precisely predict the OS of individual COAD cancer patients. Immune correlation analysis and functional enrichment analysis results revealed that immunology-related pathways were abundant, and the immune states of the high-risk group and the low-risk group were different.

CONCLUSION

In conclusion, a novel five FRG model can be utilized for predicting prognosis in COAD. Targeting ferroptosis may be a treatment option for COAD.

Network analysis identifies DAPK3 as a potential biomarker for lymphatic invasion and colon adenocarcinoma prognosis

Colon adenocarcinoma is a prevalent malignancy with significant mortality. Hence, the identification of molecular biomarkers with prognostic significance is important for improved treatment and patient outcomes. Clinical traits and RNA-Seq of 551 patient samples in the UCSC Toil Recompute Compendium of The Cancer Genome Atlas TARGET and Genotype Tissue Expression project datasets (primary_site = colon) were used for weighted gene co-expression network analysis to reveal the association between gene networks and cancer cell invasion. One module, containing 151 genes, was significantly correlated with lymphatic invasion, a histopathological feature of higher risk colon cancer. DAPK3 (death-associated protein kinase 3) was identified as the pseudohub of the module. Gene ontology identified gene enrichment related to cytoskeletal organization and apoptotic signaling processes, suggesting modular involvement in tumor cell survival, migration, and epithelial-mesenchymal transformation. Although DAPK3 expression was reduced in patients with colon cancer, high expression of DAPK3 was significantly correlated with greater lymphatic invasion and poor overall survival.

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WCGNA reveals a gene module linked to lymphatic invasion in colon adenocarcinoma

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DAPK3 is a pseudohub gene with differential expression in colon cancer

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Gene ontology identified relationships to cytoskeletal organization and apoptosis

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DAPK3 was correlated with lymphatic invasion and poor overall survival

Three-Dimensional Culture Models to Study Innate Anti-Tumor Immune Response: Advantages and Disadvantages

Several approaches have shown that the immune response against tumors strongly affects patients' clinical outcome. Thus, the study of anti-tumor immunity is critical to understand and potentiate the mechanisms underlying the elimination of tumor cells. Natural killer (NK) cells are members of innate immunity and represent powerful anti-tumor effectors, able to eliminate tumor cells without a previous sensitization. Thus, the study of their involvement in anti-tumor responses is critical for clinical translation. This analysis has been performed in vitro, co-incubating NK with tumor cells and quantifying the cytotoxic activity of NK cells. In vivo confirmation has been applied to overcome the limits of in vitro testing, however, the innate immunity of mice and humans is different, leading to discrepancies. Different activating receptors on NK cells and counter-ligands on tumor cells are involved in the antitumor response, and innate immunity is strictly dependent on the specific microenvironment where it takes place. Thus, three-dimensional (3D) culture systems, where NK and tumor cells can interact in a tissue-like architecture, have been created. For example, tumor cell spheroids and primary organoids derived from several tumor types, have been used so far to analyze innate immune response, replacing animal models. Herein, we briefly introduce NK cells and analyze and discuss in detail the properties of 3D tumor culture systems and their use for the study of tumor cell interactions with NK cells.

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.