Assessment of targeted therapy opportunities in sinonasal cancers using patient-derived functional tumor models
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PROVIDER: PRJEB69277 | ENA |
REPOSITORIES: ENA
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Project description:Malignant tumors derived from the epithelium lining the nasal cavity region are termed sinonasal cancers, a highly heterogeneous group of rare tumors accounting for 3 - 5 % of all head and neck cancers. Progress with next-generation molecular profiling has improved our understanding of the complexity of sinonasal cancers and resulted in the identification of an increasing number of distinct tumor entities. Despite these significant developments, the treatment of sinonasal cancers has hardly evolved since the 1980s, and an advanced sinonasal cancer presents a poor prognosis as targeted therapies are usually not available. To gain insights into potential targeted therapeutic opportunities, we performed a multiomics profiling of patient-derived functional tumor models to identify molecular characteristics associated with pharmacological responses in the different subtypes of sinonasal cancer.MethodsPatient-derived ex vivo tumor models representing four distinct sinonasal cancer subtypes: sinonasal intestinal-type adenocarcinoma, sinonasal neuroendocrine carcinoma, sinonasal undifferentiated carcinoma and SMARCB1 deficient sinonasal carcinoma were included in the analyses. Results of functional drug screens of 160 anti-cancer therapies were integrated with gene panel sequencing and histological analyses of the tumor tissues and the ex vivo cell cultures to establish associations between drug sensitivity and molecular characteristics including driver mutations.ResultsThe different sinonasal cancer subtypes display considerable differential drug sensitivity. Underlying the drug sensitivity profiles, each subtype was associated with unique molecular features. The therapeutic vulnerabilities correlating with specific genomic background were extended and validated with in silico analyses of cancer cell lines representing different human cancers and with reported case studies of sinonasal cancers treated with targeted therapies.ConclusionThe results demonstrate the importance of understanding the differential biology and the molecular features associated with the different subtypes of sinonasal cancers. Patient-derived ex vivo tumor models can be a powerful tool for investigating these rare cancers and prioritizing targeted therapeutic strategies for future clinical development and personalized medicine.
| S-EPMC10973676 | biostudies-literature
Project description:Using NGS-based miRNome, followed by AGO2-RIP-seq, the miR-34c and miR-449a and their direct targets were identified as factors involved in the development and progression of sinonasal cancers (SNCs). Both miR-34c and miR-449a were independent prognostic biomarkers and were associated with patient outcome.
2023-12-28 | GSE192595 | GEO
Project description:Using NGS-based miRNome, followed by AGO2-RIP-seq, the miR-34c and miR-449a and their direct targets were identified as factors involved in the development and progression of sinonasal cancers (SNCs). Both miR-34c and miR-449a were independent prognostic biomarkers and were associated with patient outcome.
2023-12-28 | GSE192594 | GEO
Project description:Epithelial, non-glandular sinonasal cancers (SNCs) is a rare disease, with a global dismal prognosis. There are no recognized targeted treatments and the knowledge of molecular mechanisms involved in the resistance to available therapies is limited. Dissecting the heterogeneity of paranasal sinus cancersSNCs and providing valuable information on the biology of the malignancy is eagerly needed to improve therapeutic approaches.
2019-12-26 | GSE118386 | GEO
Project description:The diagnosis of sinonasal tumors is challenging due to a heterogeneous spectrum of various differential diagnoses as well as poorly defined, disputed entities such as sinonasal undifferentiated carcinomas (SNUCs). In this study, we apply machine learning algorithm based on DNA methylation patterns to classify sinonasal tumors with clinical-grade reliability. We further show that sinonasal tumors with SNUC morphology are not as undifferentiated as their current terminology suggests but rather reassigned to four distinct molecular classes defined by epigenetic, mutational and proteomic profiles. This includes two classes with neuroendocrine differentiation, characterized by IDH2 or SMARCA4/ARID1A mutations with an overall favorable clinical course, whereas tumors that are driven by SMARCB1-deficiency and tumors that represent previously misclassified adenoid cystic carcinomas are highly aggressive. Our findings have the potential to dramatically improve the diagnostic classification of sinonasal tumors and will fundamentally change the current perception of SNUCs.
2022-09-25 | GSE196227 | GEO
Project description:Comparative analysis of gene expression in murine sinonasal mucosa in wild-type and CC10-knockout littermates with allergic eosinophilic chronic rhinosinusitis. The data provide a comprehensive overview of genes expressed in the mouse sinonasal mucosa and show that the expression of several known and unidentified genes is modified by disruption of the CC10 gene. Total RNA isolated from sinonasal mucosae of 6- to 8-week-old mice, C57BL/6 strain, was used for this comparison. Three groups: wild-type control, wild-type with allergic eosinophilic chronic rhinosinusitis, and CC10-knockout with allergic eosinophilic chronic rhinosinusitis.
2010-12-01 | E-GEOD-20969 | biostudies-arrayexpress
Project description:The histopathological diagnosis of sinonasal tumors is challenging as it encompasses a heterogeneous spectrum of various differential diagnoses as well as poorly defined, disputed entities such as sinonasal undifferentiated carcinomas (SNUCs). In this study, we show that a machine learning algorithm based on DNA methylation is able to classify sinonasal tumors with clinical-grade reliability. We further show that tumors with SNUC morphology are not as undifferentiated as their current terminology suggests, but can be assigned to four molecular classes defined by distinct epigenic, mutational and proteomic profiles. This includes two classes with neuroendocrine differentiation, characterized by IDH2 or SWI/SNF chromatin remodeling complex mutations and overall favorable clinical course, highly aggressive tumors that are driven by SMARCB1-deficiency and tumors that represent previously misclassified adenoid-cystic carcinomas. Our findings have the potential to dramatically improve the diagnostic of challenging sinonasal tumors and could fundamentally change the current perception of SNUCs.
2022-09-25 | GSE189778 | GEO
Project description:Human sinonasal cavity Targeted loci environmental
| PRJNA407725 | ENA
Project description:Comparative analysis of gene expression in murine sinonasal mucosa in wild-type and CC10-knockout littermates with allergic eosinophilic chronic rhinosinusitis. The data provide a comprehensive overview of genes expressed in the mouse sinonasal mucosa and show that the expression of several known and unidentified genes is modified by disruption of the CC10 gene.
2010-12-01 | GSE20969 | GEO
Project description:Transcriptional profiling of ethmoïd tumors samples comparing normal samples from the controlateral sinus. RNA were extracted from biopsies. Sinonasal adenocarcinomas are uncommon tumors developping in ethmoid sinus after wood dust exposure. Although the etiology of these tumors is well defined very little is known regarding the molecular basis of these tumors. In an attempt to identify genes involved in this disease we proceed to a gene expression profiling using cancer-dedicated microarrays, on matched samples of nine sinonasal adenocarcinomas and non-tumoral sinusal tissue. Among the genes with significant differential expression we selected: LGALS4, ACS5, CLU, BAX, PDGFRa, SRI and CCT5 for further exploration by quantitative real-time reverse-transcription-PCR on a larger set of tumors and confirmed the microarray data. Protein expression alterations were shown for LGALS4, ACS5, and CLU by immunohistochemistry. Our results suggest that two genes might be involved in the pathogenesis of these tumors: LGALS4 highly up-regulated, particularly in the most differentiated tumors, and CLU, whose expression was lost. After further evaluation these genes could be used as markers for a better characterization of these tumors and will potentially help to an earlier detection of cancer in woodworkers, who have high risk of developing sinonasal adenocarcinomas.
2009-07-31 | GSE17433 | GEO