High baseline expression of IL-6 and IL-10 decreased CCR7 B cells in individuals with previous SARS-CoV-2 infection during BNT162b2 vaccination.

The current pandemic generated by SARS-CoV-2 has led to mass vaccination with different biologics that have shown wide variations among human populations according to the origin and formulation of the vaccine. Studies evaluating the response in individuals with a natural infection before vaccination have been limited to antibody titer analysis and evaluating a few humoral and cellular response markers, showing a more rapid and intense humoral response than individuals without prior infection. However, the basis of these differences has not been explored in depth. In the present work, we analyzed a group of pro and anti-inflammatory cytokines, antibody titers, and cell populations in peripheral blood of individuals with previous SARS-CoV-2 infection using BNT162b2 biologic. Our results suggest that higher antibody concentration in individuals with an earlier disease could be generated by higher production of plasma cells to the detriment of the presence of memory B cells in the bloodstream, which could be related to the high baseline expression of cytokines (IL-6 and IL-10) before vaccination.

Data set of the protein expression profiles of Luminal A, Claudin-low and overexpressing HER2(+) breast cancer cell lines by iTRAQ labelling and tandem mass spectrometry.

Breast cancer is the most common and the leading cause of mortality in women worldwide. There is a dire necessity of the identification of novel molecules useful in diagnosis and prognosis. In this work we determined the differentially expression profiles of four breast cancer cell lines compared to a control cell line. We identified 1020 polypeptides labelled with iTRAQ with more than 95% in confidence. We analysed the common proteins in all breast cancer cell lines through IPA software (IPA core and Biomarkers). In addition, we selected the specific overexpressed and subexpressed proteins of the different molecular classes of breast cancer cell lines, and classified them according to protein class and biological process. Data in this article is related to the research article "Determination of the protein expression profiles of breast cancer cell lines by Quantitative Proteomics using iTRAQ Labelling and Tandem Mass Spectrometry" (Calderón-González et al. [1] in press).

Determination of the protein expression profiles of breast cancer cell lines by quantitative proteomics using iTRAQ labelling and tandem mass spectrometry.

Breast cancer is the principal cancer in women worldwide. Although there are serum tumor markers such as CEA and HER2, they are detected in advanced stages of the disease and used as progression and recurrence markers. Therefore, there is a necessity for the identification of new markers that might lead to an early detection and also provide evidence of an effective treatment. The aim of this work was to determine the differential protein expression profiles of four breast cancer cell lines in comparison to a normal control cell line by iTRAQ labelling and tandem mass spectrometry, in order to identify putative biomarkers of the disease. We identified 1,020 iTRAQ-labelled polypeptides with at least one peptide identified with more than 95% in confidence. Overexpressed polypeptides in all cancer cell lines were 78, whilst the subexpressed were 128. We categorised them with PANTHER program into biological processes, being the metabolic pathways the most affected. We detected six groups of proteins with the STRING program involved in DNA topology, glycolysis, translation initiation, splicing, pentose pathway, and proteasome degradation. The main subexpressed protein network included mitochondrial proteins involved in oxidative phosphorylation. We propose BAG6, DDX39, ANXA8 and COX4 as putative biomarkers in breast cancer. BIOLOGICAL SIGNIFICANCE: We report a set of differentially expressed proteins in the MCF7 and T47D (Luminal A), MDA-MB-231 (Claudin low) and SK-BR-3 (HER2(+)) breast cancer cell lines that have not been previously reported in breast cancer disease. From these proteins, we propose BAG6, DDX39, ANXA8 and COX4 as putative biomarkers in breast cancer. On the other hand, we propose sets of unique polypeptides in each breast cancer cell line that can be useful in the classification of different subtypes of breast cancer.