Inactivating CUX1 mutations promote tumorigenesis

Abstract

A major challenge for cancer genetics is to determine which low frequency somatic mutations are drivers of tumorigenesis. Here we interrogate the genomes of 7,651 diverse human cancers to identify novel drivers and find inactivating mutations in the homeodomain transcription factor CUX1 (cut-like homeobox 1) in ~1-5% of tumors. Meta-analysis of CUX1 mutational status in 2,519 cases of myeloid malignancies reveals disruptive mutations associated with poor survival, highlighting the clinical significance of CUX1 loss. In parallel, we validate CUX1 as a bona fide tumor suppressor using mouse transposon-mediated insertional mutagenesis and Drosophila cancer models. We demonstrate that CUX1 deficiency activates phosphoinositide 3-kinase (PI3K) signaling through direct transcriptional downregulation of the PI3K inhibitor PIK3IP1 (phosphoinositide-3-kinase interacting protein 1), leading to increased tumor growth, while exposing susceptibility to PI3K-AKT inhibition. Thus, our complementary approaches identify CUX1 as a new pan-driver of tumorigenesis and uncover a potential strategy for treating CUX1-mutant tumors.

Newly emerged isolated Del(7q) in patients with prior cytotoxic therapies may not always be associated with therapy-related myeloid neoplasms

“…24 CUX1, located on 7q22, was expressed in haploinsufficient level in patients with myeloid malignancies involving del(7q), 11 and the decreased expression of CUX1 contributed to tumorigenesis by activating the PI3K/Akt/mTOT pathway. 25 MLL3, located on 7q36.1, might also be involved in the pathogenesis of myeloid malignancy; a 50% knockdown of MLL3 in murine lead to the development of myelodysplasia and leukemia. 26 EZH2, located on 7q36.1, has been shown to be mutated in myeloid malignancies and portends high-risk disease.…”

“…Of the remaining 27 patients, blasts were not increased and criteria for therapy-related myeloid neoplasms were not met in the diagnostic bone marrow sample at the time of del(7q) identification. This group included 10 patients (cases [13][14][15][19][20][21][22][23][24][25] with mild dysplasia, 16 patients (cases 16-18, 26-38) who did not have dysplasia and 1 patient in whom morphological assessment was difficult due to significant involvement by lymphoma (case 39) (Figure 1).…”

“…Seven patients (cases 25,26,29,30,[32][33][34] had no indication for myeloid neoplasms and no follow-up bone marrow evaluation was done; eight patients (cases 20, 21, 24, 27, 28, 31, 35, 36) had undetectable del(7q) in the follow-up bone marrow and no indication for a secondary myeloid neoplasm; patient 19 was suspected to have a therapy-related myelodysplastic syndrome and died 4 months later but no follow-up bone marrow was performed; patient 39 had del(7q) detected intermittently in 5-10% metaphases, and no indication for a myeloid neoplasm. By the end of follow-up, 6 patients died of their primary cancer or complications, 13 were alive with no evidence of primary cancer or therapy-related myeloid neoplasms, 1 was alive with primary cancer and 1 was lost to follow-up (Table 1).…”

Universal patterns of selection in cancer and somatic tissues

“…Fourthly, to detect selection at the level of individual genes reliably, and particularly for driver gene discovery, we refined dN/dS to consider the variation of the mutation rate along the human genome. A simple way to do so is estimating a separate mutation rate for every gene (Wong et al, 2014), but this approach has poor statistical efficiency with current sample sizes. Instead, we developed a statistical model (dNdScv) that combines the local observed synonymous mutation rate with a regression model using covariates that predict the variable mutation rate across the genome (Lawrence et al, 2013;Polak et al, 2015;Schuster-Bockler and Lehner, 2012) (Supplementary Methods S1.3 and Supplementary Text S9).…”

“…Although both the variable rate dN/dS model (which we used in (Wong et al, 2014)) and dNdScv have good specificity under challenging conditions, they differ dramatically in terms of their sensitivity. This is shown in Fig.…”