An N-Cadherin 2 expressing epithelial cell subpopulation predicts response to surgery, chemotherapy and immunotherapy in bladder cancer

Patient-derived organoid co-culture systems as next-generation models for bladder cancer stem cell research

Three-dimensional patient-derived organoids (PDOs) have emerged as a powerful model for investigating the molecular and cellular mechanisms underlying bladder cancer, particularly in the context of cancer stem cells (CSCs) and drug screening. However, a significant limitation of conventional PDOs is the absence of tumor microenvironment (TME), which includes critical stromal, immune and microbial components that influence tumor behavior and treatment response. In this review, we provide a comprehensive overview of the recent advancements in PDO co-culture systems designed to integrate TME elements. Additionally, we emphasize the role of biomedical engineering technologies, such as 3D bioprinting and organoids-on-a-chip, in enhancing the physiological relevance of these models. Furthermore, we explore how bladder PDO co-culture systems are applied in research on bladder CSC characterization, evolution and treatment responses. Finally, we discuss future directions for improving PDO systems to achieve more accurate preclinical modeling and drug discovery.

Tumour-infiltrating immune cells as a novel prognostic model for bladder cancer

Bladder cancer (BLCA) is the tenth most commonly diagnosed cancer and poses a significant challenge due to its complexity and associated high morbidity and mortality rates in the absence of optimal treatment. The tumor microenvironment (TME) is recognized as a critical factor in tumor initiation, progression and therapeutic response, and offers numerous potential targets for intervention. A comprehensive understanding of immune infiltration patterns in BLCA is essential for the development of effective prevention and treatment strategies. In this study, bioinformatics analysis was used to identify differentially expressed genes (DEGs) and tumor-infiltrating immune cells (TIICs) between BLCA tissues and adjacent normal tissues. Weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) analysis were used to identify the top 10 hub genes with the most significant co-expression effects, and their potential relationship with patient prognosis was then predicted. The random survival forest (RSF) model was used to further identify six variables among the hub genes and establish a novel scoring system, defined as the tumor-infiltrating immune score (TIIS) to predict the prognosis of BLCA patients. In addition, the correlation analysis between TIIS and drug sensitivity was investigated using the Genomics of Drug Sensitivity in Cancer (GDSC) and Cancer Therapeutics Response Portal (CTRP) databases. Patients with high TIIS were found to have a poor prognosis but may be more sensitive to Cisplatin and certain novel agents. This study provided a systematic analysis of immune cell infiltration in BLCA and established TIIS to predict patient prognosis and the efficacy of specific drugs in the treatment of BLCA.

Nerve infiltration of bladder cancer predicts response to immunotherapy

Immune checkpoint therapy (ICT), particularly Programmed Death-1 (PD1) antibody treatment, has revolutionized the clinical management of many previously undruggable types bladder cancer (BC). However, it remains unclear whether nerve-invaded BC patients benefit from immunotherapy. Here, we utilized public databases to show that BC patients with high neural signal expression are associated with more advanced tumor stages. Analysis of patient tumor samples revealed significant neural expression within classical tertiary lymphoid structures, and this was inversely correlated with the immune levels. In a denervated mouse bladder tumor model, we found that nerve ablation significantly inhibited tumor progression. Single-nucleus RNA sequencing data revealed that nerve fibers suppressed the activity of immune cells within the tumor microenvironment, while denervation alleviated immune suppression and restored cytotoxic activity. Denervation enhanced the immune response by downregulating Pdcd1 (encoded Pd1) expression in natural killer (NK) cells. Pathological analysis of patient tumor samples further confirmed that higher neural abundance was strongly correlated with PD1 expression. Finally, through database analysis and clinical sample validation, we demonstrated that BC patients with high neural signaling showed better responses to ICT. Overall, this study highlights the potential for targeted immunotherapy in nerve-invasive BC, providing a novel framework for enhancing the effectiveness of ICT in treating this subset of bladder cancer.

A single-cell atlas of bladder cancer unveils dynamic cellular composition and endothelial functional shifts during progression

PURPOSE

Bladder cancer (BC) is characterized by high heterogeneity, with non-muscle-invasive (NMIBC) and muscle-invasive (MIBC) stages differing significantly in clinical behavior and outcomes. The transition from NMIBC to MIBC involves extensive tumor microenvironment (TME) remodeling, particularly in endothelial cells (ECs), which drive angiogenesis and modulate immune and extracellular matrix (ECM) interactions. However, the precise roles of ECs in this progression remain poorly defined.

METHODS

Public single-cell RNA sequencing (scRNA-seq) datasets from 47 BC patients were analyzed to characterize endothelial cell heterogeneity and functional states across NMIBC and MIBC. Computational tools such as CellChat were applied to reconstruct cell-cell communication networks, focusing on pathways related to angiogenesis, immune crosstalk, and ECM remodeling.

RESULTS

Twelve major cell types were identified, with endothelial cells exhibiting distinct transcriptional profiles between NMIBC and MIBC. NMIBC-associated ECs promoted adhesion and migration through HMGB1 and CXCL12 signaling. In contrast, MIBC was enriched in an ADAM10+ endothelial subset associated with vascular remodeling and activation of Wnt signaling via CTNNB1. Key ligand-receptor interactions highlighted the dynamic roles of ECs in TME modulation during BC progression.

CONCLUSIONS

This study reveals stage-specific endothelial cell phenotypes and signaling networks in BC. The identification of an MIBC-specific ADAM10+ endothelial subset underscores its potential role in driving tumor progression and highlights opportunities for stage-adapted vascular-targeted therapies. These findings advance our understanding of BC pathogenesis and provide the foundation for novel therapeutic strategies.

Mapping immunotherapy potential: spatial transcriptomics in the unraveling of tumor-immune microenvironments in head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC) often exhibits poor response rates to immune checkpoint inhibitor (ICI) therapies, largely owing to the intricate composition and spatial organization of immune cells within the tumor-immune microenvironment (TIME). The diversity of immune cell populations, their spatial relationships, and dynamic interactions significantly influence the immunosuppressive nature of the TIME, thereby limiting the efficacy of immunotherapy. To address these challenges and enhance the therapeutic potential of ICIs in HNSCC, a comprehensive analysis of the TIME is essential. Spatial transcriptomics (ST), a cutting-edge technology, enables high-resolution mapping of gene expression within the spatial context of the tumor, providing critical insights into the functional roles and interactions of immune cells in the TIME. This review highlights the importance of ST in uncovering the complexities of the TIME in HNSCC and proposes strategies for leveraging these insights to develop more effective immunotherapeutic approaches. By integrating spatial and molecular information, this review aims to pave the way for personalized and precision-based treatments in HNSCC, ultimately improving patient outcomes.

Metabolites and metabolic pathway reactions links to sensitization of immunotherapy in pan-cancer

Metabolic features are crucial in tumor immune interactions, but their relationship with antitumor immune responses is not yet fully understood. This study used Mendelian randomization analysis to identify the causal relationships between blood metabolites and immune cells and to evaluate the effects of metabolic pathways and reactions on antitumor immune responses in various cancers. Levels of 156 metabolites exhibited significant associations with selected immune cells. Metabolic enrichment analysis indicated laurate, propionyl-carnitine, carnitine and l-acetylcarnitine are enriched in fatty acid (FA) metabolism pathways. These enriched pathways are significantly correlated to CD8+ T cell function signatures in tumor environment and favor better prognostic outcomes. Metabolic reactions contributing to better immunotherapy responses were identified and used to establish the immuno-metabolic reaction score (IMRS). IMRS were significantly correlated to CD8+ T cell infiltration levels and CD8+ T cell signature scores in either 10× Visium spatial transcriptomic or RNA-seq samples. Finally, IMRS could significantly predict favorable survival outcomes in different cancer patients treated with immunotherapy. Our study revealed a link between certain metabolites and their related metabolic pathways to tumor immune landscape and immune functions. These results could promote the accurate stratification of patients before treatment and improve the efficacy of immunotherapy.

Analyze the Diversity and Function of Immune Cells in the Tumor Microenvironment From the Perspective of Single-Cell RNA Sequencing

BACKGROUND

Cancer development is closely associated with complex alterations in the tumor microenvironment (TME). Among these, immune cells within the TME play a huge role in personalized tumor diagnosis and treatment.

OBJECTIVES

This review aims to summarize the diversity of immune cells in the TME, their impact on patient prognosis and treatment response, and the contributions of single-cell RNA sequencing (scRNA-seq) in understanding their functional heterogeneity.

METHODS

We analyzed recent studies utilizing scRNA-seq to investigate immune cell populations in the TME, focusing on their interactions and regulatory mechanisms.

RESULTS

ScRNA-seq reveals the functional heterogeneity of immune cells, enhances our understanding of their role in tumor antibody responses, and facilitates the construction of immune cell interaction networks. These insights provide guidance for the development of cancer immunotherapies and personalized treatment approaches.

CONCLUSION

Applying scRNA-seq to immune cell analysis in the TME offers a novel pathway for personalized cancer treatment. Despite its promise, several challenges remain, highlighting the need for further advancements to fully integrate scRNA-seq into clinical applications.

Integrated ceRNAs regulating relationship and bioinformatics analysis to study the molecular mechanisms of the inhibition of puerarin on bladder cancer cell

Based on previous experiments, we demonstrated puerarin inhibited the proliferation of BC T24 cells. To further explore the molecular mechanisms, whole transcriptome sequencing combined with bioinformatics analysis was performed. The results showed puerarin significantly inhibited T24 proliferation and pathway enrichment analysis of differentially expressed RNAs were mainly enriched in Cell cycle, PI3K/AKT, Ras family chromatin remodeling. lncRNAs and circRNAs may regulate miRNAs, thereby regulating the expression of ITGA1, PAK2 and UTRN. The predicted upstream transcription factor ERG and puerarin were well docked, which may be one of the underlying mechanisms by which puerarin inhibiting BC cells.

Single-Cell RNA Sequencing Reveals the Tumor Heterogeneity and Immunosuppressive Microenvironment in Urothelial Carcinoma

Urothelial carcinoma (UC) can arise from either the lower urinary tract or the upper tract; they represent different disease entities and require different clinical treatment strategies. A full understanding of the cellular characteristics in UC may guide the development of novel therapies. Here, we performed single-cell transcriptome analysis from four patients with UC of the bladder (UCB), five patients with UC of the ureter (UCU), and four patients with UC of the renal pelvis (UCRP) to develop a comprehensive cell atlas of UC. We found the rare epithelial cell subtype EP9 with epithelial-to-mesenchymal transition (EMT) and cancer stem cell (CSC) features, and specifically expressed SOX6, which was associated with poor prognosis. We also found that ACKR1+ endothelial cells and inflammatory cancer-associated fibroblasts (iCAFs) were more enriched in UCU, which may promote pathogenesis. While ESM1+ endothelial cells may more actively participate in UCB and UCRP tumorigenesis by promoting angiogenesis. Additionally, CD8 + effector T cells were more enriched in UCU and UCRP patients, while Tregs were mainly enriched in UCB tumors. C1QC+ macrophages and LAMP3+ dendritic cells were more enriched in UCB, which is closely related to the formation of the heterogeneous immunosuppressive microenvironment. Furthermore, we found strong interactions between iCAFs, EP9, and Endo_ESM1, and different degrees of activation of the FGF-FGFR3 axis and immune checkpoint pathway were observed in different UC subtypes. Our study elucidated the cellular heterogeneity and the components of the microenvironment in UC arising from the upper and lower urinary tracts and provided novel therapeutic targets.

Biomarkers for predicting bladder cancer therapy response

The advent of precision medicine has underscored the importance of biomarkers in predicting therapy response for bladder cancer, a malignancy marked by considerable heterogeneity. This review critically examines the current landscape of biomarkers to forecast treatment outcomes in bladder cancer patients. We explore a range of biomarkers, including genetic, epigenetic, proteomic, and transcriptomic indicators, from multiple sample sources, including urine, tumor tissue and blood, assessing their efficacy in predicting responses to chemotherapy, immunotherapy, and targeted therapies. Despite promising developments, the translation of these biomarkers into clinical practice faces significant challenges, such as variability in biomarker performance, the necessity for large-scale validation studies, and the integration of biomarker testing into routine clinical workflows. We also highlight the need for standardized methodologies and robust assays to ensure consistency and reliability. Future directions point towards longitudinal studies and the development of combination biomarker panels to enhance predictive accuracy. This review emphasizes the transformative potential of predictive biomarkers in improving patient outcomes and advocates for continued collaborative efforts to overcome existing barriers in this rapidly evolving field.

Single-cell RNA sequencing and spatial transcriptome analysis in bladder cancer: Current status and future perspectives

Background

Bladder cancer is one of the most prevalent malignancies, and the mechanisms underlying its progression and the role of the tumor microenvironment (TME) are unclear. Recent advancements in single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) enable detailed analysis of the cellular heterogeneity, gene expression, and cell-cell interactions in bladder diseases.

Methodology

We conducted a comprehensive search for recent articles that have investigated bladder diseases using scRNA-seq and ST.

Results

scRNA-seq and ST have led to significant discoveries in bladder disease research. These technologies have enabled the identification of multiple molecular subtypes within individual tumors and of the mechanisms of treatment resistance. Additionally, molecular differences based on gender have been explored, explaining the heterogeneity of the incidence and progression of bladder cancer. These findings deepen our understanding of the pathology of bladder diseases and highlight the transformative potential of scRNA-seq and ST in identifying novel biomarkers and therapeutic targets.

Conclusions

Integrating scRNA-seq and ST has considerably enhanced our understanding of tumor heterogeneity and the tumor microenvironment within tissues. These insights may lead to the development of personalized therapies and the improvement of patient outcomes. Several challenges, such as technical limitations and access difficulties, need to be addressed for the future clinical application of these technologies.

Clinical Implications of Basic Research: Exploring the Transformative Potential of Spatial 'Omics in Uro-oncology

New spatial molecular technologies are poised to transform our understanding and treatment of urological cancers. By mapping the spatial molecular architecture of tumours, these platforms uncover the complex heterogeneity within and around individual malignancies, offering novel insights into disease development, progression, diagnosis, and treatment. They enable tracking of clonal phylogenetics in situ and immune-cell interactions in the tumour microenvironment. A whole transcriptome/genome/proteome-level spatial analysis is hypothesis generating, particularly in the areas of risk stratification and precision medicine. Current challenges include reagent costs, harmonisation of protocols, and computational demands. Nonetheless, the evolving landscape of the technology and evolving machine learning applications have the potential to overcome these barriers, pushing towards a future of personalised cancer therapy, leveraging detailed spatial cellular and molecular data. PATIENT SUMMARY: Tumours are complex and contain many different components. Although we have been able to observe some of these differences visually under the microscope, until recently, we have not been able to observe the genetic changes that underpin cancer development. Scientists are now able to explore molecular/genetic differences using approaches such as "spatial transcriptomics" and "spatial proteomics", which allow them to see genetic and cellular variation across a region of normal and cancerous tissue without destroying the tissue architecture. Currently, these technologies are limited by high associated costs, and a need for powerful and complex computational analysis workflows. Future advancements and results through these new technologies may assist patients and their doctors as they make decisions about treating their cancer.

Oncolytic immunotherapy with nivolumab in muscle-invasive bladder cancer: a phase 1b trial

There is a critical unmet need for safe and efficacious neoadjuvant treatment for cisplatin-ineligible patients with muscle-invasive bladder cancer. Here we launched a phase 1b study using the combination of intravesical cretostimogene grenadenorepvec (oncolytic serotype 5 adenovirus encoding granulocyte-macrophage colony-stimulating factor) with systemic nivolumab in cisplatin-ineligible patients with cT2-4aN0-1M0 muscle-invasive bladder cancer. The primary objective was to measure safety, and the secondary objective was to assess the anti-tumor efficacy as measured by pathologic complete response along with 1-year recurrence-free survival. No dose-limiting toxicity was encountered in 21 patients enrolled and treated. Combination treatment achieved a pathologic complete response rate of 42.1% and a 1-year recurrence-free survival rate of 70.4%. Pathologic response was associated with baseline free E2F activity and tumor mutational burden but not PD-L1 status. Although T cell infiltration was broadly induced after intravesical oncolytic immunotherapy, the formation, enlargement and maturation of tertiary lymphoid structures was specifically associated with complete response, supporting the importance of coordinated humoral and cellular immune responses. Together, these results highlight the potential of this combination regimen to enhance therapeutic efficacy in cisplatin-ineligible patients with muscle-invasive bladder cancer, warranting additional study as a neoadjuvant therapeutic option. ClinicalTrials.gov identifier: NCT04610671 .

Spatially-resolved analyses of muscle invasive bladder cancer microenvironment unveil a distinct fibroblast cluster associated with prognosis

Background

Muscle-invasive bladder cancer (MIBC) is a prevalent cancer characterized by molecular and clinical heterogeneity. Assessing the spatial heterogeneity of the MIBC microenvironment is crucial to understand its clinical significance.

Methods

In this study, we used imaging mass cytometry (IMC) to assess the spatial heterogeneity of MIBC microenvironment across 185 regions of interest in 40 tissue samples. We focused on three primary parameters: tumor (T), leading-edge (L), and nontumor (N). Cell gating was performed using the Cytobank platform. We calculated the Euclidean distances between cells to determine cellular interactions and performed single-cell RNA sequencing (scRNA-seq) to explore the molecular characteristics and mechanisms underlying specific fibroblast (FB) clusters. scRNA-seq combined with spatial transcriptomics (ST) facilitated the identification of ligand-receptor (L-R) pairs that mediate interactions between specific FB clusters and endothelial cells. Machine learning algorithms were used to construct a prognostic gene signature.

Results

The microenvironments in the N, L, and T regions of MIBC exhibited spatial heterogeneity and regional diversity in their components. A distinct FB cluster located in the L region-identified as S3-is strongly associated with poor prognosis. IMC analyses demonstrated a close spatial association between S3 and endothelial cells, with S3-positive tumors exhibiting increased blood vessel density and altered vascular morphology. The expression of vascular endothelial growth factor receptor and active vascular sprouting were significant in S3-positive tumors. scRNA-seq and ST analyses indicated that the genes upregulated in S3 were associated with angiogenesis. NOTCH1-JAG2 signaling pathway was identified as a significant L-R pair specific to S3 and endothelial cell interactions. Further analysis indicated that YAP1 was a potential regulator of S3. Machine learning algorithms and Gene Set Variation Analysis were used to establish an S3-related gene signature that was associated with the poor prognosis of tumors including MIBC, mesothelioma, glioblastoma multiforme, lower-grade glioma, stomach adenocarcinoma, uveal melanoma, kidney renal clear cell carcinoma, kidney renal papillary cell carcinoma, and lung squamous cell carcinoma.

Conclusions

We assessed the spatial landscape of the MIBC microenvironment and revealed a specific FB cluster with prognostic potential. These findings offer novel insights into the spatial heterogeneity of the MIBC microenvironment and highlight its clinical significance.

Single-cell dissection of multifocal bladder cancer reveals malignant and immune cells variation between primary and recurrent tumor lesions

Bladder carcinoma (BLCA) is characterized by a high rate of post-surgery recurrence and multifocality. Multifocal tumors have a higher risk of recurrence compared to single tumors, significantly impacting bladder cancer-specific mortality. However, the interregional or intraregional heterogeneity within both primary and recurrent tumors remains poorly understood. Here, we employed single-cell RNA sequencing to analyze tumor lesions from five multifocal bladder cancer patients comprising three primary tumors and two recurrent tumors. Our findings revealed that malignant cells derived from recurrent multifocal bladder cancer exhibited higher interregional transcriptional similarity and consistent cellular communication. Furthermore, our analysis uncovered that malignant cells from recurrent tumors may evade immune destruction by suppressing cytokine responses and natural killer cell activity. Notably, we identified a preference for the expression of the tryptophan metabolic enzyme IL4I1 on SPP1+ macrophages in recurrent tumors. Functional analyses have revealed that IL4I1 may promotes tumor progression in recurrent tumors by activating the aryl hydrocarbon receptor (AHR) and recruiting regulatory T cells to suppress adaptive immunity. Taken together, our study provides a comprehensive understanding of primary and recurrent multifocal bladder tumors, offering valuable resources for analyzing the multifocality and recurrence of bladder cancer.

The implications for urological malignancies of non-coding RNAs in the the tumor microenvironment

Urological malignancies are a major global health issue because of their complexity and the wide range of ways they affect patients. There's a growing need for in-depth research into these cancers, especially at the molecular level. Recent studies have highlighted the importance of non-coding RNAs (ncRNAs) – these don't code for proteins but are crucial in controlling genes – and the tumor microenvironment (TME), which is no longer seen as just a background factor but as an active player in cancer progression. Understanding how ncRNAs and the TME interact is key for finding new ways to diagnose and predict outcomes in urological cancers, and for developing new treatments. This article reviews the basic features of ncRNAs and goes into detail about their various roles in the TME, focusing specifically on how different ncRNAs function and act in urological malignancies.

Single cell analysis identified a basal cell transition state associated with the development and progression of bladder cancer

BACKGROUND

Bladder cancer (BC) is a prevalent malignancy characterized by significant cellular heterogeneity. While single-cell multi-omics studies have provided valuable insights, much of the existing data remains underexplored, limiting our understanding of BC's molecular mechanisms. Uncovering the pathogenesis of BC and finding new treatment methods are urgent problems to be solved. This study aims to address this gap by re-analyzing available single-cell datasets to uncover novel insights into BC.

METHODS

In this study, we retrieved three single-cell transcriptome datasets by searching the Gene Expression Omnibus (GEO) database, focusing on single-cell sequencing of normal mouse bladder within the past 5 years. Through quality control and batch effect elimination, we obtained a total of 24,930 cells including epithelial, stromal, and immune cells. Subgroup analysis, pseudotemporal analysis, cell-cell communication, and transcription factor analysis were conducted specifically on epithelial cells to identify a transitional state during basal cell differentiation. We further compared the expression profiles of key transcription factors in cancer and normal tissues. In addition, we also performed immunohistochemical staining and survival analysis for key transcription factors.

RESULTS

Subgroup analysis revealed multiple subtypes of epithelial cells, including basal, umbrella, and intermediate cells. Through pseudotemporal analysis, we discovered the developmental trajectory from basal cells to umbrella cells and further found that Basal_I is a transitional state for basal cell differentiation. Cell-to-cell communication analyses highlighted the pivotal role of Basal_I in cell-cell interactions, and key ligand-receptor pairs associated with cancer progression were also identified. Furthermore, elevated expression levels of key transcription factors in Basal_I were found to be closely associated with the stage and prognosis of BC. Immunohistochemical staining results further confirmed the upregulated expression of these transcription factors in BC.

CONCLUSIONS

Collectively, we found a transitional state of basal cells in normal bladder epithelial cells in mice, which may be related to the occurrence and development of BC, providing important clues for further understanding of the pathogenesis of BC. Our study provided possible molecular mechanisms or target for the research and treatment of BC.

Bladder cancer immune-related markers: diagnosis, surveillance, and prognosis

As an immune-related tumor type, bladder cancer has been attracting much attention in the study of its markers. In recent years, researchers have made rapid progress in the study of immune-related markers for bladder cancer. Studies have shown that immune-related markers play an important role in the diagnosis, prognosis assessment and treatment of bladder cancer. In addition, the detection of immune-related markers can also be used to evaluate the efficacy of immunotherapy and predict the treatment response of patients. Therefore, in depth study of the expression of immune-related markers in bladder cancer and their application in the clinic is of great significance and is expected to provide new breakthroughs for individualized treatment of bladder cancer. Future studies will focus more on how to detect immune-related markers with low cost and high accuracy, as well as develop new immunotherapeutic strategies to bring better therapeutic outcomes to bladder cancer patients.

Efficacy and safety analysis of neoadjuvant chemotherapy combined with immunotherapy in patients with muscle-invasive bladder cancer

Introduction

This study examined the efficacy and safety of neoadjuvant chemotherapy combined with immunotherapy in patients with muscle-invasive bladder cancer (MIBC).

Methods

This retrospective cohort study included patients diagnosed with MIBC at the First Affiliated Hospital of Soochow University between January 1, 2020, and December 31, 2023, assigned to either chemotherapy (gemcitabine with cisplatin) or combination (chemotherapy plus toripalimab or tislelizumab) groups based on the neoadjuvant treatment regimen. Key metrics, including pathological downstaging rate (PDR), pathological complete response rate (PCRR), and incidence and severity of adverse events (AEs), were compared between groups.

Results

This study included 53 patients (mean age: 67.21 years). In the combination group, 14 patients (51.85%) achieved pathological complete remission (ypT0), and seven (25.93%) achieved partial remission (ypT1), resulting in a PDR and PCRR of 77.78 and 51.85%, respectively. In the chemotherapy group, six patients (23.08%) achieved complete remission, and five (19.23%) achieved partial remission, resulting in a PDR and PCRR of 42.31 and 23.08%, respectively. Differences between groups were statistically significant (p < 0.05). There were no significant differences in pathological downstaging or complete remission rates among subgroups in the combination group (p > 0.05). No serious allergic reactions or fatal AEs were detected in either group, with no grade 4 AEs. Grade 3 AE rates were 22.22 and 20.83% in the combination and chemotherapy groups, respectively, although non-significant (p > 0.05).

Conclusion

Neoadjuvant chemotherapy combined with immunotherapy had enhanced efficacy and manageable safety in patients with MIBC, suggesting its potential for integration into clinical practice.

Spatial transcriptomics in pancreatic cancer: Advances, prospects and challenges

Pancreatic cancer remains one of the deadliest malignancies with an overall 5-year survival rate of 13 %. This dismal fact can be partly attributed to currently limited understanding of tumor heterogeneity and immune microenvironment. Traditional bulk-sequencing techniques overlook the diversity of tumor cells, while single-cell sequencing disorganizes the position localizing of cells in tumor microenvironment. The advent of spatial transcriptomics (ST) presents a novel solution by integrating location and whole transcript expression information. This technology allows for detailed observation of spatio-temporal changes across various cell subtypes within the pancreatic tumor microenvironment, providing insights into their potential functions. This review offers an overview of recent studies implementing ST in pancreatic cancer research, highlighting its instrumental role in investigating the heterogeneity and functions of tumor cells, stromal cells, and immune cells. On the basis, we also prospected and summarized the clinical application scenarios, technical limitations and challenges of ST technology in pancreatic cancer.

FTO/IGF2BP2-mediated N6 methyladenosine modification in invasion and metastasis of thyroid carcinoma via CDH12

Epigenetic reprogramming plays a critical role in cancer progression of cancer, and N6-methyladenosine (m6A) is the most common RNA modification in eukaryotes. The purpose of this study was to explore the related modification mode of m6A regulator construction and evaluate the invasion and migration of thyroid cancer. Our results showed that m6A levels were significantly increased in papillary thyroid cancer (PTC) and anaplastic thyroid cancer (ATC) samples, which may have been induced by the down-regulation of demethylase fat mass and obesity-associated gene (FTO). Moreover, FTO inhibited PTC and ATC invasion and metastasis through the epithelial-to-mesenchymal transition (EMT) pathway in vivo and in vitro. Mechanistically, an m6A-mRNA epitranscriptomic microarray showed that Cadherin 12 (CDH12) is the key target gene mediated by FTO in an m6A-dependent manner. CDH12 promotes invasion and metastasis through the EMT pathway in thyroid cancer, both in vivo and in vitro. Furthermore, we found that insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2) is an important m6A reading protein, that regulates the stability of CDH12 mRNA and mediates EMT progression, thereby promoting the invasion and metastasis of PTC and ATC. Thus, FTO, IGF2BP2 and CDH12 may be effective therapeutic targets for PTC and ATC with significant invasion or distant metastasis. Schematic summary of FTO-IGF2BP2 axis in modulation of CDH12 mRNA m6A and upregulation of CDH12 expression in the invasion and metastasis of thyroid carcinoma.

Multi-omics analysis unveils the predictive value of IGF2BP3/SPHK1 signaling in cancer stem cells for prognosis and immunotherapeutic response in muscle-invasive bladder cancer

BACKGROUND

Muscle invasive bladder cancer (MIBC) is a life-threatening malignant tumor characterized by high metastasis rates, poor prognosis, and limited treatment options. Immune checkpoint inhibitors (ICIs) targeting PD-1 and PD-L1 represent an emerging treatment for MIBC immunotherapy. However, the characteristics of patients likely to benefit from immunotherapy remain unclear.

METHODS

We performed single-cell mass cytometry (CyTOF) analysis of 179,483 single cells to characterize potential immunotherapy-related cancer stem cells (CSCs)-like populations in the tumor microenvironment of 38 MIBC tissues. The upregulated expression of IGF2BP3 in CD274 + ALDH + CSC-like cells, which was associated with poor clinical prognosis, was analyzed by bulk RNA-sequencing data from an in-house cohort. The functional role of IGF2BP3 was determined through cell proliferation, colony formation, cell apoptosis and sphere formation assays. The regulation of SPHK1 expression by IGF2BP3 was  investigated using methylated RNA immunoprecipitation sequencing (MeRIP-seq) and bulk RNA-sequencing (bulk RNA-seq). We further utilized single-nucleus RNA sequencing (snRNA-seq) data from 67,988 cells of 25 MIBC tissues and single-cell RNA sequencing (scRNA-seq) data from MIBC patient-derived organoids to characterize the molecular features of bladder cancer cells co-expressing IGF2BP3 and SPHK1. Spatial transcriptomics (ST) and co-detection by indexing (CODEX) analysis were used to describe the spatial distribution and interactions of IGF2BP3 + SPHK1 + bladder cancer cells and immune cells.

RESULTS

A subset of CD274 + ALDH + CSC-like cells was identified, associating with immunosuppression and low survival rates in MIBC patients. IGF2BP3, an m6A reader gene, was found to be upregulated in the CD274 + ALDH + CSC-like cell population and linked to poor clinical prognosis in MIBC. Knockout of IGF2BP3 dramatically promoted cell apoptosis and reduced cell proliferation in T24 cells. By integrating MeRIP-seq and bulk RNA-seq analyses, we identified SPHK1 served as a substrate for IGF2BP3 in an m6A-dependent manner. Further snRNA-seq, scRNA-seq, ST, and CODEX analysis revealed a closer topographical distance between IGF2BP3 + SPHK1 + bladder cancer cells and exhausted CD8 + T cells, providing one explanation for the superior response to immunotherapy in IGF2BP3 + SPHK1 + bladder cancer cells-enriched patients. Finally, an ICI-associated signature was developed based on the enriched genes of IGF2BP3 + SPHK1 + bladder cancer cells, and its potential ability to predict the response to immunotherapy was validated in two independent immunotherapy cohort.

CONCLUSIONS

Our study highlighted the critical involvement of the IGF2BP3/SPHK1 signaling in maintaining the stemness of CSCs and promoting MIBC progression. Additionally, these findings suggested that the IGF2BP3/SPHK1 signaling might serve as a biomarker for prognosis and immunotherapy response in MIBC.

Advances in spatial multi-omics in tumors

Single-cell techniques have convincingly demonstrated that tumor tissue usually contains multiple genetically defined cell subclones with different gene mutation sets as well as various transcriptional profiles, but the spatial heterogeneity of the microenvironment and the macrobiological characteristics of the tumor ecosystem have not been described. For the past few years, spatial multi-omics technologies have revealed the cellular interactions, microenvironment, and even systemic tumor-host interactions in the tumor ecosystem at the spatial level, which can not only improve classical therapies such as surgery, radiotherapy, and chemotherapy but also promote the development of emerging targeted therapies in immunotherapy. Here, we review some emerging spatial omics techniques in cancer research and therapeutic applications and propose prospects for their future development.

Biomarkers of treatment response in bladder cancer

INTRODUCTION

There have been many recent advancements in the treatment of bladder cancer including the approval of novel intravesical agents for non-muscle-invasive disease and systemic-targeted therapeutics for muscle-invasive and advanced disease. However, treatment strategies for bladder cancer are still largely based on clinicopathologic characteristics.

AREAS COVERED

Based on primary literature sourced from PubMed, Embase, and Cochrane Library, we review the current status of molecular markers and biomarker panels with respective to their value in predicting response to standard chemotherapeutics and novel agents in non-muscle-invasive, muscle-invasive, and advanced bladder cancer.

EXPERT OPINION

Several biomarkers based on molecular characterization of tumors and quantification of circulating tumor DNA have been associated with response or resistance to standard chemotherapeutics. More recent investigations have reported on predictive biomarkers for novel therapeutics in bladder cancer, although large-scale validation is still needed. Given the increasing therapeutic options for this disease, employment of such predictive biomarkers may help guide treatment selection and sequencing.

Single-cell RNA-binding protein pattern-mediated molecular subtypes depict the hallmarks of the tumor microenvironment in bladder urothelial carcinoma

Objectives

Bladder carcinoma (BC) is a common malignancy of the urinary tract. As a new hallmark of cancer for drug therapy, RNA-binding proteins (RBPs) are key regulatory factors in alternative splicing events. This work is to uncover the relationship between BC and RBP in order to find drug targets in BC.

Methods

In this work, data from single-cell RNA-seq GSE1355337, PRJNA662018, and the TCGA-Bladder urothelial carcinoma (BLCA) cohorts are integrated to identify their relationships. A scoring system is constructed according to RBPs gene expression and patients’ survival. A network is constructed to analyze the alternative splicing events and RBP genes.

Results

A scoring system identified 321 RBPs significantly associated with the prognosis of patients. Subsequent typing of these RBP genes in two single-cell datasets demonstrated that most of the RBP genes had variable copy numbers. Three RBP clusters were identified. Using RBP genes as a signature in BC epithelial cells allows for differentiation between different grades of BC samples. The novel RBP genes-based subtype system reflects BC clinical staging. Notably, CellChat analysis revealed that the RBP genes-associated cell subtypes of T cells had extensive interactions with epithelial cells. Further analysis showed that the ligand-receptor pair MIF-CXCR4 mediated the communication between RBP-associated subtypes of BC epithelial cells and T cells.

Conclusions

Taken together, RBP genes are associated with BC progress and offer new indicators for precision medicine in BC.

Spatially Resolved Single-Cell Omics: Methods, Challenges, and Future Perspectives

Overlaying omics data onto spatial biological dimensions has been a promising technology to provide high-resolution insights into the interactome and cellular heterogeneity relative to the organization of the molecular microenvironment of tissue samples in normal and disease states. Spatial omics can be categorized into three major modalities: (a) next-generation sequencing-based assays, (b) imaging-based spatially resolved transcriptomics approaches including in situ hybridization/in situ sequencing, and (c) imaging-based spatial proteomics. These modalities allow assessment of transcripts and proteins at a cellular level, generating large and computationally challenging datasets. The lack of standardized computational pipelines to analyze and integrate these nonuniform structured data has made it necessary to apply artificial intelligence and machine learning strategies to best visualize and translate their complexity. In this review, we summarize the currently available techniques and computational strategies, highlight their advantages and limitations, and discuss their future prospects in the scientific field.

Signaling dynamics in coexisting monoclonal cell subpopulations unveil mechanisms of resistance to anti-cancer compounds

BACKGROUND

Tumor heterogeneity is a main contributor of resistance to anti-cancer targeted agents though it has proven difficult to study. Unfortunately, model systems to functionally characterize and mechanistically study dynamic responses to treatment across coexisting subpopulations of cancer cells remain a missing need in oncology.

METHODS

Using single cell cloning and expansion techniques, we established monoclonal cell subpopulations (MCPs) from a commercially available epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancer cell line. We then used this model sensitivity to the EGFR inhibitor osimertinib across coexisting cell populations within the same tumor. Pathway-centered signaling dynamics associated with response to treatment and morphological characteristics of the MCPs were assessed using Reverse Phase Protein Microarray. Signaling nodes differentially activated in MCPs less sensitive to treatment were then pharmacologically inhibited to identify target signaling proteins putatively implicated in promoting drug resistance.

RESULTS

MCPs demonstrated highly heterogeneous sensitivities to osimertinib. Cell viability after treatment increased > 20% compared to the parental line in selected MCPs, whereas viability decreased by 75% in other MCPs. Reduced treatment response was detected in MCPs with higher proliferation rates, EGFR L858R expression, activation of EGFR binding partners and downstream signaling molecules, and expression of epithelial-to-mesenchymal transition markers. Levels of activation of EGFR binding partners and MCPs' proliferation rates were also associated with response to c-MET and IGFR inhibitors.

CONCLUSIONS

MCPs represent a suitable model system to characterize heterogeneous biomolecular behaviors in preclinical studies and identify and functionally test biological mechanisms associated with resistance to targeted therapeutics.

Single-cell spatial multiomics reveals tumor microenvironment vulnerabilities in cancer resistance to immunotherapy

Heterogeneous resistance to immunotherapy remains a major challenge in cancer treatment, often leading to disease progression and death. Using CITE-seq and matched 40-plex PhenoCycler tissue imaging, we performed longitudinal multimodal single-cell analysis of tumors from metastatic melanoma patients with innate resistance, acquired resistance, or response to immunotherapy. We established the multimodal integration toolkit to align transcriptomic features, cellular epitopes, and spatial information to provide deeper insights into the tumors. With longitudinal analysis, we identified an "immune-striving" tumor microenvironment marked by peri-tumor lymphoid aggregates and low infiltration of T cells in the tumor and the emergence of MITF+SPARCL1+ and CENPF+ melanoma subclones after therapy. The enrichment of B cell-associated signatures in the molecular composition of lymphoid aggregates was associated with better survival. These findings provide further insights into the establishment of microenvironmental cell interactions and molecular composition of spatial structures that could inform therapeutic intervention.

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.

Spatial Dissection of the Immune Landscape of Solid Tumors to Advance Precision Medicine

Chemotherapeutics, radiation, targeted therapeutics, and immunotherapeutics each demonstrate clinical benefits for a small subset of patients with solid malignancies. Immune cells infiltrating the tumor and the surrounding stroma play a critical role in shaping cancer progression and modulating therapy response. They do this by interacting with the other cellular and molecular components of the tumor microenvironment. Spatial multi-omics technologies are rapidly evolving. Currently, such technologies allow high-throughput RNA and protein profiling and retain geographical information about the tumor microenvironment cellular architecture and the functional phenotype of tumor, immune, and stromal cells. An in-depth spatial characterization of the heterogeneous tumor immune landscape can improve not only the prognosis but also the prediction of therapy response, directing cancer patients to more tailored and efficacious treatments. This review highlights recent advancements in spatial transcriptomics and proteomics profiling technologies and the ways these technologies are being applied for the dissection of the immune cell composition in solid malignancies in order to further both basic research in oncology and the implementation of precision treatments in the clinic.

Advances in the Clinical Application of High-throughput Proteomics

High-throughput proteomics has become an exciting field and a potential frontier of modern medicine since the early 2000s. While significant progress has been made in the technical aspects of the field, translating proteomics to clinical applications has been challenging. This review summarizes recent advances in clinical applications of high-throughput proteomics and discusses the associated challenges, advantages, and future directions. We focus on research progress and clinical applications of high-throughput proteomics in breast cancer, bladder cancer, laryngeal squamous cell carcinoma, gastric cancer, colorectal cancer, and coronavirus disease 2019. The future application of high-throughput proteomics will face challenges such as varying protein properties, limitations of statistical modeling, technical and logistical difficulties in data deposition, integration, and harmonization, as well as regulatory requirements for clinical validation and considerations. However, there are several noteworthy advantages of high-throughput proteomics, including the identification of novel global protein networks, the discovery of new proteins, and the synergistic incorporation with other omic data. We look forward to participating in and embracing future advances in high-throughput proteomics, such as proteomics-based single-cell biology and its clinical applications, individualized proteomics, pathology informatics, digital pathology, and deep learning models for high-throughput proteomics. Several new proteomic technologies are noteworthy, including data-independent acquisition mass spectrometry, nanopore-based proteomics, 4-D proteomics, and secondary ion mass spectrometry. In summary, we believe high-throughput proteomics will drastically shift the paradigm of translational research, clinical practice, and public health in the near future.

Recent contributions of single-cell and spatial profiling to the understanding of bladder cancer

PURPOSE OF REVIEW

Current risk stratification and treatment decision-making for bladder cancer informed by histopathology as well as molecular diagnostics face limitations. This review summarizes recent advancements in single-cell and spatial omics methodologies for understanding bladder cancer biology and their potential impact on development of novel therapeutic strategies.

RECENT FINDINGS

Single-cell RNA sequencing and spatial omics techniques offer unprecedented insights into various aspects of tumor microenvironment (TME), bladder cancer heterogeneity, cancer stemness, and cellular plasticity. Studies have identified multiple malignant cell subpopulations within tumors, revealing diverse transcriptional states and clonal evolution. Additionally, intratumor heterogeneity has been linked to tumor progression and therapeutic response. Immune cell composition analysis has revealed immunosuppressive features in the TME, impacting treatment response. Furthermore, studies have elucidated the role of cancer-associated fibroblasts and endothelial cells in shaping the tumor immune landscape and response to therapy.

SUMMARY

Single-cell and spatial omics technologies have revolutionized our understanding of bladder cancer biology, uncovering previously unseen complexities. These methodologies provide valuable insights into tumor heterogeneity and microenvironmental interactions, with implications for therapeutic development. However, challenges remain in translating research findings into clinical practice and implementing personalized treatment strategies. Continued interdisciplinary collaboration and innovation are essential for overcoming these challenges and leveraging the full potential of single-cell and spatial omics in improving bladder cancer diagnosis and treatment.

Spatial Transcriptomics: A Powerful Tool in Disease Understanding and Drug Discovery

Recent advancements in modern science have provided robust tools for drug discovery. The rapid development of transcriptome sequencing technologies has given rise to single-cell transcriptomics and single-nucleus transcriptomics, increasing the accuracy of sequencing and accelerating the drug discovery process. With the evolution of single-cell transcriptomics, spatial transcriptomics (ST) technology has emerged as a derivative approach. Spatial transcriptomics has emerged as a hot topic in the field of omics research in recent years; it not only provides information on gene expression levels but also offers spatial information on gene expression. This technology has shown tremendous potential in research on disease understanding and drug discovery. In this article, we introduce the analytical strategies of spatial transcriptomics and review its applications in novel target discovery and drug mechanism unravelling. Moreover, we discuss the current challenges and issues in this research field that need to be addressed. In conclusion, spatial transcriptomics offers a new perspective for drug discovery.

Single-cell and multi-omics analyses highlight cancer-associated fibroblasts-induced immune evasion and epithelial mesenchymal transition for smoking bladder cancer

Tobacco carcinogens are recognized as critical hazard factors for bladder tumorigenesis, affecting the prognosis of patients through aromatic amines components. However, the specific function of tobacco carcinogens and systematic assessment models in the prognosis of bladder cancer remains poorly elucidated. We retrieved bladder cancer specific tobacco carcinogens-related genes from Comparative Toxicogenomic Database, our Nanjing Bladder Cancer cohort and TCGA database. Gene×Gene interaction method was utilized to establish a prognostic signature. Integrative assessment of immunogenomics, tumor microenvironments and single-cell RNA-sequencing were performed to illustrate the internal relations of key events from different levels. Finally, we comprehensively identified 33 essential tobacco carcinogens-related genes to construct a novel prognostic signature, and found that high-risk patients were characterized by significantly worse overall survival (HR=2.25; Plog-rank < 0.01). Single-cell RNA-sequencing and multi-omics analysis demonstrated that cancer-associated fibroblasts mediated the crosstalk between epithelial-mesenchymal transition progression and immune evasion. Moreover, an adverse outcome pathway framework was established to facilitate our understanding to the tobacco carcinogens-triggered bladder tumorigenesis. Our study systematically provided immune microenvironmental alternations for smoking-induced adverse survival outcomes in bladder cancer. These findings facilitated the integrative multi-omics insights into risk assessment and toxic mechanisms of tobacco carcinogens.

Tumor immune dysfunction and exclusion subtypes in bladder cancer and pan-cancer: a novel molecular subtyping strategy and immunotherapeutic prediction model

BACKGROUND

Molecular subtyping is expected to enable precise treatment. However, reliable subtyping strategies for clinical application remains defective and controversial. Given the significance of tumor immune dysfunction and exclusion (TIDE), we aimed to develop a novel TIDE-based subtyping strategy to guide personalized immunotherapy in the bladder cancer (BC).

METHODS

Transcriptome data of BC was used to evaluate the heterogeneity and the status of TIDE patterns. Subsequently, consensus clustering was applied to classify BC patients based on TIDE marker-genes. Patients' clinicopathological, molecular features and signaling pathways of the different TIDE subtypes were well characterized. We also utilize the deconvolution algorithms to analyze the tumor microenvironment, and further explore the sensitivity and mechanisms of each subtype to immunotherapy. Furthermore, BC patient clinical information, real-world BC samples and urine samples were collected for the validation of our findings, which were used for RNA-seq analysis, H&E staining, immunohistochemistry and immunofluorescence staining, and enzyme-linked immunosorbent assay. Finally, we also explored the conservation of our novel TIDE subtypes in pan-cancers.

RESULTS

We identified 69 TIDE biomarker genes and classified BC samples into three subtypes using consensus clustering. Subtype I showed the lowest TIDE status and malignancy with the best prognosis and highest sensitivity to immune checkpoint blockade (ICB) treatment, which was enriched of metabolic related signaling pathways. Subtype III represented the highest TIDE status and malignancy with the poorest prognosis and resistance to ICB treatment, resulting from its inhibitory immune microenvironment and T cell terminal exhaustion. Subtype II was in a transitional state with intermediate TIDE level, malignancy, and prognosis. We further confirmed the existence and characteristics of our novel TIDE subtypes using real-world BC samples and collected patient clinical data. This subtyping method was proved to be more efficient than previous known methods in identifying non-responders to immunotherapy. We also propose that combining our TIDE subtypes with known biomarkers can potentially improve the sensitivity and specificity of these biomarkers. Moreover, besides guiding ICB treatment, this classification approach can assist in selecting the frontline or recommended drugs. Finally, we confirmed that the TIDE subtypes are conserved across the pan-tumors.

CONCLUSIONS

Our novel TIDE-based subtyping method can serve as a powerful clinical tool for BC and pan-cancer patients, and potentially guiding personalized therapy decisions for selecting potential beneficiaries and excluding resistant patients of ICB therapy.

The potential role of precision medicine to alleviate racial disparities in prostate, bladder and renal urological cancer care

Background

Racial disparities in oncological outcomes resulting from differences in social determinants of health (SDOH) and tumour biology are well described in prostate cancer (PCa) but similar inequities exist in bladder (BCa) and renal cancers (RCCs). Precision medicine (PM) aims to provide personalized treatment based on individual patient characteristics and has the potential to reduce these inequities in GU cancers.

Objective

This article aims to review the current evidence outlining racial disparities in GU cancers and explore studies demonstrating improved oncological outcomes when PM is applied to racially diverse patient populations.

Evidence acquisition

Evidence was obtained from Pubmed and Web of Science using keywords prostate, bladder and renal cancer, racial disparity and precision medicine. Because limited studies were found, preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines were not applied but rather related articles were studied to explore existing debates, identify the current status and speculate on future applications.

Results

Evidence suggests addressing SDOH for PCa can reverse racial inequities in oncological outcomes but differences in incidence remain. Similar disparities in BCa and RCC are seen, and it would be reasonable to suggest achieving parity in SDOH for all races would do the same. Research applying a PM approach to different ethnicities is lacking although in African Americans (AAs) with metastatic castrate-resistant prostate cancer (mCRPCa) better outcomes have been shown with androgen receptor inhibitors, radium-223 and sipuleucel. Exploiting the abscopal effect with targeted radiation therapy (RT) and immunotherapy has promise but requires further study, as does defining actionable mutations in specific patient groups to tailor treatments as appropriate.

Conclusion

For all GU cancers, the historical underrepresentation of ethnic minorities in clinical trials still exists and there is an urgent need for recruitment strategies to address this. PM is a promising development with the potential to reduce inequities in GU cancers, however, both improved understanding of race-specific tumour biology, and enhanced recruitment of minority populations into clinical trials are required. Without this, the benefits of PM will be limited.

Redefining clinical practice through spatial profiling: a revolution in tissue analysis

Spatial biology, which combines molecular biology and advanced imaging, enhances our understanding of tissue cellular organisation. Despite its potential, spatial omics encounters challenges related to data complexity, computational requirements and standardisation of analysis. In clinical applications, spatial omics has the potential to revolutionise biomarker discovery, disease stratification and personalised treatments. It can identify disease-specific cell patterns, and could help risk stratify patients for clinical trials and disease-appropriate therapies. Although there are challenges in adopting it in clinical practice, spatial omics has the potential to significantly enhance patient outcomes. In this paper, we discuss the recent evolution of spatial biology, and its potential for improving our tissue level understanding and treatment of disease, to help advance precision and effectiveness in healthcare interventions.

Spatial proximity of tumor-immune interactions predicts patient outcome in hepatocellular carcinoma

BACKGROUND AND AIMS

The fitness and viability of a tumor ecosystem are influenced by the spatial organization of its cells. We aimed to study the structure, architecture, and cell-cell dynamics of the heterogeneous liver cancer tumor microenvironment using spatially resolved multiplexed imaging.

APPROACH AND RESULTS

We performed co-detection by indexing multiplexed immunofluorescence imaging on 68 HCC biopsies from Thai patients [(Thailand Initiative in Genomics and Expression Research for Liver Cancer (TIGER-LC)] as a discovery cohort, and then validated the results in an additional 190 HCC biopsies from Chinese patients [Liver Cancer Institute (LCI)]. We segmented and annotated 117,270 and 465,632 cells from the TIGER-LC and LCI cohorts, respectively. We observed 4 patient groups of TIGER-LC (IC1, IC2, IC3, and IC4) with distinct tumor-immune cellular interaction patterns. In addition, patients from IC2 and IC4 had much better overall survival than those from IC1 and IC3. Noticeably, tumor and CD8 + T-cell interactions were strongly enriched in IC2, the group with the best patient outcomes. The close proximity between the tumor and CD8 + T cells was a strong predictor of patient outcome in both the TIGER-LC and the LCI cohorts. Bulk transcriptomic data from 51 of the 68 HCC cases were used to determine tumor-specific gene expression features of our classified subtypes. Moreover, we observed that the presence of immune spatial neighborhoods in HCC as a measure of overall immune infiltration is linked to better patient prognosis.

CONCLUSIONS

Highly multiplexed imaging analysis of liver cancer reveals tumor-immune cellular heterogeneity within spatial contexts, such as tumor and CD8 + T-cell interactions, which may predict patient survival.

In situ characterization of the tumor microenvironment

The development of new therapies for cancer is underpinned by an increasing need to comprehensively characterize the tumor microenvironment (TME). While traditional approaches have relied on bulk or single-cell approaches, these are limited in their ability to provide cellular context. Deconvolution of the complex TME is fundamental to understanding tumor dynamics and treatment resistance. Spatially resolved characterization of the TME is likely to provide greater insights into the cellular architecture, tumor-immune cell interactions, receptor-ligand interactions, and cell niches. In turn, these aid in dictating the optimal way in which to target each patient's individual cancer. In this review, we discuss a number of cutting-edge in situ spatial profiling methods giving us new insights into tumor biology.

Clinical implications of single cell sequencing for bladder cancer

Bladder cancer (BC) is the 10th most common cancer worldwide, with about 0.5 million reported new cases and about 0.2 million deaths per year. In this scoping review, we summarize the current evidence regarding the clinical implications of single-cell sequencing for bladder cancer based on PRISMA guidelines. We searched PubMed, CENTRAL, Embase, and supplemented with manual searches through the Scopus, and Web of Science for published studies until February 2023. We included original studies that used at least one single-cell technology to study bladder cancer. Forty-one publications were included in the review. Twenty-nine studies showed that this technology can identify cell subtypes in the tumor microenvironment that may predict prognosis or response to immune checkpoint inhibition therapy. Two studies were able to diagnose BC by identifying neoplastic cells through single-cell sequencing urine samples. The remaining studies were mainly a preclinical exploration of tumor microenvironment at single cell level. Single-cell sequencing technology can discriminate heterogeneity in bladder tumor cells and determine the key molecular properties that can lead to the discovery of novel perspectives on cancer management. This nascent tool can advance the early diagnosis, prognosis judgment, and targeted therapy of bladder cancer.

Transcriptome Analysis Reveals Distinct Patterns Between the Invasive and Noninvasive Pituitary Neuroendocrine Tumors

Although most pituitary neuroendocrine tumors (PitNETs)/pituitary adenomas remain intrasellar, a significant proportion of tumors show parasellar invasive growth and 6% to 8% infiltrate the bone structures, thus affecting the prognosis. There is an unmet need to identify novel markers that can predict the parasellar growth of PitNETs. Furthermore, mechanisms that regulate bone invasiveness of PitNETs and factors related to tumor vascularization are largely unknown. We used genome-wide mRNA analysis in a cohort of 77 patients with PitNETs of different types to explore the differences in gene expression patterns between invasive and noninvasive tumors with respect to the parasellar growth and regarding the rare phenomenon of bone invasiveness. Additionally, we studied the genes correlated to the contrast enhancement quotient, a novel radiological parameter of tumor vascularization. Most of the genes differentially expressed related to the parasellar growth were genes involved in tumor invasiveness. Differentially expressed genes associated with bone invasiveness are involved in NF-κB pathway and antitumoral immune response. Lack of clear clustering regarding the parasellar and bone invasiveness may be explained by the influence of the cell lineage-related genes in this heterogeneous cohort of PitNETs. Our transcriptomics analysis revealed differences in the molecular fingerprints between invasive, including bone invasive, and noninvasive PitNETs, although without clear clustering. The contrast enhancement quotient emerged as a radiological parameter of tumor vascularization, correlating with several angiogenesis-related genes. Several of the top genes related to the PitNET invasiveness and vascularization have potential prognostic and therapeutic application requiring further research.

Tissue biomarkers of immune checkpoint inhibitor therapy

Cancer immunotherapy has been rejuvenated by the growing understanding of the immune system's role in tumor activity over the past two decades. During cancer initiation and progression, tumor cells employ various mechanisms that resemble peripheral immune tolerance to evade the antitumor responses of the immune system. Immune checkpoint molecules are the major mechanism of immune resistance that are exploited by tumor cells to inhibit T-cell activation and suppress immune responses. The targeting of immune checkpoint pathways has led to substantial improvements in survival rates in a number of solid cancers. However, a lack of understanding of the heterogeneity of the tumor microenvironment (TME) has resulted in inefficient therapy responses. A greater understanding of the TME is needed to identify patients likely to respond, and those that will have resistance to immune checkpoint inhibitors (ICIs). Advancement in spatial single-cell technologies has allowed deeper insight into the phenotypic and functional diversities of cells in the TME. In this review, we provide an overview of ICI biomarkers and highlight how high-dimensional spatially resolved, single-cell approaches provide deep molecular insights into the TME and allow for the discovery of biomarkers of clinical benefit.

Radiogenomics uncovers an interplay between angiogenesis and clinical outcomes in bladder cancer

BACKGROUND

Precision medicine has become a promising clinical treatment strategy for various cancers, including bladder cancer, where angiogenesis plays a critical role in cancer progression. However, the relationship between angiogenesis, immune cell infiltration, clinical outcomes, chemotherapy, and targeted therapy remains unclear.

METHODS

We conducted a comprehensive evaluation of angiogenesis-related genes (ARGs) to identify their association with immune cell infiltration, transcription patterns, and clinical outcomes in bladder cancer. An ARG score was constructed to identify angiogenic subgroups in each sample and we evaluated their predictive performance for overall survival rate and treatment response. In addition, we optimized existing clinical detection protocols by performing image data processing.

RESULTS

Our study revealed the genomic-level mutant landscape and expression patterns of ARGs in bladder cancer specimens. Using analysis, we identified three molecular subgroups where ARG mutations correlated with patients' pathological features, clinical outcomes, and immune cell infiltration. To facilitate clinical applicability, we constructed a precise nomogram based on the ARG score, which significantly correlated with stem cell index and drug sensitivity. Finally, we proposed the radiogenomics model, which combines the precision of genomics with the convenience of radiomics.

CONCLUSION

Our study sheds light on the prognostic characteristics of ARGs in bladder cancer and provides insights into the tumor environment's characteristics to explore more effective immunotherapy strategies. The findings have significant implications for the development of personalized treatment approaches in bladder cancer and pave the way for future studies in this field.

Tunable PhenoCycler imaging of the murine pre-clinical tumour microenvironments

BACKGROUND

The tumour microenvironment (TME) consists of tumour-supportive immune cells, endothelial cells, and fibroblasts. PhenoCycler, a high-plex single cell spatial biology imaging platform, is used to characterize the complexity of the TME. Researchers worldwide harvest and bank tissues from mouse models which are employed to model a plethora of human disease. With the explosion of interest in spatial biology, these panoplies of archival tissues provide a valuable resource to answer new questions. Here, we describe our protocols for developing tunable PhenoCycler multiplexed imaging panels and describe our open-source data analysis pipeline. Using these protocols, we used PhenoCycler to spatially resolve the TME of 8 routinely employed pre-clinical models of lymphoma, breast cancer, and melanoma preserved as FFPE.

RESULTS

Our data reveal distinct TMEs in the different cancer models that were imaged and show that cell-cell contacts differ depending on the tumour type examined. For instance, we found that the immune infiltration in a murine model of melanoma is altered in cellular organization in melanomas that become resistant to αPD-1 therapy, with depletions in a number of cell-cell interactions.

CONCLUSIONS

This work presents a valuable resource study seamlessly adaptable to any field of research involving murine models. The methodology described allows researchers to address newly formed hypotheses using archival materials, bypassing the new to perform new mouse studies.

Breaks for Precision Medicine in Cancer: Development and Prospects of Spatiotemporal Transcriptomics

With the development of the social economy and the deepening understanding of cancer, cancer has become a significant cause of death, threatening human health. Although researchers have made rapid progress in cancer treatment strategies in recent years, the overall survival of cancer patients is still not optimistic. Therefore, it is essential to reveal the spatial pattern of gene expression, spatial heterogeneity of cell populations, microenvironment interactions, and other aspects of cancer. Spatiotemporal transcriptomics can help analyze the mechanism of cancer occurrence and development, greatly help precise cancer treatment, and improve clinical prognosis. Here, we review the integration strategies of single-cell RNA sequencing and spatial transcriptomics data, summarize the recent advances in spatiotemporal transcriptomics in cancer studies, and discuss the combined application of spatial multiomics, which provides new directions and strategies for the precise treatment and clinical prognosis of cancer.

The post-chemotherapy changes of tumor physical microenvironment: Targeting extracellular matrix to address chemoresistance

The tumor physical microenvironment (TPME) contributes to cancer chemoresistance in both mechanical and mechanobiological approaches. Along with chemotherapy, the tumor microenvironment undergoes dramatic changes, most of which can regulate TPME through extracellular matrix (ECM) remodeling and related signaling pathways. However, there is still no discussion about the post-chemotherapy TPME changes mediated by ECM remodeling, and consequent impact on chemoresistance. Herein, we summarize the TPME alterations induced by chemotherapy and corresponding influence on chemotherapy response of cancer cells in context of ECM. The response of cancer cell to chemotherapy, imposed by post-chemotherapy ECM, are discussed in both mechanical (ECM physical features) and mechanobiological (ECM-responsive signaling pathways) manner. In the end, we present ECM remodeling and related signaling pathways as two promising clinic strategies to relieve or overcome chemoresistance induced by TPME change, and summarize the corresponding therapeutic agents currently being tested in clinical trials.

Generalized machine learning based on multi-omics data to profile the effect of ferroptosis pathway on prognosis and immunotherapy response in patients with bladder cancer

INTRODUCTION

Bladder cancer (BLCA) affects millions of people worldwide, with high rates of incidence and mortality. Ferroptosis proves to be a novel form of cell death process that is triggered by oxidative stress.

METHODS

We procured a total of 25 single nuclear RNA-seq (snRNA-seq) samples from GSE169379 in GEO database. We obtained different cohorts of BLCA patients from the TCGA and GEO databases for model training and validation. A total of 369 ferroptosis-related genes (FRGs) were selected from the FerrDb database. AUCell analysis was performed to assign ferroptosis scores to all the cell types. Weighted Gene Co-Expression Network Analysis (WGCNA), COX, and LASSO regression analysis were conducted to retain and finalize the genes of prognostic values. Various bioinformatic approaches were utilized to depict immune infiltration profile. We conducted a series of colony formation analysis, flow cytometry and western blot (WB) analysis to determine the role of SKAP1 in BLCA.

RESULTS

We divided the cells into high ferroptosis group and low ferroptosis group according to ferroptosis activity score, and then screened 2150 genes most associated with ferroptosis by differential expression analysis, which are related to UV-induced DNA damage, male hormone response, fatty acid metabolism and hypoxia. Subsequently, WGCNA algorithm further screened 741 ferroptosis related genes from the 2150 genes for the construction of prognostic model. Lasso-Cox regression analysis was used to construct the prognostic model, and the prognostic model consisting of 6 genes was obtained, namely JUN, SYT1, MAP3K8, GALNT14, TCIRG1, and SKAP1. Next, we constructed a nomogram model that integrated clinical factors to improving the accuracy. In addition, we performed drug sensitivity analyses in different subgroups and found that Staurosporine, Rapamycin, Gemcitabine, and BI-2536 may be candidates for the drugs treatment in high-risk populations. The ESTIMATE results showed higher stromal scores, immune scores, and ESTIMATE scores in the low-risk group, indicating a higher overall immunity level and immunogenicity of tumor microenvironment (TME) in this group, and tumor immune dysfunction and exclusion (TIDE) analysis confirmed a better response to immunotherapy in the low-risk group. Finally, we selected the oncogene SKAP1 in the prognostic gene for in vitro validation, and found that SKAP1 directly regulated BLCA cell proliferation and apoptosis.

CONCLUSION

We identified a set of six genes, JUN, SYT1, MAP3K8, GALNT14, TCIRG1, and SKAP1, that exhibited significant potential in stratification of BLCA patients with varying prognosis. In addition, we uncovered the direct regulatory effect of SKAP1 on BLCA cell proliferation and apoptosis, shedding some light on the role of FRGs in pathogenesis of BLCA.

Mapping cancer biology in space: applications and perspectives on spatial omics for oncology

Technologies to decipher cellular biology, such as bulk sequencing technologies and single-cell sequencing technologies, have greatly assisted novel findings in tumor biology. Recent findings in tumor biology suggest that tumors construct architectures that influence the underlying cancerous mechanisms. Increasing research has reported novel techniques to map the tissue in a spatial context or targeted sampling-based characterization and has introduced such technologies to solve oncology regarding tumor heterogeneity, tumor microenvironment, and spatially located biomarkers. In this study, we address spatial technologies that can delineate the omics profile in a spatial context, novel findings discovered via spatial technologies in oncology, and suggest perspectives regarding therapeutic approaches and further technological developments.

ADGRE5-centered Tsurv model in T cells recognizes responders to neoadjuvant cancer immunotherapy

Background

Neoadjuvant immunotherapy with anti-programmed death-1 (neo-antiPD1) has revolutionized perioperative methods for improvement of overall survival (OS), while approaches for major pathologic response patients' (MPR) recognition along with methods for overcoming non-MPR resistance are still in urgent need.

Methods

We utilized and integrated publicly-available immune checkpoint inhibitors regimens (ICIs) single-cell (sc) data as the discovery datasets, and innovatively developed a cell-communication analysis pipeline, along with a VIPER-based-SCENIC process, to thoroughly dissect MPR-responding subsets. Besides, we further employed our own non-small cell lung cancer (NSCLC) ICIs cohort's sc data for validation in-silico. Afterward, we resorted to ICIs-resistant murine models developed by us with multimodal investigation, including bulk-RNA-sequencing, Chip-sequencing and high-dimensional cytometry by time of flight (CYTOF) to consolidate our findings in-vivo. To comprehensively explore mechanisms, we adopted 3D ex-vivo hydrogel models for analysis. Furthermore, we constructed an ADGRE5-centered Tsurv model from our discovery dataset by machine learning (ML) algorithms for a wide range of tumor types (NSCLC, melanoma, urothelial cancer, etc.) and verified it in peripheral blood mononuclear cells (PBMCs) sc datasets.

Results

Through a meta-analysis of multimodal sequential sc sequencing data from pre-ICIs and post-ICIs, we identified an MPR-expanding T cells meta-cluster (MPR-E) in the tumor microenvironment (TME), characterized by a stem-like CD8+ T cluster (survT) with STAT5-ADGRE5 axis enhancement compared to non-MPR or pre-ICIs TME. Through multi-omics analysis of murine TME, we further confirmed the existence of survT with silenced function and immune checkpoints (ICs) in MPR-E. After verification of the STAT5-ADGRE5 axis of survT in independent ICIs cohorts, an ADGRE5-centered Tsurv model was then developed through ML for identification of MPR patients pre-ICIs and post-ICIs, both in TME and PBMCs, which was further verified in pan-cancer immunotherapy cohorts. Mechanistically, we unveiled ICIs stimulated ADGRE5 upregulation in a STAT5-IL32 dependent manner in a 3D ex-vivo system (3D-HYGTIC) developed by us previously, which marked Tsurv with better survival flexibility, enhanced stemness and potential cytotoxicity within TME.

Conclusion

Our research provides insights into mechanisms underlying MPR in neo-antiPD1 and a well-performed model for the identification of non-MPR.

Silencing LINC00663 inhibits inflammation and angiogenesis through downregulation of NR2F1 via EBF1 in bladder cancer

This study is to elucidate the effect of the LINC00663/EBF1/NR2F1 axis on inflammation and angiogenesis in bladder cancer (BC) and related molecular mechanisms. After transfection, functional experiments were conducted to test cell proliferation and invasion, tube formation ability, and content of inflammatory factors, Snail, E-cadherin, and VEGFA. Meanwhile, the relationships among LINC00663, EBF1, and NR2F1 were predicted and verified. In addition, xenograft experiments in nude mice were performed to observe the oncogenicity of 5637 BC cells in vivo. In BC tissues and cells, LINC00663 and NR2F1 were upregulated. Silencing NR2F1 or LINC00663 repressed cell proliferation and invasion, weakened vascular mimicry in vitro, decreased inflammatory factor, Snail, and VEGFA levels, and increased expression of E-cadherin. LINC00663 positively regulated NR2F1 expression through EBF1. Additionally, in vivo experiments showed that NR2F1 upregulation reversed the suppression effects of LINC00663 silencing on tumour growth, inflammation, and angiogenesis. Silencing LINC00663 decreased NR2F1 expression by mediating EBF1, thereby inhibiting BC inflammation and angiogenesis.