Researchers Report Promising Strategy to Develop Personalized Therapy for Neuroblastoma

New research shows promise for a strategy of genomic profiling and drug screening of patient-derived cell cultures to help “guide personalized therapy” for neuroblastoma and other mutationally quiet cancers.

Researchers, writing in Frontiers in Oncology, integrated genomic profiling and personalized preclinical tumor models to identify copy-number dependent drug susceptibilities in neuroblastoma. Using excess tumor tissue from pediatric patients with neuroblastoma undergoing surgery, researchers characterized single nucleotide and copy number variations, performed drug-response testing on patient-derived cell cultures, and investigated correlations between copy number and cytotoxicity of drug treatment.

The investigators noted that neuroblastoma is the most common pediatric extracranial malignant tumor, responsible for 15% of all deaths from cancer in children. The authors described neuroblastoma as a “mutationally quiet” cancer, with copy number variations (CNVs) more prevalent than single nucleotide variations (SNVs). They proposed that these CNVs “may reflect fundamental oncogenic dependencies that can be potentially exploited for cancer therapeutics.”

Matching the patient to a treatment in neuroblastoma is challenging, the authors wrote, because of the cancer’s “histologic and biologic heterogeneity,” and they suggested that “therapeutic advancements for neuroblastoma may be better realized with a personalized approach.” PDCs could be used as personalized models of the patient’s tumor to allow rapid testing of multiple agents ex vivo, the authors said.

Genomic profiling

Genomic profiling was carried out on tumor tissue from 13 patients with a median age of 2.65 (range 1.45-7.80) using ThermoFisher’s Oncomine Childhood Cancer Research Assay (OCCRA) DNA panel. As the investigators expected, the mean incidence of single nucleotide variants (SNVs) was “infrequent” at 3.1 per case, however they found “frequent and heterogenous copy number variations (CNVs).” Copy number losses the authors called characteristic of neuroblastoma were detected in chromosome arms 1p and 11q, along with copy number gains in 17q.

Ex vivo drug screening

Following genetic profiling, PDCs were screened using an established library of 418 kinase inhibitors. Overall, the authors noted the drug classes that resulted in the greatest cytotoxicity targeted cytoskeletal signaling, the cell cycle, angiogenesis, and the PI3K/Akt/mTOR signaling pathway.

Of the 418 compounds, 70 (16.7%) caused greater than 33% cytotoxicity and were therefore considered hits. The most common genes targeted by these 70 drugs included mTOR (24%), CDK (11%), FLT3 (7%), and JAK (7%). For example, the pan-CDK inhibitors flavopiridol and dinaciclib, which the authors mentioned are in early-phase trials for neuroblastoma and advanced solid tumors, were among the hits.

Correlations between cytotoxicity and copy number: novel gene-drug associations

The investigators hypothesized that the extent of copy number changes would correlate with drug cytotoxicity, and they found “susceptibility to PI3K and cell cycle agents was significantly associated with copy number gains of PI3K and STAT family genes, particularly on 17q.” They found significant correlations between copy number and cytotoxicity in 1278 gene-drug pairs, including 49 drugs that were considered hits. Only 4 of these were expected associations based on drug library specifications.

In the other 1274 gene-drug pairs, correlations were observed despite not being expected. The authors say this suggested “a substantial number of novel gene-drug associations,” and they next verified these associations against six public datasets of gene-drug interactions and an in silico model. Of the 1278 gene-drug pairs, 19 (1.5%) were verified in at least 1 public dataset, though only 1 of these pairs was a hit (JAK3 and AT9283).

The authors noted “the high incidence of hits among unverified top gene-drug pairs further suggested that important gene-drug relationships may exist among this group.”

Most common gene-drug associations

The strongest correlations between copy number and drug cytotoxicity were found in PPM1D, GNA13, and STAT family genes, which the authors noted are “all on 17q and implicated in up to 70% of neuroblastomas.” Also frequent were correlations between PI3K/Akt/mTOR pathway genes and their inhibitors. The authors noted these drugs accounted for half of the top 20 drug hits, and that upregulation of this pathway “occurs in 62% of neuroblastomas and is a promising therapeutic target.”

The authors acknowledged the small number of cases in their study as a limitation, which could “limit the robustness of the gene-drug correlations identified, and the inherent inability to test every drug hit in individual patients.”

Reference

Wong RLY, Wong MRE, Kuick CH, et al. integrated genomic profiling and drug screening of patient-derived cultures identifies individualized copy number-dependent susceptibilities involving PI3K pathway and 17q genes in neuroblastoma. Front Oncol. Published online October 14, 2021. doi: 10.3389/fonc.2021.709525.