scholarly journals Efficient molecular subtype classification of high-grade serous ovarian cancer

2015 ◽  
Vol 236 (3) ◽  
pp. 272-277 ◽  
Author(s):  
Huei San Leong ◽  
Laura Galletta ◽  
Dariush Etemadmoghadam ◽  
Joshy George ◽  
Martin Köbel ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Molecular Subtype ◽  
High Grade ◽  
Serous Ovarian Cancer ◽  
Subtype Classification

Dynamic of molecular subtypes of high‐grade serous ovarian cancer in paired primary and relapsed biopsies.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e17091-e17091
Author(s):  
Elena Ioana Braicu ◽  
Hagen Kulbe ◽  
Felix Dreher ◽  
Eliane T Taube ◽  
Frauke Ringel ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Clinical Outcome ◽  
Molecular Subtypes ◽  
Molecular Subtype ◽  
High Grade ◽  
Serous Ovarian Cancer ◽  
Microarray Gene Expression ◽  
Tissue Samples ◽  
Paired Samples ◽  
Nanostring Technology

e17091 Background: Previously four molecular subtypes of high grade serous ovarian cancer (HGSOC) with distinct biological features and clinical outcome have been described: C1 (mesenchymal), C2 (immunoreactive), C4 (differentiated), and C5 (proliferative). Using Nanostring technique and a minimal signature of 39 classifier genes could reproduce the subtypes identified by microarray gene expression profiling (Leong HS et al. Australian Ovarian Cancer Study. J Pathol. 2015). Methods: We characterized paraffin embedded tissue samples from 279 HGSOC patients for molecular subtypes, utilizing the 39 classifier signature and 9 control genes by Nanostring nCounter Analysis System. From 16 patients paired primary and relapsed samples were available. Only chemonaive primary HGSOC patients were included in the study. FFPEs and clinical data were provided by TOC ( www.toc-network.de ). For each sample, probability scores for the four molecular subtypes (C1, C2, C4, and C5) were calculated. The highest calculated score determined the most likely subtype of the tumor. Results: Of all analyzed primary tumor samples, 88 (31.5%) were classified as C1, 83 (29.8%), 53 (19.0%) and 55 (19.7%) as subtypes C2, C4 and C5, respectively. Our results confirmed data by the AOCS study, which described the distribution of HGSOC with 40.2% (C1), 22.5% (C2), 20.1% (C4) and 17.2% (C5), respectively. Within the paired samples, for 12 of the 16 patients dynamic changes in the molecular subtypes between primary and relapse occurred, while in the remaining 4 patients the phenotype was stable. Conclusions: Molecular subtypes of HGSOC using Nanostring technology with a small panel of classifier genes can be confirmed. Furthermore, the data showed that a change of the established molecular subtype might occur during the evolution of the disease, and therefore translate in a different clinical outcome.

scholarly journals The impact of stroma on the discovery of molecular subtypes and prognostic gene signatures in serous ovarian cancer

2018 ◽  
Author(s):  
Matthew Schwede ◽  
Levi Waldron ◽  
Samuel C. Mok ◽  
Wei Wei ◽  
Azfar Basunia ◽  
...  
Keyword(s):  
Gene Expression ◽  
Ovarian Cancer ◽  
Stromal Cells ◽  
Molecular Subtypes ◽  
Molecular Subtype ◽  
High Grade ◽  
Serous Ovarian Cancer ◽  
Gene Signatures ◽  
Prognostic Gene ◽  
Bulk Tissue

AbstractPurposeRecent efforts to improve outcomes for high-grade serous ovarian cancer, a leading cause of cancer death in women, have focused on identifying molecular subtypes and prognostic gene signatures, but existing subtypes have poor cross-study robustness. We tested the contribution of cell admixture in published ovarian cancer molecular subtypes and prognostic gene signatures.Experimental DesignPublic gene expression data, two molecular subtype classifications, and 61 published gene signatures of ovarian cancer were examined. Using microdissected data, we developed gene signatures of ovarian tumor and stroma. Computational simulations of increasing stromal cell proportion were performed by mixing gene expression profiles of paired microdissected ovarian tumor and stroma.ResultsEstablished ovarian cancer molecular subtypes are strongly associated with the cell admixture. Tumors were classified as different molecular subtypes in simulations, when the percentage of stromal cells increased. Stromal gene expression in bulk tumor was weakly prognostic, and in one dataset, increased stroma was associated with anatomic sampling location. Five published prognostic gene signatures were no longer prognostic in a multivariate model that adjusted for stromal content alone.ConclusionsThe discovery that molecular subtypes of high grade serous ovarian cancer is influenced by cell admixture, and stromal cell gene expression is crucial for interpretation and reproduction of ovarian cancer molecular subtypes and gene signatures derived from bulk tissue. Single cell analysis may be required to refine the molecular subtypes of high grade serous ovarian cancer. Because stroma proportion was weakly prognostic, elucidating the role of the tumor microenvironment’s components will be important.Translational relevanceOvarian cancer is a leading cause of cancer death in women in the United States. Although the tumor responds to standard therapy for the majority of patients, it frequently recurs and becomes drug-resistant. Recent efforts have focused on identifying molecular subtypes and prognostic gene signatures of ovarian cancer in order to tailor therapy and improve outcomes. This study demonstrates that molecular subtype identification depends on the ratio of tumor to stroma within the specimen. We show that the specific anatomic location of the biopsy may influence the proportion of stromal involvement and potentially the resulting gene expression pattern. It will be crucial for these factors to be taken into consideration when interpreting and reproducing ovarian cancer molecular subtypes and gene signatures derived using bulk tissue and single cells. Furthermore, it will be important to define the relative proportions of stromal cells and model their prognostic importance in the tumor microenvironment.

scholarly journals Factors that influence survival in high-grade serous ovarian cancer: A complex relationship between molecular subtype, disease dissemination, and operability

2018 ◽  
Vol 150 (2) ◽  
pp. 227-232 ◽  
Author(s):  
Diogo Torres ◽  
Chen Wang ◽  
Amanika Kumar ◽  
Jamie N. Bakkum-Gamez ◽  
Amy L. Weaver ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Molecular Subtype ◽  
High Grade ◽  
Complex Relationship ◽  
Serous Ovarian Cancer

scholarly journals Orthogonal Proteomic Platforms and Their Implications for the Stable Classification of High-Grade Serous Ovarian Cancer Subtypes

iScience ◽  
2020 ◽  
Vol 23 (6) ◽  
pp. 101079 ◽  
Author(s):  
Stefani N. Thomas ◽  
Betty Friedrich ◽  
Michael Schnaubelt ◽  
Daniel W. Chan ◽  
Hui Zhang ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
High Grade ◽  
Serous Ovarian Cancer ◽  
Cancer Subtypes ◽  
Stable Classification

scholarly journals High-dimensional analysis of the adenosine pathway in high-grade serous ovarian cancer

2021 ◽  
Vol 9 (3) ◽  
pp. e001965
Author(s):  
Yacine Bareche ◽  
Sandra Pommey ◽  
Mayra Carneiro ◽  
Laurence Buisseret ◽  
Isabelle Cousineau ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Molecular Subtype ◽  
Meta Analysis ◽  
Gene Signature ◽  
Immune Gene ◽  
Prognostic Impact ◽  
High Grade ◽  
Serous Ovarian Cancer ◽  
Platinum Based Chemotherapy ◽  
The Impact

BackgroundHydrolysis of extracellular ATP to adenosine (eADO) is an important immune checkpoint in cancer immunology. We here investigated the impact of the eADO pathway in high-grade serous ovarian cancer (HGSC) using multiparametric platforms.MethodsWe performed a transcriptomic meta-analysis of eADO-producing CD39 and CD73, an eADO signaling gene signature, immune gene signatures and clinical outcomes in approximately 1200 patients with HGSC. Protein expression, localization and prognostic impact of CD39, CD73 and CD8 were then performed on approximately 1000 cases on tissue microarray, and tumor-infiltrating lymphocytes (TILs) were analyzed by flow cytometry and single-cell RNA sequencing on a subset of patients.ResultsConcomitant CD39 and CD73 gene expression, as well as high levels of an eADO gene signature, were associated with worse prognosis in patients with HGSC, notably in the immunoregulatory molecular subtype, characterized by an immune-active microenvironment. CD39 was further associated with primary chemorefractory and chemoresistant human HGSC and platinum-based chemotherapy of murine HGSC was significantly more effective in CD39-deficient mice. At protein level, CD39 and CD73 were predominantly expressed by cancer-associated fibroblasts, and CD39 was expressed on severely exhausted, clonally expanded and putative tissue-resident memory TILs.ConclusionsOur study revealed the clinical, immunological, subtype-specific impacts of eADO signaling in HGSC, unveiled the chemoprotective effect of CD39 and supports the evaluation of eADO-targeting agents in patients with ovarian cancer.

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