An outcome model for human bladder cancer: A comprehensive study based on weighted gene co-expression network analysis

A LASSO Cox Regression Predictive Model for Patients Undergoing Surgery for Pancreatic Body and Tail Adenocarcinoma Patients: Comparative Long-Term Survival Analysis of Radical Antegrade Modular Pancreatosplenectomy (RAMPS) and Standard Retrograde Pancreatosplenectomy (SPRS)

PURPOSE

This study was designed to assess the advantages of radical antegrade modular pancreatosplenectomy (RAMPS) over standard retrograde pancreatosplenectomy (SPRS) in terms of disease-free survival (DFS) by comparing clinical outcomes.

METHODS

Clinical data from 154 patients who underwent distal pancreatectomy at Tianjin Medical University Cancer Institute and Hospital between January 2015 and August 2018 were collected. We compared the preoperative conditions, postoperative complications, and survival outcomes of patients who underwent two different surgical procedures. By creating a LASSO-Cox model, we determined the parameters affecting DFS and the risk ratios of the two surgical procedures on DFS.

RESULTS

The R0 resection rate (85.23% vs. 68.18%, P = 0.003), negative posterior margin rate (96.59% vs. 75.76%, P < 0.001), and tumor bed recurrence rate (15.29% vs. 40.00%, P = 0.001) significantly differed between the RAMPS and SPRS groups. The 1-, 3-, and 5-year survival and DFS rates of the RAMPS group were significantly better than those of the SPRS group (P < 0.05). Disease-free survival analysis based on Kaplan-Meier curves revealed that RAMPS was superior to SPRS (P < 0.001).

CONCLUSIONS

We recommend RAMPS as the preferred procedure for treating ductal adenocarcinoma of the pancreatic body and tail due to its enhanced lymph node repair capacity and visualization of posterior pancreatic sections, which can increase DFS in patients.

FOXP3 inhibits proliferation and migration by competitively inhibiting YAP1 in nasopharyngeal carcinoma

Hippo signalling is involved in the coordination of extracellular signals that control tissue homeostasis and organ size. Yes-associated protein 1 (YAP1) is regulated primarily by Hippo signalling through coactivation of transcription factors with GATA domains called TEADs. However, small-molecule orthosteric inhibitors of YAP1 are difficult to develop due to its tight binding to TEAD4 via a flat interface. Previous studies have shown that chlorpromazine (CPZ) can inhibit YAP1 expression. MTT, colony formation, wound healing, Transwell migration and Western blot assays were performed to explore how CPZ affects nasopharyngeal carcinoma (NPC) cells through FOXP3. In addition, immunofluorescence and live-cell imaging were used to detect YAP1 intracellular localization after CPZ administration. Through the HDOCK website, we predicted protein binding regions between FOXP3 and TEAD4. Western blot and co-IP experiments were used to verify the relationship between FOXP3 and YAP1. The UCSC Xena database, LinkedOmics database and KM plotter website were used to assess the prognostic value of FOXP3 in head and neck squamous cell carcinoma (HNSCC). Age, sex, pathological tumour-node-metastasis (pTMN) stage, grade, smoking status and FOXP3 expression were included in an overall survival nomogram model. Our findings revealed that FOXP3 has the ability to competitively interacts competitively with TEAD4 to inhibit YAP1 expression. By increasing FOXP3 expression, CPZ induces YAP1 nuclear export and phosphorylation, consequently suppressing NPC cell proliferation and migration. Collectively, our findings indicate that FOXP3 competitively binds TEAD4 to regulate YAP1 localization in the nucleus and cytoplasm to suppress NPC progression. Consequently, FOXP3 may be a prognostic indicator for HNSCC.

UBE2C as an Immune-Related Biomarker for Breast Cancer: A Study Based on Multiple Databases

OBJECTIVES

To screen the target genes that are associated with survival of breast cancer (BRCA) and explore their prognostic values and immune correlations with BRCA using multiple databases..

METHODS

The microarray expression datasets of BRCA were downloaded from the Gene Expresssion Omnibus database (GEO) and analyzed to obtain differentially expressed genes (DEGs). Hub genes were obtained by constructing and visualizing the protein-protein interaction network of DEGs. The key gene was determined using R language, STRING, and Cytoscape, and the differential expression of the key gene was verified using external datasets The Cancer Genome Atlas (TCGA) and quantitative real-time PCR (qRT-PCR) for BRCA tissues of 37 patients. The prognostic value and immunological correlation of UBE2C in BRCA were explored using R language, TIMER, and Gene Set Enrichment Analysis (GSEA).

RESULTS

Of 10 hub genes seleceed from 302 DEGS, UBE2C was identified as the gene associated with BRCA survival. The expression of UBE2C was differentially upregulated in BRCA, as verified by TCGA and qRT-PCR. Prognostic analysis revealed that UBE2C served as an independent prognostic factor. High expression of UBE2C was associated with decreased immune infiltration levels of B cells, CD4+ T cells, CD8+ T cells, macrophages, and myeloid dendritic cells in BRCA tissue. The expression of UBE2C in BRCA showed a significant correlation with immune checkpoints genes PDCD1, CD274, and CTLA4 expressions. There was a positive correlation between the expression of UBE2C and the tumor mutational burden and microsatellite instability. GSEA demonstrated that UBE2C expression significantly enriched 786 immune-related gene sets.

CONCLUSIONS

UBE2C expression in BRCA tissues is closely related to the BRCA immune microenvironment and showes predictive values on the survivals and prognosis of BRCA patients and the effecacy of immunotherapy. UBE2C may be an potential immune-related prognostic biomarker for BRCA.

ALYREF m5C RNA methylation reader predicts bladder cancer prognosis by regulating the tumor immune microenvironment

BACKGROUND

5-Methylcytidine (m5C) methylation is a recently emerging epigenetic modification that is closely related to tumor proliferation, occurrence, and metastasis. This study aimed to investigate the clinicopathological characteristics and prognostic value of m5C regulators in bladder cancer (BLCA), and their correlation with the tumor immune microenvironment.

METHODS

Thirteen m5C RNA methylation regulators were analyzed using RNA-sequencing and corresponding clinical information obtained from the TCGA database. The Cluster Profiler package was used to analyze the gene ontology function of potential targets and enriched the Kyoto Encyclopedia of Genes and Genomes pathway. Kaplan-Meier survival analysis was used to compare survival differences using the log-rank test and univariate Cox proportional hazards regression. The correlation between signature prognostic m5C regulators and various immune cells was analyzed. Univariate and multivariate Cox regression analyses identified independence of the ALYREF gene signature.

RESULTS

Nine out of the 13 m5C RNA methylation regulators were differentially expressed in BLCA and normal samples and were co-expressed. These 9 regulators were associated with clinicopathological tumor characteristics, particularly high or low tumor risk, pT or pTNM stage, and migration. Consensus clustering analysis divides the BLCA samples into 4 clusters. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment annotation and gene ontology function analysis identified 273 upregulated and 594 downregulated genes in BLCA. Notably, only ALYREF was significantly correlated with OS (P < .05). ALYREF exhibited significant infiltration levels in macrophage cells. Therefore, we constructed a nomogram for ALYREF as an independent prognostic factor. Additionally, we observed that both the mRNA and protein levels of ALYREF were upregulated, and immunofluorescence showed that ALYREF was mainly distributed in nuclear speckles. ALYREF overexpression was significantly associated with poor OS.

CONCLUSION

Our findings demonstrated the potential of ALYREF to predict clinical prognostic risks in BLCA patients and regulate the tumor immune microenvironment. As such, ALYREF may serve as a novel prognostic indicator in BLCA patients.

Prognostic role of long non-coding RNA USP30-AS1 in ovarian cancer: insights into immune cell infiltration in the tumor microenvironment

Ovarian cancer represents a formidable gynecologic malignancy bearing a dismal prognosis owing to the dearth of reliable early detection approaches and a high recurrence rate. Long non-coding RNAs (lncRNAs) have garnered immense attention as key orchestrators involved in diverse biological processes and take part in cancer initiation and progression. The present study investigated the potential significance of lncRNA USP30-AS1 in ovarian cancer prognosis, as well as its putative association with immune cell infiltration in tumor immune microenvironment (TIME). By analyzing publicly available datasets, we identified six lncRNAs with prognostic prediction ability, including USP30-AS1. The results revealed a significant positive correlation of USP30-AS1 expression with the infiltration of immune cells such as Th1 cells, TFH, CD8 T cells, B cells, antigen-presenting dendritic cells (aDC), and plasmacytoid dendritic cells (pDC) in ovarian cancer specimens. These findings provide compelling evidence of the potential involvement of lncRNA in the regulation of the TME in ovarian carcinoma. The outcomes from this study underscore the potential of USP30-AS1 as a promising prognostic biomarker for ovarian cancer. Additionally, the findings offer significant insights into the plausible role of lncRNAs in modulating immune activities, thus adding to our understanding of the disease biology. Additional investigations are necessary to unravel the molecular mechanisms underpinning these connections and validate the results seen in independent cohorts and experimental models.

Prognostic related gene index for predicting survival and immunotherapeutic effect of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common malignant liver tumor. It is an aggressive disease with high mortality rate. In this study, we investigated a new prognosis-related gene index (PRGI) that can predict the survival and efficacy of immunotherapy in patients with HCC. RNA-seq data and clinical data of HCC samples were obtained from the cancer genome atlas and ICGC databases. Prognosis-related genes were obtained using log-rank tests and univariate Cox proportional hazards regression. Univariate and multivariate analyses were performed on the overall survival rate of patients with prognosis-related genes and multiple clinicopathological factors, and a nomogram was constructed. A PRGI was then constructed based on least absolute shrinkage and selection operator or multivariate Cox Iterative Regression. The possible correlation between PRGI and immune cell infiltration or immunotherapy efficacy was discussed. Eight genes were identified to construct the PRGI. PRGI can predict the infiltration of immune cells into the tumor microenvironment of HCC and the response to immunotherapy. PRGI can accurately predict the survival rate of patients with HCC, reflect the immune microenvironment, and predict the efficacy of immunotherapy.

PHF5A is a potential diagnostic, prognostic, and immunological biomarker in pan-cancer

Studying the molecular mechanisms and regulatory functions of genes is crucial for exploring new approaches and tactics in cancer therapy. Studies have shown that the aberrant expression of PHF5A in tumors is linked to the origin and advancement of multiple cancers. However, its role in diagnosis, prognosis, and immunological prediction has not been comprehensively investigated in a pan-cancer analysis. Using several bioinformatic tools, we conducted a systematic examination of the potential carcinogenesis of PHF5A in various tumors from multiple aspects. Our analysis indicated that PHF5A expression varied between normal and tumor tissues and was linked to clinical diagnosis and prognosis in various cancers. The results confirmed a notable variation in the levels of PHF5A promoter methylation among several types of primary tumor and normal tissues and methylation of the PHF5A promoter played a guiding role in prognosis in some cancers. According to our findings, PHF5A played a critical role in tumor immunity and it might be an excellent target for anticancer immunotherapy. To sum up, PHF5A can be used in pan-cancer diagnostics, prognostics, and immunotherapy.

Matrix metalloproteinase 1 is a poor prognostic biomarker for patients with hepatocellular carcinoma

Hepatocellular carcinoma (HCC) remains an incurable malignancy despite the treatment methods being continually updated. Matrix metalloproteinases (MMPs) promote the progression of HCC; however, no consensus exists on which MMP plays the predominant role in HCCs. In the present study, we analyzed differentially expressed genes in HCCs, especially MMPs, compared with adjacent tissues using the Cancer Genome Atlas database. The KEGG enrichment pathway using differentially expressed genes included extracellular matrix-receptor interaction, which was correlated with MMPs. We found that among the MMP family, only MMP1, MMP3, MMP8, MMP9, MMP11, MMP12, MMP14, MMP15, MMP20, MMP21, and MMP24 significantly increased in HCCs compared with adjacent tissues. Crucially, survival and univariate analyses indicated that only MMPs 1, 9, 12, and 14 predict poor overall survival; however, multivariate Cox analysis and a nomogram demonstrated that only MMP1 is a poor prognostic biomarker for HCCs. In addition, we observed significant enrichment of uncharacterized cells but decreased macrophages in HCC tissues. Consistent with decreased macrophages in HCCs, MMP1 was negatively associated with macrophages but positively correlated with uncharacterized cells, indicating that the main producer of MMP1 is uncharacterized cells. Furthermore, MMP1 expression was negatively correlated with immune responses of HCCs. Taken together, our findings indicated that MMP1 is a poor and predominant prognostic biomarker for patients with HCC and that anti-MMP1 may be a novel therapy that is worth studying in depth.

Role of the membrane-spanning 4A gene family in lung adenocarcinoma

Lung adenocarcinoma, which is the second most prevalent cancer in the world, has a poor prognosis and a low 5-year survival rate. The MS4A protein family is crucial to disease development and progression, particularly for cancers, allergies, metabolic disorders, autoimmune diseases, infections, and neurodegenerative disorders. However, its involvement in lung adenocarcinoma remains unclear. In this study, we found that 11 MS4A family genes were upregulated or downregulated in lung adenocarcinoma. Furthermore, we described the genetic variation landscape of the MS4A family in lung adenocarcinoma. Notably, through functional enrichment analysis, we discovered that the MS4A family is involved in the immune response regulatory signaling pathway and the immune response regulatory cell surface receptor signaling pathway. According to the Kaplan-Meier curve, patients with lung adenocarcinoma having poor expression of MS4A2, MS4A7, MS4A14, and MS4A15 had a low overall survival rate. These four prognostic genes are substantially associated with immune-infiltrating cells, and a prognosis model incorporating them may more accurately predict the overall survival rate of patients with lung adenocarcinoma than current models. The findings of this study may offer creative suggestions and recommendations for the identification and management of lung adenocarcinoma.

SLC2As as diagnostic markers and therapeutic targets in LUAD patients through bioinformatic analysis

Facilitative glucose transporters (GLUTs), which are encoded by solute carrier 2A (SLC2A) genes, are responsible for mediating glucose absorption. In order to meet their higher energy demands, cancer cells are more likely than normal tissue cells to have elevated glucose transporters. Multiple pathogenic processes, such as cancer and immunological disorders, have been linked to GLUTs. Few studies, meanwhile, have been conducted on individuals with lung adenocarcinoma (LUAD) to evaluate all 14 SLC2A genes. We first identified increased protein levels of SLC2A1, SLC2A5, SLC2A6, and SLC2A9 via HPA database and downregulated mRNA levels of SLC2A3, SLC2A6, SLC2A9, and SLC2A14 by ONCOMINE and UALCAN databases in patients with LUAD. Additionally, lower levels of SLC2A3, SLC2A6, SLC2A9, SLC2A12, and SLC2A14 and higher levels of SLC2A1, SLC2A5, SLC2A10, and SLC2A11 had an association with advanced tumor stage. SLC2A1, SLC2A7, and SLC2A11 were identified as prognostic signatures for LUAD. Kaplan-Meier analysis, Univariate Cox regression, multivariate Cox regression and ROC analyses further revealed that these three genes signature was a novel and important prognostic factor. Mechanistically, the aberrant expression of these molecules was caused, in part, by the hypomethylation of SLC2A3, SLC2A10, and SLC2A14 and by the hypermethylation of SLC2A1, SLC2A2, SLC2A5, SLC2A6, SLC2A7, and SLC2A11. Additionally, SLC2A3, SLC2A5, SLC2A6, SLC2A9, and SLC2A14 contributed to LUAD by positively modulating M2 macrophage and T cell exhaustion. Finally, pathways involving SLC2A1/BUB1B/mitotic cell cycle, SLC2A5/CD86/negative regulation of immune system process, SLC2A6/PLEK/lymphocyte activation, SLC2A9/CD4/regulation of cytokine production might participate in the pathogenesis of LUAD. In summary, our results will provide the theoretical basis on SLC2As as diagnostic markers and therapeutic targets in LUAD.

Overexpression of LIMA1 Indicates Poor Prognosis and Promotes Epithelial-Mesenchymal Transition in Head and Neck Squamous Cell Carcinoma

Background:

LIMA1 encodes LIM domain and actin binding 1, a cytoskeleton-associated protein whose loss has been linked to migration and invasion behavior of cancer cells. However, the roles of LIMA1 underlying the malignant behavior of tumors in head and neck squamous cell carcinoma (HNSC) are not fully understood.

Methods:

We conducted a multi-omics study on the role of LIMA1 in HNSC based on The Cancer Genome Atlas data. Subsequent in vitro experiments were performed to validate the results of bioinformatic analysis. We first identified the correlation between LIMA1 and tumor cell functional states according to single-cell sequencing data in HNSC. The potential downstream effects of LIMA1 were explored for gene ontology and Kyoto Encyclopedia of Genes and Genomes pathways through functional enrichment analysis of the gene sets that correlated with LIMA1 in HNSC. The prognostic role of LIMA1 was assessed using the log rank test to compare difference in survival between LIMA1^High and LIMA1^Low patients. Univariate Cox regression and multivariate Cox regression were further carried out to identify the prognostic value of LIMA1 in HNSC.

Results:

LIMA1 was identified as a prognostic biomarker and is associated with epithelial-mesenchymal transition (EMT) progress in HNSC. In vitro silencing of LIMA1 suppressed EMT and related pathways in HNSC.

Conclusions:

LIMA1 promotes EMT and further leads to tumor invasion and metastasis. Increased expression of LIMA1 indicates poor survival, identifying it as a prognostic biomarker in HNSC.

Systematic Analysis of the Expression Profile and Prognostic Significance of the IGF2BP Family in Lung Adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD)，the most common type of lung cancer associated with poor prognosis, has become a major health problem for human health. IGF2BPs are types of N6-methyladenosine reader proteins, comprising IGF2BP1, IGF2BP2, and IGF2BP3, that promote LUAD progression. However, the expression profiles and prognostic value of IGF2BPs in LUAD remain unclear.

OBJECTIVE

To analyze the expression profiles and prognostic significance of the IGF2BP family in lung adenocarcinoma.

METHODS

In our study, we utilized LUAD patient and normal or para-carcinoma tissue data from TCGA database and the GTEx project. Using survival analysis, Kaplan-Meier curves, and Cox proportional hazards model, we analyzed the expression profiles and prognostic significance of the IGF2BP family.

RESULTS

Patients with high expression levels of IGF2BPs showed significant association with poor overall survival (p < 0.05). Moreover, the somatic mutation rates of IGF2BP1, IGF2BP2, IGF2BP3 were determined as 2.65, 1.59, and 1.76%, respectively, by investigating the genetic mutation. In addition, there were significant associations between TMB and IGF2BP family expression profiles, which positively correlated with the expression of PD-1 (p < 0.05). Cox proportional hazard model for LUAD showed the risk score for IGF2BP1, p-TNM stage, and so forth, all independent prognostic indicators for LUAD patients. Finally, the co-expression genes were obtained to build a PPI network and analyze the hub genes of the IGF2BP family.

CONCLUSION

Our study provides further insights into the role of the IGF2BP family in LUAD and identifies 10 genes that may be associated with IGF2BPs in LUAD patients.

CENPF/CDK1 signaling pathway enhances the progression of adrenocortical carcinoma by regulating the G2/M-phase cell cycle

Background

Adrenocortical carcinoma (ACC) is an aggressive and rare malignant tumor and is prone to local invasion and metastasis. And, overexpressed Centromere Protein F (CENPF) is closely related to the oncogenesis of various neoplasms, including ACC. However, the prognosis and exact biological function of CENPF in ACC remains largely unclear.

Methods

In the present essay, the expression patterns and prognostic value of CENPF in ACC were investigated in clinical specimens and public cancer databases, including GEO and TCGA. The potential signaling mechanism of CENPF in ACC was studied based on gene-set enrichment analysis (GSEA). Furthermore, a small RNA interference experiment was conducted to probe the underlying biological function of CENPF in the human ACC cell line, SW13 cells. Lastly, two available therapeutic strategies, including immunotherapy and chemotherapy, have been further explored.

Results

The expression of CENPF in human ACC samples, GEO, and TCGA databases depicted that CENPF was overtly hyper-expressed in ACC patients and positively correlated with tumor stage. The aberrant expression of CENPF was significantly correlated with unfavorable overall survival (OS) in ACC patients. Then, the GSEA analysis declared that CENPF was mainly involved in the G2/M-phase mediated cell cycle and p53 signaling pathway. Further, the in vitro experiment demonstrated that the interaction between CENPF and CDK1 augmented the G2/M-phase transition of mitosis, cell proliferation and might induce p53 mediated anti-tumor effect in human ACC cell line, SW13 cells. Lastly, immune infiltration analysis highlighted that ACC patients with high CENPF expression harbored significantly different immune cell populations, and high TMB/MSI score. The gene-drug interaction network stated that CENPF inhibitors, such as Cisplatin, Sunitinib, and Etoposide, might serve as potential drugs for the therapy of ACC.

Conclusion

The result points out that CENPF is significantly overexpressed in ACC patients. The overexpressed CENPF predicts a poor prognosis of ACC and might augment the progress of ACC. Thus, CENPF and related genes might serve as a novel prognostic biomarker or latent therapeutic target for ACC patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03277-y.

CDK3, CDK5 and CDK8 Proteins as Prognostic and Potential Biomarkers in Colorectal Cancer Patients

Introduction

Methods

Results

Conclusion

EMS1/DLL4-Notch Signaling Axis Augments Cell Cycle-Mediated Tumorigenesis and Progress in Human Adrenocortical Carcinoma

Adrenocortical carcinoma (ACC) is a rare malignant neoplasm that is prone to local invasion and metastasis. Meanwhile, overexpressed endothelial cell-specific molecule 1 (ESM1) is closely related to tumorigenesis of multitudinous tumors. However, the prognosis value and biological function of ESM1 in ACC remains undefined. In the current essay, the assessment in human ACC samples and multiple public cancer databases suggested that ESM1 was significantly overexpressed in ACC patients. The abnormal expression of ESM1 was evidently correlated with dismal overall survival (OS) in ACC patients. Then, the gene-set enrichment analysis (GSEA) was applied to unravel that ESM1 was mostly involved in cell cycle and Notch4 signaling pathway. Furthermore, in vitro experiment, RNA interference of ESM1 was carried out to state that ESM1 augments CDK1 and p21-mediated G2/M-phase transition of mitosis, cell proliferation via DLL4-Notch signaling pathway in human ACC cell line, SW13 cells. Additionally, two possible or available therapeutic strategies, including immunotherapy and chemotherapy, have been further explored. Immune infiltration analysis highlighted that no significant difference was found in ACC patients between EMS1^high and EMS1^low group for immune checkpoint-related genes. In addition, the overexpression of ESM1 might trigger the accumulation of tumor mutation burden (TMB) during the cell cycle of DNA replication in ACC. The gene-drug interaction network then indicated that ESM1 inhibitors, such as cisplatin, might serve as potential drugs for the therapy of ACC. Collectively, the results asserted that ESM1 and related regulators might act as underlying prognostic biomarkers or novel therapeutic targets for ACC.

Identification and validation of a novel redox-related lncRNA prognostic signature in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is one of the main causes of cancer deaths globally. Redox is emerging as a crucial contributor to the pathophysiology of LUAD, which can be regulated by long non-coding RNAs (lncRNAs). The aim of our research is to identify a novel redox-related lncRNA prognostic signature (redox-LPS) for better prediction of LUAD prognosis. 535 LUAD samples from The Cancer Genome Atlas (TCGA) database and 226 LUAD samples from the Gene Expression Omnibus (GEO) database were included in our study. 67 redox genes and 313 redox-related lncRNAs were identified. After performing LASSO-Cox regression analysis, a redox-LPS consisting of four lncRNAs (i.e., CRNDE, CASC15, LINC01137, and CYP1B1-AS1) was developed and validated. Our redox-LPS was superior to another three established models in predicting survival probability of LUAD patients. Univariate and multivariate Cox regression analysis revealed that risk score and stage were independent prognostic indicators. A nomogram plot including risk score and stage was constructed to predict survival probability of LUAD patients; this was further verified by calibration curves. Functional enrichment analysis and gene set enrichment analysis, were performed to determine the differences in cellular processes and signaling pathways between the high – and low-risk subgroups. A variety of algorithms (such as single-sample gene set enrichment analysis and CIBERSOFT) were conducted to uncover the landscape of tumor immune microenvironment in the high- and low-risk subgroups. In conclusion, a novel independent redox-LPS was constructed and validated for LUAD patients, which might provide new insights for clinical decision-making and precision medicine.

Identification of Lymph Node Metastasis-Related Key Genes and Prognostic Risk Model in Bladder Cancer by Co-Expression Analysis

Background: Lymph node metastasis (LNM) is an important pathological characteristic of bladder cancer (BCa). However, the molecular mechanism underlying LNM was not thoroughly elaborated. Identification for LNM-related biomarkers may contribute to making suitable therapies. So, the current study was aimed to identify key genes and construct a prognostic signature. Methods: Based on the Cancer Genome Atlas (TCGA) database, gene expression and clinical information were obtained. Then, the weighted gene co-expression network analysis (WGCNA) was performed to identify the key modules and hub genes. A function analysis and a gene set enrichment analysis were applied to explore biological functions and pathways of interested genes. Furthermore, a prognostic model based on LNM-related genes was constructed by using the least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Results: Finally, nine co-expression modules were constructed, and two modules (turquoise and green) were significantly associated with LNM. Three hub genes were identified as DACT3, TNS1, and MSRB3, which were annotated in actin binding, actin cytoskeleton, adaptive immune response, and cell adhesion molecular binding by the GSEA method. Further analysis demonstrated that three hub genes were associated with the overall survival of BCa patients. In addition, we built a prognostic signature based on the genes from LNM-related modules and evaluated the prognostic value of this signature. Conclusion: In general, this study revealed the key genes related to LNM and prognostic signature, which might provide new insights into therapeutic target of BCa.

Development and validation of a novel N6-methyladenosine (m6A)-related multi- long non-coding RNA (lncRNA) prognostic signature in pancreatic adenocarcinoma

Accumulating evidence has unveiled the pivotal roles of N6-methyladenosine (m6A) in pancreatic adenocarcinoma (PAAD). However, there are not many researches to predict the prognosis of PAAD using m6A-related long non-coding RNAs (lncRNAs). Raw data from The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), and the Genotype-Tissue Expression project (GTEx) were utilized to comprehensively analyze the expression and prognostic performances of 145 m6A-related lncRNAs in PAAD and to develop and validate a novel m6A-related multi-lncRNA prognostic signature (m6A-LPS) for PAAD patients. In total, 57 differentially expressed m6A-related lncRNAs with prognostic values were identified. Based on LASSO-Cox regression analysis, m6A-LPS was constructed and verified by using five-lncRNA expression profiles for TCGA and ICGC cohorts. PAAD patients were then divided into high- and low-risKBIE_A_1933868k subgroups with different clinical outcomes according to the median risk score; this was further verified by time-dependent receiver operating characteristic curves. Risk scores were significantly associated with clinical parameters such as histological grade and cancer status among PAAD patients. A nomogram consisting of risk score, grade, and cancer status was generated to predict the survival probability of PAAD patients, as also demonstrated by calibration curves. Discrepancies in cellular processes, signaling pathways, and immune status between the high- and low-risk subgroups were investigated by functional and single-sample gene set enrichment analyses. In conclusion, the novel m6A-LPS for PAAD patients was developed and validated, which might provide new insight into clinical decision-making and precision medicine.

A Ferroptosis-Related Gene Signature Identified as a Novel Prognostic Biomarker for Colon Cancer

Background

Colon cancer (CC) is a common gastrointestinal malignant tumor with high heterogeneity in clinical behavior and response to treatment, making individualized survival prediction challenging. Ferroptosis is a newly discovered iron-dependent cell death that plays a critical role in cancer biology. Therefore, identifying a prognostic biomarker with ferroptosis-related genes provides a new strategy to guide precise clinical decision-making in CC patients.

Methods

Alteration in the expression profile of ferroptosis-related genes was initially screened in GSE39582 dataset involving 585 CC patients. Univariate Cox regression analysis and LASSO-penalized Cox regression analysis were combined to further identify a novel ferroptosis-related gene signature for overall survival prediction. The prognostic performance of the signature was validated in the GSE17536 dataset by Kaplan-Meier survival curve and time-dependent ROC curve analyses. Functional annotation of the signature was explored by integrating GO and KEGG enrichment analysis, GSEA analysis and ssGSEA analysis. Furthermore, an outcome risk nomogram was constructed considering both the gene signature and the clinicopathological features.

Results

The prognostic signature biomarker composed of 9 ferroptosis-related genes accurately discriminated high-risk and low-risk patients with CC in both the training and validation datasets. The signature was tightly linked to clinicopathological features and possessed powerful predictive ability for distinct clinical subgroups. Furthermore, the risk score was confirmed to be an independent prognostic factor for CC patients by multivariate Cox regression analysis (p < 0.05). Functional annotation analyses showed that the prognostic signature was closely correlated with pivotal cancer hallmarks, particularly cell cycle, transcriptional regulation, and immune-related functions. Moreover, a nomogram with the signature was also built to quantify outcome risk for each patient.

Conclusion

The novel ferroptosis-related gene signature biomarker can be utilized for predicting individualized prognosis, optimizing survival risk assessment and facilitating personalized management of CC patients.

VHL regulates the sensitivity of clear cell renal cell carcinoma to SIRT4-mediated metabolic stress via HIF-1α/HO-1 pathway

Clear cell renal cell carcinomas (ccRCC) reprogram carbon metabolism responses to hypoxia, thereby promoting utilization of glutamine. Recently, sirtuin 4 (SIRT4), a novel molecular has turned out to be related to alternating glutamine metabolism and modulating the tumor microenvironment. However, the role of SIRT4 in ccRCC remains poorly understood. Here, we illustrated that the expression of SIRT4 is markedly reduced in cancerous tissues, and closely associated with malignancy stage, grade, and prognosis. In ccRCC cells, SIRT4 exerted its proapoptotic activity through enhancing intracellular reactive oxygen species (ROS). Heme oxygenase-1 (HO-1) is part of an endogenous defense system against oxidative stress. Nevertheless, overexpression of SIRT4 hindered the upregulation of HO-1 in von Hippel-Lindau (VHL)-proficient cells and repressed its expression in VHL-deficient cells. This discrepancy indicated that competent VHL withstands the inhibitory role of SIRT4 on HIF-1α/HO-1. Functionally, overexpression of HO-1 counteracted the promotional effects of SIRT4 on ROS accumulation and apoptosis. Mechanistically, SIRT4 modulates ROS and HO-1 expression via accommodating p38-MAPK phosphorylation. By contrast, downregulation of p38-MAPK by SB203580 decreased intracellular ROS level and enhanced the expression of HO-1. Collectively, this work revealed a potential role for SIRT4 in the stimulation of ROS and the modulation of apoptosis. SIRT4/HO-1 may act as a potential therapeutic target, especially in VHL-deficient ccRCCs.

The Value of Immune-Related Genes Signature in Osteosarcoma Based on Weighted Gene Co-expression Network Analysis

Background. Osteosarcoma (OS) is a serious malignant tumor that is more common in adolescents or children under 20 years of age. This study is aimed at obtaining immune-related genes (IRGs) associated with the progression and prognosis of OS. Method. Expression profiling data and clinical data for OS were downloaded from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database. ESTIMATE calculates immune scores and stromal scores of samples and performs the prognostic analysis. Weighted gene coexpression network analysis (WGCNA) was used to find modules correlated with immune and stromal scores. Cox regression analysis and least absolute shrinkage and selection operator (LASSO) analysis were used to explore IRGs associated with OS prognosis and construct and validate a hazard score model. Finally, we verified the expression and function of EVI2B in OS. Results. WGCNA selected twenty-eight IRGs, 10 of which were associated with OS prognosis, and LASSO further obtained three key prognostic genes. A prognostic model of EVI2B was constructed, and according to the risk score model, patients in the high-risk group had a worse prognosis than those in the low-risk group, and the prognosis was statistically significant in the high- and low-risk groups. Receiver operating characteristic (ROC) curves were used to assess the prognostic model’s accuracy and externally validate the independent GSE21257 cohort. The results of immunohistochemical staining and qPCR showed that EVI2B was a tumor suppressor gene. The differential genes in the high- and low-risk groups were analyzed by enrichment analysis of GO and KEGG, indicating that the EVI2B model is associated with immune response. Conclusion. In this study, IRG EVI2B is closely related to OS’s prognosis and can be used as a potential biomarker for prognosis and treatment of OS.

Comprehensive analysis of immune-related prognostic genes in the tumour microenvironment of hepatocellular carcinoma

BACKGROUND

The mortality rate of hepatocellular carcinoma (HCC) remains high worldwide despite surgery and chemotherapy. Immunotherapy is a promising treatment for the rapidly expanding HCC spectrum. Therefore, it is necessary to further explore the immune-related characteristics of the tumour microenvironment (TME), which plays a vital role in tumour initiation and progression.

METHODS

In this research, 866 immune-related differentially expressed genes (DEGs) were identified by integrating the DEGs of samples from The Cancer Genome Atlas (TCGA)-HCC dataset and the immune-related genes from databases (InnateDB; ImmPort). Afterwards, 144 candidate prognostic genes were defined through weighted gene co-expression network analysis (WGCNA).

RESULTS

Seven immune-related prognostic DEGs were identified using the L1-penalized least absolute shrinkage and selection operator (LASSO) Cox proportional hazards (PH) model, and the ImmuneRiskScore model was constructed on this basis. The prognostic index of the ImmuneRiskScore model was then validated in the relevant dataset. Patients were divided into high- and low-risk groups according to the ImmuneRiskScore. Differences in the immune cell infiltration of patients with different ImmuneRiskScore values were clarified, and the correlation of immune cell infiltration with immunotherapy biomarkers was further explored.

CONCLUSION

The ImmuneRiskScore of HCC could be a prognostic marker and can reflect the immune characteristics of the TME. Furthermore, it provides a potential biomarker for predicting the response to immunotherapy in HCC patients.

Centromere Protein F (CENPF) Serves as a Potential Prognostic Biomarker and Target for Human Hepatocellular Carcinoma

Overexpression of Centromere Protein F (CENPF) is associated with tumorigenesis of many human malignant tumors. But the molecular mechanism and prognostic value of CENPF in patients with hepatocellular carcinoma (HCC) are still unclear. In this essay, expression of CENPF in HCC tumors were evaluated in a series of databases, including GEO, TCGA, Oncomine, GEPIA, The Human Protein Atlas and Kaplan-Meier plotter. It was apparent that mRNA and protein expression levels of CENPF were significantly increased in patients with HCC and were manifestly associated with the tumor stage of HCC. Aberrant expressions of CENPF were significantly linked with worse overall survival (OS) and progression-free survival (PFS) in HCC patients. Then, immunohistochemistry of CENPF in human HCC samples was carried out to suggest that CENPF protein was over-expressed in HCC tissues, compared with paired adjacent non-cancerous samples. And small interfering RNAs of CENPF in the human HepG2 cells were further performed to reveal that down-regulation of CENPF significantly inhibited cell proliferation, cell migration, and cell invasion, but slightly promoted cell apoptosis in human HepG2 cells. Moreover, the gene-set enrichment analysis (GSEA) was conducted to probe the biology process and molecular signaling pathway of CENPF in HCC. The GSEA analysis pointed out that CENPF was principally enriched in cell cycle and closely related to E2F1 and CDK1 in the regulation of cell cycle, especially during G2/M transition of mitosis in HCC. Additionally, immune infiltration analysis by CIBERSORTx revealed that mutilpe immune cells, including T_reg, etc., were significantly different in HCC samples with CENPF^high, compared with CENPF^low. These results collectively demonstrated that CENPF might serve as a potential prognostic biomarker and novel therapeutic target for HCC. However, further research is needed to validate our findings and promote the clinical application of CENPF in HCC.

A prognostic nomogram based on LASSO Cox regression in patients with alpha-fetoprotein-negative hepatocellular carcinoma following non-surgical therapy

Background

Alpha-fetoprotein-negative hepatocellular carcinoma (AFP-NHCC) (< 8.78 ng/mL) have special clinicopathologic characteristics and prognosis. The aim of this study was to apply a new method to establish and validate a new model for predicting the prognosis of patients with AFP-NHCC.

Methods

A total of 410 AFP-negative patients with clinical diagnosed with HCC following non-surgical therapy as a primary cohort; 148 patients with AFP-NHCC following non-surgical therapy as an independent validation cohort. In primary cohort, independent factors for overall survival (OS) by LASSO Cox regression were all contained into the nomogram1; by Forward Stepwise Cox regression were all contained into the nomogram2. Nomograms performance and discriminative power were assessed with concordance index (C-index) values, area under curve (AUC), Calibration curve and decision curve analyses (DCA). The results were validated in the validation cohort.

Results

The C-index of nomogram1was 0.708 (95%CI: 0.673–0.743), which was superior to nomogram2 (0.706) and traditional modes (0.606–0.629). The AUC of nomogram1 was 0.736 (95%CI: 0.690–0.778). In the validation cohort, the nomogram1 still gave good discrimination (C-index: 0.752, 95%CI: 0.691–0.813; AUC: 0.784, 95%CI: 0.709–0.847). The calibration curve for probability of OS showed good homogeneity between prediction by nomogram1 and actual observation. DCA demonstrated that nomogram1 was clinically useful. Moreover, patients were divided into three distinct risk groups for OS by the nomogram1: low-risk group, middle-risk group and high-risk group, respectively.

Conclusions

Novel nomogram based on LASSO Cox regression presents more accurate and useful prognostic prediction for patients with AFP-NHCC following non-surgical therapy. This model could help patients with AFP-NHCC following non-surgical therapy facilitate a personalized prognostic evaluation.

Systematic identification of key functional modules and genes in esophageal cancer

BACKGROUND

Esophageal cancer is associated with high incidence and mortality worldwide. Differential expression genes (DEGs) and weighted gene co-expression network analysis (WGCNA) are important methods to screen the core genes as bioinformatics methods.

METHODS

The DEGs and WGCNA were combined to screen the hub genes, and pathway enrichment analyses were performed on the hub module in the WGCNA. The CCNB1 was identified as the hub gene based on the intersection between DEGs and the greenyellow module in WGCNA. Expression levels and prognostic values of CCNB1 were verified in UALCAN, GEPIA2, HCMDB, Kaplan-Meier plotter, and TIMER databases.

RESULTS

We identified 1,044 DEGs from dataset GSE20347, 1,904 from GSE29001, and 2,722 from GSE111044, and 32 modules were revealed by WGCNA. The greenyellow module was identified as the hub module in the WGCNA. CCNB1 gene was identified as the hub gene, which was upregulated in tumour tissues. Moreover, esophageal cancer patients with higher expression of CCNB1 showed a worse prognosis. However, CCNB1 'might not play an important role in immune cell infiltration.

CONCLUSIONS

Based on DEGs and key modules related to esophageal cancer, CCNB1 was identified as the hub gene, which offered novel insights into the development and treatment of esophageal cancer.

WGCNA reveals key gene modules regulated by the combined treatment of colon cancer with PHY906 and CPT11

Irinotecan (CPT11) is one of the most effective drugs for treating colon cancer, but its severe side effects limit its application. Recently, a traditional Chinese herbal preparation, named PHY906, has been proved to be effective for improving therapeutic effect and reducing side effects of CPT11. The aim of the present study was to provide novel insight to understand the molecular mechanism underlying PHY906-CPT11 intervention of colon cancer. Based on the GSE25192 dataset, for different three treatments (PHY906, CPT11, and PHY906-CPT11), we screened out differentially expressed genes (DEGs) and constructed a co-expression network by weighted gene co-expression network analysis (WGCNA) to identify hub genes. The key genes of the three treatments were obtained by merging the DEGs and hub genes. For the PHY906-CPT11 treatment, a total of 18 key genes including Eif4e, Prr15, Anxa2, Ddx5, Tardbp, Skint5, Prss12 and Hnrnpa3, were identified. The results of functional enrichment analysis indicated that the key genes associated with PHY906-CPT11 treatment were mainly enriched in ‘superoxide anion generation’ and ‘complement and coagulation cascades’. Finally, we validated the key genes by Gene Expression Profiling Interactive Analysis (GEPIA) and RT-PCR analysis, the results indicated that EIF4E, PRR15, ANXA2, HNRNPA3, NCF1, C3AR1, PFDN2, RGS10, GNG11, and TMSB4X might play an important role in the treatment of colon cancer with PHY906-CPT11. In conclusion, a total of 18 key genes were identified in the present study. These genes showed strong correlation with PHY906-CPT11 treatment in colon cancer, which may help elucidate the underlying molecular mechanism of PHY906-CPT11 treatment in colon cancer.

RNA delivery by extracellular vesicles in mammalian cells and its applications

The term 'extracellular vesicles' refers to a heterogeneous population of vesicular bodies of cellular origin that derive either from the endosomal compartment (exosomes) or as a result of shedding from the plasma membrane (microvesicles, oncosomes and apoptotic bodies). Extracellular vesicles carry a variety of cargo, including RNAs, proteins, lipids and DNA, which can be taken up by other cells, both in the direct vicinity of the source cell and at distant sites in the body via biofluids, and elicit a variety of phenotypic responses. Owing to their unique biology and roles in cell-cell communication, extracellular vesicles have attracted strong interest, which is further enhanced by their potential clinical utility. Because extracellular vesicles derive their cargo from the contents of the cells that produce them, they are attractive sources of biomarkers for a variety of diseases. Furthermore, studies demonstrating phenotypic effects of specific extracellular vesicle-associated cargo on target cells have stoked interest in extracellular vesicles as therapeutic vehicles. There is particularly strong evidence that the RNA cargo of extracellular vesicles can alter recipient cell gene expression and function. During the past decade, extracellular vesicles and their RNA cargo have become better defined, but many aspects of extracellular vesicle biology remain to be elucidated. These include selective cargo loading resulting in substantial differences between the composition of extracellular vesicles and source cells; heterogeneity in extracellular vesicle size and composition; and undefined mechanisms for the uptake of extracellular vesicles into recipient cells and the fates of their cargo. Further progress in unravelling the basic mechanisms of extracellular vesicle biogenesis, transport, and cargo delivery and function is needed for successful clinical implementation. This Review focuses on the current state of knowledge pertaining to packaging, transport and function of RNAs in extracellular vesicles and outlines the progress made thus far towards their clinical applications.

An outcome model for human bladder cancer: A comprehensive study based on weighted gene co-expression network analysis

The precision evaluation of prognosis is crucial for clinical treatment decision of bladder cancer (BCa). Therefore, establishing an effective prognostic model for BCa has significant clinical implications. We performed WGCNA and DEG screening to initially identify the candidate genes. The candidate genes were applied to construct a LASSO Cox regression analysis model. The effectiveness and accuracy of the prognostic model were tested by internal/external validation and pan‐cancer validation and time‐dependent ROC. Additionally, a nomogram based on the parameter selected from univariate and multivariate cox regression analysis was constructed. Eight genes were eventually screened out as progression‐related differentially expressed candidates in BCa. LASSO Cox regression analysis identified 3 genes to build up the outcome model in E‐MTAB‐4321 and the outcome model had good performance in predicting patient progress free survival of BCa patients in discovery and test set. Subsequently, another three datasets also have a good predictive value for BCa patients' OS and DFS. Time‐dependent ROC indicated an ideal predictive accuracy of the outcome model. Meanwhile, the nomogram showed a good performance and clinical utility. In addition, the prognostic model also exhibits good performance in pan‐cancer patients. Our outcome model was the first prognosis model for human bladder cancer progression prediction via integrative bioinformatics analysis, which may aid in clinical decision‐making.