Exploring TCGA database for identification of potential prognostic genes in stomach adenocarcinoma

The MexTAg collaborative cross: host genetics affects asbestos related disease latency, but has little influence once tumours develop

Objectives: This study combines two innovative mouse models in a major gene discovery project to assess the influence of host genetics on asbestos related disease (ARD). Conventional genetics studies provided evidence that some susceptibility to mesothelioma is genetic. However, the identification of host modifier genes, the roles they may play, and whether they contribute to disease susceptibility remain unknown. Here we report a study designed to rapidly identify genes associated with mesothelioma susceptibility by combining the Collaborative Cross (CC) resource with the well-characterised MexTAg mesothelioma mouse model. Methods: The CC is a powerful mouse resource that harnesses over 90% of common genetic variation in the mouse species, allowing rapid identification of genes mediating complex traits. MexTAg mice rapidly, uniformly, and predictably develop mesothelioma, but only after asbestos exposure. To assess the influence of host genetics on ARD, we crossed 72 genetically distinct CC mouse strains with MexTAg mice and exposed the resulting CC-MexTAg (CCMT) progeny to asbestos and monitored them for traits including overall survival, the time to ARD onset (latency), the time between ARD onset and euthanasia (disease progression) and ascites volume. We identified phenotype-specific modifier genes associated with these traits and we validated the role of human orthologues in asbestos-induced carcinogenesis using human mesothelioma datasets. Results: We generated 72 genetically distinct CCMT strains and exposed their progeny (2,562 in total) to asbestos. Reflecting the genetic diversity of the CC, there was considerable variation in overall survival and disease latency. Surprisingly, however, there was no variation in disease progression, demonstrating that host genetic factors do have a significant influence during disease latency but have a limited role once disease is established. Quantitative trait loci (QTL) affecting ARD survival/latency were identified on chromosomes 6, 12 and X. Of the 97-protein coding candidate modifier genes that spanned these QTL, eight genes (CPED1, ORS1, NDUFA1, HS1BP3, IL13RA1, LSM8, TES and TSPAN12) were found to significantly affect outcome in both CCMT and human mesothelioma datasets. Conclusion: Host genetic factors affect susceptibility to development of asbestos associated disease. However, following mesothelioma establishment, genetic variation in molecular or immunological mechanisms did not affect disease progression. Identification of multiple candidate modifier genes and their human homologues with known associations in other advanced stage or metastatic cancers highlights the complexity of ARD and may provide a pathway to identify novel therapeutic targets.

CHST4 Gene as a Potential Predictor of Clinical Outcome in Malignant Pleural Mesothelioma

Malignant pleural mesothelioma (MPM) develops primarily from asbestos exposures and has a poor prognosis. In this study, The Cancer Genome Atlas was used to perform a comprehensive survival analysis, which identified the CHST4 gene as a potential predictor of favorable overall survival for patients with MPM. An enrichment analysis of favorable prognostic genes, including CHST4, showed immune-related ontological terms, whereas an analysis of unfavorable prognostic genes indicated cell-cycle-related terms. CHST4 mRNA expression in MPM was significantly correlated with Bindea immune-gene signatures. To validate the relationship between CHST4 expression and prognosis, we performed an immunohistochemical analysis of CHST4 protein expression in 23 surgical specimens from surgically treated patients with MPM who achieved macroscopic complete resection. The score calculated from the proportion and intensity staining was used to compare the intensity of CHST4 gene expression, which showed that CHST4 expression was stronger in patients with a better postoperative prognosis. The median overall postoperative survival was 107.8 months in the high-expression-score group and 38.0 months in the low-score group (p = 0.044, log-rank test). Survival after recurrence was also significantly improved by CHST4 expression. These results suggest that CHST4 is useful as a prognostic biomarker in MPM.

GPR137 inactivates Hippo signaling to promote gastric cancer cell malignancy

As the fifth most common cancer in the world, gastric cancer (GC) ranks as the third major cause of cancer-related death globally. Although surgical resection and chemotherapy still remains the mainstay of potentially curative treatment for GC, chemotherapy resistance and adverse side effects limit their clinical applications. Thus, further investigation of the mechanisms of carcinogenesis in GC and discovery of novel biomarkers is of great concern. We herein report that the elevated expression of GPR137 is correlated with GC. Overexpression of GPR137 potentiates human gastric cancer AGS cell malignancy, including proliferation, migration, invasion, colony formation and xenograft growth in nude mice in vivo, whereas knockout of GPR137 by CRISPR/Cas9 gene editing exerts the opposite effects. Mechanistically, GPR137 could bind to MST, the upstream kinases in Hippo pathway, which disrupts the association of MST with LATS, subsequently activating the transcriptional co-activators, YAP and TAZ, and thereby triggering the target transcription and the alterations in GC cell biological actions consequently. Therefore, our findings may provide with the evidence of developing a potentially novel treatment method with specific target for GC.

DNA cytosine deamination is associated with recurrent Somatic Copy Number Alterations in stomach adenocarcinoma

Stomach Adenocarcinoma (STAD) is a leading cause of death worldwide. Somatic Copy Number Alterations (SCNAs), which result in Homologous recombination (HR) deficiency in double-strand break repair, are associated with the progression of STAD. However, the landscape of frequent breakpoints of SCNAs (hotspots) and their functional impacts remain poorly understood. In this study, we aimed to explore the frequency and impact of these hotspots in 332 STAD patients and 1,043 cancer cells using data from the Cancer Genome Atlas (TCGA) and Cancer Cell Line Encyclopedia (CCLE). We studied the rates of DSB (Double-Strand Breaks) loci in STAD patients by employing the Non-Homogeneous Poisson Distribution (λ), based on which we identified 145 DSB-hotspots with genes affected. We further verified DNA cytosine deamination as a critical process underlying the burden of DSB in STAD. Finally, we illustrated the clinical impact of the significant biological processes. Our findings highlighted the relationship between DNA cytosine deamination and SCNA in cancer was associated with recurrent Somatic Copy Number Alterations in STAD.

Characterization of tumor microenvironment in glioblastoma multiforme identifies ITGB2 as a key immune and stromal related regulator in glial cell types

Glioblastoma multiforme (GBM) is the most aggressive form of brain tumor characterized by inter and intra-tumor heterogeneity and complex tumor microenvironment. To uncover the molecular targets in this milieu, we systematically identified immune and stromal interactions at the glial cell type level that leverages on RNA-sequencing data of GBM patients from The Cancer Genome Atlas. The perturbed genes between the high vs low immune and stromal scored patients were subjected to weighted gene co-expression network analysis to identify the glial cell type specific networks in immune and stromal infiltrated patients. The intramodular connectivity analysis identified the highly connected genes in each module. Combining it with univariable and multivariable prognostic analysis revealed common vital gene ITGB2, between the immune and stromal infiltrated patients enriched in microglia and newly formed oligodendrocytes. We found following unique hub genes in immune infiltrated patients; COL6A3 (microglia), ITGAM (oligodendrocyte precursor cells), TNFSF9 (microglia), and in stromal infiltrated patients, SERPINE1 (microglia) and THBS1 (newly formed oligodendrocytes, oligodendrocyte precursor cells). To validate these hub genes, we used external GBM patient single cell RNA-sequencing dataset and this identified ITGB2 to be significantly enriched in microglia, newly formed oligodendrocytes, T-cells, macrophages and adipocyte cell types in both immune and stromal datasets. The tumor infiltration analysis of ITGB2 showed that it is correlated with myeloid dendritic cells, macrophages, monocytes, neutrophils, B-cells, fibroblasts and adipocytes. Overall, the systematic screening of tumor microenvironment components at glial cell types uncovered ITGB2 as a potential target in primary GBM.

The Role of Cocaine- and Amphetamine-Regulated Transcript (CART) in Cancer: A Systematic Review

The functions of cocaine- and amphetamine-regulated transcript (CART) neuropeptide encoded by the CARTPT gene vary from modifying behavior and pain sensitivity to being an antioxidant. Putative CART peptide receptor GPR160 was implicated recently in the pathogenesis of cancer. However, the exact role of CART protein in the development of neoplasms remains unclear. This systematic review includes articles retrieved from the Scopus, PubMed, Web of Science and Medline Complete databases. Nineteen publications that met the inclusion criteria and describe the association of CART and cancer were analyzed. CART is expressed in various types of cancer, e.g., in breast cancer and neuroendocrine tumors (NETs). The role of CART as a potential biomarker in breast cancer, stomach adenocarcinoma, glioma and some types of NETs was suggested. In various cancer cell lines, CARTPT acts an oncogene, enhancing cellular survival by the activation of the ERK pathway, the stimulation of other pro-survival molecules, the inhibition of apoptosis or the increase in cyclin D1 levels. In breast cancer, CART was reported to protect tumor cells from tamoxifen-mediated death. Taken together, these data support the role of CART activity in the pathogenesis of cancer, thus opening new diagnostic and therapeutic approaches in neoplastic disorders.

An integrated analysis of prognostic mRNA signature in early- and progressive-stage gastric adenocarcinoma

The pathogenesis and vital factors of early and progressive stages of stomach adenocarcinoma (STAD) have not been fully elucidated. In order to discover novel and potential targets to guide effective treatment strategies, a comprehensive bioinformatics study was performed, and the representative results were then validated by quantitative polymerase chain reaction (qPCR) and immunohistochemical (IMC) staining in clinical samples. A total of 4,627, 4,715, and 3,465 differentially expressed genes (DEGs) from overall-, early-, and progressive-stage STAD were identified, respectively. Prognostic models of 5-year OS were established for overall-, early-, and progressive-stage STAD, and ROC curves demonstrated AUC values for each model were 0.73, 0.87, and 0.92, respectively. Function analysis revealed that mRNAs of early-stage STAD were enriched in chemical stimulus-related pathways, whereas remarkable enrichment of mRNAs in progressive-stage STAD mainly lay in immune-related pathways. Both qPCR and IHC data confirmed the up-regulation of IGFBP1 in the early-stage and CHAF1A in progressive-stage STAD compared with their matched normal tissues, indicating that these two representative targets could be used to predict the prognostic status of the patients in these two distinct STAD stages, respectively. In addition, seven mRNAs (F2, GRID2, TF, APOB, KIF18B, INCENP, and GCG) could be potential novel biomarkers for STAD at different stages from this study. These results contributed to identifying STAD patients at high-risk, thus guiding targeted treatment with efficacy in these patients.

Expression and promoter methylation of mitogen-activated protein kinase 1 in tumor and marginal cells of breast cancer

AIM

In the present study, we sought to explore potential differences in the expression and promoter methylation of mitogen-activated protein kinase 1 (MAPK1) between tumor and marginal cells of breast cancer lesions.

METHODS

A total of 50 randomly selected patients with breast cancer (BCa) undergoing needle biopsy were enrolled. Clinical specimens containing both tumor and marginal cells were collected and preserved. After DNA extraction using specific primers, MAPK1 mRNA and promoter methylation were measured with spectrophotometry at 260/280 nm absorption wavelengths. To deliver a comparative analysis, data from The Cancer Genome Atlas (TCGA) program regarding breast cancer (BRCA), were downloaded from Xena Functional Genomics Explorer and separately analyzed. The suitability of MAPK1 expression and promoter methylation as biomarkers for BCa was analyzed with receiver operating characteristic (ROC) curves.

RESULTS

We found a positive correlation between tumor stage and MAPK1 expression (P-value: 0.029) in BCa. Likewise, MAPK1 expression was significantly associated with lymph node metastasis (P-value: 0.018). There was a significant difference in the expression of MAPK1 mRNA between tumor and marginal cells of BCa and BRCA (P-value < 0.001). However, we did not find any statistically significant difference in MAPK1 promoter methylation between tumor and marginal cells of both BCa and BRCA. With an area under the curve (AUC) of 0.71, the diagnostic accuracy of MAPK1 expression in BCa and BRCA was validated. However, MAPK1 promoter methylation was not found to be a suitable biomarker.

CONCLUSION

Our findings suggest that while MAPK1 expression, might be a promising biomarker for evaluating oncogenic activity in patients suspected of BCa. We were not able to detect a prognostic/diagnostic role for MAPK1 promoter methylation.

Identification of prognostic genes in the pancreatic adenocarcinoma immune microenvironment by integrated bioinformatics analysis

PURPOSE

Pancreatic adenocarcinoma (PAAD) is one of the most common causes of death among solid tumors, and its pathogenesis remains to be clarified. This study aims to elucidate the value of immune/stromal-related genes in the prognosis of PAAD through comprehensive bioinformatics analysis based on the immune microenvironment and validated in Chinese pancreatic cancer patients.

METHODS

Gene expression profiles of pancreatic cancer patients were obtained from TCGA database. Differentially expressed genes (DEGs) were identified based on the ESTIMATE algorithm. Gene co-expression networks were constructed using WGCNA. In the key module, survival analysis was used to reveal the prognostic value. Subsequently, we performed functional enrichment analysis to construct a protein-protein interaction (PPI) network. The relationship between tumor immune infiltration and hub genes was analyzed by TIMER and CIBERSORT. Finally, it was validated in the GEO database and in tissues of Chinese pancreatic cancer patients.

RESULTS

In the TCGA pancreatic cancer cohort, a low immune/stromal score was associated with a good prognosis. After bioinformatic analysis, 57 genes were identified to be significantly associated with pancreatic cancer prognosis. Among them, up-regulation of four genes (COL6A3, PLAU, MMP11 and MMP14) indicated poor prognosis and was associated with multiple immune cell infiltration. IHC results showed that PLAU protein levels from Chinese pancreatic cancer tissues were significantly higher than those from adjacent non-tumor tissues and were also associated with tumor TNM stage and lymph node metastasis.

CONCLUSION

In conclusion, this study demonstrates that PLAU may serve as a new diagnostic and therapeutic target, which is highly expressed in Chinese pancreatic cancer tissues and associated with lymph node metastasis.

Characteristics of immunophenotypes and immunological in tumor microenvironment and analysis of immune implication of CXCR4 in gastric cancer

The formation of gastric cancer (GC) is a complicated process involving multiple factors and multiple steps. The tumor–immune microenvironment is essential for the growth of GC and affects the prognosis of patients. We performed multiple machine learning algorithms to identify immunophenotypes and immunological characteristics in GC patients’ information from the TCGA database and extracted immune genes relevance of the GC immune microenvironment. C-X-C motif chemokine receptor 4 (CXCR4), belongs to the C-X-C chemokine receptor family, which can promote the invasion and migration of tumor cells. CXCR4 expression is significantly correlated to metastasis and the worse prognosis. In this work, we assessed the condition of immune cells and identified the connection between CXCR4 and GC immune microenvironment, as well as the signaling pathways that mediate the immune responses involved in CXCR4. The work showed the risk scores generated by CXCR4-related immunomodulators could distinguish risk groups consisting of differential expression genes and could use for the personalized prognosis prediction. The findings suggested that CXCR4 is involved in tumor immunity of GC, and CXCR4 is considered as a potential prognostic biomarker and immunotherapy target of GC. The prognostic immune markers from CXCR4-associated immunomodulators can independently predict the overall survival of GC.

A Comprehensive Bioinformatic Analysis of NOTCH Pathway Involvement in Stomach Adenocarcinoma

Background

Activation of NOTCH signaling pathways, which are key regulators of multiple cellular functions, has been frequently implicated in cancer pathogenesis, and NOTCH inhibitors have received much recent focus in the context of cancer therapeutics. However, the role and possible involvement of NOTCH pathways in stomach adenocarcinoma (STAD) are unclear. Here, putative regulatory mechanisms and functions of NOTCH pathways in STAD were investigated.

Methods

Publicly available data from the TCGA-STAD database were utilized to explore the involvement of canonical NOTCH pathways in STAD by analyzing RNA expression levels of NOTCH receptors, ligands, and downstream genes. Statistical analysis of the data pertaining to cancer and noncancerous samples was performed using R software packages and public databases/webservers.

Results

Significant differential gene expression between control and STAD samples was noted for all NOTCH receptors (NOTCH1, 2, 3, and 4), the delta-like NOTCH ligands (DLL-3 and 4), and typical downstream genes (HES1 and HEY1). Four genes (NOTCH1, NOTCH2, NOTCH3, and HEY1) presented prognostic values for the STAD outcome in terms of overall survival. Functional enrichment analysis indicated that NOTCH family genes-strongly correlated genes were mainly enriched in several KEGG signaling pathways such as the PI3K-Akt signaling pathway, human papillomavirus infection, focal adhesion, Rap1 signaling pathway, and ECM-receptor interaction. Gene set enrichment analysis (GSEA) results showed that NOTCH family genes-significantly correlated genes were mainly enriched in four signaling pathways, ECM (extracellular matrix), tumor angiogenesis, inflammatory response, and immune regulation.

Conclusions

NOTCH family genes may play an essential role in the progression of STAD by modulating immune cells and mediating ECM synthesis, angiogenesis, focal adhesion, and PI3K-Akt signaling. Multiple NOTCH family genes are valuable candidate biomarkers or therapeutic targets for the management of STAD.

Identification of Immune-Related Risk Characteristics and Prognostic Value of Immunophenotyping in TNBC

Background: Triple-negative breast cancer (TNBC) is not sensitive to targeted therapy with HER-2 monoclonal antibody and endocrine therapy due to lack of ER, PR, and HER-2 receptors. TNBC is a breast cancer subtype with the worst prognosis and the highest mortality rate compared with other subtypes. Materials and Methods: Breast cancer-related data were retrieved from The Cancer Genome Atlas (TCGA) database, and 116 cases of triple-negative breast cancer were identified from the data. GSE31519 dataset was retrieved from Gene Expression Omnibus (GEO) database, comprising a total of 68 cases with TNBC. Survival analysis was performed based on immune score, infiltration score and mutation score to explore differences in prognosis of different immune types. Analysis of differentially expressed genes was conducted and GSEA analysis based on these genes was conducted to explore the potential mechanism. Results: The findings showed that comprehensive immune typing is highly effective and accurate in assessing prognosis of TNBC patients. Analysis showed that MMP9, CXCL9, CXCL10, CXCL11 and CD7 are key genes that may affect immune typing of TNBC patients and play an important role in prediction of prognosis in TNBC patients. Conclusion: The current study presents an evaluation system based on immunophenotyping, which provides a more accurate prognostic evaluation tool for TNBC patients. Differentially expressed genes can be targeted to improve treatment of TNBC.

Drug metabolism-related eight-gene signature can predict the prognosis of gastric adenocarcinoma

Background

Metabolic abnormalities in patients with gastric adenocarcinoma lead to drug resistance and poor prognosis. Therefore, this study aimed to explore biomarkers that can predict the prognostic risk of gastric adenocarcinoma by analyzing drug metabolism‐related genes.

Methods

The RNA‐seq and clinical information on gastric adenocarcinoma were downloaded from the UCSC and gene expression omnibus databases. Univariate and least absolute shrinkage and selection operator regression analyses were used to identify the prognostic gene signature of gastric adenocarcinoma. The relationships between gastric adenocarcinoma prognostic risk and tumor microenvironment were assessed using CIBERSORT, EPIC, QUANTISEQ, MCPCounter, xCell, and TIMER algorithms. The potential drugs that could target the gene signatures were predicted in WebGestalt, and molecular docking analysis verified their binding stabilities.

Results

Combined with clinical information, an eight‐gene signature, including GPX3, ABCA1, NNMT, NOS3, SLCO4A1, ADH4, DHRS7, and TAP1, was identified from the drug metabolism‐related gene set. Based on their expressions, risk scores were calculated, and patients were divided into high‐ and low‐risk groups, which had significant differences in survival status and immune infiltrations. Risk group was also identified as an independent prognostic factor of gastric adenocarcinoma, and the established prognostic and nomogram models exhibited excellent capacities for predicting prognosis. Finally, miconazole and niacin were predicted as potential therapeutic drugs for gastric adenocarcinoma that bond stably with NOS3 and NNMT through hydrogen interactions.

Conclusions

This study proposed a drug metabolism‐related eight‐gene signature as a potential biomarker to predict the gastric adenocarcinoma prognosis risks.

Identification of Key Genes Affecting the Tumor Microenvironment and Prognosis of Triple-Negative Breast Cancer

Although the tumor microenvironment (TME) plays an important role in the development of many cancers, its roles in breast cancer, especially triple-negative breast cancer (TNBC), are not well studied. This study aimed to identify genes related to the TME and prognosis of TNBC. Firstly, we identified differentially expressed genes (DEG) in the TME of TNBC, using Expression data (ESTIMATE) datasets obtained from the Cancer Genome Atlas (TCGA) and Estimation of Stromal and Immune cells in Malignant Tumor tissues. Next, survival analysis was performed to analyze the relationship between TME and prognosis of TNBC, as well as determine DEGs. Genes showing significant differences were scored as alternative genes. A protein-protein interaction (PPI) network was constructed and functional enrichment analysis conducted using the DEG. Proteins with a degree greater than 5 and 10 in the PPI network correspond with hub genes and key genes, respectively. Finally, CCR2 and CCR5 were identified as key genes in TME and prognosis of TNBC. Finally, these results were verified using Gene Expression Omnibus (GEO) datasets and immunohistochemistry of TNBC patients. In conclusion, CCR2 and CCR5 are key genes in the TME and prognosis of TNBC with the potential of prognostic biomarkers in TNBC.

Elevated expression of MKRN3 in squamous cell carcinoma of the head and neck and its clinical significance

BACKGROUND

Squamous cell carcinoma of the head and neck (SCCHN) is one of the most common types of cancer that cause a substantial number of cancer-related deaths. Our previous study has revealed that makorin ring finger protein 3 (MKRN3) may act as a key regulator of the SCCHN tumorigenesis; however, its specific role in SCCHN progression has not been reported.

METHODS

The Cancer Genome Atlas (TCGA) data analysis and quantitative polymerase chain reaction (qPCR) were used to quantify the MKRN3 mRNA expression levels in SCCHN; immunohistochemical staining or immunoblotting analyses were performed to detect MKRN3 protein expression. Kaplan-Meier plotter was used to assess the prognostic values of MKRN3 in terms of overall survival and disease-free survival. The expression differences based on various clinicopathological features were evaluated using subgroup analysis and forest map analysis. The regulatory mechanism of MKRN3 was further investigated using gene ontology and Kyoto Encyclopedia of Genes and Genomes analyses. Subsequently, STRING was used to perform a co-expression and enrichment analysis for MKRN3. Homologous modeling, molecular docking, and western blot analyses were performed to investigate the relationship between MKRN3 and its potential target gene P53.

RESULTS

MKRN3 was ectopically expressed between cancerous and noncancerous SCCHN tissues, and its expression level was tightly associated with high T classifications as well as advanced clinical stages. qPCR analysis revealed that MKRN3 was upregulated in the SCCHN cell line. Moreover, Kaplan-Meier and Cox regression analyses indicated that SCCHN patients with high MKRN3 expression had poorer prognosis and that MKRN3 was a potential prognostic marker for SCCHN. Using gene ontology and Kyoto Encyclopedia of Genes and Genomes analyses, we determined that MKRN3 may be involved in the regulation of synthesis and metabolism and cell growth, death and motility, as well as cancer pathways associated with SCCHN progression. Mechanism investigation further revealed that P53, a potential target of MKRN3, may be involved in the SCCHN tumorigenesis mediated by MKRN3.

CONCLUSIONS

We performed a comprehensive evaluation of the clinical significance of MKRN3 and explored its underlying mechanisms. We concluded that MKRN3 represents a valuable predictive biomarker and potential therapeutic target in SCCHN.

Combining Algorithms to Find Signatures That Predict Risk in Early-Stage Stomach Cancer

This study applied two mathematical algorithms, lattice up-stream targeting (LUST) and D-basis, to the identification of prognostic signatures from cancer gene expression data. The LUST algorithm looks for metagenes, which are sets of genes that are either overexpressed or underexpressed in the same patients. Whereas LUST runs unsupervised by clinical data, the D-basis algorithm uses implications and association rules to relate gene expression to clinical outcomes. The D-basis selects a small subset of the metagene (a signature) to predict survival. The two algorithms, LUST and D-basis, were combined and applied to mRNA expression and clinical data from The Cancer Genome Atlas (TCGA) for 203 stage 1 and 2 stomach cancer patients. Two small (four-gene) signatures effectively predict survival in early-stage stomach cancer patients. These signatures could be used as a guide for treatment. The first signature (DU4) consists of genes that are underexpressed on the long-survival/low-risk group: FLRT2, KCNB1, MYOC, and TNXB. The second signature consists of genes that are overexpressed on the short-survival/high-risk group: ASB5, SFRP1, SMYD1, and TACR2. Another nine-gene signature (REC9) predicts recurrence: BNC2, CCDC8, DPYSL3, MOXD1, MXRA8, PRELP, SCARF2, TAGLN, and ZNF423. Each patient is assigned a score that is a linear combination of the expression levels for the genes in the signature. Scores below a selected threshold predict low-risk/long survival, whereas high scores indicate a high risk of short survival. The metagenes associate with TCGA cluster C1. Both our signatures and cluster C1 identify tumors that are genomically silent, and have a low mutation load or mutation count. Furthermore, our signatures identify tumors that are predominantly in the WHO classification of poorly cohesive and the Lauren class of diffuse samples, which have a poor prognosis.

P2RY14 Is a Potential Biomarker of Tumor Microenvironment Immunomodulation and Favorable Prognosis in Patients With Head and Neck Cancer

The tumor microenvironment (TME) has a crucial role in tumor development, progression, and treatment response. Yet, the exact interaction between cancer biology and the TME is not fully understood. The following study analyzed the correlation between immune/stromal/estimate scores and survival prognosis in head and neck squamous cell carcinoma (HNSC) using a bioinformatic method. As a result, a predictive biomarker, UDP-glucose-specific G(i) protein-coupled P2Y receptor (P2RY14), was discovered. The potential role of P2RY14-driven signaling pathways in the immune-remodeling of TME was then investigated. Briefly, low immune scores were associated with unfavorable prognosis and clinical-stage, larger tumor size, and the down-regulation of P2RY14 in HNSC patients. In addition, the survival analysis showed that HNSC patients with high expression had longer survival than patients with low expression from both TCGA databases and our own patients. We further discovered that P2RY14 is involved in the immune activity in the TME of HNSC; a downregulation of P2RY14 resulted in being an indicator for the conversion of TME status (from immune-dominant to metabolic-dominant status). The intersection analysis of genes co-expressed with P2RY14 indicated that the T-cell receptor signaling pathway and PD-L1 expression and PD-1 checkpoint pathway were candidate signaling pathways driven by the P2RY14 gene in HNSC. Further investigation of immune-associated signaling pathways regulated by P2RY14 may help HNSC patients gain higher immunotherapy benefits.

Identification of Prognostic Genes in the Tumor Microenvironment of Hepatocellular Carcinoma

Background: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors in the world. The efficacy of immunotherapy usually depends on the interaction of immunomodulation in the tumor microenvironment (TME). This study aimed to explore the potential stromal-immune score-based prognostic genes related to immunotherapy in HCC through bioinformatics analysis.

Methods: ESTIMATE algorithm was applied to calculate the immune/stromal/Estimate scores and tumor purity of HCC using the Cancer Genome Atlas (TCGA) transcriptome data. Functional enrichment analysis of differentially expressed genes (DEGs) was analyzed by the Database for Annotation, Visualization, and Integrated Discovery database (DAVID). Univariate and multivariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) regression analysis were performed for prognostic gene screening. The expression and prognostic value of these genes were further verified by KM-plotter database and the Human Protein Atlas (HPA) database. The correlation of the selected genes and the immune cell infiltration were analyzed by single sample gene set enrichment analysis (ssGSEA) algorithm and Tumor Immune Estimation Resource (TIMER).

Results: Data analysis revealed that higher immune/stromal/Estimate scores were significantly associated with better survival benefits in HCC within 7 years, while the tumor purity showed a reverse trend. DEGs based on both immune and stromal scores primarily affected the cytokine–cytokine receptor interaction signaling pathway. Among the DEGs, three genes (CASKIN1, EMR3, and GBP5) were found most significantly associated with survival. Moreover, the expression levels of CASKIN1, EMR3, and GBP5 genes were significantly correlated with immune/stromal/Estimate scores or tumor purity and multiple immune cell infiltration. Among them, GBP5 genes were highly related to immune infiltration.

Conclusion: This study identified three key genes which were related to the TME and had prognostic significance in HCC, which may be promising markers for predicting immunotherapy outcomes.

C3AR1 mRNA as a Potential Therapeutic Target Associates With Clinical Outcomes and Tumor Microenvironment in Osteosarcoma

Objective: Targeting cancer-specific messenger RNAs (mRNAs) may offer novel insights into therapeutic strategies in osteosarcoma. This study aimed to discover possible osteosarcoma-specific mRNA and probe its biological functions.

Methods: Based on mRNA-seq data from the TARGET database, stromal and immune scores were estimated for each osteosarcoma sample via the ESTIMATE algorithm. Stromal and immune mRNAs were obtained via integration of differentially expressed mRNAs between high and low stromal / immune score groups. Among hub and prognostic mRNAs, C3AR1 mRNA was focused and its prognostic value was assessed. The associations between C3AR1 mRNA and immune cells were analyzed via the CIBERSORT algorithm. Its expression was verified in osteosarcoma tissues and cells by RT-qPCR and western blot. The functions of C3AR1 were investigated by a series of experiments.

Results: Low stromal and immune scores were both indicative of unfavorable outcomes for osteosarcoma patients. Eighty-eight up-regulated and seven down-regulated stromal and immune mRNAs were identified. Among 30 hub mRNAs, low expression of C3AR1 mRNA indicated worse outcomes than its high expression. There was a lower mRNA expression of C3AR1 in metastatic than non-metastatic osteosarcoma. C3AR1 mRNA was closely correlated to various immune cells such as macrophages. C3AR1 was verified to be down-regulated in osteosarcoma tissues and cells. Its overexpression suppressed proliferation, migration and invasion and induced apoptosis in osteosarcoma cells.

Conclusion: C3AR1 mRNA could be a promising therapeutic target for osteosarcoma, linked with prognosis and tumor microenvironment.

Identification of Key Genes of Prognostic Value in Clear Cell Renal Cell Carcinoma Microenvironment and a Risk Score Prognostic Model

Objective

We aimed at identifying the key genes of prognostic value in clear cell renal cell carcinoma (ccRCC) microenvironment and construct a risk score prognostic model.

Materials and Methods

Immune and stromal scores were calculated using the ESTIMATE algorithm. A total of 539 ccRCC cases were divided into high- and low-score groups. The differentially expressed genes in immune and stromal cells for the prognosis of ccRCC were screened. The relationship between survival outcome and gene expression was evaluated using univariate and multivariate Cox proportional hazard regression analyses. A risk score prognostic model was constructed based on the immune/stromal scores.

Results

The median survival time of the low immune score group was longer than that of the high immune score group (p = 0.044). Ten tumor microenvironment-related genes were selected by screening, and a predictive model was established, based on which patients were divided into high- and low-risk groups with markedly different overall survival (p < 0.0001). Multivariate Cox analyses showed that the risk score prognostic model was independently associated with overall survival, with a hazard ratio of 1.0437 (confidence interval: 1.0237-1.0641, p < 0.0001).

Conclusions

Low immune scores were associated with extended survival time compared to high immune scores. The novel risk predictive model based on tumor microenvironment-related genes may be an independent prognostic biomarker in ccRCC.