scholarly journals P13.10 Glioblastoma within the subventricular zone associates with increased mesenchymal transition: an intratumoral gene expression analysis

2019 ◽  
Vol 21 (Supplement_3) ◽  
pp. iii64-iii64
Author(s):  
S Berendsen ◽  
D Dalemans ◽  
K Draaisma ◽  
P A Robe ◽  
T J Snijders

Abstract BACKGROUND Involvement of the subventricular zone (SVZ) in GBM is associated with poor prognosis and suggested to associate with specific tumor-biological characteristics. The SVZ microenvironment can influence gene expression and migration in GBM cells in preclinical models. We aimed to investigate whether the SVZ microenvironment has any influence on intratumoral gene expression patterns in GBM patients. MATERIAL AND METHODS The publicly available Ivy GBM database contains clinical, radiological and whole exome sequencing data from multiple regions from en bloc resected GBMs. SVZ involvement of the various tissue samples was evaluated on MRI scans. In the tumors that contacted the SVZ, we performed gene expression analyses and gene set enrichment analyses to compare gene (set) expression in tumor regions within the SVZ to tumor regions outside the SVZ, within the same tumors. We also compared these samples to GBMs that made no contact with the SVZ. RESULTS Within GBMs that contacted the SVZ, tissue samples within the SVZ showed enrichment of gene sets involved in (epithelial-)mesenchymal transition, NF-κB and STAT3 signaling, angiogenesis and hypoxia, compared to the samples outside of the SVZ region from the same tumors (p<0.05, FDR<0.25). Comparison of GBM samples within the SVZ region to samples from tumors that did not contact the SVZ yielded similar results. In contrast, we observed no difference in gene set enrichment when comparing the samples outside of the SVZ from SVZ-contacting GBMs with samples from GBMs that did not contact the SVZ at all. CONCLUSION GBM samples in the SVZ region associate with increased (epithelial-)mesenchymal transition and angiogenesis/hypoxia signaling, possibly mediated by the SVZ microenvironment.

Cancers ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 3764
Author(s):  
Diana J. Z. Dalemans ◽  
Sharon Berendsen ◽  
Kaspar Draaisma ◽  
Pierre A. Robe ◽  
Tom J. Snijders

Background: Involvement of the subventricular zone (SVZ) in glioblastoma is associated with poor prognosis and is associated with specific tumor-biological characteristics. The SVZ microenvironment can influence gene expression in glioblastoma cells in preclinical models. We aimed to investigate whether the SVZ microenvironment has any influence on intratumoral gene expression patterns in glioblastoma patients. Methods: The publicly available Ivy Glioblastoma database contains clinical, radiological and whole exome sequencing data from multiple regions from resected glioblastomas. SVZ involvement of the various tissue samples was evaluated on MRI scans. In tumors that contacted the SVZ, we performed gene expression analyses and gene set enrichment analyses to compare gene (set) expression in tumor regions within the SVZ to tumor regions outside the SVZ. We also compared these samples to glioblastomas that did not contact the SVZ. Results: Within glioblastomas that contacted the SVZ, tissue samples within the SVZ showed enrichment of gene sets involved in (epithelial-)mesenchymal transition, NF-κB and STAT3 signaling, angiogenesis and hypoxia, compared to the samples outside of the SVZ region from the same tumors (p < 0.05, FDR < 0.25). Comparison of glioblastoma samples within the SVZ region to samples from tumors that did not contact the SVZ yielded similar results. In contrast, we observed no differences when comparing the samples outside of the SVZ from SVZ-contacting glioblastomas with samples from glioblastomas that did not contact the SVZ at all. Conclusion: Glioblastoma samples in the SVZ region are enriched for increased (epithelial-)mesenchymal transition and angiogenesis/hypoxia signaling, possibly mediated by the SVZ microenvironment.


Author(s):  
VG LeBlanc ◽  
D Trinh ◽  
M Hughes ◽  
I Luthra ◽  
D Livingstone ◽  
...  

Glioblastomas (GBMs) account for nearly half of all primary malignant brain tumours, and current therapies are often only marginally effective. Our understanding of the underlying biology of these tumours and the development of new therapies have been complicated in part by widespread inter- and intratumoural heterogeneity. To characterize this heterogeneity, we performed regional subsampling of primary glioblastomas and derived organoids from these tissue samples. We then performed single-cell RNA-sequencing (scRNA-seq) on these primary regional subsamples and 1-3 matched organoids per sample. We have profiled samples from six tumour sets to date and have obtained sequencing data for 21,234 primary tissue cells and 14,742 organoid cells. While the most apparent differences in gene expression appear to be between individual tumours, we were also able to identify similar cellular subpopulations across tissue samples and across organoids. Importantly, organoids derived from the same tissue sample appeared to be composed of similar cellular subpopulations and were highly comparable to each other, indicating that replicate organoids faithfully represent the original tumour tissue. Overall, our scRNA-seq approach will help evaluate the utility of tumour-derived organoids as model systems for GBM and will aid in identifying cellular subpopulations defined by gene expression patterns, both in primary GBM regional subsamples and their associated organoids. These analyses will allow for the characterization of clonal or subclonal populations that are likely to respond to different therapeutic approaches and may also uncover novel therapeutic targets previously unrevealed through bulk analyses.


Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 1402-1402 ◽  
Author(s):  
Haitham Abdelhakim ◽  
Ahmad Elkhanany ◽  
Mohammad Telfah ◽  
Tara L. Lin ◽  
Andrew K Godwin

Background: Mutations in the nucleophosmin (NPM1) gene are associated with better responses to chemotherapy and improved survival among acute myeloid leukemia (AML) patients. However, older AML patients (≥ 60 years old) with NPM1 mutation have worse survival outcomes than younger patients (&lt;60 years old). This may be attributed to more adverse biologic features (frequent complex karyotype, FLT3 mutations) in addition to lower odds to receive intensive curative chemotherapy due to co-morbidities. We sought to compare the outcomes of older NPM1 mutated AML patients with younger NPM1 mutated patients after exclusions of patients with adverse-risk per ELN 2017 criteria. We also compared their genomic mutation profile and gene expression utilizing the Beat AML dataset. Methods: We queried the Beat AML dataset, supported in part by the Leukemia & Lymphoma Society and the OHSU Knight Cancer Institute, for pts with NPM1 gene mutations who did not have adverse-risk ELN 2017 (poor cytogenetic profile or mutations in FLT3, TP53 or ASXL1). Descriptive statistics described baseline characteristics and responses. Kaplan-Meier with log-rank test was used for survival analysis. DNA mutation data were obtained from the exome sequencing and analyzed using the beat AML data viewer (Vizome). RNA exome sequencing data were downloaded. Differential expression of raw count RNA-Seq and gene set enrichment was done using R via limma and ClusterProfiler packages. Results: Among 562 unique patients in the Beat AML umbrella trial, there were 81 patients with newly diagnosed NPM1 mutated AML after exclusion of patients with ELN 2017 adverse-risk category. Among these patients there was 49 older patients (≥ 60 years old) and 32 younger patients (&lt;60 years old). 39 (77.6%) in the older group received intensive induction chemotherapy and 30 patients (93.7%) in the younger group. 29 (59.1%) patients achieved complete morphologic responses in the older patient group compared to 28 (84.4%) in the younger patient group (OR 0.2, P=0.009). Median overall survival in the older patient group was 20.1 months compared to 25.4 months in the younger group (HR 0.52, P=0.08). Exome sequencing data were available for 43 and 30 patients from the older and younger group respectively. There was a median of 6.5 (2-20) and 7 (2-19) mutations in the older and younger group respectively (P=0.78). After exclusion of the benign mutations and variant of unknown significance, the median number of mutations was 4 in both group (P=0.28). Both groups shared only 24 (3.9%) of the gene mutations while there were 334 unique gene mutations in the older group and 262 in the younger group. Most common gene mutations were DNMT3a, TET2, NRAS, WT1, and PTPN11 with frequencies are shown (Figure 1). RNA sequencing data was available for 26 patients from the older group and 18 patients from the younger group. We explored the gene expression profile of the top 1000 differentially expressed genes in both groups after adjustment. There was distinctive clustering of the gene expression profile between the two groups (Figure 2). Gene set enrichment analysis identified multiple immune-related pathways among the highly enriched gene sets in both groups but with different functions in the two groups. There was significant gene set enrichment in the TGFβ signaling in the older patient group which is associated with immune suppression and microenvironment modulation. While the younger group showed significant enrichment in the TNFa, IL17, PI3K-AKT signaling which are associated with inflammation. Conclusion: Older AML patients with NPM1 mutations, and no adverse risk features, had lower rate of complete responses and a trend towards a worse survival compared to younger patients. Whole exome sequencing did not show increased mutational burden. However, 96% of the mutated genes were different between the two groups as were the gene expression profiles. Gene set enrichment analysis showed contrasting enriched immune-related pathways between both groups. The immunosuppressive TGFβ signaling gene set were significantly enriched in the older group while the inflammatory TNFa, IL17, PI3K-AKT signaling gene sets were significantly enriched in the younger group. Older AML patient with NPM1 mutations have distinctive genomic landscape compared to the younger patient which may explain in part the worse clinical outcomes in the absence of other adverse risk features. Disclosures Lin: Jazz Pharmaceuticals: Honoraria; Pfizer: Membership on an entity's Board of Directors or advisory committees.


2018 ◽  
Author(s):  
Dongya Jia ◽  
Jason T. George ◽  
Satyendra C. Tripathi ◽  
Deepali L. Kundnani ◽  
Mingyang Lu ◽  
...  

AbstractThe epithelial-mesenchymal transition (EMT) plays a central role in cancer metastasis and drug resistance – two persistent clinical challenges. Epithelial cells can undergo a partial or full EMT, attaining either a hybrid epithelial/mesenchymal (E/M) or mesenchymal phenotype, respectively. Recent studies have emphasized that hybrid E/M cells may be more aggressive than their mesenchymal counterparts. However, mechanisms driving hybrid E/M phenotypes remain largely elusive. Here, to better characterize the hybrid E/M phenotype(s) and tumor aggressiveness, we integrate two computational methods – (a) RACIPE – to identify the robust gene expression patterns emerging from the dynamics of a given gene regulatory network, and (b) EMT scoring metric - to calculate the probability that a given gene expression profile displays a hybrid E/M phenotype. We apply the EMT scoring metric to RACIPE-generated gene expression data generated from a core EMT regulatory network and classify the gene expression profiles into relevant categories (epithelial, hybrid E/M, mesenchymal). This categorization is broadly consistent with hierarchical clustering readouts of RACIPE-generated gene expression data. We show that the EMT scoring metric can be used to distinguish between samples composed of exclusively hybrid E/M cells and those containing mixtures of epithelial and mesenchymal subpopulations using the RACIPE-generated gene expression data.


2013 ◽  
Vol 31 (15_suppl) ◽  
pp. 3555-3555
Author(s):  
Kristen Keon Ciombor ◽  
Natasha G Deane ◽  
Keeli B Lewis ◽  
Xi Chen ◽  
Bing Zhang ◽  
...  

3555 Background: A more accurate method of identifying stage 2 and 3 colorectal cancer (CRC) patients at highest risk for recurrence after surgical resection is needed. Gene expression signatures utilizing microarray-derived gene expression data from fresh frozen primary CRCs to predict risk of recurrence have been developed by us and others. Advances in technology platforms for gene expression measurements and their applicability to formalin-fixed, paraffin-embedded (FFPE) specimens offer new opportunity to develop clinically useful diagnostics based on molecular profiles. Methods: 58 patient FFPE samples of all stages stored from 1-12 years were collected from the Vanderbilt GI SPORE Translational Pathology and Imaging Core and annotated with appropriate clinicopathologic data. 414 genes were selected from our 34-gene prognostic classifier and other published CRC gene signatures, as well as gene elements associated with intestinal stem cell biology and epithelial-to-mesenchymal transition (EMT). RNA was extracted from the tumors, and gene expression analysis was completed using the nCounterplatform. Results: Quality of extracted RNA from tumor blocks was similar among the tumors and adequate for analysis. No significant differences were seen in signal strength (p=0.94, Kruskal-Wallis test) or intra-class variation (correlation coefficient = 0.99) across material extracted from new and old blocks. Fold change values for the 70 most highly differentially expressed genes on the nCounter platform correlated well with Affymetrix U133 plus 2 microarray (R2=0.819). Genes associated with EMT clustered according to prognosis, with poorer prognoses seen in patients with high TWIST expression or low E-cadherin and SMAD4 expression. There was a trend toward better survival outcomes with high expression of E-cadherin and SMAD4 (p=0.072, log-rank test). Conclusions: This preliminary study demonstrates the feasibility of this approach to determine gene expression patterns in FFPE tumor tissue samples. Our data suggest that this approach may be applied to identify clinically applicable prognostic gene expression profiles that may be validated in archived patient samples that are well annotated with patient outcome data.


2009 ◽  
Vol 9 (3) ◽  
pp. 55-63 ◽  
Author(s):  
Wei Zhang ◽  
R. Stephanie Huang ◽  
Shiwei Duan ◽  
M. Eileen Dolan

2021 ◽  
Vol 11 ◽  
Author(s):  
Junqing Wu ◽  
Yue Huang ◽  
Chengxuan Yu ◽  
Xia Li ◽  
Limengmeng Wang ◽  
...  

Enchondroma (EC) is a common benign bone tumor. It has the risk of malignant transformation to Chondrosarcoma (CS). However, the underlying mechanism is unclear. The gene expression profile of EC and CS was obtained from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified using GEO2R. We conducted the enrichment analysis and constructed the gene interaction network using the DEGs. We found that the epithelial-mesenchymal transition (EMT) and the VEGFA-VEGF2R signaling pathway were more active in CS. The CD8+ T cell immunity was enhanced in CS I. We believed that four genes (MFAP2, GOLM1, STMN1, and HN1) were poor predictors of prognosis, while two genes (CAB39L and GAB2) indicated a good prognosis. We have revealed the mechanism in the tumor progression and identified the key genes that predicted the prognosis. This study provided new ideas for the diagnosis and treatment of EC and CS.


2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Wanting Song ◽  
Yi Bai ◽  
Jialin Zhu ◽  
Fanxin Zeng ◽  
Chunmeng Yang ◽  
...  

Abstract Background Gastric cancer (GC) represents a major malignancy and is the third deathliest cancer globally. Several lines of evidence indicate that the epithelial-mesenchymal transition (EMT) has a critical function in the development of gastric cancer. Although plentiful molecular biomarkers have been identified, a precise risk model is still necessary to help doctors determine patient prognosis in GC. Methods Gene expression data and clinical information for GC were acquired from The Cancer Genome Atlas (TCGA) database and 200 EMT-related genes (ERGs) from the Molecular Signatures Database (MSigDB). Then, ERGs correlated with patient prognosis in GC were assessed by univariable and multivariable Cox regression analyses. Next, a risk score formula was established for evaluating patient outcome in GC and validated by survival and ROC curves. In addition, Kaplan-Meier curves were generated to assess the associations of the clinicopathological data with prognosis. And a cohort from the Gene Expression Omnibus (GEO) database was used for validation. Results Six EMT-related genes, including CDH6, COL5A2, ITGAV, MATN3, PLOD2, and POSTN, were identified. Based on the risk model, GC patients were assigned to the high- and low-risk groups. The results revealed that the model had good performance in predicting patient prognosis in GC. Conclusions We constructed a prognosis risk model for GC. Then, we verified the performance of the model, which may help doctors predict patient prognosis.


Cancers ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 1090
Author(s):  
Hassan Sadozai ◽  
Animesh Acharjee ◽  
Thomas Gruber ◽  
Beat Gloor ◽  
Eva Karamitopoulou

Tumor budding is associated with epithelial-mesenchymal transition and diminished survival in a number of cancer types including pancreatic ductal adenocarcinoma (PDAC). In this study, we dissect the immune landscapes of patients with high grade versus low grade tumor budding to determine the features associated with immune escape and disease progression in pancreatic cancer. We performed immunohistochemistry-based quantification of tumor-infiltrating leukocytes and tumor bud assessment in a cohort of n = 111 PDAC patients in a tissue microarray (TMA) format. Patients were divided based on the ITBCC categories of tumor budding as Low Grade (LG: categories 1 and 2) and High Grade (HG: category 3). Tumor budding numbers and tumor budding grade demonstrated a significant association with diminished overall survival (OS). HG cases exhibit notably reduced densities of stromal (S) and intratumoral (IT) T cells. HG cases also display lower M1 macrophages (S) and increased M2 macrophages (IT). These findings were validated using gene expression data from TCGA. A published tumor budding gene signature demonstrated a significant association with diminished survival in PDAC patients in TCGA. Immune-related gene expression revealed an immunosuppressive TME in PDAC cases with high expression of the budding signature. Our findings highlight a number of immune features that permit an improved understanding of disease progression and EMT in pancreatic cancer.


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