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The aim of the current study was to investigate the tear proteome in children and adolescents with type 1 diabetes (T1D) compared to healthy controls, and to identify differences in the tear proteome of children with T1D depending on different characteristics of the disease. Fifty-six children with T1D at least one year after diagnosis, aged 6-17 years old, and fifty-six healthy age- and sex-matched controls were enrolled in this cross-sectional study. The proteomic analysis was based on liquid chromatography tandem mass spectrometry (LC-MS/MS) enabling the identification and quantification of the protein content via Data-Independent Acquisition by Neural Networks (DIA-NN). Data are available via ProteomeXchange with the identifier PXD052994. In total, 3302 proteins were identified from tear samples. Two hundred thirty-nine tear proteins were differentially expressed in children with T1D compared to healthy controls. Most of them were involved in the immune response, tissue homeostasis and inflammation. The presence of diabetic ketoacidosis at diagnosis and the level of glycemic control of children with T1D influenced the tear proteome. Tear proteomics analysis revealed a different proteome pattern in children with T1D compared to healthy controls offering insights on deregulated biological processes underlying the pathogenesis of T1D. Differences within the T1D group could unravel biomarkers for early detection of long-term complications of T1D.

Objective: The interplay of gut microbiota with the kidney system in chronic kidney disease (CKD), is characterized by increased concentrations of uric acid in the gut, which in turn, may increase bacterial uricase activity and may lead to the generation of uremic toxins. Nevertheless, knowledge on these underlying bidirectional molecular mechanisms is still limited., Methods: In this exploratory study, proteomic analysis was performed on fecal samples, targeting to investigate this largely unexplored biological material as a source of information reflecting the gut-kidney axis. Specifically, fecal suspension samples from patients with CKD1 ( n  = 12) and CKD4 ( n  = 17) were analysed by LC-MS/MS, using both the Human and Bacterial UniProt RefSeq reviewed databases., Results: This fecal proteomic analysis collectively identified 701 human and 1011 bacterial proteins of high confidence. Differential expression analysis (CKD4/CKD1) revealed significant changes in human proteins ( n  = 8, including proteins such as galectin-3-binding protein and prolactin-inducible protein), that were found to be associated with inflammation and CKD. The differential protein expression of pancreatic alpha-amylase further suggested plausible reduced saccharolytic fermentation in CKD4/CKD1. Significant changes in bacterial proteins ( n  = 9, such as glyceraldehyde-3-phosphate dehydrogenase and enolase), participating in various carbohydrate and metabolic pathways important for the synthesis of butyrate, in turn suggested differential butyrate synthesis in CKD4/CKD1. Further, targeted quantification of fecal pancreatic alpha-amylase and butyrate in the same fecal suspension samples, supported these hypotheses., Conclusion: Collectively, this exploratory fecal proteomic analysis highlighted changes in human and bacterial proteins reflecting inflammation and reduced saccharolytic fermentation in CKD4/CKD1, plausibly affecting the butyrate synthesis pathways in advanced stage kidney disease. Integrative multi-omics validation is planned., Competing Interests: The authors report that there are no competing interests to declare. Some components of the study design figure (Fig. 1) were exported from biorender.com., (© 2024 The Authors. Published by Elsevier Ltd.)

Quiescence is a common cellular state, required for stem cell maintenance and microorganismal survival under stress conditions or starvation. However, the mechanisms promoting quiescence maintenance remain poorly known. Plasma membrane components segregate into distinct microdomains, yet the role of this compartmentalization in quiescence remains unexplored. Here, we show that flavodoxin-like proteins (FLPs), ubiquinone reductases of the yeast eisosome membrane compartment, protect quiescent cells from lipid peroxidation and ferroptosis. Eisosomes and FLPs expand specifically in respiratory-active quiescent cells, and mutants lacking either show accelerated aging and defective quiescence maintenance and accumulate peroxidized phospholipids with monounsaturated or polyunsaturated fatty acids (PUFAs). FLPs are essential for the extramitochondrial regeneration of the lipophilic antioxidant ubiquinol. FLPs, alongside the Gpx1/2/3 glutathione peroxidases, prevent iron-driven, PUFA-dependent ferroptotic cell death. Our work describes ferroptosis-protective mechanisms in yeast and introduces plasma membrane compartmentalization as an important factor in the long-term survival of quiescent cells., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Locally advanced rectal cancer (LARC) presents a challenge in identifying molecular markers linked to the response to neoadjuvant chemoradiotherapy (nCRT). This study aimed to utilize a sensitive proteomic method, data-independent mass spectrometry (DIA-MS), to extensively analyze the LARC proteome, seeking individuals with favorable initial responses suitable for a watch-and-wait approach. This research addresses the unmet need to understand the response to treatment, potentially guiding personalized strategies for LARC patients. Post-treatment assessment included MRI scans and proctoscopy. This research involved 97 LARC patients treated with intense chemoradiotherapy, comprising radiation and chemotherapy. Out of 97 LARC included in this study, we selected 20 samples with the most different responses to nCRT for proteome profiling (responders vs. non-responders). This proteomic approach shows extensive proteome coverage in LARC samples. The analysis identified a significant number of proteins compared to a prior study. A total of 915 proteins exhibited differential expression between the two groups, with certain signaling pathways associated with response mechanisms, while top candidates had good predictive potential. Proteins encoded by genes SMPDL3A , PCTP , LGMN , SYNJ2 , NHLRC3 , GLB1, and RAB43 showed high predictive potential of unfavorable treatment outcome, while RPA2 , SARNP , PCBP2 , SF3B2 , HNRNPF , RBBP4 , MAGOHB , DUT , ERG28 , and BUB3 were good predictive biomarkers of favorable treatment outcome. The identified proteins and related biological processes provide promising insights that could enhance the management and care of LARC patients.

Purpose: In the search for candidate predictive biomarkers to evaluate response to neoadjuvant chemoradiotherapy (nCRT) in rectal cancer, only a few studies report proteomic profiles of tumor tissue before and after nCRT. The aim of our study was to determine differentially expressed proteins between responders and non-responders before and after the therapy in order to identify candidate molecules for prediction and follow-up of response to nCRT., Experimental Design: The study has included tissue sections of rectal tumor and non-tumor mucosa from five responders and five non-responders taken before and after nCRT from patients with locally advanced rectal cancer. Extracted proteins were analyzed by LC-MS/MS analysis followed by a set of bioinformatics analyses., Result: Proteomics analysis provided a mean of approximately 1050 protein identifications per sample. A comparison of proteomic profiles between responders and non-responders has identified 18 differentially expressed proteins. Pathway analysis demonstrated high metabolic activity in non-responders' tumors before nCRT, indicating the presence of intrinsic chemoradioresistance in these subjects. Two proteins associated with poor prognosis in colorectal cancer, ADAM10 and CAD, were identified as candidate predictive biomarkers as they were present in non-responders only., Conclusions and Clinical Relevance: Shortlisted proteins from our study should be further validated as candidate biomarkers for response to routinely applied nCRT protocols., (© 2022 Wiley-VCH GmbH.)

Prostate cancer (PCa) is the second most common cancer in men. Diagnosis and risk assessment are widely based on serum Prostate Specific Antigen (PSA) and biopsy, which might not represent the exact degree of PCa risk. Towards the discovery of biomarkers for better patient stratification, we performed proteomic analysis of Formalin Fixed Paraffin Embedded (FFPE) prostate tissue specimens using liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). Comparative analysis of 86 PCa samples among grade groups 1-5 identified 301 significantly altered proteins. Additional analysis based on biochemical recurrence (BCR; BCR+ n = 14, BCR- n = 51) revealed 197 significantly altered proteins that indicate disease persistence. Filtering the overlapping proteins of these analyses, seven proteins ( NPM1 , UQCRH , HSPA9 , MRPL3 , VCAN , SERBP1 , HSPE1 ) had increased expression in advanced grades and in BCR+/BCR- and may play a critical role in PCa aggressiveness. Notably, all seven proteins were significantly associated with progression in Prostate Cancer Transcriptome Atles (PCTA) and NPM1NPM1 , UQCRH , and VCAN were further validated in The Cancer Genome Atlas (TCGA), where they were upregulated in BCR+/BCR-. UQCRH levels were also associated with poorer 5-year survival. Our study provides valuable insights into the key regulators of PCa progression and aggressiveness. The seven selected proteins could be used for the development of risk assessment tools.

Significant inter-individual variation in terms of susceptibility to several stress-related disorders, such as myocardial infarction and Alzheimer's disease, and therapeutic response has been observed among healthy subjects. The molecular features responsible for this phenomenon have not been fully elucidated. Proteomics, in association with bioinformatics analysis, offer a comprehensive description of molecular phenotypes with clear links to human disease pathophysiology. The aim of this study was to conduct a comparative plasma proteomics analysis of glucocorticoid resistant and glucocorticoid sensitive healthy subjects and provide clues of the underlying physiological differences. For this purpose, 101 healthy volunteers were given a very low dose (0.25 mg) of dexamethasone at midnight, and were stratified into the 10% most glucocorticoid sensitive (S) ( n = 11) and 10% most glucocorticoid resistant (R) ( n = 11) according to the 08:00 h serum cortisol concentrations determined the following morning. One month following the very-low dose dexamethasone suppression test, DNA and plasma samples were collected from the 22 selected individuals. Sequencing analysis did not reveal any genetic defects in the human glucocorticoid receptor ( NR3C1 ) gene. To investigate the proteomic profile of plasma samples, we used Liquid Chromatography-Mass Spectrometry (LC-MS/MS) and found 110 up-regulated and 66 down-regulated proteins in the S compared to the R group. The majority of the up-regulated proteins in the S group were implicated in platelet activation. To predict response to cortisol prior to administration, a random forest classifier was developed by using the proteomics data in order to distinguish S from R individuals. Apolipoprotein A4 (APOA4) and gelsolin (GSN) were the most important variables in the classification, and warrant further investigation. Our results indicate that a proteomics signature may differentiate the S from the R healthy subjects, and may be useful in clinical practice. In addition, it may provide clues of the underlying molecular mechanisms of the chronic stress-related diseases, including myocardial infarction and Alzheimer's disease.