Expression patterns of novel immunotherapy targets in intermediate- and high-grade lung neuroendocrine neoplasms.

BACKGROUND: Advancements in immunotherapeutic approaches only had a modest impact on the therapy of lung neuroendocrine neoplasms (LNENs). Our multicenter study aimed to investigate the expression patterns of novel immunotherapy targets in intermediate- and high-grade LNENs. METHODS: The expressions of V-domain Ig suppressor of T cell activation (VISTA), OX40L, Glucocorticoid-induced TNF receptor (GITR), and T cell immunoglobulin and mucin domain 3 (TIM3) proteins were measured by immunohistochemistry in surgically resected tumor samples of 26 atypical carcinoid (AC), 49 large cell neuroendocrine lung cancer (LCNEC), and 66 small cell lung cancer (SCLC) patients. Tumor and immune cells were separately scored. RESULTS: Tumor cell TIM3 expression was the highest in ACs (p < 0.001), whereas elevated tumor cell GITR levels were characteristic for both ACs and SCLCs (p < 0.001 and p = 0.011, respectively). OX40L expression of tumor cells was considerably lower in ACs (vs. SCLCs; p < 0.001). Tumor cell VISTA expression was consistently low in LNENs, with no significant differences across histological subtypes. ACs were the least immunogenic tumors concerning immune cell abundance (p < 0.001). Immune cell VISTA and GITR expressions were also significantly lower in these intermediate-grade malignancies than in SCLCs or in LCNECs. Immune cell TIM3 and GITR expressions were associated with borderline prognostic significance in our multivariate model (p = 0.057 and p = 0.071, respectively). CONCLUSIONS: LNEN subtypes have characteristic and widely divergent VISTA, OX40L, GITR, and TIM3 protein expressions. By shedding light on the different expression patterns of these immunotherapy targets, the current multicenter study provides support for the future implementation of novel immunotherapeutic approaches.

Immune phenotype-genotype associations in primary clear cell renal cell carcinoma and matched metastatic tissue.

Adjuvant immunotherapy has been recently recommended for patients with metastatic ccRCC, but there are no tissue biomarkers to predict treatment response in ccRCC. Potential predictive biomarkers are mainly assessed in primary tumor tissue, whereas metastases remain understudied. To explore potential differences between genomic alterations and immune phenotypes in primary tumors and their matched metastases, we analyzed primary tumors (PTs) of 47 ccRCC patients and their matched distant metastases (METs) by comprehensive targeted parallel sequencing, whole-genome copy number variation (CNV) analysis, determination of microsatellite instability (MSI) and tumor mutational burden (TMB). We quantified the spatial distribution of tumor-infiltrating CD8+ T cells, and co-expression of the T-cell-exhaustion marker TOX by digital immunoprofiling and quantified tertiary lymphoid structures (TLS). Most METs were pathologically "cold". Inflamed, pathologically "hot" PTs were associated with a decreased disease-free survival (DFS), worst for patients with high levels of CD8+TOX+ T cells. Interestingly, inflamed METs showed a relative increase of exhausted CD8+TOX+ T cells and increased accumulative size of TLS compared to PTs. Integrative analysis of molecular and immune phenotypes revealed BAP1 and CDKN2A/B deficiency to be associated with an inflamed immune phenotype. Our results highlight the distinct spatial distribution and differentiation of CD8+ T cells at metastatic sites, and the association of an inflamed microenvironment with specific genomic alterations.

Egg-sensitised infants have elevated CD4+ effector memory T regulatory cells from birth.

BACKGROUND: IgE-mediated sensitisation to egg is common in infants. In some cases, the processes leading to egg sensitisation are established in early life, even before introduction to solid foods. The underlying mechanisms remain poorly understood. METHODS: We performed detailed immune cell phenotyping of peripheral blood mononuclear cells and determined in vitro cytokine responses following allergen specific and non-specific immune stimulation. To determine if unique immune profiles were linked to early-life egg sensitisation, we compared 92 infants at 4-6 months of age, with (EggCAP+, n = 41) and without (EggCAP-, n = 51) early egg sensitisation. Additionally, 47 cord blood samples were analysed. For a subset of participants (n = 39), matching cord blood mononuclear cells were assessed by flow cytometry to establish the impact of IgE sensitisation on immune developmental trajectories. RESULTS: EggCAP+ infants were found to exhibit a unique immune phenotype characterised by increased levels of circulating CD4+ T regulatory cells (Treg), CD4+ effector memory (EM) Treg and increased expression of the IgE receptor, FcεR1, on basophils. The increased CD4+ EM Treg profiles were already present in cord blood samples from EggCAP+ infants. A general Th2-skewing of the immune system was observed based on increased IL-13 production following phytohemagglutinin stimulation and by comparing immune developmental trajectories, EggCAP+ infants displayed an expansion of basophils and reduced levels of CD4- T cells compared to EggCAP- infants. CONCLUSIONS: Immunological profiles associated with egg sensitisation are detectable in infant circulation at 4-6 months of age and at birth. Understanding the immune mechanisms underlying early-life sensitisation could provide important insights for future food allergy prevention strategies.

Measuring the composition of the tumor microenvironment with transcriptome analysis: past, present and future.

Interactions between tumor cells and immune cells in the tumor microenvironment (TME) play a vital role the mechanisms of immune evasion, by which cancer cells escape immune elimination. Thus, the characterization and quantification of different components in the TME is a hot topic in molecular biology and drug discovery. Since the development of transcriptome sequencing in bulk tissue, single cells and spatial dimensions, there are increasing methods emerging to deconvolute and subtype the TME. This review discusses and compares such computational strategies and downstream subtyping analyses. Integrative analyses of the transcriptome with other data, such as epigenetics and T-cell receptor sequencing, are needed to obtain comprehensive knowledge of the dynamic TME.

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Fundamentals and Applications of Focused Ultrasound-Assisted Cancer Immune Checkpoint Inhibition for Solid Tumors.

Despite spectacular clinical successes across several cancer types, immune checkpoint inhibition is effective only in subgroups of patients and suffers from significant systemic toxicities, highlighting the need to understand and locally overcome the mechanisms of therapeutic resistance. Similarly to other therapeutics, immunotherapies face delivery challenges (for example, antibodies need to reach their targets) and immunological barriers that are unique to solid tumors and their microenvironment. Interestingly, focused ultrasound (FUS), with or without microbubbles, which has been shown to enhance gene and drug delivery, notably in oncology, has been recently found to trigger immunological responses. In recent years, there has been a strong emphasis on understanding the biological and immunological effects of FUS for cancer therapy, and FUS is now emerging as an approach that can improve cancer immunotherapy. We herein review: (1) the immunological barriers implicated in ICI resistance; (2) the fundamentals of FUS +/- MB and the current knowledge on leveraging FUS +/- MB bioeffects for improving ICI therapy efficacy; (3) the immune profile of tumor models that have been successfully treated with FUS and ICI; and finally, (4) we discuss the challenges ahead for translating FUS and MB treatments to the clinic, highlighting the exciting perspectives for this new research area.

Integrated genetic, epigenetic, and immune landscape of TP53 mutant AML and higher risk MDS treated with azacitidine.

Background: TP53 mutations are associated with an adverse prognosis in acute myeloid leukemia (AML) and higher-risk myelodysplastic syndromes (HR-MDS). However, the integrated genetic, epigenetic, and immunologic landscape of TP53-mutated AML/HR-MDS is not well defined. Objectives: To define the genetic, epigenetic, and immunologic landscape of TP53-mutant and TP53 wild-type AML and HR-MDS patients. Design: Post hoc analysis of TP53-mutant and TP53 wild-type patients treated on the randomized FUSION trial with azacitidine ± the anti-PD-L1 antibody durvalumab. Methods: We performed extensive molecular, epigenetic, and immunologic assays on a well-annotated clinical trial dataset of 61 patients with TP53-mutated disease (37 AML, 24 MDS) and 144 TP53 wild-type (89 AML, 55 MDS) patients, all of whom received azacitidine-based therapy. A 38 gene-targeted myeloid mutation analysis from screening bone marrow (BM) was performed. DNA methylation arrays, immunophenotyping and immune checkpoint expression by flow cytometry, and gene expression profiles by bulk RNA sequencing were assessed at baseline and serially during the trial. Results: Global DNA methylation from peripheral blood was independent of TP53 mutation and allelic status. AZA therapy led to a statistically significant decrease in global DNA methylation scores independent of TP53 mutation status. In BM from TP53-mutant patients, we found both a higher T-cell population and upregulation of inhibitory immune checkpoint proteins such as PD-L1 compared to TP53 wild-type. RNA sequencing analyses revealed higher expression of the myeloid immune checkpoint gene LILRB3 in TP53-mutant samples suggesting a novel therapeutic target. Conclusion: This integrated analysis of the genetic, epigenetic, and immunophenotypic landscape of TP53 mutant AML/HR-MDS suggests that differences in the immune landscape resulting in an immunosuppressive microenvironment rather than epigenetic differences contribute to the poor prognosis of TP53-mutant AML/HR-MDS with mono- or multihit TP53 mutation status. Trial registration: FUSION trial (NCT02775903).

Tumor battlefield within inflamed, excluded or desert immune phenotypes: the mechanisms and strategies.

The tumor microenvironment demonstrates great immunophenotypic heterogeneity, which has been leveraged in traditional immune-hot/cold tumor categorization based on the abundance of intra-tumoral immune cells. By incorporating the spatial immune contexture, the tumor immunophenotype was further elaborated into immune-inflamed, immune-excluded, and immune-desert. However, the mechanisms underlying these different immune phenotypes are yet to be comprehensively elucidated. In this review, we discuss how tumor cells and the tumor microenvironment interact collectively to shape the immune landscape from the perspectives of tumor cells, immune cells, the extracellular matrix, and cancer metabolism, and we summarize potential therapeutic options according to distinct immunophenotypes for personalized precision medicine.

MOICS, a novel classier deciphering immune heterogeneity and aid precise management of clear cell renal cell carcinoma at multiomics level.

Recent studies have indicated that the tumor immune microenvironment plays a pivotal role in the initiation and progression of clear cell renal cell carcinoma (ccRCC). However, the characteristics and heterogeneity of tumor immunity in ccRCC, particularly at the multiomics level, remain poorly understood. We analyzed immune multiomics datasets to perform a consensus cluster analysis and validate the clustering results across multiple internal and external ccRCC datasets; and identified two distinctive immune phenotypes of ccRCC, which we named multiomics immune-based cancer subtype 1 (MOICS1) and subtype 2 (MOICS2). The former, MOICS1, is characterized by an immune-hot phenotype with poor clinical outcomes, marked by significant proliferation of CD4+ and CD8+ T cells, fibroblasts, and high levels of immune inhibitory signatures; the latter, MOICS2, exhibits an immune-cold phenotype with favorable clinical characteristics, characterized by robust immune activity and high infiltration of endothelial cells and immune stimulatory signatures. Besides, a significant negative correlation between immune infiltration and angiogenesis were identified. We further explored the mechanisms underlying these differences, revealing that negatively regulated endopeptidase activity, activated cornification, and neutrophil degranulation may promote an immune-deficient phenotype, whereas enhanced monocyte recruitment could ameliorate this deficiency. Additionally, significant differences were observed in the genomic landscapes between the subtypes: MOICS1 exhibited mutations in TTN, BAP1, SETD2, MTOR, MUC16, CSMD3, and AKAP9, while MOICS2 was characterized by notable alterations in the TGF-ß pathway. Overall, our work demonstrates that multi-immune omics remodeling analysis enhances the understanding of the immune heterogeneity in ccRCC and supports precise patient management.

Bariatric Surgery Induces Alterations in the Immune Profile of Peripheral Blood T Cells.

Low-grade inflammation is closely linked to obesity and obesity-related comorbidities; therefore, immune cells have become an important topic in obesity research. Here, we performed a deep phenotypic characterization of circulating T cells in people with obesity, using flow cytometry. Forty-one individuals with obesity (OB) and clinical criteria for bariatric surgery were enrolled in this study. We identified and quantified 44 different circulating T cell subsets and assessed their activation status and the expression of immune-checkpoint molecules, immediately before (T1) and 7-18 months after (T2) the bariatric surgery. Twelve age- and sex-matched healthy individuals (nOB) were also recruited. The OB participants showed higher leukocyte counts and a higher percentage of neutrophils. The percentage of circulating Th1 cells were negatively correlated to HbA1c and insulin levels. OB Th1 cells displayed a higher activation status and lower PD-1 expression. The percentage of Th17 and Th1/17 cells were increased in OB, whereas the CD4+ Tregs' percentage was decreased. Interestingly, a higher proportion of OB CD4+ Tregs were polarized toward Th1- and Th1/17-like cells and expressed higher levels of CCR5. Bariatric surgery induced the recovery of CD4+ Treg cell levels and the expansion and activation of Tfh and B cells. Our results show alterations in the distribution and phenotype of circulating T cells from OB people, including activation markers and immune-checkpoint proteins, demonstrating that different metabolic profiles are associated to distinct immune profiles, and both are modulated by bariatric surgery.

Machine learning-based derivation and validation of three immune phenotypes for risk stratification and prognosis in community-acquired pneumonia: a retrospective cohort study.

Background: The clinical presentation of Community-acquired pneumonia (CAP) in hospitalized patients exhibits heterogeneity. Inflammation and immune responses play significant roles in CAP development. However, research on immunophenotypes in CAP patients is limited, with few machine learning (ML) models analyzing immune indicators. Methods: A retrospective cohort study was conducted at Xinhua Hospital, affiliated with Shanghai Jiaotong University. Patients meeting predefined criteria were included and unsupervised clustering was used to identify phenotypes. Patients with distinct phenotypes were also compared in different outcomes. By machine learning methods, we comprehensively assess the disease severity of CAP patients. Results: A total of 1156 CAP patients were included in this research. In the training cohort (n=809), we identified three immune phenotypes among patients: Phenotype A (42.0%), Phenotype B (40.2%), and Phenotype C (17.8%), with Phenotype C corresponding to more severe disease. Similar results can be observed in the validation cohort. The optimal prognostic model, SuperPC, achieved the highest average C-index of 0.859. For predicting CAP severity, the random forest model was highly accurate, with C-index of 0.998 and 0.794 in training and validation cohorts, respectively. Conclusion: CAP patients can be categorized into three distinct immune phenotypes, each with prognostic relevance. Machine learning exhibits potential in predicting mortality and disease severity in CAP patients by leveraging clinical immunological data. Further external validation studies are crucial to confirm applicability.