Pan-cancer single-cell landscape of tumor-infiltrating T cells

Combination of radiotherapy and PD-L1 blockade induces abscopal responses in EGFR-mutated lung cancer through activating CD8+ T cells

Patients with EGFR-mutated non-small cell lung cancer (NSCLC) respond poorly to immune checkpoint inhibitors (ICIs). It has been reported that the number of CD8+T cells is reduced in EGFR-mutated NSCLC. However, the extent of heterogeneity and effector function of distinct populations of CD8+T cells has not been investigated intensively. In addition, studies investigating whether a combination of radiotherapy and ICIs can improve the efficacy of ICIs in EGFR-mutated lung cancer are lacking. Single-cell RNA sequencing (scRNA-seq) was used to investigate the heterogeneity of CD8+T cell populations in EGFR-mutated NSCLC. The STING pathway was explored after hypofractionated radiation of EGFR-mutated and wild-type cells. Mice bearing LLC-19del and LLC-EGFR tumors were treated with radiotherapy plus anti-PD-L1. The scRNA-seq data showed the percentage of progenitor exhausted CD8+T cells was lower in EGFR-mutated NSCLC. In addition, CD8+T cells in EGFR-mutated NSCLC were enriched in oxidative phosphorylation. In EGFR-mutated and wild-type cells, 8 Gy × 3 increased the expression of chemokines that recruit T cells and activate the cGAS-STING pathway. In the LLC-19del and LLC-EGFR mouse model, the combination of radiation and anti-PD-L1 significantly inhibited the growth of abscopal tumors. The enhanced abscopal effect was associated with systemic CD8+T cell infiltration. This study provided an intensive understanding of the heterogeneity and effector functions of CD8+T cells in EGFR-mutated NSCLC. We showed that the combination of hypofractionated radiation and anti-PD-L1 significantly enhanced the abscopal responses in both EGFR-mutated and wild-type lung cancer by activating CD8+T cells in mice.

Single-cell transcriptomic analysis of immune cell dynamics in the healthy human endometrium

The microenvironment of the endometrial immune system is crucial to the success of placental implantation and healthy pregnancy. However, the functionalities of immune cells across various stages of the reproductive cycle have yet to be fully comprehended. To address this, we conducted advanced bioinformatic analysis on 230,049 high-quality single-cell transcriptomes from healthy endometrial samples obtained during the proliferative, secretory, early pregnancy, and late pregnancy stages. Our investigation has unveiled that proliferative natural killer (NK) cells, a potential source of endometrial NK cells, exhibit the most robust proliferative and differentiation potential during non-pregnant stages. We have also identified similar differentiation trajectories of NK cells originating from proliferative NK cells across four stages. Notably, during early pregnancy, NK cells demonstrate the highest oxidative phosphorylation metabolism activity, and, in conjunction with macrophages and T cells, exhibit the strongest type II interferon response. With spatial transcriptome data, we have discerned that the most robust immune-non-immune interactions are associated with the promotion and inhibition of cell proliferation, differentiation and migration during four stages. Furthermore, we have compiled lists of stage-specific risk genes implicated in reproductive diseases, which hold promise as potential disease biomarkers. Our study provides insights into the dynamics of the endometrial immune microenvironment during different reproductive cycle stages, thus serving as a reference for detecting pathological changes during pregnancy.

Pan-cancer single-cell landscape of drug-metabolizing enzyme genes

OBJECTIVE

Varied expression of drug-metabolizing enzymes (DME) genes dictates the intensity and duration of drug response in cancer treatment. This study aimed to investigate the transcriptional profile of DMEs in tumor microenvironment (TME) at single-cell level and their impact on individual responses to anticancer therapy.

METHODS

Over 1.3 million cells from 481 normal/tumor samples across 9 solid cancer types were integrated to profile changes in the expression of DME genes. A ridge regression model based on the PRISM database was constructed to predict the influence of DME gene expression on drug sensitivity.

RESULTS

Distinct expression patterns of DME genes were revealed at single-cell resolution across different cancer types. Several DME genes were highly enriched in epithelial cells (e.g. GPX2, TST and CYP3A5 ) or different TME components (e.g. CYP4F3 in monocytes). Particularly, GPX2 and TST were differentially expressed in epithelial cells from tumor samples compared to those from normal samples. Utilizing the PRISM database, we found that elevated expression of GPX2, CYP3A5 and reduced expression of TST was linked to enhanced sensitivity of particular chemo-drugs (e.g. gemcitabine, daunorubicin, dasatinib, vincristine, paclitaxel and oxaliplatin).

CONCLUSION

Our findings underscore the varied expression pattern of DME genes in cancer cells and TME components, highlighting their potential as biomarkers for selecting appropriate chemotherapy agents.

Nuclear HMGB1 is critical for CD8 T cell IFN-γ production and anti-tumor immunity

HMGB1 (high-mobility group box-1) has been extensively studied as a damage-associated molecular pattern, with secreted cytokine function. However, its regulation on T cells, especially the function in the nucleus, has not been elucidated. Here, we use conditional knockout (HMGB1-f/f; CD2-cre) mice and find that HMGB1 potentiates the proliferation and interferon gamma (IFN-γ) expression of CD8 T cells rather than CD4 T cells. Notably, nuclear, but not secreted, HMGB1 supports the expression of IFN-γ in CD8 T cells via directly regulating the activity of Eomes, the transcription factor for IFN-γ. Functional study shows that HMGB1 promotes the anti-tumor ability of CD8 T cells in vitro and in vivo. Finally, tumor environmental interleukin-7 promotes HMGB1 and IFN-γ production via fatty acid oxidation in CD8 T cells. Overall, we identify the role of nuclear HMGB1 in CD8 T cell differentiation and demonstrate that it plays an important role in the anti-tumor programs of CD8 T cells.

Somatic mutations in tumor-infiltrating lymphocytes impact on antitumor immunity

Immune checkpoint inhibitors (ICIs) exert clinical efficacy against various types of cancers by reinvigorating exhausted CD8+ T cells that can expand and directly attack cancer cells (cancer-specific T cells) among tumor-infiltrating lymphocytes (TILs). Although some reports have identified somatic mutations in TILs, their effect on antitumor immunity remains unclear. In this study, we successfully established 18 cancer-specific T cell clones, which have an exhaustion phenotype, from the TILs of four patients with melanoma. We conducted whole-genome sequencing for these T cell clones and identified various somatic mutations in them with high clonality. Among the somatic mutations, an SH2D2A loss-of-function frameshift mutation and TNFAIP3 deletion could activate T cell effector functions in vitro. Furthermore, we generated CD8+ T cell-specific Tnfaip3 knockout mice and showed that Tnfaip3 function loss in CD8+ T cell increased antitumor immunity, leading to remarkable response to PD-1 blockade in vivo. In addition, we analyzed bulk CD3+ T cells from TILs in additional 12 patients and identified an SH2D2A mutation in one patient through amplicon sequencing. These findings suggest that somatic mutations in TILs can affect antitumor immunity and suggest unique biomarkers and therapeutic targets.

The heterogeneity of cellular metabolism in the tumour microenvironment of hepatocellular carcinoma with portal vein tumour thrombus

Given the growing interest in the metabolic heterogeneity of hepatocellular carcinoma (HCC) and portal vein tumour thrombus (PVTT). This study comprehensively analysed the metabolic heterogeneity of HCC, PVTT, and normal liver samples using multi-omics combinations. A single-cell RNA sequencing dataset encompassing six major cell types was obtained for integrated analysis. The optimal subtypes were identified using cluster stratification and validated using spatial transcriptomics and fluorescent multiplex immunohistochemistry. Then, a combined index based meta-cluster was calculated to verify its prognostic significance using multi-omics data from public cohorts. Our study first depicted the metabolic heterogeneity landscape of non-malignant cells in HCC and PVTT at multiomics levels. The optimal subtypes interpret the metabolic characteristics of PVTT formation and development. The combined index provided effective predictions of prognosis and immunotherapy responses. Patients with a higher combined index had a relatively poor prognosis (p <0.001). We also found metabolism of polyamines was a key metabolic pathway involved in conversion of metabolic heterogeneity in HCC and PVTT, and identified ODC1 was significantly higher expressed in PVTT compared to normal tissue (p =0.03). Our findings revealed both consistency and heterogeneity in the metabolism of non-malignant cells in HCC and PVTT. The risk stratification based on cancer-associated fibroblasts and myeloid cells conduce to predict prognosis and guide treatment. This offers new directions for understanding disease development and immunotherapy responses.

METI: deep profiling of tumor ecosystems by integrating cell morphology and spatial transcriptomics

Recent advances in spatial transcriptomics (ST) techniques provide valuable insights into cellular interactions within the tumor microenvironment (TME). However, most analytical tools lack consideration of histological features and rely on matched single-cell RNA sequencing data, limiting their effectiveness in TME studies. To address this, we introduce the Morphology-Enhanced Spatial Transcriptome Analysis Integrator (METI), an end-to-end framework that maps cancer cells and TME components, stratifies cell types and states, and analyzes cell co-localization. By integrating spatial transcriptomics, cell morphology, and curated gene signatures, METI enhances our understanding of the molecular landscape and cellular interactions within the tissue. We evaluate the performance of METI on ST data generated from various tumor tissues, including gastric, lung, and bladder cancers, as well as premalignant tissues. We also conduct a quantitative comparison of METI with existing clustering and cell deconvolution tools, demonstrating METI's robust and consistent performance.

Mapping spatial organization and genetic cell-state regulators to target immune evasion in ovarian cancer

The drivers of immune evasion are not entirely clear, limiting the success of cancer immunotherapies. Here we applied single-cell spatial and perturbational transcriptomics to delineate immune evasion in high-grade serous tubo-ovarian cancer. To this end, we first mapped the spatial organization of high-grade serous tubo-ovarian cancer by profiling more than 2.5 million cells in situ in 130 tumors from 94 patients. This revealed a malignant cell state that reflects tumor genetics and is predictive of T cell and natural killer cell infiltration levels and response to immune checkpoint blockade. We then performed Perturb-seq screens and identified genetic perturbations-including knockout of PTPN1 and ACTR8-that trigger this malignant cell state. Finally, we show that these perturbations, as well as a PTPN1/PTPN2 inhibitor, sensitize ovarian cancer cells to T cell and natural killer cell cytotoxicity, as predicted. This study thus identifies ways to study and target immune evasion by linking genetic variation, cell-state regulators and spatial biology.

Immune suppression by human thymus-derived effector Tregs relies on glucose/lactate-fueled fatty acid synthesis

Regulatory T cells (Tregs) suppress pro-inflammatory conventional T cell (Tconv) responses. As lipids impact cell signaling and function, we compare the lipid composition of CD4+ thymus-derived (t)Tregs and Tconvs. Lipidomics reveal constitutive enrichment of neutral lipids in Tconvs and phospholipids in tTregs. TNFR2-co-stimulated effector tTregs and Tconvs are both glycolytic, but only in tTregs are glycolysis and the tricarboxylic acid (TCA) cycle linked to a boost in fatty acid (FA) synthesis (FAS), supported by relevant gene expression. FA chains in tTregs are longer and more unsaturated than in Tconvs. In contrast to Tconvs, tTregs effectively use either lactate or glucose for FAS and rely on this process for proliferation. FASN and SCD1, enzymes responsible for FAS and FA desaturation, prove essential for the ability of tTregs to suppress Tconvs. These data illuminate how effector tTregs can thrive in inflamed or cancerous tissues with limiting glucose but abundant lactate levels.

Tumor immune microenvironment of NSCLC with EGFR exon 20 insertions may predict efficacy of first-line ICI-combined regimen

OBJECTIVES

Non-small cell lung cancer (NSCLC) patients with exon 20 insertion mutations (ex20ins) of the epidermal growth factor receptor (EGFR) were resistant to monotherapy of immune checkpoint inhibitor (ICI). However, recent reports have shown that the combination of ICI and chemotherapy (ICI-combined regimen) exhibited certain efficacy for NSCLC with EGFR ex20ins. The mechanisms behind this phenomenon have not been thoroughly clarified. Hence, we conducted this study tofind correlations between the tumor immune microenvironment of EGFR ex20ins and the efficacy of ICI-combined regimen.

METHODS

We performed single-cell transcriptome sequencing and multiplex immunofluorescence staining (mIF) to investigate the immune microenvironment of NSCLC patients with EGFR ex20ins, L858R, and EGFR wild-type. We analyzed 15 treatment-naïve NSCLC samples utilizing single-cell RNA sequencing (scRNA-seq). Another 30 cases of EGFR L858R and 4 cases of wild-type were recruited to compare the immune microenvironment with that of EGFR ex20ins (28 cases) by mIF.

RESULTS

We observed that cell components, function and interactions varied between EGFR ex20ins, L858R, and wild-type NSCLC.We discovered similar T cell and CD8+ T cell distributions among groups but found noninferior or even better T cell activation in ex20ins patients. Infiltrating CD8+ FOXP3- T cells were significantly lower in the tumor region of EGFR ex20ins compared to wild-type. T cells from the ex20ins group had a greater tendency to promote cancer cell inflammation and epithelial-mesenchymal transition (EMT) compared to wild-type group. For macrophages, there were more M2-like macrophages in ex20ins patients. M1-like macrophages in ex20ins group produced fewer antitumor cytokines than in other groups.

CONCLUSIONS

The immune microenvironment of EGFR ex20ins is more suppressive than that of L858R and wild-type, suggesting that ICI monotherapy may not be sufficient for these patients. ICI-combined regimen might be a treatment option for EGFR ex20ins due to tumor-promoting inflammation and noninferior T cell functions in the immune microenvironment.

Pan-cancer single-cell dissection reveals phenotypically distinct B cell subtypes

Characterizing the compositional and phenotypic characteristics of tumor-infiltrating B cells (TIBs) is important for advancing our understanding of their role in cancer development. Here, we establish a comprehensive resource of human B cells by integrating single-cell RNA sequencing data of B cells from 649 patients across 19 major cancer types. We demonstrate substantial heterogeneity in their total abundance and subtype composition and observe immunoglobulin G (IgG)-skewness of antibody-secreting cell isotypes. Moreover, we identify stress-response memory B cells and tumor-associated atypical B cells (TAABs), two tumor-enriched subpopulations with prognostic potential, shared in a pan-cancer manner. In particular, TAABs, characterized by a high clonal expansion level and proliferative capacity as well as by close interactions with activated CD4 T cells in tumors, are predictive of immunotherapy response. Our integrative resource depicts distinct clinically relevant TIB subsets, laying a foundation for further exploration of functional commonality and diversity of B cells in cancer.

Tumor editing suppresses innate and adaptive antitumor immunity and is reversed by inhibiting DNA methylation

Cancer cells edit gene expression to evade immunosurveillance. However, genome-wide studies of gene editing during early tumorigenesis are lacking. Here we used single-cell RNA sequencing in a breast cancer genetically engineered mouse model (GEMM) to identify edited genes without bias. Late tumors repressed antitumor immunity genes, reducing infiltrating immune cells and tumor-immune cell communications. Innate immune genes, especially interferon-stimulated genes, dominated the list of downregulated tumor genes, while genes that regulate cell-intrinsic malignancy were mostly unedited. Naive and activated CD8+ T cells in early tumors were replaced with exhausted or precursor-exhausted cells in late tumors. Repression of immune genes was reversed by inhibiting DNA methylation using low-dose decitabine, which suppressed tumor growth and restored immune control, increasing the number, functionality and memory of tumor-infiltrating lymphocytes and reducing the number of myeloid suppressor cells. Decitabine induced important interferon, pyroptosis and necroptosis genes, inflammatory cell death and immune control in GEMM and implanted breast and melanoma tumors.

Precise detection of cell-type-specific domains in spatial transcriptomics

Cell-type-specific domains are the anatomical domains in spatially resolved transcriptome (SRT) tissues where particular cell types are enriched coincidentally. It is challenging to use existing computational methods to detect specific domains with low-proportion cell types, which are partly overlapped with or even inside other cell-type-specific domains. Here, we propose De-spot, which synthesizes segmentation and deconvolution as an ensemble to generate cell-type patterns, detect low-proportion cell-type-specific domains, and display these domains intuitively. Experimental evaluation showed that De-spot enabled us to discover the co-localizations between cancer-associated fibroblasts and immune-related cells that indicate potential tumor microenvironment (TME) domains in given slices, which were obscured by previous computational methods. We further elucidated the identified domains and found that Srgn may be a critical TME marker in SRT slices. By deciphering T cell-specific domains in breast cancer tissues, De-spot also revealed that the proportions of exhausted T cells were significantly increased in invasive vs. ductal carcinoma.

Exploring the role of the immune microenvironment in hepatocellular carcinoma: Implications for immunotherapy and drug resistance

Hepatocellular carcinoma (HCC), the most common type of liver tumor, is a leading cause of cancer-related deaths, and the incidence of liver cancer is still increasing worldwide. Curative hepatectomy or liver transplantation is only indicated for a small population of patients with early-stage HCC. However, most patients with HCC are not candidates for radical resection due to disease progression, leading to the choice of the conventional tyrosine kinase inhibitor drug sorafenib as first-line treatment. In the past few years, immunotherapy, mainly immune checkpoint inhibitors (ICIs), has revolutionized the clinical strategy for HCC. Combination therapy with ICIs has proven more effective than sorafenib, and clinical trials have been conducted to apply these therapies to patients. Despite significant progress in immunotherapy, the molecular mechanisms behind it remain unclear, and immune resistance is often challenging to overcome. Several studies have pointed out that the complex intercellular communication network in the immune microenvironment of HCC regulates tumor escape and drug resistance to immune response. This underscores the urgent need to analyze the immune microenvironment of HCC. This review describes the immunosuppressive cell populations in the immune microenvironment of HCC, as well as the related clinical trials, aiming to provide insights for the next generation of precision immunotherapy.

Resident memory T cells and cancer

Tissue-resident memory T (TRM) cells positively correlate with cancer survival, but the anti-tumor mechanisms underlying this relationship are not understood. This review reconciles these observations, summarizing concepts of T cell immunosurveillance, fundamental TRM cell biology, and clinical observations on the role of TRM cells in cancer and immunotherapy outcomes. We also discuss emerging strategies that utilize TRM-phenotype cells for patient diagnostics, staging, and therapy. Current challenges are highlighted, including a lack of standardized T cell nomenclature and our limited understanding of relationships between T cell markers and underlying tumor biology. Existing findings are integrated into a summary of the field while emphasizing opportunities for future research.

Single-cell long-read targeted sequencing reveals transcriptional variation in ovarian cancer

Single-cell RNA sequencing predominantly employs short-read sequencing to characterize cell types, states and dynamics; however, it is inadequate for comprehensive characterization of RNA isoforms. Long-read sequencing technologies enable single-cell RNA isoform detection but are hampered by lower throughput and unintended sequencing of artifacts. Here we develop Single-cell Targeted Isoform Long-Read Sequencing (scTaILoR-seq), a hybridization capture method which targets over a thousand genes of interest, improving the median number of on-target transcripts per cell by 29-fold. We use scTaILoR-seq to identify and quantify RNA isoforms from ovarian cancer cell lines and primary tumors, yielding 10,796 single-cell transcriptomes. Using long-read variant calling we reveal associations of expressed single nucleotide variants (SNVs) with alternative transcript structures. Phasing of SNVs across transcripts enables the measurement of allelic imbalance within distinct cell populations. Overall, scTaILoR-seq is a long-read targeted RNA sequencing method and analytical framework for exploring transcriptional variation at single-cell resolution.

Interferon signaling and ferroptosis in tumor immunology and therapy

This study sought to elucidate the mechanisms underlying the impact of the interferon signaling pathway on Ferroptosis in tumor cells and its correlation with CD8 + T cell exhaustion. Using mouse models and single-cell sequencing, the researchers studied the interaction between CD8 + T cells and the interferon signaling pathway. Differential gene analysis revealed key genes involved in CD8 + T cell exhaustion, and their downstream factors were explored using bioinformatics tools. The expression levels of interferon-related genes associated with Ferroptosis were analyzed using data from the TCGA database, and their relevance to tumor tissue Ferroptosis and patients' prognosis was determined. In vitro experiments were conducted to measure the levels of IFN-γ, MDA, and LPO, as well as tumor cell viability and apoptosis. In vivo validation using a mouse tumor model confirmed the results obtained from the in vitro experiments, highlighting the potential of silencing HSPA6 or DNAJB1 in enhancing the efficacy of PD-1 therapy and inhibiting tumor growth and migration.

Single-cell transcriptome profiles the heterogeneity of tumor cells and microenvironments for different pathological endometrial cancer and identifies specific sensitive drugs

Endometrial cancer (EC) is a highly heterogeneous malignancy characterized by varied pathology and prognoses, and the heterogeneity of its cancer cells and the tumor microenvironment (TME) remains poorly understood. We conducted single-cell RNA sequencing (scRNA-seq) on 18 EC samples, encompassing various pathological types to delineate their specific unique transcriptional landscapes. Cancer cells from diverse pathological sources displayed distinct hallmarks labeled as immune-modulating, proliferation-modulating, and metabolism-modulating cancer cells in uterine clear cell carcinomas (UCCC), well-differentiated endometrioid endometrial carcinomas (EEC-I), and uterine serous carcinomas (USC), respectively. Cancer cells from the UCCC exhibited the greatest heterogeneity. We also identified potential effective drugs and confirmed their effectiveness using patient-derived EC organoids for each pathological group. Regarding the TME, we observed that prognostically favorable CD8+ Tcyto and NK cells were prominent in normal endometrium, whereas CD4+ Treg, CD4+ Tex, and CD8+ Tex cells dominated the tumors. CXCL3+ macrophages associated with M2 signature and angiogenesis were exclusively found in tumors. Prognostically relevant epithelium-specific cancer-associated fibroblasts (eCAFs) and SOD2+ inflammatory CAFs (iCAFs) predominated in EEC-I and UCCC groups, respectively. We also validated the oncogenic effects of SOD2+ iCAFs in vitro. Our comprehensive study has yielded deeper insights into the pathogenesis of EC, potentially facilitating personalized treatments for its varied pathological types.

Glycosphingolipid synthesis mediates immune evasion in KRAS-driven cancer

Cancer cells frequently alter their lipids to grow and adapt to their environment1-3. Despite the critical functions of lipid metabolism in membrane physiology, signalling and energy production, how specific lipids contribute to tumorigenesis remains incompletely understood. Here, using functional genomics and lipidomic approaches, we identified de novo sphingolipid synthesis as an essential pathway for cancer immune evasion. Synthesis of sphingolipids is surprisingly dispensable for cancer cell proliferation in culture or in immunodeficient mice but required for tumour growth in multiple syngeneic models. Blocking sphingolipid production in cancer cells enhances the anti-proliferative effects of natural killer and CD8+ T cells partly via interferon-γ (IFNγ) signalling. Mechanistically, depletion of glycosphingolipids increases surface levels of IFNγ receptor subunit 1 (IFNGR1), which mediates IFNγ-induced growth arrest and pro-inflammatory signalling. Finally, pharmacological inhibition of glycosphingolipid synthesis synergizes with checkpoint blockade therapy to enhance anti-tumour immune response. Altogether, our work identifies glycosphingolipids as necessary and limiting metabolites for cancer immune evasion.

Deciphering the interplay of HPV infection, MHC-II expression, and CXCL13+ CD4+ T cell activation in oropharyngeal cancer: implications for immunotherapy

BACKGROUND

Human papillomavirus (HPV) infection has become an important etiological driver of oropharyngeal squamous cell carcinoma (OPSCC), leading to unique tumor characteristics. However, the interplay between HPV-associated tumor cells and tumor microenvironment (TME) remains an enigma.

METHODS

We performed a single-cell RNA-sequencing (scRNA-seq) on HPV-positive (HPV+) and HPV-negative (HPV‒) OPSCC tumors, each for three samples, and one normal tonsil tissue. Ex vivo validation assays including immunofluorescence staining, cell line co-culture, and flow cytometry analysis were used to test specific subtypes of HPV+ tumor cells and their communications with T cells.

RESULTS

Through a comprehensive single-cell transcriptome analysis, we uncover the distinct transcriptional signatures between HPV+ and HPV‒ OPSCC. Specifically, HPV+ OPSCC tumor cells manifest an enhanced interferon response and elevated expression of the major histocompatibility complex II (MHC-II), potentially bolstering tumor recognition and immune response. Furthermore, we identify a CXCL13+CD4+ T cell subset that exhibits dual features of both follicular and pro-inflammatory helper T cells. Noteworthily, HPV+ OPSCC tumor cells embrace extensive intercellular communications with CXCL13+CD4+ T cells. Interaction with HPV+ OPSCC tumor cells amplifies CXCL13 and IFNγ release in CD4+T cells, fostering a pro-inflammatory TME. Additionally, HPV+ tumor cells expressing high MHC-II and CXCL13+CD4+ T cell prevalence are indicative of favorable overall survival rates in OPSCC patients.

CONCLUSIONS

Together, our study underscores a synergistic inflammatory immune response orchestrated by highly immunogenic tumor cells and CXCL13+CD4+ T cells in HPV+ OPSCC, offering useful insights into strategy development for patient stratification and effective immunotherapy in OPSCC.

Advancing precision medicine in gliomas through single-cell sequencing: unveiling the complex tumor microenvironment

Glioblastoma (GBM) displays an infiltrative growth characteristic that recruits neighboring normal cells to facilitate tumor growth, maintenance, and invasion into the brain. While the blood-brain barrier serves as a critical natural defense mechanism for the central nervous system, GBM disrupts this barrier, resulting in the infiltration of macrophages from the peripheral bone marrow and the activation of resident microglia. Recent advancements in single-cell transcriptomics and spatial transcriptomics have refined the categorization of cells within the tumor microenvironment for precise identification. The intricate interactions and influences on cell growth within the tumor microenvironment under multi-omics conditions are succinctly outlined. The factors and mechanisms involving microglia, macrophages, endothelial cells, and T cells that impact the growth of GBM are individually examined. The collaborative mechanisms of tumor cell-immune cell interactions within the tumor microenvironment synergistically promote the growth, infiltration, and metastasis of gliomas, while also influencing the immune status and therapeutic response of the tumor microenvironment. As immunotherapy continues to progress, targeting the cells within the inter-tumor microenvironment emerges as a promising novel therapeutic approach for GBM. By comprehensively understanding and intervening in the intricate cellular interactions within the tumor microenvironment, novel therapeutic modalities may be developed to enhance treatment outcomes for patients with GBM.

Single-cell tumor heterogeneity landscape of hepatocellular carcinoma: unraveling the pro-metastatic subtype and its interaction loop with fibroblasts

BACKGROUND

Tumor heterogeneity presents a formidable challenge in understanding the mechanisms driving tumor progression and metastasis. The heterogeneity of hepatocellular carcinoma (HCC) in cellular level is not clear.

METHODS

Integration analysis of single-cell RNA sequencing data and spatial transcriptomics data was performed. Multiple methods were applied to investigate the subtype of HCC tumor cells. The functional characteristics, translation factors, clinical implications and microenvironment associations of different subtypes of tumor cells were analyzed. The interaction of subtype and fibroblasts were analyzed.

RESULTS

We established a heterogeneity landscape of HCC malignant cells by integrated 52 single-cell RNA sequencing data and 5 spatial transcriptomics data. We identified three subtypes in tumor cells, including ARG1+ metabolism subtype (Metab-subtype), TOP2A+ proliferation phenotype (Prol-phenotype), and S100A6+ pro-metastatic subtype (EMT-subtype). Enrichment analysis found that the three subtypes harbored different features, that is metabolism, proliferating, and epithelial-mesenchymal transition. Trajectory analysis revealed that both Metab-subtype and EMT-subtype originated from the Prol-phenotype. Translation factor analysis found that EMT-subtype showed exclusive activation of SMAD3 and TGF-β signaling pathway. HCC dominated by EMT-subtype cells harbored an unfavorable prognosis and a deserted microenvironment. We uncovered a positive loop between tumor cells and fibroblasts mediated by SPP1-CD44 and CCN2/TGF-β-TGFBR1 interaction pairs. Inhibiting CCN2 disrupted the loop, mitigated the transformation to EMT-subtype, and suppressed metastasis.

CONCLUSION

By establishing a heterogeneity landscape of malignant cells, we identified a three-subtype classification in HCC. Among them, S100A6+ tumor cells play a crucial role in metastasis. Targeting the feedback loop between tumor cells and fibroblasts is a promising anti-metastatic strategy.

Neoantigen-specific cytotoxic Tr1 CD4 T cells suppress cancer immunotherapy

CD4+ T cells can either enhance or inhibit tumour immunity. Although regulatory T cells have long been known to impede antitumour responses1-5, other CD4+ T cells have recently been implicated in inhibiting this response6,7. Yet, the nature and function of the latter remain unclear. Here, using vaccines containing MHC class I (MHC-I) neoantigens (neoAgs) and different doses of tumour-derived MHC-II neoAgs, we discovered that whereas the inclusion of vaccines with low doses of MHC-II-restricted peptides (LDVax) promoted tumour rejection, vaccines containing high doses of the same MHC-II neoAgs (HDVax) inhibited rejection. Characterization of the inhibitory cells induced by HDVax identified them as type 1 regulatory T (Tr1) cells expressing IL-10, granzyme B, perforin, CCL5 and LILRB4. Tumour-specific Tr1 cells suppressed tumour rejection induced by anti-PD1, LDVax or adoptively transferred tumour-specific effector T cells. Mechanistically, HDVax-induced Tr1 cells selectively killed MHC-II tumour antigen-presenting type 1 conventional dendritic cells (cDC1s), leading to low numbers of cDC1s in tumours. We then documented modalities to overcome this inhibition, specifically via anti-LILRB4 blockade, using a CD8-directed IL-2 mutein, or targeted loss of cDC2/monocytes. Collectively, these data show that cytotoxic Tr1 cells, which maintain peripheral tolerance, also inhibit antitumour responses and thereby function to impede immune control of cancer.

Tumour vasculature at single-cell resolution

Tumours can obtain nutrients and oxygen required to progress and metastasize through the blood supply1. Inducing angiogenesis involves the sprouting of established vessel beds and their maturation into an organized network2,3. Here we generate a comprehensive atlas of tumour vasculature at single-cell resolution, encompassing approximately 200,000 cells from 372 donors representing 31 cancer types. Trajectory inference suggested that tumour angiogenesis was initiated from venous endothelial cells and extended towards arterial endothelial cells. As neovascularization elongates (through angiogenic stages SI, SII and SIII), APLN+ tip cells at the SI stage (APLN+ TipSI) advanced to TipSIII cells with increased Notch signalling. Meanwhile, stalk cells, following tip cells, transitioned from high chemokine expression to elevated TEK (also known as Tie2) expression. Moreover, APLN+ TipSI cells not only were associated with disease progression and poor prognosis but also hold promise for predicting response to anti-VEGF therapy. Lymphatic endothelial cells demonstrated two distinct differentiation lineages: one responsible for lymphangiogenesis and the other involved in antigen presentation. In pericytes, endoplasmic reticulum stress was associated with the proangiogenic BASP1+ matrix-producing pericytes. Furthermore, intercellular communication analysis showed that neovascular endothelial cells could shape an immunosuppressive microenvironment conducive to angiogenesis. This study depicts the complexity of tumour vasculature and has potential clinical significance for anti-angiogenic therapy.

Cranioencephalic functional lymphoid units in glioblastoma

The ecosystem of brain tumors is considered immunosuppressed, but our current knowledge may be incomplete. Here we analyzed clinical cell and tissue specimens derived from patients presenting with glioblastoma or nonmalignant intracranial disease to report that the cranial bone (CB) marrow, in juxtaposition to treatment-naive glioblastoma tumors, harbors active lymphoid populations at the time of initial diagnosis. Clinical and anatomical imaging, single-cell molecular and immune cell profiling and quantification of tumor reactivity identified CD8+ T cell clonotypes in the CB that were also found in the tumor. These were characterized by acute and durable antitumor response rooted in the entire T cell developmental spectrum. In contrast to distal bone marrow, the CB niche proximal to the tumor showed increased frequencies of tumor-reactive CD8+ effector types expressing the lymphoid egress marker S1PR1. In line with this, cranial enhancement of CXCR4 radiolabel may serve as a surrogate marker indicating focal association with improved progression-free survival. The data of this study advocate preservation and further exploitation of these cranioencephalic units for the clinical care of glioblastoma.

Integrative single-cell analysis of longitudinal t(8;21) AML reveals heterogeneous immune cell infiltration and prognostic signatures

Introduction

Immunotherapies targeting T cells in solid cancers are revolutionizing clinical treatment. Novel immunotherapies have had extremely limited benefit for acute myeloid leukemia (AML). Here, we characterized the immune microenvironment of t(8;21) AML patients to determine how immune cell infiltration status influenced prognosis.

Methods

Through multi-omics studies of primary and longitudinal t(8;21) AML samples, we characterized the heterogeneous immune cell infiltration in the tumor microenvironment and their immune checkpoint gene expression. Further external cohorts were also included in this research.

Results

CD8+ T cells were enriched and HAVCR2 and TIGIT were upregulated in the CD34+CD117dim%-High group; these features are known to be associated with immune exhaustion. Data integration analysis of single-cell dynamics revealed that a subset of T cells (cluster_2) (highly expressing GZMB, NKG7, PRF1 and GNLY) evolved and expanded markedly in the drug-resistant stage after relapse. External cohort analysis confirmed that the cluster_2 T-cell signature could be utilized to stratify patients by overall survival outcome.

Discussion

In conclusion, we discovered a distinct T-cell signature by scRNA-seq that was correlated with disease progression and drug resistance. Our research provides a novel system for classifying patients based on their immune microenvironment.

Pan-cancer mapping of single CD8+ T cell profiles reveals a TCF1:CXCR6 axis regulating CD28 co-stimulation and anti-tumor immunity

CD8+ T cells must persist and function in diverse tumor microenvironments to exert their effects. Thus, understanding common underlying expression programs could better inform the next generation of immunotherapies. We apply a generalizable matrix factorization algorithm that recovers both shared and context-specific expression programs from diverse datasets to a single-cell RNA sequencing (scRNA-seq) compendium of 33,161 CD8+ T cells from 132 patients with seven human cancers. Our meta-single-cell analyses uncover a pan-cancer T cell dysfunction program that predicts clinical non-response to checkpoint blockade in melanoma and highlights CXCR6 as a pan-cancer marker of chronically activated T cells. Cxcr6 is trans-activated by AP-1 and repressed by TCF1. Using mouse models, we show that Cxcr6 deletion in CD8+ T cells increases apoptosis of PD1+TIM3+ cells, dampens CD28 signaling, and compromises tumor growth control. Our study uncovers a TCF1:CXCR6 axis that counterbalances PD1-mediated suppression of CD8+ cell responses and is essential for effective anti-tumor immunity.

Neoadjuvant sintilimab plus chemotherapy in EGFR-mutant NSCLC: Phase 2 trial interim results (NEOTIDE/CTONG2104)

The clinical efficacy of neoadjuvant immunotherapy plus chemotherapy remains elusive in localized epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancer (NSCLC). Here, we report interim results of a Simon's two-stage design, phase 2 trial using neoadjuvant sintilimab with carboplatin and nab-paclitaxel in resectable EGFR-mutant NSCLC. All 18 patients undergo radical surgery, with one patient experiencing surgery delay. Fourteen patients exhibit confirmed radiological response, with 44% achieving major pathological response (MPR) and no pathological complete response (pCR). Similar genomic alterations are observed before and after treatment without influencing the efficacy of subsequent EGFR-tyrosine kinase inhibitors (TKIs) in vitro. Infiltration and T cell receptor (TCR) clonal expansion of CCR8+ regulatory T (Treg)hi/CXCL13+ exhausted T (Tex)lo cells define a subtype of EGFR-mutant NSCLC highly resistant to immunotherapy, with the phenotype potentially serving as a promising signature to predict immunotherapy efficacy. Informed circulating tumor DNA (ctDNA) detection in EGFR-mutant NSCLC could help identify patients nonresponsive to neoadjuvant immunochemotherapy. These findings provide supportive data for the utilization of neoadjuvant immunochemotherapy and insight into immune resistance in EGFR-mutant NSCLC.

Directly selecting cell-type marker genes for single-cell clustering analyses

In single-cell RNA sequencing (scRNA-seq) studies, cell types and their marker genes are often identified by clustering and differentially expressed gene (DEG) analysis. A common practice is to select genes using surrogate criteria such as variance and deviance, then cluster them using selected genes and detect markers by DEG analysis assuming known cell types. The surrogate criteria can miss important genes or select unimportant genes, while DEG analysis has the selection-bias problem. We present Festem, a statistical method for the direct selection of cell-type markers for downstream clustering. Festem distinguishes marker genes with heterogeneous distribution across cells that are cluster informative. Simulation and scRNA-seq applications demonstrate that Festem can sensitively select markers with high precision and enables the identification of cell types often missed by other methods. In a large intrahepatic cholangiocarcinoma dataset, we identify diverse CD8+ T cell types and potential prognostic marker genes.

A single-cell atlas deconstructs heterogeneity across multiple models in murine traumatic brain injury and identifies novel cell-specific targets

Traumatic brain injury (TBI) heterogeneity remains a critical barrier to translating therapies. Identifying final common pathways/molecular signatures that integrate this heterogeneity informs biomarker and therapeutic-target development. We present the first large-scale murine single-cell atlas of the transcriptomic response to TBI (334,376 cells) across clinically relevant models, sex, brain region, and time as a foundational step in molecularly deconstructing TBI heterogeneity. Results were unique to cell populations, injury models, sex, brain regions, and time, highlighting the importance of cell-level resolution. We identify cell-specific targets and previously unrecognized roles for microglial and ependymal subtypes. Ependymal-4 was a hub of neuroinflammatory signaling. A distinct microglial lineage shared features with disease-associated microglia at 24 h, with persistent gene-expression changes in microglia-4 even 6 months after contusional TBI, contrasting all other cell types that mostly returned to naive levels. Regional and sexual dimorphism were noted. CEREBRI, our searchable atlas (https://shiny.crc.pitt.edu/cerebri/), identifies previously unrecognized cell subtypes/molecular targets and is a leverageable platform for future efforts in TBI and other diseases with overlapping pathophysiology.

Single-Cell Analysis Identifies Distinct Populations of Cytotoxic CD4+ T Cells Linked to the Therapeutic Efficacy of Immune Checkpoint Inhibitors in Metastatic Renal Cell Carcinoma

Background

The involvement of cytotoxic CD4+ T cells (CD4+ CTLs) and their potential role in dictating the response to immune checkpoint inhibitors (ICIs) in patients with metastatic renal cell carcinoma (mRCC) remains an unexplored area of research.

Methods

Utilizing single-cell RNA sequencing, we analyzed the immunophenotype and expression patterns of CD4+ T lymphocyte subtypes in mRCC patients, followed by preliminary validation via multi-immunofluorescent staining. In addition, we obtained a comprehensive immunotherapy dataset encompassing single-cell RNA sequencing datasets and bulk RNA-seq cohorts from the European Genome-Phenome Archive and ArrayExpress database. Utilizing the CIBERSORTx deconvolution algorithms, we derived a signature score for CD4+ CTLs from the bulk-RNA-seq datasets of the CheckMate 009/025 clinical trials.

Results

Single-cell analysis of CD4+ T lymphocytes in mRCC reveals several cancer-specific states, including diverse phenotypes of regulatory T cells. Remarkably, we observe that CD4+ CTLs cells constitute a substantial proportion of all CD4+ T lymphocyte sub-clusters in mRCC patients, highlighting their potential significance in the disease. Furthermore, within mRCC patients, we identify two distinct cytotoxic states of CD4+ T cells: CD4+GZMK+ T cells, which exhibit a weaker cytotoxic potential, and CD4+GZMB+ T cells, which demonstrate robust cytotoxic activity. Both regulatory T cells and CD4+ CTLs originate from proliferating CD4+ T cells within mRCC tissues. Intriguingly, our trajectory analysis indicates that the weakly cytotoxic CD4+GZMK+ T cells differentiate from their more cytotoxic CD4+GZMB+ counterparts. In comparing patients with lower CD4+ CTLs levels to those with higher CD4+ CTLs abundance in the CheckMate 009 and 25 immunotherapy cohorts, the latter group exhibited significantly improved OS and PFS probability.

Conclusion

Our study underscores the pivotal role that intratumoral CD4+ CTLs may play in bolstering anti-tumor immunity, suggesting their potential as a promising biomarker for predicting response to ICIs in patients with mRCC.

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.

ATP6V0A1-dependent cholesterol absorption in colorectal cancer cells triggers immunosuppressive signaling to inactivate memory CD8+ T cells

Obesity shapes anti-tumor immunity through lipid metabolism; however, the mechanisms underlying how colorectal cancer (CRC) cells utilize lipids to suppress anti-tumor immunity remain unclear. Here, we show that tumor cell-intrinsic ATP6V0A1 drives exogenous cholesterol-induced immunosuppression in CRC. ATP6V0A1 facilitates cholesterol absorption in CRC cells through RAB guanine nucleotide exchange factor 1 (RABGEF1)-dependent endosome maturation, leading to cholesterol accumulation within the endoplasmic reticulum and elevated production of 24-hydroxycholesterol (24-OHC). ATP6V0A1-induced 24-OHC upregulates TGF-β1 by activating the liver X receptor (LXR) signaling. Subsequently, the release of TGF-β1 into the tumor microenvironment by CRC cells activates the SMAD3 pathway in memory CD8+ T cells, ultimately suppressing their anti-tumor activities. Moreover, we identify daclatasvir, a clinically used anti-hepatitis C virus (HCV) drug, as an ATP6V0A1 inhibitor that can effectively enhance the memory CD8+ T cell activity and suppress tumor growth in CRC. These findings shed light on the potential for ATP6V0A1-targeted immunotherapy in CRC.

Neoadjuvant PARPi or chemotherapy in ovarian cancer informs targeting effector Treg cells for homologous-recombination-deficient tumors

Homologous recombination deficiency (HRD) is prevalent in cancer, sensitizing tumor cells to poly (ADP-ribose) polymerase (PARP) inhibition. However, the impact of HRD and related therapies on the tumor microenvironment (TME) remains elusive. Our study generates single-cell gene expression and T cell receptor profiles, along with validatory multimodal datasets from >100 high-grade serous ovarian cancer (HGSOC) samples, primarily from a phase II clinical trial (NCT04507841). Neoadjuvant monotherapy with the PARP inhibitor (PARPi) niraparib achieves impressive 62.5% and 73.6% response rates per RECIST v.1.1 and GCIG CA125, respectively. We identify effector regulatory T cells (eTregs) as key responders to HRD and neoadjuvant therapies, co-occurring with other tumor-reactive T cells, particularly terminally exhausted CD8+ T cells (Tex). TME-wide interferon signaling correlates with cancer cells upregulating MHC class II and co-inhibitory ligands, potentially driving Treg and Tex fates. Depleting eTregs in HRD mouse models, with or without PARP inhibition, significantly suppresses tumor growth without observable toxicities, underscoring the potential of eTreg-focused therapeutics for HGSOC and other HRD-related tumors.

An atlas of transcribed enhancers across helper T cell diversity for decoding human diseases

Transcribed enhancer maps can reveal nuclear interactions underpinning each cell type and connect specific cell types to diseases. Using a 5' single-cell RNA sequencing approach, we defined transcription start sites of enhancer RNAs and other classes of coding and noncoding RNAs in human CD4+ T cells, revealing cellular heterogeneity and differentiation trajectories. Integration of these datasets with single-cell chromatin profiles showed that active enhancers with bidirectional RNA transcription are highly cell type-specific and that disease heritability is strongly enriched in these enhancers. The resulting cell type-resolved multimodal atlas of bidirectionally transcribed enhancers, which we linked with promoters using fine-scale chromatin contact maps, enabled us to systematically interpret genetic variants associated with a range of immune-mediated diseases.

Identification of potential immune-related mechanisms related to the development of multiple myeloma

BACKGROUND

Although significant advances have been made in the treatment of multiple myeloma (MM), leading to unprecedented response and survival rates among patients, the majority eventually relapse, and a cure remains elusive. This situation is closely related to an incomplete understanding of the immune microenvironment, especially monocytes/macrophages in patients with treatment-naïve MM. The aim of this study was to provide insight into the immune microenvironment, especially monocytes/macrophages, in patients with treatment-naïve MM.

METHODS

This study used the single-cell RNA sequencing (scRNA-seq) data of both patients with MM and heathy donors to identify immune cells, including natural killer (NK) cells, T cells, dendritic cells (DCs), and monocytes/macrophages. Transcriptomic data and flow cytometry analysis of monocytes/macrophages were used to further examine the effect of monocytes/macrophages in treatment-naïve MM patients.

RESULTS

A significant difference was observed between the bone marrow (BM) immune cells of the healthy controls and treatment-naïve MM patients through scRNA-seq. It is noteworthy that, through an scRNA-seq data analysis, this study found that interferon (IFN)-induced NK/T cells, terminally differentiated effector memory (TEMRA) cells, T-helper cells characterized by expression of IFN-stimulated genes (ISG + Th cells), IFN-responding exhausted T cells, mannose receptor C-type 1 (MRC1) + DCs, IFN-responding DCs, MHCII + DCs, and immunosuppressive monocytes/macrophages were enriched in patients with treatment-naïve MM. Significantly, transcriptomic data of monocytes/macrophages demonstrated that "don't eat me"-related genes and IFN-induced genes increase in treatment-naïve MM patients. Furthermore, scRNA-seq, transcriptomic data, and flow cytometry also showed an increased proportion of CD16 + monocytes/macrophages and expression level of CD16. Cell-cell communication analysis indicated that monocytes/macrophages, whose related important signaling pathways include migration inhibitory factor (MIF) and interleukin 16 (IL-16) signaling pathway, are key players in treatment-naïve MM patients.

CONCLUSIONS

Our findings provide a comprehensive and in-depth molecular characterization of BM immune cell census in MM patients, especially for monocytes/macrophages. Targeting macrophages may be a novel treatment strategy for patients with MM.

Integrating single-nucleus RNA sequencing and spatial transcriptomics to elucidate a specialized subpopulation of astrocytes, microglia and vascular cells in brains of mouse model of lipopolysaccharide-induced sepsis-associated encephalopathy

BACKGROUND

Understanding the mechanism behind sepsis-associated encephalopathy (SAE) remains a formidable task. This study endeavors to shed light on the complex cellular and molecular alterations that occur in the brains of a mouse model with SAE, ultimately unraveling the underlying mechanisms of this condition.

METHODS

We established a murine model using intraperitoneal injection of lipopolysaccharide (LPS) in wild type and Anxa1-/- mice and collected brain tissues for analysis at 0-hour, 12-hour, 24-hour, and 72-hour post-injection. Utilizing advanced techniques such as single-nucleus RNA sequencing (snRNA-seq) and Stereo-seq, we conducted a comprehensive characterization of the cellular responses and molecular patterns within the brain.

RESULTS

Our study uncovered notable temporal differences in the response to LPS challenge between Anxa1-/- (annexin A1 knockout) and wild type mice, specifically at the 12-hour and 24-hour time points following injection. We observed a significant increase in the proportion of Astro-2 and Micro-2 cells in these mice. These cells exhibited a colocalization pattern with the vascular subtype Vas-1, forming a distinct region known as V1A2M2, where Astro-2 and Micro-2 cells surrounded Vas-1. Moreover, through further analysis, we discovered significant upregulation of ligands and receptors such as Timp1-Cd63, Timp1-Itgb1, Timp1-Lrp1, as well as Ccl2-Ackr1 and Cxcl2-Ackr1 within this region. In addition, we observed a notable increase in the expression of Cd14-Itgb1, Cd14-Tlr2, and Cd14-C3ar1 in regions enriched with Micro-2 cells. Additionally, Cxcl10-Sdc4 showed broad upregulation in brain regions containing both Micro-2 and Astro-2 cells. Notably, upon LPS challenge, there was an observed increase in Anxa1 expression in the mouse brain. Furthermore, our study revealed a noteworthy increase in mortality rates following Anxa1 knockdown. However, we did not observe substantial differences in the types, numbers, or distribution of other brain cells between Anxa1-/- and wildtype mice over time. Nevertheless, when comparing the 24-hour post LPS injection time point, we observed a significant decrease in the proportion and distribution of Micro-2 and Astro-2 cells in the vicinity of blood vessels in Anxa1-/- mice. Additionally, we noted reduced expression levels of several ligand-receptor pairs including Cd14-Tlr2, Cd14-C3ar1, Cd14-Itgb1, Cxcl10-Sdc4, Ccl2-Ackr1, and Cxcl2-Ackr1.

CONCLUSIONS

By combining snRNA-seq and Stereo-seq techniques, our study successfully identified a distinctive cellular colocalization, referred to as a special pathological niche, comprising Astro-2, Micro-2, and Vas-1 cells. Furthermore, we observed an upregulation of ligand-receptor pairs within this niche. These findings suggest a potential association between this cellular arrangement and the underlying mechanisms contributing to SAE or the increased mortality observed in Anxa1 knockdown mice.

Preclinical study and phase II trial of adapting low-dose radiotherapy to immunotherapy in small cell lung cancer

BACKGROUND

Immune checkpoint inhibitors (ICIs) provide modest but unsatisfactory benefits for extensive-stage small cell lung cancer (ES-SCLC). Developing strategies for treating ES-SCLC is critical.

METHODS

We preliminarily explored the outcomes of salvage low-dose radiotherapy (LDRT) plus ICI on refractory SCLC patients. Next, we evaluated the combinational efficacy in murine SCLC. The tumor immune microenvironment (TIME) was analyzed for mechanistic study. Subsequently, we conducted a multicenter, prospective phase II trial that administered concurrent thoracic LDRT plus chemoimmunotherapy to treatment-naive ES-SCLC patients (MATCH trial, NCT04622228). The primary endpoint was confirmed objective response rate (ORR), and the key secondary endpoints included progression-free survival (PFS) and safety.

FINDINGS

Fifteen refractory SCLC patients treated with LDRT plus ICI were retrospectively reviewed. The ORR was 73.3% (95% confidence interval [CI], 44.9-92.2). We identified a specific dose of LDRT (15 Gy/5 fractions) that exhibited growth retardation and improved survival in murine SCLC when combined with ICIs. This combination recruited a special T cell population, TCF1+ PD-1+ CD8+ stem-like T cells, from tumor-draining lymph nodes into the TIME. The MATCH trial showed a confirmed ORR of 87.5% (95% CI, 75.9-94.8). The median PFS was 6.9 months (95% CI, 5.4-9.3).

CONCLUSIONS

These findings verified that LDRT plus chemoimmunotherapy was safe, feasible, and effective for ES-SCLC, warranting further investigation.

FUNDING

This research was funded by West China Hospital (no. ZYJC21003), the National Natural Science Foundation of China (no. 82073336), and the MATCH trial was fully funded by Roche (China) Holding Ltd. (RCHL) and Shanghai Roche Pharmaceuticals Ltd. (SRPL).

High-dimensional mapping of human CEACAM1 expression on immune cells and association with melanoma drug resistance

BACKGROUND

Human carcinoembryonic antigen cell adhesion molecule 1 (CEACAM1) is an inhibitory cell surface protein that functions through homophilic and heterophilic ligand binding. Its expression on immune cells in human tumors is poorly understood.

METHODS

An antibody that distinguishes human CEACAM1 from other highly related CEACAM family members was labeled with 159Tb and inserted into a panel of antibodies that included specificity for programmed cell death protein 1 (PD1) and PD-L1, which are targets of immunotherapy, to gain a data-driven immune cell atlas using cytometry by time-of-flight (CyTOF). A detailed inventory of CEACAM1, PD1, and PD-L1 expression on immune cells in metastatic lesions to lymph node or soft tissues and peripheral blood samples from patients with treatment-naive and -resistant melanoma as well as peripheral blood samples from healthy controls was performed.

RESULTS

CEACAM1 is absent or at low levels on healthy circulating immune cells but is increased on immune cells in peripheral blood and tumors of melanoma patients. The majority of circulating PD1-positive NK cells, innate T cells, B cells, monocytic cells, dendritic cells, and CD4+ T cells in the peripheral circulation of treatment-resistant disease co-express CEACAM1 and are demonstrable as discrete populations. CEACAM1 is present on distinct types of cells that are unique to the tumor microenvironment and exhibit expression levels that are highest in treatment resistance; this includes tumor-infiltrating CD8+ T cells.

CONCLUSIONS

To the best of our knowledge, this work represents the first comprehensive atlas of CEACAM1 expression on immune cells in a human tumor and reveals an important correlation with treatment-resistant disease. These studies suggest that agents targeting CEACAM1 may represent appropriate partners for PD1-related pathway therapies.

Advances and challenges of exosome-derived noncoding RNAs for hepatocellular carcinoma diagnosis and treatment

Exosomes, also termed extracellular vesicles (EVs), are an important component of the tumor microenvironment (TME) and exert versatile effects on the molecular communications in the TME of hepatocellular carcinoma (HCC). Exosome-mediated intercellular communication is closely associated with the tumorigenesis and development of HCC. Exosomes can be extracted through ultracentrifugation and size exclusion, followed by molecular analysis through sequencing. Increasing studies have confirmed the important roles of exosome-derived ncRNAs in HCC, including tumorigenesis, progression, immune escape, and treatment resistance. Due to the protective membrane structure of exosomes, the ncRNAs carried by exosomes can evade degradation by enzymes in body fluids and maintain good expression stability. Thus, exosome-derived ncRNAs are highly suitable as biomarkers for the diagnosis and prognostic prediction of HCC, such as exosomal miR-21-5p, miR-221-3p and lncRNA-ATB. In addition, substantial studies revealed that the up-or down-regulation of exosome-derived ncRNAs had an important impact on HCC progression and response to treatment. Exosomal biomarkers, such as miR-23a, lncRNA DLX6-AS1, miR-21-5p, lncRNA TUC339, lncRNA HMMR-AS1 and hsa_circ_0004658, can reshape immune microenvironment by regulating M2-type macrophage polarization and then promote HCC development. Therefore, by controlling exosome biogenesis and modulating exosomal ncRNA levels, HCC may be inhibited or eliminated. In this current review, we summarized the recent findings on the role of exosomes in HCC progression and analyzed the relationship between exosome-derived ncRNAs and HCC diagnosis and treatment.

Exploring the role of CD8+ T cells in clear renal cell carcinoma metastasis

Clear cell renal cell carcinoma (ccRCC) accounts for approximately 75-80% of all patients with renal cell carcinoma. Despite its prevalence, little is known regarding the key components involved in ccRCC metastasis. In this study, scRNA-seq analysis was employed to classify CD8+ T cells into four sub-clusters based on their genetic profiles and immunofluorescence experiments were used to validate two key clusters. Through gene set enrichment analysis, these newly identified sub-clusters were found to exhibit distinct biological characteristics. Notably, TYMP, TOP2A, CHI3L2, CDKN3, CENPM, and RZH2 were highly expressed in these sub-clusters, indicating a correlation with poor prognosis. Among these sub-clusters, CD8+ T cells (MT-ND4) were identified as potentially playing a critical role in mediating ccRCC metastasis. These results contribute to our understanding of CD8+ T cell heterogeneity in ccRCC and shed light on the mechanisms underlying the loss of immune response against cancer.

Exploiting temporal aspects of cancer immunotherapy

Many mechanisms underlying an effective immunotherapy-induced antitumour response are transient and critically time dependent. This is equally true for several immunological events in the tumour microenvironment induced by other cancer treatments. Immune checkpoint therapy (ICT) has proven to be very effective in the treatment of some cancers, but unfortunately, with many cancer types, most patients do not experience a benefit. To improve outcomes, a multitude of clinical trials are testing combinations of ICT with various other treatment modalities. Ideally, those combination treatments should take time-dependent immunological events into account. Recent studies have started to map the dynamic cellular and molecular changes that occur during treatment with ICT, in the tumour and systemically. Here, we overlay the dynamic ICT response with the therapeutic response following surgery, radiotherapy, chemotherapy and targeted therapies. We propose that by combining treatments in a time-conscious manner, we may optimally exploit the interactions between the individual therapies.

Comprehensive investigation of malignant epithelial cell-related genes in clear cell renal cell carcinoma: development of a prognostic signature and exploration of tumor microenvironment interactions

Clear cell renal cell carcinoma (ccRCC) is a prevalent malignancy with complex heterogeneity within epithelial cells, which plays a crucial role in tumor progression and immune regulation. Yet, the clinical importance of the malignant epithelial cell-related genes (MECRGs) in ccRCC remains insufficiently understood. This research aims to undertake a comprehensive investigation into the functions and clinical relevance of malignant epithelial cell-related genes in ccRCC, providing valuable understanding of the molecular mechanisms and offering potential targets for treatment strategies. Using data from single-cell sequencing, we successfully identified 219 MECRGs and established a prognostic model MECRGS (MECRGs' signature) by synergistically analyzing 101 machine-learning models using 10 different algorithms. Remarkably, the MECRGS demonstrated superior predictive performance compared to traditional clinical features and 92 previously published signatures across six cohorts, showcasing its independence and accuracy. Upon stratifying patients into high- and low-MECRGS subgroups using the specified cut-off threshold, we noted that patients with elevated MECRGS scores displayed characteristics of an immune suppressive tumor microenvironment (TME) and showed worse outcomes after immunotherapy. Additionally, we discovered a distinct ccRCC tumor cell subtype characterized by the high expressions of PLOD2 (procollagen-lysine,2-oxoglutarate 5-dioxygenase 2) and SAA1 (Serum Amyloid A1), which we further validated in the Renji tissue microarray (TMA) cohort. Lastly, 'Cellchat' revealed potential crosstalk patterns between these cells and other cell types, indicating their potential role in recruiting CD163 + macrophages and regulatory T cells (Tregs), thereby establishing an immunosuppressive TME. PLOD2 + SAA1 + cancer cells with intricate crosstalk patterns indeed show promise for potential therapeutic interventions.

Building and analyzing metacells in single-cell genomics data

The advent of high-throughput single-cell genomics technologies has fundamentally transformed biological sciences. Currently, millions of cells from complex biological tissues can be phenotypically profiled across multiple modalities. The scaling of computational methods to analyze and visualize such data is a constant challenge, and tools need to be regularly updated, if not redesigned, to cope with ever-growing numbers of cells. Over the last few years, metacells have been introduced to reduce the size and complexity of single-cell genomics data while preserving biologically relevant information and improving interpretability. Here, we review recent studies that capitalize on the concept of metacells-and the many variants in nomenclature that have been used. We further outline how and when metacells should (or should not) be used to analyze single-cell genomics data and what should be considered when analyzing such data at the metacell level. To facilitate the exploration of metacells, we provide a comprehensive tutorial on the construction and analysis of metacells from single-cell RNA-seq data ( https://github.com/GfellerLab/MetacellAnalysisTutorial ) as well as a fully integrated pipeline to rapidly build, visualize and evaluate metacells with different methods ( https://github.com/GfellerLab/MetacellAnalysisToolkit ).

Machine learning for the identification of neoantigen-reactive CD8 + T cells in gastrointestinal cancer using single-cell sequencing

BACKGROUND

It appears that tumour-infiltrating neoantigen-reactive CD8 + T (Neo T) cells are the primary driver of immune responses to gastrointestinal cancer in patients. However, the conventional method is very time-consuming and complex for identifying Neo T cells and their corresponding T cell receptors (TCRs).

METHODS

By mapping neoantigen-reactive T cells from the single-cell transcriptomes of thousands of tumour-infiltrating lymphocytes, we developed a 26-gene machine learning model for the identification of neoantigen-reactive T cells.

RESULTS

In both training and validation sets, the model performed admirably. We discovered that the majority of Neo T cells exhibited notable differences in the biological processes of amide-related signal pathways. The analysis of potential cell-to-cell interactions, in conjunction with spatial transcriptomic and multiplex immunohistochemistry data, has revealed that Neo T cells possess potent signalling molecules, including LTA, which can potentially engage with tumour cells within the tumour microenvironment, thereby exerting anti-tumour effects. By sequencing CD8 + T cells in tumour samples of patients undergoing neoadjuvant immunotherapy, we determined that the fraction of Neo T cells was significantly and positively linked with the clinical benefit and overall survival rate of patients.

CONCLUSION

This method expedites the identification of neoantigen-reactive TCRs and the engineering of neoantigen-reactive T cells for therapy.

Summary data-based Mendelian randomization and single-cell RNA sequencing analyses identify immune associations with low-level LGALS9 in sepsis

Sepsis is one of the major challenges in intensive care units, characterized by the complexity of the host immune status. To gain a deeper understanding of the pathogenesis of sepsis, it is crucial to study the phenotypic changes in immune cells and their underlying molecular mechanisms. We conducted Summary data-based Mendelian randomization analysis by integrating genome-wide association studies data for sepsis with expression quantitative trait locus data, revealing a significant decrease in the expression levels of 17 biomarkers in sepsis patients. Furthermore, based on single-cell RNA sequencing data, we elucidated potential molecular mechanisms at single-cell resolution and identified that LGALS9 inhibition in sepsis patients leads to the activation and differentiation of monocyte and T-cell subtypes. These findings are expected to assist researchers in gaining a more in-depth understanding of the immune dysregulation in sepsis.

CD8-Targeted IL2 Unleashes Tumor-Specific Immunity in Human Cancer Tissue by Reviving the Dysfunctional T-cell Pool

Tumor-specific CD8+ T cells are key effectors of antitumor immunity but are often rendered dysfunctional in the tumor microenvironment. Immune-checkpoint blockade can restore antitumor T-cell function in some patients; however, most do not respond to this therapy, often despite T-cell infiltration in their tumors. We here explored a CD8-targeted IL2 fusion molecule (CD8-IL2) to selectively reactivate intratumoral CD8+ T cells in patient-derived tumor fragments. Treatment with CD8-IL2 broadly armed intratumoral CD8+ T cells with enhanced effector capacity, thereby specifically enabling reinvigoration of the dysfunctional T-cell pool to elicit potent immune activity. Notably, the revival of dysfunctional T cells to mediate effector activity by CD8-IL2 depended on simultaneous antigen recognition and was quantitatively and qualitatively superior to that achieved by PD-1 blockade. Finally, CD8-IL2 was able to functionally reinvigorate T cells in tumors resistant to anti-PD-1, underscoring its potential as a novel treatment strategy for patients with cancer. Significance: Reinvigorating T cells is crucial for response to checkpoint blockade therapy. However, emerging evidence suggests that the PD-1/PD-L1 axis is not the sole impediment for activating T cells within tumors. Selectively targeting cytokines toward specific T-cell subsets might overcome these barriers and stimulate T cells within resistant tumors. See related article by Moynihan et al., p. 1206 (32).

Mouse Models to Evaluate the Functional Role of the Tumor Microenvironment in Cancer Progression and Therapy Responses

The tumor microenvironment (TME) is a complex ecosystem of both cellular and noncellular components that functions to impact the evolution of cancer. Various aspects of the TME have been targeted for the control of cancer; however, TME composition is dynamic, with the overall abundance of immune cells, endothelial cells (ECs), fibroblasts, and extracellular matrix (ECM) as well as subsets of TME components changing at different stages of progression and in response to therapy. To effectively treat cancer, an understanding of the functional role of the TME is needed. Genetically engineered mouse models have enabled comprehensive insight into the complex interactions within the TME ecosystem that regulate disease progression. Here, we review recent advances in mouse models that have been employed to understand how the TME regulates cancer initiation, progression, metastasis, and response to therapy.

Interconnected lineage trajectories link conventional and natural killer (NK)-like exhausted CD8+ T cells beneficial in type 1 diabetes

Distinct Natural Killer (NK)-like CD57+ and PD-1+ CD8+ exhausted-like T cell populations (Tex) have both been linked to beneficial immunotherapy response in autoimmune type 1 diabetes (T1D) patients. The origins and relationships between these cell types are poorly understood. Here we show that while PD-1+ and CD57+ Tex populations are epigenetically similar, CD57+ Tex cells display unique increased chromatin accessibility of inhibitory Killer Cell Immunoglobulin-like Receptor (iKIR) and other NK cell genes. PD-1+ and CD57+ Tex also show reciprocal expression of Inhibitory Receptors (IRs) and iKIRs accompanied by chromatin accessibility of Tcf1 and Tbet transcription factor target sites, respectively. CD57+ Tex show unappreciated gene expression heterogeneity and share clonal relationships with PD-1+ Tex, with these cells differentiating along four interconnected lineage trajectories: Tex-PD-1+, Tex-CD57+, Tex-Branching, and Tex-Fluid. Our findings demonstrate new relationships between Tex-like populations in human autoimmune disease and suggest that modulating common precursor populations may enhance response to autoimmune disease treatment.

TimiGP-Response: the pan-cancer immune landscape associated with response to immunotherapy

Accumulating evidence suggests that the tumor immune microenvironment (TIME) significantly influences the response to immunotherapy, yet this complex relationship remains elusive. To address this issue, we developed TimiGP-Response (TIME Illustration based on Gene Pairing designed for immunotherapy Response), a computational framework leveraging single-cell and bulk transcriptomic data, along with response information, to construct cell-cell interaction networks associated with responders and estimate the role of immune cells in treatment response. This framework was showcased in triple-negative breast cancer treated with immune checkpoint inhibitors targeting the PD-1:PD-L1 interaction, and orthogonally validated with imaging mass cytometry. As a result, we identified CD8+ GZMB+ T cells associated with responders and its interaction with regulatory T cells emerged as a potential feature for selecting patients who may benefit from these therapies. Subsequently, we analyzed 3,410 patients with seven cancer types (melanoma, non-small cell lung cancer, renal cell carcinoma, metastatic urothelial carcinoma, hepatocellular carcinoma, breast cancer, and esophageal cancer) treated with various immunotherapies and combination therapies, as well as several chemo- and targeted therapies as controls. Using TimiGP-Response, we depicted the pan-cancer immune landscape associated with immunotherapy response at different resolutions. At the TIME level, CD8 T cells and CD4 memory T cells were associated with responders, while anti-inflammatory (M2) macrophages and mast cells were linked to non-responders across most cancer types and datasets. Given that T cells are the primary targets of these immunotherapies and our TIME analysis highlights their importance in response to treatment, we portrayed the pan-caner landscape on 40 T cell subtypes. Notably, CD8+ and CD4+ GZMK+ effector memory T cells emerged as crucial across all cancer types and treatments, while IL-17-producing CD8+ T cells were top candidates associated with immunotherapy non-responders. In summary, this study provides a computational method to study the association between TIME and response across the pan-cancer immune landscape, offering resources and insights into immune cell interactions and their impact on treatment efficacy.