Abstract
Complexity and integration are longstanding widely debated issues in philosophy of science and recent contributions have largely focused on biology and biomedicine. This paper specifically considers some methodological novelties in cancer research, motivated by various features of tumours as complex diseases, and shows how they encourage some rethinking of philosophical discourses on those topics. In particular, we discuss the integrative-cluster approach, and analyse its potential in the epistemology of cancer. We suggest that, far from being the solution to tame cancer complexity, this approach offers a philosophically interesting new manner of considering integration, and show how it can help addressing the apparent contrast between a pluralistic and a unitary account.
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Notes
See e.g. Lemoine (2017).
On integration in biology, along a few of the different dimensions we have recalled, see, e.g., Leonelli (2008, 2016) ch. 6; Brigandt (2010, 2013); O’Malley and Soyer (2012); VV. AA. (2013). On the possible benefits of different ways of conceiving integration, and possible epistemic trade-offs, see also Chang (2012), ch. 5, and Plutynski (2013).
On pathways to the clinic, see also Fagan (2017).
See the position paper of European Society for Predictive, Preventive and Personalised Medicine (EPMA) by Golubnitschaja et al. (2016).
See, https://ghr.nlm.nih.gov/ Precision Medicine; see also https://www.nih.gov/research-training/allofus-research-program (Accessed 30 April 2017).
See the recent issue of Nature (VV. AA. 2013, issue 501) devoted to it.
The receptor status is identified by immunohistochemistry, which stains the cells based on the presence (ER+, PR+, HER2+) or the absence (ER-, PR-, HER2-) of the receptor itself.
A particularly interesting and successful approach proposal on tumour heterogeneity – specifically, in breast cancer - and modes of providing distinctive molecular portraits of each tumour is provided by Perou and Sorlie (see e.g. Perou et al. 2000). As we discuss in the following, what characterizes iCluster with respect to this classification and similar ones is that while these latter are based on molecular features, the former is characterized by both molecular and clinical features.
Of course, this is not the right place to enter technical details on the statistical algorithms that are used. They could be easily retrieved in textbooks on cluster theory, or in the scientific papers adopting statistical models based on it. Our current focus is on the epistemological impact of the adoption of iCluster in dealing with cancer complexity, especially from a classificatory and a prognostic standpoint.
Against the reductionism concerning molecular mechanisms and in favour of a more holist approach based on pathways, see Boniolo and Campaner (2018).
The group obtained about 1000 frozen breast cancer samples from five tumor biobanks in the UK and Canada. It should be noted that “Nearly all oestrogen receptor (ER)-positive and/or lymph node (LN)-negative patients did not receive chemotherapy, whereas ER-negative and LN-positive patients did. Additionally, none of the HER21patients received trastuzumab. As such, the treatments were homogeneous with respect to clinically relevant groupings.” (Curtis et al. 2012, p. 346).
The SNPs are the most common type of genetic variation among people. Each SNP represents a difference in a single DNA nucleotide. CNV is a repetition of sections of the genome the number of repetition varies among people. CNA is a repetition of sections of the genome that has arisen in somatic tissue. Cis module and trasn module are stretches of DNA that affect the expression, respectively, of nearby and distant genes
PAM50 (Prosigna®) is a tumour profiling test that helps determine the benefit of using chemotherapy in addition to hormone therapy for some oestrogen receptor-positive (ER-positive) and HER2-negative breast cancers.
An analogous figure, but contemplating also a column explicitly dedicated to prognosis, is Table II in Dawson et al. (2013).
A tumour is said to have had a pathological Complete Response (i.e. a pCR) if, after surgery, no residual cancer cells remain.
This is what is happening inside the Personalised Breast Cancer Project! See, https://crukcambridgecentre.org.uk/news/personalised-breast-cancer-program-launches-cambridge.
On measures and evaluation of the usefulness of clusters for particular tasks, and for a catalogue of clustering problems, see e.g. Von Luxburg et al. (2012).
For instance, in discussing IntCluster3, Dawson et al. (2013) state: “The excellent prognosis of this subtype emphasizes the importance of identifying this cluster within the previously defined luminal A intrinsic subtype, as these individuals represent a distinct group that could potentially be spared treatment with systemic chemotherapy” (p. 622), while InCluster4 provides hints as to specific immunological responses, to be exploited for future therapies.
See e.g. Hennig (2017).
For some theoretical reflections on the relations between clusters and ways of conceiving natural kinds, reality and truth, see Hennig (2015). Hennig discusses context- and aims-dependence of clustering methods, comparisons and choices among them, and related impacts in practice.
On problems for cancer classification see also Song et al. (2015).
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We would like to thanks the four anonymous referees, whose comments have been very useful to improve early versions of the manuscript.
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Boniolo, G., Campaner, R. Complexity and integration. A philosophical analysis of how cancer complexity can be faced in the era of precision medicine. Euro Jnl Phil Sci 9, 34 (2019). https://doi.org/10.1007/s13194-019-0257-5
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DOI: https://doi.org/10.1007/s13194-019-0257-5