Siglec15 shapes a non-inflamed tumor microenvironment and predicts the molecular subtype in bladder cancer.
ABSTRACT: Rationale: Siglec15 is an emerging target for normalization cancer immunotherapy. However, pan-cancer anti-Siglec15 treatment is not yet validated and the potential role of Siglec15 in bladder cancer (BLCA) remains elusive. Methods: We comprehensively evaluated the expression pattern and immunological role of Siglec15 using pan-cancer analysis based on RNA sequencing data obtained from The Cancer Genome Atlas. We then systematically correlated Siglec15 with immunological characteristics in the BLCA tumor microenvironment (TME), including immunomodulators, cancer immunity cycles, tumor-infiltrating immune cells (TIICs), immune checkpoints, and T cell inflamed score. We also analyzed the role of Siglec15 in predicting the molecular subtype and the response to several treatment options in BLCA. Our results were validated in several public cohorts as well as our BLCA tumor microarray cohort, the Xiangya cohort. We developed an immune risk score (IRS), validated it, and tested its ability to predict the prognosis and response to cancer immunotherapy. Results: We found that Siglec15 was specifically overexpressed in the TME of various cancers. We hypothesize that Siglec15 designs a non-inflamed TME in BLCA based on the evidence that Siglec15 negatively correlated with immunomodulators, TIICs, cancer immunity cycles, immune checkpoints, and T cell inflamed score. Bladder cancer with high Siglec15 expression was not sensitive to cancer immunotherapy, but exhibited a higher incidence of hyperprogression. High Siglec15 levels indicated a luminal subtype of BLCA characterized by lower immune infiltration, lower response to cancer immunotherapy and neoadjuvant chemotherapy, but higher response to anti-angiogenic therapy and targeted therapies such as blocking Siglec15, ?-catenin, PPAR-?, and FGFR3 pathways. Notably, a combination of anti-Siglec15 and cancer immunotherapy may be a more effective strategy than monotherapy. IRS can accurately predict the prognosis and response to cancer immunotherapy. Conclusions: Anti-Siglec15 immunotherapy might be suitable for BLCA treatment as Siglec15 correlates with a non-inflamed TME in BLCA. Siglec15 could also predict the molecular subtype and the response to several treatment options.
Project description:<h4>Objectives</h4>Bladder urothelial carcinoma (BLCA) is one of the most common malignancies in urinary system. With the development of next-generation sequencing technology, we intended to investigate prognostic immune cells and related signature to predict the prognosis of BLCA and potential therapeutic targets.<h4>Methods</h4>We obtained the transcriptome profiles of 573 BLCA patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The fractions of immune cells in each sample was calculated by "CIBERSORT" algorithm. Tumor Infiltrating Immune Cells Scores (TIICS) was accordingly derived and Receiver Operating Characteristic (ROC) curve was conducted to evaluate the predictive efficiency. Moreover, differential analysis was performed between two TIICS groups and hub TIICS-related immune signature was identified. The correlation of key immune genes and immune-infiltrating immune cells was evaluated based on the TIMER database. An Immune Signature Prognostic Index (ISPI) based on these signatures was constructed with superior predictive accuracy. Last, the TIICS model or related immune signature were all validated in an independent cohort from the GSE13507.<h4>Results</h4>The least absolute shrinkage and selection operator (LASSO) algorithm was utilized to screen the 6 hub tumor-infiltrating immune cells in TCGA cohort, where higher infiltrating levels of M0 Macrophages, M2 Macrophages and Neutrophils were hazard factors, while CD8<sup>+</sup> T cells and memory activated CD4<sup>+</sup> T cells were protective factors.<h4>Conclusion</h4>Taken together, our study identified several prognostic immune cells and related immune signature in BLCA, shedding insight on the individualized immunotherapy or potential drug targets.
Project description:BACKGROUND:The epigenetic regulation of immune response has been demonstrated in recent studies. Nonetheless, potential roles of RNA N6-methyladenosine (m6A) modification in tumor microenvironment (TME) cell infiltration remain unknown. METHODS:We comprehensively evaluated the m6A modification patterns of 1938 gastric cancer samples based on 21 m6A regulators, and systematically correlated these modification patterns with TME cell-infiltrating characteristics. The m6Ascore was constructed to quantify m6A modification patterns of individual tumors using principal component analysis algorithms. RESULTS:Three distinct m6A modification patterns were determined. The TME cell-infiltrating characteristics under these three patterns were highly consistent with the three immune phenotypes of tumors including immune-excluded, immune-inflamed and immune-desert phenotypes. We demonstrated the evaluation of m6A modification patterns within individual tumors could predict stages of tumor inflammation, subtypes, TME stromal activity, genetic variation, and patient prognosis. Low m6Ascore, characterized by increased mutation burden and activation of immunity, indicated an inflamed TME phenotype, with 69.4% 5-year survival. Activation of stroma and lack of effective immune infiltration were observed in the high m6Ascore subtype, indicating a non-inflamed and immune-exclusion TME phenotype, with poorer survival. Low m6Ascore was also linked to increased neoantigen load and enhanced response to anti-PD-1/L1 immunotherapy. Two immunotherapy cohorts confirmed patients with lower m6Ascore demonstrated significant therapeutic advantages and clinical benefits. CONCLUSIONS:This work revealed the m6A modification played a nonnegligible role in formation of TME diversity and complexity. Evaluating the m6A modification pattern of individual tumor will contribute to enhancing our cognition of TME infiltration characterization and guiding more effective immunotherapy strategies.
Project description:Background:As bladder cancer was recognized to be immunogenic, dozens of studies have focused on immune biology of BLCA, but little is known about its relationship with the long non-coding RNAs (lncRNAs). Methods:LASSO Cox regression model was used to establish immune-related lncRNAs signature (IRLS) in BLCA. The immune infiltration landscape of BLCA was conducted via ssGSEA and immunotherapy response was calculated through TIDE algorithm. Results:A total of 82 immune-related lncRNAs were screened out according to spearman correlation analysis with the immune score (|R|?>?0.4, p?<?0.05). We selected 5 prognostic lncRNAs to construct immune-related lncRNAs signature (IRLS) through LASSO Cox regression analysis. Then we validated that 5 enrolled lncRNAs was downregulated in BLCA tissues and cells when compared with paracancerous tissues and normal bladder epithelium cell. The univariate and multivariate Cox regression analysis both demonstrated the IRLS was a robust independent prognostic factor in overall survival prediction with high accuracy. The GSVA and GSEA also suggested that the IRLS are involved in the immune-related biological processes and pathways which are very well known in the context of BLCA tumorigenesis. In addition, we found that IRLS is strikingly positive correlated with tumour microenvironment (TME) immune cells infiltration and expression of critical immune checkpoints, indicating that the poor prognosis might be caused partly by immunosuppressive TME. Finally, the results from the TIDE analysis revealed that IRLS could efficiently predict the clinical response of immunotherapy in BLCA. Conclusion:We have developed a novel IRLS, which have a latent prognostic value for BLCA patients and might facilitate personalized counselling for immunotherapy.
Project description:Background: The efficiency of immune checkpoint inhibitors (ICIs) in bladder cancer (BLCA) treatment has been widely validated; however, the tumor response to ICIs was generally low. It is critical and urgent to find biomarkers that can predict tumor response to ICIs. The tumor microenvironment (TME), which may play important roles to either dampen or enhance immune responses, has been widely concerned. Methods: The cancer genome atlas BLCA (TCGA-BLCA) cohort (n = 400) was used in this study. Based on the proportions of 22 types of immune cells calculated by CIBERSORT, TME was classified by K-means Clustering and differentially expressed genes (DEGs) were determined. Based on DEGs, patients were classified into three groups, and cluster signature genes were identified after reducing redundant genes. Then TMEscore was calculated based on cluster signature genes, and the samples were classified to two subtypes. We performed somatic mutation and copy number variation analysis to identify the genetic characteristics of the two subtypes. Correlation analysis was performed to explore the correlation between TMEscore and the tumor response to ICIs as well as the prognosis of BLCA. Results: According to the proportions of immune cells, two TME clusters were determined, and 1,144 DEGs and 138 cluster signature genes were identified. Based on cluster signature genes, samples were classified into TMEscore-high (n = 199) and TMEscore-low (n = 201) subtypes. Survival analysis showed patients with TMEscore-high phenotype had better prognosis. Among the 45 differentially expressed micro-RNAs (miRNAs) and 1,033 differentially expressed messenger RNAs (mRNAs) between the two subtypes, 16 miRNAs and 287 mRNAs had statistically significant impact on the prognosis of BLCA. Furthermore, there were 94 genes with significant differences between the two subtypes, and they were enriched in RTK-RAS, NOTCH, WNT, Hippo, and PI3K pathways. The Tumor Immune Dysfunction and Exclusion (TIDE) score of TMEscore-high BLCA was statistically lower than that of TMEscore-low BLCA. Receiver operating characteristic (ROC) curve analysis showed that the area under the curve (AUC) of TMEscore and tumor mutation burden (TMB) is 0.6918 and 0.5374, respectively. Conclusion: We developed a method to classify BLCA patients to two TME subtypes, TMEscore-high and TMEscore-low, and we found TMEscore-high subtype of BLCA had a good prognosis and a good response to ICIs.
Project description:<h4>Purpose</h4>Identify immune-related lncRNA (IRL) signature related to the prognosis and immunotherapeutic efficiency for bladder cancer (BLCA) patients.<h4>Methods</h4>A total of 397 samples, which contained RNA-seq and clinical information from The Cancer Genome Atlas (TCGA) database, were used for the following study. Then the Lasso penalized Cox proportional hazards regression model was used to construct prognostic signature. According to the optimal cut-off value determined by time-dependent ROC curve, low and high-risk groups were set up. One immunotherapy microarray dataset as validation set was used to verify the ability of predicting immunotherapy efficacy. Furthermore, more evaluation between two risk groups related clinical factors were conducted. Finally, external validation of IRL-signature was conducted in Zhengzhou cohort.<h4>Result</h4>Four IRLs (<i>HCP5, IPO5P1, LINC00942</i>, and <i>LINC01356</i>) with significant prognostic value (P<0.05) were distinguished. This signature can accurately predict the overall survival of BLCA patients and was verified in the immunotherapy validation set. IRL-signatures can be used as independent prognostic risk factor in various clinical subgroups. According to the results of GSVA and MCP algorithm, we found that IRL-signature risk score is strikingly negative correlated with tumor microenvironment (TME) CD8+T cells and Cytotoxic lymphocytes infiltration, indicating that the better prognosis and immunotherapy might be caused partly by these. Then, the results from the TIDE analysis revealed that IRL could efficiently predict the response of immunotherapy in BLCA. External validation had similar results with TCGA-BLCA cohort.<h4>Conclusions</h4>The novel IRL-signature has a significant prognostic value for BLCA patients might facilitate predicting the efficacy of immunotherapy.
Project description:Bladder cancer (BLCA) is the fifth most common cancer and has the features of low survival rate and high morbidity and mortality. The Cancer Genome Atlas (TCGA) is a pool of global gene expression profile and contains huge amounts of cancer genomics data, which makes it possible to inquire the relationship between gene expression and prognosis of a series of malignant tumors including BLCA. Immune and stromal cells are two major components of tumor microenvironment (TME) which play an important role in judging the prognosis of tumor and influencing the progression of malignant, inflammatory, and metabolic disorders. In our study, we conducted a quantitative analysis of immune and stromal elements based on the ESTIMATE algorithm and thus divided BLCA cases into high and low groups. Then the differentially expressed genes closely related to tumor prognosis between groups were identified and had been shown to correlate with immune response and stromal alterations, which was further confirmed by functional enrichment analysis and protein-protein interaction networks. We validated those genes through BLCA dates downloaded from ArrayExpress and thus got the marker genes to predict prognosis of BLCA. Additionally, immune cell infiltration analysis explored the correlation between the verified genes and immune cells. In conclusion, we identified a series of TME-related genes that assess the prognosis and explored the interaction between TME and tumor prognosis to guide clinical individualized treatment.
Project description:BACKGROUND:Recent efforts of gene expression profiling analyses recognized at least four different triple-negative breast cancer (TNBC) molecular subtypes. However, little is known regarding their tumor microenvironment (TME) heterogeneity. METHODS:Here, we investigated TME heterogeneity within each TNBC molecular subtype, including immune infiltrate localization and composition together with expression of targetable immune pathways, using publicly available transcriptomic and genomic datasets from a large TNBC series totaling 1512 samples. Associations between molecular subtypes and specific features were assessed using logistic regression models. All statistical tests were two-sided. RESULTS:We demonstrated that each TNBC molecular subtype exhibits distinct TME profiles associated with specific immune, vascularization, stroma, and metabolism biological processes together with specific immune composition and localization. The immunomodulatory subtype was associated with the highest expression of adaptive immune-related gene signatures and a fully inflamed spatial pattern appearing to be the optimal candidate for immune check point inhibitors. In contrast, most mesenchymal stem-like and luminal androgen receptor tumors showed an immunosuppressive phenotype as witnessed by high expression levels of stromal signatures. Basal-like, luminal androgen receptor, and mesenchymal subtypes exhibited an immune cold phenotype associated with stromal and metabolism TME signatures and enriched in margin-restricted spatial pattern. Tumors with high chromosomal instability and copy number loss in the chromosome 5q and 15q regions, including genomic loss of major histocompatibility complex related genes, showed reduced cytotoxic activity as a plausible immune escape mechanism. CONCLUSIONS:Our results demonstrate that each TNBC subtype is associated with specific TME profiles, setting the ground for a rationale tailoring of immunotherapy in TNBC patients.
Project description:BACKGROUND & AIMS:Intrahepatic cholangiocarcinoma (ICC) is asevere malignant tumor in which the standard therapies are mostly ineffective. The biological significance of the desmoplastic tumor microenvironment (TME) of ICC has been stressed, but was insufficiently taken into account in the search for classifications of ICC adapted to clinical trial design. We investigated the heterogeneous tumor stroma composition and built a TME-based classification of ICC tumors, which detects potentially targetable ICC subtypes. METHODS:We established the bulk gene expression profiles of 78 ICCs. Epithelial and stromal compartments of 23 ICCs were laser microdissected. We quantified 14 gene-expression signatures of the TME and those of 3 functional indicators (liver activity, inflammation, immune resistance). The cell population abundances were quantified using the Microenvironment Cell Populations (MCP)-counter package and compared with immunohistochemistry. We performed an unsupervised TME-based classification of 198 ICCs (training set) and 368 ICCs (validation set). We determined immune response and signaling features of the different immune subtypes by functional annotations. RESULTS:We showed that a set of 198 ICCs could be classified into 4 TME-based subtypes related to distinct immune escape mechanisms and patient outcomes. The validity of these immune subtypes was confirmed over an independent set of 368 ICCs and by immunohistochemical analysis of 64 ICC tissue samples. About 45% of ICCs displayed an immune desert phenotype. The other subtypes differed in the nature (lymphoid, myeloid, mesenchymal) and abundance of tumor infiltrating cells. The inflamed subtype (11%) presented a massive T-lymphocyte infiltration, an activation of inflammatory and immune checkpoint pathways, and was associated with the longest patient survival. CONCLUSION:We revealed the existence of an inflamed ICC subtype, which is potentially treatable with checkpoint blockade immunotherapy.
Project description:Ovarian cancer (OC) is associated with poor survival because there are a limited number of effective therapies. Two processes key to OC progression, angiogenesis and immune evasion, act synergistically to promote tumor progression. Tumor-associated angiogenesis promotes immune evasion, and tumor-related immune responses in the peritoneal cavity and tumor microenvironment (TME) affect neovascular formation. Therefore, suppressing the angiogenic pathways could facilitate the arrival of immune effector cells and reduce the presence of myeloid cells involved in immune suppression. To date, clinical studies have shown significant benefits with antiangiogenic therapy as first-line therapy in OC, as well as in recurrent disease, and the vascular endothelial growth factor (VEGF) inhibitor bevacizumab is now an established therapy. Clinical data with immunomodulators in OC are more limited, but suggest that they could benefit some patients with recurrent disease. The preliminary results of two phase III trials have shown that the addition of immunomodulators to chemotherapy does not improve progression-free survival. For this reason, it could be interesting to look for synergistic effects between immunomodulators and other active drugs in OC. Since bevacizumab is approved for use in OC, and is tolerable when used in combination with immunotherapy in other indications, a number of clinical studies are underway to investigate the use of bevacizumab in combination with immunotherapeutic agents in OC. This strategy seeks to normalize the TME via the anti-VEGF actions of bevacizumab, while simultaneously stimulating the immune response via the immunotherapy. Results of these studies are awaited with interest.
Project description:The tumor microenvironment consists of an intricately organized system through which immune cells and cancer cells may communicate to regulate anti-tumor immunogenicity. To this end, non-small cell lung cancer (NSCLC) has been shown to activate a variety of immunological mechanisms, thereby broadening our understanding of lung cancer immunobiology. However, while recent work has highlighted the importance of NSCLC immunology and prognosis, studies have not yet examined the tumor microenvironment (TME) globally in regards to the survival outcomes between two major NSCLC subtypes: lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). In the present study, we identify an immunogenic tumor microenvironment state in NSCLC that is enriched for the lung adenocarcinoma subtype. By utilizing TME cell enrichment scores and RNA-seq expression data, we show that the inflamed TME is associated with favorable patient survival in lung adenocarcinoma, but this does not hold true for lung squamous cell carcinoma. Moreover, differentially regulated pathways between immune-inflamed and immune-excluded tumors within LUAD and LUSC were not subtype specific. Instead, immune-inflamed LUSC samples possessed elevated immune checkpoint marker expression when compared to those of the LUAD samples, thereby offering a putative explanation for our prognostic observations. These results shed light on the immunological prognostic effects within lung cancer and may encourage further TME exploration between these two subtypes as the landscape of NSCLC therapy progresses.