Integrated Genomic Profiling and Drug Screening of Patient-Derived Cultures Identifies Individualized Copy Number-Dependent Susceptibilities Involving PI3K Pathway and 17q Genes in Neuroblastoma

Abstract

Neuroblastoma is the commonest extracranial pediatric malignancy. With few recurrent single nucleotide variations (SNVs), mutation-based precision oncology approaches have limited utility, but its frequent and heterogenous copy number variations (CNVs) could represent genomic dependencies that may be exploited for personalized therapy. Patient-derived cell culture (PDC) models can facilitate rapid testing of multiple agents to determine such individualized drug-responses. Thus, to study the relationship between individual genomic aberrations and therapeutic susceptibilities, we integrated comprehensive genomic profiling of neuroblastoma tumors with drug screening of corresponding PDCs against 418 targeted inhibitors. We quantified the strength of association between copy number and cytotoxicity, and validated significantly correlated gene-drug pairs in public data and using machine learning models. Somatic mutations were infrequent (3.1 per case), but copy number losses in 1p (31%) and 11q (38%), and gains in 17q (69%) were prevalent. Critically, in-vitro cytotoxicity significantly correlated only with CNVs, but not SNVs. Among 1278 significantly correlated gene-drug pairs, copy number of GNA13 and DNA damage response genes CBL, DNMT3A, and PPM1D were most significantly correlated with cytotoxicity; the drugs most commonly associated with these genes were PI3K/mTOR inhibitor PIK-75, and CDK inhibitors P276-00, SNS-032, AT7519, flavopiridol and dinaciclib. Predictive Markov random field models constructed from CNVs alone recapitulated the true z-score-weighted associations, with the strongest gene-drug functional interactions in subnetworks involving PI3K and JAK-STAT pathways. Together, our data defined individualized dose-dependent relationships between copy number gains of PI3K and STAT family genes particularly on 17q and susceptibility to PI3K and cell cycle agents in neuroblastoma. Integration of genomic profiling and drug screening of patient-derived models of neuroblastoma can quantitatively define copy number-dependent sensitivities to targeted inhibitors, which can guide personalized therapy for such mutationally quiet cancers.

17q Gain in Neuroblastoma: A Review of Clinical and Biological Implications

“…The study by Schleiermacher et al reported that 17q gain, along with 1p deletion and MYCN amplification, resulted in an exchange of genetic material that was replicated early in the cell cycle's S-phase [35]. Wong et al demonstrated dose-dependent relationships between the copy number gains of PI3K and STAT family genes on 17q and the susceptibility of NB to cell cycle and PI3K inhibitors [110]. 17q gain's importance in NB development was also demonstrated using animal models.…”

Insights into the Clinical, Biological and Therapeutic Impact of Copy Number Alteration in Cancer

“…They also showed that the combination of seven markers can differentiate patients with localised and advanced stages of prostate cancer. Another important aspect of screening CNAs in cancer patient samples is the potential to identify if CNAs infer sensitivity or cytotoxicity to therapeutic agents, as recently shown in melanoma and neuroblastoma [96,97]. Wong et al correlated the gain of PPM1D/GNA13 genes or loss of CBL/DNMT3A genes with enhanced cytotoxicity, whilst gains of PI3K or STAT family genes sensitise neuroblastoma cells to cell cycle inhibitors [97].…”

“…Another important aspect of screening CNAs in cancer patient samples is the potential to identify if CNAs infer sensitivity or cytotoxicity to therapeutic agents, as recently shown in melanoma and neuroblastoma [96,97]. Wong et al correlated the gain of PPM1D/GNA13 genes or loss of CBL/DNMT3A genes with enhanced cytotoxicity, whilst gains of PI3K or STAT family genes sensitise neuroblastoma cells to cell cycle inhibitors [97]. Moreover, using the cancer proteome atlas, a predictive link between CNAs and phosphorylation changes has been discovered, providing a new potential readout to assess sensitivity to kinase inhibition in cancer [98].…”