Composition Of Microenvironment Research Articles

Glioma immune microenvironment composition calculator (GIMiCC): a method of estimating the proportions of eighteen cell types from DNA methylation microarray data

A scalable platform for cell typing in the glioma microenvironment can improve tumor subtyping and immune landscape detection as successful immunotherapy strategies continue to be sought and evaluated. DNA methylation (DNAm) biomarkers for molecular classification of tumor subtypes have been developed for clinical use. However, tools that predict the cellular landscape of the tumor are not well-defined or readily available. We developed the Glioma Immune Microenvironment Composition Calculator (GIMiCC), an approach for deconvolution of cell types in gliomas using DNAm data. Using data from 17 isolated cell types, we describe the derivation of the deconvolution libraries in the biological context of selected genomic regions and validate deconvolution results using independent datasets. We utilize GIMiCC to illustrate that DNAm-based estimates of immune composition are clinically relevant and scalable for potential clinical implementation. In addition, we utilize GIMiCC to identify composition-independent DNAm alterations that are associated with high immune infiltration. Our future work aims to optimize GIMiCC and advance the clinical evaluation of glioma.

Spatial transcriptomics: a new frontier in accurate localization of breast cancer diagnosis and treatment.

Breast cancer is one of the most prevalent cancers in women globally. Its treatment and prognosis are significantly influenced by the tumor microenvironment and tumor heterogeneity. Precision therapy enhances treatment efficacy, reduces unwanted side effects, and maximizes patients' survival duration while improving their quality of life. Spatial transcriptomics is of significant importance for the precise treatment of breast cancer, playing a critical role in revealing the internal structural differences of tumors and the composition of the tumor microenvironment. It offers a novel perspective in studying the spatial structure and cell interactions within tumors, facilitating more effective personalized treatments for breast cancer. This article will summarize the latest findings in the diagnosis and treatment of breast cancer from the perspective of spatial transcriptomics, focusing on the revelation of the tumor microenvironment, identification of new therapeutic targets, enhancement of disease diagnostic accuracy, comprehension of tumor progression and metastasis, assessment of drug responses, creation of high-resolution maps of tumor cells, representation of tumor heterogeneity, and support for clinical decision-making, particularly in elucidating the tumor microenvironment, tumor heterogeneity, immunotherapy and their correlation with clinical outcomes.

8109 Cancer-Associated Fibroblasts Correlate with Aggressive Thyroid Cancer Behavior: Insights from Four Large Patient Cohorts

Abstract Disclosure: M.A. Loberg: None. X. George: None. P.J. Courtney: None. H.C. Eric: None. A. Golding: None. B. David: None. M. Alshalalfa: Employee; Self; Veracyte, Inc.. Stock Owner; Self; Veracyte, Inc. Y. Hao: Employee; Self; Veracyte, Inc.. Stock Owner; Self; Veracyte, Inc. J.P. Klopper: Employee; Self; Veracyte, Inc.. Stock Owner; Self; Veracyte, Inc. R.T. Kloos: Employee; Self; Veracyte, Inc.. Stock Owner; Self; Veracyte, Inc.. V. Weiss: None. Thyroid tumor molecular analysis often utilizes fine-needle aspirate (FNA) samples to predict malignancy with high sensitivity. An outstanding question is if molecular sequencing can provide prognostic information to predict disease aggression, potentially informing management. Recently, the composition of the tumor microenvironment, in particular the presence of tumor-promoting fibroblasts, has been associated with aggressive thyroid cancer. However, fibroblast gene expression has not previously been analyzed in thyroid tumor FNA samples. In this work, we detect cancer-associated fibroblast (CAF) gene signatures across 4 distinct bulk RNA sequencing cohorts and confirm detection in FNA samples. Associations between CAF gene signatures and tumor characteristics were explored in: Afirma Genomic Sequencing Classifier (GSC) cohort from FNA (n=47,695), a Memorial Healthcare System (MHS) retrospective FNA cohort with pathology outcome data (n=318), TCGA papillary thyroid cancers (n=496), and a Vanderbilt University Medical Center-University of Washington (VUMC-UW) resection cohort (n=312). Published breast CAF gene sets were used to generate normal fibroblast and CAF subtype scores. Novel thyroid cancer specific CAF gene sets were generated from thyroid cancer single-cell RNA sequencing data. Scores for each gene set were calculated as the average Z-score. Across all cohorts, multiple CAF subsets were enriched in samples with BRAFV600E and papillary histology. The strongest enrichment was in an SFRP2+ CAF subset identified in thyroid cancer single-cell sequencing data. In Afirma GSC FNA samples, SFRP2+ CAFs were enriched in GSC-suspicious and Bethesda V/VI relative to GSC-benign nodules (Wilcoxon p value < 2e-[1]6 for all). In TCGA, SFRP2+ CAFs were associated with extrathyroidal extension, advanced disease stage, and aggressive histology. In the MHS cohort of 318 malignant FNA samples, SFRP2+ CAFs were significantly higher in patients with vascular invasion or lymph node metastasis (LNM) (OR:2.75 [95% CI 1.63-4.75], p=4e-5). In the VUMC-UW cohort, SFRP2+ CAFs were associated with shorter progression-free survival (PFS) (p=0.0033). In summary we created a novel thyroid cancer-specific CAF gene signature that is elevated in BRAFV600E+ and aggressive thyroid cancers across multiple large patient cohorts. We also demonstrated the ability to detect these CAF signatures in thyroid FNAs using the Afirma GSC molecular testing platform, with enrichment in suspicious and malignant samples. Amongst the CAF scores tested, thyroid-specific CAF subsets had the highest prognostic potential, and SFRP2+ CAFs, specifically, were associated with shorter PFS, tumor invasion and LNM. Together, these results highlight the potential of interrogating the thyroid tumor stroma in FNA using RNA-based assays to inform prognosis and possibly management. Presentation: 6/3/2024

Clinicogenomic predictors of outcomes in patients with hepatocellular carcinoma treated with immunotherapy.

Immune checkpoint inhibitor (ICI) combinations extend overall survival (OS) while anti-PD-1/L1 monotherapy is non-inferior to sorafenib in treatment-naïve, patients with advanced hepatocellular carcinoma (HCC). Clinicogenomic features are posited to influence patient outcomes. The primary objective of this retrospective study was to define the clinical, pathologic, and genomic factors associated with outcomes to ICI therapy in patients with HCC. Patients with histologically confirmed advanced HCC treated with ICI at Memorial Sloan Kettering Cancer Center from 2012 to 2022 were included. Association between clinical, pathological, and genomic characteristics were assessed with univariable and multivariable Cox regression model for progression-free survival (PFS) and OS. Two-hundred and forty-two patients were treated with ICI-based therapy. Patients were predominantly male (82%) with virally mediated HCC (53%) and Child Pugh A score (70%). Median follow-up was 28 months (0.5-78.4). Median PFS for those treated in 1st line, 2nd line and ≥ 3rd line was 4.9 (range: 2.9-6.2), 3.1 (2.3-4.0), and 2.5 (2.1-4.0) months, respectively. Median OS for those treated in 1st line, 2nd line, and ≥ 3rd line was 16 (11-22), 7.5 (6.4-11), and 6.4 (4.6-26) months, respectively. Poor liver function and performance status associated with worse PFS and OS, while viral hepatitis C was associated with favorable outcome. Genetic alterations were not associated with outcomes. Clinicopathologic factors were the major determinates of outcomes for patients with advanced HCC treated with ICI. Molecular profiling did not aid in stratification of ICI outcomes. Future studies should explore alternative biomarkers such as the level of immune activation or the pretreatment composition of the immune tumor microenvironment.

Dissecting the Mechanisms of Intestinal Immune Homeostasis by Analyzing T-Cell Immune Response in Crohn's Disease and Colorectal Cancer.

Crohn's disease (CD) and colorectal cancer (CRC) represent a group of intestinal disorders characterized by intricate pathogenic mechanisms linked to the disruption of intestinal immune homeostasis. Therefore, comprehending the immune response mechanisms in both categories of intestinal disorders is of paramount significance in the prevention and treatment of these debilitating intestinal ailments. IIn this study, we conducted single-cell analysis on paired samples obtained from primary colorectal tumors and individuals with Crohn's disease, which was aimed at deciphering the factors influencing the composition of the intestinal immune microenvironment. By aligning T cells across different tissues, we identified various T cell subtypes, such as γδ T cell, NK T cell, and regulatory T (Treg) cell, which maintained immune system homeostasis and were confirmed in enrichment analyses. Subsequently, we generated pseudo-time trajectories for subclusters of T cells in both syndromes to delineate their differentiation patterns and identify key driver genes Result: Furthermore, cellular communication and transcription factor regulatory networks are all essential components of the intricate web of mechanisms that regulate intestinal immune homeostasis. The identified complex cellular interaction suggested potential T-lineage immunotherapeutic targets against epithelial cells with high copy number variation (CNV) levels in CD and CRC. Finally, the analysis of regulon networks revealed several promising candidates for cell-specific transcription factors (TFs). This study focused on the immune molecular mechanism under intestinal diseases. It contributed to the novel insight of depicting a detailed immune landscape and revealing T-cell responding mechanisms in CD and CRC.

Comprehensive Analysis of a Platelet- and Coagulation-Related Prognostic Gene Signature Identifies CYP19A1 as a Key Tumorigenic Driver of Colorectal Cancer.

The intricate interplay between the platelet-coagulation system and the progression of malignant tumors has profound therapeutic implications. However, a thorough examination of platelet and coagulation markers specific to colorectal cancer (CRC) is conspicuously absent in the current literature. Consequently, there is an urgent need for further exploration into the mechanistic underpinnings of these markers and their potential clinical applications. By integrating RNA-seq data and clinicopathological information from patients with CRC in the cancer genome atlas, we identified genes related to the platelet-coagulation system using weighted gene co-expression networks and univariate Cox analysis. We established a prognostic risk model based on platelet- and coagulation-related genes using Lasso Cox regression analysis and validated the model in two independent CRC cohorts. We explored potential biological functional disparities between high-risk and low-risk groups through comprehensive bioinformatics analysis. Our findings indicate that colorectal cancer patients classified as high-risk generally exhibit poorer prognoses. Moreover, the model's risk scores were associated with the differential composition of the immune tumor microenvironment, suggesting its applicability to infer immunotherapy responsiveness. Cellular functional experiments and animal experiments indicated that CYP19A1 expression in CRC influences malignant phenotype and platelet activation. In summary, we present a novel platelet- and coagulation-related risk model for prognostic assessment of patients with CRC and confirm the important role of CYP19A1 in promoting malignant progression of CRC.

The role of microenvironmental factors in the pre-ovulatory oocyte in the pathogenesis of “poor” ovarian response to in vitro fertilization (IVF) programs

Background. The “poor” response to ovarian stimulation during IVF (in vitro fertilization) cycles depends on various factors, including the biochemical composition of the follicle microenvironment. Recent studies have focused on the relationship between vascular tone regulators, angiogenic factors, oxidative stress, and the quality of oocytes. Despite this, there is still no consensus on the exact effect of these factors on folliculogenesis or their role in “poor” responses.Objective. To evaluate the content of biochemical factors and regulators of vascular tone and angiogenesis in follicular fluid in patients with a “poor” ovarian response to stimulation in IVF programs, compared to similar indicators in women with a normal ovarian response.Materials and methods. An open prospective cohort study was conducted, including 56 patients who were part of the IVF program. The criterion for separating the cohort of women was their response to controlled ovarian stimulation during the IVF cycle. Women with a “poor” response (n=32) were placed in the main group, while those with a normal response (n=24) were in the comparison group. Follicular fluid samples from women with a “poor” response were divided into two subgroups based on the presence or absence of an oocyte-cumulus complex in the follicle. The biochemical and soluble regulatory factors in follicular fluid were analyzed in both groups after controlled ovarian stimulation was completed. Statistical analysis of the data was done using methods from variation statistics. A critical level of significance for the differences was set at p ≤0.05.Result. The levels of urea, glucose, high-density lipoprotein, and total antioxidant status (TAOS) in follicular fluid (FF) from patients with a “poor” ovarian response were statistically significantly higher compared to those in the control group. The levels of bilirubin, low-density lipoprotein, and uric acid were also significantly lower in VF from patients in the main group compared to the control group, p<0.05. The indices of vascular endothelial growth factor (VEGF-A) and vascular endothelial growth receptor-2 (VEGFR-2) in FF from women with a “poor” response were significantly lower than those from patients with a normal response, while the levels of endogenous nitric oxide were significantly higher in the former group compared to the latter, p<0.05.Conclusion. The absence of an oocyte-cumulus complex in the pre-ovulatory follicle, which is associated with a “poor” response of the ovary to stimulation, is likely due to a disruption in vascularization processes. This is supported by a decrease in the levels of pro- and anti-angiogenic factors, such as VEGF-A and VEGFR-2.

Abstract A061: The impact of race and obesity on the prostate tumor microenvironment

Abstract Black Americans have the highest prostate cancer incidence and are twice as likely to die from their disease compared to Non-Hispanic White men, making this one of the largest cancer disparities between these two racial groups in the United States. While access to health care is one of the strongest contributors to this disparity, studies suggest biological distinctions exist between tumors from Black and Non-Hispanic White men. Furthermore, obesity is associated with worse prostate cancer outcomes, and research showing a stronger association between obesity and prostate cancer risk among Black men compared to Non-Hispanic White men suggests obesity and Black race may work in combination to create aggressive disease. Hence, we sought to thoroughly and precisely characterize tumors from Black men, with and without obesity, to identify tumor behavior and potential therapeutic options for this population, which to date, has not been done mostly because of the lack of racially diverse cohorts of prostate cancer. Also, we sought to determine the impact of obesity on the composition of the prostate tumor microenvironment, which to date remains unknown. Given that in the US obesity rates are over 40% and the pressing need to better address high-risk populations, it is critical to better understand how obesity and race impact disease biology. We hypothesized obesity and Black race, individually and combined, increase tumor immune infiltration, creating a distinct tumor microenvironment. Specifically, we hypothesized this microenvironment will be characterized by higher overall inflammation, but also will enable us to identify therapeutic targets that in time can lead to the creation of personalized treatments for this population. To test this hypothesis, we used a large and racially diverse patient cohort from men who underwent radical prostatectomy at the Veterans Affairs Medical Center in Durham, North Carolina. To analyze the tumor microenvironment at the single cell level and define spatial organization, we used imaging mass cytometry in tissue microarrays of tumor and normal prostate samples from patients similar in tumor stage. We created a customized marker panel to determine cell phenotype and expression of immune checkpoints. We detected 25 cell phenotypes in the prostate microenvironment and determined differential phenotypic abundance and interactions by race and obesity. Next, we will expand our study to include a larger number of samples and associate tumor microenvironment characteristics with patient recurrence, metastasis, and survival. In this study, we generated new insights into disease drivers in an understudied and disproportionately affected population and lay important groundwork for future research identifying novel therapeutic targets for high-risk populations, such as men with African descent and obesity. Citation Format: Gloria Cecilia Galvan, Simeon Mahov, Sungyong You, Simon Knott, Michael Freeman, Akil Merchant, Stephen J Freedland. The impact of race and obesity on the prostate tumor microenvironment [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr A061.

Genomic map of the cellular composition of the tumor microenvironment.

Genomic map of the cellular composition of the tumor microenvironment.

Abstract A031: Identification of therapeutic vulnerabilities in the subset of pancreatic ductal adenocarcinoma (PDAC) with homologous recombination deficiency

Abstract The genetic landscape of pancreatic ductal adenocarcinoma (PDAC) is characterized by mutations in the KRAS, TP53, CDKN2A and SMAD4 genes alongside multiple low-frequency mutations, which may offer opportunities for precision medicine. The success of poly-ADP-ribose polymerase (PARP) inhibitors in metastatic PDAC characterized by germline mutations in the Breast Cancer (BRCA) genes has led to the hypothesis that mutations in other BRCAness genes may sensitize PDAC to PARP inhibitors. To test this hypothesis, we used KPC mice as a backbone (Pdx1-Cre; LSL-KrasG12D/+; LSL-Trp53R172H/+) to generate models of PDAC driven by the loss of Ataxia Telangiectasia mutated (Atm, KPCA) or Brca1 (KPCB). Loss of Atm or Brca1 resulted in homologous recombination deficiency and genomic instability in vivo. In vitro cultures of KPCA and KPCB PDAC cells had higher numbers of micronuclei and were more radiosensitive than KPC cells. Next, we performed bulk and single-cell RNA sequencing to identify therapeutic vulnerabilities associated with Atm or Brca1 loss. We found that loss of Atm upregulated ATR signaling, suggesting ATR as a therapeutic target in KPCA mice. In agreement, ATR inhibition improved the survival of KPCA mice, with evidence of tumor growth delay. However, though PARP inhibition significantly improved the survival of KPCB mice, with delayed tumor growth, it was ineffective in KPCA mice. In addition, transcriptomic analysis showed an enrichment of immune cells in KPCB PDAC compared to KPC and KPCA PDAC. Notably, we found greater levels of STING signaling, a more diverse and abundant cytokine profile and more CD8 T cells in KPCB PDAC, suggesting sensitivity to immune checkpoint blockade (ICB). However, ICB was ineffective in KPCB mice as a single agent or in combination with PARP inhibition. Based on our transcriptomic data, we hypothesized that boosting antigen priming using a CD40 agonist (CD40a) in combination with FLT3-L may improve ICB efficacy in our mouse models of BRCAness. Immunotherapy consisting of combined ICB, CD40a and FLT-3L had little efficacy in either KPCA or KPCB mice. However, ATR inhibition improved the efficacy of combined ICB, CD40a and FLT-3L in KPCA mice, as indicated by increased CD8 T cell infiltration in the tumor, delayed tumor growth and longer survival. In contrast, we found that PARP inhibition combined with ICB, CD40a and FLT-3L was ineffective in KPCB mice. In summary, we present evidence to suggest that PDAC characterized by BRCAness is not a homogeneous group with respect to sensitivity to PARP inhibition, composition of the tumor microenvironment and response to immunotherapy. We highlight ATM loss as a potential predictive biomarker of ATR inhibitor efficacy and immunotherapy in PDAC. Future directions include the evaluation of inflammation as a therapeutic vulnerability in murine PDAC with loss of Brca1. Ultimately, we aim to inform clinical trials to refine precision medicine of PDAC characterized by BRCAness. Citation Format: Mathias Tesson, Kay Kong, Peter Repsicak, Aldo Bader, Ya-Ching Hsieh, Craig Nourse, Kristina Kirschner, Crispin Miller, Ed Roberts, David Chang, Jen Morton. Identification of therapeutic vulnerabilities in the subset of pancreatic ductal adenocarcinoma (PDAC) with homologous recombination deficiency [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr A031.

An atlas of genetic effects on cellular composition of the tumor microenvironment.

Deciphering the composition of the tumor microenvironment (TME) is critical for understanding tumorigenesis and to design immunotherapies. In the present study, we mapped genetic effects on cell-type proportions using single-cell and bulk RNA sequencing data, identifying 3,494 immunity quantitative trait loci (immunQTLs) across 23 cancer types from The Cancer Genome Atlas. Functional annotation revealed regulatory potential and we further assigned 1,668 genes that regulate TME composition. We constructed a combined immunQTL map by integrating data from European and Chinese colorectal cancer (CRC) samples. A polygenic risk score that incorporates these immunQTLs and hits on a genome-wide association study outperformed in CRC risk stratification within 447,495 multiethnic individuals. Using large-scale population cohorts, we identified that the immunQTL rs1360948 is associated with CRC risk and prognosis. Mechanistically, the rs1360948-G-allele increases CCL2 expression, recruiting regulatory T cells that can exert immunosuppressive effects on CRC progression. Blocking the CCL2-CCR2 axis enhanced anti-programmed cell death protein 1 ligand therapy. Finally, we have established a database (CancerlmmunityQTL2) to serve the research community and advance our understanding of immunogenomic interactions in cancer pathogenesis.

Analysis of ductal carcinoma in situ by self-reported race reveals molecular differences related to outcome

BackgroundDuctal carcinoma in situ (DCIS) is a non-obligate precursor to invasive breast cancer (IBC). Studies have indicated differences in DCIS outcome based on race or ethnicity, but molecular differences have not been investigated.MethodsWe examined the molecular profile of DCIS by self-reported race (SRR) and outcome groups in Black (n = 99) and White (n = 191) women in a large DCIS case-control cohort study with longitudinal follow up.ResultsGene expression and pathway analyses suggested that different genes and pathways are involved in diagnosis and ipsilateral breast outcome (DCIS or IBC) after DCIS treatment in White versus Black women. We identified differences in ER and HER2 expression, tumor microenvironment composition, and copy number variations by SRR and outcome groups.ConclusionsOur results suggest that different molecular mechanisms drive initiation and subsequent ipsilateral breast events in Black versus White women.

AI drives the assessment of lung cancer microenvironment composition

PurposeThe abundance and distribution of tumor-infiltrating lymphocytes (TILs) as well as that of other components of the tumor microenvironment is of particular importance for predicting response to immunotherapy in lung cancer (LC). We describe here a pilot study employing artificial intelligence (AI) in the assessment of TILs and other cell populations, intending to reduce the inter- or intra-observer variability that commonly characterizes this evaluation. DesignWe developed a machine learning-based classifier to detect tumor, immune, and stromal cells on hematoxylin and eosin-stained sections, using the open-source framework QuPath. We evaluated the quantity of the aforementioned three cell populations among 37 LC whole slide images regions of interest, comparing the assessments made by five pathologists, both before and after using graphical predictions made by AI, for a total of 1110 quantitative measurements. ResultsOur findings indicate noteworthy variations in score distribution among pathologists and between individual pathologists and AI. The AI-guided pathologist's evaluations resulted in reduction of significant discrepancies across pathologists: three comparisons showed a loss of significance (p > 0.05),whereas other four showed a reduction in significance (p > 0.01). ConclusionsWe show that employing a machine learning approach in cell population quantification reduces inter- and intra-observer variability, improving reproducibility and facilitating its use in further validation studies.

Identifying epithelial-mesenchymal transition-related genes as prognostic biomarkers and therapeutic targets of hepatocellular carcinoma by integrated analysis of single-cell and bulk-RNA sequencing data.

Hepatocellular carcinoma (HCC) remains one of the most lethal cancers globally. Patients with advanced HCC tend to have poor prognoses and shortened survival. Recently, data from bulk RNA sequencing have been employed to discover prognostic markers for various cancers. However, they fall short in precisely identifying core molecular and cellular activities within tumor cells. In our present study, we combined bulk-RNA sequencing (bulk RNA-seq) data with single-cell RNA sequencing (scRNA-seq) to develop a prognostic model for HCC. The goal of our research is to uncover new biomarkers and enhance the accuracy of HCC prognosis prediction. Integrating single-cell sequencing data with transcriptomics were used to identify epithelial-mesenchymal transition (EMT)-related genes (ERGs) implicated in HCC progression and their clinical significance was elucidated. Utilizing marker genes derived from core cells and ERGs, we constructed a prognostic model using univariate Cox analysis, exploring a multitude of algorithmic combinations, and further refining it through multivariate Cox analysis. Additionally, we conducted an in-depth investigation into the disparities in clinicopathological features, immune microenvironment composition, immune checkpoint expression, and chemotherapeutic drug sensitivity profiles between high- and low-risk patient cohorts. We developed a prognostic model predicated on the expression profiles of eight signature genes, namely HSP90AA1, CIRBP, CCR7, S100A9, ADAM17, ENG, PGF, and INPP4B, aiming at predicting overall survival (OS) outcomes. Notably, patients classified with high-risk scores exhibited a propensity towards diminished OS rates, heightened frequencies of stage III-IV disease, increased tumor mutational burden (TMB), augmented immune cell infiltration, and diminished responsiveness to immunotherapeutic interventions. This study presented a novel prognostic model for predicting the survival of HCC patients by integrating scRNA-seq and bulk RNA-seq data. The risk score emerges as a promising independent prognostic factor, showing a correlation with the immune microenvironment and clinicopathological features. It provided new clinical tools for predicting prognosis and aided future research into the pathogenesis of HCC.

Prediction of Prognosis and Immunotherapy Response of Gastric Cancer Based on Glutamine Metabolism-Related Genes.

Reprogramming of glutamine metabolism in Gastric Cancer (GC) can significantly affect the tumor immune microenvironment and immunotherapy. This study examines the role of glutamine metabolism in the microenvironment and prognosis of gastric cancer. We obtained gene expression data and clinical information of patients from the TCGA database. The patients were divided into two metabolic subtypes based on consistent clustering. A prognostic risk model containing three glutamine metabolism-related genes (GMRGs) was developed using Lasso-Cox. It was validated by the GEO validation cohort. Additionally, the immune microenvironment composition of the highand low-risk groups was assessed using ESTIMATE, CIBERSORT, and ssGSEA. Drug sensitivity analysis was conducted using the "oncoPredict" R package. We outlined the distinct clinical characteristics of two subtypes and developed a prognostic risk model. The high-risk group has a poorer prognosis due to an increased expression of immune checkpoints and immunosuppressive cellular infiltration. Our analysis, which included Cox risk regression, ROC curves, and nomogram, demonstrated that this risk model is an independent prognostic factor. The TIDE score was higher in the high-risk group than in the low-risk group. Additionally, the high-risk group did not respond well to chemotherapeutic drug treatment. This study shows that modelling glutamine metabolism is a good predictor of prognosis and immunotherapy efficacy in gastric cancer. Thus, we can better understand the role of glutamine metabolism in the development of cancer and use these insights to develop more targeted and effective treatments.

Biomarkers Identification in the Microenvironment of Oral Squamous Cell Carcinoma: A Systematic Review of Proteomic Studies.

An important determinant for oral squamous cell carcinoma (OSCC) onset and outcome is the composition of the tumor microenvironment (TME). Thus, the study of the interactions occurring among cancer cells, immune cells, and cancer-associated fibroblasts within the TME could facilitate the understanding of the mechanisms underlying OSCC development and progression, as well as of its sensitivity or resistance to the therapy. In this context, it must be highlighted that the characterization of TME proteins is enabled by proteomic methodologies, particularly mass spectrometry (MS). Aiming to identify TME protein markers employable for diagnosing and prognosticating OSCC, we have retrieved a total of 119 articles spanning 2001 to 2023, of which 17 have passed the selection process, satisfying all its criteria. We have found a total of 570 proteins detected by MS-based proteomics in the TME of OSCC; among them, 542 are identified by a single study, while 28 are cited by two or more studies. These 28 proteins participate in extracellular matrix remodeling and/or energy metabolism. Here, we propose them as markers that could be used to characterize the TME of OSCC for diagnostic/prognostic purposes. Noteworthy, most of the 28 individuated proteins share one feature: being modulated by the hypoxia that is present in the proliferating OSCC mass.

Cracking the Codes behind Cancer Cells' Immune Evasion.

Immune evasion is a key phenomenon in understanding tumor recurrence, metastasis, and other critical steps in tumor progression. The tumor microenvironment (TME) is in constant flux due to the tumor's ability to release signals that affect it, while immune cells within it can impact cancer cell behavior. Cancer cells undergo several changes, which can change the enrichment of different immune cells and modulate the activity of existing immune cells in the tumor microenvironment. Cancer cells can evade immune surveillance by downregulating antigen presentation or expressing immune checkpoint molecules. High levels of tumor-infiltrating lymphocytes (TILs) correlate with better outcomes, and robust immune responses can control tumor growth. On the contrary, increased enrichment of Tregs, myeloid-derived suppressor cells, and M2-like anti-inflammatory macrophages can hinder effective immune surveillance and predict poor prognosis. Overall, understanding these immune evasion mechanisms guides therapeutic strategies. Researchers aim to modulate the TME to enhance immune surveillance and improve patient outcomes. In this review article, we strive to summarize the composition of the tumor immune microenvironment, factors affecting the tumor immune microenvironment (TIME), and different therapeutic modalities targeting the immune cells. This review is a first-hand reference to understand the basics of immune surveillance and immune evasion.

A Whole-Transcriptomic Analysis of Canine Oral Melanoma: A Chance to Disclose the Radiotherapy Effect and Outcome-Associated Gene Signature.

Oral melanoma (OM) is the most common malignant oral tumour among dogs and shares similarities with human mucosal melanoma (HMM), validating the role of canine species as an immunocompetent model for cancer research. In both humans and dogs, the prognosis is poor and radiotherapy (RT) represents a cornerstone in the management of this tumour, either as an adjuvant or a palliative treatment. In this study, by means of RNA-seq, the effect of RT weekly fractionated in 9 Gray (Gy), up to a total dose of 36 Gy (4 weeks), was evaluated in eight dogs affected by OM. Furthermore, possible transcriptomic differences in blood and biopsies that might be associated with a longer overall survival (OS) were investigated. The immune response, glycosylation, cell adhesion, and cell cycle were the most affected pathways by RT, while tumour microenvironment (TME) composition and canonical and non-canonical WNT pathways appeared to be modulated in association with OS. Taking these results as a whole, this study improved our understanding of the local and systemic effect of RT, reinforcing the pivotal role of anti-tumour immunity in the control of canine oral melanoma (COM).

Single-nuclei sequencing of uterine serous carcinoma reveals racial differences in immune signaling

Significant racial disparities exist between Black and White patients with uterine serous carcinoma (USC). While the reasons for these disparities are unclear, several studies have demonstrated significantly different rates of driver mutations between racial groups, including TP53. However, limited research has investigated the transcriptional differences of tumors or the composition of the tumor microenvironment (TME) between these groups. Here, we report the single-nuclei RNA-sequencing profiles of primary USC tumors from diverse racial backgrounds. We find that there are significant differences between the tumors of Black and White patients. Tumors from Black patients exhibited higher expression of specific genes associated with aggressiveness, such as PAX8, and axon guidance and synaptic signaling pathways. We also demonstrated that T cell populations are reduced in the tumor tissue compared to matched benign, while anti-inflammatory macrophage populations are retained within the TME. Furthermore, we investigated the connection between PAX8 overexpression and immunosuppression in USC through regulation of several cytokines and chemokines. Notably, we show that PAX8 activity can influence macrophage gene expression and protein secretion. These studies provide a detailed understanding of the USC transcriptome and TME, and identify differences in tumor biology from patients of different racial backgrounds.

The spatial structure of the tumor immune microenvironment can explain and predict patient response in high-grade serous carcinoma.

Ovarian cancer is the deadliest gynecological malignancy, and therapeutic options and mortality rates over the last three decades have largely not changed. Recent studies indicate that the composition of the tumor immune microenvironment (TIME) influences patient outcomes. To improve spatial understanding of the TIME, we performed multiplexed ion beam imaging on 83 human high-grade serous carcinoma tumor samples, identifying about 160,000 cells across 23 cell types. For 77 of these samples meeting inclusion criteria, we generated composition features based on cell type proportions, spatial features based on the distances between cell types, and spatial network features representing cell interactions and cell clustering patterns, which we linked to traditional clinical and immunohistochemical variables and patient overall survival (OS) and progression-free survival (PFS) outcomes. Among these features, we found several significant univariate correlations, including B-cell contact with M1 macrophages (OS hazard ratio HR=0.696, p=0.011, PFS HR=0.734, p=0.039). We then used high-dimensional random forest models to evaluate out-of-sample predictive performance for OS and PFS outcomes and to derive relative feature importance scores for each feature. The top model for predicting low or high PFS used TIME composition and spatial features and achieved an average AUC (area under the receiver-operating characteristic curve) score of 0.71. The results demonstrate the importance of spatial structure in understanding how the TIME contributes to treatment outcomes. Furthermore, the present study provides a generalizable roadmap for spatial analyses of the TIME in ovarian cancer research.