Delineating intra-tumoral heterogeneity and tumor evolution in breast cancer using precision-based approaches

被引:7
作者
Xulu, Kutlwano Rekgopetswe [1 ]
Nweke, Ekene Emmanuel [2 ]
Augustine, Tanya Nadine [1 ]
机构
[1] Univ Witwatersrand, Fac Hlth Sci, Sch Anat Sci, Johannesburg, South Africa
[2] Univ Witwatersrand, Fac Hlth Sci, Sch Clin Med, Dept Surg, Johannesburg, South Africa
基金
新加坡国家研究基金会;
关键词
breast cancer; breast cancer genetics; signaling pathways; precision medicine; targeted therapy; tumor evolution; tumor heterogeneity; TRASTUZUMAB EMTANSINE T-DM1; GENE-EXPRESSION; ELECTROCHEMICAL IMMUNOSENSOR; INFILTRATING LYMPHOCYTES; MOLECULAR CLASSIFICATION; ESTROGEN; CELLS; ASSAY; MACROPHAGES; SUBTYPES;
D O I
10.3389/fgene.2023.1087432
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
The burden of breast cancer continues to increase worldwide as it remains the most diagnosed tumor in females and the second leading cause of cancer-related deaths. Breast cancer is a heterogeneous disease characterized by different subtypes which are driven by aberrations in key genes such as BRCA1 and BRCA2, and hormone receptors. However, even within each subtype, heterogeneity that is driven by underlying evolutionary mechanisms is suggested to underlie poor response to therapy, variance in disease progression, recurrence, and relapse. Intratumoral heterogeneity highlights that the evolvability of tumor cells depends on interactions with cells of the tumor microenvironment. The complexity of the tumor microenvironment is being unraveled by recent advances in screening technologies such as high throughput sequencing; however, there remain challenges that impede the practical use of these approaches, considering the underlying biology of the tumor microenvironment and the impact of selective pressures on the evolvability of tumor cells. In this review, we will highlight the advances made thus far in defining the molecular heterogeneity in breast cancer and the implications thereof in diagnosis, the design and application of targeted therapies for improved clinical outcomes. We describe the different precision-based approaches to diagnosis and treatment and their prospects. We further propose that effective cancer diagnosis and treatment are dependent on unpacking the tumor microenvironment and its role in driving intratumoral heterogeneity. Underwriting such heterogeneity are Darwinian concepts of natural selection that we suggest need to be taken into account to ensure evolutionarily informed therapeutic decisions.
引用
收藏
页数:19
相关论文
共 182 条
[1]   Machine learning approaches to decipher hormone and HER2 receptor status phenotypes in breast cancer [J].
Adabor, Emmanuel S. ;
Acquaah-Mensah, George K. .
BRIEFINGS IN BIOINFORMATICS, 2019, 20 (02) :504-514
[2]   The repertoire of mutational signatures in human cancer [J].
Alexandrov, Ludmil B. ;
Kim, Jaegil ;
Haradhvala, Nicholas J. ;
Huang, Mi Ni ;
Ng, Alvin Wei Tian ;
Wu, Yang ;
Boot, Arnoud ;
Covington, Kyle R. ;
Gordenin, Dmitry A. ;
Bergstrom, Erik N. ;
Islam, S. M. Ashiqul ;
Lopez-Bigas, Nuria ;
Klimczak, Leszek J. ;
McPherson, John R. ;
Morganella, Sandro ;
Sabarinathan, Radhakrishnan ;
Wheeler, David A. ;
Mustonen, Ville ;
Getz, Gad ;
Rozen, Steven G. ;
Stratton, Michael R. .
NATURE, 2020, 578 (7793) :94-+
[3]   Estrogen and Progesterone Receptor Testing in Breast Cancer: ASCO/CAP Guideline Update [J].
Allison, Kimberly H. ;
Hammond, M. Elizabeth H. ;
Dowsett, Mitchell ;
McKernin, Shannon E. ;
Carey, Lisa A. ;
Fitzgibbons, Patrick L. ;
Hayes, Daniel F. ;
Lakhani, Sunil R. ;
Chavez-MacGregor, Mariana ;
Perlmutter, Jane ;
Perou, Charles M. ;
Regan, Meredith M. ;
Rimm, David L. ;
Symmans, W. Fraser ;
Torlakovic, Emina E. ;
Varella, Leticia ;
Viale, Giuseppe ;
Weisberg, Tracey F. ;
McShane, Lisa M. ;
Wolff, Antonio C. .
JOURNAL OF CLINICAL ONCOLOGY, 2020, 38 (12) :1346-+
[4]   Triple-Negative Breast Cancer: A Brief Review About Epidemiology, Risk Factors, Signaling Pathways, Treatment and Role of Artificial Intelligence [J].
Almansour, Nahlah Makki .
FRONTIERS IN MOLECULAR BIOSCIENCES, 2022, 9
[5]   Applications of Computational Methods in Biomedical Breast Cancer Imaging Diagnostics: A Review [J].
Aruleba, Kehinde ;
Obaido, George ;
Ogbuokiri, Blessing ;
Fadaka, Adewale Oluwaseun ;
Klein, Ashwil ;
Adekiya, Tayo Alex ;
Aruleba, Raphael Taiwo .
JOURNAL OF IMAGING, 2020, 6 (10)
[6]   Proteomic analysis of archival breast cancer clinical specimens identifies biological subtypes with distinct survival outcomes [J].
Asleh, Karama ;
Negri, Gian Luca ;
Miko, Sandra E. Spencer ;
Colborne, Shane ;
Hughes, Christopher S. ;
Wang, Xiu Q. ;
Gao, Dongxia ;
Gilks, C. Blake ;
Chia, Stephen K. L. ;
Nielsen, Torsten O. ;
Morin, Gregg B. .
NATURE COMMUNICATIONS, 2022, 13 (01)
[7]   Multiple Protein Analysis of Formalin-fixed and Paraffin-embedded Tissue Samples with Reverse phase Protein Arrays [J].
Assadi, Maziar ;
Lamerz, Jens ;
Jarutat, Tiantom ;
Farfsing, Alexandra ;
Paul, Hubert ;
Gierke, Berthold ;
Breitinger, Ewa ;
Templin, Markus F. ;
Essioux, Laurent ;
Arbogast, Susanne ;
Venturi, Miro ;
Pawlak, Michael ;
Langen, Hanno ;
Schindler, Thomas .
MOLECULAR & CELLULAR PROTEOMICS, 2013, 12 (09) :2615-2622
[8]   Rising global burden of breast cancer: the case of sub-Saharan Africa (with emphasis on Nigeria) and implications for regional development: a review [J].
Azubuike, Samuel O. ;
Muirhead, Colin ;
Hayes, Louise ;
McNally, Richard .
WORLD JOURNAL OF SURGICAL ONCOLOGY, 2018, 16
[9]   Selecting patients with HER2-low breast cancer: Getting out of the tangle [J].
Baez-Navarro, Ximena ;
Salgado, Roberto ;
Denkert, Carsten ;
Lennerz, Jochen K. ;
Penault-Llorca, Frederique ;
Viale, Giuseppe ;
Bartlett, John M. S. ;
van Deurzen, Carolien H. M. .
EUROPEAN JOURNAL OF CANCER, 2022, 175 :187-192
[10]   Tumor microenvironment complexity and therapeutic implications at a glance [J].
Baghba, Roghayyeh ;
Roshangar, Leila ;
Jahanban-Esfahlan, Rana ;
Seidi, Khaled ;
Ebrahimi-Kalan, Abbas ;
Jaymand, Mehdi ;
Kolahian, Saeed ;
Javaheri, Tahereh ;
Zare, Peyman .
CELL COMMUNICATION AND SIGNALING, 2020, 18 (01)