Small cell lung carcinoma cell line screen of etoposide/carboplatin plus a third agent

Abstract

The SCLC combination screen examined a 9‐point concentration response of 180 third agents, alone and in combination with etoposide/carboplatin. The predominant effect of adding a third agent to etoposide/carboplatin was additivity. Less than additive effects occurred frequently in SCLC lines sensitive to etoposide/carboplatin. In SCLC lines with little or no response to etoposide/carboplatin, greater than additive SCLC killing occurred over the entire spectrum of SCLC lines but never occurred in all SCLC lines. Exposing SCLC lines to tubulin‐targeted agents (paclitaxel or vinorelbine) simultaneously with etoposide/carboplatin resulted primarily in less than additive cell killing. As single agents, nuclear kinase inhibitors including Aurora kinase inhibitors, Kinesin Spindle Protein/EG5 inhibitors, and Polo‐like kinase‐1 inhibitors were potent cytotoxic agents in SCLC lines; however, simultaneous exposure of the SCLC lines to these agents along with etoposide/carboplatin, generally, resulted in less than additive cell killing. Several classes of agents enhanced the cytotoxicity of etoposide/carboplatin toward the SCLC lines. Exposure of the SCLC lines to the MDM2 inhibitor JNJ‐27291199 produced enhanced killing in 80% of the SCLC lines. Chk‐1 inhibitors such as rabusertib increased the cytotoxicity of etoposide/carboplatin to the SCLC lines in an additive to greater than additive manner. The combination of GSK‐3β inhibitor LY‐2090314 with etoposide/carboplatin increased killing in approximately 40% of the SCLC lines. Exposure to the BET bromodomain inhibitor MK‐8628 increased the SCLC cell killing by etoposide/carboplatin in 20–25% of the SCLC lines. Only 10–15% of the SCLC lines had an increased response to etoposide/carboplatin when simultaneously exposed to the PARP inhibitor talazoparib.

Epigenome-wide DNA methylation analysis of small cell lung cancer cell lines suggests potential chemotherapy targets

“…We examined association of log(IC50) of these agents with methylation of individual probes and gene regions of 78 genes representing drug-specific targets and 48 additional genes involved in drug target pathways (Supplementary Table 2). In addition, we analyzed association of methylation of log(IC50) of each of the 44 agents with methylation of individual probes and gene regions of 159 proteincoding genes that included genes with relevance to SCLC lineage determination; SCLC lineage markers; genes that carry frequent mutations or genome alterations in SCLC; genes which are commonly inactivated, overexpressed, or epigenetically modified in SCLC tumors or in specific SCLC subtypes; as well as genes previously reported as being involved in pathways leading to SCLC pathogenesis; or those suggested as being relevant to SCLC response to chemotherapy [3,5,11,13,15,24,[34][35][36][37][38][39]. The list of these genes is provided in the legend to Supplementary Table 2.…”

“…For this purpose, we used gene expression and miRNA measurements generated and processed by an earlier study of our group [24], which generated transcript expression data using Affymetrix GeneChip®Human Exon 1.0 ST Arrays (NCBI GEO accession number GSE73160) and NanoString miRNA expression measurements (NCBI GEO accession GSE73161). Experimental and computational procedures for mRNA and miRNA data collection, processing, QC, data normalization, and adjustment for batch effects were reported previously [24,38]. We used mRNA expression measures normalized using Robust Multi-Array Average (RMA) and summarized at the whole transcript level using AROMA [40]; we also utilized miRNA data which were normalized and log 2 + 1 transformed [24].…”

“…Combinations of BET inhibitors with other agents in SCLC with increased ERBB2 expression may be a potential way to overcome drug resistance. Indeed, addition of the BET inhibitor MK-8628 increased the killing of SCLC lines in combination with etoposide or topotecan in a study of triple drug combinations [38]. Table 2 provides the list of gene regions associated with log(IC50) with p FDR < 0.1 at the epigenome-wide level (with Spearman |ρ| > 0.607).…”

“…TSS200 was significantly negatively associated with expression of the MDM2 transcript NM_002392 (cluster ID 3421300, r = − 0.4269, p = 0.0004), which was correlated with sensitivity to both Bcl-2 inhibitors (ρ = − 0.4017, p = 0.0008 for ABT-263 and r = − 0.3867, p = 0.0012 for ABT-737). While MDM2 inhibitors alone were not effective in the in vitro screens of SCLC cell lines [24,38] and TP53 is nearly universally inactivated in SCLC [3,5], surprisingly, the combination of the MDM2 inhibitor JNJ-27291199 with etoposide and carboplatin resulted in enhanced cytotoxicity against SCLC cell lines [38]. Methylation of the TSS1500 of IGFBP5, which encodes an endogenous IGF1R inhibitor and is expressed at low levels in the POU2F3-regulated tuft cell-like SCLC subtype and at high levels in the subtype with high ASCL1 expression [12,13], was associated with resistance to the mTOR inhibitor INK-128 (sapanisertib; ρ = 0.5107, p FDR = 0.0896; Table 4).…”

Molecular genomic features associated with in vitro response of the NCI‐60 cancer cell line panel to natural products

“…to multiple categories of DNA-damaging antitumor agents including topoisomerase I and II inhibitors, PARP inhibitors, and platinum compounds in a variety of cancers[54][55][56][57][58][59][60][61][62].Figure S3shows the midpoint rooted hierarchical clustering [44] of 1302 natural products based on their log(GI50) values across the NCI-60 cell lines. Those compounds for which the sensitivity was significantly correlated with SLFN11 expression (FDR adjusted P < 0.05) are highlighted in yellow.…”