Special Issue "Proteomics and Its Applications in Cancer"

A special issue of Biomedicines (ISSN 2227-9059). This special issue belongs to the section "Cancer Biology and Therapeutics".

Deadline for manuscript submissions: 31 October 2023 | Viewed by 1061

Special Issue Editors

Department of Bioinformatics and Structural Biochemistry, Institute of Biochemistry of the Romanian Academy (IBRA), 296 Spl. Independenţei, 060031 Bucharest, Romania
Interests: Mass-spectrometry based proteomics; glycoproteomics; interaction-proteomics; HLA peptidomics
1. Faculty of Chemistry, Al. I. Cuza University of Iasi, 11, Carol I Boulevard, 700506 Iasi, Romania
2. Department of Chemistry & Biomolecular Science, Clarkson University, 8 Clarkson Avenue, Potsdam, NY 13699, USA
3. Center for Fundamental Research and Experimental Development in Translation Medicine–TRANSCEND, Regional Institute of Oncology, 700483 Iasi, Romania
Interests: peptide chemistry; amyloid peptides; mass spectrometry; proteomics; enzymatic substrates; lysosomal rare diseases
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Current technological advancements in mass spectrometry and separation instrumentation had allowed proteome characterization at an unprecedented depth deciphering the molecular phenotype of various pathologies. Among them, cancer still constitutes a significant therapeutic challenge, particularly for late-stage diagnosed clinical cases or uncommon cancer forms, for which proteome characterization and biomarker identification continue to get a lot of attention. Quantitative proteomics established itself as a key-method in explaining molecular changes during malignant transformation, as recently proved by various consortia aiming to bring proteomics technologies closer to the clinics.

The current special issue concentrates on the application of proteomics-derived technologies. Systems-level characterization of various post translational modifications with an emphasize on tumor biology are also welcomed.

We are interested in both, original manuscripts, and reviews for this special issue.

Dr. Cristian Munteanu
Dr. Brînduşa Alina Petre
Guest Editors

Manuscript Submission Information

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  • proteomics
  • mass spectrometry
  • bioinformatics
  • tumor biology
  • biomarkers
  • glycoproteomics
  • phosphoproteomics

Published Papers (1 paper)

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Integrating Proteomics and Lipidomics for Evaluating the Risk of Breast Cancer Progression: A Pilot Study
Biomedicines 2023, 11(7), 1786; https://doi.org/10.3390/biomedicines11071786 - 22 Jun 2023
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Metastasis is a serious and often life-threatening condition, representing the leading cause of death among women with breast cancer (BC). Although the current clinical classification of BC is well-established, the addition of minimally invasive laboratory tests based on peripheral blood biomarkers that reflect [...] Read more.
Metastasis is a serious and often life-threatening condition, representing the leading cause of death among women with breast cancer (BC). Although the current clinical classification of BC is well-established, the addition of minimally invasive laboratory tests based on peripheral blood biomarkers that reflect pathological changes in the body is of utmost importance. In the current study, the serum proteome and lipidome profiles for 50 BC patients with (25) and without (25) metastasis were studied. Targeted proteomic analysis for concertation measurements of 125 proteins in the serum was performed via liquid chromatography–multiple reaction monitoring mass spectrometry (LC–MRM MS) using the BAK 125 kit (MRM Proteomics Inc., Victoria, BC, Canada). Untargeted label-free lipidomic analysis was performed using liquid chromatography coupled to tandem mass-spectrometry (LC–MS/MS), in both positive and negative ion modes. Finally, 87 serum proteins and 295 lipids were quantified and showed a moderate correlation with tumor grade, histological and biological subtypes, and the number of lymph node metastases. Two highly accurate classifiers that enabled distinguishing between metastatic and non-metastatic BC were developed based on proteomic (accuracy 90%) and lipidomic (accuracy 80%) features. The best classifier (91% sensitivity, 89% specificity, AUC = 0.92) for BC metastasis diagnostics was based on logistic regression and the serum levels of 11 proteins: alpha-2-macroglobulin, coagulation factor XII, adiponectin, leucine-rich alpha-2-glycoprotein, alpha-2-HS-glycoprotein, Ig mu chain C region, apolipoprotein C-IV, carbonic anhydrase 1, apolipoprotein A-II, apolipoprotein C-II and alpha-1-acid glycoprotein 1. Full article
(This article belongs to the Special Issue Proteomics and Its Applications in Cancer)
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