Single-cell landscape reveals the immune heterogeneity of bone marrow involvement in peripheral T-cell lymphoma.

The prognosis of patients with peripheral T-cell lymphoma (PTCL) depends on bone marrow involvement (BMI). The bone marrow (BM) tumor microenvironment in PTCL remains unclear. We performed single-cell RNA sequencing (scRNA-seq) on 11 fresh BM samples from patients with BMI to reveal the associations of immune landscape and genetic variations with the prognosis of PTCL patients. Compared with PTCL not otherwise specified (NOS), angioimmunoblastic T-cell lymphoma (AITL) had a higher number of T cells, lower number of lymphocytes, and greater inflammation. Immune heterogeneity in AITL is associated with prognosis. In particular, specific T-cell receptor (TCR) T cells are enriched in patients with good response to anti-CD30 therapy. We observed RhoA mutation-associated neoantigens. Chidamide-treated patients had a higher number of CD4+ regulatory cells and a better treatment response compared with other patients. In the nonresponder group, T-cell enrichment progressed to secondary B-cell enrichment and subsequently diffuse large B-cell lymphoma. Moreover, AITL patients with lymphoma-associated hemophagocytic syndrome had more T follicular helper (Tfh) cells with copy number variations in CHR5. To our knowledge, this study is the first to reveal the single-cell landscape of BM microenvironment heterogeneity in PTCL patients with BMI. scRNA-seq can be used to investigate the immune heterogeneity and genetic variations in AITL associated with prognosis.

Precise Molecular Subtyping Reveals Heterogeneity of Lung Adenocarcinoma Based on DNA Methylation.

BACKGROUND: Due to the high heterogeneity of lung adenocarcinoma (LUAD), which restricts the effectiveness of therapy, precise molecular subgrouping of LUAD is of great significance. Clinical research has demonstrated the significant potential of DNA methylation as a classification indicator for human malignancies. METHODS: WGML framework (which was developed based on weighted gene correlation network analysis (WGCNA), Gene Ontology (GO), and machine learning) was developed to precisely subgroup molecular subtypes of LUAD. This framework included two parts: the WG algorithm and the machine learning part. The WG algorithm part was an original algorithm used to obtain a crucial module, which was characterized by weighted correlation network analysis, functional annotation, and mathematical algorithms. The machine learning part utilized the Boruta algorithm, random forest algorithm, and Gradient Boosting Regression Tree algorithm to select feature genes. Then, based on the results of the WGML framework, subtypes were computed by the hierarchical clustering algorithm. A series of analyses, including dimensionality reduction methods, survival analysis, clinical stage analysis, immune infiltration analysis, tumor environment analysis, immune checkpoints analysis, TIDE analysis, CYT analysis, somatic mutation analysis, and drug sensitivity analysis, were utilized to demonstrate the effectiveness of subgrouping. GEO datasets were used to externally validate the results. Meanwhile, another subgrouping method of LUAD from another study was employed to compare with the WGML framework. RESULT: By importing DNA methylation data into the WGML framework, nine genes were obtained to further subgroup LUAD. Three subtypes, the Carcinogenesis subtype, Immune-infiltration subtype, and Chemoresistance subtype, were identified. The dimensionality reduction method exhibited great distinctness between subtypes. A series of analyses were employed to exhibit the difference among the three subtypes and to demonstrate the accuracy of the definition of subtypes. Besides, the WGML framework was compared with a LUAD subgrouping method from another research, which demonstrated that WGML had better efficiency for subgrouping LUAD. CONCLUSION: This study provides a novel LUAD subgrouping framework named WGML for the accurate subgrouping of lung adenocarcinoma.

Immune landscape and heterogeneity of cervical squamous cell carcinoma and adenocarcinoma.

Despite the differences in disease outcomes and pathological features between cervical squamous cell carcinoma (CSCC) and adenocarcinoma (ADC), the molecular characteristics in immune heterogeneity of the tumor microenvironment remain unclear. Here, we explored the immune landscape and heterogeneity between CSCC and ADC. Gene expression and clinical characteristics of cervical carcinoma from The Cancer Genome Atlas (TCGA) were downloaded. Differentially expressed genes (DEGs), immune cell infiltration, and pathway enrichment analyses were used to explore the immune landscape and heterogeneity between CSCC and ADC. Furthermore, distinct immune signatures between CSCC and ADC were validated based on clinical samples. In total, 4,132 upregulated DEGs and 2,307 down-regulated DEGs were identified between CSCC and ADC, with enrichments in immune related-pathways in CSCC. In addition, 54 hub DEGs correlated with patients' prognosis and immunocytes infiltration were identified. The CSCC patients had a higher ImmuneScore and more abundant immunocytes infiltration compared to ADC patients, as validated by immunohistochemistry (IHC) and multicolor immunofluorescence (mIF) analyses of collected samples. Furthermore, CSCC displayed higher inhibitory immune checkpoints expression, tumor mutation burden (TMB), and microsatellite instability (MSI) compared to ADC, which indicated CSCC patients were more likely to benefit from immunotherapy. In summary, our results revealed the huge immune heterogeneity between CSCC and ADC, and provided guidance for immunotherapy selection for different pathological types of cervical cancer.

[Research Progress of Immune Heterogeneity in Leukemia Microenvironment--Review].

Although the body has a strong immune system which can resists the invasion of leukemia cells, leukemia cells disseminate systemically and form an immunosuppressive microenvironment through a variety of mechanisms, including regulation of antigen presentation, utilization of immunosuppressive enzyme AXL, immune cell inhibitory checkpoint NKG2A and immunoregulatory gene VISTA, resulting in immune escape. Therefore, most types of leukemia are inevitable for the affliction of drug resistance or relapse, and the immune efficacy is not as significant as that of other hematological tumors and the prognosis is suboptimal. This article reviews the immune heterogeneity of leukemia microenvironment from many aspects, including anti-leukemia immunity and immune escape. In addition, it also reviews the latest progress and future prospects of immune checkpoint inhibition, adoptive cell therapy and vaccine therapy in leukemia, providing a theoretical basis for the development of personalized combination therapy strategies with less toxic side effects.

Heterogeneity of the tumor immune microenvironment and clinical interventions.

The tumor immune microenvironment (TIME) is broadly composed of various immune cells, and its heterogeneity is characterized by both immune cells and stromal cells. During the course of tumor formation and progression and anti-tumor treatment, the composition of the TIME becomes heterogeneous. Such immunological heterogeneity is not only present between populations but also exists on temporal and spatial scales. Owing to the existence of TIME, clinical outcomes can differ when a similar treatment strategy is provided to patients. Therefore, a comprehensive assessment of TIME heterogeneity is essential for developing precise and effective therapies. Facilitated by advanced technologies, it is possible to understand the complexity and diversity of the TIME and its influence on therapy responses. In this review, we discuss the potential reasons for TIME heterogeneity and the current approaches used to explore it. We also summarize clinical intervention strategies based on associated mechanisms or targets to control immunological heterogeneity.

Tumor cell heterogeneity drives spatial organization of the intratumoral immune response in squamous cell skin carcinoma.

Intratumoral heterogeneity (ITH)-defined as genetic and cellular diversity within a tumor-is linked to failure of immunotherapy and an inferior anti-tumor immune response. The underlying mechanism of this association is unknown. To address this question, we modeled heterogeneous tumors comprised of a pro-inflammatory ("hot") and an immunosuppressive ("cold") tumor population, labeled with YFP and RFP tags respectively to enable precise spatial tracking. The resulting mixed-population tumors exhibited distinct regions comprised of YFP+ (hot) cells, RFP+ (cold) cells, or a mixture. We found that tumor regions occupied by hot tumor cells (YFP+) harbored more total T cells and a higher frequency of Th1 cells and IFNγ+ CD8 T cells compared to regions occupied by cold tumor cells (RFP+), whereas immunosuppressive macrophages showed the opposite spatial pattern. We identified the chemokine CX3CL1, produced at higher levels by our cold tumors, as a mediator of intratumoral macrophage accumulation, particularly immunosuppressive CD206Hi macrophages. Furthermore, we examined the response of heterogeneous tumors to a therapeutic combination of PD-1 blockade and CD40 agonist on a region-by-region basis. While the combination successfully increases Th1 abundance in "cold" tumor regions, it fails to bring overall T cell activity to the same level as seen in "hot" regions. The presence of the "cold" cells thus ultimately leads to a failure of the therapy to induce tumor rejection. Collectively, our results demonstrate that the organization of heterogeneous tumor cells has a profound impact on directing the spatial organization and function of tumor-infiltrating immune cells as well as on responses to immunotherapy.

Deciphering the immune heterogeneity dominated by natural killer cells with prognostic and therapeutic implications in hepatocellular carcinoma.

Belonging to type 1 innate lymphoid cells (ILC1), natural killer (NK) cells play an important role not only in fighting microbial infections but also in anti-tumor response. Hepatocellular carcinoma (HCC) represents an inflammation-related malignancy and NK cells are enriched in the liver, making them an essential component of the HCC immune microenvironment. In this study, we performed single-cell RNA-sequencing (scRNA-seq) analysis to identify the NK cell marker genes (NKGs) and uncovered 80 prognosis-related ones by the TCGA-LIHC dataset. Based on prognostic NKGs, HCC patients were categorized into two subtypes with distinct clinical outcomes. Subsequently, we conducted LASSO-COX and stepwise regression analysis on prognostic NKGs to establish a five-gene (UBB, CIRBP, GZMH, NUDC, and NCL) prognostic signature-NKscore. Different mutation statuses of the two risk groups stratified by NKscore were comprehensively characterized. Besides, the established NKscore-integrated nomogram presented enhanced predictive performance. Single sample gene set enrichment analysis (ssGSEA) analysis was used to uncover the landscape of the tumor immune microenvironment (TIME) and the high-NKscore risk group was characterized with an immune-exhausted phenotype while the low-NKscore risk group held relatively strong anti-cancer immunity. T cell receptor (TCR) repertoire, tumor inflammation signature (TIS), and Immunophenoscore (IPS) analyses revealed differences in immunotherapy sensitivity between the two NKscore risk groups. Taken together, we developed a novel NK cell-related signature to predict the prognosis and immunotherapy efficacy for HCC patients.

The Oncogenesis of Glial Cells in Diffuse Gliomas and Clinical Opportunities.

Glioma is the most common and lethal intrinsic primary tumor of the brain. Its controversial origins may contribute to its heterogeneity, creating challenges and difficulties in the development of therapies. Among the components constituting tumors, glioma stem cells are highly plastic subpopulations that are thought to be the site of tumor initiation. Neural stem cells/progenitor cells and oligodendrocyte progenitor cells are possible lineage groups populating the bulk of the tumor, in which gene mutations related to cell-cycle or metabolic enzymes dramatically affect this transformation. Novel approaches have revealed the tumor-promoting properties of distinct tumor cell states, glial, neural, and immune cell populations in the tumor microenvironment. Communication between tumor cells and other normal cells manipulate tumor progression and influence sensitivity to therapy. Here, we discuss the heterogeneity and relevant functions of tumor cell state, microglia, monocyte-derived macrophages, and neurons in glioma, highlighting their bilateral effects on tumors. Finally, we describe potential therapeutic approaches and targets beyond standard treatments.

The Oncogenesis of Glial Cells in Diffuse Gliomas and Clinical Opportunities / 神经科学通报·英文版

Glioma is the most common and lethal intrinsic primary tumor of the brain. Its controversial origins may contribute to its heterogeneity, creating challenges and difficulties in the development of therapies. Among the components constituting tumors, glioma stem cells are highly plastic subpopulations that are thought to be the site of tumor initiation. Neural stem cells/progenitor cells and oligodendrocyte progenitor cells are possible lineage groups populating the bulk of the tumor, in which gene mutations related to cell-cycle or metabolic enzymes dramatically affect this transformation. Novel approaches have revealed the tumor-promoting properties of distinct tumor cell states, glial, neural, and immune cell populations in the tumor microenvironment. Communication between tumor cells and other normal cells manipulate tumor progression and influence sensitivity to therapy. Here, we discuss the heterogeneity and relevant functions of tumor cell state, microglia, monocyte-derived macrophages, and neurons in glioma, highlighting their bilateral effects on tumors. Finally, we describe potential therapeutic approaches and targets beyond standard treatments.

Heterogeneity of the tumor immune microenvironment and clinical interventions / 医学前沿

The tumor immune microenvironment (TIME) is broadly composed of various immune cells, and its heterogeneity is characterized by both immune cells and stromal cells. During the course of tumor formation and progression and anti-tumor treatment, the composition of the TIME becomes heterogeneous. Such immunological heterogeneity is not only present between populations but also exists on temporal and spatial scales. Owing to the existence of TIME, clinical outcomes can differ when a similar treatment strategy is provided to patients. Therefore, a comprehensive assessment of TIME heterogeneity is essential for developing precise and effective therapies. Facilitated by advanced technologies, it is possible to understand the complexity and diversity of the TIME and its influence on therapy responses. In this review, we discuss the potential reasons for TIME heterogeneity and the current approaches used to explore it. We also summarize clinical intervention strategies based on associated mechanisms or targets to control immunological heterogeneity.

Research Progress of Immune Heterogeneity in Leukemia Microenvironment--Review / 中国实验血液学杂志

Although the body has a strong immune system which can resists the invasion of leukemia cells, leukemia cells disseminate systemically and form an immunosuppressive microenvironment through a variety of mechanisms, including regulation of antigen presentation, utilization of immunosuppressive enzyme AXL, immune cell inhibitory checkpoint NKG2A and immunoregulatory gene VISTA, resulting in immune escape. Therefore, most types of leukemia are inevitable for the affliction of drug resistance or relapse, and the immune efficacy is not as significant as that of other hematological tumors and the prognosis is suboptimal. This article reviews the immune heterogeneity of leukemia microenvironment from many aspects, including anti-leukemia immunity and immune escape. In addition, it also reviews the latest progress and future prospects of immune checkpoint inhibition, adoptive cell therapy and vaccine therapy in leukemia, providing a theoretical basis for the development of personalized combination therapy strategies with less toxic side effects.

Immunometabolism characteristics and a potential prognostic risk model associated with TP53 mutations in breast cancer.

TP53, a gene with high-frequency mutations, plays an important role in breast cancer (BC) development through metabolic regulation, but the relationship between TP53 mutation and metabolism in BC remains to be explored. Our study included 1,066 BC samples from The Cancer Genome Atlas (TCGA) database, 415 BC cases from the Gene Expression Omnibus (GEO) database, and two immunotherapy cohorts. We identified 92 metabolic genes associated with TP53 mutations by differential expression analysis between TP53 mutant and wild-type groups. Univariate Cox analysis was performed to evaluate the prognostic effects of 24 TP53 mutation-related metabolic genes. By unsupervised clustering and other bioinformatics methods, the survival differences and immunometabolism characteristics of the distinct clusters were illustrated. In a training set from TCGA cohort, we employed the least absolute shrinkage and selection operator (LASSO) regression method to construct a metabolic gene prognostic model associated with TP53 mutations, and the GEO cohort served as an external validation set. Based on bioinformatics, the connections between risk score and survival prognosis, tumor microenvironment (TME), immunotherapy response, metabolic activity, clinical characteristics, and gene characteristics were further analyzed. It is imperative to note that our model is a powerful and robust prognosis factor in comparison to other traditional clinical features and also has high accuracy and clinical usefulness validated by receiver operating characteristic (ROC) and decision curve analysis (DCA). Our findings deepen our understanding of the immune and metabolic characteristics underlying the TP53 mutant metabolic gene profile in BC, laying a foundation for the exploration of potential therapies targeting metabolic pathways. In addition, our model has promising predictive value in the prognosis of BC.

Single-Cell Landscape of Mouse Islet Allograft and Syngeneic Graft.

Islet transplantation to treat the late stage of type 1 diabetic patient (T1DM) has recently made inspiring success in clinical trials. However, most patients experience a decline in islet graft function in one to three years due to immune rejection. Although the mechanisms of immune cells, including macrophages, dendritic cells (DCs), neutrophils, natural killer cells (NKs), B cells, and T cells, that mediate immune rejection have been investigated, the overall characteristics of immune infiltrates in islet allografts and syngeneic grafts remain unclear. Single-cell RNA sequencing (scRNA-seq) has provided us with new opportunities to study the complexity of the immune microenvironment in islet transplants. In the present study, we used scRNA-seq to comprehensively analyze the immune heterogeneity in the mouse model of islet transplantation. Our data revealed T lymphocytes and myeloid cells as the main immune components of grafts 7 days post-islet transplantation, especially in allografts. Moreover, our results indicated that allogeneic islet cells were transformed into antigen-presenting cell-like cells with highly expressed MHC class I molecules and genes involved in MHC class I-mediated antigen presentation. This transformation may dramatically facilitate the interaction with cytotoxic CD8+ T cells and promote the destruction of islet allografts. Our study provides insight into the transcriptomics and diverse microenvironment of islet grafts and their impacts on immune rejection.

Dysregulated ferroptosis-related genes indicate potential clinical benefits for anti-PD-1/PD-L1 immunotherapy in lung adenocarcinoma.

BACKGROUND: Ferroptosis is an iron-dependent programmed cell death mechanism that influences the development of malignancy. Lung adenocarcinoma (LUAD) is the most common type of lung cancer with no known cure. Anti-PD-1/PD-L immunotherapy is effective for patients with partial LUAD. Therefore, there is an immediate requirement of novel markers to predict the individualised benefits of immunotherapy. METHODS: We manually collected the ferroptosis-related gene (FERG) set and employed the Wilcoxon rank-sum test to identify the differentially expressed FERGs. Subsequently, we constructed a recursive partitioning and regression tree (RPART) model to predict the benefits of anti-PD-1/PD-L1 immunotherapy. Subsequently, the ROC curve and AUC were used to evaluate the model efficiency in an independent dataset. RESULTS: In this study, we found that the dysregulated FERGs were closely associated with multiple metabolic processes in LUAD. Furthermore, we identified three ferroptosis-related tumour subtypes (F1, F3 and F3). The F3 subtype exhibited higher immunoactivity and lower tumour purity, mutation count and aneuploidy and had better survival outcomes compared with the other two subtypes, implying that FERGs played an important role in intertumoral immune heterogeneity. We further explored the role of FERGs in the anti-PD-1/PD-L1 immunotherapy. We identified a set of three-FERGs signature (CD44, G6PD and ZEB1) that acted as a promising indicator (AUC = 0.697) for the prediction of the benefits of anti-PD-1/PD-L1 immunotherapy. CONCLUSION: Ferroptosis, as emerging programmed cell death mechanism, was associated with cancer development. We used ferroptosis-related genes to predict the immunotherapy benefits that may facilitate the development of individualised anti-cancer treatment strategies.

Comprehensive Characterization of RNA Processing Factors in Gastric Cancer Identifies a Prognostic Signature for Predicting Clinical Outcomes and Therapeutic Responses.

RNA processing converts primary transcript RNA into mature RNA. Altered RNA processing drives tumor initiation and maintenance, and may generate novel therapeutic opportunities. However, the role of RNA processing factors in gastric cancer (GC) has not been clearly elucidated. This study presents a comprehensive analysis exploring the clinical, molecular, immune, and drug response features underlying the RNA processing factors in GC. This study included 1079 GC cases from The Cancer Genome Atlas (TCGA, training set), our hospital cohort, and two other external validation sets (GSE15459, GSE62254). We developed an RNA processing-related prognostic signature using Cox regression with the least absolute shrinkage and selection operator (LASSO) penalty. The prognostic value of the signature was evaluated using a multiple-method approach. The genetic variants, pathway activation, immune heterogeneity, drug response, and splicing features associated with the risk signature were explored using bioinformatics methods. Among the tested 819 RNA processing genes, we identified five distinct RNA processing patterns with specific clinical outcomes and biological features. A 10-gene RNA processing-related prognostic signature, involving ZBTB7A, METTL2B, CACTIN, TRUB2, POLDIP3, TSEN54, SUGP1, RBMS1, TGFB1, and PWP2, was further identified. The signature was a powerful and robust prognosis factor in both the training and validation datasets. Notably, it could stratify the survival of patients with GC in specific tumor-node-metastasis (TNM) classification subgroups. We constructed a composite prognostic nomogram to facilitate clinical practice by integrating this signature with other clinical variables (TNM stage, age). Patients with low-risk scores were characterized with good clinical outcomes, proliferation, and metabolism hallmarks. Conversely, poor clinical outcome, invasion, and metastasis hallmarks were enriched in the high-risk group. The RNA processing signature was also involved in tumor microenvironment reprogramming and regulating alternative splicing, causing different drug response features between the two risk groups. The low-risk subgroup was characterized by high genomic instability, high alternative splicing and might benefit from the immunotherapy. Our findings highlight the prognostic value of RNA processing factors for patients with GC and provide insights into the specific clinical and molecular features underlying the RNA processing-related signature, which may be important for patient management and targeting treatment.

The Immune Atlas of Human Deciduas With Unexplained Recurrent Pregnancy Loss.

Recurrent pregnancy loss (RPL) is a common fertility problem that affects 1%-2% of couples all over the world. Despite exciting discoveries regarding the important roles of the decidual natural killer cell (dNK) and regulatory T cell in pregnancy, the immune heterogeneity in patients with unexplained recurrent pregnancy loss (URPL) remains elusive. Here, we profiled the transcriptomes of 13,953 CD45+ cells from three normal and three URPL deciduas. Based on our data, the cellular composition revealed three major populations of immune cells including dNK cell, T cell, and macrophage, and four minor populations including monocytes, dendritic cell (DC), mast cell, and B cell. Especially, we identified a subpopulation of CSF1+ CD59+ KIRs-expressing dNK cells in normal deciduas, while the proportion of this subpopulation was decreased in URPL deciduas. We also identified a small subpopulation of activated dDCs that were accumulated mainly in URPL deciduas. Furthermore, our data revealed that in decidua at early pregnancy, CD8+ T cells exhibited cytotoxic properties. The decidual macrophages expressed high levels of both M1 and M2 feature genes, which made them unique to the conventional M1/M2 classification. Our single-cell data revealed the immune heterogeneity in decidua and the potentially pathogenic immune variations in URPL.

An Immune-Related Gene Pairs Signature Predicts Prognosis and Immune Heterogeneity in Glioblastoma.

PURPOSE: Glioblastoma is one of the most aggressive nervous system neoplasms. Immunotherapy represents a hot spot and has not been included in standard treatments of glioblastoma. So in this study, we aim to filtrate an immune-related gene pairs (IRGPs) signature for predicting survival and immune heterogeneity. METHODS: We used gene expression profiles and clinical information of glioblastoma patients in the TCGA and CGGA datasets, dividing into discovery and validation cohorts. IRGPs significantly correlative with prognosis were selected to conduct an IRGPs signature. Low and high risk groups were separated by this IRGPs signature. Univariate and multivariate cox analysis were adopted to check whether risk can be a independent prognostic factor. Immune heterogeneity between different risk groups was analyzed via immune infiltration and gene set enrichment analysis (GSEA). Some different expressed genes between groups were selected to determine their relationship with immune cells and immune checkpoints. RESULTS: We found an IRGPs signature consisting of 5 IRGPs. Different risk based on IRGPs signature is a independent prognostic factor both in the discovery and validation cohorts. High risk group has some immune positive cells and more immune repressive cells than low risk group by means of immune infiltration. We discovered some pathways are more active in the high risk group, leading to immune suppression, drug resistance and tumor evasion. In two specific signaling, some genes are over expressed in high risk group and positive related to immune repressive cells and immune checkpoints, which indicate aggression and immunotherapy resistance. CONCLUSION: We identified a robust IRGPs signature to predict prognosis and immune heterogeneity in glioblastoma patients. Some potential targets and pathways need to be further researched to make different patients benefit from personalized immunotherapy.

Decoding Immune Heterogeneity of Melanoma and identifying immune-prognostic hub genes.

Melanoma is an aggressive skin cancer that has gained attention worldwide. Growing evidence has highlighted that the tumor microenvironment (TME) is an important feature of carcinogenesis and contributes to therapeutic efficacy in melanoma. However, additional advances in melanoma immuno-oncology are necessary to achieve a comprehensive knowledge of the immune infiltrate population and to identify accurate and readily measurable biomarkers. In this study, we analyzed gene expression of 468 melanoma cases from the TCGA database, which led to the identification of three melanoma clusters (representedby low, median and high infiltration) that display unique immune features. We found that the microenvironment clusters had substantial prognostic efficacy. The median cluster was characterized by an inability to draw immune cells, highlighting possible immune escape mechanisms, and lower CXCL9 and CXCL10 expression, which was correlated to poor prognosis. Deep molecular characterization of immune cells, cytolytic-activity and tumor-inflammatory status revealed diversity of the local immune infiltration landscape in the melanoma clusters. Differentially expressed genes related to TME were extracted from each infiltration cluster. Functional annotations revealed that these genes were mainly related to immune system activation and the processes of immunoreaction. The top ten hub genes in immune infiltration-related protein-protein interaction (PPI) networks were selected for further prognostic investigation. Further validation showed that five of ten hub genes were good prognostic biomarkers for melanoma in two independent groups from the Gene Expression Omnibus database. In brief, these data highlight that systemic characterization of melanoma could uncover tumor infiltrate characteristics, which can help select the most adequate treatment and identify consistent and important indicators of the local immune tumor microenvironment in melanoma patients.

Co-option of Neutrophil Fates by Tissue Environments.

Classically considered short-lived and purely defensive leukocytes, neutrophils are unique in their fast and moldable response to stimulation. This plastic behavior may underlie variable and even antagonistic functions during inflammation or cancer, yet the full spectrum of neutrophil properties as they enter healthy tissues remains unexplored. Using a new model to track neutrophil fates, we found short but variable lifetimes across multiple tissues. Through analysis of the receptor, transcriptional, and chromatin accessibility landscapes, we identify varying neutrophil states and assign non-canonical functions, including vascular repair and hematopoietic homeostasis. Accordingly, depletion of neutrophils compromised angiogenesis during early age, genotoxic injury, and viral infection, and impaired hematopoietic recovery after irradiation. Neutrophils acquired these properties in target tissues, a process that, in the lungs, occurred in CXCL12-rich areas and relied on CXCR4. Our results reveal that tissues co-opt neutrophils en route for elimination to induce programs that support their physiological demands.

Immune Heterogeneity Between Primary Tumors and Corresponding Metastatic Lesions and Response to Platinum Therapy in Primary Ovarian Cancer.

CD3+ and CD8+ lymphocytes are well known prognostic markers in primary ovarian cancer. In contrast, the predictive value of the immune infiltrate concerning treatment response and the involvement of immune heterogeneity between primary and metastatic lesions are poorly understood. In this study, the immune infiltrate of 49 primary tumors and 38 corresponding lesions in the omentum (n = 23) and the peritoneum (n = 15) was immunohistochemically analyzed and correlated with clinicopathological factors and platinum-sensitivity. Immune heterogeneity was observed between paired primary and metastatic lesions for all immune cell phenotypes. The stromal immune infiltrate was higher in the omental lesions than in the primary tumors, which was reflected by CD45 (p=0.007), CD3 (p=0.005), CD8 (p=0.012), and PD-1 (programmed cell-death protein 1) (p=0.013). A higher stromal infiltrate of both CD45+ and CD3+ cells in the omental lesions was associated with the detection of lymph node metastasis (CD45, p=0.018; CD3, p=0.037). Platinum-sensitive ovarian cancers revealed a higher intratumoral CD8+ infiltrate in the peritoneal lesions compared to the primary tumors (p=0.045). In contrast, higher counts of stromal PD-1+ cells in the peritoneal lesions have been associated with reduced platinum-sensitivity (p=0.045). Immune heterogeneity was associated with platinum response and might represent a selection marker for personalized therapy.