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Phosphatase and tensin homolog (PTEN) is one of the highly susceptible genes to breast cancer (BC); however, the role of PTEN-related RNAs in BC remains poorly understood. Understanding the effect of PTEN-related RNAs and their mechanisms may be helpful to clinicians. We screened the differentially expressed RNAs (deRNAs) related to PTEN and established the competitive endogenous RNA (ceRNA) network by integrating several databases. After that, the RNA model, prolactin receptor (PRLR)/calcium voltage-gated channel auxiliary subunit alpha2delta 1 (CACNA2D1), was obtained by KM survival analysis and logistic regression analysis. Finally, mutation, methylation, functional enrichment, and immune correlation were analyzed to explore the roles of these RNAs. Our results showed that PRLR might be harmful to BC, while CACNA2D1 might be beneficial to BC. Furthermore, the abnormal expression of PRLR in BC might result from mutation and hypomethylation, while the aberrant expression of CACNA2D1 might be ascribed to methylation. Mechanistically, PRLR might affect the prognosis of BC by inhibiting the expression of immune checkpoints, while CACNA2D1 might improve the prognosis of BC by increasing the immune cells infiltrating into BC and up-regulating the expression of immune checkpoints. The abnormal expression of PRLR and CACNA2D1 in BC is closely related to the prognosis of BC, and they may serve as targets for the treatment of BC.

Chengwen Zhao,1,* Yonghui Liu,1,* Shaoqing Ju,1,2 Xudong Wang1,2 1Department of Laboratory Medicine, Affiliated Hospital of Nantong University, Nantong, Jiangsu, People’s Republic of China; 2Department of Public Health, Nantong University, Nantong, Jiangsu, People’s Republic of China*These authors contributed equally to this workCorrespondence: Xudong WangDepartment of Laboratory Medicine, Affiliated Hospital of Nantong University, 20 Xisi Road, Nantong, Jiangsu, 226006, People’s Republic of ChinaTel +86 13951318000Email wangxudong88@hotmail.comBackground: Fat mass and obesity-associated protein (FTO) is a critical N6-methyladenosine (m6A) demethylase that participates in tumorigenesis and is associated with the prognosis of patients in some cancers. However, the key roles of FTO in pan-cancer are still largely obscure.Methods: FTO expression levels in pan-cancer were estimated via the Genotype-Tissue Expression (GTEx), Cancer Cell Line Encyclopedia (CCLE), and The Cancer Genome Atlas (TCGA) databases. Univariate survival analysis was used to estimate the effects of FTO on prognosis. In addition, we used the Tumor Immune Evaluation Resource (TIMER) to assess the immune cell infiltration of FTO gene across cancers. The association of FTO expression with immune checkpoint genes expression, DNA mismatch repair (MMR) gene mutation, DNA methyltransferases, microsatellite instability (MSI), and tumor mutational burden (TMB) was investigated using Spearman’s correlation analysis. Moreover, Gene Set Enrichment Analysis (GSEA) was utilized to identify critical pathways in cancers. The STRING website was used to reveal the protein–protein interaction (PPI) network of FTO.Results: FTO was aberrantly expressed across cancers and survival analysis demonstrated that its expression was associated with clinical prognosis of many cancer patients. Specifically, FTO expression was significantly associated with immune infiltrating cells in colon adenocarcinoma, kidney renal clear cell carcinoma, and liver hepatocellular carcinoma. In addition, FTO expression was significantly associated with immune checkpoint genes expression, MMR, DNA methyltransferases levels, TMB, and MSI in multiple cancers. Moreover, the GSEA unveiled that FTO was involved in the regulation of tumors and immune-related signaling pathways. In addition, several m6A related genes were implicated in the PPI network of FTO.Conclusion: FTO was related to patients’ prognosis and tumor immune infiltrates in various cancers, and may serve as a novel and potential prognostic and immune biomarker in human pan-cancer.Keywords: FTO, biomarker, prognosis, tumor immune, pan-cancer

Chengwen Zhao,1,* Yonghui Liu,1,* Shaoqing Ju,1,2 Xudong Wang1,2 1Department of Laboratory Medicine, Affiliated Hospital of Nantong University, Nantong, Jiangsu, People’s Republic of China; 2Department of Public Health, Nantong University, Nantong, Jiangsu, People’s Republic of China*These authors contributed equally to this workCorrespondence: Xudong WangDepartment of Laboratory Medicine, Affiliated Hospital of Nantong University, 20 Xisi Road, Nantong, Jiangsu, 226006, People’s Republic of ChinaTel +86 13951318000Email wangxudong88@hotmail.comBackground: Fat mass and obesity-associated protein (FTO) is a critical N6-methyladenosine (m6A) demethylase that participates in tumorigenesis and is associated with the prognosis of patients in some cancers. However, the key roles of FTO in pan-cancer are still largely obscure.Methods: FTO expression levels in pan-cancer were estimated via the Genotype-Tissue Expression (GTEx), Cancer Cell Line Encyclopedia (CCLE), and The Cancer Genome Atlas (TCGA) databases. Univariate survival analysis was used to estimate the effects of FTO on prognosis. In addition, we used the Tumor Immune Evaluation Resource (TIMER) to assess the immune cell infiltration of FTO gene across cancers. The association of FTO expression with immune checkpoint genes expression, DNA mismatch repair (MMR) gene mutation, DNA methyltransferases, microsatellite instability (MSI), and tumor mutational burden (TMB) was investigated using Spearman’s correlation analysis. Moreover, Gene Set Enrichment Analysis (GSEA) was utilized to identify critical pathways in cancers. The STRING website was used to reveal the protein–protein interaction (PPI) network of FTO.Results: FTO was aberrantly expressed across cancers and survival analysis demonstrated that its expression was associated with clinical prognosis of many cancer patients. Specifically, FTO expression was significantly associated with immune infiltrating cells in colon adenocarcinoma, kidney renal clear cell carcinoma, and liver hepatocellular carcinoma. In addition, FTO expression was significantly associated with immune checkpoint genes expression, MMR, DNA methyltransferases levels, TMB, and MSI in multiple cancers. Moreover, the GSEA unveiled that FTO was involved in the regulation of tumors and immune-related signaling pathways. In addition, several m6A related genes were implicated in the PPI network of FTO.Conclusion: FTO was related to patients’ prognosis and tumor immune infiltrates in various cancers, and may serve as a novel and potential prognostic and immune biomarker in human pan-cancer.Keywords: FTO, biomarker, prognosis, tumor immune, pan-cancer

Pancreatic cancer (PACA), which is characterized by an immunosuppressive nature, remains one of the deadliest malignancies worldwide. Aberrant DNA methylation (DNAm) reportedly influences tumor immune microenvironment. Here, we evaluated the role of DNA methylation driven genes (MDGs) in PACA through integrative analyses of epigenomic, transcriptomic, genomic and clinicopathological data obtained from TCGA, ICGC, ArrayExpress and GEO databases. Thereafter, we established a four-MDG signature, comprising GPRC5A, SOWAHC, S100A14, and ARNTL2. High signature risk-scores were associated with poor histologic grades and late TNM stages. Survival analyses showed the signature had a significant predictive effect on OS. WGCNA revealed that the signature may be associated with immune system, while high risk-scores might reflect immune dysregulation. Furthermore, GSEA and GSVA revealed significant enrichment of p53 pathway and mismatch repair pathways in high risk-score subgroups. Immune infiltration analysis showed that CD8+ T cells were more abundant in low score subgroups, while M0 macrophages exhibited an opposite trend. Moreover, negative regulatory genes of cancer-immunity cycle (CIC) illustrated that immunosuppressors TGFB1, VEGFA, and CD274 (PDL1) were all positively correlated with risk-scores. Furthermore, the four signature genes were negatively correlated with CD8+ lymphocytes, but positively associated with myeloid derived suppressor cells (MDSC). Conversely, specimens with high risk-scores exhibited heavier tumor mutation burdens (TMB) and might show better responses to some chemotherapy and targeted drugs, which would benefit stratification of PACA patients. On the other hand, we investigated the corresponding proteins of the four MDGs using paraffin-embedded PACA samples collected from patients who underwent radical surgery in our center and found that all these four proteins were elevated in cancerous tissues and might serve as prognostic markers for PACA patients, high expression levels indicated poor prognosis. In conclusion, we successfully established a four-MDG-based prognostic signature for PACA patients. We envisage that this signature will help in evaluation of intratumoral immune texture and enable identification of novel stratification biomarkers for precision therapies.

BackgroundRecent studies have confirmed that AT-rich interactive domain-containing protein 1A (ARID1A) plays a critical role in tumorigenesis, but its role in gallbladder cancer (GBC) remains unclear.MethodsIn total, 224 patients from Zhongshan Hospital were recruited for this retrospective study. The clinicopathological and baseline characteristics of the patients were collected. Bioinformatics analysis was performed to reveal variations in genes and signaling pathways, and ARID1A and PD-L1 expression and the number of PD1+ tumor-infiltrating lymphocytes (TILs) were measured by immunohistochemical staining.ResultsARID1A expression was negatively correlated with overall survival in patients with GBC, and multivariate analysis identified ARID1A as an independent prognostic factor for overall survival. A heatmap and gene set enrichment analysis suggested that cytotoxic T lymphocyte signatures and immune-related signaling pathways were downregulated in ARID1A low tumors. Subsequent immunohistochemical staining confirmed that ARID1A expression was negatively correlated with PD-L1 expression and PD1+ TILs in the tumor microenvironment. The Kaplan–Meier analysis suggested that high ARID1A expression combined with low PD-L1 expression or low PD1+ TIL counts is associated with the best prognosis in patients with GBC.ConclusionARID1A inactivation can lead to a worse prognosis in patients with GBC, potentially by mediating immune evasion through the PD1/PD-L1 pathway.

Recent studies have reported that tumor‐infiltrating mast cells (TIM) play an important role in tumor regression, but the effect of TIM in gallbladder cancer (GBC) remains unclear. The present study aims to investigate the prognostic value of TIM in GBC patients and its responsiveness to gemcitabine‐based adjuvant chemotherapy (ACT). A total of 298 GBC patients from Zhongshan Hospital were recruited for this study. TIM infiltration was measured by immunohistochemical staining. Accumulation of TIM is significantly associated with prolonged overall survival in GBC patients. The benefit from gemcitabine‐based ACT was superior among patients with high infiltration of TIM with GBC. Multivariate analysis identified TIM infiltration as an independent prognostic factor for overall survival. A heatmap showed that TIM‐activated gene signatures were positively correlated with CD8+ T cells' gene signatures. Gene set enrichment analysis (GSEA) suggested that TIM was related to multiple T cell‐related processes and signaling pathways, including the interferon gamma signaling pathway and the leukocyte migration signaling pathway. It was confirmed that CD8+ T cell infiltration was positively correlated with high TIM infiltration in tissue microarray (TMA), suggesting that TIM infiltration was linked to the immune surveillance in GBC. TIM can be used as an independent prognostic factor and a predictor of therapeutic response of gemcitabine‐based ACT in GBC patients, which may mediate immune surveillance by recruiting and activating CD8+ T cells in GBC., In gallbladder cancer patients who received chemotherapy, a part of population has been associated with better prognosis. In these patients, elevated recruitment of tumor‐infiltrating mast cells (TIM) resulted in reduced tumor burden and enhanced anti–tumor effect through recruitment and activation of CD8+ T cells. The mechanisms responsible for a tumor‐protective function of TIM and links to the known anti–tumor function of infiltrating cells have remained elusive. Based on the results reported here, we hypersized that interaction between TIM and CD8+ T cells with a pivotal role of chemokines and their receptors underlies these clinical observations.

Lactate dehydrogenase A (LDHA) is an important glycolytic enzyme that promotes glycolysis and plays a crucial role in cancer cell invasion and immune infiltration. However, the relevance of LDHA in colon adenocarcinoma (COAD) remains unclear. In this study, we analyzed the correlation between the expression of LDHA and clinicopathological characteristics in COAD using immunohistochemistry analysis, and then used integrative bioinformatics analyses to further study the function and role of LDHA in COAD. We found that LDHA was highly expressed in COAD tissues compared with adjacent normal tissues, and that COAD patients with high LDHA expression levels showed poor survival. In addition, LDHA expression was closely associated with the immune infiltrating levels of CD8+ T cells, neutrophils, and dendritic cells. Our findings highlight the potential role of LDHA in the tumorigenesis and prognosis of COAD. Furthermore, our results indicate that COAD is a novel immune checkpoint in the diagnosis and treatment of COAD.

The cyclic GMP-AMP synthase-stimulator of interferon genes (cGAS-STING) pathway play a significant role in the production of inflammatory cytokines and type I interferons. This study aims to develop a cGAS-STING pathway-related genes (CSRs) prediction model to predict prognosis in gastric cancer (GC). In the present study, we used The Cancer Genome Atlas (TCGA), Gene Expression Omnibus databases (GEO), CIBERSORT and Tumor Immune Estimation Resource databases (TIMER). The risk model based on five hub genes (IFNB1, IFNA4, IL6, NFKB2, and TRIM25) was constructed to predict the overall survival (OS) of GC. Further univariate Cox regression (URC) and multivariate Cox regression (MCR) analyses revealed that this risk scoring model was an independent factor. The results were verified by GEO external validation set. Multiple immune pathways were assessed by Gene Set Enrichment Analysis (GSEA). TIMER analysis demonstrated that risk score strongly correlated with Macrophage, B cells and CD8 + T cells infiltration. In addition, through ‘CIBERSORT’ package, the higher levels of infiltration of T cell follicular assistance (P = 0.011), NK cells-activated (P = 0.034), and Dendritic cells resting (P = 0.033) exhibited in high-risk group. Kaplan–Meier (K-M) survival analysis illustrated T cells CD4 memory resting and T cells follicular helper infiltration correlated with overall survival (OS) of GC patients in TCGA and GEO databases. Altogether, the risk score model can be conveniently used to predict prognosis. The immunocyte infiltration analysis provided a novel horizon for monitoring the status of the GC immune microenvironment. Abbreviations:TCGA: The Cancer Genome Atlas databases; GEO: Gene Expression Omnibus databases; GC: Gastric cancer; CSRs: cGAS-STING pathway-related genes; DECSRs: Differential expressed cGAS-STING pathway-related genes; PCSRs: Prognosis related cGAS-STING pathway genes; URC: Univariate Cox regression analyses; MCR: Multivariate Cox regression analyses GSEA: Gene set enrichment analysis; TIIC: Tumor-infiltrating immune cell.

Background: The treatment modalities for pancreatic ductal adenocarcinoma (PDAC) are limited and unsatisfactory. Although many novel drugs targeting the tumor microenvironment, such as immune checkpoint inhibitors, have shown promising efficacy for some tumors, few of them significantly prolong the survival of patients with PDAC due to insufficient knowledge on the tumor microenvironment.Methods: A single-cell RNA sequencing (scRNA-seq) dataset and seven PDAC cohorts with complete clinical and bulk sequencing data were collected for bioinformatics analysis. The relative proportions of each cell type were estimated using the gene set variation analysis (GSVA) algorithm based on the signatures identified by scRNA-seq or previous literature.Results: A meta-analysis of 883 PDAC patients showed that neutrophils are associated with worse overall survival (OS) for PDAC, while CD8+ T cells, CD4+ T cells, and B cells are related to prolonged OS for PDAC, with marginal statistical significance. Seventeen cell categories were identified by clustering analysis based on single-cell sequencing. Among them, CD8+ T cells and NKT cells were universally exhausted by expressing exhaustion-associated molecular markers. Interestingly, signatures of CD8+ T cells and NKT cells predicted prolonged OS for PDAC only in the presence of “targets” for pyroptosis and ferroptosis induction. Moreover, a specific state of T cells with overexpression of ribosome-related proteins was associated with a good prognosis. In addition, the hematopoietic stem cell (HSC)-like signature predicted prolonged OS in PDAC. Weighted gene co-expression network analysis identified 5 hub genes whose downregulation may mediate the observed survival benefits of the HSC-like signature. Moreover, trajectory analysis revealed that myeloid cells evolutionarily consisted of 7 states, and antigen-presenting molecules and complement-associated genes were lost along the pseudotime flow. Consensus clustering based on the differentially expressed genes between two states harboring the longest pseudotime span identified two PDAC groups with prognostic differences, and more infiltrated immune cells and activated immune signatures may account for the survival benefits.Conclusion: This study systematically investigated the prognostic implications of the components of the PDAC tumor microenvironment by integrating single-cell sequencing and bulk sequencing, and future studies are expected to develop novel targeted agents for PDAC treatment.

Macrophage differentiation is associated with tumorigenesis, including the tumorigenesis of hepatocellular carcinoma (HCC). Herein, we explored the value of macrophage differentiation-associated genes (MDGs) in the prognosis of HCC using data from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) databases. We performed multivariate Cox regression analyses to identify the hub genes affecting HCC patient prognoses. The correlations between hub genes and macrophage differentiation and immune checkpoint inhibitors (PD-1, PD-L1, and CTLA4) were investigated. Finally, the potential mechanism was examined with gene set enrichment analysis (GSEA). In total, seventeen differentially expressed MDGs were obtained after intersecting data from the two databases. Multivariate analysis indicated that CDC42 expression was an independent prognostic indicator in both databases. Furthermore, CDC42 showed a strong correlation with the tumor infiltration levels of immune cells in HCC tissue. Correlation analysis revealed that CDC42 expression was positively associated with M2 macrophage markers and immune checkpoint inhibitors, which indicated that CDC42 expression might be related to M2 macrophage differentiation and HCC cell immune tolerance. Finally, GSEA showed that CDC42 expression was most significantly related to the Wnt signaling pathway. In conclusion, this study showed that CDC42 expression might be an important MDG in HCC and may prove to be a new gene for studying macrophage differentiation in HCC. Abbreviations: HCC: hepatocellular carcinoma; TCGA: The Cancer Genome Atlas; ICGC: International Cancer Genome Consortium; GSEA: gene set enrichment analysis; GO: Gene Ontology; KEGG: Kyoto Encyclopedia of Genes and Genomes; ROC: receiver operating characteristic; K-M: Kaplan-Meier; AUC: the area under the ROC curve; TNM: Tumor size/lymph nodes/distance metastasis, Graphical abstract

Background Tumor-infiltrating immune cells (TIICs) are highly relevant to clinical outcome of glioma. However, previous studies cannot account for the diverse functions that make up the immune response in malignant transformation (MT) from low-grade glioma (LGG) to high-grade glioma (HGG). Methods Transcriptome level, genomic profiles and its relationship with clinical practice were obtained from TCGA and CGGA database. The “Cell type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT)” algorithm was used to estimate the fraction of 22 immune cell types. We divided the TCGA and CGGA set into an experiment set (n = 174) and a validation set (n = 74) by random number table method. Univariate and multivariate analyses were performed to evaluate the 22 TIICs’ value for MT in LGG. ROC curve was plotted to calculate area under curve (AUC) and cut-off value. Results Heterogeneity between TIICs exists in both intra- and inter-groups. Several TIICs are notably associated with tumor grade, molecular subtypes and survival. T follicular helper (TFH) cells, activated NK Cells and M0 macrophages were screened out to be independent predictors for MT in LGG and formed an immune risk score (IRS) (AUC = 0.732, p Conclusions The proposed IRS model provides promising novel signatures for predicting MT from LGG to HGG and may bring a better design of glioma immunotherapy studies in years to come.

Cervical cancer is primarily caused by the infection of high-risk human papillomavirus (hrHPV). Moreover, tumor immune microenvironment plays a significant role in the tumorigenesis of cervical cancer. Therefore, it is necessary to comprehensively identify predictive biomarkers from immunogenomics associated with cervical cancer prognosis. The Cancer Genome Atlas (TCGA) public database has stored abundant sequencing or microarray data, and clinical data, offering a feasible and reliable approach for this study. In the present study, gene profile and clinical data were downloaded from TCGA, and the Immunology Database and Analysis Portal (ImmPort) database. Wilcoxon-test was used to compare the difference in gene expression. Univariate analysis was adopted to identify immune-related genes (IRGs) and transcription factors (TFs) correlated with survival. A prognostic prediction model was established by multivariate cox analysis. The regulatory network was constructed and visualized by correlation analysis and Cytoscape, respectively. Gene functional enrichment analysis was performed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). A total of 204 differentially expressed IRGs were identified, and 22 of them were significantly associated with the survival of cervical cancer. These 22 IRGs were actively involved in the JAK-STAT pathway. A prognostic model based on 10 IRGs (APOD, TFRC, GRN, CSK, HDAC1, NFATC4, BMP6, IL17RD, IL3RA, and LEPR) performed moderately and steadily in squamous cell carcinoma (SCC) patients with FIGO stage I, regardless of the age and grade. Taken together, a risk score model consisting of 10 novel genes capable of predicting survival in SCC patients was identified. Moreover, the regulatory network of IRGs associated with survival (SIRGs) and their TFs provided potential molecular targets.

Myeloid-derived suppressor cells (MDSCs) are a group of heterogeneous myeloid cells that can suppress antitumor immunity. MDSCs are divided into granulocytic (G-MDSCs) and monocytic subsets. In the present study, the microRNA profiles of the G-MDSCs were determined and the differential expression of microRNAs between G-MDSCs from tumor-bearing mice and tumor-free mice was examined. The number of G-MDSCs in spleens of Lewis lung carcinoma (LLC)-bearing mice was ~6-fold higher than in spleens of normal mice (13.54±1.74% vs. 2.14±1.44%; P1.3-fold increased or decreased change were differentially expressed between the experimental and control group mice. The levels of nine of these differentially expressed miRNAs, miRNA-468 (miR-486), miR-192, miR-128, miR-125a, miR-149, miR-27a, miR-125b, miR-350 and miR-328, were also analyzed by RT-qPCR to validate the microarray data. The concordance rate between the results tested by the two methods was 88.9%. Bioinformatics analyses revealed that these miRNAs may act on various target genes, including Adar, Pik3r1, Rybp and Rabgap1, to regulate the survival, differentiation and the function of tumor-induced granulocytic MDSCs. The results revealed microRNAs and potential targets that may be vital for regulating survival, differentiation and function of G-MDSCs induced by LLC. Further investigation should be performed to clarify the roles of these microRNAs in regulating LLC-induced granulocytic MDSCs and the target genes that mediate their functions.