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History teaches us that while public health advocates can do much, a country needs well informed and courageous members of Congress to put useful public health measures into law. In the late 20th century, the work of one such individual, Congressman Joseph Moakley (D-MASS), helped to revolutionize the laws on food advertising and labeling and resulted in major gains in information for consumers. Given the recent modernization of nutrition labeling, this article attempts to highlight the initiatives led by the unsung hero of recent past, Congressman Moakley. Specifically, in the practice of nutrition, the behind-the-scenes initiatives that have helped standardize food labels and better educate the consumers to improve public health often go underrecognized. This article presents a brief overview of Moakley's contributions in these domains and identifies gaps for future works in the field of nutrition labeling.
Unchecked hyperadiposity causes systemic metabolic perturbations and subclinical chronic inflammation, promoting hormone receptor positive (HR+) breast cancer. Murine models of high-fat diet-induced obesity have shown alterations in proteins involved in fatty acid binding and mitochondrial beta-oxidation, including enoyl-CoA hydratase short chain 1 (ECHS1), which promote increased uptake of fatty acids by primary tumor cells. This creates a metabolic tug of war between tumor and immune cells in the tumor microenvironment, thereby depriving cytotoxic immune cells of the metabolic reprogramming for anti-tumor functionality. Nonetheless, metabolic gene expression changes in breast tumor microenvironment of obese individuals remain elusive. We hypothesize that increased expression of ECHS1 leads to immune dysregulation in breast tumor microenvironment and increases risk of cancer progression. Proteomic and genomic expression and survival characteristics of ECHS1 in invasive breast cancer was explored in The Cancer Genome Atlas (TCGA) and the Clinical Proteomic Tumor Analysis Consortium. We the modeled the effects of ECHS1 expression on immune infiltration in the tumor microenvironment using a regression framework. We also performed single cell RNA sequencing analysis for differential expression of ECHS1 in various human breast cells. Additionally, expression level of ECHS1 was validated in silico in adipose tissue to elucidate increased immune dysregulation and risk of progression of breast carcinoma in obese individuals. We found a significantly increased expression of ECHS1 at both RNA and protein levels in HR+ breast cancer (p<0.001 for both), compared to Herceptin 2 receptor-positive or triple negative breast cancer. High expression of ECHS1 in female breast cancer is also associated with significantly decreased survival based on the TCGA data. Further, we found a significantly negative correlation of CD8+ T cells, neutrophils, and macrophages, and a significantly positive correlation of regulatory T cells with ECHS1 expression in the breast tumor microenvironment. We discovered increased expression of ECHS1 in luminal epithelial cells compared to myoepithelial cells based on single cell RNA sequencing. Lastly, high expression of ECHS1 protein expression based on immunohistochemistry was confirmed in human adipocytes. Collectively, our observations support the hypothesis that preferential uptake of free fatty acid through increased expression of ECHS1 in HR+ breast cancer impairs cytotoxic and anti-tumor effects of CD8+ T cells in the tumor microenvironment. Immune dysregulation is further amplified in obese individuals given increased levels of adipose cells and higher ECHS1 expression. Altogether, ECHS1 is a putative biomarker and potential therapeutic target as its downregulation may improve survival in obese patients with HR+ breast cancer. Citation Format: Tina Bharani, Divyansh Agarwal, Estefania Roldan-Vasquez, Jessalyn Ubellacker, Ted A. James. ECHS1 mediates metabolic disruption in hormone receptor-positive breast tumor microenvironment [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 1270.
With advances in single cell RNA sequencing (scRNAseq), accurate detection of perturbed pathways between conditions or cell types of interest becomes a critical analytical step. The ability to model alterations in a set of genes corresponding of a biological function is particularly useful when comparing cells between healthy and tumor tissues. Yet, few tools exist to detect changes in the multivariate distribution of genes corresponding to a given pathway. We developed a novel, graph-based statistical framework based on optimal matching for testing differential distribution of biological pathways in scRNAseq. We applied our method to data generated from >4,000 T cells isolated from six individuals with hepatocellular carcinoma (HCC). The T cell populations were purified from three tissue locations: peripheral blood, tumor-infiltrating immune cells (TIICs), and normal tissue adjacent to the tumor. We examined the distribution of gene sets that belong to a particular metabolic pathway across T cell subtypes to address the following questions: (1) Which pathways have a similar distribution across T cell subtypes in a given tissue? (2) Are there pathways that have a stable distribution across T cell subtypes in a normal/healthy tissue, but a perturbed distribution in HCC? (3) For pathways that have a disparate distribution across the T cell subtypes, which subtypes show the most distinct distribution? Of the 86 metabolic pathways compared, 41, 63 and 76 metabolic pathways were indistinguishable across T cell subtypes in the tumor, peripheral blood and adjacent normal tissues, respectively. We observed that most metabolic pathways do not show evidence for dissimilar distribution across cell types, suggesting that T cell subtypes might be more similar than previously appreciated in terms of how they regulate their basic metabolic machinery. Further, for each pair of tissue locations, we computed the overlap in perturbed pathways, and found that the concordance was substantially higher for blood and adjacent normal, than what either of these tissues had with the tumor tissue. Interestingly, five metabolic pathways were differentially distributed across the T cell subtypes in each tissue examined in HCC: glycolysis, purine metabolism, glycosphingolipid biosynthesis, pyruvate metabolism, and glycerophospholipid metabolism. Our model also found that CD4+ regulatory T cells were the strongest contributors, driving the differential distribution of these pathways between T cell subtypes in HCC. Altogether, our approach allows for a systems level characterization of pathway activity across multiple cell types with a variety of applications in single cell pathway analysis in oncology. Our work here also highlights unexpected regulatory mechanisms of regulatory T cells that might play in role in the immunobiology of HCC. Citation Format: Divyansh Agarwal, Tina Bharani, Somabha Mukherjee. Graph-based pathway analysis of T cell populations in hepatocellular carcinoma reveals novel metabolic regulators of tumor-infiltration lymphocyte activity [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 2042.
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