EGFR-mutated lung adenocarcinomas from patients who progressed on EGFR-inhibitors show high engraftment rates in xenograft models

Representation of genomic intratumor heterogeneity in multi-region non-small cell lung cancer patient-derived xenograft models

Patient-derived xenograft (PDX) models are widely used in cancer research. To investigate the genomic fidelity of non-small cell lung cancer PDX models, we established 48 PDX models from 22 patients enrolled in the TRACERx study. Multi-region tumor sampling increased successful PDX engraftment and most models were histologically similar to their parent tumor. Whole-exome sequencing enabled comparison of tumors and PDX models and we provide an adapted mouse reference genome for improved removal of NOD scid gamma (NSG) mouse-derived reads from sequencing data. PDX model establishment caused a genomic bottleneck, with models often representing a single tumor subclone. While distinct tumor subclones were represented in independent models from the same tumor, individual PDX models did not fully recapitulate intratumor heterogeneity. On-going genomic evolution in mice contributed modestly to the genomic distance between tumors and PDX models. Our study highlights the importance of considering primary tumor heterogeneity when using PDX models and emphasizes the benefit of comprehensive tumor sampling.

Patient-derived xenograft models in cancer therapy: technologies and applications

Patient-derived xenograft (PDX) models, in which tumor tissues from patients are implanted into immunocompromised or humanized mice, have shown superiority in recapitulating the characteristics of cancer, such as the spatial structure of cancer and the intratumor heterogeneity of cancer. Moreover, PDX models retain the genomic features of patients across different stages, subtypes, and diversified treatment backgrounds. Optimized PDX engraftment procedures and modern technologies such as multi-omics and deep learning have enabled a more comprehensive depiction of the PDX molecular landscape and boosted the utilization of PDX models. These irreplaceable advantages make PDX models an ideal choice in cancer treatment studies, such as preclinical trials of novel drugs, validating novel drug combinations, screening drug-sensitive patients, and exploring drug resistance mechanisms. In this review, we gave an overview of the history of PDX models and the process of PDX model establishment. Subsequently, the review presents the strengths and weaknesses of PDX models and highlights the integration of novel technologies in PDX model research. Finally, we delineated the broad application of PDX models in chemotherapy, targeted therapy, immunotherapy, and other novel therapies.

Kinomic profiling of tumour xenografts derived from patients with non-small cell lung cancer confirms their fidelity and reveals potentially actionable pathways

INTRODUCTION

High fidelity between non-small cell lung cancer (NSCLC) primary tumours and patient-derived tumour xenografts (PDTXs) is of paramount relevance to spur their application. Extensive proteomic and kinomic analysis of these preclinical models are missing and may inform about their functional status, in terms of phosphopeptides and hyperactive signalling pathways.

METHODS

We investigated tumour xenografts derived from patients with NSCLC to identify hyperactive signalling pathways. Fresh tumour fragments from 81 NSCLC surgical samples were implanted in Nod/Scid/Gamma mice, and engrafted tumours were compared with primary specimens by morphology, immunohistochemistry, gene mutation analyses, and kinase activity profiling. Four different tyrosine and serine/threonine kinase inhibitors were tested against primary tumour and PDTX lysates using the PamGene peptide microarray platform.

RESULTS

The engraftment rate was 33%, with successful engraftment being more associated with poor clinical outcomes. Genomic profiles led to the recognition of hotspot mutations, some of which were initially undetected in donor samples. Kinomic analyses showed that characteristics of primary tumours were retained in PDTXs, and tyrosine kinase inhibitors (TKIs) responses of individual PDTX lines were either expected, based on the genetic status, or alternatively defined suitable targets unpredictable by single-genome fingerprints.

CONCLUSIONS

Collectively, PDTXs mostly resembled their parental NSCLC. Combining genomic and kinomic analyses of tumour xenografts derived from patients with NSCLC, we identified patients' specific targetable pathways, confirming PDTXs as a preclinical tool for biomarker identification and therapeutic algorithm'' improvement.