Genomic data from 48 Asian gastric patient-derived xenograft (PDX) models, 7 Asian gastric patient tumors and the 8 corresponding normal tissues
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PROVIDER: PRJNA475762 | ENA |
REPOSITORIES: ENA
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Project description:There is a strong need to develop patient-derived xenograft (PDX) tumor models for studying new treatment options for gastric cancer (GC). With low engraftment success, few collections of GC PDX have been reported and molecular basis of the model establishment remain largely unknown. Here we established n=27 PDX models from n=100 GC tumors and compared their characteristics to GC patient tumors based on the recent work done by ACRG and TCGA, to evaluate the representativeness and relevance of the collection for drug testing. We show that MSI, CIN and MSS/TP53- tumors were preferentially established as PDX, while MSS/EMT and EBV not and that PDX models retained histology and molecular subtypes of parental tumors. By using synapse database, we identified 48 druggable alterations that could be investigated with the collection. Counting alterations for these 48 genes in PDX compared to TCGA tumors revealed models frequently classified with heavily altered tumors but well preserved genomic alteration patterns specific of each GC subtype. The molecular analysis of n=8/27 tumors and corresponding PDX at passage P1, P2 and P3 revealed variations in somatic alteration content both at single nucleotide and chromosomal level in highly unstable MSI and CIN tumors, with changes occurring mainly at P1. In two cases, we show likely emergence of rare subclones carrying known oncogenic alterations in KRAS and PIK3CA. Significance. This study presents a resource of fully annotated GC PDX models for anticancer agent testing. We show that beside close resemblance of PDX with parental tumors, not all subtypes are established, and that the clonal selection plays a key role the establishment of certain tumors. This may have a bearing on translation of observations into the clinic and underline the need to frequently survey the molecular characteristics of the PDX models.
2020-07-15 | GSE115674 | GEO
Project description:Expression data from 27 Asian gastric patient-derived xenograft (PDX) models
| PRJNA475607 | ENA
Project description:There is a strong need to develop patient-derived xenograft (PDX) tumor models for studying new treatment options for gastric cancer (GC). With low engraftment success, few collections of GC PDX have been reported and molecular basis of the model establishment remain largely unknown. Here we established n=27 PDX models from n=100 GC tumors and compared their characteristics to GC patient tumors based on the recent work done by ACRG and TCGA, to evaluate the representativeness and relevance of the collection for drug testing. We show that MSI, CIN and MSS/TP53- tumors were preferentially established as PDX, while MSS/EMT and EBV not and that PDX models retained histology and molecular subtypes of parental tumors. By using synapse database, we identified 48 druggable alterations that could be investigated with the collection. Counting alterations for these 48 genes in PDX compared to TCGA tumors revealed models frequently classified with heavily altered tumors but well preserved genomic alteration patterns specific of each GC subtype. The molecular analysis of n=8/27 tumors and corresponding PDX at passage P1, P2 and P3 revealed variations in somatic alteration content both at single nucleotide and chromosomal level in highly unstable MSI and CIN tumors, with changes occurring mainly at P1. In two cases, we show likely emergence of rare subclones carrying known oncogenic alterations in KRAS and PIK3CA. Significance. This study presents a resource of fully annotated GC PDX models for anticancer agent testing. We show that beside close resemblance of PDX with parental tumors, not all subtypes are established, and that the clonal selection plays a key role the establishment of certain tumors. This may have a bearing on translation of observations into the clinic and underline the need to frequently survey the molecular characteristics of the PDX models.
2020-07-15 | GSE115637 | GEO
Project description:establishment of patient derived tumor xenografts from Asian gastric adenocarcinoma is driven by molecular selection with implications for anticancer agent testing
| PRJEB26640 | ENA
Project description:Gastric cancer is the most common cancer in Asia and most developing countries. To identify the molecular underpinnings of gastric cancer in the Asian population, we applied an RNA-sequencing approach to gastric tumor and noncancerous specimens to quantitatively characterize the entire transcriptome of gastric cancer (including mRNAs and microRNAs). A multi-layer analysis was then developed to identify multiple types of transcriptional aberrations associated with different stages of gastric cancer, including differentially expressed mRNAs, recurrent somatic mutations and key differentially expressed microRNAs. Through this approach, we identified the central metabolic regulator AMPK-α as a potential functional target in Asian gastric cancer. Further, we experimentally demonstrated the translational relevance of this gene as a potential therapeutic target for early-stage gastric cancer in Asian patients. Together, our findings not only provide a valuable information resource for identifying and elucidating the molecular mechanisms of Asian gastric cancer, but also represent a general integrative framework to develop more effective therapeutic targets.
2012-04-03 | GSE36968 | GEO
Project description:Osteosarcoma (OS) and Ewing’s sarcoma (EW) are the two most common pediatric solid tumors, after brain tumors. Multimodal treatments have significantly improved prognosis in localized disease but outcome is still poor in metastatic patients, for whom therapeutic options are often inadequate. Preclinical drug testing to identify promising treatment options that match the molecular make-up of these tumors is hampered by the lack of appropriate and molecularly well-characterized patient-derived models. To address this need, a panel of patient-derived xenografts (PDX) was established by subcutaneous implantation of fresh, surgically resected OS and EW tumors in NSG mice. Tumors were re-transplanted to next mice generations and fragments were collected for histopathological and molecular characterization. A model was considered established after observing stable histological and molecular features for at least three passages. To evaluate the similarity of the model with primary tumor, we performed a global gene expression profiling and tissue microarrays (TMA), to assess tumor specific biomarkers on tissues from OS/EW tumors and their PDXs (1st and 3rd passage). Moreover, we verified the feasibility of these models for preclinical drug testing. We implanted 61 OS and 29 EW samples: 14/38 (37%) primary OS and 9/23 (39%) OS lung metastases successfully engrafted; while among EW, 5/26 (19%) primary samples and 1/3 (33%) metastases were established. Comparison between patient samples and PDXs, highlighted that histology and genetic characteristics of PDXs were stable and maintained over passages. In particular, correlative analysis between OS and EW samples and their PDXs was extremely high (Pearson’s r range r=0.94-0.96), while patient-derived primary cultures displayed reduced correlation with human samples (r=0.90-0.93), indicating that in vitro adaptation superimpose molecular alterations that create genetic diversion from original tumors. No significant differentially expressed gene profile was observed from the comparison between EW samples and PDXs (fold change > 2, adjusted p <0.05 at paired t-test). In OS, the comparison between OS patient-derived tumors and PDX indicated differences in 397 genes, mostly belonging to immune system functional category. This is in line with the idea that human immune cells are gradually replaced by murine counterparts upon engraftment in the mouse. As proof-of concept, two EW PDX and one OS PDX have been treated with conventional and innovated drugs to test their value in terms of drug-sensitivity prediction. Overall, our study indicated that PDX models maintained the histological and genetic markers of the tumor samples and represent reliable models to test sensitivity to novel drug associations.
2019-08-27 | E-MTAB-7568 | biostudies-arrayexpress
Project description:Gastric cancer is the most common cancer in Asia and most developing countries. To identify the molecular underpinnings of gastric cancer in the Asian population, we applied an RNA-sequencing approach to gastric tumor and noncancerous specimens to quantitatively characterize the entire transcriptome of gastric cancer (including mRNAs and microRNAs). A multi-layer analysis was then developed to identify multiple types of transcriptional aberrations associated with different stages of gastric cancer, including differentially expressed mRNAs, recurrent somatic mutations and key differentially expressed microRNAs. Through this approach, we identified the central metabolic regulator AMPK-M-NM-1 as a potential functional target in Asian gastric cancer. Further, we experimentally demonstrated the translational relevance of this gene as a potential therapeutic target for early-stage gastric cancer in Asian patients. Together, our findings not only provide a valuable information resource for identifying and elucidating the molecular mechanisms of Asian gastric cancer, but also represent a general integrative framework to develop more effective therapeutic targets. Using Life Technologies SOLiDM-bM-^DM-" sequencing platform, we performed transcriptome-wide profiling of gastric cancer samples from 30 anonymous, unrelated Asians of both sexes. Included were six noncancerous gastric tissue samples and 24 gastric tumor samples that represented stages I through IV of tumor development. From the WT-seq protocol we generated a WT-seq dataset of 2.1 billion 50-nt short reads from the 30 samples; Applying the second small RNA-seq protocol to 19 gastric tumor samples (5 of the original 24 yielded insufficient sample amounts) and 6 noncancerous gastric tissue samples resulted in a small RNA-seq dataset.
2012-04-03 | E-GEOD-36968 | biostudies-arrayexpress
Project description:Gastric cancer (GC) is the world's third leading cause of cancer mortality. In spite of significant therapeutic improvement, the clinical outcome for patients with advanced GC is poor; thus, the identification and validation of novel targets is extremely important from a clinical point of view. We generated a wide, multi-level platform of GC models, comprising 100 Patient-derived xenografts (PDXs), primary cell lines and organoids. Samples were classified according to their histology, microsatellite stability (MS) and Epstein-Barr virus status, and molecular profile. This PDX platform is the widest in an academic institution and it includes all the GC histologic and molecular types identified by TCGA. PDX histopathological features were consistent with those of patients’ primary tumors and were maintained throughout passages in mice. Factors modulating grafting rate were histology, TNM stage, copy number variation of tyrosine kinases/KRAS genes and MSI status. PDX and PDX-derived cells/organoids demonstrated potential usefulness to study targeted therapy response. Finally, PDX transcriptomic analysis identified a cancer cell intrinsic MSI signature, which was efficiently exported to gastric cancer, allowing the identification -among MSS patients- of a subset of MSI-like tumors with common molecular assets and significant better prognosis. We generated a wide gastric cancer PDX platform, whose exploitation will help identify and validate novel 'druggable' targets and define the best therapeutic strategies. Moreover, transcriptomic analysis of GC PDXs allowed the identification of a cancer cell intrinsic MSI signature, recognizing a subset of MSS patients with MSI transcriptional traits, endowed with better prognosis.
2019-10-15 | GSE128459 | GEO
Project description:The interaction between cancer and depressive disorder remains unclear. In this study, we obtained patient data from TCGA and MDD-related (Major Depressive Disorder) genes from the GEO database and the sequencing data of the PDX model with chronic unpredictable stress (CUS). Molecular subtypes and a prognostic signature were generated based on the MDD-related genes obtained by differential expression analysis. According to our analysis, the gene signature was a promising biomarker in distinguishing the prognosis, the molecular or immune characteristics, and the depressive risk, as well as the therapy candidates for gastric adenocarcinoma patients.
2024-07-19 | GSE262056 | GEO
Project description:Genome-wide mRNA expression profiles of 70 primary gastric tumors from the Australian patient cohort. Like many cancers, gastric adenocarcinomas (gastric cancers) show considerable heterogeneity between patients. Thus, there is intense interest in using gene expression profiles to discover subtypes of gastric cancers with particular biological properties or therapeutic vulnerabilities. Identification of such subtypes could generate insights into the mechanisms of cancer progression or lay the foundation for personalized treatments. Here we report a robust gene-xpression-based clustering of a large collection of gastric adenocarcinomas from Singaporean patients [GSE34942 and GSE15459]. We developed and validated a classifier for the three subtypes in Australian patient cohort. Profiling of 70 primary gastric tumors on Affymetrix GeneChip Human Genome U133 Plus 2.0 Array. All tumors were collected with approvals from Peter MacCallum Cancer Center, Australia; the Research Ethics Review Committee; and signed patient informed consent.
2012-07-04 | E-GEOD-35809 | biostudies-arrayexpress