Fibroblast growth factor receptor 3 alterations and response to immune checkpoint inhibition in metastatic urothelial cancer: a real world experience

A versatile and upgraded version of the LundTax classification algorithm applied to independent cohorts

Stratification of cancer into biologically and molecularly similar subgroups is a cornerstone of precision medicine. The Lund Taxonomy classification system for urothelial carcinoma (UC) aims to be applicable across the whole disease spectrum including both non-muscle invasive and invasive bladder cancer. For a classification system to be useful it is of critical importance that it can be applied robustly and reproducibly to new samples. However, transcriptomic methods used for subtype classification are affected by analytic platform, data preprocessing, cohort composition, and tumor purity. Furthermore, only limited data has been published evaluating the transferability of existing classification algorithms to external datasets. In the present investigation a single sample classifier was developed based on in-house microarray and RNA-sequencing data, intended to be broadly applicable across studies and platforms. The new classification algorithm was applied to 10 published external bladder cancer cohorts (n=2560 cases) to evaluate its ability to capture characteristic subtype-associated gene expression signatures and complementary data such as mutations, clinical outcomes, treatment response, or histological subtypes. The effect of sample purity on the classification results was evaluated by generating low-purity versions of samples in silico. The classifier was robustly applicable across different gene expression profiling platforms and preprocessing methods and was less sensitive to variations in sample purity.

A multi-task deep learning model based on comprehensive feature integration and self-attention mechanism for predicting response to anti-PD1/PD-L1

BACKGROUND

Immune checkpoint inhibitor (ICI) has been widely used in the treatment of advanced cancers, but predicting their efficacy remains challenging. Traditional biomarkers are numerous but exhibit heterogeneity within populations. For comprehensively utilizing the ICI-related biomarkers, we aim to conduct multidimensional feature selection and deep learning model construction.

METHODS

We used statistical and machine learning methods to map features of different levels to next-generation sequencing gene expression. We integrated genes from different sources into the feature input of a deep learning model, by means of self-attention mechanism.

RESULTS

We performed feature selection at the single-cell sequencing level, PD-L1 (CD274) analysis level, tumor mutational burden (TMB)/mismatch repair (MMR) level, and somatic copy number alteration (SCNA) level, obtaining 96 feature genes. Based on the pan-cancer dataset, we trained a multi-task deep learning model. We tested the model in the bladder urothelial carcinoma testing set 1 (AUC = 0.62, n = 298), bladder urothelial carcinoma testing set 2 (AUC = 0.66, n = 89), non-small cell lung cancer testing set (AUC = 0.85, n = 27), and skin cutaneous melanoma testing set (AUC = 0.71, n = 27).

CONCLUSION

Our study demonstrates the potential of the deep learning model for integrating multidimensional features in predicting the outcome of ICI. Our study also provides a potential methodological case for medical scenarios requiring the integration of multiple levels of features.

Identification of a circadian-based prognostic signature predicting cancer-associated fibroblasts infiltration and immunotherapy response in bladder cancer

Circadian rhythm disruption impacts the efficiency of both chemotherapy and immunotherapy, yet identifying the key factors involved remains challenging. Circadian rhythm disruption can trigger aberrant fibroblasts activation, suggesting potential roles of cancer-associated fibroblasts (CAFs) in addressing this issue. In this paper, TCGA-BLCA patients were classified into two subgroups based on the expression of core circadian rhythm genes (CCRGs). The CCRG-based subgroups showed distinct fibroblast-related signals, from which a risk model composed of five fibroblast-related genes was finally established with excellent survival prognostic value in both TCGA and GEO datasets. The risk model was positively associated with the infiltration of CAFs and can efficiently predict the immunotherapy response in BLCA. Besides, high-risk score was associated with reduced sensitivity to a majority of traditional chemotherapeutic drugs such as oxaliplatin and gemcitabine. Further, the correlation between CCRGs and the risk genes was analyzed. Among the five risk genes, FAM20C displayed the most extensive correlation with the CCRGs and exhibited the strongest connection with CAFs infiltration. Moreover, FAM20C independently served as a predictor for the response to immunotherapy in BLCA. In conclusion, this study has identified a circadian-based signature for evaluating CAFs infiltration and predicting the efficacy of chemotherapy and immunotherapy. The central gene FAM20C has emerged as a promising candidate which merits further investigations.

Establish TIIC signature score based the machine learning fusion in bladder cancer

BACKGROUND

Bladder cancer is a prevalent malignant tumor with high heterogeneity. Current treatments, such as transurethral resection of bladder tumor (TURBT) and intravesical Bacillus Calmette-Guérin (BCG) therapy, still have limitations, with approximately 30% of non-muscle-invasive bladder cancer (NMIBC) progressing to muscle-invasive bladder cancer (MIBC), and a substantial number of MIBC patients experiencing recurrence after surgery. Immunotherapy has shown potential benefits, but accurate prediction of its prognostic effects remains challenging.

METHODS

We analyzed bladder cancer RNA-seq data and clinical information from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, and used various machine learning algorithms to screen for feature RNAs related to tumor-infiltrating immune cells (TIICs) from single-cell data. Based on these RNAs, we established a TIIC signature score and evaluated its relationship with overall survival (OS) and immunotherapy response in bladder cancer patients.

RESULTS

The study identified 171 TIIC-RNAs and selected 11 TIIC-RNAs with prognostic value through survival analysis. The TIIC signature score established using a machine learning fusion method was significantly associated with OS and showed good predictive performance in different datasets. Additionally, the signature score was negatively correlated with immunotherapy response, with patients with low TIIC feature scores showing better survival outcomes after immunotherapy. Further biological functional analysis revealed a close association between the TIIC signature score and immune regulation processes, cellular metabolism, and genetic variations.

CONCLUSION

This study successfully constructed and validated an RNA signature scoring system based on tumor-infiltrating immune cell (TIIC) features, which can effectively predict OS and the effectiveness of immunotherapy in bladder cancer patients.

APOL6 predicts immunotherapy efficacy of bladder cancer by ferroptosis

BACKGROUND

Immune checkpoint inhibitors (ICIs) are rapidly evolving in the management of bladder cancer (BLCA). Nevertheless, effective biomarkers for predicting immunotherapeutic outcomes in BLCA are still insufficient. Ferroptosis, a form of immunogenic cell death, has been found to enhance patient sensitivity to ICIs. However, the underlying mechanisms of ferroptosis in promoting immunotherapy efficacy in BLCA remain obscure.

METHODS

Our analysis of The Cancer Genome Atlas (TCGA) mRNA data using single sample Gene Set Enrichment Analysis (ssGSEA) revealed two immunologically distinct subtypes. Based on these subtypes and various other public cohorts, we identified Apolipoprotein L6 (APOL6) as a biomarker predicting the efficacy of ICIs and explored its immunological correlation and predictive value for treatment. Furthermore, the role of APOL6 in promoting ferroptosis and its mechanism in regulating this process were experimentally validated.

RESULTS

The results indicate that APOL6 has significant immunological relevance and is indicative of immunologically hot tumors in BLCA and many other cancers. APOL6, interacting with acyl-coenzyme A synthetase long-chain family member 4 (ACSL4), mediates immunotherapy efficacy by ferroptosis. Additionally, APOL6 is regulated by signal transducer and activator of transcription 1 (STAT1).

CONCLUSIONS

To conclude, our findings indicate APOL6 has potential as a predictive biomarker for immunotherapy treatment success estimation and reveal the STAT1/APOL6/GPX4 axis as a critical regulatory mechanism in BLCA.

Integrated analysis reveals a novel 5-fluorouracil resistance-based prognostic signature with promising implications for predicting the efficacy of chemotherapy and immunotherapy in patients with colorectal cancer

BACKGROUND

5-Fluorouracil (5-FU) has been used as a standard first-line treatment for colorectal cancer (CRC) patients. Although 5-FU-based chemotherapy and immune checkpoint blockade (ICB) have achieved success in treating CRC, drug resistance and low response rates remain substantial limitations. Thus, it is necessary to construct a 5-FU resistance-related signature (5-FRSig) to predict patient prognosis and identify ideal patients for chemotherapy and immunotherapy.

METHODS

Using bulk and single-cell RNA sequencing data, we established and validated a novel 5-FRSig model using stepwise regression and multiple CRC cohorts and evaluated its associations with the prognosis, clinical features, immune status, immunotherapy, neoadjuvant therapy, and drug sensitivity of CRC patients through various bioinformatics algorithms. Unsupervised consensus clustering was performed to categorize the 5-FU resistance-related molecular subtypes of CRC. The expression levels of 5-FRSig, immune checkpoints, and immunoregulators were determined using quantitative real-time polymerase chain reaction (RT‒qPCR). Potential small-molecule agents were identified via Connectivity Map (CMap) and molecular docking.

RESULTS

The 5-FRSig and cluster were confirmed as independent prognostic factors in CRC, as patients in the low-risk group and Cluster 1 had a better prognosis. Notably, 5-FRSig was significantly associated with 5-FU sensitivity, chemotherapy response, immune cell infiltration, immunoreactivity phenotype, immunotherapy efficiency, and drug selection. We predicted 10 potential compounds that bind to the core targets of 5-FRSig with the highest affinity.

CONCLUSION

We developed a valid 5-FRSig to predict the prognosis, chemotherapeutic response, and immune status of CRC patients, thus optimizing the therapeutic benefits of chemotherapy combined with immunotherapy, which can facilitate the development of personalized treatments and novel molecular targeted therapies for patients with CRC.

Integrative and comprehensive pan-cancer analysis of ubiquitin specific peptidase 11 (USP11) as a prognostic and immunological biomarker

The significance of USP11 as a critical regulator in cancer has garnered substantial attention, primarily due to its catalytic activity as a deubiquitinating enzyme. Nonetheless, a thorough evaluation of USP11 across various cancer types in pan-cancer studies remains absent. Our analysis integrates data from a variety of sources, including five immunotherapy cohorts, thirty-three cohorts from The Cancer Genome Atlas (TCGA), and sixteen cohorts from the Gene Expression Omnibus (GEO), two of which involve single-cell transcriptomic data. Our findings indicate that aberrant USP11 expression is predictive of survival outcomes across various cancer types. The highest frequency of genomic alterations was observed in uterine corpus endometrial carcinoma (UCEC), with single-cell transcriptome analysis revealing significantly higher USP11 expression in plasmacytoid dendritic cells and mast cells. Notably, USP11 expression was associated with the infiltration levels of CD8+ T cells and natural killer (NK) activated cells. Additionally, in the skin cutaneous melanoma (SKCM) phs000452 cohort, patients with higher USP11 mRNA levels during immunotherapy experienced a significantly shorter median progression-free survival. USP11 emerges as a promising molecular biomarker with significant potential for predicting patient prognosis and immunoreactivity across various cancer types.

Impact of LAG-3/FGL1 pathway on immune evasive contexture and clinical outcomes in advanced urothelial carcinoma

BACKGROUND

Anti-programmed death-1 (PD-1)/anti-PD-ligand-1 (PD-L1) pathway inhibition is a standard regimen for advanced urothelial carcinoma (UC); however, its limited efficacy has been reflected in reported medium response rates. This study explored the role of next-generation coinhibitory receptors (IRs; lymphocyte activation gene 3 (LAG-3), T-cell immunoglobulin and mucin domain 3 (TIM-3), and T-cell immunoreceptor with Ig and ITIM domains (TIGIT)) and their ligands (LGs) in the response to PD-(L)1 blockade therapy and the oncological outcomes in patients with UC.

METHODS

We investigated metastatic UC cases who underwent PD-(L)1 therapy (cohort 1: n=348, cohort 2: n=89, and cohort 4: n=29) or advanced UC cases involving surgery (cohort 3: n=293 and cohort 5: n=90). We assessed the mRNA expression profiles and corresponding clinical information regarding IRs and LGs using cohorts 1, 2, and 3. Additionally, we elucidated the spatial features of these targeted markers using multiplex immunohistochemistry (mIHC) on formalin-fixed paraffin-embedded samples from cohorts 4 and 5. Survival, differential expressed gene, and Gene Set Enrichment analyses were performed. For mIHC, quantitative analyses were also performed to correlate immune and tumor cell densities with patient survival.

RESULTS

LAG-3 expression was strongly associated with the responsiveness of PD-(L)1 blockade compared with the expression of TIM-3 and TIGIT. In tumors with high LAG-3 levels, the increased expression of fibrinogen-like protein 1 (FGL1) had a significantly negative effect on the response to PD-(L)1 blockade and overall survival. Moreover, high FGL1 levels were associated with elevated CD4+ regulatory T-cell gene signatures and the upregulation of CD39 and neuropilin-1, with both indicating CD8+ T-cell exhaustion. mIHC analyses revealed that patients with stromal CD8+LAG-3+cellshigh-tumor FGL1+cellshigh exhibited a significant negative correlation with survival rates compared with those with stromal CD8+LAG-3+cellshigh-tumor FGL1+cellslow.

CONCLUSIONS

LAG-3 expression and high FGL1 coexpression are important predictive factors of adverse oncological outcomes related to the presence of immunosuppressive contextures. These findings are hypothesis-generating, warranting further mechanistic and clinical studies aimed to evaluate LAG-3/FGL1 blockade in UC.

Identification of tumor-specific T cell signature predicting cancer immunotherapy response in bladder cancer by multi-omics analysis and experimental verification

BACKGROUND

Numerous gene signatures predicting the prognosis of bladder cancer have been identified. However, a tumor-specific T cell signature related to immunotherapy response in bladder cancer remains under investigation.

METHODS

Single-cell RNA and TCR sequencing from the Gene expression omnibus (GEO) database were used to identify tumor-specific T cell-related genes in bladder cancer. Subsequently, we constructed a tumor-specific T cell signature (TstcSig) and validated its clinical relevance for predicting immunotherapy response in multiple immunotherapy cohorts. Further analyses explored the immune characteristics of TstcSig in bladder cancer patients from other cohorts in the TCGA and GEO databases. Western blot (WB), multicolor immunofluorescence (MIF), qRT-PCR and flow cytometry assays were performed to validate the results of bioinformatics analysis.

RESULTS

The established TstcSig, based on five tumor-specific T cell-related genes, could predict outcomes in a bladder cancer immunotherapy cohort. This was verified using two additional immunotherapy cohorts and showed better predictive performance compared to 109 published T cell signatures. TstcSig was strongly correlated with immune characteristics such as immune checkpoint gene expression, tumor mutation burden, and T cell infiltration, as validated by single-cell and spatial transcriptomics datasets. Notably, the positive correlation between TstcSig and T cell infiltration was confirmed in the TCGA cohort. Furthermore, pan-cancer analysis demonstrated the heterogeneity of the prognostic value of TstcSig. Tumor-specific T cells highly expressed CD27, IFNG, GZMB and CXCL13 and secreted more effector cytokines for tumor cell killing, as validated experimentally.

CONCLUSION

We developed a five-gene signature (including VAMP5, TIGIT, LCK, CD27 and CACYBP) based on tumor-specific T cell-related genes to predict the immunotherapy response in bladder cancer patients.

Role of TAP1 in the identification of immune-hot tumor microenvironment and its prognostic significance for immunotherapeutic efficacy in gastric carcinoma

Background

Gastric cancer (GC), a multifaceted gastrointestinal malignancy, is the fourth most prevalent contributor to cancer-related fatalities globally. As a member of the ATP-binding cassette (ABC) family, transporter associated with antigen processing 1 (TAP1) is crucial for conveying antigen peptides from the cytoplasm to the lumen of the endoplasmic reticulum and subsequently loading them onto the major histocompatibility complex (MHC) class I molecules. Recent studies have established the biological significance of TAP1 in upholding tumor survival and facilitating immune evasion by remodeling the tumor microenvironment (TME) and orchestrating immune infiltration. The study was conducted to elucidate the association of TAP1 expression with immunological characteristics, and sought to exploit the value of TAP1 as a biomarker reflecting the inflamed TME and immunotherapeutic response.

Methods

RNA-sequencing profiles and clinical annotations were obtained from The Cancer Genome Atlas-stomach adenocarcinoma (TCGA-STAD) cohort and Gene Expression Omnibus (GEO) portal. Preprocessing was conducting using the limma package. Weighted gene co-expression network analysis (WGCNA) was used to identify gene modules and TAP1 co-expressed genes (CEGs) based on correlation patterns. Consensus clustering and silhouette analysis determined the optimal number of TAP1-related groups. Gene expression profiles were integrated and classified using the pamr package. The Estimation of STromal and Immune cells in MAlignant Tumors using Expression data (ESTIMATE) algorithm and single-sample gene set enrichment analysis (ssGSEA) were used to evaluate immunological characteristics. Differential expression analysis was conducted using the limma package. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed. Single-cell RNA sequencing (scRNA-seq) datasets were analyzed using the Seurat toolkit to characterize cell types.

Results

Within this investigation, no significant differences in TAP1 expression were observed among patients exhibiting various clinicopathological features, indicating that TAP1 expression was not specific to molecular subtypes. Subsequent analysis revealed a positive correlation between TAP1 and diverse immunological traits, encompassing immunomodulators, tumor-infiltrating immune cells, as well as immune checkpoints across multiple datasets. Besides, within a GC immunotherapy cohort, individuals displaying high TAP1 expression demonstrated an increased likelihood of achieving complete remission (CR) post-treatment, suggesting heightened sensitivity to immunotherapy. In the clinical cohort, TAP1 overexpression in GC patients was positively correlated with CD8.

Conclusions

TAP1 appears linked to an inflamed TME and serves as a prospective biomarker for discerning immunological attributes and gauging immunotherapeutic responses in GC, particularly in identifying immune-reactive tumors.

Identification of a Macrophage marker gene signature to evaluate immune infiltration and therapeutic response in hepatocellular carcinoma

Background

Only a minority of hepatocellular carcinoma (HCC) patients can benefit from systemic regimens. Macrophages, which abundantly infiltrate in HCC, could mediate tumour microenvironment remodelling and immune escape, proving to be powerful weapons in combating HCC. Thus, a deeper understanding of macrophages is necessary for improving existing antitumour treatments.

Methods

With a series of bioinformatic approaches, we comprehensively explored the role of macrophage-related genes in human HCCs from multiple single-cell and bulk RNA sequencing datasets. Unsupervised clustering was performed to cluster the macrophage marker genes (MMGs). GSVA and functional enrichment analysis were used to elucidate the functional differences among the MMG-associated clusters. Subsequently, a component analysis algorithm was used to construct a Macrosig score, and the prognosis, biological characteristics, mutation profile, TME cell infiltration status and drug response of patients with different Macrosig scores were further analysed.

Results

We identified 13 MMGs in 574 HCC samples, based on which three MMG-associated clusters were defined. Overall survival time, clinicopathological features and immune infiltration scores differed among the different clusters. On this basis, 12 hub genes were identified among these clusters; subsequently, a scoring system was constructed to determine the Macrosig score. Importantly, patients with low-Macrosig scores, characterized by increased immune infiltration, increased mutation frequency and increased immune checkpoint expression, including CTLA-4, LAG3, PDCD1 and TIGIT, exhibited enhanced efficacy of immunotherapy when validated in an external database. Moreover, a low-Macrosig score indicates increased sensitivity to AZD.2281, A.443654, ABT.263, ABT.888, AG.014699 and ATRA, while a high Macrosig score indicates increased sensitivity to AZD6482, AKT inhibitor VIII, AS601245, AZ628, AZD.0530 and AZD6244.

Conclusions

A novel scoring system was constructed to guide more effective prognostic evaluation and tailoring therapeutic regimens for HCC patients.

IDMIR: identification of dysregulated miRNAs associated with disease based on a miRNA-miRNA interaction network constructed through gene expression data

Micro ribonucleic acids (miRNAs) play a pivotal role in governing the human transcriptome in various biological phenomena. Hence, the accumulation of miRNA expression dysregulation frequently assumes a noteworthy role in the initiation and progression of complex diseases. However, accurate identification of dysregulated miRNAs still faces challenges at the current stage. Several bioinformatics tools have recently emerged for forecasting the associations between miRNAs and diseases. Nonetheless, the existing reference tools mainly identify the miRNA-disease associations in a general state and fall short of pinpointing dysregulated miRNAs within a specific disease state. Additionally, no studies adequately consider miRNA-miRNA interactions (MMIs) when analyzing the miRNA-disease associations. Here, we introduced a systematic approach, called IDMIR, which enabled the identification of expression dysregulated miRNAs through an MMI network under the gene expression context, where the network's architecture was designed to implicitly connect miRNAs based on their shared biological functions within a particular disease context. The advantage of IDMIR is that it uses gene expression data for the identification of dysregulated miRNAs by analyzing variations in MMIs. We illustrated the excellent predictive power for dysregulated miRNAs of the IDMIR approach through data analysis on breast cancer and bladder urothelial cancer. IDMIR could surpass several existing miRNA-disease association prediction approaches through comparison. We believe the approach complements the deficiencies in predicting miRNA-disease association and may provide new insights and possibilities for diagnosing and treating diseases. The IDMIR approach is now available as a free R package on CRAN (https://CRAN.R-project.org/package=IDMIR).

Identifying cancer subtypes based on embryonic and hematopoietic stem cell signatures in pan-cancer

PURPOSE

Cancer cells with stem cell-like properties may contribute to cancer development and therapy resistance. The advancement of multi-omics technology has sparked interest in exploring cancer stemness from a multi-omics perspective. However, there is a limited number of studies that have attempted to subtype cancer by combining different types of stem cell signatures.

METHODS

In this study, 10,323 cancer specimens from 33 TCGA cancer types were clustered based on the enrichment scores of six stemness gene sets, representing two types of stem cell backgrounds: embryonic stem cells (ESCs) and hematopoietic stem cells (HSCs).

RESULTS

We identified four subtypes of pan-cancer, termed StC1, StC2, StC3 and StC4, which displayed distinct molecular and clinical features, including stemness, genome integrity, intratumor heterogeneity, methylation levels, tumor microenvironment, tumor progression, responses to chemotherapy and immunotherapy, and survival prognosis. Importantly, this subtyping method for pan-cancer is reproducible at the protein level.

CONCLUSION

Our findings indicate that the ESC signature is an adverse prognostic factor in cancer, while the HSC signature and ratio of HSC/ESC signatures are positive prognostic factors. The subtyping of cancer based on ESC and HSC signatures may provide insights into cancer biology and clinical implications of cancer.

FGFR-targeted therapeutics: clinical activity, mechanisms of resistance and new directions

Fibroblast growth factor (FGF) signalling via FGF receptors (FGFR1-4) orchestrates fetal development and contributes to tissue and whole-body homeostasis, but can also promote tumorigenesis. Various agents, including pan-FGFR inhibitors (erdafitinib and futibatinib), FGFR1/2/3 inhibitors (infigratinib and pemigatinib), as well as a range of more-specific agents, have been developed and several have entered clinical use. Erdafitinib is approved for patients with urothelial carcinoma harbouring FGFR2/3 alterations, and futibatinib and pemigatinib are approved for patients with cholangiocarcinoma harbouring FGFR2 fusions and/or rearrangements. Clinical benefit from these agents is in part limited by hyperphosphataemia owing to off-target inhibition of FGFR1 as well as the emergence of resistance mutations in FGFR genes, activation of bypass signalling pathways, concurrent TP53 alterations and possibly epithelial-mesenchymal transition-related isoform switching. The next generation of small-molecule inhibitors, such as lirafugratinib and LOXO-435, and the FGFR2-specific antibody bemarituzumab are expected to have a reduced risk of hyperphosphataemia and the ability to overcome certain resistance mutations. In this Review, we describe the development and current clinical role of FGFR inhibitors and provide perspective on future research directions including expansion of the therapeutic indications for use of FGFR inhibitors, combination of these agents with immune-checkpoint inhibitors and the application of novel technologies, such as artificial intelligence.

Modulator of TMB-associated immune infiltration (MOTIF) predicts immunotherapy response and guides combination therapy

Patients with high tumor mutational burden (TMB) levels do not consistently respond to immune checkpoint inhibitors (ICIs), possibly because a high TMB level does not necessarily result in adequate infiltration of CD8+ T cells. Using bulk ribonucleic acid sequencing (RNA-seq) data from 9311 tumor samples across 30 cancer types, we developed a novel tool called the modulator of TMB-associated immune infiltration (MOTIF), which comprises genes that can determine the extent of CD8+ T cell infiltration prompted by a certain TMB level. We confirmed that MOTIF can accurately reflect the integrity and defects of the cancer-immunity cycle. By analyzing 84 human single-cell RNA-seq datasets from 32 types of solid tumors, we revealed that MOTIF can provide insights into the diverse roles of various cell types in the modulation of CD8+ T cell infiltration. Using pretreatment RNA-seq data from 13 ICI-treated cohorts, we validated the use of MOTIF in predicting CD8+ T cell infiltration and ICI efficacy. Among the components of MOTIF, we identified EMC3 as a negative regulator of CD8+ T cell infiltration, which was validated via in vivo studies. Additionally, MOTIF provided guidance for the potential combinations of programmed death 1 blockade with certain immunostimulatory drugs to facilitate CD8+ T cell infiltration and improve ICI efficacy.

Synergistic role of activated CD4+ memory T cells and CXCL13 in augmenting cancer immunotherapy efficacy

The development of immune checkpoint inhibitors (ICIs) has significantly advanced cancer treatment. However, their efficacy is not consistent across all patients, underscoring the need for personalized approaches. In this study, we examined the relationship between activated CD4+ memory T cell expression and ICI responsiveness. A notable correlation was observed between increased activated CD4+ memory T cell expression and better patient survival in various cohorts. Additionally, the chemokine CXCL13 was identified as a potential prognostic biomarker, with higher expression levels associated with improved outcomes. Further analysis highlighted CXCL13's role in influencing the Tumor Microenvironment, emphasizing its relevance in tumor immunity. Using these findings, we developed a deep learning model by the Multi-Layer Aggregation Graph Neural Network method. This model exhibited promise in predicting ICI treatment efficacy, suggesting its potential application in clinical practice.

Unraveling the role of M1 macrophage and CXCL9 in predicting immune checkpoint inhibitor efficacy through multicohort analysis and single-cell RNA sequencing

The exact function of M1 macrophages and CXCL9 in forecasting the effectiveness of immune checkpoint inhibitors (ICIs) is still not thoroughly investigated. We investigated the potential of M1 macrophage and C-X-C Motif Chemokine Ligand 9 (CXCL9) as predictive markers for ICI efficacy, employing a comprehensive approach integrating multicohort analysis and single-cell RNA sequencing. A significant correlation between high M1 macrophage and improved overall survival (OS) and objective response rate (ORR) was found. M1 macrophage expression was most pronounced in the immune-inflamed phenotype, aligning with increased expression of immune checkpoints. Furthermore, CXCL9 was identified as a key marker gene that positively correlated with M1 macrophage and response to ICIs, while also exhibiting associations with immune-related pathways and immune cell infiltration. Additionally, through exploring RNA epigenetic modifications, we identified Apolipoprotein B MRNA Editing Enzyme Catalytic Subunit 3G (APOBEC3G) as linked to ICI response, with high expression correlating with improved OS and immune-related pathways. Moreover, a novel model based on M1 macrophage, CXCL9, and APOBEC3G-related genes was developed using multi-level attention graph neural network, which showed promising predictive ability for ORR. This study illuminates the pivotal contributions of M1 macrophages and CXCL9 in shaping an immune-active microenvironment, correlating with enhanced ICI efficacy. The combination of M1 macrophage, CXCL9, and APOBEC3G provides a novel model for predicting clinical outcomes of ICI therapy, facilitating personalized immunotherapy.

Quantified pathway mutations associate epithelial-mesenchymal transition and immune escape with poor prognosis and immunotherapy resistance of head and neck squamous cell carcinoma

BACKGROUND

Pathway mutations have been calculated to predict the poor prognosis and immunotherapy resistance in head and neck squamous cell carcinoma (HNSCC). To uncover the unique markers predicting prognosis and immune therapy response, the accurate quantification of pathway mutations are required to evaluate epithelial-mesenchymal transition (EMT) and immune escape. Yet, there is a lack of score to accurately quantify pathway mutations.

MATERIAL AND METHODS

Firstly, we proposed Individualized Weighted Hallmark Gene Set Mutation Burden (IWHMB, https://github.com/YuHongHuang-lab/IWHMB ) which integrated pathway structure information and eliminated the interference of global Tumor Mutation Burden to accurately quantify pathway mutations. Subsequently, to further elucidate the association of IWHMB with EMT and immune escape, support vector machine regression model was used to identify IWHMB-related transcriptomic features (IRG), while Adversarially Regularized Graph Autoencoder (ARVGA) was used to further resolve IRG network features. Finally, Random walk with restart algorithm was used to identify biomarkers for predicting ICI response.

RESULTS

We quantified the HNSCC pathway mutation signatures and identified pathway mutation subtypes using IWHMB. The IWHMB-related transcriptomic features (IRG) identified by support vector machine regression were divided into 5 communities by ARVGA, among which the Community 1 enriching malignant mesenchymal components promoted EMT dynamically and regulated immune patterns associated with ICI responses. Bridge Hub Gene (BHG) identified by random walk with restart was key to IWHMB in EMT and immune escape, thus, more predictive for ICI response than other 70 public signatures.

CONCLUSION

In summary, the novel pathway mutation scoring-IWHMB suggested that the elevated malignancy mediated by pathway mutations is a major cause of poor prognosis and immunotherapy failure in HNSCC, and is capable of identifying novel biomarkers to predict immunotherapy response.

POLQ identifies a better response subset to immunotherapy in muscle-invasive bladder cancer with high PD-L1

BACKGROUND

Though programmed cell death-ligand 1 (PD-L1) has been used in predicting the efficacy of immune checkpoint blockade (ICB), it is insufficient as a single biomarker. As a key effector of an intrinsically mutagenic microhomology-mediated end joining (MMEJ) pathway, DNA polymerase theta (POLQ) was overexpressed in various malignancies, whose expression might have an influence on genomic stability, therefore altering the sensitivity to chemotherapy and immunotherapy.

METHODS

A total of 1304 patients with muscle-invasive bladder cancer (MIBC) from six independent cohorts were included in this study. The Zhongshan Hospital (ZSHS) cohort (n = 134), The Cancer Genome Atlas (TCGA) cohort (n = 391), and the Neo-cohort (n = 148) were included for the investigation of chemotherapeutic response. The IMvigor210 cohort (n = 234) and the UNC-108 cohort (n = 89) were used for the assessment of immunotherapeutic response. In addition, the relationship between POLQ and the immune microenvironment was assessed, and GSE32894 (n = 308) was used only for the evaluation of the immune microenvironment.

RESULTS

We identified POLQhigh PD-L1high patients could benefit more from immunotherapy and platinum-based chemotherapy. Further analysis revealed that high POLQ expression was linked to chromosome instability and higher tumor mutational burden (TMB), which might elicit the production of neoantigens. Further, high POLQ expression was associated with an active tumor immune microenvironment with abundant infiltration of immune effector cells and molecules.

CONCLUSIONS

The study demonstrated that high POLQ expression was correlated with chromosome instability and antitumor immune microenvironment in MIBC, and the combination of POLQ and PD-L1 could be used as a superior companion biomarker for predicting the efficacy of immunotherapy.

Deciphering the tumor-suppressive role of PSMB9 in melanoma through multi-omics and single-cell transcriptome analyses

Skin cutaneous melanoma (SKCM) poses a significant challenge in skin cancers. Recent immunotherapy breakthroughs have revolutionized melanoma treamtment, yet tumor heterogeneity persists as an obstacle. Epigenetic modifications orchestrated by DNA methylation contributed to tumorigenesis, thus potentially unveiling melanoma prognosis. Here, we identified an interferon-gamma (IFN-g) sensitive subtype, which possesses favorable outcomes, robust infiltration CD8+T cells, and IFN-g score in bulk RNA-seq profile. Subsequently, we established an IFN-g sensitivity signature based on machine learning. We validated that PSMB9 is strongly correlated with immunotherapy response in both methylation and expression cohorts in this 10-probe signature. We assumed that PSMB9 acts as a putative melanoma suppressor, for its activation of CD8+T cell; capacity to modulate IFN-γ secretion; and dynamics altering IFN-g receptors in bulk tissue. We performed single-cell RNA-seq on immunotherapy patients' tissue to uncover the nuanced role of PSMB9 in activating CD8T + cells, enhancing IFN-g, and influencing malignant cells receptors and transcriptional factors. Overexpress PSMB9 in two SKCM cell lines to mimic the hypomethylated state to approve our conjecture. Strong cell proliferation and migration inhibition were detected on both cells, indicating that PSMB9 is present in tumor cells and that high expression is detrimental to tumor growth and migration. Overall, comprehensive integrated analysis shows that PSMB9 emerges as a vital prognostic marker, acting predictive potential regarding immunotherapy in melanoma. This evidence not only reveals the multifaceted impact of PSMB9 on both malignant and immune cells but also serves as a prospective target for undergoing immunotherapeutic strategies in the future.

High B7-H3 expression with low PD-L1 expression identifies armored-cold tumors in triple-negative breast cancer

Triple-negative breast cancer (TNBC) is generally regarded as the most aggressive subtype among breast cancers, but exhibits higher chemotherapeutic and immunotherapeutic responses due to its unique immunogenicity. Thus, appropriate discrimination of subtypes is critical for guiding therapeutic options in clinical practice. In this research, using multiple in-house and public cohorts, we investigated the expression features and immuno-correlations of B7-H3 in breast cancer and checked the anti-tumor effect of the B7-H3 monoclonal antibody in a mouse model. We also developed a novel classifier combining B7-H3 and PD-L1 expression in TNBC. B7-H3 was revealed to be related to immuno-cold features and accumulated collagen in TNBC. In addition, targeting B7-H3 using the monoclonal antibody significantly suppressed mouse TNBC growth, reversed the armored-cold phenotype, and also boosted anti-PD-1 immunotherapy. In addition, patients with B7-H3 high and PD-L1 low expression showed the lowest anti-tumor immune infiltration, the highest collagen level, and the lowest therapeutic responses to multiple therapies, which mostly belong to armored-cold tumors. Overall, this research provides a novel subtyping strategy based on the combination of B7-H3/PD-L1 expression, which leads to a novel approach for the management of TNBC.

FGFR inhibition augments anti-PD-1 efficacy in murine FGFR3-mutant bladder cancer by abrogating immunosuppression

The combination of targeted therapy with immune checkpoint inhibition (ICI) is an area of intense interest. We studied the interaction of fibroblast growth factor receptor (FGFR) inhibition with ICI in urothelial carcinoma (UC) of the bladder, in which FGFR3 is altered in 50% of cases. Using an FGFR3-driven, Trp53-mutant genetically engineered murine model (UPFL), we demonstrate that UPFL tumors recapitulate the histology and molecular subtype of their FGFR3-altered human counterparts. Additionally, UPFL1 allografts exhibit hyperprogression to ICI associated with an expansion of T regulatory cells (Tregs). Erdafitinib blocked Treg proliferation in vitro, while in vivo ICI-induced Treg expansion was fully abrogated by FGFR inhibition. Combined erdafitinib and ICI resulted in high therapeutic efficacy. In aggregate, our work establishes that, in mice, co-alteration of FGFR3 and Trp53 results in high-grade, non-muscle-invasive UC and presents a previously underappreciated role for FGFR inhibition in blocking ICI-induced Treg expansion.

ZNF689 deficiency promotes intratumor heterogeneity and immunotherapy resistance in triple-negative breast cancer

Triple-negative breast cancer (TNBC) is an aggressive disease characterized by remarkable intratumor heterogeneity (ITH), which poses therapeutic challenges. However, the clinical relevance and key determinant of ITH in TNBC are poorly understood. Here, we comprehensively characterized ITH levels using multi-omics data across our center's cohort (n = 260), The Cancer Genome Atlas cohort (n = 134), and four immunotherapy-treated cohorts (n = 109). Our results revealed that high ITH was associated with poor patient survival and immunotherapy resistance. Importantly, we identified zinc finger protein 689 (ZNF689) deficiency as a crucial determinant of ITH formation. Mechanistically, the ZNF689-TRIM28 complex was found to directly bind to the promoter of long interspersed element-1 (LINE-1), inducing H3K9me3-mediated transcriptional silencing. ZNF689 deficiency reactivated LINE-1 retrotransposition to exacerbate genomic instability, which fostered ITH. Single-cell RNA sequencing, spatially resolved transcriptomics and flow cytometry analysis confirmed that ZNF689 deficiency-induced ITH inhibited antigen presentation and T-cell activation, conferring immunotherapy resistance. Pharmacological inhibition of LINE-1 significantly reduced ITH, enhanced antitumor immunity, and eventually sensitized ZNF689-deficient tumors to immunotherapy in vivo. Consistently, ZNF689 expression positively correlated with favorable prognosis and immunotherapy response in clinical samples. Altogether, our study uncovers a previously unrecognized mechanism underlying ZNF689 deficiency-induced ITH and suggests LINE-1 inhibition combined with immunotherapy as a novel treatment strategy for TNBC.

Progress in systemic therapy for advanced-stage urothelial carcinoma

Despite recent advances, advanced-stage urothelial carcinoma (aUC) remains incurable, with 5-year survival rates of approximately 10%. Platinum-based chemotherapy has a major role as first-line therapy for most patients with aUC. The approval of the anti-PD-L1 antibody avelumab as maintenance therapy for patients without initial disease progression on platinum-based chemotherapy is an important development that has improved the survival outcomes of patients with this disease. Otherwise, the use of first-line immune-checkpoint inhibitors (ICIs) targeting PD-1 or PD-L1 has been restricted to patients who are ineligible for platinum-containing chemotherapy regimens. Other important developments include the FDA-accelerated approval of first-line enfortumab vedotin plus pembrolizumab for patients ineligible to receive cisplatin and the availability of FGFR inhibitors, enfortumab vedotin and sacituzumab govitecan for subsequent lines of therapy. Several research questions remain unaddressed including the lack of adequate biomarkers, how to assign priority to the different treatment options for individual patients and which agents can be effective as monotherapies. The future is promising with the emergence of modalities such as antibody-drug conjugate-like drugs, next-generation ICIs, bispecific antibodies and cellular therapies. In this Review, we summarize the evolution of systemic therapy for patients with aUC and provide insights into the unmet needs.

Machine-learning based integrating bulk and single-cell RNA sequencing reveals the SLC38A5-CCL5 signaling as a promising target for clear cell renal cell carcinoma treatment

Cancer-associated fibroblasts paly critical roles in regulating cancer cell biological properties by intricate and dynamic communication networks. But the mechanism of CAFs in clear cell renal cell carcinoma (ccRCC) is not clear. In our study, we identified CAFs and malignant cells from the integrated scRNA-seq datasets and establish a CAF-derived communication signature based on the highly activated regulons ETS1 and MEF2C. We stratified the ccRCC TME into two molecular subtypes with distinct prognoses, immune cell infiltration landscapes, and immune-related characteristics. The model derived from signature demonstrated high accuracy and robustness in predicting prognosis and ICIs therapy responses. Subsequently, the SLC38A5 of the model was found upregulated in CAFs and was related to decreased survival probabilities, inflamed TME, and upregulated inhibitory checkpoints. SLC38A5 inhibition could attenuate the pro-tumoral abilities of CAFs in terms of proliferation, migration, and invasion. Mechanically, CCL5 could restore these properties induced by SLC38A5 inhibition. In conclusion, our communication signature and its derived model enabled a more precise selection of ccRCC patients who were potential beneficiaries of ICIs. Besides, the SLC38A5-CCL5 axis may serve as a promising target for ccRCC treatment.

The Impact of FGFR3 Alterations on the Tumor Microenvironment and the Efficacy of Immune Checkpoint Inhibitors in Bladder Cancer

BACKGROUND

Currently, only limited knowledge is available regarding the phenotypic association between fibroblast growth factor receptor 3 (FGFR3) alterations and the tumor microenvironment (TME) in bladder cancer (BLCA).

METHODS

A multi-omics analysis on 389 BLCA and 35 adjacent normal tissues from a cohort of OMPU-NCC Consortium Japan was retrospectively performed by integrating the whole-exome and RNA-sequence dataset and clinicopathological record. A median follow-up duration of all BLCA cohort was 31 months.

RESULTS

FGFR3 alterations (aFGFR3), including recurrent mutations and fusions, accounted for 44% of non-muscle invasive bladder cancer (NMIBC) and 15% of muscle-invasive bladder cancer (MIBC). Within MIBC, the consensus subtypes LumP was significantly more prevalent in aFGFR3, whereas the Ba/Sq subtype exhibited similarity between intact FGFR3 (iFGFR3) and aFGFR3 cases. We revealed that basal markers were significantly increased in MIBC/aFGFR3 compared to MIBC/iFGFR3. Transcriptome analysis highlighted TIM3 as the most upregulated immune-related gene in iFGFR3, with differential immune cell compositions observed between iFGFR3 and aFGFR3. Using EcoTyper, TME heterogeneity was discerned even within aFGFR cases, suggesting potential variations in the response to checkpoint inhibitors (CPIs). Among 72 patients treated with CPIs, the objective response rate (ORR) was comparable between iFGFR3 and aFGFR3 (20% vs 31%; p = 0.467). Strikingly, a significantly higher ORR was noted in LumP/aFGFR3 compared to LumP/iFGFR3 (50% vs 5%; p = 0.022). This trend was validated using data from the IMvigor210 trial. Additionally, several immune-related genes, including IDO1, CCL24, IL1RL1, LGALS4, and NCAM (CD56) were upregulated in LumP/iFGFR3 compared to LumP/aFGFR3 cases.

CONCLUSIONS

Differential pathways influenced by aFGFR3 were observed between NMIBC and MIBC, highlighting the upregulation of both luminal and basal markers in MIBC/aFGFR3. Heterogeneous TME was identified within MIBC/aFGFR3, leading to differential outcomes for CPIs. Specifically, a favorable ORR in LumP/aFGFR3 and a poor ORR in LumP/iFGFR3 were observed. We propose TIM3 as a potential target for iFGFR3 (ORR: 20%) and several immune checkpoint genes, including IDO1 and CCL24, for LumP/iFGFR3 (ORR: 5%), indicating promising avenues for precision immunotherapy for BLCA.

Clinical and Genomic Landscape of FGFR3-Altered Urothelial Carcinoma and Treatment Outcomes with Erdafitinib: A Real-World Experience

PURPOSE

Erdafitinib is the only FDA-approved targeted therapy for FGFR2/3-altered metastatic urothelial cancer. We characterized the genetic landscape of FGFR-altered urothelial carcinoma and real-world clinical outcomes with erdafitinib, including on-treatment genomic evolution.

EXPERIMENTAL DESIGN

Prospectively collected clinical data were integrated with institutional genomic data to define the landscape of FGFR2/3-altered urothelial carcinoma. To identify mechanisms of erdafitinib resistance, a subset of patients underwent prospective cell-free (cf) DNA assessment.

RESULTS

FGFR3 alterations predictive of erdafitinib sensitivity were identified in 39% (199/504) of patients with non-muscle invasive, 14% (75/526) with muscle-invasive, 43% (81/187) with localized upper tract, and 26% (59/228) with metastatic specimens. One patient had a potentially sensitizing FGFR2 fusion. Among 27 FGFR3-altered cases with a primary tumor and metachronous metastasis, 7 paired specimens (26%) displayed discordant FGFR3 status. Erdafitinib achieved a response rate of 40% but median progression-free and overall survival of only 2.8 and 6.6 months, respectively (n = 32). Dose reductions (38%, 12/32) and interruptions (50%, 16/32) were common. Putative resistance mutations detected in cfDNA involved TP53 (n = 5), AKT1 (n = 1), and second-site FGFR3 mutations (n = 2).

CONCLUSIONS

FGFR3 mutations are common in urothelial carcinoma, whereas FGFR2 alterations are rare. Discordance of FGFR3 mutational status between primary and metastatic tumors occurs frequently and raises concern over sequencing archival primary tumors to guide patient selection for erdafitinib therapy. Erdafitinib responses were typically brief and dosing was limited by toxicity. FGFR3, AKT1, and TP53 mutations detected in cfDNA represent putative mechanisms of acquired erdafitinib resistance.

Construction of a novel prognostic model in skin cutaneous melanoma based on chemokines-related gene signature

Skin cutaneous melanoma, SKCM, is one of the most aggressive treatment-resistant tumours. Despite the fact that the BRAF oncogene and immunological checkpoints such as PD-1/PD-L1 and CTLA-4 have enhanced the therapeutic efficacy of SKCM, the subsequent resistance mechanisms and remedies have raised concerns. Chemokines have a significant role in the immunological milieu of tumor, which may increase the efficacy of checkpoint blockade and serve as a possible therapeutic intervention route. However, there is still no chemokine-based typing and risk model to provide a prognosis and therapeutic efficacy assessment for SKCM patients. In this study, we verified the distinct differences of prognostic stratification as well as immune characteristics between two chemokine-related clusters in SKCM patients. Two clusters of DEGs were discovered to be primarily enriched in B and T cell receptor signaling pathways as well as TNF signaling via NF-kappa-B. Based on 14 prognosis-related DEGs from aforementioned two clusters (CCL8, GBP2, GBP4, SRNG, HLA-DMB, RARRES3, HLA-DQA1, PARP12, APOL3, IRF1, HLA-DRA, UBE2L6, IL2RA and CD38), a chemokine-related 14-gene prognostic model was established. At the same time, researchers explored differences between the low-risk and high-risk groups in clinical traits, the proportion of infiltration of 22 different types of immune cells, and how well medications worked. The risk score model's immunotherapy and prognostic predictions were also confirmed in testing groups. Based on the finding, we can claim that there is a clear link between chemokines and TME in SKCM. The risk score may perform as a trustworthy prediction model, giving therapeutic benefits for both chemotherapy and immunotherapy, as well as being beneficial for clinical decision making in SKCM patients.

GBP2 is a prognostic biomarker and associated with immunotherapeutic responses in gastric cancer

BACKGROUND

The interferon-induced protein known as guanylate-binding protein 2 (GBP2) has been linked to multiple different cancer types as an oncogenic gene. Although the role of GBP2 in cancer has been preliminarily explored, it is unclear how this protein interacts with tumor immunity in gastric cancer.

METHODS

The expression, prognostic value, immune-correlations of GBP2 in gastric cancer was explored in multiple public and in-house cohorts. In addition, the pan-cancer analysis was performed to investigate the immunological role of GBP2 based on The Cancer Genome Atlas (TCGA) dataset, and the predictive value of GBP2 for immunotherapy was also examined in multiple public cohorts.

RESULTS

GBP2 was highly expressed in tumor tissues and associated with poor prognosis in gastric cancer. In addition, GBP2 was associated with the immune-hot phenotype. To be more specific, GBP2 was positively related to immuno-modulators, tumor-infiltrating immune cells (TIICs), immunotherapy biomarkers, and even well immunotherapeutic response. In addition to gastric cancer, GBP2 was expected to be an indicator of high immunogenicity in most cancer types. Importantly, GBP2 could predict the immunotherapeutic responses in at least four different cancer types, including melanoma, urothelial carcinoma, non-small cell lung cancer, and breast cancer.

CONCLUSIONS

To sum up, GBP2 expression is a promising pan-cancer biomarker for estimating the immunological characteristics of tumors and may be utilized to detect immuno-hot tumors in gastric cancer.

Integrating angiogenesis signature and tumor mutation burden for improved patient stratification in immune checkpoint blockade therapy for muscle-invasive bladder cancer

BACKGROUND

Muscle-invasive bladder cancer (MIBC) patients have benefitted greatly from immune checkpoint blockade (ICB) therapy. However, there is a pressing need to identify factors underlying the heterogeneity of clinical responses to ICB.

METHODS

We conducted a study on 848 MIBC patients from 4 independent cohorts to investigate the key biological characteristics affecting ICB responses. The IMvigor210 cohort (n = 234) was used to identify the key factor, followed by exploration of the correlation between tumor angiogenesis and immune suppression in the IMvigor210, TCGA (n = 391), and UNC-108 (n = 89) cohorts. The ZSHS cohort (n = 134) was used for validation. Additionally, we integrated angiogenesis signature with tumor mutation burden (TMB) to decipher the heterogeneity of clinical outcomes to ICB in MIBC patients.

RESULTS

Our analysis revealed that nonresponders to PD-L1 blockade were enriched with angiogenesis signature. Furthermore, we observed a correlation between angiogenesis signature and decreased neoantigen load, downregulated T-cell antigen recognition, and noninflamed immunophenotype. We identified a subgroup of patients resistant to ICB, characterized by high angiogenesis signature and low tumor mutation burden (TMB), and found the activation of TGF-β signaling and downregulation of T-cell cytolytic signatures in this subgroup.

CONCLUSIONS

The study concluded that angiogenesis signature is closely associated with an immunosuppressive microenvironment, leading to resistance to ICB therapy in MIBC patients. The study further suggested that the combination of angiogenesis signature and TMB can serve as an integrated biomarker for better stratification of patients' clinical outcomes to ICB therapy.

Artificial Intelligence in Digital Pathology for Bladder Cancer: Hype or Hope? A Systematic Review

Bladder cancer (BC) diagnosis and prediction of prognosis are hindered by subjective pathological evaluation, which may cause misdiagnosis and under-/over-treatment. Computational pathology (CPATH) can identify clinical outcome predictors, offering an objective approach to improve prognosis. However, a systematic review of CPATH in BC literature is lacking. Therefore, we present a comprehensive overview of studies that used CPATH in BC, analyzing 33 out of 2285 identified studies. Most studies analyzed regions of interest to distinguish normal versus tumor tissue and identify tumor grade/stage and tissue types (e.g., urothelium, stroma, and muscle). The cell's nuclear area, shape irregularity, and roundness were the most promising markers to predict recurrence and survival based on selected regions of interest, with >80% accuracy. CPATH identified molecular subtypes by detecting features, e.g., papillary structures, hyperchromatic, and pleomorphic nuclei. Combining clinicopathological and image-derived features improved recurrence and survival prediction. However, due to the lack of outcome interpretability and independent test datasets, robustness and clinical applicability could not be ensured. The current literature demonstrates that CPATH holds the potential to improve BC diagnosis and prediction of prognosis. However, more robust, interpretable, accurate models and larger datasets-representative of clinical scenarios-are needed to address artificial intelligence's reliability, robustness, and black box challenge.

Fibroblast growth factor receptor 3 mutation attenuates response to immune checkpoint blockade in metastatic urothelial carcinoma by driving immunosuppressive microenvironment

BACKGROUND

Immune checkpoint blockade (ICB) therapy holds promise in metastatic urothelial carcinoma (UC). Fibroblast growth factor receptor 3 (FGFR3) mutation drives T-cell-depleted microenvironment in UC, which led to the hypothesis that FGFR3 mutation might attenuate response to ICB in patients with metastatic UC. The study aims to compare prognosis and response between patients with FGFR3-mutated and FGFR3-wildtype metastatic UC after ICB therapy, and decode the potential molecular mechanisms.

METHODS

Based on the single-arm, multicenter, phase 2 trial, IMvigor210, we conducted a propensity score matched (PSM) analysis. After a 1:1 ratio PSM method, 39 patients with FGFR3-mutated and 39 FGFR3-wildtype metastatic UC treated with atezolizumab were enrolled. A meta-analysis through systematical database retrieval was conducted for validation. In addition, we performed single-cell RNA sequencing on three FGFR3-mutated and three FGFR3-wildtype UC tumors and analyzed 58,069 single cells.

RESULTS

The PSM analysis indicated FGFR3-mutated patients had worse overall survival (OS) in comparison to FGFR3-wildtype patients (HR=2.11, 95% CI=(1.16 to 3.85), p=0.015) receiving atezolizumab. The median OS was 9.2 months (FGFR3-mutated) versus 21.0 months (FGFR3-wildtype). FGFR3-mutated patients had lower disease control rate than FGFR3-wildtype patients (41.0% vs 66.7%, p=0.023). The meta-analysis involving 938 patients with metastatic UC confirmed FGFR3 mutation was associated with worse OS after ICB (HR=1.28, 95% CI=(1.04 to 1.59), p=0.02). Single-cell RNA transcriptome analysis identified FGFR3-mutated UC carried a stronger immunosuppressive microenvironment compared with FGFR3-wildtype UC. FGFR3-mutated UC exhibited less immune infiltration, and lower T-cell cytotoxicity. Higher TREM2+ macrophage abundance in FGFR3-mutated UC can undermine and suppress the T cells, potentially contributing to the formation of an immunosuppressive microenvironment. Lower inflammatory-cancer-associated fibroblasts in FGFR3-mutated UC recruited less chemokines in antitumor immunity but expressed growth factors to promote FGFR3-mutated malignant cell development. FGFR3-mutated UC carried abundance of malignant cells characterized by high hypoxia/metabolism and low interferon response phenotype.

CONCLUSIONS

FGFR3 mutation can attenuate prognosis and response to ICB in patients with metastatic UC. FGFR3-mutated UC carries a stronger immunosuppressive microenvironment in comparison with FGFR3-wildtype UC. Inhibition of FGFR3 might activate the immune microenvironment, and the combination of FGFR inhibitor targeted therapy and ICB might be a promising therapeutic regimen in metastatic UC, providing important implications for UC clinical management.

A robust gene prognostic index composed of GZMB, IRF1, and TP63 can stratify the risk of two metastatic urothelial carcinoma cohorts based on immune checkpoint blockade therapy

BACKGROUND

Immune checkpoint blockade (ICB) therapy has become a first-line treatment option for metastatic urothelial carcinoma (mUC) patients who do not meet the criteria of cisplatin. Still, only a few people can benefit from it, so useful predictive markers are needed.

METHODS

Download the ICB-based mUC and chemotherapy-based bladder cancer cohorts, and extract the expression data of pyroptosis-related genes (PRG). The LASSO algorithm was used to construct the PRG prognostic index (PRGPI) in the mUC cohort, and we verified the prognostic ability of PRGPI in two mUC and two bladder cancer cohorts.

RESULTS

Most of the PRG in the mUC cohort were immune-activated genes, and a few were immunosuppressive genes. The PRGPI composed of GZMB, IRF1, and TP63 can stratify the risk of mUC. In IMvigor210 and GSE176307 cohorts, the P-values of Kaplan Meier analysis was < 0.01 and 0.002, respectively. PRGPI could also predict ICB response, and the chi-square test of the two cohorts had P-values of 0.002 and 0.046, respectively. In addition, PRGPI can also predict the prognosis of two bladder cancer cohorts without ICB therapy. The PRGPI and the expression of PDCD1/CD274 had a high degree of synergistic correlation. The Low PRGPI group showed prominent characteristics of immune infiltration and was enriched in the immune signal activation pathway.

CONCLUSION

The PRGPI we constructed can effectively predict the treatment response and overall survival rate of mUC patients treated with ICB. The PRGPI can help mUC patients achieve individualized and accurate treatment in the future.

Predictive biomarkers of immunotherapy response with pharmacological applications in solid tumors

Immune-checkpoint inhibitors show promising effects in the treatment of multiple tumor types. Biomarkers are biological indicators used to select patients for a systemic anticancer treatment, but there are only a few clinically useful biomarkers such as PD-L1 expression and tumor mutational burden, which can be used to predict immunotherapy response. In this study, we established a database consisting of both gene expression and clinical data to identify biomarkers of response to anti-PD-1, anti-PD-L1, and anti-CTLA-4 immunotherapies. A GEO screening was executed to identify datasets with simultaneously available clinical response and transcriptomic data regardless of cancer type. The screening was restricted to the studies involving administration of anti-PD-1 (nivolumab, pembrolizumab), anti-PD-L1 (atezolizumab, durvalumab) or anti-CTLA-4 (ipilimumab) agents. Receiver operating characteristic (ROC) analysis and Mann-Whitney test were executed across all genes to identify features related to therapy response. The database consisted of 1434 tumor tissue samples from 19 datasets with esophageal, gastric, head and neck, lung, and urothelial cancers, plus melanoma. The strongest druggable gene candidates linked to anti-PD-1 resistance were SPIN1 (AUC = 0.682, P = 9.1E-12), SRC (AUC = 0.667, P = 5.9E-10), SETD7 (AUC = 0.663, P = 1.0E-09), FGFR3 (AUC = 0.657, P = 3.7E-09), YAP1 (AUC = 0.655, P = 6.0E-09), TEAD3 (AUC = 0.649, P = 4.1E-08) and BCL2 (AUC = 0.634, P = 9.7E-08). In the anti-CTLA-4 treatment cohort, BLCAP (AUC = 0.735, P = 2.1E-06) was the most promising gene candidate. No therapeutically relevant target was found to be predictive in the anti-PD-L1 cohort. In the anti-PD-1 group, we were able to confirm the significant correlation with survival for the mismatch-repair genes MLH1 and MSH6. A web platform for further analysis and validation of new biomarker candidates was set up and available at https://www.rocplot.com/immune . In summary, a database and a web platform were established to investigate biomarkers of immunotherapy response in a large cohort of solid tumor samples. Our results could help to identify new patient cohorts eligible for immunotherapy.

A novel genes-based signature with prognostic value and predictive ability to select patients responsive to Atezolizumab treatment in bladder cancer: an analysis on data from real-world studies

Background

There is a lack of molecular markers that effectively predict response to treatment with immune checkpoint inhibitors in patients with uroepithelial bladder carcinoma. The purpose of this study was to explore molecular markers that effectively predict the efficacy of Atezolizumab in the treatment of uroepithelial bladder carcinoma based on real-world clinical trial data.

Methods

Gene expression and clinical information of two groups of patients in two datasets, IMvigor210 and GSE176307, who were treated effectively and ineffectively with the programmed cell death 1 ligand 1 (PD-L1) inhibitor Atezolizumab, were obtained. Bioinformatic methods were used to screen out differentially expressed genes and detect the correlation between their expression and immune-related indicators. Subsequently, we assessed the ability of differentially expressed genes to predict the therapeutic response and prognosis of bladder cancer patients following Atezolizumab treatment.

Results

A total of 2 differentially expressed genes, CXC motif chemokine ligand 9 (CXCL9) and CXC motif chemokine ligand 10 (CXCL10) [all P<0.05, log|fold change (FC)| >1], which were co-upregulated, were screened as study targets. In The Cancer Genome Atlas (TCGA) database, CXCL9/10 mRNA expression was positively correlated with both PD-L1 and tumor mutation burden (TMB) (all P<0.05). In the IMvigor210 dataset, the area under the receiver operating characteristic (ROC) curve for CXCL9, CXCL10 and PD-L1 mRNA expression to predict response to treatment with Atezolizumab were 0.645, 0.636 and 0.566, respectively; And CXCL9/10 mRNA was effective in predicting overall survival in patients receiving treatment (all P<0.05). In the GSE176307 dataset, the area under the ROC curve for CXCL9, CXCL10 and PD-L1 mRNA expression to predict response to treatment with Atezolizumab were 0.829, 0.829 and 0.765, respectively; And CXCL9/10 mRNA was not effective in predicting overall survival in patients receiving treatment (all P>0.05).

Conclusions

The mRNA expression levels of CXCL9/10 have the potential to serve as a molecular marker for predicting the therapeutic response and overall survival outcomes of bladder cancer patients treated with Atezolizumab.

A novel metabolic subtype with S100A7 high expression represents poor prognosis and immuno-suppressive tumor microenvironment in bladder cancer

BACKGROUND

Bladder cancer (BLCA) represents a highly heterogeneous disease characterized by distinct histological, molecular, and clinical features, whose tumorigenesis and progression require aberrant metabolic reprogramming of tumor cells. However, current studies have not expounded systematically and comprehensively on the metabolic heterogeneity of BLCA.

METHODS

The UCSC XENA portal was searched to obtain the expression profiles and clinical annotations of BLCA patients in the TCGA cohort. A total of 1,640 metabolic-related genes were downloaded from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Then, consensus clustering was performed to divide the BLCA patients into two metabolic subtypes according to the expression of metabolic-related genes. Kaplan-Meier analysis was used to measure the prognostic values of the metabolic subtypes. Subsequently, comparing the immune-related characteristics between the two metabolic subtypes to describe the immunological difference. Then, the Scissor algorithm was applied to link the metabolic phenotypes and single-cell transcriptome datasets to determine the biomarkers associated with metabolic subtypes and prognosis. Finally, the clinical cohort included 63 BLCA and 16 para-cancerous samples was used to validate the prognostic value and immunological correlation of the biomarker.

RESULTS

BLCA patients were classified into two heterogeneous metabolic-related subtypes (MRSs) with distinct features: MRS1, the subtype with no active metabolic characteristics but an immune infiltration microenvironment; and MRS2, the lipogenic subtype with upregulated lipid metabolism. These two subtypes had distinct prognoses, molecular subtypes distributions, and activations of therapy-related pathways. MRS1 BLCAs preferred to be immuno-suppressive and up-regulated immune checkpoints expression, suggesting the well-therapeutic response of MRS1 patients to immunotherapy. Based on the Scissor algorithm, we found that S100A7 both specifically up-regulated in the MRS1 phenotype and MRS1-tumor cells, and positively correlated with immunological characteristics. In addition, in the clinical cohort included 63 BLCA and 16 para-cancerous samples, S100A7 was obviously associated with poor prognosis and enhanced PD-L1 expression.

CONCLUSIONS

The metabolic subtype with S100A7 high expression recognizes the immuno-suppressive tumor microenvironment and predicts well therapeutic response of immunotherapy in BLCA. The study provides new insights into the prognostic and therapeutic value of metabolic heterogeneity in BLCA.

Identification of the relationship between single-cell N6-methyladenosine regulators and the infiltrating immune cells in esophageal carcinoma

Background

N6-methyladenosine (m⁶A) RNA methylation plays a crucial role in important genomic processes in a variety of malignancies. However, the characterization of m⁶A with infiltrating immune cells in the tumor microenvironment (TME) in esophageal squamous carcinoma (ESCC) remains unknown.

Methods

The single-cell transcriptome data from five ESCC patients in our hospital were analyzed, and TME clusters associated with prognosis and immune checkpoint genes were investigated. Cell isolation and qPCR were conducted to validate the gene characterization in different cells.

Results

According to distinct biological processes and marker genes, macrophages, T cells, and B cells clustered into three to four different subgroups. In addition, we demonstrated that m⁶A RNA methylation regulators were strongly related to the clinical and biological features of ESCC. Analysis of transcriptome data revealed that m⁶A-mediated TME cell subsets had high predictive value and showed a close relationship with immune checkpoint genes. The validation results from qPCR demonstrated the characteristics of essential genes. CellChat analysis revealed that RNA from TME cells m⁶A methylation-associated cell subtypes had substantial and diversified interactions with cancer cells. Further investigation revealed that MIF- (CD74+CXCR4) and MIF- (CD74⁺CD44) ligand-receptor pairings facilitated communication between m⁶A-associated subtypes of TME cells and cancer cells.

Conclusion

Overall, our study demonstrated for the first time the function of m⁶A methylation-mediated intercellular communication in the microenvironment of tumors in controlling tumor development and anti-tumor immune regulation in ESCC.

Aggrephagy-related patterns in tumor microenvironment, prognosis, and immunotherapy for acute myeloid leukemia: a comprehensive single-cell RNA sequencing analysis

Acute myeloid leukemia (AML) is a complex mixed entity composed of malignant tumor cells, immune cells and stromal cells, with intra-tumor and inter-tumor heterogeneity. Single-cell RNA sequencing enables a comprehensive study of the highly complex tumor microenvironment, which is conducive to exploring the evolutionary trajectory of tumor cells. Herein, we carried out comprehensive analyses of aggrephagy-related cell clusters based on single-cell sequencing for patients with acute myeloid leukemia. A total of 11 specific cell types (T, NK, CMP, Myeloid, GMP, MEP, Promono, Plasma, HSC, B, and Erythroid cells) using t-SNE dimension reduction analysis. Several aggrephagy-related genes were highly expressed in the 11 specific cell types. Using Monocle analysis and NMF clustering analysis, six aggrephagy-related CD8+ T clusters, six aggrephagy-related NK clusters, and six aggrephagy-related Mac clusters were identified. We also evaluated the ligand-receptor links and Cell-cell communication using CellChat package and CellChatDB database. Furthermore, the transcription factors (TFs) of aggrephagy-mediated cell clusters for AML were assessed through pySCENIC package. Prognostic analysis of the aggrephagy-related cell clusters based on R package revealed the differences in prognosis of aggrephagy-mediated cell clusters. Immunotherapy of the aggrephagy-related cell clusters was investigated using TIDE algorithm and public immunotherapy cohorts. Our study revealed the significance of aggrephagy-related patterns in tumor microenvironment, prognosis, and immunotherapy for AML.

Procoagulant genes may affect angiogenesis, epithelial-mesenchymal transition, survival prognosis and tumor immune microenvironment in patients with urothelial carcinoma

Factors related to coagulation regulation are closely related to angiogenesis, epithelial-mesenchymal transition, tumor proliferation and metastasis, and tumor immune microenvironment remodeling in tumors. To date, there are no quantitative indicators of coagulation associated with urothelial cancer. We classified urothelial cancer into high coagulation and low coagulation subtypes by screening for procoagulant-related molecular features and screened out relevant genes representing the coagulation state of urothelial carcinoma. Tumors with increased procoagulant gene expression were consistently associated with higher T-staging (p < 0.001), lymph node metastasis (p < 0.001), stage (p < 0.001), and grade (p = 0.046). Furthermore, high expression of procoagulant genes predicts a worse prognosis, a higher tumor proliferation rate and increased angiogenesis within the tumor. In addition, according to cibersort algorithm, the increased expression of procoagulant gene was negatively correlated with the degree of T-lymphocyte infiltration and positively correlated with the degree of M2 macrophage infiltration. Increased expression of procoagulant genes in data sets treated with immune checkpoints also predicted worse response and worse prognosis. At the same time, the expression of procoagulant genes in bladder cancer promoted the activation of coagulation, EMT, TGF-β and WNT pathways.

Upper Tract Urothelial Carcinoma: A Rare Malignancy with Distinct Immuno-Genomic Features in the Era of Precision-Based Therapies

Upper tract urothelial carcinoma (UTUC) is a rare malignancy, occurring in 5-10% of patients diagnosed with UC, and involves the renal pelvis, calyces, or ureters. UTUC can be sporadic or hereditary as a clinical manifestation of Lynch syndrome. Therapeutic management of these patients is challenging. Following risk stratification of localized disease, patients with low-grade UTUC may undergo kidney-sparing surgery or radical nephroureterectomy (RNU) and/or chemoablation with mitomycin-c instillation to reduce recurrence. In high-grade disease, RNU followed by adjuvant chemotherapy remains the standard of care. For decades, platinum-based chemotherapy has been the cornerstone of treatment for locally advanced and metastatic disease. The aim of the present review is to summarize recent advances in UTUC's therapeutic management through the lens of its genomic and immune landscape. Accumulating knowledge on the genetic and immune aspects of UTUC tumors has increased our understanding of their underlying biology, supporting a luminal papillary, T-cell depleted contexture and enrichment in fibroblast growth factor receptor (FGFR) expression. These advances have fueled successful clinical testing of several precision-based therapeutic approaches, including immune checkpoint inhibitors (ICIs), the antibody-drug conjugates (ADCs) enfortumab vedotin and sacituzumab govitecan, and agents targeting the FGFR axis such as erdafitinib and other kinase inhibitors, allowing their entry into the therapeutic armamentarium and improving the prognosis of these patients. Not all patients respond to these precision-based targeted therapies; thus, validating and expanding the toolkit of potential biomarkers of response or resistance, including molecular subtypes, FGFR pathway gene alterations, DNA repair gene defects, tumor mutational burden (TMB), circulating tumor DNA (ctDNA), nectin-4, TROP2, and programmed death ligand-1 (PD-L1), are key to maximizing the benefit to these particular subgroups of patients.

The cuproptosis-associated 11 gene signature as a predictor for outcomes and response to Bacillus Calmette-Guerin and immune checkpoint inhibitor therapies in bladder carcinoma

Bladder cancer (BC) or carcinoma (BLCA) is predominantly derived from urothelium and includes non-muscle invasive BC (NMIBC) and muscle invasive BC (MIBC). Bacillus Calmette-Guerin (BCG) has long been applied for NMIBC to effectively reduce disease recurrence or progression, whereas immune checkpoint inhibitors (ICIs) were recently introduced to treat advanced BLCA with good efficacy. For BCG and ICI applications, reliable biomarkers are required to stratify potential responders for better personalized interventions, and ideally, they can replace or reduce invasive examinations such as cystoscopy in monitoring treatment efficacy. Here we developed the cuproptosis-associated 11 gene signature (CuAGS-11) model to accurately predict survival and response to BCG and ICI regimens in BLCA patients. In both discovery and validation cohorts where BLCA patients were divided into high- and low-risk groups based on a median CuAGS-11 score as the cutoff, the high-risk group was associated with significantly shortened overall survival (OS) and progression-free survival (PFS) independently. The survival predictive accuracy was comparable between CuAGS-11 and stage, and their combination-based nomograms showed high consistence between predicted and observed OS/PFS. The analysis of 3 BLCA cohorts treated with BCG unveiled lower response rates and higher frequencies of recurrence or progression coupled with shorter survival in CuAGS-11 high-risk groups. In contrast, almost none of patients underwent progression in low-risk groups. In IMvigor210 cohort of 298 BLCA patients treated with ICI Atezolizumab, complete/partial remissions were 3-fold higher accompanied by significantly longer OS in the CuAGS-11 low- than high-risk groups (P = 7.018E-06). Very similar results were obtained from the validation cohort (P = 8.65E-05). Further analyses of Tumor Immune Dysfunction and Exclusion (TIDE) scores revealed that CuAGS-11 high-risk groups displayed robustly higher T cell exclusion scores in both discovery (P = 1.96E-05) and validation (P = 0.008) cohorts. Collectively, the CuAGS-11 score model is a useful predictor for OS/PFS and BCG/ICI efficacy in BLCA patients. For BCG-treated patients, reduced invasive examinations are suggested for monitoring the CuAGS-11 low-risk patients. The present findings thus provide a framework to improve BLCA patient stratification for personalized interventions and to reduce invasive monitoring inspections.

Identification of a single cell-based signature for predicting prognosis risk and immunotherapy response in patients with glioblastoma

This study constructed a novel gene pair signature based on bulk and single-cell sequencing samples in relative expression order within the samples. The subsequent analysis included glioma samples from Xiangya Hospital. Gene pair signatures possessed a solid ability to predict the prognosis of glioblastoma and pan-cancer. Samples having different malignant biological hallmarks were distinguished by the algorithm, with the high gene pair score group featuring classic copy number variations, oncogenic mutations, and extensive hypomethylation, mediating poor prognosis. The increased gene pair score group with a poorer prognosis demonstrated significant enrichment in tumor and immune-related signaling pathways while presenting immunological diversity. The remarkable infiltration of M2 macrophages in the high gene pair score group was validated by multiplex immunofluorescence, suggesting that combination therapies targeting adaptive and innate immunity may serve as a therapeutic option. Overall, a gene pair signature applicable to predict prognosis hopefully provides a reference to guide clinical practice.

Unleashing the potential of combining FGFR inhibitor and immune checkpoint blockade for FGF/FGFR signaling in tumor microenvironment

BACKGROUND

Fibroblast growth factors (FGFs) and their receptors (FGFRs) play a crucial role in cell fate and angiogenesis, with dysregulation of the signaling axis driving tumorigenesis. Therefore, many studies have targeted FGF/FGFR signaling for cancer therapy and several FGFR inhibitors have promising results in different tumors but treatment efficiency may still be improved. The clinical use of immune checkpoint blockade (ICB) has resulted in sustained remission for patients. MAIN: Although there is limited data linking FGFR inhibitors and immunotherapy, preclinical research suggest that FGF/FGFR signaling is involved in regulating the tumor microenvironment (TME) including immune cells, vasculogenesis, and epithelial-mesenchymal transition (EMT). This raises the possibility that ICB in combination with FGFR-tyrosine kinase inhibitors (FGFR-TKIs) may be feasible for treatment option for patients with dysregulated FGF/FGFR signaling.

CONCLUSION

Here, we review the role of FGF/FGFR signaling in TME regulation and the potential mechanisms of FGFR-TKI in combination with ICB. In addition, we review clinical data surrounding ICB alone or in combination with FGFR-TKI for the treatment of FGFR-dysregulated tumors, highlighting that FGFR inhibitors may sensitize the response to ICB by impacting various stages of the "cancer-immune cycle".

Integrative analysis revealed that distinct cuprotosis patterns reshaped tumor microenvironment and responses to immunotherapy of colorectal cancer

Background

Cuprotosis is a novel form of programmed cell death that involves direct targeting of key enzymes in the tricarboxylic acid (TCA) cycle by excess copper and may result in mitochondrial metabolic dysfunction. However, whether cuprotosis may mediate the tumor microenvironment (TME) and immune regulation in colorectal cancer (CRC) remains unclear.

Methods

Ten cuprotosis-related genes were selected and unsupervised consensus clustering was performed to identify the cuprotosis patterns and the correlated TME characteristics. Using principal component analysis, a COPsig score was established to quantify cuprotosis patterns in individual patients. The top 9 most important cuprotosis signature genes were analyzed using single-cell transcriptome data.

Results

Three distinct cuprotosis patterns were identified. The TME cell infiltration characteristics of three patterns were associated with immune-excluded, immune-desert, and immune-inflamed phenotype, respectively. Based on individual cuprotosis patterns, patients were assigned into high and low COPsig score groups. Patients with a higher COPsig score were characterized by longer overall survival time, lower immune cell as well as stromal infiltration, and greater tumor mutational burden. Moreover, further analysis demonstrated that CRC patients with a higher COPsig score were more likely to respond to immune checkpoint inhibitors and 5-fluorouracil chemotherapy. Single-cell transcriptome analysis indicated that cuprotosis signature genes recruited tumor-associated macrophages to TME through the regulation of TCA and the metabolism of glutamine and fatty acid, thus influencing the prognosis of CRC patients.

Conclusion

This study indicated that distinct cuprotosis patterns laid a solid foundation to the explanation of heterogeneity and complexity of individual TME, thus guiding more effective immunotherapy as well as adjuvant chemotherapy strategies.

Cancer-associated Fibroblasts in Bladder Cancer: Origin, Biology, and Therapeutic Opportunities

CONTEXT

Bladder cancer (BLCA) is a highly prevalent tumour and a health problem worldwide, especially among men. Recent work has highlighted the relevance of the tumour microenvironment (TME) in cancer biology with translational implications. Cancer-associated fibroblasts (CAFs) are a prominent, heterogeneous population of cells in the TME. CAFs have been associated with tumour development, progression, and poor prognosis in several neoplasms. However, their role in BLCA has not yet been exploited deeply.

OBJECTIVE

To review the role of CAFs in BLCA biology and provide an understanding of CAF origin, subtypes, markers, and phenotypic and functional characteristics to improve patient management.

EVIDENCE ACQUISITION

A PubMed search was performed to review manuscripts published using the terms "cancer associated fibroblast" and "bladder cancer" or "urothelial cancer". All abstracts were reviewed, and the full content of all relevant manuscripts was analysed. In addition, selected manuscripts on CAFs in other tumours were considered.

EVIDENCE SYNTHESIS

CAFs have been studied less extensively in BLCA than in other tumours. Thanks to new techniques, such as single-cell RNA-seq and spatial transcriptomics, it is now possible to accurately map and molecularly define the phenotype of fibroblasts in normal bladder and BLCA. Bulk transcriptomic analyses have revealed the existence of subtypes among both non-muscle-invasive and muscle-invasive BLCA; these subtypes display distinct features regarding their CAF content. We provide a higher-resolution map of the phenotypic diversity of CAFs in these tumour subtypes. Preclinical studies and recent promising clinical trials leverage on this knowledge through the combined targeting of CAFs or their effectors and the immune microenvironment.

CONCLUSIONS

Current knowledge of BLCA CAFs and the TME is being increasingly applied to improve BLCA therapy. There is a need to acquire a deeper understanding of CAF biology in BLCA.

PATIENT SUMMARY

Tumour cells are surrounded by nontumoural cells that contribute to the determination of the behaviour of cancers. Among them are cancer-associated fibroblasts. The "neighbourhoods" established through these cellular interactions can now be studied with much greater resolution. Understanding these features of tumours will contribute to the designing of more effective therapies, especially in relationship to bladder cancer immunotherapy.

Crosstalk between Mesenchymal Stem Cells and Cancer Stem Cells Reveals a Novel Stemness-Related Signature to Predict Prognosis and Immunotherapy Responses for Bladder Cancer Patients

Mesenchymal stem cells (MSCs) and cancer stem cells (CSCs) maintain bladder cancer (BCa) stemness and facilitate the progression, metastasis, drug resistance, and prognosis. Therefore, we aimed to decipher the communication networks, develop a stemness-related signature (Stem. Sig.), and identify a potential therapeutic target. BCa single-cell RNA-seq datasets (GSE130001 and GSE146137) were used to identify MSCs and CSCs. Pseudotime analysis was performed by Monocle. Stem. Sig. was developed by analyzing the communication network and gene regulatory network (GRN) that were decoded by NicheNet and SCENIC, respectively. The molecular features of the Stem. Sig. were evaluated in TCGA-BLCA and two PD-(L)1 treated datasets (IMvigor210 and Rose2021UC). A prognostic model was constructed based on a 101 machine-learning framework. Functional assays were performed to evaluate the stem traits of the hub gene. Three subpopulations of MSCs and CSCs were first identified. Based on the communication network, the activated regulons were found by GRN and regarded as the Stem. Sig. Following unsupervised clustering, two molecular subclusters were identified and demonstrated distinct cancer stemness, prognosis, immunological TME, and response to immunotherapy. Two PD-(L)1 treated cohorts further validated the performance of Stem. Sig. in prognosis and immunotherapeutic response prediction. A prognostic model was then developed, and a high-risk score indicated a poor prognosis. Finally, the hub gene SLC2A3 was found exclusively upregulated in extracellular matrix-related CSCs, predicting prognosis, and shaping an immunosuppressive tumor microenvironment. Functional assays uncovered the stem traits of SLC2A3 in BCa by tumorsphere formation and western blotting. The Stem. Sig. derived from MSCs and CSCs can predict prognosis and response to immunotherapy for BCa. Besides, SLC2A3 may serve as a promising stemness target facilitating cancer effective management.

Actionable genomic landscapes from a real-world cohort of urothelial carcinoma patients

BACKGROUND

Recent targeted therapies for advanced and metastatic urothelial cancer have generated enthusiasm, but the actionable genomic landscape of early-stage disease remains largely unknown. Here, we utilized a large, real-world cohort to comprehensively investigate the incidence of genetic alterations with potential therapeutic implications at all stages of bladder cancer.

MATERIALS AND METHODS

We retrospectively analyzed next-generation sequencing (NGS) data from 1,562 bladder cancer patients (stages I-IV) with formalin-fixed, paraffin-embedded tumor biopsies sequenced using the Tempus xT solid tumor assay. Incidence of genetic alterations, tumor mutational burden (TMB), microsatellite instability (MSI), and PD-L1 status were assessed and stratified by bladder cancer stage. For patients with tumor-normal match sequencing (n=966), incidental germline alterations in 50 genes were assessed.

RESULTS

The cohort was composed of 165 stage I-II, 211 stage III, and 1,186 stage IV tumors. TMB-high, PD-L1 positive, and MSI-high status were noted in 14%, 33%, and 0.7% of tumors, respectively, and were similar across stages. Alterations in fibroblast growth factor receptor (FGFR)2/3, homologous recombination repair genes, additional DNA repair gene mutations (ERCC2, RB1, FANCC), and NTRK fusions were detected at similar frequencies across disease stages. We identified a low rate of incidental germline mutations in all tumors (5.2%) and in specific genes: MUTYH (1.9%), BRCA2 (0.5%), and ATM (0.8%).

CONCLUSIONS

Important subsets of patients demonstrate genetic alterations in potentially actionable molecular pathways at all stages. This analysis found minimal variability in these alterations across stages, providing rationale for early identification of genetic alterations and personalization of therapies at all stages for patients with bladder cancer.

The 27-gene IO score is associated with efficacy of PD-1/L1 inhibitors independent of FGFR expression in a real-world metastatic urothelial carcinoma cohort

Multiple targeted therapeutics have been approved by the FDA for mUC, including immune checkpoint inhibitors (ICIs) and more recently targeted agents for both FGFR and Nectin-4. FGFR3-aberrant and Nectin-4 expressing cells have been associated with an immunosuppressed phenotype. Given that less than half of all patients respond to these agents as monotherapies and less than 20% are eligible to receive salvage therapy, effective personalized treatment plans are critical. Typical biomarkers for ICIs such as PD-L1 and TMB have not been definitive in mUC, yet a biomarker-driven optimization of first-line therapy and subsequent sequencing have the potential to achieve higher and more durable response rates. The IO score is a 27-gene tumor immune microenvironment (TIME) classifier that has been associated with the clinical benefits of ICIs in multiple cancer types, including mUC. This study demonstrates that the IO score was associated with both progression-free survival (PFS) and overall survival (OS) in a real-world cohort of mUC patients treated with ICIs. Furthermore, the IO score was independent of and provided information incremental to TMB. Interestingly, the IO score predicted benefit in patients with high FGFR expression, despite conflicting data regarding response rates among the FGFR aberrant population. Taken together, these results demonstrate that the IO score assessment of the TIME is associated with a clinical benefit from ICI therapy and that this novel biomarker may inform therapeutic sequencing decisions in mUC, potentially improving outcomes for this notoriously difficult-to-treat disease.

SECTM1 is upregulated in immuno-hot tumors and predicts immunotherapeutic efficacy in multiple cancers

Immune checkpoint inhibitors (ICIs) have transformed the management of advanced cancers. However, many patients could not benefit from ICIs therapy, and thus several biomarkers for therapeutic prediction have been uncovered. In this research, more than ten public and in-house cohorts were used to explore the predictive value and immunological correlations of secreted and transmembrane 1 (SECTM1) in cancers. SECTM1 expression was enhanced in tumors from patients with well immunotherapeutic responses in multiple cancers. In addition, SECTM1 was immuno-correlated in pan-cancer and enhanced in immuno-hot tumors. In vitro assays revealed that SECTM1 was upregulated by the IFN-γ/STAT1 signaling. Moreover, analysis of in-house immunotherapy cohorts suggested both tumor-expressed and circulating SECTM1 are promising biomarkers to predict therapeutic responses. Overall, this study reveals that SECTM1 is a biomarker of benefit to ICIs in cancer patients. Further studies including large-scale patients are needed to establish its utilization as a biomarker of benefit to ICIs.

Predicting prognosis and clinical efficacy of immune checkpoint blockade therapy via interferon-alpha response in muscle-invasive bladder cancer

Background: Immune checkpoint blockade (ICB) can prompt durable and robust responses in multiple cancers, involving muscle-invasive bladder cancer (MIBC). However, only a limited fraction of patients received clinical benefit. Clarifying the determinants of response and exploring corresponding predictive biomarkers is key to improving outcomes. Methods: Four independent formerly published cohorts consisting of 641 MIBC patients were enrolled in this study. We first analyzed the associations between various cancer hallmarks and ICB therapy response in two immunotherapeutic cohorts to identify the leading prognostic hallmark in MIBC. Furthermore, advanced machine learning methods were performed to select robust and promising predictors from genes functioning in the above leading pathway. The predictive ability of selected genes was also validated in multiple MIBC cohorts. Results: We identified and verified IFNα response as the leading cancer hallmark indicating better treatment responses, favorable overall survival, and an inflamed tumor microenvironment with higher infiltration of immune effector cells in MIBC patients treated with ICB therapy. Subsequently, two commonly selected genes, CXCL10 and LAMP3, implied better therapy response and the CXCL10^highLAMP3^high patients would benefit more from ICB therapy, which was comprehensively validated from the perspective of gene expression, clinical response, patient survival and immune features. Conclusion: Higher IFNα response primarily predicted better ICB therapeutic responses and reflected an inflamed microenvironment in MIBC. A composite of CXCL10 and LAMP3 expression could serve as promising predictive biomarkers for ICB therapeutic responses and be beneficial for clinical decision-making in MIBC.