Comparison of the Genetic Alterations between Primary Colorectal Cancers and Their Corresponding Patient-Derived Xenograft Tissues.
ABSTRACT: Patient-derived xenograft (PDX) models are useful tools for tumor biology research and testing the efficacy of candidate anticancer drugs targeting the druggable mutations identified in tumor tissue. However, it is still unknown how much of the genetic alterations identified in primary tumors are consistently detected in tumor tissues in the PDX model. In this study, we analyzed the genetic alterations of three primary colorectal cancers (CRCs) and matched xenograft tissues in PDX models using a next-generation sequencing cancer panel. Of the 17 somatic mutations identified from the three CRCs, 14 (82.4%) were consistently identified in both primary and xenograft tumors. The other three mutations identified in the primary tumor were not detected in the xenograft tumor tissue. There was no newly identified mutation in the xenograft tumor tissues. In addition to the somatic mutations, the copy number alteration profiles were also largely consistent between the primary tumor and xenograft tissue. All of these data suggest that the PDX tumor model preserves the majority of the key mutations detected in the primary tumor site. This study provides evidence that the PDX model is useful for testing targeted therapies in the clinical field and research on precision medicine.
Project description:Patient-derived xenograft (PDX) mouse models are frequently used to test the drug efficacy in diverse types of cancer. They are known to recapitulate the patient characteristics faithfully, but a systematic survey with a large number of cases is yet missing in lung cancer. Here we report the comparison of genomic characters between mouse and patient tumor tissues in lung cancer based on exome sequencing data. We established PDX mouse models for 132 lung cancer patients and performed whole exome sequencing for trio samples of tumor-normal-xenograft tissues. Then we computed the somatic mutations and copy number variations, which were used to compare the PDX and patient tumor tissues. Genomic and histological conclusions for validity of PDX models agreed in most cases, but we observed eight (~7%) discordant cases. We further examined the changes in mutations and copy number alterations in PDX model production and passage processes, which highlighted the clonal evolution in PDX mouse models. Our study shows that the genomic characterization plays complementary roles to the histological examination in cancer studies utilizing PDX mouse models.
Project description:BACKGROUND:Patient-derived xenograft (PDX) models are in vivo models of human cancer that have been used for translational cancer research and therapy selection for individual patients. The Jackson Laboratory (JAX) PDX resource comprises 455 models originating from 34 different primary sites (as of 05/08/2019). The models undergo rigorous quality control and are genomically characterized to identify somatic mutations, copy number alterations, and transcriptional profiles. Bioinformatics workflows for analyzing genomic data obtained from human tumors engrafted in a mouse host (i.e., Patient-Derived Xenografts; PDXs) must address challenges such as discriminating between mouse and human sequence reads and accurately identifying somatic mutations and copy number alterations when paired non-tumor DNA from the patient is not available for comparison. RESULTS:We report here data analysis workflows and guidelines that address these challenges and achieve reliable identification of somatic mutations, copy number alterations, and transcriptomic profiles of tumors from PDX models that lack genomic data from paired non-tumor tissue for comparison. Our workflows incorporate commonly used software and public databases but are tailored to address the specific challenges of PDX genomics data analysis through parameter tuning and customized data filters and result in improved accuracy for the detection of somatic alterations in PDX models. We also report a gene expression-based classifier that can identify EBV-transformed tumors. We validated our analytical approaches using data simulations and demonstrated the overall concordance of the genomic properties of xenograft tumors with data from primary human tumors in The Cancer Genome Atlas (TCGA). CONCLUSIONS:The analysis workflows that we have developed to accurately predict somatic profiles of tumors from PDX models that lack normal tissue for comparison enable the identification of the key oncogenic genomic and expression signatures to support model selection and/or biomarker development in therapeutic studies. A reference implementation of our analysis recommendations is available at https://github.com/TheJacksonLaboratory/PDX-Analysis-Workflows .
Project description:Precision medicine approaches are ideally suited for rare tumors where comprehensive characterization may have diagnostic, prognostic, and therapeutic value. We describe the clinical case and molecular characterization of an adolescent with metastatic poorly differentiated carcinoma (PDC). Given the rarity and poor prognosis associated with PDC in children, we utilized genomic analysis and preclinical models to validate oncogenic drivers and identify molecular vulnerabilities.We utilized whole exome sequencing (WES) and transcriptome analysis to identify germline and somatic alterations in the patient's tumor. In silico and in vitro studies were used to determine the functional consequences of genomic alterations. Primary tumor was used to generate a patient-derived xenograft (PDX) model, which was used for in vivo assessment of predicted therapeutic options.WES revealed a novel germline frameshift variant (p.E1554fs) in APC, establishing a diagnosis of Gardner syndrome, along with a somatic nonsense (p.R790*) APC mutation in the tumor. Somatic mutations in TP53, MAX, BRAF, ROS1, and RPTOR were also identified and transcriptome and immunohistochemical analyses suggested hyperactivation of the Wnt/ß-catenin and AKT/mTOR pathways. In silico and biochemical assays demonstrated that the MAX p.R60Q and BRAF p.K483E mutations were activating mutations, whereas the ROS1 and RPTOR mutations were of lower utility for therapeutic targeting. Utilizing a patient-specific PDX model, we demonstrated in vivo activity of mTOR inhibition with temsirolimus and partial response to inhibition of MEK.This clinical case illustrates the depth of investigation necessary to fully characterize the functional significance of the breadth of alterations identified through genomic analysis.
Project description:Genomic studies have identified recurrent somatic mutations in acute leukemias. However, current murine models do not sufficiently encompass the genomic complexity of human leukemias. To develop preclinical models, we transplanted 160 samples from patients with acute leukemia (acute myeloid leukemia, mixed lineage leukemia, B-cell acute lymphoblastic leukemia, T-cell ALL) into immunodeficient mice. Of these, 119 engrafted with expected immunophenotype. Targeted sequencing of 374 genes and 265 frequently rearranged RNAs detected recurrent and novel genetic lesions in 48 paired primary tumor (PT) and patient-derived xenotransplant (PDX) samples. Overall, the frequencies of 274 somatic variant alleles correlated between PT and PDX samples, although the data were highly variable for variant alleles present at 0-10%. Seventeen percent of variant alleles were detected in either PT or PDX samples only. Based on variant allele frequency changes, 24 PT-PDX pairs were classified as concordant while the other 24 pairs showed various degree of clonal discordance. There was no correlation of clonal concordance with clinical parameters of diseases. Significantly more bone marrow samples than peripheral blood samples engrafted discordantly. These data demonstrate the utility of developing PDX banks for modeling human leukemia, and emphasize the importance of genomic profiling of PDX and patient samples to ensure concordance before performing mechanistic or therapeutic studies.
Project description:Subgroups of colorectal carcinomas (CRCs) characterized by DNA methylation anomalies are termed CpG island methylator phenotype (CIMP)1, CIMP2, or CIMP-negative. The pathogenesis of CIMP1 colorectal carcinomas, and their effects on patients' prognoses and responses to treatment, differ from those of other CRCs. We sought to identify genetic somatic alterations associated with CIMP1 CRCs.We examined genomic DNA samples from 100 primary CRCs, 10 adenomas, and adjacent normal-appearing mucosae from patients undergoing surgery or colonoscopy at 3 tertiary medical centers. We performed exome sequencing of 16 colorectal tumors and their adjacent normal tissues. Extensive comparison with known somatic alterations in CRCs allowed segregation of CIMP1-exclusive alterations. The prevalence of mutations in selected genes was determined from an independent cohort.We found that genes that regulate chromatin were mutated in CIMP1 CRCs; the highest rates of mutation were observed in CHD7 and CHD8, which encode members of the chromodomain helicase/adenosine triphosphate-dependent chromatin remodeling family. Somatic mutations in these 2 genes were detected in 5 of 9 CIMP1 CRCs. A prevalence screen showed that nonsilencing mutations in CHD7 and CHD8 occurred significantly more frequently in CIMP1 tumors (18 of 42 [43%]) than in CIMP2 (3 of 34 [9%]; P < .01) or CIMP-negative tumors (2 of 34 [6%]; P < .001). CIMP1 markers had increased binding by CHD7, compared with all genes. Genes altered in patients with CHARGE syndrome (congenital malformations involving the central nervous system, eye, ear, nose, and mediastinal organs) who had CHD7 mutations were also altered in CRCs with mutations in CHD7.Aberrations in chromatin remodeling could contribute to the development of CIMP1 CRCs. A better understanding of the biological determinants of CRCs can be achieved when these tumors are categorized according to their epigenetic status.
Project description:N-of-1 trials target actionable mutations, yet such approaches do not test genomically-informed therapies in patient tumor models prior to patient treatment. To address this, we developed patient-derived xenograft (PDX) models from fine needle aspiration (FNA) biopsies (FNA-PDX) obtained from primary pancreatic ductal adenocarcinoma (PDAC) at the time of diagnosis. Here, we characterize PDX models established from one primary and two metastatic sites of one patient. We identified an activating KRAS G12R mutation among other mutations in these models. In explant cells derived from these PDX tumor models with a KRAS G12R mutation, treatment with inhibitors of CDKs (including CDK9) reduced phosphorylation of a marker of CDK9 activity (phospho-RNAPII CTD Ser2/5) and reduced viability/growth of explant cells derived from PDAC PDX models. Similarly, a CDK inhibitor reduced phospho-RNAPII CTD Ser2/5, increased apoptosis, and inhibited tumor growth in FNA-PDX and patient-matched metastatic-PDX models. In summary, PDX models can be constructed from FNA biopsies of PDAC which in turn can enable genomic characterization and identification of potential therapies.
Project description:Background:Metastasis is a major cause of failed colorectal cancer (CRC) treatment. While lung metastasis (LM) is observed in 10-15% of patients with CRC, the genetic mechanisms that cause CRC to metastasize to the lung remain unclear. Methods:In this study, we employed whole exome sequencing (WES) of primary CRC tumors and matched isolated LM lesions to compare their genomic profiles. Comprehensive genomic analyses of five freshly frozen primary tumor lesions, five paired LM lesions, and matched non-cancerous tissues was achieved by WES. Results:An integrated analysis of somatic mutations, somatic copy number alterations, and clonal structures revealed that genomic alterations were present in primary and metastatic CRCs with various levels of discordance, indicating substantial levels of intertumor heterogeneity. Moreover, our results suggest that the founder clone of the primary tumor was responsible for the formation of the metastatic lesion. Additionally, only a few metastasis-specific mutations were identified, suggesting that LM-promoting mutations might be pre-existing in primary tumors. Conclusions:Primary and metastatic CRC show intertumor heterogeneity; however, both lesions were founded by the same clone. These results indicate that malignant clones contributing to disease progression should be identified during the genetic prognosis of cancer metastasis.
Project description:Intrinsic and acquired resistance to targeted therapies is a significant clinical problem in cancer. We previously showed that resistance to regorafenib, a multi-kinase inhibitor for treating colorectal cancer (CRC) patients, can be caused by mutations in the tumor suppressor FBW7, which block degradation of the pro-survival Bcl-2 family protein Mcl-1. We tested if Mcl-1 inhibition can be used to develop a precision combination therapy for overcoming regorafenib resistance. METHODS:Small-molecule Mcl-1 inhibitors were tested on CRC cells with knock-in (KI) of a non-degradable Mcl-1. Effects of Mcl-1 inhibitors on regorafenib sensitivity were determined in FBW7-mutant and -wild-type (WT) CRC cells and tumors, and in those with acquired regorafenib resistance due to enriched FBW7 mutations. Furthermore, translational potential was explored by establishing and analyzing FBW7-mutant and -WT patient-derived organoid (PDO) and xenograft (PDX) tumor models. RESULTS:We found that highly potent and specific Mcl-1 inhibitors such as S63845 overcame regorafenib resistance by restoring apoptosis in multiple regorafenib-resistant CRC models. Mcl-1 inhibition re-sensitized CRC tumors with intrinsic and acquired regorafenib resistance in vitro and in vivo, including those with FBW7 mutations. Importantly, Mcl-1 inhibition also sensitized FBW7-mutant PDO and PDX models to regorafenib. In contrast, Mcl-1 inhibition had no effect in FBW7-WT CRCs. CONCLUSIONS:Our results demonstrate that Mcl-1 inhibitors can overcome intrinsic and acquired regorafenib resistance in CRCs by restoring apoptotic response. FBW7 mutations might be a potential biomarker predicting for response to the regorafenib/Mcl-1 inhibitor combination.
Project description:Patient-derived tumor xenograft (PDX) mouse models are widely used for drug screening. The underlying assumption is that PDX tissue is very similar with the original patient tissue, and it has the same response to the drug treatment. To investigate whether the primary tumor site information is well preserved in PDX, we analyzed the gene expression profiles of PDX mouse models originated from different tissues, including breast, kidney, large intestine, lung, ovary, pancreas, skin, and soft tissues. The popular Monte Carlo feature selection method was employed to analyze the expression profile, yielding a feature list. From this list, incremental feature selection and support vector machine (SVM) were adopted to extract distinctively expressed genes in PDXs from different primary tumor sites and build an optimal SVM classifier. In addition, we also set up a group of quantitative rules to identify primary tumor sites. A total of 755 genes were extracted by the feature selection procedures, on which the SVM classifier can provide a high performance with MCC 0.986 on classifying primary tumor sites originated from different tissues. Furthermore, we obtained 16 classification rules, which gave a lower accuracy but clear classification procedures. Such results validated that the primary tumor site specificity was well preserved in PDX as the PDXs from different primary tumor sites were still very different and these PDX differences were similar with the differences observed in patients with tumor. For example, VIM and ABHD17C were highly expressed in the PDX from breast tissue and also highly expressed in breast cancer patients.
Project description:BACKGROUND:Patient-derived xenograft (PDX) models increasingly are used in translational research. However, the engraftment rates of patient tumor samples in immunodeficient mice to PDX models vary greatly. METHODS:Tumor tissue samples from 308 patients with non-small cell lung cancer were implanted in immunodeficient mice. The patients were followed for 1.5 to approximately 6 years. The authors performed histological analysis of PDXs and some residual tumor tissues in mice with failed PDX growth at 1 year after implantation. Quantitative polymerase chain reaction and enzyme-linked immunoadsorbent assay were performed to measure the levels of Epstein-Barr virus genes and human immunoglobulin G in PDX samples. Patient characteristics were compared for PDX growth and overall survival as outcomes using Cox regression analyses. Disease staging was based on the 7th TNM staging system. RESULTS:The overall engraftment rate for PDXs from patients with non-small cell lung cancer was 34%. Squamous cell carcinomas had a higher engraftment rate (53%) compared with adenocarcinomas. Tumor samples from patients with stage II and stage III disease and from larger tumors were found to have relatively high engraftment rates. Patients whose tumors successfully engrafted had worse overall survival, particularly those individuals with adenocarcinoma, stage III or stage IV disease, and moderately differentiated tumors. Lymphoma formation was one of the factors associated with engraftment failure. Human CD8-positive and CD20-positive cells were detected in residual samples of tumor tissue that failed to generate a PDX at 1 year after implantation. Human immunoglobulin G was detected in the plasma of mice that did not have PDX growth at 14 months after implantation. CONCLUSIONS:The results of the current study indicate that the characteristics of cancer cells and the tumor immune microenvironment in primary tumors both can affect engraftment of a primary tumor sample.