Antibodies for profiling the human proteome-The Human Protein Atlas as a resource for cancer research

Exploring the potential biological significance of KDELR family genes in lung adenocarcinoma

The Lys-Asp-Glu-Leu receptor (KDELR) family genes play critical roles in a variety of biological processes in different tumors. Our study aimed to provide a comprehensive analysis of the potential roles of KDELRs in lung adenocarcinoma (LUAD). Utilizing data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database, as well as clinical samples, we conducted a series of analyses and validations using R software tools and various online resources. The results showed that KDELR family genes and proteins were highly expressed and associated with a poor prognosis of LUAD. Promoter hypomethylation and the competing endogenous RNA (ceRNA) network of PCAT6/hsa-miR-326/KDELR1 might be potential causes of aberrant KDELR1 overexpression in LUAD. Three key Transcription factors (TFs) (SPI1, EP300, and MAZ) and a TFs-miRNAs-KDELRs network (involving 11 TFs) might be involved in modulating KDELRs expression abnormalities. Gene Set Enrichment Analysis (GSEA) indicated enrichment of genes highly expressing KDELR1, KDELR2, and KDELR3 in MTORC1_SIGNALING, P53_PATHWAY, and ANGIOGENESIS. Negative correlations between KDELRs expression and CD8 + T cell infiltration, as well as CTLA-4 expression. Our multiple analyses suggested that the KDELRs are important signaling molecules in LUAD. These results provided novel insights for developing prognostic markers and novel therapies of LUAD.

Comprehensive bioinformatics analysis of integrator complex subunits: expression patterns, immune infiltration, and prognostic signature, validated through experimental approaches in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is a common gastrointestinal malignancy with a high incidence and poor prognosis. The subunits of the integrator complex (INTS1-14) play a crucial role in regulating genes dependent on RNA Polymerase II, which may be associated with cancer. However, the role of INTSs in HCC remains unclear. This study aims to comprehensively analyze the clinical value and potential role of INTS family genes in HCC through systematic bioinformatics analysis.

METHODS

We employed various public databases, including UALCAN, HPA, Kaplan-Meier Plotter, GEPIA2, TNMplot, STRING, TIMER, and TISIDB, to investigate the expression levels, clinicopathological correlations, diagnostic and prognostic value, genetic alterations, co-expression network, molecular targets, and immune infiltration of INTSs in HCC. Additionally, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were utilized to investigate the biological functions of genes associated with INTSs. Furthermore, Western blot, real-time fluorescence quantitative reverse transcription polymerase chain reaction (RT-qPCR), and immunohistochemistry techniques were employed to assess the expression of relevant proteins and genes. The proliferation of HCC cells was evaluated using the CCK8 assay.

RESULTS

We found that in HCC, there was a significant upregulation of INTSs at the transcriptional level, particularly INTS1, INTS4, INTS7, and INTS8. Additionally, the protein levels of INTS1 and INTS8 were notably elevated. The overexpression of these INTSs was strongly correlated with tumor stages in HCC patients. INTS1, INTS4, INTS7, and INTS8 exhibited significant diagnostic and prognostic value in HCC. Moreover, their expression was associated with immune infiltrations and activated status, including B cells, CD8 + T cells, CD4 + T cells, NK cells, macrophages, and dendritic cells. Functional predictions indicated that INTS1, INTS4, INTS7, and INTS8 were involved in various cancer-related signaling pathways, such as TRAIL, IFN-gamma, mTOR, CDC42, Apoptosis, and the p53 pathway. Furthermore, we observed a significant upregulation of INTS1, INTS4, INTS7, and INTS8 expression in HCC cell lines compared to normal liver cell lines. The level of INTS1 protein was higher in cancerous tissues compared to adjacent non-cancerous tissues (n = 16), and the suppression of INTS1 resulted in a significant decrease in the proliferation of Huh7 cells.

CONCLUSION

These findings indicate the potential of INTS family genes as diagnostic biomarkers and therapeutic targets in HCC. Further research is needed to understand the underlying mechanisms and explore clinical applications.

Comprehensive analysis of the prognostic value of glutathione S-transferases Mu family members in breast cancer

Breast cancer (BC) remains a significant public health concern globally, with a high number of reported cases and a substantial number of deaths every year. Accumulating reactive oxygen species (ROS) and oxidative stress are related to BC and the Glutathione S-transferases Mu (GSTM) family is one of the most important enzymatic detoxifiers associated with many cancers. In this study, UALCAN, Kaplan-Meier plotter, bc-GenExMiner, cBioPortal, STRING, Enrichr, and TIMER databases were employed to carry out a comprehensive bioinformatic analysis and provide new insight into the prognostic value of GSTMs in BC. GSTM2-5 genes in mRNA and protein levels were found to be expressed at lower levels in breast tumors compared to normal tissues, and reduction in mRNA levels is linked to shorter overall survival (OS) and relapse-free survival (RFS). The lower mRNA levels of GSTMs were strongly associated with the worse Scarff-Bloom-Richardson (SBR) grades (p < 0.0001). The mRNA levels of all five GSTMs were substantially higher in estrogen receptor (ER)-positive and progesterone receptor (PR)-positive compared to ER-negative and PR-negative BC patients. As well, when nodal status was compared, GSTM1, GSTM3, and GSTM5 were significantly higher in nodal-positive BC patients (p < .01). Furthermore, GSTM4 had the most gene alteration (4%) among other family members, and GSTM5 showed the strongest correlation with CD4+ T cells (Cor= .234, p = 2.22e-13). In conclusion, our results suggest that GSTM family members may be helpful as biomarkers for prognosis and as therapeutic targets in BC.

A prognostic four-gene signature and a therapeutic strategy for hepatocellular carcinoma: Construction and analysis of a circRNA-mediated competing endogenous RNA network

BACKGROUND

Hepatocellular carcinoma (HCC) has a poor long-term prognosis. The competition of circular RNAs (circRNAs) with endogenous RNA is a novel tool for predicting HCC prognosis. Based on the alterations of circRNA regulatory networks, the analysis of gene modules related to HCC is feasible.

METHODS

Multiple expression datasets and RNA element targeting prediction tools were used to construct a circRNA-microRNA-mRNA network in HCC. Gene function, pathway, and protein interaction analyses were performed for the differentially expressed genes (DEGs) in this regulatory network. In the protein-protein interaction network, hub genes were identified and subjected to regression analysis, producing an optimized four-gene signature for prognostic risk stratification in HCC patients. Anti-HCC drugs were excavated by assessing the DEGs between the low- and high-risk groups. A circRNA-microRNA-hub gene subnetwork was constructed, in which three hallmark genes, KIF4A, CCNA2, and PBK, were subjected to functional enrichment analysis.

RESULTS

A four-gene signature (KIF4A, CCNA2, PBK, and ZWINT) that effectively estimated the overall survival and aided in prognostic risk assessment in the The Cancer Genome Atlas (TCGA) cohort and International Cancer Genome Consortium (ICGC) cohort was developed. CDK inhibitors, PI3K inhibitors, HDAC inhibitors, and EGFR inhibitors were predicted as four potential mechanisms of drug action (MOA) in high-risk HCC patients. Subsequent analysis has revealed that PBK, CCNA2, and KIF4A play a crucial role in regulating the tumor microenvironment by promoting immune cell invasion, regulating microsatellite instability (MSI), and exerting an impact on HCC progression.

CONCLUSIONS

The present study highlights the role of the circRNA-related regulatory network, identifies a four-gene prognostic signature and biomarkers, and further identifies novel therapy for HCC.

An integrated investigation of sulfotransferases (SULTs) in hepatocellular carcinoma and identification of the role of SULT2A1 on stemness

The cytosolic sulfotransferases (SULTs) are phase II conjugating enzymes, which are widely expressed in the liver and mainly mediate the sulfation of numerous xenobiotics and endogenous compounds. However, the role of various SULTs genes has not been reported in hepatocellular carcinoma (HCC). This study aims to analyze the expression and potential functional roles of SULTs genes in HCC and to identify the role of SULT2A1 in HCC stemness as well as the possible mechanism. We found that all of the 12 SULTs genes were differentially expressed in HCC. Moreover, clinicopathological features and survival rates were also investigated. Multivariate regression analysis showed that SULT2A1 and SULT1C2 could be used as independent prognostic factors in HCC. SULT1C4, SULT1E1, and SULT2A1 were significantly associated with immune infiltration. SULT2A1 deficiency in HCC promoted chemotherapy resistance and stemness maintenance. Mechanistically, silencing of SULT2A1 activated the AKT signaling pathway, on the one hand, promoted the expression of downstream stemness gene c-Myc, on the other hand, facilitated the NRF2 expression to reduce the accumulation of ROS, and jointly increased HCC stemness. Moreover, knockdown NR1I3 was involved in the transcriptional regulation of SULT2A1 in stemness maintenance. In addition, SULT2A1 knockdown HCC cells promoted the proliferation and activation of hepatic stellate cells (HSCs), thereby exerting a potential stroma remodeling effect. Our study revealed the expression and role of SULTs genes in HCC and identified the contribution of SULT2A1 to the initiation and progression of HCC.

HMGN1 loss sensitizes lung cancer cells to chemotherapy

The high mobility group nucleosome binding (HMGN) family, constitutes a large family of non-histone protein family known to bind the acidic patch of the nucleosomes with various key cellular functions. Several studies have highlighted the pivotal roles of HMGNs in the pathogenic process of various cancer types. However, the roles of HMGN family in lung adenocarcinoma (LUAD) have not been fully elucidated. Herein, integrative analyses of multiple-omics data revealed that HMGNs frequently exhibit dysregulation in LUAD. Subsequent analysis of the clinical relevance of HMGN1 demonstrated its association with poor prognosis in LUAD and its potential as a diagnostic marker to differentiate LUAD from healthy controls. Additionally, functional enrichment analysis suggested that HMGN1 was mainly involved in DNA repair. To corroborate these findings, cellular experiments were conducted, confirming HMGN1's crucial involvement in homologous recombination repair and its potential to enhance the sensitivity of LUAD cells to standard chemotherapeutic drugs. This study proposes HMGN1 as a novel prognostic biomarker and a promising target for chemotherapy in lung adenocarcinoma.

The role of transcription factor FOXA1/C2/M1/O3/P1/Q1 in breast cancer

Breast cancer is a common malignancy with the highest mortality rate among women worldwide. Its incidence is on the rise year after year, accounting for more than one-tenth of new cancers worldwide. Increasing evidence suggests that forkhead box (FOX) transcription factors play an important role in the occurrence and development of breast cancer. However, little is known about the relationship between the expression, prognostic value, function, and immune infiltration of FOX transcription factors in tumor microenvironment. We used bioinformatics to investigate expression and function of FOX factor in breast cancer. Our results revealed the expression levels of FOXA1 and FOXM1 were significantly higher in breast cancer tissues than in normal tissues. The high expression of mRNA in FOXA1 (P < .05), FOXM1 (P < .01), and FOXP1 (P < .05) groups was related to tumor stage. Survival analysis results showed that increased FOXP1 mRNA levels were significantly associated with overall survival (OS), recurrence-free survival (RFS), and distant metastasis-free survival (DMFS) in all patients with breast cancer (P < .05). Patients with the FOXA1 high-expression group had better RFS and DMFS than the low-expression group (P < .05), while patients with FOXM1 high-expression group had worse RFS, OS, and DMFS than the low-expression group (P < .05). Meanwhile, mutation analysis showed that genetic alterations in FOX transcription factors were significantly associated with shorter OS and progression-free survival (P < .05), but not with disease-free survival (P = .710) in patients with breast cancer. FOXP1, FOXA1, and FOXM1 may be used as potential biomarkers to predict the prognosis of patients with breast cancer. Functional enrichment indicated that FOX was mainly involved in cell division, cell senescence, cell cycle, and prolactin signaling pathway. In patients with breast cancer, FOXC2 expression was negatively correlated with the infiltration of B cells and positively correlated with the infiltration of neutrophils and dendritic cells. However, FOXM1 was negatively correlated with the infiltration of CD8 + T cells and macrophages and positively correlated with the infiltration of neutrophils and dendritic cells. These findings provided novel insights into the screening of prognostic biomarkers of the FOX family in breast cancer and laid a foundation for further research on the immune infiltration of the FOX transcription factor family members in tumors.

Identification and validation of a novel signature based on macrophage marker genes for predicting prognosis and drug response in kidney renal clear cell carcinoma by integrated analysis of single cell and bulk RNA sequencing

Macrophages are found in a variety of tumors and play a critical role in shaping the tumor microenvironment, affecting tumor progression, metastasis, and drug resistance. However, the clinical relevance of marker genes associated with macrophage in kidney renal clear cell carcinoma (KIRC) has yet to be documented. In this study, we initiated a thorough examination of single-cell RNA sequencing (scRNA-seq) data for KIRC retrieved from the Gene Expression Omnibus (GEO) database and determined 244 macrophage marker genes (MMGs). Univariate analysis, LASSO regression, and multivariate regression analysis were performed to develop a five-gene prognostic signature in The Cancer Genome Atlas (TCGA) database, which could divide KIRC patients into low-risk (L-R) and high-risk (H-R) groups. Then, a nomogram was constructed to predict the survival rate of KIRC patients at 1, 3, and 5 years, which was well assessed by receiver operating characteristic curve (ROC), calibration curve, and decision curve analyses (DCA). Functional enrichment analysis showed that immune-related pathways (such as immunoglobulin complex, immunoglobulin receptor binding, and cytokine-cytokine receptor interaction) were mainly enriched in the H-R group. Additionally, in comparison to the L-R cohort, patients belonging to the H-R cohort exhibited increased immune cell infiltration, elevated expression of immune checkpoint genes (ICGs), and a higher tumor immune dysfunction and exclusion (TIDE) score. This means that patients in the H-R group may be less sensitive to immunotherapy than those in the L-R group. Finally, IFI30 was validated to increase the ability of KIRC cells to proliferate, invade and migrate in vitro. In summary, our team has for the first time developed and validated a predictive model based on macrophage marker genes to accurately predict overall survival (OS), immune characteristics, and treatment benefit in KIRC patients.

Multi-omics pan-cancer analyses identify MCM4 as a promising prognostic and diagnostic biomarker

Minichromosome Maintenance Complex Component 4 (MCM4) is a vital component of the mini-chromosome maintenance complex family, crucial for initiating the replication of eukaryotic genomes. Recently, there has been a growing interest in investigating the significance of MCM4 in different types of cancer. Despite the existing research on this topic, a comprehensive analysis of MCM4 across various cancer types has been lacking. This study aims to bridge this knowledge gap by presenting a thorough pan-cancer analysis of MCM4, shedding light on its functional implications and potential clinical applications. The study utilized multi-omics samples from various databases. Bioinformatic tools were employed to explore the expression profiles, genetic alterations, phosphorylation states, immune cell infiltration patterns, immune subtypes, functional enrichment, disease prognosis, as well as the diagnostic potential of MCM4 and its responsiveness to drugs in a range of cancers. Our research demonstrates that MCM4 is closely associated with the oncogenesis, prognosis and diagnosis of various tumors and proposes that MCM4 may function as a potential biomarker in pan-cancer, providing a deeper understanding of its potential role in cancer development and treatment.

Identification of a novel inflammatory-related gene signature to evaluate the prognosis of gastric cancer patients

BACKGROUND

Gastric cancer (GC) is a highly aggressive malignancy with a heterogeneous nature, which makes prognosis prediction and treatment determination difficult. Inflammation is now recognized as one of the hallmarks of cancer and plays an important role in the aetiology and continued growth of tumours. Inflammation also affects the prognosis of GC patients. Recent reports suggest that a number of inflammatory-related biomarkers are useful for predicting tumour prognosis. However, the importance of inflammatory-related biomarkers in predicting the prognosis of GC patients is still unclear.

AIM

To investigate inflammatory-related biomarkers in predicting the prognosis of GC patients.

METHODS

In this study, the mRNA expression profiles and corresponding clinical information of GC patients were obtained from the Gene Expression Omnibus (GEO) database (GSE66229). An inflammatory-related gene prognostic signature model was constructed using the least absolute shrinkage and selection operator Cox regression model based on the GEO database. GC patients from the GSE26253 cohort were used for validation. Univariate and multivariate Cox analyses were used to determine the independent prognostic factors, and a prognostic nomogram was established. The calibration curve and the area under the curve based on receiver operating characteristic analysis were utilized to evaluate the predictive value of the nomogram. The decision curve analysis results were plotted to quantify and assess the clinical value of the nomogram. Gene set enrichment analysis was performed to explore the potential regulatory pathways involved. The relationship between tumour immune infiltration status and risk score was analysed via Tumour Immune Estimation Resource and CIBERSORT. Finally, we analysed the association between risk score and patient sensitivity to commonly used chemotherapy and targeted therapy agents.

RESULTS

A prognostic model consisting of three inflammatory-related genes (MRPS17, GUF1, and PDK4) was constructed. Independent prognostic analysis revealed that the risk score was a separate prognostic factor in GC patients. According to the risk score, GC patients were stratified into high- and low-risk groups, and patients in the high-risk group had significantly worse prognoses according to age, sex, TNM stage and Lauren type. Consensus clustering identified three subtypes of inflammation that could predict GC prognosis more accurately than traditional grading and staging. Finally, the study revealed that patients in the low-risk group were more sensitive to certain drugs than were those in the high-risk group, indicating a link between inflammation-related genes and drug sensitivity.

CONCLUSION

In conclusion, we established a novel three-gene prognostic signature that may be useful for predicting the prognosis and personalizing treatment decisions of GC patients.

SP140 inhibitor suppressing TRIM22 expression regulates glioma progress through PI3K/AKT signaling pathway

BACKGROUND

SP gene family, consisting of SP100, SP110, SP140, and SP140L, has been implicated in the initiation and advancement of numerous malignancies. Nevertheless, their clinical significance in glioma remains incompletely understood.

METHOD

Expression levels and prognostic significance of SP family members were evaluated in the TCGA and CGGA datasets. Multifactorial analysis was used to identify SP gene family members that can independently impact the prognosis of glioma patients. A SP140-based predictive risk model/nomogram was developed in TCGA dataset and validated in CGGA dataset. The model's performance was evaluated through receiver operating characteristic (ROC) curves, calibration plots, and decision curve analyses. Phenotypic associations of SP140 and TRIM22 were examined through CancerSEA and TIMER. The effect of SP140 inhibitor in glioma progress and TRIM22/PI3K/AKT signaling pathway was confirmed in U251/U87 glioma cells.

RESULTS

The SP family members exhibited elevated expression in gliomas and were negatively correlated with prognosis. SP140 emerged as an independent prognostic factor, and a SP140-based nomogram/predictive risk model demonstrated high accuracy. SP140 inhibitor, GSK761, lead to the suppression of TRIM22 expression and the PI3K/AKT signaling pathway. GSK761 also restrain glioma proliferation, migration, and invasion. Furthermore, SP140 and TRIM22 coexpressed in glioma cells with high level of vascular proliferation, TRIM22 is closely associated with the immune cell infiltration.

CONCLUSION

SP140-based nomogram proved to be a practical tool for predicting the survival of glioma patients. SP140 inhibitor could suppress glioma progress via TRIM22/PI3K/AKT signaling pathway.

TCHH as a Novel Prognostic Biomarker for Patients with Gastric Cancer by Bioinformatics Analysis

Background

This study aims to investigate the clinicopathological significance and prognostic value of Trichohyalin (TCHH) in gastric cancer patients through bioinformatics analysis.

Materials and Methods

Data on TCHH expression and clinicopathological information were sourced from The Cancer Genome Atlas (TCGA). The Wilcoxon signed-rank test was used for evaluating the correlation between TCHH mRNA expression levels and clinicopathological features. The predictive significance of TCHH mRNA expression for overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) in patients with gastric cancer was assessed using Cox regression models. Furthermore, measures of immune cell infiltration in gastric cancer were made, and studies of gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment were also carried out to investigate the possible roles of TCHH in patients with gastric cancer.

Results

Compared to normal tissues, gastric cancer had a considerably higher expression of TCHH mRNA (P < 0.05). Wilcoxon analysis revealed a significant association between TCHH mRNA expression and the pathologic M stage (P = 0.017). High TPMT mRNA levels were also correlated with worse OS, DFS, and PFI in gastric cancer patients (both P < 0.05). TCHH showed significant negative correlations with the levels of NK CD56dim infiltration (r = -0.157, p = 0.002), Th17 cells infiltration (r = -0.235, P < 0.001), and Th2 infiltration (r = -0.195, P < 0.001). Furthermore, enrichment analysis indicated potential involvement in intermediate filament cytoskeleton organization, DNA methylation in gamete generation, cell-cell recognition, and G protein-coupled peptide receptor (GPCRs) activity.

Conclusion

The level of TCHH mRNA may serve as a novel prognostic biomarker for gastric cancer patients.

Pan-cancer analyses of bromodomain containing 9 as a novel therapeutic target reveals its diagnostic, prognostic potential and biological mechanism in human tumours

BACKGROUND

Mutations in one or more genes responsible for encoding subunits within the SWItch/Sucrose Non-Fermentable (SWI/SNF) chromatin-remodelling complexes are found in approximately 25% of cancer patients. Bromodomain containing 9 (BRD9) is a more recently identified protein coding gene, which can encode SWI/SNF chromatin-remodelling complexes subunits. Although initial evaluations of the potential of BRD9-based targeted therapy have been explored in the clinical application of a small number of cancer types, more detailed study of the diagnostic and prognostic potential, as well as the detailed biological mechanism of BRD9 remains unreported.

METHODS

We used various bioinformatics tools to generate a comprehensive, pan-cancer analyses of BRD9 expression in multiple disease types described in The Cancer Genome Atlas (TCGA). Experimental validation was conducted in tissue microarrays and cell lines derived from lung and colon cancers.

RESULTS

Our study revealed that BRD9 exhibited elevated expression in a wide range of tumours. Analysis of survival data and DNA methylation for BRD9 indicated distinct conclusions for multiple tumours. mRNA splicing and molecular binding were involved in the functional mechanism of BRD9. BRD9 may affect cancer progression through different phosphorylation sites or N6 -methyladenosine site modifications. BRD9 could potentially serve as a novel biomarker for diagnosing different cancer types, especially could accurately forecast the prognosis of melanoma patients receiving anti-programmed cell death 1 immunotherapy. BRD9 has the potential to serve as a therapeutic target, when pairing with etoposide in patients with melanoma. The BRD9/SMARCD1 axis exhibited promising discriminative performance in forecasting the prognosis of patients afflicted with liver hepatocellular carcinoma (LIHC) and mesothelioma. Additionally, this axis appears to potentially influence the immune response in LIHC by regulating the programmed death-ligand 1 immune checkpoint. For experimental validation, high expression levels of BRD9 were observed in tumour tissue samples from both lung and colon cancer patients. Knocking down BRD9 led to the inhibition of lung and colon cancer development, likely via the Wnt/β-catenin signalling pathway.

CONCLUSIONS

These pan-cancer study revealed the diagnostic and prognostic potential, along with the biological mechanism of BRD9 as a novel therapeutic target in human tumours.

Upregulation of CCNB2 and a novel lncRNAs-related risk model predict prognosis in clear cell renal cell carcinoma

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is the main type of renal cell carcinoma. Cyclin B2 (CCNB2) is a subtype of B-type cyclin that is associated with the prognosis of several cancers. This study aimed to identify the relationship between CCNB2 and progression of ccRCC and construct a novel lncRNAs-related model to predict prognosis of ccRCC patients.

METHODS

The data were obtained from public databases. We identified CCNB2 in ccRCC using Kaplan-Meier survival analysis, univariate and multivariate Cox regression, and Gene Ontology analysis. External validation was then performed. The risk model was constructed based on prognostic lncRNAs by the LASSO algorithm and multivariate Cox regression. Receiver operating characteristics (ROC) curves were used to evaluate the model. Consensus clustering analysis was performed to re-stratify the patients. Finally, we analyzed the tumor-immune microenvironment and performed screening of potential drugs.

RESULTS

CCNB2 associated with late clinicopathological parameters and poor prognosis in ccRCC and was an independent predictor for disease-free survival. In addition, CCNB2 shared the same expression pattern with known suppressive immune checkpoints. A risk model dependent on the expression of three prognostic CCNB2-related lncRNAs (SNHG17, VPS9D1-AS1, and ZMIZ1-AS1) was constructed. The risk signature was an independent predictor of ccRCC. The area under the ROC (AUC) curve for overall survival at 1-, 3-, 5-, and 8-year was 0.704, 0.702, 0.741, and 0.763. The high-risk group and cluster 2 had stronger immunogenicity and were more sensitive to immunotherapy.

CONCLUSION

CCNB2 could be an important biomarker for predicting prognosis in ccRCC patients. Furthermore, we developed a novel lncRNAs-related risk model and identified two CCNB2-related molecular clusters. The risk model performed well in predicting overall survival and immunological microenvironment of ccRCC.

CC chemokine receptors are prognostic indicators of gastric cancer and are associated with immune infiltration

BACKGROUND

CC chemokine receptors are responsible for regulating the tumor microenvironment (TME) and participating in carcinogenesis and tumor advancement. However, no functional study has investigated CC chemokine receptors in gastric cancer (GC) prognosis, risk, immunotherapy, or other treatments.

METHODS

We conducted a bioinformatics analysis on GC data using online databases, including the Human Protein Atlas (HPA), Kaplan-Meier (KM) plotter, GeneMANIA, MethSurv, the University of ALabama at Birmingham CANcer (UALCAN) Data Analysis Portal, Gene Set Cancer Analysis (GSCA), cBioportal, and Tumor IMmune Estimation Resource (TIMER).

RESULTS

We noted that CC chemokine receptor expression correlated with survival in GC. CC chemokine receptor expression was also strongly linked to different tumor-infiltrating immune cells. Additionally, CC chemokine receptors were found to be broadly drug-resistant in GC.

CONCLUSION

Our study identifed CC chemokine receptor expression helped in predicting the prognosis of patients diagnosed with GC. The expression level of the CC chemokine receptors was also positively related to multiple tumor-infiltrating lymphocytes (TILs). These findings provide evidence to monitor patients with GC using CC chemokine receptors, which can be used as an effective biomarker for predicting the disease prognosis and be regarded as a therapeutic target for modulating the tumor immune microenvironment.

Exosomal hsa-miR-151a-3p and hsa-miR-877-5p are potential novel biomarkers for predicting bone metastasis in lung cancer

Exosomal miRNAs (exo-miRNAs) have arisen as novel diagnostic biomarkers for various cancers. However, few reports on exo-miRNAs related to bone metastasis (BM) in lung cancer exist. This study aims to screen out key exo-miRNAs and estimate their prognostic values for predicting BM in lung cancer. The differentially expressed exo-miRNAs between the highly-metastatic (95D) and lowly-metastatic (A549) human lung cancer cell lines were comprehensively analyzed using high-throughput sequencing followed by bioinformatic analyses. 29 candidate exo-miRNAs were identified, and 101 BM-related target genes were predicted. Enrichment analysis revealed that these target genes were mainly involved in regulating transcription and pathways in cancer. An exosomal miRNA-mRNA regulatory network consisting of 7 key miRNAs and 10 hub genes was constructed. Further function analysis indicated that these 10 hub genes were mainly enriched in regulating cancer's apoptosis and central carbon metabolism. The survival analysis indicated that 7 of 10 hub genes were closely related to prognosis. Mutation analysis showed that lung cancer patients presented certain genetic alterations in the 7 real hub genes. GSEA for a single hub gene suggested that 6 of 7 real hub genes had close associations with lung cancer development. Finally, ROC analysis revealed that hsa-miR-151a-3p and hsa-miR-877-5p provided high diagnostic accuracy in discriminating patients with bone metastasis (BM+) from patients without bone metastasis (BM-). These findings provided a comprehensive analysis of exo-miRNAs and target genes in the regulatory network of BM in lung cancer. In particular, hsa-miR-151a-3p and hsa-miR-877-5p may be novel biomarkers for predicting BM in lung cancer.

PKM2 is a potential prognostic biomarker and related to immune infiltration in lung cancer

Pyruvate kinase M2 (PKM2), a subtype of pyruvate kinase, plays a crucial role as a key enzyme in the final step of glycolysis. It is involved in regulating the tumor microenvironment and accelerating tumor progression. However, the relationship between PKM2 expression and the prognosis and immune infiltration remains unclear in lung cancer. In this study, we analyzed PKM2 expression in pan-cancer, and investigated its association with prognosis and immune cell infiltration of lung cancer by using multiple online databases, including Gent2, Tumor Immune Estimation Resource (TIMER), Gene Expression Profiling Interactive Analysis (GEPIA), PrognoScan, Kaplan-Meier plotter, and The Human Protein Atlas (HPA). The results showed that PKM2 expression is elevated in tumor tissues compared with the adjacent normal tissues of most cancers, including lung cancer. Prognostic analysis indicated that high expression of PKM2 was associated with poorer prognosis in overall lung cancer patients, especially in lung adenocarcinoma (LUAD). Notably, PKM2 exhibited a strong correlation with B cells and CD4+ T cells in LUAD; and with B cells, CD8+ T cells, CD4+ cells, and macrophages in lung squamous cell carcinoma (LUSC). Furthermore, PKM2 expression displayed a significant negative correlation with the expression of immune cell markers in both LUAD and LUSC. These findings suggested that PKM2 could serve as a promising prognostic biomarker for lung cancer and provided insights into its essential role in modulating the immune cell infiltration.

Crosstalk of cuproptosis-related prognostic signature and competing endogenous RNAs regulation in hepatocellular carcinoma

BACKGROUND

Cuproptosis is a new type of programmed cell death involved in the regulation of neuroendocrine tumors, immune microenvironment, and substance metabolism. However, the role of cuproptosis-related genes (CRGs) in Hepatocellular carcinoma (HCC) remains unclear.

METHOD

Through multiple bioinformatics analysis, we constructed a prognostic gene model and competing endogenous RNA (ceRNA) network. The correlation between CRGs and prognosis, immune infiltration, immune checkpoints, microsatellite instability (MSI) and tumor mutational burden (TMB) was analyzed by Kaplan-Meier curve, univariate Cox, multivariate regression, and Spearman's analysis in HCC patients. Besides, the qRT-PCR and immunohistochemistry assays were used to determine prognostic CRGs mRNA and protein expression in HCC.

RESULTS

We established a novel 3-gene signature related to CRGs for evaluating the prognosis of HCC patients. HCC patients with high risk scores had a poor prognosis with an area under the curve of 0.737, 0.646, and 0.634 on 1-year, 3-year, and 5-year receiver operating characteristic curves. Significant correlation was observed between prognostic CRGs and immune infiltration, immune checkpoints, MSI and TMB. We also developed five ceRNA networks to regulate the occurrence and progression of HCC. CDKN2A, DLAT, and PDHA1 protein expression was up-regulated in HCC versus normal tissues. Besides, the mRNA expression levels of CDKN2A, DLAT, GLS, and PDHA1 were elevated in the HCC cell lines compared to the normal liver cell lines.

CONCLUSIONS

This novel prognostic CRGs signature could be accurately predict the prognosis of patients with HCC. The ceRNA regulatory network might be potential prognostic biomarkers and therapeutic targets for HCC patients.

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

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

Fatty acid metabolism-related genes as a novel module biomarker for kidney renal clear cell carcinoma: Bioinformatics modeling with experimental verification

BACKGROUNDS

Lipid metabolism reprogramming is a hallmark of cancer, however, the associations between fatty acid metabolism (FAM) and kidney renal clear cell carcinoma (KIRC) prognosis are still less investigated.

METHODS

The gene expression and clinical data of KIRC were obtained from TCGA. Using Cox regression and LASSO regression, a novel prognostic risk score model based on FAM-related genes was constructed, and a nomogram for prediction of overall survival rate of patients with KIRC was proposed. The correlation between risk score and the immune cell infiltration, immune-related function and tumor mutation burden (TMB) were explored. Finally, a hub gene was extracted from the model, and RT-qPCR, Western blot, Immunohistochemical, EdU, Scratch assay and Transwell experiments were conducted to validate and decipher the biomarker role of the hub gene in KIRC theranostics.

RESULTS

In this study, a novel risk score model and a nomogram were constructed based on 20 FAM-related genes to predict the prognosis of KIRC patients with AUC>0.7 at 1-, 3-, and 5-years. Patients in different subgroups showed different phenotypes in immune cell infiltration, immune-related function, TMB, and sensitivity to immunotherapy. In particular, the hub gene in the model, i.e., ACADM, was significantly down-expressed in human KIRC samples, and the knockdown of OCLN promoted proliferation, migration and invasion of KIRC cells in vitro.

CONCLUSIONS

In this study, a novel risk score model and a module biomarker based on FAM-related genes were screened for KIRC prognosis. More clinical carcinogenic validations will be performed for future translational applications of the findings.

Inflammation-related signature for prognostic prediction, tumor immune, genomic heterogeneity, and drug choices in prostate cancer: Integrated analysis of bulk and single-cell RNA-sequencing

Background

Prostate cancer (PCa) ranks as the second most prevalent malignancy among males on a global scale. Accumulating evidence suggests that inflammation has an intricate relationship with tumorigenesis, tumor progression and tumor immune microenvironment. However, the overall impact of inflammation-related genes on the clinical prognosis and tumor immunity in PCa remains unclear.

Methods

Machine learning methods were utilized to construct and validate a signature using The Cancer Genome Atlas (TCGA) for training, while the Memorial Sloan Kettering Cancer Center (MSKCC) and GSE70769 cohorts for independent validation. The efficacy of the signature in predicting outcomes and its clinical utility were assessed through a series of investigations encompassing in vitro experiments, survival analysis, and nomogram development. The association between the signature and precision medicine was explored via tumor immunity, genomic heterogeneity, therapeutic response, and molecular docking analyses, using bulk and single-cell RNA-sequencing data.

Results

We identified 7 inflammation-related genes with prognostic significance and developed an inflammation-related prognostic signature (IRPS) with 6 genes. Furthermore, we demonstrated that both the IRPS and a nomogram integrating risk score and pathologic T stage exhibited excellent predictive ability for the survival outcomes in PCa patients. Moreover, the IRPS was found to be significantly associated with the tumor immune, genomic heterogeneity, therapeutic response, and drug selection.

Conclusion

IRPS can serve as a reliable predictor for PCa patients. The signature may provide clinicians with valuable information on the efficacy of therapy and help personalize treatment for PCa patients.

OCLN as a novel biomarker for prognosis and immune infiltrates in kidney renal clear cell carcinoma: an integrative computational and experimental characterization

Background

Occludin (OCLN) is an important tight junction protein and has been reported to be abnormally expressed in the development of malignant tumors. However, its biomarker and carcinogenic roles in kidney renal clear cell carcinoma (KIRC) are less investigated.

Methods

The Cancer Genome Atlas database and Human Protein Atlas database were used to analyze the expression of OCLN in KIRC. UALCAN database and methylation-specific PCR assay were used to evaluate the methylation level of OCLN in KIRC. Univariate and multivariate Cox regression analyses were performed to model the prognostic significance of OCLN in KIRC patient cohorts. The correlation between OCLN expression and the immune cell infiltration, immune-related function and immune checkpoints were explored. Finally, EdU, scratch assay and transwell experiments were conducted to validate the role of OCLN in KIRC development.

Results

The expression of OCLN was significantly downregulated in KIRC, compared with normal renal tissues (p<0.001). Patients with low OCLN expression showed a worse prognosis and poorer clinicopathological characteristics. Functional enrichment analysis revealed that OCLN was mainly involved in biological processes such as immune response, immunoglobulin complex circulating and cytokine and chemokine receptor to mediate KIRC development. Immune-related analysis indicated that OCLN could potentially serve as a candidate target for KIRC immunotherapy. OCLN overexpression inhibited proliferation, migration and invasion of KIRC cells in vitro.

Conclusion

OCLN was validated as a candidate prognostic biomarker and therapeutic target of KIRC based both on computational and experimental approaches. More in vivo experiments will be conducted to decode its molecular mechanism in KIRC carcinogenesis in the future work.

Integrative analysis identifies AKAP8L as an immunological and prognostic biomarker of pan-cancer

A-kinase anchoring protein 8L (AKAP8L) belong to the A-kinase anchoring protein (AKAP) family. Recent studies have proved that AKAP8L is associated with the progression of various tumors. To establish a more complete understanding of the significance of AKAP8L across various types of cancers, we conducted a detailed analysis of multiple histological datasets, including the level of gene expression in pancancer, biological function, molecular characteristics, as well as the diagnostic and prognostic value of AKAP8L in pancancer. Furthermore, we focused on renal clear cell carcinoma (KIRC), and of explored the correlation of AKAP8L with clinical characteristics, prognosis of distinct patient subsets, co-expression genes and differentially expressed genes (DEG). We also performed the immunohistochemical staining and semi-quantitative verification of the monoclonal antibody established by AKAP8L. Our findings indicate that AKAP8L expression varied significantly not only across most cancer types, but also across different cancer molecules and immune subtypes. In addition, the robust ability to accurately predict cancer and its strong correlation with the prognosis of cancer strongly suggest that AKAP8L may be a potential biomarker for cancer diagnosis and prognosis. Furthermore, the high expression levels of AKAP8L were related to the worse overall survival (OS), disease-specific survival (DSS) as well as progression-free interval (PFI) of KIRC with statistical significance, especially among distinct clinical subgroups of KIRC. To sum up, AKAP8L has the potential to serve as a critical molecular biomarker for the diagnosis and prognosis of pancancer, an independent prognostic risk factor of KIRC, and a novel molecular target for cancer therapies.

Glycolysis-related biomarker TCIRG1 participates in regulation of renal cell carcinoma progression and tumor immune microenvironment by affecting aerobic glycolysis and AKT/mTOR signaling pathway

BACKGROUND

Renal cell carcinoma (RCC) is a hypermetabolic disease. Abnormal up-regulation of glycolytic signaling promotes tumor growth, and glycolytic metabolism is closely related to immunotherapy of renal cancer. The aim of the present study was to determine whether and how the glycolysis-related biomarker TCIRG1 affects aerobic glycolysis, the tumor microenvironment (TME) and malignant progression of clear cell renal cell carcinoma (ccRCC).

METHODS

Based on The Cancer Genome Atlas (TCGA, n = 533) and the glycolysis-related gene set from MSigDB, we identified the glycolysis-related gene TCIRG1 by bioinformatics analysis, analyzed its immunological properties in ccRCC and observed how it affected the biological function and glycolytic metabolism using online databases such as TIMER 2.0, UALCAN, LinkedOmics and in vitro experiments.

RESULTS

It was found that the expression of TCIRG1, was significantly increased in ccRCC tissue, and that high TCIRG1 expression was associated with poor overall survival (OS) and short progression-free interval (PFI). In addition, TCIRG1 expression was highly correlated with the infiltration immune cells, especially CD4+T cell Th1, CD8+T cell, NK cell, and M1 macrophage, and positively correlated with PDCD1, CTLA4 and other immunoinhibitors, CCL5, CXCR3 and other chemokines and chemokine receptors. More importantly, TCIRG1 may regulate aerobic glycolysis in ccRCC via the AKT/mTOR signaling pathway, thereby affecting the malignant progression of ccRCC cell lines.

CONCLUSIONS

Our results demonstrate that the glycolysis-related biomarker TCIRG1 is a tumor-promoting factor by affecting aerobic glycolysis and tumor immune microenvironment in ccRCC, and this finding may provide a new idea for the treatment of ccRCC by combination of metabolic intervention and immunotherapy.

Integrated computational screening and liquid biopsy approach to uncover the role of biomarkers for oral cancer lymph node metastasis

Cancer is an abnormal, heterogeneous growth of cells with the ability to invade surrounding tissue and even distant organs. Worldwide, GLOBOCAN had an estimated 18.1 million new cases and 9.6 million death rates of cancer in 2018. Among all cancers, Oral cancer (OC) is the sixth most common cancer worldwide, and the third most common in India, the most frequent type, oral squamous cell carcinoma (OSCC), tends to spread to lymph nodes in advanced stages. Throughout the past few decades, the molecular landscape of OSCC biology has remained unknown despite breakthroughs in our understanding of the genome-scale gene expression pattern of oral cancer particularly in lymph node metastasis. Moreover, due to tissue variability in single-cohort studies, investigations on OSCC gene-expression profiles are scarce or inconsistent. The work provides a comprehensive analysis of changed expression and lays a major focus on employing a liquid biopsy base method to find new therapeutic targets and early prediction biomarkers for lymph node metastasis. Therefore, the current study combined the profile information from GSE9844, GSE30784, GSE3524, and GSE2280 cohorts to screen for differentially expressed genes, and then using gene enrichment analysis and protein-protein interaction network design, identified the possible candidate genes and pathways in lymph node metastatic patients. Additionally, the mRNA expression of discovered genes was assessed using real-time PCR, and the Human Protein Atlas database was utilized to determine the protein levels of hub genes in tumor and normal tissues. Angiogenesis was been investigated using the Chorioallentoic membrane (CAM) angiogenesis test. In a cohort of OSCC patients, fibronectin (FN1), C-X-C Motif Chemokine Ligand 8 (CXCL8), and matrix metallopeptidase 9 (MMP9) were significantly upregulated, corroborating these findings. Our identified significant gene signature showed greater serum exosome effectiveness in early detection and clinically linked with intracellular communication in the establishment of the premetastatic niche. Also, the results of the CAM test reveal that primary OC derived exosomes may have a function in angiogenesis. As a result, our study finds three potential genes that may be used as a possible biomarker for lymph node metastasis early detection and sheds light on the underlying processes of exosomes that cause a premetastatic condition.

Machine learning modeling and prognostic value analysis of invasion-related genes in cutaneous melanoma

In this study, we aimed to develop an invasion-related risk signature and prognostic model for personalized treatment and prognosis prediction in skin cutaneous melanoma (SKCM), as invasion plays a crucial role in this disease. We identified 124 differentially expressed invasion-associated genes (DE-IAGs) and selected 20 prognostic genes (TTYH3, NME1, ORC1, PLK1, MYO10, SPINT1, NUPR1, SERPINE2, HLA-DQB2, METTL7B, TIMP1, NOX4, DBI, ARL15, APOBEC3G, ARRB2, DRAM1, RNF213, C14orf28, and CPEB3) using Cox and LASSO regression to establish a risk score. Gene expression was validated through single-cell sequencing, protein expression, and transcriptome analysis. Negative correlations were discovered between risk score, immune score, and stromal score using ESTIMATE and CIBERSORT algorithms. High- and low-risk groups exhibited significant differences in immune cell infiltration and checkpoint molecule expression. The 20 prognostic genes effectively differentiated between SKCM and normal samples (AUCs >0.7). We identified 234 drugs targeting 6 genes from the DGIdb database. Our study provides potential biomarkers and a risk signature for personalized treatment and prognosis prediction in SKCM patients. We developed a nomogram and machine-learning prognostic model to predict 1-, 3-, and 5-year overall survival (OS) using risk signature and clinical factors. The best model, Extra Trees Classifier (AUC = 0.88), was derived from pycaret's comparison of 15 classifiers. The pipeline and app are accessible at https://github.com/EnyuY/IAGs-in-SKCM.

An integrative bioinformatics investigation and experimental validation of chromobox family in diffuse large B-cell lymphoma

BACKGROUND

Diffuse large B-cell lymphoma (DLBCL) is one of the most aggressive malignant tumors. Chromobox (CBX) family plays the role of oncogenes in various malignancies.

METHODS

The transcriptional and protein levels of CBX family were confirmed by GEPIA, Oncomine, CCLE, and HPA database. Screening of co-expressed genes and gene function enrichment analysis were performed by GeneMANIA and DAVID 6.8. The prognostic value, immune cell infiltration and drug sensitivity analysis of CBX family in DLBCL were performed by Genomicscape, TIMER2.0, and GSCALite database. Confirmatory Tests of CBX family protein expression in DLBCL were performed by immunohistochemistry.

RESULTS

The mRNA and protein expressions of CBX1/2/3/5/6 were higher in DLBCL tissues than control groups. Enrichment analysis showed that the functions of CBX family were mainly related to chromatin remodeling, methylation-dependent protein binding, and VEGF signaling pathway. The high mRNA expressions of CBX2/3/5/6 were identified to be associated with short overall survival (OS) in DLBCL patients. Multivariate COX regression indicated that CBX3 was independent prognostic marker. Immune infiltration analysis revealed that the mRNA expressions of CBX family (especially CBX1, CBX5, and CBX6) in DLBCL were significantly correlated with the infiltration of most immune cells (including B cells, CD8 + T cells, CD4 + T cells, neutrophils, monocytes, macrophages, and Treg cells). Meanwhile, there was a strong correlation between the expression levels of CBX1/5/6 and surface markers of immune cells, such as the widely studied PVR-like protein receptor/ligand and PDL-1 immune checkpoint. Notably, our study found that DLBCL cells with CBX1 over-expression were resistant to the common anti-tumor drugs, but CBX2/5 had two polarities. Finally, we confirmed the higher expressions of CBX1/2/3/5/6 in DLBCL tissues compared with control groups by immunohistochemistry.

CONCLUSION

We provided a detailed analysis of the relationship between the CBX family and the prognosis of DLBCL. Distinguished from other studies, We found that high mRNA expressions of CBX2/3/5/6 were associated with poor prognosis in DLBCL patients, and Multivariate COX regression indicated that CBX3 was independent prognostic marker. Besides, our study also found an association between the CBX family and anti-tumour drug resistance, and provided a relationship between CBX family expression and immune cell infiltration.

METTL5 serves as a diagnostic and prognostic biomarker in hepatocellular carcinoma by influencing the immune microenvironment

Despite the abnormal expression of 18S rRNA m6A methyltransferase METTL5 being reported in some types of human malignancies, but its effect on hepatocellular carcinoma (HCC) remains to be unclear. This study aims to elucidate the influences of METTL5 on the carcinogenesis and progression of HCC. Expressions of METTL5 gene, transcript, protein, and promoter methylation in HCC were examined through multiple databases, c-BioPortal was used to confirm the genomic alterations of METTL5, the biological functions, target networks of kinases and microRNAs of METTL5, and its interactive differential genes were investigated through LinkedOmics. The possible correlation of METTL5 with the tumor-related infiltration of immune cells for HCC were explored comprehensively by using the online tools of TIMER and TISIDB. Expressions of METTL5 gene, mRNA, and protein were considerably overexpressed in HCC samples in comparison with healthy samples. The high methylation of the METTL5 promoter was observed in HCC tissues. Elevated METTL5 expression exhibited unfavorable survival outcomes in HCC patients. METTL5 expression were enriched in the signaling pathways of ribosome and oxidative phosphorylation, mismatch repair, and spliceosome through the involvement of several cancer-related kinases and miRNAs. The METTL5 expression has a positive correlation with the infiltration degree of B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils, and dendritic cells in HCC. Marker genes of tumor immune-infiltrated cells have strong connection with METTL5. Furthermore, the upregulation of METTL5 was strongly correlated with the immune regulation of immunomodulators, chemokines, and chemokine receptors in the immune microenvironment. The oncogenesis and development of HCC are closely related to METTL5 expression, and the overexpression of METTL5 resulted in the poor survival outcome of HCC patients by regulating tumor immune microenvironment.

High expression of GPR176 predicts poor prognosis of gastric cancer patients and promotes the proliferation, migration, and invasion of gastric cancer cells

G-protein-coupled receptors (GPCRs) are the most prominent family of cell surface receptors, which can regulate various biological functions and play an essential role in many diseases. GPR176 is a member of the GPCRs family and has been rarely studied in cancer. We aim to investigate the diagnostic and prognostic value of GPR176 in gastric cancer (GC) and explore its potential mechanism. Through the TCGA database and real-time quantitative PCR, we found that the expression level of GPR176 was significantly increased in GC and had good value in the diagnosis and prognosis of GC. Vitro experiments revealed that GPR176 could promote the proliferation, migration, and invasion of GC cells and may be involved in regulating multiple tumors and immune-related signaling pathways. In addition, we found that GPR176 is associated with GC immune infiltration and may affect the immune efficacy of GC patients. In summary, the high GPR176 expression level was associated with poor prognosis, more robust immune infiltration, and worse immunotherapy efficacy in GC patients, suggesting that GPR176 may be an immune-related biomarker for GC that can promote the proliferation, migration, and invasion of GC cells.

Identification of the prognostic biomarkers and their correlations with immune infiltration in colorectal cancer through bioinformatics analysis and in vitro experiments

Colorectal cancer (CRC) is the third most diagnosed malignancy and the second leading cause of cancer death. The objective was to identify novel hub genes that were helpful for prognosis and targeted therapy in CRC. GSE23878, GSE24514, GSE41657, GSE81582 were filtered from the gene expression omnibus (GEO). Differentially expressed genes (DEGs) were identified through GEO2R, which were enriched in the GO term and KEGG pathway in DAVID. PPI network was constructed and analyzed using STRING and hub genes were screened out. The relationships between hub genes and prognoses in CRC were evaluated in GEPIA based on the cancer genome atlas (TCGA) and genotype-tissue expression (GTEx). The transcription factors and miRNA-mRNA interaction networks for hub genes were performed using miRnet and miRTarBase. The relationship between hub genes and tumor-infiltrating lymphocytes were analyzed in TIMER. The protein levels of hub genes were identified in HPA. The expression levels of hub gene in CRC and its effect on the biological effect of CRC cells were identified in vitro. As hub genes, the mRNA levels of BIRC5, CCNB1, KIF20A, NCAPG, and TPX2 were highly expressed in CRC and had excellent prognostic value. The BIRC5, CCNB1, KIF20A, NCAPG, and TPX2 were closely associated with transcription factors, miRNAs, tumor-infiltrating lymphocytes, suggesting their involvement in the regulation of CRC. BIRC5 highly expressed in CRC tissues and cells, and promoted the proliferation, migration, and invasion of CRC cells. BIRC5, CCNB1, KIF20A, NCAPG, and TPX2 are hub genes that serve as promising prognostic biomarkers in CRC. BIRC5 plays an important role in the development and progression of CRC.

Identification and in vitro and in vivo validation of the key role of GSDME in pyroptosis-related genes signature in hepatocellular carcinoma

We used pyroptosis-related genes to establish a risk-score model for prognostic prediction of liver hepatocellular carcinoma (LIHC) patients. A total of 52 pyroptosis-associated genes were identified. Then, data for 374 LIHC patients and 50 normal individuals were acquired from the TCGA database. Through gene expression analyses, differentially expressed genes (DEGs) were determined. The 13 pyroptosis-related genes (PRGs) confirmed as potential prognostic factors through univariate Cox regression analysis were entered into Lasso and multivariate Cox regression to build a PRGs prognostic signature, containing four PRGs (BAK1, GSDME, NLRP6, and NOD2) determined as independent prognostic factors. mRNA levels were evaluated by qRT-PCR, while overall survival (OS) rates were assessed by the Kaplan-Meier method. Enrichment analyses were done to establish the mechanisms associated with differential survival status of LIHC patients from a tumor immunology perspective. Additionally, a risk score determined by the prognostic model could divide LIHC patients into low- and high-risk groups using median risk score as cut-off. A prognostic nomogram, derived from the prognostic model and integrating clinical characteristics of patients, was constructed. The prognostic function of the model was also validated using GEO, ICGC cohorts, and online databases Kaplan-Meier Plotter. Small interfering RNA-mediated knockdown of GSDME, as well as lentivirus-mediated GSDME knockdown, were performed to validate that knockdown of GSDME markedly suppressed growth of HCC cells both in vivo and in vitro. Collectively, our study demonstrated a PRGs prognostic signature that had great clinical value in prognosis assessment.

Identification of the Prognostic Biomarkers CBX6 and CBX7 in Bladder Cancer

BACKGROUND

Chromobox (CBX) proteins are essential components of polycomb group proteins and perform essential functions in bladder cancer (BLCA). However, research on CBX proteins is still limited, and the function of CBXs in BLCA has not been well illustrated.

METHODS AND RESULTS

We analyzed the expression of CBX family members in BLCA patients from The Cancer Genome Atlas database. By Cox regression analysis and survival analysis, CBX6 and CBX7 were identified as potential prognostic factors. Subsequently, we identified genes associated with CBX6/7 and performed enrichment analysis, and they were enriched in urothelial carcinoma and transitional carcinoma. Mutation rates of TP53 and TTN correlate with expression of CBX6/7. In addition, differential analysis indicated that the roles played by CBX6 and CBX7 may be related to immune checkpoints. The CIBERSORT algorithm was used to screen out immune cells that play a role in the prognosis of bladder cancer patients. Multiplex immunohistochemistry staining confirmed a negative correlation between CBX6 and M1 macrophages, as well as a consistent alteration in CBX6 and regulatory T cells (Tregs), a positive correlation between CBX7 and resting mast cells, and a negative correlation between CBX7 and M0 macrophages.

CONCLUSIONS

CBX6 and CBX7 expression levels may assist in predicting the prognosis of BLCA patients. CBX6 may contribute to a poor prognosis in patients by inhibiting M1 polarization and promoting Treg recruitment in the tumor microenvironment, while CBX7 may contribute to a better prognosis in patients by increasing resting mast cell numbers and decreasing macrophage M0 content.

Bioinformatics Prediction and Experimental Verification Identify CAB39L as a Diagnostic and Prognostic Biomarker of Kidney Renal Clear Cell Carcinoma

Background and Objectives: Calcium-binding protein 39-like (CAB39L) has been reported to be downregulated and possessed diagnostic and prognostic values in several types of cancer. However, the clinical value and mechanism of CAB39L in kidney renal clear cell carcinoma (KIRC) remain unclear. Materials and Methods: Bioinformatics analysis was conducted using different databases including TCGA, UALCAN, GEPIA, LinkedOmics, STRING, and TIMER. One-way variance analysis and t-test were chosen to investigate the statistical differences of CAB39L expression in KIRC tissues with different clinical characteristics. The receiver operating characteristic (ROC) curve was chosen to assess the discriminatory capacity of CAB39L. Kaplan-Meier curves were employed for assessing the influence of CAB39L on the progression-free survival (PFS), disease-specific survival (DSS), and overall survival (OS) of KIRC patients. The independent prognostic significance of clinical parameters for OS such as CAB39L expression in KIRC patients was estimated by Cox analysis. A series of in vitro functional experiments and Western blot (WB) and immunohistochemistry (IHC) were used to validate the relative protein expression and function of CAB39L. Results: The mRNA and protein levels of CAB39L were relatively downregulated in KIRC samples. Meanwhile, hypermethylation of the CAB39L promoter region was possibly associated with its low expression in KIRC. The ROC curve showed that the mRNA expression of CAB39L had a strong diagnostic value for both early and late KIRC. Kaplan-Meier survival curves indicated that a higher mRNA level of CAB39L predicted good PFS, DSS, and OS. The mRNA expression of CAB39L was an independent prognostic factor (hazard ratio = 0.6, p = 0.034) identified by multivariate Cox regression analysis. The Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analysis exhibited that CAB39L was mainly associated with substance and energy metabolism. Finally, overexpression of CAB39L impaired the proliferation and metastasis of KIRC cells in vitro. Conclusions: CAB39L possesses prognostic and diagnostic capacity in KIRC.

Expression profile and prognostic values of GATA family members in kidney renal clear cell carcinoma

To investigate the possible diagnostic and prognostic biomarkers of kidney renal clear cell carcinoma (KIRC), an integrated study of accumulated data was conducted to obtain more reliable information and more feasible measures. Using the Tumor Immune Estimation Resource (TIMER), University of Alabama at Birmingham Cancer Data Analysis Portal (UALCAN), Human Protein Atlas (HPA), Kaplan-Meier plotter database, Gene Expression Profiling Interactive Analysis (GEPIA2) database, cBioPortal, and Metascape, we analyzed the expression profiles and prognoses of six members of the GATA family in patients with KIRC. Compared to normal samples, KIRC samples showed significantly lower GATA2/3/6 mRNA and protein expression levels. KIRC's pathological grades, clinical stages, and lymph node metastases were closely related to GATA2 and GATA5 levels. Patients with KIRC and high GATA2 and GATA5 expression had better overall survival (OS) and recurrence-free survival (RFS), while those with higher expression of GATA3/4/6 had worse outcomes. The role and underlying mechanisms of the GATA family in cell cycle, cell proliferation, metabolic processes, and other aspects were evaluated based on Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses. Furthermore, we found that infiltrating immune cells were highly correlated with GATA expression profiles. These results showed that GATA family members may serve as prognostic biomarkers and therapeutic targets for KIRC.

Multimolecular characteristics and role of BRCA1 interacting protein C-terminal helicase 1 (BRIP1) in human tumors: a pan-cancer analysis

BACKGROUND

The aberrant expression of BRIP1 was associated with several cancers; however, the panoramic picture of BRIP1 in human tumors remains unclear. This study aims to explore the pan-cancerous picture of the expression of BRIP1 across 33 human cancers.

METHODS

Based on the data from TCGA and GTEx, a series of bioinformatic analyses were applied to systematically explore the genetic landscape and biologic function of BRIP1 in 33 human tumors.

RESULTS

We observed prognosis-related differential BRIP1 expressions between various carcinomas and the corresponding normal tissues. "Basal transcription factors," "homologous recombination," "nucleotide excision repair," and DNA metabolism pathways may play a role in the functional mechanisms of BRIP1. Patients with uterine corpus endometrial carcinoma presented with the highest alteration frequency of BRIP1 (nearly 10%). Single-nucleotide and copy number variations of BRIP1 were noticed in multiple cancers, and the expression of BRIP1 is significantly regulated by copy number variation in breast invasive carcinoma and lung squamous cell carcinoma. BRIP1 expression is negatively correlated with the DNA methylation levels in many tumors and is associated with the activation of apoptosis, cell cycle, DNA damage response, and inhibition of hormone ER and RNS/MARK signaling pathways. Moreover, a positive correlation was observed between BRIP1 expression and the immune infiltration levels of cancer-associated fibroblasts and CD8+ T cells in lung adenocarcinoma.

CONCLUSION

Our pan-cancer analysis of BRIP1 provides a valuable resource for understanding the multimolecular characteristics and biological function of BRIP1 across human cancers.

A comprehensive pan-cancer analysis unveiling the oncogenic effect of plant homeodomain finger protein 14 (PHF14) in human tumors

The plant homeodomain (PHD) finger refers to a protein motif that plays a key role in the recognition and translation of histone modification marks by promoting gene transcriptional activation and silencing. As an important member of the PHD family, the plant homeodomain finger protein 14 (PHF14) affects the biological behavior of cells as a regulatory factor. Several emerging studies have demonstrated that PHF14 expression is closely associated with the development of some cancers, but there is still no feasible pan-cancer analysis. Based on existing datasets from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO), we performed a systematic analysis of the oncogenic role of the PHF14 gene in 33 human cancers. The expression level of PHF14 was significantly different between different types of tumors and adjacent normal tissues, and the expression or genetic alteration of PHF14 gene was closely related to the prognosis of most cancer patients. Levels of cancer-associated fibroblasts (CAFs) infiltration in various cancer types were also observed to correlate with PHF14 expression. In some tumors, PFH14 may play a role in tumor immunity by regulating the expression levels of immune checkpoint genes. In addition, the results of enrichment analysis showed that the main biological activities of PHF14 were related to various signaling pathways or chromatin complex effects. In conclusion, our pan-cancer research shows that the expression level of PHF14 is closely related to the carcinogenesis and prognosis of certain tumors, which needs to be further verified by more experiments and more in-depth mechanism exploration.

Identification of a copper metabolism-related gene signature for predicting prognosis and immune response in glioma

BACKGROUND

Gliomas are highly refractory intracranial cancers characterized by genetic and transcriptional heterogeneity. However, therapeutic options are limited. In the last years, copper-induced cell death is becoming a prospective treatment strategy for gliomas and other solid tumors, but copper metabolism-related genes associated with cancer development remain unclear.

METHODS

We first collected gene expression data from The Cancer Genome Atlas (TCGA) to identify significantly differentially expressed copper metabolism-related genes in gliomas. Using these genes, we performed COX regression and Least Absolute Shrinkage and Selection Operator (LASSO) regression to construct the prognostic model. The prognostic value of the model was further validated by CGGA testing set. Subsequently, functional analyses were carried out, including gene set enrichment analysis (GSEA), immune infiltration analysis, and mutation analysis. Finally, the expression levels of these genes were verified by immunohistochemical analysis.

RESULTS

The prognostic model consisted of 7 genes: CDK1, LOXL2, LOXL3, NFE2L2, SLC31A1, SUMF1 and FDX1. According to this prognosis model, glioma patients could be split into the high-risk group or low-risk group, and the low-risk group showed significantly better prognostic survival (p < 0.001). Moreover, the high-risk group had higher levels of immune cell infiltration, immune checkpoint genes expression, and higher tumor mutational burden (TMB), which indicates that they might benefit more from immunotherapy. Finally, we confirmed the expression level of FDX1, SUMF1, and SLC31A1 protein as significantly different in glioblastoma, lower-grade glioma, and non-tumor brain tissues by immunohistochemical analysis, and the high expression of FDX1 and SLC31A1 protein was related to poor survival in glioma patients.

CONCLUSIONS

Our study could contribute to the prognosis prediction and decision-making in patients with gliomas.

Comprehensive Analysis of the Expression and Prognosis of chromobox Family Members in Breast Cancer

BACKGROUND

Chromobox proteins are canonical components of the Polycomb group family and play pivotal roles in several cancers. However, little is known about the function, prognostic value and drug sensitivity of CBX family members in breast cancer.

METHODS

In this study we investigated the expression, prognosis value and drug sensitivity of CBX family in breast cancer using the ONCOMINE, GEPIA, Human Protein Atlas and Kaplan-Meier Plotter databases, etc. and preliminary verified the expression of CBX family in breast cancer cell lines by RT-qPCR.

RESULTS

We found that the expression levels of CBX1/2/3/4/8 members were elevated in breast cancer tissues compared to adjacent normal breast tissues, while the expression levels of CBX6/7 genes were reduced in breast cancer tissue. In vitro qRT-PCR validated the expression differences of CBX1/2/3/4/8 in breast cancer cell lines. Further analysis showed expression of CBX family members was remarkably correlated with cancer subgroups. As nodal metastasis status increased, the mRNA expression of CBX1/2/3/4/8 members tended to be higher, while CBX6/7 tended to be lower. The expression of CBX1/2/3 was higher in patients with TP53 mutation and CBX6/7 expression tended to be lower in patients with TP53 mutation groups. High transcription levels of CBX2/3 were significantly associated with shorter overall survival in breast cancer patients, while lower expression of CBX4/5/6/7 members was associated with unfavorable overall survival. Moreover, a high mutation rate of CBX gene members (43%) was observed in breast cancer patients, and genetic alterations in CBX genes was associated with poor prognosis.

CONCLUSION

Taken together, our results indicated that CBX2/3/6/7/8 could be considered prognostic and therapeutic biomarkers of breast cancer and are worthy of further study.

A combined analysis of bulk and single-cell sequencing data reveals metabolic enzyme, pyruvate dehydrogenase E1 subunit beta (PDHB), as a prediction biomarker for the tumor immune response and immunotherapy

Pyruvate dehydrogenase E1 subunit beta (PDHB) is located in mitochondria and catalyzes the conversion of glucose-derived acetyl-CoA. The detailed roles of PDHB in human cancers is unclear. Here, through comprehensive bioinformatics analysis, we found that PDHB was aberrantly expressed in multiple human cancers and is associated with patients' clinical stage. The abnormal expression of PDHB was related to the prognostic values of cancers, such as kidney renal clear cell carcinoma (KIRC) and kidney renal papillary cell carcinoma (KIRP). The Wanderer database with clinical data from Cancer Genome Atlas (TCGA) showed a significant correlation between PDHB expression and the pathologic stage of KIRP patients. We also evaluated the mutation profiles of PDHB in pan-cancer, and showed its roles on the patients' prognosis. At last, from several immunity algorithms, we demonstrated that the expression of PDHB was correlated with the infiltration of various immune cells in pan-cancer. Moreover, the aberrant PDHB had effects on the response to immune checkpoint inhibitors in cancer patients, such as anti-PD-1. Taken together, our study demonstrated the prognostic values of PDHB in pan-cancers. PDHB may be a potential molecular marker to predicting the immune response in cancer patients.

SMYD Family Members Serve as Potential Prognostic Markers and Correlate with Immune Infiltrates in Gastric Cancer

Background

The SMYD family comprises a group of genes encoding lysine methyltransferases, which are closely related to tumorigenesis. However, a systematic understanding of their role in gastric cancer (GC) is lacking.

Methods

Using databases and tools such as the Cancer Genome Atlas, Human Protein Atlas, Kaplan-Meier Plotter, Gene Expression Profiling Interactive Analysis, and Metascape, we comprehensively analyzed differences in SMYD expression and its prognostic value as well as the association of SMYDs with immune cell infiltration, tumor mutational burden (TMB), and microsatellite instability (MSI). We conducted functional enrichment analysis and explored a competing endogenous RNA mechanism regulating SMYD mRNA and protein levels in patients with GC.

Results

In GC, the expression of SMYD2/3/4/5 mRNA was significantly upregulated, as opposed to that of SMYD1 mRNA, which was significantly downregulated. The protein levels of SMYDs were consistent with mRNA levels. SMYD1/2/4/5 was negatively correlated with overall survival; SMYD1/2/3/5 was negatively correlated with progression-free survival. Our SMYD-based signature and nomogram model may be useful for inferring the prognosis of GC. All SMYDs were closely associated with the infiltration of six immune cell types: uncharacterized, CD8⁺ T, CD4⁺ T, macrophage, endothelial, and B cells. TMB was significantly negatively correlated with SMYD1 expression, while a significant positive correlation was observed with SMYD2/5. Furthermore, MSI was significantly positively correlated with SMYD2/5 expression. Long non-coding RNAs, such as chr22-38_28785274-29006793.1, XLOC_002309, and CTD-2008N3.1, were suggested to regulate SMYD expression by sponging multiple microRNAs.

Conclusion

SMYDs are differentially expressed in GC and are thus potential prognostic markers. SMYD expression is closely related to immune infiltration, TMB, and MSI, all of which are closely related to the response to targeted immune therapy.

CD93 serves as a potential biomarker of gastric cancer and correlates with the tumor microenvironment

BACKGROUND

The tumor microenvironment (TME) plays an important role in the growth and expansion of gastric cancer (GC). Studies have identified that CD93 is involved in abnormal tumor angiogenesis, which may be related to the regulation of the TME.

AIM

To determine the role of CD93 in GC.

METHODS

Transcriptomic data of GC was investigated in a cohort from The Cancer Genome Atlas. Additionally, RNA-seq data sets from Gene Expression Omnibus (GSE118916, GSE52138, GSE79973, GSE19826, and GSE84433) were applied to validate the results. We performed the immune infiltration analyses using ESTIMATE, CIBERSORT, and ssGSEA. Furthermore, weighted gene co-expression network analysis (WGCNA) was conducted to identify the immune-related genes.

RESULTS

Compared to normal tissues, CD93 significantly enriched in tumor tissues (t = 4.669, 95%CI: 0.342-0.863, P < 0.001). Higher expression of CD93 was significantly associated with shorter overall survival (hazard ratio = 1.62, 95%CI: 1.09-2.4, P = 0.017), less proportion of CD8 T and activated natural killer cells in the TME (P < 0.05), and lower tumor mutation burden (t = 4.131, 95%CI: 0.721-0.256, P < 0.001). Genes co-expressed with CD93 were mainly enriched in angiogenesis. Moreover, 11 genes were identified with a strong relationship between CD93 and the immune microenvironment using WGCNA.

CONCLUSION

CD93 is a novel prognostic and diagnostic biomarker for GC, that is closely related to the immune infiltration in the TME. Although this retrospective study was a comprehensive analysis, the prospective cohort studies are preferred to further confirm these conclusions.

Fatty acid synthase (FASN) inhibits the cervical squamous cell carcinoma (CESC) progression through the Akt/mTOR signaling pathway

BACKGROUND

Cervical cancer is a malignant tumor that affects females and remains the cause of the highest morbidity and mortality among women worldwide. Currently, gene-targeted therapy is a novel treatment option for clinicians. Furthermore, fatty acid synthase (FASN) plays a therapeutic role in various cancers. Nonetheless, the mechanism of action of this enzyme in cervical squamous cell carcinoma and cervical duct adenocarcinoma (CESC) has not yet been reported.

METHODS

RNA (ribonucleic acid) sequencing data and clinical information were obtained from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx). The expression levels of FASN were obtained from Gene Expression Profiling Interactive Analysis 2 (GEPIA2) and Human Protein Atlas (HPA). Univariate and multivariate Cox regression analyses were utilized to assess independent prognostic factors associated with survival. A nomogram and receiver operating characteristic curve (ROC) were employed to evaluate survival and predictive power. In vitro experiments and real-time quantitative reverse transcription polymerase chain reaction (RT-qPCR) were conducted to identify cell interference efficiency. MTS, monoclonal formation, and EDU assays were used to determine cell viability. Wound healing and invasion assays (transwell assay) were used to evaluate cell migration and invasion. Finally, Hoechst 33342, propidium iodide (PI) staining and Annexin V-FITC staining were used to assess apoptosis and the cell cycle, while western blotting was utilized to determine the protein expression levels.

RESULTS

FASN was aberrantly expressed in various cancers, including CESC, where it was highly expressed. Kaplan-Meier, univariate, multivariate Cox regression analyses and ROC curve indicated that FASN is a potential key indicator of survival prognosis among CESC patients and demonstrated good predictive ability and efficacy. Complementary in vitro experiments confirmed that FASN is an important target for CESC therapy.

CONCLUSION

The current study validated the biological and clinical significance of FASN in CESC prognosis, suggesting that FASN knockdown may exert antitumor activity against cervical cancer through the Akt/mTOR signaling pathway.

Identification of EMP1 as a critical gene for cisplatin resistance in ovarian cancer by using integrated bioinformatics analysis

BACKGROUND

Cisplatin resistance is among the main reasons for the poor prognosis of ovarian cancer (OC) patients. Until now, effective biomarkers for predicting cisplatin resistance in OC and specific drugs for reversing this resistance are lacking. This study identified the critical gene associated with cisplatin resistance in OC and provided a potential target for overcoming this resistance.

METHODS

Differentially expressed genes between cisplatin-resistant and -sensitive OCs were identified by screening public datasets. Survival analysis was conducted to screen prognosis-related DEGs. CIBERSORT, ESTIMATE, and immune checkpoint genes were used to assess the association between EMP1 expression and tumor microenvironment features. CTRP and GDSC databases were employed to analyze the correlation between EMP1 expression and cisplatin resistance. Furthermore, immunohistochemistry, qPCR, Western blotting, siRNA interference, and the CCK8 assay were performed to verify the role of EMP1 in cisplatin resistance in vitro. Finally, xenograft mouse models were generated to further confirm the role of EMP1 in cisplatin resistance in vivo.

RESULTS

EMP1 was identified as a critical gene associated with cisplatin resistance in OC. According to bioinformatics analyses, increased EMP1 expression was linked to higher stromal/ESTIMATE scores as well as greater ICG expression levels. The in vitro experiments showed that EMP1 was highly expressed in cisplatin-resistant OC tissues and cells, and silencing this EMP1 expression enhanced OC cell sensitivity to cisplatin. Finally, in vivo experiments confirmed that EMP1 promotes tumor growth and cisplatin resistance.

CONCLUSIONS

EMP1 can act as a predictive biomarker for cisplatin resistance in OC and as a potential therapeutic target.

Molecular subtypes based on cuproptosis-related genes and tumor microenvironment infiltration characteristics in pancreatic adenocarcinoma

BACKGROUND

Multiple molecular subtypes with distinct clinical outcomes in pancreatic adenocarcinoma (PAAD) have been identified in recent years. Cuproptosis is a new form of cell death that likely involved in tumor progression. However, the cuproptosis-related molecular subtypes as well as its mediated tumor microenvironment (TME) cell infiltration characteristics largely remain unclear.

METHODS

Expression profiles of 10 cuproptosis-related genes (CRGs) and their association with patient survival, TME, cancer stemness and drug resistance were studied in 33 cancer types using the TCGA pan-cancer data. Using 437 PAAD samples from five cohorts (TCGA-PAAD cohort and four GEO cohorts), we explored the molecular subtypes mediated by CRGs, along with the associated TME cell infiltration. Unsupervised methods were utilized to perform cuproptosis subtype clustering. The cuproptosis score was constructed using the COX regression model with least absolute shrinkage and selection operator regression (LASSO) algorithm to quantify the cuproptosis characteristics of a single tumor.

RESULTS

The expression of 10 CRGs varies in different cancer types with striking inter- and intra- cancer heterogeneity. We integrated the genomic profiling of the CRGs and identified three distinct cuproptosis subtypes, and found that multi-layer CRG alterations were correlated with patient prognosis and TME cell infiltration characteristics. In addition, a cuproptosis score signature was constructed to predict prognosis, and its clinical impacts were characterized in the TCGA-PAAD cohort. The cuproptosis signature was significantly associated with prognosis, tumor subtypes, CD8 T-cell infiltration, response to immune checkpoint inhibitors (ICIs) and chemotherapeutic drug sensitivity. Furthermore, the expression patterns of CRGs in pancreatic cancer cells and normal controls were validated, which was almost consistent with the results from the public database. The expression level and prognostic predictive capability of DLAT were verified in 97 PAAD patients from our patient cohort.

CONCLUSIONS

These findings may help understand the roles of CRGs in PAAD and the molecular characterization of cuproptosis subtypes. In addition, the cuproptosis score could serve as a promising biomarker for predicting prognosis and response to immunotherapy in PAAD patients.

Overexpression of TPM4 is associated with worse prognosis and immune infiltration in patients with glioma

BACKGROUND

Tropomyosin 4 (TPM4), a member of the tropomyosin family, is aberrantly expressed and plays an important role in a variety of cancers. However, studies on TPM4 in glioma patients are currently lacking.

OBJECTIVE

Our study aimed to evaluate the diagnostic and prognostic characteristics of TPM4 in glioma and its correlation with immune infiltration.

METHODS

Bioinformatic analysis was performed to determine whether TPM4 has diagnostic and prognostic value for glioma. The following databases and analytical tools were used to explore the clinical significance of TPM4 in glioma: TCGA, GTEx, GEO, STRING, and TISIDB.

RESULTS

Our study showed that the mRNA and protein expression levels of TPM4 were significantly higher in glioma than in healthy brain tissue. Kaplan-Meier analysis indicated that high expression of TPM4 in glioma correlated with poor prognosis. Univariate Cox analysis indicated that the high expression level of TPM4 in glioma was an independent prognostic characteristic for low overall survival (OS). The areas under the 1-year survival ROC, 2-year survival ROC, and 3-year survival ROC were all greater than 0.8. GO and KEGG enrichment analysis and GSEA showed that humoral immune response and cytokine receptor interaction were significantly enriched in the TPM4 high expression group, where M phase of the cell cycle, neutrophil degranulation, signaling by interleukins, and signaling by rho GTPases were significantly enriched. Furthermore, according to the analysis of immune cell infiltration, TPM4 was associated with tumor infiltration of a variety of immune cells.

CONCLUSIONS

In conclusion, our study suggests that TPM4 may be an effective prognostic biomarker for glioma patients, providing new ideas and research directions for glioma research.

A novel prognostic gene set for colon adenocarcinoma relative to the tumor microenvironment, chemotherapy, and immune therapy

Background: Colon adenocarcinoma (COAD) is a common aggressive malignant tumor. Heterogeneity in tumorigenesis and therapy response leads to an unsatisfactory overall survival of colon adenocarcinoma patients. Our study aimed to identify tools for a better prediction of colon adenocarcinoma prognosis, bolstering the development of a better personalized treatment and management. Method: We used the least absolute shrinkage and selection operator (LASSO) Cox model to analyze the prognosis-related gene datasets from the Gene Expression Omnibus (GEO) database and verified them using The Cancer Genome Atlas (TCGA) database. The area under the curve (AUC) was calculated using the receiver operating characteristic (ROC) curve to evaluate the predictive ability of the risk score model. Gene Set Enrichment Analysis (GSEA) was used to identify the significantly enriched and depleted biological processes. The tumor immune dysfunction and exclusion (TIDE) algorithm was taken to explore the relationship between the risk score and immunotherapy. The observations collectively helped us construct a nomogram to predict prognosis. Finally, the correlation between drug sensitivity and prognostic gene sets was conducted based on the Cancer Therapeutics Response Portal (CTRP) analyses. Results: We constructed a scoring model to assess the significance of the prognosis risk-related gene signatures, which was relative to common tumor characteristics and tumor mutational burdens. Patients with a high-risk score had higher tumor stage and poor prognosis (p< 0.05). Moreover, the expressions of these genes were in correlation with changes in the tumor microenvironment (TME). The risk score is an independent prognostic factor for COAD (p< 0.05). The accuracy of the novel nomogram model with a risk score and TNM-stage prediction prognosis in the predicting prognosis was higher than that of the TNM stage. Further analysis showed that a high-risk score was associated with tumor immune rejection. Patients with a low-risk score have a better prognosis with chemotherapy than those with a high-risk score. Compared to patients in the high-risk group, patients in the low-risk group had a significant survival advantage after receiving chemotherapy. In addition, the prognostic gene sets aid the assessment of drug sensitivity. Conclusion: This study establishes a new prognostic model to better predict the clinical outcome and TME characteristics of colon adenocarcinoma. We believe, our model also serves as a useful clinical tool to strengthen the functioning of chemotherapy, immunotherapy, and targeted drugs.

Immune microenvironment infiltration landscape and immune-related subtypes in prostate cancer

Background

The tumor microenvironment (TME) primarily comprises cancer cells, cancer-infiltrating immune cells, and stromal cells. The tumor cells alter the TME by secreting signaling molecules to induce immune tolerance. The immune cell infiltrating the TME influences the prognosis of patients with cancers. However, immune cell infiltration (ICI) in the TME of patients with prostate cancer (PC) has not yet been studied.

Methods

In this study, we used Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) and Estimation of Stromal and Immune cells in Malignant Tumors using Expression data (ESTIMATE) algorithms to identify three ICI clusters based on 1,099 genes associated with ICI in the TME. The patients were classified into three distinct ICI gene clusters based on overlapping differentially expressed genes in ICI clusters. Furthermore, the ICI scores were calculated using principal component analysis.

Results

The results revealed that patients with high ICI scores had poor prognoses and reduced expression of immune-checkpoint genes and immune-related genes. Furthermore, the transforming growth factor-beta (TGF-β) and WNT-β signaling pathways were enriched in the high ICI score subgroup, which suggests that suppression of T cells could contribute to poor prognosis of patients with PC. A positive correlation was observed between the high-ICI-score subgroup and the high tumor mutation burden (TMB) value. Patients with low ICI scores could benefit from immunotherapy, indicating that the ICI score could be used to predict the efficacy of immunotherapeutic response.

Conclusions

In summary, we provide a comprehensive overview of the landscape of ICI in PC, which could aid in designing the strategies for immunotherapy for patients with PC.

Multi-omics analysis reveals a macrophage-related marker gene signature for prognostic prediction, immune landscape, genomic heterogeneity, and drug choices in prostate cancer

Introduction

Macrophages are components of the innate immune system and can play an anti-tumor or pro-tumor role in the tumor microenvironment owing to their high heterogeneity and plasticity. Meanwhile, prostate cancer (PCa) is an immune-sensitive tumor, making it essential to investigate the value of macrophage-associated networks in its prognosis and treatment.

Methods

Macrophage-related marker genes (MRMGs) were identified through the comprehensive analysis of single-cell sequencing data from GSE141445 and the impact of macrophages on PCa was evaluated using consensus clustering of MRMGs in the TCGA database. Subsequently, a macrophage-related marker gene prognostic signature (MRMGPS) was constructed by LASSO-Cox regression analysis and grouped based on the median risk score. The predictive ability of MRMGPS was verified by experiments, survival analysis, and nomogram in the TCGA cohort and GEO-Merged cohort. Additionally, immune landscape, genomic heterogeneity, tumor stemness, drug sensitivity, and molecular docking were conducted to explore the relationship between MRMGPS and the tumor immune microenvironment, therapeutic response, and drug selection.

Results

We identified 307 MRMGs and verified that macrophages had a strong influence on the development and progression of PCa. Furthermore, we showed that the MRMGPS constructed with 9 genes and the predictive nomogram had excellent predictive ability in both the TCGA and GEO-Merged cohorts. More importantly, we also found the close relationship between MRMGPS and the tumor immune microenvironment, therapeutic response, and drug selection by multi-omics analysis.

Discussion

Our study reveals the application value of MRMGPS in predicting the prognosis of PCa patients. It also provides a novel perspective and theoretical basis for immune research and drug choices for PCa.

Central resources of variant discovery and annotation and its role in precision medicine

Rapid technological advancement in high-throughput genomics, microarray, and deep sequencing technologies has accelerated the possibility of more complex precision medicine research using large amounts of heterogeneous health-related data from patients, including genomic variants. Genomic variants can be identified and annotated based on the reference human genome either within the sequence as a whole or in a putative functional genomic element. The American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) mutually created standards and guidelines for the appraisal of proof to expand consistency and straightforwardness in clinical variation interpretations. Various efforts toward precision medicine have been facilitated by many national and international public databases that classify and annotate genomic variation. In the present study, several resources are highlighted with recognition and data spreading of clinically important genetic variations.

IGF2BP2 serves as a core m6A regulator in head and neck squamous cell carcinoma

Methylation of N6 adenosine (m6A) plays a crucial role in the development and progression of cancers. Its modification is regulated by three types of m6A-related regulators (methyltransferases (writers), demethylases (erasers), and RNA-binding proteins (readers)). Till now, the functions and roles of these regulators in head and neck squamous cell carcinoma (HNSC) remain largely unexplored. Therefore, we utilized the open HNSC dataset in The Cancer Genome Atlas (TCGA), four different cell lines, and our HNSC patient samples (n=40) to explore the clinical significance of 19 m6A regulators, and selected the most significant prognosis-related regulator. Authentic analyses based on online websites were also used in the study (Oncomine, UALCAN, Kaplan-Meier plotter, Human Protein Atlas (HPA), cBioPortal, LinkedOmics, String, etc.). From the results, general overexpression of m6A regulators was observed in pan-cancer, especially in HNSC. IGF2BP2 was recognized as the hub m6A regulator, which was an independent, unfavorable prognostic factor in HNSC. Its mRNA and protein expression in HNSC were significantly up-regulated. Gene mutation types of IGF2BP2 in HNSC (32%) were mainly mRNA High or Amplification, which represented the high expression of IGF2BP2. And these mutations were associated with a poor prognosis. In functional analysis, IGF2BP2 was negatively correlated to tumor immune infiltration in HNSC. Finally, HMGA2 might interact with the IGF2BP2 in HNSC. In conclusion, IGF2BP2 serves as a core m6A regulator among all regulators in HNSC, which has a high expression and predicts the poor prognosis of HNSC patients independently. IGF2BP2 might bring a new direction for HNSC treatment in the future.