1. Definition of a Multi-Omics Signature for Esophageal Adenocarcinoma Prognosis Prediction.
- Author
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Lambroia, Luca, Conca Dioguardi, Carola Maria, Puccio, Simone, Pansa, Andrea, Alvisi, Giorgia, Basso, Gianluca, Cibella, Javier, Colombo, Federico Simone, Marano, Salvatore, Basato, Silvia, Alfieri, Rita, Giudici, Simone, Castoro, Carlo, and Peano, Clelia
- Subjects
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ADENOCARCINOMA , *SQUAMOUS cell carcinoma , *FLOW cytometry , *PREDICTION models , *MULTIOMICS , *ESOPHAGEAL tumors , *TRANSCRIPTION factors , *TREATMENT effectiveness , *TUMOR markers , *DESCRIPTIVE statistics , *RNA , *GENE expression , *ADJUVANT chemotherapy , *SEQUENCE analysis - Abstract
Simple Summary: Esophageal cancer, a highly lethal tumor, contributes to 5% of all cancer deaths, with its primary subtypes being esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC). While most studies focus on ESCC, this study investigates EAC using single-cell RNA sequencing (scRNA-seq) to analyze CD45+ immune cells from tumors and matched non-tumor tissues in therapy-naïve patients. By examining the transcriptional profiles of these immune cells and the entire transcriptome in a cohort of 23 patients, this study identifies distinct transcriptional signatures. These signatures were used to stratify a large cohort of TCGA EAC patients, revealing strong associations with prognosis and clinical outcomes. The findings suggest that these transcriptional profiles can improve prognosis accuracy post-surgery and potentially guide effective therapies, including immunotherapy, for EAC patients. Esophageal cancer is a highly lethal malignancy, representing 5% of all cancer-related deaths. The two main subtypes are esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC). While most research has focused on ESCC, few studies have analyzed EAC for transcriptional signatures linked to diagnosis or prognosis. In this study, we utilized single-cell RNA sequencing and bulk RNA sequencing to identify specific immune cell types that contribute to anti-tumor responses, as well as differentially expressed genes (DEGs). We have characterized transcriptional signatures, validated against a wide cohort of TCGA patients, that are capable of predicting clinical outcomes and the prognosis of EAC post-surgery with efficacy comparable to the currently accepted prognostic factors. In conclusion, our findings provide insights into the immune landscape and therapeutic targets of EAC, proposing novel immunological biomarkers for predicting prognosis, aiding in patient stratification for post-surgical outcomes, follow-up, and personalized adjuvant therapy decisions. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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