Tumor purity as a prognosis and immunotherapy relevant feature in gastric cancer

Clinical translation of nanomedicine with integrated digital medicine and machine learning interventions

Nanomaterials based therapeutics transform the ways of disease prevention, diagnosis and treatment with increasing sophistications in nanotechnology at a breakneck pace, but very few could reach to the clinic due to inconsistencies in preclinical studies followed by regulatory hinderances. To tackle this, integrating the nanomedicine discovery with digital medicine provide technologies as tools of specific biological activity measurement. Hence, overcome the redundancies in nanomedicine discovery by the on-site data acquisition and analytics through integrating intelligent sensors and artificial intelligence (AI) or machine learning (ML). Integrated AI/ML wearable sensors directly gather clinically relevant biochemical information from the subject's body and process data for physicians to make right clinical decision(s) in a time and cost-effective way. This review summarizes insights and recommend the infusion of actionable big data computation enabled sensors in burgeoning field of nanomedicine at academia, research institutes, and pharmaceutical industries, with a potential of clinical translation. Furthermore, many blind spots are present in modern clinically relevant computation, one of which could prevent ML-guided low-cost new nanomedicine development from being successfully translated into the clinic was also discussed.

GJA4 expressed on cancer associated fibroblasts (CAFs)-A 'promoter' of the mesenchymal phenotype

BACKGROUND

Colorectal cancer (CRC) is the third most common cancer worldwide. Connexin is a transmembrane protein involved in gap junctions (GJs) formation. Our previous study found that connexin 37 (Cx37), encoded by gap junction protein alpha 4 (GJA4), expressed on fibroblasts acts as a promoter of CRC and is closely related to epithelial-mesenchymal transition (EMT) and tumor immune microenvironment. However, to date, the mechanism concerning the malignancy of GJA4 in tumor stroma has not been studied.

METHODS

Hematoxylin-eosin (HE) and immunohistochemical (IHC) staining were used to validate the expression and localization of GJA4. Using single-cell analysis, enrichment analysis, spatial transcriptomics, immunofluorescence staining (IF), Sirius red staining, wound healing and transwell assays, western blotting (WB), Cell Counting Kit-8 (CCK8) assay and in vivo experiments, we investigated the possible mechanisms of GJA4 in promoting CRC.

RESULTS

We discovered that in CRC, GJA4 on fibroblasts is involved in promoting fibroblast activation and promoting EMT through a fibroblast-dependent pathway. Furthermore, GJA4 may act synergistically with M2 macrophages to limit T cell infiltration by stimulating the formation of an immune-excluded desmoplasic barrier. Finally, we found a significantly correlation between GJA4 and pathological staging (P < 0.0001) or D2 dimer (R = 0.03, P < 0.05).

CONCLUSION

We have identified GJA4 expressed on fibroblasts is actually a promoter of the tumor mesenchymal phenotype. Our findings suggest that the interaction between GJA4+ fibroblasts and M2 macrophages may be an effective target for enhancing tumor immunotherapy.

Tumor purity-related genes for predicting the prognosis and drug sensitivity of DLBCL patients

Background

Diffuse large B-cell lymphoma (DLBCL) is the predominant type of malignant B-cell lymphoma. Although various treatments have been developed, the limited efficacy calls for more and further exploration of its characteristics.

Methods

Datasets from the Gene Expression Omnibus (GEO) database were used for identifying the tumor purity of DLBCL. Survival analysis was employed for analyzing the prognosis of DLBCL patients. Immunohistochemistry was conducted to detect the important factors that influenced the prognosis. Drug-sensitive prediction was performed to evaluate the value of the model.

Results

VCAN, CD3G, and C1QB were identified as three key genes that impacted the outcome of DLBCL patients both in GEO datasets and samples from our center. Among them, VCAN and CD3G+ T cells were correlated with favorable prognosis, and C1QB was correlated with worse prognosis. The ratio of CD68 + macrophages and CD8 + T cells was associated with better prognosis. In addition, CD3G+T cells ratio was significantly correlated with CD68 + macrophages, CD4 + T cells, and CD8 +T cells ratio, indicating it could play an important role in the anti-tumor immunity in DLBCL. The riskScore model constructed based on the RNASeq data of VCAN, C1QB, and CD3G work well in predicting the prognosis and drug sensitivity.

Conclusions

VCAN, CD3G, and C1QB were three key genes that influenced the tumor purity of DLBCL, and could also exert certain impact on drug sensitivity and prognosis of DLBCL patients.

Funding

This work is supported by the Shenzhen High-level Hospital Construction Fund and CAMS Innovation Fund for Medical Sciences (CIFMS) (2022-I2M-C&T-B-062).

A disulfidptosis-related lncRNAs cluster to forecast the prognosis and immune landscapes of ovarian cancer

Objective

Disulfidptosis is a newly recognized form of regulated cell death that has been linked to cancer progression and prognosis. Despite this association, the prognostic significance, immunological characteristics and treatment response of disulfidptosis-related lncRNAs (DRLs) in ovarian cancer have not yet been elucidated.

Methods

The lncRNA data and clinical information for ovarian cancer and normal samples were obtained from the UCSC XENA. Differential expression analysis and Pearson analysis were utilized to identify core DRLs, followed by LASSO algorithm. Random Survival Forest was used to construct a prognostic model. The relationships between risk scores, RNA methylation, immune cell infiltration, mutation, responses to immunotherapy and drug sensitivity analysis were further examined. Additionally, qRT-PCR experiments were conducted to validate the expression of the core DRLs in human ovarian cancer cells and normal ovarian cells and the scRNA-seq data of the core DRLs were obtained from the GEO dataset, available in the TISCH database.

Results

A total of 8 core DRLs were obtained to construct a prognostic model for ovarian cancer, categorizing all patients into low-risk and high-risk groups using an optimal cutoff value. The AUC values for 1-year, 3-year and 5-year OS in the TCGA cohort were 0.785, 0.810 and 0.863 respectively, proving a strong predictive capability of the model. The model revealed the high-risk group patients exhibited lower overall survival rates, higher TIDE scores and lower TMB levels compared to the low-risk group. Variations in immune cell infiltration and responses to therapeutic drugs were observed between the high-risk and low-risk groups. Besides, our study verified the correlations between the DRLs and RNA methylation. Additionally, qRT-PCR experiments and single-cell RNA sequencing data analysis were conducted to confirm the significance of the core DRLs at both cellular and scRNA-seq levels.

Conclusion

We constructed a reliable and novel prognostic model with a DRLs cluster for ovarian cancer, providing a foundation for further researches in the management of this disease.

Multi-omics analysis of macrophage-associated receptor and ligand reveals a strong prognostic signature and subtypes in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a significant contributor to morbidity and mortality worldwide. The interaction between receptors and ligands is the primary mode of intercellular signaling and plays a vital role in the progression of HCC. This study aimed to identify the macrophage-related receptor ligand marker genes associated with HCC and further explored the molecular immune mechanisms attributed to altered biomarkers. Single-cell RNA sequencing data containing primary and recurrent samples were downloaded from the China National GeneBank. Cell types were first identified to explore differences between immune cells from different sample sources. CellChat analysis was used to infer and analyze intercellular communication networks quantitatively. Three molecular subtypes were constructed based on the screened twenty macrophage-associated receptor ligand genes. Bulk RNA-Seq data were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases. After the screening, the minor absolute shrinkage and selection operator (LASSO) regression model was employed to identify key markers. After collecting peripheral blood and clinical information from patients, an enzyme-linked immunosorbent assay (ELISA) was used to detect the correlation between key markers and IL-10, one of the macrophage markers. After developing a new HCC risk adjustment model and conducting analysis, it was found that there were significant differences in immune status and gene mutations between the high-risk and low-risk groups of patients based on macrophage-associated receptor and ligand genes. This study identified SPP1, ANGPT2, and NCL as key biological targets for HCC. The drug-gene interaction network analysis identified wortmannin, ribavirin, and tarnafloxin as potential therapeutic drugs for the three key markers. In a clinical cohort study, patients with immune checkpoint inhibitor (ICI) resistance had significantly higher expression levels of OPN, ANGPT2, NCL, and IL-10 than patients with ICI-responsiveness. These three key markers were positively correlated with the expression level of IL-10. The signature based on macrophage-associated receptor and ligand genes can accurately predict the prognosis of patients with HCC and the sensitivity to immunotherapy. These results may help guide the development of targeted prevention and personalized treatment of HCC.

Defining three ferroptosis-based molecular subtypes and developing a prognostic risk model for high-grade serous ovarian cancer

BACKGROUND

As a newly defined regulated cell death, ferroptosis is a potential biomarker in ovarian cancer (OV). However, its underlying mechanism in tumor microenvironment (TME) and clinical prediction significance in OV remained to be elucidated.

METHODS

The transcriptome data of high-grade serous OV from The Cancer Genome Atlas (TCGA) database were downloaded. Molecular subtypes were classified based on ferroptosis-correlated genes from the FerrDb database by performing consensus clustering analysis. The associations between the subtypes and clinicopathologic characteristics, mutation, regulatory pathways and immune landscape were assessed. A ferroptosis-related prognostic model was constructed and verified using International Cancer Genome Consortium (ICGC) cohort and GSE70769.

RESULTS

Three molecular subtypes of OV were defined. Patients in subtype C3 tended to have the most favorable prognosis, while subtype C1 showing more mesenchymal cells, increased immune infiltration of Macrophages_M2, lower tumor purity, and epithelial-to-mesenchymal transition (EMT) features had the poorest prognosis. A ferroptosis-related risk model was constructed using 8 genes (PDP1, FCGBP, EPHA4, GAS1, SLC7A11, BLOC1S1, SPOCK2, and CXCL9) and manifested a strong prediction performance. High-risk patients had enriched EMT pathways, more Macrophages_M2, less plasma cells and CD8 cell infiltration, greater tendency of immune escape and worse prognosis. The risk score has negatively correlated relation with LAG3, TIGIT, CTLA4, IDO1, CD27, ICOS, and IL2RB but positively correlated with PVR, CD276, and CD28. Moreover, low-risk patients were more sensitive to Cisplatin and Gefitinib, Gemcitabine.

CONCLUSIONS

Our results could improve the understanding of ferroptosis in OV, providing promising insights for the clinical targeted therapy for the cancer.

An inflammation-related subtype classification for analyzing tumor microenvironment and clinical prognosis in colorectal cancer

Background

The inflammatory response plays an essential role in the tumor microenvironment (TME) of colorectal cancer (CRC) by modulating tumor growth, progression, and response to therapy through the recruitment of immune cells, production of cytokines, and activation of signaling pathways. However, the molecular subtypes and risk score prognostic model based on inflammatory response remain to be further explored.

Methods

Inflammation-related genes were collected from the molecular signature database and molecular subtypes were identified using nonnegative matrix factorization based on the TCGA cohort. We compared the clinicopathological features, immune infiltration, somatic mutation profile, survival prognosis, and drug sensitivity between the subtypes. The risk score model was developed using LASSO and multivariate Cox regression in the TCGA cohort. The above results were independently validated in the GEO cohort. Moreover, we explored the biological functions of the hub gene, receptor interacting protein kinase 2 (RIPK2), leveraging proteomics data, in vivo, and in vitro experiments.

Results

We identified two inflammation-related subtypes (inflammation-low and inflammation-high) and have excellent internal consistency and stability. Inflammation-high subtype showed higher immune cell infiltration and increased sensitivity to common chemotherapeutic drugs, while inflammation-low subtype may be more suitable for immunotherapy. Besides, the two subtypes differ significantly in pathway enrichment and biological functions. In addition, the 11-gene signature prognostic model constructed from inflammation-related genes showed strong prognostic assessment power and could serve as a novel prognostic marker to predict the survival of CRC patients. Finally, RIPK2 plays a crucial role in promoting malignant proliferation of CRC cell validated by experiment.

Conclusions

This study provides new insights into the heterogeneity of CRC and provides novel opportunities for treatment development and clinical decision making.

Integrated analysis of single-cell and bulk RNA-sequencing reveals a novel signature based on NK cell marker genes to predict prognosis and immunotherapy response in gastric cancer

Natural killer (NK) cells play essential roles in the tumor development, diagnosis, and prognosis of tumors. In this study, we aimed to establish a reliable signature based on marker genes in NK cells, thus providing a new perspective for assessing immunotherapy and the prognosis of patients with gastric cancer (GC). We analyzed a total of 1560 samples retrieved from the public database. We performed a comprehensive analysis of single-cell RNA-sequencing (scRNA-seq) data of gastric cancer and identified 377 marker genes for NK cells. By performing Cox regression analysis, we established a 12-gene NK cell-associated signature (NKCAS) for the Cancer Genome Atlas (TCGA) cohort, that assigned GC patients into a low-risk group (LRG) or a high-risk group (HRG). In the TCGA cohort, the areas under curve (AUC) value were 0.73, 0.81, and 0.80 at 1, 3, and 5 years. External validation of the predictive ability for the signature was then validated in the Gene Expression Omnibus (GEO) cohorts (GSE84437). The expression levels of signature genes were measured and validated in GC cell lines by real-time PCR. Moreover, NKCAS was identified as an independent prognostic factor by multivariate analysis. We combined this with a variety of clinicopathological characteristics (age, M stage, and tumor grade) to construct a nomogram to predict the survival outcomes of patients. Moreover, the LRG showed higher immune cell infiltration, especially CD8+ T cells and NK cells. The risk score was negatively associated with inflammatory activities. Importantly, analysis of the independent immunotherapy cohort showed that the LRG had a better prognosis and immunotherapy response when compared with the HRG. The identification of NK cell marker genes in this study suggests potential therapeutic targets. Additionally, the developed predictive signatures and nomograms may aid in the clinical management of GC.

The prognostic biomarker TPGS2 is correlated with immune infiltrates in pan-cancer: a bioinformatics analysis

Background

Tubulin polyglutamylase complex subunit 2 (TPGS2) is an element of the neuronal polyglutamylase complex that plays a role in the post-translational addition of glutamate residues to C-terminal tubulin tails. Recent research has shown that TPGS2 is associated with some tumors, but the roles of TPGS2 in tumor immunity remain unclear.

Methods

The research data were mainly sourced from The Cancer Genome Atlas. The data were analyzed to identify potential correlations between TPGS2 expression and survival, gene alterations, the tumor mutational burden (TMB), microsatellite instability (MSI), immune infiltration, and various immune-related genes across various cancers. The Wilcoxon rank-sum test was used to identify the significance. A log-rank test and univariate Cox regression analysis were performed to assess the survival state of the patients. Spearman's correlation coefficients were used to show the correlations.

Results

TPGS2 exhibited abnormal expression patterns in most types of cancers, and has promising prognostic potential in adrenocortical carcinoma and liver hepatocellular carcinoma. Further, TPGS2 expression was significantly correlated with molecular and immune subtypes. Moreover, the single-cell analyses showed that the expression of TPGS2 was associated with the cell cycle, metastasis, invasion, inflammation, and DNA damage. In addition, the immune cell infiltration analysis and gene-set enrichment analysis demonstrated that a variety of immune cells and immune processes were associated with TPGS2 expression in various cancers. Further, immune regulators, including immunoinhibitors, immunostimulators, the major histocompatibility complex, chemokines, and chemokine receptors, were correlated with TPGS2 expression in different cancer types. Finally, the TMB and MSI, which have been identified as powerful predictors of immunotherapy, were shown to be correlated with the expression of TPGS2 across human cancers.

Conclusions

TPGS2 is aberrantly expressed in most cancer tissues and might be associated with immune cell infiltration in the tumor microenvironment. TPGS2 could serve not only as a biomarker for predicting clinical outcomes, but also as a promising biomarker for evaluating and developing new approaches to immunotherapy in many types of cancers, especially colon adenocarcinoma and stomach adenocarcinoma.

Bioinformatics analysis and clinical significance of NRP-1 in triple-negative breast cancer

Purpose

This study aimed to investigate the diagnostic and prognostic values of neuropilin-1 (NRP-1) in triple-negative breast cancer (TNBC) and analyze its immune function in the tumor microenvironment.

Methods

Based on The Cancer Genome Atlas (TCGA), Gene Expression Omnibus, Genotype Tissue Expression, Immune Cell Abundance Identifier (ImmuCellAI), Reactome, and Genomics of Drug Sensitivity in Cancer databases, the cancer tissues from 50 patients with TNBC and corresponding adjacent noncancerous tissues from 10 patients (tissue microarrays were purchased from Shanghai Xinchao Biotechnology Co., Ltd.) were collected for validation. Bioinformatics combined with immunohistochemistry was used to analyze the relationship among NRP-1 expression, prognosis, tumor immune cell infiltration, immune genes, and drug resistance so as to investigate the role of NRP-1 in the development of TNBC.

Results

A significant difference in NRP-1 gene expression was found between the cancerous and noncancerous tissues (p-value < 0.05); NRP-1 expression was high in carcinoma. No significant correlation was found between NRP-1 protein expression levels and each stage in the TCGA database. Prognostic expression survival analysis showed that the survival probability of patients with high NRP-1 expression was significantly lower than that of patients with low NRP-1 expression (p-value < 0.05), suggesting that the gene might be a pro-oncogene. The data from 50 clinical samples also confirmed that the NRP-1 expression was significantly higher in triple-negative breast cancer (TNBC) tissues than in adjacent noncancerous tissues. The NRP-1 expression significantly correlated with the tumor diameter and pathological grade (p-value < 0.05), but not with age, stage, and ki67 (p-value > 0.05). The Kaplan-Meier survival curves suggested that the median overall survival was significantly shorter in patients with high NRP-1 expression than in those with low NRP-1 expression (13.6 months vs 15.2 months, p-value < 0.05). The 300 genes most significantly positively associated with this gene were selected for Gene Ontology (including Biological Process, Molecular Function, and Cellular Component groups) and Kyoto Encyclopedia of Genes and Genomics enrichment analysis. The findings showed that NRP-1 was involved in immune regulation in TNBC. In addition, the NRP-1 expression in TNBC positively correlated with a variety of immune cells and checkpoints.

Conclusion

NRP-1 can be used as a potential biomarker and therapeutic target in TNBC.

Identification and validation of shared gene signature of kidney renal clear cell carcinoma and COVID-19

Background

COVID-19 is a severe infectious disease caused by the SARS-CoV-2 virus, and previous studies have shown that patients with kidney renal clear cell carcinoma (KIRC) are more susceptible to SARS-CoV-2 infection than the general population. Nevertheless, their co-pathogenesis remains incompletely elucidated.

Methods

We obtained shared genes between these two diseases based on public datasets, constructed a prognostic risk model consisting of hub genes, and validated the accuracy of the model using internal and external validation sets. We further analyzed the immune landscape of the prognostic risk model, investigated the biological functions of the hub genes, and detected their expression in renal cell carcinoma cells using qPCR. Finally, we searched the candidate drugs associated with hub gene-related targets from DSigDB and CellMiner databases.

Results

We obtained 156 shared genes between KIRC and COVID-19 and constructed a prognostic risk model consisting of four hub genes. Both shared genes and hub genes were highly enriched in immune-related functions and pathways. Hub genes were significantly overexpressed in COVID-19 and KIRC. ROC curves, nomograms, etc., showed the reliability and robustness of the risk model, which was validated in both internal and external datasets. Moreover, patients in the high-risk group showed a higher proportion of immune cells, higher expression of immune checkpoint genes, and more active immune-related functions. Finally, we identified promising drugs for COVID-19 and KIRC, such as etoposide, fulvestrant, and topotecan.

Conclusion

This study identified and validated four shared genes for KIRC and COVID-19. These genes are associated with immune functions and may serve as potential prognostic biomarkers for KIRC. The shared pathways and genes may provide new insights for further mechanistic research and treatment of comorbidities.

A prospective phase II single-arm study and predictive factor analysis of irinotecan as third-line treatment in patients with metastatic gastric cancer

Background

Currently, there is no recommended standard third-line chemotherapy for metastatic gastric cancer.

Objectives

In this study, we aimed to evaluate irinotecan's efficacy and safety in treating metastatic gastric cancer after the failure of first- and second-line chemotherapy.

Design

Prospective single-arm, two-center, phase II trial.

Methods

Patients were aged 18-70 years, with histologically confirmed gastric adenocarcinoma and an Eastern Cooperative Oncology Group performance status of 0-1, progressed during or within 3 months following the last administration of second-line chemotherapy and had no other severe hematologic, cardiac, pulmonary, hepatic, or renal functional abnormalities or immunodeficiency diseases. Eligible patients received 28-day cycles of irinotecan (180 mg/m2 intravenously, days 1 and 15) and were assessed according to the RECIST 1.1 criteria every two cycles. Patients who discontinued treatment for any reason were followed up every 2 months until death. The primary endpoint was overall survival (OS), and the secondary endpoints were progression-free survival (PFS), objective response rate (ORR), disease control rate (DCR), and toxicity.

Results

A total of 98 eligible patients were enrolled in this study. In the intention-to-treat population, the median OS was 7.17 months, the median PFS was 3.47 months, and the ORR and DCR were 4.08% and 47.96%, respectively. In the per-protocol population, the median OS was 7.77 months, the median PFS was 3.47 months, and the ORR and DCR were 4.82% and 50.60%, respectively. The incidence of grade 3 or 4 hematological and non-hematological toxicities was 19.4%, and none of the patients died owing to adverse events. Cox regression analysis revealed neutropenia and baseline thrombocyte levels were independently correlated with PFS and OS.

Conclusion

Irinotecan monotherapy is an efficient, well-tolerated, and economical third-line treatment for patients with metastatic gastric cancer as a third-line treatment.

Trial registration

ClinicalTrials.gov identifier: NCT02662959.

Systematic analysis of the prognostic value and immunological function of LTBR in human cancer

Lymphotoxin beta receptor (LTBR) is a positive T cell proliferation regulator gene. It is closely associated with the tumor immune microenvironment. However, its role in cancer and immunotherapy is unclear. Firstly, the expression level and prognostic value of LTBR were analyzed. Secondly, the expression of LTBR in clinical stages, immune subtypes, and molecular subtypes was analyzed. The correlation between LTBR and immune regulatory genes, immune checkpoint genes, and RNA modification genes was then analyzed. Correlations between LTBR and immune cells, scores, cancer-related functional status, tumor stemness index, mismatch repair (MMR) genes, and DNA methyltransferase were also analyzed. In addition, we analyzed the role of LTBR in DNA methylation, mutational status, tumor mutation burden (TMB), and microsatellite instability (MSI). Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) were used to explore the role of LTBR in pan-cancer. Finally, the drugs associated with LTBR were analyzed. The expression of LTBR was confirmed using quantitative real-time PCR and Western blot. LTBR is significantly overexpressed in most cancers and is associated with low patient survival. In addition, LTBR expression was strongly correlated with immune cells, score, cancer-related functional status, tumor stemness index, MMR genes, DNA methyltransferase, DNA methylation, mutational status, TMB, and MSI. Enrichment analysis revealed that LTBR was associated with apoptosis, necroptosis, and immune-related pathways. Finally, multiple drugs targeting LTBR were identified. LTBR is overexpressed in several tumors and is associated with a poor prognosis. It is related to immune-related genes and immune cell infiltration.

Prognostic value of mitochondrial CKMT2 in Pan-cancer and its tumor immune correlation analysis

Mitochondrial metabolism has been shown to play a key role in immune cell survival and function, but mitochondrial creatine kinase 2 (CKMT2) has been relatively little studied about tumor immunity. We aimed to explore the prognostic value of CKMT2 in 33 cancer types and investigate its potential immune function. We used a range of bioinformatics approaches to explore the potential carcinogenic role of CKMT2 in multiple cancers. CKMT2 was lowly expressed in 14 tumor tissues and highly expressed in 4 tumor tissues. Immunohistochemical assays showed overexpression of CKMT2 in colon cancer and rectal cancer. CKMT2 overexpression was positively correlated with the prognosis of lung adenocarcinoma and prostate cancer. CKMT2 overexpression is mainly enriched in the adaptive immune system and immune regulatory pathways of immunoglobulins. Seven cancers were positively correlated with low CKMT2 expression in tumor microenvironment analysis. Among the five cancers, low expression of CKMT2 resulted in better immunotherapy treatment outcomes. There was a strong correlation between CKMT2 and most immune-related genes in specific cancer types. CKMT2 plays an important role in tumorigenesis and cancer immunity and can be used as a prognostic biomarker and potential target for cancer immunotherapy.

Combined OLA1 and CLEC3B Gene Is a Prognostic Signature for Hepatocellular Carcinoma and Impact Tumor Progression

Hepatocellular carcinoma (HCC), partly because of its complexity and high heterogeneity, has a poor prognosis and an extremely high mortality rate. In this study, mRNA sequencing expression profiles and relevant clinical data of HCC patients were gathered from different public databases. Kaplan-Meier survival curves as well as ROC curves validated that OLA1|CLEC3B was an independent predictor with better predictive capability of HCC prognosis compared to OLA1 and CLEC3B separately. Further, the cell transfection experiment verified that knockdown of OLA1 inhibited cell proliferation, facilitated apoptosis, and improved sensitivity of HCC cells to gemcitabine. In this study, the prognostic model of HCC composed of OLA1/CLEC3B genes was constructed and verified, and the prediction ability was favorable. A higher level of OLA1 along with a lower level of CEC3B is a sign of poor prognosis in HCC. We revealed a novel gene pair OLA1|CLEC3B overexpressed in HCC patients, which may serve as a promising independent predictor of HCC survival and an approach for innovative diagnostic and therapeutic strategies.

Construction of RNA Methylation Modification-immune-related lncRNA Molecular Subtypes and Prognostic Scoring System in Lung Adenocarcinoma

BACKGROUND

RNA methylation modification is not only intimately interrelated with cancer development and progression but also actively influences immune cell infiltration in the tumor microenvironment (TME). RNA methylation modification genes influence the therapeutic progression of lung adenocarcinoma (LUAD), and mining RNA methylation modification prognosis-related markers in LUAD is crucial for its precise prognosis.

METHODS

RNA-Seq data and Gene sets were collected from online databases or published literature. Genomic variation analysis was conducted by the Maftools package. RNA methylation-immune-related lncRNAs were obtained by Pearson correlation analysis. Then, Consistent clustering analysis was performed to obtain RNA methylation modification- immune molecular subtypes (RMM-I Molecular subtypes) in LUAD based on selected lncRNAs. COX and random survival forest analysis were carried out to construct the RMM-I Score. The receiver operating characteristic (ROC) curve and Kaplan Meier survival analysis were used to assess survival differences. Tumor immune microenvironment was assessed through related gene signatures and CIBERSORT algorithm. In addition, drug sensitivity analysis was executed by the pRRophetic package.

RESULTS

Four RNA methylation modified-immune molecular subtypes (RMM-I1, RMM- I2, RMM-I3, RMM-I4) were presented in LUAD. Patients in RMM-I4 exhibited excellent survival advantages and immune activity. HAVCR2, CD274, and CTLA-4 expression were activated in RMM-I4, which might be heat tumors and a potential beneficial group for immunotherapy. OGFRP1, LINC01116, DLGAP1-AS2, CRNDE, LINC01137, MIR210HG, and CYP1B1-AS1 comprised the RMM-I Score. The RMM-I Score exhibited excellent accuracy in the prognostic assessment of LUAD, as patients with a low RMM- I Score exhibited remarkable survival advantage. Patients with a low RMM-I score might be more sensitive to treatment with Docetaxel, Vinorelbine, Paclitaxel, Cisplatin, and immunotherapy.

CONCLUSION

The RMM-I molecular subtype constituted the novel molecular characteristic subtype of LUAD, which complemented the existing pathological typing. More refined and accurate molecular subtypes provide help to reveal the mechanism of LUAD development. In addition, the RMM-I score offers a reliable tool for accurate prognosis of LUAD.

Unraveling the hypoxia modulating potential of VEGF family genes in pan-cancer

Tumor hypoxia, oxygen deprivation state, occurs in most cancers and promotes angiogenesis, enhancing the potential for metastasis. The vascular endothelial growth factor (VEGF) family genes play crucial roles in tumorigenesis by promoting angiogenesis. To investigate the malignant processes triggered by hypoxia-induced angiogenesis across pan-cancers, we comprehensively analyzed the relationships between the expression of VEGF family genes and hypoxic microenvironment based on integrated bioinformatics methods. Our results suggest that the expression of VEGF family genes differs significantly among various cancers, highlighting their heterogeneity effect on human cancers. Across the 33 cancers, VEGFB and VEGFD showed the highest and lowest expression levels, respectively. The survival analysis showed that VEGFA and placental growth factor (PGF) were correlated with poor prognosis in many cancers, including kidney renal cell and liver hepatocellular carcinoma. VEGFC expression was positively correlated with glioma and stomach cancer. VEGFA and PGF showed distinct positive correlations with hypoxia scores in most cancers, indicating a potential correlation with tumor aggressiveness. The expression of miRNAs targeting VEGF family genes, including hsa-miR-130b-5p and hsa-miR-940, was positively correlated with hypoxia. In immune subtypes analysis, VEGFC was highly expressed in C3 (inflammatory) and C6 (transforming growth factor β dominant) across various cancers, indicating its potential role as a tumor promotor. VEGFC expression exhibited positive correlations with immune infiltration scores, suggesting low tumor purity. High expression of VEGFA and VEGFC showed favorable responses to various drugs, including BLU-667, which abrogates RET signaling, an oncogenic driver in liver and thyroid cancers. Our findings suggest potential roles of VEGF family genes in malignant processes related with hypoxia-induced angiogenesis.

Unraveling the molecular crosstalk and immune landscape between COVID-19 infections and ischemic heart failure comorbidity: New insights into diagnostic biomarkers and therapeutic approaches

BACKGROUND

Coronavirus disease 2019 (COVID-19), resulting from severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), remains a persistent global health concern. Evidence has highlighted a significant association between COVID-19 and ischemic heart failure (IHF), contributing to disease progression and increased mortality. This study identified diagnostic biomarkers for these comorbidities and elucidated disease progression's molecular mechanisms.

METHODS

We retrieved differentially expressed gene (DEG) data for COVID-19 and IHF from publicly available microarray and RNA-Seq datasets to investigate the underlying mechanisms and potential pathways associated with the co-occurrence of COVID-19 and IHF. By intersecting the results from the two diseases, we obtained diagnostic biomarkers using SVM-RFE and LASSO algorithms. Animal experiments and immunological analyses were conducted to help understand the association between SARS-CoV-2 and IHF in patients, enabling early diagnosis of disease progression. Finally, we analyzed the regulatory network of critical genes and identified potential drug compounds that could target the genetic links identified in our study.

RESULTS

1974 common DEGs were identified between COVID-19 and IHF, contributing to disease progression and potential cancer risk by participating in immune and cancer-related pathways. In addition, we identified six hub genes (VDAC3, EIF2AK2, CHMP5, FTL, VPS4A, and CHMP4B) associated with the co-morbidity, and their diagnostic potential was confirmed through validation using relevant datasets and a mouse model. Functional enrichment analysis and examination of immune cell infiltration revealed immune dysregulation after disease progression. The comorbid hub genes exhibited outstanding immunomodulatory capacities. We also constructed regulatory networks tightly linked to both disorders, including transcription factors (TFs), miRNAs, and genes at both transcriptional and post-transcriptional levels. Finally, we identified 92 potential drug candidates to enhance the precision of anti-comorbidity treatment strategies.

CONCLUSION

Our study reveals a shared pathogenesis between COVID-19 and IHF, demonstrating that their coexistence exacerbates disease severity. By identifying and consolidating hub genes as pivotal diagnostic biomarkers for COVID-19 and IHF comorbidity, we have made significant advancements in understanding the underlying mechanisms of these conditions. Moreover, our study highlights dysregulated immunity and increased cancer risk in the advanced stages of disease progression. These findings offer novel perspectives for diagnosing and treating IHF progression during SARS-CoV-2 infection.

A novel tumor purity and immune infiltration-related model for predicting distant metastasis-free survival in prostate cancer

BACKGROUND

umor cells, immune cells and stromal cells jointly modify tumor development and progression. We aim to explore the potential effects of tumor purity on the immune microenvironment, genetic landscape and prognosis in prostate cancer (PCa).

METHODS

Tumor purity of prostate cancer patients was extracted from The cancer genome atlas (TCGA). Immune cellular proportions were calculated by the CIBERSORT. To identify critical modules related to tumor purity, we used weighted gene co-expression network analysis (WGCNA). Using STRING and Cytoscape, protein-protein interaction (PPI) networks were constructed and analyzed. A Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, Disease Ontology (DO), and Gene Set Enrichment Analysis (GSEA) enrichment analysis of identified modules was conducted. To identify the expression of key genes at protein levels, we used the Human Protein Atlas (HPA) platform.

RESULTS

A model of tumor purity score (TPS) was constructed in the gene expression omnibus series (GSE) 116,918 cohort. TCGA cohort served as a validation set and was employed to validate the TPS. TPS model, as an independent prognostic factor of distant metastasis-free survival (DMFS) in PCa. Patients had higher tumor purity and better prognosis in the low-TPS group. Tumor purity was related to the infiltration of mast cells and macrophage cells positively, whereas related to the infiltration of dendritic cells, T cells and B cells negatively in PCa. The nomogram based on TPS, Age, Gleason score and T stage had a good predictive value and could evaluate the prognosis of PCa metastasis. GO and KEGG enrichment analyses showed that hub genes mainly participate in T cell activation and T-helper lymphocytes (TH) differentiation. Hub genes were mainly enriched in primary immunodeficiency disease, according to DO analysis. SLAMF8 was identified as the most critical gene by Cytoscape and HPA analysis.

CONCLUSIONS

Dynamic changes in the immune microenvironment associated with tumor purity could correlate with a poor DMFS of low-purity PCa. The TPS can predict the DMFS of PCa. In addition, prostate cancer metastases may be related to immunosuppression caused by a disorder of the immune microenvironment.

Identification and validation of molecular subtypes' characteristics in bladder urothelial carcinoma based on autophagy-dependent ferroptosis

Background

Nowadays, more evidences indicated that autophagy-dependent ferroptosis regulatory molecules (ADFRMs) may be closely related to various tumors. In current study, we intended to establish a prognostic ADFRMs signature and investigated its potential roles in bladder urothelial carcinoma (BLCA).

Methods

Two distinct clusters were determined by consensus clustering with expression of 119 identified ADFRMs in BLCA. The tumor microenvironment was investigated through "CIBERSORT" algorithm, and enrichment analyses were utilized to seek molecular characteristics of differentially expressed genes (DEGs) between clusters. Moreover, a 2-ADFRMs prognostic signature including TRIB3 and WIPI1 was identified in TCGA cohort and further evaluated in the GSE13507 cohort. The qRT-PCR was conducted to examine the expression of prognostic genes. Further, the risk score was gained through calculating the level of TRIB3 and WIPI1 expression through the coefficient. The correlations between risk score with clinicopathologica features, tumor microenvironment, and drug sensitivity were explored.

Results

Patients in TCGA-BLCA were grouped into two clusters with different expression patterns of ADFRMs. And the overall survival, tumor microenvironment and biological functions were significant different between two clusters. Moreover, a 2-ADFRMs model was constructed, and patients were separated into a low-risk and high-risk group. Survival analysis indicated patients with low risk promised a good prognosis, suggesting the risk score determined with ADFRMs signature exhibited an acceptable capacity for survival prediction in BLCA. Correlation analysis demonstrated risk score had close ties with age, stage, and tumor microenvironment. In vivo, the expression of prognostic genes was identified to be up-regulated in BLCA cell line T24.

Conclusion

The constructed 2-ADFRMs signature was a promising model to predict prognosis and correlated with tumor microenvironment, which had latent clinical value in the intervention for BLCA.

Identification of a disulfidptosis-related genes signature for prognostic implication in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is the most prevalent subtype of non-small cell lung cancer. Additionally, disulfidptosis, a newly discovered type of cell death, has been found to be closely associated with the onset and progression of tumors.

METHODS

The study first identified genes related to disulfidptosis through correlation analysis. These genes were then screened using univariate cox regression and LASSO regression, and a prognostic model was constructed through multivariate cox regression. A nomogram was also created to predict the prognosis of LUAD. The model was validated in three independent data sets: GSE72094, GSE31210, and GSE37745. Next, patients were grouped based on their median risk score, and differentially expressed genes between the two groups were analyzed. Enrichment analysis, immune infiltration analysis, and drug sensitivity evaluation were also conducted.

RESULTS

In this study, we examined 21 genes related to disulfidptosis and developed a gene signature that was found to be associated with a poorer prognosis in LUAD. Our model was validated using three independent datasets and showed AUC values greater than 0.5 at 1, 3, and 5 years. Enrichment analysis revealed that the disulfidptosis-related genes signature had a multifaceted impact on LUAD, particularly in relation to tumor development, proliferation, and metastasis. Patients in the high-risk group exhibited higher tumor purity and lower stromal score, ESTIMATE score, and Immune score.

CONCLUSION

This study constructed a gene signature related to disulfidptosis in lung adenocarcinoma and analyzed its impact on the disease and its association with the tumor microenvironment. The findings of this research provide valuable insights into the understanding of lung adenocarcinoma and could potentially lead to the development of new treatment strategies.

A Novel Gene Pair CSTF2/DPE2A Impacts Prognosis and Cell Cycle of Hepatocellular Carcinoma

Background

Hepatocellular carcinoma (HCC), one of the commonest cancers at present, possesses elevated mortality. This study explored the predictive value of CSTF2/PDE2A for HCC prognosis.

Methods

In this study, clinical information and RNA sequencing expression profiles of HCC patients were acquired from common databases. Kaplan-Meier curve compound with time-dependent ROC curve, nomogram model, and univariate/multivariate Cox analysis were carried out to access the prediction capacity of CSTF2/PDE2A. The immune status, tumor microenvironment, drug sensitivity, biological function and pathway between HCC and adjacent non-tumorous tissue were analyzed and compared. Finally, RT-qPCR, Western blot, and apoptosis assays were performed to verify the effect on HCC cells of CSTF2/PDE2A.

Results

The optimal cut-off value of CSTF2, PDE2A and CSTF2/PDE2A was 6.95, 0.95 and 3.63, respectively. In TCGA and ICGC cohorts, the high group of CSTF2/PDE2A presented higher OS compared to low group. The area under the curve (AUC) for OS at 1-, 2-, and 3-years predicted by CSTF2/PDE2A were 0.731/0.695, 0.713/0.732 and 0.689/0.755, higher than the counterparts of the single gene CSTF2 and PDE2A. Multivariate Cox analysis revealed that CSTF2/PDE2A (HR = 1.860/3.236, 95% CI = 1.265-2.733/1.575-6.645) was an independent prognostic factor for HCC. The OS nomogram model created according to five independent factors including CSTF2/PDE2A showed excellent capacity for HCC prognosis. Furthermore, the immune status of the CSTF2/PDE2A high group was deleted, cell cycle-related genes and chemotherapy resistance were increased. Finally, cell experiments revealed distinct differences in the proliferation, apoptosis, protein and mRNA expression of HCC cells after si-CSTF2 transfection compared with the negative control.

Conclusion

Taken together, the gene pair CSTF2/PDE2A is able to forecast the prognosis of HCC and regulates cell cycle, which is promising as a novel prognostic predictor of HCC.

The immune checkpoint adenosine 2A receptor is associated with aggressive clinical outcomes and reflects an immunosuppressive tumor microenvironment in human breast cancer

Background

The crosstalk between the immune system and cancer cells has aroused considerable interest over the past decades. To escape immune surveillance cancer cells evolve various strategies orchestrating tumor microenvironment. The discovery of the inhibitory immune checkpoints was a major breakthrough due to their crucial contribution to immune evasion. The A2AR receptor represents one of the most essential pathways within the TME. It is involved in several processes such as hypoxia, tumor progression, and chemoresistance. However, its clinical and immunological significance in human breast cancer remains elusive.

Methods

The mRNA expression and protein analysis were performed by RT-qPCR and immunohistochemistry. The log-rank (Mantel-Cox) test was used to estimate Kaplan-Meier analysis for overall survival. Using large-scale microarray data (METABRIC), digital cytometry was conducted to estimate cell abundance. Analysis was performed using RStudio software (7.8 + 2023.03.0) with EPIC, CIBERSORT, and ImmuneCellAI algorithms. Tumor purity, stromal and immune scores were calculated using the ESTIMATE computational method. Finally, analysis of gene set enrichment (GSEA) and the TISCH2 scRNA-seq database were carried out.

Results

Gene and protein analysis showed that A2AR was overexpressed in breast tumors and was significantly associated with high grade, elevated Ki-67, aggressive molecular and histological subtypes, as well as poor survival. On tumor infiltrating immune cells, A2AR was found to correlate positively with PD-1 and negatively with CTLA-4. On the other hand, our findings disclosed more profuse infiltration of protumoral cells such as M0 and M2 macrophages, Tregs, endothelial and exhausted CD8+ T cells within A2ARhigh tumors. According to the Single-Cell database, A2AR is expressed in malignant, stromal and immune cells. Moreover, it is related to tumor purity, stromal and immune scores. Our results also revealed that CD8+T cells from A2ARhigh patients exhibited an exhausted functional profile. Finally, GSEA analysis highlighted the association of A2AR with biological mechanisms involved in tumor escape and progression.

Conclusion

The present study is the first to elucidate the clinical and immunological relevance of A2AR in breast cancer patients. In light of these findings, A2AR could be deemed a promising therapeutic target to overcome immune evasion prevailing within the TME of breast cancer patients.

HGH1 and the immune landscape: a novel prognostic marker for immune-desert tumor microenvironment identification and immunotherapy outcome prediction in human cancers

HGH1 homolog, a protein-coding gene, plays a crucial role in human growth and development. However, its role in human cancer remains unclear. For the first time, this study comprehensively evaluated the potential involvement of HGH1 in cancer prognosis and immunological function. To achieve this, data from various databases, including The Cancer Genome Atlas, Genotype Tissue Expression, Cancer Cell Lineage Encyclopedia, Human Protein Atlas, cBioPortal, Tumor Immune Estimation Resource and Immune Cell Abundance Identifier, were collated, as well as from one large clinical study, three immunotherapy cohorts and in vitro experiments. This study aims to elucidate the role of HGH1 expression in cancer prognosis and immune response. Our findings revealed a significant association between increased HGH1 expression and a worse prognosis across various cancer types. Predominantly, copy number variations were identified as the most common genetic mutations. Additionally, HGH1 was observed to not only regulate cell cycle-related functions to promote cell proliferation but also influence autoimmunity-related functions within both the innate and adaptive immune systems, along with other relevant immune-related signaling pathways. Gene set enrichment analysis and gene set variation analysis were used to substantiate these findings. HGH1 overexpression contributed to an immune-deficient (immune-desert) tumor microenvironment, which was characterized by a significant expression of immune-related features such as immune-related gene and pathway expression and the number of immune-infiltrating cells. Furthermore, the correlation between HGH1 expression and tumor mutational burden in four cancers and microsatellite instability in eight cancers was observed. This suggests that HGH1 has potential as an immunotherapeutic target. Immunotherapy data analysis supports this notion, demonstrating that patients with low HGH1 expression treated with immune checkpoint inhibitors exhibit improved survival rates and a higher likelihood of responding to immunotherapy than patients with high HGH1 expression. Collectively, these findings highlight the significant role of HGH1 in human cancers, illuminating its involvement in tumorigenesis and cancer immunity. Elevated HGH1 expression was identified to be indicative of an immune-desert tumor microenvironment. Consequently, the targeting of HGH1, particularly in combination with immune checkpoint inhibitor therapy, holds promise for enhancing therapeutic outcomes in patients with cancer.

Tumor purity-associated genes influence hepatocellular carcinoma prognosis and tumor microenvironment

Introduction

Tumor purity takes on critical significance to the progression of solid tumors. The aim of this study was at exploring potential prognostic genes correlated with tumor purity in hepatocellular carcinoma (HCC) by bioinformatics analysis.

Methods

The ESTIMATE algorithm was applied for determining the tumor purity of HCC samples from The Cancer Genome Atlas (TCGA). The tumor purity-associated genes with differential expression (DEGs) were identified based on overlap analysis, weighted gene co-expression network analysis (WGCNA), and differential expression analysis. The prognostic genes were identified in terms of the prognostic model construction based on the Kaplan-Meier (K-M) survival analysis and Least Absolute Shrinkage and Selection Operator (LASSO) regression analyses. The expression of the above-described genes was further validated by the GSE105130 dataset from the Gene Expression Omnibus (GEO) database. We also characterized the clinical and immunophenotypes of prognostic genes. Gene set enrichment analysis (GSEA) was carried out for exploring the biological signaling pathway.

Results

A total of 26 tumor purity-associated DEGs were identified, which were involved in biological processes such as immune/inflammatory responses and fatty acid elongation. Ultimately, we identified ADCK3, HK3, and PPT1 as the prognostic genes for HCC. Moreover, HCC patients exhibiting higher ADCK3 expression and lower HK3 and PPT1 expressions had a better prognosis. Furthermore, high HK3 and PPT1 expressions and low ADCK3 expression resulted in high tumor purity, high immune score, high stromal score, and high ESTIMATE score. GSEA showed that the abovementioned prognostic genes showed a significant correlation with immune-inflammatory response, tumor growth, and fatty acid production/degradation.

Discussion

In conclusion, this study identified novel predictive biomarkers (ADCK3, HK3, and PPT1) and studied the underlying molecular mechanisms of HCC pathology initially.

Prognostic and Immunological Role of Asporin across Cancers and Exploration in Bladder Cancer

BACKGROUND

Asporin (ASPN) has been identified as a player in tumorigenesis, but its precise roles and modulatory function are largely unknown.

METHODS

In the present study, ASPN expression was first explored, followed by a prognostic evaluation of ASPN and a comprehensive investigation of the connections between ASPN and immunomodulation, immune cell infiltration and potential compounds on a pancancer level. Finally, ASPN expression was validated in bladder urothelial carcinoma (BLCA) tissues, and the potential function of ASPN, including its effects on migration and invasion capabilities, was investigated in tumor cells.

RESULTS

The expression of ASPN exhibited significant variation across cancers and was found to be associated with patient prognosis. In addition, the expression level of APSN was markedly correlated with the abundances of infiltrating immune cells and cancer-associated fibroblasts and the expression levels of immunomodulatory genes based on the results of pancancer analysis. Metastasis and immune-associated signaling pathways were identified in enrichment analysis based on ASPN expression. Finally, we confirmed that ASPN expression increased with the degree of malignancy in BLCA tissues and cell lines and that low expression of ASPN hindered the migration and invasion of cells.

CONCLUSIONS

ASPN has the potential to be a biomarker of cancer prognosis and a therapeutic target, and it also has predictive capability for the progression of BLCA.

Novel Genetic Subtypes of Urothelial Carcinoma With Differential Outcomes on Immune Checkpoint Blockade

PURPOSE

Immune checkpoint blockade (ICB) therapy has significantly improved clinical outcomes in bladder cancer. Identification of correlates of benefit is critical to select appropriate therapy for individual patients.

METHODS

To reveal genetic variables associated with benefit from ICB, we performed whole-exome sequencing on tumor specimens from 88 patients with advanced bladder cancer treated with ICB.

RESULTS

We identified several genetic factors that correlated with progression-free and overall survival after ICB therapy including ARID1A mutation, tumor mutational burden, intratumoral heterogeneity, the ratio of nonsynonymous to synonymous mutations in the immunopeptidome (immune dN/dS), and tumor cell purity. In addition, we noted that neutrophil-to-lymphocyte ratio and smoking history were negatively associated with overall survival. These genetic characteristics define four molecular subtypes demonstrating differential sensitivity to ICB. We validated the association of these four subtypes with clinical benefit from ICB in an independent cohort (IMvigor210). Finally, we showed that these molecular subtypes also correlate with outcome, although with distinct relationships, among patients not treated with ICB using The Cancer Genome Atlas (TCGA) bladder cancer cohort. Using parallel RNA sequencing data, the subtypes were also shown to correlate with immune infiltration and inflammation, respectively, in the IMvigor210 and TCGA cohorts.

CONCLUSION

Together, our study defines molecular subgroups of bladder cancer that influence benefit from ICB.

Systematic pan-cancer analysis identifies cuproptosis-related gene DLAT as an immunological and prognostic biomarker

Lipoylated dihydrolipoamide S-acetyltransferase (DLAT), the component E2 of the multi-enzyme pyruvate dehydrogenase complex, is one of the key molecules of cuproptosis. However, the prognostic value and immunological role of DLAT in pan-cancer are still unclear. Using a series of bioinformatics approaches, we studied combined data from different databases, including the Cancer Genome Atlas, Genotype Tissue-Expression, the Cancer Cell Line Encyclopedia, Human Protein Atlas, and cBioPortal to investigate the role of DLAT expression in prognosis and tumor immunity response. We also reveal the potential correlations between DLAT expression and gene alterations, DNA methylation, copy number variation (CNV), tumor mutational burden (TMB), microsatellite instability (MSI), tumor microenvironment (TME), immune infiltration levels, and various immune-related genes across different cancers. The results show that DLAT displays abnormal expression within most malignant tumors. Through gene set enrichment analysis (GSEA), we found that DLAT was significantly associated with immune-related pathways. Further, the expression of DLAT was also confirmed to be correlated with the tumor microenvironment and diverse infiltration of immune cells, especially tumor-associated macrophages (TAMs). In addition, we found that DLAT is co-expressed with genes encoding major histocompatibility complex (MHC), immunostimulators, immune inhibitors, chemokines, and chemokine receptors. Meanwhile, we demonstrate that DLAT expression is correlated with TMB in 10 cancers and MSI in 11 cancers. Our study reveals that DLAT plays an essential role in tumorigenesis and cancer immunity, which may be used to function as a prognostic biomarker and potential target for cancer immunotherapy.

Epigenetically regulated gene expression profiles decipher four molecular subtypes with prognostic and therapeutic implications in gastric cancer

BACKGROUND

Gastric cancer (GC) is one of the most common malignant tumors of the digestive tract which seriously endangers the health of human beings worldwide. Transcriptomic deregulation by epigenetic mechanisms plays a crucial role in the heterogeneous progression of GC. This study aimed to investigate the impact of epigenetically regulated genes on the prognosis, immune microenvironment, and potential treatment of GC.

RESULTS

Under the premise of verifying significant co-regulation of the aberrant frequencies of microRNA (miRNA) correlated (MIRcor) genes and DNA methylation-correlated (METcor) genes. Four GC molecular subtypes were identified and validated by comprehensive clustering of MIRcor and METcor GEPs in 1521 samples from five independent multicenter GC cohorts: cluster 1 was characterized by up-regulated cell proliferation and transformation pathways, with good prognosis outcomes, driven by mutations, and was sensitive to 5-fluorouracil and paclitaxel; cluster 2 performed moderate prognosis and benefited more from apatinib and cisplatin; cluster 3 was featured by an up-regulated ligand-receptor formation-related pathways, poor prognosis, an immunosuppression phenotype with low tumor purity, resistant to chemotherapy (e.g., 5-fluorouracil, paclitaxel, and cisplatin), and targeted therapy drug (apatinib) and sensitive to dasatinib; cluster 4 was characterized as an immune-activating phenotype, with advanced tumor stages, benefit more from immunotherapy and displayed worst prognosis.

CONCLUSIONS

According to the epigenetically regulated GEPs, we developed four robust GC molecular subtypes, which facilitated the understanding of the epigenetic mechanisms underlying GC heterogeneity, offering an optimized decision-making and surveillance platform for GC patients.

Design and Computational Analysis of an MMP9 Inhibitor in Hypoxia-Induced Glioblastoma Multiforme

The main therapeutic difficulties in treating hypoxia-induced glioblastoma multiforme (GBM) are toxicity of current treatments and the resistance brought on by the microenvironment. More effective therapeutic alternatives are urgently needed to reduce tumor lethality. Hence, we screened plant-based natural product panels intending to identify novel drugs without elevating drug resistance. We explored GEO for the hypoxia GBM model and compared hypoxic genes to non-neoplastic brain cells. A total of 2429 differentially expressed genes expressed exclusively in hypoxia were identified. The functional enrichment analysis demonstrated genes associated with GBM, further PPI network was constructed, and biological pathways associated with them were explored. Seven webtools, including GEPIA2.0, TIMER2.0, TCGA-GBM, and GlioVis, were used to validate 32 hub genes discovered using Cytoscape tool in GBM patient samples. Four GBM-specific hypoxic hub genes, LYN, MMP9, PSMB9, and TIMP1, were connected to the tumor microenvironment using TIMER analysis. 11 promising hits demonstrated positive drug-likeness with nontoxic characteristics and successfully crossed blood-brain barrier and ADMET analyses. Top-ranking hits have stable intermolecular interactions with the MMP9 protein according to molecular docking, MD simulation, MM-PBSA, PCA, and DCCM analyses. Herein, we have reported flavonoids, 7,4'-dihydroxyflavan, (3R)-3-(4-hydroxybenzyl)-6-hydroxy-8-methoxy-3,4-dihydro-2H-1-benzopyran, and 4'-hydroxy-7-methoxyflavan, to inhibit MMP9, a novel hypoxia gene signature that could serve as a promising predictor in various clinical applications, including GBM diagnosis, prognosis, and targeted therapy.

Constructing a novel mitochondrial-related gene signature for evaluating the tumor immune microenvironment and predicting survival in stomach adenocarcinoma

BACKGROUND

The incidence and mortality of gastric cancer ranks fifth and fourth worldwide among all malignancies, respectively. Accumulating evidences have revealed the close relationship between mitochondrial dysfunction and the initiation and progression of stomach cancer. However, rare prognostic models for mitochondrial-related gene risk have been built up in stomach cancer.

METHODS

In current study, the expression and prognostic value of mitochondrial-related genes in stomach adenocarcinoma (STAD) patients were systematically analyzed to establish a mitochondrial-related risk model based on available TCGA and GEO databases. The tumor microenvironment (TME), immune cell infiltration, tumor mutation burden, and drug sensitivity of gastric adenocarcinoma patients were also investigated using R language, GraphPad Prism 8 and online databases.

RESULTS

We established a mitochondrial-related risk prognostic model including NOX4, ALDH3A2, FKBP10 and MAOA and validated its predictive power. This risk model indicated that the immune cell infiltration in high-risk group was significantly different from that in the low-risk group. Besides, the risk score was closely related to TME signature genes and immune checkpoint molecules, suggesting that the immunosuppressive tumor microenvironment might lead to poor prognosis in high-risk groups. Moreover, TIDE analysis demonstrated that combined analysis of risk score and immune score, or stromal score, or microsatellite status could more effectively predict the benefit of immunotherapy in STAD patients with different stratifications. Finally, rapamycin, PD-0325901 and dasatinib were found to be more effective for patients in the high-risk group, whereas AZD7762, CEP-701 and methotrexate were predicted to be more effective for patients in the low-risk group.

CONCLUSIONS

Our results suggest that the mitochondrial-related risk model could be a reliable prognostic biomarker for personalized treatment of STAD patients.

A comprehensive analysis of PANoptosome to prognosis and immunotherapy response in pan-cancer

PANoptosis, a programmed cell death, shares key characteristics of apoptosis, pyroptosis, and necroptosis. Accumulating evidence suggests that PANoptosis plays a crucial role in tumorigenesis. However, the respective regulation mechanisms in cancer are so far unclear. Using various bioinformatic approaches, we comprehensively analyzed the expression patterns, genetic alterations, prognostic value, and immunological role of PANoptosis genes in pan-cancer. Expression of the PANoptosis gene, PYCARD, was validated based on the Human Protein Atlas database and real-time quantitative reverse transcription polymerase chain reaction (RT-PCR). We found that PANoptosis genes were aberrantly expressed in most cancer types, which was consistent with the validation of PYCARD expression. Concurrently, PANoptosis genes and PANoptosis scores were significantly associated with patient survival in 21 and 14 cancer types, respectively. Pathway analysis showed that PANoptosis score was positively correlated with pathways linked to immune and inflammatory responses in pan-cancer, such as IL6-JAK-STAT3 signaling, the interferon-gamma response, and IL2-STAT5 signaling. In addition, the PANoptosis score was significantly correlated with the tumor microenvironment, the infiltration levels of most immune cells (i.e.NK cells, CD8+ T cells, CD4+ T cells, DC cells), and immune-related genes. Furthermore, it was a predictive indicator of immunotherapy response in patients with tumors. These insights substantially improve our understanding of PANoptosis components in cancers and may inspire the discovery of novel prognostic and immunotherapy response biomarkers.

Pan-cancer analysis of the prognostic and immunological role of SNX29: a potential target for survival and immunotherapy

BACKGROUND

There is growing evidence that the SNX family is critical for clinical prognosis, immune infiltration and drug sensitivity in many types of tumors. The relationships between the SNX29 gene and clinical prognosis as well as pan-cancer cell infiltration and drug sensitivity have not been fully elucidated.

METHODS

In the current study, we explored the correlation between SNX29 expression and 33 types of malignancies via TCGA and GTEx. The relationship between SNX29 expression and prognostic outcome in the pan-caner cohort was also analyzed. Immune infiltration, microsatellite instability, tumor mutational burden and potential therapeutic targets of SNX29 were investigated by analyzing public databases.

RESULTS

The expression of SNX29 was found to be significantly upregulated in most tumor tissues compared to normal tissues. SNX29 expression was associated with prognosis and clinical stage. In the immune infiltration analysis, a significant relationship was found between SNX29 expression and the level of immune infiltration. In addition, we found associations between the SNX29 gene and tumor mutation burden, microsatellite instability, immunoinhibition-related genes and autophagy-related genes. Finally, the expression of SNX29 was significantly associated with the sensitivity of various tumor cell lines to 8 antitumor drugs. These results suggest that SNX29 expression is important in determining the progression, immune infiltration and drug sensitivity of various cancers.

CONCLUSION

This study provides novel insights into the potential pan-cancer targets of SNX29.

An immune-related prognostic signature associated with immune landscape and therapeutic responses in gastric cancer

Immune-related genes (IRGs) have attracted attention in recent years as therapeutic targets in various tumors. However, the role of IRGs in gastric cancer (GC) has not been clearly elucidated. This study presents a comprehensive analysis exploring the clinical, molecular, immune, and drug response features characterizing the IRGs in GC. Data were acquired from the TCGA and GEO databases. The Cox regression analyses were performed to develop a prognostic risk signature. The genetic variants, immune infiltration, and drug responses associated with the risk signature were explored using bioinformatics methods. Lastly, the expression of the IRS was verified by qRT-PCR in cell lines. In this manner, an immune-related signature (IRS) was established based on 8 IRGs. According to the IRS, patients were divided into the low-risk group (LRG) and high-risk group (HRG). Compared with the HRG, the LRG was characterized by a better prognosis, high genomic instability, more CD8+ T cell infiltration, greater sensitivity to chemotherapeutic drugs, and greater likelihood of benefiting from the immunotherapy. Moreover, the expression result showed good consistency between the qRT-PCR and TCGA cohort. Our findings provide insights into the specific clinical and immune features underlying the IRS, which may be important for patient treatment.

Comprehensive Analysis Reveals Distinct Immunological and Prognostic Characteristics of CD276/B7-H3 in Pan-Cancer

Background

CD276 (also known as B7-H3), a newly discovered immunoregulatory protein that belongs to the B7 family, is a significant and attractive target for cancer immunotherapy. Existing evidence demonstrates its pivotal role in the tumorigenesis of some cancers. However, there still lacks a systematic and comprehensive pan-cancer analysis of the role of CD276 in tumor immunology and prognosis.

Methods

We explored and validated the mRNA and protein expression levels of CD276 in multiple tumors through public databases and clinical tissues specimens. The Univariate Cox regression analysis and Kaplan-Meier analysis were applied to assess the prognostic value of CD276. The correlation between CD276 expression and clinical characteristics and immunological features in diverse tumors was also explored. GSEA was performed to illuminate the biological function and involved pathways of CD276. Moreover, the CellMiner database was used to interpret the relationship between CD276 and multiple chemotherapeutic agents. CCK-8 assay was performed to validate the biological function of CD276 in vitro.

Results

In general, CD276 was differentially expressed between most tumor tissues and their corresponding normal tissues. Higher expression levels of CD276 were associated with poorer survival outcomes in most tumor cohorts from TCGA. There was a close correlation between CD276 expression and clinical features, the infiltration levels of specific immune cells, immune subtypes, TMB, MSI, MMR, recognized immunoregulatory genes and drug sensitivity across diverse human cancers. The scRNA-seq data analysis further revealed that CD276 was mainly expressed on the tumor infiltrating macrophages. Additionally, in vitro experiments showed that knockdown of CD276 inhibited the proliferation of ovarian cancer (OV) and cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) cell lines.

Conclusion

CD276 is a potent biomarker for predicting the prognosis and immunological features in some tumors, and it may play a critical role in the tumor immune microenvironment (TIME) through macrophage-associated signaling.

Identification and validation of signature for prognosis and immune microenvironment in gastric cancer based on m6A demethylase ALKBH5

Background

N6-methyladenosine (m6A) RNA regulators play important roles in cancers, but their functions and mechanism have not been demonstrated clearly in gastric cancer (GC).

Methods

In this study, the GC samples with clinical information and RNA transcriptome were downloaded from The Cancer Genome Atlas database. The different expression genes were compared by the absolute value and median ± standard deviation. Samples with complete information were randomly divided into a training dataset and a test dataset. The differential expression genes (DEGs) between ALKBH5-low and ALKBH5-high subgroups were identified in the training dataset and constructed a risk model by Cox and least absolute shrinkage and selection operator regression. The model was testified in test datasets, overall survival (OS) was compared with the Kaplan-Meier method, and immune cell infiltration was calculated by the CIBERSORT algorithm in the low-risk and high-risk subgroups based on the model. The protein levels of ALKBH5 were detected with immunohistochemistry. The relative expression of messenger-ribonucleic acid (mRNA) was detected with quantitative polymerase chain reaction.

Results

ALKBH5 was the only regulator whose expression was lower in tumor samples than that in normal samples. The low expression of ALKBH5 led to the poor OS of GC patients and seemed to be an independent protective factor. The model based on ALKBH5-regulated genes was validated in both datasets (training/test) and displayed a potential capacity to predict a clinical prognosis. Gene Ontology analysis implied that the DEGs were involved in the immune response; CIBERSORT results indicated that ALKBH5 and its related genes could alter the immune microenvironment of GC. The protein levels of ALKBH5 were verified as lowly expressed in GC tissues. SLC7A2 and CGB3 were downregulated with ALKBH5 knockdown.

Conclusions

In this study, we found that ALKBH5 might be a suppressor of GC; ALKBH5 and its related genes were latent biomarkers and immunotherapy targets.

SHMT2 is Associated with Tumor Purity, CD8+ T Immune Cells Infiltration, and a Novel Therapeutic Target in Four Different Human Cancers

AIMS

This study was launched to identify the SHMT2 associated Human Cancer subtypes.

BACKGROUND

Cancer is the 2nd leading cause of death worldwide. Previous reports revealed the limited involvement of SHMT2 in human cancer. In the current study, we comprehensively analyzed the role of SHMT2 in 24 major subtypes of human cancers using in silico approach and identified a few subtypes that are mainly associated with SHMT2.

OBJECTIVE

We aim to comprehensively analyze the role of SHMT2 in 24 major subtypes of human cancers using in silico approach and identified a few subtypes that are mainly associated with SHMT2. Earlier, limited knowledge exists in the medical literature regarding the involvement of Serine Hydroxymethyltransferase 2 (SHMT2) in human cancer.

METHODS

In the current study, we comprehensively analyzed the role of SHMT2 in 24 major subtypes of human cancers using in silico approach and identified a few subtypes that are mainly associated with SHMT2. Pan-cancer transcriptional expression profiling of SHMT2 was done using UALCAN while further validation was performed using GENT2. For translational profiling of SHMT2, we utilized Human Protein Atlas (HPA) platform. Promoter methylation, genetic alteration, and copy number variations (CNVs) profiles were analyzed through MEXPRESS and cBioPortal. Survival analysis was carried out through Kaplan-Meier (KM) plotter platform. Pathway enrichment analysis of SHMT2 was performed using DAVID, while the gene-drug network was drawn through CTD and Cytoscape. Furthermore, in the tumor microenvironment, a correlation between tumor purity, CD8+ T immune cells infiltration, and SHMT2 expression was accessed using TIMER.

RESULTS

SHMT2 was found overexpressed in 24 different subtypes of human cancers and its overexpression was significantly associated with the reduced Overall survival (OS) and Relapse-free survival durations of Breast cancer (BRCA), Kidney renal papillary cell carcinoma (KIRP), Liver hepatocellular carcinoma (LIHC), and Lung adenocarcinoma (LUAD) patients. This implies that SHMT2 plays a significant role in the development and progression of these cancers. We further noticed that SHMT2 was also up-regulated in BRCA, KIRP, LIHC, and LUAD patients of different clinicopathological features. Pathways enrichment analysis revealed the involvement of SHMT2 enriched genes in five diverse pathways. Furthermore, we also explored some interesting correlations between SHMT2 expression and promoter methylation, genetic alterations, CNVs, tumor purity, and CD8+ T immune cell infiltrates.

CONCLUSION

Our results suggested that overexpressed SHMT2 is correlated with the reduced OS and RFS of the BRCA, KIRP, LIHC, and LUAD patients and can be a potential diagnostic and prognostic biomarker for these cancers.

Effect of crosstalk among conspirators in tumor microenvironment on niche metastasis of gastric cancer

In Traditional Chinese medicine, the metaphoric views of the human body are based on observations of nature guided by the theory of "Yin-Yang". The direct meanings of yin and yang are the bright and dark sides of an object, which often represent a wider range of opposite properties. When we shifted our view to gastric cancer (GC), we found that there are more distinctive Yin and Yang features in the mechanism of GC development and metastasis, which is observed in many mechanisms such as GC metastasis, immune escape, and stem cell homing. When illustrating this process from the yin-yang perspective, categorizing different cells in the tumor microenvironment enables new and different perspectives to be put forward on the mechanism and treatment of GC metastasis.

Immune infiltration could predict the efficacy of short-term radiotherapy in patients with cervical cancer

Radiotherapy is the main treatment for cervical cancer. It is usually applied alone or in combination with surgery and/or chemotherapy. To explore the association between immune microenvironment of cervical cancer and radiotherapy response, we collected 20 paired cervical cancer tumor samples before and after radiotherapy and partial clinical information. With paired-end RNA-seq, we quantified the immune infiltration and tumor purity of these samples, and obtained 6350 differentially expressed genes before and after radiotherapy. With the help of R language, the function enrichment analysis and 22 immune cells infiltration analysis were carried out. Moreover, we built a random forest model based on the immune microenvironment to predict the short-term efficacy of radiotherapy. We found that the effect of radiotherapy on the immune microenvironment of stage III and IV cervical cancer patients was weaker than that of stage I and II cervical cancer patients. Radiotherapy can significantly reduce the tumor purity and increase immune infiltration. The proportions of the immune infiltrating cells are predictive of the radiotherapy efficacy. In addition, the local mucositis caused by radiotherapy can improve the curative effect of radiotherapy.

The role of Angiogenesis and remodeling (AR) associated signature for predicting prognosis and clinical outcome of immunotherapy in pan-cancer

Background

Angiogenesis and remodeling (AR) is necessary for the growth and metastasis of cancers. Although AR related genes involved in this process are reported, the correlation between AR and clinical outcome, immune cell infiltration, and immunotherapy is still unknown in diverse cancers. This study aimed to investigate the role of AR in the tumor immune microenvironment (TIME) in pan-cancer, and explore its values in prognostic prediction and therapeutic responses.

Methods

Firstly, AR genes (including angiogenesis genes and blood vessel remodeling genes) are collected from MsigDB database. The differential expression, and prognostic value of AR genes were studied in 33 tumor types based on TCGA and GTEx data. The AR score of each sample was calculated using the "ssGSEA" function of R package "GSVA" in pan-cancer. The correlation of the AR score with TIME index, such as the amount of stromal and immune components and the immune cell infiltration, was evaluated via integrating multiple computational methods. And we also utilized IMvigor210 and GSE78220 data to explore the prediction value of the AR score on the immunotherapy response.

Results

Significant differences in AR gene expression between tumors and adjacent normal tissues were found in most cancer types. The AR score varied depending on the types of tumors, and high score was related to worse survival in various tumors, such as pancreatic and stomach adenocarcinoma and so on. Moreover, the AR score was further explored to be positively correlated with proportions and pathways of immune and stromal in TIME. And the AR score was positively correlated with immunosuppressive cells, including TAMs and iTregs, while negatively with CD8+ T cells. Further analysis revealed that patients with high AR had worse therapy efficacy and survival status in bladder cancer and melanomas.

Conclusions

Our systematic analysis revealed that AR is closely associated TIME, and prognosis, and clinical characteristics in multiple cancers. Targeting AR genes may activate immune microenvironment and increase the efficacy of immunotherapy.

Single-cell sequencing analysis and transcriptome analysis constructed the macrophage related gene-related signature in lung adenocarcinoma and verified by an independent cohort

BACKGROUND

Recent studies have emphasized the close relationship between macrophages and tumor immunity, and the prognosis of lung adenocarcinoma (LUAD) patients is intimately linked to this. Nonetheless, the prognostic signature and classification of different immune patterns in LUAD patients based on the macrophages is largely unexplored.

METHODS

Two sc-RNAseq datasets of LUAD patients were collected and reprocessed. The differentially expressed genes (DEGs) related to macrophages between LUAD tissues and normal lung tissues were then identified. Based upon the above genes, three distinct immune patterns in the TCGA-LUAD cohort were identified. The ssGSEA and CIBERSORT were applied for immune profiling and characterization of different subtypes. A four-gene prognostic signature for LUAD patients was established based on the DEGs between the subtypes using stepwise multi-Cox regression. TCGA-LUAD cohort was used as training set. Five GEO-LUAD datasets and an independent cohort containing 112 LUAD samples were used for validation. TIDE (tumor immune dysfunction and exclusion) and drug sensitivity analyses were also performed.

RESULTS

Macrophage-related differentially expressed genes were found out using the publicly available scRNA-seq data of LUAD. Three different immune patterns which were proved to have distinct immune infiltration characteristics in the TCGA-LUAD cohort were recognized based on the above macrophage-related genes. Thereafter, 174 DEGs among the above three different immune patterns were figured out; on the basis of this, a four-gene prognostic signature was constructed. This signature distinguished the prognosis of LUAD patients well in various GSE datasets as well as our independent cohort. Further analyses revealed that patients which had a higher risk score also accompanied with a lower immune infiltration level and a worse response to several immunotherapy biomarkers.

CONCLUSION

This study highlighted that macrophage were significantly associated with TME diversity and complexity. The four-gene prognostic signature could be used for predicting outcomes and immune landscapes for patients with LUAD.

Tumor immune cell infiltration score based model predicts prognosis in multiple myeloma

The tumor microenvironment plays an important role in various processes, including tumorigenesis, cancer progression, and metastasis. Immune signatures have been identified and verified for use in diagnosis and prognosis prediction. We used single-sample Gene Set Enrichment Analysis to evaluate tumor immune cell infiltration score (TIICs) and verify their prognostic significance in both training and validation cohorts and using this information to build a prognostic model. A total of 1281 samples were obtained for further evaluation of the immune enrichment scores of 28 immune cells, showing that Th17 cell contributed most significantly to survival. Using the median TIICs as a cutoff to divide the samples into two groups, we found that the high-TIICs group was associated with favorable outcomes in both the training and validation sets. We then constructed a prognostic model to predict the 6, 8, and 10-year survival outcomes. Further analysis showed that immune score and tumor purity were higher in the high-TIICs group, while the matrix score was lower in this group. Forty-two differentially expressed genes were identified between the two groups. This new prognostic model based on immune cell infiltration indicates the potential for TIICs in predicting prognosis and as targets for treatment.

Construction of a co-expression network and prediction of metastasis markers in colorectal cancer patients with liver metastasis

BACKGROUND

Colorectal cancer (CRC) is a common global malignancy associated with high invasiveness, high metastasis, and poor prognosis. CRC commonly metastasizes to the liver, where the treatment of metastasis is both difficult and an important topic in current CRC management.

METHODS

Microarrays data of human CRC with liver metastasis (CRCLM) were downloaded from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) database to identify potential key genes. Differentially expressed (DE) genes (DEGs) and DEmiRNAs of primary CRC tumor tissues and metastatic liver tissues were identified. Microenvironment Cell Populations (MCP)-counter was used to estimate the abundance of immune cells in the tumor micro-environment (TME), and weighted gene correlation network analysis (WGCNA) was used to construct the co-expression network analysis. Gene Ontology and Kyoto Encyclopaedia of Gene and Genome (KEGG) pathway enrichment analyses were conducted, and the protein-protein interaction (PPI) network for the DEGs were constructed and gene modules were screened.

RESULTS

Thirty-five pairs of matched colorectal primary cancer and liver metastatic gene expression profiles were screened, and 610 DEGs (265 up-regulated and 345 down-regulated) and 284 DEmiRNAs were identified. The DEGs were mainly enriched in the complement and coagulation cascade pathways and renin secretion. Immune infiltrating cells including neutrophils, monocytic lineage, and cancer-associated fibroblasts (CAFs) differed significantly between primary tumor tissues and metastatic liver tissues. WGCN analysis obtained 12 modules and identified 62 genes with significant interactions which were mainly related to complement and coagulation cascade and the focal adhesion pathway. The best subset regression analysis and backward stepwise regression analysis were performed, and eight genes were determined, including F10, FGG, KNG1, MBL2, PROC, SERPINA1, CAV1, and SPP1. Further analysis showed four genes, including FGG, KNG1, CAV1, and SPP1 were significantly associated with CRCLM.

CONCLUSIONS

Our study implies complement and coagulation cascade and the focal adhesion pathway play a significant role in the development and progression of CRCLM, and FGG, KNG1, CAV1, and SPP1 may be metastatic markers for its early diagnosis.

Prognostic and Immunological Role of STK38 across Cancers: Friend or Foe?

Although STK38 (serine-threonine kinase 38) has been proven to play an important role in cancer initiation and progression based on a series of cell and animal experiments, no systemic assessment of STK38 across human cancers is available. We firstly performed a pan-cancer analysis of STK38 in this study. The expression level of STK38 was significantly different between tumor and normal tissues in 15 types of cancers. Meanwhile, a prognosis analysis showed that a distinct relationship existed between STK38 expression and the clinical prognosis of cancer patients. Furthermore, the expression of STK38 was related to the infiltration of immune cells, such as NK cells, memory CD4+ T cells, mast cells and cancer-associated fibroblasts in a few cancers. There were three immune-associated signaling pathways involved in KEGG analysis of STK38. In general, STK38 shows a significant prognostic value in different cancers and is closely associated with cancer immunity.

Mitochondrial Aldehyde Dehydrogenase 2 Represents a Potential Biomarker of Biochemical Recurrence in Prostate Cancer Patients

BACKGROUND

We aimed to explore the role of mitochondrial aldehyde dehydrogenase 2 (ALDH2) in prostate cancer (PCa) patients and provide insights into the tumor immune microenvironment (TME) for those patients undergoing radical radiotherapy.

METHODS

We performed all analyses using R version 3.6.3 and its suitable packages. Cytoscape 3.8.2 was used to establish network of competing endogenous RNAs (ceRNAs).

RESULTS

Downregulation of ADLH2 was significantly associated with higher risk of BCR-free survival (HR: 0.40, 95%CI: 0.24-0.68, p = 0.001) and metastasis-free survival (HR: 0.21, 95%CI: 0.09-0.49, p = 0.002). Additionally, ALDH2 repression contributed to significantly shorter BCR-free survival in the TCGA database (HR: 0.55, 95%CI: 0.33-0.93, p = 0.027). For immune checkpoints, patients that expressed a higher level of CD96 had a higher risk of BCR than their counterparts (HR: 1.79, 95%CI: 1.06-3.03, p = 0.032), as well as NRP1 (HR: 2.18, 95%CI: 1.29-3.69, p = 0.005). In terms of the TME parameters, the spearman analysis showed that ALDH was positively associated with B cells (r: 0.13), CD8+ T cells (r: 0.19), neutrophils (r: 0.13), and macrophages (r: 0.17). Patients with higher score of neutrophils (HR: 1.75, 95%CI: 1.03-2.95, p = 0.038), immune score (HR: 1.92, 95%CI: 1.14-3.25, p = 0.017), stromal score (HR: 2.52, 95%CI: 1.49-4.26, p = 0.001), and estimate score (HR: 1.81, 95%CI: 1.07-3.06, p = 0.028) had higher risk of BCR than their counterparts. Our ceRNA network found that PART1 might regulate the expression of ALDH via has-miR-578 and has-miR-6833-3p. Besides, PHA-793887, PI-103, and piperlongumine had better correlations with ALDH2.

CONCLUSIONS

We found that ALDH2 might serve as a potential biomarker predicting biochemical recurrence for PCa patients.

A cuproptosis-related lncRNA signature identified prognosis and tumour immune microenvironment in kidney renal clear cell carcinoma

Kidney renal clear cell carcinoma (KIRC) is a heterogeneous malignant tumor with high incidence, metastasis, and mortality. The imbalance of copper homeostasis can produce cytotoxicity and cause cell damage. At the same time, copper can also induce tumor cell death and inhibit tumor transformation. The latest research found that this copper-induced cell death is different from the known cell death pathway, so it is defined as cuproptosis. We included 539 KIRC samples and 72 normal tissues from the Cancer Genome Atlas (TCGA) in our study. After identifying long non-coding RNAs (lncRNAs) significantly associated with cuproptosis, we clustered 526 KIRC samples based on the prognostic lncRNAs and obtained two different patterns (Cuproptosis.C1 and C2). C1 indicated an obviously worse prognostic outcome and possessed a higher immune score and immune cell infiltration level. Moreover, a prognosis signature (CRGscore) was constructed to effectively and accurately evaluate the overall survival (OS) of KIRC patients. There were significant differences in tumor immune microenvironment (TIME) and tumor mutation burden (TMB) between CRGscore-defined groups. CRGscore also has the potential to predict medicine efficacy.

Identification of prognostic gene expression signatures based on the tumor microenvironment characterization of gastric cancer

Increasing evidence has elucidated that the tumor microenvironment (TME) shows a strong association with tumor progression and therapeutic outcome. We comprehensively estimated the TME infiltration patterns of 111 gastric cancer (GC) and 21 normal stomach mucosa samples based on bulk transcriptomic profiles based on which GC could be clustered as three subtypes, TME-Stromal, TME-Mix, and TME-Immune. The expression data of TME-relevant genes were utilized to build a GC prognostic model—GC_Score. Among the three GC TME subtypes, TME-Stomal displayed the worst prognosis and the highest GC_Score, while TME-Immune had the best prognosis and the lowest GC_Score. Connective tissue growth factor (CTGF), the highest weighted gene in the GC_Score, was found to be overexpressed in GC. In addition, CTGF exhibited a significant correlation with the abundance of fibroblasts. CTGF has the potential to induce transdifferentiation of peritumoral fibroblasts (PTFs) to cancer-associated fibroblasts (CAFs). Beyond characterizing TME subtypes associated with clinical outcomes, we correlated TME infiltration to molecular features and explored their functional relevance, which helps to get a better understanding of carcinogenesis and therapeutic response and provide novel strategies for tumor treatments.

The DDR-related gene signature with cell cycle checkpoint function predicts prognosis, immune activity, and chemoradiotherapy response in lung adenocarcinoma

BACKGROUND

As a DNA surveillance mechanism, cell cycle checkpoint has recently been discovered to be closely associated with lung adenocarcinoma (LUAD) prognosis. It is also an essential link in the process of DNA damage repair (DDR) that confers resistance to radiotherapy. Whether genes that have both functions play a more crucial role in LUAD prognosis remains unclear.

METHODS

In this study, DDR-related genes with cell cycle checkpoint function (DCGs) were selected to investigate their effects on the prognosis of LUAD. The TCGA-LUAD cohort and two GEO external validation cohorts (GSE31210 and GSE42171) were performed to construct a prognosis model based on the least absolute shrinkage and selection operator (LASSO) regression. Patients were divided into high-risk and low-risk groups based on the model. Subsequently, the multivariate COX regression was used to construct a prognostic nomogram. The ssGSEA, CIBERSORT algorithm, TIMER tool, CMap database, and IC50 of chemotherapeutic agents were used to analyze immune activity and responsiveness to chemoradiotherapy.

RESULTS

4 DCGs were selected as prognostic signatures, and patients in the high-risk group had a lower overall survival (OS). The lower infiltration levels of immune cells and the higher expression levels of immune checkpoints appeared in the high-risk group. The damage repair pathways were upregulated, and chemotherapeutic agent sensitivity was poor in the high-risk group.

CONCLUSIONS

The 4-DCGs signature prognosis model we constructed could predict the survival rate, immune activity, and chemoradiotherapy responsiveness of LUAD patients.

Identification of prognostic and immunotherapy-related eRNA ID2-AS1 in bladder cancer

AbstractEnhancer RNAs (eRNAs) can participate in enhancer regulation and target gene transcription, thus affecting the occurrence and development of tumors. In this study, we identified eRNAs closely related to bladder cancer (BLCA). Gene expression profiles and clinical information from The Cancer Genome Atlas (TCGA) database were used in this study. The Atlas of Noncoding RNAs in Cancer (TANRIC) co-expression data was also studied to evaluate correlations between the inferred levels of eRNA and its predicted target genes. Moreover, we evaluated differences in tumor microenvironment between high and low ID2-AS1 expression groups, and predicted the response of high- and low-expression groups to immune checkpoint inhibitor (ICI) treatment. Finally, we analyzed the prognostic value of ID2-AS1 in different tumors. ID2-AS1 and ID2 were identified as eRNAs and target genes related to the prognosis of BLCA. Low ID2-AS1 levels were associated with advanced age, low overall survival, high histological grade, and late BLCA staging. ID2-AS1 appeared to regulate epithelial mesenchymal transition, mitotic spindle assembly, and angiogenesis, thereby affecting BLCA progression. The ID2-AS1 high-expression group had better ICI treatment response. In addition, ID2-AS1 also had prognostic value in other cancers. ID2-AS1 helps predict prognostic and immunotherapeutic effects in BLCA.