Expression, Prognostic Value, and Functional Mechanism of the KDM5 Family in Pancreatic Cancer

Background: The histone lysine demethylase KDM5 family is an important epigenetic state-modifying enzyme family. Increasing evidence supports that epigenetic abnormalities in the KDM5 family are related to multiple cancers in humans. However, the role of the KDM5 family in pancreatic cancer is not clear, and related research is very scarce.

Methods: R software, Kaplan–Meier Plotter, cBioPortal, TIMER, LinkedOmics, STRING, Metascape, TISIDB, and the GSCA Lite online tool were utilized for bioinformatics analysis.

Results: KDM5A/B/C was significantly overexpressed in many kinds of tumor tissues, including pancreatic adenocarcinoma (PAAD), while the expression of KDM5D was significantly downregulated. The high expression of KDM5A/B/C was related to poor clinical features, such as worse treatment efficacy, higher tumor grade, and more advanced clinical stage. Patients with a family history of breast cancer and melanoma, history of drinking or history chronic pancreatitis were more likely to have KDM5A/B/C gene abnormalities, which were related to a variety of adverse clinical features. The results of gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) pathway analyses of the KDM5 family and its 800 co-expressed genes showed that many gene terms related to cell proliferation, migration and many carcinogenic pathways. Notably, we found that the expression level of KDM5A/B/C was positively correlated with the expression of multiple key driver genes such as KRAS, BRCA1, and BRCA2 etc. In addition, PPI network analysis showed KDM5 family proteins have strong interactions with histone deacetylase family 1 (HDAC1), which could modify the lysines of histone H3, and co-act on many pathways, including the “longevity-regulating pathway” and “Notch signaling pathway”. Moreover, the upregulation of KDM5A/B/C expression was associated with an increase in the infiltration of B cells, CD8⁺ T cells and other infiltrating immune lymphocytes and the expression levels of immune molecules such as NT5E and CD274. Interestingly, the overexpression of KDM5A/C was also corelated with reduced sensitivity of pancreatic cancer cells to many kinds of pancreatic cancer-targeting or chemotherapeutic drugs, including axitinib and gemcitabine.

Conclusion: KDM5 family members may be prognostic markers and new therapeutic targets for patients with pancreatic cancer.

Fatty Acid Synthase Is the Key Regulator of Fatty Acid Metabolism and Is Related to Immunotherapy in Bladder Cancer

Fatty acid metabolism (FAM) genes are potentially useful for predicting prognosis and immunotherapy response in bladder cancer (BC). To examine this, we constructed a prognostic model and identified key FAM genes in BC. Using transcriptional expression profiles and clinical data of BC patients from public datasets and Changhai (CH) hospital, we built and validated a risk-score model based on 13 prognostic FAM genes. Differential gene expression identified fatty acid synthase (FASN) as central to fatty acid metabolism in BC. FASN was differentially expressed between normal and tumor tissue, and was related to survival. In the CH dataset, FASN independently predicted muscle-invasive BC. FASN differential expression was significantly related to immune-cell infiltration and patients with low FASN expression responded better to immune checkpoint inhibitor (ICI) treatment. SREBF1 was predicted as the most significant transcription factor for FASN. Competing endogenous RNA network analysis suggested that lncRNA AC107027.3 may upregulate FASN by competitively binding miR-27A-3p, thereby regulating the immunotherapy response in BC. Dasatinib and temsirolimus are potential FASN-targeting drugs. Our model efficiently predicted prognosis in BC. FASN is central to fatty acid metabolism, and a potential indicator and regulator of ICI treatment.

Identify the Prognostic and Immune Profile of VSIR in the Tumor Microenvironment: A Pan-Cancer Analysis

VSIR is a critical immunomodulatory receptor that inhibits T cell effector function and maintains peripheral tolerance. However, the mechanism by which VSIR participates in tumor immunity in the pan-cancer tumor microenvironment remains unclear. This study systematically explored the prognostic and immune profile of VSIR in the tumor microenvironment of 33 cancers. We compared the expression patterns and molecular features of VSIR in the normal and cancer samples both from the public databases and tumor chips. VSIR level was significantly related to patients' prognosis and could be a promising predictor in many tumor types, such as GBM, KIRC, SKCM, READ, and PRAD. Elevated VSIR was closely correlated with infiltrated inflammatory cells, neoantigens expression, MSI, TMB, and classical immune checkpoints in the tumor microenvironment. Enrichment signaling pathways analysis indicated VSIR was involved in several immune-related pathways such as activation, proliferation, and migration of fibroblast, T cell, mast cell, macrophages, and foam cell. In addition, VSIR was found to widely express on cancer cells, fibroblasts, macrophages, and T cells in many tumor types based on the single-cell sequencing analysis and co-express with M2 macrophage markers CD68, CD163 based on the immunofluorescence staining. Finally, we predicted the sensitive drugs targeting VSIR and the immunotherapeutic value of VSIR. In sum, VSIR levels strongly correlated with the clinical outcome and tumor immunity in multiple cancer types. Therefore, therapeutic strategies targeting VSIR in the tumor microenvironment may be valuable tools for cancer immunotherapy.

Circular RNA CircITCH (has-circ-0001141) suppresses hepatocellular carcinoma (HCC) progression by sponging miR-184

Aberrant expression of circular RNA (circRNA) is involved in the occurrence of various diseases and tumor development, in which plays a vital role, including hepatocellular carcinoma (HCC). Nevertheless, the regulation mechanism and biological function of circITCH in hepatocellular carcinoma (HCC) remain unclear. The expression level of circular RNA itchy E3 ubiquitin protein ligase (circ-ITCH) was identified and validated by real-time polymerase-chain reaction (RT-qPCR) in HCC cell lines. The stability of circITCH was confirmed by Ribonuclease R (RNase R) assay. Subsequently, through silencing and overexpression of circITCH to investigate the functional roles of circITCH in HCC proliferation, invasion, and apoptosis. We also carried out bioinformatics analysis, luciferase reporter assays to define the relationship between microRNA (miR)-184 and circITCH. Moreover, xenograft mouse models and immunohistochemistry were employed to assess the function of circITCH in HCC. CircITCH (hsa_circ_0001141) was a stable circRNA and downregulated in HCC cells. Overexpression of circITCH inhibited cell proliferation, migration, invasion, and promoted apoptosis in vitro and in vivo, whereas knockdown of circITCH had the opposite effects. Mechanistically, miR-184 could be sponged by circITCH, and its overexpression could mitigate the suppressive effects of circITCH overexpression on HCC progression. Through biological website to predict the target genes of miR-184 may be combined. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed to investigate mRNAs with significant functional enrichment and pathways, also which its relationship with HCC-related pathway and immune cells. Our findings reveal that circITCH served as a repressor to restrain HCC malignancy via miR-184. Therefore, circITCH may serve as a potential prognostic marker and therapeutic target for HCC.

Abbreviations: HCC: hepatocellular carcinoma; CircRNA: Circular RNA; miRNA: MicroRNA; Circ-ITCH: circular RNA itchy E3 ubiquitin protein ligase; RT-qPCR: real-time polymerase-chain reaction; RNase R: Ribonuclease R; CeRNA: competing endogenous RNAs; SiRNA: small interfering RNA

Transcriptomics and Metabolomics Identify Drug Resistance of Dormant Cell in Colorectal Cancer

Background: Tumor dormancy is an important way to develop drug resistance. This study aimed to identify the characteristics of colorectal cancer (CRC) cell dormancy.

Methods: Based on the CRC cohorts, a total of 1,044 CRC patients were included in this study, and divided into a dormant subgroup and proliferous subgroup. Non-negative matrix factorization (NMF) was used to distinguish the dormant subgroup of CRC via transcriptome data of cancer tissues. Gene Set Enrichment Analysis (GSEA) was used to explore the characteristics of dormant CRC. The characteristics were verified in the cell model, which was used to predict key factors driving CRC dormancy. Potential treatments for CRC dormancy were also examined.

Results: The dormant subgroup had a poor prognosis and was more likely to relapse. GSEA analysis showed two defining characteristics of the dormant subgroup, a difference in energy metabolism and synergistic effects of cancer-associated fibroblasts (CAFs), which were verified in a dormant cell model. Transcriptome and clinical data identified LMOD1, MAB21L2, and ASPN as important factors associated with cell dormancy and verified that erlotinib, and CB-839 were potential treatment options.

Conclusion: Dormant CRC is associated with high glutamine metabolism and synergizes with CAFs in 5-FU resistance, and the key effectors are LMOD1, MAB21L2, and ASPN. Austocystin D, erlotinib, and CB-839 may be useful for dormant CRC.

cSurvival: a web resource for biomarker interactions in cancer outcomes and in cell lines

Survival analysis is a technique for identifying prognostic biomarkers and genetic vulnerabilities in cancer studies. Large-scale consortium-based projects have profiled >11 000 adult and >4000 pediatric tumor cases with clinical outcomes and multiomics approaches. This provides a resource for investigating molecular-level cancer etiologies using clinical correlations. Although cancers often arise from multiple genetic vulnerabilities and have deregulated gene sets (GSs), existing survival analysis protocols can report only on individual genes. Additionally, there is no systematic method to connect clinical outcomes with experimental (cell line) data. To address these gaps, we developed cSurvival (https://tau.cmmt.ubc.ca/cSurvival). cSurvival provides a user-adjustable analytical pipeline with a curated, integrated database and offers three main advances: (i) joint analysis with two genomic predictors to identify interacting biomarkers, including new algorithms to identify optimal cutoffs for two continuous predictors; (ii) survival analysis not only at the gene, but also the GS level; and (iii) integration of clinical and experimental cell line studies to generate synergistic biological insights. To demonstrate these advances, we report three case studies. We confirmed findings of autophagy-dependent survival in colorectal cancers and of synergistic negative effects between high expression of SLC7A11 and SLC2A1 on outcomes in several cancers. We further used cSurvival to identify high expression of the Nrf2-antioxidant response element pathway as a main indicator for lung cancer prognosis and for cellular resistance to oxidative stress-inducing drugs. Altogether, these analyses demonstrate cSurvival’s ability to support biomarker prognosis and interaction analysis via gene- and GS-level approaches and to integrate clinical and experimental biomedical studies.

Next-generation sequencing identifies HOXA6 as a novel oncogenic gene in low grade glioma

Background: Low grade glioma is one of the most common lethal cancers in the human nervous system. Emerging evidence has demonstrated that homeobox A cluster (HOXA) gene family plays a critical role in the transcriptional regulation as well as cancer initiation and progression. However, the expression, biological functions and upstream regulatory mechanism of 11 HOXAs in low grade glioma are not yet clear.

Methods: In this study, we utilized various public databases and bioinformatics analyzed, including TCGA, CGGA, Rembrandt, HPA, LinkedOmics, cBioPortal, TISDIB, single-sample GSEA (ssGSEA), TIMER, LnCeVar, LASSO regression, Cox regression, Kaplan-Meier plot, and receiver operating, characteristic (ROC) analyses, GDSC and CTRP databases to analyzed the mRNA and protein expression profiles, gene mutation, clinical features, diagnosis, prognosis, signaling pathway, TMB, immune subtype, immune cell infiltration, immune modulator, ceRNA network and drug sensitivity of 11 HOXAs. Growth curve and transwell assays were utilized to study the biological characteristics of HOXA6 in LGG progression.

Results: In the present study, we found that 11 HOXAs (HOXA1, HOXA2, HOXA3, HOXA4, HOXA5, HOXA6, HOXA7, HOXA9, HOXA10, HOXA11 and HOXA3) were consistently up-regulated in LGG tissues and GBM tissues. Up-regulated of the HOXAs expression were significantly correlated with higher tumor stage, IDH mutation status, 1p/19q co-deletion, histological type and primary therapy outcome. Survival analyses showed that higher expression of HOXA1, HOXA2, HOXA3, HOXA4, HOXA5, HOXA7, HOXA9, HOXA10, HOXA11 and HOXA13 were correlated with shorter overall survival (OS), disease-specific survival (DSS) and progression-free survival (PFS) in LGG patients. Univariate and multivariate analyses revealed that HOXA1, HOXA6 expression and tumor grade, age, primary therapy outcome and age were independent factors affecting the prognosis of LGG patients. ROC curve analysis of HOXAs showed that HOXAs had a high accuracy (AUC > 0.80) in predicting LGG. Furthermore, gene functional enrichment analysis indicated that HOXAs mainly involved in the inflammatory response and immune regulation signaling pathway. CNV and DNA methylation significantly affect the expression of HOXAs. Finally, we uncover that HOXAs expression are highly correlated with immune cells infiltrate, immune modulator and drug sensitivity. We also uncover that the HOXAs related ceRNA network in LGG. More importantly, we found that HOXA6 was highly expressed in LGG cells lines and significantly affected their proliferation and migration abilities.

Conclusions: In conclusion, our data demonstrated that HOXA was correlated with progression and immune infiltration, and could serve as a prognostic biomarker for LGG.

Comprehensive analysis of the correlations of S100B with hypoxia response and immune infiltration in hepatocellular carcinoma

S100B has been found to be dysregulated in many cancers including hepatocellular carcinoma (HCC). However, the functions of S100B and its underlying mechanisms in HCC remain poorly understood, especially in the tumor microenvironment. In this study, functions enrichment analysis indicated that S100B expression was correlated with hypoxia and immune responses. We found that hypoxia could induce S100B expression in an HIF-1α-dependent manner in HepG2 cells. Luciferase reporter and ChIP-qRCR assays demonstrated that HIF-1α regulates S100B transcription by directly binding to hypoxia-response elements (HREs) of the S100B promoter. Functionally, knockdown of S100B reduces hypoxia-induced HepG2 cell invasion and migration. Furthermore, GSVA enrichment results displayed that S100B and its co-expressed genes were positively correlated with EMT pathway in HCC. Additionally, GO/KEGG cluster analysis results indicated that co-expressed genes of S100B were involved in biological processes of immune response and multiple tumor immune-related signaling pathways in HCC. S100B expression was positively correlated with multiple immune cells tumor infiltration and associated with chemokines/chemokine receptors and immune checkpoint genes. Moreover, S100B is predominantly expressed in immune cells, especially NK (Natural Killer) cell. In addition, the hub genes of S100B co-expression and hypoxia response in HepG2 cell were also associated with immune cells infiltration in HCC. Taken together, these findings provide a new insight into the complex networks between hypoxia response and immune cells infiltration in tumor microenvironment of liver cancer. S100B maybe serve as a novel target for future HCC therapies.

Comprehensive Analysis of HHLA2 as a Prognostic Biomarker and Its Association With Immune Infiltrates in Hepatocellular Carcinoma

BACKGROUND

Inhibitory immune checkpoint proteins promote tumor immune escape and are associated with inferior patient outcome. However, the biological functions and regulatory roles of one of its members, HHLA2, in the tumor immune microenvironment have not been explored.

METHODS

RandomForest analyses (371 cases), qRT-PCR (15 cases), and immunohistochemical staining (189 cases) were used to validate the prognostic value of HHLA2 in hepatocellular carcinoma (HCC) patients. Bioinformatic analyses were further performed to explore the biological functions and potential signaling pathways affected by HHLA2. Moreover, ESTIMATE, single sample gene set enrichment analysis, CIBERSORT, TIMER, and other deconvolution methods were used to analyze the composition and infiltration level of immune cells. Multiplex immunofluorescence assays were employed to validate the fractions of suppressive immune cells, and HHLA2-related molecular alterations were investigated. Finally, the clinical response to chemotherapy and immune checkpoint blockade was predicted by TIDE, Submap, and several other in silico analyses.

RESULTS

RandomForest analysis revealed that HHLA2 was the most important inhibitory immune checkpoint associated with HCC patient prognosis (relative importance = 1). Our HCC cohorts further revealed that high HHLA2 expression was an independent prognostic biomarker of shorter overall survival (P<0.01) and time to recurrence (P<0.001) for HCC patients. Bioinformatics experiments revealed that HHLA2 may accelerate the cell cycle of cancer cells. Additionally, we found that high expression of HHLA2 was associated with immune infiltrates, including some immunosuppressive cells, cytokines, chemokines, and corresponding receptors, resulting in an immunosuppressive environment. Notably, HHLA2 expression was positively correlated with the infiltration of exhausted CD8+ T cells, which was validated by immunofluorescence. Genomic alteration analyses revealed that promoter hypermethylation of HHLA2 may be associated with its low expression. More importantly, patients with high HHLA2 expression may be more sensitive to chemotherapy and have better responses to immunotherapy.

CONCLUSIONS

High expression of HHLA2 is an independent prognostic biomarker for HCC patients. It can activate the cell cycle and foster an immunosuppressive tumor microenvironment by enriching exhausted CD8+ T cells. Promoter hypermethylation might lead to low expression of HHLA2 in HCC. Thus, targeting HHLA2 may be a practical therapeutic strategy for HCC patients in the future.

Identification of proteomic markers for prediction of the response to 5-Fluorouracil based neoadjuvant chemoradiotherapy in locally advanced rectal cancer patients

Background

Neoadjuvant chemoradiotherapy (nCRT) prior to surgery is the standard treatment for patients with locally advanced rectal cancer (LARC), while parts of them show poor therapeutic response accompanied by therapy adverse effects. Predictive biomarkers for nCRT response could facilitate the guidance on treatment decisions but are still insufficient until now, which limits the clinical applications of nCRT in LARC patients.

Methods

In our study, 37 formalin-fixed paraffin-embedded tumor biopsies were obtained from patients with LARC before receiving 5-fluorouracil based nCRT. Proteomics analyses were conducted to identify the differentially expressed proteins (DEPs) between total responders (TR) and poor responders (PR). The DEPs were validated via ROC plotter web tool and their predictive performance was evaluated by receiver operating characteristic analysis. Functional enrichment analyses were performed to further explore the potential mechanisms underlying nCRT response.

Results

Among 3,998 total proteins, 91 DEPs between TR and PR were screened out. HSPA4, NIPSNAP1, and SPTB all with areas under the curve (AUC) ~ 0.8 in the internal discovery cohort were independently validated by the external mRNA datasets (AUC ~ 0.7), and their protein levels were linearly correlated with the graded responses to nCRT in the internal cohort. The combination of HSPA4 and SPTB could distinctly discriminate the TR and PR groups (AUC = 0.980, p < 0.0001). Moreover, multiple combinations of the three proteins realized increased specificity and/or sensitivity, while achieving favorable predictive value when moderate responders were introduced into the ROC analysis. Pathways including DNA damage repair, cell cycle, and epithelial mesenchymal transition were involved in nCRT response according to the enrichment analysis results.

Conclusions

HSPA4, SPTB and NIPSNAP1 in tumor biopsies and/or their optional combinations might be potential predictive markers for nCRT response in patients with LARC. The DEPs and their related functions have implications for the potential mechanisms of treatment response to nCRT in patients with LARC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-022-02530-0.

A Pan-Cancer Bioinformatic Analysis of RAD51 Regarding the Values for Diagnosis, Prognosis, and Therapeutic Prediction

BACKGROUND

RAD51, a critical protein for DNA repairment, has been found to associate with multiple cancer types, but, so far, a systematic pan-cancer analysis of RAD51 has not been done yet.

METHODS

Data were obtained from multiple open databases and genetic alteration, gene expression, survival association, functional enrichment, stemness, mutation association, immunity association, and drug therapy association of RAD51were analyzed. A prognostic model of RAD51 for overall glioma was constructed as an example application of RAD51 as a biomarker.

RESULTS

RAD51 was overexpressed in 28 types of cancers and was associated with worse overall survival in 11 cancer types. RAD51 correlated genes were enriched in cell cycle terms. RAD51 was associated with cancer stemness, tumor mutational burden, and multiple immunomodulators in different cancer types. RAD51 expression was different across immune subtypes in 11 cancer types. RAD51 was closely associated with cancer immune microenvironments in some cancer types. Proliferating T cells was the cell type that expressed highest RAD51 across most of the cancer samples analyzed. RAD51 expression had an AUC of over 0.5 in 12 of the 23 ICB subcohorts. The Tumor Immune Dysfunction and Exclusion of 9 cancer types were different between RAD51 high and low groups. RAD51 expression showed negative correlations with the sensitivity of most drugs. A prognostic nomogram was constructed with a high confidence.

CONCLUSION

RAD51 is a clinical valuable biomarker for multiple cancer types, regarding its potential power for diagnosis, prognosis, and therapeutic prediction.

Identification of a five-gene signature deriving from the vacuolar ATPase (V-ATPase) sub-classifies gliomas and decides prognoses and immune microenvironment alterations

Aberrant expression of coding genes of the V-ATPase subunits has been reported in glioma patients that can activate oncogenic pathways and result in worse prognosis. However, the predictive effect of a single gene is not specific or sensitive enough. In this study, by using a series of bioinformatics analyses, we identified five coding genes (ATP6V1C2, ATP6V1G2, TCIRG1, ATP6AP1 and ATP6AP2) of the V-ATPase that were related to glioma patient prognosis. Based on the expression of these genes, glioma patients were sub-classified into different prognosis clusters, of which C1 cluster performed better prognosis; however, C2 cluster showed more malignant phenotypes with oncogenic and immune-related pathway activation. The single-cell RNA-seq data revealed that ATP6AP1, ATP6AP2, ATP6V1G2 and TCIRG1 might be cell-type potential markers. Copy number variation and DNA promoter methylation potentially regulate these five gene expressions. A risk score model consisted of these five genes effectively predicted glioma prognosis and was fully validated by six independent datasets. The risk scores also showed a positive correlation with immune checkpoint expression. Importantly, glioma patients with high-risk scores presented resistance to traditional treatment. We also revealed that more inhibitory immune cells infiltration and higher rates of “non-response” to immune checkpoint blockade (ICB) treatment in the high-risk score group. In conclusion, our study identified a five-gene signature from the V-ATPase that could sub-classify gliomas into different phenotypes and their abnormal expression was regulated by distinct mechanisms and accompanied with immune microenvironment alterations potentially act as a biomarker for ICB treatment.

Developing an immune-related gene prognostic index associated with progression and providing new insights into the tumor immune microenvironment of prostate cancer

We developed an immune-related gene prognostic index (IGPI) associated with progression and provided new insights into the tumor immune microenvironment (TIME) for prostate cancer (PCA) patients undergoing radical prostatectomy. All analyses were conducted with R software (version 3.6.3) and its suitable packages. Meta analysis was performed through STATA 16.0. TUBB3, WDR62, and PPARGC1A were finally identified to establish the IGPI score. IGPI score increased with the augment of Gleason score and T stage, as well as biochemical recurrence (BCR) and prostate specific antigen (PSA). Patients with higher IGPI score were at higher risk of progress (HR: 2.88; 95%CI: 95%CI: 1.80-4.61). Gene set enrichment analysis indicated that patients in high-risk group was positively associated with mismatch repair, cell cycle, DNA replication, base excision repair, nucleotide excision repair, homologous recombination, and pyrimidine metabolism. We observed that patients in the high-risk group had significantly higher tumor mutation burden score and microsatellite instability score than those in the low-risk group. For analysis of immune checkpoint, ADORA2A, CD80, TNFRSF4, TNFRSF18, and TNFRSF25 were differentially expressed between no progress and progress groups, and were significantly associated with progress free survival. We observed positive correlations between IGPI score, and lymphoid immune cells, macrophages M2 and immune score, while negative association between IGPI score, and dendritic cells, fibroblasts, stromal score, and microenvironment score. In conclusion, the IGPI score constructed in this study might serve as an independent risk factor associated with PCA progression. ADORA2A, CD80, TNFRSF4, TNFRSF18, and TNFRSF25 might be the potential targets in the treatment of PCA.

Construction and Validation of Two Hepatocellular Carcinoma-Progression Prognostic Scores Based on Gene Set Variation Analysis

Background: Liver hepatocellular carcinoma (LIHC) remains a global health challenge with a low early diagnosis rate and high mortality. Therefore, finding new biomarkers for diagnosis and prognosis is still one of the current research priorities.

Methods: Based on the variation of gene expression patterns in different stages, the LIHC-development genes (LDGs) were identified by differential expression analysis. Then, prognosis-related LDGs were screened out to construct the LIHC-unfavorable gene set (LUGs) and LIHC-favorable gene set (LFGs). Gene set variation analysis (GSVA) was conducted to build prognostic scoring models based on the LUGs and LFGs. ROC curve analysis and univariate and multivariate Cox regression analysis were carried out to verify the diagnostic and prognostic utility of the two GSVA scores in two independent datasets. Additionally, the key LCGs were identified by the intersection analysis of the PPI network and univariate Cox regression and further evaluated their performance in expression level and prognosis prediction. Single-sample GSEA (ssGSEA) was performed to understand the correlation between the two GSVA enrichment scores and immune activity.

Result: With the development of LIHC, 83 LDGs were gradually upregulated and 247 LDGs were gradually downregulated. Combining with LIHC survival analysis, 31 LUGs and 32 LFGs were identified and used to establish the LIHC-unfavorable GSVA score (LUG score) and LIHC-favorable GSVA score (LFG score). ROC curve analysis and univariate/multivariate Cox regression analysis suggested the LUG score and LFG score could be great indicators for the early diagnosis and prognosis prediction. Four genes (ESR1, EHHADH, CYP3A4, and ACADL) were considered as the key LCGs and closely related to good prognosis. The frequency of TP53 mutation and copy number variation (CNV) were high in some LCGs. Low-LFG score patients have active metabolic activity and a more robust immune response. The high-LFG score patients characterized immune activation with the higher infiltration abundance of type I T helper cells, DC, eosinophils, and neutrophils, while the high-LUG score patients characterized immunosuppression with the higher infiltration abundance of type II T helper cells, TRegs, and iDC. The high- and low-LFG score groups differed significantly in immunotherapy response scores, immune checkpoints expression, and IC50 values of common drugs.

Conclusion: Overall, the LIHC-progression characteristic genes can be great diagnostic and prognostic signatures and the two GSVA score systems may become promising indices for guiding the tumor treatment of LIHC patients.

Systematic Analysis and Validation of the Prognosis, Immunological Role and Biology Function of the Ferroptosis-Related lncRNA GSEC/miRNA-101-3p/CISD1 Axis in Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) is the most common type of lung cancer, accounting for approximately 85% of pulmonary malignancies. Emerging evidence has demonstrated that ferroptosis plays a central role in both immunities as well as tumor proliferation. However, the clinical significance, immunological function, and upstream modulatory mechanism of ferroptosis-related genes in LUAD remain unclear. Here, we utilized various bioinformatics data to identify differentially expressed (DEGs) and prognosis-related ferroptosis (FRGs) genes in LUAD. Based upon identified DEGs, FRG, and ceRNA modulatory networks were constructed. Pearson’s correlation analysis was used to evaluate the correlation between FRGs and the tumor mutational burden, microsatellite instability, tumor-infiltrating immunity, cellular checkpoint control, and drug sensitivity in LUAD. A loss-of-function analysis was performed to verify the function of CISD1 in LUAD progression. Our findings revealed that certain FRGs (CISD1, ATP5MC3, PGD, SLC7A11, ACSL3, and FANCD2) are significantly upregulated in LUAD and that their elevated expression is associated with both advanced tumor stage and unfavorable prognosis. Furthermore, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment results revealed these FRGs to be primarily involved in ferroptosis and glutathione metabolism in LUAD. We constructed a prognostic FRG-based model capable of accurately predicting LUAD patient overall survival with high specificity. The upstream lncRNA GSEC/miRNA-101-3p regulatory axis involving CISD1, ATP5MC3, and PGD was identified to be relevant in tumor progression. We also found GSEC, CISD1, ATP5MC3, and PGD to be upregulated, with miRNA-101-3p downregulated, in the setting of LUAD. Immunohistochemical analysis revealed CISD1, ATP5MC3, and PGD overexpression in LUAD tissue samples; CISD1 knockdown was noted to significantly inhibit LUAD proliferation and migration. In summary, this study characterizes relevant functional roles of the lncRNA GSEC/miR-101-3p axis in the setting of LUAD and suggests diagnostic and therapeutic biomarkers potentially useful in the clinical management of this illness.

DOK2 Has Prognostic and Immunologic Significance in Adults With Acute Myeloid Leukemia: A Novel Immune-Related Therapeutic Target

Background

The role of downstream tyrosine kinase 2 (DOK2), a major member of the DOK family, remains poorly defined in acute myeloid leukemia (AML). Herein, we investigated the expression levels, clinical outcomes, and biological functions of DOK2 in patients with AML.

Methods

Datasets were obtained from the Cancer Genome Atlas (TCGA) database for transcriptomic and clinical information. Nomogram construction and assessment were conducted using Cox regression analysis, receiver operating characteristic (ROC) curves, and calibration plots. Public databases, including the Gene Expression Omnibus, Cancer Cell Line Encyclopedia, LinkedOmics, GeneMANIA, TISIDB, and Gene Set Cancer Analysis, were employed for relevant bioinformatic studies. Moreover, we utilized the CIBERSORT algorithm to evaluate the level of infiltration of immune cells into the bone marrow microenvironment.

Results

We observed that DOK2 transcription levels were markedly upregulated in AML samples (P &lt; 0.001), and its high expression was associated with inferior overall survival (OS) (HR = 2.17, P &lt; 0.001) and disease-free survival (DFS) (HR = 2.50, P &lt; 0.001). ROC curve analysis also showed the reliable diagnostic efficiency of DOK2 in AML. For treatment regimens, patients with high DOK2 expression could significantly prolong OS by receiving hematopoietic stem cell transplantation (HSCT) (P &lt; 0.001), whereas those with low DOK2 expression were more likely to improve DFS by chemotherapy alone rather than HSCT. Nomograms constructed for predicting OS and DFS exhibited satisfactory discrimination and accuracy. Functional enrichment analysis identified that DOK2 was involved in important pathways associated with immune-related activities. Furthermore, CIBERSORT scores reflected negative correlations of DOK2 with activated mast cells and resting CD4+ memory T cells, which indicated its adverse immunomodulatory potential.

Conclusion

We suggest that elevated DOK2 expression could be an unfavorable prognostic indicator of survival in patients with AML. Our findings provide new insights into the role of DOK2 in AML, with promising clinical implications.

Identification of a Novel Nomogram to Predict Progression Based on the Circadian Clock and Insights Into the Tumor Immune Microenvironment in Prostate Cancer

Background

Currently, the impact of the circadian rhythm on the tumorigenesis and progression of prostate cancer (PCA) has yet to be understood. In this study, we first established a novel nomogram to predict PCA progression based on circadian clock (CIC)-related genes and provided insights into the tumor immune microenvironment.

Methods

The TCGA and Genecards databases were used to identify potential candidate genes. Lasso and Cox regression analyses were applied to develop a CIC-related gene signature. The tumor immune microenvironment was evaluated through appropriate statistical methods and the GSCALite database.

Results

Ten genes were identified to construct a gene signature to predict progression probability for patients with PCA. Patients with high-risk scores were more prone to progress than those with low-risk scores (hazard ratio (HR): 4.11, 95% CI: 2.66-6.37; risk score cut-off: 1.194). CLOCK, PER (1, 2, 3), CRY2, NPAS2, RORA, and ARNTL showed a higher correlation with anti-oncogenes, while CSNK1D and CSNK1E presented a greater relationship with oncogenes. Overall, patients with higher risk scores showed lower mRNA expression of PER1, PER2, and CRY2 and higher expression of CSNK1E. In general, tumor samples presented higher infiltration levels of macrophages, T cells and myeloid dendritic cells than normal samples. In addition, tumor samples had higher immune scores, lower stroma scores and lower microenvironment scores than normal samples. Notably, patients with higher risk scores were associated with significantly lower levels of neutrophils, NK cells, T helper type 1, and mast cells. There was a positive correlation between the risk score and the tumor mutation burden (TMB) score, and patients with higher TMB scores were more prone to progress than those with lower TMB scores. Likewise, we observed similar results regarding the correlation between the microsatellite instability (MSI) score and the risk score and the impact of the MSI score on the progression-free interval. We observed that anti-oncogenes presented a significantly positive correlation with PD-L1, PD-L2, TIGIT and SIGLEC15, especially PD-L2.

Conclusion

We identified ten prognosis-related genes as a promising tool for risk stratification in PCA patients from the fresh perspective of CIC.

Comprehensive Analysis of the Expression and Clinical Significance of THO Complex Members in Hepatocellular Carcinoma

Background

Methods

Results

Conclusion

Diagnostic, Therapeutic, and Prognostic Value of the m6A Writer Complex in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) has poor prognosis and is usually diagnosed only at an advanced stage. Identification of novel biomarkers is critical to early diagnosis and better prognosis for HCC patients. N6-methyladenosine (m⁶A) RNA methylation regulators play important roles in the development of many tumors. However, the m⁶A writer complex, a key executor of m⁶A methylation modification, has not been independently investigated, and its specific bioinformatics analysis has not yet been performed in HCC. In this study, we used multiple public databases to evaluate the diagnostic, therapeutic, and prognostic value of the m⁶A writers in HCC. The results showed that expression levels of METTL3, VIRMA and CBLL1 were significantly increased, while expression levels of METTL14 and ZC3H13 were significantly decreased in HCC, which was closely related to clinicopathological factors, such as tumor stage and prognosis. Bioinformatics further explored the possible underlying mechanisms by which the m⁶A writer complex are involved in activation of tumor-promoting pathways and/or inhibition of tumor-suppressing pathways, including apoptosis, cell cycle, DNA damage response and EMT. Furthermore, we showed that the m⁶A writer complex is correlated with immune cell infiltration and immunoregulator expression in HCC. In conclusion, the m⁶A writer complex may represent a promising biomarker and target that can guide targeted therapy or immunotherapy for HCC patients.

Comprehensive Analysis of HOX Family Members as Novel Diagnostic and Prognostic Markers for Hepatocellular Carcinoma

Background. The homeobox (HOX) gene family has been found to be involved in human cancers. However, its involvement in hepatocellular carcinoma (HCC) has not been well documented. Here, we comprehensively evaluated the role of HOXs in HCC. Methods. RNA sequencing profile of TCGA-LIHC and LIRI-JP were obtained from the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC), respectively. Data of TCGA-LIHC methylation were downloaded from UCSC Xena. Genetic alteration data for the TCGA samples was obtained from cBioPortal and GSCA. The diagnostic efficiency was assessed using ROC curves. The prognostic significance was evaluated by the Kaplan–Meier method and Cox regression analysis. Subsequent functional analysis was performed through the clusterProfiler package. ssGSEA, ESTIMATE, and TIDE algorithms were employed to explore the relationship between HOXs and the HCC microenvironment. Finally, pRRophetic package and NCI-60 cancerous cell lines were applied to estimate anticancer drug sensitivity. Results. The mRNA levels of HOXs in HCC tissues were higher than those of noncancerous tissues and were correlated with poor overall survival (OS). HOXA6, C6, D9, D10, and D13 could serve as independent risk factors for OS. Further functional analysis revealed that these five HOXs regulate the cell proliferation, cell cycle, immune response, and microenvironment composition of HCC. In addition, the aberrant expression and methylation of HOXs is of great value in the diagnosis of HCC. Conclusion. HOXs play crucial roles in HCC and could serve as potential markers for HCC diagnosis and prognosis.

Network Pharmacology-Based Strategy to Investigate the Anti-Breast Cancer Mechanisms of Spatholobus suberectus Dunn

Spatholobus suberectus Dunn (SSD) possesses potential antitumor activity; however, the mechanism underlying its anti-proliferative effect on breast cancer is unclear. In this study, we explored potential SSD targets for breast cancer treatment through a network pharmacology approach. First, by integrating multiple databases, a total of 16 potential bioactive compounds and 252 targets were screened. Differentially expressed genes (DEGs) were screened by analyzing breast cancer gene chip data from The Cancer Genome Atlas and Gene Expression Omnibus databases. By overlapping drug targets and DEGs, 33 common targets were found; their functions were further analyzed with Gene Ontology and KEGG analysis. A network of 16 compounds and 33 common targets was constructed, from which 10 hub targets were identified using CytoHubba. Based on the KEGG result and network analysis, the 33 common targets were mainly enriched in the peroxisome proliferator-activated receptor (PPAR) signaling pathway and PPARγ was identified as the potential target of SSD. Moreover, the 10 hub targets were correlated with prognosis and immune infiltration in breast cancer via bioinformatic analysis. Finally, molecular docking and experiments in vitro further verified the targeting ability and anti-breast cancer activity of SSD. SSD is promising in the treatment of breast cancer; PPARγ may be its potential therapeutic target.

A Pan-Cancer Analysis of the Oncogenic Role of Cell Division Cycle-Associated Protein 4 (CDCA4) in Human Tumors

Purpose

To unravel the oncogenic role of CDCA4 in different cancers from the perspective of tumor immunity.

Methods

Raw data on CDCA4 expression in tumor samples and paracancerous samples were obtained from TCGA and GTEX databases. In addition, we investigated pathological stages and the survival analysis of CDCA4 in pan-cancer across Gene Expression Profiling Interactive Analysis (GEPIA) database. Cox Proportional Hazards Model shows that high CDCA4 levels are associated with several vital indicators in oncology. On the one hand, we explored the correlation between CADA4 expression and tumor immune infiltration by the TIMER tool; On the other hand, we utilized the methods of CIBERSORT and ESTIMATE computational to evaluate the proportion of tumor infiltrating immune cells (TIIC) and the amounts of stromal and immune components based on TCGA database. The use of antineoplastic drugs and the expression of CDCA4 also showed a high correlation via linear regression. Protein–Protein Interaction analysis was performed in the GeneMANIA database, and enrichment analysis was performed and predicted signaling pathways were identified by using Gene Ontology and Kyoto Encyclopedia of Genes. The correlation between CDCA4 expression with Copy number variations (CNV) and methylation is detailed, respectively. Molecular biology experiments including Western blotting, flow cytometry, EDU staining, Transwell and Wound Healing assay to validate the cancer promoting role of CDCA4 in hepatocellular carcinoma (HCC).

Results

Most tumors highly expressed CDCA4. Elevated CDCA4 expression was associated with poor OS and DFS. There was a significant correlation between CDCA4 expression and TITCs. Moreover, markers of TIICs exhibited distinct patterns of CDCA4 associated immune infiltration. In addition, we pay attention to the association between the expression of CDCA4 and the use of the anti-tumor drugs. CDCA4 is related to biological progress (BP), cellular component (CC) and molecular function (MF). Dopaminergic Synapse, AMPK, Sphingolipid, Chagas Disease, mRNA Surveillance were significantly enriched pathways in positive and negative correlation genes with CDCA4. CNV is thought to be a positive correlation with CDCA4 expression. Conversely, methylation is negative correlation with CDCA4 expression. Molecular biology experiments confirm a cancer promoting role for CDCA4 in HCC

Conclusion

CDCA4 may serve as a biomarker for cancer immunologic infiltration and poor prognosis, providing a new way of thinking for cancer treatment.

Identification of Circular RNA-Based Immunomodulatory Networks in Colorectal Cancer

BACKGROUND

Circular RNAs (circRNAs) have been recently proposed as hub molecules in various diseases, especially in tumours. We found that circRNAs derived from ribonuclease P RNA component H1 (RPPH1) were highly expressed in colorectal cancer (CRC) samples from Gene Expression Omnibus (GEO) datasets.

OBJECTIVE

We sought to identify new circRNAs derived from RPPH1 and investigate their regulation of the competing endogenous RNA (ceRNA) and RNA binding protein (RBP) networks of CRC immune infiltration.

METHODS

The circRNA expression profiles miRNA and mRNA data were extracted from the GEO and The Cancer Genome Atlas (TCGA) datasets, respectively. The differentially expressed (DE) RNAs were identified using R software and online server tools, and the circRNA-miRNA-mRNA and circRNA-protein networks were constructed using Cytoscape. The relationship between targeted genes and immune infiltration was identified using the GEPIA2 and TIMER2 online server tools.

RESULTS

A ceRNA network, including eight circRNAs, five miRNAs, and six mRNAs, was revealed. Moreover, a circRNA-protein network, including eight circRNAs and 49 proteins, was established. The targeted genes, ENOX1, NCAM1, SAMD4A, and ZC3H10, are closely related to CRC tumour-infiltrating macrophages.

CONCLUSIONS

We analysed the characteristics of circRNA from RPPH1 as competing for endogenous RNA binding miRNA or protein in CRC macrophage infiltration. The results point towards the development of a new diagnostic and therapeutic paradigm for CRC.

A Pan-Cancer Analysis of the Oncogenic Role of Nuclear Transport Factor 2 in Human Cancers

Nuclear transport factor 2 (NUTF2) is a GDP-binding protein that participates in the nucleocytoplasmic transport process. The role of NUTF2 in cancer development is largely unknown and lacks systemic assessment across human cancers. In this study, we performed a pan-cancer analysis of NUTF2 in human cancers. Out of 33 types of cancers, 19 types had significantly different expression of NUTF2 between tumor and normal tissues. Meanwhile, survival analysis showed that NUTF2 could be an independent prognostic factor in several tumor types. Further analysis suggested that the expression of NUTF2 expression was correlated with the infiltration of immune cells, such as CD8⁺ T cells, effector memory CD4⁺ T cells, and cancer-associated fibroblasts in kidney renal clear cell carcinoma. Moreover, co-expression analysis showed the positive association between NUTF2 and cell proliferation biomarkers (MKI67and PCNA) and epithelial–mesenchymal transition markers (VIM, TWIST1, SNAI1, SNAI2, FN1, and CDH2), suggesting that NUTF2 plays important roles in regulating cancer proliferation and metastasis. This pan-cancer analysis of NUTF2 provides a systemic understanding of its oncogenic role across different types of cancers.

A pan-cancer analysis of molecular characteristics and oncogenic role of gasdermins

Background

The gasdermins (GSDMs) family is proposed to be pore-forming effector proteins that cause cell membrane permeabilization and pyroptosis. Despite our increasing knowledge of GSDMD, GSDME and GSDMB, the biological functions and the regulation of GSDM expression and activation remain elusive for most GSDMs. In this study, we analyzed the molecular characteristics and oncogenic role of GSDM family genes systematically.

Methods

TCGA, CCLE, cBioPortal, GEPIA, CellMiner and BioGRID databases were utilized in this study. Immunohistochemical analysis and a series of in vitro experiments were conducted.

Results

We found that, in cancer, GSDM genes and their expressions extensively changed, which were associated with patient survival. The expression of GSDMs was widely associated with cancer-related pathways, drug resistance, immune subtypes, tumor microenvironment and cancer cell stemness. However, an intra- and inter-cancer heterogeneity was discovered regarding the corresponding GSDM gene. We found that GSDMA and GSDMB regulated drug resistance to the opposite direction of GSDME. In colorectal cancer, GSDME might be a positive regulator in cell invasion and metastasis through cell migration and angiogenesis, while GSDMA, GSDMB and GSDMD might be a negatively regulator of cell migration.

Conclusions

GSDM family genes might play important roles in cancer other than pyroptosis. We suggest more efforts be made to investigate the GSDM family and each GSDM gene be studied as an entity in each type of cancer.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-022-02483-4.

Identifying Mitotic Kinesins as Potential Prognostic Biomarkers in Ovarian Cancer Using Bioinformatic Analyses

Ovarian cancer (OC) is characterized by late-stage presentation, chemoresistance, and poor survival. Evaluating the prognosis of OC patients via effective biomarkers is essential to manage OC progression and to improve survival; however, it has been barely established. Here, we intend to identify differentially expressed genes (DEGs) as potential prognostic biomarkers of OC via bioinformatic analyses. Initially, a total of thirteen DEGs were extracted from different public databases as candidates. The expression of KIF20A, one of the DEGs, was correlated with a worse outcome of OC patients. The functional correlation of the DEGs with mitosis and the prognostic value of KIF20A imply a high correlation between mitotic kinesins (KIFs) and OC development. Finally, we found that KIF20A, together with the other nine mitotic KIFs (4A, 11, 14, 15, 18A, 18B, 23, C1, and2C) were upregulated and activated in OC tissues. Among the ten, seven overexpressed mitotic KIFs (11, 14, 18B, 20A, 23, and C1) were correlated with unfavorable clinical prognosis. Moreover, KIF20A and KIF23 overexpression was associated with worse prognosis in OC patients treated with platinum/taxol chemotherapy, while OCs overexpressing mitotic KIFs (11, 15, 18B, and C1) were resistant to MAPK pathway inhibitors. In conclusion, worse outcomes of OC patients were correlated with overexpression of several mitotic KIFs, which may serve both as prognostic biomarkers and therapeutic targets for OC.

ERCC6L is a biomarker and therapeutic target for non-small cell lung adenocarcinoma

BACKGROUND

Non-small cell lung carcinoma (NSCLC) accounts for the majority of lung cancer which is one of the most common cancer types and results in high percentage of cancer-related deaths. Although NSCLC patients have been benefiting from the existing standard treatments, more candidate biomarkers for effective diagnosis and targets for therapy are still required to be uncovered. The expression pattern and biological function of Excision repair cross-complementation group 6 like (ERCC6L) in NSCLC are ill-investigated.

METHODS

We performed bioinformatic analyses in NSCLC patients with lung adenocarcinoma (LUAD) or lung squamous cell carcinoma (LUSC), respectively. Patient survival determination and meta-analysis were carried out to check the clinical significance of ERCC6L. Datamining was also performed to evaluate the ERCC6L mRNA and protein expression levels in patients with LUAD and the correlation with immune cell infiltration. In silico prediction indicated the potential interacting proteins and correlated pathways of ERCC6L in LUAD. Loss-of-function studies were performed to determine the role of ERCC6L in LUAD cells.

RESULTS

Here, we found that ERCC6L is upregulated in patients with LUAD and LUSC and is strongly associated with poor outcomes of LUAD, but not LUSC, patients. In addition, ERCC6L mRNA and protein were shown to be more expressed in patients with advanced stages of LUAD. Finally, functional analyses reveal the promoting effects of ERCC6L on LUAD cell survival, migration and invasion.

CONCLUSIONS

Cohort data analysis and experimental validation shed light on the promising prognostic and therapeutic application of ERCC6L in LUAD, but maybe not LUSC, patients.

A Ferroptosis-Related Gene Prognostic Index Associated With Biochemical Recurrence and Radiation Resistance for Patients With Prostate Cancer Undergoing Radical Radiotherapy

Background: Ferroptosis is a new type of programmed cell death which has been reported to be involved in the development of various cancers. In this study, we attempted to explore the possible links between ferroptosis and prostate cancer (PCa), and a novel ferroptosis-related gene prognostic index (FGPI) was constructed to predict biochemical recurrence (BCR) and radiation resistance for PCa patients undergoing radical radiotherapy (RRT). Moreover, the tumor immune microenvironment (TME) of PCa was analyzed.

Methods: We merged four GEO datasets by removing batch effects. All analyses were conducted with R version 3.6.3 and its suitable packages. Cytoscape 3.8.2 was used to establish a network of transcriptional factor and competing endogenous RNA.

Results: We established the FGPI based on ACSL3 and EPAS1. We observed that FGPI was an independent risk factor of BCR for PCa patients (HR: 3.03; 95% CI: 1.68–5.48), consistent with the result of internal validation (HR: 3.44; 95% CI: 1.68–7.05). Furthermore, FGPI showed high ability to identify radiation resistance (AUC: 0.963; 95% CI: 0.882–1.00). LncRNA PART1 was significantly associated with BCR and might modulate the mRNA expression of EPAS1 and ACSL3 through interactions with 60 miRNAs. Gene set enrichment analysis indicated that FGPI was enriched in epithelial–mesenchymal transition, allograft rejection, TGF beta signaling pathway, and ECM receptor interaction. Immune checkpoint and m6A analyses showed that PD-L2, CD96, and METTL14 were differentially expressed between BCR and no BCR groups, among which CD96 was significantly associated with BCR-free survival (HR: 1.79; 95% CI: 1.06–3.03). We observed that cancer-related fibroblasts (CAFs), macrophages, stromal score, immune score, estimate score, and tumor purity were differentially expressed between BCR and no BCR groups and closely related to BCR-free survival (HRs were 2.17, 1.79, 2.20, 1.93, 1.92, and 0.52 for cancer-related fibroblasts, macrophages, stromal score, immune score, estimate score, and tumor purity, respectively). Moreover, cancer-related fibroblasts (coefficient: 0.20), stromal score (coefficient: 0.14), immune score (coefficient: 0.14), estimate score (coefficient: 0.15), and tumor purity (coefficient: −0.15) were significantly related to FGPI, among which higher positive correlation between cancer-related fibroblasts and FGPI was observed.

Conclusion: We found that FGPI based on ACSL3 and EPAS1 might be used to predict BCR and radiation resistance for PCa patients. CD96 and PD-L2 might be a possible target for drug action. Besides, we highlighted the importance of immune evasion in the process of BCR.

Clinical and molecular assessment of an onco-immune signature with prognostic significance in patients with colorectal cancer

Understanding the complex tumor microenvironment is key to the development of personalized therapies for the treatment of cancer including colorectal cancer (CRC). In the past decade, significant advances in the field of immunotherapy have changed the paradigm of cancer treatment. Despite significant improvements, tumor heterogeneity and lack of appropriate classification tools for CRC have prevented accurate risk stratification and identification of a wider patient population that may potentially benefit from targeted therapies. To identify novel signatures for accurate prognostication of CRC, we quantified gene expression of 12 immune‐related genes using a medium‐throughput NanoString quantification platform in 93 CRC patients. Multivariate prognostic analysis identified a combined four‐gene prognostic signature (TGFB1, PTK2, RORC, and SOCS1) (HR: 1.76, 95% CI: 1.05–2.95, *p < 0.02). The survival trend was captured in an independent gene expression data set: GSE17536 (177 patients; HR: 3.31, 95% CI: 1.99–5.55, *p < 0.01) and GSE14333 (226 patients; HR: 2.47, 95% CI: 1.35–4.53, *p < 0.01). Further, gene set enrichment analysis of the TCGA data set associated higher prognostic scores with epithelial–mesenchymal transition (EMT) and inflammatory pathways. Comparatively, a lower prognostic score was correlated with oxidative phosphorylation and MYC and E2F targets. Analysis of immune parameters identified infiltration of T‐reg cells, CD8⁺ T cells, M2 macrophages, and B cells in high‐risk patient groups along with upregulation of immune exhaustion genes. This molecular study has identified a novel prognostic gene signature with clinical utility in CRC. Therefore, along with prognostic features, characterization of immune cell infiltrates and immunosuppression provides actionable information that should be considered while employing personalized medicine.

The Mechanism and Prognostic Value of DNA Polymerase δ Subunits in Hepatocellular Carcinoma: Implications for Precision Therapy

PURPOSE

Polymerase δ (POLD) proteins is a pivotal B-family DNA polymerase in the process of genome replication and repair and are comprised of POLD1-4. The predictive value of POLDs in hepatocellular carcinoma (HCC) has not been evaluated until now.

PATIENTS AND METHODS

A total of 369 hepatocellular carcinoma samples and 50 adjacent normal samples were enrolled from the TCGA-LIHC database, and the GSE10186 database was also used. Transcription, methylation and genetic alteration status of HCC patients were evaluated by GEPIA, Kaplan-Meier plotter, cBioPortal, MethHC, MethSurv. SurvExpress was employed to generate the overall prognosis prediction signature of POLDs. POLDs coexpressed genes were explored and enriched in potential pathways. K-M curves were generated to compare the different survival results in different groups, while ROC curves were used to validate the efficiency of the POLD signature.

RESULTS

All four POLD subunits were highly expressed in HCC tumor tissues. POLD1-3 and increased mRNA levels were also positively associated with advanced tumor stage and OS prognosis. Methylation in the promoter of POLDs affects mRNA expression and OS, especially for some specific CpG sites. Meanwhile, POLDs could preferably predict the prognosis for patients who suffered from a high gene mutation burden. We evaluated the combined prognostic predictive value of four POLD subunits in both the TCGA-LIHC and GSE10186 databases and recognized the statistically significant HR of the high-risk group, along with the reliable predictive value. The coexpressed gene sets and annotation results showed that the POLD coexpressed genes were mostly associated with DNA repair and cell cycle regulation pathways.

CONCLUSION

POLD is an essential predictive factor for the prognosis of HCC. The united signature could precisely identify unfavorable clinical outcome of HCC.

Preclinical Identification of Sulfasalazine's Therapeutic Potential for Suppressing Colorectal Cancer Stemness and Metastasis through Targeting KRAS/MMP7/CD44 Signaling

Approximately 25% of colorectal cancer (CRC) patients will develop metastatic (m)CRC despite treatment interventions. In this setting, tumor cells are attracted to the epidermal growth factor receptor (EGFR) oncogene. Kirsten rat sarcoma (RAS) 2 viral oncogene homolog (KRAS) mutations were reported to drive CRC by promoting cancer progression in activating Wnt/β-catenin and RAS/extracellular signal-regulated kinase (ERK) pathways. In addition, KRAS is associated with almost 40% of patients who acquire resistance to EGFR inhibitors in mCRC. Multiple studies have demonstrated that cancer stem cells (CSCs) promote tumorigenesis, tumor growth, and resistance to therapy. One of the most common CSC prognostic markers widely reported in CRC is a cluster of differentiation 44 (CD44), which regulates matrix metalloproteinases 7/9 (MMP7/9) to promote tumor progression and metastasis; however, the molecular role of CD44 in CRC is still unclear. In invasive CRC, overexpression of MMP7 was reported in tumor cells compared to normal cells and plays a crucial function in CRC cetuximab and oxaliplatin resistance and distant metastasis. Here, we utilized a bioinformatics analysis and identified overexpression of KRAS/MMP7/CD44 oncogenic signatures in CRC tumor tissues compared to normal tissues. In addition, a high incidence of mutations in KRAS and CD44 were associated with some of the top tumorigenic oncogene's overexpression, which ultimately promoted a poor response to chemotherapy and resistance to some FDA-approved drugs. Based on these findings, we explored a computational approach to drug repurposing of the drug, sulfasalazine, and our in silico molecular docking revealed unique interactions of sulfasalazine with the KRAS/MMP7/CD44 oncogenes, resulting in high binding affinities compared to those of standard inhibitors. Our in vitro analysis demonstrated that sulfasalazine combined with cisplatin reduced cell viability, colony, and sphere formation in CRC cell lines. In addition, sulfasalazine alone and combined with cisplatin suppressed the expression of KRAS/MMP7/CD44 in DLD-1 and HCT116 cell lines. Thus, sulfasalazine is worthy of further investigation as an adjuvant agent for improving chemotherapeutic responses in CRC patients.

Characterization of Cell Cycle-Related Competing Endogenous RNAs Using Robust Rank Aggregation as Prognostic Biomarker in Lung Adenocarcinoma

Lung adenocarcinoma (LUAD), one of the most common pathological subtypes in lung cancer, has been of concern because it is the leading cause of cancer-related deaths. Due to its poor prognosis, to identify a prognostic biomarker, this study performed an integrative analysis to screen curial RNAs and discuss their cross-talks. The messenger RNA (mRNA) profiles were primarily screened using robust rank aggregation (RRA) through several datasets, and these deregulated genes showed important roles in multiple biological pathways, especially for cell cycle and oocyte meiosis. Then, 31 candidate genes were obtained via integrating 12 algorithms, and 16 hub genes (containing homologous genes) were further screened according to the potential prognostic values. These hub genes were used to search their regulators and biological-related microRNAs (miRNAs). In this way, 10 miRNAs were identified as candidate small RNAs associated with LUAD, and then miRNA-related long non-coding RNAs (lncRNAs) were further obtained. In-depth analysis showed that 4 hub mRNAs, 2 miRNAs, and 2 lncRNAs were potential crucial RNAs in the occurrence and development of cancer, and a competing endogenous RNA (ceRNA) network was then constructed. Finally, we identified CCNA2/MKI67/KIF11:miR-30a-5p:VPS9D1-AS1 axis-related cell cycle as a prognostic biomarker, which provided RNA cross-talks among mRNAs and non-coding RNAs (ncRNAs), especially at the multiple isomiR levels that further complicated the coding–non-coding RNA regulatory network. Our findings provide insight into complex cross-talks among diverse RNAs particularly involved in isomiRs, which will enrich our understanding of mRNA–ncRNA interactions in coding–non-coding RNA regulatory networks and their roles in tumorigenesis.

Insights into the Association Between QSER1 and M2 Macrophages and Remarkable Malignancy Characteristics in Hepatocellular Carcinoma

Purpose

Glutamine and serine rich 1 (QSER1), as a DNA methylation modulator, play a crucial role in transforming tumor cells. Previous studies have shown that QSER1 plays a role in regulating the progression of various malignancies and that QSER1 dysfunction is connected with precancerous lesions of hepatocellular carcinoma (HCC) as well as HCC prognosis. However, little is known about the detailed contribution of QSER1 in HCC.

Patients and Methods

Various statistical methods such as Kaplan–Meier method, AUC analysis, GSEA, and immune-infiltration analysis were used to evaluate the relationship between QSER1 expression and clinical features, prognostic factors, and potential functional mechanisms of QSER1.

Results

QSER1 expression was negatively correlated with clinicopathological features (clinical stage, pathological grade, TP53 mutation, lymph node metastasis) and clinical outcome (overall survival versus recurrence). Functional enrichment analysis further suggested that QSER1 is involved in multiple pathways related to DNA replication and tumor immunity. TIMER analysis indicated that high QSER1 expression was significantly associated with higher macrophage infiltration and poorer macrophage-related outcomes. In particular, QSER1 was significantly more associated with M2 macrophages than M1 macrophages.

Conclusion

Overall, elevated QSER1 is a potential prognostic marker for HCC and is associated with immune infiltration in HCC.

Identification of a Novel Theranostic Signature of Metabolic and Immune-Inflammatory Dysregulation in Myocardial Infarction, and the Potential Therapeutic Properties of Ovatodiolide, a Diterpenoid Derivative

Myocardial infarction (MI) is a multifactorial global disease, recognized as one of the leading causes of cardiovascular morbidity and mortality. Timely and correct diagnoses and effective treatments could significantly reduce incidence of complications and improve patient prognoses. In this study, seven unconventional differentially expressed genes (DEGs) (MAN2A2, TNFRSF12A, SPP1, CSNK1D, PLAUR, PFKFB3, and CXCL16, collectively termed the MTSCPPC signature) were identified through integrating DEGs from six MI microarray datasets. The pathological and theranostic roles of the MTSCPPC signature in MI were subsequently analyzed. We evaluated interactions of the MTSCPPC signature with ovatodiolide, a bioactive compound isolated from Anisomeles indica (L.) Kuntze, using in silico molecular docking tools and compared it to specific inhibitors of the members of the MTSCPPC signature. Single-cell transcriptomic analysis of the public databases revealed high expression levels of the MTSCPPC signature in immune cells of adult human hearts during an MI event. The MTSCPPC signature was significantly associated with the cytokine–cytokine receptor interactions, chemokine signaling, immune and inflammatory responses, and metabolic dysregulation in MI. Analysis of a micro (mi)RNA regulatory network of the MTSCPPC signature suggested post-transcriptional activation and the roles of miRNAs in the pathology of MI. Our molecular docking analysis suggested a higher potential for ovatodiolide to target MAN2A2, CSNK1D, and TNFRSF12A. Collectively, the results derived from the present study further advance our understanding of the complex regulatory mechanisms of MI and provide a potential MI theranostic signature with ovatodiolide as a therapeutic candidate.

Genetic Alteration, Prognostic and Immunological Role of Acyl-CoA Synthetase Long-Chain Family Member 4 in a Pan-Cancer Analysis

Acyl-CoA Synthetase long-chain family member 4 (ACSL4) is a member of acyl-CoA synthetase protein long-chain family, which is associated with amino acid synthesis, lipid synthesis and lipid peroxidation dependent iron death. However, the role of ACSL4 in generalized carcinoma remains unclear. We aim to analyze the expression and prognostic value of ACSL4 in pan-cancer, and further explore the correlation between ACSL4 and immune infiltration. Through ONCOMINE, TIMER (Tumor Immune Estimation Resource), GEPIA (Gene expression Profiling Interactive), UALCAN and HPA, ACSL4 expression patterns of in pan-cancer were analyzed. The prognostic value of ACSL4 was analyzed using PrognoScan and Kaplan-Meier Plotter databases. Furthermore, gene variation and epigenetic modification of ACSL4 were analyzed by cBioPortal and GSCA databases. Meanwhile, GEPIA and TIMER databases applied to evaluate the relationship between ACSL4 expression and immune infiltration. These results indicate that ACSL4 expression is down-regulated and associated with prognosis in most tumors. In general, lower ACSL4 expression shows more beneficial prognosis. The most common genetic alteration of ACSL4 is point mutation. ACSL4 is negatively correlated with DNA methylation levels in most cancers. ACSL4 mutations or hypomethylation are associated with poor prognosis. In addition, ACSL4 is positively correlated with immune infiltration in cancers. ACSL4 and immune infiltration are strongly associated with prognosis in BRCA (Breast invasive carcinoma) and SKCM (Skin Cutaneous Melanoma). ACSL4 mutation caused significant changes of immune infiltration in UCEC (Uterine Corpus Endometrial Carcinoma) and SARC (Sarcoma). ACSL4 may be a promising prognostic biomarker for pan-cancer and is closely associated with immune infiltration in the tumor microenvironment.

Development of a CAFs-related gene signature to predict survival and drug response in bladder cancer

As one of important components of tumor microenvironment, CAFs (cancer-associated fibroblasts) play a vital role in the development and metastasis of bladder cancer. The present study aimed to develop a CAFs-related gene signature to predict the prognosis of patients and the response to chemotherapy and immunotherapy based on research of multidatabase. Expression data and clinical information were obtained from TCGA and GEO databases. Different bioinformatic and statistical methods were combined to construct the robust CAFs-related gene signature for prognosis. The model was explored from four aspects: single-cell source, immune infiltration, correlation with cancer-related genes and pathways, and prediction of drug response. After screening, five genes (BNC2, LAMA2, MFAP5, NID1, and OLFML1) related to CAFs were used for constructing the signature to divide patients into high- and low-risk groups. Patients in low-risk group had better prognosis and multidatabase analysis confirmed the predictive value. The five genes were mainly expressed by fibroblasts and involved in regulation of pathways related with glycolysis, hypoxia, and epithelial-mesenchymal transition (EMT). BNC2, LAMA2, and NID1 were strongly associated with drug sensitivity. Moreover, the immunological status was different between high- and low-risk groups. High-risk patients had poor response to chemotherapy or immunotherapy. The CAFs-related gene signature might help to optimize risk stratification and provide a new insight in individual treatment for bladder cancer.

Exploring the potential biomarkers for prognosis of glioblastoma via weighted gene co-expression network analysis

BACKGROUND

Glioblastoma (GBM) is the most common malignant tumor in the central system with a poor prognosis. Due to the complexity of its molecular mechanism, the recurrence rate and mortality rate of GBM patients are still high. Therefore, there is an urgent need to screen GBM biomarkers to prove the therapeutic effect and improve the prognosis.

RESULTS

We extracted data from GBM patients from the Gene Expression Integration Database (GEO), analyzed differentially expressed genes in GEO and identified key modules by weighted gene co-expression network analysis (WGCNA). GSE145128 data was obtained from the GEO database, and the darkturquoise module was determined to be the most relevant to the GBM prognosis by WGCNA (r =  - 0.62, p = 0.01). We performed enrichment analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) to reveal the interaction activity in the selected modules. Then Kaplan-Meier survival curve analysis was used to extract genes closely related to GBM prognosis. We used Kaplan-Meier survival curves to analyze the 139 genes in the darkturquoise module, identified four genes (DARS/GDI2/P4HA2/TRUB1) associated with prognostic GBM. Low expression of DARS/GDI2/TRUB1 and high expression of P4HA2 had a poor prognosis. Finally, we used tumor genome map (TCGA) data, verified the characteristics of hub genes through Co-expression analysis, Drug sensitivity analysis, TIMER database analysis and GSVA analysis. We downloaded the data of GBM from the TCGA database, the results of co-expression analysis showed that DARS/GDI2/P4HA2/TRUB1 could regulate the development of GBM by affecting genes such as CDC73/CDC123/B4GALT1/CUL2. Drug sensitivity analysis showed that genes are involved in many classic Cancer-related pathways including TSC/mTOR, RAS/MAPK.TIMER database analysis showed DARS expression is positively correlated with tumor purity (cor = 0.125, p = 1.07e-02)), P4HA2 expression is negatively correlated with tumor purity (cor =-0.279, p = 6.06e-09). Finally, GSVA analysis found that DARS/GDI2/P4HA2/TRUB1 gene sets are closely related to the occurrence of cancer.

CONCLUSION

We used two public databases to identify four valuable biomarkers for GBM prognosis, namely DARS/GDI2/P4HA2/TRUB1, which have potential clinical application value and can be used as prognostic markers for GBM.

Increased co-expression of MEST and BRCA1 is associated with worse prognosis and immune infiltration in ovarian cancer

OBJECTIVE

The crosstalk between tumor microenvironment (TME) and cancer cells plays a critical role in the occurrence and development of ovarian cancer. Imprinted gene MEST is a tumor-promoting factor that modulates several carcinogenic signaling pathways. This study aimed to investigate the expression pattern of MEST and its association with immune cell infiltration.

METHODS

The transcriptome data of The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database was utilized, and the expression and immune characteristics of MEST were verified by immunohistochemistry of ovarian cancer specimens. Kaplan-Meier Plotter was used to assess the prognostic value in patients with ovarian cancer.

RESULTS

We found that high expression of MEST was associated with diminished immune cell infiltration and worse prognosis of ovarian cancer patients in independent cohorts. There was a positive correlation between MEST and BRCA1 expression. The MEST^highBRCA1^high ovarian cancer group was correlated with lower infiltration of CD4⁺ cells, CD57⁺ cells, CD68⁺ cells and MPO⁺ cells, had worse overall survival (OS) in TCGA (HR = 1.57, p = 0.0004) and GSE27651 (HR = 4.27, p = 0.0002) cohorts, and predicted poor progress free survival (PFS) in GSE9891 (HR = 1.76, p = 0.0098) and GSE15622 (HR = 4.80, p = 0.0121) cohorts. Moreover, the expression of PD-L1 predicted unfavorable OS (HR = 2.48, p = 0.0415) and PFS (HR = 2.36, p = 0.0215) in MEST^lowBRCA1^low ovarian cancer group in GSE9891 cohort.

CONCLUSION

These findings suggest that the co-expression of MEST and BRCA1 may be an ideal combination for predicting the prognosis and response to immunotherapy in patients with ovarian cancer.

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.

A Gene Prognostic Index Associated With Epithelial-Mesenchymal Transition Predicting Biochemical Recurrence and Tumor Chemoresistance for Prostate Cancer

BACKGROUND

We aimed to establish a novel epithelial-mesenchymal transition (EMT)-related gene prognostic index (EMTGPI) associated with biochemical recurrence (BCR) and drug resistance for prostate cancer (PCa).

METHODS

We used Lasso and Cox regression analysis to establish the EMTGPI. All analyses were conducted with R version 3.6.3 and its suitable packages.

RESULTS

We established the EMTGPI based on SFRP4 and SPP1. Patients in high-risk group had 2.23 times of BCR risk than those in low-risk group (p = 0.003), as well as 2.36 times of metastasis risk (p = 0.053). In external validation, we detected similar diagnostic efficacy and prognostic value in terms of BCR free survival. For drug resistance, we observe moderately diagnostic accuracy of EMTGPI score (AUC: 0.804). We found that PDCD1LG2 (p = 0.04) and CD96 (p = 0.01) expressed higher in BCR patients compared with their counterpart. For TME analysis, we detected that CD8+ T cells and M1 macrophages expressed higher in BCR group. Moreover, stromal score (p = 0.003), immune score (p = 0.01), and estimate score (p = 0.003) were higher in BCR patients. We found that EMTGPI was significantly related to HAVCR2 (r: 0.34), CD96 (r: 0.26), CD47 (r: 0.22), KIR3DL1 (r: -0.21), KLRD1 (r: -0.21), and CD2 (r: 0.21). In addition, we observed that EMTGPI was significantly associated with M1 macrophages (r: 0.6), M2 macrophages (r: -0.33), monocytes (r: -0.18), neutrophils (r: -0.43), CD8+ T cells (r: 0.13), and dendritic cells (r: 0.37). PHA-793887 was the common drug sensitive to SPP1 and SFRP4, and PC3 and DU145 were the common PCa-related cell lines of SPP1, SFRP4, and PHA-793887.

CONCLUSIONS

We concluded that the EMTGPI score based on SFRP4 and SPP1 could be used to predict BCR for PCa patients. We confirmed the impact of immune evasion on the BCR process of PCa.

Comprehensive Analyses of the Expression, Genetic Alteration, Prognosis Significance, and Interaction Networks of m6A Regulators Across Human Cancers

Accumulating lines of evidence indicate that the deregulation of m⁶A is involved in various cancer types. The m⁶A RNA methylation is modulated by m⁶A methyltransferases, demethylases, and reader proteins. Although the aberrant expression of m⁶A RNA methylation contributes to the development and progression of multiple cancer types, the roles of m⁶A regulators across numerous types of cancers remain largely unknown. Here, we comprehensively investigated the expression, genetic alteration, and prognosis significance of 20 commonly studied m⁶A regulators across diverse cancer types using TCGA datasets via bioinformatic analyses. The results revealed that the m⁶A regulators exhibited widespread dysregulation, genetic alteration, and the modulation of oncogenic pathways across TCGA cancer types. In addition, most of the m⁶A regulators were closely relevant with significant prognosis in many cancer types. Furthermore, we also constructed the protein–protein interacting network of the 20 m⁶A regulators, and a more complex interacting regulatory network including m⁶A regulators and their corresponding interacting factors. Besides, the networks between m⁶A regulators and their upstream regulators such as miRNAs or transcriptional factors were further constructed in this study. Finally, the possible chemicals targeting each m⁶A regulator were obtained by bioinformatics analysis and the m⁶A regulators–potential drugs network was further constructed. Taken together, the comprehensive analyses of m⁶A regulators might provide novel insights into the m⁶A regulators’ roles across cancer types and shed light on their potential molecular mechanisms as well as help develop new therapy approaches for cancers.

Immune Signature-Based Risk Stratification and Prediction of Immunotherapy Efficacy for Bladder Urothelial Carcinoma

Immune-related genes (IRGs) are closely related to tumor progression and the immune microenvironment. Few studies have investigated the effect of tumor immune microenvironment on the survival and response to immune checkpoint inhibitors of patients with bladder urothelial carcinoma (BLCA). We constructed two IRG-related prognostic signatures based on gene–immune interaction for predicting risk stratification and immunotherapeutic responses. We also verified their predictive ability on internal and overall data sets. Patients with BLCA were divided into high- and low-risk groups. The high-risk group had poor survival, enriched innate immune-related cell subtypes, low tumor mutation burden, and poor response to anti-PD-L1 therapy. Our prognostic signatures can be used as reliable prognostic biomarkers, which may be helpful to screen the people who will benefit from immunotherapy and guide the clinical decision-making of patients with BLCA.

The Potential Mechanism of Cancer Patients Appearing More Vulnerable to SARS-CoV-2 and Poor Outcomes: A Pan-Cancer Bioinformatics Analysis

To explore the potential mechanism of cancer patients appearing more vulnerable to SARS-CoV-2 infection and poor COVID-19 outcomes, we conducted an integrative bioinformatics analysis for SARS-CoV-2-required genes and host genes and variants related to SARS-CoV-2 susceptibility and COVID-19 severity. BLCA, HNSC, KIRC, KIRP, LGG, PCPG, PRAD, TGCT, and THCA patients carrying rs10774671-A (OAS1) genotype may be more likely to have poor COVID-19 outcomes relative to those who carry rs10774671-G, because individuals carrying rs10774671-A will have lower expression of OAS1, which serves as a protective factor against SARS-CoV-2 processes and poor COVID-19 outcomes. SARS-CoV-2-required genes were correlated with TME, immune infiltration, overall survival, and anti-cancer drug sensitivity. CHOL patients may have a higher risk of SARS-CoV-2 infection than healthy subjects. SARS-CoV-2-induced ACE2 and NPC1 elevation may have a negative influence on the immune responses of LUSC and CD8+T infiltration of LUAD, and negatively affect the sensitivity of anti-lung cancer drugs. LUSC and LUAD patients may have a varying degree of adverse outcomes if they are infected with SARS-CoV-2. miR-760 may target and inhibit ACE2 expression. Cancer patients appearing vulnerable to SARS-CoV-2 infection and having poor COVID-19 outcomes may be partly due to host genetic factors and dysregulation of SARS-CoV-2-required genes. OAS1, ACE2, and miR-760 could serve as the treatment and intervention targets for SARS-CoV-2.

Comprehensive analysis of expression profile and prognostic significance of interferon regulatory factors in pancreatic cancer

BACKGROUND

Pancreatic cancer (PC) is a highly lethal disease and an increasing cause of cancer-associated mortality worldwide. Interferon regulatory factors (IRFs) play vital roles in immune response and tumor cellular biological processes. However, the specific functions of IRFs in PC and tumor immune response are far from systematically clarified. This study aimed to explorer the expression profile, prognostic significance, and biological function of IRFs in PC.

RESULTS

We observed that the levels of IRF2, 6, 7, 8, and 9 were elevated in tumor compared to normal tissues in PC. IRF7 expression was significantly associated with patients' pathology stage in PC. PC patients with high IRF2, low IRF3, and high IRF6 levels had significantly poorer overall survival. High mRNA expression, amplification and, deep deletion were the three most common types of genetic alterations of IRFs in PC. Low expression of IRF2, 4, 5, and 8 was resistant to most of the drugs or small molecules from Genomics of Drug Sensitivity in Cancer. Moreover, IRFs were positively correlated with the abundance of tumor infiltrating immune cells in PC, including B cells, CD8+ T cells, CD4+ T cells, macrophages, Neutrophil, and Dendritic cells. Functional analysis indicated that IRFs were involved in T cell receptor signaling pathway, immune response, and Toll-like receptor signaling pathway.

CONCLUSIONS

Our results indicated that certain IRFs could serve as potential therapeutic targets and prognostic biomarkers for PC patients. Further basic and clinical studies are needed to validate our findings and generalize the clinical application of IRFs in PC.

Network models of prostate cancer immune microenvironments identify ROMO1 as heterogeneity and prognostic marker

Prostate cancer (PCa) is the fifth leading cause of death from cancer in men worldwide. Its treatment remains challenging due to the heterogeneity of the tumor, mainly because of the lack of effective and targeted prognostic markers at the system biology level. First, the data were retrieved from TCGA dataset, and valid samples were obtained by consistent clustering and principal component analysis; next, key genes were analyzed for prognosis of PCa using WGCNA, MEGENA, and LASSO Cox regression model analysis, while key genes were screened based on disease-free survival significance. Finally, TIMER data were selected to explore the relationship between genes and tumor immune infiltration, and GSCAlite was used to explore the small-molecule targeted drugs that act with them. Here, we used tumor subtype analysis and an energetic co-expression network algorithm of WGCNA and MEGENA to identify a signal dominated by the ROMO1 to predict PCa prognosis. Cox regression analysis of ROMO1 was an independent influence, and the prognostic value of this biomarker was validated in the training set, the validated data itself, and external data, respectively. This biomarker correlates with tumor immune infiltration and has a high degree of infiltration, poor prognosis, and strong correlation with CD8+T cells. Gene function annotation and other analyses also implied a potential molecular mechanism for ROMO1. In conclusion, we putative ROMO1 as a portal key prognostic gene for the diagnosis and prognosis of PCa, which provides new insights into the diagnosis and treatment of PCa.

Epigenetic therapy combination of UNC0638 and CI-994 suppresses breast cancer via epigenetic remodeling of BIRC5 and GADD45A

BACKGROUND

There is currently a growing interest in the roles of epigenetic mechanisms in the diagnosis, prognosis, and therapies associated with precision oncology for breast cancer (BC). This study aimed to demonstrate the clinical significance of euchromatic histone lysine methyltransferase 2 (EHMT2), histone deacetylase 1 (HDAC1) and HDAC2 in BC, to evaluate the antitumor effectiveness of a combination of the selective inhibitors UNC0638 and CI-994 (U+C), and to clarify the underlying mechanisms.

METHODS

Multi-omic analysis was used to study the clinical significance of the biomarkers of interest. The effects of U+C treatment were evaluated by detecting cell viability, cell cycle, apoptosis, and representative gene expressions. RNA-Seq and Gene Set Enrichment Analysis (GSEA) were employed to identify over-represented genes associated with the treatment. Chromatin immunoprecipitation and qPCR (ChIP-qPCR) assay were applied to verify epigenetic profiling on the identified promoters.

RESULTS

The significance of elevated expressions of EHMT2, HDAC1, and HDAC2 in tumor tissue and BC basal-like subtype in predicting a poor prognosis was noted. The U+C combined treatment showed an enhanced suppressive effect as compared to single agent treatment, perturbed the cell cycle, induced apoptosis, reduced expressions of the genes representing anti-apoptosis, stemness, drug resistance and basal-like state, while increasing luminal-like state genes. In addition, the combined U+C treatment suppressed xenograft tumor growth. The epigenetic reprogramming of histones was identified in the down-regulated BIRC5 and upregulated GADD45A.

CONCLUSION

These findings demonstrate that selectively targeting EHMT2, HDAC1, and HDAC2 by concurrent U+C treatment suppresses BC tumor progression via epigenetic remodeling of BIRC5 and GADD45A.

Endometrial polyps are non-neoplastic but harbor epithelial mutations in endometrial cancer drivers at low allelic frequencies

Endometrial polyps (EMPs) are common exophytic masses associated with abnormal uterine bleeding and infertility. Unlike normal endometrium, which is cyclically shed, EMPs persist over ovulatory cycles and after the menopause. Despite their usual classification as benign entities, EMPs are paradoxically associated with endometrial carcinomas of diverse histologic subtypes, which frequently arise within EMPs. The etiology and potential origins of EMPs as clonally-derived neoplasms are uncertain, but previous investigations suggested that EMPs are neoplasms of stromal origin driven by recurring chromosomal rearrangements. To better define benign EMPs at the molecular genetic level, we analyzed individual EMPs from 31 women who underwent hysterectomy for benign indications. The 31 EMPs were subjected to comprehensive genomic profiling by exome sequencing of a large panel of tumor-related genes including oncogenes, tumor suppressors, and chromosomal translocation partners. There were no recurring chromosomal rearrangements, and copy-number analyses did not reveal evidence of significant chromosome-level events. Surprisingly, there was a high incidence of single nucleotide variants corresponding to classic oncogenic drivers (i.e., definitive cancer drivers). The spectrum of known oncogenic driver events matched that of endometrial cancers more closely than any other common cancer. Further analyses including laser-capture microdissection showed that these mutations were present in the epithelial compartment at low allelic frequencies. These results establish a link between EMPs and the acquisition of endometrial cancer driver mutations. Based on these findings, we propose a model where the association between EMPs and endometrial cancer is explained by the age-related accumulation of endometrial cancer drivers in a protected environment that-unlike normal endometrium-is not subject to cyclical shedding.

Pyroptosis regulators exert crucial functions in prognosis, progression and immune microenvironment of pancreatic adenocarcinoma: a bioinformatic and in vitro research

Pyroptosis is an inflammatory programmed cell death, showing potentials to be a novel anti-cancer approach. However, the roles of pyroptosis-related (PR) genes (PRGs) in pancreatic adenocarcinoma (PAAD) remain elusive. In the present study, we constructed a novel PR risk signature through the lasso regression analysis. The risk signature was greatly conducive to PAAD prognostic assessment. PR risk score was identified as an independent prognostic factor and could distinguish the prognostic differences of most clinical subgroups. Meanwhile, it could improve the traditional prognostic models based on TNM-staging. Next, its prognostic value was also tested in five validation cohorts. Using CIBERSORT, ESTIMATE, and ssGSEA algorithms, the effects of PR risk signature on tumor immune microenvironment (TIM) were explored. High PR risk suppressed antitumor immune through decreasing the infiltrating levels of CD8 T and NK cells. The genomic information and histological expression of risk PRGs were uncovered by USCA and HPA databases. Somatic mutation, methylation alteration, and homozygous CNV of eight PRGs barely occurred in PAAD samples. As for therapeutic correlation, PR risk score may not predict the efficacy of PD-1/L1 inhibitors and was weakly associated with multiple drug susceptibilities. Finally, the biofunctions of toll like receptor 3 (TLR3) in pancreatic cancer (PC) cells were investigated through qPCR, MTT, colony formation, and Transwell assays. Overexpression of TLR3 could promote the proliferation, migration, and invasion of PC cells. In conclusion, PRGs play crucial roles in prognosis, progression, and immune microenvironment of PAAD. TLR3 is expected to be a promising therapeutic target.

A comprehensive multi-omics analysis reveals molecular features associated with cancer via RNA cross-talks in the Notch signaling pathway

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Many Notch genes are identified as cancer-associated genes with an important role in tumorigenesis.

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Dynamic expression patterns are associated with the Notch activity that are largely regulated by multiple ncRNAs.

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Cross-talks among diverse RNAs are crucial in cancers via ceRNA network.

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The Notch pathway shows a robust prognostic ability via integrating multi-omics features as well as their targets.

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The Notch pathway is also correlated with immune infiltration and maybe available cancer treatment drug targets.

The Notch signaling has an important role in multiple cellular processes and is related to carcinogenic process. To understand the potential molecular features of the crucial Notch pathway, a comprehensive multi-omics analysis is performed to explore its contributions in cancer, mainly including analysis of somatic mutation landscape, pan-cancer expression, ncRNA regulation and potential prognostic power. The screened 22 Notch core genes are relative stable in DNA variation. Dynamic expression patterns are associated with the Notch activity, which are mainly regulated by multiple ncRNAs via interactions of ncRNA:mRNA and ceRNA networks. The Notch pathway shows a potential prognostic ability through integrating multi-omics features as well as their targets, and it is correlated with immune infiltration and maybe available drug targets, implying the potential role in individualized treatment. Collectively, all of these findings contribute to exploring crucial role of the key pathway in cancer pathophysiology and gaining mechanistic insights into cross-talks among RNAs and biological pathways, which indicates the possible application of the well-conserved Notch signaling pathway in precision medicine.