SUMMARY Reprogrammed metabolism and cell cycle dysregulation are two cancer hallmarks. p16 is a cell cycle inhibitor and tumor suppressor that is upregulated during oncogene-induced senescence (OIS). Loss of p16 allows for uninhibited cell cycle progression, bypass of OIS, and tumorigenesis. Whether p16 loss affects pro-tumorigenic metabolism is unclear. We report that suppression of p16 plays a central role in reprogramming metabolism by increasing nucleotide synthesis. This occurs by activation of mTORC1 signaling, which directly mediates increased translation of the mRNA encoding ribose-5-phosphate isomerase A ( RPIA ), a pentose phosphate pathway enzyme. p16 loss correlates with activation of the mTORC1-RPIA axis in multiple cancer types. Suppression of RPIA inhibits proliferation only in p16-low cells by inducing senescence both in vitro and in vivo . These data reveal the molecular basis whereby p16 loss modulates pro-tumorigenic metabolism through mTORC1-mediated upregulation of nucleotide synthesis and reveals a metabolic vulnerability of p16-null cancer cells.

2 SummaryReprogrammed metabolism and cell cycle dysregulation are two cancer hallmarks. p16 is a cell cycle inhibitor and tumor suppressor that is upregulated during oncogeneinduced senescence (OIS). Loss of p16 allows for uninhibited cell cycle progression, bypass of OIS, and tumorigenesis. Whether p16 loss affects pro-tumorigenic metabolism is unclear. We report that suppression of p16 plays a central role in

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Study Design. A case-control genome-wide association study (GWAS) on spondylosis. Objective. Leveraging Geisinger's MyCode initiative's multimodal dataset, we aimed to identify genetic associations with degenerative spine disease. Summary of Background Data. Degenerative spine conditions are a leading cause of global disability; however, the genetic underpinnings of these conditions remain under-investigated. Previous studies using candidate-gene approach suggest a genetic risk for degenerative spine conditions, but large-scale GWASs are lacking. Methods. We identified 4434 patients with a diagnosis of spondylosis using ICD diagnosis codes with genotype data available. We identified a population-based control of 12,522 patients who did not have any diagnosis for osteoarthritis. A linear-mix, additive genetic model was employed to perform the genetic association tests adjusting for age, sex, and genetic principal components to account for the population structure and relatedness. Gene-based association tests were performed and heritability and genetic correlations with other traits were investigated.Results. We identified a genome-wide significant locus at rs12190551 (odds ratio ¼ 1.034, 95% confidence interval 1.022-1.046, P ¼ 8.5 Â 10 -9 , minor allele frequency ¼ 36.9%) located in the intron of BMP6. Additionally, NIPAL1 and CNGA1 achieved Bonferroni significance in the gene-based association tests. The estimated heritability was 7.19%. Furthermore, significant genetic correlations with pain, depression, lumbar spine bone mineral density, and osteoarthritis were identified. Conclusion. We demonstrated the use of a massive database of genotypes combined with electronic health record data to identify a novel and significant association spondylosis. We also identified significant genetic correlations with pain, depression, bone mineral density, and osteoarthritis, suggesting shared genetic etiology and molecular pathways with these phenotypes.

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