Evaluation of molecular subtypes and clonal selection during establishment of patient-derived tumor xenografts from gastric adenocarcinoma

Peille, Anne-Lise; Vuaroqueaux, Vincent; Wong, Swee-Seong; Ting, Jason C.; Klingner, Kerstin; Zeitouni, Bruno; Landesfeind, Manuel; Kim, Woo Ho; Lee, Hyuk-Joon; Kong, Seong‐Ho; Wulur, Isabella H.; Bray, Steven M.; Bronsert, Peter; Zanella, Nina; Donoho, Greg; Yang, Han–Kwang; Fiebig, Heinz‐Herbert; Reinhard, Christoph; Aggarwal, Amit

doi:10.1038/s42003-020-1077-z

Cited by 13 publications

(11 citation statements)

References 39 publications

(61 reference statements)

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“…This finding can be attributed to expansion of select cell populations in mice during PDX establishment, or sampling bias due to intra-tumoral heterogeneity. As a consequence, certain variants are observed at a higher frequency in PDX than the parental tumors, which is suggestive of engraftment-related clonal selection within PDX, as observed previously (Peille et al , 2020). For example, NF1 and SUZ12 were mutated only in the PDX line of MN-2, but not in the parental tumor.…”

Section: Resultssupporting

confidence: 82%

Ex vivo to in vivo model of malignant peripheral nerve sheath tumors for precision oncology

Bhatia

Larsson

Calizo

et al. 2022

Preprint

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Malignant peripheral nerve sheath tumors (MPNST) are aggressive soft tissue sarcomas that often develop in patients with neurofibromatosis type 1 (NF1-MPNST), but can occur sporadically. Through a multi-institution collaboration, we have developed 13 NF1-associated MPNST patient-derived xenografts (PDX). Genomic analysis of the PDX-tumor pairs identified somatic mutations in NF1 (61%), SUZ12 (61%), EED (15%), and TP53 (15%), and chromosome 8 (Chr8) gain (77%), consistent with published data. Pre-clinical models that capture this molecular heterogeneity are needed to identify and prioritize effective drug candidates for clinical translation. Here, we describe the successful development of a medium-throughput ex vivo 3D microtissue model with several advantages over 2D cell line growth, which can be utilized to predict drug response in vivo. Herein, we present proof-of-principle of this PDX-to-microtissue system, using four genomically representative MPNST and three drugs. This work highlights the development of a novel ex vivo to in vivo preclinical platform in MPNST that successfully captures the genomic diversity observed in patients and represents a resource to identify future therapeutic strategies.

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Section: Resultssupporting

confidence: 82%

Ex vivo to in vivo model of malignant peripheral nerve sheath tumors for precision oncology

Bhatia

Larsson

Calizo

et al. 2022

Preprint

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“…33 This study found that diffuse-type tumors and low tumor cell percentages were associated with poor engraftment. Another study attempted to generate PDXs from 100 gastric tumors, successfully generating 27 PDXs, which were more likely intestinal histology, CIN subtype, and MSI-H. 34 Finally, a collection of 100 gastric cancer PDXs generated from 349 tumors was recently reported (28.7% success rate). 35 Again, histologic type and MSI-H status were associated with engraftment, as well as advanced stage and high RTK/RAS copy-number variation.…”

Section: Discussionmentioning

confidence: 99%

Defining and Targeting Esophagogastric Cancer Genomic Subsets With Patient-Derived Xenografts

Moy

Walch

Mattar

et al. 2022

JCO Precision Oncology

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PURPOSE Comprehensive genomic profiling has defined key oncogenic drivers and distinct molecular subtypes in esophagogastric cancer; however, the number of clinically actionable alterations remains limited. To establish preclinical models for testing genomically driven therapeutic strategies, we generated and characterized a large collection of esophagogastric cancer patient–derived xenografts (PDXs). MATERIALS AND METHODS We established a biobank of 98 esophagogastric cancer PDX models derived from primary tumors and metastases. Clinicopathologic features of each PDX and the corresponding patient sample were annotated, including stage at diagnosis, treatment history, histology, and biomarker profile. To identify oncogenic DNA alterations, we analyzed and compared targeted sequencing performed on PDX and parent tumor pairs. We conducted xenotrials in genomically defined models with oncogenic drivers. RESULTS From April 2010 to June 2019, we implanted 276 patient tumors, of which 98 successfully engrafted (35.5%). This collection is enriched for PDXs derived from patients with human epidermal growth factor receptor 2–positive esophagogastric adenocarcinoma (62 models, 63%), the majority of which were refractory to standard therapies including trastuzumab. Factors positively correlating with engraftment included advanced stage, metastatic origin, intestinal-type histology, and human epidermal growth factor receptor 2–positivity. Mutations in TP53 and alterations in receptor tyrosine kinases ( ERBB2 and EGFR), RAS/PI3K pathway genes, cell-cycle mediators ( CDKN2A and CCNE1), and CDH1 were the predominant oncogenic drivers, recapitulating clinical tumor sequencing. We observed antitumor activity with rational combination strategies in models established from treatment-refractory disease. CONCLUSION The Memorial Sloan Kettering Cancer Center PDX collection recapitulates the heterogeneity of esophagogastric cancer and is a powerful resource to investigate mechanisms driving tumor progression, identify predictive biomarkers, and develop therapeutic strategies for molecularly defined subsets of esophagogastric cancer.

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“…Studies on mosaicism detection in cancer mainly used BAFSegmentation, TAPS, PICNIC, GISTIC and CNAG relating acute myeloid leukemia [ 234 ], hyperdiploid childhood acute lymphoblastic leukemia [ 235 ], ossification of fibromyxoid tumors [ 236 ], gastric adenocarcinoma [ 237 ], hepatoblastoma [ 238 ], lymphoblastic leukemia [ 239 ] and non-Hodgkin B-cell lymphoma [ 240 ]. Also, mosaicism genotyping was performed with MoChA, MAD, BAFSegmentation and PICNICfor mastocytosis [ 241 ] and drug resistance.…”

Section: Recent Studies Applying Inference Methods Of Snp Datamentioning

confidence: 99%

Fully exploiting SNP arrays: a systematic review on the tools to extract underlying genomic structure

Balagué-Dobón

Cáceres

González

2022

Briefings in Bioinformatics

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Single nucleotide polymorphisms (SNPs) are the most abundant type of genomic variation and the most accessible to genotype in large cohorts. However, they individually explain a small proportion of phenotypic differences between individuals. Ancestry, collective SNP effects, structural variants, somatic mutations or even differences in historic recombination can potentially explain a high percentage of genomic divergence. These genetic differences can be infrequent or laborious to characterize; however, many of them leave distinctive marks on the SNPs across the genome allowing their study in large population samples. Consequently, several methods have been developed over the last decade to detect and analyze different genomic structures using SNP arrays, to complement genome-wide association studies and determine the contribution of these structures to explain the phenotypic differences between individuals. We present an up-to-date collection of available bioinformatics tools that can be used to extract relevant genomic information from SNP array data including population structure and ancestry; polygenic risk scores; identity-by-descent fragments; linkage disequilibrium; heritability and structural variants such as inversions, copy number variants, genetic mosaicisms and recombination histories. From a systematic review of recently published applications of the methods, we describe the main characteristics of R packages, command-line tools and desktop applications, both free and commercial, to help make the most of a large amount of publicly available SNP data.

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Evaluation of molecular subtypes and clonal selection during establishment of patient-derived tumor xenografts from gastric adenocarcinoma

Cited by 13 publications

References 39 publications

Ex vivo to in vivo model of malignant peripheral nerve sheath tumors for precision oncology

Ex vivo to in vivo model of malignant peripheral nerve sheath tumors for precision oncology

Defining and Targeting Esophagogastric Cancer Genomic Subsets With Patient-Derived Xenografts

Fully exploiting SNP arrays: a systematic review on the tools to extract underlying genomic structure

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