A pan-cancer blueprint of the heterogeneous tumor microenvironment revealed by single-cell profiling

Genomic and microenvironmental heterogeneity shaping epithelial-to-mesenchymal trajectories in cancer

The epithelial to mesenchymal transition (EMT) is a key cellular process underlying cancer progression, with multiple intermediate states whose molecular hallmarks remain poorly characterised. To fill this gap, we present a method to robustly evaluate EMT transformation in individual tumours based on transcriptomic signals. We apply this approach to explore EMT trajectories in 7180 tumours of epithelial origin and identify three macro-states with prognostic and therapeutic value, attributable to epithelial, hybrid E/M and mesenchymal phenotypes. We show that the hybrid state is relatively stable and linked with increased aneuploidy. We further employ spatial transcriptomics and single cell datasets to explore the spatial heterogeneity of EMT transformation and distinct interaction patterns with cytotoxic, NK cells and fibroblasts in the tumour microenvironment. Additionally, we provide a catalogue of genomic events underlying distinct evolutionary constraints on EMT transformation. This study sheds light on the aetiology of distinct stages along the EMT trajectory, and highlights broader genomic and environmental hallmarks shaping the mesenchymal transformation of primary tumours.

The immune-metabolic crosstalk between CD3+C1q+TAM and CD8+T cells associated with relapse-free survival in HCC

Introduction

Although multiple targeted treatments have appeared, hepatocellular carcinoma (HCC) is still one of the most common causes of cancer-related deaths. The immunosuppressive tumor microenvironment (TME) is a critical factor in the oncogenesis and progression of HCC. The emerging scRNA-seq makes it possible to explore the TME at a high resolution. This study was designed to reveal the immune-metabolic crosstalk between immune cells in HCC and provide novel strategies to regulate immunosuppressive TME.

Method

In this study, we performed scRNA-seq on paired tumor and peri-tumor tissues of HCC. The composition and differentiation trajectory of the immune populations in TME were portrayed. Cellphone DB was utilized to calculate interactions between the identified clusters. Besides, flow cytometry, RT-PCR and seahorse experiments were implemented to explore potential metabolic and epigenetic mechanisms of the inter-cellular interaction.

Result

A total of 19 immune cell clusters were identified and 7 were found closely related to HCC prognosis. Besides, differentiation trajectories of T cells were also presented. Moreover, a new population, CD3+C1q+ tumor-associated macrophages (TAM) were identified and found significantly interacted with CD8+ CCL4+T cells. Compared to the peri-tumor tissue, their interaction was attenuated in tumor. Additionally, the dynamic presence of this newly found cluster was also verified in the peripheral blood of patients with sepsis. Furthermore, we found that CD3+C1q+TAM affected T cell immunity through C1q signaling-induced metabolic and epigenetic reprogramming, thereby potentially affecting tumor prognosis.

Conclusion

Our study revealed the interaction between CD3+C1q+TAM and CD8+ CCL4+T cells and may provide implications for tackling the immunosuppressive TME in HCC.

Identification and Biological Validation of a Chemokine/Chemokine Receptor-Based Risk Model for Predicting Immunotherapeutic Response and Prognosis in Head and Neck Squamous Cell Carcinoma

Over 80% of head and neck squamous cell carcinoma (HNSCC) patients failed to respond to immunotherapy, which can likely be attributed to the tumor microenvironment (TME) remolding mediated by chemokines/chemokine receptors (C/CR). This study aimed to establish a C/CR-based risk model for better immunotherapeutic responses and prognosis. After assessing the characteristic patterns of the C/CR cluster from the TCGA-HNSCC cohort, a six-gene C/CR-based risk model was developed to stratify patients by LASSO Cox analysis. The screened genes were multidimensionally validated by RT-qPCR, scRNA-seq, and protein data. A total of 30.4% of patients in the low-risk group had better responses to anti-PD-L1 immunotherapy. A Kaplan-Meier analysis showed that patients in the low-risk group had longer overall survival. A time-dependent receiver operating characteristic curve and Cox analyses indicated that risk score served as an independent predictive indicator. The robustness of the immunotherapy response and prognosis prediction was also validated in independent external datasets. Additionally, the TME landscape revealed that the low-risk group was immune activated. Furthermore, the cell communication analysis on the scRNA-seq dataset revealed that cancer-associated fibroblasts were the main communicators within the C/CR ligand-receptor network of TME. Collectively, The C/CR-based risk model simultaneously predicted immunotherapeutic response and prognosis, potentially optimizing personalized therapeutic strategies of HNSCC.

Meta-Analysis of Human Cancer Single-Cell RNA-Seq Datasets Using the IMMUcan Database

The development of single-cell RNA sequencing (scRNA-seq) technologies has greatly contributed to deciphering the tumor microenvironment (TME). An enormous amount of independent scRNA-seq studies have been published representing a valuable resource that provides opportunities for meta-analysis studies. However, the massive amount of biological information, the marked heterogeneity and variability between studies, and the technical challenges in processing heterogeneous datasets create major bottlenecks for the full exploitation of scRNA-seq data. We have developed IMMUcan scDB (https://immucanscdb.vital-it.ch), a fully integrated scRNA-seq database exclusively dedicated to human cancer and accessible to nonspecialists. IMMUcan scDB encompasses 144 datasets on 56 different cancer types, annotated in 50 fields containing precise clinical, technological, and biological information. A data processing pipeline was developed and organized in four steps: (i) data collection; (ii) data processing (quality control and sample integration); (iii) supervised cell annotation with a cell ontology classifier of the TME; and (iv) interface to analyze TME in a cancer type-specific or global manner. This framework was used to explore datasets across tumor locations in a gene-centric (CXCL13) and cell-centric (B cells) manner as well as to conduct meta-analysis studies such as ranking immune cell types and genes correlated to malignant transformation. This integrated, freely accessible, and user-friendly resource represents an unprecedented level of detailed annotation, offering vast possibilities for downstream exploitation of human cancer scRNA-seq data for discovery and validation studies.

SIGNIFICANCE

The IMMUcan scDB database is an accessible supportive tool to analyze and decipher tumor-associated single-cell RNA sequencing data, allowing researchers to maximally use this data to provide new insights into cancer biology.

Mature dendritic cells enriched in immunoregulatory molecules (mregDCs): A novel population in the tumour microenvironment and immunotherapy target

BACKGROUND

Dendritic cells (DCs) mediate divergent immune effects by activating T cells or negatively regulating the immune response to promote immune tolerance. They perform specific functions determined by their tissue distribution and maturation state. Traditionally, immature and semimature DCs were described to have immunosuppressive effects, leading to immune tolerance. Nonetheless, recent research has demonstrated that mature DCs can also suppress the immune response under certain circumstances.

MAIN BODY

Mature DCs enriched in immunoregulatory molecules (mregDCs) have emerged as a regulatory module across species and tumour types. Indeed, the distinct roles of mregDCs in tumour immunotherapy have sparked the interest of researchers in the field of single-cell omics. In particular, these regulatory cells were found to be associated with a positive response to immunotherapy and a favourable prognosis.

CONCLUSION

Here, we provide a general overview of the latest and most notable advances and recent findings regarding the basic features and complex roles of mregDCs in nonmalignant diseases and the tumour microenvironment. We also emphasise the important clinical implications of mregDCs in tumours.

Molecular Dissection of Somatic Skeletal Disease in Neurofibromatosis Type 1

Neurofibromatosis type 1 (NF1) is a tumor predisposition syndrome caused by heterozygous NF1 gene mutations. Patients with NF1 present with pleiotropic somatic secondary manifestations, including development of bone pseudarthrosis after fracture. Somatic NF1 gene mutations were reproducibly identified in patient-derived pseudarthrosis specimens, suggesting a local mosaic cell population including somatic pathologic cells. The somatic cellular pathogenesis of NF1 pseudarthroses remains unclear, though defects in osteogenesis have been posited. Here, we applied time-series single-cell RNA-sequencing (scRNA-seq) to patient-matched control and pseudarthrosis-derived primary bone stromal cells (BSCs). We show that osteogenic specification to an osteoblast progenitor cell population was evident for control bone-derived cells and haploinsufficient pseudarthrosis-derived cells. Similar results were observed for somatic patient fracture-derived NF1^-/- cells; however, expression of genetic pathways associated with skeletal mineralization were significantly reduced in NF1^-/- cells compared with fracture-derived NF1^+/- cells. In mice, we show that Nf1 expressed in bone marrow osteoprogenitors is required for the maintenance of the adult skeleton. Results from our study implicate impaired Clec11a-Itga11-Wnt signaling in the pathogenesis of NF1-associated skeletal disease. © 2022 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

Single-cell analysis reveals prognostic fibroblast subpopulations linked to molecular and immunological subtypes of lung cancer

Fibroblasts are poorly characterised cells that variably impact tumour progression. Here, we use single cell RNA-sequencing, multiplexed immunohistochemistry and digital cytometry (CIBERSORTx) to identify and characterise three major fibroblast subpopulations in human non-small cell lung cancer: adventitial, alveolar and myofibroblasts. Alveolar and adventitial fibroblasts (enriched in control tissue samples) localise to discrete spatial niches in histologically normal lung tissue and indicate improved overall survival rates when present in lung adenocarcinomas (LUAD). Trajectory inference identifies three phases of control tissue fibroblast activation, leading to myofibroblast enrichment in tumour samples: initial upregulation of inflammatory cytokines, followed by stress-response signalling and ultimately increased expression of fibrillar collagens. Myofibroblasts correlate with poor overall survival rates in LUAD, associated with loss of epithelial differentiation, TP53 mutations, proximal molecular subtypes and myeloid cell recruitment. In squamous carcinomas myofibroblasts were not prognostic despite being transcriptomically equivalent. These findings have important implications for developing fibroblast-targeting strategies for cancer therapy.

Single-cell analysis of acute lymphoblastic and lineage-ambiguous leukemia: approaches and molecular insights

Despite recent progress in identifying the genetic drivers of acute lymphoblastic leukemia (ALL), prognosis remains poor for those individuals who experience disease recurrence. Moreover, acute leukemias of ambiguous lineage lack a biologically informed framework to guide classification and therapy. These needs have driven the adoption of multiple complementary single-cell sequencing approaches to explore key issues in the biology of these leukemias, including cell of origin, developmental hierarchy and ontogeny, and the molecular heterogeneity driving pathogenesis, progression, and therapeutic responsiveness. There are multiple single-cell techniques for profiling a specific modality, including RNA, DNA, chromatin accessibility and methylation; and an expanding range of approaches for simultaneous analysis of multiple modalities. Single-cell sequencing approaches have also enabled characterization of cell-intrinsic and -extrinsic features of ALL biology. In this review we describe these approaches and highlight the extensive heterogeneity that underpins ALL gene expression, cellular differentiation, and clonal architecture throughout disease pathogenesis and treatment resistance. In addition, we discuss the importance of the dynamic interactions that occur between leukemia cells and the nonleukemia microenvironment. We discuss potential opportunities and limitations of single-cell sequencing for the study of ALL biology and treatment responsiveness.

Single-cell RNA binding protein regulatory network analyses reveal oncogenic HNRNPK-MYC signalling pathway in cancer

RNA-binding proteins (RBPs) are key players of gene expression and perturbations of RBP-RNA regulatory network have been observed in various cancer types. Here, we propose a computational method, RBPreg, to identify the RBP regulators by integration of single cell RNA-Seq (N = 233,591) and RBP binding data. Pan-cancer analyses suggest that RBP regulators exhibit cancer and cell specificity and perturbations of RBP regulatory network are involved in cancer hallmark-related functions. We prioritize an oncogenic RBP-HNRNPK, which is highly expressed in tumors and associated with poor prognosis of patients. Functional assays performed in cancer cells reveal that HNRNPK promotes cancer cell proliferation, migration, and invasion in vitro and in vivo. Mechanistic investigations further demonstrate that HNRNPK promotes tumorigenesis and progression by directly binding to MYC and perturbed the MYC targets pathway in lung cancer. Our results provide a valuable resource for characterizing RBP regulatory networks in cancer, yielding potential biomarkers for precision medicine.

Single-cell analysis reveals the COL11A1+ fibroblasts are cancer-specific fibroblasts that promote tumor progression

Background: Cancer-associated fibroblasts (CAFs) promote tumor progression through extracellular matrix (ECM) remodeling and extensive communication with other cells in tumor microenvironment. However, most CAF-targeting strategies failed in clinical trials due to the heterogeneity of CAFs. Hence, we aimed to identify the cluster of tumor-promoting CAFs, elucidate their function and determine their specific membrane markers to ensure precise targeting. Methods: We integrated multiple single-cell RNA sequencing (scRNA-seq) datasets across different tumors and adjacent normal tissues to identify the tumor-promoting CAF cluster. We analyzed the origin of these CAFs by pseudotime analysis, and tried to elucidate the function of these CAFs by gene regulatory network analysis and cell-cell communication analysis. We also performed cell-type deconvolution analysis to examine the association between the proportion of these CAFs and patients' prognosis in TCGA cancer cohorts, and validated that through IHC staining in clinical tumor tissues. In addition, we analyzed the membrane molecules in different fibroblast clusters, trying to identify the membrane molecules that were specifically expressed on these CAFs. Results: We found that COL11A1+ fibroblasts specifically exist in tumor tissues but not in normal tissues and named them cancer-specific fibroblasts (CSFs). We revealed that these CSFs were transformed from normal fibroblasts. CSFs represented a more activated CAF cluster and may promote tumor progression through the regulation on ECM remodeling and antitumor immune responses. High CSF proportion was associated with poor prognosis in bladder cancer (BCa) and lung adenocarcinoma (LUAD), and IHC staining of COL11A1 confirmed their specific expression in tumor stroma in clinical BCa samples. We also identified that CSFs specifically express the membrane molecules LRRC15, ITGA11, SPHK1 and FAP, which could distinguish CSFs from other fibroblasts. Conclusion: We identified that CSFs is a tumor specific cluster of fibroblasts, which are in active state, may promote tumor progression through the regulation on ECM remodeling and antitumor immune responses. Membrane molecules LRRC15, ITGA11, SPHK1 and FAP could be used as therapeutic targets for CSF-targeting cancer treatment.

CD200+ cytotoxic T lymphocytes in the tumor microenvironment are crucial for efficacious anti-PD-1/PD-L1 therapy

Anti-PD-1/PD-L1 therapy, either by anti-PD-1 antibody or anti-PD-L1 antibody, has efficacy by reinvigorating tumor-infiltrating CD8⁺ T cells in a subset of patients with cancer, but it has unequal effects on heterogeneous CD8⁺ T cell populations. Hence, the subset crucial to efficacious PD-1 blockade therapy remains elusive. Here, we found an increase in tumor-infiltrating CD200⁺ cytotoxic T lymphocytes (CTLs) upon PD-1/PD-L1 blockade, with higher proportions of CD200⁺ T cells positively related to a favorable clinical outcome to anti-PD-1/PD-L1 therapy in three independent cohorts of patients with cancer. Using multiple mouse tumor models, we demonstrated that CD200⁺ CTLs are essential for efficacious anti-PD-L1 therapy. Mechanistically, we observed a unique chromatin landscape in CD200⁺ CTLs and found that these cells are enriched for tumor antigen-specific CTLs and have antitumor effector functions. Coinoculation of CD200⁺ CTLs with tumor cells led to robust tumor regression in two transplanted mouse models. Clinically, we found that infiltration of CD200⁺ CTLs into tumors could predict immunotherapy efficacy in six patient cohorts. Together, our findings reveal that CD200⁺ CTLs in the tumor microenvironment are crucial for efficacious anti-PD-1/PD-L1 therapy and could serve as a predictor of successful immunotherapy in the clinic.

A spatial map of human macrophage niches reveals context-dependent macrophage functions in colon and breast cancer

Tumor-associated macrophages (TAMs) display heterogeneous phenotypes. Yet the exact tissue cues that shape macrophage functional diversity are incompletely understood. Here we discriminate, spatially resolve and reveal the function of five distinct macrophage niches within malignant and benign breast and colon tissue. We found that SPP1 TAMs reside in hypoxic and necrotic tumor regions, and a novel subset of FOLR2 tissue resident macrophages (TRMs) supports the plasma cell tissue niche. We discover that IL4I1 macrophages populate niches with high cell turnover where they phagocytose dying cells. Significantly, IL4I1 TAMs abundance correlates with anti-PD1 treatment response in breast cancer. Furthermore, NLRP3 inflammasome activation in NLRP3 TAMs correlates with neutrophil infiltration in the tumors and is associated with poor outcome in breast cancer patients. This suggests the NLRP3 inflammasome as a novel cancer immunetherapy target. Our work uncovers context-dependent roles of macrophage subsets, and suggests novel predictive markers and macrophage subset-specific therapy targets.

The mutation in splicing factor genes correlates with unfavorable prognosis, genomic instability, anti-tumor immunosuppression and increased immunotherapy response in pan-cancer

Splicing abnormality resulting from somatic mutations in key splicing factor genes (SFG) has been detected in various cancers. Hence, an in-depth study of splicing factor genes mutations' impact on pan-cancer is meaningful. This study investigated associations of splicing factor genes mutations with clinical features, tumor progression phenotypes, genomic integrity, anti-tumor immune responses, and immunotherapy response in 12 common cancer types from the TCGA database. Compared to SFG-wildtype cancers, SFG-mutated cancers displayed worse survival prognosis, higher tumor mutation burden and aneuploidy levels, higher expression of immunosuppressive signatures, and higher levels of tumor stemness, proliferation potential, and intratumor heterogeneity (ITH). However, splicing factor genes-mutated cancers showed higher response rates to immune checkpoint inhibitors than splicing factor genes-wildtype cancers in six cancer cohorts. Single-cell data analysis confirmed that splicing factor genes mutations were associated with increased tumor stemness, proliferation capacity, PD-L1 expression, intratumor heterogeneity, and aneuploidy levels. Our data suggest that the mutation in key splicing factor genes correlates with unfavorable clinical outcomes and disease progression, genomic instability, anti-tumor immunosuppression, and increased immunotherapy response in pan-cancer. Thus, the splicing factor genes mutation is an adverse prognostic factor and a positive marker for immunotherapy response in cancer.

A comprehensive single-cell map of T cell exhaustion-associated immune environments in human breast cancer

Immune checkpoint therapy in breast cancer remains restricted to triple negative patients, and long-term clinical benefit is rare. The primary aim of immune checkpoint blockade is to prevent or reverse exhausted T cell states, but T cell exhaustion in breast tumors is not well understood. Here, we use single-cell transcriptomics combined with imaging mass cytometry to systematically study immune environments of human breast tumors that either do or do not contain exhausted T cells, with a focus on luminal subtypes. We find that the presence of a PD-1^high exhaustion-like T cell phenotype is associated with an inflammatory immune environment with a characteristic cytotoxic profile, increased myeloid cell activation, evidence for elevated immunomodulatory, chemotactic, and cytokine signaling, and accumulation of natural killer T cells. Tumors harboring exhausted-like T cells show increased expression of MHC-I on tumor cells and of CXCL13 on T cells, as well as altered spatial organization with more immature rather than mature tertiary lymphoid structures. Our data reveal fundamental differences between immune environments with and without exhausted T cells within luminal breast cancer, and show that expression of PD-1 and CXCL13 on T cells, and MHC-I - but not PD-L1 - on tumor cells are strong distinguishing features between these environments.

A high interferon gamma signature of CD8+ T cells predicts response to neoadjuvant immunotherapy plus chemotherapy in gastric cancer

Background

While the tumor microenvironment (TME) affects immune checkpoint blockade (ICB) efficacy, ICB also reshapes the characteristics of TME. Thus far, studies have focused on the TME evolution during neoadjuvant or adjuvant ICB therapy in gastric cancer (GC). However, the interaction between TME characteristics and neoadjuvant immunotherapy plus chemotherapy remains to be elucidated.

Methods

We performed single-cell RNA sequencing on ten GC specimens pre- and post-neoadjuvant camrelizumab plus mFOLFOX6 to determine the impact of the TME on the efficacy of the combination therapy and the remodeling of TME by the therapy.

Results

A high baseline interferon gamma (IFN-γ) signature in CD8⁺ T cells predicts better responses to the combination therapy. We also observed that the IFN-γ signature significantly decreased in multiple cell types, and the exhausted signature of CD8⁺ T cells was significantly suppressed during the neoadjuvant therapy.

Conclusions

Our data reveal interactions between the TME and neoadjuvant immunotherapy plus chemotherapy in GC. Importantly, it also highlights the signature of CD8⁺ T cells in predicting response to the combination therapy in GC.

Therapeutic Targeting of Cancer-Associated Fibroblasts in the Non-Small Cell Lung Cancer Tumor Microenvironment

Lung cancer is the most frequently diagnosed cancer and the leading cause of cancer death worldwide. The most common lung cancer is non-small cell lung cancer (NSCLC), with an overall 5-year survival rate of around 20% because NSCLC is a metastatic disease. A better understanding of the mechanism underlying lung cancer metastasis is therefore urgently needed. The tumor microenvironment involves different types of stromal cells and functions as key components in the progression of NSCLC. Through epithelial-mesenchymal transition (EMT), in which epithelial cells lose their polarity and acquire mesenchymal potential, cancer cells acquire metastatic abilities, as well as cancer stem-cell-like potential. We previously reported that cancer-associated fibroblasts (CAFs) interact with lung cancer cells to allow for the acquisition of malignancy and treatment resistance by paracrine loops via EMT signals in the tumor microenvironment. Furthermore, CAFs regulate the cytotoxic activity of immune cells via various cytokines and chemokines, creating a microenvironment of immune tolerance. Regulation of CAFs can therefore affect immune responses. Recent research has shown several roles of CAFs in NSCLC tumorigenesis, owing to their heterogeneity, so molecular markers of CAFs should be elucidated to better classify tumor-promoting subtypes and facilitate the establishment of CAF-specific targeted therapies. CAF-targeted cancer treatments may suppress EMT and regulate the niche of cancer stem cells and the immunosuppressive network and thus may prove useful for NSCLC treatment through multiple mechanisms.

ATF6-Mediated Signaling Contributes to PARP Inhibitor Resistance in Ovarian Cancer

High-grade serous ovarian cancer (HGSOC) is the deadliest ovarian cancer histotype due in-part to the lack of therapeutic options for chemotherapy-resistant disease. PARP inhibitors (PARPi) represent a targeted treatment. However, PARPi resistance is becoming a significant clinical challenge. There is an urgent need to overcome resistance mechanisms to extend disease-free intervals. We established isogeneic PARPi-sensitive and -resistant HGSOC cell lines. In three PARPi-resistant models, there is a significant increase in AP-1 transcriptional activity and DNA repair capacity. Using RNA-sequencing and an shRNA screen, we identified activating transcription factor 6 (ATF6) as a mediator of AP-1 activity, DNA damage response, and PARPi resistance. In publicly available datasets, ATF6 expression is elevated in HGSOC and portends a poorer recurrence-free survival. In a cohort of primary HGSOC tumors, higher ATF6 expression significantly correlated to PARPi resistance. In PARPi-resistant cell lines and a PDX model, inhibition of a known ATF6 regulator, p38, attenuated AP-1 activity and RAD51 foci formation, enhanced DNA damage, significantly inhibited tumor burden, and reduced accumulation of nuclear ATF6.

IMPLICATIONS

This study highlights that a novel p38-ATF6-mediated AP-1 signaling axis contributes to PARPi resistance and provides a clinical rationale for combining PARPi and AP-1 signaling inhibitors.

Immune desert in MMR-deficient tumors predicts poor responsiveness of immune checkpoint inhibition

Background

Although many efforts have been devoted to identify biomarkers to predict the responsiveness of immune checkpoint inhibitors, including expression of programmed death-ligand 1 (PD-L1) and major histocompatibility complex (MHC) I, microsatellite instability (MSI), mismatch repair (MMR) defect, tumor mutation burden (TMB), tertiary lymphoid structures (TLSs), and several transcriptional signatures, the sensitivity of these indicators remains to be further improved.

Materials and methods

Here, we integrated T-cell spatial distribution and intratumor transcriptional signals in predicting the response to immune checkpoint therapy in MMR-deficient tumors including tumors of Lynch syndrome (LS).

Results

In both cohorts, MMR-deficient tumors displayed personalized tumor immune signatures, including inflamed, immune excluded, and immune desert, which were not only individual-specific but also organ-specific. Furthermore, the immune desert tumor exhibited a more malignant phenotype characterized by low differentiation adenocarcinoma, larger tumor sizes, and higher metastasis rate. Moreover, the tumor immune signatures associated with distinct populations of infiltrating immune cells were comparable to TLSs and more sensitive than transcriptional signature gene expression profiles (GEPs) in immunotherapy prediction. Surprisingly, the tumor immune signatures might arise from the somatic mutations. Notably, patients with MMR deficiency had benefited from the typing of immune signatures and later immune checkpoint inhibition.

Conclusion

Our findings suggest that compared to PD-L1 expression, MMR, TMB, and GEPs, characterization of the tumor immune signatures in MMR-deficient tumors improves the efficiency of predicting the responsiveness of immune checkpoint inhibition.

Phenotypes and Functions of Human Dendritic Cell Subsets in the Tumor Microenvironment

Dendritic cells (DCs) play a key role in the antitumor immunity, as they are at the interface of innate and adaptive immunity. This important task can only be performed thanks to the broad range of mechanisms that DCs can perform to activate other immune cells. As DCs are well known for their outstanding capacity to prime and activate T cells through antigen presentation, DCs were intensively investigated during the past decades. Numerous studies have identified new DC subsets, leading to a large variety of subsets commonly separated into cDC1, cDC2, pDCs, mature DCs, Langerhans cells, monocyte-derived DCs, Axl-DCs, and several other subsets. Here, we review the specific phenotypes, functions, and localization within the tumor microenvironment (TME) of human DC subsets thanks to flow cytometry and immunofluorescence but also with the help of high-output technologies such as single-cell RNA sequencing and imaging mass cytometry (IMC).

Immune landscape of viral cancers: Insights from single-cell sequencing

Viral infections trigger a wide range of immune responses thought to drive tumorigenesis and malignant progression. Dissecting virus-induced changes in the tumor immune microenvironment (TIME) is therefore crucial to identify key leukocyte populations that may represent novel targets for cancer therapy. Single-cell sequencing approaches have now been widely applied to the analysis of various tumors, thus enabling multiomics characterization of the highly heterogeneous TIME that bulk-sequencing cannot fully elucidate. In this review, we summarized key recent findings from sequencing studies of the immune infiltrate and antitumor response in virus-associated cancers at single cell resolution. Additionally, we also reviewed recent developments in immunotherapy for virus-associated cancers. We anticipate that the strategic use of single-cell sequencing will advance our understanding of the TIME of viral cancers, leading to the development of more potent novel treatments.

Single-cell and spatial analyses reveal the association between gene expression of glutamine synthetase with the immunosuppressive phenotype of APOE+CTSZ+TAM in cancers

An immunosuppressive state is regulated by various factors in the tumor microenvironment (TME), including, but not limited to, metabolic plasticity of immunosuppressive cells and cytokines secreted by these cells. We used single-cell RNA-sequencing (scRNA-seq) data and applied single-cell flux estimation analysis to characterize the link between metabolism and cellular function within the hypoxic TME of colorectal (CRC) and lung cancer. In terms of metabolic heterogeneity, we found myeloid cells potentially inclined to accumulate glutamine but tumor cells inclined to accumulate glutamate. In particular, we uncovered a tumor-associated macrophage (TAM) subpopulation, APOE+CTSZ+TAM, that was present in high proportions in tumor samples and exhibited immunosuppressive characteristics through upregulating the expression of anti-inflammatory genes. The proportion of APOE+CTSZ+TAM and regulatory T cells (Treg) were positively correlated across CRC scRNA-seq samples. APOE+CTSZ+TAM potentially interacted with Treg via CXCL16-CCR6 signals, as seen by ligand-receptor interactions analysis. Notably, glutamate-to-glutamine metabolic flux score and glutamine synthetase (GLUL) expression were uniquely higher in APOE+CTSZ+TAM, compared with other cell types within the TME. GLUL expression in macrophages was positively correlated with anti-inflammatory score and was higher in high-grade and invasive tumor samples. Moreover, spatial transcriptome and multiplex immunofluorescence staining of samples showed that APOE+CTSZ+TAM and Treg potentially colocalized in the tissue sections from CRC clinical samples. These results highlight the specific role and metabolic characteristic of the APOE+CTSZ+TAM subpopulation and provide a new perspective for macrophage subcluster-targeted therapeutic interventions or metabolic checkpoint-based cancer therapies.

Integrating single-cell RNA-seq and bulk RNA-seq to construct prognostic signatures to explore the role of glutamine metabolism in breast cancer

BACKGROUND

Although breast cancer (BC) treatment has entered the era of precision therapy, the prognosis is good in the case of comprehensive multimodal treatment such as neoadjuvant, endocrine, and targeted therapy. However, due to its high heterogeneity, some patients still cannot benefit from conventional treatment and have poor survival prognoses. Amino acids and their metabolites affect tumor development, alter the tumor microenvironment, play an increasingly obvious role in immune response and regulation of immune cell function, and are involved in acquired and innate immune regulation; therefore, amino acid metabolism is receiving increasing attention.

METHODS

Based on public datasets, we carried out a comprehensive transcriptome and single-cell sequencing investigation. Then we used 2.5 Weighted Co-Expression Network Analysis (WGCNA) and Cox to evaluate glutamine metabolism-related genes (GRGs) in BC and constructed a prognostic model for BC patients. Finally, the expression and function of the signature key gene SNX3 were examined by in vitro experiments.

RESULTS

In this study, we constituted a risk signature to predict overall survival (OS) in BC patients by glutamine-related genes. According to our risk signature, BC patients can obtain a Prognostic Risk Signature (PRS), and the response to immunotherapy can be further stratified according to PRS. Compared with traditional clinicopathological features, PRS demonstrated robust prognostic power and accurate survival prediction. In addition, altered pathways and mutational patterns were analyzed in PRS subgroups. Our study sheds some light on the immune status of BC. In in vitro experiments, the knockdown of SNX3, an essential gene in the signature, resulted in a dramatic reduction in proliferation, invasion, and migration of MDA-MB-231 and MCF-7 cell lines.

CONCLUSION

We established a brand-new PRS consisting of genes associated with glutamine metabolism. It expands unique ideas for the diagnosis, treatment, and prognosis of BC.

Single-cell analysis of multiple cancer types reveals differences in endothelial cells between tumors and normal tissues

Endothelial cells (ECs) play an important role in tumor progression. Currently, the main target of anti-angiogenic therapy is the vascular endothelial growth factor (VEGF) pathway. Some patients do benefit from anti-VEGF/VEGFR therapy; however, a large number of patients do not have response or acquire drug resistance after treatment. Moreover, anti-VEGF/VEGFR therapy may lead to nephrotoxicity and cardiovascular-related side effects due to its action on normal ECs. Therefore, it is necessary to identify targets that are specific to tumor ECs and could be applied to various cancer types. We integrated single-cell RNA sequencing data from six cancer types and constructed a multi-cancer EC atlas to decode the characteristic of tumor ECs. We found that tip-like ECs mainly exist in tumor tissues but barely exist in normal tissues. Tip-like ECs are involved in the promotion of tumor angiogenesis and inhibition on anti-tumor immune responses. Moreover, tumor cells, myeloid cells, and pericytes are the main sources of pro-angiogenic factors. High proportion of tip-like ECs is associated with poor prognosis in multiple cancer types. We also identified that prostate-specific membrane antigen (PSMA) is a specific marker for tip-like ECs in all the cancer types we studied. In summary, we demonstrate that tip-like ECs are the main differential EC subcluster between tumors and normal tissues. Tip-like ECs may promote tumor progression through promoting angiogenesis while inhibiting anti-tumor immune responses. PSMA was a specific marker for tip-like ECs, which could be used as a potential target for the diagnosis and treatment of non-prostate cancers.

Evaluation of single-cell RNAseq labelling algorithms using cancer datasets

Single-cell RNA sequencing (scRNA-seq) clustering and labelling methods are used to determine precise cellular composition of tissue samples. Automated labelling methods rely on either unsupervised, cluster-based approaches or supervised, cell-based approaches to identify cell types. The high complexity of cancer poses a unique challenge, as tumor microenvironments are often composed of diverse cell subpopulations with unique functional effects that may lead to disease progression, metastasis and treatment resistance. Here, we assess 17 cell-based and 9 cluster-based scRNA-seq labelling algorithms using 8 cancer datasets, providing a comprehensive large-scale assessment of such methods in a cancer-specific context. Using several performance metrics, we show that cell-based methods generally achieved higher performance and were faster compared to cluster-based methods. Cluster-based methods more successfully labelled non-malignant cell types, likely because of a lack of gene signatures for relevant malignant cell subpopulations. Larger cell numbers present in some cell types in training data positively impacted prediction scores for cell-based methods. Finally, we examined which methods performed favorably when trained and tested on separate patient cohorts in scenarios similar to clinical applications, and which were able to accurately label particularly small or under-represented cell populations in the given datasets. We conclude that scPred and SVM show the best overall performances with cancer-specific data and provide further suggestions for algorithm selection. Our analysis pipeline for assessing the performance of cell type labelling algorithms is available in https://github.com/shooshtarilab/scRNAseq-Automated-Cell-Type-Labelling.

Single-Cell RNA Sequencing Reveals Heterogeneity in the Tumor Microenvironment between Young-Onset and Old-Onset Colorectal Cancer

BACKGROUND

The incidence of sporadic young-onset colorectal cancer (yCRC) is increasing. Compared with old-onset colorectal cancer (oCRC), yCRC has different clinical and molecular characteristics. However, the difference in the tumor microenvironment (TME) between yCRC and oCRC remains unclear.

METHODS

Fourteen untreated CRC tumor samples were subjected to single-cell RNA sequencing analysis.

RESULTS

B cells and naïve T cells are enriched in yCRC, while effector T cells and plasma cells are enriched in oCRC. Effector T cells of yCRC show decreased interferon-gamma response and proliferative activity; meanwhile, Treg cells in yCRC show stronger oxidative phosphorylation and TGF-β signaling than that in oCRC. The down-regulated immune response of T cells in yCRC may be regulated by immune and malignant cells, as we observed a downregulation of antigen presentation and immune activations in B cells, dendritic cells, and macrophages. Finally, we identified malignant cells in yCRC and oCRC with high heterogeneity and revealed their interactions with immune cells in the TME.

CONCLUSIONS

Our data reveal significant differences of TME between yCRC and oCRC, of which the TME of yCRC is more immunosuppressive than oCRC. Malignant cells play an essential role in the formation of the suppressive tumor immune microenvironment.

An integrated map of fibroblastic populations in human colon mucosa and cancer tissues

Fibroblasts and myofibroblasts are major mesenchymal cells in the lamina propria of colon mucosa and in colon cancer tissues. Detailed insight into the highly specific populations of fibroblasts and myofibroblasts is required to understand the integrity and homeostasis of human colon mucosa and colon cancer. Based on gene expression profiles of single cells, we identified fibroblast populations that produce extracellular matrix components, Wnt ligand- and BMP-secreting fibroblasts, chemokine- and chemokine ligand-generating fibroblasts, highly activated fibroblasts, immune-modulating fibroblasts, epithelial cell-modulating myofibroblasts, stimuli-responsive myofibroblasts, proliferating myofibroblasts, fibroblast-like myofibroblasts, matrix producing myofibroblasts, and contractile myofibroblasts in human colon mucosa. In colon cancer tissue, the compositions of fibroblasts and myofibroblasts were highly altered, as were the expressing patterns of genes including BMPs, Wnt ligands, chemokines, chemokine ligands, growth factors and extracellular matrix components in fibroblasts and myofibroblasts. Our work expands the working atlas of fibroblasts and myofibroblasts and provides a framework for interrogating the complexity of stromal cells in human healthy colon mucosa and colon cancer tissues.

Targeting cancer-associated fibroblasts: Challenges, opportunities and future directions

Cancer-associated fibroblasts (CAFs) are a common cell in the tumour microenvironment with diverse tumour-promoting functions. Their presence in tumours is commonly associated with poor prognosis making them attractive therapeutic targets, particularly in the context of immunotherapy where CAFs have been shown to promote resistance to checkpoint blockade. Previous attempts to inhibit CAFs clinically have not been successful, however, in part due to a lack of understanding of CAF heterogeneity and function, with some fibroblast populations potentially being tumour suppressive. Recent single-cell transcriptomic studies have advanced our understanding of fibroblast phenotypes in normal tissues and cancers, allowing for a more precise characterisation of CAF subsets and providing opportunities to develop new therapies. Here we review recent advances in the field, focusing on the evolving area of therapeutic CAF targeting.

Activation of innate-adaptive immune machinery by poly(I:C) exposes a therapeutic vulnerability to prevent relapse in stroma-rich colon cancer

OBJECTIVE

Stroma-rich tumours represent a poor prognostic subtype in stage II/III colon cancer (CC), with high relapse rates and limited response to standard adjuvant chemotherapy.

DESIGN

To address the lack of efficacious therapeutic options for patients with stroma-rich CC, we stratified our human tumour cohorts according to stromal content, enabling identification of the biology underpinning relapse and potential therapeutic vulnerabilities specifically within stroma-rich tumours that could be exploited clinically. Following human tumour-based discovery and independent clinical validation, we use a series of in vitro and stroma-rich in vivo models to test and validate the therapeutic potential of elevating the biology associated with reduced relapse in human tumours.

RESULTS

By performing our analyses specifically within the stroma-rich/high-fibroblast (HiFi) subtype of CC, we identify and validate the clinical value of a HiFi-specific prognostic signature (HPS), which stratifies tumours based on STAT1-related signalling (High-HPS v Low-HPS=HR 0.093, CI 0.019 to 0.466). Using in silico, in vitro and in vivo models, we demonstrate that the HPS is associated with antigen processing and presentation within discrete immune lineages in stroma-rich CC, downstream of double-stranded RNA and viral response signalling. Treatment with the TLR3 agonist poly(I:C) elevated the HPS signalling and antigen processing phenotype across in vitro and in vivo models. In an in vivo model of stroma-rich CC, poly(I:C) treatment significantly increased systemic cytotoxic T cell activity (p<0.05) and reduced liver metastases (p<0.0002).

CONCLUSION

This study reveals new biological insight that offers a novel therapeutic option to reduce relapse rates in patients with the worst prognosis CC.

Biophysical heterogeneity of myeloid-derived microenvironment to regulate resistance to cancer immunotherapy

Despite the advances in immunotherapy for cancer treatment, patients still obtain limited benefits, mostly owing to unrestrained tumour self-expansion and immune evasion that exploits immunoregulatory mechanisms. Traditionally, myeloid cells have a dominantly immunosuppressive role. However, the complicated populations of the myeloid cells and their multilateral interactions with tumour/stromal/lymphoid cells and physical abnormalities in the tumour microenvironment (TME) determine their heterogeneous functions in tumour development and immune response. Tumour-associated myeloid cells (TAMCs) include monocytes, tumour-associated macrophages (TAMs), myeloid-derived suppressor cells (MDSCs), dendritic cells (DCs), and granulocytes. Single-cell profiling revealed heterogeneous TAMCs composition, sub-types, and transcriptomic signatures across 15 human cancer types. We systematically reviewed the biophysical heterogeneity of TAMC composition and pro/anti-tumoral and immuno-suppressive/stimulating properties of myeloid-derived microenvironments. We also summarised comprehensive clinical strategies to overcome resistance to immunotherapy from three dimensions: targeting TAMCs, reversing physical abnormalities, utilising nanomedicines, and finally, put forward futuristic perspectives for scientific and clinical research.

Low-dose apatinib combined with camrelizumab and the SOX regimen in the neoadjuvant treatment of locally advanced gastric/gastroesophageal junction adenocarcinoma (SPACE-neo): a protocol for an open-label, single-arm, clinical trial

Background

Neoadjuvant chemotherapy with S-1 plus oxaliplatin (SOX regimen) has shown promising results in pathological response rate and survival rate in patients with locally advanced resectable gastric cancer (LAGC). We previously carried out the SPACE study to assess efficacy and safety of low-dose apatinib combined with camrelizumab and the SOX regimen as a first-line treatment of advanced gastric/gastroesophageal junction adenocarcinoma (AGC/GEJC). The preliminary results demonstrated a high objective response rate. However, the SPACE study was conducted in patients with AGC, but the efficacy of LAGC patients is not yet known. The SPACE-neo study is designed to investigate whether this combination could improve outcomes in patients with locally advanced gastric/gastroesophageal junction cancer (LAGC/GEJC) as neoadjuvant therapy.

Methods

SPACE-neo is a prospective, open-label, single-arm study conducted in China at the First Affiliated Hospital of Nanjing Medical University (Jiangsu Province Hospital). Thirty-two patients with human epidermal growth factor receptor 2 (HER2)-negative or HER2-unknown LAGC/GEJC confirmed by histopathology or cytology will be recruited. Included patients shall be clinically staged as M0 and either T3 to T4 or N+ assessed by ultrasound endoscopy and thoracoabdominal-enhanced computed tomography or magnetic resonance imaging. The patients will receive three cycles of this combined regimen as a neoadjuvant treatment. Each patient will receive screening visits within 2 weeks before the first cycle and planned visits before every cycle of treatment. Key monitoring data include imaging data, pathological findings, and adverse events associated with neoadjuvant and surgical treatment. The primary endpoints are major pathological response (MPR) and safety. MPR is the proportion of patients whose residual tumor cells make up less than 10% of the primary tumor from among the total cohort. Clopper-Pearson method will be used to estimate the 95% confidence interval of MPR and safety data will be reported as descriptive statistical analysis.

Discussion

The SPACE-neo trial aims to evaluate the safety and preliminary efficacy of this regimen in the neoadjuvant treatment of LAGC/GEJC. It is hoped that the study can achieve a higher pathological response rate and longer survival rate.

Trial Registration

ChiCTR.gov.cn: ChiCTR2100049305.

The promising therapeutic effects of metformin on metabolic reprogramming of cancer-associated fibroblasts in solid tumors

Tumor-infiltrated lymphocytes are exposed to many toxic metabolites and molecules in the tumor microenvironment (TME) that suppress their anti-tumor activity. Toxic metabolites, such as lactate and ketone bodies, are produced mainly by catabolic cancer-associated fibroblasts (CAFs) to feed anabolic cancer cells. These catabolic and anabolic cells make a metabolic compartment through which high-energy metabolites like lactate can be transferred via the monocarboxylate transporter channel 4. Moreover, a decrease in molecules, including caveolin-1, has been reported to cause deep metabolic changes in normal fibroblasts toward myofibroblast differentiation. In this context, metformin is a promising drug in cancer therapy due to its effect on oncogenic signal transduction pathways, leading to the inhibition of tumor proliferation and downregulation of key oncometabolites like lactate and succinate. The cross-feeding and metabolic coupling of CAFs and tumor cells are also affected by metformin. Therefore, the importance of metabolic reprogramming of stromal cells and also the pivotal effects of metformin on TME and oncometabolites signaling pathways have been reviewed in this study.

Dynamic Changes in the Extracellular Matrix in Primary, Metastatic, and Recurrent Ovarian Cancers

Cancer-associated fibroblasts (CAFs) and their extracellular matrix are active participants in cancer progression. While it is known that functionally different subpopulations of CAFs co-exist in ovarian cancer, it is unclear whether certain CAF subsets are enriched during metastatic progression and/or chemotherapy. Using computational image analyses of patient-matched primary high-grade serous ovarian carcinomas, synchronous pre-chemotherapy metastases, and metachronous post-chemotherapy metastases from 42 patients, we documented the dynamic spatiotemporal changes in the extracellular matrix, fibroblasts, epithelial cells, immune cells, and CAF subsets expressing different extracellular matrix components. Among the different CAF subsets, COL11A1+ CAFs were associated with linearized collagen fibers and exhibited the greatest enrichment in pre- and post-chemotherapy metastases compared to matched primary tumors. Although pre- and post-chemotherapy metastases were associated with increased CD8+ T cell infiltration, the infiltrate was not always evenly distributed between the stroma and cancer cells, leading to an increased frequency of the immune-excluded phenotype where the majority of CD8+ T cells are present in the tumor stroma but absent from the tumor parenchyma. Overall, most of the differences in the tumor microenvironment were observed between primary tumors and metastases, while fewer differences were observed between pre- and post-treatment metastases. These data suggest that the tumor microenvironment is largely determined by the primary vs. metastatic location of the tumor while chemotherapy does not have a significant impact on the host microenvironment.

Cell atlas of the immune microenvironment in gastrointestinal cancers: Dendritic cells and beyond

Gastrointestinal (GI) cancers occur in the alimentary tract and accessory organs. They exert a global burden with high morbidity and mortality. Inside the tumor microenvironment, dendritic cells (DCs) are the most efficient antigen-presenting cells and are necessary for adaptive immune responses such as T and B-cell maturation. However, the subsets of DCs revealed before were mostly based on flow cytometry and bulk sequencing. With the development of single-cell RNA sequencing (scRNA-seq), the tumor and microenvironment heterogeneity of GI cancer has been illustrated. In this review, we summarize the classification and development trajectory of dendritic cells at the single-cell level in GI cancer. Additionally, we focused on the interaction of DCs with T cells and their effect on the response to immunotherapy. Specifically, we focused on the newly identified tumor-infiltrating dendritic cells and discuss their potential function in antitumor immunity.

Extracellular matrix profiles determine risk and prognosis of the squamous cell carcinoma subtype of non-small cell lung carcinoma

BACKGROUND

Squamous cell carcinoma (SqCC) is a subtype of non-small cell lung cancer for which patient prognosis remains poor. The extracellular matrix (ECM) is critical in regulating cell behavior; however, its importance in tumor aggressiveness remains to be comprehensively characterized.

METHODS

Multi-omics data of SqCC human tumor specimens was combined to characterize ECM features associated with initiation and recurrence. Penalized logistic regression was used to define a matrix risk signature for SqCC tumors and its performance across a panel of tumor types and in SqCC premalignant lesions was evaluated. Consensus clustering was used to define prognostic matreotypes for SqCC tumors. Matreotype-specific tumor biology was defined by integration of bulk RNAseq with scRNAseq data, cell type deconvolution, analysis of ligand-receptor interactions and enriched biological pathways, and through cross comparison of matreotype expression profiles with aging and idiopathic pulmonary fibrosis lung profiles.

RESULTS

This analysis revealed subtype-specific ECM signatures associated with tumor initiation that were predictive of premalignant progression. We identified an ECM-enriched tumor subtype associated with the poorest prognosis. In silico analysis indicates that matrix remodeling programs differentially activate intracellular signaling in tumor and stromal cells to reinforce matrix remodeling associated with resistance and progression. The matrix subtype with the poorest prognosis resembles ECM remodeling in idiopathic pulmonary fibrosis and may represent a field of cancerization associated with elevated cancer risk.

CONCLUSIONS

Collectively, this analysis defines matrix-driven features of poor prognosis to inform precision medicine prevention and treatment strategies towards improving SqCC patient outcome.

Single cell sequencing revealed the mechanism of PD-1 resistance affected by the expression profile of peripheral blood immune cells in ESCC

BACKGROUND

Esophageal squamous carcinoma (ESCC) is a highly lethal malignancy with poor prognosis. The effect of transcriptome characteristics of patient immune microenvironment (TME) on the efficacy of immunosuppressive agents is still poorly understood.

METHODS

Here we extracted and isolated immune cells from peripheral blood of patients with PD-1 monoclonal antibody sensitivity and resistance, and conducted deep single-cell RNA sequencing to describe the baseline landscape of the composition, lineage, and functional status of infiltrating immune cells in peripheral blood of patients with esophageal cancer.

RESULTS

The transcriptome characteristics of immune cells were comprehensively analyzed, and the dynamic changes of cell percentage, heterogeneity of cell subtypes and interactions between cells were explained. Co-expression and pedigree tracking based on T-cell antigen receptors revealed a significant proportion of highly migratory intertissue-effector T cells. GO and KEGG enrichment pathway Analysis of CD8+ effect-T cells ESCC_S group and ESCC_D1,2 group, found that in the up-regulated enrichment pathway, ESCC_S group enriched more PD-L1 and PD-1 checkpoint pathways expressed in tumors (JUN/NFKBIA/FOS/KRAS/IFNG), which also exist in T cell receptor signaling pathways. MT2A, MT1X and MT1E were differentially expressed in ESCC patients with PD-1 monoclonal antibody resistance, which may be related to the resistance of PD-1 mMAB.

CONCLUSIONS

This study has an in-depth understanding of the influence of peripheral immune cell infiltration on the sensitivity of monoclonal antibody PD-1 in patients with esophageal cancer, which is helpful to promote the immunotherapy of patients with esophageal cancer.

CLEC-1 is a death sensor that limits antigen cross-presentation by dendritic cells and represents a target for cancer immunotherapy

Tumors exploit numerous immune checkpoints, including those deployed by myeloid cells to curtail antitumor immunity. Here, we show that the C-type lectin receptor CLEC-1 expressed by myeloid cells senses dead cells killed by programmed necrosis. Moreover, we identified Tripartite Motif Containing 21 (TRIM21) as an endogenous ligand overexpressed in various cancers. We observed that the combination of CLEC-1 blockade with chemotherapy prolonged mouse survival in tumor models. Loss of CLEC-1 reduced the accumulation of immunosuppressive myeloid cells in tumors and invigorated the activation state of dendritic cells (DCs), thereby increasing T cell responses. Mechanistically, we found that the absence of CLEC-1 increased the cross-presentation of dead cell-associated antigens by conventional type-1 DCs. We identified antihuman CLEC-1 antagonist antibodies able to enhance antitumor immunity in CLEC-1 humanized mice. Together, our results demonstrate that CLEC-1 acts as an immune checkpoint in myeloid cells and support CLEC-1 as a novel target for cancer immunotherapy.

scHumanNet: a single-cell network analysis platform for the study of cell-type specificity of disease genes

A major challenge in single-cell biology is identifying cell-type-specific gene functions, which may substantially improve precision medicine. Differential expression analysis of genes is a popular, yet insufficient approach, and complementary methods that associate function with cell type are required. Here, we describe scHumanNet (https://github.com/netbiolab/scHumanNet), a single-cell network analysis platform for resolving cellular heterogeneity across gene functions in humans. Based on cell-type-specific gene networks (CGNs) constructed under the guidance of the HumanNet reference interactome, scHumanNet displayed higher functional relevance to the cellular context than CGNs built by other methods on single-cell transcriptome data. Cellular deconvolution of gene signatures based on network compactness across cell types revealed breast cancer prognostic markers associated with T cells. scHumanNet could also prioritize genes associated with particular cell types using CGN centrality and identified the differential hubness of CGNs between disease and healthy conditions. We demonstrated the usefulness of scHumanNet by uncovering T-cell-specific functional effects of GITR, a prognostic gene for breast cancer, and functional defects in autism spectrum disorder genes specific for inhibitory neurons. These results suggest that scHumanNet will advance our understanding of cell-type specificity across human disease genes.

Pan-cancer single-cell analysis reveals the heterogeneity and plasticity of cancer-associated fibroblasts in the tumor microenvironment

Cancer-associated fibroblasts (CAFs) are the predominant components of the tumor microenvironment (TME) and influence cancer hallmarks, but without systematic investigation on their ubiquitous characteristics across different cancer types. Here, we perform pan-cancer analysis on 226 samples across 10 solid cancer types to profile the TME at single-cell resolution, illustrating the commonalities/plasticity of heterogenous CAFs. Activation trajectory of the major CAF types is divided into three states, exhibiting distinct interactions with other cell components, and relating to prognosis of immunotherapy. Moreover, minor CAF components represent the alternative origin from other TME components (e.g., endothelia and macrophages). Particularly, the ubiquitous presentation of endothelial-to-mesenchymal transition CAF, which may interact with proximal SPP1⁺ tumor-associated macrophages, is implicated in endothelial-to-mesenchymal transition and survival stratifications. Our study comprehensively profiles the shared characteristics and dynamics of CAFs, and highlight their heterogeneity and plasticity across different cancer types. Browser of integrated pan-cancer single-cell information is available at https://gist-fgl.github.io/sc-caf-atlas/ .

Developmental Deconvolution for Classification of Cancer Origin

Cancer is partly a developmental disease, with malignancies named based on cell or tissue of origin. However, a systematic atlas of tumor origins is lacking. Here we map the single-cell organogenesis of 56 developmental trajectories to the transcriptomes of over 10,000 tumors across 33 cancer types. We deconvolute tumor transcriptomes into signals for individual developmental trajectories. Using these signals as inputs, we construct a developmental multilayer perceptron (D-MLP) classifier that outputs cancer origin. D-MLP (ROC-AUC: 0.974 for top prediction) outperforms benchmark classifiers. We analyze tumors from patients with cancer of unknown primary (CUP), selecting the most difficult cases in which extensive multimodal workup yielded no definitive tumor type. Interestingly, CUPs form groups distinguished by developmental trajectories, and classification reveals diagnosis for patient tumors. Our results provide an atlas of tumor developmental origins, provide a tool for diagnostic pathology, and suggest developmental classification may be a useful approach for patient tumors.

SIGNIFICANCE

Here we map the developmental trajectories of tumors. We deconvolute tumor transcriptomes into signals for mammalian developmental programs and use this information to construct a deep learning classifier that outputs tumor type. We apply the classifier to CUP and reveal the developmental origins of patient tumors. See related commentary by Wang, p. 2498. This article is highlighted in the In This Issue feature, p. 2483.

Cancer-associated fibroblasts-derived lncRNA signature as a putative biomarker in breast cancer

Long noncoding RNAs (lncRNAs) have been reported to play a key role in regulating tumor microenvironment and immunity. Cancer-associated fibroblasts (CAFs) are abundant in many tumors. However, the functional and clinical significance of lncRNAs specifically expressed in CAFs has not been fully elucidated. In this study, we identified a list of 95 CAF-specific lncRNAs (FibLnc), including HHLA3, TP53TG1, ST7-AS1, LINC00536, ZNF503-AS1, MIR22HG, and MAPT-AS1, based on immune cell transcriptome expression profiling data. Based on the Cancer Genome Atlas and Gene Expression Omnibus datasets, we found that the FibLnc score predicted differences in overall patient survival and performed well in multiple datasets. FibLnc score was associated with the clinical stage of patients with breast cancer but did not significantly correlate with the PAM50 classification. Functional analysis showed that FibLnc was positively correlated with signaling pathways associated with malignant tumor progression. In addition, FibLnc was positively correlated with tumor mutational load and could predict immunotherapy response in patients with breast cancer receiving anti-PD-1 or anti-CTLA4 therapy. Our proposed FibLnc score was able to reflect the status of the immune environment and immunotherapeutic response in breast cancer, which could help explore potential therapeutic decisions and regulatory mechanisms of CAF-specific lncRNAs.

Therapeutic targeting of regulatory T cells in cancer

The success of immunotherapy in oncology underscores the vital role of the immune system in cancer development. Regulatory T cells (Tregs) maintain a fine balance between autoimmunity and immune suppression. They have multiple roles in the tumor microenvironment (TME) but act particularly in suppressing T cell activation. This review focuses on the detrimental and sometimes beneficial roles of Tregs in tumors, our current understanding of recruitment and stabilization of Tregs within the TME, and current Treg-targeted therapeutics. Research identifying subpopulations of Tregs and their respective functions and interactions within the complex networks of the TME will be crucial to develop the next generation of immunotherapies. Through these advances, Treg-targeted immunotherapy could have important implications for the future of oncology.

Effect of the intratumoral microbiota on spatial and cellular heterogeneity in cancer

The tumour-associated microbiota is an intrinsic component of the tumour microenvironment across human cancer types1,2. Intratumoral host-microbiota studies have so far largely relied on bulk tissue analysis1-3, which obscures the spatial distribution and localized effect of the microbiota within tumours. Here, by applying in situ spatial-profiling technologies4 and single-cell RNA sequencing5 to oral squamous cell carcinoma and colorectal cancer, we reveal spatial, cellular and molecular host-microbe interactions. We adapted 10x Visium spatial transcriptomics to determine the identity and in situ location of intratumoral microbial communities within patient tissues. Using GeoMx digital spatial profiling6, we show that bacterial communities populate microniches that are less vascularized, highly immuno‑suppressive and associated with malignant cells with lower levels of Ki-67 as compared to bacteria-negative tumour regions. We developed a single-cell RNA-sequencing method that we name INVADEseq (invasion-adhesion-directed expression sequencing) and, by applying this to patient tumours, identify cell-associated bacteria and the host cells with which they interact, as well as uncovering alterations in transcriptional pathways that are involved in inflammation, metastasis, cell dormancy and DNA repair. Through functional studies, we show that cancer cells that are infected with bacteria invade their surrounding environment as single cells and recruit myeloid cells to bacterial regions. Collectively, our data reveal that the distribution of the microbiota within a tumour is not random; instead, it is highly organized in microniches with immune and epithelial cell functions that promote cancer progression.

Efficacy of CD40 Agonists Is Mediated by Distinct cDC Subsets and Subverted by Suppressive Macrophages

Agonistic αCD40 therapy has been shown to inhibit cancer progression in only a fraction of patients. Understanding the cancer cell-intrinsic and microenvironmental determinants of αCD40 therapy response is therefore crucial to identify responsive patient populations and to design efficient combinatorial treatments. Here, we show that the therapeutic efficacy of αCD40 in subcutaneous melanoma relies on preexisting, type 1 classical dendritic cell (cDC1)-primed CD8+ T cells. However, after administration of αCD40, cDC1s were dispensable for antitumor efficacy. Instead, the abundance of activated cDCs, potentially derived from cDC2 cells, increased and further activated antitumor CD8+ T cells. Hence, distinct cDC subsets contributed to the induction of αCD40 responses. In contrast, lung carcinomas, characterized by a high abundance of macrophages, were resistant to αCD40 therapy. Combining αCD40 therapy with macrophage depletion led to tumor growth inhibition only in the presence of strong neoantigens. Accordingly, treatment with immunogenic cell death-inducing chemotherapy sensitized lung tumors to αCD40 therapy in subcutaneous and orthotopic settings. These insights into the microenvironmental regulators of response to αCD40 suggest that different tumor types would benefit from different combinations of therapies to optimize the clinical application of CD40 agonists.

SIGNIFICANCE

This work highlights the temporal roles of different dendritic cell subsets in promoting CD8+ T-cell-driven responses to CD40 agonist therapy in cancer.

The single cell transcriptional landscape of esophageal adenocarcinoma and its modulation by neoadjuvant chemotherapy

Immune checkpoint blockade has recently proven effective in subsets of patients with esophageal adenocarcinoma (EAC) but little is known regarding the EAC immune microenvironment. We determined the single cell transcriptional profile of EAC in 8 patients who were treatment-naive (n = 4) or had received neoadjuvant chemotherapy (n = 4). Analysis of 52,387 cells revealed 10 major cell subsets of tumor, immune and stromal cells. Prior to chemotherapy tumors were heavy infiltrated by T regulatory cells and exhausted effector T cells whilst plasmacytoid dendritic cells were markedly expanded. Two dominant cancer-associated fibroblast populations were also observed whilst endothelial populations were suppressed. Pathological remission following chemotherapy associated with broad reversal of immune abnormalities together with fibroblast transition and an increase in endothelial cells whilst a chemoresistant epithelial stem cell population correlated with poor response. These findings reveal features that underlie and limit the response to current immunotherapy and identify a range of novel opportunities for targeted therapy.

Decoding the colorectal cancer ecosystem emphasizes the cooperative role of cancer cells, TAMs and CAFsin tumor progression

Background

Single-cell transcription data provided unprecedented molecular information, enabling us to directly encode the ecosystem of colorectal cancer (CRC). Characterization of the diversity of epithelial cells and how they cooperate with tumor microenvironment cells (TME) to endow CRC with aggressive characteristics at single-cell resolution is critical for the understanding of tumor progression mechanism.

Methods

In this study, we comprehensively analyzed the single-cell transcription data, bulk-RNA sequencing data and pathological tissue data. In detail, cellular heterogeneity of TME and epithelial cells were analyzed by unsupervised classification and consensus nonnegative matrix factorization analysis, respectively. Functional status of epithelial clusters was annotated by CancerSEA and its crosstalk with TME cells was investigated using CellPhoneDB and correlation analysis. Findings from single-cell transcription data were further validated in bulk-RNA sequencing data and pathological tissue data.

Results

A distinct cellular composition was observed between tumor and normal tissues, and tumors exhibited immunosuppressive phenotypes. Regarding epithelial cells, we identified one highly invasiveQuery cluster, C4, that correlated closely with tumor-associated macrophages (TAMs) and cancer-associated fibroblasts (CAFs). Further analysis emphasized the TAMs subclass TAM1 and CAFs subclass S5 are closely related with C4.

Conclusions

In summary, our study elaborates on the cellular heterogeneity of CRC, revealing that TAMs and CAFs were critical for crosstalk network epithelial cells and TME cells. This in-depth understanding of cancer cell-TME network provided theoretical basis for the development of new drugs targeting this sophisticated network in CRC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03661-8.

Integrated analysis of cervical squamous cell carcinoma cohorts from three continents reveals conserved subtypes of prognostic significance

Human papillomavirus (HPV)-associated cervical cancer is a leading cause of cancer deaths in women. Here we present an integrated multi-omic analysis of 643 cervical squamous cell carcinomas (CSCC, the most common histological variant of cervical cancer), representing patient populations from the USA, Europe and Sub-Saharan Africa and identify two CSCC subtypes (C1 and C2) with differing prognosis. C1 and C2 tumours can be driven by either of the two most common HPV types in cervical cancer (16 and 18) and while HPV16 and HPV18 are overrepresented among C1 and C2 tumours respectively, the prognostic difference between groups is not due to HPV type. C2 tumours, which comprise approximately 20% of CSCCs across these cohorts, display distinct genomic alterations, including loss or mutation of the STK11 tumour suppressor gene, increased expression of several immune checkpoint genes and differences in the tumour immune microenvironment that may explain the shorter survival associated with this group. In conclusion, we identify two therapy-relevant CSCC subtypes that share the same defining characteristics across three geographically diverse cohorts.

Human papillomavirus (HPV) is a known cause of cervical cancer. Here, the authors perform a multi-omic analysis using published cervical squamous cell carcinoma cohorts from the USA, Europe, and SubSaharan Africa and identify two cervical squamous cell carcinoma subtypes that display prognostic differences.

Single-cell dissection of remodeled inflammatory ecosystem in primary and metastatic gallbladder carcinoma

Gallbladder carcinoma (GBC) is the most common biliary tract malignancy with the lowest survival rate, primarily arising from chronic inflammation. To better characterize the progression from inflammation to cancer to metastasis, we performed single-cell RNA sequencing across samples of 6 chronic cholecystitis, 12 treatment-naive GBCs, and 6 matched metastases. Benign epithelial cells from inflamed gallbladders displayed resting, immune-regulating, and gastrointestinal metaplastic phenotypes. A small amount of PLA2G2A⁺ epithelial cells with copy number variation were identified from a histologically benign sample. We validated significant overexpression of PLA2G2A across in situ GBCs, together with increased proliferation and cancer stemness in PLA2G2A-overexpressing GBC cells, indicating an important role for PLA2G2A during early carcinogenesis. Malignant epithelial cells displayed pervasive cancer hallmarks and cellular plasticity, differentiating into metaplastic, inflammatory, and mesenchymal subtypes with distinct transcriptomic, genomic, and prognostic patterns. Chronic cholecystitis led to an adapted microenvironment characterized by MDSC-like macrophages, CD8⁺ T_RM cells, and CCL2⁺ immunity-regulating fibroblasts. By contrast, GBC instigated an aggressive and immunosuppressive microenvironment, featured by tumor-associated macrophages, Treg cells, CD8⁺ T_EX cells, and STMN1⁺ tumor-promoting fibroblasts. Single-cell and bulk RNA-seq profiles consistently showed a more suppressive immune milieu for GBCs with inflammatory epithelial signatures, coupled with strengthened epithelial-immune crosstalk. We further pinpointed a subset of senescence-like fibroblasts (FN1⁺TGM2⁺) preferentially enriched in metastatic lesions, which promoted GBC migration and invasion via their secretory phenotype. Collectively, this study provides comprehensive insights into epithelial and microenvironmental reprogramming throughout cholecystitis-propelled carcinogenesis and metastasis, laying a new foundation for the precision therapy of GBC.

Transcriptional Heterogeneity of Cellular Senescence in Cancer

Cellular senescence plays a paradoxical role in tumorigenesis through the expression of diverse senescence-associated (SA) secretory phenotypes (SASPs). The heterogeneity of SA gene expression in cancer cells not only promotes cancer stemness but also protects these cells from chemotherapy. Despite the potential correlation between cancer and SA biomarkers, many transcriptional changes across distinct cell populations remain largely unknown. During the past decade, single-cell RNA sequencing (scRNA-seq) technologies have emerged as powerful experimental and analytical tools to dissect such diverse senescence-derived transcriptional changes. Here, we review the recent sequencing efforts that successfully characterized scRNA-seq data obtained from diverse cancer cells and elucidated the role of senescent cells in tumor malignancy. We further highlight the functional implications of SA genes expressed specifically in cancer and stromal cell populations in the tumor microenvironment. Translational research leveraging scRNA-seq profiling of SA genes will facilitate the identification of novel expression patterns underlying cancer susceptibility, providing new therapeutic opportunities in the era of precision medicine.

Dendritic Cells: The Long and Evolving Road towards Successful Targetability in Cancer

Dendritic cells (DCs) are a unique myeloid cell lineage that play a central role in the priming of the adaptive immune response. As such, they are an attractive target for immune oncology based therapeutic approaches. However, targeting these cells has proven challenging with many studies proving inconclusive or of no benefit in a clinical trial setting. In this review, we highlight the known and unknown about this rare but powerful immune cell. As technologies have expanded our understanding of the complexity of DC development, subsets and response features, we are now left to apply this knowledge to the design of new therapeutic strategies in cancer. We propose that utilization of these technologies through a multiomics approach will allow for an improved directed targeting of DCs in a clinical trial setting. In addition, the DC research community should consider a consensus on subset nomenclature to distinguish new subsets from functional or phenotypic changes in response to their environment.

Recent developments in application of single-cell RNA sequencing in the tumour immune microenvironment and cancer therapy

The advent of single-cell RNA sequencing (scRNA-seq) has provided insight into the tumour immune microenvironment (TIME). This review focuses on the application of scRNA-seq in investigation of the TIME. Over time, scRNA-seq methods have evolved, and components of the TIME have been deciphered with high resolution. In this review, we first introduced the principle of scRNA-seq and compared different sequencing approaches. Novel cell types in the TIME, a continuous transitional state, and mutual intercommunication among TIME components present potential targets for prognosis prediction and treatment in cancer. Thus, we concluded novel cell clusters of cancer-associated fibroblasts (CAFs), T cells, tumour-associated macrophages (TAMs) and dendritic cells (DCs) discovered after the application of scRNA-seq in TIME. We also proposed the development of TAMs and exhausted T cells, as well as the possible targets to interrupt the process. In addition, the therapeutic interventions based on cellular interactions in TIME were also summarized. For decades, quantification of the TIME components has been adopted in clinical practice to predict patient survival and response to therapy and is expected to play an important role in the precise treatment of cancer. Summarizing the current findings, we believe that advances in technology and wide application of single-cell analysis can lead to the discovery of novel perspectives on cancer therapy, which can subsequently be implemented in the clinic. Finally, we propose some future directions in the field of TIME studies that can be aided by scRNA-seq technology.