In a review published in April 2021 in Cancer Letters (Rovigatti, U.: “The glycosphingolipid GD2 as an effective but enigmatic target of passive immunotherapy in children with aggressive neuroblastoma (HR-NBL) ”CL, 503: pp 220-230), I suggested that the present understanding of the pediatric tumor neuroblastoma (NBL) is insufficient for disease onset and progression, despite approximately four decades of molecular discoveries and characterization of genetic and genomic aberrations. In this sense, NBL epitomizes the genetic landscape of the majority of human cancers, where the appearance of genetic alterations was often considered independent from direct causality. An extreme version of such modeling was presented a few years ago by Tomasetti and Vogelstein and has been often recognized as the “bad luck” model (Science Vol. 355, pp. 1330-1334). In this type of modeling, causation appears to be irrelevant and the emphasis is placed upon therapeutic interventions. In NBL however, amplification of the MYCN oncogene (MNA) is a recurrent event in 20%-25% of cases and this dramatic genomic aberration is difficult to reconcile with a normal-rate mutation accrual. Furthermore, NMA patients have a “different disease” in terms of prognosis and excellent sensitivity to passive immunotherapy with anti-GD2 monoclonal antibodies (Kushner et al. 2017, Oncotarget, 8: 95.293- 302). Similar recurring aberrations are present in lung, breast, colon cancer etc. (Vogelstein et al. Cancer Genome Landscapes: Science Vol. 339, pp. 1546-1558). From the study of a cancer-cluster of NBL cases, we have isolated a dsRNA virus capable of inducing MNA in previously diploid cells (called Micro-Foci inducing Virus or MFV). Therefore, the excellent sensitivity of these patients to anti-GD2 monoclonals therapy –which is not otherwise explainable with the plethora of NBL genomic aberrations- could be explained by the chemical nature of GD2, which appears to be a receptor for this family of viruses (Reoviridae). In the concluding general discussion, I will present new data against a unique or dominating model for cancer onset and progression (such as Hallmarks of Cancer, 2000 and 2011) and encourage alternative explicatory mechanisms which are more capable of resolving the different puzzles of cancer genetic and genomics (Rovigatti, U.: Cancer Modeling in the NGS Era: CROH 2015, 96: 274-307 ).