Gene mutations in primary tumors and corresponding patient-derived xenografts derived from non-small cell lung cancer

Highlights

• 23 PDXs from lung cancer and their primary tumors were sequenced by exome sequencing analysis on 202 cancer-related genes.

• Numbers of primary tumors with mutations in TP53, KRAS, PI3KCA, ALK, STK11, and EGFR were 10, 5, 4, 4, 3, and 2, respectively.

• Other genes with mutations in ≥3 tumors were MLL3, SETD2, ATM, ARID1A, CRIPAK, HGF, BAI3, EP300, KDR, PDGRRA and RUNX1.

• 93% of mutations detected in the primary tumors were also detected in their corresponding PDXs.

• Some mutations had higher allele frequencies in the PDXs than in the primary tumors, suggesting tumor cell enrichment in PDXs.

Abstract

Molecular annotated patient-derived xenograft (PDX) models are useful for the preclinical investigation of anticancer drugs and individualized anticancer therapy. We established 23 PDXs from 88 surgical specimens of lung cancer patients and determined gene mutations in these PDXs and their paired primary tumors by ultradeep exome sequencing on 202 cancer-related genes. The numbers of primary tumors with deleterious mutations in TP53, KRAS, PI3KCA, ALK, STK11, and EGFR were 43.5%, 21.7%, 17.4%, 17.4%, 13.0%, and 8.7%, respectively. Other genes with deleterious mutations in ≥3 (13.0%) primary tumors were MLL3, SETD2, ATM, ARID1A, CRIPAK, HGF, BAI3, EP300, KDR, PDGRRA and RUNX1. Of 315 mutations detected in the primary tumors, 293 (93%) were also detected in their corresponding PDXs, indicating that PDXs have the capacity to recapitulate the mutations in primary tumors. Nevertheless, a substantial number of mutations had higher allele frequencies in the PDXs than in the primary tumors, or were not detectable in the primary tumor, suggesting the possibility of tumor cell enrichment in PDXs or heterogeneity in the primary tumors. The molecularly annotated PDXs generated from this study could be useful for future translational studies.

Introduction

Lung cancer is the leading cause of cancer-related deaths both in the United States and worldwide, with an annual global incidence of about 1.6 million and mortality of 1.4–1.5 million [1], [2], [3]. Recent advances in genomic profiling have led to the identification of a number of frequently mutated genes in lung cancer [4], [5], [6], [7]. Lung cancers with the same histological diagnosis and clinical stages can be classified into molecular subgroups based on gene mutations. Substantial efforts have been made to develop genotype-specific anticancer therapeutics. The finding that lung cancer cells with mutations in the epidermal growth factor receptor gene (EGFR) are highly susceptible to the EGFR inhibitors gefitinib [8], [9], [10], erlotinib [8], [11] and afatinib has made these agents the first choice for treating EGFR mutant lung cancer. Both gefitinib and erlotinib have been reported to significantly prolong progression-free survival in patients with EGFR-mutant lung cancer [12], [13]. Similarly, small molecular inhibitors for anaplastic lymphoma kinase (ALK) and ROS1 have been proven to be highly effective for treatment of lung cancers with ALK and ROS1 gene translocations [14], [15], [16]. However, despite the excitement accompanying the targeted therapeutics, only a subset of patients with the aberration respond and responses are often unfortunately brief. Furthermore, our knowledge of genetic alterations, their functional consequences and combinatorial effects in lung cancer is still not comprehensive. For most potential driver mutations identified in lung cancer, there are no effective therapeutic agents available. The success of the EGFR inhibitors underscores the urgency of developing effective genotype-specific anticancer therapeutics.

Anticancer drug development is often impeded by a lack of preclinical tumor models that are highly predictive of therapeutic effects in humans. Previous studies have shown that in vitro cell line models and in vivo xenograft tumors derived from established human cancer cell lines have limited predictive value for antitumor activity of a drug in clinical trials [17], [18], [19]. Anticancer agents that showed promising in vivo antitumor activity in xenograft tumor models have often been ineffective for the same type of cancer in clinical trials [20]. In fact, only about 5% of anticancer agents evaluated in human studies between 1991 and 2000 were successfully registered [20]. The majority of failures in late-phase clinical trials result from a lack of clinical efficacy caused primarily by the lack of efficacy proof of concept in humans, lack of predictive biomarkers to identify patient responders, and safety issues [20], [21]. Thus, clinically relevant tumor models that accurately predict therapeutic efficacies would be highly valuable for anticancer drug development.

Evidence from recent studies has shown that patient-derived xenografts (PDXs) established directly from patients' primary tumors preserve the histomorphologic features, heterogeneity, gene expression pattern (including cytokine expression by tumor stromal cells), DNA copy number alterations, and gene mutations of the original tumors [22], [23], [24]. These features were preserved after a series of passages of the tumorgrafts in mice [22], [24]. When PDXs were treated with agents used in a parallel patient population, response rates similar to those reported in human studies were observed, suggesting that the PDX model is clinically relevant for evaluating the efficacy of anticancer drugs [22], [25], [26], [27], [28]. A remarkable correlation between drug activity in PDXs and clinical outcome was reported when patients with advanced cancer were treated with selected regimens based on the treatment responses of their PDX [29], [30], suggesting that PDXs could provide robust models for identifying effective treatment for cancer patients and for predicting clinical efficacy of drug candidates. Consequently, PDXs derived from various types of cancers have been reported recently, including those established from lung cancer [23], [26], [28], [31]. Those studies have demonstrated the feasibility of using PDXs for translational studies in drug development, for molecular characterization of cancer biology, and for strategic development of individualized therapy. Nevertheless, few molecularly-annotated lung cancer PDXs are reported in literature and are not readily available for preclinical studies.

Our purpose here was to develop molecularly annotated PDXs for evaluation of investigational anticancer agents and mechanistic characterization of lung cancers. We established PDXs from surgical specimens of lung cancer patients and characterized the gene mutations in those PDXs and the corresponding primary tumors. Our results show that some novel genes were frequently mutated in primary lung cancers and that the mutations in primary tumors can be recapitulated by their corresponding PDX.