Aneuploidy is a very rare and tissue‐specific event in normal conditions, occurring in a low number of brain and liver cells. Its frequency increases in age‐related disorders and is one of the hallmarks of cancer. Aneuploidy has been associated with defects in the spindle assembly checkpoint (SAC). However, the relationship between chromosome number alterations, SAC genes and tumor susceptibility remains unclear. Here, we provide a comprehensive review of SAC gene alterations at genomic and transcriptional level across human cancers and discuss the oncogenic and tumor suppressor functions of aneuploidy. SAC genes are rarely mutated but frequently overexpressed, with a negative prognostic impact on different tumor types. Both increased and decreased SAC gene expression show oncogenic potential in mice. SAC gene upregulation may drive aneuploidization and tumorigenesis through mitotic delay, coupled with additional oncogenic functions outside mitosis. The genomic background and environmental conditions influence the fate of aneuploid cells. Aneuploidy reduces cellular fitness. It induces growth and contact inhibition, mitotic and proteotoxic stress, cell senescence and production of reactive oxygen species. However, aneuploidy confers an evolutionary flexibility by favoring genome and chromosome instability (CIN), cellular adaptation, stem cell‐like properties and immune escape. These properties represent the driving force of aneuploid cancers, especially under conditions of stress and pharmacological pressure, and are currently under investigation as potential therapeutic targets. Indeed, promising results have been obtained from synthetic lethal combinations exploiting CIN, mitotic defects, and aneuploidy‐tolerating mechanisms as cancer vulnerability.

Detecting somatic mutations in whole exome sequencing data of cancer samples has become a popular approach for profiling cancer development, progression and chemotherapy resistance. Several studies have proposed software packages, filters and parametrizations. However, many research groups reported low concordance among different methods. We aimed to develop a pipeline which detects a wide range of single nucleotide mutations with high validation rates. We combined two standard tools – Genome Analysis Toolkit (GATK) and MuTect – to create the GATK-LODN method. As proof of principle, we applied our pipeline to exome sequencing data of hematological (Acute Myeloid and Acute Lymphoblastic Leukemias) and solid (Gastrointestinal Stromal Tumor and Lung Adenocarcinoma) tumors. We performed experiments on simulated data to test the sensitivity and specificity of our pipeline. The software MuTect presented the highest validation rate (90 %) for mutation detection, but limited number of somatic mutations detected. The GATK detected a high number of mutations but with low specificity. The GATK-LODN increased the performance of the GATK variant detection (from 5 of 14 to 3 of 4 confirmed variants), while preserving mutations not detected by MuTect. However, GATK-LODN filtered more variants in the hematological samples than in the solid tumors. Experiments in simulated data demonstrated that GATK-LODN increased both specificity and sensitivity of GATK results. We presented a pipeline that detects a wide range of somatic single nucleotide variants, with good validation rates, from exome sequencing data of cancer samples. We also showed the advantage of combining standard algorithms to create the GATK-LODN method, that increased specificity and sensitivity of GATK results. This pipeline can be helpful in discovery studies aimed to profile the somatic mutational landscape of cancer genomes.

Background: Aneuploidy occurs in more than 20% of acute myeloid leukemia (AML) cases and correlates with an adverse prognosis. Methods: To understand the molecular bases of aneuploid acute myeloid leukemia (A‐AML), this study examined the genomic profile in 42 A‐AML cases and 35 euploid acute myeloid leukemia (E‐AML) cases. Results: A‐AML was characterized by increased genomic complexity based on exonic variants (an average of 26 somatic mutations per sample vs 15 for E‐AML). The integration of exome, copy number, and gene expression data revealed alterations in genes involved in DNA repair (eg, SLX4IP , RINT1 , HINT1 , and ATR ) and the cell cycle (eg, MCM2 , MCM4 , MCM5 , MCM7 , MCM8 , MCM10 , UBE2C , USP37 , CK2 , CK3 , CK4 , BUB1B , NUSAP1 , and E2F ) in A‐AML, which was associated with a 3‐gene signature defined by PLK1 and CDC20 upregulation and RAD50 downregulation and with structural or functional silencing of the p53 transcriptional program. Moreover, A‐AML was enriched for alterations in the protein ubiquitination and degradation pathway (eg, increased levels of UHRF1 and UBE2C and decreased UBA3 expression), response to reactive oxygen species, energy metabolism, and biosynthetic processes, which may help in facing the unbalanced protein load. E‐AML was associated with BCOR / BCORL1 mutations and HOX gene overexpression. Conclusions: These findings indicate that aneuploidy‐related and leukemia‐specific alterations cooperate to tolerate an abnormal chromosome number in AML, and they point to the mitotic and protein degradation machineries as potential therapeutic targets.

Somatic variants in TET2 and DNMT3A are founding mutations in hematological malignancies that affect the epigenetic regulation of DNA methylation. Mutations in both genes often co-occur with activating mutations in genes encoding oncogenic tyrosine kinases such as FLT3ITD, BCR-ABL1, JAK2V617F, and MPLW515L, or with mutations affecting related signaling pathways such as NRASG12D and CALRdel52. Here, we show that TET2 and DNMT3A mutations exert divergent roles in regulating DNA repair activities in leukemia cells expressing these oncogenes. Malignant TET2-deficient cells displayed downregulation of BRCA1 and LIG4, resulting in reduced activity of BRCA1/2-mediated homologous recombination (HR) and DNA-PK–mediated non-homologous end-joining (D-NHEJ), respectively. TET2-deficient cells relied on PARP1-mediated alternative NHEJ (Alt-NHEJ) for protection from the toxic effects of spontaneous and drug-induced DNA double-strand breaks. Conversely, DNMT3A-deficient cells favored HR/D-NHEJ owing to downregulation of PARP1 and reduction of Alt-NHEJ. Consequently, malignant TET2-deficient cells were sensitive to PARP inhibitor (PARPi) treatment in vitro and in vivo, whereas DNMT3A-deficient cells were resistant. Disruption of TET2 dioxygenase activity or TET2—Wilms' tumor 1 (WT1)–binding ability was responsible for DNA repair defects and sensitivity to PARPi associated with TET2 deficiency. Moreover, mutation or deletion of WT1 mimicked the effect of TET2 mutation on DSB repair activity and sensitivity to PARPi. Collectively, these findings reveal that TET2 and WT1 mutations may serve as biomarkers of synthetic lethality triggered by PARPi, which should be explored therapeutically. Significance: TET2 and DNMT3A mutations affect distinct DNA repair mechanisms and govern the differential sensitivities of oncogenic tyrosine kinase–positive malignant hematopoietic cells to PARP inhibitors.

Although targeting of cell metabolism is a promising therapeutic strategy in acute myeloid leukemia (AML), metabolic dependencies are largely unexplored. We aimed to classify AML patients based on their metabolic landscape and map connections between metabolic and genomic profiles. Combined serum and urine metabolomics improved AML characterization compared with individual biofluid analysis. At intracellular level, AML displayed dysregulated amino acid, nucleotide, lipid, and bioenergetic metabolism. The integration of intracellular and biofluid metabolomics provided a map of alterations in the metabolism of polyamine, purine, keton bodies and polyunsaturated fatty acids and tricarboxylic acid cycle. The intracellular metabolome distinguished three AML clusters, correlating with distinct genomic profiles: NPM1-mutated(mut), chromatin/spliceosome-mut and TP53-mut/aneuploid AML that were confirmed by biofluid analysis. Interestingly, integrated genomic-metabolic profiles defined two subgroups of NPM1-mut AML. One was enriched for mutations in cohesin/DNA damage-related genes (NPM1/cohesin-mut AML) and showed increased serum choline + trimethylamine-N-oxide and leucine, higher mutation load, transcriptomic signatures of reduced inflammatory status and better ex-vivo response to EGFR and MET inhibition. The transcriptional differences of enzyme-encoding genes between NPM1/cohesin-mut and NPM1-mut allowed in silico modeling of intracellular metabolic perturbations. This approach predicted alterations in NAD and purine metabolism in NPM1/cohesin-mut AML that suggest potential vulnerabilities, worthy of being therapeutically explored.