PD-1 topographically defines distinct T cell subpopulations in urothelial cell carcinoma of the bladder and predicts patient survival

NAD+ metabolism enzyme NNMT in cancer-associated fibroblasts drives tumor progression and resistance to immunotherapy by modulating macrophages in urothelial bladder cancer

BACKGROUND

This study comprehensively investigates the association between the expression of nicotinamide N-methyltransferase (NNMT) and clinical outcomes of urothelial bladder cancer (UBC), as well as the molecular mechanisms by which NNMT in cancer-associated fibroblast (CAF) modulates tumor progression and immunotherapy resistance in UBC.

METHODS

Single-cell transcriptomic analyses, immunohistochemical and immunofluorescence assays were performed on bladder cancer samples to validate the relationship between NNMT expression and clinical outcomes. A series of experiments, including chromatin immunoprecipitation assay, liquid chromatography tandem mass spectrometry assay, and CRISPR‒Cas9 (Clustered Regularly Interspaced Short Palindromic Repeats and CRISPR-associated protein 9) knockout, together with in vivo models, have been established to determine the molecular functions of NNMT in CAFs in UBC.

RESULTS

We demonstrated that elevated expression of the nicotinamide adenine dinucleotide (NAD+) metabolism enzyme NNMT in CAFs (NNMT+ CAFs) was significantly associated with non-response to programmed death-ligand 1 (PD-L1) blockade immunotherapy in patients with UBC and predicted the unfavorable prognosis of UBC in two independent large cohorts. Targeting NNMT using the inhibitor 5-Amino-1-methylquinolinium iodide significantly reduced tumor growth and enhanced the apoptotic effects of the anti-PD-L1 antibody in UBC mouse models. Mechanistically, NNMT+ CAFs recruit tumor-associated macrophages via epigenetic reprogramming of serum amyloid A (SAA) to drive tumor cell proliferation and confer resistance to programmed death-1/PD-L1 blockade immunotherapy.

CONCLUSIONS

NNMT+ CAFs were significantly associated with non-response to PD-L1 blockade immunotherapy in patients with UBC. Elevated NNMT, specifically in CAFs, upregulates SAA expression and enhances the recruitment and differentiation of macrophages in the tumor microenvironment, thereby directly or indirectly promoting tumor progression and conferring resistance to immunotherapies in bladder cancer.

Impact of tumour stroma-immune interactions on survival prognosis and response to neoadjuvant chemotherapy in bladder cancer

BACKGROUND

The tumour stroma is associated with unfavourable prognosis in diverse solid tumours, but its prognostic and predictive value in bladder cancer (BCa) is unclear.

METHODS

In this multicentre, retrospective study, we included 830 patients with BCa from six independent cohorts. Differences in overall survival (OS) and cancer-specific survival (CSS) were investigated between high-tumour stroma ratio (TSR) and low-TSR groups. Multi-omics analyses, including RNA sequencing, immunohistochemistry, and single-cell RNA sequencing, were performed to study stroma-immune interactions. TSR prediction models were developed based on pelvic CT scans, and the best performing model was selected based on receiver operator characteristic analysis.

FINDINGS

Compared to low-TSR tumours, high-TSR tumours were significantly associated with worse OS (HR = 1.193, 95% CI: 1.046-1.361, P = 0.008) and CSS (HR = 1.337, 95% CI: 1.139-1.569, P < 0.001), and lower rate of pathological complete response (pCR) to neoadjuvant chemotherapy (NAC). High-TSR tumours exhibited higher infiltration of immunosuppressive cells, including Tregs and tumour-associated neutrophils, while low-TSR tumours exhibited higher infiltration of immune-activating cells such as CD8+ Teff and XCR1+ dendritic cells. The TSR prediction model was developed by combining the intra-tumour and tumour base radiomics features, and showed good performance to predict high-TSR, as indicted by area under the curve of 0.871 (95% CI: 0.821-0.921), 0.821 (95% CI: 0.731-0.911), and 0.801 (95% CI: 0.737-0.865) in the training, internal validation, and external validation cohorts, respectively. In patients with low predicted TSR, 92.3% (12/13) achieved pCR, while only 35.3% (6/17) of patients with high predicted TSR achieved pCR.

INTERPRETATION

The tumour stroma was found to be significantly associated with clinical outcomes in patients with BCa as a result of tumour stroma-immune interactions. The radiomics prediction model provided non-invasive evaluation of TSR and was able to predict pCR in patients receiving NAC for BCa.

FUNDING

This work was supported by National Natural Science Foundation of China (Grant No. 82373254 and 81961128027), Guangdong Provincial Natural Science Foundation (Grant No. 2023A1515010258), Science and Technology Planning Project of Guangdong Province (Grant No. 2023B1212060013). Science and Technology Program of Guangzhou (SL2022A04J01754), Sun Yat-Sen Memorial Hospital Clinical Research 5010 Program (Grant No. SYS-5010Z-202401).

LASSO regression and WGCNA-based telomerase-associated lncRNA signaling predicts clear cell renal cell carcinoma prognosis and immunotherapy response

OBJECTIVE

To investigate whether telomerase-associated lncRNA expression affects the prognosis and anti-tumor immunity of patients with renal clear cell carcinoma (ccRCC).

METHODS

A series of analyses were performed to establish a prognostic risk model and validate its accuracy. Immune-related analyses were performed to assess further the association between immune status, tumor microenvironment, and prognostic risk models.

RESULTS

Eight telomerase-associated lncRNAs associated with prognosis were identified and applied to establish a prognostic risk model. Overall survival was higher in the low-risk group.

CONCLUSION

The established prognostic risk model has a good predictive ability for the prognosis of ccRCC patients and provides a new possible therapeutic target for ccRCC.

Chitinase 3-like 1 expression associated with lymphatic metastasis and prognosis in urothelial carcinoma of the bladder

Objectives

Lymphatic metastasis, an early stage of the metastasis process, is associated with adverse clinical outcomes in urothelial carcinoma of the bladder (UCB). However, the role of inflammation in triggering lymphatic metastasis remains unclear.

Methods

We employed an RNA-sequencing cohort (n = 50) from Sun Yat-Sen Memorial Hospital (SYMH) to identify the most highly upregulated inflammatory gene associated with lymphatic metastasis. Using immunohistochemistry and immunofluorescence analyses, we validated the association of the identified molecule with clinical features and prognosis in an independent UCB cohort (n = 244) from SYMH. We also analysed TCGA-BLCA cohort (n = 408) to identify its potential biological pathways and immune landscape.

Results

In our study, chitinase 3-like 1 (CHI3L1) emerged as a significantly overexpressed proinflammatory mediator in UCB tissues with lymphatic metastasis compared to those without lymphatic metastasis (81.1% vs. 47.8%, P < 0.001). Within UCB tissues, CHI3L1 was expressed in both stromal cells (52.8%) and tumor cells (7.3%). Moreover, CHI3L1+ stromal cells, but not tumor cells, exhibited independent prognostic significance for both overall survival (P < 0.001) and recurrence-free survival (P = 0.006). CHI3L1+ stromal cells were positively associated with D2-40+ lymphatic vessel density (P < 0.001) and the immunosuppressive PD-L1/PD-1/CD8 axis in UCB tissues (all P < 0.05). A bioinformatics analysis also identified a positive association between CHI3L1 expression and lymphangiogenesis or immunosuppression pathways.

Conclusion

Our study established a clear association between stromal CHI3L1 expression and lymphatic metastasis, suggesting that stromal CHI3L1 expression is a potential prognostic marker for bladder cancer patients.

[Profile and immune environment of upper tract urothelial carcinoma]

INTRODUCTION AND OBJECTIVES

Upper Tract Urothelial Carcinoma (UTUC) are tumors that share similarities with bladder tumors. Immunotherapy is already used for bladder locations and appears to have interest for UTUC. In order to rationalize the immunotherapy development pipeline it seemed necessary to describe the immune infiltrate of a cohort of UTUC treated with nephroureterectomy and to determine the expression of a panel of immune checkpoints and co-stimulatory molecules on tumor cells as well as on infiltrating and circulating lymphocytes.

MATERIALS AND METHODS

This is a monocentric, prospective and exploratory work. Patients treated with total nephroureterectomy or segmental ureterectomy for presumably infiltrative (≥ T1) UTUC managed at the Saint-Louis Hospital were included from January 2019 to July 2020. A set of markers and immune checkpoints were studied by flow fluorocytometry on circulating lymphocytes (PBMCs) and tumor-infiltrating lymphocytes (TILs). Some markers were also studied by immunohistochemistry on tumor sample.

RESULTS

In total, 14 patients were included and 13 patients could be analyzed. 1 patient had no residual tumor. 5 tumors out of the 12 (41.7%) showed a lymphocytic inflammatory infiltrate. PD1 was the most represented checkpoint with a median expression rate of 41.4% on CD4+ TILs and 3.89% on circulating CD4+ T cells. This rate was 62.4% and 7.45% respectively on CD8+ T cells. TIGIT was the second most represented marker with a median expression rate on tumor-infiltrating CD4+ T cells of 25% and 2.9% on circulating CD4+ T cells. The median expression level of TIGIT on tumor-infiltrating CD8+ T cells was 23.3% and 3.2% on circulating CD8+ T cells. ICOS was highly expressed on CD4+ TILS with a median of 33.9% in contrast to CD8+ TILS (median: 6.67%). Variable expression of other checkpoints (ILT2, TIM3, LAG3 and OX40) was found without clear trend.

CONCLUSION

This exploratory work highlighted that PD1 was the most represented checkpoint. TIGIT was the second most represented checkpoint while ICOS, TIM3 and LAG3 were 3 other checkpoints whose expression was found to be less important. ILT2 and OX40 appeared to be weakly expressed.

LEVEL OF EVIDENCE

II.

M7G-related LncRNAs: A comprehensive analysis of the prognosis and immunity in glioma

Today, numerous international researchers have demonstrated that N7-methylguanosine (m7G) related long non-coding RNAs (m7G-related lncRNAs) are closely linked to the happenings and developments of various human beings’ cancers. However, the connection between m7G-related lncRNAs and glioma prognosis has not been investigated. We did this study to look for new potential biomarkers and construct an m7G-related lncRNA prognostic signature for glioma. We identified those lncRNAs associated with DEGs from glioma tissue sequences as m7G-related lncRNAs. First, we used Pearson’s correlation analysis to identify 28 DEGs by glioma and normal brain tissue gene sequences and predicated 657 m7G-related lncRNAs. Then, eight lncRNAs associated with prognosis were obtained and used to construct the m7G risk score model by lasso and Cox regression analysis methods. Furthermore, we used Kaplan-Meier analysis, time-dependent ROC, principal component analysis, clinical variables, independent prognostic analysis, nomograms, calibration curves, and expression levels of lncRNAs to determine the model’s accuracy. Importantly, we validated the model with external and internal validation methods and found it has strong predictive power. Finally, we performed functional enrichment analysis (GSEA, aaGSEA enrichment analyses) and analyzed immune checkpoints, associated pathways, and drug sensitivity based on predictors. In conclusion, we successfully constructed the formula of m7G-related lncRNAs with powerful predictive functions. Our study provides instructional value for analyzing glioma pathogenesis and offers potential research targets for glioma treatment and scientific research.

A new CCCH-type zinc finger-related lncRNA signature predicts the prognosis of clear cell renal cell carcinoma patients

Background: Clear cell renal cell carcinoma (ccRCC) is the main component of renal cell carcinoma (RCC), and advanced ccRCC frequently indicates a poor prognosis. The significance of the CCCH-type zinc finger (CTZF) gene in cancer has been increasingly demonstrated during the past few years. According to studies, targeted radical therapy for cancer treatment may be a revolutionary therapeutic approach. Both lncRNAs and CCCH-type zinc finger genes are essential in ccRCC. However, the predictive role of long non-coding RNA (lncRNA) associated with the CCCH-type zinc finger gene in ccRCC needs further elucidation. This study aims to predict patient prognosis and investigate the immunological profile of ccRCC patients using CCCH-type zinc finger-associated lncRNAs (CTZFLs).

Methods: From the Cancer Genome Atlas database, RNA-seq and corresponding clinical and prognostic data of ccRCC patients were downloaded. Univariate and multivariate Cox regression analyses were conducted to acquire CTZFLs for constructing prediction models. The risk model was verified using receiver operating characteristic curve analysis. The Kaplan-Meier method was used to analyze the overall survival (OS) of high-risk and low-risk groups. Multivariate Cox and stratified analyses were used to assess the prognostic value of the predictive feature in the entire cohort and different subgroups. In addition, the relationship between risk scores, immunological status, and treatment response was studied.

Results: We constructed a signature consisting of eight CTZFLs (LINC02100, AC002451.1, DBH-AS1, AC105105.3, AL357140.2, LINC00460, DLGAP1-AS2, AL162377.1). The results demonstrated that the prognosis of ccRCC patients was independently predicted by CTZFLs signature and that the prognosis of high-risk groups was poorer than that of the lower group. CTZFLs markers had the highest diagnostic adequacy compared to single clinicopathologic factors, and their AUC (area under the receiver operating characteristic curve) was 0.806. The overall survival of high-risk groups was shorter than that of low-risk groups when patients were divided into groups based on several clinicopathologic factors. There were substantial differences in immunological function, immune cell score, and immune checkpoint expression between high- and low-risk groups. Additionally, Four agents, including ABT737, WIKI4, afuresertib, and GNE 317, were more sensitive in the high-risk group.

Conclusion: The Eight-CTZFLs prognostic signature may be a helpful prognostic indicator and may help with medication selection for clear cell renal cell carcinoma.

The Research Progress of PD-1/PD-L1 Inhibitors Enhancing Radiotherapy Efficacy

Approximately 60%–70% of patients with malignant tumours require radiotherapy. The clinical application of immune checkpoint inhibitors (ICIs), such as anti-PD-1/PD-L1, has revolutionized cancer treatment and greatly improved the outcome of a variety of cancers by boosting host immunity.However, radiotherapy is a double-edged sword for PD-1/PD-L immunotherapy. Research on how to improve radiotherapy efficacy using PD-1/PD-L1 inhibitor is gaining momentum. Various studies have reported the survival benefits of the combined application of radiotherapy and PD-1/PD-L1 inhibitor. To fully exerts the immune activation effect of radiotherapy, while avoiding the immunosuppressive effect of radiotherapy as much as possible, the dose selection, segmentation mode, treatment timing and the number of treatment sites of radiotherapy play a role. Therefore, we aim to review the effect of radiotherapy combined with anti-PD-1/PD-L1 on the immune system and its optimization.

A New Ferroptosis-Related lncRNA Signature Predicts the Prognosis of Bladder Cancer Patients

Background: Ferroptosis is closely related to the occurrence and development of cancer. An increasing number of studies have induced ferroptosis as a treatment strategy for cancer. However, the predictive value of ferroptosis-related lncRNAs in bladder cancer (BC) still need to be further elucidated. The purpose of this study was to construct a predictive signature based on ferroptosis-related long noncoding RNAs (lncRNAs) to predict the prognosis of BC patients.

Methods: We downloaded RNA-seq data and the corresponding clinical and prognostic data from The Cancer Genome Atlas (TCGA) database and performed univariate and multivariate Cox regression analyses to obtain ferroptosis-related lncRNAs to construct a predictive signature. The Kaplan-Meier method was used to analyze the overall survival (OS) rate of the high-risk and low-risk groups. Gene set enrichment analysis (GSEA) was performed to explore the functional differences between the high- and low-risk groups. Single-sample gene set enrichment analysis (ssGSEA) was used to explore the relationship between the predictive signature and immune status. Finally, the correlation between the predictive signature and the treatment response of BC patients was analyzed.

Results: We constructed a signature composed of nine ferroptosis-related lncRNAs (AL031775.1, AL162586.1, AC034236.2, LINC01004, OCIAD1-AS1, AL136084.3, AP003352.1, Z84484.1, AC022150.2). Compared with the low-risk group, the high-risk group had a worse prognosis. The ferroptosis-related lncRNA signature could independently predict the prognosis of patients with BC. Compared with clinicopathological variables, the ferroptosis-related lncRNA signature has a higher diagnostic efficiency, and the area under the receiver operating characteristic curve was 0.707. When patients were stratified according to different clinicopathological variables, the OS of patients in the high-risk group was shorter than that of those in the low-risk group. GSEA showed that tumor- and immune-related pathways were mainly enriched in the high-risk group. ssGSEA showed that the predictive signature was significantly related to the immune status of BC patients. High-risk patients were more sensitive to anti-PD-1/L1 immunotherapy and the conventional chemotherapy drugs sunitinib, paclitaxel, cisplatin, and docetaxel.

Conclusion: The predictive signature can independently predict the prognosis of BC patients, provides a basis for the mechanism of ferroptosis-related lncRNAs in BC and provides clinical treatment guidance for patients with BC.

Development and validation of a PD-L1/PD-1/CD8 axis-based classifier to predict cancer survival of upper tract urothelial carcinoma after radical nephroureterectomy

The expression status of programmed cell death-ligand 1/programmed cell death 1 (PD-L1/PD-1) and the infiltration of CD8⁺ T cells in tumor tissues are considered to be related to immunotherapy efficacy and patient prognosis. The purpose of this study is to clarify the prognostic value of the PD-L1/PD-1/CD8 axis, and to develop and validate a comprehensive scoring system based on multiple immune variables to predict cancer survival of upper tract urothelial carcinoma (UTUC) after radical nephroureterectomy (RNU). The immunohistochemical method was used to detect the expression of PD-L1, PD-1, and CD8 in cancer tissues of UTUC patients after RNU. Then, an immunoscore was constructed using the least absolute shrinkage and selection operator (LASSO) Cox regression model in the training cohort (n = 120), and it was verified in the validation cohort (n = 54). We found that infiltration of PD-L1⁺ immune cells (ICs), stromal PD-1⁺ tumor-infiltrating lymphocytes (TILs), and intratumoral CD8⁺ TILs was associated with poor overall survival (OS). The immunoscore based on the three immune variables further divided the patients into low- and high-risk groups, and there was a significant difference in the survival rate. A nomogram was constructed by combining tumor-node-metastasis (TNM) stage and immunoscore, and the area under the curve of the receiver-operating characteristic (ROC) (0.78) for predicting 5-year mortality was better than that of the TNM stage (0.70) and immunoscore (0.76). Our results show that the PD-L1/PD-1/CD8 axis-based classifier have potential clinical application to predict cancer survival of UTUC patients after RNU.

Development and validation of a molecular prognostic index of bladder cancer based on immunogenomic landscape analysis

Background

Bladder cancer (BCa) is one of the important tumors that have been proven to be treatable with immunotherapy. This study aims to identify and validate a molecular prognostic index of BCa based on immunogenomic landscape analysis.

Methods

The cancer genome atlas (TCGA) database and immunology database and analysis portal (ImmPort) database were used to identified differentially expressed immune-related genes (IRGs). Prognostic IRGs were screened and protein-protein interaction (PPI) network was constructed. Multivariate Cox analysis was performed to develop a molecular prognostic index of BCa. Internal and external validation were then performed in TCGA cohort and GEO cohort, respectively. Besides, we also explore the relationship between this index and clinical characteristics, immune cell infiltration and tumor microenvironment.

Results

A total of 61 prognostic IRGs were identified and a molecular prognostic index was developed. The top four hub genes included MMP9, IGF1, CXCL12 and PGF. The difference in overall survival between high-risk group and low-risk group was statistically significant. The area under curve of the receiver operating characteristic (ROC) curve was 0.757, suggesting the potential for this index. Besides, Internal validation using TCGA cohort and external validation using GEO cohort indicated that this index was of great performance in predicting outcome. T cells CD8, T cells CD4 memory activated, T cells follicular helper, macrophages M0, macrophages M2 and neutrophils were significantly associated with prognosis of BCa patients. Female, high grade, stage III&IV, N1-3 and T3-4 were associated significantly with higher risk score compared with male, low grade, stage I&II, N0 and T1-2, respectively. High risk score had a positive association with higher stromal score and ESTIMATE score while high risk score had a negative association with tumor purity.

Conclusions

This study identified several prognostic immune-related genes of clinical value. Besides, we developed and validated a molecular index based on immunogenomic landscape analysis, which performed well in predicting prognosis of BCa. Further researches are needed to verify the effectiveness of this index and these vital genes.