Integrated multi-omics data analyses for exploring the co-occurring and mutually exclusive gene alteration events in colorectal cancer

The multiple roles of interferon regulatory factor family in health and disease

Interferon Regulatory Factors (IRFs), a family of transcription factors, profoundly influence the immune system, impacting both physiological and pathological processes. This review explores the diverse functions of nine mammalian IRF members, each featuring conserved domains essential for interactions with other transcription factors and cofactors. These interactions allow IRFs to modulate a broad spectrum of physiological processes, encompassing host defense, immune response, and cell development. Conversely, their pivotal role in immune regulation implicates them in the pathophysiology of various diseases, such as infectious diseases, autoimmune disorders, metabolic diseases, and cancers. In this context, IRFs display a dichotomous nature, functioning as both tumor suppressors and promoters, contingent upon the specific disease milieu. Post-translational modifications of IRFs, including phosphorylation and ubiquitination, play a crucial role in modulating their function, stability, and activation. As prospective biomarkers and therapeutic targets, IRFs present promising opportunities for disease intervention. Further research is needed to elucidate the precise mechanisms governing IRF regulation, potentially pioneering innovative therapeutic strategies, particularly in cancer treatment, where the equilibrium of IRF activities is of paramount importance.

Downstream Target Analysis for miR-365 among Oral Squamous Cell Carcinomas Reveals Differential Associations with Chemoresistance

Expression of microRNAs, such as miR-365, is known to be dysregulated in many tumors, including oral cancers, although little is known about their role or functions. The objective of this project is to evaluate the downstream targets of miR-365 to determine any potential pathways or effects. Downstream targets for miR-365 (miRdatabase target scores > 90) were used for qPCR screening of oral cancer cell lines (SCC4, SCC9, SCC15, SCC25, CAL27). Each oral cancer cell line expressed miR-365 downstream targets molybdenum cofactor synthesis-2 (MOCS2), erythropoietin receptor (EPOR), IQ motif containing-K (IQCK), carboxypeptidase A3 (CPA3), solute carrier family 24 member-3 (SLC24A3), and coiled-coil domain containing 47 (CCDC47)-although the expression levels varied somewhat. However, differential results were observed with ubiquitin protein ligase E3 component n-recognin-3 (UBR3), nudix hydrolase-12 (NUDT12), zinc finger CCHC-type containing-14 (ZCCHC14), and homeobox and leucine zipper encoding (HOMEZ). These data suggest that many of the miR-365 targets are expressed in the oral cancers screened, with the differential expression of UBR3, ZCCHC14, HOMEZ, and NUDT12, which may be correlated with chemoresistance among two specific oral cancer cell lines (SCC25, SCC9). These results suggest this differential expression may signal potential targets for patient treatment with tumors exhibiting miR-365 and chemotherapeutic resistance.

Mutational profile evaluates metastatic capacity of Chinese colorectal cancer patients, revealed by whole-exome sequencing

Colorectal cancer (CRC) is the third most common cancer and the prevalence rate of CRC is increasing in the China. In this study, whole-exome sequencing (WES) was performed on primary tissues of 47 CRC Chinese patients including 22 metastatic and 25 non-metastatic patients. By comparison with data from western colorectal cancer patients in the Cancer Genome Atlas (TCGA), we identified a number of genes that are more likely to be mutated in Chinese colorectal cancer patients, such as MUC12, MUC12, MUC2, MUC4, HYDIN and KMT2C. Interestingly, MUC family genes including MUC12, MUC2 and MUC4, have mutation rates of >20%, while the mutation frequency was extremely low in western colorectal cancer patients, which were <3% in TCGA and 0% in Memorial Sloan Kettering Cancer Center (MSKCC). We detected metastasis-specific mutated genes including TCF7L2, MST1L, HRNR and SMAD4, while MUC4, NEB, FLG and RFPL4A alteration is more prevalent in the non-metastasis group. Further analysis reveals mutation genes in metastasis group are more focus in the Wnt and Hippo signaling pathway. APC, SMAD4 and TCF7L2 accounted for the major genetic abnormalities in this pathway. In conclusion, this study identified the unique characteristics of gene mutations in Chinese patients with colorectal cancer, and is a valuable reference for personalized treatment in Chinese CRC patients.

Unraveling the immune landscape and therapeutic biomarker PMEPA1 for oxaliplatin resistance in colorectal cancer: A comprehensive approach

Oxaliplatin (OXA) is a platinum-based chemotherapeutic agent with promising applications in the treatment of various malignancies, particularly colorectal cancer (CRC). However, the management of OXA resistance remains an ongoing obstacle in CRC therapy. This study aims to comprehensively investigate the immune landscape, targeted therapeutic biomarkers, and mechanisms that influence OXA resistance in CRC. Our results demonstrated that our OXA- resistant CRC prognostic model not only provides risk assessment for patients but also reflects the immune landscape of patients. Additionally, we identified prostate transmembrane protein, androgen-induced1 (PMEPA1) as a promising molecular targeted therapeutic biomarker for patients with OXA-resistant CRC. The mechanism of PMEPA1 may involve cell adhesion, pathways in cancer, and the TGF-β signaling pathway. Furthermore, analysis of CRC clinical samples indicated that patients resistant to OXA exhibited elevated serum levels of TGF-β1, increased expression of PMEPA1 in tumors, a lower proportion of CD8+ T cell positivity, and a higher proportion of M0 macrophage positivity, in comparison to OXA-sensitive individuals. Cellular experiments indicated that selective silencing of PMEPA1, alone or in combination with OXA, inhibited proliferation and metastasis in OXA-resistant CRC cells, HCT116R. Animal experiments further confirmed that PMEPA1 silencing suppressed subcutaneous graft tumor growth and liver metastasis in mice bearing HCT116R and synergistically enhanced the efficacy of OXA. These data highlight the potential of leveraging the therapeutic biomarker PMEPA1, CD8+ T cells, and M0 macrophages as innovative targets for effectively addressing the challenges associated with OXA resistance. Our findings hold promising implications for further clinical advancements in this field.

Proteomic and metabolomic features in patients with HCC responding to lenvatinib and anti-PD1 therapy

Combination therapy (lenvatinib/programmed death-1 inhibitor) is effective for treating unresectable hepatocellular carcinoma (uHCC). We reveal that responders have better overall and progression-free survival, as well as high tumor mutation burden and special somatic variants. We analyze the proteome and metabolome of 82 plasma samples from patients with hepatocellular carcinoma (HCC; n = 51) and normal controls (n = 15), revealing that individual differences outweigh treatment differences. Responders exhibit enhanced activity in the alternative/lectin complement pathway and higher levels of lysophosphatidylcholines (LysoPCs), predicting a favorable prognosis. Non-responders are enriched for immunoglobulins, predicting worse outcomes. Compared to normal controls, HCC plasma proteins show acute inflammatory response and platelet activation, while LysoPCs decrease. Combination therapy increases LysoPCs/phosphocholines in responders. Logistic regression/random forest models using metabolomic features achieve good performance in the prediction of responders. Proteomic analysis of cancer tissues unveils molecular features that are associated with side effects in responders receiving combination therapy. In conclusion, our analysis identifies plasma features associated with uHCC responders to combination therapy.

Nesprin1 Deficiency Is Associated with Poor Prognosis of Renal Cell Carcinoma and Resistance to Sunitinib Treatment

INTRODUCTION

Nuclear envelope spectrin repeat protein (Nesprin) 1 encoded by SYNE1, crucially regulates the morphology and functions of the cell. Mutations in the SYNE1 gene are associated with various diseases; however, their significance in renal cell carcinoma (RCC) remains unknown. In this study, we have investigated the association of SYNE1/Nesprin1 with the progression and prognosis of clear cell RCC (ccRCC).

METHODS

In silico analyses of publicly available datasets of patients with RCC were performed. Based on the cohort data, Nesprin1 expression in nephrectomized tissue samples acquired from patients with ccRCC was analyzed using immunohistochemical staining. The invasion, migration, and proliferation of the SYNE1-knockdown human RCC cell lines were analyzed in vitro; moreover, RNA sequencing and gene set enrichment analysis were conducted to study the molecular mechanism underlying the association of SYNE1/Nesprin1 with prognosis of RCC.

RESULTS

Patients with RCC-associated SYNE1 gene mutations exhibited significantly worse overall and progression-free survivals. Patients with Nesprin1-negative ccRCC tumors exhibit significantly poorer overall, cancer-specific, and recurrence-free survival rates than those recorded in the Nesprin1-positive group. SYNE1 knockdown enhanced the invasion and migration of RCC cells; however, it did not influence the proliferation of cells. RNA sequencing and gene set enrichment analysis revealed that SYNE1 knockdown significantly altered the expression of genes associated with oxidative phosphorylation. Consistently, patients with RCC exhibiting low SYNE1 expression, who were treated with the vascular endothelial growth factor receptor inhibitor sunitinib, had worse progression-free survival.

CONCLUSIONS

The results indicate that the expression of SYNE1/Nesprin1 and SYNE1 mutations in patients with RCC are closely linked to their prognosis and responsiveness to sunitinib treatment.

Clinical value of FAT1 mutations to indicate the immune response in colorectal cancer patients

Immunotherapy is currently approved for CRC whose tumors have high MSI-H. To find additional biomarkers for immunotherapy in CRC, targeted sequencing was performed on tumor tissues from a discovery cohort of 161 CRC patients. Validation cohorts from the cBioPortal were also used for survival and tumor cell infiltration analyses. The FAT1-mutated CRC group often co-occurred with MSI events and displayed a higher tumor mutational burden compared to the FAT1 wild-type CRC. Overall survival was higher in patients with FAT1 mutations than in patients with wild type FAT1. The altered PI3K-AKT pathway and immune pathways were enriched in the FAT1-mutated CRC. A higher infiltration rate of immune cells including CD4+ T cells, CD8+ T cells, macrophages M1 and regulatory T cells were also observed in the colorectal tumors with FAT1 mutation compared to tumors with wild type FAT1. The results showed that CRC patients with FAT1 mutations exhibited an immunotherapy-favorable profile.

Role of interferon regulatory factor 5 (IRF5) in tumor progression: Prognostic and therapeutic potential

Canonically, the transcription factor interferon regulatory factor 5 (IRF5) is a key mediator of innate and adaptive immunity downstream of pathogen recognition receptors such as Toll-like receptors (TLRs). Hence, dysregulation of IRF5 function has been widely implicated in inflammatory and autoimmune diseases. Over the last few decades, dysregulation of IRF5 expression has been also reported in hematologic malignancies and solid cancers that support a role for IRF5 in malignant transformation, tumor immune regulation, clinical prognosis, and treatment response. This review will provide an in-depth overview of the current literature regarding the mechanisms by which IRF5 functions as either a tumor suppressor or oncogene, its role in metastasis, regulation of the tumor-immune microenvironment, utility as a prognostic indicator of disease, and new developments in IRF5 therapeutics that may be used to remodel tumor immunity.

Systematic analysis of glutamine metabolism family genes and exploration of the biological role of GPT in colorectal cancer

BACKGROUND

Colorectal cancer (CRC) is a malignancy of the digestive system with high incidence rate and mortality, and reliable diagnostic and prognostic markers for CRC are still lacking. Glutamine metabolism is crucial to the occurrence and development of CRC. However, no research has systematically analyzed the biological role of glutamine metabolism-related genes (GMRGs) in CRC.

METHODS

We downloaded gene expression data and clinical data of CRC patients from the TCGA database. The UCSC database downloads pan-cancer gene expression data and prognosis data. Characteristic GMRGs were screened out using differential analysis and two types of machine learning (SVM-REF and RandomForest). Single-cell RNA-sequencing data from CRC patients were downloaded from GEO data. ROC curve was used to evaluate the diagnostic value. Kaplan-Meier method and univariate Cox regression analysis were used to evaluate the prognostic value. The oncopredict package is used to calculate IC50 values for common drugs in CRC patients.

RESULTS

A total of 31 differentially expressed GMRGs were identified, 9 of which were identified as characteristic GMRGs. Further evaluation of diagnostic and prognostic value finally identified GPT as the most important GMRGs in CRC. scRNA-seq analysis revealed that GPT is almost exclusively expressed in epithelial cells. GPT expression is closely related to the tumor microenvironment and can effectively distinguish the sensitivity of different CRC patients to clinical drugs. In addition, pan-cancer analysis showed that GPT is an excellent diagnostic and prognostic marker for multiple cancers.

CONCLUSIONS

GPT is a reliable diagnostic, prognostic marker and therapeutic target in CRC.

Mutational landscape of cancer-driver genes across human cancers

The genetic mutations that contribute to the transformation of healthy cells into cancerous cells have been the subject of extensive research. The molecular aberrations that lead to cancer development are often characterised by gain-of-function or loss-of-function mutations in a variety of oncogenes and tumour suppressor genes. In this study, we investigate the genomic sequences of 20,331 primary tumours representing 41 distinct human cancer types to identify and catalogue the driver mutations present in 727 known cancer genes. Our findings reveal significant variations in the frequency of cancer gene mutations across different cancer types and highlight the frequent involvement of tumour suppressor genes (94%), oncogenes (93%), transcription factors (72%), kinases (64%), cell surface receptors (63%), and phosphatases (22%), in cancer. Additionally, our analysis reveals that cancer gene mutations are predominantly co-occurring rather than exclusive in all types of cancer. Notably, we discover that patients with tumours displaying different combinations of gene mutation patterns tend to exhibit variable survival outcomes. These findings provide new insights into the genetic landscape of cancer and bring us closer to a comprehensive understanding of the underlying mechanisms driving the development of various forms of cancer.

Data mining identifies novel RNA-binding proteins involved in colon and rectal carcinomas

Colorectal adenocarcinoma (COREAD) is the second most deadly cancer and third most frequently encountered malignancy worldwide. Despite efforts in molecular subtyping and subsequent personalized COREAD treatments, multidisciplinary evidence suggests separating COREAD into colon cancer (COAD) and rectal cancer (READ). This new perspective could improve diagnosis and treatment of both carcinomas. RNA-binding proteins (RBPs), as critical regulators of every hallmark of cancer, could fulfill the need to identify sensitive biomarkers for COAD and READ separately. To detect new RBPs involved in COAD and READ progression, here we used a multidata integration strategy to prioritize tumorigenic RBPs. We analyzed and integrated 1) RBPs genomic and transcriptomic alterations from 488 COAD and 155 READ patients, 2) ∼ 10,000 raw associations between RBPs and cancer genes, 3) ∼ 15,000 immunostainings, and 4) loss-of-function screens performed in 102 COREAD cell lines. Thus, we unraveled new putative roles of NOP56, RBM12, NAT10, FKBP1A, EMG1, and CSE1L in COAD and READ progression. Interestingly, FKBP1A and EMG1 have never been related with any of these carcinomas but presented tumorigenic features in other cancer types. Subsequent survival analyses highlighted the clinical relevance of FKBP1A, NOP56, and NAT10 mRNA expression to predict poor prognosis in COREAD and COAD patients. Further research should be performed to validate their clinical potential and to elucidate their molecular mechanisms underlying these malignancies.

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

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

TMC5 is Highly Expressed in Human Cancers and Corelates to Prognosis and Immune Cell Infiltration: A Comprehensive Bioinformatics Analysis

Background: The oncological role of TMC5 in human cancers has only been revealed partially. We performed integrated bioinformatics analysis to provide a thorough and detailed insight of associations between TMC5 and tumorigenesis, cancer progression, and prognosis.

Methods: With reference to the accessible online databases, the TMC5 expressions in tumor tissues and corresponding normal tissues, different pathological stages, and various cancer cells were analyzed, while the protein levels of TMC5 in different cancers were also inspected. Meanwhile, the prognostic value of TMC5 expression in multiple cancers as well as in advanced-stage patients was investigated. Furthermore, the mutational data of TMC5 and its correlation with cancer prognosis were assessed. Moreover, the association between the TMC5 level and immune cell infiltration was evaluated. Next, TMC5-related pathway alterations and drug responses were summarized. Finally, the TMC5 based protein network was generated, and relevant enrichment was performed.

Results: In our study, the expression level of TMC5 was significantly higher in the tumor tissue than that of the normal tissues in most cancer types. Fluctuations of TMC5 levels were also observed among different pathological stages. In the meantime, the protein level elevated in the tumor tissue in the cancers enrolled. Moreover, the expression of TMC5 was not only prognostic for overall survival (OS) or recurrence free survival (RFS) in various types of cancers but also correlated to OS in patients with more advanced cancers. Additionally, the mutational status of TMC5 is also associated with prognosis in cancer patients. It is worth noting that the TMC5 level was closely related to immune cell infiltrations, especially in ESCA, TGCT, and USC. The TMC5 expression was also identified as an activator for pathways including PI3K/AKT, RAS/MAPK, and TSC/mTOR, proved to be associated with multiple drug responses and assessed to be interactive with the TMEM family.

Conclusion: TMC5 might function as a potential marker for cancer survival and immune responses.

Prognosis Implication of a Novel Metabolism-Related Gene Signature in Ewing Sarcoma

Ewing sarcoma (ES) is one of the most common bone cancers in adolescents and children. Growing evidence supports the view that metabolism pathways play critical roles in numerous cancers (He et al. (2020)). However, the correlation between metabolism-associated genes (MTGs) and Ewing sarcoma has not been investigated systematically. Here, based on the univariate Cox regression analysis, we get survival genes from differentially expressed genes (DEGs) from Gene Expression Omnibus (GEO) cohort. Multivariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) regression analysis were employed to establish the MTG signature. Comprehensive survival analyses including receiver operating characteristic (ROC) curves and Kaplan-Meier analysis were applied to estimate the independent prognostic value of the signature. The ICGC cohort served as the validation cohort. A nomogram was constructed based on the risk score of the MTG signature and other independent clinical variables. The CIBERSORT algorithm was applied to estimate immune infiltration. In addition, we explored the correlation between MTG signature and immune checkpoints. Collectively, this work presents a novel MTG signature for prognostic prediction of Ewing sarcoma. It also suggests six genes that are potential prognostic indicators and therapeutic targets for ES.

Regulation of signal transduction pathways in colorectal cancer: implications for therapeutic resistance

Resistance to anti-cancer treatments is a critical and widespread health issue that has brought serious impacts on lives, the economy and public policies. Mounting research has suggested that a selected spectrum of patients with advanced colorectal cancer (CRC) tend to respond poorly to both chemotherapeutic and targeted therapeutic regimens. Drug resistance in tumours can occur in an intrinsic or acquired manner, rendering cancer cells insensitive to the treatment of anti-cancer therapies. Multiple factors have been associated with drug resistance. The most well-established factors are the emergence of cancer stem cell-like properties and overexpression of ABC transporters that mediate drug efflux. Besides, there is emerging evidence that signalling pathways that modulate cell survival and drug metabolism play major roles in the maintenance of multidrug resistance in CRC. This article reviews drug resistance in CRC as a result of alterations in the MAPK, PI3K/PKB, Wnt/β-catenin and Notch pathways.

Identification of a Genome Instability-Associated LncRNA Signature for Prognosis Prediction in Colon Cancer

Long non-coding RNAs (lncRNAs) were reported to have the potential in maintaining genome instability, but the identification of lncRNAs related to genome instability and their prognostic value have not been largely explored in colon cancer. In this study, we obtained 155 genome instability-associated lncRNAs based on somatic mutation profiles in colon cancer from The Cancer Genome Atlas (TCGA) database. Functional enrichment analysis revealed the possible roles of genes co-expressed with those lncRNAs involved in some cancer, genome instability and immune related biological processes. Combined with overall survival data, a seven-lncRNA signature was established for prognosis prediction. According to the risk score calculated by this signature, high-risk patients characterized by high somatic mutation count, high microsatellite instability, significantly poorer clinical outcomes and specific tumor immune infiltration status compared with low-risk patients. The lncRNA signature was validated to be an independent prognostic indicator with good predictive performance in TCGA cohort. Furthermore, the prognostic value of the ZNF503-AS1 in lncRNA signature was confirmed in another independent dataset from Gene Expression Omnibus database. In summary, the genome instability-associated lncRNA signature in this study could be a promising tool for effectively predicting survival outcomes in colon cancer.