Literature DB >> 34659875

Proteomics and its applications in breast cancer.

Anca-Narcisa Neagu1,2, Danielle Whitham1, Emma Buonanno1, Avalon Jenkins1, Teodora Alexa-Stratulat3, Bogdan Ionel Tamba4, Costel C Darie1.   

Abstract

Breast cancer is an individually unique, multi-faceted and chameleonic disease, an eternal challenge for the new era of high-integrated precision diagnostic and personalized oncomedicine. Besides traditional single-omics fields (such as genomics, epigenomics, transcriptomics and metabolomics) and multi-omics contributions (proteogenomics, proteotranscriptomics or reproductomics), several new "-omics" approaches and exciting proteomics subfields are contributing to basic and advanced understanding of these "multiple diseases termed breast cancer": phenomics/cellomics, connectomics and interactomics, secretomics, matrisomics, exosomics, angiomics, chaperomics and epichaperomics, phosphoproteomics, ubiquitinomics, metalloproteomics, terminomics, degradomics and metadegradomics, adhesomics, stressomics, microbiomics, immunomics, salivaomics, materiomics and other biomics. Throughout the extremely complex neoplastic process, a Breast Cancer Cell Continuum Concept (BCCCC) has been modeled in this review as a spatio-temporal and holistic approach, as long as the breast cancer represents a complex cascade comprising successively integrated populations of heterogeneous tumor and cancer-associated cells, that reflect the carcinoma's progression from a "driving mutation" and formation of the breast primary tumor, toward the distant secondary tumors in different tissues and organs, via circulating tumor cell populations. This BCCCC is widely sustained by a Breast Cancer Proteomic Continuum Concept (BCPCC), where each phenotype of neoplastic and tumor-associated cells is characterized by a changing and adaptive proteomic profile detected in solid and liquid minimal invasive biopsies by complex proteomics approaches. Such a profile is created, beginning with the proteomic landscape of different neoplastic cell populations and cancer-associated cells, followed by subsequent analysis of protein biomarkers involved in epithelial-mesenchymal transition and intravasation, circulating tumor cell proteomics, and, finally, by protein biomarkers that highlight the extravasation and distant metastatic invasion. Proteomics technologies are producing important data in breast cancer diagnostic, prognostic, and predictive biomarkers discovery and validation, are detecting genetic aberrations at the proteome level, describing functional and regulatory pathways and emphasizing specific protein and peptide profiles in human tissues, biological fluids, cell lines and animal models. Also, proteomics can identify different breast cancer subtypes and specific protein and proteoform expression, can assess the efficacy of cancer therapies at cellular and tissular level and can even identify new therapeutic target proteins in clinical studies. AJCR
Copyright © 2021.

Entities:  

Keywords:  Proteomics; biomarkers; breast cancer cell continuum concept; breast cancer proteomic continuum concept

Year:  2021        PMID: 34659875      PMCID: PMC8493401     

Source DB:  PubMed          Journal:  Am J Cancer Res        ISSN: 2156-6976            Impact factor:   5.942


  426 in total

Review 1.  Pharmacogenetics and pharmacogenomics as tools in cancer therapy.

Authors:  Ana E Rodríguez-Vicente; Eva Lumbreras; Jesus M Hernández; Miguel Martín; Antonio Calles; Carlos López Otín; Salvador Martín Algarra; David Páez; Miquel Taron
Journal:  Drug Metab Pers Ther       Date:  2016-03

Review 2.  CDK1 in Breast Cancer: Implications for Theranostic Potential.

Authors:  Sepideh Izadi; Afshin Nikkhoo; Mohammad Hojjat-Farsangi; Afshin Namdar; Gholamreza Azizi; Hamed Mohammadi; Mehdi Yousefi; Farhad Jadidi-Niaragh
Journal:  Anticancer Agents Med Chem       Date:  2020       Impact factor: 2.505

3.  Presence of tertiary lymphoid structures determines the level of tumor-infiltrating lymphocytes in primary breast cancer and metastasis.

Authors:  Miseon Lee; Sun-Hee Heo; In Hye Song; Hajar Rajayi; Hye Seon Park; In Ah Park; Young-Ae Kim; Heejae Lee; Gyungyub Gong; Hee Jin Lee
Journal:  Mod Pathol       Date:  2018-08-28       Impact factor: 7.842

4.  Weibel-Palade Bodies Orchestrate Pericytes During Angiogenesis.

Authors:  Mélissande Cossutta; Marie Darche; Gilles Carpentier; Claire Houppe; Matteo Ponzo; Fabio Raineri; Benoit Vallée; Maud-Emmanuelle Gilles; Delphine Villain; Emilie Picard; Caterina Casari; Cécile Denis; Michel Paques; José Courty; Ilaria Cascone
Journal:  Arterioscler Thromb Vasc Biol       Date:  2019-07-18       Impact factor: 8.311

Review 5.  Targeting the phosphoinositide 3-kinase pathway in cancer.

Authors:  Pixu Liu; Hailing Cheng; Thomas M Roberts; Jean J Zhao
Journal:  Nat Rev Drug Discov       Date:  2009-08       Impact factor: 84.694

6.  Occludin is required for apoptosis when claudin-claudin interactions are disrupted.

Authors:  N Beeman; P G Webb; H K Baumgartner
Journal:  Cell Death Dis       Date:  2012-02-23       Impact factor: 8.469

Review 7.  New Insights Into Implementation of Mesenchymal Stem Cells in Cancer Therapy: Prospects for Anti-angiogenesis Treatment.

Authors:  Mohammad Reza Javan; Arezou Khosrojerdi; Seyed Mohammad Moazzeni
Journal:  Front Oncol       Date:  2019-08-28       Impact factor: 6.244

8.  Circulating tumor cell clusters are oligoclonal precursors of breast cancer metastasis.

Authors:  Nicola Aceto; Aditya Bardia; David T Miyamoto; Maria C Donaldson; Ben S Wittner; Joel A Spencer; Min Yu; Adam Pely; Amanda Engstrom; Huili Zhu; Brian W Brannigan; Ravi Kapur; Shannon L Stott; Toshi Shioda; Sridhar Ramaswamy; David T Ting; Charles P Lin; Mehmet Toner; Daniel A Haber; Shyamala Maheswaran
Journal:  Cell       Date:  2014-08-28       Impact factor: 41.582

Review 9.  Mass spectrometry-based N-glycoproteomics for cancer biomarker discovery.

Authors:  Ying Zhang; Jing Jiao; Pengyuan Yang; Haojie Lu
Journal:  Clin Proteomics       Date:  2014-05-05       Impact factor: 3.988

10.  Proteomic Analysis of Urine to Identify Breast Cancer Biomarker Candidates Using a Label-Free LC-MS/MS Approach.

Authors:  Julia Beretov; Valerie C Wasinger; Ewan K A Millar; Peter Schwartz; Peter H Graham; Yong Li
Journal:  PLoS One       Date:  2015-11-06       Impact factor: 3.240

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