Bladder cancer intrinsic LRFN2 drives anticancer immunotherapy resistance by attenuating CD8+ T cell infiltration and functional transition.

BACKGROUND: Immune checkpoint inhibitor (ICI) therapy improves the survival of patients with advanced bladder cancer (BLCA); however, its overall effectiveness is limited, and many patients still develop immunotherapy resistance. The leucine-rich repeat and fibronectin type-III domain-containing protein (LRFN) family has previously been implicated in regulating brain dysfunction; however, the mechanisms underlying the effect of LRFN2 on the tumor microenvironment (TME) and immunotherapy remain unclear. METHODS: Here we combined bulk RNA sequencing, single-cell RNA sequencing, ProcartaPlex multiple immunoassays, functional experiments, and TissueFAXS panoramic tissue quantification assays to demonstrate that LRFN2 shapes a non-inflammatory TME in BLCA. RESULTS: First, comprehensive multiomics analysis identified LRFN2 as a novel immunosuppressive target specific to BLCA. We found that tumor-intrinsic LRFN2 inhibited the recruitment and functional transition of CD8+ T cells by reducing the secretion of pro-inflammatory cytokines and chemokines, and this mechanism was verified in vitro and in vivo. LRFN2 restrained antitumor immunity by inhibiting the infiltration, proliferation, and differentiation of CD8+ T cells in vitro. Furthermore, a spatial exclusivity relationship was observed between LRFN2+ tumor cells and CD8+ T cells and cell markers programmed cell death-1 (PD-1) and T cell factor 1 (TCF-1). Preclinically, LRFN2 knockdown significantly enhanced the efficacy of ICI therapy. Clinically, LRFN2 can predict immunotherapy responses in real-world and public immunotherapy cohorts. Our results reveal a new role for LRFN2 in tumor immune evasion by regulating chemokine secretion and inhibiting CD8+ T-cell recruitment and functional transition. CONCLUSIONS: Thus, LRFN2 represents a new target that can be combined with ICIs to provide a potential treatment option for BLCA.

S100A5 Attenuates Efficiency of Anti-PD-L1/PD-1 Immunotherapy by Inhibiting CD8+ T Cell-Mediated Anti-Cancer Immunity in Bladder Carcinoma.

Although immune checkpoint blockade (ICB) therapies have been approved for bladder cancer (BLCA), only a minority of patients respond to these therapies, and there is an urgent need to explore combined therapies. Systematic multi-omics analysis identified S100A5 as a novel immunosuppressive target for BLCA. The expression of S100A5 in malignant cells inhibited CD8+ T cell recruitment by decreasing pro-inflammatory chemokine secretion. Furthermore, S100A5 attenuated effector T cell killing of cancer cells by inhibiting CD8+ T cell proliferation and cytotoxicity. In addition, S100A5 acted as an oncogene, thereby promoting tumor proliferation and invasion. Targeting S100A5 synergized with the efficacy of anti-PD-1 treatment by enhancing infiltration and cytotoxicity of CD8+ T cells in vivo. Clinically, there was a spatially exclusive relationship between S100A5+ tumor cells and CD8+ T cells in tissue microarrays. Moreover, S100A5 negatively correlated with immunotherapy efficacy in our real-world and several public immunotherapy cohorts. In summary, S100A5 shapes a non-inflamed tumor microenvironment in BLCA by inhibiting the secretion of pro-inflammatory chemokines and the recruitment and cytotoxicity of CD8+ T cells. Targeting S100A5 converts cold tumors into hot tumors, thus enhancing the efficacy of ICB therapy in BLCA.

ACSM6 overexpression indicates a non-inflammatory tumor microenvironment and predicts treatment response in bladder cancer: results from multiple real-world cohorts.

Background: ACSMs play critical roles in lipid metabolism; however, their immunological function within the tumor microenvironment (TME) remains unclear, especially that of ACSM6. In this study, we investigate the latent effect of ACSM6 on bladder cancer (BLCA). Methods: Several real-world cohorts, including the Xiangya (in-house), The Cancer Genome Atlas (TCGA-BLCA), and IMvigor210 cohorts, with TCGA-BLCA cohort serving as the discovery cohort were compared. We investigated the potential immunological effects of ACSM6 in regulating the BLCA tumor microenvironment by analyzing its correlation with immunomodulators, anti-cancer immune cycles, immune checkpoints, tumor-infiltrating immune cells, and the T-cell inflamed score (TIS). Additionally, we assessed the precision of ACSM6 in predicting BLCA molecular subtypes and responses to several treatments using ROC analysis. To ensure the robustness of our findings, all results were confirmed in two independent external cohorts: the IMvigor210 and Xiangya cohorts. Results: ACSM6 expression was markedly upregulated in BLCA. Our analysis suggests that ACSM6 might have significant impact to promote the formation of a non-inflamed tumor microenvironment because of its negative correlation with immunomodulators, anticancer immune cycles, immune checkpoints, tumor-infiltrating immune cells, and the T-cell inflamed score (TIS). Additionally, high ACSM6 expression levels in BLCA may predict the luminal subtype, which is typically associated with resistance to chemotherapy, neoadjuvant chemotherapy, and radiotherapy. These findings were consistent across both the IMvigor210 and Xiangya cohorts. Conclusion: ACSM6 has the potential to serve as a valuable predictor of the tumor microenvironment phenotypes and treatment outcomes in BLCA, thereby contributing to more precise treatment.

Molecular vasculogenic mimicry-Related signatures predict clinical outcomes and therapeutic responses in bladder cancer: Results from real-world cohorts.

Bladder cancer (BLCA) is a heterogeneous disease, and there are many classical molecular subtypes that reflect tumor immune microenvironment (TME) heterogeneity but their clinical utility is limited and correct individual treatment and prognosis cannot be predicted based on them. To find reliable and effective biomarkers and tools for predicting patients' clinical responses to several therapies, we developed a new systemic indicator of molecular vasculogenic mimicry (VM)-related genes mediated by molecular subtypes based on the Xiangya cohort and additional external BLCA cohorts using a random forest algorithm. A correlation was then done between the VM_Score and classical molecular subtypes, clinical outcomes, immunophenotypes, and treatment options for BLCA. With the VM_Score, it is possible to predict classical molecular subtypes, immunophenotypes, prognosis, and therapeutic potential of BLCA with high accuracy. The VM_Scores of high levels indicate a more anticancer immune response but a worse prognosis due to a more basal and inflammatory phenotype. The VM_Score was also found associated with low sensitivity to antiangiogenic and targeted therapies targeting the FGFR3, ß-catenin, and PPAR-γ pathways but with high sensitivity to cancer immunotherapy, neoadjuvant chemotherapy, and radiotherapy. A number of aspects of BLCA biology were reflected in the VM_Score, providing new insights into precision medicine. Additionally, the VM_Score may be used as an indicator of pan-cancer immunotherapy response and prognosis.

A novel platelet risk score for stratifing the tumor immunophenotypes, treatment responses and prognosis in bladder carcinoma: results from real-world cohorts.

Background: Although the durable efficacy of immune checkpoint inhibitors (ICIs) in BLCA has been confirmed in numerous studies, not all patients benefit from their application in the clinic. Platelets are increasingly being found to be closely associated with cancer progression and metastasis; however, their comprehensive role in BLCA remains unclear. Methods: We comprehensively explored platelet expression patterns in BLCA patients using an integrated set of 244 related genes. Correlations between these platelet patterns with tumor microenvironment (TME) subtypes, immune characteristics and immunotherapy efficacies were explored. In addition, a platelet risk score (PRS) was generated for individual prognosis and verified the ability to predict prognosis, precise TME phenotypes, and immunotherapy efficacies. Results: Genes were clustered into two patterns that represented different TME phenotypes and had the ability to predict immunotherapy efficacy. We constructed a PRS that could predict individual prognosis with satisfactory accuracy using TCGA-BLCA. The results remained consistent when PRS was validated in the GSE32894 and Xiangya cohort. Moreover, we found that our PRS was positively related to tumor-infiltrating lymphocytes (TILs) in the TCGA-BLCA and Xiangya cohort. As expected, patients with higher PRS exhibited more sensitive to immunotherapy than patients with lower PRS. Finally, we discovered that a high PRS indicated a basal subtype of BLCA, whereas a low PRS indicated a luminal subtype. Conclusion: Platelet-related genes could predict TME phenotypes in BLCA. We constructed a PRS that could predict the TME, prognosis, immunotherapy efficacy, and molecular subtypes in BLCA.

ACER2 forms a cold tumor microenvironment and predicts the molecular subtype in bladder cancer: Results from real-world cohorts.

Background: ACER2 is a critical gene regulating cancer cell growth and migration, whereas the immunological role of ACER2 in the tumor microenvironment (TME) is scarcely reported. Thus, we lucubrate the potential performance of ACER2 in bladder cancer (BLCA). Methods: We initially compared ACER2 expressions in BLCA with normal urothelium tissues based on data gathered from the Cancer Genome Atlas (TCGA) and our Xiangya cohort. Subsequently, we systematically explored correlations between ACER2 with immunomodulators, anti-cancer immune cycles, tumor-infiltrating immune cells, immune checkpoints and the T-cell inflamed score (TIS) to further confirm its immunological role in BLCA TME. In addition, we performed ROC analysis to illustrate the accuracy of ACER2 in predicting BLCA molecular subtypes and explored the response to several cancer-related treatments. Finally, we validated results in an immunotherapy cohort and Xiangya cohort to ensure the stability of our study. Results: Compared with normal urinary epithelium, ACER2 was significantly overexpressed in several cell lines and the tumor tissue of BLCA. ACER2 can contribute to the formation of non-inflamed BLCA TME supported by its negative correlations with immunomodulators, anti-cancer immune cycles, tumor-infiltrating immune cells, immune checkpoints and the TIS. Moreover, BLCA patients with high ACER2 expression were inclined to the luminal subtype, which were characterized by insensitivity to neoadjuvant chemotherapy, chemotherapy and radiotherapy but not to immunotherapy. Results in the IMvigor210 and Xiangya cohort were consistent. Conclusion: ACER2 could accurately predict the TME and clinical outcomes for BLCA. It would be served as a promising target for precision treatment in the future.

BCAT2 Shapes a Noninflamed Tumor Microenvironment and Induces Resistance to Anti-PD-1/PD-L1 Immunotherapy by Negatively Regulating Proinflammatory Chemokines and Anticancer Immunity.

To improve response rate of monotherapy of immune checkpoint blockade (ICB), it is necessary to find an emerging target in combination therapy. Through analyzing tumor microenvironment (TME)-related indicators, it is validated that BCAT2 shapes a noninflamed TME in bladder cancer. The outcomes of multiomics indicate that BCAT2 has an inhibitory effect on cytotoxic lymphocyte recruitment by restraining activities of proinflammatory cytokine/chemokine-related pathways and T-cell-chemotaxis pathway. Immunoassays reveal that secretion of CD8+ T-cell-related chemokines keeps a robust negative correlation with BCAT2, generating a decreasing tendency of CD8+ T cells around BCAT2+ tumor cells from far to near. Cotreatment of BCAT2 deficiency and anti-PD-1 antibody has a synergistic effect in vivo, implying the potential of BCAT2 in combination therapy. Moreover, the value of BCAT2 in predicting efficacy of immunotherapy is validated in multiple immunotherapy cohorts. Together, as a key molecule in TME, BCAT2 is an emerging target in combination with ICB and a biomarker of guiding precision therapy.

A novel signature to predict the neoadjuvant chemotherapy response of bladder carcinoma: Results from a territory multicenter real-world study.

Background: Although neoadjuvant chemotherapy (NAC) has become the standard treatment option for muscle invasive bladder carcinoma (MIBC), its application is still limited because of the lack of biomarkers for NAC prediction. Methods: We conducted a territory multicenter real-world study to summarize NAC practice in China and its associated clinicopathologic variables with NAC response. Then, we developed and validated a robust gene-based signature for accurate NAC prediction using weighted correlation network analysis (WGCNA), the least absolute shrinkage and selector operation (LASSO) algorithm, a multivariable binary logistic regression model, and immunohistochemistry (IHC). Results: In total, we collected 69 consecutive MIBC patients treated with NAC from four clinical centers. The application of NAC in the real world was relatively safe, with only two grade Ⅳ and seven grade Ⅲ AEs and no treatment-related deaths being reported. Among these patients, 16 patients gave up surgery after NAC, leaving 53 patients for further analysis. We divided them into pathological response and non-response groups and found that there were more patients with a higher grade and stage in the non-response group. Patients with a pathological response could benefit from a significant overall survival (OS) improvement. In addition, univariate and multivariate logistic analyses indicated that tumor grade and clinical T stage were both independent factors for predicting NAC response. Importantly, we developed and validated a five-gene-based risk score for extremely high predictive accuracy for NAC response. Conclusion: NAC was relatively safe and could significantly improve OS for MIBC patients in the real-world practice. Our five-gene-based risk score could guide personalized therapy and promote the application of NAC.

An EMT-based risk score thoroughly predicts the clinical prognosis, tumor immune microenvironment and molecular subtypes of bladder cancer.

Background: Epithelial mesenchymal transition (EMT) is closely related to the occurrence, development, metastasis and antitumor immunity of tumors. However, comprehensive studies correlating EMT and prognosis, tumor microenvironment (TME) and molecular subtypes of bladder cancer (BLCA) are lacking. Methods: TCGA-BLCA was chosen as our training cohort, while Xiangya cohort, GSE13507, GSE48075 were selected as our validation cohorts. Prognostic genes were screened out using univariate Cox analysis and the least absolute shrinkage and selection operator (LASSO) algorithm. Then we developed an EMT risk score based on these prognostic genes and systematically correlated the risk score with prognosis, TME and molecular subtypes of BLCA. Results: Based on EMT related genes, we developed two different EMT patterns, named EMT cluster 1 and cluster 2, and found that cluster 2 showed a worse prognosis and an inflammatory TME phenotype. For personalized prognosis and TME phenotypes predicting, we developed and validated an EMT-based risk score by 7 candidate genes (ANXA10, CNTN1, FAM180A, FN1, IGFL2, KANK4 and TOX3). Patients with high EMT risk scores had lower overall survival (OS) with high predictive accuracy both in the training cohort and validation cohort. In addition, we comprehensively correlated the EMT risk score with TME and molecular subtype, and found that high EMT risk score suggested higher levels of immune cell infiltration and more inclined to present the basal molecular subtype. It was noteworthy that the same results also appeared in the validation of Xiangya cohort. Conclusions: EMT related genes play an important role in tumor progression and immunity in BLCA. Our EMT risk score could accurately predict prognosis and immunophenotype of a single patient, which could guide more effective precision medical strategies.

Neoadjuvant immunotherapy, chemotherapy, and combination therapy in muscle-invasive bladder cancer: A multi-center real-world retrospective study.

To parallelly compare the efficacy of neoadjuvant immunotherapy (tislelizumab), neoadjuvant chemotherapy (gemcitabine and cisplatin), and neoadjuvant combination therapy (tislelizumab + GC) in patients with muscle-invasive bladder cancer (MIBC) and explore the efficacy predictors, we perform a multi-center, real-world cohort study that enrolls 253 patients treated with neoadjuvant treatments (combination therapy: 98, chemotherapy: 107, and immunotherapy: 48) from 15 tertiary hospitals. We demonstrate that neoadjuvant combination therapy achieves the highest complete response rate and pathological downstaging rate compared with neoadjuvant immunotherapy or chemotherapy. We develop and validate an efficacy prediction model consisting of pretreatment clinical characteristics, which can pinpoint candidates to receive neoadjuvant combination therapy. We also preliminarily reveal that patients who achieve pathological complete response after neoadjuvant treatments plus maximal transurethral resection of the bladder tumor may be safe to receive bladder preservation therapy. Overall, this study highlights the benefit of neoadjuvant combination therapy based on tislelizumab for MIBC.

Robust pyroptosis risk score guides the treatment options and predicts the prognosis of bladder carcinoma.

Background: Bladder carcinoma (BLCA) is a heterogeneous disease that makes it difficult to achieve proper individual treatment and predict prognosis. This study aimed to develop a risk score from a new perspective of pyroptosis and guide accurate treatment and prognosis prediction for BLCA. Methods: The TCGA-BLCA cohort data were downloaded from The Cancer Genome Atlas database. Two external validation cohorts were collected from the Gene Expression Omnibus. Another independent validation cohort (the Xiangya cohort) was recruited from our hospital. The least absolute shrinkage and selector operation (LASSO) algorithm and Cox regression models were used to establish the pyroptosis risk score. Thereafter, we correlated the pyroptosis risk score with prognosis, tumor microenvironment (TME) immune hallmarks, and multiple treatments, including anticancer immunotherapy, chemotherapy, radiotherapy, and targeted therapy. Results: The pyroptosis risk score was an independent prognostic predictor of BLCA. We found that the activities of multiple steps of the anticancer immune response cycle, such as the release of cancer cell antigens, CD8 T cell recruitment, and NK cell recruitment, were significantly higher in the high-risk score group than in the low-risk score group. In addition, the infiltration levels of the corresponding tumor-infiltrating immune cells (TIICs), such as CD8 T cells and NK cells, were positively correlated with the pyroptosis risk score. Thus, BLCA with a high-risk score may be associated with inflamed phenotypes. Simultaneously, the expression of multiple immune checkpoints (such as PD-L1, CTLA-4, and PD-1) and enrichment scores of gene signatures positively correlated with immunotherapy response were positively correlated with the pyroptosis risk score. Therefore, patients with a high pyroptosis risk score may be more sensitive to immunotherapy. In addition, patients with high pyroptosis risk scores may be more sensitive to chemotherapeutic drugs, such as cisplatin, docetaxel, and paclitaxel. In addition, the pyroptosis risk score accurately predicted the molecular subtypes of BLCA, which were cross-validated in several independent systems. Conclusions: This study developed and validated a robust pyroptosis risk score that can predict the clinical outcomes and TME immune phenotypes of BLCA. In summary, the pyroptosis risk score helps drive precision therapy in patients with BLCA.

An IFN-γ-related signature predicts prognosis and immunotherapy response in bladder cancer: Results from real-world cohorts.

Bladder cancer (BLCA) is featured with high incidence and mortality. Whether the IFN-γ signaling could be used as an immunotherapy determinant for BLCA has not been fully confirmed. In this study, the transcriptome data and clinical information of BLCA samples were collected from The Cancer Genome Atlas (TCGA). Besides, four immunotherapy cohorts including IMvigor210 cohort, Gide cohort, Van Allen cohort, and Lauss cohort were collected. The Xiangya real-world cohort was used for independent validation. An IFN-γ-related signature was developed and validated in BLCA for predicting prognosis, mutation, tumor microenvironment status, and immunotherapy response. This is the first study focusing on the comprehensive evaluation of predictive values on the IFN-γ-related signature in BLCA. The potential clinical application of the IFN-γ-related signature was expected to be further validated with more prospective clinical cohorts.

Multi-population genetic algorithm with ER network for solving flexible job shop scheduling problems.

A genetic algorithm (GA) cannot always avoid premature convergence, and multi-population is usually used to overcome this limitation by dividing the population into several sub-populations (sub-population number) with the same number of individuals (sub-population size). In previous research, the questions of how a network structure composed of sub-populations affects the propagation rate of advantageous genes among sub-populations and how it affects the performance of GA have always been ignored. Therefore, we first propose a multi-population GA with an ER network (MPGA-ER). Then, by using the flexible job shop scheduling problem (FJSP) as an example and considering the total individual number (TIN), we study how the sub-population number and size and the propagation rate of advantageous genes affect the performance of MPGA-ER, wherein the performance is evaluated by the average optimal value and success rate based on TIN. The simulation results indicate the following regarding the performance of MPGA-ER: (i) performance shows considerable improvement compared with that of traditional GA; (ii) for an increase in the sub-population number for a certain TIN, the performance first increases slowly, and then decreases rapidly; (iii) for an increase in the sub-population size for a certain TIN, the performance of MPGA-ER first increases rapidly and then tends to remain stable; and (iv) with an increase in the propagation rate of advantageous genes, the performance first increases rapidly and then decreases slowly. Finally, we use a parameter-optimized MPGA-ER to solve for more FJSP instances and demonstrate its effectiveness by comparing it with that of other algorithms proposed in other studies.

Different Performances of Different Intelligent Algorithms for Solving FJSP: A Perspective of Structure.

There are several intelligent algorithms that are continually being improved for better performance when solving the flexible job-shop scheduling problem (FJSP); hence, there are many improvement strategies in the literature. To know how to properly choose an improvement strategy, how different improvement strategies affect different algorithms and how different algorithms respond to the same strategy are critical questions that have not yet been addressed. To address them, improvement strategies are first classified into five basic improvement strategies (five structures) used to improve invasive weed optimization (IWO) and genetic algorithm (GA) and then seven algorithms (S1-S7) used to solve five FJSP instances are proposed. For the purpose of comparing these algorithms fairly, we consider the total individual number (TIN) of an algorithm and propose several evaluation indexes based on TIN. In the process of decoding, a novel decoding algorithm is also proposed. The simulation results show that different structures significantly affect the performances of different algorithms and different algorithms respond to the same structure differently. The results of this paper may shed light on how to properly choose an improvement strategy to improve an algorithm for solving the FJSP.