Spatially organized multicellular immune hubs in human colorectal cancer

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.

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.

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.

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.

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.

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.

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.

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.

Microsatellite instability at U2AF-binding polypyrimidic tract sites perturbs alternative splicing during colorectal cancer initiation

BACKGROUND

Microsatellite instability (MSI) due to mismatch repair deficiency (dMMR) is common in colorectal cancer (CRC). These cancers are associated with somatic coding events, but the noncoding pathophysiological impact of this genomic instability is yet poorly understood. Here, we perform an analysis of coding and noncoding MSI events at the different steps of colorectal tumorigenesis using whole exome sequencing and search for associated splicing events via RNA sequencing at the bulk-tumor and single-cell levels.

RESULTS

Our results demonstrate that MSI leads to hundreds of noncoding DNA mutations, notably at polypyrimidine U2AF RNA-binding sites which are endowed with cis-activity in splicing, while higher frequency of exon skipping events are observed in the mRNAs of MSI compared to non-MSI CRC. At the DNA level, these noncoding MSI mutations occur very early prior to cell transformation in the dMMR colonic crypt, accounting for only a fraction of the exon skipping in MSI CRC. At the RNA level, the aberrant exon skipping signature is likely to impair colonic cell differentiation in MSI CRC affecting the expression of alternative exons encoding protein isoforms governing cell fate, while also targeting constitutive exons, making dMMR cells immunogenic in early stage before the onset of coding mutations. This signature is characterized by its similarity to the oncogenic U2AF1-S34F splicing mutation observed in several other non-MSI cancer.

CONCLUSIONS

Overall, these findings provide evidence that a very early RNA splicing signature partly driven by MSI impairs cell differentiation and promotes MSI CRC initiation, far before coding mutations which accumulate later during MSI tumorigenesis.

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.

Histopathological-Based Analysis of Human Kidney Spatial Transcriptomics Data: Toward Precision Pathology

The application of spatial transcriptomics (ST) technologies is booming and has already yielded important insights across many different tissues and disease models. In nephrology, ST technologies have helped to decipher the cellular and molecular mechanisms at work in kidney diseases and have allowed the recent creation of spatially anchored human kidney atlases in healthy and diseased kidney tissues. During ST data analysis, the obtained computationally annotated clusters are often superimposed on a histologic image without their initial identification being based on the morphologic and spatial analyses of the tissues and lesions. In this study, we conduct a histopathologic-based analysis of ST data on a human kidney sample corresponding as closely as possible to the reality of the interpretation of a kidney biopsy sample in a health care or research context. This study shows the feasibility of a morphology-based approach to interpreting ST data, helping to improve our understanding of the lesion phenomena at work in chronic kidney disease at both the cellular and the molecular level. Finally, we show that our newly identified pathology-based clusters can be accurately projected onto other slides from nephrectomy or needle biopsy samples. They thus serve as a reference for analyzing other kidney tissues, paving the way for the future of molecular microscopy and precision pathology.

CNTools: A computational toolbox for cellular neighborhood analysis from multiplexed images

Recent studies show that cellular neighborhoods play an important role in evolving biological events such as cancer and diabetes. Therefore, it is critical to accurately and efficiently identify cellular neighborhoods from spatially-resolved single-cell transcriptomic data or single-cell resolution tissue imaging data. In this work, we develop CNTools, a computational toolbox for end-to-end cellular neighborhood analysis on annotated cell images, comprising both the identification and analysis steps. It includes state-of-the-art cellular neighborhood identification methods and post-identification smoothing techniques, with our newly proposed Cellular Neighbor Embedding (CNE) method and Naive Smoothing technique, as well as several established downstream analysis approaches. We applied CNTools on three real-world CODEX datasets and evaluated identification methods with smoothing techniques quantitatively and qualitatively. It shows that CNE with Naive Smoothing overall outperformed other methods and revealed more convincing biological insights. We also provided suggestions on how to choose proper identification methods and smoothing techniques according to input data.

Advancements in 3D In Vitro Models for Colorectal Cancer

The process of drug discovery and pre-clinical testing is currently inefficient, expensive, and time-consuming. Most importantly, the success rate is unsatisfactory, as only a small percentage of tested drugs are made available to oncological patients. This is largely due to the lack of reliable models that accurately predict drug efficacy and safety. Even animal models often fail to replicate human-specific pathologies and human body's complexity. These factors, along with ethical concerns regarding animal use, urge the development of suitable human-relevant, translational in vitro models.

T cell dysfunction and therapeutic intervention in cancer

Recent advances in immunotherapy have affirmed the curative potential of T cell-based approaches for treating relapsed and refractory cancers. However, the therapeutic efficacy is limited in part owing to the ability of cancers to evade immunosurveillance and adapt to immunological pressure. In this Review, we provide a brief overview of cancer-mediated immunosuppressive mechanisms with a specific focus on the repression of the surveillance and effector function of T cells. We discuss CD8+ T cell exhaustion and functional heterogeneity and describe strategies for targeting the molecular checkpoints that restrict T cell differentiation and effector function to bolster immunotherapeutic effects. We also delineate the emerging contributions of the tumor microenvironment to T cell metabolism and conclude by highlighting discovery-based approaches for developing future cellular therapies. Continued exploration of T cell biology and engineering hold great promise for advancing therapeutic interventions for cancer.

Cancer organoids 2.0: modelling the complexity of the tumour immune microenvironment

The development of neoplasia involves a complex and continuous interplay between malignantly transformed cells and the tumour microenvironment (TME). Cancer immunotherapies targeting the immune TME have been increasingly validated in clinical trials but response rates vary substantially between tumour histologies and are often transient, idiosyncratic and confounded by resistance. Faithful experimental models of the patient-specific tumour immune microenvironment, capable of recapitulating tumour biology and immunotherapy effects, would greatly improve patient selection, target identification and definition of resistance mechanisms for immuno-oncology therapeutics. In this Review, we discuss currently available and rapidly evolving 3D tumour organoid models that capture important immune features of the TME. We highlight diverse opportunities for organoid-based investigations of tumour immunity, drug development and precision medicine.

Immunosuppression and phenotypic plasticity in an atlas of human hepatocholangiocarcinoma

Background

Hepatocholangiocarcinoma (H-ChC) has the clinicopathological features of both hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (iCCA) and is a more aggressive subtype of primary hepatic carcinoma than HCC or iCCA.

Methods

We sequenced 91,112 single-cell transcriptomes from 16 human samples to elucidate the molecular mechanisms underlying the coexistence of HCC and iCCA components in H-ChC.

Results

We observed two molecular subtypes of H-ChC at the whole-transcriptome level (CHP and CIP), where a metabolically active tumour cell subpopulation enriched in CHP was characterized by a cellular pre-differentiation property. To define the heterogeneity of tumours and their associated microenvironments, we observe greater tumour diversity in H-ChC than HCC and iCCA. H-ChC exhibits weaker immune cell infiltration and greater CD8+ exhausted T cell (Tex) dysfunction than HCC and iCCA. Then we defined two broad cell states of 6,852 CD8+ Tex cells: GZMK+ CD8+ Tex cells and terminal CD8+ Tex cells. GZMK+ CD8+ Tex cells exhibited higher infiltration of after treatment in H-ChC, the effector scores and expression of the immune checkpoints of them greatly increased after immunotherapy, which indicated that H-ChC might be more sensitive than HCC or iCCA to immunotherapy.

Conclusions

In this paper, H-ChC was explored, hoping to contribute to the study of mixed tumours in other cancers.

Targeting the devil: Strategies against cancer-associated fibroblasts in colorectal cancer

Cancer-associated fibroblasts (CAFs), as significant constituents of the tumor microenvironment (TME), play a pivotal role in the progression of cancers, including colorectal cancer (CRC). In this comprehensive review, we presented the origins and activation mechanisms of CAFs in CRC, elaborating on how CAFs drive tumor progression through their interactions with CRC cells, immune cells, vascular endothelial cells, and the extracellular matrix within the TME. We systematically outline the intricate web of interactions among CAFs, tumor cells, and other TME components, and based on this complex interplay, we summarize various therapeutic strategies designed to target CAFs in CRC. It is also essential to recognize that CAFs represent a highly heterogeneous group, encompassing various subtypes such as myofibroblastic CAF (myCAF), inflammatory CAF (iCAF), antigen-presenting CAF (apCAF), vessel-associated CAF (vCAF). Herein, we provide a summary of studies investigating the heterogeneity of CAFs in CRC and the characteristic expression patterns of each subtype. While the majority of CAFs contribute to the exacerbation of CRC malignancy, recent findings have revealed specific subtypes that exert inhibitory effects on CRC progression. Nevertheless, the comprehensive landscape of CAF heterogeneity still awaits exploration. We also highlight pivotal unanswered questions that need to be addressed before CAFs can be recognized as feasible targets for cancer treatment. In conclusion, the aim of our review is to elucidate the significance and challenges of advancing in-depth research on CAFs, while outlining the pathway to uncover the complex roles of CAFs in CRC and underscore their significant potential as therapeutic targets.

Antitumor Activity of a Novel LAIR1 Antagonist in Combination with Anti-PD1 to Treat Collagen-Rich Solid Tumors

We recently reported that resistance to PD-1 blockade in a refractory lung cancer-derived model involved increased collagen deposition and the collagen-binding inhibitory receptor leukocyte-associated immunoglobulin-like receptor 1 (LAIR1). Thus, we hypothesized that LAIR1 and collagen cooperated to suppress therapeutic response. In this study, we report that LAIR1 is associated with tumor stroma and is highly expressed by intratumoral myeloid cells in both human tumors and mouse models of cancer. Stroma-associated myeloid cells exhibit a suppressive phenotype and correlate with LAIR1 expression in human cancer. NGM438, a novel humanized LAIR1 antagonist mAb, elicits myeloid inflammation and allogeneic T-cell responses by binding to LAIR1 and blocking collagen engagement. Furthermore, a mouse-reactive NGM438 surrogate antibody sensitized refractory KP mouse lung tumors to anti-PD-1 therapy and resulted in increased intratumoral CD8+ T-cell content and inflammatory gene expression. These data place LAIR1 at the intersection of stroma and suppressive myeloid cells and support the notion that blockade of the LAIR1/collagen axis can potentially address resistance to checkpoint inhibitor therapy in the clinic.

The prognostic effect of tumor-associated macrophages in stage I-III colorectal cancer depends on T cell infiltration

BACKGROUND

Tumor-associated macrophages (TAMs) are associated with unfavorable patient prognosis in many cancer types. However, TAMs are a heterogeneous cell population and subsets have been shown to activate tumor-infiltrating T cells and confer a good patient prognosis. Data on the prognostic value of TAMs in colorectal cancer are conflicting. We investigated the prognostic effect of TAMs in relation to tumor-infiltrating T cells in colorectal cancers.

METHODS

The TAM markers CD68 and CD163 were analyzed by multiplex fluorescence immunohistochemistry and digital image analysis on tissue microarrays of 1720 primary colorectal cancers. TAM density in the tumor stroma was scored in relation to T cell density (stromal CD3+ and epithelial CD8+ cells) and analyzed in Cox proportional hazards models of 5-year relapse-free survival. Multivariable survival models included clinicopathological factors, MSI status and BRAFV600E mutation status.

RESULTS

High TAM density was associated with a favorable 5-year relapse-free survival in a multivariable model of patients with stage I-III tumors (p = 0.004, hazard ratio 0.94, 95% confidence interval 0.90-0.98). However, the prognostic effect was dependent on tumoral T-cell density. High TAM density was associated with a good prognosis in patients who also had high T-cell levels in their tumors, while high TAM density was associated with poorer prognosis in patients with low T-cell levels (pinteraction = 0.0006). This prognostic heterogeneity was found for microsatellite stable tumors separately.

CONCLUSIONS

This study supported a phenotypic heterogeneity of TAMs in colorectal cancer, and showed that combined tumor immunophenotyping of multiple immune cell types improved the prediction of patient prognosis.

Computational methods and biomarker discovery strategies for spatial proteomics: a review in immuno-oncology

Advancements in imaging technologies have revolutionized our ability to deeply profile pathological tissue architectures, generating large volumes of imaging data with unparalleled spatial resolution. This type of data collection, namely, spatial proteomics, offers invaluable insights into various human diseases. Simultaneously, computational algorithms have evolved to manage the increasing dimensionality of spatial proteomics inherent in this progress. Numerous imaging-based computational frameworks, such as computational pathology, have been proposed for research and clinical applications. However, the development of these fields demands diverse domain expertise, creating barriers to their integration and further application. This review seeks to bridge this divide by presenting a comprehensive guideline. We consolidate prevailing computational methods and outline a roadmap from image processing to data-driven, statistics-informed biomarker discovery. Additionally, we explore future perspectives as the field moves toward interfacing with other quantitative domains, holding significant promise for precision care in immuno-oncology.

ReCIDE: robust estimation of cell type proportions by integrating single-reference-based deconvolutions

In this study, we introduce Robust estimation of Cell type proportions by Integrating single-reference-based DEconvolutions (ReCIDE), an innovative framework for robust estimation of cell type proportions by integrating single-reference-based deconvolutions. ReCIDE outperforms existing approaches in benchmark and real datasets, particularly excelling in estimating rare cell type proportions. Through exploratory analysis on public bulk data of triple-negative breast cancer (TNBC) patients using ReCIDE, we demonstrate a significant correlation between the prognosis of TNBC patients and the proportions of both T cell and perivascular-like cell subtypes. Built upon this discovery, we develop a prognostic assessment model for TNBC patients. Our contribution presents a novel framework for enhancing deconvolution accuracy, showcasing its effectiveness in medical research.

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.

Systematic Analysis of Human Colorectal Cancer scRNA-seq Revealed Limited Pro-tumoral IL-17 Production Potential in Gamma Delta T Cells

Gamma delta (γδ) 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 (TME) of colorectal cancer (CRC) remains controversial. In this study, we re-analyzed nine published human CRC whole-tissue single-cell RNA sequencing (scRNA-seq) 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 Teff, TRM, Tpex, and Tex, and noted an increased expression of cytotoxic molecules in tumor-infiltrating γδ T cells compared to their normal area counterparts. 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.

Mismatch repair-proficient tumor footprints in the sands of immune desert: mechanistic constraints and precision platforms

Mismatch repair proficient (MMRp) tumors of colorectal origin are one of the prevalent yet unpredictable clinical challenges. Despite earnest efforts, optimal treatment modalities have yet to emerge for this class. The poor prognosis and limited actionability of MMRp are ascribed to a low neoantigen burden and a desert-like microenvironment. This review focuses on the critical roadblocks orchestrated by an immune evasive mechanistic milieu in the context of MMRp. The low density of effector immune cells, their weak spatiotemporal underpinnings, and the high-handedness of the IL-17-TGF-β signaling are intertwined and present formidable challenges for the existing therapies. Microbiome niche decorated by Fusobacterium nucleatum alters the metabolic program to maintain an immunosuppressive state. We also highlight the evolving strategies to repolarize and reinvigorate this microenvironment. Reconstruction of anti-tumor chemokine signaling, rational drug combinations eliciting T cell activation, and reprograming the maladapted microbiome are exciting developments in this direction. Alternative vulnerability of other DNA damage repair pathways is gaining momentum. Integration of liquid biopsy and ex vivo functional platforms provide precision oncology insights. We illustrated the perspectives and changing landscape of MMRp-CRC. The emerging opportunities discussed in this review can turn the tide in favor of fighting the treatment dilemma for this elusive cancer.

Association of CD8+TILs co-expressing granzyme A and interferon-γ with colon cancer cells in the tumor microenvironment

CD8+T cells secreting granzyme A (GZMA) can induce pyroptosis in tumor cells by effectively cleaving gasdermin B (GSDMB), which is stimulated by interferon-γ (IFN-γ). However, the interaction between GZMA-expressing CD8+T cells and GSDMB-expressing tumor cells in colon cancer remains poorly understood. Our research employed multi-color immunohistochemistry (mIHC) staining and integrated clinical data to explore the spatial distribution and clinical relevance of GZMA- and IFN-γ-expressing CD8+ tumor-infiltrating lymphocytes (TILs), as well as GSDMB-expressing CK+ cells, within the tumor microenvironment (TME) of human colon cancer samples. Additionally, we utilizing single-cell RNA sequencing (scRNA-seq) data to examine the functional dynamics and interactions among these cell populations. scRNA-seq analysis of colorectal cancer (CRC) tissues revealed that CD8+TILs co-expressed GZMA and IFN-γ, but not other cell types. Our mIHC staining results indicated that a significant reduction in the infiltration of GZMA+IFN-γ+CD8+TILs in colon cancer patients (P < 0.01). Functional analysis results indicated that GZMA+IFN-γ+CD8+TILs demonstrated enhanced activation and effector functions compared to other CD8+TIL subsets. Furthermore, GSDMB-expressing CK+ cells exhibited augmented immunogenicity. Correlation analysis highlighted a positive association between GSDMB+CK+ cells and GZMA+IFN-γ+CD8+TILs (r = 0.221, P = 0.033). Analysis of cell-cell interactions further showed that these interactions were mediated by IFN-γ and transforming growth factor-β (TGF-β), the co-stimulatory molecule ICOS, and immune checkpoint molecules TIGIT and TIM-3. These findings suggested that GZMA+IFN-γ+CD8+TILs modulating GSDMB-expressing tumor cells, significantly impacted the immune microenvironment and patients' prognosis in colon cancer. By elucidating these mechanisms, our present study aims to provide novel insights for the advancement of immunotherapeutic strategies in colon cancer.

Endogenous retroviruses mediate transcriptional rewiring in response to oncogenic signaling in colorectal cancer

Cancer cells exhibit rewired transcriptional regulatory networks that promote tumor growth and survival. However, the mechanisms underlying the formation of these pathological networks remain poorly understood. Through a pan-cancer epigenomic analysis, we found that primate-specific endogenous retroviruses (ERVs) are a rich source of enhancers displaying cancer-specific activity. In colorectal cancer and other epithelial tumors, oncogenic MAPK/AP1 signaling drives the activation of enhancers derived from the primate-specific ERV family LTR10. Functional studies in colorectal cancer cells revealed that LTR10 elements regulate tumor-specific expression of multiple genes associated with tumorigenesis, such as ATG12 and XRCC4. Within the human population, individual LTR10 elements exhibit germline and somatic structural variation resulting from a highly mutable internal tandem repeat region, which affects AP1 binding activity. Our findings reveal that ERV-derived enhancers contribute to transcriptional dysregulation in response to oncogenic signaling and shape the evolution of cancer-specific regulatory networks.

Integrated single-cell and bulk RNA sequencing revealed an epigenetic signature predicts prognosis and tumor microenvironment colorectal cancer heterogeneity

BACKGROUND

Colorectal cancer (CRC) prognosis prediction is currently a major challenge. Epigenetic regulation has been widely reported for its role in cancer development.

AIM

To construct a robust prognostic signature, we used developed and validated across datasets.

METHODS

After constructing the signature, the prognostic value of the signature was evaluated in the TCGA cohort and six independent datasets (GSE17526, GSE17537, GSE33113, GSE37892, GSE39048 and GSE39582). The clinical, genomic and transcriptomic features related to the signature were identified. The correlations of the signature score with immune cell infiltration and cell-cell interactions were analyzed. The correlations between the signature score and the sensitivity to different drugs were also predicted.

RESULTS

In the TCGA cohort, patients in the low-risk group according to the signature score had longer survival than those in the high-risk group, and this finding was validated in the validation datasets. The signature was a prognostic factor independent of age and sex and was correlated with stage and PD-1/PD-L1 expression. Area under the receiving operating characteristic curve was 0.72. Genomic association analyses revealed that samples from high-risk patients exhibited chromosomal instability. Transcriptomic analyses revealed that the signature score was significantly associated with multiple cellular pathways. Bulk RNA-seq and single-cell sequencing data revealed that the signature reflected differences in infiltrating immune cell-tumor cell interactions, especially for macrophages. The signature also predicted the putative drug sensitivity of CRC samples.

CONCLUSION

The signature is a valuable biomarker for predicting CRC prognosis and reflects multiple features of CRC, especially macrophage infiltration in the microenvironment.

Spatiotemporal single-cell analysis decodes cellular dynamics underlying different responses to immunotherapy in colorectal cancer

Expanding the efficacy of immune checkpoint blockade (ICB) in colorectal cancer (CRC) presses for a comprehensive understanding of treatment responsiveness. Here, we analyze multiple sequential single-cell samples from 22 patients undergoing PD-1 blockade to map the evolution of local and systemic immunity of CRC patients. In tumors, we identify coordinated cellular programs exhibiting distinct response associations. Specifically, exhausted T (Tex) or tumor-reactive-like CD8+ T (Ttr-like) cells are closely related to treatment efficacy, and Tex cells show correlated proportion changes with multiple other tumor-enriched cell types following PD-1 blockade. In addition, we reveal the less-exhausted phenotype of blood-associated Ttr-like cells in tumors and find that their higher abundance suggests better treatment outcomes. Finally, a higher major histocompatibility complex (MHC) II-related signature in circulating CD8+ T cells at baseline is linked to superior responses. Our study provides insights into the spatiotemporal cellular dynamics following neoadjuvant PD-1 blockade in CRC.

Type I Interferon Activates PD-1 Expression through Activation of the STAT1-IRF2 Pathway in Myeloid Cells

PD-1 (Programmed cell death protein 1) regulates the metabolic reprogramming of myeloid-derived suppressor cells and myeloid cell differentiation, as well as the type I interferon (IFN-I) signaling pathway in myeloid cells in the tumor microenvironment. PD-1, therefore, is a key inhibitory receptor in myeloid cells. However, the regulation of PD-1 expression in myeloid cells is unknown. We report that the expression level of PDCD1, the gene that encodes the PD-1 protein, is positively correlated with the levels of IFNB1 and IFNAR1 in myeloid cells in human colorectal cancer. Treatment of mouse myeloid cell lines with recombinant IFNβ protein elevated PD-1 expression in myeloid cells in vitro. Knocking out IFNAR1, the gene that encodes the IFN-I-specific receptor, diminished the inductive effect of IFNβ on PD-1 expression in myeloid cells in vitro. Treatment of tumor-bearing mice with a lipid nanoparticle-encapsulated IFNβ-encoding plasmid (IFNBCOL01) increased IFNβ expression, resulting in elevated PD-1 expression in tumor-infiltrating myeloid cells. At the molecular level, we determined that IFNβ activates STAT1 (signal transducer and activator of transcription 1) and IRFs (interferon regulatory factors) in myeloid cells. Analysis of the cd279 promoter identified IRF2-binding consensus sequence elements. ChIP (chromatin immunoprecipitation) analysis determined that the pSTAT1 directly binds to the irf2 promoter and that IRF2 directly binds to the cd279 promoter in myeloid cells in vitro and in vivo. In colon cancer patients, the expression levels of STAT1, IRF2 and PDCD1 are positively correlated in tumor-infiltrating myeloid cells. Our findings determine that IFNβ activates PD-1 expression at least in part by an autocrine mechanism via the stimulation of the pSTAT1-IRF2 axis in myeloid cells.

HEARTSVG: a fast and accurate method for identifying spatially variable genes in large-scale spatial transcriptomics

Identifying spatially variable genes (SVGs) is crucial for understanding the spatiotemporal characteristics of diseases and tissue structures, posing a distinctive challenge in spatial transcriptomics research. We propose HEARTSVG, a distribution-free, test-based method for fast and accurately identifying spatially variable genes in large-scale spatial transcriptomic data. Extensive simulations demonstrate that HEARTSVG outperforms state-of-the-art methods with higherF 1 scores (averageF 1 Score=0.948), improved computational efficiency, scalability, and reduced false positives (FPs). Through analysis of twelve real datasets from various spatial transcriptomic technologies, HEARTSVG identifies a greater number of biologically significant SVGs (average AUC = 0.792) than other comparative methods without prespecifying spatial patterns. Furthermore, by clustering SVGs, we uncover two distinct tumor spatial domains characterized by unique spatial expression patterns, spatial-temporal locations, and biological functions in human colorectal cancer data, unraveling the complexity of tumors.

Using a pan-cancer atlas to investigate tumour associated macrophages as regulators of immunotherapy response

The paradigm for macrophage characterization has evolved from the simple M1/M2 dichotomy to a more complex model that encompasses the broad spectrum of macrophage phenotypic diversity, due to differences in ontogeny and/or local stimuli. We currently lack an in-depth pan-cancer single cell RNA-seq (scRNAseq) atlas of tumour-associated macrophages (TAMs) that fully captures this complexity. In addition, an increased understanding of macrophage diversity could help to explain the variable responses of cancer patients to immunotherapy. Our atlas includes well established macrophage subsets as well as a number of additional ones. We associate macrophage composition with tumour phenotype and show macrophage subsets can vary between primary and metastatic tumours growing in sites like the liver. We also examine macrophage-T cell functional cross talk and identify two subsets of TAMs associated with T cell activation. Analysis of TAM signatures in a large cohort of immune checkpoint inhibitor-treated patients (CPI1000 + ) identify multiple TAM subsets associated with response, including the presence of a subset of TAMs that upregulate collagen-related genes. Finally, we demonstrate the utility of our data as a resource and reference atlas for mapping of novel macrophage datasets using projection. Overall, these advances represent an important step in both macrophage classification and overcoming resistance to immunotherapies in cancer.

Identification of intracellular bacteria from multiple single-cell RNA-seq platforms using CSI-Microbes

The study of the tumor microbiome has been garnering increased attention. We developed a computational pipeline (CSI-Microbes) for identifying microbial reads from single-cell RNA sequencing (scRNA-seq) data and for analyzing differential abundance of taxa. Using a series of controlled experiments and analyses, we performed the first systematic evaluation of the efficacy of recovering microbial unique molecular identifiers by multiple scRNA-seq technologies, which identified the newer 10x chemistries (3' v3 and 5') as the best suited approach. We analyzed patient esophageal and colorectal carcinomas and found that reads from distinct genera tend to co-occur in the same host cells, testifying to possible intracellular polymicrobial interactions. Microbial reads are disproportionately abundant within myeloid cells that up-regulate proinflammatory cytokines like IL1Β and CXCL8, while infected tumor cells up-regulate antigen processing and presentation pathways. These results show that myeloid cells with bacteria engulfed are a major source of bacterial RNA within the tumor microenvironment (TME) and may inflame the TME and influence immunotherapy response.

Hypoxia inhibits the iMo/cDC2/CD8+ TRMs immune axis in the tumor microenvironment of human esophageal cancer

BACKGROUND

Esophageal cancer (ESCA) is a form of malignant tumor associated with chronic inflammation and immune dysregulation. However, the specific immune status and key mechanisms of immune regulation in this disease require further exploration.

METHODS

To investigate the features of the human ESCA tumor immune microenvironment and its possible regulation, we performed mass cytometry by time of flight, single-cell RNA sequencing, multicolor fluorescence staining of tissue, and flow cytometry analyses on tumor and paracancerous tissue from treatment-naïve patients.

RESULTS

We depicted the immune landscape of the ESCA and revealed that CD8+ (tissue-resident memory CD8+ T cells (CD8+ TRMs) were closely related to disease progression. We also revealed the heterogeneity of CD8+ TRMs in the ESCA tumor microenvironment (TME), which was associated with their differentiation and function. Moreover, the subset of CD8+ TRMs in tumor (called tTRMs) that expressed high levels of granzyme B and immune checkpoints was markedly decreased in the TME of advanced ESCA. We showed that tTRMs are tumor effector cells preactivated in the TME. We then demonstrated that conventional dendritic cells (cDC2s) derived from intermediate monocytes (iMos) are essential for maintaining the proliferation of CD8+ TRMs in the TME. Our preliminary study showed that hypoxia can promote the apoptosis of iMos and impede the maturation of cDC2s, which in turn reduces the proliferative capacity of CD8+ TRMs, thereby contributing to the progression of cancer.

CONCLUSIONS

Our study revealed the essential antitumor roles of CD8+ TRMs and preliminarily explored the regulation of the iMo/cDC2/CD8+ TRM immune axis in the human ESCA TME.

Supervised discovery of interpretable gene programs from single-cell data

Factor analysis decomposes single-cell gene expression data into a minimal set of gene programs that correspond to processes executed by cells in a sample. However, matrix factorization methods are prone to technical artifacts and poor factor interpretability. We address these concerns with Spectra, an algorithm that combines user-provided gene programs with the detection of novel programs that together best explain expression covariation. Spectra incorporates existing gene sets and cell-type labels as prior biological information, explicitly models cell type and represents input gene sets as a gene-gene knowledge graph using a penalty function to guide factorization toward the input graph. We show that Spectra outperforms existing approaches in challenging tumor immune contexts, as it finds factors that change under immune checkpoint therapy, disentangles the highly correlated features of CD8+ T cell tumor reactivity and exhaustion, finds a program that explains continuous macrophage state changes under therapy and identifies cell-type-specific immune metabolic programs.

Defining clinically useful biomarkers of immune checkpoint inhibitors in solid tumours

Although more than a decade has passed since the approval of immune checkpoint inhibitors (ICIs) for the treatment of melanoma and non-small-cell lung, breast and gastrointestinal cancers, many patients still show limited response. US Food and Drug Administration (FDA)-approved biomarkers include programmed cell death 1 ligand 1 (PDL1) expression, microsatellite status (that is, microsatellite instability-high (MSI-H)) and tumour mutational burden (TMB), but these have limited utility and/or lack standardized testing approaches for pan-cancer applications. Tissue-based analytes (such as tumour gene signatures, tumour antigen presentation or tumour microenvironment profiles) show a correlation with immune response, but equally, these demonstrate limited efficacy, as they represent a single time point and a single spatial assessment. Patient heterogeneity as well as inter- and intra-tumoural differences across different tissue sites and time points represent substantial challenges for static biomarkers. However, dynamic biomarkers such as longitudinal biopsies or novel, less-invasive markers such as blood-based biomarkers, radiomics and the gut microbiome show increasing potential for the dynamic identification of ICI response, and patient-tailored predictors identified through neoadjuvant trials or novel ex vivo tumour models can help to personalize treatment. In this Perspective, we critically assess the multiple new static, dynamic and patient-specific biomarkers, highlight the newest consortia and trial efforts, and provide recommendations for future clinical trials to make meaningful steps forwards in the field.

InstaPrism: an R package for fast implementation of BayesPrism

SUMMARY

Computational cell-type deconvolution is an important analytic technique for modeling the compositional heterogeneity of bulk gene expression data. A conceptually new Bayesian approach to this problem, BayesPrism, has recently been proposed and has subsequently been shown to be superior in accuracy and robustness against model misspecifications by independent studies; however, given that BayesPrism relies on Gibbs sampling, it is orders of magnitude more computationally expensive than standard approaches. Here, we introduce the InstaPrism package which re-implements BayesPrism in a derandomized framework by replacing the time-consuming Gibbs sampling step with a fixed-point algorithm. We demonstrate that the new algorithm is effectively equivalent to BayesPrism while providing a considerable speed and memory advantage. Furthermore, the InstaPrism package is equipped with a precompiled, curated set of references tailored for a variety of cancer types, streamlining the deconvolution process.

AVAILABILITY AND IMPLEMENTATION

The package InstaPrism is freely available at: https://github.com/humengying0907/InstaPrism. The source code and evaluation pipeline used in this paper can be found at: https://github.com/humengying0907/InstaPrismSourceCode.

Circadian control of tumor immunosuppression affects efficacy of immune checkpoint blockade

The circadian clock is a critical regulator of immunity, and this circadian control of immune modulation has an essential function in host defense and tumor immunosurveillance. Here we use a single-cell RNA sequencing approach and a genetic model of colorectal cancer to identify clock-dependent changes to the immune landscape that control the abundance of immunosuppressive cells and consequent suppression of cytotoxic CD8+ T cells. Of these immunosuppressive cell types, PD-L1-expressing myeloid-derived suppressor cells (MDSCs) peak in abundance in a rhythmic manner. Disruption of the epithelial cell clock regulates the secretion of cytokines that promote heightened inflammation, recruitment of neutrophils and the subsequent development of MDSCs. We also show that time-of-day anti-PD-L1 delivery is most effective when synchronized with the abundance of immunosuppressive MDSCs. Collectively, these data indicate that circadian gating of tumor immunosuppression informs the timing and efficacy of immune checkpoint inhibitors.

Advances in spatial transcriptomics and its applications in cancer research

Malignant tumors have increasing morbidity and high mortality, and their occurrence and development is a complicate process. The development of sequencing technologies enabled us to gain a better understanding of the underlying genetic and molecular mechanisms in tumors. In recent years, the spatial transcriptomics sequencing technologies have been developed rapidly and allow the quantification and illustration of gene expression in the spatial context of tissues. Compared with the traditional transcriptomics technologies, spatial transcriptomics technologies not only detect gene expression levels in cells, but also inform the spatial location of genes within tissues, cell composition of biological tissues, and interaction between cells. Here we summarize the development of spatial transcriptomics technologies, spatial transcriptomics tools and its application in cancer research. We also discuss the limitations and challenges of current spatial transcriptomics approaches, as well as future development and prospects.

Distinctive multicellular immunosuppressive hubs confer different intervention strategies for left- and right-sided colon cancers

Primary colon cancers arising from the left and right sides exhibit distinct clinical and molecular characteristics. Sidedness-associated heterogeneity relies intricately on the oncogenic properties of cancer cells and multicellular interactions in tumor microenvironments. Here, combining transcriptomic profiling of 426,863 single cells from 105 colon cancer patients and validation with spatial transcriptomics and large-scale histological analysis, we capture common transcriptional heterogeneity patterns between left- and right-sided malignant epithelia through delineating two side-specific expression meta-programs. The proliferation stemness meta-program is notably enriched in left-sided malignant epithelia that colocalize with Mph-PLTP cells, activated regulatory T cells (Tregs), and exhausted CD8-LAYN cells, constituting the glucose metabolism reprogramming niche. The immune secretory (IS) meta-program exhibits specific enrichment in right-sided malignant epithelia, especially in smoking patients with right-sided colon cancer. The IShigh malignant epithelia spatially localize in hypoxic regions and facilitate immune evasion through attenuating Mph-SPP1 cell antigen presentation and recruiting innate-like cytotoxicity-reduced CD8-CD161 cells.

Interleukin-17 directly stimulates tumor infiltrating Tregs to prevent cancer development

Background

Interleukin-17 (IL-17) family cytokines promote protective inflammation for pathogen resistance, but also facilitate autoimmunity and tumor development. A direct signal of IL-17 to regulatory T cells (Tregs) has not been reported and may help explain these dichotomous responses.

Methods

We generated a conditional knockout of Il17ra in Tregs by crossing Foxp3-YFP-Cre mice to Il17ra-flox mice (Il17ra ΔTreg mice). Subsequently, we adoptively transferred bone marrow cells from Il17ra ΔTreg mice to a mouse model of sporadic colorectal cancer (Cdx2-Cre +/Apc F/+), to selectively ablate IL-17 direct signaling on Tregs in colorectal cancer. Single cell RNA sequencing and bulk RNA sequencing were performed on purified Tregs from mouse colorectal tumors, and compared to those of human tumor infiltrating Treg cells.

Results

IL-17 Receptor A (IL-17RA) is expressed in Tregs that reside in mouse mesenteric lymph nodes and colon tumors. Ablation of IL-17RA, specifically in Tregs, resulted in increased Th17 cells, and exacerbated tumor development. Mechanistically, tumor-infiltrating Tregs exhibit a unique gene signature that is linked to their activation, maturation, and suppression function, and this signature is in part supported by the direct signaling of IL-17 to Tregs. To study pathways of Treg programming, we found that loss of IL-17RA in tumor Tregs resulted in reduced RNA splicing, and downregulation of several RNA binding proteins that are known to regulate alternative splicing and promote Treg function.

Conclusion

IL-17 directly signals to Tregs and promotes their maturation and function. This signaling pathway constitutes a negative feedback loop that controls cancer-promoting inflammation in CRC.

Advances in Integrated Multi-omics Analysis for Drug-Target Identification

As an essential component of modern drug discovery, the role of drug-target identification is growing increasingly prominent. Additionally, single-omics technologies have been widely utilized in the process of discovering drug targets. However, it is difficult for any single-omics level to clearly expound the causal connection between drugs and how they give rise to the emergence of complex phenotypes. With the progress of large-scale sequencing and the development of high-throughput technologies, the tendency in drug-target identification has shifted towards integrated multi-omics techniques, gradually replacing traditional single-omics techniques. Herein, this review centers on the recent advancements in the domain of integrated multi-omics techniques for target identification, highlights the common multi-omics analysis strategies, briefly summarizes the selection of multi-omics analysis tools, and explores the challenges of existing multi-omics analyses, as well as the applications of multi-omics technology in drug-target identification.

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.

Characterising plasmacytoid and myeloid AXL+ SIGLEC-6+ dendritic cell functions and their interactions with HIV

AXL+ Siglec-6+ dendritic cells (ASDC) are novel myeloid DCs which can be subdivided into CD11c+ and CD123+ expressing subsets. We showed for the first time that these two ASDC subsets are present in inflamed human anogenital tissues where HIV transmission occurs. Their presence in inflamed tissues was supported by single cell RNA analysis of public databases of such tissues including psoriasis diseased skin and colorectal cancer. Almost all previous studies have examined ASDCs as a combined population. Our data revealed that the two ASDC subsets differ markedly in their functions when compared with each other and to pDCs. Relative to their cell functions, both subsets of blood ASDCs but not pDCs expressed co-stimulatory and maturation markers which were more prevalent on CD11c+ ASDCs, thus inducing more T cell proliferation and activation than their CD123+ counterparts. There was also a significant polarisation of naïve T cells by both ASDC subsets toward Th2, Th9, Th22, Th17 and Treg but less toward a Th1 phenotype. Furthermore, we investigated the expression of chemokine receptors that facilitate ASDCs and pDCs migration from blood to inflamed tissues, their HIV binding receptors, and their interactions with HIV and CD4 T cells. For HIV infection, within 2 hours of HIV exposure, CD11c+ ASDCs showed a trend in more viral transfer to T cells than CD123+ ASDCs and pDCs for first phase transfer. However, for second phase transfer, CD123+ ASDCs showed a trend in transferring more HIV than CD11c+ ASDCs and there was no viral transfer from pDCs. As anogenital inflammation is a prerequisite for HIV transmission, strategies to inhibit ASDC recruitment into inflamed tissues and their ability to transmit HIV to CD4 T cells should be considered.

RAC1-mediated integrin alpha-6 expression in E-cadherin-deficient gastric cancer cells promotes interactions with the stroma and peritoneal dissemination

Diffuse-type gastric cancer (DGC) is a subtype of gastric cancer that is prone to peritoneal dissemination, with poor patient prognosis. Although intercellular adhesion loss between cancer cells is a major characteristic of DGCs, the mechanism underlying the alteration in cell-to-extracellular matrix (ECM) adhesion is unclear. We investigated how DGCs progress and cause peritoneal dissemination through interactions between DGC cells and the tumour microenvironment (TME). P53 knockout and KRASG12V-expressing (GAN-KP) cells and Cdh1-deleted GAN-KP (GAN-KPC) cells were orthotopically transplanted into the gastric wall to mimic peritoneal dissemination. The GAN-KPC tumour morphology was similar to that of human DGCs containing abundant stroma. RNA sequencing revealed that pathways related to Rho GTPases and integrin-ECM interactions were specifically increased in GAN-KPC cells compared with GAN-KP cells. Notably, we found that Rac Family Small GTPase 1 (RAC1) induces Integrin Subunit Alpha 6 (ITGA6) trafficking, leading to its enrichment on the GC cell membrane. Fibroblasts activate the FAK/AKT pathway in GC cells by mediating extracellular matrix (ECM)-Itga6 interactions, exacerbating the malignant phenotype. In turn, GC cells induce abnormal expression of fibroblast collagen and its transformation into cancer-associated fibroblasts (CAFs), resulting in DGC-like subtypes. These findings indicate that Cdh1 gene loss leads to abnormal expression and changes in the subcellular localization of ITGA6 through RAC1 signalling. The latter, through interactions with CAFs, allows for peritoneal dissemination.

Single-cell transcriptomics reveals antigen-presenting capacity and therapeutic resistance potential of immunomodulatory endothelial cells in colorectal cancer

BACKGROUND

The heterogeneity of tumor endothelial cells (TECs) hinders the efficacy of antiangiogenic therapies (AATs). Only a small percentage of angiogenic TECs are considered effective targets for AATs. Immunomodulatory ECs (IMECs), as a newly focused functional subgroup of endothelial cells (ECs), are being evaluated for their ability to regulate tumor immune balance and influence existing AATs.

METHODS

Based on single-cell transcriptome data from colorectal cancer in a publicly available database, we conducted a wide array of bioinformatic approaches to study EC subsets that meet the IMECs definition. Our investigation encompassed the gene expression signatures of these subsets, cellular composition differences, cell-cell interactions.

RESULTS

Two subsets that meet the IMECs definition were found in tumors and para-cancerous tissues. Combined with the results of gene ontological analysis and interaction with CD4+ T cells, we found that IMECs can present MHC-II antigens to mature CD4+ T cells. There were differences in the level of interaction between IMECs and different types of mature CD4+ T cell subsets. In addition, IMEC subsets had different expression levels of angiogenesis related genes. The angiogenesis score of IMECs decreased after patients received immunotherapy. IMEC subsets do not depend on a single proangiogenic receptor and are involved in regulating angiogenesis, which may reduce the efficacy of AATs. The adverse effects of specific IMEC subsets on AATs were validated in the RNA-seq dataset of the bevacizumab treatment group.

CONCLUSION

Our study suggests the potential MHC-II antigen presentation capacity of IMECs and the enhanced angiogenesis characteristics within tumors. The function of IMECs in the vascular network may have a potentially adverse effect on AATs. Controlling the functional properties of IMECs may be a new angle for tumor therapy.

Obesity induces PD-1 on macrophages to suppress anti-tumour immunity

Obesity is a leading risk factor for progression and metastasis of many cancers1,2, yet can in some cases enhance survival3-5 and responses to immune checkpoint blockade therapies, including anti-PD-1, which targets PD-1 (encoded by PDCD1), an inhibitory receptor expressed on immune cells6-8. Although obesity promotes chronic inflammation, the role of the immune system in the obesity-cancer connection and immunotherapy remains unclear. It has been shown that in addition to T cells, macrophages can express PD-19-12. Here we found that obesity selectively induced PD-1 expression on tumour-associated macrophages (TAMs). Type I inflammatory cytokines and molecules linked to obesity, including interferon-γ, tumour necrosis factor, leptin, insulin and palmitate, induced macrophage PD-1 expression in an mTORC1- and glycolysis-dependent manner. PD-1 then provided negative feedback to TAMs that suppressed glycolysis, phagocytosis and T cell stimulatory potential. Conversely, PD-1 blockade increased the level of macrophage glycolysis, which was essential for PD-1 inhibition to augment TAM expression of CD86 and major histocompatibility complex I and II molecules and ability to activate T cells. Myeloid-specific PD-1 deficiency slowed tumour growth, enhanced TAM glycolysis and antigen-presentation capability, and led to increased CD8+ T cell activity with a reduced level of markers of exhaustion. These findings show that obesity-associated metabolic signalling and inflammatory cues cause TAMs to induce PD-1 expression, which then drives a TAM-specific feedback mechanism that impairs tumour immune surveillance. This may contribute to increased cancer risk yet improved response to PD-1 immunotherapy in obesity.