High-grade serous ovarian cancer is the most malignant form of ovarian cancer, causing up to 70% of ovarian cancer deaths. The new study validated a new classifier tool called the predictor of high-grade serous ovarian carcinoma (HGSOC) molecular subtype (ProType), which encompasses 55 genes plus five housekeeping genes and is based on the NanoString platform.
Using the classification information as a reference with tissue samples, it is possible to break down this form of ovarian cancer into groups that can be targeted and which correlate with clinical factors and outcomes, reported Dr. Michael Anglesio, an assistant professor in obstetrics and gynecology at the University of British Columbia, and colleagues.
"This fully defined and locked-down clinical-grade assay will enable trial design with molecular subtype stratification and allow for objective assessment of the predictive value of HGSOC molecular subtypes in precision medicine applications," the authors reported.
Molecular subtyping underused
Whereas subtypes of serous ovarian cancer have been identified by a number of research groups, there has been a lack of agreement and clarity about classification.
"No methods discussed to date provide a workflow with compatibility for fixed/archival tissues that are the mainstay of modern pathology laboratories," Anglesio et al wrote. "Thus, the potential of gene-expression subtype information to guide patient management remains unrealized."
Investigators reported significant differences in survival between subtypes for progression-free survival and overall survival, in line with past reports.
Source: Anglesio et al,
||Desmoplastic stroma, high expression of extracellular matrix components, and poor outcomes.
||Intratumoral cluster of differentiation 3 CD3+/CD8+ cellular infiltration, inflammatory cytokine expression, and generally more favorable outcomes.
||High expression of cancer antigen 125 (CA125)/mucin 16 (MUC16), a subset of immuno-modulatory cytokines, modest lymphocyte infiltration, and clinical outcome indistinguishable from C2.IMM.
||Depleted for both stromal and immune elements, overexpress oncofetal and stem cell-associated genes, and unfavorable outcomes.
Clinical Cancer Research.
But subtyping of high-grade serous ovarian cancer has been underused in translational research and in clinical trials, the investigators wrote.
"To optimize clinical uptake, a classification scheme needs to be cost-effective, compatible with available clinical specimens (i.e. formalin-fixed paraffin embedded; FFPE), and be technically reproducible on single patient samples," Anglesio et al explained.
The authors believe their ProType test fits the bill. The study was supported by a retrospective analysis of tissue specimens and data from 20 studies conducted through the Ovarian Tumor Tissue Analysis (OTTA) consortium, and data from the Cancer Genome Atlas (TCGA) program. Investigators noted that they had data from more than 5,800 cancer patients worldwide.
"PrOTYPE subtypes are significantly associated with age, stage, residual disease, tumor infiltrating lymphocytes, and outcome," they reported. "The locked-down clinical-grade PrOTYPE test includes a model with 55 genes that predicted gene-expression subtype with >95% accuracy that was maintained in all analytical and biological validations."
Expanding treatment options
New options for patients with high-grade serous ovarian cancer include targeted poly (ADP-ribose) polymerase (PARP) inhibitors, angiogenesis inhibitors, and immune modulators.
"Similar to molecular profiling tools that are already emerging for other cancers, the clinical-grade PrOTYPE assay is ready for integration into clinical trials as well as research applications," the authors wrote.
The classifier is already being used in some clinical trials. Investigators are hoping that in the future, treatment options for ovarian cancer patients will be reevaluated in the context of molecular subtypes, identifying a strategy targeted to the patient's biology, Dr. Aline Talhouk, assistant professor in obstetrics and gynecology at the University of British Columbia, commented in an interview.
It may also be possible to retrospectively look at trial results and identify outcomes based on molecular subtype, provided tissue specimens are available, Anglesio said in an interview. Going forward, the subtype information could complement the information pathologists get beyond looking at the morphology of the tissue itself, he said.
Copyright © 2020 LabPulse.com