The Genetic Landscape of Metastasis and Recurrence in HNSCC
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA299345 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:<p>Recurrence and/or metastasis occur in more than half of patients with head and neck squamous cell carcinoma (HNSCC) and pose the greatest threats to long-term survival. The genetic alterations underlying recurrent/metastatic HNSCC are unknown. This study represents the first whole exome sequencing (WES) cohort study of patient-matched tumor pairs in recurrent or metastatic HNSCC. Synchronous lymph node metastases are genetically more similar to their paired index primary tumors than metachronous recurrent tumors are. Newly arisen mutations in recurrent or metastatic tumors, may have therapeutic implications. Several genes were found to be mutated in multiple metastatic or recurrent tumors, but not in their respective primaries, including C17orf104, ITPR3, and DDR2. DDR2 mutations have been shown to confer enhanced sensitivity to Src-family kinase (SFK) inhibitors in other malignancies. Similarly, we found HNSCC cell lines harboring endogenous and engineered DDR2 mutations to be more sensitive to the SFK inhibitor dasatinib, than those with WT DDR2. This study outlines the first compendium of somatic mutations in primary, metastatic and/or recurrent HNSCC cancers that arise in individual patients; and demonstrates how such data can be used to interrogate potential predictive/prognostic biomarkers to inform and guide personalized therapy.</p>
| phs001007 | dbGaP
Project description:The risk of locoregional or distant failure in advanced HPV-negative head and neck squamous cell carcinoma (HNSCC) patients is high. However, no suitable markers for stratification are clinically available. Thus, we aimed to identify a microRNA(miRNA)-signature predicting disease recurrence. For this purpose the miRNA profiles from 162 HNSCC samples were analysed with regard to identification of a low-complex porgnostic signature. The data set consists of a discovery dataset (n=85) and a validation dataset (n=77). The study resulted in a prognostic 5-miRNA signature significantly predicting the relevant clinical endpoint freedom from recurrence.
2018-09-06 | E-MTAB-5793 | biostudies-arrayexpress
Project description:The Genetic Landscape of Metastasis and Recurrence in HNSCC
| PRJNA299346 | ENA
Project description:Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer in the world. Its mortality rate is high, and metastasis is one of the main reasons for the poor prognosis. Therefore, it is quite urgent to elucidate the mechanism of HNSCC metastasis and to discover valuable therapeutic targets. Circular RNAs (circRNAs) have been characterized as key regulators of gene expression in numerous malignances. However, the role of circRNAs in HNSCC metastasis remains largely unknown. In this study, circRFWD3, was defined. We demonstrated a novel circRNA, circRFWD3, was significantly upregulated in HNSCC tissues and cell lines by circRNA microarray analysis and qPCR. Notably, high expression of circRFWD3 is related to highly aggressive HNSCC cell lines and lymph node metastasis in HNSCC patients. After that, Sanger sequencing, RNase R and actinomycin D assay were performed to verify the ring structure of circRFWD3. Then functional experiments found it could promote the metastasis of HNSCC cells both in vitro and in vivo. Mechanistically, dual luciferase reporter assay, FISH, RIP, RNA pull-down, RNA-seq and western blot experiments were employed, and found that circRFWD3 served as a miRNAs sponge for miR-27a/27b, leading to upregulation of PPARγ, and then activate NF-κB/MMP13 signaling. Finally, ISH and IHC were carried out to determine the expression levels and clinical significances of circRFWD3 and PPARγ in clinical cohorts of HNSCC. According to the analysis results from two independent HNSCC cohorts, upregulated expression of circRFWD3 and PPARγ were positively associated with worse survival in patients with HNSCC. Overall, our results uncover that circRFWD3 acts a critical role in promoting the aggressiveness of HNSCC cells and is a prognostic marker for the disease, indicating that circRFWD3 may act as a potential therapeutic target in HNSCC. CircRNA microarray analysis of HNSCC
2023-11-29 | GSE200946 | GEO
Project description:Epigenetic Landscape of Pediatric Ependymoma Recurrence
| PRJNA658524 | ENA
Project description:60 fresh frozen HNSCC from the University of North Carolina at Chapel Hill (UNC) were obtained from the UNC Tissue Procurement Facility under an IRB approved protocol. 55 tumor samples were collected from the primary tumor and five tumor samples were collected from a local recurrence at the primary site; one tumor also had a sample of the primary tumor and an associated lymph node metastasis . In addition, we profiled three normal tonsillar epithelium samples that were collected from three pediatric patients following routine tonsillectomy and four HNSCC tumor derived cell lines (UNC7, UMSCCA1, CAL27 and JHU022). Each experimental sample (tumor, normal or cell line) was assayed versus a â??common referenceâ?? sample that was a pool of total RNA derived from 30 of the HNSCC samples. This tumor pool reference strategy has been successfully used in another profiling study. In total, 78 experiments were performed, which utilized three separate preparations of the common reference pool. Keywords = Head and neck cancer Keywords = gene expression profiles Keywords = microarray
2010-06-09 | E-GEOD-686 | biostudies-arrayexpress
Project description:This SuperSeries is composed of the following subset Series:; GSE17536: Metastasis Gene Expression Profile Predicts Recurrence and Death in Colon Cancer Patients (Moffitt Samples); GSE17537: Metastasis Gene Expression Profile Predicts Recurrence and Death in Colon Cancer Patients (VMC Samples) Experiment Overall Design: Refer to individual Series
2009-11-23 | E-GEOD-17538 | biostudies-arrayexpress
Project description:Background and Aims: Staging inadequately predicts metastatic risk in colon cancer patients. We used a gene expression profile derived from invasive murine colon cancer cells that were highly metastatic in an immunocompetent mouse model to identify colon cancer patients at risk for recurrence in a phase I, exploratory biomarker study. Methods: 55 colorectal cancer patients from Vanderbilt Medical Center (VMC) were used as the training dataset and 177 patients from the Moffitt Cancer Center were used as the independent dataset. The metastasis-associated gene expression profile developed from the mouse model was refined using comparative functional genomics in the VMC gene expression profiles to identify a 34-gene classifier associated with high risk of metastasis and death from colon cancer. A recurrence score derived from the biologically based classifier was tested in the Moffitt dataset. Results: A high score was significantly associated with increased risk of metastasis and death from colon cancer across all pathological stages and specifically in stage II and stage III patients. The recurrence score was shown to independently predict risk of cancer recurrence and death in both univariate and multivariate models. For example, among stage III patients, a high score translated to increased relative risk for cancer recurrence (hazard ratio = 4.7 (95% CI=1.566-14.05)). Furthermore, the recurrence score identified stage III patients whose five-year recurrence-free survival was >88% and for whom adjuvant chemotherapy did not provide improved survival. Conclusion: Our biologically based gene expression profile yielded a potentially useful classifier to predict cancer recurrence and death independently of conventional measures in colon cancer patients. Experiment Overall Design: Gene expression array differences between highly invasive mouse colon cancer cells and non-invasive colon cancer cells were used to develop a metastasis gene expression profile. It was refined using gene expression data from 55 patient (VMC) samples and trained using 177 patient (Moffitt) samples.
2009-12-02 | E-GEOD-17537 | biostudies-arrayexpress
Project description:Head and neck squamous cell carcinoma (HNSCC) is the 6th most common cancer worldwide and the human papillomavirus (HPVP+P)-driven subtype is the fastest rising in North America. Although most cases of HPV+ HNSCC respond to radiation and chemotherapy in combination with surgery, up to 20% of patients recur after primary treatment with poor prognosis. To gain insights into the mechanism of recurrence to inform patient stratification and precision treatment, we carried out RNA-seq analysis on 43 HPV+ HNSCC specimens, of which 15, including 7 recurrent tumors, were analyzed by quantitative mass spectrometry. The proteome and phosphoproteome, but not the transcriptome, were found to be distinct between the recurrent and non-recurrent tumors. Specifically, recurrent tumors featured a pro-fibrotic and immune suppressive tumor microenvironment (TME) characterized with more abundant cancer associated fibroblasts, extracellular matrix (ECM), neutrophils and suppressive myeloid cells, increased potential for epithelial-mesenchymal transition and defective T cell function, accompanied by aberrant changes in the corresponding signaling pathways. Mechanistically, kinome reprogramming played a pivotal role in mediating recurrence through regulating TME remodelling, cytoskeletal reorganization, cell adhesion, neutrophil function, and coagulation. Besides providing systems-level insights into the molecular basis of recurrence, our work led to the identification of numerous mechanism-based biomarkers and therapeutic targets that may aid future endeavours of developing prognostic biomarkers and precision medicine for recurrent HPV+ HNSCC.
2022-06-01 | PXD030343 | Pride
Project description:A classifier was build on 82 training samples to differentiate between lymph node negative (N0) and lymph node metastasis (N+) head and neck squamous-cell carcinomas (HNSCC). The 102 predictor genes that resulted from this classifier where then validated against a independent validation set.
2005-01-09 | E-UMCU-11 | biostudies-arrayexpress