7Despite recent advances in treatment, cancer continues to be one of the most lethal human 8 maladies. One of the challenges of cancer treatment is the extreme diversity among seemingly 9 identical tumors: while some tumors may have good prognosis and are treatable, others are quite 10 aggressive, and may lack of effective therapies. Most of this variability comes from wide-spread 11 mutations and epigenetic alterations. Using a novel omic-integration method, we have exploited 12 this molecular information to re-classify tumors beyond the constraints of cell type. Eight novel 13 tumor groups (C1-8) emerged, characterized by unique cancer signatures. C3 had better prognosis, 14 genome stability, and immune infiltration. C2 and C5 had higher genome instability and poorer 15 clinical outcomes. Remaining clusters were characterized by worse outcomes, along with higher 16 genome instability. C1, C7, and C8 were upregulated for cellular and mitochondrial translation, 17 and relatively low proliferation. C6 and C4 were also downregulated for cellular and mitochondrial 18 translation, and had high proliferation rates. C4 was represented by copy losses on chromosome 19 6, and had the highest number of metastatic samples. C8 was characterized by copy losses on 20 chromosome 11, having also the lowest lymphocytic infiltration rate. C6 had the lowest natural 21 killer infiltration rate and was represented by copy gains of genes in chromosome 11. C7 was 22 represented by copy gains on chromosome 6, and had the highest upregulation in mitochondrial 23 translation. We believe that, since molecularly alike tumors could respond similarly to treatment, 24 our results could inform therapeutic action. 25 Significance 26 Cancer has been traditionally studied as a family of different diseases from different anatomical 27 sites. Nevertheless, regardless of the tissue of origin, cancer can be characterized by molecular 28 alterations on mechanisms controlling cell fate and progression. In this study, we integrate 33 29 cancer types and show the existence of eight clusters with unique genomic signatures and clinical 30 characteristics, beyond the site of origin of the tumor. The study and treatment of cancer, based on 31 predominant molecular features, rather than site of origin, can potentially aid in the discovery of 32 novel therapeutic alternatives.33