Purpose: To analyze the use of proteomic profiles to discriminate healthy from patients with colorectal liver metastases (CLM) and to predict neoplastic recurrence after CLM resection.
Methods: From April 2005 to October 2008, 70 patients operated for first curative resection of CLM and 60 healthy controls underwent determination of preoperative serum proteomic profile. We performed a preliminary training with patients and controls and obtained a classification system based on these patients' proteomic profiles training. The system was then tested about the ability to predict the colon versus rectum origin, metachronous or synchronous appearance, risk of recurrence after CLM resection and whether a sample was from a control or a CLM patient.
Results: Sensitivity, specificity, positive and negative predictive values for detecting CLM patients were 75, 100, 100 and 54.6 %, respectively. Best CLM appearance time identification was 50 % and primary tumor origin identification was 62.5 %. Best classifications of neoplastic recurrence within the first year after CLM resection and during the follow-up period were 47.5 and 45 %, respectively. Larger training sets and prevalence-based training sets led to better classification of patients and characteristics.
Conclusion: Proteomic profiles are a promising tool for discriminating CLM patients from healthy patients and for predicting neoplastic recurrence.
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http://dx.doi.org/10.1007/s12094-012-0990-0 | DOI Listing |
J Proteome Res
January 2025
Discovery Research, AbbVie, Inc., 1 North Waukegan Rd., North Chicago, Illinois 60064, United States.
Affinity capture (AC) combined with mass spectrometry (MS)-based proteomics is highly utilized throughout the drug discovery pipeline to determine small-molecule target selectivity and engagement. However, the tedious sample preparation steps and time-consuming MS acquisition process have limited its use in a high-throughput format. Here, we report an automated workflow employing biotinylated probes and streptavidin magnetic beads for small-molecule target enrichment in the 96-well plate format, ending with direct sampling from EvoSep Solid Phase Extraction tips for liquid chromatography (LC)-tandem mass spectrometry (MS/MS) analysis.
View Article and Find Full Text PDFThyroid
January 2025
Department of Cancer Biology and Genetics, The Ohio State University, Columbus, Ohio, USA.
Medullary thyroid cancer (MTC) is a frequently metastatic tumor of the thyroid that develops from the malignant transformation of C-cells. These tumors most commonly have activating mutations within the RET or RAS proto-oncogenes. Germline mutations within RET result in C-cell hyperplasia, and cause the MTC pre-disposition disorder, multiple endocrine neoplasia, type 2A (MEN2A).
View Article and Find Full Text PDFZinc is central to the function of many proteins, yet the mechanisms of zinc homeostasis and their interplay with other cellular systems remain underexplored. In this study, we employ data-dependent acquisition (DDA) and data-independent acquisition (DIA) mass spectrometry to investigate proteome changes in under conditions of different zinc availability. Using these methods, we detected 2143 unique proteins, 1578 of which were identified by both DDA and DIA.
View Article and Find Full Text PDFAugmented extracellular matrix (ECM) stiffness is a mechanical hallmark of cancer. Mechanotransduction studies have extensively probed the mechanisms by which ECM stiffness regulates intracellular communication. However, the influence of stiffness on intercellular communication aiding tumor progression in three-dimensional microenvironments remains unknown.
View Article and Find Full Text PDFCytotechnology
April 2025
University Centre for Research and Development, University Institute of Pharmaceutical Sciences, Chandigarh University, Gharuan, Mohali, 140413 India.
When juxtaposed with 2D cell culture models, multicellular tumor spheroids demonstrate a capacity to faithfully replicate certain features inherent to solid tumors. These include spatial architecture, physiological responses, the release of soluble mediators, patterns of gene expression, and mechanisms of drug resistance. The morphological and behavioural similarities between 3D-cultured cells and cells within tumor masses highlight the potential of these models in studying cancer biology and drug responses.
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