Race, race, race.
Read here. Excerpts, emphasis added:
Assessing the role of ancestry-associated genetic variations in disease etiology is further complicated by the recent admixture that characterizes various populations of the world (24). Hence, an individual’s ancestry can be described by quantifying the proportion of the genome derived from each contributing population (global ancestry). Heterogeneity is also observed locally in the genome, as variability is observed in the ancestral origins of any particular segment of chromosomes (local ancestry; ref. 25). Ultimately, genetics plays a role in the biological characteristics of a cancer in the form of both germline variation and somatic alterations. Further research is needed to determine the extent to which genetic differences align with ancestral genetic changes (26).
Cell lines reported as “African” or “Black” clustered with African-American populations in 81.6% of the cases, emphasizing the ambiguity of the existing nomenclature. In fact, the proportion of the genome inferred to be of European origin in these cell lines averaged 18.32% (ranging from 0% to 95.09%). Another type of ambiguity concerns the cell line Hs 698.T labeled as originating from an “American Indian,” which clusters with populations of South Asia, suggesting an origin in India rather than from a Native/Indigenous American individual. A total of 26 cell lines were reported as Caucasian but clustered genetically with other populations including African (n = 2), African American (n = 6), East Asian (n = 1), Hispanic/Latinos (n = 16), and South Asian (n = 1). Interestingly, 89% of the cell lines identified as Hispanic/Latino from admixture patterns and clustering are reported as “Caucasian.” Several groups have reported a concordance between self- or observer-reported belonging to major racial/ethnic groups (141–143). However, these categories do not capture the inherent heterogeneity of admixed populations (144–147). What appears as inconsistencies in self-report and genetic data may result from individuals having limited knowledge of their ancestral origins, or culturally identifying to an ethnic group that is not representative of one’s admixture proportions (18). Sociological, behavioral, and biological factors that underlie race, ethnicity, and ancestry are likely to interact (148). Consequently, from a biomedical research perspective, both self-reports of race/ethnicity group as well as genetically determined clustering and admixture are expected to be relevant in understanding disease susceptibility, and ultimately, the causes of health disparities (18, 148, 149).
Note the last phrase. Also, importantly, there is misclassification. Given that people are not always accurate about their own self-reported ancestry, what can we say about the ancestry testing companies that use customer samples to inflate their pathetically limited parental/reference population datasets?
Also consider Figure 1 in the paper. It looks to me like the cancer cell lines exhibit more admixture than the actual human population samples. At the very least,there are observable differences in ancestral proportions. Some of that of course is simply the well known admixture in “African Americans,” but what about the other populations? That could be due to the misclassification mentioned above, there are of course issues about sample size, and concerns over how accurate the ancestry testing is. Cancer cell lines also tend to have high mutation rates, reflecting the situation in the tumor of origin. However, even with all those caveats, can we consider the possibility that increased admixture is associated with a higher cancer risk; hence, cancer cell lines show more admixture because cancer patients are on average more admixed than is typical of the general population? Given how prevalent cancer is, the differences are not great, as we are dividing populations in two relatively similar “chunks” (the difference being cancer vs. non-cancer); but still, if there is going to be any differences between the two “chunks” – perhaps the cancer “chunk” exhibits more admixture than the non-cancer “chunk?” Anyone willing to test the hypothesis? Or, we can consider the more general hypothesis of statistically significant differences in ancestry between cancer vs. non-cancer for each population group (regardless of admixture, or which group has more admixture, etc.).