Cancer subtypes in aetiological research
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Researchers often attempt to categorize tumors into more homogeneous subtypes to better predict prognosis or understand pathogenic mechanisms. In clinical research, typically the focus is on prognosis: the tumor subtypes are intended to be associated with specific responses to treatment and/or different clinical outcomes. In aetiological research, the focus is on identifying distinct pathogenic mechanisms, which may involve different risk factors. We used directed acyclic graphs to present a framework for considering potential biases arising in aetiological research of tumor subtypes, when there is incomplete correspondence between the identified subtypes and the underlying pathogenic mechanisms. We identified two main scenarios: (1) weak effect, when the tumor subtypes are identified through combinations of characteristics and some of these characteristics are affected by factors that are unrelated with the underlying pathogenic mechanisms; and (2) lack of causality, when the set of characteristics corresponds with a mechanism that is actually not a cause of the tumor of interest. Examples of the magnitude of bias that can be introduced in these situations are provided. Although categorization of tumors into homogenous subtypes may have important implications for aetiological research and identification of risk factors, the characteristics used to classify tumors into subtypes should be as close as possible to the actual pathogenic mechanisms to avoid interpretative biases. Whenever our knowledge of these mechanisms is limited, research into risk factors for tumor subtypes should first aim to causally link the characteristics to the pathogenic mechanisms.
KeywordsCancer subtypes Molecular characteristics Bias Disease classification Aetiological research
We would like to thank Dr. Andreas Pettersson for helpful comments on earlier versions of this paper.
Lorenzo Richiardi was partially supported by a Fulbright Research Scholar fellowship when working on this paper. The research leading to these results has received funding from the European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013)/ERC Grant Agreement No. 668954.
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interest.
- 2.Muraro A, Lemanske RF Jr, Hellings PW, Akdis CA, Bieber T, Casale TB, et al. Precision medicine in patients with allergic diseases: airway diseases and atopic dermatitis-PRACTALL document of the European Academy of Allergy and Clinical Immunology and the American Academy of Allergy, Asthma and Immunology. J Allergy Clin Immunol. 2016;137(5):1347–58.CrossRefPubMedGoogle Scholar
- 5.Blows FM, Driver KE, Schmidt MK, Broeks A, van Leeuwen FE, Wesseling J, et al. Subtyping of breast cancer by immunohistochemistry to investigate a relationship between subtype and short and long term survival: a collaborative analysis of data for 10,159 cases from 12 studies. PLoS Med. 2010;7(5):e1000279.CrossRefPubMedPubMedCentralGoogle Scholar
- 7.Goldhirsch A, Winer EP, Coates AS, Gelber RD, Piccart-Gebhart M, Thürlimann B, et al. Personalizing the treatment of women with early breast cancer: highlights of the St Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2013. Ann Oncol. 2013;24(9):2206–23.CrossRefPubMedPubMedCentralGoogle Scholar
- 9.WHO/IARC Classification of tumours, http://publications.iarc.fr/Book-And-Report-Series/Who-Iarc-Classification-Of-Tumours. Accessed 28 Jul 2016.
- 11.Blows FM, Driver KE, Schmidt MK, Broeks A, van Leeuwen FE, Wesseling J, et al. Subtyping of breast cancer by immunohistochemistry to investigate a relationship between subtype and short and long term survival: a collaborative analysis of data for 10,159 cases from 12 studies. PLoS Med. 2010;7(5):e1000279.CrossRefPubMedPubMedCentralGoogle Scholar
- 19.Hamada T, Keum N, Nishihara R, Ogino S. Molecular pathological epidemiology: new developing frontiers of big data science to study etiologies and pathogenesis. J Gastroenterol. 2016 Oct 13.Google Scholar
- 27.Laible M, Schlombs K, Kaiser K, Veltrup E, Herlein S, Lakis S, Stöhr R, Eidt S, Hartmann A, Wirtz RM, Sahin U. Technical validation of an RT-qPCR in vitro diagnostic test system for the determination of breast cancer molecular subtypes by quantification of ERBB2, ESR1, PGR and MKI67 mRNA levels from formalin-fixed paraffin-embedded breast tumor specimens. BMC Cancer. 2016;7(16):398.CrossRefGoogle Scholar
- 30.Denkert C, Liedtke C, Tutt A, von Minckwitz G. Molecular alterations in triple-negative breast cancer-the road to new treatment strategies. Lancet. 2016. doi: 10.1016/S0140-6736(16)32454-0.