Recharacterizing Tumor-Infiltrating Lymphocytes by Single-Cell RNA Sequencing

Integrated analysis of single-cell and bulk RNA sequencing data reveals a myeloid cell-related regulon predicting neoadjuvant immunotherapy response across cancers

BACKGROUND

Immunotherapy has brought about a paradigm shift in the treatment of cancer. However, the majority of patients exhibit resistance or become refractory to immunotherapy, and the underlying mechanisms remain to be explored.

METHODS

Sing-cell RNA sequencing (scRNA‑seq) datasets derived from 1 pretreatment and 1 posttreatment achieving pathological complete response (pCR) patient with lung adenocarcinoma (LUAD) who received neoadjuvant immunotherapy were collected, and pySCENIC was used to find the gene regulatory network (GRN) between cell types and immune checkpoint inhibitor (ICI) response. A regulon predicting ICI response was identified and validated using large‑scale pan-cancer data, including a colorectal cancer scRNA‑seq dataset, a breast cancer scRNA‑seq dataset, The Cancer Genome Atlas (TCGA) pan-cancer cohort, and 5 ICI transcriptomic cohorts. Symphony reference mapping was performed to construct the myeloid cell map.

RESULTS

Thirteen major cluster cell types were identified by comparing pretreatment and posttreatment patients, and the fraction of myeloid cells was higher in the posttreatment group (19.0% vs. 11.8%). A PPARG regulon (containing 23 target genes) was associated with ICI response, and its function was validated by a colorectal cancer scRNA‑seq dataset, a breast cancer scRNA‑seq dataset, TCGA pan-cancer cohort, and 5 ICI transcriptomic cohorts. Additionally, a myeloid cell map was developed, and cluster I, II, and III myeloid cells with high expression of PPARG were identified. Moreover, we constructed a website called PPARG ( https://pparg.online/PPARG/ or http://43.134.20.130:3838/PPARG/ ), which provides a powerful discovery tool and resource value for researchers.

CONCLUSIONS

The PPARG regulon is a predictor of ICI response. The myeloid cell map enables the identification of PPARG subclusters in public scRNA-seq datasets and provides a powerful discovery tool and resource value.

Unravelling immune microenvironment features underlying tumor progression in the single-cell era

The relationship between the immune cell and tumor occurrence and progression remains unclear. Profiling alterations in the tumor immune microenvironment (TIME) at high resolution is crucial to identify factors influencing cancer progression and enhance the effectiveness of immunotherapy. However, traditional sequencing methods, including bulk RNA sequencing, exhibit varying degrees of masking the cellular heterogeneity and immunophenotypic changes observed in early and late-stage tumors. Single-cell RNA sequencing (scRNA-seq) has provided significant and precise TIME landscapes. Consequently, this review has highlighted TIME cellular and molecular changes in tumorigenesis and progression elucidated through recent scRNA-seq studies. Specifically, we have summarized the cellular heterogeneity of TIME at different stages, including early, late, and metastatic stages. Moreover, we have outlined the related variations that may promote tumor occurrence and metastasis in the single-cell era. The widespread applications of scRNA-seq in TIME will comprehensively redefine the understanding of tumor biology and furnish more effective immunotherapy strategies.

SPP1+ TAM subpopulations in tumor microenvironment promote intravasation and metastasis of head and neck squamous cell carcinoma

Macrophages are heterogeneous cells that play multifaceted roles in cancer progression and metastasis. However, the phenotypic diversity of tumor-associated macrophages (TAMs) in head and neck squamous carcinomas (HNSCC) remains poorly characterized. Here, we comprehensively analyzed the HNSCC single-cell transcriptomic dataset (GSE172577) and identified 5 subsets of myeloid-driven cells as TAMs using Seurat. Deciphering the lineage trajectory of TAMs, we revealed that FCN1+ TAMs could give rise to pro-angiogenesis SPP1+CCL18+ and SPP1+FOLR2+ populations through SPP1-CCL18+ and CXCL9+CXCL10+ TAMs. SPP1+CCL18+ and SPP1+FOLR2+ TAMs harbored pro-angiogenic and metastatic transcriptional programs and were correlated with poor survival of HNSCC patients. Our immunostaining examination revealed that infiltration of SPP1+ TAMs is associated with lymph node metastasis and poor prognosis in patients with HNSCC. Cell-cell communication analysis implied that SPP1+ TAM populations may employ SPP1 signaling to activate metastasis-related ECs. In vitro and in vivo studies, we demonstrated that SPP1hi TAMs enhanced tumor intravasation and metastasis in HNSCC in a manner dependent on the secretion of SPP1, CCL18, and CXCL8. Taken together, our study characterized the cellular heterogeneity of TAM populations and identified two SPP1+ TAM populations that play key roles in HNSCC intravasation and metastasis and serve as predictive markers for patients with HNSCC.

From Genes to Therapy: Pituitary Adenomas in the Era of Precision Medicine

This review presents a comprehensive analysis of pituitary adenomas, a type of brain tumor with diverse behaviors and complexities. We cover various treatment approaches, including surgery, radiotherapy, chemotherapy, and their integration with newer treatments. Key to the discussion is the role of biomarkers in oncology for risk assessment, diagnosis, prognosis, and the monitoring of pituitary adenomas. We highlight advances in genomic, epigenomic, and transcriptomic analyses and their contributions to understanding the pathogenesis and molecular pathology of these tumors. Special attention is given to the molecular mechanisms, including the impact of epigenetic factors like histone modifications, DNA methylation, and transcriptomic changes on different subtypes of pituitary adenomas. The importance of the tumor immune microenvironment in tumor behavior and treatment response is thoroughly analyzed. We highlight potential breakthroughs and innovations for a more effective management and treatment of pituitary adenomas, while shedding light on the ongoing need for research and development in this field to translate scientific knowledge into clinical advancements, aiming to improve patient outcomes.

Advancing the frontiers of adaptive cell therapy: A transformative mechanistic journey from preclinical to clinical settings

Although the concept of using the patient's immune system to combat cancer has been around for a while, it is only in recent times that substantial progress has been achieved in this field. Over the last ten years, there has been a significant advancement in the treatment of cancer through immune checkpoint blockade. This treatment has been approved for multiple types of tumors. Another approach to modifying the immune system to detect tumor cells and fight them off is adaptive cell therapy (ACT). This therapy involves using T cells that have been modified with either T cell receptors (TCR) or chimeric antigen receptors (CAR) to target the tumor cells. ACT has demonstrated encouraging outcomes in different types of tumors, and clinical trials are currently underway worldwide to enhance this form of treatment. This review focuses on the advancements that have been made in ACT from preclinical to clinical settings till now.

A bioinformatic analysis of the role of TP53 status on the infiltration of CD8+ T cells into the tumor microenvironment

CD8+ T cells play basic roles in the immune system in a tumor microenvironment (TME) to fight cancer. Several reports have suggested signs of the involvement of tumor protein p53 (TP53) in a complex immune system network. Moreover, our previous research indicated that TP53 orchestrates the polarization and infiltration of macrophages into the TME. In the present study, the clinical function of TP53 status (wild/mutant) in CD8+ T cell infiltration was assessed using more than 10,000 The Cancer Genome Atlas (TCGA) samples from 30 cancer types through Tumor Immune Estimation (TIMER). Our investigation revealed that CD8+ T cell infiltration was higher in head and neck squamous cell carcinoma (HNSC) and uterine corpus endometrial carcinoma (UCEC) patients with wild-type TP53 than in those with mutant TP53. Wild-type TP53 conferred a good prognosis for HNSC and UCEC (P<0.05). In contrast, CD8+ T cell infiltration in lung adenocarcinoma (LUAD) patients with wild-type TP53 was much lower than in those with mutant TP53. Notably, clinical outcomes for LUAD with wild-type TP53 were poor (P<0.05). This study was the first to provide insights into the novel association of TP53 with CD8+ T cells infiltration in the TME in patients with HNSC, LUAD, and UCEC. Therefore, TP53 status acts as a prognostic marker, and this can be used as a basis to further study the effect of targeting TP53 in these patients. Furthermore, our study found that TP53 status was a reliable predictive factor and therapeutic target in patients with HNSC and UCEC.

Lung tumor-infiltrating Treg have divergent transcriptional profiles and function linked to checkpoint blockade response

Regulatory T cells (Treg) are conventionally viewed as suppressors of endogenous and therapy-induced antitumor immunity; however, their role in modulating responses to immune checkpoint blockade (ICB) is unclear. In this study, we integrated single-cell RNA-seq/T cell receptor sequencing (TCRseq) of >73,000 tumor-infiltrating Treg (TIL-Treg) from anti-PD-1-treated and treatment-naive non-small cell lung cancers (NSCLC) with single-cell analysis of tumor-associated antigen (TAA)-specific Treg derived from a murine tumor model. We identified 10 subsets of human TIL-Treg, most of which have high concordance with murine TIL-Treg subsets. Only one subset selectively expresses high levels of TNFRSF4 (OX40) and TNFRSF18 (GITR), whose engangement by cognate ligand mediated proliferative programs and NF-κB activation, as well as multiple genes involved in Treg suppression, including LAG3. Functionally, the OX40hiGITRhi subset is the most highly suppressive ex vivo, and its higher representation among total TIL-Treg correlated with resistance to PD-1 blockade. Unexpectedly, in the murine tumor model, we found that virtually all TIL-Treg-expressing T cell receptors that are specific for TAA fully develop a distinct TH1-like signature over a 2-week period after entry into the tumor, down-regulating FoxP3 and up-regulating expression of TBX21 (Tbet), IFNG, and certain proinflammatory granzymes. Transfer learning of a gene score from the murine TAA-specific TH1-like Treg subset to the human single-cell dataset revealed a highly analogous subcluster that was enriched in anti-PD-1-responding tumors. These findings demonstrate that TIL-Treg partition into multiple distinct transcriptionally defined subsets with potentially opposing effects on ICB-induced antitumor immunity and suggest that TAA-specific TIL-Treg may positively contribute to antitumor responses.

T cells in health and disease

T cells are crucial for immune functions to maintain health and prevent disease. T cell development occurs in a stepwise process in the thymus and mainly generates CD4⁺ and CD8⁺ T cell subsets. Upon antigen stimulation, naïve T cells differentiate into CD4⁺ helper and CD8⁺ cytotoxic effector and memory cells, mediating direct killing, diverse immune regulatory function, and long-term protection. In response to acute and chronic infections and tumors, T cells adopt distinct differentiation trajectories and develop into a range of heterogeneous populations with various phenotype, differentiation potential, and functionality under precise and elaborate regulations of transcriptional and epigenetic programs. Abnormal T-cell immunity can initiate and promote the pathogenesis of autoimmune diseases. In this review, we summarize the current understanding of T cell development, CD4⁺ and CD8⁺ T cell classification, and differentiation in physiological settings. We further elaborate the heterogeneity, differentiation, functionality, and regulation network of CD4⁺ and CD8⁺ T cells in infectious disease, chronic infection and tumor, and autoimmune disease, highlighting the exhausted CD8⁺ T cell differentiation trajectory, CD4⁺ T cell helper function, T cell contributions to immunotherapy and autoimmune pathogenesis. We also discuss the development and function of γδ T cells in tissue surveillance, infection, and tumor immunity. Finally, we summarized current T-cell-based immunotherapies in both cancer and autoimmune diseases, with an emphasis on their clinical applications. A better understanding of T cell immunity provides insight into developing novel prophylactic and therapeutic strategies in human diseases.

T cell receptor and B cell receptor exhibit unique signatures in tumor and adjacent non-tumor tissues of hepatocellular carcinoma

Background

The tumor microenvironment in hepatocellular carcinoma (HCC) is complicated. Tumor-infiltrating T and B cells play a pivotal role in anti-tumor immunity. T cell receptor (TCR) and B cell receptor (BCR) features may reflect the disease-associated antigen response.

Methods

By combining bulk TCR/BCR-sequencing, RNA-sequencing, whole exome-sequencing, and human leukocyte antigen-sequencing, we examined the immune repertoire (IR) features of tumor and adjacent non-tumor tissues obtained from 64 HCC patients.

Results

High IR heterogeneity with weak similarity was discovered between tumor and non-tumor tissues. Higher BCR diversity, richness, and somatic hypermutation (SHM) were found in non-tumor tissues, while TCRα and TCRβ diversity and richness were comparable or higher in tumor. Additionally, lower immune infiltration was found in tumor than non-tumor tissues; the microenvironment in tumor appeared to keep stably inhibited and changed slightly with tumor progression. Moreover, BCR SHM was stronger, whereas TCR/BCR diversity declined with HCC progression. Importantly, we found that higher IR evenness in tumor and lower TCR richness in non-tumor tissues indicated better survival in HCC patients. Collectively, the results revealed that TCR and BCR exhibited distinct features in tumor and non-tumor tissues.

Conclusions

We demonstrated that IR features vary between different tissues of HCC. IR features may represent a biomarker for the diagnosis and treatment of HCC patients, providing references for subsequent immunotherapy research and strategy selection.

Integrated analysis of single-cell RNA-seq and bulk RNA-seq unravels T cell-related prognostic risk model and tumor immune microenvironment modulation in triple-negative breast cancer

BACKGROUND

Triple negative breast cancer (TNBC) is an aggressive and fatal malignancy. The current success of tumor immunotherapy has focused attention on intermediate T-cell subsets and the tumor microenvironment, which are essential for activation of the anti-tumor response. Therefore, both areas require further research to accelerate progress in developing tailored immunotherapeutic approaches for patients with TNBC.

METHODS

We obtained scRNA-seq data of TNBC from the GEO database. A multiplex strategy was used to analyze and identify the T-cell heterogeneity of TNBC. By combining the METABRIC and GEO databases, a prognostic risk model for T-cell marker genes was constructed and validated. In addition, the immune-infiltrating cells of TNBC was analyzed using CIBERSORT, and the association between the risk model and response to immunotherapy was investigated.

RESULTS

Based on scRNA-seq data, 25,932 cells were identified for multiple analyzes. T cells were studied with a focus on 2 subtypes, including CD8⁺ and CD4⁺. There were also communication relationships between T cells and multiple cell types. The results of the enrichment analysis showed that the T-cell marker genes were focused in pathways related to the immune system. In addition, OPTN, TMEM176A, PKM and HES1 deserve attention as prognostic markers in TNBC. The immune infiltration results showed that the high-risk group had significant immune cell infiltration and immunosuppression status.

CONCLUSION

This study provides a resource for understanding T-cell heterogeneity and the associated prognostic risk model for TNBC. The results show that the model helps predict prognosis and response to treatment in breast cancer.

Single-Cell Analysis in Immuno-Oncology

The complexity of the cellular and non-cellular milieu surrounding human tumors plays a decisive role in the course and outcome of disease. The high variability in the distribution of the immune and non-immune compartments within the tumor microenvironments (TME) among different patients governs the mode of their response or resistance to current immunotherapeutic approaches. Through deciphering this diversity, one can tailor patients' management to meet an individual's needs. Single-cell (sc) omics technologies have given a great boost towards this direction. This review gathers recent data about how multi-omics profiling, including the utilization of single-cell RNA sequencing (scRNA-seq), assay for transposase-accessible chromatin with sequencing (scATAC-seq), T-cell receptor sequencing (scTCR-seq), mass, tissue-based, or microfluidics cytometry, and related bioinformatics tools, contributes to the high-throughput assessment of a large number of analytes at single-cell resolution. Unravelling the exact TCR clonotype of the infiltrating T cells or pinpointing the classical or novel immune checkpoints across various cell subsets of the TME provide a boost to our comprehension of adaptive immune responses, their antigen specificity and dynamics, and grant suggestions for possible therapeutic targets. Future steps are expected to merge high-dimensional data with tissue localization data, which can serve the investigation of novel multi-modal biomarkers for the selection and/or monitoring of the optimal treatment from the current anti-cancer immunotherapeutic armamentarium.

CD83 expression characterizes precursor exhausted T cell population

T cell exhaustion is a main obstacle against effective cancer immunotherapy. Exhausted T cells include a subpopulation that maintains proliferative capacity, referred to as precursor exhausted T cells (T_PEX). While functionally distinct and important for antitumor immunity, T_PEX possess some overlapping phenotypic features with the other T-cell subsets within the heterogeneous tumor-infiltrating T-lymphocytes (TIL). Here we explore surface marker profiles unique to T_PEX using the tumor models treated by chimeric antigen receptor (CAR)-engineered T cells. We find that CD83 is predominantly expressed in the CCR7⁺PD1⁺ intratumoral CAR-T cells compared with the CCR7^-PD1⁺ (terminally differentiated) and CAR-negative (bystander) T cells. The CD83⁺CCR7⁺ CAR-T cells exhibit superior antigen-induced proliferation and IL-2 production compared with the CD83^- T cells. Moreover, we confirm selective expression of CD83 in the CCR7⁺PD1⁺ T-cell population in primary TIL samples. Our findings identify CD83 as a marker to discriminate T_PEX from terminally exhausted and bystander TIL.

A senescence-based prognostic gene signature for colorectal cancer and identification of the role of SPP1-positive macrophages in tumor senescence

Background

Senescence is significantly associated with cancer prognosis. This study aimed to construct a senescence-related prognostic model for colorectal cancer (CRC) and to investigate the influence of senescence on the tumor microenvironment.

Methods

Transcriptome and clinical data of CRC cases were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Senescence-related prognostic genes detected by univariate Cox regression were included in Least Absolute Shrinkage and Selection Operator (LASSO) analysis to construct a model. The efficacy of the model was validated using the receiver operating characteristic (ROC) curve and survival analysis. Differentially expressed genes (DEGs) were identified and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were performed. CIBERSORT and Immuno-Oncology Biological Research (IOBR) were used to investigate the features of the tumor microenvironment. Single-cell RNA-seq data were used to investigate the expression levels of model genes in various cell types. Immunofluorescence staining for p21, SPP1, and CD68 was performed with human colon tissues.

Results

A seven-gene (PTGER2, FGF2, IGFBP3, ANGPTL4, DKK1, WNT16 and SPP1) model was finally constructed. Patients were classified as high- or low-risk using the median score as the threshold. The area under the ROC curve (AUC) for the 1-, 2-, and 3-year disease-specific survival (DSS) were 0.731, 0.651, and 0.643, respectively. Survival analysis showed a better 5-year DSS in low-risk patients in the construction and validation cohorts. GO and KEGG analyses revealed that DEGs were enriched in extracellular matrix (ECM)-receptor interactions, focal adhesion, and protein digestion and absorption. CIBERSORT and IOBR analyses revealed an abundance of macrophages and an immunosuppressive environment in the high-risk subgroup. Low-risk patients had higher response rates to immunotherapy than high-risk patients. ScRNA-seq data revealed high expression of SPP1 in a subset of macrophages with strong senescence-associated secretory phenotype (SASP) features. Using CRC tumor tissues, we discovered that SPP1⁺ macrophages were surrounded by a large number of senescent tumor cells in high-grade tumors.

Conclusion

Our study presents a novel model based on senescence-related genes that can identify CRC patients with a poor prognosis and an immunosuppressive tumor microenvironment. SPP1⁺ macrophages may correlate with cell senescence leading to poor prognosis.

Tumor infiltrating lymphocytes as an endpoint in cancer vaccine trials

Checkpoint inhibitors have invigorated cancer immunotherapy research, including cancer vaccination. Classic early phase trial design and endpoints used in developing chemotherapy are not suited for evaluating all forms of cancer treatment. Peripheral T cell response dynamics have demonstrated inconsistency in assessing the efficacy of cancer vaccination. Tumor infiltrating lymphocytes (TILs), reflect the local tumor microenvironment and may prove a superior endpoint in cancer vaccination trials. Cancer vaccines may also promote success in combination immunotherapy treatment of weakly immunogenic tumors. This review explores the impact of TILs as an endpoint for cancer vaccination in multiple malignancies, summarizes the current literature regarding TILs analysis, and discusses the challenges of providing validity and a standardized implementation of this approach.

Promising immunotherapeutic targets in lung cancer based on single-cell RNA sequencing

Immunotherapy has made great strides in the treatment of lung cancer, but a significant proportion of patients still do not respond to treatment. Therefore, the identification of novel targets is crucial to improving the response to immunotherapy. The tumor microenvironment (TME) is a complex niche composed of diverse pro-tumor molecules and cell populations, making the function and mechanism of a unique cell subset difficult to understand. However, the advent of single-cell RNA sequencing (scRNA-seq) technology has made it possible to identify cellular markers and understand their potential functions and mechanisms in the TME. In this review, we highlight recent advances emerging from scRNA-seq studies in lung cancer, with a particular focus on stromal cells. We elucidate the cellular developmental trajectory, phenotypic remodeling, and cell interactions during tumor progression. Our review proposes predictive biomarkers and novel targets for lung cancer immunotherapy based on cellular markers identified through scRNA-seq. The identification of novel targets could help improve the response to immunotherapy. The use of scRNA-seq technology could provide new strategies to understand the TME and develop personalized immunotherapy for lung cancer patients.

Single-cell transcriptome analysis of tumor immune microenvironment characteristics in colorectal cancer liver metastasis

BACKGROUND

Liver metastasis is the leading cause of death in colorectal cancer (CRC) patients, and the precise mechanisms remain unclear. In this study, single-cell RNA sequencing (scRNA-seq) was used to analyze the cellular and molecular heterogeneity between CRC primary lesion and corresponding liver metastasis, and to clarify the characteristics of the tumor microenvironment (TME) in synchronous liver metastasis of CRC.

METHODS

A case of microsatellite stable (MSS) sigmoid carcinoma with synchronous liver metastasis was selected, and tissues from the primary tumor and the liver metastasis were collected for scRNA-seq. The EdgeR package software was used to identify the differentially expressed genes between cells. Gene Set Enrichment Analysis (GSEA) was performed and the clusterProfiler R package was used for Gene Ontology (GO) enrichment analysis. The SCENIC and CellphoneDB packages were used to reconstruct the transcriptional regulatory networks and to analyze the intercellular interaction network, respectively.

RESULTS

Compared to the primary tumor, the proportion of myeloid cells in the metastatic tumor was significantly increased, while B cells and plasma cells were decreased. In the metastatic tumor, the myeloid-derived suppressor cell (MDSC) characteristic gene, mannose receptor C-type 1 (MRC1) and tumor associated macrophage 2 (TAM2)-related gene, were highly expressed. Furthermore, angiogenesis, oxidative phosphorylation, and endothelial mesenchymal transition (EMT) of myeloid cells were also significantly enhanced. There were less myeloid cells in primary tumors, and these were mainly monocytes and TAM1; while the number of TAM2 was significantly upregulated in the metastatic samples. In liver metastasis, the T cell population was exhausted, and this was accompanied by a significant increase in the number of CD4+ T cells and a decrease in the number of CD8+ T cells. Furthermore, some immune checkpoint molecules were highly expressed. Interactions between myeloid cells and other cell populations appeared to be strong.

CONCLUSIONS

The TME of CRC liver metastasis is significantly immunosuppressed. Interactions between myeloid cells and other cell populations in the TME contribute to the establishment of a pro-metastatic niche that promotes colonization and growth of CRC cells in the liver. TAMs may be a potential immunotherapeutic target for MSS CRC.

Divergent outcomes of anti-PD-L1 treatment coupled with host-intrinsic differences in TCR repertoire and distinct T cell activation states in responding versus non-responding tumors

Differential responses to immune checkpoint inhibitors (ICI) may be attributed to tumor-intrinsic factors or environmental cues; however, these mechanisms cannot fully explain the variable ICI responses in different individuals. Here, we investigate the potential contribution of immunological heterogeneity with a focus on differences in T-cell receptor (TCR) repertoire to ICI responses, which has not been defined previously. To reveal additional factors underlying heterogeneous responses to ICI, we employed a squamous cell carcinoma (SCC) mouse model in which tumor-bearing recipients unambiguously diverged into responders (R) or non-responders (NR) upon anti-PD-L1 treatment. Treatment efficacy absolutely required CD8 T-cells and correlated positively with effector functions of CD8 tumor-infiltrating lymphocytes (TILs). We showed that TCR repertoires exhibited a similar magnitude of clonal expansion in R vs. NR CD8 TILs. However, the top expanded TCR clonotypes appeared to be mutually exclusive between R and NR CD8 TILs, which also occurred in a recipient-specific manner, demonstrating preferential expansion of distinct TCR clonotypes against the same SCC tumor. Unexpectedly, R vs. NR CD8 TILs reached all activation clusters and did not exhibit substantial global differences in transcriptomes. By linking single-cell transcriptomic data with unique TCR clonotypes, CD8 TILs harboring top TCR clonotypes were found to occupy distinct activation clusters and upregulate genes favoring anti-tumor immunity to different extents in R vs. NR. We conclude that stochastic differences in CD8 TIL TCR repertoire and distinct activation states of top TCR clonotypes may contribute to differential anti-PD-L1 responses. Our study suggests that host-intrinsic immunological heterogeneity may offer a new explanation for differential ICI responses in different individuals, which could impact on strategies for personalized cancer immunotherapy.

Integrated Single-Cell and RNA Sequencing Analysis Identifies Key Immune Cell and Dendritic Cells Associated Genes Participated in Myocarditis

Myocarditis is a complex disease characterized by myocardial inflammatory cell infiltration. The purpose of our study was to investigate the gene and single-cell signature to explore the involvement of immune cells in myocarditis. Gene expressions merged from GSE35182 and GSE35182 datasets were subjected to differential expression gene (DEG) analysis and PPI network construction. The correlation analysis of DEGs with immune cell infiltration was performed. Single-cell RNA sequencing (scRNA-seq) was downloaded from GSE174458. A total of 58 DEGs were identified, including 51 DEGs upregulated and 7 DEGs downregulated in the myocarditis group compared with the control group. GO and KEGG enrichment analyses revealed that myocarditis triggered DEGs mainly involved in immune-related processes and pathways. PPI network analysis identified 20 central hub genes. Occurrence of myocarditis induced significant enrichment of conventional dendritic cell 2 (cDC2), plasmacytoid DC, and plasma cell in myocardial tissue. Mmp12, Gpnmb, and Atp6v0d2 expressions were positively correlated with cDC abundance, of which only Mmp1 and Gpnmb were shared with hub gene list. A total of 20972 cells in scRNA-seq yielded 26 cell clusters and annotated 9 cell types, including fibroblasts, neutrophils, stromal cells, monocytes, basophils, B cells, natural killer T cells, innate lymphoid cells, and T cells, and only proportion of natural killer T cells and monocytes were higher in the myocarditis than in control. Monocytes annotated 3 subclusters including DC, macrophage, and monocytes. Hub genes of Ctss, Mpeg1, Cybb, H2-Ab1, Ly86, CD74, and Lgals3 were highly expressed in monocytes cluster. Among DC-correlated DEGs, Mmp12 was mainly expressed in monocyte cluster, and Gpnmb was mainly expressed in fibroblast cluster, whereas Atp6v0d2 expression has a weaker signal and weaker cell preference. In conclusion, DC infiltration and its associated pivotal genes may be responsible for progression of myocarditis. Our study expands and provides novel information on the immune cell engagement of myocarditis.

Advances in precise single-cell capture for analysis and biological applications

Cells are the basic structural and functional units of living organisms. However, conventional cell analysis only averages millions of cell populations, and some important information is lost. It is essential to quantitatively characterize the physiology and pathology of single-cell activities. Precise single-cell capture is an extremely challenging task during cell sample preparation. In this review, we summarize the category of technologies to capture single cells precisely with a focus on the latest development in the last five years. Each technology has its own set of benefits and specific challenges, which provide opportunities for researchers in different fields. Accordingly, we introduce the applications of captured single cells in cancer diagnosis, analysis of metabolism and secretion, and disease treatment. Finally, some perspectives are provided on the current development trends, future research directions, and challenges of single-cell capture.

Characterizing the landscape of cervical squamous cell carcinoma immune microenvironment by integrating the single-cell transcriptomics and RNA-Seq

Background

Cervical squamous cell carcinoma (CSCC), caused by the infection of high‐risk human papillomavirus, is one of the most common malignancies in women worldwide.

Methods

RNA expression data, including those from the Cancer Genome Atlas, Gene Expression Omnibus, and Genotype‐Tissue Expression databases, were used to identify the expression of RNAs in normal and tumor tissue. Correlation analysis was performed to identify the immune‐related long noncoding RNAs (IRLs) and hypoxia‐related genes (IRHs) that can influence the activity of the immune system. Prognosis models of immune‐related RNAs (IRRs) were used to construct a coexpression network of the immune system. We identified the role of IRRs in immunotherapy by correlation analysis with immune checkpoint genes (ICGs). We then validated the expression data by integrating two single‐cell sequencing data sets of CSCC to identify the key immune features.

Results

In total, six immune‐related gene (IRG), four IRL, and five IRH signatures that can significantly influence the characteristics of the tumor immune microenvironment (TIME) were selected using machine learning methods. The expression level of ICGs was significantly upregulated in GZMB⁺CD8⁺ T‐cells and tumor‐associated macrophages (TAMs) in tumor tissues. TGFBI⁺ TAMs are a kind of blood‐derived monocyte‐derived M0‐like TAM linked to hypoxia and a poor prognosis. IFI30⁺ M1‐like TAMs participate in the process of immune‐regulation and showed a role in the promotion of CD8⁺ T‐cells and Type 1 T helper (Th1)/Th2 cells in the coexpression network, together with several IRLs, IRGs, and ICGs.

Conclusions

CD16⁺ monocyte‐derived IFI30⁺ TAMs participated in our coexpression network to regulate the TIME, showing the potential to be a novel immunotherapy target. The enrichment of M0‐like TAMs was associated with a worse prognosis in the high‐risk score group with IRH signatures. Remarkably, M0‐like TAMs in tumor tissues overexpressed TGFBI and were associated with several well‐known tumor‐proliferation pathways.

Single-Cell Atlas of Lineage States, Tumor Microenvironment, and Subtype-Specific Expression Programs in Gastric Cancer

Gastric cancer heterogeneity represents a barrier to disease management. We generated a comprehensive single-cell atlas of gastric cancer (>200,000 cells) comprising 48 samples from 31 patients across clinical stages and histologic subtypes. We identified 34 distinct cell-lineage states including novel rare cell populations. Many lineage states exhibited distinct cancer-associated expression profiles, individually contributing to a combined tumor-wide molecular collage. We observed increased plasma cell proportions in diffuse-type tumors associated with epithelial-resident KLF2 and stage-wise accrual of cancer-associated fibroblast subpopulations marked by high INHBA and FAP coexpression. Single-cell comparisons between patient-derived organoids (PDO) and primary tumors highlighted inter- and intralineage similarities and differences, demarcating molecular boundaries of PDOs as experimental models. We complemented these findings by spatial transcriptomics, orthogonal validation in independent bulk RNA-sequencing cohorts, and functional demonstration using in vitro and in vivo models. Our results provide a high-resolution molecular resource of intra- and interpatient lineage states across distinct gastric cancer subtypes.

SIGNIFICANCE

We profiled gastric malignancies at single-cell resolution and identified increased plasma cell proportions as a novel feature of diffuse-type tumors. We also uncovered distinct cancer-associated fibroblast subtypes with INHBA-FAP-high cell populations as predictors of poor clinical prognosis. Our findings highlight potential origins of deregulated cell states in the gastric tumor ecosystem. This article is highlighted in the In This Issue feature, p. 587.

An artificial intelligence method to assess the tumor microenvironment with treatment outcomes for gastric cancer patients after gastrectomy

Background

The tumor microenvironment (TME) plays an important role in the occurrence and development of gastric cancer (GC) and is widely used to assess the treatment outcomes of GC patients. Immunohistochemistry (IHC) and gene sequencing are the main analysis methods for the TME but are limited due to the subjectivity of observers, the high cost of equipment and the need for professional analysts.

Methods

The ImmunoScore (IS) was developed in the TCGA cohort and validated in GEO cohorts. The Radiomic ImmunoScore (RIS) was developed in the TCGA cohort and validated in the Nanfang cohort. A nomogram was developed and validated in the Nanfang cohort based on RIS and clinical features.

Results

For IS, the area under the curves (AUCs) were 0.798 for 2-year overall survival (OS) and 0.873 for 4-year overall survival. For RIS, in the TCGA cohort, the AUCs distinguishing High-IS or Low-IS and predicting prognosis were 0.85 and 0.81, respectively; in the Nanfang cohort, the AUC predicting prognosis was 0.72. The nomogram performed better than the TNM staging system according to the ROC curve (all P < 0.01). Patients with TNM stage II and III in the High-nomogram group were more likely to benefit from adjuvant chemotherapy than Low-nomogram group patients.

Conclusions

The RIS and the nomogram can be used to assess the TME, prognosis and adjuvant chemotherapy benefit of GC patients after radical gastrectomy and are valuable additions to the current TNM staging system. High-nomogram GC patients may benefit more from adjuvant chemotherapy than Low-nomogram GC patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03298-7.

High-Throughput immunogenetics for precision medicine in cancer

Cancer is characterized by an extremely complex biological background, which hinders personalized therapeutic interventions. Precision medicine promises to overcome this obstacle through integrating information from different 'subsystems', including the host, the external environment, the tumor itself and the tumor micro-environment. Immunogenetics is an essential tool that allows dissecting both lymphoid cancer ontogeny at both a cell-intrinsic and a cell-extrinsic level, i.e. through characterizing micro-environmental interactions, with a view to precision medicine. This is particularly thanks to the introduction of powerful, high-throughput approaches i.e. next generation sequencing, which allow the comprehensive characterization of immune repertoires. Indeed, NGS immunogenetic analysis (Immune-seq) has emerged as key to both understanding cancer pathogenesis and improving the accuracy of clinical decision making in oncology. Immune-seq has applications in lymphoid malignancies, assisting in the diagnosis e.g. through differentiating from reactive conditions, as well as in disease monitoring through accurate assessment of minimal residual disease. Moreover, Immune-seq facilitates the study of T cell receptor clonal dynamics in critical clinical contexts, including transplantation as well as innovative immunotherapy for solid cancers. The clinical utility of Immune-seq represents the focus of the present contribution, where we highlight what can be achieved but also what must be addressed in order to maximally realize the promise of Immune-seq in precision medicine in cancer.

Crosstalk Between the Tumor Microenvironment and Cancer Cells: A Promising Predictive Biomarker for Immune Checkpoint Inhibitors

Immune checkpoint inhibitors (ICIs) have changed the landscape of cancer treatment and are emerging as promising curative treatments in different type of cancers. However, only a small proportion of patients have benefited from ICIs and there is an urgent need to find robust biomarkers for individualized immunotherapy and to explore the causes of immunotherapy resistance. In this article, we review the roles of immune cells in the tumor microenvironment (TME) and discuss the effects of ICIs on these cell populations. We discuss the potential of the functional interaction between the TME and cancer cells as a predictive biomarker for ICIs. Furthermore, we outline the potential personalized strategies to improve the effectiveness of ICIs with precision.

Single-cell sequencing reveals antitumor characteristics of intratumoral immune cells in old mice

Background

Aging has long been thought to be a major risk factor for various types of cancers. However, accumulating evidence indicates increased resistance of old animals to tumor growth. An in-depth understanding of how old individuals defend against tumor invasion requires further investigations.

Methods

We revealed age-associated alterations in tumor-infiltrating immune cells between young and old mice using single-cell RNA and coupled T cell receptor (TCR) sequencing analysis. Multiple bioinformatics methods were adopted to analyze the characteristics of the transcriptome between two groups. To explore the impacts of young and old CD8⁺ T cells on tumor growth, mice were treated with anti-CD8 antibody every 3 days starting 7 days after tumor inoculation. Flow cytometry was used to validate the differences indicated by sequencing analysis between young and old mice.

Results

We found a higher proportion of cytotoxic CD8⁺ T cells, naturally occurring Tregs, conventional dendritic cell (DC), and M1-like macrophages in tumors of old mice compared with a higher percentage of exhausted CD8⁺ T cells, induced Tregs, plasmacytoid DC, and M2-like macrophages in young mice. Importantly, TCR diversity analysis showed that top 10 TCR clones consisted primarily of exhausted CD8⁺ T cells in young mice whereas top clones were predominantly cytotoxic CD8⁺ T cells in old mice. Old mice had more CD8⁺ T cells with a ‘progenitor’ and less ‘terminally’ exhausted phenotypes than young mice. Consistently, trajectory inference demonstrated that CD8⁺ T cells preferentially differentiated into cytotoxic cells in old mice in contrast to exhausted cells in young mice. Importantly, elimination of CD8⁺ T cells in old mice during tumor growth significantly accelerated tumor development. Moreover, senescent features were demonstrated in exhausted but not cytotoxic CD8⁺ T cells regardless of young and old mice.

Conclusions

Our data revealed that a significantly higher proportion of effector immune cells in old mice defends against tumor progression, providing insights into understanding the altered kinetics of cancer development and the differential response to immunotherapeutic modulation in elderly patients.

Overcoming Resistance to Immunotherapy in Advanced Cutaneous Squamous Cell Carcinoma

Cutaneous squamous cell carcinoma (CSCC) is the second most frequent cancer in humans, and is now responsible for as many deaths as melanoma. Immunotherapy has changed the therapeutic landscape of advanced CSCC after the FDA approval of anti-PD1 molecules for the treatment of locally advanced and metastatic CSCC. However, roughly 50% of patients will not respond to this systemic treatment and even those who do respond can develop resistance over time. The etiologies of primary and secondary resistance to immunotherapy involve changes in the neoplastic cells and the tumor microenvironment. Indirect modulation of immune system activation with new therapies, such as vaccines, oncolytic viruses, and new immunotherapeutic agents, and direct modulation of tumor immunogenicity using other systemic treatments or radiotherapy are now under evaluation in combined regimens. The identification of predictors of response is an important area of research. In this review, we focus on the features associated with the response to immunotherapy, and the evaluation of combination treatments and new molecules, a more thorough knowledge of which is likely to improve the survival of patients with advanced CSCC.

Prognostic Value and Immunological Characteristics of a Novel RNA Binding Protein Signature in Cutaneous Melanoma

Background

The existing studies indicate that RNA binding proteins (RBPs) are closely correlated with the genesis and development of cancers. However, the role of RBPs in cutaneous melanoma remains largely unknown. Therefore, the present study aims to establish a reliable prognostic signature based on RBPs to distinguish cutaneous melanoma patients with different prognoses and investigate the immune infiltration of patients.

Methods

After screening RBPs from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, Cox and least absolute shrinkage and selection operator (LASSO) regression analysis were then used to establish a prediction model. The relationship between the signature and the abundance of immune cell types, the tumor microenvironment (TME), immune-related pathways, and immune checkpoints were also analyzed.

Results

In total, 7 RBPs were selected to establish the prognostic signature. Patients categorized as a high-risk group demonstrated worse overall survival (OS) rates compared to those of patients categorized as a low-risk group. The signature was validated in an independent external cohort and indicated a promising prognostic ability. Further analysis indicated that the signature wasan independent prognostic indicator in cutaneous melanoma. A nomogram combining risk score and clinicopathological features was then established to evaluate the 3- and 5-year OS in cutaneous melanoma patients. Analyses of immune infiltrating, the TME, immune checkpoint, and drug susceptibility revealed significant differences between the two groups. GSEA analysis revealed that basal cell carcinoma, notch signaling pathway, melanogenesis pathways were enriched in the high-risk group, resulting in poor OS.

Conclusion

We established and validated a robust 7-RBP signature that could be a potential biomarker to predict the prognosis and immunotherapy response of cutaneous melanoma patients, which provides new insights into cutaneous melanoma immunotherapeutic strategies.

Tumor Expression Profile Analysis Developed and Validated a Prognostic Model Based on Immune-Related Genes in Bladder Cancer

Background: Bladder cancer (BLCA) ranks 10th in incidence among malignant tumors and 6th in incidence among malignant tumors in males. With the application of immune therapy, the overall survival (OS) rate of BLCA patients has greatly improved, but the 5-year survival rate of BLCA patients is still low. Furthermore, not every BLCA patient benefits from immunotherapy, and there are a limited number of biomarkers for predicting the immunotherapy response. Therefore, novel biomarkers for predicting the immunotherapy response and prognosis of BLCA are urgently needed.

Methods: The RNA sequencing (RNA-seq) data, clinical data and gene annotation files for The Cancer Genome Atlas (TCGA) BLCA cohort were extracted from the University of California, Santa Cruz (UCSC) Xena Browser. The BLCA datasets GSE31684 and GSE32894 from the Gene Expression Omnibus (GEO) database were extracted for external validation. Immune-related genes were extracted from InnateDB. Significant differentially expressed genes (DEGs) were identified using the R package “limma,” and Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis for the DEGs were performed using R package “clusterProfiler.” Least absolute shrinkage and selection operator (LASSO) regression analysis were used to construct the signature model. The infiltration level of each immune cell type was estimated using the single-sample gene set enrichment analysis (ssGSEA) algorithm. The performance of the model was evaluated with receiver operating characteristic (ROC) curves and calibration curves.

Results: In total, 1,040 immune-related DEGs were identified, and eight signature genes were selected to construct a model using LASSO regression analysis. The risk score of BLCA patients based on the signature model was negatively correlated with OS and the immunotherapy response. The ROC curve for OS revealed that the model had good accuracy. The calibration curve showed good agreement between the predictions and actual observations.

Conclusions: Herein, we constructed an immune-related eight-gene signature that could be a potential biomarker to predict the immunotherapy response and prognosis of BLCA patients.

Identification and validation of a ferroptosis-related gene signature predictive of prognosis in breast cancer

Ferroptosis, a novel form of regulated cell death, is closely associated with the occurrence and development of malignant tumors. Here, we utilized a bioinformatics approach to identify ferroptosis-related genes to establish a robust and reliable prognostic signature in breast cancer (BC). Univariate Cox regression and LASSO regression analyses of patient's survival and gene expression data identified a prognostic signature consisting of 10 ferroptosis-related genes (FRGs). The signature demonstrated a favorable prediction performance, and was validated in two independent datasets, GSE21653 and GSE25066. Analyses of immune infiltrates, tumor microenvironment, immune checkpoints, mutations, drug sensitivity, and clinicopathological features revealed significant differences between low- and high-risk BC patients. A multivariate analysis revealed that the signature was an independent prognostic predictor in BC, and a nomogram combining the risk score and tumor stage intuitively displayed high accuracy and reliability with respect to predicting the survival outcomes of BC patients. These findings indicate that the identified prognostic signature is a potential indicator predictive of prognosis and immunotherapeutic responses in BC patients.

Moving pan-cancer studies from basic research toward the clinic

Although all cancers share common hallmarks, we have long realized that there is no silver-bullet treatment for the disease. Many clinical oncologists specialize in a single cancer type, based predominantly on the tissue of origin. With advances brought by genetics and cancer genomic research, we now know that cancers are profoundly different, both in origins and in genetic alterations. At the same time, commonalities such as key driver mutations, altered pathways, mutational, immune and microbial signatures and other areas (many revealed by pan-cancer studies) point to the intriguing possibility of targeting common traits across diverse cancer types with the same therapeutic strategies. Studies designed to delineate differences and similarities across cancer types are thus critical in discerning the basic dynamics of oncogenesis, as well as informing diagnoses, prognoses and therapies. We anticipate growing emphases on the development and application of therapies targeting underlying commonalities of different cancer types, while tailoring to the unique tissue environment and intrinsic molecular fingerprints of each cancer type and subtype. Here we summarize the facets of pan-cancer research and how they are pushing progress toward personalized medicine.

MultiK: an automated tool to determine optimal cluster numbers in single-cell RNA sequencing data

Single-cell RNA sequencing (scRNA-seq) provides new opportunities to characterize cell populations, typically accomplished through some type of clustering analysis. Estimation of the optimal cluster number (K) is a crucial step but often ignored. Our approach improves most current scRNA-seq cluster methods by providing an objective estimation of the number of groups using a multi-resolution perspective. MultiK is a tool for objective selection of insightful Ks and achieves high robustness through a consensus clustering approach. We demonstrate that MultiK identifies reproducible groups in scRNA-seq data, thus providing an objective means to estimating the number of possible groups or cell-type populations present.

Cancer biology deciphered by single-cell transcriptomic sequencing

Tumors are complex ecosystems in which heterogeneous cancer cells interact with their microenvironment composed of diverse immune, endothelial, and stromal cells. Cancer biology had been studied using bulk genomic and gene expression profiling, which however mask the cellular diversity and average the variability among individual molecular programs. Recent advances in single-cell transcriptomic sequencing have enabled a detailed dissection of tumor ecosystems and promoted our understanding of tumorigenesis at single-cell resolution. In the present review, we discuss the main topics of recent cancer studies that have implemented single-cell RNA sequencing (scRNA-seq). To study cancer cells, scRNA-seq has provided novel insights into the cancer stem-cell model, treatment resistance, and cancer metastasis. To study the tumor microenvironment, scRNA-seq has portrayed the diverse cell types and complex cellular states of both immune and non-immune cells interacting with cancer cells, with the promise to discover novel targets for future immunotherapy.

Tumor immunology in the age of single-cell genomics

Immunotherapies that were developed based on our understandings of tumor immunology have revolutionized cancer treatment. However, the success of immunotherapy is eclipsed by several grand challenges, including low response rate, intrinsic/acquired resistance and adverse effects. While a deeper understanding of the interaction between tumor and our immune system, especially the tumor immune niche, is essential to overcome those challenges, we are limited by the fact that most of our knowledge about tumor immunology is based on studies analyzing bulk populations of cells, which are often unable to fully characterize the various cell types and states engaged in immune cell functions. The advent of cutting single-cell genomic technologies empowers us to dissect the tumor immune niche in a genome-wide and spatially resolved manner in single cells, trace their clonal histories, and unveil their regulatory circuits. Future studies on tumor immunology in the age of single-cell genomics, therefore, hold the promise to develop more effective and precise immunotherapies for human cancers. In this perspective, we will discuss how advanced single-cell genomics approaches will revolutionize tumor immunology research and immunotherapies by catering the demand in the field of tumor immunology.

Applications of single-cell sequencing in cancer research: progress and perspectives

Single-cell sequencing, including genomics, transcriptomics, epigenomics, proteomics and metabolomics sequencing, is a powerful tool to decipher the cellular and molecular landscape at a single-cell resolution, unlike bulk sequencing, which provides averaged data. The use of single-cell sequencing in cancer research has revolutionized our understanding of the biological characteristics and dynamics within cancer lesions. In this review, we summarize emerging single-cell sequencing technologies and recent cancer research progress obtained by single-cell sequencing, including information related to the landscapes of malignant cells and immune cells, tumor heterogeneity, circulating tumor cells and the underlying mechanisms of tumor biological behaviors. Overall, the prospects of single-cell sequencing in facilitating diagnosis, targeted therapy and prognostic prediction among a spectrum of tumors are bright. In the near future, advances in single-cell sequencing will undoubtedly improve our understanding of the biological characteristics of tumors and highlight potential precise therapeutic targets for patients.

Insights Gained from Single-Cell Analysis of Immune Cells in the Tumor Microenvironment

Understanding tumor immune microenvironments is critical for identifying immune modifiers of cancer progression and developing cancer immunotherapies. Recent applications of single-cell RNA sequencing (scRNA-seq) in dissecting tumor microenvironments have brought important insights into the biology of tumor-infiltrating immune cells, including their heterogeneity, dynamics, and potential roles in both disease progression and response to immune checkpoint inhibitors and other immunotherapies. This review focuses on the advances in knowledge of tumor immune microenvironments acquired from scRNA-seq studies across multiple types of human tumors, with a particular emphasis on the study of phenotypic plasticity and lineage dynamics of immune cells in the tumor environment. We also discuss several imminent questions emerging from scRNA-seq observations and their potential solutions on the horizon.

Current and Future Perspectives of PD-1/PDL-1 Blockade in Cancer Immunotherapy

Cancer immunotherapy, which reactivates weakened immune cells of cancer patients, has yielded great success in recent years. Among immunotherapeutic agents, immune checkpoint inhibitors have been of particular interest and have gained approval by the FDA for treatment of cancers. Immune checkpoint blockade through targeting programmed cell death protein-1 (PD-1) has demonstrated promising antitumor effects in cancer immunotherapy of many different solid and hematologic malignancies. However, despite promising results, a favorable response is observed only in a fraction of patients, and there is still lack of a single therapy modality with curative ability. In this paper, we review the current and future perspectives of PD-1/L1 blockade in cancer immunotherapy, with a particular focus on predictive biomarkers of response to therapy. We also discuss the adverse events associated with PD-1/L1/2 inhibitors, ranging from severe life-threatening conditions such as autoimmune myocarditis to mild and moderate reactions such as skin rashes, and explore the potential strategies for improving the efficacy of immunotherapy with PD-1/L1 checkpoint inhibitors.

Regulatory T Cells in the Tumor Microenvironment

Regulatory T cells (T_regs) are an immunosuppressive subpopulation of CD4⁺ T cells that are endowed with potent suppressive activity and function to limit immune activation and maintain homeostasis. These cells are identified by the hallmark transcription factor FOXP3 and the high-affinity interleukin-2 (IL-2) receptor chain CD25. T_regs can be recruited to and persist within the tumor microenvironment (TME), acting as a potent barrier to effective antitumor immunity. This chapter will discuss [i] the history and hallmarks of T_regs; [ii] the recruitment, development, and persistence of T_regs within the TME; [iii] T_reg function within TME; asnd [iv] the therapeutic targeting of T_regs in the clinic. This chapter will conclude with a discussion of likely trends and future directions.

Differences in TCR repertoire and T cell activation underlie the divergent outcomes of antitumor immune responses in tumor-eradicating versus tumor-progressing hosts

Background

Antitumor immunity is highly heterogeneous between individuals; however, underlying mechanisms remain elusive, despite their potential to improve personalized cancer immunotherapy. Head and neck squamous cell carcinomas (HNSCCs) vary significantly in immune infiltration and therapeutic responses between patients, demanding a mouse model with appropriate heterogeneity to investigate mechanistic differences.

Methods

We developed a unique HNSCC mouse model to investigate underlying mechanisms of heterogeneous antitumor immunity. This model system may provide a better control for tumor-intrinsic and host-genetic variables, thereby uncovering the contribution of the adaptive immunity to tumor eradication. We employed single-cell T-cell receptor (TCR) sequencing coupled with single-cell RNA sequencing to identify the difference in TCR repertoire of CD8 tumor-infiltrating lymphocytes (TILs) and the unique activation states linked with different TCR clonotypes.

Results

We discovered that genetically identical wild-type recipient mice responded heterogeneously to the same squamous cell carcinoma tumors orthotopically transplanted into the buccal mucosa. While tumors initially grew in 100% of recipients and most developed aggressive tumors, ~25% of recipients reproducibly eradicated tumors without intervention. Heterogeneous antitumor responses were dependent on CD8 T cells. Consistently, CD8 TILs in regressing tumors were significantly increased and more activated. Single-cell TCR-sequencing revealed that CD8 TILs from both growing and regressing tumors displayed evidence of clonal expansion compared with splenic controls. However, top TCR clonotypes and TCR specificity groups appear to be mutually exclusive between regressing and growing TILs. Furthermore, many TCRα/TCRβ sequences only occur in one recipient. By coupling single-cell transcriptomic analysis with unique TCR clonotypes, we found that top TCR clonotypes clustered in distinct activation states in regressing versus growing TILs. Intriguingly, the few TCR clonotypes shared between regressors and progressors differed greatly in their activation states, suggesting a more dominant influence from tumor microenvironment than TCR itself on T cell activation status.

Conclusions

We reveal that intrinsic differences in the TCR repertoire of TILs and their different transcriptional trajectories may underlie the heterogeneous antitumor immune responses in different hosts. We suggest that antitumor immune responses are highly individualized and different hosts employ different TCR specificities against the same tumors, which may have important implications for developing personalized cancer immunotherapy.

Single-Cell Analyses Inform Mechanisms of Myeloid-Targeted Therapies in Colon Cancer

Single-cell RNA sequencing (scRNA-seq) is a powerful tool for defining cellular diversity in tumors, but its application toward dissecting mechanisms underlying immune-modulating therapies is scarce. We performed scRNA-seq analyses on immune and stromal populations from colorectal cancer patients, identifying specific macrophage and conventional dendritic cell (cDC) subsets as key mediators of cellular cross-talk in the tumor microenvironment. Defining comparable myeloid populations in mouse tumors enabled characterization of their response to myeloid-targeted immunotherapy. Treatment with anti-CSF1R preferentially depleted macrophages with an inflammatory signature but spared macrophage populations that in mouse and human expresses pro-angiogenic/tumorigenic genes. Treatment with a CD40 agonist antibody preferentially activated a cDC population and increased Bhlhe40⁺ Th1-like cells and CD8⁺ memory T cells. Our comprehensive analysis of key myeloid subsets in human and mouse identifies critical cellular interactions regulating tumor immunity and defines mechanisms underlying myeloid-targeted immunotherapies currently undergoing clinical testing.

Plasma-derived extracellular vesicle analysis and deconvolution enable prediction and tracking of melanoma checkpoint blockade outcome

Immune checkpoint inhibitors (ICIs) show promise, but most patients do not respond. We identify and validate biomarkers from extracellular vesicles (EVs), allowing non-invasive monitoring of tumor- intrinsic and host immune status, as well as a prediction of ICI response. We undertook transcriptomic profiling of plasma-derived EVs and tumors from 50 patients with metastatic melanoma receiving ICI, and validated with an independent EV-only cohort of 30 patients. Plasma-derived EV and tumor transcriptomes correlate. EV profiles reveal drivers of ICI resistance and melanoma progression, exhibit differentially expressed genes/pathways, and correlate with clinical response to ICI. We created a Bayesian probabilistic deconvolution model to estimate contributions from tumor and non-tumor sources, enabling interpretation of differentially expressed genes/pathways. EV RNA-seq mutations also segregated ICI response. EVs serve as a non-invasive biomarker to jointly probe tumor-intrinsic and immune changes to ICI, function as predictive markers of ICI responsiveness, and monitor tumor persistence and immune activation.

Tumor-infiltrating lymphocytes: Warriors fight against tumors powerfully

Tumor-infiltrating lymphocytes (TILs) are infiltrating lymphocytes in tumor tissues. After isolation, screening and amplification in vitro, they will be implanted into patients and play a specific killing effect on tumors. Since TILs have not been genetically modified and come from the body of patients, there will be relatively few adverse reactions. This is also the advantage of TIL treatment. In recent years, its curative effect on solid tumors began to show its sharpness. However, due to the limitations of the immune microenvironment and the mutation of antigens, TIL's development was slowed down. This article reviews the research progress, biological characteristics, preparation and methods of enhancing the therapeutic effect of tumor-infiltrating lymphocytes, their roles in different tumors and prognosis, and emphasizes the important value of tumor-infiltrating lymphocytes in anti-tumor.

Immune landscape and biomarkers for immuno-oncology in colorectal cancers

Recent advances in immuno-oncology have increased understanding of the tumor immune microenvironment (TIME), and clinical trials for immune checkpoint inhibitor treatment have shown remission and/or durable response in certain proportions of patients stratified by predictive biomarkers. The TIME in colorectal cancer (CRC) was initially evaluated several decades ago. The prognostic value of the immune response to tumors, including tumor-infiltrating lymphocytes, peritumoral lymphoid reaction, and Crohn's-like lymphoid reaction, has been well demonstrated. In this review, we describe the chronology of TIME research and review the up-to-date high-dimensional TIME landscape of CRC. We also summarize the clinical relevance of several biomarkers associated with immunotherapy in CRC, such as microsatellite instability, tumor mutational burden, POLE/POLD mutation, consensus molecular subtype, and programmed death-ligand 1 expression.

Leveraging Public Single-Cell and Bulk Transcriptomic Datasets to Delineate MAIT Cell Roles and Phenotypic Characteristics in Human Malignancies

Mucosa-associated invariant T (MAIT) cells are unconventional, innate-like T lymphocytes that recognize vitamin B metabolites of microbial origin among other antigens displayed by the monomorphic molecule MHC class I-related protein 1 (MR1). Abundant in human tissues, reactive to local inflammatory cues, and endowed with immunomodulatory and cytolytic functions, MAIT cells are likely to play key roles in human malignancies. They accumulate in various tumor microenvironments (TMEs) where they often lose some of their functional capacities. However, the potential roles of MAIT cells in anticancer immunity or cancer progression and their significance in shaping clinical outcomes remain largely unknown. In this study, we analyzed publicly available bulk and single-cell tumor transcriptomic datasets to investigate the tissue distribution, phenotype, and prognostic significance of MAIT cells across several human cancers. We found that expanded MAIT cell clonotypes were often shared between the blood, tumor tissue and adjacent healthy tissue of patients with colorectal, hepatocellular, and non-small cell lung carcinomas. Gene expression comparisons between tumor-infiltrating and healthy tissue MAIT cells revealed the presence of activation and/or exhaustion programs within the TMEs of primary hepatocellular and colorectal carcinomas. Interestingly, in basal and squamous cell carcinomas of the skin, programmed cell death-1 (PD-1) blockade upregulated the expression of several effector genes in tumor-infiltrating MAIT cells. We derived a signature comprising stable and specific MAIT cell gene markers across several tissue compartments and cancer types. By applying this signature to estimate MAIT cell abundance in pan-cancer gene expression data, we demonstrate that a heavier intratumoral MAIT cell presence is positively correlated with a favorable prognosis in esophageal carcinoma but predicts poor overall survival in colorectal and squamous cell lung carcinomas. Finally, in colorectal carcinoma and four other cancer types, we found a positive correlation between MR1 expression and estimated MAIT cell abundance. Collectively, our findings indicate that MAIT cells serve important but diverse roles in human cancers. Our work provides useful models and resources that employ gene expression data platforms to enable future studies in the realm of MAIT cell biology.

The history and advances in cancer immunotherapy: understanding the characteristics of tumor-infiltrating immune cells and their therapeutic implications

Immunotherapy has revolutionized cancer treatment and rejuvenated the field of tumor immunology. Several types of immunotherapy, including adoptive cell transfer (ACT) and immune checkpoint inhibitors (ICIs), have obtained durable clinical responses, but their efficacies vary, and only subsets of cancer patients can benefit from them. Immune infiltrates in the tumor microenvironment (TME) have been shown to play a key role in tumor development and will affect the clinical outcomes of cancer patients. Comprehensive profiling of tumor-infiltrating immune cells would shed light on the mechanisms of cancer-immune evasion, thus providing opportunities for the development of novel therapeutic strategies. However, the highly heterogeneous and dynamic nature of the TME impedes the precise dissection of intratumoral immune cells. With recent advances in single-cell technologies such as single-cell RNA sequencing (scRNA-seq) and mass cytometry, systematic interrogation of the TME is feasible and will provide insights into the functional diversities of tumor-infiltrating immune cells. In this review, we outline the recent progress in cancer immunotherapy, particularly by focusing on landmark studies and the recent single-cell characterization of tumor-associated immune cells, and we summarize the phenotypic diversities of intratumoral immune cells and their connections with cancer immunotherapy. We believe such a review could strengthen our understanding of the progress in cancer immunotherapy, facilitate the elucidation of immune cell modulation in tumor progression, and thus guide the development of novel immunotherapies for cancer treatment.

Unravelling the heterogeneity and dynamic relationships of tumor-infiltrating T cells by single-cell RNA sequencing analysis

T cells are crucial for the success of immune-based cancer therapy. Reinvigorating antitumor T cell activity by blocking checkpoint inhibitory receptors has provided clinical benefits for many cancer patients. However, the efficacy of these treatments varies in cancer patients and the mechanisms underlying these diverse responses remain elusive. The density and status of tumor-infiltrating T cells have been shown to positively correlate with patient response to checkpoint blockades. Therefore, further understanding of the heterogeneity, clonal expansion, migration, and effector functions of tumor-infiltrating T cells will provide fundamental insights into antitumor immune responses. To this end, recent advances in single-cell RNA sequencing technology have enabled profound and extensive characterization of intratumoral immune cells and have improved our understanding of their dynamic relationships. Here, we summarize recent progress in single-cell RNA sequencing technology and current strategies to uncover heterogeneous tumor-infiltrating T cell subsets. In particular, we discuss how the coupling of deep transcriptome information with T cell receptor (TCR)-based lineage tracing has furthered our understanding of intratumoral T cell populations. We also discuss the functional implications of various T cell subsets in tumors and highlight the identification of novel T cell markers with therapeutic or prognostic potential.

Single-Cell Analysis Reveals Fibroblast Clusters Linked to Immunotherapy Resistance in Cancer

A subset of cancer-associated fibroblasts (FAP⁺/CAF-S1) mediates immunosuppression in breast cancers, but its heterogeneity and its impact on immunotherapy response remain unknown. Here, we identify 8 CAF-S1 clusters by analyzing more than 19,000 single CAF-S1 fibroblasts from breast cancer. We validate the five most abundant clusters by flow cytometry and in silico analyses in other cancer types, highlighting their relevance. Myofibroblasts from clusters 0 and 3, characterized by extracellular matrix proteins and TGFβ signaling, respectively, are indicative of primary resistance to immunotherapies. Cluster 0/ecm-myCAF upregulates PD-1 and CTLA4 protein levels in regulatory T lymphocytes (Tregs), which, in turn, increases CAF-S1 cluster 3/TGFβ-myCAF cellular content. Thus, our study highlights a positive feedback loop between specific CAF-S1 clusters and Tregs and uncovers their role in immunotherapy resistance. SIGNIFICANCE: Our work provides a significant advance in characterizing and understanding FAP⁺ CAF in cancer. We reached a high resolution at single-cell level, which enabled us to identify specific clusters associated with immunosuppression and immunotherapy resistance. Identification of cluster-specific signatures paves the way for therapeutic options in combination with immunotherapies.This article is highlighted in the In This Issue feature, p. 1241.

Prognostic impact of stromal and intratumoral CD3, CD8 and FOXP3 in adjuvantly treated breast cancer: do they add information over stromal tumor-infiltrating lymphocyte density?

BACKGROUND

Tumor-infiltrating lymphocytes (TILs) and their subsets contribute to breast cancer prognosis. We investigated the prognostic impact of CD3+, CD8+ and FOXP3+ TILs in patients with early intermediate/high-risk breast cancer treated with adjuvant anthracycline-based chemotherapy within two randomized trials conducted by our Group.

METHODS

We examined 1011 patients (median follow-up 130.9 months) and their tumors for total, stromal (s) and intratumoral (i) CD3, CD8 and FOXP3 lymphocyte density (counts/mm²) on tissue-microarray cores by immunohistochemistry. Morphological sTIL density on whole H&E-stained sections was also evaluated.

RESULTS

The majority of TILs were CD3+. Total CD3 and CD8, sCD3 and sCD8, iCD3 and iCD8, sFOXP3 and iFOXP3 were strongly correlated (Spearman's rho values > 0.6). High individual lymphocytic subsets and sTIL density were strongly associated with high tumor grade, higher proliferation and HER2-positive and triple-negative tumors (all p values < 0.001). Higher sTIL density (10% increments), high density of almost each individual marker and all-high profiles conferred favorable prognosis. However, when adjusted for sTIL density, stromal and intratumoral lymphocytic subsets lost their prognostic significance, while higher sTIL density conferred up to 15% lower risk for relapse. Independently of sTIL density, higher total CD3+ and CD8+ TILs conferred 35% and 28% lower risk for relapse, respectively.

CONCLUSIONS

Stromal and intratumoral CD3+, CD8+ and FOXP3+ TIL density do not seem to add prognostic information over the morphologically assessed sTIL density, which is worth introducing in routine histology reports.

Cancer immunosurveillance by CD8 T cells

Clinical success attained in patients with cancer treated with checkpoint inhibitors has renewed the interest in the immune system and in particular in T cells as a therapeutic tool to eliminate tumors. Here, we discuss recent studies that evaluate the anti-tumor role of CD8 T cells and the mechanisms that interfere with this function. In particular, we review recent literature that has reported on the phenotype and transcriptome of tumor-infiltrating CD8 T cells and deciphered the mechanisms associated with failed tumor rejection.