Prognostic gene expression signatures of breast cancer are lacking a sensible biological meaning

被引:28
作者
Manjang, Kalifa [1 ]
Tripathi, Shailesh [1 ]
Yli-Harja, Olli [2 ,3 ,7 ]
Dehmer, Matthias [4 ,5 ,6 ]
Glazko, Galina [7 ]
Emmert-Streib, Frank [1 ,8 ]
机构
[1] Tampere Univ, Predict Soc & Data Analyt Lab, Korkeakoulunkatu 10, Tampere 33720, Finland
[2] Tampere Univ, Computat Syst Biol, Korkeakoulunkatu 10, Tampere 33720, Finland
[3] Inst Syst Biol, Seattle, WA USA
[4] Univ Appl Sci Upper Austria, Steyr Sch Management, 4400 Steyr Campus, Wels, Austria
[5] Nankai Univ, Coll Artificial Intelligence, Tianjin 300350, Peoples R China
[6] UMIT Hlth & Life Sci Univ, Dept Biomed Comp Sci & Mechatron, A-6060 Innsbruck, Austria
[7] Univ Arkansas Med Sci, Dept Biomed Informat, Little Rock, AR 72205 USA
[8] Tampere Univ, Inst Biosci & Med Technol, Korkeakoulunkatu 10, Tampere 33720, Finland
关键词
PREDICTION; SURVIVAL; DEFINITION; PROFILES;
D O I
10.1038/s41598-020-79375-y
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The identification of prognostic biomarkers for predicting cancer progression is an important problem for two reasons. First, such biomarkers find practical application in a clinical context for the treatment of patients. Second, interrogation of the biomarkers themselves is assumed to lead to novel insights of disease mechanisms and the underlying molecular processes that cause the pathological behavior. For breast cancer, many signatures based on gene expression values have been reported to be associated with overall survival. Consequently, such signatures have been used for suggesting biological explanations of breast cancer and drug mechanisms. In this paper, we demonstrate for a large number of breast cancer signatures that such an implication is not justified. Our approach eliminates systematically all traces of biological meaning of signature genes and shows that among the remaining genes, surrogate gene sets can be formed with indistinguishable prognostic prediction capabilities and opposite biological meaning. Hence, our results demonstrate that none of the studied signatures has a sensible biological interpretation or meaning with respect to disease etiology. Overall, this shows that prognostic signatures are black-box models with sensible predictions of breast cancer outcome but no value for revealing causal connections. Furthermore, we show that the number of such surrogate gene sets is not small but very large.
引用
收藏
页数:18
相关论文
共 50 条
[41]   Tumor Microenvironment Characterization in Breast Cancer Identifies Prognostic Pathway Signatures [J].
Li, Ji ;
Qiu, Jiayue ;
Han, Junwei ;
Li, Xiangmei ;
Jiang, Ying .
GENES, 2022, 13 (11)
[42]   Programmed death-ligand 1 gene expression is a prognostic marker in early breast cancer and provides additional prognostic value to 21-gene and 70-gene signatures in estrogen receptor-positive disease [J].
Zerdes, Ioannis ;
Sifakis, Emmanouil G. ;
Matikas, Alexios ;
Chretien, Sebastian ;
Tobin, Nicholas P. ;
Hartman, Johan ;
Rassidakis, George Z. ;
Bergh, Jonas ;
Foukakis, Theodoros .
MOLECULAR ONCOLOGY, 2020, 14 (05) :951-963
[43]   Gene-expression signatures in ovarian cancer: Promise and challenges for patient stratification [J].
Konecny, Gottfried E. ;
Winterhoff, Boris ;
Wang, Chen .
GYNECOLOGIC ONCOLOGY, 2016, 141 (02) :379-385
[44]   Patient sample-oriented analysis of gene expression highlights extracellular signatures in breast cancer progression [J].
Hong, Yourae ;
Kim, Nayoung ;
Li, Chao ;
Jeong, Euna ;
Yoon, Sukjoon .
BIOCHEMICAL AND BIOPHYSICAL RESEARCH COMMUNICATIONS, 2017, 487 (02) :307-312
[45]   Race, Gene Expression Signatures, and Clinical Outcomes of Patients With High-Risk Early Breast Cancer [J].
Kyalwazi, Beverly ;
Yau, Christina ;
Campbell, Michael J. ;
Yoshimatsu, Toshio F. ;
Chien, A. Jo ;
Wallace, Anne M. ;
Forero-Torres, Andres ;
Pusztai, Lajos ;
Ellis, Erin D. ;
Albain, Kathy S. ;
Blaes, Anne H. ;
Haley, Barbara B. ;
Boughey, Judy C. ;
Elias, Anthony D. ;
Clark, Amy S. ;
Isaacs, Claudine J. ;
Nanda, Rita ;
Han, Hyo S. ;
Yung, Rachel L. ;
Tripathy, Debasish ;
Edmiston, Kristen K. ;
Viscusi, Rebecca K. ;
Northfelt, Donald W. ;
Khan, Qamar J. ;
Asare, Smita M. ;
Wilson, Amy ;
Hirst, Gillian L. ;
Lu, Ruixiao ;
Symmans, William Fraser ;
Yee, Douglas ;
DeMichele, Angela M. ;
van 't Veer, Laura J. ;
Esserman, Laura J. ;
Olopade, Olufunmilayo I. .
JAMA NETWORK OPEN, 2023, 6 (12) :E2349646
[46]   Robust Prognostic Gene Expression Signatures in Bladder Cancer and Lung Adenocarcinoma Depend on Cell Cycle Related Genes [J].
Dancik, Garrett M. ;
Theodorescu, Dan .
PLOS ONE, 2014, 9 (01)
[47]   Prognostic gene signatures for non-small-cell lung cancer [J].
Boutros, Paul C. ;
Lau, Suzanne K. ;
Pintilie, Melania ;
Liu, Ni ;
Shepherd, Frances A. ;
Der, Sandy D. ;
Tsao, Ming-Sound ;
Penn, Linda Z. ;
Jurisica, Igor .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2009, 106 (08) :2824-2828
[48]   Prognostic implications of metabolism-associated gene signatures in colorectal cancer [J].
Miao, Yandong ;
Li, Qiutian ;
Wang, Jiangtao ;
Quan, Wuxia ;
Li, Chen ;
Yang, Yuan ;
Mi, Denghai .
PEERJ, 2020, 8
[49]   Investigating the Prognostic Role of Telomerase-Related Cellular Senescence Gene Signatures in Breast Cancer Using Machine Learning [J].
Li, Qiong ;
Liu, Hongde .
BIOMEDICINES, 2025, 13 (04)
[50]   A prognostic eight-gene expression signature for patients with breast cancer receiving adjuvant chemotherapy [J].
Cui, Qiuxia ;
Tang, Jianing ;
Zhang, Dan ;
Kong, Deguang ;
Liao, Xing ;
Ren, Jiangbo ;
Gong, Yan ;
Xie, Conghua ;
Wu, Gaosong .
JOURNAL OF CELLULAR BIOCHEMISTRY, 2020, 121 (8-9) :3923-3934