Composition Of Immune Infiltrate Research Articles

Emerging Treatments Targeting the Tumor Microenvironment for Advanced Chondrosarcoma.

Chondrosarcoma (ChS), a malignant cartilage-producing tumor, is the second most frequently diagnosed osseous sarcoma after osteosarcoma. It represents a very heterogeneous group of malignant chemo- and radiation-resistant neoplasms, accounting for approximately 20% of all bone sarcomas. The majority of ChS patients have a good prognosis after a complete surgical resection, as these tumors grow slowly and rarely metastasize. Conversely, patients with inoperable disease, due to the tumor location, size, or metastases, represent a great clinical challenge. Despite several genetic and epigenetic alterations that have been described in distinct ChS subtypes, very few therapeutic options are currently available for ChS patients. Therefore, new prognostic factors for tumor progression as well as new treatment options have to be explored, especially for patients with unresectable or metastatic disease. Recent studies have shown that a correlation between immune infiltrate composition, tumor aggressiveness, and survival does exist in ChS patients. In addition, the intra-tumor microvessel density has been proven to be associated with aggressive clinical behavior and a high metastatic potential in ChS. This review will provide an insight into the ChS microenvironment, since immunotherapy and antiangiogenic agents are emerging as interesting therapeutic options for ChS patients.

Tumor-derived exosomes RNA expression profiling identifies the prognosis, immune characteristics, and treatment in HR+/HER2-breast cancer.

Exosomes play crucial roles in intercellular communication and are involved in the onset and progression of various types of cancers, including breast cancer. However, the RNA composition of breast cancer-derived exosomes has not been comprehensively explored. We conducted microarray assays on exosomes isolated from breast cancer and healthy breast epithelial cells from three patients with hormone receptor (HR) +/ human epidermal growth factor receptor (HER2) - breast cancer and identified 817 differentially expressed genes (DEGs). Among these, 315 upregulated tumor-derived exosome genes (UTEGs) were used to classify HR+/HER2- breast cancers into two categories, revealing a difference in survival rates between the groups. We developed and validated a novel prognostic exosome score (ES) model consisting of four UTEGs that provides a refined prognosis prediction in HR+/HER2-breast cancer. ES reflects various immune-related features, including somatic variation, immunogenicity, and tumor immune infiltrate composition. Our findings indicate a considerable positive correlation between the ES and drug sensitivity values for vincristine, paclitaxel, and docetaxel. However, ES was remarkably higher in the endocrine therapy non-responder group than in the responder group. Immunohistochemistry confirmed the remarkable expression of the four model genes in tumor tissues, and their expression in MCF-7 cell exosomes was higher than that in MCF10A cells, as verified via qPCR. In summary, tumor-derived exosome genes provide novel insights into the subtyping, prognosis, and treatment of HR+/HER2-breast cancer.

Poster 150: Immunophenotyping of Synovial Tissue in Adolescents Undergoing ACL Reconstruction Reveals Distinct Inflammatory Responses to Injury

Objectives: Tears of the anterior cruciate ligament (ACL) are common in the pediatric athletic population. In spite of trends towards early surgical reconstruction to minimize the risk of secondary meniscus and cartilage injuries, long term disruption of knee joint homeostasis and progression to post- traumatic osteoarthritis (PTOA) occurs in 50-90% of patients - a particularly challenging problem in this young cohort. The exact pathogenesis of PTOA after ACL injury and reconstruction remains unknown. Evidence from animal models of PTOA suggests a critical role of synovial inflammatory infiltration in both the onset and progression of PTOA. However, there is a scarcity of in vivo human data documenting the synovial inflammatory response to ACL injury. One recent study has looked at immune cell composition in synovial fluid, but there are no comparable publications using synovial tissue. Our primary objective was to use flow cytometry with an advanced immune cell panel to provide a snapshot of the cellular composition of immune infiltrates in the synovium of adolescent patients at the time of ACL reconstruction. Our secondary objective was to look for correlations between demographic and injury parameters and inflammatory cell composition. Methods: Patients between the ages of 12 and 18 years who were undergoing primary ACL reconstruction were enrolled in an IRB-approved prospective study. Exclusion criteria included multiligament knee injuries, revision ACL reconstruction, history of prior knee surgery, and history of inflammatory joint disease. Demographic variables and intraoperative data were recorded. At the time of surgery, an arthroscopic synovial biopsy from the prefemoral synovium was obtained. Synovium tissue was enzymatically digested into a single cell suspension for immune profiling by multicolor flow cytometry. Data was acquired on a BD lsrFortessa flow cytometer and analyzed with FlowJo v10. Statistical analyses were performed with GraphPad Prism including parametric ANOVA (one-way or two- way), simple linear regression, Kruskal Wallis analysis of variance, Mann Whitney T-test, and parallel Principal component analyses (Eigenvalue with Monte Carlo simulation). Heat map variable scaling was calculated relative to the mean and standard deviation of all measurements. Results: Twelve patients were prospectively enrolled in the study (33% male, 67% female, n = 12). Mean age was 15.5 +/- 2.02 years. Median time between injury and surgery was 35.5 days (23.3-67.5). Meniscal tears were present in 58.3% of patients (8.3% medial only, 33.3% lateral only, 16.7% both). Cells isolated from synovium were 36.8% fibroblasts, 9.89% fibrocytes, and 36.0% hematopoietic lineage cells (Fig. 1A). Within the hematopoietic lineage, the dominant cell types were monocytes, macrophages, and T-cells (Fig. 1B). Principle component analysis (PCA) revealed three immunophenotypes. Immunotype 1 had higher mast cell content than other groups and fewer inflammatory cells such as T cells, B cells, and macrophages. Immunotype 2 had strong T/B cell infiltration and lower levels of innate immune cells. These patients also had the highest overall levels of inflammatory cells (Figure 2). Immunotype 3 had a strong innate immune response - in particular higher levels of M2 polarized macrophages - and significantly fewer T/B cells. There were no obvious effects of age, skeletal maturity, or the presence of meniscal tears on immunotype (Table 1). There was a trend towards a correlation between delay in surgery and classification within immunotype 1 (p = 0.09, Table 1). Conclusions: Our study provides the first in vivo analysis of inflammatory cell behavior in the synovium of ACL injured knees. In young patients undergoing primary ACL reconstruction, three immunotypes were discovered. Our pilot data suggest a possible relationship between delay in surgery and a high prevalence of synovial mast cells. This would be of particular interest since mast cells are known to play a role in the development of OA and possibly PTOA. In the more acute setting, two separate immunotypes were encountered, one with heavy inflammation and a predominance of T/B cells, and the other with more moderate inflammation and a higher percentage of innate immune cells / M2 polarized macrophages. These were not clearly tied to patient demographic factors, and could represent intrinsic differences in the response to injury. Future work investigating the correlation between initial immunotype and clinical outcomes – in particular the development of PTOA – may provide insight into the role of synovial inflammation in post-ACL joint health and degeneration, as well as provide strategies for personalized treatments in the prevention of PTOA. [Table: see text]

Nischarin expression may have differing roles in male and female melanoma patients.

Due to the development of resistance to previously effective therapies, there is a constant need for novel treatment modalities for metastatic melanoma. Nischarin (NISCH) is a druggable scaffolding protein reported as a tumor suppressor and a positive prognostic marker in breast and ovarian cancers through regulation of cancer cell survival, motility and invasion. The aim of this study was to examine the expression and potential role of nischarin in melanoma. We found that nischarin expression was decreased in melanoma tissues compared to the uninvolved skin, and this was attributed to the presence of microdeletions and hyper-methylation of the NISCH promoter in the tumor tissue. In addition to the previously reported cytoplasmic and membranous localization, we observed nischarin in the nuclei in melanoma patients' tissues. NISCH expression in primary melanoma had favorable prognostic value for female patients, but, unexpectedly, high NISCH expression predicted worse prognosis for males. Gene set enrichment analysis suggested significant sex-related disparities in predicted association of NISCH with several signaling pathways, as well as with different tumor immune infiltrate composition in male and female patients. Taken together, our results imply that nischarin may have a role in melanoma progression, but that fine-tuning of the pathways it regulates is sex-dependent. KEY MESSAGES: Nischarin is a tumor suppressor whose role has not been investigated in melanoma. Nischarin expression was downregulated in melanoma tissue compared to the normal skin. Nischarin had the opposite prognostic value in male and female melanoma patients. Nischarin association with signaling pathways differed in females and males. Our findings challenge the current view of nischarin as a universal tumor suppressor.

Identification of biomarkers related to sepsis diagnosis based on bioinformatics and machine learning and experimental verification.

Sepsis is a systemic inflammatory response syndrome caused by bacteria and other pathogenic microorganisms. Every year, approximately 31.5 million patients are diagnosed with sepsis, and approximately 5.3 million patients succumb to the disease. In this study, we identified biomarkers for diagnosing sepsis analyzed the relationships between genes and Immune cells that were differentially expressed in specimens from patients with sepsis compared to normal controls. Finally, We verified its effectiveness through animal experiments. Specifically, we analyzed datasets from four microarrays(GSE11755、GSE12624、GSE28750、GSE48080) that included 106 blood specimens from patients with sepsis and 69 normal human blood samples. SVM-RFE analysis and LASSO regression model were carried out to screen possible markers. The composition of 22 immune cell components in patients with sepsis were also determined using CIBERSORT. The expression level of the biomarkers in Sepsis was examined by the use of qRT-PCR and Western Blot (WB). We identified 50 differentially expressed genes between the cohorts, including 2 significantly upregulated and 48 significantly downregulated genes, and KEGG pathway analysis identified Salmonella infection, human T cell leukemia virus 1 infection, Epstein-Barr virus infection, hepatitis B, lysosome and other pathways that were significantly enriched in blood from patients with sepsis. Ultimately, we identified COMMD9, CSF3R, and NUB1 as genes that could potentially be used as biomarkers to predict sepsis, which we confirmed by ROC analysis. Further, we identified a correlation between the expression of these three genes and immune infiltrate composition. Immune cell infiltration analysis revealed that COMMD9 was correlated with T cells regulatory (Tregs), T cells follicular helper, T cells CD8, etal. CSF3R was correlated with T cells regulatory (Tregs), T cells follicular helper, T cells CD8, etal. NUB1 was correlated with T cells regulatory (Tregs), T cells gamma delta, T cells follicular helper, etal. Taken together, our findings identify potential new diagnostic markers for sepsis that shed light on novel mechanisms of disease pathogenesis and, therefore, may offer opportunities for therapeutic intervention.

Association of tumor-infiltrating lymphocytes (TILs) with clinicopathologic characteristics and prognosis in young women with HR+/HER2- breast cancer (BC).

505 Background: Increased TILs are associated with better prognosis in triple-negative BC, including in patients (pts) age < 40. However, the role of TILs remains unclear in HR+/HER2- BC and little data exist in young pts, in whom immune microenvironment could be altered by age-related host/tumor differences. We assessed the extent and composition of immune infiltration in HR+ tumors of young women and correlated with clinicopathologic features and survival outcomes. Methods: From a prospective cohort study of women with BC diagnosed age ≤40, we identified those with stage I-III HR+/HER2- BC and available pre-treatment (tx) tumor tissue. Multiplexed immunofluorescence was used to quantify cytotoxic T (CD8+), T helper (Th, CD3+CD8-), T regulatory (Tregs, FOXP3+CD3+) and exhausted T (PD1+CD8+) cells in stroma and tumor. Univariate analyses tested associations between clinicopathologic variables and immune markers by high or low expression, divided based on median. High vs. low TILs were evaluated in Cox regression analyses for invasive breast cancer-free survival (iBCFS), distant disease-free survival (DDFS) and overall survival (OS). Results: In 390 pts, median age was 37 years (21-40), most had grade 2 (51%), T1 (65%), N0 (63%) tumors and 67% received adjuvant chemotherapy. Black pts (n = 17) had higher expression of stromal CD8+ ( P= .010), FOXP3+CD3+ ( P= .027) and PD1+CD8+ TILs ( P= .043); intratumoral TILs did not differ by race. Older age (36-40) was associated with high expression of CD8+ ( P= .033) and PD1+CD8+ TILs ( P= .031) within stroma and CD3+CD8- TILs within tumor ( P= .046). Grade 3 tumors had higher stromal and intratumoral expression of CD3+CD8- ( P= .002; P< .001) and FOXP3+CD3+ TILs ( P= .020; P< .001). No differences in TILs were seen according to recency of pregnancy, BRCA1/2 status or T/N stage. Over a median follow up of 8 years, 85 iBCFS events, 64 DDFS events and 37 deaths occurred. High stromal expression of CD3+CD8- TILs was associated with better iBCFS (HR 0.49, P= .002) and DDFS (HR 0.57, P= .046), which remained significant when adjusted for T/N stage, grade and chemotherapy (iBCFS HR 0.41, P< .001; DDFS HR 0.45, P= .008). High stromal expression of CD3+CD8- and FOXP3+CD3+ TILs was associated with better OS (HR 0.47, P= .038) and iBCFS (HR 0.58, P= .018), respectively, on adjusted analyses only. High intratumoral expression of CD3+CD8- and FOXP3+CD3+ TILs was associated with better iBCFS (HR 0.59, P= .025; HR 0.63, P= .043) after adjustment only. Conclusions: The distribution of TIL subtypes in young women’s HR+ BC varied according to race, age and grade. High stromal and intratumoral expression of Th and Tregs was associated with improved BC outcomes. Characterization of immune cell subsets could help refine the prognostic value of TILs in HR+ BC, particularly in young pts who may benefit from individualized escalated/de-escalated tx strategies.

Celloscope: a probabilistic model for marker-gene-driven cell type deconvolution in spatial transcriptomics data

Spatial transcriptomics maps gene expression across tissues, posing the challenge of determining the spatial arrangement of different cell types. However, spatial transcriptomics spots contain multiple cells. Therefore, the observed signal comes from mixtures of cells of different types. Here, we propose an innovative probabilistic model, Celloscope, that utilizes established prior knowledge on marker genes for cell type deconvolution from spatial transcriptomics data. Celloscope outperforms other methods on simulated data, successfully indicates known brain structures and spatially distinguishes between inhibitory and excitatory neuron types based in mouse brain tissue, and dissects large heterogeneity of immune infiltrate composition in prostate gland tissue.

Abstract 2389: In vivo multiphoton autofluorescence imaging is sensitive to CD8 T cell and tumor cell metabolic changes during immunotherapy in a murine melanoma model

Abstract Introduction: In vivo multiphoton autofluorescence microscopy provides live, label free, single cell imaging of metabolic changes. These metabolic changes are quantified via the metabolic coenzymes NAD(P)H and FAD which are autofluorescent molecules endogenous to all cells. Metabolic reprogramming of tumor and immune cells is closely associated with cancer progression and cell phenotype. We aim to study metabolic changes during administration of an effective, triple-combination immunotherapy within murine melanoma tumors. This therapy includes external beam radiation, intratumoral hu14.18-IL2 immunocytokine (anti-GD2 mAb fused to IL2, provided by Anyxis Immuno-Oncology GmbH of Vienna, Austria), and intraperitoneal anti-CTLA-4 leading to in situ vaccination and cure of GD2+ murine tumors. Previous work has shown that a T cell response is critical to the efficacy of this therapy, so we created an mCherry-labeled T cell mouse model to study this response. Methods: We implanted syngeneic B78 (GD2+) melanoma cells into the flanks of mCherry-labeled CD8 T cell reporter mice (C57Bl/6 background) to induce tumors. Under anesthesia, skin flap surgery was performed and tumors were imaged at several time points during therapy. Multiphoton imaging was performed to collect NAD(P)H, FAD, mCherry, and collagen signal with a 40X objective. Fluorescence lifetime data was collected using time correlated single photon counting electronics. Tissues were harvested and analyzed via flow cytometry and multiplex immunofluorescence to corroborate intravital imaging findings and characterize the immune infiltrate. Results: Here we demonstrate that our in vivo imaging is sensitive to metabolic changes in both B78 melanoma and CD8 T cells from immunotherapy treated versus control tumors. These metabolic differences include changes in protein binding, redox balance, and fluorescence lifetime. We also show remodeling of collagen, a major component of the extracellular matrix, during immunotherapy that may be explained by an observed decrease in macrophages. Flow cytometry and multiplex immunofluorescence illustrate changes in the immune infiltrate composition, activation, cytotoxicity, and spatial distribution during therapy. We are also currently investigating metabolic changes in an MC38 mouse model - a hot tumor model - that we anticipate will provide excellent metabolic contrast to our B78 immunologically cold tumor model. Conclusions: These results show that in vivo metabolic imaging enables single cell quantification of metabolic changes in tumor and immune cells during therapy. Combined with other traditional assays, we can elucidate key immune cell populations and the crucial timepoints during therapy where changes are occurring. With continued efforts, this imaging platform may be leveraged to develop new combinations of immunotherapies. Citation Format: Alexa R. Heaton, Anna Hoefges, Peter R. Rehani, Nathaniel J. Burkard, Arika S. Feils, Dan V. Spiegelman, Noah W. Tsarovsky, Alina A. Hampton, Amy K. Erbe Gurel, Alexander L. Rakhmilevich, Paul M. Sondel, Melissa C. Skala. In vivo multiphoton autofluorescence imaging is sensitive to CD8 T cell and tumor cell metabolic changes during immunotherapy in a murine melanoma model [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2389.

Genome-Wide Analysis of the Regulatory Network of Immune Infiltration-Related RAS and RBP Regulators in Metastatic Osteosarcoma

Background: Osteosarcoma is a primary malignant bone tumor commonly found in children and young adults. The prognosis of patients with metastatic osteosarcoma is very poor. Different studies have shown that immune infiltration is associated with osteosarcoma metastasis. However, the cellular composition of immune infiltrates may vary slightly in osteosarcoma metastases. Recent studies have reported that abnormal alternative splicing regulation is related to the occurrence and development of cancer.

Bioinformatics-based diagnosis and evaluation of several pivotal genes and pathways associated with immune infiltration at different time points in spinal cord injury

ABSTRACT Spinal Cord Injury (SCI) is a devastating neurological event. To assess the degree of spinal cord damage and classify the injury, it is recommended to use the 2019 version of the AIS standard. The severity of trauma was evaluated using the Trauma Severity Score, and various classification systems have been proposed for injuries at different parts and segments of the spine. Understanding the regulated signaling pathways and immune processes following SCI can lead to a better understanding of SCI-induced biomarkers and their underlying mechanisms. In this study, two gene expression datasets (GSE464 and GSE45006) from the Gene Expression Omnibus database were utilized. Differential gene expression and co-expression network analysis were performed, revealing 370 shared genes in the 3-day group and 111 shared genes in the 14-day group after SCI. The study used functional enrichment analysis methods such as Gene Set Enrichment Analysis, Gene Ontology, and Kyoto Encyclopedia of Genes and Genomes. The ssGSEA method was used to assess the levels and composition of immune infiltration in both the sham (control) and SCI groups. The single-cell transcriptomics dataset GSE182803 was analyzed to identify genes associated with immune marker cells. Four key genes (Ptgs2, Fn1, Ccl2, and Icam1) were identified in the 3-day group, while only one gene (Cyp51) was identified in the 14-day group after SCI. The findings offer significant insights into the immune-related genes and signaling pathways involved in secondary SCI at different time points and hold potential for the development of intervention strategies for acute and chronic post-SCI.

Oral Lichen Planus and Oral Squamous Cell Carcinoma share key oncogenic signatures

To investigate similarities in the gene profile of Oral Lichen Planus and Oral Squamous Cell Carcinoma that may justify a carcinogenic potential, we analyzed the gene expression signatures of Oral Lichen Planus and Oral Squamous Cell Carcinoma in early and advanced stages. Based on gene expression data from public databases, we used a bioinformatics approach to compare expression profiles, estimate immune infiltrate composition, identify differentially and co-expressed genes, and propose putative therapeutic targets and associated drugs. Our results revealed gene expression patterns related to processes of keratinization, keratinocyte differentiation, cell proliferation and immune response in common between Oral Lichen Planus and early and advanced Oral Squamous Cell Carcinoma, with the cornified envelope formation and antigen processing cross-presentation pathways in common between Oral Lichen Planus and early Oral Squamous Cell Carcinoma. Together, these results reveal that key tumor suppressors and oncogenes such as PI3, SPRR1B and KRT17, as well as genes associated with different immune processes such as CXCL13, HIF1A and IL1B are dysregulated in OLP.

840 Unsupervised learning reveals different degrees of heterogeneity as well as cell involvement in cutaneous lupus erythematous antimalarial treatment response subgroups

First-line treatment for cutaneous lupus erythematosus involves the use of antimalarials. Treatment response is highly variable with some patients responding well to hydroxychloroquine (HCQ), some necessitating the addition of quinacrine (QC) and others refractory to treatment from both (NR). Here we used unsupervised learning to highlight differences between the immune infiltrate composition of the three treatment groups. Infiltrate composition was characterized using imaging mass cytometry, where we stained biopsies (12 HCQ, 11 QC, 20 NR) with two separate panels of 37-metal conjugated antibodies, which enabled the measurement of different cell types, cytokines and pathway proteins within the tissue sample.

Automated tumor immunophenotyping and response to immunotherapy in non-small cell lung cancer using a spatial statistics approach.

2626 Background: Based on the clinical success of immuno-oncology therapeutics, tissue-based, biomarker analyses have shifted from a focus on tumor cell phenotypes to spatial and functional analyses of the tumor immune environment. Distribution and composition of immune infiltrates have shown prognostic or predictive value in various studies; however, standardized approaches to categorize tumors into “Desert”, “Excluded” or “Inflamed” immunophenotypes based on the density and pattern of immune infiltrates are missing. This categorization is typically based on visual inspection of a stained tissue section; it is labor-intensive and associated with poor inter-observer concordance. To eliminate these barriers we developed an automated approach that relies on a set of derived spatial features and named this analysis pipeline LATIS (metric Learning based Automated Tumor Immunophenotyping with Spatial statistics). Methods: We used two clinical trials, POPLAR (phase II; n=258) and OAK (phase III; n=623) that compared anti-PD-L1 treatment vs chemotherapy in patients with advanced non-small cell lung cancer to develop and validate this approach. LATIS utilizes scans of slides stained immunohistochemically for CD8 and cytokeratin (CK); images were tiled and classified according to CK status (positive/negative). First, CD8 positive and CK density was calculated for each tile. Twenty six spatial features were then extracted for each tiled image scan. We used a labeled (manual immunophenotype calls) POPLAR dataset to learn a metric that separates classes of labeled data best with respect of spatial features provided for each data point. Then, to co-embed OAK dataset with POPLAR dataset into the same space, we used that learned metric as a measure of distance between new unlabeled points (OAK data set). K-means clustering in the embedded space was used to identify clusters of data points followed by QFMatch to assign class labels (“Inflamed”, “Excluded”, “Desert”) to each data point. Results: LATIS successfully relates spatial features to both, manual reads and patient response to therapy. In OAK, anti-PD-L1 treated patients experienced longer median overall survival (OS) when tumors showed intra-epithelial CD8+ cells (Inflamed) compared to tumors with a stromal pattern of CD8+ cells (Excluded) or a low density of CD8+ cells (Desert): 17.6 months vs 10.3 (Excluded) vs 12.1 (Desert) [p=0.0061]. Median progression-free survival (PFS) was 3.2 months (Inflamed) vs 2.6 (Excluded) vs 1.4 (Desert) [p=0.00058]. OS and PFS were not significantly different for the three categories in chemotherapy only arm. Conclusions: We suggest that tumor immunophenotype categories generated in an automated fashion by LATIS can serve as predictive biomarker for cancer immunotherapy.

Intratumoral Electroporation of Plasmid Encoded IL12 and Membrane-Anchored Anti-CD3 Increases Systemic Tumor Immunity.

This DNA-encodable polyclonal T-cell stimulator (membrane-anchored anti-CD3 plasmid) may represent a key addition to intratumoral IL12 therapies in the clinic.

Muscle inflammatory pattern in alpha- and gamma-sarcoglycanopathies.

Since the immune system plays a role in the pathogenesis of several muscular dystrophies, we aim to characterize several muscular inflammatory features in α- (LGMD R3) and γ-sarcoglycanopathies (LGMD R5). We explored the expression of major histocompatibility complex class I molecules (MHCI), and we analyzed the composition of the immune infiltrates in muscle biopsies from 10 patients with LGMD R3 and 8 patients with LGMD R5, comparing the results to Duchenne muscular dystrophy patients (DMD). A consistent involvement of the immune response was observed in sarcoglycanopathies, although it was less evident than in DMD. LGMD R3-R5 and DMD shared an abnormal expression of MHCI, and the composition of the muscular immune cell infiltrate was comparable. These findings might serve as a rationale to fine-tune a disease-specific immunomodulatory regimen, particularly relevant in view of the rapid development of gene therapy for sarcoglycanopathies.

The pan-cancer landscape of crosstalk between epithelial-mesenchymal transition and immune evasion relevant to prognosis and immunotherapy response

An emerging body of evidence has recently recognized the coexistence of epithelial-mesenchymal transition (EMT) and immune response. However, a systems-level view and survey of the interplay between EMT and immune escape program, and their impact on tumor behavior and clinical outcome across various types of cancer is lacking. Here, we performed comprehensive multi-omics analyses to characterize the landscape of crosstalk between EMT and immune evasion and their clinical relevance across 17 types of solid cancer. Our study showed the presence of complex and dynamic immunomodulatory crosstalk between EMT and immune evasion shared by pan-cancer, and the crosstalk was significantly associated with cancer prognosis and immunotherapy response. Integrative quantitative analyses of genomics and immunogenomics revealed that cellular composition of immune infiltrates, non-synonymous mutation burden, chromosomal instability and oncogenic gene alterations are associated with the balance between EMT and immune evasion. Finally, we proposed a scoring model termed EMT-CYT Index (ECI) to quantify the EMT-immunity axis, which was a superior predictor of prognosis and immunotherapy response across different malignancies. By providing a systematic overview of crosstalk between EMT and immune evasion, our study highlights the potential of pan-cancer EMT-immunity crosstalk as a paradigm for dissecting molecular mechanisms underlying cancer progression and guiding more effective and generalized immunotherapy strategies.

ST8Sia6 expression in beta cells mitigates onset of autoimmune diabetes in the murine NOD model

Abstract Cell surface hypersialylation is used by malignant cells as a survival mechanism, leveraging interactions with inhibitory Siglec receptors to dampen immune rejection. In this study, we harnessed this mechanism to prevent autoimmune rejection of beta cells in the context of Type 1 Diabetes. Mice were engineered to express the sialyltransferase ST8Sia6 in a beta cell specific manner (βST mice) and crossed to the non-obese diabetic (NOD) mouse model of spontaneous autoimmune diabetes. Both female and male littermates on the NOD background developed diabetes by 300 days (56% and 80.8%, respectively). βST mice, however, demonstrated minimal occurrence of disease (5.3% and 16.6%). Additionally, histologic analysis of pancreas sections from non-diabetic βST and littermate mice suggested a similar degree of immune infiltration at 4 and 8 weeks of age, but the severity of infiltration was drastically reduced only in the βST mice at 20 weeks of age. IHC for various leukocyte markers suggested no difference in composition of immune infiltrates at the 8 week time point. To determine whether protection was due to central or peripheral mechanisms, euglycemic βST and littermate mice at 16 weeks of age were challenged with anti-PD-L1 monoclonal antibodies; both groups resulted in similar induction of disease, suggesting that ST8Sia6 dependent protection occurs peripherally. Physiologically, an insulin tolerance test demonstrated no difference between βST mice and littermates, suggesting no systemic effects of beta cell ST8Sia6 expression. The induced expression of ST8Sia6 has been shown to mitigate autoimmune attack in the NOD mouse and presents a novel path forward for improving the success of curative islet transplant into diabetic patients.

Immune microenvironment and intrinsic subtyping in hormone receptor-positive/HER2-negative breast cancer

Little is known regarding the interaction between immune microenvironment and tumor biology in hormone receptor (HR)+/HER2− breast cancer (BC). We here assess pretreatment gene-expression data from 66 HR+/HER2− early BCs from the LETLOB trial and show that non-luminal tumors (HER2-enriched, Basal-like) present higher tumor-infiltrating lymphocyte levels than luminal tumors. Moreover, significant differences in immune infiltrate composition, assessed by CIBERSORT, were observed: non-luminal tumors showed a more proinflammatory antitumor immune infiltrate composition than luminal ones.

Mutational Signatures Driven by Epigenetic Determinants Enable the Stratification of Patients with Gastric Cancer for Therapeutic Intervention.

Simple SummaryMutational signatures due to DNA mismatch repair deficiency (dMMR) is common in many cancers. However, the prognostic value of dMMR-associated mutational signatures remains to be assessed. Here, we performed a de novo extraction of mutational signatures in a cohort of 787 patients with gastric cancer. We detected three dMMR-related signatures, one of which clearly discriminates tumors with MLH1 gene silencing through hypermethylation of its promoter. We showed evidence that classification based on mutational signature exposure can be used to identify groups of patients with common clinical, immunological, and mutational features related directly to better prognosis.DNA mismatch repair deficiency (dMMR) is associated with the microsatellite instability (MSI) phenotype and leads to increased mutation load, which in turn may impact anti-tumor immune responses and treatment effectiveness. Various mutational signatures directly linked to dMMR have been described for primary cancers. To investigate which mutational signatures are associated with prognosis in gastric cancer, we performed a de novo extraction of mutational signatures in a cohort of 787 patients. We detected three dMMR-related signatures, one of which clearly discriminates tumors with MLH1 gene silencing caused by promoter hypermethylation (area under the curve = 98%). We then demonstrated that samples with the highest exposure of this signature share features related to better prognosis, encompassing clinical and molecular aspects and altered immune infiltrate composition. Overall, the assessment of the prognostic value and of the impact of modifications in MMR-related genes on shaping specific dMMR mutational signatures provides evidence that classification based on mutational signature exposure enables prognosis stratification.

Profiles of immune infiltration in abdominal aortic aneurysm and their associated marker genes: a gene expression-based study.

Immune-mediated inflammation plays a key role in the pathology of abdominal aortic aneurysm (AAA). We aimed to use a computational approach to profile the immune infiltration patterns and related core genes in AAA samples based on the overexpression of gene signatures. The microarray datasets of AAA and normal abdominal tissues were acquired from gene expression omnibus (GEO) database. We evaluated the composition of immune infiltrates through microenvironment cell populations (MCP)-counter. Weighted gene correlation network analysis (WGCNA) was employed to construct the co-expression network and extract gene information in the most relevant module. Functional and pathway enrichment analysis was performed and immune infiltration related core genes were screened. AAA tissues had a higher level of infiltration by cytotoxic lymphocytes, NK cells, T cells, fibroblasts, myeloid dendritic cells, and neutrophils than normal aorta. The red module was strongly correlated with the infiltrating levels of T cells and cytotoxic lymphocytes. Gene ontology (GO) and pathway analyses revealed that genes in the most relevant module were mainly enriched in T cell activation, regulation of lymphocyte activation, cytokine-cytokine receptor interaction, and chemokine signaling pathway, etc. The expression of GZMK, CCL5, GZMA, CD2, and EOMES showed significant correlations with cytotoxic lymphocytes, while CD247, CD2, CD6, RASGRP1, and CD48 expression were positively associated with T cell infiltration. In conclusion, we comprehensively analyzed profiles of infiltrated immune cells in AAA tissues and their associated marker genes. Our data may provide a novel clue to indicate the underlying molecular mechanisms of AAA formation in terms of immune infiltration.