Collaborative study from the Bladder Cancer Advocacy Network for the genomic analysis of metastatic urothelial cancer

Poor Prognosis among Radiation-Associated Bladder Cancer Is Defined by Clinicogenomic Features

Radiotherapy (RT) for prostate cancer has been associated with an increased risk for the development of bladder cancer. We aimed to integrate clinical and genomic data to better understand the development of RT-associated bladder cancer. A retrospective analysis was performed to identify control patients (CTRL; n = 41) and patients with RT-associated bladder cancer (n = 41). RT- and CTRL-specific features were then identified through integration and analysis of the genomic sequencing data and clinical variables. RT-associated bladder tumors were significantly enriched for alterations in KDM6A and ATM, whereas CTRL tumors were enriched for CDKN2A mutation. Globally, there were an increased number of variants within RT tumors, albeit at a lower variant allele frequency. Mutational signature analysis revealed three predominate motif patterns, with similarity to SBS2/13 (APOBEC3A), SBS5 (ERCC2/smoking), and SBS6/15 (MMR). Poor prognostic factors in the RT cohort include a short tumor latency, smoking status, the presence of the smoking and X-ray therapy mutational signatures, and CDKN2A copy number loss. Based on the clinical and genomic findings, we suggest at least two potential pathways leading to RT-associated bladder cancer: The first occurs in the setting of field cancerization related to smoking or preexisting genetic alterations and leads to the development of more aggressive bladder tumors, and the second involves RT initiating the oncogenic process in otherwise healthy urothelium, leading to a longer latency and less aggressive disease.

SIGNIFICANCE

Clinicogenomic analysis of radiation-associated bladder cancer uncovered mutational signatures that, in addition to a short tumor latency, smoking, and CDKN2A loss, are associated with a poor outcome. These clinical and genomic features provide a potential method to identify patients with prostate cancer who are at an increased risk for the development of aggressive bladder cancer following prostate RT.

Integrating single-cell RNA-seq to identify fibroblast-based molecular subtypes for predicting prognosis and therapeutic response in bladder cancer

BACKGROUND

Bladder cancer (BLCA) is a highly aggressive and heterogeneous disease, posing challenges for diagnosis and treatment. Cancer immunotherapy has recently emerged as a promising option for patients with advanced and drug-resistant cancers. Fibroblasts, a significant component of the tumor microenvironment, play a crucial role in tumor progression, but their precise function in BLCA remains uncertain.

METHODS

Single-cell RNA sequencing (scRNA-seq) data for BLCA were obtained from the Gene Expression Omnibus database. The R package "Seurat" was used for processing scRNA-seq data, with uniform manifold approximation and projection (UMAP) for downscaling and cluster identification. The FindAllMarkers function identified marker genes for each cluster. Differentially expressed genes influencing overall survival (OS) of BLCA patients were identified using the limma package. Differences in clinicopathological characteristics, immune microenvironment, immune checkpoints, and chemotherapeutic drug sensitivity between high- and low-risk groups were investigated. RT-qPCR and immunohistochemistry validated the expression of prognostic genes.

RESULTS

Fibroblast marker genes identified three molecular subtypes in the testing set. A prognostic signature comprising ten genes stratified BLCA patients into high- and low-score groups. This signature was validated in one internal and two external validation sets. High-score patients exhibited increased immune cell infiltration, elevated chemokine expression, and enhanced immune checkpoint expression but had poorer OS and a reduced response to immunotherapy. Six sensitive anti-tumor drugs were identified for the high-score group. RT-qPCR and immunohistochemistry showed that CERCAM, TM4SF1, FN1, ANXA1, and LOX were highly expressed, while EMP1, HEYL, FBN1, and SLC2A3 were downregulated in BLCA.

CONCLUSION

A novel fibroblast marker gene-based signature was established, providing robust predictions of survival and immunotherapeutic response in BLCA patients.

Similar genetic profile in early and late stage urothelial tract cancer

INTRODUCTION

Urothelial tract cancer (UTC) ranks as the tenth most prevalent cancer and holds the seventh position in terms of mortality worldwide. Despite its prevalence and mortality ranking, there are still gaps in the knowledge of the mutational landscape in patients with advanced disease who have limited therapeutic options after multiple lines of prior treatment. This study compares the genomic and transcriptomic landscape, and targeted treatment options between metastatic UTC (mUTC) patients treated with multiple lines of therapy compared to newly diagnosed, untreated Muscle Invasive Bladder Cancer (MIBC).

METHODS

We compared genomic and clinical data from two cohorts: mUTC patients who received multiple lines of therapy and were referred to the Copenhagen Prospective Personalized Oncology (CoPPO) project at Rigshospitalet, University of Copenhagen. Data for MIBC UTC patients were acquired from the Cancer Genome Atlas Bladder Cancer (TCGA BLCA) cohort. Biopsies in CoPPO were performed at the time of enrollment. 523 highly important cancer-related genes (TrueSight Oncology-500 targeted sequencing panel) were used from both cohorts for comparative analysis. Analyses included RNA count data to compare predicted molecular subtypes in each cohort separately.

RESULTS

Patients from the CoPPO cohort had a lower median age at first-line treatment than the TCGA BLCA cohort, with no significant gender disparity. The predominant histology was urothelial cell carcinoma in both cohorts. Genomic analysis revealed no significant difference between the top mutated genes in the two cohorts, specifically looking into DNA damage repair genes. Molecular subtyping indicated a higher frequency of neuroendocrine differentiation in the CoPPO cohort. 13% of patients in the CoPPO cohort received targeted therapy based on genomic findings, and 16% received non-targeted treatment, totaling 29% receiving CoPPO treatment (9 patients). The remaining 71% received best supportive care. Kaplan-Meier analysis showed a non-significant survival benefit for the intervention group in the CoPPO cohort.

CONCLUSION

When focusing on 523 highly relevant cancer genes, the mutational profile of mUTC patients who have undergone numerous treatment lines resembles that of newly diagnosed MIBC. These alterations can be targeted, indicating the potential advantage of early genomic testing for personalized treatment within clinical trials.

Remodeling of anti-tumor immunity with antibodies targeting a p53 mutant

BACKGROUND

p53, the most frequently mutated gene in cancer, lacks effective targeted drugs.

METHODS

We developed monoclonal antibodies (mAbs) that target a p53 hotspot mutation E285K without cross-reactivity with wild-type p53. They were delivered using lipid nanoparticles (LNPs) that encapsulate DNA plasmids. Western blot, BLI, flow cytometry, single-cell sequencing (scRNA-seq), and other methods were employed to assess the function of mAbs in vitro and in vivo.

RESULTS

These LNP-pE285K-mAbs in the IgG1 format exhibited a robust anti-tumor effect, facilitating the infiltration of immune cells, including CD8+ T, B, and NK cells. scRNA-seq revealed that IgG1 reduces immune inhibitory signaling, increases MHC signaling from B cells to CD8+ T cells, and enriches anti-tumor T cell and B cell receptor profiles. The E285K-mAbs were also produced in the dimeric IgA (dIgA) format, whose anti-tumor activity depended on the polymeric immunoglobulin receptor (PIGR), a membrane Ig receptor, whereas that of IgG1 relied on TRIM21, an intracellular IgG receptor.

CONCLUSIONS

Targeting specific mutant epitopes using DNA-encoded and LNP-delivered mAbs represents a potential precision medicine strategy against p53 mutants in TRIM21- or PIGR-positive cancers.

Immune features are associated with response to neoadjuvant chemo-immunotherapy for muscle-invasive bladder cancer

Neoadjuvant cisplatin-based chemotherapy is standard of care for muscle-invasive bladder cancer (MIBC). Immune checkpoint inhibition (ICI) alone, and ICI in combination with chemotherapy, have demonstrated promising pathologic response ( Collapse

Key Words

• predictive markers
• bladder cancer
• immunotherapy
• tumour immunology

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MESH Headings

• Humans
• Urinary Bladder Neoplasms/drug therapy
• Urinary Bladder Neoplasms/immunology
• Urinary Bladder Neoplasms/therapy
• Urinary Bladder Neoplasms/pathology
• Neoadjuvant Therapy/methods
• Deoxycytidine/analogs & derivatives
• Deoxycytidine/therapeutic use
• Deoxycytidine/administration & dosage
• Gemcitabine
• Immunotherapy/methods
• Male
• Cisplatin/therapeutic use
• Cisplatin/administration & dosage
• Female
• Antibodies, Monoclonal, Humanized/therapeutic use
• Antineoplastic Combined Chemotherapy Protocols/therapeutic use
• Immune Checkpoint Inhibitors/therapeutic use
• Aged
• Middle Aged
• Neoplasm Invasiveness
• Interleukin-9/metabolism
• B7-H1 Antigen/metabolism
• Biomarkers, Tumor/blood
• Treatment Outcome

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Grants

• F30 CA278317 NCI NIH HHS
• 1F30CA278317-01A1 U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI)
• Merck & Co., Inc. | Merck Sharp and Dohme (Merck Sharp & Dohme)
• U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI)

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Affiliation(s)

Wolfgang Beckabir Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA Department of Microbiology and Immunology, UNC School of Medicine, Chapel Hill, NC, USA
Mi Zhou Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Jin Seok Lee Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA Curriculum in Bioinformatics and Computational Biology, UNC School of Medicine, Chapel Hill, NC, USA
Steven P Vensko Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Mark G Woodcock Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA Division of Oncology, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Hsing-Hui Wang Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA Department of Microbiology and Immunology, UNC School of Medicine, Chapel Hill, NC, USA
Sara E Wobker Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA Department of Pathology and Laboratory Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Gatphan Atassi Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Alec D Wilkinson Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Kenneth Fowler Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Leah M Flick Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Jeffrey S Damrauer Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA Division of Oncology, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Michael R Harrison Division of Medical Oncology, Department of Medicine, Duke Cancer Institute, Duke University, Durham, NC, USA
Karen P McKinnon Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA Department of Microbiology and Immunology, UNC School of Medicine, Chapel Hill, NC, USA
Tracy L Rose Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA Division of Oncology, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Matthew I Milowsky Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA Division of Oncology, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Jonathan S Serody Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. Department of Microbiology and Immunology, UNC School of Medicine, Chapel Hill, NC, USA. Division of Oncology, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
William Y Kim Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. Division of Oncology, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. Division of Hematology, Department of Medicine, UNC School of Medicine, Chapel Hill, NC, USA.
Benjamin G Vincent Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. Curriculum in Bioinformatics and Computational Biology, UNC School of Medicine, Chapel Hill, NC, USA. Division of Oncology, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. Computational Medicine Program, UNC School of Medicine, Chapel Hill, NC, USA.

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Spatial Relationships in the Tumor Microenvironment Demonstrate Association with Pathologic Response to Neoadjuvant Chemoimmunotherapy in Muscle-invasive Bladder Cancer

BACKGROUND

Platinum-based neoadjuvant chemotherapy (NAC) is standard for patients with muscle-invasive bladder cancer (MIBC). Pathologic response (complete: ypT0N0 and partial:

OBJECTIVE

Using the NanoString GeoMx platform, we performed proteomic digital spatial profiling (DSP) on transurethral resections of bladder tumors from 18 responders (

DESIGN, SETTING, AND PARTICIPANTS

Pretreatment tumor samples were stained by hematoxylin and eosin and immunofluorescence (panCK and CD45) to select four regions of interest (ROIs): tumor enriched (TE), immune enriched (IE), tumor/immune interface (tumor interface = TX and immune interface = IX).

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

DSP was performed with 52 protein markers from immune cell profiling, immunotherapy drug target, immune activation status, immune cell typing, and pan-tumor panels.

RESULTS AND LIMITATIONS

Protein marker expression patterns were analyzed to determine their association with pathologic response, incorporating or agnostic of their ROI designation (TE/IE/TX/IX). Overall, DSP-based marker expression showed high intratumoral heterogeneity; however, response was associated with markers including PD-L1 (ROI agnostic), Ki-67 (ROI agnostic, TE, IE, and TX), HLA-DR (TX), and HER2 (TE). An elastic net model of response with ROI-inclusive markers demonstrated better validation set performance (area under the curve [AUC] = 0.827) than an ROI-agnostic model (AUC = 0.432). A model including DSP, tumor mutational burden, and clinical data performed no better (AUC = 0.821) than the DSP-only model.

CONCLUSIONS

Despite high intratumoral heterogeneity of DSP-based marker expression, we observed associations between pathologic response and specific DSP-based markers in a spatially dependent context. Further exploration of tumor region-specific biomarkers may help predict response to neoadjuvant chemoimmunotherapy in MIBC.

PATIENT SUMMARY

In this study, we used the GeoMx platform to perform proteomic digital spatial profiling on transurethral resections of bladder tumors from 18 responders and 18 nonresponders from two studies of neoadjuvant chemotherapy (gemcitabine and cisplatin) plus immune checkpoint inhibitor therapy (LCCC1520 [pembrolizumab] and BLASST-1 [nivolumab]). We found that assessing protein marker expression in the context of tumor architecture improved response prediction.

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Key Words

• BLASST-1
• Bladder cancer
• Digital spatial profiling
• Elastic net regression
• GeoMx
• LCCC1520
• Neoadjuvant chemoimmunotherapy

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MESH Headings

• Humans
• Cisplatin
• Neoadjuvant Therapy/methods
• Gemcitabine
• Nivolumab/therapeutic use
• Proteomics
• Tumor Microenvironment
• Urinary Bladder Neoplasms/drug therapy
• Urinary Bladder Neoplasms/pathology
• Biomarkers, Tumor
• Muscles/pathology
• Immunotherapy
• Neoplasm Invasiveness
• Cystectomy

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Grants

• F30 CA278317 NCI NIH HHS
• P30 CA016086 NCI NIH HHS
• R01 CA241810 NCI NIH HHS
• T32 CA244125 NCI NIH HHS

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Affiliation(s)

Wolfgang Beckabir Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Department of Microbiology and Immunology, UNC School of Medicine, Chapel Hill, NC, USA
Sara E Wobker Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Department of Pathology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Jeffrey S Damrauer Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Division of Oncology, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Bentley Midkiff Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Gabriela De la Cruz Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Vladmir Makarov Department of Hematology and Oncology, Taussig Cancer Institute, Cleveland Clinic, Cleveland, OH, USA
Leah Flick Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Mark G Woodcock Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Department of Microbiology and Immunology, UNC School of Medicine, Chapel Hill, NC, USA
Petros Grivas Department of Medicine, Division of Medical Oncology, University of Washington, Fred Hutchinson Cancer Center, Seattle, WA, USA
Marc A Bjurlin Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Department of Urology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Michael R Harrison Division of Medical Oncology, Department of Medicine, Duke Cancer Institute, Duke University, Durham, NC, USA
Benjamin G Vincent Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Department of Microbiology and Immunology, UNC School of Medicine, Chapel Hill, NC, USA; Division of Hematology, Department of Medicine, UNC School of Medicine, Chapel Hill, NC, USA; Computational Medicine Program, UNC School of Medicine, Chapel Hill, NC, USA; Curriculum in Bioinformatics and Computational Biology, UNC School of Medicine, Chapel Hill, NC, USA
Tracy L Rose Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Division of Oncology, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Shilpa Gupta Department of Hematology and Oncology, Taussig Cancer Institute, Cleveland Clinic, Cleveland, OH, USA
William Y Kim Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Division of Oncology, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Matthew I Milowsky Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Division of Oncology, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.

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A Large-Scale Meta-Analysis Reveals Positive Feedback between Macrophages and T Cells That Sensitizes Tumors to Immunotherapy

Although considerable efforts have been dedicated to identifying predictive signatures for immune checkpoint inhibitor (ICI) treatment response, current biomarkers suffer from poor generalizability and reproducibility across different studies and cancer types. The integration of large-scale multiomics studies holds great promise for discovering robust biomarkers and shedding light on the mechanisms of immune resistance. In this study, we conducted the most extensive meta-analysis involving 3,037 ICI-treated patients with genetic and/or transcriptomics profiles across 14 types of solid tumor. The comprehensive analysis uncovered both known and novel reliable signatures associated with ICI treatment outcomes. The signatures included tumor mutational burden (TMB), IFNG and PDCD1 expression, and notably, interactions between macrophages and T cells driving their activation and recruitment. Independent data from single-cell RNA sequencing and dynamic transcriptomic profiles during the ICI treatment provided further evidence that enhanced cross-talk between macrophages and T cells contributes to ICI response. A multivariable model based on eight nonredundant signatures significantly outperformed existing models in five independent validation datasets representing various cancer types. Collectively, this study discovered biomarkers predicting ICI response that highlight the contribution of immune cell networks to immunotherapy efficacy and could help guide patient treatment.

SIGNIFICANCE

Identification of robust immunogenomic connections, particularly macrophage T-cell interactions, in a large-scale pan-cancer meta-analysis and development of a predictive model for immunotherapy response that outperformed existing models could facilitate clinical decision-making.

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.

Impact of consensus molecular subtypes on survival with and without adjuvant chemotherapy in muscle-invasive urothelial bladder cancer

AIMS

Adjuvant chemotherapy after radical cystectomy can reduce the risk of recurrence and death in advanced muscle-invasive urothelial bladder cancer (MIBC). Molecular subtypes have been shown to be associated with survival. However, their predictive value to guide treatment decisions is controversial and data to use subtypes as guidance for adjuvant chemotherapy is sparse. We aimed to assess survival rates based on MIBC consensus molecular subtypes with and without adjuvant chemotherapy.

METHODS

Gene expression profiles of 143 patients with MIBC undergoing radical cystectomy were determined from formalin-fixed, paraffin-embedded specimen to assign consensus molecular subtypes. Expression of programmed cell death ligand-1 (PD-L1) and immune cell infiltration were determined using multiplex immunofluorescence. Matched-pair analysis was performed to evaluate the effect of adjuvant chemotherapy on overall survival (OS) for molecular subtypes applying Kaplan-Meier and Cox regression survival analyses.

RESULTS

Samples were luminal papillary: 9.1% (n=13), luminal non-specified: 6.3% (n=9), luminal unstable: 4.9% (n=7), stroma-rich: 27.9% (n=40), basal/squamous (Ba/Sq): 48.9% (n=70) and neuroendocrine-like (NE-like): 2.8% (n=4). Ba/Sq tumours had the highest concentration of PD-L1+ tumour and immune cells. Patients with luminal subtypes had better OS than those with NE-like (HR 0.2, 95% CI 0.1 to 0.7, p<0.05) and Ba/Sq (HR 0.5, 95% CI 0.2 to 0.9, p<0.05). No survival benefit with adjuvant chemotherapy was observed for luminal tumours, whereas Ba/Sq had significantly improved survival rates with adjuvant chemotherapy. Retrospective design and sample size are the main limitations.

CONCLUSION

Consensus molecular subtypes can be used to stratify patients with MIBC. Luminal tumours have the best prognosis and less benefit when receiving adjuvant chemotherapy compared with Ba/Sq tumours.

Human APOBEC3B promotes tumor development in vivo including signature mutations and metastases

The antiviral DNA cytosine deaminase APOBEC3B has been implicated as a source of mutation in many cancers. However, despite years of work, a causal relationship has yet to be established in vivo. Here, we report a murine model that expresses tumor-like levels of human APOBEC3B. Animals expressing full-body APOBEC3B appear to develop normally. However, adult males manifest infertility, and older animals of both sexes show accelerated rates of carcinogenesis, visual and molecular tumor heterogeneity, and metastasis. Both primary and metastatic tumors exhibit increased frequencies of C-to-T mutations in TC dinucleotide motifs consistent with the established biochemical activity of APOBEC3B. Enrichment for APOBEC3B-attributable single base substitution mutations also associates with elevated levels of insertion-deletion mutations and structural variations. APOBEC3B catalytic activity is required for all of these phenotypes. Together, these studies provide a cause-and-effect demonstration that human APOBEC3B is capable of driving both tumor initiation and evolution in vivo.

Survival and Enrichment Analysis of Epithelial-Mesenchymal Transition Genes in Bladder Urothelial Carcinoma

The escalating prevalence of bladder cancer, particularly urothelial carcinoma, necessitates innovative approaches for prognosis and therapy. This study delves into the significance of genes related to epithelial-mesenchymal transition (EMT), a process inherently linked to carcinogenesis and comparatively better studied in other cancers. We examined 1184 EMT-related gene expression levels in bladder urothelial cancer cases through the TCGA dataset. Genes shown to be differentially expressed in relation to survival underwent further network and enrichment analysis to uncover how they might shape disease outcomes. Our in silico analysis revealed a subset of 32 genes, including those significantly represented in biological pathways such as VEGF signaling and bacterium response. In addition, these genes interact with genes involved in the JAK-STAT signaling pathway. Additionally, some of those 32 genes have been linked to immunomodulators such as chemokines CCL15 and CCL18, as well as to various immune cell infiltrates. Our findings highlight the prognostic utility of various EMT-related genes and identify possible modulators of their effect on survival, allowing for further targeted wet lab research and possible therapeutic intervention.

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.

Structural basis of histone H2A lysine 119 deubiquitination by Polycomb repressive deubiquitinase BAP1/ASXL1

Histone H2A lysine 119 (H2AK119Ub) is monoubiquitinated by Polycomb repressive complex 1 and deubiquitinated by Polycomb repressive deubiquitinase complex (PR-DUB). PR-DUB cleaves H2AK119Ub to restrict focal H2AK119Ub at Polycomb target sites and to protect active genes from aberrant silencing. The PR-DUB subunits (BAP1 and ASXL1) are among the most frequently mutated epigenetic factors in human cancers. How PR-DUB establishes specificity for H2AK119Ub over other nucleosomal ubiquitination sites and how disease-associated mutations of the enzyme affect activity are unclear. Here, we determine a cryo-EM structure of human BAP1 and the ASXL1 DEUBAD in complex with a H2AK119Ub nucleosome. Our structural, biochemical, and cellular data reveal the molecular interactions of BAP1 and ASXL1 with histones and DNA that are critical for restructuring the nucleosome and thus establishing specificity for H2AK119Ub. These results further provide a molecular explanation for how >50 mutations in BAP1 and ASXL1 found in cancer can dysregulate H2AK119Ub deubiquitination, providing insight into understanding cancer etiology.

Phase II study of a trastuzumab biosimilar in combination with paclitaxel for HER2-positive recurrent or metastatic urothelial carcinoma: KCSG GU18-18

BACKGROUND

Human epidermal growth factor receptor 2 (HER2) is a widely explored therapeutic target in solid tumors. We evaluated the efficacy and safety of trastuzumab-pkrb, a biosimilar of trastuzumab, in combination with paclitaxel, in HER2-positive recurrent or metastatic urothelial carcinoma (UC).

PATIENTS AND METHODS

We enrolled 27 patients; they were administered a loading dose of 8 mg/kg trastuzumab-pkrb on day 1, followed by 6 mg/kg and 175 mg/m2 paclitaxel on day 1 every 3 weeks, intravenously. All patients received six cycles of the combination treatment and continued to receive trastuzumab-pkrb maintenance until disease progression, unacceptable toxicity, or for up to 2 years. HER2 positivity (based on immunohistochemistry analysis) was determined according to the 2013 American Society of Clinical Oncology /College of American Pathologists HER2 testing guidelines. The primary endpoint was objective response rate (ORR); the secondary endpoints were overall survival (OS), progression-free survival (PFS), and safety.

RESULTS

Twenty-six patients were evaluated via primary endpoint analysis. The ORR was 48.1% (1 complete and 12 partial responses) and the duration of response was 6.9 months [95% confidence interval (CI) 4.4-9.3 months]. With a median follow-up of 10.5 months, the median PFS and OS were 8.4 months (95% CI 6.2-8.8 months) and 13.5 months (95% CI 9.8 months-not reached), respectively. The most common treatment-related adverse event (TRAE) of any grade was peripheral neuropathy (88.9%). The most common grade 3/4 TRAEs were neutropenia (25.9%), thrombocytopenia (7.4%), and anemia (7.4%).

CONCLUSIONS

Trastuzumab-pkrb plus paclitaxel demonstrates promising efficacy with manageable toxicity profiles in patients with HER2-positive recurrent or metastatic UC.

Optimizing identification of consensus molecular subtypes in muscle-invasive bladder cancer: a comparison of two sequencing methods and gene sets using FFPE specimens

BACKGROUND

Molecular subtypes predict prognosis in muscle-invasive bladder cancer (MIBC) and are explored as predictive markers. To provide a common base for molecular subtyping and facilitate clinical applications, a consensus classification has been developed. However, methods to determine consensus molecular subtypes require validation, particularly when FFPE specimens are used. Here, we aimed to evaluate two gene expression analysis methods on FFPE samples and to compare reduced gene sets to classify tumors into molecular subtypes.

METHODS

RNA was isolated from FFPE blocks of 15 MIBC patients. Massive analysis of 3' cDNA ends (MACE) and the HTG transcriptome panel (HTP) were used to retrieve gene expression. We used normalized, log2-transformed data to call consensus and TCGA subtypes with the consensusMIBC package for R using all available genes, a 68-gene panel (ESSEN1), and a 48-gene panel (ESSEN2).

RESULTS

Fifteen MACE-samples and 14 HTP-samples were available for molecular subtyping. The 14 samples were classified as Ba/Sq in 7 (50%), LumP in 2 (14.3%), LumU in 1 (7.1%), LumNS in 1 (7.1%), stroma-rich in 2 (14.3%) and NE-like in 1 (7.1%) case based on MACE- or HTP-derived transcriptome data. Consensus subtypes were concordant in 71% (10/14) of cases when comparing MACE with HTP data. Four cases with aberrant subtypes had a stroma-rich molecular subtype with either method. The overlap of the molecular consensus subtypes with the reduced ESSEN1 and ESSEN2 panels were 86% and 100%, respectively, with HTP data and 86% with MACE data.

CONCLUSION

Determination of consensus molecular subtypes of MIBC from FFPE samples is feasible using various RNA sequencing methods. Inconsistent classification mainly involves the stroma-rich molecular subtype, which may be the consequence of sample heterogeneity with (stroma)-cell sampling bias and highlights the limitations of bulk RNA-based subclassification. Classification is still reliable when analysis is reduced to selected genes.

Human APOBEC3B promotes tumor heterogeneity in vivo including signature mutations and metastases

The antiviral DNA cytosine deaminase APOBEC3B has been implicated as a source of mutation in many different cancers. Despite over 10 years of work, a causal relationship has yet to be established between APOBEC3B and any stage of carcinogenesis. Here we report a murine model that expresses tumor-like levels of human APOBEC3B after Cre-mediated recombination. Animals appear to develop normally with full-body expression of APOBEC3B. However, adult males manifest infertility and older animals of both sexes show accelerated rates of tumorigenesis (mostly lymphomas or hepatocellular carcinomas). Interestingly, primary tumors also show overt heterogeneity, and a subset spreads to secondary sites. Both primary and metastatic tumors exhibit increased frequencies of C-to-T mutations in TC dinucleotide motifs consistent with the established biochemical activity of APOBEC3B. Elevated levels of structural variation and insertion-deletion mutations also accumulate in these tumors. Together, these studies provide the first cause-and-effect demonstration that human APOBEC3B is an oncoprotein capable of causing a wide range of genetic changes and driving tumor formation in vivo .