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Dynamics of multiple resistance mechanisms in plasma DNA and their clinical implications for NSCLC patients receiving EGFR-targeted therapies

ABSTRACT: Background:The development of resistance mechanisms to targeted therapies is complicated by underlying tumour heterogeneity. When multiple resistance mechanisms co-exist, identifying the dominant driver(s) is critical for selection of treatment. Patients and methods:We studied the relative dynamics of multiple oncogenic drivers and resistance mechanisms in 50 patients with EGFR-mutant non-small cell lung cancer (NSCLC), during treatment with gefitinib and hydroxychloroquine (NCT00809237). We performed digital PCR and targeted deep sequencing of cell-free DNA from longitudinal plasma samples from all patients, and shallow whole genome sequencing of serial samples from three patients who underwent histological transformation to small-cell lung cancer (SCLC). ResultsEGFR activating mutations were assessed in tumour samples and accurately identified in plasma samples of 95% of patients (41/43). We identified additional mutations including EGFR T790M (31/50, 62%), TP53 (23/50, 46%), PIK3CA (7/50, 14%), and PTEN (4/50, 8%), and tracked their relative levels in plasma. Patients with both TP53 and EGFR mutations detected in plasma pre-treatment tended to have worse overall survival than those where only EGFR was detected. The resistance-conferring EGFR T790M mutation was identified in 62% of the patients who progressed. Changes in relative levels of T790M and activating mutations in EGFR corresponded to clinical responses in two patients who were given sequential treatments. Patients who progressed without T790M detected in plasma had worse PFS during TKI continuation, and developed alternative resistance mechanisms, that could be identified in plasma DNA, including SCLC-associated copy number changes and TP53 mutations, that tracked with progression and response to subsequent therapies. Conclusion:Longitudinal analysis of multiple oncogenic drivers in ctDNA may help identifying dominant mechanisms of resistance to EGFR-targeted therapies, and highlight the importance of monitoring genetic events that are not direct drug targets but provide non-invasive molecular information that may guide clinical management.

PROVIDER: EGAS00001002908 | EGA |

REPOSITORIES: EGA

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Project description:Lung cancer continues to be the leading cause of cancer mortality worldwide. The treatment of lung cancer patients harboring mutant EGFR with orally administered EGFR TKIs has been a paradigm shift. Osimertinib and rociletinib are two 3rd generation irreversible EGFR TKIs targeting the EGFR T790M mutation. Osimertinib is the current standard care for patients with EGFR mutations due to increased efficacy, lower side effects, and enhanced brain penetrance. Unfortunately, all patients develop resistance to it. Genomic approaches have primarily been used to interrogate resistance mechanisms. Here, we have characterized the proteome and phosphoproteome of a series of isogenic EGFR mutant lung adenocarcinoma cell lines that are either sensitive or resistant to these drugs. To our knowledge, this is the most comprehensive proteomic dataset resource to date to investigate 3rd generation EGFR TKI resistance in lung adenocarcinoma. We have interrogated this unbiased global quantitative proteomic and phosphoproteomic dataset to uncover alterations in signaling pathways, and to reveal a proteomic signature of EMT and kinases / phosphatases with altered protein expression and phosphorylation in the TKI resistant cells. We validated the significant role of SHP2 in the activation of RAS/MAPK and PI3K/AKT signaling pathways. Furthermore, we performed anticorrelation analyses of this phosphoproteomic dataset with the published drug-induced P100 phosphoproteomic datasets from the Library of Integrated Network-Based Cellular Signatures (LINCS) program to predict drugs with the potential to overcome EGFR TKI resistance. We identified that dactolisib, a PI3K/mTOR inhibitor, in combination with osimertinib, may overcome osimertinib resistance both in vitro and in vivo. Introduction Lung cancer continues to be the leading cause of cancer mortality in the world (1). Many lung adenocarcinoma patients with activating epidermal growth factor receptor (EGFR) mutations initially respond dramaticlly to the first- or second-generation EGFR tyrosine kinase inhibitors (TKIs). However, they eventually develop resistance. The most common mechanism of acquired resistance is the EGFR T790M gatekeeper site residue mutation (2). Osimertinib, a third generation irreversible EGFR TKI has been approved by the FDA to treat patients harboring the EGFR T790M mutation who have developed resistance to first- and second- generation EGFR TKIs (3). Recently, osimertinib was also approved for the front-line treatment of patients harboring EGFR mutations (4). Rociletinib is another irreversible inhibitor targeting the EGFR T790M mutation, which has minimal activity against wild-type EGFR. Both drugs have therapeutic benefits and have demonstrated activity in tumors with T790M-mediated resistance to other EGFR tyrosine kinase inhibitors (5, 6). Further development of rociletinib was ceased in 2016 due to less than expected efficacy, poor brain penetration leading to tumor progression in brain tissues and off-target effects on IGFR activation leading to hyperglycemia (7, 8). Although 3rd-generation TKIs provide clinical benefit to most patients with EGFR mutations, some patients, demonstrating primary resistance, still do not respond to these inhibitors. Complete responses are rare, and all patients eventually develop resistance, suggesting primary and acquired resistance mechanisms decrease the efficacy of the drugs (9, 10). Genomic approaches have been used primarily to interrogate osimertinib resistance mechanisms (9, 11-15). Several mechanisms of osimertinib resistance have been identified (16), including novel second site EGFR mutations, activated bypass pathways such as MET amplification, HER2 amplification, RAS mutations, BRAF mutations, PIK3CA mutations, and novel fusion events (17). However, the resistance mechanism is complex and still not fully understood. Previously, we have used SILAC-based quantitative phosphoproteomics to identify the global dynamic modification which occur upon treatment of TKI-sensitive and -resistant lung adenocarcinoma cells with the 1st and 2nd generation EGFR TKIs, erlotinib and afatinib. Utilizing this strategy, we identified the targets of mutant EGFR signaling pathways responsible for TKI resistance, and possible off-target effects of the drugs (18, 19). In this study, we employed SILAC-based quantitative mass spectrometry to characterize alterations in the proteome and phosphoproteome which occur upon acquired resistance and sought to identify novel mechanisms of resistance to the third generation EGFR TKIs, osimertinib and rociletinib. To our knowledge, this is the most comprehensive 3rd generation EGFR TKI resistant proteome and phosphoproteome analysis resource available to date.

Project description:Background: Although TP53 gain-of-function (GOF) mutations promote cancer survival, its effect on EGFR-TKI efficacy remains unclear. We established EGFR-mutant lung cancer cell lines expressing various TP53 genotypes using CRISPR-Cas9 technology and found that TP53-GOF mutant cells develop an early resistance to EGFR-TKI osimertinib.The goal of this study is to elucidate the mechanisms underlying resistance to osimertinib treatment in TP53 GOF mutations through comprehensive gene analysis using RNA-seq with next-generation sequencing (NGS). Methods: Total RNA was isolated from PC-9 cells overexpressing TP53 R248Q mutation (PC9/p53R248Q: TP53 GOF mutation) and PC-9 cells overexpressing empty vector plasmid (PC9/p53EV: TP53 null) treated with DMSO or osimertinib for 24hours, using the RNeasy Micro Kit , in accordance with the manufacturer’s instructions. RNA samples were quantified by NanoDrop-2000 spectrophotometer, and the quality was confirmed with a 2200 TapeStation. rRNA was removed using MGI Easy rRNA Depletion Kit according to manufacturer's instructions followed by library construction using MGIEasy RNA Directional Library Prep Set (MGI). MGI DNBseq-G400 FAST was used to perform the amplicons deep sequencing following the standard operation protocol. The sequence format was 150bp pair read for all samples. All sequencing reads were trimmed low-quality bases and adapters with Trimmomatic (v.0.38) , and RNA sequencing reads were mapped to hg38 using HISAT2 software . Raw counts for each gene were estimated in each sample using RSEM version 1.3.0 and Bowtie 2. Calculation of the log fold-change (log FC) and p-value were performed using edgeR. Results: We explored the functions of specifically upregulated genes in TP53 GOF mutation after osimertinib treatment by KEGG pathway-enrichment analysis and found that the cytokine-cytokine receptor interaction was the most significantly altered pathway. Hallmark pathway analysis identified the TNF-α/NF-κB pathway was significantly enriched. Furthermore, TRRUST analysis showed enhanced activity of transcription factors especially RELA (p65) and NF-kB1. Conclusions: TP53 GOF mutaion induces osimertinib resistance by activating TNF-α/NF-κB pathway.

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Dynamics of multiple resistance mechanisms in plasma DNA and their clinical implications for NSCLC patients receiving EGFR-targeted therapies

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