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

SPASCER: spatial transcriptomics annotation at single-cell resolution

In recent years, the explosive growth of spatial technologies has enabled the characterization of spatial heterogeneity of tissue architectures. Compared to traditional sequencing, spatial transcriptomics reserves the spatial information of each captured location and provides novel insights into diverse spatially related biological contexts. Even though two spatial transcriptomics databases exist, they provide limited analytical information. Information such as spatial heterogeneity of genes and cells, cell-cell communication activities in space, and the cell type compositions in the microenvironment are critical clues to unveil the mechanism of tumorigenesis and embryo differentiation. Therefore, we constructed a new spatial transcriptomics database, named SPASCER (https://ccsm.uth.edu/SPASCER), designed to help understand the heterogeneity of tissue organizations, region-specific microenvironment, and intercellular interactions across tissue architectures at multiple levels. SPASCER contains datasets from 43 studies, including 1082 sub-datasets from 16 organ types across four species. scRNA-seq was integrated to deconvolve/map spatial transcriptomics, and processed with spatial cell-cell interaction, gene pattern and pathway enrichment analysis. Cell-cell interactions and gene regulation network of scRNA-seq from matched spatial transcriptomics were performed as well. The application of SPASCER will provide new insights into tissue architecture and a solid foundation for the mechanistic understanding of many biological processes in healthy and diseased tissues.

Spatially resolved transcriptomics: advances and applications

Spatial transcriptomics, which is capable of both measuring all gene activity in a tissue sample and mapping where this activity occurs, is vastly improving our understanding of biological processes and disease. The field has expanded rapidly in recent years, and the development of several new technologies has resulted in spatially resolved transcriptomics (SRT) becoming highly multiplexed, high-resolution, and high-throughput. Here, we summarize and compare the major methods of SRT, including imaging-based methods, sequencing-based methods, and in situ sequencing methods. We also highlight some typical applications of SRT in neuroscience, cancer biology, developmental biology, and hematology. Finally, we discuss future possibilities for improving spatially resolved transcriptomic methods and the expected applications of such methods, especially in the adult bone marrow, anticipating that new developments will unlock the full potential of spatially resolved multi-omics in both biological research and the clinic.

Highly multiplexed spatial profiling with CODEX: bioinformatic analysis and application in human disease

Multiplexed imaging, which enables spatial localization of proteins and RNA to cells within tissues, complements existing multi-omic technologies and has deepened our understanding of health and disease. CODEX, a multiplexed single-cell imaging technology, utilizes a microfluidics system that incorporates DNA barcoded antibodies to visualize 50 + cellular markers at the single-cell level. Here, we discuss the latest applications of CODEX to studies of cancer, autoimmunity, and infection as well as current bioinformatics approaches for analysis of multiplexed imaging data from preprocessing to cell segmentation and marker quantification to spatial analysis techniques. We conclude with a commentary on the challenges and future developments for multiplexed spatial profiling.

Crosstalk of disulfidptosis-related subtypes, establishment of a prognostic signature and immune infiltration characteristics in bladder cancer based on a machine learning survival framework

Background

Bladder cancer (BLCA) is the most common malignancy of the urinary tract. On the other hand, disulfidptosis, a mechanism of disulfide stress-induced cell death, is closely associated with tumorigenesis and progression. Here, we investigated the impact of disulfidptosis-related genes (DRGs) on the prognosis of BLCA, identified various DRG clusters, and developed a risk model to assess patient prognosis, immunological profile, and treatment response.

Methods

The expression and mutational characteristics of four DRGs were first analyzed in bulk RNA-Seq and single-cell RNA sequencing data, IHC staining identified the role of DRGs in BLCA progression, and two DRG clusters were identified by consensus clustering. Using the differentially expressed genes (DEGs) from these two clusters, we transformed ten machine learning algorithms into more than 80 combinations and finally selected the best algorithm to construct a disulfidptosis-related prognostic signature (DRPS). We based this selection on the mean C-index of three BLCA cohorts. Furthermore, we explored the differences in clinical characteristics, mutational landscape, immune cell infiltration, and predicted efficacy of immunotherapy between high and low-risk groups. To visually depict the clinical value of DRPS, we employed nomograms. Additionally, we verified whether DRPS predicts response to immunotherapy in BLCA patients by utilizing the Tumour Immune Dysfunction and Rejection (TIDE) and IMvigor 210 cohorts.

Results

In the integrated cohort, we identified several DRG clusters and DRG gene clusters that differed significantly in overall survival (OS) and tumor microenvironment. After the integration of clinicopathological features, DRPS showed robust predictive power. Based on the median risk score associated with disulfidptosis, BLCA patients were divided into low-risk (LR) and high-risk (HR) groups, with patients in the LR group having a better prognosis, a higher tumor mutational load and being more sensitive to immunotherapy and chemotherapy.

Conclusion

Our study, therefore, provides a valuable tool to further guide clinical management and tailor the treatment of BLCA patients, offering new insights into individualized treatment.

Spatial biology of cancer evolution

The natural history of cancers can be understood through the lens of evolution given that the driving forces of cancer development are mutation and selection of fitter clones. Cancer growth and progression are spatial processes that involve the breakdown of normal tissue organization, invasion and metastasis. For these reasons, spatial patterns are an integral part of histological tumour grading and staging as they measure the progression from normal to malignant disease. Furthermore, tumour cells are part of an ecosystem of tumour cells and their surrounding tumour microenvironment. A range of new spatial genomic, transcriptomic and proteomic technologies offers new avenues for the study of cancer evolution with great molecular and spatial detail. These methods enable precise characterizations of the tumour microenvironment, cellular interactions therein and micro-anatomical structures. In conjunction with spatial genomics, it emerges that tumours and microenvironments co-evolve, which helps explain observable patterns of heterogeneity and offers new routes for therapeutic interventions.

Structural or functional defects of PTEN in urothelial cells lacking P53 drive basal/squamous-subtype muscle-invasive bladder cancer

Muscle-invasive bladder cancer (MIBC) exhibits strong inter- and intra-tumor heterogeneity that affects biological behaviors, therapeutic responses, and prognoses. Mutations that activate RTK-RAS-PI3K and inactivate P19-P53-P21 coexist in 60-70% of MIBC. By time-controlled ablation of Tp53 and Pten, singly or combined, in adult mouse urothelium, we found that Tp53 loss alone produced no abnormality. While Pten loss elicited hyperplasia, it synergized with Tp53 loss to trigger 100% penetrant MIBC that exhibited basal/squamous features that resembled its human counterpart. Furthermore, PTEN was inactivated in human MIBC cell lines and specimens primarily by hyperphosphorylation of the C-terminus. Mutated or tailless PTEN incapable of C-terminal phosphorylation demonstrated increased inhibition of proliferation and invasion than full-length PTEN in cultured MIBC cells. In xenograft and transgenic mice, tailless PTEN, but not full-length PTEN, prevented further growth in established tumors. Collectively, deficiencies of both PTEN and P53 drive basal/squamous subtype MIBC. PTEN is inactivated by C-terminal hyperphosphorylation, and this modification may serve as a biomarker for subtyping MIBC and predicting tumor progression. Tailless PTEN is a potential molecular therapeutic for tumors, such as bladder cancer (BC), that can be readily accessed.

Assessment of spatial transcriptomics for oncology discovery

Tumor heterogeneity is a major challenge for oncology drug discovery and development. Understanding of the spatial tumor landscape is key to identifying new targets and impactful model systems. Here, we test the utility of spatial transcriptomics (ST) for oncology discovery by profiling 40 tissue sections and 80,024 capture spots across a diverse set of tissue types, sample formats, and RNA capture chemistries. We verify the accuracy and fidelity of ST by leveraging matched pathology analysis, which provides a ground truth for tissue section composition. We then use spatial data to demonstrate the capture of key tumor depth features, identifying hypoxia, necrosis, vasculature, and extracellular matrix variation. We also leverage spatial context to identify relative cell-type locations showing the anti-correlation of tumor and immune cells in syngeneic cancer models. Lastly, we demonstrate target identification approaches in clinical pancreatic adenocarcinoma samples, highlighting tumor intrinsic biomarkers and paracrine signaling.

Spatial multi-omics analyses of the tumor immune microenvironment

In the past decade, single-cell technologies have revealed the heterogeneity of the tumor-immune microenvironment at the genomic, transcriptomic, and proteomic levels and have furthered our understanding of the mechanisms of tumor development. Single-cell technologies have also been used to identify potential biomarkers. However, spatial information about the tumor-immune microenvironment such as cell locations and cell-cell interactomes is lost in these approaches. Recently, spatial multi-omics technologies have been used to study transcriptomes, proteomes, and metabolomes of tumor-immune microenvironments in several types of cancer, and the data obtained from these methods has been combined with immunohistochemistry and multiparameter analysis to yield markers of cancer progression. Here, we review numerous cutting-edge spatial 'omics techniques, their application to study of the tumor-immune microenvironment, and remaining technical challenges.

Single-cell sequencing technologies in bladder cancer research: Applications and challenges

Bladder cancer is among the most common malignant tumors with highly heterogeneous molecular characteristics. Despite advancements of the available therapeutic options, several bladder cancer patients exhibit unsatisfactory clinical outcomes. The lack of specific biomarkers for effective targeted therapy or immunotherapy remains a major obstacle in treating bladder cancer. The rapid development of single-cell techniques is transforming our understanding of the intra-tumoral heterogeneity, thereby providing us with a powerful high-throughput sequencing tool that can reveal tumorigenesis, progression, and invasion in bladder tumors. In this review, we summarise and discuss how single-cell sequencing technologies have been applied in bladder cancer research, to advance our collective knowledge on the heterogeneity of bladder tumor cells, as well as to provide new insights into the complex ecosystem of the tumor microenvironment. The application of single-cell approaches also uncovers the therapeutic resistance mechanism in bladder cancer and facilitates the detection of urinary-exfoliated tumor cells. Moreover, benefiting from the powerful technical advantages of single-cell techniques, several key therapeutic targets and prognostic models of bladder cancer have been identified. It is hoped that this paper can provide novel insights into the precision medicine of bladder cancer.

Spatial transcriptomics technology in cancer research

In recent years, spatial transcriptomics (ST) technologies have developed rapidly and have been widely used in constructing spatial tissue atlases and characterizing spatiotemporal heterogeneity of cancers. Currently, ST has been used to profile spatial heterogeneity in multiple cancer types. Besides, ST is a benefit for identifying and comprehensively understanding special spatial areas such as tumor interface and tertiary lymphoid structures (TLSs), which exhibit unique tumor microenvironments (TMEs). Therefore, ST has also shown great potential to improve pathological diagnosis and identify novel prognostic factors in cancer. This review presents recent advances and prospects of applications on cancer research based on ST technologies as well as the challenges.

The Role of Cadherin 12 (CDH12) in the Peritoneal Fluid among Patients with Endometriosis and Endometriosis-Related Infertility

Cadherin 12 (CDH 12) can play a role in the pathogenesis of endometriosis. The aim of this study was to compare the levels of cadherin 12 in the peritoneal fluid between women with and without endometriosis. This was a multicenter cross-sectional study. Eighty-two patients undergoing laparoscopic procedures were enrolled in the study. Cadherin 12 concentrations were determined using the enzyme-linked immunosorbent assay. The level of statistical significance was set at p < 0.05. No differences in cadherin 12 concentrations between patients with and without endometriosis were observed (p = 0.4). Subgroup analyses showed that CDH 12 concentrations were significantly higher in patients with infertility or primary infertility and endometriosis in comparison with patients without endometriosis and without infertility or primary infertility (p = 0.02) and also higher in patients with stage I or II endometriosis and infertility or primary infertility than in patients without endometriosis and infertility or primary infertility (p = 0.03, p = 0.048, respectively). In total, CDH 12 levels were significantly higher in patients diagnosed with infertility or primary infertility (p = 0.0092, p = 0.009, respectively) than in fertile women. Cadherin 12 can possibly play a role in the pathogenesis of infertility, both in women with and without endometriosis.

Clinical application of advanced multi-omics tumor profiling: Shaping precision oncology of the future

Next-generation DNA sequencing technology has dramatically advanced clinical oncology through the identification of therapeutic targets and molecular biomarkers, leading to the personalization of cancer treatment with significantly improved outcomes for many common and rare tumor entities. More recent developments in advanced tumor profiling now enable dissection of tumor molecular architecture and the functional phenotype at cellular and subcellular resolution. Clinical translation of high-resolution tumor profiling and integration of multi-omics data into precision treatment, however, pose significant challenges at the level of prospective validation and clinical implementation. In this review, we summarize the latest advances in multi-omics tumor profiling, focusing on spatial genomics and chromatin organization, spatial transcriptomics and proteomics, liquid biopsy, and ex vivo modeling of drug response. We analyze the current stages of translational validation of these technologies and discuss future perspectives for their integration into precision treatment.

Characterizing molecular subtypes of high-risk non-muscle-invasive bladder cancer in African American patients

BACKGROUND

We sought to determine whether differences in subtype distribution and differentially expressed genes exist between African Americans (AAs) and European Americans (EAs) in patients with high-risk nonmuscle-invasive bladder cancer (NMIBC).

METHODS

We performed a retrospective cohort study including 26 patients (14 AAs and 12 EAs) from the University of Texas Medical Branch and the Durham Veterans Affair Health Care System from 2010 to 2020 among treatment naïve, high-risk NMIBC. Profiled gene expressions were performed using the UROMOL classification system.

RESULTS

UROMOL racial subtype distributions were similar with class 2a being most common with 10 genes commonly upregulated in AAs compared to EAs including EFEMP1, S100A16, and MCL1 which are associated with progression to muscle-invasive bladder cancer, mitomycin C resistance, and bacillus Calmette-Guérin durability, respectively. We used single nuclei analysis to map the malignant cell heterogeneity in urothelial cancer which 5 distinct malignant epithelial subtypes whose presence has been associated with different therapeutic response prediction abilities. We mapped the expression of the 10 genes commonly upregulated by race as a function of the 5 malignant subtypes. This showed borderline (P = 0.056) difference among the subtypes suggesting AAs and EAs may be expected to have different therapeutic responses to treatments for bladder cancer. AAs were enriched with immune-related, inflammatory, and cellular regulation pathways compared to EAs, yet appeared to have reduced levels of the aggressive C3/CDH12 bladder tumor cell population.

CONCLUSIONS

While premature, gene expression differed between AAs and EAs, supporting potential race-based etiologies for muscle-invasion, response to treatments, and transcriptome pathway regulations.

DNMT3A/miR-129-2-5p/Rac1 Is an Effector Pathway for SNHG1 to Drive Stem-Cell-like and Invasive Behaviors of Advanced Bladder Cancer Cells

The stem-cell-like behavior of cancer cells plays a central role in tumor heterogeneity and invasion and correlates closely with drug resistance and unfavorable clinical outcomes. However, the molecular underpinnings of cancer cell stemness remain incompletely defined. Here, we show that SNHG1, a long non-coding RNA that is over-expressed in ~95% of human muscle-invasive bladder cancers (MIBCs), induces stem-cell-like sphere formation and the invasion of cultured bladder cancer cells by upregulating Rho GTPase, Rac1. We further show that SNHG1 binds to DNA methylation transferase 3A protein (DNMT3A), and tethers DNMT3A to the promoter of miR-129-2, thus hyper-methylating and repressing miR-129-2-5p transcription. The reduced binding of miR-129-2 to the 3'-UTR of Rac1 mRNA leads to the stabilization of Rac1 mRNA and increased levels of Rac1 protein, which then stimulates MIBC cell sphere formation and invasion. Analysis of the Human Protein Atlas shows that a high expression of Rac1 is strongly associated with poor survival in patients with MIBC. Our data strongly suggest that the SNHG1/DNMT3A/miR-129-2-5p/Rac1 effector pathway drives stem-cell-like and invasive behaviors in MIBC, a deadly form of bladder cancer. Targeting this pathway, alone or in combination with platinum-based therapy, may reduce chemoresistance and improve longer-term outcomes in MIBC patients.

Discoidin Domain Receptor-Driven Gene Signatures as Markers of Patient Response to Anti-PD-L1 Immune Checkpoint Therapy

BACKGROUND

Anti-programmed cell death 1 (anti-PD-1) and PD ligand 1 (PD-L1) immune checkpoint therapies (ICTs) provided durable responses only in a subset of cancer patients. Thus, biomarkers are needed to predict nonresponders and offer them alternative treatments. We recently implicated discoidin domain receptor tyrosine kinase 2 (DDR2) as a contributor to anti-PD-1 resistance in animal models; therefore, we sought to investigate whether this gene family may provide ICT response prediction.

METHODS

We assessed mRNA expression of DDR2 and its family member DDR1. Transcriptome analysis of bladder cancer (BCa) models in which DDR1 and 2 were perturbed was used to derive DDR1- and DDR2-driven signature scores. DDR mRNA expression and gene signature scores were evaluated using BCa-The Cancer Genome Atlas (n = 259) and IMvigor210 (n = 298) datasets, and their relationship to BCa subtypes, pathway enrichment, and immune deconvolution analyses was performed. The potential of DDR-driven signatures to predict ICT response was evaluated and independently validated through a statistical framework in bladder and lung cancer cohorts. All statistical tests were 2-sided.

RESULTS

DDR1 and DDR2 showed mutually exclusive gene expression patterns in human tumors. DDR2high BCa exhibited activation of immune pathways and a high immune score, indicative of a T-cell-inflamed phenotype, whereas DDR1high BCa exhibited a non-T-cell-inflamed phenotype. In IMvigor210 cohort, tumors with high DDR1 (hazard ratio [HR] = 1.53, 95% confidence interval [CI] = 1.16 to 2.06; P = .003) or DDR2 (HR = 1.42, 95% CI = 1.01 to 1.92; P = .04) scores had poor overall survival. Of note, DDR2high tumors from IMvigor210 and CheckMate 275 (n = 73) cohorts exhibited poorer overall survival (HR = 1.56, 95% CI = 1.20 to 2.06; P &lt; .001) and progression-free survival (HR = 1.77 95%, CI = 1.05 to 3.00; P = .047), respectively. This result was validated in independent cancer datasets.

CONCLUSIONS

These findings implicate DDR1 and DDR2 driven signature scores in predicting ICT response.

Opportunities and Challenges in Understanding Atherosclerosis by Human Biospecimen Studies

Over the last few years, new high-throughput biotechnologies and bioinformatic methods are revolutionizing our way of deep profiling tissue specimens at the molecular levels. These recent innovations provide opportunities to advance our understanding of atherosclerosis using human lesions aborted during autopsies and cardiac surgeries. Studies on human lesions have been focusing on understanding the relationship between molecules in the lesions with tissue morphology, genetic risk of atherosclerosis, and future adverse cardiovascular events. This review will highlight ways to utilize human atherosclerotic lesions in translational research by work from large cardiovascular biobanks to tissue registries. We will also discuss the opportunities and challenges of working with human atherosclerotic lesions in the era of next-generation sequencing.

Discovery of Notch Pathway-Related Genes for Predicting Prognosis and Tumor Microenvironment Status in Bladder Cancer

Background: Notch signaling is a key regulator of immune cell differentiation and linked to autoimmune diseases, tumorigenesis and tumor-induced immunomodulation. An abnormally activated Notch signaling pathway contributes to almost all of the key features of cancer, including tumor angiogenesis, stemness, and epithelial-mesenchymal transition. Consequently, we investigated Notch pathway-related genes for developing prognostic marker and assessing immune status in bladder cancer.

Methods: The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were utilized to analyze RNA-seq data for bladder cancer. Cluster subtypes were identified using the NMF algorithm. In order to establish a prognostic risk signature, the least absolute shrinkage and selection operator (Lasso) and Cox regression analysis was utilized. GSEA was carried out to investigate the molecular mechanisms. Immune cell infiltration levels in bladder cancer were calculated using the CIBERSORT algorithm. External clinical tissue samples were used to validate the expression levels of signature genes.

Results: Based on the NMF algorithm, bladder cancer samples were divided into two cluster subtypes and displayed different survival outcome and immune microenvironment. A six-gene risk signature (DTX3L, CNTN1, ENO1, GATA3, MAGEA1, and SORBS2) was independent for prognosis and showed good stability. The infiltration of immune cells and clinical variables were significantly different among the risk groups of patients. Response to immunotherapy also differed between different risk groups. Furthermore, the mRNA expression levels of the signature genes were verified in tissue samples by qRT-PCR.

Conclusion: We established a 6-gene signature associated with Notch pathway in bladder cancer to effectively predict prognosis and reflect immune microenvironment status.

Clinical and translational values of spatial transcriptomics

The combination of spatial transcriptomics (ST) and single cell RNA sequencing (scRNA-seq) acts as a pivotal component to bridge the pathological phenomes of human tissues with molecular alterations, defining in situ intercellular molecular communications and knowledge on spatiotemporal molecular medicine. The present article overviews the development of ST and aims to evaluate clinical and translational values for understanding molecular pathogenesis and uncovering disease-specific biomarkers. We compare the advantages and disadvantages of sequencing- and imaging-based technologies and highlight opportunities and challenges of ST. We also describe the bioinformatics tools necessary on dissecting spatial patterns of gene expression and cellular interactions and the potential applications of ST in human diseases for clinical practice as one of important issues in clinical and translational medicine, including neurology, embryo development, oncology, and inflammation. Thus, clear clinical objectives, designs, optimizations of sampling procedure and protocol, repeatability of ST, as well as simplifications of analysis and interpretation are the key to translate ST from bench to clinic.

Identification and Validation of N6-Methyladenosine-Related Biomarkers for Bladder Cancer: Implications for Immunotherapy

N6-methyladenosine (m⁶A) has emerged as one of the most important modifications of RNA. Based on the expression of 23 different modes of m⁶A regulatory factors, we identified three different m⁶A modification patterns in bladder cancer. The effects of the three different modes of m⁶A modification on clinicopathological characteristics, immune cell infiltration levels and expression levels of immune checkpoint genes were comprehensively analyzed. In addition, the effects of different modes of m⁶A modification on the therapeutic efficacy of anti-PD-L1 immunotherapy (atezolizumab) are also discussed. Our results confirm that m⁶A methylation plays an important role in immune cell recruitment in the tumor microenvironment of bladder cancer, which influences the efficacy of anti-PD-L1 therapy for bladder cancer. We further confirmed the important role of FTO protein in the biological function of bladder cancer cells by performing in vitro experiments. FTO functions as an oncogene in bladder cancer cells, and upon FTO knockdown, the level of m⁶A enzyme activity in bladder cancer cells was significantly increased, apoptosis was increased, and cell proliferation and cell invasion were reduced. In addition, our study also confirmed that K216H and K216E are probably important targets for regulating FTO. We provide new insights into the regulatory pathways of the immune microenvironment and the methylation function of m⁶A in bladder cancer, which will help in designing novel diagnostic methods, prognostic tools, and therapeutic targets.

The emerging roles of exosomal long non-coding RNAs in bladder cancer

Extracellular vesicles (EVs), especially exosomes, have been reported to play essential roles as extracellular messengers by transporting goods in various diseases, while their potential roles in bladder cancer (BC) still remain to be further studied. BC exhibits a high degree of chemoresistance and metastatic ability, which may be affected by cancer‐derived exosomes that carry proteins, lipids and RNA. To date, the most studied exosomal molecular cargo is long non‐coding RNA (lncRNA). Although there is increasing interest in its role and function, there is relatively little knowledge about it compared with other RNA transcripts. Nevertheless, in the past ten years, we have witnessed increasing interest in the role and function of lncRNA. For example, lncRNAs have been studied as potential biomarkers for the diagnosis of BC. They may play a role as a therapeutic target in precision medicine, but they may also be directly involved in the characteristics of tumour progression, such as metastasis, epithelial‐mesenchymal transition and drug resistance. Cancer cells are on chemotherapy acting. The function of lncRNA in various cancer exosomes has not yet been determined. In this review, we summarize the current studies about the prominent roles of exosomal lncRNAs in genome integrity, BC progression and carcinogenic features.

Directing the Future Breakthroughs in Immunotherapy: The Importance of a Holistic Approach to the Tumour Microenvironment

Simple Summary

Immunotherapies have changed the way we treat cancer and, while some patients have benefitted greatly, there are still those that do not respond to therapy. Understanding why some patients respond to therapy and others do not is critical in developing new immunotherapeutic strategies. The increasing awareness of the importance of investigating the tumour in its entirety, including the surrounding tissue and role of various immune cells is helping to differentiate responders and non-responders. In addition, the resolution gained by the development of sophisticated bioinformatic technologies allows for a deeper understanding of the complex roles of individual cells in the tumour. This advancement will be critical for the development of novel therapies to treat cancer.

Abstract

Immunotherapy has revolutionised the treatment of cancers by exploiting the immune system to eliminate tumour cells. Despite the impressive response in a proportion of patients, clinical benefit has been limited thus far. A significant focus to date has been the identification of specific markers associated with response to immunotherapy. Unfortunately, the heterogeneity between patients and cancer types means identifying markers of response to therapy is inherently complex. There is a growing appreciation for the role of the tumour microenvironment (TME) in directing response to immunotherapy. The TME is highly heterogeneous and contains immune, stromal, vascular and tumour cells that all communicate and interact with one another to form solid tumours. This review analyses major cell populations present within the TME with a focus on their diverse and often contradictory roles in cancer and how this informs our understanding of immunotherapy. Furthermore, we discuss the role of integrated omics in providing a comprehensive view of the TME and demonstrate the potential of leveraging multi-omics to decipher the underlying mechanisms of anti-tumour immunity for the development of novel immunotherapeutic strategies.