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Cancer

Identifying biomarkers for cancer

Cancers are complex disorders since their risk is influenced by environmental and genetic components. While the environmental components are largely known, the genetic ones remain to be explored. One informative clue that help understand the genetic risk is the difference prevalence that cancers exhibit in different human populations. Multiple myeloma (MM), for example, is two- to three-fold more common in African Americans compared to European Americans. This striking disparity, one of the highest of any cancer, may be due to underlying genetic
predisposition between these groups. But how can we tell who is who? Self-defined race is a highly biased way to characterize populations, which is likely why previous efforts to understand this disparity have failed. 

To mitigate these difficulties, we collaborated with researchers from the Mayo Clinic in collecting the DNA from hundreds of patients with monoclonal gammopathies and calculating their biogeographical ancestry using the Geographic Population Structure Origins (GPS) tool. 

Scientific diagram.
Percent African ancestry by self-reported race in cohort of 881 individuals. From Baughn et al. (2018)

Distribution of the percent of African ancestry based on teh sum of all 10 African regional ancestries within teh 881 samples in this study by self-report race in 393 samples or non-reported race information in 488 samples.

We found the first biomarkers that increased the risk for MM for cancer in African Americans. Similar analyses on other type of cancers were carried with other research centers around the world.

Papers

  1. Baughn LB, Pearce K, Larson D, Polley M-Y, Elhaik E, Baird M, Colby C, Benson J, Li Z, Asmann Y et al: Differences in genomic abnormalities among African individuals with monoclonal gammopathies using calculated ancestry. Blood Cancer Journal 2018, 8(10):96.
  2. Elhaik E, Tatarinova T, Chebotarev D, Piras IS, Maria Calò C, De Montis A, Atzori M, Marini M, Tofanelli S, Francalacci P et al: Geographic population structure analysis of worldwide human populations infers their biogeographical origins. Nat Commun 2014, 5:1-12.
  3. Bartelli TF, Senda de Abrantes LL, Freitas HC, Thomas AM, Silva JM, Albuquerque GE, Araújo LF, Branco GP, de Amorim MG, Serpa MS et al: Genomics and epidemiology for gastric adenocarcinomas (GE4GAC): a Brazilian initiative to study gastric cancer. Applied Cancer Research 2019, 39(1):12
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