Breaking barriers: patient-derived xenograft (PDX) models in lung cancer drug development—are we close to the finish line?

The epidermal growth factor receptor (EGFR) gene was discovered in 1978 (1) but only later in 2004 was the role of EGFR activating mutations in lung cancer identified (2). EGFR mutations (EGFRm) are seen in 15–25% of patients with non-small cell lung cancer (NSCLC), especially adenocarcinomas, never smokers, females, and Asians. Activating EGFRm occur in exons 18–21. Deletions in exon 19 and L858R missense mutation in exon 21 represent the classical mutation types, whereas mutations in exons 18 and 20 are relatively rare. In addition to their rarity, exon 20 mutations are also resistant to EGFR tyrosine kinase inhibitors (TKIs) approved for the treatment of lung cancer with classical EGFRm (3). First-generation EGFR TKIs (e.g., erlotinib and gefitinib) are reversible and non-selective. Second-generation (e.g., afatinib and dacomitinib) are irreversible and non-selective (4). Osimertinib, which is a highly selective 3^rd generation EGFR TKI, is characterized by its smaller molecular size, irreversible binding to EGFR TKI, ability to cross blood brain barrier, and better tolerability. In addition, it is effective in targeting T790M mutations, a well-known resistance mechanism to earlier generation EGFR TKI (5). This has led to a wide spectrum of indications for osimertinib both in advanced and early stage EGFR-driven NSCLC, encompassing second-line therapy after progression on an earlier generation TKI with T790M mutation (6), first-line therapy as a single agent (7), or in combination with chemotherapy (8), and adjuvant therapy for resected EGFR-driven localized NSCLC stages IB–IIIA (9).

In patients with advanced stage NSCLC, treatment with EGFR TKIs results in an excellent initial response but resistance does eventually develop, and a wide variety of resistance mechanisms have been identified. Resistance mechanisms to osimertinib is different from that of earlier generation TKIs (10). On-target resistance usually is the result of secondary mutations in the TK domain of the EGFR gene, whereas, the common off-target mechanisms involve MET (5–24%), HER2 (2–5%), HER3, RAS/RAF (1–3%), AKT/mTOR (4–11%), and epithelial-to-mesenchymal transition (11). Amplification or over-expression of the MET gene as a resistance mechanism to osimertinib, is relatively common with a reported frequency of 5–24% (11). Single agent capmatinib has shown activity in patients with MET-amplified NSCLC (12). Therefore, combining osimertinib with an MET TKI presents a rational choice to overcome MET-mediated resistance (Table 1).

Savolitinib, a MET TKI and osimertinib combination was evaluated in the multi-cohort phase IB TATTON trial (13,14). Patients with EGFRm NSCLC who had progressed on EGFR TKI and had overexpression or amplification of MET were enrolled in this trial. Naïve EGFR TKI cohorts had higher response rates and median progression free survival (PFS) than prior EGFR TKI cohort. In the follow-up phase II SAVANNAH trial, savolitinib was added after patients developed MET-mediated resistance to osimertinib (15,16). Preliminary findings from the ORCHARD trial further supported these results with the same combination in post-osimertinib EGFRm patients with MET alterations (Table 2) (17). Studies with other MET TKIs have also reported similar results. In the INSIGHT2 trial, tepotinib was added to osimertinib (18). The SAFFRON is an ongoing phase III trial further investigating the role of osimertinib plus savolitinib versus platinum-doublet chemotherapy. The GEOMETRY-E was another phase III trial that was investigating the role of osimertinib plus capmatinib against platinum-doublet chemotherapy, but unfortunately was terminated based on business considerations of the funding company (19,20).

Dating back to 1969, patient-derived xenograft (PDX) models have shown an optimum tumor “simulation”, i.e., maintaining the primary tumor characteristics, since the real tumor tissue was implanted in the host (21). This differentiates PDX models from the previous cheaper and more readily available cell-line derived xenograft (CDX) models, in which tumor cell lines were synthetized in the lab. Lacking tumor heterogeneity particularly the microenvironment, and immunologic milieu, CDX models were increasingly replaced by PDX models in the drug development process, studying drug activity, and mechanisms of resistance (22). To further enhance the role of PDX models, host modifications, e.g., genome-edited mouse models (GEMMs) and humanized mouse models were introduced and increasingly used, instead of nude mice, severely combined immunodeficient (SCID) mice, and non-obese diabetic (NOD-SCID) mice (23). By mimicking the human tumor microenvironment and tumor heterogeneity, investigators will be able to address clinical questions as well as specific precision oncology concepts, e.g., target therapy, immunotherapy (24). Nonetheless, PDX models face multiple challenges as variable take rates (depending on tumor type and host), long tumor latency (4–6 months versus few weeks for CDX), need for specialized equipment, well trained personnel and higher cost (25).

Jones and colleagues have conducted a pharmacokinetic (PK) and pharmacodynamic (PD) evaluation of savolitinib and osimertinib in a PDX model of MET-amplified and EGFRm NSCLC tumor previously treated with erlotinib (26). Treatment with single agent osimertinib was ineffective whereas single agent savolitinib had minimal antitumor activity. But savolitinib plus osimertinib combination had significantly better antitumor activity at 90% or more tumor regression confirming the efficacy of the combination. Phosphorylated MET (pMET) levels were significantly reduced by savolitinib, but not with osimertinib. Savolitinib alone did not inhibit phosphorylated EGFR (pEGFR) levels, but the combination was effective in reducing both pMET and pEGFR levels confirming the rationale to combine the two agents. PK and PD analysis were performed in the PDX model. The authors developed a PK/PD model linking savolitinib/osimertinib exposure (PK) to inhibition of pMET/pEGFR (PD) as well as to anti-tumor effects. By applying the PDX model parameters in human PK models the authors were able to simulate pEGFR and pMET inhibition in humans for different savolitinib doses while keeping osimertinib at a fixed dose of 80 mg once daily. They identified that savolitinib at either 600 mg once daily or 300 mg twice daily were the most effective dose levels.

Using PDX models to screen targeted therapies could minimize resource loss due to failed human trials and increase likelihood of success for the candidate drug. However, challenges remain, patients with MET amplification-based resistance to EGFR TKIs are quite heterogeneous with wide variability in their molecular phenotype, clinical characteristics and ability to tolerate the combination dosage. Therefore, a single model to guide treatment may be insufficient. The savolitinib and osimertinib combination has been extensively evaluated in human phase I studies and dosage levels for phase II studies have already been established. The PK and PD analysis using the PDX model by Jones and colleagues serves as a useful proof of principle.

PDX models are a key addition in the drug development pipeline, their ability to phenocopy drug resistant tumors might lead to more precise assessment of drug efficacy than conventional cell line studies. PK and PD analysis to model appropriate doses for early phase human trials is another potential advantage. At the same time there are no established protocols on incorporating PDX model studies with other preclinical studies to select the best candidates for human trials. The generalizability of PDX model study results to human studies requires further study and validation. The work by Jones and colleagues is an important step in that direction, given the ever-growing number of therapeutic targets in lung cancer and cancer in general, we expect to see more PDX model studies in the preclinical setting. Such studies could define the role of PDX model studies in drug development.

Acknowledgments

Funding: None.

Footnote

Provenance and Peer Review: This article was commissioned by the editorial office, Translational Lung Cancer Research. The article has undergone external peer review.

Peer Review File: Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-24-206/prf

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-24-206/coif). J.S. reports that he served as a consultant for Abbvie, DSI, Oncohost, Astra Zeneca, Genentech, Guidepoint, GLG, Onviv, Novocure, and Cardinal and as a speaker for AstraZeneca, Janssen, Jazz, and Merck. The other authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Carpenter G, King L Jr, Cohen S. Epidermal growth factor stimulates phosphorylation in membrane preparations in vitro. Nature 1978;276:409-10. [Crossref] [PubMed]
2. Paez JG, Jänne PA, Lee JC, et al. EGFR mutations in lung cancer: correlation with clinical response to gefitinib therapy. Science 2004;304:1497-500. [Crossref] [PubMed]
3. Bethune G, Bethune D, Ridgway N, et al. Epidermal growth factor receptor (EGFR) in lung cancer: an overview and update. J Thorac Dis 2010;2:48-51. [PubMed]
4. Zhang H. Three generations of epidermal growth factor receptor tyrosine kinase inhibitors developed to revolutionize the therapy of lung cancer. Drug Des Devel Ther 2016;10:3867-72. [Crossref] [PubMed]
5. Nagano T, Tachihara M, Nishimura Y. Mechanism of Resistance to Epidermal Growth Factor Receptor-Tyrosine Kinase Inhibitors and a Potential Treatment Strategy. Cells 2018;7:212. [Crossref] [PubMed]
6. Yang JC, Ahn MJ, Kim DW, et al. Osimertinib in Pretreated T790M-Positive Advanced Non-Small-Cell Lung Cancer: AURA Study Phase II Extension Component. J Clin Oncol 2017;35:1288-96. [Crossref] [PubMed]
7. Soria JC, Ohe Y, Vansteenkiste J, et al. Osimertinib in Untreated EGFR-Mutated Advanced Non-Small-Cell Lung Cancer. N Engl J Med 2018;378:113-25. [Crossref] [PubMed]
8. Planchard D, Jänne PA, Cheng Y, et al. Osimertinib with or without Chemotherapy in EGFR-Mutated Advanced NSCLC. N Engl J Med 2023;389:1935-48. [Crossref] [PubMed]
9. Herbst RS, Wu YL, John T, et al. Adjuvant Osimertinib for Resected EGFR-Mutated Stage IB-IIIA Non-Small-Cell Lung Cancer: Updated Results From the Phase III Randomized ADAURA Trial. J Clin Oncol 2023;41:1830-40. [Crossref] [PubMed]
10. Du X, Yang B, An Q, et al. Acquired resistance to third-generation EGFR-TKIs and emerging next-generation EGFR inhibitors. Innovation (Camb) 2021;2:100103. [Crossref] [PubMed]
11. Gomatou G, Syrigos N, Kotteas E. Osimertinib Resistance: Molecular Mechanisms and Emerging Treatment Options. Cancers (Basel) 2023;15:841. [Crossref] [PubMed]
12. Wolf J, Seto T, Han JY, et al. Capmatinib in MET Exon 14-Mutated or MET-Amplified Non-Small-Cell Lung Cancer. N Engl J Med 2020;383:944-57. [Crossref] [PubMed]
13. Hartmaier RJ, Markovets AA, Ahn MJ, et al. Osimertinib + Savolitinib to Overcome Acquired MET-Mediated Resistance in Epidermal Growth Factor Receptor-Mutated, MET-Amplified Non-Small Cell Lung Cancer: TATTON. Cancer Discov 2023;13:98-113. [Crossref] [PubMed]
14. Oxnard GR, Yang JC, Yu H, et al. TATTON: a multi-arm, phase Ib trial of osimertinib combined with selumetinib, savolitinib, or durvalumab in EGFR-mutant lung cancer. Ann Oncol 2020;31:507-16. [Crossref] [PubMed]
15. Ahn M, De Marinis F, Bonanno L, et al. EP08.02-140 MET Biomarker-based Preliminary Efficacy Analysis in SAVANNAH: savolitinib+osimertinib in EGFRm NSCLC Post-Osimertinib. J Thorac Oncol 2022;17:S469-70. [Crossref]
16. Sequist LV, Han JY, Ahn MJ, et al. Osimertinib plus savolitinib in patients with EGFR mutation-positive, MET-amplified, non-small-cell lung cancer after progression on EGFR tyrosine kinase inhibitors: interim results from a multicentre, open-label, phase 1b study. Lancet Oncol 2020;21:373-86. [Crossref] [PubMed]
17. Yu HA, Ambrose H, Baik C, et al. 1239P ORCHARD osimertinib + savolitinib interim analysis: A biomarker-directed phase II platform study in patients (pts) with advanced non-small cell lung cancer (NSCLC) whose disease has progressed on first-line (1L) osimertinib. Ann Oncol 2021;32:S978-9. [Crossref]
18. Tan DS-W, Kim TM, Guarneri V, et al. Tepotinib + osimertinib for EGFR mutant (EGFRm) NSCLC with MET amplification (METamp) after first-line (1L) osimertinib. J Clin Oncol 2023;41:abstr 9021.
19. Lu S, Xu W, Telaranta-Keerie A, et al. EP08.02-138 SAFFRON: Ph3 Savolitinib + Osimertinib vs Chemotherapy in EGFRm NSCLC with MET Overexpression/Amplification Post-Osimertinib. J Thorac Oncol 2022;17:S468-9. [Crossref]
20. Wu YL, Han JY, Kato T, et al. Capmatinib plus osimertinib versus platinum-pemetrexed doublet chemotherapy as second-line therapy in patients with stage IIIb/IIIc or IV EGFR-mutant, T790M-negative NSCLC harboring MET amplification. J Clin Oncol 2022;40:abstr TPS9153.
21. Rygaard J, Poulsen CO. Heterotransplantation of a human malignant tumour to “nude” mice. Acta Pathol Microbiol Scand 1969;77:758-60. [Crossref] [PubMed]
22. Lallo A, Schenk MW, Frese KK, et al. Circulating tumor cells and CDX models as a tool for preclinical drug development. Transl Lung Cancer Res 2017;6:397-408. [Crossref] [PubMed]
23. Okada S, Vaeteewoottacharn K, Kariya R. Application of Highly Immunocompromised Mice for the Establishment of Patient-Derived Xenograft (PDX) Models. Cells 2019;8:889. [Crossref] [PubMed]
24. Liu Y, Wu W, Cai C, et al. Patient-derived xenograft models in cancer therapy: technologies and applications. Signal Transduct Target Ther 2023;8:160. [Crossref] [PubMed]
25. Abdolahi S, Ghazvinian Z, Muhammadnejad S, et al. Patient-derived xenograft (PDX) models, applications and challenges in cancer research. J Transl Med 2022;20:206. [Crossref] [PubMed]
26. Jones RDO, Petersson K, Tabatabai A, et al. Pharmacokinetic/Pharmacodynamic Analysis of Savolitinib plus Osimertinib in an EGFR Mutation-Positive, MET-Amplified Non-Small Cell Lung Cancer Model. Mol Cancer Ther 2023;22:679-90. [Crossref] [PubMed]