Autophagy-related gene 12 (ATG12) is a novel determinant of primary resistance to HER2-targeted therapies: utility of transcriptome analysis of the autophagy interactome to guide breast cancer treatment

Abstract

The autophagic process, which can facilitate breast cancer resistance to endocrine, cytotoxic, and molecularly targeted agents, is mainly regulated at the post-translational level. Although recent studies have suggested a possible transcriptome regulation of the autophagic genes, little is known about either the analysis tools that can be applied or the functional importance of putative candidate genes emerging from autophagy-dedicated transcriptome studies. In this context, we evaluated whether the constitutive activation of the autophagy machinery, as revealed by a transcriptome analysis using an autophagy-focused polymerase chain reaction (PCR) array, might allow for the identification of novel autophagy-specific biomarkers for intrinsic (primary) resistance to HER2-targeted therapies. Quantitative real-time PCR (qRT-PCR)-based profiling of 84 genes involved in autophagy revealed that, when compared to trastuzumab-sensitive SKBR3 cells, the positive regulator of autophagic vesicle formation ATG12 (autophagy-related gene 12) was the most differentially up-regulated gene in JIMT1 cells, a model of intrinsic cross-resistance to trastuzumab and other HER1/2-targeting drugs. An analysis of the transcriptional status of ATG12 in > 50 breast cancer cell lines suggested that the ATG12 transcript is commonly upregulated in trastuzumab-unresponsive HER2-overexpressing breast cancer cells. A lentiviral-delivered small hairpin RNA stable knockdown of the ATG12 gene fully suppressed the refractoriness of JIMT1 cells to trastuzumab, erlotinib, gefitinib, and lapatinib in vitro. ATG12 silencing significantly reduced JIMT1 tumor growth induced by subcutaneous injection in nude mice. Remarkably, the outgrowth of trastuzumab-unresponsive tumors was prevented completely when trastuzumab treatment was administered in an ATG12-silenced genetic background. We demonstrate for the first time the usefulness of low-density, autophagy-dedicated qRT-PCR-based platforms for monitoring primary resistance to HER2-targeted therapies by transcriptionally screening the autophagy interactome. The degree of predictive accuracy warrants further investigation in the clinical situation.

Figure 1. Analysis of autophagy genes in trastuzumab-refractory breast cancer cells

Left. Total RNA from trastuzumab-sensitive SKBR3 and trastuzumab-refractory JIMT-1 cells was characterized in technical triplicates using the Autophagy RT² Profiler PCR Array as per the manufacturer's instructions (SABiosciences; http://www.sabiosciences.com/rt_pcr_product/HTML/PAHS-084A.html). Representative scatter plots of the difference (≥ 2-fold; green and red symbols indicate downregulation and upregulation vs. expression levels in SKBR3 cells, respectively) in relative transcript abundance of 84 key genes involved in autophagy are shown. Grey symbols denote the fold-change results to be validated with a sufficient number of biological replicates [i.e., fold-change results may have greater variations if the p-value > 0.05, or the p-value for the fold-change is either unavailable or relatively high (p > 0.05)] or that are uninterpretable because the gene's average threshold cycles were either not determined or were greater than the defined cut-off value (default 35) in both samples. Total. The transcript abundance of selected autophagy-related genes were calculated using the delta Ct method and presented as fold-change vs. basal expression in trastuzumab-sensitive SKBR3 cells.

Figure 2. Differential expression of ATG12 in trastuzumab-responsive and trastuzumab-resistant breast cancer cell lines

Distribution of ATG12 gene expression in trastuzumab-responsive and trastuzumab-resistant breast cancer cell lines across the Adai data set (top) and the Neve's data set (bottom).

Figure 3. Impact of shRNA-driven genetic ablation of ATG12 on the efficacy of the anti-HER2 monoclonal antibody trastuzumab (Herceptin) in vitro

The metabolic status of JIMT1 parental cells, control shRNA-JIMT1 cells, and ATG12 shRNA-JIMT1 cells treated with graded concentrations trastuzumab was evaluated using MTT-based cell viability assays, followed by the generation of dose-response graphs depicting the % of untreated cells (untreated control cells = 100% cell viability). The results are presented as the means (columns) and 95% confidence intervals (bars) of three independent experiments performed in triplicate. [n.s. not significant; * P < 0.05]

Figure 4. Impact of shRNA-driven genetic ablation of ATG12 on the efficacy of HER1/2-tyrosine kinase inhibitors in vitro

Left panels. The metabolic status of JIMT1 parental cells, control shRNA-JIMT1 cells, and ATG12 shRNA-JIMT1 cells treated with graded concentrations of erlotinib, gefitinib, and lapatinib was evaluated using MTT-based cell viability assays, followed by the generation of dose-response graphs depicting the % of untreated cells (untreated control cells = 100% cell viability). The results are presented as the means (columns) and 95% confidence intervals (bars) of three independent experiments performed in triplicate. Right panels. The degree of sensitivity of JIMT1 parental cells, control shRNA-JIMT1 cells, and ATG12 shRNA-JIMT1 cells to HER1/2-targeting drugs is illustrated by bars representing mean IC₅₀ values in each cell line. Error bars show standard deviations. [n.s. not significant; ** P < 0.005]

Figure 5. Impact of shRNA-driven genetic ablation of ATG12 on the efficacy of trastuzumab in vivo

Shown are the mean tumor volumes (±SD) in JIMT1 and ATG12 shRNA-JIMT1 xenograft-bearing nude mice following injection with trastuzumab (5 mg/kg/week) for nine weeks. Data from control shRNA-JIMT1 cells were superimposable with those obtained in JIMT1 parental cells and have been omitted for simplicity.