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Preclinical models are critical for all aspects of translational cancer research, including disease characterization, discovery of actionable vulnerabilities unique to cancer versus normal cells, and the development of efficacious therapies that exploit these vulnerabilities to increase the overall survival of patients. In the melanoma field, tens of thousands of cell line models have been heavily utilized for drug screening, with >4,000 contributed by our group alone (WMXXX series). These cell line models were derived from melanoma patients with various forms of cutaneous melanoma (i.e., acral, uveal, and superficial spreading) and diverse genotypes (i.e., BRAFV600-mutant and neuroblastoma RAS viral oncogene homolog [NRASQ61R-mutant]), which span the spectrum of disease present in the clinic1,2.
Unequivocally, the most successful, targeted therapy strategy in the melanoma field has emerged from 1) the genomic characterization of patients’ tumors identifying BRAF mutations in ~50% of melanomas3 and from 2) preclinical investigation leveraging melanoma cell line models4. The BRAF/MEK inhibitor combination was Food and Drug Administration (FDA)-approved in 2014 for the treatment of patients whose melanomas harbor activating BRAFV600E/K mutations and boasts a >75% response rate5. Despite this initial efficacy, resistance rapidly arises in nearly every case due to multifarious intrinsic and acquired resistance mechanisms and intratumoral heterogeneity. Unfortunately, cell line models do not recapitulate representative biological heterogeneity when grown in two-dimensional culture in plastic vessels, which masks their clinically predictive potential when investigators attempt to experimentally determine therapies that might be effective in patients with a specific form or genotype of melanoma6. Understanding how to best model patient intratumoral heterogeneity will allow investigators to better develop therapeutic modalities that can kill therapy-resistant subpopulations that drive failure to current standard-of-care therapies.
Paramount to the limited predictive value of cell line models is how they are initially established. Irreversible alterations occur in the tumor clonal landscape when a single-cell suspension of a patients’ tumor is grown on two-dimensional, plastic tissue culture vessels, including changes in proliferative and invasive potential, the elimination of specific subpopulations, and the alteration of genetic information7. Xenografts into mice of these melanoma cell line models represent the most frequently used in vivo platform for preclinical studies; however, this strategy also suffers from the poor recapitulation of complex tumor heterogeneity observed clinically. To overcome this shortcoming, there has been a growing interest in incorporating more sophisticated preclinical models of melanoma, including the PDX model. PDX models have been utilized for >30 years, with seminal studies in lung cancer patients demonstrating concordance between the patients' response to cytotoxic agents and the response of the PDX model derived from the same patient8. Recently, there has been a drive to utilize PDX models as the tool of choice for preclinical investigations both in the industry and in academic centers. PDX models, because of their superior recapitulation of tumor heterogeneity in human patients, are more clinically relevant to use in therapy optimization efforts than cell line xenografts9. In melanoma, there are immense hurdles that blunt the therapeutic management of advanced disease10. Clinically relevant PDX models have been used to model clinical resistance and identify therapeutic strategies with clinically available agents to treat therapy-resistant tumors11,12. Briefly, the protocol presented here to generate PDX models requires the subcutaneous implantation of fresh tissue from primary or metastatic melanomas (collected by biopsy or surgery) into NOD/scid/IL2-receptor null (NSG) mice. Different variations in methodological approach are used by different groups; however, a fundamental core exists13.