ediatric cancer is rare, with fewer than 10,000 solid tumors diagnosed in children annually in the United States 1. Previous studies interrogating germline predisposition broadly across pediatric cancer types have found heritable germline predisposition in 8-12% of patients. The yield of germline predisposition detected is dependent on the genes included for analysis and variant interpretation as well as the ascertainment biases found in each cohort. Iterative data are required to expand upon the understanding of susceptibility to pediatric cancer and determine the extent to which germline data may translate into clinical practice 2-7. Certain pediatric cancer diagnoses have well-established associations with germline mutations in specific genes and should automatically prompt clinical suspicion of a cancer predisposition, for example, retinoblastoma (RB1), pleuropulmonary blastoma (DICER1), optic pathway glioma (NF1), atypical teratoid/rhabdoid tumors (SMARCB1), small cell hypercalcemic ovarian tumors (SMARCA4), adrenal cortical tumors (TP53) and hypodiploid acute lymphoblastic leukemia (TP53) 8-10. Germline testing can also be critical for distinguishing between conditions like neurofibromatosis type 1 (NF1) and constitutional mismatch repair deficiency (CMMRD), which can be phenocopies of each other. For example, a child presenting with numerous café au lait spots and leukemia may have either of these conditions, but treatment and screening recommendations for the proband and family members will differ depending on the germline diagnosis 11. Besides the known associations of causal germline mutations, broad tumor-normal sequencing has revealed novel associations 9,12. While some of these findings likely represent population detection and do not play a role in the pathogenesis of the cancer in question 13 , other novel associations are likely causal. Population detection

The proteasome cleaves intracellular proteins into peptides. Earlier studies found that treatment of human embryonic kidney 293T (HEK293T) cells with epoxomicin (an irreversible proteasome inhibitor) generally caused a decrease in levels of intracellular peptides. However, bortezomib (an antitumor drug and proteasome inhibitor) caused an unexpected increase in the levels of most intracellular peptides in HEK293T and SH-SY5Y cells. To address this apparent paradox, quantitative peptidomics was used to study the effect of a variety of other proteasome inhibitors on peptide levels in HEK293T and SH-SY5Y cells. Inhibitors tested included carfilzomib, MG132, MG262, MLN2238, AM114, and clasto-Lactacystin β-lactone. Only MG262 caused a substantial elevation in peptide levels that was comparable to the effect of bortezomib, although carfilzomib and MLN2238 elevated the levels of some peptides. To explore off-target effects, the proteosome inhibitors were tested with various cellular peptidases. Bortezomib did not inhibit tripeptidyl peptidase 2 and only weakly inhibited cellular aminopeptidase activity, as did some of the other proteasome inhibitors. However, potent inhibitors of tripeptidyl peptidase 2 (butabindide) and cellular aminopeptidases (bestatin) did not substantially alter the peptidome, indicating that the increase in peptide levels due to proteasome inhibitors is not a result of peptidase inhibition. Although we cannot exclude other possibilities, we presume that the paradoxical increase in peptide levels upon treatment with bortezomib and other inhibitors is the result of allosteric effects of these compounds on the proteasome. Because intracellular peptides are likely to be functional, it is possible that some of the physiologic effects of bortezomib and carfilzomib arise from the perturbation of peptide levels inside the cell.

Peptides function as signaling molecules in species as diverse as humans and yeast. Mass spectrometry-based peptidomics techniques provide a relatively unbiased method to assess the peptidome of biological samples. In the present study, we used a quantitative peptidomic technique to characterize the peptidome of the yeast Saccharomyces cerevisiae and compare it to the peptidomes of mammalian cell lines and tissues. Altogether, 297 yeast peptides derived from 75 proteins were identified. The yeast peptides are similar to those of the human peptidome in average size and amino acid composition. Inhibition of proteasome activity with either bortezomib or epoxomicin led to decreased levels of some yeast peptides, suggesting that these peptides are generated by the proteasome. Approximately 30% of the yeast peptides correspond to the N- or C-terminus of the protein; the human peptidome is also highly represented in N- or C-terminal protein fragments. Most yeast and humans peptides are derived from a subset of abundant proteins, many with functions involving cellular metabolism or protein synthesis and folding. Of the 75 yeast proteins that give rise to peptides, 24 have orthologs that give rise to human and/or mouse peptides and for some, the same region of the proteins are found in the human, mouse, and yeast peptidomes. Taken together, these results support the hypothesis that intracellular peptides may have specific and conserved biological functions.

Background: Blm10 binds to the proteasome core particle and stimulates its proteolytic activity. Results: Loss of BLM10 results in impaired respiration, elevated oxidative stress sensitivity, increased mitochondrial fission, and stabilization of the fission protein Dnm1. Conclusion: Blm10 proteasome-mediated Dnm1 degradation is a regulatory mechanism to maintain correct mitochondrial function. Significance: Blm10 is involved in mitochondrial quality control under oxidative stress.

Elevated proteasome activity extends lifespan in model organisms such as yeast, worms and flies. This pro-longevity effect might be mediated by improved protein homeostasis, as this protease is an integral module of the protein homeostasis network. Proteasomes also regulate cellular processes through temporal and spatial degradation of signaling pathway components. Here we demonstrate that the regulatory function of the proteasome plays an essential role in aging cells and that the beneficial impact of elevated proteasome capacity on lifespan partially originates from deregulation of the AMPK signaling pathway. Proteasome-mediated lifespan extension activity was carbon-source dependent and cells with enhancement proteasome function exhibited increased respiratory activity and oxidative stress response. These findings suggested that the pro-aging impact of proteasome upregulation might be related to changes in the metabolic state through a premature induction of respiration. Deletion of yeast AMPK, SNF1, or its activator SNF4 abrogated proteasome-mediated lifespan extension, supporting this hypothesis as the AMPK pathway regulates metabolism. We found that the premature induction of respiration in cells with increased proteasome activity originates from enhanced turnover of Mig1, an AMPK/Snf1 regulated transcriptional repressor that prevents the induction of genes required for respiration. Increasing proteasome activity also resulted in partial relocation of Mig1 from the nucleus to the mitochondria. Collectively, the results argue for a model in which elevated proteasome activity leads to the uncoupling of Snf1-mediated Mig1 regulation, resulting in a premature activation of respiration and thus the induction of a mitohormetic response, beneficial to lifespan. In addition, we observed incorrect Mig1 localization in two other long-lived yeast aging models: cells that overexpress SIR2 or deleted for the Mig1-regulator HXK2. Finally, compromised proteasome function blocks lifespan extension in both strains. Thus, our findings suggest that proteasomes, Sir2, Snf1 and Hxk2 form an interconnected aging network that controls metabolism through coordinated regulation of Mig1.