Tumor Immune Microenvironment Research Articles

Transcriptional repression by HDAC3 mediates T cell exclusion from Kras mutant lung tumors

Histone Deacetylase 3 (HDAC3) function in vivo is nuanced and directed in a tissue-specific fashion. The importance of HDAC3 in Kras mutant lung tumors has recently been identified, but HDAC3 function in this context remains to be fully elucidated. Here, we identified HDAC3 as a lung tumor cell-intrinsic transcriptional regulator of the tumor immune microenvironment. In Kras mutant lung cancer cells, we found that HDAC3 is a direct transcriptional repressor of a cassette of secreted chemokines, including Cxcl10. Genetic and pharmacological inhibition of HDAC3 robustly up-regulated this gene set in human and mouse Kras, LKB1 (KL) and Kras, p53 (KP) mutant lung cancer cells through an NF-κB/p65-dependent mechanism. Using genetically engineered mouse models, we found that HDAC3 inactivation in vivo induced expression of this gene set selectively in lung tumors and resulted in enhanced T cell recruitment at least in part via Cxcl10. Furthermore, we found that inhibition of HDAC3 in the presence of Kras pathway inhibitors dissociated Cxcl10 expression from that of immunosuppressive chemokines and that combination treatment of entinostat with trametinib enhanced T cell recruitment into lung tumors in vivo. Finally, we showed that T cells contribute to in vivo tumor growth control in the presence of entinostat and trametinib combination treatment. Together, our findings reveal that HDAC3 is a druggable endogenous repressor of T cell recruitment into Kras mutant lung tumors.

STARD7 could be an immunological and prognostic biomarker: from pan-cancer analysis to hepatocellular carcinoma validation

BackgroundAs the emergence of technologies such as sequencing and gene mapping, significant advancements have been made in understanding the landscape of tumors. However, the effective treatment of tumors continues to pose a tremendous challenge in clinical practice, which highlights the importance of predicting tumor markers and studying drug resistance mechanisms. The prognosis and differential expression of STARD7 in human pan-cancer were investigated by bioinformatic methods and experimental verification.MethodsThe expression, diagnostic, and prognostic significance of the STARD7 gene were comprehensive analyzed using bioinformatics techniques. Furthermore, we validated our projected outcomes in liver cancer through experimental methodologies, including the use of qRT-PCR, CCK8 and transwell assays.ResultsThe STARD7 gene exhibits differential expression in 25 tumors, with high expression observed in 22 tumors. These distinct expression patterns within different tumor types are closely associated with poor prognosis and diagnosis. Furthermore, the STARD7 gene plays a role in regulating the tumor immune microenvironment. Methylation levels of STARD7 vary among 20 types of tumors and are correlated with survival outcomes. Furthermore, the experiment results demonstrated that STARD7 is highly expressed in hepatocellular carcinoma cells. Suppression of STARD7 significantly impedes the proliferation, migration, and invasion of HepG-2 and SMMC-7721 cells.ConclusionsSTARD7 has the potential to function as a crucial prognostic biomarker and exhibit correlation with tumor immunity in various types of human cancers. The implications of our findings extend to informing cancer immune-therapy and promoting the advancement of precision immune-oncology.

Prognostic risk model of LIHC T-cells based on scRNA-seq and RNA-seq and the regulation of the tumor immune microenvironment

BackgroundT-cell-related genes play a crucial role in LIHC development. However, a reliable prognostic profile based on risk models of these genes has yet to be identified.MethodsSingle-cell datasets from both tumor and normal tissue samples were obtained from the GEO database. We identified T-cell marker genes and developed a genetic risk model using the TCGA-LIHC dataset, which was subsequently validated with an independent GEO dataset. We also explored the relationship between risk model predictions and immune responses.ResultsWe constructed a prognostic risk model using eight gene features identified through screening 860 T-cell marker genes via scRNA-seq and RNA-seq, which was subsequently integrated with the TCGA dataset. Its validity was independently confirmed using GEO and ICGC datasets. The TCGA dataset was stratified into high-risk and low-risk groups based on the risk model. Multivariate Cox regression analysis confirmed the risk score as an independent prognostic factor. GSEA indicated ribosomal transporter metabolism enrichment in the high-risk group and significant transcriptional activation in the low-risk group. ESTIMATE analysis showed higher ESTIMATE, immune, and stromal scores in the low-risk group, which also exhibited lower tumor purity than the high-risk group. Immunophenotyping revealed distinct patterns of immune cell infiltration and an immunosuppressive environment in the high-risk group.ConclusionsThis study introduces a T-cell marker-based prognostic risk model for LIHC patients. This model effectively predicted survival outcomes and immunotherapy effectiveness in LIHC patients, aligning with diverse immune responses and the distinct immunological profiles observed in the high-risk group.

Cancer-Associated Fibroblast Subtypes Reveal Distinct Gene Signatures in the Tumor Immune Microenvironment of Vestibular Schwannoma.

Cancer-associated fibroblast (CAF) composition within the same organ varies across different cancer subtypes. Distinct CAF subtypes exhibit unique features due to interactions with immune cells and the tumor microenvironment. However, data on CAF subtypes in individuals with vestibular schwannoma (VS) are lacking. Therefore, we aimed to distinguish CAF subtypes at the single-cell level, investigate how stem-like CAF characteristics influence the tumor immune microenvironment, and identify CAF subtype-specific metabolic reprogramming pathways that contribute to tumor development. Data were analyzed from three patients with VS, encompassing 33,081 single cells, one bulk transcriptome cohort, and The Cancer Genome Atlas Pan-Cancer database (RNA sequencing and clinical data). Our findings revealed that antigen-presenting CAFs are linked to substantially heightened immune activity, supported by metabolic reprogramming, which differs from tumorigenesis. High expression of the stem-like CAF gene signature correlated with poor prognosis in low-grade gliomas within the pan-cancer database. This is the first study to classify CAF subtypes in VS patients and identify a therapeutic vulnerability biomarker by developing a stem-like CAF gene signature. Personalized treatments tailored to individual patients show promise in advancing precision medicine.

Mitochondrial-uncoupling nanomedicine for self-heating and immunometabolism regulation in cancer cells

Developing endogenous hyperthermia offers a promising strategy to address challenges with current exogenous hyperthermia techniques in clinics. Herein, a CD44-targeted and thermal-responsive nanocarrier was developed for the simultaneous delivery of 2,4-dinitrophenol and syrosingopine. The objective was to induce endogenous hyperthermia and regulate immunometabolism, ultimately augmenting anti-tumour immune responses. Dinitrophenol as mitochondrial uncoupler can convert electrochemical potential energy of inner mitochondrial membrane into heat, facilitating endogenous hyperthermia. Meanwhile, syrosingopine not only inhibits excessive lactate efflux caused by dinitrophenol but also downregulates tumour cell glycolysis, thus alleviating immunosuppression and heat shock protein (HSP)-dependent thermo-resistance through immunometabolism regulation. The synergistic effects of endogenous hyperthermia and immunometabolism regulation by this nanomedicine have potential to enhance tumor immunogenicity, reshape the tumour immune microenvironment, and effectively suppress the growth of subcutaneous tumours and patient-derived organoids in triple-negative breast cancer. Therefore, the endogenous hyperthermia strategy developed in this study would revolutionize hyperthermia for cancer treatment.

Systemic delivery of tannic acid-ferric-masked oncolytic adenovirus reprograms tumor microenvironment for improved therapeutic efficacy in glioblastoma.

Glioblastoma (GBM) represents the most aggressive primary brain tumor, and urgently requires effective treatments. Oncolytic adenovirus (OA) shows promise as a potential candidate for clinical antitumor therapy, including in the treatment of GBM. Nevertheless, the systemic delivery of OA continues to face challenges, leading to significantly compromised antitumor efficacy. In this study, we developed an innovative approach by encapsulating CXCL11-armed OA with tannic acid and Fe3+ (TA-Fe3+) to realize the systemic delivery of OA. The nanocarrier's ability to protect the OA from elimination by host immune response was evaluated in vitro and in vivo. We evaluated the antitumor effect and safety profile of OA@TA-Fe3+ in a GBM-bearing mice model. OA@TA-Fe3+ effectively safeguarded the virus from host immune clearance and extended its circulation in vivo. After targeting tumor sites, TA-Fe3+ could dissolve and release Fe3+ and OA. Fe3+-induced O2 production from H2O2 relieved the hypoxic state, and promoted OA replication, leading to a remarkable alteration of tumor immune microenvironment and enhancement in antitumor efficacy. Moreover, the systemic delivery of OA@TA-Fe3+ was safe without inflammation or organ damage. Our findings demonstrated the promising potential of systemically delivering the engineered OA for effective oncolytic virotherapy against GBM.

BANF1 is a novel prognostic biomarker linked to immune infiltration in head and neck squamous cell carcinoma.

Barrier-to-autointegration factor 1 (BANF1) is an abundant and ubiquitously expressed postnatal mammalian protein that is overexpressed in numerous human cancers and can promote cancer cell proliferation. However, the role of BANF1 in prognosis remains unclear in head and neck squamous cell carcinoma (HNSCC). BANF1 expression data were obtained from the GEO and TCGA databases. We used Cox regression and Kaplan-Meier curves to assess the prognostic potential of BANF1. The role of BANF1-related genes was investigated using Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses. In addition, we explored the link between BANF1, drug sensitivity, and the tumor immune microenvironment. Finally, functional in vitro and in vivo assays were used to explore the effects of BANF1 on tumor growth and metastasis of HNSCC. BANF1 was markedly overexpressed in HNSCC and was correlated with clinicopathological characteristics. According to survival analysis, BANF1 can be inversely correlated with patient survival and can act as a prognostic risk indicator. IC50 values for chemotherapeutic treatments indicated that the group with high BANF1 expression was more responsive to most antitumor treatments. Furthermore, higher TIDE scores were observed in the low BANF1 expression group, indicating a decline in the efficacy of immune checkpoint inhibitor therapy. Functionally, the malignant biological behavior of HNSCC cell lines was inhibited when BANF1 expression was knocked down. BANF1 can promote tumor progression in patients with HNSCC. BANF1 shows great promise as a potential biomarker to assess the prognosis.

Multi-omics analysis identifies BCAT2 as a potential pan-cancer biomarker for tumor progression and immune microenvironment modulation.

Branched-chain amino acid transaminase 2 (BCAT2) encodes a crucial protein involved in the initial catalysis of branched-chain amino acid (BCAA) catabolism, with emerging evidence suggesting its association with tumor progression. This study explores BCAT2 in a pan-cancer multi-omics context and evaluates its prognostic significance. We utilized a multi-database approach, analyzing cBioPortal for genetic alterations, RNA-Seq data from TCGA and GTEx for expression patterns, and RSEM for transcript analysis. Protein expression and interaction networks were assessed using the Human Protein Atlas, UniProt, and STRING. Prognostic value was determined through Cox regression analysis of TCGA clinical survival data, while immune cell infiltration across various cancers was examined using TCGA data and the TIMER2 platform. Our results revealed that BCAT2 alterations are primarily amplifications and is upregulated in various tumors, correlating with poor survival rates in several tumor types, including GBMLGG, LGG, and UVM. Elevated BCAT2 protein levels were common in pan-cancer, interacting with a range of metabolic enzymes. Additionally, BCAT2 expression significantly influenced CD4+ T cells, CD8+ T cells, and Treg cells infiltration, with varied correlations across cancer types. These findings indicate BCAT2 as a potential biomarker for cancer diagnosis and therapy, potentially regulating key metabolic and immune factors to mediate tumor progression and the microenvironment.

Ultrasound-Responsive Nanocarriers Delivering siRNA and Fe3O4 Nanoparticles Reprogram Macrophages and Inhibit M2 Polarization for Enhanced NSCLC Immunotherapy.

Lung cancer has emerged as the second most common type of malignant tumor worldwide, and it has the highest mortality rate. The overall 5-year survival rate stands at less than 20%, which is primarily related to the limited therapeutic options and the complexity of the tumor immune microenvironment. In the tumor microenvironment, M1 macrophages are known for their tumor-killing capabilities. Although they are less numerous, they play an important role in tumor immunity. Therefore, increasing M1 macrophages' presence is considered a strategy to enhance targeted phagocytosis and antitumor efficacy in nonsmall cell lung cancer (NSCLC). This study introduces the development of folic acid (FA)-conjugated liposomal nanobubbles for precise delivery of PFH, STAT3 siRNA, and Fe3O4 to the tumor microenvironment. These encapsulated PFH liposomal nanobubbles exhibit significant visualization potential and underwent phase transition when exposed to low-intensity focused ultrasound (LIFU). The release of Fe3O4 activates the IRF5 signaling pathway, converting M2-like macrophages to M1. In addition, STAT3 siRNA effectively interrupts the JAK-STAT3 pathway, inhibiting the polarization of M2-like macrophages in tumor-associated macrophages (TAMs). This dual-action therapy facilitates T-cell activation and proliferation, thereby enhancing the immune response against NSCLC.

Towards a framework for predicting immunotherapy outcome: a hybrid multiscale mathematical model of immune response to vascular tumor growth.

Studying tumor immune microenvironment (TIME) is pivotal to understand the mechanism and predict the outcome of cancer immunotherapy. Systems biology mathematical models can consider and control various factors of TIME and therefore explore the anti-tumor immune response meticulously. However, the role of tumor vasculature in the recruitment of T cells and the mechanism of T cell migration through TIME have not been studied comprehensively. In this work, we developed a hybrid discrete-continuum multi-scale model to study TIME. The mathematical model includes angiogenesis and T cell recruitment via tumor vasculature. Moreover, solid tumor growth, vascular growth and remodeling, interstitial fluid flow, hemodynamics, and blood rheology are all considered in the model. In addition, different aspects of T cells, including their migration, proliferation, subtype conversion, and interaction with tumor cells are thoroughly included. The model reproduces spatiotemporal distribution of tumor infiltrating T cells that mimics histopathological patterns. Furthermore, TIME model robustly recapitulates different phases of tumor immunoediting. We also examined a number of biomarkers to predict the outcome of immune checkpoint blockade (ICB) treatment. The results demonstrated that although tumor mutational burden (TMB) may predict non-responders to ICB, a combination of different biomarkers is essential to predict the majority of the responders. Based on our results, the ICB response rate varies significantly from 28 to 89% depending on the values of different parameters, even in the cases with high TMB.

SB7-H4 is a diagnostic biomarker in epithelial ovarian cancer and correlates to platinum resistance.

Ovarian cancer, with its high mortality rate among gynecological cancers, is often diagnosed late due to the lack of early diagnostic symptoms and biomarkers. The tumor immune microenvironment has become a focal point in cancer diagnostic and therapeutic research. Among these, B7-H4, a checkpoint protein, plays a crucial role in immune regulation and tumor suppression, contributing to immune evasion within the tumor microenvironment. This study aims to identify the concentration of soluble B7-H4(sB7-H4) in the plasma of patients with ovarian cancer and to evaluate its clinical significance. Through a comprehensive analysis involving enzyme-linked immunosorbent assay, immunohistochemistry, and multicolor immunofluorescence, we quantified sB7-H4 levels in patient plasma and ascites, correlating these findings with tissue expression and clinical outcomes. Results indicated a strong association between high sB7-H4 levels and advanced disease, surgical outcomes, lymphatic metastasis, and platinum resistance. When compared with traditional biomarkers CA125 and HE4, sB7-H4, especially in conjunction with these markers, enhances the diagnostic accuracy for epithelial ovarian cancer, offering insights into disease progression and therapeutic efficacy. This comprehensive analysis suggests that sB7-H4 is a promising biomarker for EOC, providing valuable insights into diagnosis, stage differentiation, treatment effectiveness, and prognosis.

Unraveling the Heterogeneity of Tumor Immune Microenvironment in Hepatocellular Carcinoma by SingleCell RNA Sequencing and its Implications for Prognosis and Therapeutic Response

Unraveling the Heterogeneity of Tumor Immune Microenvironment in Hepatocellular Carcinoma by SingleCell RNA Sequencing and its Implications for Prognosis and Therapeutic Response

Engineered microparticles modulate arginine metabolism to repolarize tumor-associated macrophages for refractory colorectal cancer treatment

BackgroundArginase is abundantly expressed in colorectal cancer and disrupts arginine metabolism, promoting the formation of an immunosuppressive tumor microenvironment. This significant factor contributes to the insensitivity of colorectal cancer to immunotherapy. Tumor-associated macrophages (TAMs) are major immune cells in this environment, and aberrant arginine metabolism in tumor tissues induces TAM polarization toward M2-like macrophages. The natural compound piceatannol 3ʹ-O-glucoside inhibits arginase activity and activates nitric oxide synthase, thereby reducing M2-like macrophages while promoting M1-like macrophage polarization.MethodsThe natural compounds piceatannol 3ʹ-O-glucoside and indocyanine green were encapsulated within microparticles derived from tumor cells, termed PG/ICG@MPs. The enhanced cancer therapeutic effect of PG/ICG@MP was assessed both in vitro and in vivo.ResultsPG/ICG@MP precisely targets the tumor site, with piceatannol 3ʹ-O-glucoside concurrently inhibiting arginase activity and activating nitric oxide synthase. This process promotes increased endogenous nitric oxide production through arginine metabolism. The combined actions of nitric oxide and piceatannol 3ʹ-O-glucoside facilitate the repolarization of tumor-associated macrophages toward the M1 phenotype. Furthermore, the increase in endogenous nitric oxide levels, in conjunction with the photodynamic effect induced by indocyanine green, increases the quantity of reactive oxygen species. This dual effect not only enhances tumor immunity but also exerts remarkable inhibitory effects on tumors.ConclusionOur research results demonstrate the excellent tumor-targeting effect of PG/ICG@MPs. By modulating arginine metabolism to improve the tumor immune microenvironment, we provide an effective approach with clinical translational significance for combined cancer therapy.

Clinical and immune responses to neoadjuvant fulvestrant with or without enzalutamide in ER+/Her2- breast cancer.

Most ER+ breast cancers (BC) express androgen receptors (AR). This randomized phase II trial of 4 months of neoadjuvant fulvestrant (Fulv) alone or with enzalutamide (Combo) assessed whether adding AR blockade to Fulv would limit residual tumor at the time of surgery, as measured by modified preoperative endocrine predictive index (PEPI) score. Eligible patients were women with ER+/HER2- primary BC cT2 or greater. Stratification factors were clinical node and T-stage. Fresh tumor biopsies were required at study entry, after 4 weeks on therapy (W5), and at surgery. Laboratory analyses on tumors included immunochemistry (IHC) for ER/PR/AR/GR and Ki67 protein, evaluation of gene expression, multiplex for myeloid lineage immune cells, reverse-phase protein array, and plasma metabolomic analyses. Of 69 consented patients, 59 were evaluable. Toxicity was as expected with endocrine therapy. Combo achieved PEPI = 0 more frequently (24%: 8/33) than Fulv (8%: 2/26). Ki67 was ≤10% across arms by W5 in 76% of tumors. Activation of mTOR pathway proteins was elevated in tumors with poor Ki67 response. Tumors in both arms showed decreased estrogen-regulated and cell division gene sets, while Combo arm tumors uniquely exhibited enrichment of immune activation gene sets, including interferon gamma, complement, inflammation, antigen processing, and B and T cell activation. Multiplex IHC showed significantly reduced tumor-associated macrophages and CD14+/HLADR-/CD68- MDSCs in Combo tumors at W5. In summary, Combo tumors showed a higher PEPI = 0 response, Ki67 response, and more activated tumor immune microenvironment than Fulv. The odds of response were 4.6-fold higher for patients with ILC versus IDC. (Trial registration: This trial is registered at Clinicaltrials.gov ( https://www.clinicaltrials.gov/study/NCT02955394?id=16-1042&rank=1 ). The trial registration number is NCT02955394. The full trial protocol is available under Study Details at the Clinicaltrials.gov link provided).

Losartan rewires the tumor-immune microenvironment and suppresses IGF-1 to overcome resistance to chemo-immunotherapy in ovarian cancer.

Ovarian cancer (OvCa) is the most lethal of the gynecologic malignancies. Immune checkpoint inhibitors, which have revolutionized the treatment of multiple malignancies, have had limited efficacy in OvCa patients. This lack of effectiveness is partly due to the abnormal ovarian tumor microenvironment (TME), displaying a desmoplastic, highly fibrotic extracellular matrix. High extracellular matrix deposition leads to a buildup of compressive forces that cause tumor blood vessel collapse, reduced vessel perfusion, poor delivery of drugs, and compromised trafficking of cytotoxic T-cells to these tumors. Using two syngeneic OvCa models, we tested the effect of losartan, a widely prescribed anti-hypertensive drug, on reprogramming the TME and chemosensitizing the cancer cells. Losartan treatment (i) reprograms the TME leading to increased vascular perfusion, and thus enhances drug delivery and immune effector cell intratumoral infiltration and function; and (ii) rewires the OvCa cells by suppressing the IGF-1 signaling, resulting in enhanced chemosensitivity. As a result of the combined tumor and stromal effects, losartan treatment enhances the efficacy of chemo-immunotherapy in OvCa models. The safety and low cost ( < $1-2/day) of losartan warrant rapid translation of our findings to patients with OvCa.

Construction and validation of an immune-related gene signature predictive of survival and response to immunotherapy for colorectal cancer.

Colorectal cancer is a common malignant tumor with the second incidence rate and the third mortality rate worldwide. In this study, we identified and validated an immune-related gene signature, explored the clinical and molecular characteristics of the signature-defined risk groups, and assessed its ability in predicting prognosis, immune cell infiltration and immunotherapy responses. The Cancer Genome Atlas database was used as the training set while GSE39582 database as the validation set. Immune-related hub genes were selected by the Least Absolute Shrinkage and Selection Operator-penalized Cox regression model, and the signature was then constructed by the selected genes and their relevant coefficients. Prognostic performance of the signature and the signature-base nomogram models were assessed by time-dependent receiver operating characteristic curves and calibration plots in both training and validation cohorts. Clinical and mutation-related data were downloaded and analyzed to explore their associations with signature-defined risk groups. Proportions of infiltrated immune cells was estimated via CIBERSORT algorithm and immunotherapy response was evaluated by immunophenoscore and tumor immune dysfunction and exclusion scores. Seven among 790 immune-related differentially-expressed genes were selected and use to construct the signature. The signature and signature-base nomograms showed promising prognostic performance in both training and validation cohorts. Signature-defined high-risk group was associated with advanced disease, poor pathological prognostic factors and less active immune infiltration microenvironment. Besides, the response to immunotherapy of high-risk group was predicted to be poorer by immunophenoscore and tumor immune dysfunction and exclusion scores. Our signature proved its efficacy in predicting prognosis, tumor immune microenvironment and responses to immunotherapy in colorectal cancer.

RNF144A as a potential risk gene for endometrial carcinoma: Insights from Mendelian randomization, bulk RNA sequencing, single-cell RNA, and experimental analysis.

Endometrial carcinoma (EC) is a prevalent gynecological malignancy that poses a significant threat to women's health worldwide. However, its pathogenesis and underlying mechanisms remains unclear. In this study, expression quantitative trait loci data, Mendelian randomization analysis, and differential expression analysis were performed to identify potential targets. A prognostic risk signature was subsequently constructed for EC patients based on the expression of these genes. Four bioinformatics algorithms, including generalized linear model, extreme gradient boosting, support vector machine, and random forest, were used to identify hub genes in EC. The expression of ring finger protein 144A (RNF144A) was validated using quantitative real-time polymerase chain reaction. Cellular proliferation and migration ability were evaluated using CCK-8 and Transwell assays, respectively. The genes RNF144A, ketohexokinase, and Rab interacting lysosomal protein like 2 were identified as potential targets for EC. Their differential expression was observed in EC patients, and Mendelian randomization analysis revealed a negative correlation between these genes and the development of EC. Mechanistic analyses suggested a strong association between these genes and the tumor immune microenvironment. The constructed risk signature was significantly associated with the prognosis, age, cancer stage, and grade of EC patients. Furthermore, based on interacted model algorithms, RNF144A was identified as a hub gene in EC. It was found to be significantly downregulated in EC samples, and its expression was positively correlated with the stage and grade of EC patients. In vitro experiments showed that overexpression of RNF144A significantly promoted cell growth and migration in EC cells. In conclusion, this study provides insights into the molecular mechanisms underlying EC progression and identifies preliminary candidate biomarkers for the development of EC treatment strategies.

PARP inhibitors enhance antitumor immune responses by triggering pyroptosis via TNF–caspase 8–GSDMD/E axis in ovarian cancer

BackgroundIn addition to their established action of synthetic lethality in tumor cells, poly(ADP-ribose) polymerase inhibitors (PARPis) also orchestrate tumor immune microenvironment (TIME) that contributes to suppressing tumor growth. However, it...

Ironing Out the Kinks: Arming Natural Killer Cells against Ovarian Cancer.

Ameliorating the tumor immune microenvironment is a key strategy to improve the therapeutic outcomes of patients with cancer. Sandoval and colleagues demonstrate that iron chelation enhances type I IFN production, promotes NK cell tumor trafficking and activation, and synergizes with chemotherapy drug cisplatin to reduce metastatic ovarian cancer progression in murine models. See related article by Sandoval et al., p. 1901.

Integrative analysis of H&E and IHC identifies prognostic immune subtypes in HPV related oropharyngeal cancer

BackgroundDeep learning techniques excel at identifying tumor-infiltrating lymphocytes (TILs) and immune phenotypes in hematoxylin and eosin (H&E)-stained slides. However, their ability to elucidate detailed functional characteristics of diverse cellular phenotypes within tumor immune microenvironment (TME) is limited. We aimed to enhance our understanding of cellular composition and functional characteristics across TME regions and improve patient stratification by integrating H&E with adjacent immunohistochemistry (IHC) images.MethodsA retrospective study was conducted on patients with Human Papillomavirus-positive oropharyngeal squamous cell carcinoma (OPSCC). Using paired H&E and IHC slides for 11 proteins, a deep learning pipeline was used to quantify tumor, stroma, and TILs in the TME. Patients were classified into immune inflamed (IN), immune excluded (IE), or immune desert (ID) phenotypes. By registering the IHC and H&E slides, we integrated IHC data to capture protein expression in the corresponding tumor regions. We further stratified patients into specific immune subtypes, such as IN, with increased or reduced CD8+ cells, based on the abundance of these proteins. This characterization provided functional insight into the H&E-based subtypes.ResultsAnalysis of 88 primary tumors and 70 involved lymph node tissue images reveals an improved prognosis in patients classified as IN in primary tumors with high CD8 and low CD163 expression (p = 0.007). Multivariate Cox regression analysis confirms a significantly better prognosis for these subtypes.ConclusionsIntegrating H&E and IHC data enhances the functional characterization of immune phenotypes of the TME with biological interpretability, and improves patient stratification in HPV( + ) OPSCC.