Pancreatic cancer cell lines as patient-derived avatars: genetic characterisation and functional utility

Abstract

ObjectivePancreatic ductal adenocarcinoma (PDAC) is a therapy recalcitrant disease with the worst survival rate of common solid tumours. Preclinical models that accurately reflect the genetic and biological diversity of PDAC will be important for delineating features of tumour biology and therapeutic vulnerabilities.Design27 primary PDAC tumours were employed for genetic analysis and development of tumour models. Tumour tissue was used for derivation of xenografts and cell lines. Exome sequencing was performed on the originating tumour and developed models. RNA sequencing, histological and functional analyses were employed to determine the relationship of the patient-derived models to clinical presentation of PDAC.ResultsThe cohort employed captured the genetic diversity of PDAC. From most cases, both cell lines and xenograft models were developed. Exome sequencing confirmed preservation of the primary tumour mutations in developed cell lines, which remained stable with extended passaging. The level of genetic conservation in the cell lines was comparable to that observed with patient-derived xenograft (PDX) models. Unlike historically established PDAC cancer cell lines, patient-derived models recapitulated the histological architecture of the primary tumour and exhibited metastatic spread similar to that observed clinically. Detailed genetic analyses of tumours and derived models revealed features of ex vivo evolution and the clonal architecture of PDAC. Functional analysis was used to elucidate therapeutic vulnerabilities of relevance to treatment of PDAC.ConclusionsThese data illustrate that with the appropriate methods it is possible to develop cell lines that maintain genetic features of PDAC. Such models serve as important substrates for analysing the significance of genetic variants and create a unique biorepository of annotated cell lines and xenografts that were established simultaneously from same primary tumour. These models can be used to infer genetic and empirically determined therapeutic sensitivities that would be germane to the patient.

Pancreatic Cancer: Current Status and Challenges

“…KRAS mutation is one of the first activating mutations found in pancreatic cancer progression and occurs in over 92% of PanIN-1 [15, 46]. Inactivating mutation of Cyclin dependent kinase 2A (CDKN2A) due to methylation of p16 gene are found in PanIN-2 lesions and their occurrence rate is between 56–78% [15, 46]. Mutations in Tumor protein 53 (TP53) are often found in PanIN-3 lesions with an occurrence rate of approximately 80% [15, 46].…”

“…Inactivating mutation of Cyclin dependent kinase 2A (CDKN2A) due to methylation of p16 gene are found in PanIN-2 lesions and their occurrence rate is between 56–78% [15, 46]. Mutations in Tumor protein 53 (TP53) are often found in PanIN-3 lesions with an occurrence rate of approximately 80% [15, 46]. SMAD4 mutations can also be found in PanIN-3 lesions with an incidence rate of approximately 50% [15, 46].…”

“…Mutations in Tumor protein 53 (TP53) are often found in PanIN-3 lesions with an occurrence rate of approximately 80% [15, 46]. SMAD4 mutations can also be found in PanIN-3 lesions with an incidence rate of approximately 50% [15, 46]. Mutations to SMAD4 result in loss of signaling, which then leads to loss of TGF-β control of cellular proliferation and differentiation [47].…”

“…Mutations to SMAD4 result in loss of signaling, which then leads to loss of TGF-β control of cellular proliferation and differentiation [47]. Other genetic mutations, including those associated with familial pancreatic cancer, generally occur at frequencies of less than 25% [15, 46]. Furthermore, whole genome sequencing and copy number analysis have revealed a number of pathways involved in pancreatic cancer pathogenesis like KRAS, hedgehog, c-Jun N-terminal kinase (JNK), and transforming growth factor β (TGF-β) [45].…”

Understanding Disease Biology and Informing the Management of Pancreas Cancer With Preclinical Model Systems

“…Such humanized mouse models are expensive, however, and slow to develop, and are thus less likely to benefit the original patient. A series of PDXs derived from defined subsets of patients could nevertheless be used to generate a representative and informative screening platform for preclinical evaluations of drug action and efficacy 64–67 .…”