Aging is one of the hallmarks of multiple human diseases, including cancer. We hypothesized that variations in the number of copies (CNVs) of specific genes may protect some long-living organisms theoretically more susceptible to tumorigenesis from the onset of cancer. Based on the statistical comparison of gene copy numbers within the genomes of both cancer-prone and -resistant species, we identified novel gene targets linked to tumor predisposition, such as CD52, SAT1 and SUMO. Moreover, considering their genome-wide copy number landscape, we discovered that microRNAs (miRNAs) are among the most significant gene families enriched for cancer progression and predisposition. Through bioinformatics analyses, we identified several alterations in miRNAs copy number patterns, involving miR-221, miR-222, miR-21, miR-372, miR-30b, miR-30d and miR-31, among others. Therefore, our analyses provide the first evidence that an altered miRNAs copy number signature can statistically discriminate species more susceptible to cancer from those that are tumor resistant, paving the way for further investigations.

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Aging is one of the hallmarks of multiple human diseases, including cancer. However, the molecular mechanisms associated with high longevity and low cancer incidence percentages characterizing long-living organisms have not been fully understood yet. In this context, we hypothesized that variations in the number of copies (CNVs) of specific genes may protect some species from cancer onset. Based on the statistical comparison of gene copy numbers within the genomes of cancer -prone and -resistant organisms, we identified novel gene targets linked to the tumor predisposition of a species, such as CD52, SAT1 and SUMO protein family members. Furthermore, for the first time, we were able to discover that, considering the entire genome copy number landscape of a species, microRNAs (miRNAs) are among the most significant gene families enriched for cancer progression and predisposition. However, their roles in ageing and cancer resistance from a comparative perspective remains largely unknown. To this end, we identified through bioinformatics analysis, several alterations in miRNAs copy number patterns, represented by duplication of miR-221, miR-222, miR-21, miR-372, miR-30b, miR-30d and miR-31 among others. Therefore, our analysis provides the first evidence that an altered copy number miRNAs signature is able to statistically discriminate species more susceptible to cancer than those that are tumor resistant, helping researchers to discover new possible therapeutic targets involved in tumor predisposition.