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Mesenchymal stem cells (MSCs) gain an increasing focus in the field of regenerative medicine due to their differentiation abilities into chondrocytes, adipocytes, and osteoblastic cells. However, it is apparent that the transformation processes are extremely complex and cause cellular heterogeneity. The study aimed to characterize differences between MSCs and cells after adipogenic (AD) or osteoblastic (OB) differentiation at the proteome level. Comparative proteomic profiling was performed using tandem mass spectrometry in data-independent acquisition mode. Proteins were quantified by deep neural networks in library-free mode and correlated to the Molecular Signature Database (MSigDB) hallmark gene set collections for functional annotation. We analyzed 4108 proteins across all samples, which revealed a distinct clustering between MSCs and cell differentiation states. Protein expression profiling identified activation of the Peroxisome proliferator-activated receptors (PPARs) signaling pathway after AD. In addition, two distinct protein marker panels could be defined for osteoblastic and adipocytic cell lineages. Hereby, overexpression of AEBP1 and MCM4 for OB as well as of FABP4 for AD was detected as the most promising molecular markers. Combination of deep neural network and machine-learning algorithms with data-independent mass spectrometry distinguish MSCs and cell lineages after adipogenic or osteoblastic differentiation. We identified specific proteins as the molecular basis for bone formation, which could be used for regenerative medicine in the future. [ABSTRACT FROM AUTHOR]

B Change in Author Names b In the original version of our article [[1]], insufficient acknowledgement was given for the proteomic experiments, sample selection, analysis of results and drafting of the manuscript. B Change in the Authors Contributions b Due to the change in the author list, the Author contributions were corrected in the original article version [[1]]. All authors read as well as approved the final manuscript and agreed to be personally accountable for the author's own contributions. [Extracted from the article]

Simple Summary: The majority (69.7%) of women diagnosed with breast cancer are above the age of 55. The population of older breast cancer patients is growing. Nevertheless, older patients are underrepresented in cancer research. Therefore, our study set the focus on breast cancer patients aged 50 years and older with a median age of 67 years aiming to understand the influence of aneuploidy, genomic instability and inter- and intratumor heterogeneity on disease outcome, being a major obstacle for precise prognostication and successful treatment. We analyzed chromosomal copy number changes, ploidy and specific gene mutations and found an enormous degree of genomic instability and intratumor heterogeneity in our cohort. However, neither the ploidy, the degree of intratumor heterogeneity nor the presence of specific gene mutations was correlated with prognosis. Our findings provide a precise description of the degree of intratumor heterogeneity, genomic instability, and gene mutations in breast cancer patients aged 50 years and older, revealing significant differences between diploid and aneuploid tumors regarding copy number alterations and the extent of genomic instability. Purpose: Older breast cancer patients are underrepresented in cancer research even though the majority (81.4%) of women dying of breast cancer are 55 years and older. Here we study a common phenomenon observed in breast cancer which is a large inter- and intratumor heterogeneity; this poses a tremendous clinical challenge, for example with respect to treatment stratification. To further elucidate genomic instability and tumor heterogeneity in older patients, we analyzed the genetic aberration profiles of 39 breast cancer patients aged 50 years and older (median 67 years) with either short (median 2.4 years) or long survival (median 19 years). The analysis was based on copy number enumeration of eight breast cancer-associated genes using multiplex interphase fluorescence in situ hybridization (miFISH) of single cells, and by targeted next-generation sequencing of 563 cancer-related genes. Results: We detected enormous inter- and intratumor heterogeneity, yet maintenance of common cancer gene mutations and breast cancer specific chromosomal gains and losses. The gain of COX2 was most common (72%), followed by MYC (69%); losses were most prevalent for CDH1 (74%) and TP53 (69%). The degree of intratumor heterogeneity did not correlate with disease outcome. Comparing the miFISH results of diploid with aneuploid tumor samples significant differences were found: aneuploid tumors showed significantly higher average signal numbers, copy number alterations (CNAs) and instability indices. Mutations in PIKC3A were mostly restricted to luminal A tumors. Furthermore, a significant co-occurrence of CNAs of DBC2/MYC, HER2/DBC2 and HER2/TP53 and mutual exclusivity of CNAs of HER2 and PIK3CA mutations and CNAs of CCND1 and PIK3CA mutations were revealed. Conclusion: Our results provide a comprehensive picture of genome instability profiles with a large variety of inter- and intratumor heterogeneity in breast cancer patients aged 50 years and older. In most cases, the distribution of chromosomal aneuploidies was consistent with previous results; however, striking exceptions, such as tumors driven by exclusive loss of chromosomes, were identified. [ABSTRACT FROM AUTHOR]

Solid tumor biopsies are the current standard for precision medicine. However, the procedure is invasive and not always feasible. In contrast, liquid biopsies, such as serum enriched for extracellular vesicles (EVs) represent a non-invasive source of cancer biomarkers. In this study, we compared two EV isolation methods in the context of the protein biomarker detection in inflammatory bowel disease (IBD) and colorectal cancer (CRC). Using serum samples of a healthy cohort as well as CRC and IBD patients, EVs were isolated by ultracentrifugation and ExoQuick™ in parallel. EV associated protein profiles were compared by multiplex-fluorescence two-dimensional difference gel electrophoresis (2D-DIGE) and subsequent identification by mass spectrometry. Validation of gelsolin (GSN) was performed using fluorescence-quantitative western blot. 2D-DIGE resolved 936 protein spots in all serum-enriched EVs isolated by ultracentrifugation or ExoQuick™. Hereof, 93 spots were differently expressed between isolation approaches. Higher levels of GSN in EVs obtained with ExoQuick™ compared to ultracentrifugation were confirmed by western blot (p = 0.0006). Although patient groups were distinguishable after both EV isolation approaches, sample preparation strongly influences EVs' protein profile and thus impacts on inter-study reproducibility, biomarker identification and validation. The results stress the need for strict SOPs in EV research before clinical implementation can be reached. [ABSTRACT FROM AUTHOR]