Spatially organized multicellular immune hubs in human colorectal cancer

Myoferlin: A Potential Marker of Response to Radiation Therapy and Survival in Locally Advanced Rectal Cancer

PURPOSE

Patients with locally advanced rectal cancer often require neoadjuvant chemoradiation therapy to downstage the disease, but the response is variable with no predictive biomarkers. We have previously revealed through proteomic profiling that myoferlin is associated with response to radiation therapy. The aims of this study were to further validate this finding and explore the potential for myoferlin to act as a prognostic and/or therapeutic target.

METHODS AND MATERIALS

Immunohistochemical analysis of a tissue microarray (TMA) for 111 patients was used to validate the initial proteomic findings. Manipulation of myoferlin was achieved using small interfering RNA, a small molecular inhibitor (wj460), and a CRISPR-Cas9 knockout cell line. Radiosensitization after treatment was assessed using 2-dimensional clonogenic assays, 3-dimensional spheroid models, and patient-derived organoids. Underlying mechanisms were investigated using electrophoresis, immunofluorescence, and immunoblotting.

RESULTS

Analysis of both the diagnostic biopsy and tumor resection samples confirmed that low myoferlin expression correlated with a good response to neoadjuvant long-course chemoradiation therapy. High myoferlin expression was associated with spread to local lymph nodes and worse 5-year survival (P = .01; hazard ratio, 3.5; 95% CI, 1.27-10.04). This was externally validated using the Stratification in Colorectal Cancer database. Quantification of myoferlin using immunoblotting in immortalized colorectal cancer cell lines and organoids demonstrated that high myoferlin expression was associated with increased radioresistance. Biological and pharmacologic manipulation of myoferlin resulted in significantly increased radiosensitivity across all cell lines in 2-dimensional and 3-dimensional models. After irradiation, myoferlin knockdown cells had a significantly impaired ability to repair DNA double-strand breaks. This appeared to be mediated via nonhomologous end-joining.

CONCLUSIONS

We have confirmed that high expression of myoferlin in rectal cancer is associated with poor response to neoadjuvant therapy and worse long-term survival. Furthermore, the manipulation of myoferlin led to increased radiosensitivity in vitro. This suggests that myoferlin could be targeted to enhance the sensitivity of patients with rectal cancer to radiation therapy, and further work is required.

Digital spatial profiling for pathologists

The advent of "omics" technologies for high-depth tumor profiling has provided new information regarding cancer heterogeneity. However, a bulk omics profile can only partially reproduce tumor complexity, and it does not meet the preferences of pathologists used to perform an in situ assessment of marker expression, for instance, with immunohistochemistry. The NanoString GeoMx® Digital Spatial Profiler (DSP) is a platform for morphology-guided multiplex profiling of tissue slides, which allows the digital quantification of target analytes in different neoplastic settings. To illustrate the feasibility and opportunities offered by DSP from a pathologist's perspective, we applied DSP in three different representative neoplastic settings: breast carcinoma, thyroid anaplastic carcinoma, and biphasic mesothelioma. Because of the perfect overlap between the hematoxylin-eosin-stained slide and the GeoMx areas of interest, in breast carcinoma, two different antibodies allowed the distinction of the tumor cells from the surrounding tumor microenvironment. In biphasic mesothelioma, we could distinguish the epithelioid from the sarcomatoid neoplastic component, and in the thyroid, we easily separated the anaplastic areas from the well-differentiated carcinoma. DSP is a promising tool that combines traditional histological evaluation, allowing spatial assessment of a tumor and its surroundings, and innovative in situ digital profiling. Pathologists should not miss the opportunity to combine morphological and genomic analyses and be at the forefront of investigating the progression of dysplasia/neoplasia, low-grade or high-grade, epithelial/mesenchymal, and, more in general, overcoming the concept of in situ vs. bulk genomic methods.

Prostaglandin E2-EP2/EP4 signaling induces immunosuppression in human cancer by impairing bioenergetics and ribosome biogenesis in immune cells

While prostaglandin E2 (PGE2) is produced in human tumor microenvironment (TME), its role therein remains poorly understood. Here, we examine this issue by comparative single-cell RNA sequencing of immune cells infiltrating human cancers and syngeneic tumors in female mice. PGE receptors EP4 and EP2 are expressed in lymphocytes and myeloid cells, and their expression is associated with the downregulation of oxidative phosphorylation (OXPHOS) and MYC targets, glycolysis and ribosomal proteins (RPs). Mechanistically, CD8+ T cells express EP4 and EP2 upon TCR activation, and PGE2 blocks IL-2-STAT5 signaling by downregulating Il2ra, which downregulates c-Myc and PGC-1 to decrease OXPHOS, glycolysis, and RPs, impairing migration, expansion, survival, and antitumor activity. Similarly, EP4 and EP2 are induced upon macrophage activation, and PGE2 downregulates c-Myc and OXPHOS in M1-like macrophages. These results suggest that PGE2-EP4/EP2 signaling impairs both adaptive and innate immunity in TME by hampering bioenergetics and ribosome biogenesis of tumor-infiltrating immune cells.

A longitudinal single-cell atlas of anti-tumour necrosis factor treatment in inflammatory bowel disease

Precision medicine in immune-mediated inflammatory diseases (IMIDs) requires a cellular understanding of treatment response. We describe a therapeutic atlas for Crohn's disease (CD) and ulcerative colitis (UC) following adalimumab, an anti-tumour necrosis factor (anti-TNF) treatment. We generated ~1 million single-cell transcriptomes, organised into 109 cell states, from 216 gut biopsies (41 subjects), revealing disease-specific differences. A systems biology-spatial analysis identified granuloma signatures in CD and interferon (IFN)-response signatures localising to T cell aggregates and epithelial damage in CD and UC. Pretreatment differences in epithelial and myeloid compartments were associated with remission outcomes in both diseases. Longitudinal comparisons demonstrated disease progression in nonremission: myeloid and T cell perturbations in CD and increased multi-cellular IFN signalling in UC. IFN signalling was also observed in rheumatoid arthritis (RA) synovium with a lymphoid pathotype. Our therapeutic atlas represents the largest cellular census of perturbation with the most common biologic treatment, anti-TNF, across multiple inflammatory diseases.

Defining precancer: a grand challenge for the cancer community

The term 'precancer' typically refers to an early stage of neoplastic development that is distinguishable from normal tissue owing to molecular and phenotypic alterations, resulting in abnormal cells that are at least partially self-sustaining and function outside of normal cellular cues that constrain cell proliferation and survival. Although such cells are often histologically distinct from both the corresponding normal and invasive cancer cells of the same tissue origin, defining precancer remains a challenge for both the research and clinical communities. Once sufficient molecular and phenotypic changes have occurred in the precancer, the tissue is identified as a 'cancer' by a histopathologist. While even diagnosing cancer can at times be challenging, the determination of invasive cancer is generally less ambiguous and suggests a high likelihood of and potential for metastatic disease. The 'hallmarks of cancer' set out the fundamental organizing principles of malignant transformation but exactly how many of these hallmarks and in what configuration they define precancer has not been clearly and consistently determined. In this Expert Recommendation, we provide a starting point for a conceptual framework for defining precancer, which is based on molecular, pathological, clinical and epidemiological criteria, with the goal of advancing our understanding of the initial changes that occur and opportunities to intervene at the earliest possible time point.

Progressive plasticity during colorectal cancer metastasis

As cancers progress, they become increasingly aggressive-metastatic tumours are less responsive to first-line therapies than primary tumours, they acquire resistance to successive therapies and eventually cause death1,2. Mutations are largely conserved between primary and metastatic tumours from the same patients, suggesting that non-genetic phenotypic plasticity has a major role in cancer progression and therapy resistance3-5. However, we lack an understanding of metastatic cell states and the mechanisms by which they transition. Here, in a cohort of biospecimen trios from same-patient normal colon, primary and metastatic colorectal cancer, we show that, although primary tumours largely adopt LGR5+ intestinal stem-like states, metastases display progressive plasticity. Cancer cells lose intestinal cell identities and reprogram into a highly conserved fetal progenitor state before undergoing non-canonical differentiation into divergent squamous and neuroendocrine-like states, a process that is exacerbated in metastasis and by chemotherapy and is associated with poor patient survival. Using matched patient-derived organoids, we demonstrate that metastatic cells exhibit greater cell-autonomous multilineage differentiation potential in response to microenvironment cues compared with their intestinal lineage-restricted primary tumour counterparts. We identify PROX1 as a repressor of non-intestinal lineage in the fetal progenitor state, and show that downregulation of PROX1 licenses non-canonical reprogramming.

Ten challenges and opportunities in computational immuno-oncology

Immuno-oncology has transformed the treatment of cancer, with several immunotherapies becoming the standard treatment across histologies. Despite these advancements, the majority of patients do not experience durable clinical benefits, highlighting the imperative for ongoing advancement in immuno-oncology. Computational immuno-oncology emerges as a forefront discipline that draws on biomedical data science and intersects with oncology, immunology, and clinical research, with the overarching goal to accelerate the development of effective and safe immuno-oncology treatments from the laboratory to the clinic. In this review, we outline 10 critical challenges and opportunities in computational immuno-oncology, emphasizing the importance of robust computational strategies and interdisciplinary collaborations amid the constantly evolving interplay between clinical needs and technological innovation.

Mouse enteric neurons control intestinal plasmacytoid dendritic cell function via serotonin-HTR7 signaling

Serotonergic neurons in the central nervous system control behavior and mood, but knowledge of the roles of serotonergic circuits in the regulation of immune homeostasis is limited. Here, we employ mouse genetics to investigate the functions of enteric serotonergic neurons in the control of immune responses and find that these circuits regulate IgA induction and boost host defense against oral, but not systemic Salmonella Typhimurium infection. Enteric serotonergic neurons promote gut-homing, retention and activation of intestinal plasmacytoid dendritic cells (pDC). Mechanistically, this neuro-immune crosstalk is achieved through a serotonin-5-HT receptor 7 (HTR7) signaling axis that ultimately facilitates the pDC-mediated differentiation of IgA+ B cells from IgD+ precursors in the gut. Single-cell RNA-seq data further reveal novel patterns of bidirectional communication between specific subsets of enteric neurons and lamina propria DC. Our findings thus reveal a close interplay between enteric serotonergic neurons and gut immune homeostasis that enhances mucosal defense.

Systematic analysis of human colorectal cancer scRNA-seq revealed limited pro-tumoral IL-17 production potential in gamma delta T cells

Gamma delta T cells play a crucial role in anti-tumor immunity due to their cytotoxic properties. However, the role and extent of γδ T cells in production of pro-tumorigenic interleukin-17 (IL-17) within the tumor microenvironment of colorectal cancer (CRC) remains controversial. In this study, we re-analyzed nine published human CRC whole-tissue single-cell RNA sequencing datasets, identifying 18,483 γδ T cells out of 951,785 total cells, in the neoplastic or adjacent normal tissue of 165 human CRC patients. Our results confirm that tumor-infiltrating γδ T cells exhibit high cytotoxicity-related transcription in both tumor and adjacent normal tissues, but critically, none of the γδ T cell clusters showed IL-17 production potential. We also identified various γδ T cell subsets, including poised effector-like T cells, tissue-resident memory T cells, progenitor exhausted-like T cells, and exhausted T cells, and noted an increased expression of cytotoxic molecules in tumor-infiltrating γδ T cells compared to their normal area counterparts. We proposed anti-tumor γδ T effector cells may arise from tissue-resident progenitor cells based on the trajectory analysis. Our work demonstrates that γδ T cells in CRC primarily function as cytotoxic effector cells rather than IL-17 producers, mitigating the concerns about their potential pro-tumorigenic roles in CRC, highlighting the importance of accurately characterizing these cells for cancer immunotherapy research and the unneglectable cross-species discrepancy between the mouse and human immune system in the study of cancer immunology.

Systematic perturbation screens identify regulators of inflammatory macrophage states and a role for TNF mRNA m6A modification

Macrophages exhibit remarkable functional plasticity, a requirement for their central role in tissue homeostasis. During chronic inflammation, macrophages acquire sustained inflammatory 'states' that contribute to disease, but there is limited understanding of the regulatory mechanisms that drive their generation. Here we describe a systematic functional genomics approach that combines genome-wide phenotypic screening in primary murine macrophages with transcriptional and cytokine profiling of genetic perturbations in primary human macrophages to uncover regulatory circuits of inflammatory states. This process identifies regulators of five distinct states associated with key features of macrophage function. Among these regulators, loss of the N6-methyladenosine (m6A) writer components abolishes m6A modification of TNF transcripts, thereby enhancing mRNA stability and TNF production associated with multiple inflammatory pathologies. Thus, phenotypic characterization of primary murine and human macrophages describes the regulatory circuits underlying distinct inflammatory states, revealing post-transcriptional control of TNF mRNA stability as an immunosuppressive mechanism in innate immunity.

Tumor-associated macrophages confer resistance to chemotherapy (Trifluridine/Tipiracil) in digestive cancers by overexpressing thymidine phosphorylase

Pyrimidine analogs are part of the first-line chemotherapy regimen for gastrointestinal cancers. Trifluridine combined with tipiracil, a specific thymidine phosphorylase inhibitor, in TAS-102 has recently emerged as a potential alternative in the face of primary or secondary chemoresistance to 5-fluorouracil. Despite its promise, we report that macrophage-specific overexpression of thymidine phosphorylase results in macrophage-induced chemoresistance to TAS-102 that is insensitive to tipiracil inhibition. Furthermore, we illustrate the human-specific nature of this mechanism, as mouse macrophages do not express substantial levels of thymidine phosphorylase, which constrains the applicability of mouse models. To study the importance of macrophages in chemoresistance to trifluridine, we developed a humanized mouse model with tumor-implanted human macrophages and demonstrated their important role in treatment resistance to pyrimidine analogs. Additionally, our findings revealed that macrophages represent a significant source of thymidine phosphorylase expression, comprising over 40 % of the expressing cells, in human colorectal cancer, thereby contributing to chemoresistance.

PD-L1 restrains PD-1+Nrp1lo Treg cells to suppress inflammation-driven colorectal tumorigenesis

T cells function not only as an essential component of host cancer immunosurveillance but also as a regulator of colonic inflammation, a process that promotes colorectal cancer. Programmed death-ligand 1 (PD-L1) is a T cell-negative regulator, but its role in regulation of T cell functions in the context of colorectal cancer is unknown. We report that global deletion of Cd274 results in increased colonic inflammation, PD-1+ T cells, and inflammation-driven colorectal tumorigenesis in mice. Single-cell RNA sequencing (scRNA-seq) analysis revealed that PD-L1 suppresses subpopulations of programmed cell death protein 1 (PD-1)+Nrp1lo regulatory T (Treg) cells and interleukin (IL) 6+ neutrophils in colorectal tumor. Treg cells produce transforming growth factor (TGF) β to recruit IL6+ neutrophils. Neutrophils produce IL6 to inhibit activation of tumor-specific cytotoxic T lymphocytes (CTLs) and primary CTLs. Accordingly, IL6 blockade immunotherapy increases CTL activation and suppresses colon tumor growth in vivo. Our findings determine that PD-L1 restrains PD-1+Nrp1loTGFβ+ Treg cells to suppress IL6+ neutrophil tumor recruitment to sustain CTL activation to control inflammation-driven colorectal tumorigenesis.

Oral squamous cell carcinomas drive monocytes into immunosuppressive CD25+CD163+CD206+ macrophages

Tumor-associated macrophages (TAMs) are major cellular components in the tumor microenvironment of oral squamous cell carcinomas (OSCCs). Most of these TAMs derive from circulating monocytes that differentiate in situ. In this work, we show that cell culture media (CM) derived from two OSCC cell lines, H413 and TR146, promote monocyte differentiation into M2 macrophages, characterized by a high expression of CD163, CD206 and a low expression of CD11c, CD86 and HLA-DR. Monocyte-derived macrophages (moMΦ) differentiated by CM from H413 cells (H413-CM) were also unable to activate allogeneic T cells, and inhibited T cell activation and proliferation induced by CD3/CD28 stimulation. By culturing monocytes with fractionated H413-CM, we found that soluble proteins mediated CD163+CD206+ moMΦ differentiation, discarding a role for small metabolites and extracellular vesicles. Differential proteomic analyses on H413-CM fractions revealed the presence of several proteins, including the complement factor H or plasminogen activator inhibitor 1, as potential candidates to induce CD163+CD206+ moMΦ differentiation. Finally, RNAseq transcriptomic analyses of H413-CM conditioned moMΦ, identified a expression profile signature involving cytokines and cytokine receptors, which surprisingly included IL2RA (encoding CD25). CD25 enhanced expression was confirmed on H143-CM moMΦ. Collectively, these data indicate that the CM from OSCC cell lines promotes the differentiation of functionally immunosuppressive macrophages resembling TAMs, and contributes to the understanding of how OSCCs create an immunosuppressive cellular environment that favors tumor growth.

BMP suppresses Wnt signaling via the Bcl11b-regulated NuRD complex to maintain intestinal stem cells

Lgr5+ intestinal stem cells (ISCs) are crucial for the intestinal epithelium renewal and regeneration after injury. However, the mechanism underlying the interplay between Wnt and BMP signaling in this process is not fully understood. Here we report that Bcl11b, which is downregulated by BMP signaling, enhances Wnt signaling to maintain Lgr5+ ISCs and thus promotes the regeneration of the intestinal epithelium upon injury. Loss of Bcl11b function leads to a significant decrease of Lgr5+ ISCs in both intestinal crypts and cultured organoids. Mechanistically, BMP suppresses the expression of Bcl11b, which can positively regulate Wnt target genes by inhibiting the function of the Nucleosome Remodeling and Deacetylase (NuRD) complex and facilitating the β-catenin-TCF4 interaction. Bcl11b can also promote intestinal epithelium repair after injuries elicited by both irradiation and DSS-induced inflammation. Furthermore, Bcl11b deletion prevents proliferation and tumorigenesis of colorectal cancer cells. Together, our findings suggest that BMP suppresses Wnt signaling via Bcl11b regulation, thus balancing homeostasis and regeneration in the intestinal epithelium.

Suppression of epithelial proliferation and tumourigenesis by immunoglobulin A

Immunoglobulin A (IgA) is the most abundant antibody isotype produced across mammals and plays a specialized role in mucosal homeostasis 1 . Constantly secreted into the lumen of the intestine, IgA binds commensal microbiota to regulate their colonization and function 2,3 with unclear implications for health. IgA deficiency is common in humans but is difficult to study due to its complex aetiology and comorbidities 4-8 . Using genetically and environmentally controlled mice, here we show that IgA-deficient animals have increased susceptibility to endogenous colorectal tumours. Cellular and molecular analyses revealed that, in the absence of IgA, colonic epithelial cells induce antibacterial factors and accelerate cell cycling in response to the microbiota. Oral treatment with IgA was sufficient to both reduce steady-state proliferation and protect mice from tumours, but this function was due to antibody structure rather than binding specificity. In both organoid and monolayer culture systems, IgA directly suppressed epithelial growth. Co-immunoprecipitation mass spectrometry and a targeted CRISPR screen identified DMBT1 as an IgA-binding epithelial surface protein required for IgA-mediated suppression of proliferation. Together, IgA and DMBT1 regulate Notch signalling and tune the normal cycling of absorptive colonocyte progenitors. In mice, deleting the transmembrane and cytoplasmic signalling portions of DMBT1 or blocking Notch signalling was sufficient to reverse both the increased proliferation and tumour susceptibility of IgA knockouts. These experiments establish a homeostatic function for IgA in tempering physiological epithelial responses to microbiota to maintain mucosal health.

Single-cell spatiotemporal analysis reveals alveolar dendritic cell-T cell immunity hubs defending against pulmonary infection

How immune cells are spatiotemporally coordinated in the lung to effectively monitor, respond to, and resolve infection and inflammation in primed form needs to be fully illustrated. Here we apply immunocartography, a high-resolution technique that integrates spatial and single-cell RNA sequencing (scRNA-seq) through deconvolution and co-localization analyses, to the SARS-CoV-2-infected Syrian hamster model. We generate a comprehensive transcriptome map of the whole process of pulmonary infection from physiological condition, infection initiation, severe pneumonia to natural recovery at organ scale and single-cell resolution, with 142,965 cells and 45 lung lobes from 25 hamsters at 5 time points. Integrative analysis identifies that alveolar dendritic cell-T cell immunity hubs, where Ccr7+Ido1+ dendritic cells, Cd160+Cd8+ T cells, and Tnfrsf4+Cd4+ T cells physiologically co-localize, rapidly expand during SARS-CoV-2 infection, eliminate SARS-CoV-2 with the aid of Slamf9+ macrophages, and then restore to physiological levels after viral clearance. We verify the presence of these cell subpopulations in the immunity hubs in normal and SARS-CoV-2-infected hACE2 mouse models, as well as in publicly available human scRNA-seq datasets, demonstrating the potential broad relevance of our findings in lung immunity.

Integrated metabolomics and proteomics analyses to reveal anticancer mechanism of hemp oil extract in colorectal cancer

Cannabis sativa L., with a rich history in Chinese folk medicine, includes hemp strains that offer substantial economic and medical benefits due to their non-addictive properties. Hemp has demonstrated various pharmaceutical activities, including anti-inflammatory, antioxidant, and anti-tumor effects. This study explores the potential of hemp oil extract (HOE) in treating colorectal cancer (CRC). Despite its promise, the specific anticancer mechanisms of HOE have not been well understood. To elucidate these mechanisms, we employed mass spectrometry-based metabolomics and proteomics to investigate the global effects of HOE on CRC cells. Additionally, bioinformatics approaches, including bulk RNA-seq and single-cell RNA-seq, were used to identify gene expression differences and cellular heterogeneity. The results were validated using flow cytometry, western blotting, and immunohistochemistry. Our findings reveal that HOE induces significant alterations in purine metabolism pathways, down-regulates c-MYC, and inhibits the expression of cell cycle-related proteins such as CCND1, CDK4, and CDK6, leading to cell cycle arrest in the G1 phase. This comprehensive analysis demonstrates that HOE effectively blocks the cell cycle in the G1 phase, thereby inhibiting colorectal cancer cell proliferation. These findings provide experimental evidence supporting the potential therapeutic use of hemp in medicine.

Spatial oncology: Translating contextual biology to the clinic

Microscopic examination of cells in their tissue context has been the driving force behind diagnostic histopathology over the past two centuries. Recently, the rise of advanced molecular biomarkers identified through single cell profiling has increased our understanding of cellular heterogeneity in cancer but have yet to significantly impact clinical care. Spatial technologies integrating molecular profiling with microenvironmental features are poised to bridge this translational gap by providing critical in situ context for understanding cellular interactions and organization. Here, we review how spatial tools have been used to study tumor ecosystems and their clinical applications. We detail findings in cell-cell interactions, microenvironment composition, and tissue remodeling for immune evasion and therapeutic resistance. Additionally, we highlight the emerging role of multi-omic spatial profiling for characterizing clinically relevant features including perineural invasion, tertiary lymphoid structures, and the tumor-stroma interface. Finally, we explore strategies for clinical integration and their augmentation of therapeutic and diagnostic approaches.

Targeting the gut microbiota: a new strategy for colorectal cancer treatment

BACKGROUND

How to reduce the high incidence rate and mortality of colorectal cancer (CRC) effectively is the focus of current research. Endoscopic treatment of early-stage CRC and colorectal adenomas (CAC) has a high success rate, but although several treatments are available for advanced CRC, such as surgery, radiotherapy, chemotherapy, and immunotherapy, the 5-year survival rate remains low. In view of the high incidence rate and mortality of CRC, early rational drug prevention for high-risk groups and exploration of alternative treatment modalities are particularly warranted. Gut microbiota is the target of and interacts with probiotics, prebiotics, aspirin, metformin, and various Chinese herbal medicines (CHMs) for the prevention of CRC. In addition, the anti-cancer mechanisms of probiotics differ widely among bacterial strains, and both bacterial strains and their derivatives and metabolites have been found to have anti-cancer effects. Gut microbiota plays a significant role in early drug prevention of CRC and treatment of CRC in its middle and late stages, targeting gut microbiota may be a new strategy for colorectal cancer treatment.

Characterization of cell states in biliary tract cancers identifies mechanisms of therapeutic resistance in a phase II trial of DKN-01/nivolumab

Biliary tract cancers demonstrate profound therapeutic resistance, and broadly effective therapies for refractory disease are lacking. We conducted a single-arm, second-line phase II trial combining DKN-01, a humanized monoclonal antibody targeting Dickkopf-1 (DKK-1), and nivolumab to treat patients with advanced biliary tract cancer (NCT04057365). No objective responses were seen. To identify mechanisms of treatment failure, we analyzed paired pre-treatment and on-treatment biopsies using scRNA-seq and constructed a detailed molecular classification of malignant and immune cells. We annotated five biliary tract cancer malignant cell states: classical, basal, mesenchymal, neural-like, and endothelial-like. Neural-like and endothelial-like states, which drive therapeutic resistance in other cancers, have not previously been described in BTC. Malignant cell states co-varied with distinct immune cell states, revealing diverse mechanisms of myeloid and T-cell mediated immune suppression, including M2 myeloid and terminally exhausted T cell programs that were induced by DKN-01/nivolumab. Here, we provide the first systematic classification of functionally annotated cell states in biliary tract cancer and provide new insight into resistance mechanisms to an immunotherapy combination that can inform the next generation of trials.

Visualizing scRNA-Seq data at population scale with GloScope

Increasingly, scRNA-Seq studies explore cell populations across different samples and the effect of sample heterogeneity on organism's phenotype. However, relatively few bioinformatic methods have been developed which adequately address the variation between samples for such population-level analyses. We propose a framework for representing the entire single-cell profile of a sample, which we call a GloScope representation. We implement GloScope on scRNA-Seq datasets from study designs ranging from 12 to over 300 samples and demonstrate how GloScope allows researchers to perform essential bioinformatic tasks at the sample-level, in particular visualization and quality control assessment.

ATF6 Promotes Colorectal Cancer Growth and Stemness by Regulating the Wnt Pathway

SIGNIFICANCE

ATF6 intervention reduces colorectal cancer cell and organoid viability by interrupting dysregulated Wnt signaling, identifying a novel facilitator and potential therapeutic target in colorectal cancer.

Neoadjuvant immunotherapy for dMMR and pMMR colorectal cancers: therapeutic strategies and putative biomarkers of response

Approximately 15% of locally advanced colorectal cancers (CRC) have DNA mismatch repair deficiency (dMMR), resulting in high microsatellite instability and a high tumour mutational burden. These cancers are frequently sensitive to therapy with immune-checkpoint inhibitors (ICIs) in the metastatic setting. This sensitivity seems to be even more pronounced in locally advanced disease, and organ preservation has become a realistic aim in ongoing clinical trials involving patients with dMMR rectal cancer. By contrast, metastatic CRCs with proficient DNA mismatch repair (pMMR) are generally resistant to ICIs, although a proportion of locally advanced pMMR tumours seem to have a high degree of sensitivity to ICIs. In this Review, we describe the current and emerging clinical evidence supporting the use of neoadjuvant ICIs in patients with dMMR and pMMR CRC, and the potential advantages (based on a biological rationale) of such an approach. We discuss how neoadjuvant 'window-of-opportunity' trials are being leveraged to progress biomarker discovery and we provide an overview of potential predictive biomarkers of response to ICIs, exploring the challenges faced when evaluating such biomarkers in biopsy-derived samples. Lastly, we describe how these discoveries might be used to drive a rational approach to trialling novel immunotherapeutic strategies in patients with pMMR CRC, with the ultimate aim of disease eradication and the generation of long-term immunosurveillance.

STGAT: Graph attention networks for deconvolving spatial transcriptomics data

BACKGROUND AND OBJECTIVE

Spatially resolved gene expression profiles are crucial for understanding tissue structure and function. However, the lack of single-cell resolution in these profiles demands their integration with single-cell RNA sequencing data for accurate dataset deconvolution. We propose STGAT, an innovative deconvolution method that leverages graph attention networks to enhance spatial transcriptomic (ST) data analysis.

METHODS

STGAT generates pseudo-ST data that more comprehensively represents the cell-type composition within real-ST data by using three different sampling probabilities. A comprehensive combined graph is then constructed to capture the complex relationships both across pseudo- and real-ST data and within each dataset. Moreover, integrating a graph attention network further enables STGAT to dynamically assign the weights to the connections between spots, significantly enhancing the accuracy of cell-type composition predictions.

RESULTS

Extensive comparative experiments on simulated and real-world datasets, demonstrate the superior performance of STGAT for cell-type deconvolution. The method outperforms six established methods and is robust across various biological contexts.

CONCLUSION

STGAT exhibits more precise results in cell-type composition inference that are more consistent with the known knowledge, suggesting its potential utility in improving the resolution and accuracy of spatial transcriptomics data analysis.

Craters on the melanoma surface facilitate tumor-immune interactions and demonstrate pathologic response to checkpoint blockade in humans

Immunotherapy leads to cancer eradication despite the tumor's immunosuppressive environment. Here, we used extended long-term in-vivo imaging and high-resolution spatial transcriptomics of endogenous melanoma in zebrafish, and multiplex imaging of human melanoma, to identify domains that facilitate immune response during immunotherapy. We identified crater-shaped pockets at the margins of zebrafish and human melanoma, rich with beta-2 microglobulin (B2M) and antigen recognition molecules. The craters harbor the highest density of CD8+ T cells in the tumor. In zebrafish, CD8+ T cells formed prolonged interactions with melanoma cells within craters, characteristic of antigen recognition. Following immunostimulatory treatment, the craters enlarged and became the major site of activated CD8+ T cell accumulation and tumor killing that was B2M dependent. In humans, craters predicted immune response to ICB therapy, showing response better than high T cell infiltration. This marks craters as potential new diagnostic tool for immunotherapy success and targets to enhance ICB response.

Recent progress and applications of single-cell sequencing technology in breast cancer

Single-cell RNA sequencing (scRNA-seq) technology enables the precise analysis of individual cell transcripts with high sensitivity and throughput. When integrated with multiomics technologies, scRNA-seq significantly enhances the understanding of cellular diversity, particularly within the tumor microenvironment. Similarly, single-cell DNA sequencing has emerged as a powerful tool in cancer research, offering unparalleled insights into the genetic heterogeneity and evolution of tumors. In the context of breast cancer, this technology holds substantial promise for decoding the intricate genomic landscape that drives disease progression, treatment resistance, and metastasis. By unraveling the complexities of tumor biology at a granular level, single-cell DNA sequencing provides a pathway to advancing our comprehension of breast cancer and improving patient outcomes through personalized therapeutic interventions. As single-cell sequencing technology continues to evolve and integrate into clinical practice, its application is poised to revolutionize the diagnosis, prognosis, and treatment strategies for breast cancer. This review explores the potential of single-cell sequencing technology to deepen our understanding of breast cancer, highlighting key approaches, recent advancements, and the role of the tumor microenvironment in disease plasticity. Additionally, the review discusses the impact of single-cell sequencing in paving the way for the development of personalized therapies.

The burgeoning spatial multi-omics in human gastrointestinal cancers

The development and progression of diseases in multicellular organisms unfold within the intricate three-dimensional body environment. Thus, to comprehensively understand the molecular mechanisms governing individual development and disease progression, precise acquisition of biological data, including genome, transcriptome, proteome, metabolome, and epigenome, with single-cell resolution and spatial information within the body's three-dimensional context, is essential. This foundational information serves as the basis for deciphering cellular and molecular mechanisms. Although single-cell multi-omics technology can provide biological information such as genome, transcriptome, proteome, metabolome, and epigenome with single-cell resolution, the sample preparation process leads to the loss of spatial information. Spatial multi-omics technology, however, facilitates the characterization of biological data, such as genome, transcriptome, proteome, metabolome, and epigenome in tissue samples, while retaining their spatial context. Consequently, these techniques significantly enhance our understanding of individual development and disease pathology. Currently, spatial multi-omics technology has played a vital role in elucidating various processes in tumor biology, including tumor occurrence, development, and metastasis, particularly in the realms of tumor immunity and the heterogeneity of the tumor microenvironment. Therefore, this article provides a comprehensive overview of spatial transcriptomics, spatial proteomics, and spatial metabolomics-related technologies and their application in research concerning esophageal cancer, gastric cancer, and colorectal cancer. The objective is to foster the research and implementation of spatial multi-omics technology in digestive tumor diseases. This review will provide new technical insights for molecular biology researchers.

MSIsensor-RNA: Microsatellite Instability Detection for Bulk and Single-cell Gene Expression Data

Microsatellite instability (MSI) is an indispensable biomarker in cancer immunotherapy. Currently, MSI scoring methods by high-throughput omics methods have gained popularity and demonstrated better performance than the gold standard method for MSI detection. However, the MSI detection method on expression data, especially single-cell expression data, is still lacking, limiting the scope of clinical application and prohibiting the investigation of MSI at a single-cell level. Herein, we developed MSIsensor-RNA, an accurate, robust, adaptable, and standalone software to detect MSI status based on expression values of MSI-associated genes. We demonstrated the favorable performance and promise of MSIsensor-RNA in both bulk and single-cell gene expression data in multiplatform technologies including RNA sequencing (RNA-seq), microarray, and single-cell RNA-seq. MSIsensor-RNA is a versatile, efficient, and robust method for MSI status detection from both bulk and single-cell gene expression data in clinical studies and applications. MSIsensor-RNA is available at https://github.com/xjtu-omics/msisensor-rna.

Powerful microscopy technologies decode spatially organized cellular networks that drive response to immunotherapy in humans

In tumors, immune cells organize into networks of different sizes and composition, including complex tertiary lymphoid structures and recently identified networks centered around the chemokines CXCL9/10/11 and CCL19. New commercially available highly multiplexed microscopy using cyclical RNA in situ hybridization and antibody-based approaches have the potential to establish the organization of the immune response in human tissue and serve as a foundation for future immunology research.

The power of many: Multilevel targeting of representative chemokine and metabolite GPCRs in personalized cancer therapy

G protein-coupled receptors (GPCRs) are vital cell surface receptors that govern a myriad of physiological functions. Despite their crucial role in regulating antitumor immunity and tumorigenesis, therapeutic applications targeting GPCRs in oncology are currently limited. This review offers a focused examination of selected protumorigenic chemokine and metabolite-sensing GPCRs. Specifically, the review highlights five GPCRs able to orchestrate tumor immunobiology at three main levels: tumor immunity, cancer cell expansion, and blood vessel development. The review culminates by illuminating emerging therapies and discussing innovative strategies to harness the full potential of GPCR-targeted treatments, by applying a multireceptor and patient-specific logic.

An isoform-resolution transcriptomic atlas of colorectal cancer from long-read single-cell sequencing

Colorectal cancer (CRC) ranks as the second leading cause of cancer deaths globally. In recent years, short-read single-cell RNA sequencing (scRNA-seq) has been instrumental in deciphering tumor heterogeneities. However, these studies only enable gene-level quantification but neglect alterations in transcript structures arising from alternative end processing or splicing. In this study, we integrated short- and long-read scRNA-seq of CRC samples to build an isoform-resolution CRC transcriptomic atlas. We identified 394 dysregulated transcript structures in tumor epithelial cells, including 299 resulting from various combinations of splicing events. Second, we characterized genes and isoforms associated with epithelial lineages and subpopulations exhibiting distinct prognoses. Among 31,935 isoforms with novel junctions, 330 were supported by The Cancer Genome Atlas RNA-seq and mass spectrometry data. Finally, we built an algorithm that integrated novel peptides derived from open reading frames of recurrent tumor-specific transcripts with mass spectrometry data and identified recurring neoepitopes that may aid the development of cancer vaccines.

Cancer cell states: Lessons from ten years of single-cell RNA-sequencing of human tumors

Human tumors are intricate ecosystems composed of diverse genetic clones and malignant cell states that evolve in a complex tumor micro-environment. Single-cell RNA-sequencing (scRNA-seq) provides a compelling strategy to dissect this intricate biology and has enabled a revolution in our ability to understand tumor biology over the last ten years. Here we reflect on this first decade of scRNA-seq in human tumors and highlight some of the powerful insights gleaned from these studies. We first focus on computational approaches for robustly defining cancer cell states and their diversity and highlight some of the most common patterns of gene expression intra-tumor heterogeneity (eITH) observed across cancer types. We then discuss ambiguities in the field in defining and naming such eITH programs. Finally, we highlight critical developments that will facilitate future research and the broader implementation of these technologies in clinical settings.

Effect of neoadjuvant chemoradiotherapy with or without PD-1 antibody sintilimab in pMMR locally advanced rectal cancer: A randomized clinical trial

Neoadjuvant chemoradiotherapy (NACRT) was the standard treatment for patients with locally advanced rectal cancer (LARC) with proficient mismatch repair (pMMR) proteins. In this randomized phase 2 trial (ClinicalTrial.gov: NCT04304209), 134 pMMR LARC patients were randomly (1:1) assigned to receive NACRT or NACRT and the programmed cell death protein 1 (PD-1) antibody sintilimab. As the primary endpoint, the total complete response (CR) rate is 26.9% (18/67, 95% confidence interval [CI] 16.0%-37.8%) and 44.8% (30/67, 95% CI 32.6%-57.0%) in the control and experimental arm, respectively, with significant difference (p = 0.031 for chi-squared test). Response ratio is 1.667 (95% CI 1.035-2.683). Immunohistochemistry shows PD-1 ligand 1 (PD-L1) combined positive score is associated with the synergistic effect. The safety profile is similar between the arms. Adding the PD-1 antibody sintilimab to NACRT significantly increases the CR rate in pMMR LARC, with a manageable safety profile. PD-L1 positivity may help identify patients who might benefit most from the combination therapy.

Answering open questions in biology using spatial genomics and structured methods

Genomics methods have uncovered patterns in a range of biological systems, but obscure important aspects of cell behavior: the shapes, relative locations, movement, and interactions of cells in space. Spatial technologies that collect genomic or epigenomic data while preserving spatial information have begun to overcome these limitations. These new data promise a deeper understanding of the factors that affect cellular behavior, and in particular the ability to directly test existing theories about cell state and variation in the context of morphology, location, motility, and signaling that could not be tested before. Rapid advancements in resolution, ease-of-use, and scale of spatial genomics technologies to address these questions also require an updated toolkit of statistical methods with which to interrogate these data. We present a framework to respond to this new avenue of research: four open biological questions that can now be answered using spatial genomics data paired with methods for analysis. We outline spatial data modalities for each open question that may yield specific insights, discuss how conflicting theories may be tested by comparing the data to conceptual models of biological behavior, and highlight statistical and machine learning-based tools that may prove particularly helpful to recover biological understanding.

A best practices framework for spatial biology studies in drug discovery and development: enabling successful cohort studies using digital spatial profiling

The discovery of biomarkers, essential for successful drug development, is often hindered by the limited availability of tissue samples, typically obtained through core needle biopsies. Standard 'omics platforms can consume significant amounts of tissue, forcing scientist to trade off spatial context for high-plex assays, such as genome-wide assays. While bulk gene expression approaches and standard single-cell transcriptomics have been valuable in defining various molecular and cellular mechanisms, they do not retain spatial context. As such, they have limited power in resolving tissue heterogeneity and cell-cell interactions. Current spatial transcriptomics platforms offer limited transcriptome coverage and have low throughput, restricting the number of samples that can be analyzed daily or even weekly. While the Digital Spatial Profiling (DSP) method does not provide single-cell resolution, it presents a significant advancement by enabling scalable whole transcriptome and ultrahigh-plex protein analysis from distinct tissue compartments and structures using a single tissue slide. These capabilities overcome significant constraints in biomarker analysis in solid tissue specimens. These advancements in tissue profiling play a crucial role in deepening our understanding of disease biology and in identifying potential therapeutic targets and biomarkers. To enhance the use of spatial biology tools in drug discovery and development, the DSP Scientific Consortium has created best practices guidelines. These guidelines, built on digital spatial profiling data and expertise, offer a practical framework for designing spatial studies and using current and future spatial biology platforms. The aim is to improve tissue analysis in all research areas supporting drug discovery and development.

Deciphering the spatiotemporal transcriptional landscape of intestinal diseases (Review)

The intestines are the largest barrier organ in the human body. The intestinal barrier plays a crucial role in maintaining the balance of the intestinal environment and protecting the intestines from harmful bacterial invasion. Single‑cell RNA sequencing technology allows the detection of the different cell types in the intestine in two dimensions and the exploration of cell types that have not been fully characterized. The intestinal mucosa is highly complex in structure, and its proper functioning is linked to multiple structures in the proximal‑distal intestinal and luminal‑mucosal axes. Spatial localization is at the core of the efforts to explore the interactions between the complex structures. Spatial transcriptomics (ST) is a method that allows for comprehensive tissue analysis and the acquisition of spatially separated genetic information from individual cells, while preserving their spatial location and interactions. This approach also prevents the loss of fragile cells during tissue disaggregation. The emergence of ST technology allows us to spatially dissect enzymatic processes and interactions between multiple cells, genes, proteins and signals in the intestine. This includes the exchange of oxygen and nutrients in the intestine, different gradients of microbial populations and the role of extracellular matrix proteins. This regionally precise approach to tissue studies is gaining more acceptance and is increasingly applied in the investigation of disease mechanisms related to the gastrointestinal tract. Therefore, this review summarized the application of ST in gastrointestinal diseases.

Tertiary lymphoid structures in anticancer immunity

Tertiary lymphoid structures (TLS) are transient ectopic lymphoid aggregates where adaptive antitumour cellular and humoral responses can be elaborated. Initially described in non-small cell lung cancer as functional immune lymphoid structures associated with better clinical outcome, TLS have also been found in many other carcinomas, as well as melanomas and sarcomas, and associated with improved response to immunotherapy. The manipulation of TLS as a therapeutic strategy is now coming of age owing to the likely role of TLS in the improved survival of patients with cancer receiving immune checkpoint inhibitor treatment. TLS have also garnered considerable interest as a predictive biomarker of the response to antitumour therapies, including immune checkpoint blockade and, possibly, chemotherapy. However, several important questions still remain regarding the definition of TLS in terms of both their cellular composition and functions. Here, we summarize the current views on the composition of TLS at different stages of their development. We also discuss the role of B cells and T cells associated with TLS and their dialogue in mounting antibody and cellular antitumour responses, as well as some of the various mechanisms that negatively regulate antitumour activity of TLS. The prognostic value of TLS to the clinical outcome of patients with cancer and the relationship between TLS and the response to therapy are then addressed. Finally, we present some preclinical evidence that favours the idea that manipulating the formation and function of TLS could lead to a potent next-generation cancer immunotherapy.

Spatial landscapes of cancers: insights and opportunities

Solid tumours comprise many different cell types organized in spatially structured arrangements, with substantial intratumour and intertumour heterogeneity. Advances in spatial profiling technologies over the past decade hold promise to capture the complexity of these cellular architectures to build a holistic view of the intricate molecular mechanisms that shape the tumour ecosystem. Some of these mechanisms act at the cellular scale and are controlled by cell-autonomous programmes or communication between nearby cells, whereas other mechanisms result from coordinated efforts between large networks of cells and extracellular molecules organized into tissues and organs. In this Review we provide insights into the application of single-cell and spatial profiling tools, with a focus on spatially resolved transcriptomic tools developed to understand the cellular architecture of the tumour microenvironment and identify opportunities to use them to improve clinical management of cancers.

Integrative single-cell analysis of human colorectal cancer reveals patient stratification with distinct immune evasion mechanisms

The tumor microenvironment (TME) considerably influences colorectal cancer (CRC) progression, therapeutic response and clinical outcome, but studies of interindividual heterogeneities of the TME in CRC are lacking. Here, by integrating human colorectal single-cell transcriptomic data from approximately 200 donors, we comprehensively characterized transcriptional remodeling in the TME compared to noncancer tissues and identified a rare tumor-specific subset of endothelial cells with T cell recruitment potential. The large sample size enabled us to stratify patients based on their TME heterogeneity, revealing divergent TME subtypes in which cancer cells exploit different immune evasion mechanisms. Additionally, by associating single-cell transcriptional profiling with risk genes identified by genome-wide association studies, we determined that stromal cells are major effector cell types in CRC genetic susceptibility. In summary, our results provide valuable insights into CRC pathogenesis and might help with the development of personalized immune therapies.

FAT1 as a tumor mutation burden specific gene affects the immunotherapy effect in head and neck squamous cell cancer

BACKGROUND

Response to immunotherapy is the main challenge of head and neck squamous cancer (HNSCC) treatment. Previous studies have indicated that tumor mutational burden (TMB) is associated with prognosis, but it is not always a precise index. Hence, investigating specific genetic mutations and tumor microenvironment (TME) changes in TMB-high patients is essential for precision therapy of HNSCC.

METHODS

A total of 33 HNSCC patients were enrolled in this study. We calculated the TMB score based on next-generation sequencing (NGS) sequencing and grouped these patients based on TMB score. Then, we examined the immune microenvironment of HNSCC using assessments of the bulk transcriptome and the single-cell RNA sequence (scRNA-seq) focusing on the molecular nature of TMB and mutations in HNSCC from our cohort. The association of the mutation pattern and TMB was analyzed in The Cancer Genome Atlas (TCGA) and validated by our cohort.

RESULTS

33 HNSCC patients were divided into three groups (TMB-low, -medium, and -high) based on TMB score. In the result of 520-gene panel sequencing data, we found that FAT1 and LRP1B mutations were highly prevalent in TMB-high patients. FAT1 mutations are associated with resistance to immunotherapy in HNSCC patients. This involves many metabolism-related pathways like RERE, AIRE, HOMER1, etc. In the scRNA-seq data, regulatory T cells (Tregs), monocytes, and DCs were found mainly enriched in TMB-high samples.

CONCLUSION

Our analysis unraveled the FAT1 gene as an assistant predictor when we use TMB as a biomarker of drug resistance in HNSCC. Tregs, monocytes, and dendritic cells (DCs) were found mainly enriched in TMB-high samples.

Mechanisms of metastatic colorectal cancer

Despite extensive research and improvements in understanding colorectal cancer (CRC), its metastatic form continues to pose a substantial challenge, primarily owing to limited therapeutic options and a poor prognosis. This Review addresses the emerging focus on metastatic CRC (mCRC), which has historically been under-studied compared with primary CRC despite its lethality. We delve into two crucial aspects: the molecular and cellular determinants facilitating CRC metastasis and the principles guiding the evolution of metastatic disease. Initially, we examine the genetic alterations integral to CRC metastasis, connecting them to clinically marked characteristics of advanced CRC. Subsequently, we scrutinize the role of cellular heterogeneity and plasticity in metastatic spread and therapy resistance. Finally, we explore how the tumour microenvironment influences metastatic disease, emphasizing the effect of stromal gene programmes and the immune context. The ongoing research in these fields holds immense importance, as its future implications are projected to revolutionize the treatment of patients with mCRC, hopefully offering a promising outlook for their survival.

Integrated single-cell and bulk RNA-seq analysis identifies a prognostic T-cell signature in colorectal cancer

Colorectal cancer (CRC) is a major contributor to global morbidity and mortality, necessitating more effective therapeutic approaches. T cells, prominent in the tumor microenvironment, exert a crucial role in modulating immunotherapeutic responses and clinical outcomes in CRC. This study introduces a pioneering method for characterizing the CRC immune microenvironment using single-cell sequencing data. Unlike previous approaches, which focused on individual T-cell signature genes, we utilized overall infiltration levels of colorectal cancer signature T-cells. Through weighted gene co-expression network analysis, Lasso regression, and StepCox analysis, we developed a prognostic risk model, TRGS (T-cell related genes signatures), based on six T cell-related genes. Multivariate Cox analysis identified TRGS as an independent prognostic factor for CRC, showcasing its superior predictive efficacy compared to existing immune-related prognostic models. Immunoreactivity analysis revealed higher Immunophenoscore and lower Tumor Immune Dysfunction and Exclusion scores in the low-risk group, indicating potential responsiveness to immune checkpoint inhibitor therapy. Additionally, patients in the low-risk group demonstrated heightened sensitivity to 5-fluorouracil-based chemotherapy regimens. In summary, TRGS emerges as a standalone prognostic biomarker for CRC, offering insights to optimize patient responses to immunotherapy and chemotherapy, thereby laying the groundwork for personalized tumor management strategies.

Community assessment of methods to deconvolve cellular composition from bulk gene expression

We evaluate deconvolution methods, which infer levels of immune infiltration from bulk expression of tumor samples, through a community-wide DREAM Challenge. We assess six published and 22 community-contributed methods using in vitro and in silico transcriptional profiles of admixed cancer and healthy immune cells. Several published methods predict most cell types well, though they either were not trained to evaluate all functional CD8+ T cell states or do so with low accuracy. Several community-contributed methods address this gap, including a deep learning-based approach, whose strong performance establishes the applicability of this paradigm to deconvolution. Despite being developed largely using immune cells from healthy tissues, deconvolution methods predict levels of tumor-derived immune cells well. Our admixed and purified transcriptional profiles will be a valuable resource for developing deconvolution methods, including in response to common challenges we observe across methods, such as sensitive identification of functional CD4+ T cell states.

Secreted PTEN binds PLXDC2 on macrophages to drive antitumor immunity and tumor suppression

Loss of phosphatase and tensin homolog (PTEN) has been linked to an immunosuppressive tumor microenvironment, but its underlying mechanisms remain largely enigmatic. Here, we report that PTEN can be secreted by the transmembrane emp24 domain-containing protein 10 (TMED10)-channeled protein secretion pathway. Inhibiting PTEN secretion from tumor cells contributes to immunosuppression and impairs the tumor-suppressive role of PTEN, while intratumoral injection of PTEN protein promotes antitumor immunity and suppresses tumor growth in mice. Mechanistically, extracellular PTEN binds to the plexin domain-containing protein 2 (PLXDC2) on macrophages, triggering subsequent activation of JAK2-STAT1 signaling, which switches tumor-associated macrophages (TAMs) from the immunosuppressive to inflammatory phenotype, leading to enhanced activation of CD8+ T and natural killer cells. Importantly, PTEN treatment also enhances the therapeutic efficacy of anti-PD-1 treatment in mice and reverses the immune-suppressive phenotype of patient-derived primary TAMs. These data identify a cytokine-like role of PTEN in immune activation and tumor suppression and demonstrate the therapeutic potential for extracellular administration of PTEN in cancer immunotherapy.

Profiling cell identity and tissue architecture with single-cell and spatial transcriptomics

Single-cell transcriptomics has broadened our understanding of cellular diversity and gene expression dynamics in healthy and diseased tissues. Recently, spatial transcriptomics has emerged as a tool to contextualize single cells in multicellular neighbourhoods and to identify spatially recurrent phenotypes, or ecotypes. These technologies have generated vast datasets with targeted-transcriptome and whole-transcriptome profiles of hundreds to millions of cells. Such data have provided new insights into developmental hierarchies, cellular plasticity and diverse tissue microenvironments, and spurred a burst of innovation in computational methods for single-cell analysis. In this Review, we discuss recent advancements, ongoing challenges and prospects in identifying and characterizing cell states and multicellular neighbourhoods. We discuss recent progress in sample processing, data integration, identification of subtle cell states, trajectory modelling, deconvolution and spatial analysis. Furthermore, we discuss the increasing application of deep learning, including foundation models, in analysing single-cell and spatial transcriptomics data. Finally, we discuss recent applications of these tools in the fields of stem cell biology, immunology, and tumour biology, and the future of single-cell and spatial transcriptomics in biological research and its translation to the clinic.

Quantized multi-task learning for context-specific representations of gene network dynamics

While often represented as static entities, gene networks are highly context-dependent. Here, we developed a multi-task learning strategy to yield context-specific representations of gene network dynamics. We assembled a corpus comprising ~103 million human single-cell transcriptomes from a broad range of tissues and diseases and performed a two stage pretraining, first with non-malignant cells to generate a foundational model and then with continual learning on cancer cells to tune the model to the cancer domain. We performed multi-task learning with the foundational model to learn context-specific representations of a broad range of cell types, tissues, developmental stages, and diseases. We then leveraged the cancer-tuned model to jointly learn cell states and predict tumor-restricting factors within the colorectal tumor microenvironment. Model quantization allowed resource-efficient fine-tuning and inference while preserving biological knowledge. Overall, multi-task learning enables context-specific disease modeling that can yield contextual predictions of candidate therapeutic targets for human disease.

Dysfunctional tumor-infiltrating Vδ1 + T lymphocytes in microsatellite-stable colorectal cancer

Although γδ T cells are known to participate in immune dysregulation in solid tumors, their relevance to human microsatellite-stable (MSS) colorectal cancer (CRC) is still undefined. Here, using integrated gene expression analysis and T cell receptor sequencing, we characterized γδ T cells in MSS CRC, with a focus on Vδ1 + T cells. We identified Vδ1+ T cells with shared motifs in the third complementarity-determining region of the δ-chain, reflective of antigen recognition. Changes in gene and protein expression levels suggested a dysfunctional effector state of Vδ1+ T cells in MSS CRC, distinct from Vδ1+ T cells in microsatellite-instable (MSI). Interaction analysis highlighted an immunosuppressive role of fibroblasts in the dysregulation of Vδ1+ T cells in MSS CRC via the TIGIT-NECTIN2 axis. Blocking this pathway with a TIGIT antibody partially restored cytotoxicity of the dysfunctional Vδ1 phenotype. These results define an operative pathway in γδ T cells in MSS CRC.

The Wdr5-H3K4me3 Epigenetic Axis Regulates Pancreatic Tumor Immunogenicity and Immune Suppression

The WDR5/MLL1-H3K4me3 epigenetic axis is often activated in both tumor cells and tumor-infiltrating immune cells to drive various cellular responses in the tumor microenvironment and has been extensively studied in hematopoietic cancer, but its respective functions in tumor cells and immune cells in the context of tumor growth regulation of solid tumor is still incompletely understood. We report here that WDR5 exhibits a higher expression level in human pancreatic tumor tissues compared with adjacent normal pancreas. Moreover, WDR5 expression is negatively correlated with patients' response to chemotherapy or immunotherapy in human colon cancer and melanoma. However, WDR5 expression is positively correlated with the HLA level in human cancer cells, and H3K4me3 enrichment is observed at the promoter region of the HLA-A, HLA-B, and HLA-C genes in pancreatic cancer cells. Using mouse tumor cell lines and in vivo tumor models, we determined that WDR5 deficiency or inhibition significantly represses MHC I expression in vitro and in vivo in pancreatic tumor cells. Mechanistically, we determine that WDR5 deficiency inhibits H3K4me3 deposition at the MHC I (H2K) promoter region to repress MHC I (H2K) transcription. On the other hand, WDR5 depletion leads to the effective downregulation of immune checkpoints and immunosuppressive cytokines, including TGFβ and IL6, in the pancreatic tumor microenvironments. Our data determine that WDR5 not only regulates tumor cell immunogenicity to suppress tumor growth but also activates immune suppressive pathways to promote tumor immune evasion. Selective activation of the WDR5-MHC I pathway and/or selective inhibition of the WDR5-immune checkpoint and WDR5-cytokine pathways should be considered in WDR5-based epigenetic cancer immunotherapy.

Interleukin-17F suppressed colon cancer by enhancing caspase 4 mediated pyroptosis of endothelial cells

The combination of anti-angiogenic treatment and immunotherapy presents a promising strategy against colon cancer. Interleukin-17F (IL-17F) emerges as a critical immune cell cytokine expressed in colonic epithelial cells, demonstrating potential in inhibiting angiogenesis. In order to clarify the roles of IL-17F in the colon cancer microenvironment and elucidate its mechanism, we established a mouse colon carcinoma cell line CT26 overexpressing IL-17F and transplanted it subcutaneously into syngeneic BALB/c mice. We also analyzed induced colon tumor in IL-17F knockout and wild type mice. Our results demonstrated that IL-17F could suppress colon tumor growth in vivo with inhibited angiogenesis and enhanced recruitment of cysteine-cysteine motif chemokine receptor 6 (CCR6) positive immune cells. Additionally, IL-17F suppressed the tube formation, cell growth and migration of endothelial cells EOMA in vitro. Comprehensive bioinformatics analysis of transcriptome profiles between EOMA cells and those treated with three different concentrations of IL-17F identified 109 differentially expressed genes. Notably, a potential new target, Caspase 4, showed increased expressions after IL-17F treatment in endothelial cells. Further molecular validation revealed a novel downstream signaling for IL-17F: IL-17F enhanced Caspase 4/GSDMD signaling of endothelial cells, CT26 cells and CT26 transplanted tumors, while IL-17F knockout colon tumors exhibited decreased Caspase 4/GSDMD signaling. The heightened expression of the GSDMD N-terminus, coupled with increased cellular propidium iodide (PI) uptake and lactate dehydrogenase (LDH) release, revealed that IL-17F promoted pyroptosis of endothelial cells. Altogether, IL-17F could modulate the colon tumor microenvironment with inhibited angiogenesis, underscoring its potential as a therapeutic target for colon cancer.