Impact of Tumor Response After Neoadjuvant Treatment on Overall Survival Among Patients With Pancreatic Ductal Adenocarcinoma: National Cancer Database Analysis.

Background Complete pathologic response following neoadjuvant therapy (NAT) for pancreatic ductal adenocarcinoma (PDAC) is rare; alternative markers associated with survival are needed. The aim of this study was to evaluate the impact of tumor response to NAT on overall survival (OS) in PDAC patients who received NAT and curative-intent surgery. Methods A retrospective study utilizing the 2006-2018 National Cancer Database identified 6,960 adult patients with PDAC who received NAT.

Patient-reported outcomes and measures are under-utilised in advanced therapy medicinal products trials for orphan conditions.

Objectives: Advanced therapy medicinal products (ATMPs) are medicines based on genes, tissues, or cells and can include gene therapy, somatic-cell therapy, and tissue-engineered medicines. Patient-reported outcomes (PROs) are reports on health and well-being that come directly from the individual without external interpretation. Patient-reported outcome measures (PROMs) are questionnaires aimed at assessing the individual and subjective experience with health and other psychosocial aspects.

Deep learning of antibody epitopes using positional permutation vectors.

Background: The accurate computational prediction of B cell epitopes can vastly reduce the cost and time required for identifying potential epitope candidates for the design of vaccines and immunodiagnostics. However, current computational tools for B cell epitope prediction perform poorly and are not fit-for-purpose, and there remains enormous room for improvement and the need for superior prediction strategies.

Results: Here we propose a novel approach that improves B cell epitope prediction by encoding epitopes as binary positional permutation vectors that represent the position and structural properties of the amino acids within a protein antigen sequence that interact with an antibody.

Pan-cancer profiling of tumor-infiltrating natural killer cells through transcriptional reference mapping.

The functional diversity of natural killer (NK) cell repertoires stems from differentiation, homeostatic, receptor-ligand interactions and adaptive-like responses to viral infections. In the present study, we generated a single-cell transcriptional reference map of healthy human blood- and tissue-derived NK cells, with temporal resolution and fate-specific expression of gene-regulatory networks defining NK cell differentiation. Transfer learning facilitated incorporation of tumor-infiltrating NK cell transcriptomes (39 datasets, 7 solid tumors, 427 patients) into the reference map to analyze tumor microenvironment (TME)-induced perturbations.

Candidate tumor-specific CD8 T cell subsets identified in the malignant pleural effusion of advanced lung cancer patients by single-cell analysis.

Isolation of tumor-specific T cells and their antigen receptors (TCRs) from malignant pleural effusions (MPE) may facilitate the development of TCR-transduced adoptive cellular immunotherapy products for advanced lung cancer patients. However, the characteristics and markers of tumor-specific T-cells in MPE are largely undefined. To this end, to establish the phenotypes and antigen specificities of CD8 T cells, we performed single-cell RNA and TCR sequencing of samples from three advanced lung cancer patients.