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

PD-1- CD45RA+ effector-memory CD8 T cells and CXCL10+ macrophages are associated with response to atezolizumab plus bevacizumab in advanced hepatocellular carcinoma

The combination of atezolizumab plus bevacizumab (atezo/bev) has dramatically changed the treatment landscape of advanced HCC (aHCC), achieving durable responses in some patients. Using single-cell transcriptomics, we characterize the intra-tumoural and peripheral immune context of patients with aHCC treated with atezo/bev. Tumours from patients with durable responses are enriched for PDL1+ CXCL10+ macrophages and, based on cell-cell interaction analysis, express high levels of CXCL9/10/11 and are predicted to attract peripheral CXCR3+ CD8+ effector-memory T cells (CD8 TEM) into the tumour. Based on T cell receptor sharing and pseudotime trajectory analysis, we propose that CD8 TEM preferentially differentiate into clonally-expanded PD1- CD45RA+ effector-memory CD8+ T cells (CD8 TEMRA) with pronounced cytotoxicity. In contrast, in non-responders, CD8 TEM remain frozen in their effector-memory state. Finally, in responders, CD8 TEMRA display a high degree of T cell receptor sharing with blood, consistent with their patrolling activity. These findings may help understand the possible mechanisms underlying response to atezo/bev in aHCC.

Deciphering tumor-infiltrating dendritic cells in the single-cell era

Dendritic cells (DCs) serve as a pivotal link connecting innate and adaptive immunity by processing tumor-derived antigens and activating T cells. The advent of single-cell sequencing has revolutionized the categorization of DCs, enabling a high-resolution characterization of the previously unrecognized diversity of DC populations infiltrating the intricate tumor microenvironment (TME). The application of single-cell sequencing technologies has effectively elucidated the heterogeneity of DCs present in the tumor milieu, yielding invaluable insights into their subpopulation structures and functional diversity. This review provides a comprehensive summary of the current state of knowledge regarding DC subtypes in the TME, drawing from single-cell studies conducted across various human tumors. We focused on the categorization, functions, and interactions of distinct DC subsets, emphasizing their crucial roles in orchestrating tumor-related immune responses. Additionally, we delve into the potential implications of these findings for the identification of predictive biomarkers and therapeutic targets. Enhanced insight into the intricate interplay between DCs and the TME promises to advance our comprehension of tumor immunity and, in turn, pave the way for the development of more efficacious cancer immunotherapies.

Integrated single-cell and bulk RNA sequencing analysis identifies a neoadjuvant chemotherapy-related gene signature for predicting survival and therapy in breast cancer

Neoadjuvant chemotherapy (NAC) is a well-established treatment modality for locally advanced breast cancer (BC). However, it can also result in severe toxicities while controlling tumors. Therefore, reliable predictive biomarkers are urgently needed to objectively and accurately predict NAC response. In this study, we integrated single-cell and bulk RNA-seq data to identify nine genes associated with the prognostic response to NAC: NDRG1, CXCL14, HOXB2, NAT1, EVL, FBP1, MAGED2, AR and CIRBP. Furthermore, we constructed a prognostic risk model specifically linked to NAC. The clinical independence and generalizability of this model were effectively demonstrated. Additionally, we explore the underlying cancer hallmarks and microenvironment features of this NAC response-related risk score, and further assess the potential impact of risk score on drug response. In summary, our study constructed and validated a nine-gene signature associated with NAC prognosis, which was accomplished through the integration of single-cell and bulk RNA data. The results of our study are of crucial significance in the prediction of the efficacy of NAC in BC, and may have implications for the clinical management of this disease.

Clustering malignant cell states using universally variable genes

Single-cell RNA sequencing (scRNA-seq) has revealed important insights into the heterogeneity of malignant cells. However, sample-specific genomic alterations often confound such analysis, resulting in patient-specific clusters that are difficult to interpret. Here, we present a novel approach to address the issue. By normalizing gene expression variances to identify universally variable genes (UVGs), we were able to reduce the formation of sample-specific clusters and identify underlying molecular hallmarks in malignant cells. In contrast to highly variable genes vulnerable to a specific sample bias, UVGs led to better detection of clusters corresponding to distinct malignant cell states. Our results demonstrate the utility of this approach for analyzing scRNA-seq data and suggest avenues for further exploration of malignant cell heterogeneity.

Longitudinal multi-functional analysis identified responses of T cells, B cells, and monocytes as hallmarks of immunotherapy tolerance in patients with merkel cell carcinoma

PURPOSE

Merkel cell carcinoma (MCC) is a neuroendocrine carcinoma originating in the skin. Studies are needed to determine the mechanisms of immune escape in patients with MCC, and malignant cell conditions that promote immune evasion.

METHODS

We used Single-cell RNA sequencing (scRNA-seq) to determine cellular features associated with MCC disease trajectory. A longitudinal multi-omics study was performed using scRNA-seq data of peripheral blood harvested from four-time points. Six major cell types and fifteen cell subgroups were identified and confirmed their presence by expression of characteristic markers. The expression patterns and specific changes of different cells at different time points were investigated. Subsequently, bulk RNA data was used to validate key findings.

RESULTS

The dynamic characteristics of the cells were identified during the critical period between benign improvement and acquisition of resistance. Combined with the results of the validation cohort, the resistance program expressed in the relapse stage is mainly associated with T cell exhaustion and immune cell crosstalk disorder. Coinciding with immune escape, we also identified a decrease non-classical monocytes and an expansion of classical monocytes with features of high inflammation and immune deficiency.

CONCLUSION

Changes in cellular status, such as depletion of T cells and dysregulation of B cell proliferation and differentiation, may lead to drug resistance in MCC patients. Meanwhile, the widespread decreased antigen presentation ability and immune disorders caused by deletion of MHC class II gene expression should not be ignored.

Insights gained from single-cell analysis of chimeric antigen receptor T-cell immunotherapy in cancer

Advances in chimeric antigen receptor (CAR)-T cell therapy have significantly improved clinical outcomes of patients with relapsed or refractory hematologic malignancies. However, progress is still hindered as clinical benefit is only available for a fraction of patients. A lack of understanding of CAR-T cell behaviors in vivo at the single-cell level impedes their more extensive application in clinical practice. Mounting evidence suggests that single-cell sequencing techniques can help perfect the receptor design, guide gene-based T cell modification, and optimize the CAR-T manufacturing conditions, and all of them are essential for long-term immunosurveillance and more favorable clinical outcomes. The information generated by employing these methods also potentially informs our understanding of the numerous complex factors that dictate therapeutic efficacy and toxicities. In this review, we discuss the reasons why CAR-T immunotherapy fails in clinical practice and what this field has learned since the milestone of single-cell sequencing technologies. We further outline recent advances in the application of single-cell analyses in CAR-T immunotherapy. Specifically, we provide an overview of single-cell studies focusing on target antigens, CAR-transgene integration, and preclinical research and clinical applications, and then discuss how it will affect the future of CAR-T cell therapy.

Unraveling temporal and spatial biomarkers of epithelial-mesenchymal transition in colorectal cancer: insights into the crucial role of immunosuppressive cells

The occurrence and progression of tumors can be established through a complex interplay among tumor cells undergoing epithelial-mesenchymal transition (EMT), invasive factors and immune cells. In this study, we employed single-cell RNA sequencing (scRNA-seq) and spatially resolved transcriptomics (ST) to evaluate the pseudotime trajectory and spatial interactive relationship between EMT-invasive malignant tumors and immune cells in primary colorectal cancer (CRC) tissues at different stages (stage I/II and stage III with tumor deposit). Our research characterized the spatiotemporal relationship among different invasive tumor programs by constructing pseudotime endpoint-EMT-invasion tumor programs (EMTPs) located at the edge of ST, utilizing evolution trajectory analysis integrated with EMT-invasion genes. Strikingly, the invasive and expansive process of tumors undergoes remarkable spatial reprogramming of regulatory and immunosuppressive cells, such as myeloid-derived suppressor cells (MDSCs), tumor-associated macrophages (TAMs), regulatory T cells (Treg), and exhausted T cells (Tex). These EMTP-adjacent cell are linked to EMT-related invasion genes, especially the C-X-C motif ligand 1 (CXCL1) and CXCL8 genes that are important for CRC prognosis. Interestingly, the EMTPs in stage I mainly produce an inflammatory margin invasive niche, while the EMTPs in stage III tissues likely produce a hypoxic pre-invasive niche. Our data demonstrate the crucial role of regulatory and immunosuppressive cells in tumor formation and progression of CRC. This study provides a framework to delineate the spatiotemporal invasive niche in CRC samples.

Multi-scale characterisation of homologous recombination deficiency in breast cancer

BACKGROUND

Homologous recombination is a robust, broadly error-free mechanism of double-strand break repair, and deficiencies lead to PARP inhibitor sensitivity. Patients displaying homologous recombination deficiency can be identified using 'mutational signatures'. However, these patterns are difficult to reliably infer from exome sequencing. Additionally, as mutational signatures are a historical record of mutagenic processes, this limits their utility in describing the current status of a tumour.

METHODS

We apply two methods for characterising homologous recombination deficiency in breast cancer to explore the features and heterogeneity associated with this phenotype. We develop a likelihood-based method which leverages small insertions and deletions for high-confidence classification of homologous recombination deficiency for exome-sequenced breast cancers. We then use multinomial elastic net regression modelling to develop a transcriptional signature of heterogeneous homologous recombination deficiency. This signature is then applied to single-cell RNA-sequenced breast cancer cohorts enabling analysis of homologous recombination deficiency heterogeneity and differential patterns of tumour microenvironment interactivity.

RESULTS

We demonstrate that the inclusion of indel events, even at low levels, improves homologous recombination deficiency classification. Whilst BRCA-positive homologous recombination deficient samples display strong similarities to those harbouring BRCA1/2 defects, they appear to deviate in microenvironmental features such as hypoxic signalling. We then present a 228-gene transcriptional signature which simultaneously characterises homologous recombination deficiency and BRCA1/2-defect status, and is associated with PARP inhibitor response. Finally, we show that this signature is applicable to single-cell transcriptomics data and predict that these cells present a distinct milieu of interactions with their microenvironment compared to their homologous recombination proficient counterparts, typified by a decreased cancer cell response to TNFα signalling.

CONCLUSIONS

We apply multi-scale approaches to characterise homologous recombination deficiency in breast cancer through the development of mutational and transcriptional signatures. We demonstrate how indels can improve homologous recombination deficiency classification in exome-sequenced breast cancers. Additionally, we demonstrate the heterogeneity of homologous recombination deficiency, especially in relation to BRCA1/2-defect status, and show that indications of this feature can be captured at a single-cell level, enabling further investigations into interactions between DNA repair deficient cells and their tumour microenvironment.

Understanding cervical cancer at single-cell resolution

Cervical cancer is now the fourth most prevalent malignancy in women worldwide, representing a tremendous burden of cancer. The heterogeneity of complex tumor ecosystem impacts tumorigenesis, malignant progression, and response to treatment; thus, a thorough understanding of the tumor ecosystem is vital for enhancing the prognosis of patients with cervical cancer. The rapid development and widespread use of single-cell sequencing have generated a new paradigm of cancer research, providing a comprehensive and in-depth understanding of cancers. In this review, we give an overview of the recent advances made by leveraging single-cell sequencing studies in the dissection of cervical cancer ecosystem heterogeneity. We highlight the evolution of the cervical cancer ecosystem during tumor initiation, progression, and treatment. High-resolution dissection of cervical cancer at the single-cell level has the potential to drive the development of targeted therapies and enable the realization of personalized medicine.

Application of single-cell sequencing to the research of tumor microenvironment

Single-cell sequencing is a technique for detecting and analyzing genomes, transcriptomes, and epigenomes at the single-cell level, which can detect cellular heterogeneity lost in conventional sequencing hybrid samples, and it has revolutionized our understanding of the genetic heterogeneity and complexity of tumor progression. Moreover, the tumor microenvironment (TME) plays a crucial role in the formation, development and response to treatment of tumors. The application of single-cell sequencing has ushered in a new age for the TME analysis, revealing not only the blueprint of the pan-cancer immune microenvironment, but also the heterogeneity and differentiation routes of immune cells, as well as predicting tumor prognosis. Thus, the combination of single-cell sequencing and the TME analysis provides a unique opportunity to unravel the molecular mechanisms underlying tumor development and progression. In this review, we summarize the recent advances in single-cell sequencing and the TME analysis, highlighting their potential applications in cancer research and clinical translation.

Systematic analysis reveals a pan-cancer SNHG family signature predicting prognosis and immunotherapy response

Small nucleolar RNA host genes (SNHGs) are a special family of long non-coding RNAs (lncRNAs), which not only function in a way similar to other lncRNAs but also influence the intracellular level of small nucleolar RNAs to modulate cancers. However, the features of SNHGs and their role in the prognosis and immunotherapeutic response of human cancer have not been explored. We found that SNHGs were commonly deregulated and correlated with patient survival in various cancers. The critical role of DNA methylation and somatic alterations on deregulation was also identified. SNHG family score was significantly associated with survival, multiple tumor characteristics, and tumor microenvironment. SNHG-related risk score could serve as a prognostic and immunotherapeutic response biomarker based on multiple databases. This study emphasizes the potential of SNHGs as biomarkers for prognosis and immunotherapeutic response, enabling further research into the immune regulatory mechanism and therapeutic potentials of SNHGs in cancer.

Unveiling the Role of Tumor-Infiltrating T Cells and Immunotherapy in Hepatocellular Carcinoma: A Comprehensive Review

Hepatocellular carcinoma (HCC) is a rapidly rising global health concern, ranking as the third-leading cause of cancer-related mortality. Despite medical advancements, the five-year survival rate remains a dismal 18%, with a daunting 70% recurrence rate within a five-year period. Current systematic treatments, including first-line sorafenib, yield an overall response rate (ORR) below 10%. In contrast, immunotherapies have shown promise by improving ORR to approximately 30%. The IMbravel150 clinical trial demonstrates that combining atezolizumab and bevacizumab surpasses sorafenib in terms of median progression-free survival (PFS) and overall survival (OS). However, the therapeutic efficacy for HCC patients remains unsatisfactory, highlighting the urgent need for a comprehensive understanding of antitumor responses and immune evasion mechanisms in HCC. In this context, understanding the immune landscape of HCC is of paramount importance. Tumor-infiltrating T cells, including cytotoxic T cells, regulatory T cells, and natural killer T cells, are key components in the antitumor immune response. This review aims to shed light on their intricate interactions within the immunosuppressive tumor microenvironment and explores potential strategies for revitalizing dysfunctional T cells. Additionally, current immune checkpoint inhibitor (ICI)-based trials, ICI-based combination therapies, and CAR-T- or TCR-T-cell therapies for HCC are summarized, which might further improve OS and transform the management of HCC in the future.

Clinical significance and immune infiltration analyses of a novel coagulation-related signature in ovarian cancer

Ovarian cancer (OV) is the most lethal gynecological malignancies worldwide. The coagulation cascade could induce tumor cell infiltration and contribute to OV progression. However, coagulation-related gene (CRG) signature for OV prognosis hasn't been determined yet. In this study, we evaluated the prognostic value of coagulation scores through receiver operating characteristics (ROC) analysis and K-M curves, among OV patients at our institution. Based on the transcriptome data of TCGA-OV cohort, we stratified two coagulation-related subtypes with distinct differences in prognosis and tumor immune microenvironment (p < 0.05). Moreover, from the 6406 differentially-expressed genes (DEGs) between the GTEx (n = 180) and TCGA-OV cohorts (n = 376), we identified 138 potential CRGs. Through LASSO-Cox algorithm, we finally distinguished a 3-gene signature (SERPINA10, CD38, and ZBTB16), with promising prognostic ability in both TCGA (p < 0.001) and ICGC cohorts (p = 0.040). Stepwise, we constructed a nomogram based on the clinical features and coagulation-related signature for overall survival prediction, with the C-index of 0.6761, which was evaluated by calibration curves. Especially, based on tissue microarrays analysis, Quantitative real-time fluorescence PCR (qRT-PCR), and Western Blot, we found that aberrant upregulation of CRGs was related to poor prognosis in OV at both mRNA and protein level (p < 0.05). Collectively, the coagulation-related signature was a robust prognostic biomarker, which could provide therapeutic benefits for chemotherapy/immunotherapy and assist clinical decision in OV patients.

The Emerging Role of the Single-Cell and Spatial Tumor Microenvironment in High-Grade Serous Ovarian Cancer

The development of single-cell and spatial technologies has enabled a more detailed understanding of the tumor microenvironment and its role in therapy response and clinical outcome of high-grade serous ovarian cancer (HGSC). Interestingly, emerging evidence suggests that HGSCs with different genetic drivers harbor distinct tumor-immune microenvironments. Further, spatial cell-cell interactions have been shown to shape the CD8+ T-cell phenotypes and responses to immune checkpoint blockade therapies. The heterogeneous stroma consisting of cancer-associated fibroblast (CAF) subtypes, endothelia, and site-specific stromal types such as mesothelium modulates treatment responses via increasing stiffness and by producing ligands that promote drug resistance, angiogenesis, or immune escape. Chemotherapy itself shifts CAFs toward an inflammatory phenotype that associates with poor survival and immune-suppressive signaling. New emerging immunotherapies include combinational approaches and agents targeting, for example, the tumor-intrinsic endoplasmic reticulum pathway. A more detailed understanding of the spatial interplay of tumor, immune, and stromal cells in the tumor microenvironment is needed to develop more efficient immunotherapeutic strategies for HGSC.

Single-cell RNA sequencing analysis reveals transcriptional heterogeneity of multiple primary lung cancer

INTRODUCTION

With the advancements in early diagnosis, more and more patients with multiple primary lung cancer (MPLC) have been identified. However, the progression of MPLC involves complex changes in cell composition and metabolic function, which remains largely controversial.

OBJECTIVE

Our study aims to comprehensively reveal the cellular characteristics and inter-cellular connections of MPLC.

METHODS

We performed scRNA-seq from 23 samples of six MPLC patients, combined with bulk whole-exome sequencing. We performed trajectory analysis to investigate the transition of different cell types during the development of MPLC.

RESULTS

A total of 1 67 397 cells were sequenced derived from tumour and adjacent tissues of MPLC patients, and tumour, normal, immune and stromal cells were identified. Two states of epithelial cells were identified, which were associated with immune response and cell death, respectively. Furthermore, both CD8+ naïve and memory T cells participated in the differentiation of CD8+ T cells. The terminal states of CD8+ T cells were exhausted T cells and cytotoxic T cells, which positively regulated cell death and were implicated in the regulation of cytokine production, respectively. Two main subpopulations of B cells with distinct functions were identified, which participate in the regulation of the immune response and antigen presentation, respectively. In addition, we found a specific type of endothelial cells that were abundant in tumour samples, with an increasing trend from normal to tumour samples.

CONCLUSIONS

Our study showed the comprehensive landscape of different cells of MPLC, which might reveal the key cellular mechanisms and, therefore, may provide new insights into the early diagnosis and treatment of MPLC.

Integrated analysis of multiple methods reveals characteristics of the immune microenvironment in medulloblastoma

To explore the characteristics of the immune microenvironment (IME) of medulloblastoma (MB) by four methods: flow cytometry (FCM), immunohistochemical (IHC), bulk RNA expression and single cell RNA sequencing (scRNA-seq), we collected the intraoperative specimens of MB, ependymoma (EPN), high-grade glioma (HGG), and low-grade glioma (LGG) to make a cross-cancer comparison. The specimens were subjected to FCM and IHC respectively, and deconvolution from bulk RNA expression data and scRNA-seq analysis were performed in MB from the GEO database. FCM and IHC analysis found that the proportion of lymphocytes (LC) and T cells between MB and other brain tumors were significantly different. The deconvolution of bulk RNA expression data showed that only the proportion of cell types in MCPCOUNTER changed greatly. scRNA-seq found that the proportion of various immune cells in the IME of MB differed between different subtypes. Techniques such as FCM, IHC, bulk RNA expression, and scRNA-seq can sort out different immune cell subsets to a certain extent and quantify their proportions. The four methods have their own strengthens and limitations, but for highly heterogeneous tumor such as MB, integrated analysis of multiple methods is a better choice.

Revealing and harnessing CD39 for the treatment of colorectal cancer and liver metastases by engineered T cells

OBJECTIVE

Colorectal tumours are often densely infiltrated by immune cells that have a role in surveillance and modulation of tumour progression but are burdened by immunosuppressive signals, which might vary from primary to metastatic stages. Here, we deployed a multidimensional approach to unravel the T-cell functional landscape in primary colorectal cancers (CRC) and liver metastases, and genome editing tools to develop CRC-specific engineered T cells.

DESIGN

We paired high-dimensional flow cytometry, RNA sequencing and immunohistochemistry to describe the functional phenotype of T cells from healthy and neoplastic tissue of patients with primary and metastatic CRC and we applied lentiviral vectors (LV) and CRISPR/Cas9 genome editing technologies to develop CRC-specific cellular products.

RESULTS

We found that T cells are mainly localised at the front edge and that tumor-infiltrating T cells co-express multiple inhibitory receptors, which largely differ from primary to metastatic sites. Our data highlighted CD39 as the major driver of exhaustion in both primary and metastatic colorectal tumours. We thus simultaneously redirected T-cell specificity employing a novel T-cell receptor targeting HER-2 and disrupted the endogenous TCR genes (TCR editing (TCRED)) and the CD39 encoding gene (ENTPD1), thus generating TCREDENTPD1KOHER-2-redirected lymphocytes. We showed that the absence of CD39 confers to HER-2-specific T cells a functional advantage in eliminating HER-2+ patient-derived organoids in vitro and in vivo.

CONCLUSION

HER-2-specific CD39 disrupted engineered T cells are promising advanced medicinal products for primary and metastatic CRC.

A cancer-associated fibroblast subtypes-based signature enables the evaluation of immunotherapy response and prognosis in bladder cancer

Bladder cancer (BLCA) is one of the most prevalent and heterogeneous urinary malignant tumors. Previous researches have reported a significant association between cancer-associated fibroblasts (CAFs) and poor prognosis of tumor patients. However, uncertainty surrounds the role of CAFs in the BLCA tumor microenvironment, necessitating further investigation into the CAFs-related gene signatures in BLCA. In this study, we identified three CAF subtypes in BLCA according to single-cell RNA-seq data and constructed CAFs-related risk score (CRRS) by screening 102,714 signatures. The survival analysis, ROC curves, and nomogram suggested that CRRS was a valuable predictor in 2,042 patients from 9 available public datasets and Xiangya real-world cohort. We further revealed the significant correlation between CRRS and clinicopathological characteristics, genome alterations, and epithelial-mesenchymal transition (EMT). A high CRRS indicated a non-inflamed phenotype and a lower remission rate of immunotherapy in BLCA. In conclusion, the CRRS had the potential to predict the prognosis and immunotherapy response of BLCA patients.

Integrated BATF transcriptional network regulates suppressive intratumoral regulatory T cells

Human regulatory T cells (Tregs) are crucial regulators of tissue repair, autoimmune diseases, and cancer. However, it is challenging to inhibit the suppressive function of Tregs for cancer therapy without affecting immune homeostasis. Identifying pathways that may distinguish tumor-restricted Tregs is important, yet the transcriptional programs that control intratumoral Treg gene expression, and that are distinct from Tregs in healthy tissues, remain largely unknown. We profiled single-cell transcriptomes of CD4+ T cells in tumors and peripheral blood from patients with head and neck squamous cell carcinomas (HNSCC) and those in nontumor tonsil tissues and peripheral blood from healthy donors. We identified a subpopulation of activated Tregs expressing multiple tumor necrosis factor receptor (TNFR) genes (TNFR+ Tregs) that is highly enriched in the tumor microenvironment (TME) compared with nontumor tissue and the periphery. TNFR+ Tregs are associated with worse prognosis in HNSCC and across multiple solid tumor types. Mechanistically, the transcription factor BATF is a central component of a gene regulatory network that governs key aspects of TNFR+ Tregs. CRISPR-Cas9-mediated BATF knockout in human activated Tregs in conjunction with bulk RNA sequencing, immunophenotyping, and in vitro functional assays corroborated the central role of BATF in limiting excessive activation and promoting the survival of human activated Tregs. Last, we identified a suite of surface molecules reflective of the BATF-driven transcriptional network on intratumoral Tregs in patients with HNSCC. These findings uncover a primary transcriptional regulator of highly suppressive intratumoral Tregs, highlighting potential opportunities for therapeutic intervention in cancer without affecting immune homeostasis.

Machine learning reveals genetic modifiers of the immune microenvironment of cancer

Heritability in the immune tumor microenvironment (iTME) has been widely observed yet remains largely uncharacterized. Here, we developed a machine learning approach to map iTME modifiers within loci from genome-wide association studies (GWASs) for breast cancer (BrCa) incidence. A random forest model was trained on a positive set of immune-oncology (I-O) targets, and then used to assign I-O target probability scores to 1,362 candidate genes in linkage disequilibrium with 155 BrCa GWAS loci. Cluster analysis of the most probable candidates revealed two subfamilies of genes related to effector functions and adaptive immune responses, suggesting that iTME modifiers impact multiple aspects of anticancer immunity. Two of the top ranking BrCa candidates, LSP1 and TLR1, were orthogonally validated as iTME modifiers using BrCa patient biopsies and comparative mapping studies, respectively. Collectively, these data demonstrate a robust and flexible framework for functionally fine-mapping GWAS risk loci to identify translatable therapeutic targets.

Prognostic and immunological roles of IL18RAP in human cancers

Across several cancers, IL18 receptor accessory protein (IL18RAP) is abnormally expressed, and this abnormality is related to tumor immunity and heterogeneous clinical outcomes. In this study, based on bioinformatics analysis, we discovered that IL18RAP is related to the human tumor microenvironment and promotes various immune cells infiltration. Additionally, the multiple immunofluorescence staining revealed that with the increased expression of IL18RAP, the number of infiltrated M1 macrophages increased. This finding was confirmed by coculture migration analysis using three human cancer cell lines (MDA-MB-231, U251, and HepG2) with IL18RAP knockdown. We discovered a positive link between IL18RAP and the majority of immunostimulators, immunoinhibitors, major histocompatibility complex (MHC) molecules, chemokines, and chemokine receptor genes using Spearman correlation analysis. Additionally, functional IL18RAP's gene set enrichment analysis (GSEA) revealed that it is related to a variety of immunological processes, such as positive regulation of interferon gamma production and positive regulation of NK cell-mediated immunity. Moreover, we used single-cell RNA sequencing analysis to detect that IL18RAP was mainly expressed in immune cells, and HALLMARK analysis confirmed that the INF-γ gene set expression was upregulated in CD8Tex cells. In addition, in human and mouse cancer cohorts, we found that the level of IL18RAP can predict the immunotherapy response. In short, our study showed that IL18RAP is a new tumor biomarker and may become a potential immunotherapeutic target in cancer.

Dissecting pulmonary fibroblasts heterogeneity in lung development, health and diseases

Lung fibroblasts are the major components in the connective tissue of the pulmonary interstitium and play essential roles in the developing of postnatal lung, synthesizing the extracellular matrix and maintaining the integrity of the lung architecture. Fibroblasts are activated in various disease conditions and exhibit functional heterogeneities according to their origin, spatial location, activated state and microenvironment. In recent years, advances in technology have enabled researchers to identify fibroblast subpopulations in both mouse and human. Here, we discuss pulmonary fibroblast heterogeneity, focusing on the developing, healthy and pathological lung conditions. We firstly review the expression profiles of fibroblasts during lung development, and then consider fibroblast diversity according to different anatomical sites of lung architecture. Subsequently, we discuss fibroblast heterogeneity in genetic lineage. Finally, we focus on how fibroblast heterogeneity may shed light on different pathological lung conditions such as fibrotic diseases, infectious diseases including COVID-19, and lung cancers. We emphasize the importance of comparative studies to illuminate the overlapping characteristics, expression profiles and signaling pathways of the fibroblast subpopulations across disease conditions, a better characterization of the functional complexity rather than the expression of a particular gene may have important therapeutic applications.

Pan-cancer Analysis Reveals Cancer-dependent Expression of SOX17 and Associated Clinical Outcomes

BACKGROUND/AIM

SRY-box containing gene 17 (SOX17) plays a pivotal role in cancer onset and progression and is considered a potential target for cancer diagnosis and treatment. However, the expression pattern of SOX17 in cancer and its clinical relevance remains unknown. Here, we explored the relationship between the expression of SOX17 and drug response by examining SOX17 expression patterns across multiple cancer types.

MATERIALS AND METHODS

Single-cell and bulk RNA-seq analyses were used to explore the expression profile of SOX17. Analysis results were verified with qPCR and immunohistochemistry. Survival, drug response, and co-expression analyses were performed to illustrate its correlation with clinical outcomes.

RESULTS

The results revealed that abnormal expression of SOX17 is highly heterogenous across multiple cancer types, indicating that SOX17 manifests as a cancer type-dependent feature. Furthermore, the expression pattern of SOX17 is also associated with cancer prognosis in certain cancer types. Strong SOX17 expression correlates with the potency of small molecule drugs that affect PI3K/mTOR signaling. FGF18, a gene highly relevant to SOX17, is involved in the PI3K-AKT signaling pathway. Single-cell RNA-seq analysis demonstrated that SOX17 is mainly expressed in endothelial cells and barely expressed in other cells but spreads to other cell types during the development of ovarian cancer.

CONCLUSION

Our study revealed the expression pattern of SOX17 in pan-cancer through bulk and single-cell RNA-seq analyses and determined that SOX17 is related to the diagnosis, staging, and prognosis of some tumors. These findings have clinical implications and may help identify mechanistic pathways amenable to pharmacological interventions.

A Roadmap for the Human Gut Cell Atlas

The number of studies investigating the human gastrointestinal tract using various single-cell profiling methods has increased substantially in the past few years. Although this increase provides a unique opportunity for the generation of the first comprehensive Human Gut Cell Atlas (HGCA), there remains a range of major challenges ahead. Above all, the ultimate success will largely depend on a structured and coordinated approach that aligns global efforts undertaken by a large number of research groups. In this Roadmap, we discuss a comprehensive forward-thinking direction for the generation of the HGCA on behalf of the Gut Biological Network of the Human Cell Atlas. Based on the consensus opinion of experts from across the globe, we outline the main requirements for the first complete HGCA by summarizing existing data sets and highlighting anatomical regions and/or tissues with limited coverage. We provide recommendations for future studies and discuss key methodologies and the importance of integrating the healthy gut atlas with related diseases and gut organoids. Importantly, we critically overview the computational tools available and provide recommendations to overcome key challenges.

Germinal center-dependent and -independent immune responses of tumor-infiltrating B cells in human cancers

B cells play essential roles in immunity, mainly through the production of high affinity plasma cells (PCs) and memory B (Bmem) cells. The affinity maturation and differentiation of B cells rely on the integration of B-cell receptor (BCR) intrinsic and extrinsic signals provided by antigen binding and the microenvironment, respectively. In recent years, tumor infiltrating B (TIL-B) cells and PCs (TIL-PCs) have been revealed as important players in antitumor responses in human cancers, but their interplay and dynamics remain largely unknown. In lymphoid organs, B-cell responses involve both germinal center (GC)-dependent and GC-independent pathways for Bmem cell and PC production. Affinity maturation of BCR repertoires occurs in GC reactions with specific spatiotemporal dynamics of signal integration by B cells. In general, the reactivation of high-affinity Bmem cells by antigens triggers GC-independent production of large numbers of PC without BCR rediversification. Understanding B-cell dynamics in immune responses requires the integration of multiple tools and readouts such as single-cell phenotyping and RNA-seq, in situ analyses, BCR repertoire analysis, BCR specificity and affinity assays, and functional tests. Here, we review how those tools have recently been applied to study TIL-B cells and TIL-PC in different types of solid tumors. We assessed the published evidence for different models of TIL-B-cell dynamics involving GC-dependent or GC-independent local responses and the resulting production of antigen-specific PCs. Altogether, we highlight the need for more integrative B-cell immunology studies to rationally investigate TIL-B cells as a leverage for antitumor therapies.

Intercellular cross-talk through lineage-specific gap junction of cancer-associated fibroblasts related to stromal fibrosis and prognosis

Stromal fibrosis in cancer is usually associated with poor prognosis and chemotherapy resistance. It is thought to be caused by fibroblasts; however, the exact mechanism is not yet well understood. The study aimed to identify lineage-specific cancer-associated fibroblast (CAF) subgroup and their associations with extracellular matrix remodeling and clinical significances in various tumor types using single-cell and bulk RNA sequencing data. Through unsupervised clustering, six subclusters of CAFs were identified, including a cluster with exclusively high gap junction protein beta-2 (GJB2) expression. This cluster was named GJB2-positive CAF. It was found to be a unique subgroup of terminally differentiated CAFs associated with collagen gene expression and extracellular matrix remodeling. GJB2-positive CAFs showed higher communication frequency with vascular endothelial cells and cancer cells than GJB2-negative CAFs. Moreover, GJB2 was poorly expressed in normal tissues, indicating that its expression is dependent on interaction with other cells, including vascular endothelial cells and cancer cells. Finally, the study investigated the clinical significance of GJB2 signature score for GJB2-positive CAFs in cancer and found a correlation with poor prognosis. These results suggest that GJB2-positive CAF is a unique fibroblast subtype involved in extracellular matrix remodeling, with significant clinical implications in cancer.

Integration of single-cell RNA sequencing and bulk RNA transcriptome sequencing reveals a heterogeneous immune landscape and pivotal cell subpopulations associated with colorectal cancer prognosis

Introduction

Colorectal cancer (CRC) is a highly heterogeneous cancer. The molecular and cellular characteristics differ between the colon and rectal cancer type due to the differences in their anatomical location and pathological properties. With the advent of single-cell sequencing, it has become possible to analyze inter- and intra-tumoral tissue heterogeneities.

Methods

A comprehensive CRC immune atlas, comprising 62,398 immune cells, was re-structured into 33 immune cell clusters at the single-cell level. Further, the immune cell lineage heterogeneity of colon, rectal, and paracancerous tissues was explored. Simultaneously, we characterized the TAM phenotypes and analyzed the transcriptomic factor regulatory network of each macrophage subset using SCENIC. In addition, monocle2 was used to elucidate the B cell developmental trajectory. The crosstalk between immune cells was explored using CellChat and the patterns of incoming and outgoing signals within the overall immune cell population were identified. Afterwards, the bulk RNA-sequencing data from The Cancer Genome Atlas (TCGA) were combined and the relative infiltration abundance of the identified subpopulations was analyzed using CIBERSORT. Moreover, cell composition patterns could be classified into five tumor microenvironment (TME) subtypes by employing a consistent non-negative matrix algorithm. Finally, the co-expression and interaction between SPP1+TAMs and Treg cells in the tumor microenvironment were analyzed by multiplex immunohistochemistry.

Results

In the T cell lineage, we found that CXCL13+T cells were more widely distributed in colorectal cancer tissues, and the proportion of infiltration was increased. In addition, Th17 was found accounted for the highest proportion in CD39+CD101+PD1+T cells. Mover, Ma1-SPP1 showed the characteristics of M2 phenotypes and displayed an increased proportion in tumor tissues, which may promote angiogenesis. Plasma cells (PCs) displayed a significantly heterogeneous distribution in tumor as well as normal tissues. Specifically, the IgA+ PC population could be shown to be decreased in colorectal tumor tissues whereas the IgG+ PC one was enriched. In addition, information flow mediated by SPP1 and CD44, regulate signaling pathways of tumor progression. Among the five TME subtypes, the TME-1 subtype displayed a markedly reduced proportion of T-cell infiltration with the highest proportion of macrophages which was correlated to the worst prognosis. Finally, the co-expression and interaction between SPP1+TAMs and Treg cells were observed in the CD44 enriched region.

Discussion

The heterogeneity distribution and phenotype of immune cells were analyzed in colon cancer and rectal cancer at the single-cell level. Further, the prognostic role of major tumor-infiltrating lymphocytes and TME subtypes in CRC was evaluated by integrating bulk RNA. These findings provide novel insight into the immunotherapy of CRC.

Implications of tumour heterogeneity on cancer evolution and therapy resistance: lessons from breast cancer

Tumour heterogeneity is pervasive amongst many cancers and leads to disease progression, and therapy resistance. In this review, using breast cancer as an exemplar, we focus on the recent advances in understanding the interplay between tumour cells and their microenvironment using single cell sequencing and digital spatial profiling technologies. Further, we discuss the utility of lineage tracing methodologies in pre-clinical models of breast cancer, and how these are being used to unravel new therapeutic vulnerabilities and reveal biomarkers of breast cancer progression. © 2023 The Pathological Society of Great Britain and Ireland.

Promise of spatially resolved omics for tumor research

Tumors are spatially heterogeneous tissues that comprise numerous cell types with intricate structures. By interacting with the microenvironment, tumor cells undergo dynamic changes in gene expression and metabolism, resulting in spatiotemporal variations in their capacity for proliferation and metastasis. In recent years, the rapid development of histological techniques has enabled efficient and high-throughput biomolecule analysis. By preserving location information while obtaining a large number of gene and molecular data, spatially resolved metabolomics (SRM) and spatially resolved transcriptomics (SRT) approaches can offer new ideas and reliable tools for the in-depth study of tumors. This review provides a comprehensive introduction and summary of the fundamental principles and research methods used for SRM and SRT techniques, as well as a review of their applications in cancer-related fields.

Deep immunophenotyping reveals clinically distinct cellular states and ecosystems in large-scale colorectal cancer

Determining the diverse cell types in the tumor microenvironment (TME) and their organization into cellular communities, is critical for understanding the biological heterogeneity and therapy of cancer. Here, we deeply immunophenotype the colorectal cancer (CRC) by integrative analysis of large-scale bulk and single cell transcriptome of 2350 patients and 53,137 cells. A rich landscape of 42 cellular states and 7 ecosystems in TMEs is uncovered and extend the previous immune classifications of CRC. Functional pathways and potential transcriptional regulators analysis of cellular states and ecosystems reveal cancer hallmark-related pathways and several critical transcription factors in CRC. High-resolution characterization of the TMEs, we discover the potential utility of cellular states (i.e., Monocytes/Macrophages and CD8 T cell) and ecosystems for prognosis and clinical therapy selection of CRC. Together, our results expand our understanding of cellular organization in TMEs of CRC, with potential implications for the development of biomarkers and precision therapies.

Regulatory role of Chitinase 3-like 1 gene in papillary thyroid carcinoma proved by integration analyses of single-cell sequencing with cohort and experimental validations

Papillary thyroid carcinoma (PTC) is one of the most common thyroid carcinomas. The gross extrathyroidal extension and extensive metastases of PTC lead to high rates of recurrence and poor clinical outcomes. However, the mechanisms underlying PTC development are poorly understood. In this study, using single-cell RNA sequencing, the transcriptome profiles of two PTC patients were addressed, including PTC1 with low malignancy and good prognosis and PTC2 with high malignancy and poor prognosis. We found that epithelial subcluster Epi02 was the most associated with the malignant development of PTC cells, with which the fold change of Chitinase 3-like 1 (CHI3L1) is on the top of the differentially expressed genes between PTC1 and PTC2 (P < 0.001). However CHI3L1 is rarely investigated in PTC as far. We then studied its role in PTC with a series of experiments. Firstly, qRT-PCR analysis of 14 PTC patients showed that the expression of CHI3L1 was positively correlated with malignancy. In addition, overexpression or silencing of CHI3L1 in TPC-1 cells, a PTC cell line, cultured in vitro showed that the proliferation, invasion, and metastasis of the cells were promoted or alleviated by CHI3L1. Further, immunohistochemistry analysis of 110 PTC cases revealed a significant relationship between CHI3L1 protein expression and PTC progression, especially the T (P < 0.001), N (P < 0.001), M stages (P = 0.007) and gross ETE (P < 0.001). Together, our results prove that CHI3L1 is a positive regulator of malignant development of PTC, and it promotes proliferation, invasion, and metastasis of PTC cells. Our study improves understanding of the molecular mechanisms underlying the progression of PTC and provides new insights for the clinical diagnosis and treatment of PTC.

Roles of Fascin in Dendritic Cells

Dendritic cells (DCs) are professional antigen-presenting cells that play a crucial role in activating naive T cells through presenting antigen information, thereby influencing immunity and anti-cancer responses. Fascin, a 55-kDa actin-bundling protein, is highly expressed in mature DCs and serves as a marker protein for their identification. However, the precise role of fascin in intratumoral DCs remains poorly understood. In this review, we aim to summarize the role of fascin in both normal and intratumoral DCs. In normal DCs, fascin promotes immune effects through facilitating DC maturation and migration. Through targeting intratumoral DCs, fascin inhibitors enhance anti-tumor immune activity. These roles of fascin in different DC populations offer valuable insights for future research in immunotherapy and strategies aimed at improving cancer treatments.

IL1R1+ cancer-associated fibroblasts drive tumor development and immunosuppression in colorectal cancer

Fibroblasts have a considerable functional and molecular heterogeneity and can play various roles in the tumor microenvironment. Here we identify a pro-tumorigenic IL1R1⁺, IL-1-high-signaling subtype of fibroblasts, using multiple colorectal cancer (CRC) patient single cell sequencing datasets. This subtype of fibroblasts is linked to T cell and macrophage suppression and leads to increased cancer cell growth in 3D co-culture assays. Furthermore, both a fibroblast-specific IL1R1 knockout and IL-1 receptor antagonist Anakinra administration reduce tumor growth in vivo. This is accompanied by reduced intratumoral Th17 cell infiltration. Accordingly, CRC patients who present with IL1R1-expressing cancer-associated-fibroblasts (CAFs), also display elevated levels of immune exhaustion markers, as well as an increased Th17 score and an overall worse survival. Altogether, this study underlines the therapeutic value of targeting IL1R1-expressing CAFs in the context of CRC.

Shining a LIGHT on myeloid cell targeted immunotherapy

Despite over a decade of clinical trials combining inhibition of emerging checkpoints with a PD-1/L1 inhibitor backbone, meaningful survival benefits have not been shown in PD-1/L1 inhibitor resistant or refractory solid tumours, particularly tumours dominated by a myelosuppressive microenvironment. Achieving durable anti-tumour immunity will therefore likely require combination of adaptive and innate immune stimulation, myeloid repolarisation, enhanced APC activation and antigen processing/presentation, lifting of the CD47/SIRPα (Cluster of Differentiation 47/signal regulatory protein alpha) 'do not eat me' signal, provision of an apoptotic 'pro-eat me' or 'find me' signal, and blockade of immune checkpoints. The importance of effectively targeting mLILRB2 and SIRPAyeloid cells to achieve improved response rates has recently been emphasised, given myeloid cells are abundant in the tumour microenvironment of most solid tumours. TNFSF14, or LIGHT, is a tumour necrosis superfamily ligand with a broad range of adaptive and innate immune activities, including (1) myeloid cell activation through Lymphotoxin Beta Receptor (LTβR), (2) T/NK (T cell and natural killer cell) induced anti-tumour immune activity through Herpes virus entry mediator (HVEM), (3) potentiation of proinflammatory cytokine/chemokine secretion through LTβR on tumour stromal cells, (4) direct induction of tumour cell apoptosis in vitro, and (5) the reorganisation of lymphatic tissue architecture, including within the tumour microenvironment (TME), by promoting high endothelial venule (HEV) formation and induction of tertiary lymphoid structures. LTBR (Lymphotoxin beta receptor) and HVEM rank highly amongst a range of costimulatory receptors in solid tumours, which raises interest in considering how LIGHT-mediated costimulation may be distinct from a growing list of immunotherapy targets which have failed to provide survival benefit as monotherapy or in combination with PD-1 inhibitors, particularly in the checkpoint acquired resistant setting.

B-cell-specific checkpoint molecules that regulate anti-tumour immunity

The role of B cells in anti-tumour immunity is still debated and, accordingly, immunotherapies have focused on targeting T and natural killer cells to inhibit tumour growth1,2. Here, using high-throughput flow cytometry as well as bulk and single-cell RNA-sequencing and B-cell-receptor-sequencing analysis of B cells temporally during B16F10 melanoma growth, we identified a subset of B cells that expands specifically in the draining lymph node over time in tumour-bearing mice. The expanding B cell subset expresses the cell surface molecule T cell immunoglobulin and mucin domain 1 (TIM-1, encoded by Havcr1) and a unique transcriptional signature, including multiple co-inhibitory molecules such as PD-1, TIM-3, TIGIT and LAG-3. Although conditional deletion of these co-inhibitory molecules on B cells had little or no effect on tumour burden, selective deletion of Havcr1 in B cells both substantially inhibited tumour growth and enhanced effector T cell responses. Loss of TIM-1 enhanced the type 1 interferon response in B cells, which augmented B cell activation and increased antigen presentation and co-stimulation, resulting in increased expansion of tumour-specific effector T cells. Our results demonstrate that manipulation of TIM-1-expressing B cells enables engagement of the second arm of adaptive immunity to promote anti-tumour immunity and inhibit tumour growth.

Understanding tumour endothelial cell heterogeneity and function from single-cell omics

Anti-angiogenic therapies (AATs) are used to treat different types of cancers. However, their success is limited owing to insufficient efficacy and resistance. Recently, single-cell omics studies of tumour endothelial cells (TECs) have provided new mechanistic insight. Here, we overview the heterogeneity of human TECs of all tumour types studied to date, at the single-cell level. Notably, most human tumour types contain varying numbers but only a small population of angiogenic TECs, the presumed targets of AATs, possibly contributing to the limited efficacy of and resistance to AATs. In general, TECs are heterogeneous within and across all tumour types, but comparing TEC phenotypes across tumours is currently challenging, owing to the lack of a uniform nomenclature for endothelial cells and consistent single-cell analysis protocols, urgently raising the need for a more consistent approach. Nonetheless, across most tumour types, universal TEC markers (ACKR1, PLVAP and IGFBP3) can be identified. Besides angiogenesis, biological processes such as immunomodulation and extracellular matrix organization are among the most commonly predicted enriched signatures of TECs across different tumour types. Although angiogenesis and extracellular matrix targets have been considered for AAT (without the hoped success), the immunomodulatory properties of TECs have not been fully considered as a novel anticancer therapeutic approach. Therefore, we also discuss progress, limitations, solutions and novel targets for AAT development.

Prioritization and functional validation of target genes from single-cell transcriptomics studies

Translation of academic results into clinical practice is a formidable unmet medical need. Single-cell RNA-sequencing (scRNA-seq) studies generate long descriptive ranks of markers with predicted biological function, but without functional validation, it remains challenging to know which markers truly exert the putative function. Given the lengthy/costly nature of validation studies, gene prioritization is required to select candidates. We address these issues by studying tip endothelial cell (EC) marker genes because of their importance for angiogenesis. Here, by tailoring Guidelines On Target Assessment for Innovative Therapeutics, we in silico prioritize previously unreported/poorly described, high-ranking tip EC markers. Notably, functional validation reveals that four of six candidates behave as tip EC genes. We even discover a tip EC function for a gene lacking in-depth functional annotation. Thus, validating prioritized genes from scRNA-seq studies offers opportunities for identifying targets to be considered for possible translation, but not all top-ranked scRNA-seq markers exert the predicted function.

Tumor and local lymphoid tissue interaction determines prognosis in high-grade serous ovarian cancer

Tertiary lymphoid structure (TLS) is associated with prognosis in copy-number-driven tumors, including high-grade serous ovarian cancer (HGSOC), although the function of TLS and its interaction with copy-number alterations in HGSOC are not fully understood. In the current study, we confirm that TLS-high HGSOC patients show significantly better progression-free survival (PFS). We show that the presence of TLS in HGSOC tumors is associated with B cell maturation and cytotoxic tumor-specific T cell activation and proliferation. In addition, the copy-number loss of IL15 and CXCL10 may limit TLS formation in HGSOC; a list of genes that may dysregulate TLS function is also proposed. Last, a radiomics-based signature is developed to predict the presence of TLS, which independently predicts PFS in both HGSOC patients and immune checkpoint inhibitor (ICI)-treated non-small cell lung cancer (NSCLC) patients. Overall, we reveal that TLS coordinates intratumoral B cell and T cell response to HGSOC tumor, while the cancer genome evolves to counteract TLS formation and function.

Clinical Advances and Perspectives in Targeted Radionuclide Therapy

Targeted radionuclide therapy has become increasingly prominent as a nuclear medicine subspecialty. For many decades, treatment with radionuclides has been mainly restricted to the use of iodine-131 in thyroid disorders. Currently, radiopharmaceuticals, consisting of a radionuclide coupled to a vector that binds to a desired biological target with high specificity, are being developed. The objective is to be as selective as possible at the tumor level, while limiting the dose received at the healthy tissue level. In recent years, a better understanding of molecular mechanisms of cancer, as well as the appearance of innovative targeting agents (antibodies, peptides, and small molecules) and the availability of new radioisotopes, have enabled considerable advances in the field of vectorized internal radiotherapy with a better therapeutic efficacy, radiation safety and personalized treatments. For instance, targeting the tumor microenvironment, instead of the cancer cells, now appears particularly attractive. Several radiopharmaceuticals for therapeutic targeting have shown clinical value in several types of tumors and have been or will soon be approved and authorized for clinical use. Following their clinical and commercial success, research in that domain is particularly growing, with the clinical pipeline appearing as a promising target. This review aims to provide an overview of current research on targeting radionuclide therapy.

Comprehensive analysis of single-cell RNA-seq and bulk RNA-seq revealed the heterogeneity and convergence of the immune microenvironment in renal cell carcinoma

Substantial progress has been made in cancer biology and treatment in recent years, but the clinical outcome of patients with renal cell carcinoma (RCC) remains unsatisfactory. The tumor microenvironment (TME) is a potential target. By analyzing single-cell RNA sequencing (sc-RNAseq) data from six RCC tumor samples, this study identified 11 different cell types in the RCC cellular microenvironment, indicating a high degree of intratumoral heterogeneity. Through re-dimensionality reduction clustering of epithelial cells, neutrophils, macrophages, and T cells, we deeply reveal differences in the RCC tumor microenvironment. By analyzing differentially expressed genes in normal epithelial cells and malignant epithelial cells, we identify RNASET2 and GATM as potential prognostic biomarkers in RCC. In addition, by transcriptional factor analysis, we found significant differences in the expression of GZMK-CD8 T cell and B cell transcription factors between cancer tissues and normal tissues. By cell correlation analysis, we found significant correlations between neutrophils and macrophages and between IL7R-CD4 T cells and T regulatory (Treg) cells in RCC, which may be involved in the formation of immune TMEs. By cell developmental trajectory analysis, we showed that macrophages may be derived from neutrophils, whereas Treg cells may be derived from IL7R-CD4 T cells. By cell communication analysis, we found a clear interaction between macrophages and endothelial cells, neutrophils, and GZMK-CD8 T cells. In addition, we found that ADGRE5 signaling was mainly derived from mast cells and GZMK-CD8 T cells, and had a significant communication effect with neutrophils. The COLLAGEN signaling pathway is mainly derived from fibroblasts and has a significant communication effect with mast cells. Finally, we verified that RNASET2, which is highly expressed in epithelial cells, promotes proliferation and migration of RCC in vitro. RNASET2 is likely to be a potential target for renal cell carcinoma therapy. The results based on sc-RNAseq data analysis help to further elucidate the cellular microenvironment of RCC and provide help for cancer heterogeneity studies. This will help to provide more accurate personalized treatment for patients in clinical diagnosis.

Applications of single-cell RNA sequencing in drug discovery and development

Single-cell technologies, particularly single-cell RNA sequencing (scRNA-seq) methods, together with associated computational tools and the growing availability of public data resources, are transforming drug discovery and development. New opportunities are emerging in target identification owing to improved disease understanding through cell subtyping, and highly multiplexed functional genomics screens incorporating scRNA-seq are enhancing target credentialling and prioritization. ScRNA-seq is also aiding the selection of relevant preclinical disease models and providing new insights into drug mechanisms of action. In clinical development, scRNA-seq can inform decision-making via improved biomarker identification for patient stratification and more precise monitoring of drug response and disease progression. Here, we illustrate how scRNA-seq methods are being applied in key steps in drug discovery and development, and discuss ongoing challenges for their implementation in the pharmaceutical industry.

Network-based approach elucidates critical genes in BRCA subtypes and chemotherapy response in Triple Negative Breast Cancer

Breast cancers exhibit substantial transcriptional heterogeneity, posing a significant challenge to the prediction of treatment response and prognostication of outcomes. Especially, translation of TNBC subtypes to the clinic remains a work in progress, in part because of a lack of clear transcriptional signatures distinguishing the subtypes. Our recent network-based approach, PathExt, demonstrates that global transcriptional changes in a disease context are likely mediated by a small number of key genes, and these mediators may better reflect functional or translationally relevant heterogeneity. We apply PathExt to 1059 BRCA tumors and 112 healthy control samples across 4 subtypes to identify frequent, key-mediator genes in each BRCA subtype. Compared to conventional differential expression analysis, PathExt-identified genes (1) exhibit greater concordance across tumors, revealing shared as well as BRCA subtype-specific biological processes, (2) better recapitulate BRCA-associated genes in multiple benchmarks, and (3) exhibit greater dependency scores in BRCA subtype-specific cancer cell lines. Single cell transcriptomes of BRCA subtype tumors reveal a subtype-specific distribution of PathExt-identified genes in multiple cell types from the tumor microenvironment. Application of PathExt to a TNBC chemotherapy response dataset identified TNBC subtype-specific key genes and biological processes associated with resistance. We described putative drugs that target top novel genes potentially mediating drug resistance. Overall, PathExt applied to breast cancer refines previous views of gene expression heterogeneity and identifies potential mediators of TNBC subtypes, including potential therapeutic targets.

Unveiling the interplay between mutational signatures and tumor microenvironment: a pan-cancer analysis

Background

While recent studies have separately explored mutational signatures and the tumor microenvironment (TME), there is limited research on the associations of both factors in a pan-cancer context.

Materials and methods

We performed a pan-cancer analysis of over 8,000 tumor samples from The Cancer Genome Atlas (TCGA) project. Machine learning methods were employed to systematically explore the relationship between mutational signatures and TME and develop a risk score based on TME-associated mutational signatures to predict patient survival outcomes. We also constructed an interaction model to explore how mutational signatures and TME interact and influence cancer prognosis.

Results

Our analysis revealed a varied association between mutational signatures and TME, with the Clock-like signature showing the most widespread influence. Risk scores based on mutational signatures mainly induced by Clock-like and AID/APOBEC activity exhibited strong pan-cancer survival stratification ability. We also propose a novel approach to predict transcriptome decomposed infiltration levels using genome-derived mutational signatures as an alternative approach for exploring TME cell types when transcriptome data are unavailable. Our comprehensive analysis revealed that certain mutational signatures and their interaction with immune cells significantly impact clinical outcomes in particular cancer types. For instance, T cell infiltration levels only served as a prognostic biomarker in melanoma patients with high ultraviolet radiation exposure, breast cancer patients with high homologous recombination deficiency signature, and lung adenocarcinoma patients with high tobacco-associated mutational signature.

Conclusion

Our study comprehensively explains the complex interplay between mutational signatures and immune infiltration in cancer. The results highlight the importance of considering both mutational signatures and immune phenotypes in cancer research and their significant implications for developing personalized cancer treatments and more effective immunotherapy.

Identification of cervical cancer stem cells using single-cell transcriptomes of normal cervix, cervical premalignant lesions, and cervical cancer

BACKGROUND

Cervical cancer is the fourth leading cause of mortality among gynecological malignancies. However, the identification of cervical cancer stem cells remains unclear.

METHODS

We performed single-cell mRNA sequencing on ∼122,400 cells from 20 cervical biopsies, including 5 healthy controls, 4 high-grade intraepithelial neoplasias, 5 microinvasive carcinomas of the cervix, and 6 invasive cervical squamous carcinomas. Bioinformatic results were validated by multiplex immunohistochemistry (mIHC) in cervical cancer tissue microarrays (TMA) (n = 85).

FINDINGS

We identified cervical cancer stem cells and highlighted the functional changes in cervical stem cells during malignant transformation. The original non-malignant stem cell properties (characterized by high proliferation) gradually diminished, whereas the tumor stem cell properties (characterized by epithelial-mesenchymal transformation and invasion) were enhanced. The mIHC results of our TMA cohort confirmed the existence of stem-like cells and indicated that cluster correlated with neoplastic recurrence. Subsequently, we investigated malignant and immune cell heterogeneity in the cervical multicellular ecosystem across different disease stages. We observed global upregulation of interferon responses in the cervical microenvironment during lesion progression.

INTERPRETATION

Our results provide more insights into cervical premalignant and malignant lesion microenvironments.

FUNDING

This research was supported by the Guangdong Provincial Natural Science Foundation of China (2023A1515010382), Grant 2021YFC2700603 from the National Key Research & Development Program of China and the Hubei Provincial Natural Science Foundation of China (2022CFB174 and 2022CFB893).

Unlocking multidimensional cancer therapeutics using geometric data science

Personalised approaches to cancer therapeutics primarily involve identification of patient sub-populations most likely to benefit from targeted drugs. Such a stratification has led to plethora of designs of clinical trials that are often too complex due to the need for incorporating biomarkers and tissue types. Many statistical methods have been developed to address these issues; however, by the time such methodology is available research in cancer has moved on to new challenges and therefore in order to avoid playing catch-up it is necessary to develop new analytic tools alongside. One of the challenges facing cancer therapy is to effectively and appropriately target multiple therapies for sensitive patient population based on a panel of biomarkers across multiple cancer types, and matched future trial designs. We present novel geometric methods (mathematical theory of hypersurfaces) to visualise complex cancer therapeutics data as multidimensional, as well as geometric representation of oncology trial design space in higher dimensions. The hypersurfaces are used to describe master protocols, with application to a specific example of a basket trial design for melanoma, and thus setup a framework for further incorporating multi-omics data as multidimensional therapeutics.

CCL19+ dendritic cells potentiate clinical benefit of anti-PD-(L)1 immunotherapy in triple-negative breast cancer

BACKGROUND

The extensive involvement of dendritic cells (DCs) in immune contexture indicates their potent value in cancer immunotherapy. Understanding DC diversity in patient cohorts may strengthen the clinical benefit of immune checkpoint inhibitors (ICIs).

METHODS

Single-cell profiling of breast tumors from two clinical trials was performed to investigate DC heterogeneity. Multiomics, tissue characterization, and pre-clinical experiments were used to evaluate the role of the identified DCs in the tumor microenvironment. Four independent clinical trials were leveraged to explore biomarkers to predict ICI and chemotherapy outcomes.

FINDINGS

We identified a distinct CCL19-expressing functional state of DCs associated with favorable responses to anti-programmed death (ligand)-1 (PD-(L)1), which displayed migratory and immunomodulatory phenotypes. These cells were correlated with antitumor T cell immunity and the presence of tertiary lymphoid structures and lymphoid aggregates, defining immunogenic microenvironments in triple-negative breast cancer. In vivo, CCL19⁺ DC deletion by Ccl19 gene ablation dampened CCR7⁺CD8⁺ T cells and tumor elimination in response to anti-PD-1. Notably, high circulating and intratumoral CCL19 levels were associated with superior response and survival in patients receiving anti-PD-1 but not chemotherapy.

CONCLUSIONS

We uncovered a critical role of DC subsets in immunotherapy, which has implications for designing novel therapies and patient stratification strategies.

FUNDING

This study was funded by the National Key Research and Development Project of China, the National Natural Science Foundation of China, the Program of Shanghai Academic/Technology Research Leader, the Natural Science Foundation of Shanghai, the Shanghai Key Laboratory of Breast Cancer, the Shanghai Hospital Development Center (SHDC), and the Shanghai Health Commission.

Single-cell sequencing technology in colorectal cancer: a new technology to disclose the tumor heterogeneity and target precise treatment

Colorectal Cancer (CRC) is one of the most common gastrointestinal tumors, and its high tumor heterogeneity makes traditional sequencing methods incapable of obtaining information about the heterogeneity of individual cancer cells in CRC. Therefore, single-cell sequencing technology can be applied to better analyze the differences in genetic and protein information between cells, to obtain genomic sequence information of single cells, and to more thoroughly analyze the cellular characteristics and interactions in the CRC microenvironment. This will provide a more comprehensive understanding of colorectal cancer development and metastasis and indicate the treatment plan and prognosis. In this study, we review the application of single-cell sequencing to analyze the tumor microenvironment of CRC, explore the mechanisms involved in CRC metastasis and progression, and provide a reference for potential treatment options.

Mitochondrial single-cell ATAC-seq for high-throughput multi-omic detection of mitochondrial genotypes and chromatin accessibility

Natural sequence variation within mitochondrial DNA (mtDNA) contributes to human phenotypes and may serve as natural genetic markers in human cells for clonal and lineage tracing. We recently developed a single-cell multi-omic approach, called 'mitochondrial single-cell assay for transposase-accessible chromatin with sequencing' (mtscATAC-seq), enabling concomitant high-throughput mtDNA genotyping and accessible chromatin profiling. Specifically, our technique allows the mitochondrial genome-wide inference of mtDNA variant heteroplasmy along with information on cell state and accessible chromatin variation in individual cells. Leveraging somatic mtDNA mutations, our method further enables inference of clonal relationships among native ex vivo-derived human cells not amenable to genetic engineering-based clonal tracing approaches. Here, we provide a step-by-step protocol for the use of mtscATAC-seq, including various cell-processing and flow cytometry workflows, by using primary hematopoietic cells, subsequent single-cell genomic library preparation and sequencing that collectively take ~3-4 days to complete. We discuss experimental and computational data quality control metrics and considerations for the extension to other mammalian tissues. Overall, mtscATAC-seq provides a broadly applicable platform to map clonal relationships between cells in human tissues, investigate fundamental aspects of mitochondrial genetics and enable additional modes of multi-omic discovery.

Endothelial Rap1B mediates T-cell exclusion to promote tumor growth: a novel mechanism underlying vascular immunosuppression

Overcoming vascular immunosuppression: lack of endothelial cell (EC) responsiveness to inflammatory stimuli in the proangiogenic environment of tumors, is essential for successful cancer immunotherapy. The mechanisms through which Vascular Endothelial Growth Factor A(VEGF-A) modulates tumor EC response to exclude T-cells are not well understood. Here, we demonstrate that EC-specific deletion of small GTPase Rap1B, previously implicated in normal angiogenesis, restricts tumor growth in endothelial-specific Rap1B-knockout (Rap1BiΔEC) mice. EC-specific Rap1B deletion inhibits angiogenesis, but also leads to an altered tumor microenvironment with increased recruitment of leukocytes and increased activity of tumor CD8+ T-cells. Depletion of CD8+ T-cells restored tumor growth in Rap1BiΔEC mice. Mechanistically, global transcriptome and functional analyses indicated upregulation of signaling by a tumor cytokine, TNF-α, and increased NF-κB transcription in Rap1B-deficient ECs. Rap1B-deficiency led to elevated proinflammatory chemokine and Cell Adhesion Molecules (CAMs) expression in TNF-α stimulated ECs. Importantly, CAM expression was elevated in tumor ECs from Rap1BiΔEC mice. Significantly, Rap1B deletion prevented VEGF-A-induced immunosuppressive downregulation of CAM expression, demonstrating that Rap1B is essential for VEGF-A-suppressive signaling. Thus, our studies identify a novel endothelial-endogenous mechanism underlying VEGF-A-dependent desensitization of EC to proinflammatory stimuli. Significantly, they identify EC Rap1B as a potential novel vascular target in cancer immunotherapy.

Dual TLR9 and PD-L1 targeting unleashes dendritic cells to induce durable antitumor immunity

BACKGROUND

Although immune checkpoint inhibitors have been a breakthrough in clinical oncology, these therapies fail to produce durable responses in a significant fraction of patients. This lack of long-term efficacy may be due to a poor pre-existing network linking innate and adaptive immunity. Here, we present an antisense oligonucleotide (ASO)-based strategy that dually targets toll-like receptor 9 (TLR9) and programmed cell death ligand 1 (PD-L1), aiming to overcome resistance to anti-PD-L1 monoclonal therapy.

METHODS

We designed a high-affinity immunomodulatory IM-TLR9:PD-L1-ASO antisense oligonucleotide (hereafter, IM-T9P1-ASO) targeting mouse PD-L1 messenger RNA and activating TLR9. Then, we performed in vitro and in vivo studies to validate the IM-T9P1-ASO activity, efficacy, and biological effects in tumors and draining lymph nodes. We also performed intravital imaging to study IM-T9P1-ASO pharmacokinetics in the tumor.

RESULTS

IM-T9P1-ASO therapy, unlike PD-L1 antibody therapy, results in durable antitumor responses in multiple mouse cancer models. Mechanistically, IM-T9P1-ASO activates a state of tumor-associated dendritic cells (DCs), referred to here as DC3s, which have potent antitumor potential but express the PD-L1 checkpoint. IM-T9P1-ASO has two roles: it triggers the expansion of DC3s by engaging with TLR9 and downregulates PD-L1, thereby unleashing the antitumor functions of DC3s. This dual action leads to tumor rejection by T cells. The antitumor efficacy of IM-T9P1-ASO depends on the antitumor cytokine interleukin-12 (IL-12), produced by DC3s, and Batf3, a transcription factor required for DC development.

CONCLUSIONS

By simultaneously targeting TLR9 and PD-L1, IM-T9P1-ASO amplifies antitumor responses via DC activation, leading to sustained therapeutic efficacy in mice. By highlighting differences and similarities between mouse and human DCs, this study could serve to develop similar therapeutic strategies for patients with cancer.