Single-Cell Map of Diverse Immune Phenotypes in the Breast Tumor Microenvironment.

Knowledge of immune cell phenotypes in the tumor microenvironment is essential for understanding mechanisms of cancer progression and immunotherapy response. We profiled 45,000 immune cells from eight breast carcinomas, as well as matched normal breast tissue, blood, and lymph nodes, using single-cell RNA-seq. We developed a preprocessing pipeline, SEQC, and a Bayesian clustering and normalization method, Biscuit, to address computational challenges inherent to single-cell data. Despite significant similarity between normal and tumor tissue-resident immune cells, we observed continuous phenotypic expansions specific to the tumor microenvironment. Analysis of paired single-cell RNA and T cell receptor (TCR) sequencing data from 27,000 additional T cells revealed the combinatorial impact of TCR utilization on phenotypic diversity. Our results support a model of continuous activation in T cells and do not comport with the macrophage polarization model in cancer. Our results have important implications for characterizing tumor-infiltrating immune cells.

Potential involvement of oncostatin M in the immunosuppressive tumor immune microenvironment in hepatocellular carcinoma with vessels encapsulating tumor clusters.

AIM: Vessels encapsulating tumor clusters (VETC) represents an adverse prognostic morphological feature of hepatocellular carcinoma (HCC), which is associated with an immunosuppressive tumor immune microenvironment (TIM). However, the underlying factors characterizing the TIM in HCC with a VETC pattern (VETC-positive HCC) remain uncertain. Oncostatin M (OSM), a pleiotropic cytokine of the interleukin-6 family, regulates various biological processes, including inflammation, proliferation, and invasiveness of tumor cells. We aimed to test a hypothesis that OSM is associated with the immunosuppressive TIM of VETC-positive HCC. METHODS: A total of 397 consecutive HCC patients with curative-intent hepatectomy were included. OSM-positive cells and inflammatory cells including CD4-, CD8-, CD163-, and FOXP3-positive cells were immunohistochemically evaluated. We compared VETC-positive and VETC-negative HCCs in terms of the number of these cells. RESULTS: We found the VETC pattern in 62 patients (15.6%). Our analysis revealed a significant decrease in the expression of arginase-1, a marker associated with mature hepatocyte differentiation, in VETC-positive HCC (p = 0.046). The number of tumor-infiltrating OSM-positive cells was significantly low in VETC-positive HCC (p = 0.0057). Notably, in VETC-positive HCC, the number of OSM-positive cells was not associated with vascular invasion, whereas in VETC-negative HCC, an increase in the number of OSM-positive cells was associated with vascular invasion (p = 0.042). CONCLUSIONS: We identified an association between a decrease in OSM-positive cells and the VETC pattern. Additionally, our findings indicate that VETC-positive HCC is characterized by low hepatocyte differentiation and OSM-independent vascular invasion. These findings highlight the potential interaction between VETC-positive HCC cells and their TIM through the reduction of OSM-expressing cells.

The Prognostic and Therapeutic Roles of ARL-6 Gene in Hepatocellular Carcinoma.

Background: Hepatocellular carcinoma (HCC) is one of the most prevalent human cancers. ARL-6, a member of the ADP ribosylation factor (like) (ARF) protein family, has gained attention as a potential therapeutic target in various malignancies and a prognostic biomarker. However, its specific roles in HCC, both prognostically and biochemically, remain largely unclear. Methods: To examine the functional relevance of ARL-6 in HCC, we acquired data from GEPIA, UALCAN, TIMER, TCGA, GeneMANIA, and Metascape databases. Then, we conducted immunohistochemistry on a replication sample comprising 26 HCC specimens to assess the efficacy of the ARL-6 gene. To unravel the mechanistic intricacies, we employed diverse assays such as the cell counting kit 8 (CCK8), flow cytometry, and transwell invasion assessment. Results: Our findings demonstrated the mRNA expression of ARL-6 was significantly upregulated in HCC compared to normal tissue, as evidenced by comprehensive database analysis. Immunohistochemistry further revealed that ARL-6 expression was remarkably higher in HCC than in para-carcinoma tissues. Moreover, ARL-6 expression exhibited noteworthy variations across diverse LIHC characteristics, including sample type, histological subtype, TP53 mutation status, nodal metastatic status, and cancer stage. In addition, high transcriptional levels of ARL-6 were correlated with diminished overall survival (OS) and disease-free survival (DFS) in HCC patients. Furthermore, our study indicated positive correlations between ARL-6 expression levels and the activities of tumor-infiltrating immune cells such as B cells, myeloid dendritic cells, macrophages, neutrophils, CD8+T cells, and CD4+T cells. Substantiating our findings, database analysis uncovered additional evidence of ARL-6 gene co-expression and its functional significance in HCC cases. Finally, we demonstrated the involvement of the ARL-6 gene in HCC cell invasion, proliferation, and apoptosis. Conclusions: In conclusion, our investigation sheds light on the pivotal role of ARL-6 in influencing HCC prognosis and treatment by modulating the biological activities of tumor cells. These discoveries hold promise for the development of predictive biomarkers and novel therapeutic avenues for affected patients.

Tumor gene signatures that correlate with release of extracellular vesicles shape the immune landscape in head and neck squamous cell carcinoma.

Head and neck squamous cell carcinomas (HNSCCs) evade immune responses through multiple resistance mechanisms. Extracellular vesicles (EVs) released by the tumor and interacting with immune cells induce immune dysfunction and contribute to tumor progression. This study evaluates the clinical relevance and impact on anti-tumor immune responses of gene signatures expressed in HNSCC and associated with EV production/release. Expression levels of two recently described gene sets were determined in The Cancer Genome Atlas Head and Neck Cancer cohort (n = 522) and validated in the GSE65858 dataset (n = 250) as well as a recently published single-cell RNA sequencing dataset (n = 18). Clustering into HPV(+) and HPV(-) patients was performed in all cohorts for further analysis. Potential associations between gene expression levels, immune cell infiltration, and patient overall survival were analyzed using GEPIA2, TISIDB, TIMER, and the UCSC Xena browser. Compared to normal control tissues, vesiculation-related genes were upregulated in HNSCC cells. Elevated gene expression levels positively correlated (P < 0.01) with increased abundance of CD4(+) T cells, macrophages, neutrophils, and dendritic cells infiltrating tumor tissues but were negatively associated (P < 0.01) with the presence of B cells and CD8(+) T cells in the tumor. Expression levels of immunosuppressive factors NT5E and TGFB1 correlated with the vesiculation-related genes and might explain the alterations of the anti-tumor immune response. Enhanced expression levels of vesiculation-related genes in tumor tissues associates with the immunosuppressive tumor milieu and the reduced infiltration of B cells and CD8(+) T cells into the tumor.

Computational principles and practice for decoding immune contexture in the tumor microenvironment.

Tumor-infiltrating immune cells (TIICs) have been recognized as crucial components of the tumor microenvironment (TME) and induced both beneficial and adverse consequences for tumorigenesis as well as outcome and therapy (particularly immunotherapy). Computer-aided investigation of immune cell components in the TME has become a promising avenue to better understand the interplay between the immune system and tumors. In this study, we presented an overview of data sources, computational methods and software tools, as well as their application in inferring the composition of tumor-infiltrating immune cells in the TME. In parallel, we explored the future perspectives and challenges that may be faced with more accurate quantitative infiltration of immune cells in the future. Together, our study provides a little guide for scientists in the field of clinical and experimental immunology to look for dedicated resources and more competent tools for accelerating the unraveling of tumor-immune interactions with the implication in precision immunotherapy.

Microsatellite instability status differentially associates with intratumoral immune microenvironment in human cancers.

Based on clinical outcomes in colorectal cancer, high microsatellite instability (MSI-H) has recently been approved by the Food and Drug Administration (FDA) as a genetic test to select patients for immunotherapy targeting PD-1 and/or CTLA-4 without limitation to cancer type. However, it is unclear whether the MSI-H would broadly alter the tumor microenvironment to confer the therapeutic response of different cancer types to immunotherapy. To fill in this gap, we performed an in silico analysis of tumor immunity among different MSI statuses in five cancer types. We found that consistent with clinical responses to immunotherapy, MSI-H and non-MSI-H samples from colorectal cancer (COAD-READ) exhibited distinct infiltration levels and immune phenotypes. Surprisingly, the immunological difference between MSI-H and non-MSI-H samples was diminished in stomach adenocarcinoma and esophageal carcinoma (STAD-ESCA) and completely disappeared in uterine corpus endometrial carcinoma (UCEC). Regardless of cancer types, the abundance of tumor-infiltrating immune cells, rather than MSI status, strongly associated with the clinical outcome. Since preexisting antitumor immune response in the tumor (hot cancer) is accepted as a prerequisite to the therapeutic response to anti-PD-1/CTLA-4 immunotherapy, our data demonstrate that the impact of MSI varied on immune contexture will lead to the further evaluation of predictive immunotherapy responsiveness based on the universal biomarker of MSI status.

ProTICS reveals prognostic impact of tumor infiltrating immune cells in different molecular subtypes.

Different subtypes of the same cancer often show distinct genomic signatures and require targeted treatments. The differences at the cellular and molecular levels of tumor microenvironment in different cancer subtypes have significant effects on tumor pathogenesis and prognostic outcomes. Although there have been significant researches on the prognostic association of tumor infiltrating lymphocytes in selected histological subtypes, few investigations have systemically reported the prognostic impacts of immune cells in molecular subtypes, as quantified by machine learning approaches on multi-omics datasets. This paper describes a new computational framework, ProTICS, to quantify the differences in the proportion of immune cells in tumor microenvironment and estimate their prognostic effects in different subtypes. First, we stratified patients into molecular subtypes based on gene expression and methylation profiles by applying nonnegative tensor factorization technique. Then we quantified the proportion of cell types in each specimen using an mRNA-based deconvolution method. For tumors in each subtype, we estimated the prognostic effects of immune cell types by applying Cox proportional hazard regression. At the molecular level, we also predicted the prognosis of signature genes for each subtype. Finally, we benchmarked the performance of ProTICS on three TCGA datasets and another independent METABRIC dataset. ProTICS successfully stratified tumors into different molecular subtypes manifested by distinct overall survival. Furthermore, the different immune cell types showed distinct prognostic patterns with respect to molecular subtypes. This study provides new insights into the prognostic association between immune cells and molecular subtypes, showing the utility of immune cells as potential prognostic markers. Availability: R code is available at https://github.com/liu-shuhui/ProTICS.

Transcriptomes of the tumor-adjacent normal tissues are more informative than tumors in predicting recurrence in colorectal cancer patients.

BACKGROUND: Previous investigations of transcriptomic signatures of cancer patient survival and post-therapy relapse have focused on tumor tissue. In contrast, here we show that in colorectal cancer (CRC) transcriptomes derived from normal tissues adjacent to tumors (NATs) are better predictors of relapse. RESULTS: Using the transcriptomes of paired tumor and NAT specimens from 80 Korean CRC patients retrospectively determined to be in recurrence or nonrecurrence states, we found that, when comparing recurrent with nonrecurrent samples, NATs exhibit a greater number of differentially expressed genes (DEGs) than tumors. Training two prognostic elastic net-based machine learning models-NAT-based and tumor-based in our Samsung Medical Center (SMC) cohort, we found that NAT-based model performed better in predicting the survival when the model was applied to the tumor-derived transcriptomes of an independent cohort of 450 COAD patients in TCGA. Furthermore, compositions of tumor-infiltrating immune cells in NATs were found to have better prognostic capability than in tumors. We also confirmed through Cox regression analysis that in both SMC-CRC as well as in TCGA-COAD cohorts, a greater proportion of genes exhibited significant hazard ratio when NAT-derived transcriptome was used compared to when tumor-derived transcriptome was used. CONCLUSIONS: Taken together, our results strongly suggest that NAT-derived transcriptomes and immune cell composition of CRC are better predictors of patient survival and tumor recurrence than the primary tumor.

SPOCK1 and POSTN are valuable prognostic biomarkers and correlate with tumor immune infiltrates in colorectal cancer.

BACKGROUND: Immune cells and stromal cells in the tumor microenvironment play a vital role in the progression of colorectal cancer (CRC). The study aimed to screen valuable prognostic biomarkers in CRC based on stromal and immune scores. METHOD: The ESTIMATE algorithm was used to calculate the immune and stromal scores of CRC samples in TCGA. Then samples were divided into high and low score groups based on the median value of the scores. Differentially expressed genes (DEGs) associated with immune and stromal scores were screened. WGCNA and univariate COX regression analysis were performed to further identify key prognostic genes. Analysis of scRNA-seq for CRC was used for verifying the main source of the key genes. The prognostic value of they was validated based on The Gene Expression Profiling Interactive Analysis and GSE17536 dataset. TIMER and CIBERSORT algorithms were applied to analyze the correlations among key genes and tumor-infiltrating immune cells. Several pairs of colon cancer tissue were used to be proven. RESULT: 1314 upregulated and 4 downregulated genes were identified, which were significantly enriched in immune-related biological processes and pathways. Among these DEGs, SPOCK1 and POSTN were identified as key prognostic genes and mainly expressed in cancer-associated fibroblasts for CRC. High expression of SPCOK1 and POSTN was associated with advanced clinical stage, T stage, N stage, and poor prognosis of CRC. The results from CIBERSORT and TIMER revealed that SPOCK1 and POSTN were associated with tumor-infiltrating immune cells, especially macrophages and neutrophils. Meanwhile, in several pairs of human colorectal tissue samples, SPOK1 and POSTN were found to be significantly overexpressed in colorectal tissue compared with para-cancer tissue, and macrophage surface markers CD68 (co-expressed by M1 and M2 macrophages) and CD206 (M2-specific macrophage expression) were also overexpressed in cancer tissue. Besides, SPOCK1 and POSTN expression were positively correlated with the expression of immune checkpoints. CONCLUSION: Collectively, our results indicate that SPOCK1 and POSTN associated with CAF may be novel prognostic biomarkers in CRC and correlate with immune infiltrates.

Prognostic value of tumor-infiltrating immune cells in clinical early-stage oral squamous cell carcinoma.

BACKGROUND: Tumor-infiltrating immune cells (TIICs) are critical components of tumor immune microenvironment (TIME), which play crucial roles during tumor initiation, development, and progression. However, the prognostic value of TIICs is still not well documented in clinical early-stage oral squamous cell carcinoma (OSCC). In this study, we aimed to assess the prognostic value of TIICs in clinical early-stage OSCC and develop a nomogram based on TIICs to predict the prognosis. METHODS: Eighty patients with clinical early-stage (cT1,2N0M0) OSCC were enrolled in this study. Immunohistochemical staining was performed to evaluate the infiltration of TIICs, including CD8+ T cells, CD57+ NK cells, CD163+ macrophage, and CD20+ B cells. Overall survival (OS) and disease-free survival (DFS) curves were plotted by the Kaplan-Meier method. Cox's proportional hazards regression models were performed to assess the prognostic value of TIICs. Finally, a nomogram was established to predict the OS based on TIICs infiltration and assessed by concordance index (C-index) and calibration curve. RESULTS: High infiltrations of CD57+ NK cells and CD20+ B cells indicated a better OS in clinical early-stage OSCC. Moreover, high infiltration of CD20+ B cells favored a longer DFS. Of note, low infiltrations of CD57+ NK cells and CD20+ B cells were independent prognostic factors for poor OS in clinical early-stage OSCC. The nomogram that combined CD57+ NK cells with CD20+ B cells could predict the OS in clinical early-stage OSCC, and the C-index was 0.801 (95% CI: 0.679-0.924). The calibration plot showed that prediction and observation are well matched. CONCLUSIONS: High infiltration of CD57+ NK cells and CD20+ B cells indicate a favorable OS in clinical early-stage OSCC. The nomogram constructed based on TIICs might be used for predicting the prognosis in clinical early-stage OSCC.

Development of a TNF-α-mediated Trojan Horse for bacteria-based cancer therapy.

Tumor necrosis factor α (TNF-α) is upregulated in a chronic inflammatory environment, including tumors, and has been recognized as a pro-tumor factor in many cancers. Applying the traditional TNF-α antibodies that neutralize TNF-α activity, however, only exerts modest anti-tumor efficacy in clinical studies. Here, we develop an innovative approach to target TNF-α that is distinct from the neutralization mechanism. We employed phage display and yeast display to select non-neutralizing antibodies that can piggyback on TNF-α and co-internalize into cells through receptor ligation. When conjugating with toxins, the antibody exhibited cytotoxicity to cancer cells in a TNF-α-dependent manner. We further implemented the immunotoxin to an E. coli vehicle specially engineered for a high secretion level. In a syngeneic murine melanoma model, the bacteria stimulated TNF-α expression that synergized with the secreted immunotoxin and greatly inhibited tumor growth. The treatment also dramatically remodeled the tumor microenvironment in favor of several anti-tumor immune cells, including N1 neutrophils, M1 macrophages, and activated CD4+ and CD8+ lymphocytes. We anticipate that our new piggyback strategy is generalizable to targeting other soluble ligands and/or conjugates with different drugs for managing a diverse set of diseases.

Sex-biased molecular differences in lung adenocarcinoma are ethnic and smoking specific.

BACKGROUND: Sex-related differences in cancer epidemiology, tumor biology, immune system activity, and pharmacogenomics have been suggested to be important considerations for precision cancer control. Here we elucidated systematically sex biases in genetic variants, gene expression profiles, and immunological landscapes of lung adenocarcinoma patients (LUADs) with different ancestry and smoking status. METHODS: Somatic mutation and mRNA expression data of Asian and Non-Asian LUADs were obtained from public databases. Sex-biased genetic mutations, gene expression, biological pathways, and immune infiltration were identified in the context of smoking status and race. RESULTS: Among nonsmokers, male-biased mutations were prevalent in Asian LUADs, while few sex-biased mutations were detected in Non-Asian LUADs. EGFR was the only mutation whose frequency was significantly higher in females than males in both Asian and Non-Asian nonsmokers. More genes exhibited sex-biased expression in Non-Asian LUADs compared to Asian LUADs. Moreover, genes distinctly expressed in females were mainly related to immune-related pathways, whereas those in males were more involved in activation of DNA repair, E2F_targets, and MYC_targets pathways. We also detected sex-specific immune infiltration in the context of genetic variation. In EGFR-mutant LUADs, males had a significantly increased infiltration of CD8 + T cells, whereas resting CD4 + memory T cells were more abundant in females. Additionally, in KRAS-mutant LUADs, CD8 + and CD4 + T cells were more abundant in females than males. In addition, we detected all female patients with high SCGB3A2 expression were exclusively sensitive to immunotherapy, while this phenomenon was not observed in male patients. CONCLUSIONS: Our findings provided evidence that sex-related molecular and cellular components are involved in shaping tumor distinct genetic and immune features, which might have important impact on personalized targeted and immune therapy.

CD79A work as a potential target for the prognosis of patients with OSCC: analysis of immune cell infiltration in oral squamous cell carcinoma based on the CIBERSORTx deconvolution algorithm.

OBJECTIVE: To analyze the abundance of infiltrating tumor immune cells in patients with oral squamous cell carcinoma (OSCC) and to search for potential targets that can predict patient prognosis. METHODS: A total of 400 samples from 210 patients with OSCC were collected using The Cancer Genome Atlas (TCGA) database. CIBERSORTx was used to evaluate the infiltration abundance of tumor immune cells. Potential target genes were searched to predict patient prognosis through case grouping, differential analysis, and enrichment analysis. Surgical excisional tissue sections of patients with oral squamous cell carcinoma admitted to the Department of Oral and Maxillofacial Surgery, Second Affiliated Hospital of Shantou University Medical College, from 2015 to 2018 were collected and followed up. RESULTS: The CIBERSORTx deconvolution algorithm was used to analyze the infiltration abundance of immune cells in the samples. Cases with a high infiltration abundance of naive and memory B lymphocytes improved the prognosis of OSCC patients. The prognosis of patients with low CD79A expression was significantly better than that of patients with high CD79A expression. CONCLUSION: CD79A can predict the infiltration abundance of B lymphocytes in the tumor microenvironment of patients with OSCC. CD79A is a potential target for predicting the prognosis of patients with OSCC. This study provides novel ideas for the treatment of OSCC and for predicting patient prognosis.

Characterization and clinical relevance of PDGFRA pathway copy number variation gains across human cancers.

We investigated the copy number variation (CNV) of PDGFRA pathway across all common cancer types as well as its clinical relevance. This study included a total of 10,678 patients with pan-cancerous species involving 33 types of cancers and patient information was obtained from The Cancer Genome Atlas. According to the PDGFRA pathway CNV, all samples were divided into copy number gain (CN gain) group and No CN gain group. The analysis of loss of heterozygosity (LOH) fraction, CNV burden, tumor mutation burden (TMB), and the number of immunogenic mutations were performed, as well as the correlation analysis of PDGFRA pathway CN gain with tumor-related signaling pathways and tumor-infiltrating immune cell subpopulations. The results showed that CN gain of PDGFRA pathway in the cancer patients was associated with significantly shorter overall survival. The CN gain of PDGFRA pathway was identified as a prognostic risk factor for some tumors. CN gain was accompanied by an altered percentage of LOH, CNV burden, TMB, the number of immunogenic mutations were increased and tumor-infiltrating immune cell subpopulations were less. While certain tumor-related signaling pathways, such as hypoxia, cell cycle, DNA repair, and epithelial-mesenchymal transition were more enriched in the CN gain group, quiescence, and inflammation pathways were more enriched in the No CN gain group. In conclusion, PDGFRA pathway CNV gain may be a poor prognostic factor in cancer patients.

Construction of a predictive model for immunotherapy efficacy in lung squamous cell carcinoma based on the degree of tumor-infiltrating immune cells and molecular typing.

BACKGROUND: To construct a predictive model of immunotherapy efficacy for patients with lung squamous cell carcinoma (LUSC) based on the degree of tumor-infiltrating immune cells (TIIC) in the tumor microenvironment (TME). METHODS: The data of 501 patients with LUSC in the TCGA database were used as a training set, and grouped using non-negative matrix factorization (NMF) based on the degree of TIIC assessed by single-sample gene set enrichment analysis (GSEA). Two data sets (GSE126044 and GSE135222) were used as validation sets. Genes screened for modeling by least absolute shrinkage and selection operator (LASSO) regression and used to construct a model based on immunophenotyping score (IPTS). RNA extraction and qPCR were performed to validate the prognostic value of IPTS in our independent LUSC cohort. The receiver operating characteristic (ROC) curve was constructed to determine the predictive value of the immune efficacy. Kaplan-Meier survival curve analysis was performed to evaluate the prognostic predictive ability. Correlation analysis and enrichment analysis were used to explore the potential mechanism of IPTS molecular typing involved in predicting the immunotherapy efficacy for patients with LUSC. RESULTS: The training set was divided into a low immune cell infiltration type (C1) and a high immune cell infiltration type (C2) by NMF typing, and the IPTS molecular typing based on the 17-gene model could replace the results of the NMF typing. The area under the ROC curve (AUC) was 0.82. In both validation sets, the IPTS of patients who responded to immunotherapy were significantly higher than those who did not respond to immunotherapy (P = 0.0032 and P = 0.0451), whereas the AUC was 0.95 (95% CI = 1.00-0.84) and 0.77 (95% CI = 0.58-0.96), respectively. In our independent cohort, we validated its ability to predict the response to cancer immunotherapy, for the AUC was 0.88 (95% CI = 1.00-0.66). GSEA suggested that the high IPTS group was mainly involved in immune-related signaling pathways. CONCLUSIONS: IPTS molecular typing based on the degree of TIIC in the TME could well predict the efficacy of immunotherapy in patients with LUSC with a certain prognostic value.

Ferroptosis-related gene SLC1A5 is a novel prognostic biomarker and correlates with immune infiltrates in stomach adenocarcinoma.

BACKGROUND: Stomach adenocarcinoma (STAD) is associated with high morbidity and mortality rates. Ferroptosis is an iron-dependent form of cell death, which plays an important role in the development of many cancers. Tumor-associated competing endogenous RNAs (ceRNAs) regulate tumorigenesis and development. Our study aimed to construct ceRNA networks and explore the relationship between ferroptosis-related genes in the ceRNA network and immune infiltration in STAD. METHODS: Based on the interactions among long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and messenger RNAs (mRNAs), a ceRNA network was constructed to illustrate the relationships among lncRNAs, miRNAs, and mRNAs. Subsequently, gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) functional enrichment analyses were carried out to explore the functions and interactions of the differentially expressed (DE) mRNAs related to the ceRNA network. Differential expression and prognostic analysis of ferroptosis-related genes in the ceRNA network were performed using the R package "limma" and "survminer." The correlation between ferroptosis-related genes and tumor-infiltrating immune cells was analyzed using Spearman correlation analysis and CIBERSORT. Quantitative real-time PCR (qRT-PCR) was used to validate the expression of ferroptosis-related genes in STAD cells lines. RESULTS: A ceRNA network consisting of 29 DElncRNAs, 31 DEmiRNAs, and 182 DEmRNAs was constructed. These DEmRNAs were significantly enriched in pathways related to the occurrence and development of STAD. The ferroptosis-related gene SLC1A5 was upregulated in STAD (P < 0.001) and was associated with better prognosis (P = 0.049). The CIBERSORT database and Spearman correlation analysis indicated that SLC1A5 was correlated with eight types of tumor-infiltrating immune cells and immune checkpoints, including PD-L1(CD-274) and PD-1(PDCD1). The SLC1A5 mRNA was found to be highly expressed in STAD cells lines. CONCLUSIONS: Our study provides insights into the function of ceRNAs in STAD and identifies biomarkers for the development of therapies for STAD. The ferroptosis-related gene SLC1A5 in the ceRNA network was associated with both tumor-infiltrating immune cells and immune checkpoints in the tumor microenvironment, suggesting that SLC1A5 may be a novel prognostic marker and a potential target for STAD immunotherapy in the future.

Protein-based prognostic signature for predicting the survival and immunotherapeutic efficiency of endometrial carcinoma.

BACKGROUND: Endometrial cancer (EC) is the most frequent malignancy of the female genital tract worldwide. Our study aimed to construct an effective protein prognostic signature to predict prognosis and immunotherapy responsiveness in patients with endometrial carcinoma. METHODS: Protein expression data, RNA expression profile data and mutation data were obtained from The Cancer Proteome Atlas (TCPA) and The Cancer Genome Atlas (TCGA). Prognosis-related proteins in EC patients were screened by univariate Cox regression analysis. Least absolute shrinkage and selection operator (LASSO) analysis and multivariate Cox regression analysis were performed to establish the protein-based prognostic signature. The CIBERSORT algorithm was used to quantify the proportions of immune cells in a mixed cell population. The Immune Cell Abundance Identifier (ImmuCellAI) and The Cancer Immunome Atlas (TCIA) web tools were used to predict the response to immunochemotherapy. The pRRophetic algorithm was used to estimate the sensitivity of chemotherapeutic and targeted agents. RESULTS: We constructed a prognostic signature based on 9 prognostic proteins, which could divide patients into high-risk and low-risk groups with distinct prognoses. A novel prognostic nomogram was established based on the prognostic signature and clinicopathological parameters to predict 1, 3 and 5-year overall survival for EC patients. The results obtained with Clinical Proteomic Tumor Analysis Consortium (CPTAC), Human Protein Atlas (HPA) and immunohistochemical (IHC) staining data from EC samples in our hospital supported the predictive ability of these proteins in EC tumors. Next, the CIBERSORT algorithm was used to estimate the proportions of 22 immune cell types. The proportions of CD8 T cells, T follicular helper cells and regulatory T cells were higher in the low-risk group. Moreover, we found that the prognostic signature was positively associated with high tumor mutation burden (TMB) and high microsatellite instability (MSI-H) status in EC patients. Finally, ImmuCellAI and TCIA analyses showed that patients in the low-risk group were more inclined to respond to immunotherapy than patients in the high-risk group. In addition, drug sensitivity analysis indicated that our signature had potential predictive value for chemotherapeutics and targeted therapy. CONCLUSION: Our study constructed a novel prognostic protein signature with robust predictive ability for survival and efficiency in predicting the response to immunotherapy, chemotherapy and targeted therapy. This protein signature represents a promising predictor of prognosis and response to cancer treatment in EC patients.

High ratio of pCXCR4/CXCR4 tumor infiltrating immune cells in primary high grade ovarian cancer is indicative for response to chemotherapy.

BACKGROUND: Ovarian cancer (OC) is the fifth most common malignant female cancer with a high mortality, mainly because of aggressive high-grade serous carcinomas (HGSOC), but also due to absence of specific early symptoms and effective detection strategies. The CXCL12-CXCR4 axis is considered to have a prognostic impact and to serve as potential therapeutic target. Therefore we investigated the role of pCXCR4 and CXCR4 expression of the tumor cells and of tumor infiltrating immune cells (TIC) in high-grade serous OC and their association with the recurrence-free (RFS) and overall survival (OS). METHODS: A tissue microarray of 47 primary high grade ovarian serous carcinomas and their recurrences was stained with primary antibodies directed against CXCR4 and pCXCR4. Beside the evaluation of the absolute tumor as well as TIC expression in primary and recurrent cancer biopsies the corresponding ratios for pCXCR4 and CXCR4 were generated and analyzed. The clinical endpoints were response to chemotherapy, OS as well as RFS. RESULTS: Patients with a high pCXCR4/CXCR4 TIC ratio in primary cancer biopsies showed a significant longer RFS during the first two years (p = 0.025). However, this effect was lost in the long-term analysis including a follow-up period of 5 years (p = 0.128). Interestingly, the Multivariate Cox regression analysis showed that a high pCXCR4/CXCR4 TIC ratio in primary cancer independently predicts longer RFS (HR 0.33; 95CI 0.13 - 0.81; p = 0.015). Furthermore a high dichotomized distribution of CXCR4 positive tumor expression in recurrent cancer biopsies showed a significantly longer 6-month RFS rate (p = 0.018) in comparison to patients with low CXCR4 positive tumor expression. However, this effect was not independent of known risk factors in a Multivariate Cox regression (HR 0.57; 95CI 0.24 - 1.33; p = 0.193). CONCLUSIONS: To the best of our knowledge we show for the first time that a high pCXCR4/CXCR4 TIC ratio in primary HGSOC biopsies is indicative for better RFS and response to chemotherapy. HIGHLIGHTS: • We observed a significant association between high pCXCR4/CXCR4 TIC ratio and better RFS in primary cancer biopsies, especially during the early postoperative follow-up and independent of known risk factors for recurrence. • High CXCR4 tumor expression in recurrent HGSOC biopsies might be indicative for sensitivity to chemotherapy. We found evidence that at the beginning of the disease (early follow-up) the role of the immune response seems to be the most crucial factor for progression. On the other hand in recurrent/progressive disease the biology of the tumor itself becomes more important for prognosis. • We explored for the first time the predictive and prognostic role of pCXCR4/CXCR4 TIC ratio in high-grade serous ovarian cancer.

High Mast Cell Density Predicts a Favorable Prognosis in Patients with Pancreatic Neuroendocrine Neoplasms.

INTRODUCTION: Mast cells are involved in allergic diseases, immune regulation, and tumor microenvironment modulation, with both pro- and anti-tumorigenic functions, and could serve as a prognostic factor in various cancers. However, their potential role in pancreatic neuroendocrine neoplasms (PanNENs) is largely unknown. Here, our aim was to investigate the presence of mast cells in PanNENs and evaluate their association with clinicopathological parameters and other common tumor-infiltrating immune cells. METHODS: Tissue microarrays containing PanNEN samples from 187 patients were constructed and stained immunohistochemically for CD117, CD15, CD68, CD3, CD4, and CD8. Immune cells were counted from four high-power fields (HPFs; ×400) at maximal concentrations, and the mean counts were calculated per HPF. The cutoff values were set by X-tile. RESULTS: The median (interquartile range) counts of CD117+ mast cells, CD15+ neutrophils, CD68+ macrophages, CD3+ T cells, and CD4+ T cells were 3.5 (2.0-6.0), 3.0 (1.3-6), 3.8 (2.5-5.8), 13 (8.0-24.0), and 2.0 (1.0-4.0)/HPF, respectively. CD8+ T cells were not detected. The cutoff values for these immune cells were 1.5/HPF, 6/HPF, 4.8/HPF, 32.5/HPF, and 2/HPF, respectively. Low mast cell density was correlated with higher grades, noninsulinoma, and advanced stages. Moreover, high mast cell infiltration was associated with elevated CD4+ T cell and CD15+ neutrophil counts. Multivariate analysis revealed that high mast cell density was an independent predictor of prolonged progression-free survival in the entire cohort; in pancreatic neuroendocrine tumors; and in intermediate-grade, noninsulinoma, and advanced stage subgroups. CONCLUSIONS: These findings suggest a protective role of mast cells in PanNENs.

Comparison of tumor immune environment between newly diagnosed and recurrent glioblastoma including matched patients.

PURPOSE: Glioblastoma (GBM) is the most lethal primary brain tumor in adult patients. The disease progression, response to chemotherapy and radiotherapy at initial diagnosis, and prognosis are profoundly associated with the tumor microenvironment, especially the features of tumor-infiltrating immune cells (TII). Recurrent GBM is even more challenging to manage. Differences in the immune environment between newly diagnosed and recurrent GBM and an association with tumor prognosis are not well defined. METHODS: To address this knowledge gap, we analyzed the clinical data and tissue specimens from 24 GBM patients (13 at initial diagnosis and 11 at recurrence). The expression levels of multiple immunobiological markers in patients' GBM at initial diagnosis versus at recurrence were compared, including five patients with both specimens available (paired). The distribution patterns of TII were evaluated in both the intratumoral and perivascular regions. RESULTS: We found that tumors from recurrent GBM have significantly more tumor-infiltrating lymphocytes (TILs) and macrophages and higher PD-L1 and PD-1 expression than tumors at primary diagnosis and benign brain specimens from epilepsy surgery. The pattern changes of the TILs and macrophages of the five paired specimens were consistent with the unpaired patients, while the CD8 to CD4 ratio remained constant from diagnosis to recurrence in the paired tissues. The levels of TILs, macrophages, PD-1 or PD-L1+ cells at initial diagnosis did not correlate with OS. TILs, macrophages, and PD-1+ cells were increased in recurrent tumors both in intratumoral and perivascular areas, with higher distribution levels in intratumoral than perivascular regions. Higher CD4 or CD8 infiltration at recurrence was associated with a worse prognosis, respectively. CONCLUSIONS: Our study elucidated that TIL and TAM tend to accumulate in perivascular region and are more abundant in recurrent GBM than newly diagnosed GBM.