Biology subjects

Givechian, K. B.

Publications and source records attributed to Givechian, K. B..

3 recordsLinked to original sources

bioRxiv2024

ImmunoStruct: Integration of protein sequence, structure, and biochemical properties for immunogenicity prediction and interpretation

Epitope-based vaccines are promising therapeutic modalities for infectious diseases and cancer, but identifying immunogenic epitopes is challenging. The vast majority of prediction methods only use amino acid sequence information, and do not incorporate wide-scale structure data and biochemical properties across each peptide-MHC. We present ImmunoStruct, a deep-learning model that integrates sequence, structural, and biochemical information to predict multi-allele class-I peptide-MHC immunogenicity. By leveraging a multimodal dataset of[~] 27,000 peptide-MHCs, we demonstrate that ImmunoStruct improves immunogenicity prediction performance and interpretability beyond existing methods, across infectious disease epitopes and cancer neoepitopes. We further show strong alignment with in vitro assay results for a set of SARS-CoV-2 epitopes, as well as strong performance in peptide-MHC-based cancer patient survival prediction. Overall, this work also presents a new architecture that incorporates equivariant graph processing and multimodal data integration for the long standing task in immunotherapy.

immunology↗

bioRxiv2021

Multimodal Analysis Reveals Differential Immuno-Metabolic Features in Lung Squamous Cell Carcinoma and Adenocarcinoma

BackgroundThe relationship between systemic metabolism, immune function, and lung cancer is complex and remains poorly defined. Seemingly paradoxically, overweight and obesity confer an improved response to immune checkpoint inhibition in non-small cell lung cancer (NSCLC); however, it is not known whether excess body weight or adiposity impacts the immunometabolic tumor microenvironment. MethodsUtilizing three complementary National Cancer Institute-funded open-source databases containing 18F-fluorodeoxyglucose positron-emission tomography/computed tomography (PET-CT) images for tumor and tissue glucose uptake, adipose tissue and skeletal muscle mass, histology annotated with tumor infiltrating leukocytes, and tumor RNA sequencing, we performed a retrospective cross-sectional analysis to examine phenotypic, metabolic, and genomic intersections of adiposity and tumor immune-metabolism in patients with lung adenocarcinoma (LUAD) versus squamous cell carcinoma (LUSC). ResultsOur data reveal distinct immunometabolomic features of LUSC as compared to LUAD: visceral fat content was negatively correlated with both tumor glucose uptake and leukocyte infiltration. Subcutaneous and visceral adiposity conferred different effects on the tumor genetic landscapes in both tumor types. LUSC tumors showed greater gene expression pathways related to pyruvate, glucose, amino acid, and lipid metabolism, in addition to significantly greater 18F-FDG uptake compared with LUAD, suggesting deeper metabolic regulation within the LUSC tumor microenvironment. ConclusionsSeveral immunometabolomic characteristics of LUSC and LUAD differ, including tumor glucose uptake and the associated metabolic pathways in the tumor, as well as the impact of visceral adiposity on tumor metabolism. These data may highlight opportunities to advance mechanistically targeted precision medicine approaches by better understanding the interplay between metabolic, immunologic, and genomic factors in lung cancer treatment.

cancer biology↗

bioRxiv2018

Identification of an immune gene expression signature associated with favorable clinical features in Treg-enriched patient tumor samples

Immune heterogeneity within the tumor microenvironment undoubtedly adds several layers of complexity to our understanding of drug sensitivity and patient prognosis across various cancer types. Within the tumor microenvironment, immunogenicity is a favorable clinical feature in part driven by the antitumor activity of CD8+ T cells. However, tumors often inhibit this antitumor activity by exploiting the suppressive function of Regulatory T cells (Tregs), thus suppressing the adaptive immune response. Despite the seemingly intuitive immunosuppressive biology of Tregs, prognostic studies have produced contradictory results regarding the relationship between Treg enrichment and survival. We therefore analyzed RNA-seq data of Treg-enriched tumor samples to derive a pan-cancer gene signature able to help reconcile the inconsistent results of Treg studies, by better understanding the variable clinical association of Tregs across alternative tumor contexts. We show that increased expression of a 32-gene signature in Treg-enriched tumor samples (n=135) is able to distinguish a cohort of patients associated with chemosensitivity and overall survival This cohort is also enriched for CD8+ T cell abundance, as well as the antitumor M1 macrophage subtype. With a subsequent validation in a larger TCGA pool of Treg-enriched patients (n = 626), our results reveal a gene signature able to produce unsupervised clusters of Treg-enriched patients, with one cluster of patients uniquely representative of an immunogenic tumor microenvironment. Ultimately, these results support the proposed gene signature as a putative biomarker to identify certain Treg-enriched patients with immunogenic tumors that are more likely to be associated with features of favorable clinical outcome.

cancer biology↗