CDK4 overexpression is a predictive biomarker for resistance to conventional chemotherapy in osteosarcoma patients
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE154540 | GEO | 2021/06/01
REPOSITORIES: GEO
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Project description:CDK4 overexpression is a predictive biomarker for resistance to conventional chemotherapy in osteosarcoma patients
| PRJNA646638 | ENA
Project description:The aim of this study was to identify molecular markers able to classify osteosarcoma patients as good or poor responders before therapy. Methods: Gene expression profiling of 20 non-metastatic high-grade osteosarcoma patients was performed using cDNA nylon microarray which contained 8,032 unique sequenced-verified cDNA clones, representing 5,776 distinct genes. Expression of selected genes was validated using RTQ-PCR. For correlated genes, corresponding proteins were explored. Immunohistochemistry (IHC) on sections of tissue microarrays (TMA) were performed on a cohort of 50 patients, out of which 30 were new patients. Furthermore, fluorescent in situ hybridization (FISH) was performed on gene which could not be tested using IHC. Results: We have found that HSD17B10 gene expression was upregulated in the group of poor responders and that IHC expression of HSD17B10 in biopsy done before treatment was correlated to response to chemotherapy in 50 patients. Other relevant results include correlation of IFITM2, IFITM3 and RPL8 gene expression to response to chemotherapy. RPL8 gene expression also had a prognostic value for event-free survival. Moreover, a significant statistical correlation was found between polysomy 8 of RPL8 and good response to chemotherapy. Conclusion: These data suggest that HSD17B10 gene may be a biological marker and a therapeutic target in conventional osteosarcoma. This study highlights the prognostic and the predictive value of RPL8. RPL8 and IFITM2 may be useful in the assessment of patients with osteosarcoma at diagnosis and for stratifying patients taking part in randomized trials. Keywords: Gene-expression profiling Gene expression profiling of 20 non-metastatic high-grade osteosarcoma patients was performed using spotted cDNA nylon membrane
2010-02-14 | E-GEOD-11127 | biostudies-arrayexpress
Project description:The aim of this study was to identify molecular markers able to classify osteosarcoma patients as good or poor responders before therapy. Methods: Gene expression profiling of 20 non-metastatic high-grade osteosarcoma patients was performed using cDNA nylon microarray which contained 8,032 unique sequenced-verified cDNA clones, representing 5,776 distinct genes. Expression of selected genes was validated using RTQ-PCR. For correlated genes, corresponding proteins were explored. Immunohistochemistry (IHC) on sections of tissue microarrays (TMA) were performed on a cohort of 50 patients, out of which 30 were new patients. Furthermore, fluorescent in situ hybridization (FISH) was performed on gene which could not be tested using IHC. Results: We have found that HSD17B10 gene expression was upregulated in the group of poor responders and that IHC expression of HSD17B10 in biopsy done before treatment was correlated to response to chemotherapy in 50 patients. Other relevant results include correlation of IFITM2, IFITM3 and RPL8 gene expression to response to chemotherapy. RPL8 gene expression also had a prognostic value for event-free survival. Moreover, a significant statistical correlation was found between polysomy 8 of RPL8 and good response to chemotherapy. Conclusion: These data suggest that HSD17B10 gene may be a biological marker and a therapeutic target in conventional osteosarcoma. This study highlights the prognostic and the predictive value of RPL8. RPL8 and IFITM2 may be useful in the assessment of patients with osteosarcoma at diagnosis and for stratifying patients taking part in randomized trials. Keywords: Gene-expression profiling
2010-02-15 | GSE11127 | GEO
Project description:Osteosarcoma is the most common malignancy of bone, and occurs most frequently in children and adolescents. Currently, the most reliable technique for prognostication is measuring histopathologic tumor necrosis following preoperative chemotherapy, and favourable prognosis is signified by 90% or greater estimated necrosis of the tumour. Neither genetic testing nor molecular biomarkers have been described for this tumour. We used the novel nanoString mRNA expression analysis system to analyzed total RNA from 35 flash-frozen sporadic paediatric osteosarcoma biopsy and resection specimens to quantify mRNA expression for 17 oncogenes and tumour suppressor genes. Three oncogenes, cell cycle regulator gene CDC5L, the RecQ DNA helicase gene RECQL4, and the cyclin-dependent kinase gene CDK4, were more highly expressed (p<0.05) in tumours which responded poorly to neoadjuvant chemotherapy. A similar trend (p<0.10) was identified for the osteoblast-specific transcription factor gene RUNX2. No statistically significant difference existed in comparing expression of CDC5L, RECQL4, CDK4, and RUNX2 between biopsy and resection samples. Additionally, analysis of expression data in the context of histological subtype yielded preliminary results for deducing molecular subtypes of osteosarcomas. Osteoblastic osteosarcomas possessed higher expression of CDKN1A, PTEN, and RUNX2 relative to their fibroblastic counterparts (p<0.05). This research study shows that CDC5L, RECQL4, and CDK4 tumour expression levels may be useful for identifying patients who may not benefit from the current standardized chemotherapy regimen. Total RNA was isolated from 52 pediatric osteosarcoma samples (prechemotherapy biopsies and resections), 3 osteosarcoma cell lines, and normal human osteoblasts. nanoString mRNA expression analysis was applied to samples split between 3 batches to compare samples based on clinical and pathologic data reports, and to compare samples with normal human osteoblasts. For 43 samples, there were complete data and the RNA was successfully assayed. Analysis was performed using R.
2016-03-15 | E-GEOD-45275 | biostudies-arrayexpress
Project description:Osteosarcoma is the most common malignancy of bone, and occurs most frequently in children and adolescents. Currently, the most reliable technique for prognostication is measuring histopathologic tumor necrosis following preoperative chemotherapy, and favourable prognosis is signified by 90% or greater estimated necrosis of the tumour. Neither genetic testing nor molecular biomarkers have been described for this tumour. We used the novel nanoString mRNA expression analysis system to analyzed total RNA from 35 flash-frozen sporadic paediatric osteosarcoma biopsy and resection specimens to quantify mRNA expression for 17 oncogenes and tumour suppressor genes. Three oncogenes, cell cycle regulator gene CDC5L, the RecQ DNA helicase gene RECQL4, and the cyclin-dependent kinase gene CDK4, were more highly expressed (p<0.05) in tumours which responded poorly to neoadjuvant chemotherapy. A similar trend (p<0.10) was identified for the osteoblast-specific transcription factor gene RUNX2. No statistically significant difference existed in comparing expression of CDC5L, RECQL4, CDK4, and RUNX2 between biopsy and resection samples. Additionally, analysis of expression data in the context of histological subtype yielded preliminary results for deducing molecular subtypes of osteosarcomas. Osteoblastic osteosarcomas possessed higher expression of CDKN1A, PTEN, and RUNX2 relative to their fibroblastic counterparts (p<0.05). This research study shows that CDC5L, RECQL4, and CDK4 tumour expression levels may be useful for identifying patients who may not benefit from the current standardized chemotherapy regimen.
2016-03-15 | GSE45275 | GEO
Project description:In osteosarcoma patients, the development of metastases, often to the lungs, is the most frequent cause of death. To improve this situation, a deeper understanding of the molecular mechanisms governing osteosarcoma development and dissemination and the identification of novel drug targets for an improved treatment are needed. Towards this aim, we characterized osteosarcoma tissue samples compared to primary osteoblast cells using Affymetrix HG U133A microarrays.
2010-06-30 | GSE14359 | GEO
Project description:In osteosarcoma patients, the development of metastases, often to the lungs, is the most frequent cause of death. To improve this situation, a deeper understanding of the molecular mechanisms governing osteosarcoma development and dissemination and the identification of novel drug targets for an improved treatment are needed. Towards this aim, we characterized osteosarcoma tissue samples compared to primary osteoblast cells using Affymetrix HG U133A microarrays. mRNA from 5 frozen conventional osteosarcoma and 4 osteosarcoma lung metastases tumor samples and mRNA from fresh primary osteoblast cells were extracted and hybridized to HG U133A microarrays.
2010-07-30 | E-GEOD-14359 | biostudies-arrayexpress
Project description:Focal adhesion kinase (FAK) is important for tumor cell survival and metastasis in various cancers. However, its expression and prognostic value in patients with metastatic osteosarcoma remain unknown. We investigated the expression of FAK and its phosphorylated form (pFAK-Y397) in osteosarcoma tissues from 53 patients by immunohistochemistry and evaluated their correlations with clinicopathologic characteristics and outcomes. The prognostic values were assessed using Kaplan-Meier survival and Cox regression analyses. Total FAK and pFAK-Y397 were overexpressed in 48 (90.6%) and 33 (62.3%) cases, respectively. pFAK-Y397 overexpression was correlated with poor histologic response after neoadjuvant chemotherapy in patients with osteosarcoma regardless of the presence of metastasis or not. Kaplan-Meier curve showed that patients with metastatic osteosarcoma with pFAK-Y397 overexpression had significantly worse overall survival (OS) than those with non-overexpression (P = 0.044). Multivariate Cox regression analysis confirmed pFAK-Y397 overexpression as an independent prognostic predictor for OS and post metastases OS (PMOS) (P = 0.017, P = 0.006, respectively). Age at diagnosis was also an independent indicator for PMOS (P = 0.003). However, total FAK expression was not correlated with any clinicopathologic characteristics or OS in patients with metastatic osteosarcoma. In conclusion, our findings identified FAK as a common aberrant protein overexpression in various subtypes of osteosarcoma. pFAK-Y397 overexpression can be used as a prognostic biomarker predicting poor OS for patients with metastatic osteosarcoma, and the expression of pFAK-Y397 differentiated good and poor responders to neoadjuvant chemotherapy.
| S-EPMC5573209 | biostudies-literature
Project description:Cyclin D-CDK4/6 are the first CDK complexes to be activated in G1 phase in response to oncogenic pathways. The specific CDK4/6 inhibitor PD0332991 (Palbociclib) was recently approved by the FDA to treat advanced ER+ breast tumors. Unfortunately, reliable predictive tools are lacking to identify potentially responsive or insensitive tumors. We have shown that the activating T172 phosphorylation of CDK4 is the central rate-limiting event that initiates the cell cycle decision and signals the presence of active CDK4. Here, we found that, in breast cancer cell lines, the CDK4 T172 phosphorylation best correlates with the sensitivity to PD0332991. Moreover, the modification profile of CDK4 differs among breast tumors and it associates with their subtypes and risk. A gene expression signature faithfully predicted CDK4 modification profiles in tumors and cell lines. This surrogate biomarker identifies tumors that are unlikely to respond to CDK4/6 inhibitors and could allow extending the indication of the drug to HER-2 positive and some basal-like tumors. Predictive tools to identify breast cancer patients sensitive to Pfizer's new drug targeting CDK4/6 are lacking. We correlated the sensitivity of breast cancer cell lines to the drug to their post-translational modification profile of CDK4 revealed by 2D SDS/poly-acrylamide gel electrophoresis followed by CDK4 immuno-detection and their gene expression profiles. we revealed that breast tumors display similar CDK4 post-translational modification profiles as cell lines and that a gene expression profile can be used to predict the CDK4 post-translational modification profile of a tumor or cell line and thereby its sensitivity to CDK4 inhibitor
2017-01-01 | GSE87007 | GEO
Project description:Cyclin D-CDK4/6 are the first CDK complexes to be activated in G1 phase in response to oncogenic pathways. The specific CDK4/6 inhibitor PD0332991 (Palbociclib) was recently approved by the FDA to treat advanced ER+ breast tumors. Unfortunately, reliable predictive tools are lacking to identify potentially responsive or insensitive tumors. We have shown that the activating T172 phosphorylation of CDK4 is the central rate-limiting event that initiates the cell cycle decision and signals the presence of active CDK4. Here, we found that, in breast cancer cell lines, the CDK4 T172 phosphorylation best correlates with the sensitivity to PD0332991. Moreover, the modification profile of CDK4 differs among breast tumors and it associates with their subtypes and risk. A gene expression signature faithfully predicted CDK4 modification profiles in tumors and cell lines. This surrogate biomarker identifies tumors that are unlikely to respond to CDK4/6 inhibitors and could allow extending the indication of the drug to HER-2 positive and some basal-like tumors. Predictive tools to identify breast cancer patients sensitive to Pfizer's new drug targeting CDK4/6 are lacking. We correlated the sensitivity of breast cancer cell lines to the drug to their post-translational modification profile of CDK4 revealed by 2D SDS/poly-acrylamide gel electrophoresis followed by CDK4 immuno-detection and their gene expression profiles. we revealed that breast tumors display similar CDK4 post-translational modification profiles as cell lines and that a gene expression profile can be used to predict the CDK4 post-translational modification profile of a tumor or cell line and thereby its sensitivity to CDK4 inhibitor
2017-01-01 | GSE87006 | GEO