Bevacizumab May Differentially Improve Ovarian Cancer Outcome in Patients with Proliferative and Mesenchymal Molecular Subtypes

Abstract

Purpose Recent progress in understanding the molecular biology of epithelial ovarian cancer has not yet translated into individualized treatment for these women or improvements in their disease outcome. Gene expression has been utilized to identify distinct molecular subtypes, but there have been no reports investigating whether or not molecular subtyping is predictive of response to bevacizumab in ovarian cancer. Experimental Design DASL gene expression arrays were performed on FFPE tissue from patients enrolled on the ICON7 trial. Patients were stratified into four TCGA molecular subtypes. Associations between molecular subtype and the efficacy of randomly assigned therapy with bevacizumab were assessed. Results Molecular subtypes were assigned as follows: 122 immunoreactive (34%), 96 proliferative (27%), 73 differentiated (20%), and 68 mesenchymal (19%). In univariate analysis patients with tumors of proliferative subtype obtained the greatest benefit from bevacizumab with a median PFS improvement of 10.1 months (HR 0.55 [95%CI 0.34–0.90], p=0.016). For the mesenchymal subtype, bevacizumab conferred a non-significant improvement in PFS 8.2 months (HR 0.78 [95%CI 0.44–1.40], p=0.41). Bevacizumab conferred modest improvements in PFS for patients with immunoreactive subtype (3.8 months; p=0.08) or differentiated subtype (3.7 months; p=0.61). Multivariate analysis demonstrated significant PFS improvement in proliferative subtype patients only (HR 0.45 [95%CI 0.27–0.74 p=0.0015]). Conclusions Molecular subtypes with the poorest survival (proliferative and mesenchymal) derive a comparably greater benefit from treatment that includes bevacizumab. Validation of our findings in an independent cohort could enable the use of bevacizumab for those patients most likely to benefit, thereby reducing side effects and healthcare cost.

Pooled Clustering of High-Grade Serous Ovarian Cancer Gene Expression Leads to Novel Consensus Subtypes Associated with Survival and Surgical Outcomes

“…Once successfully implemented, molecular subtypes could be captured in prospective clinical trials to evaluate subtype-specific treatment benefit and serve as biomarkers for facilitating patient stratification. For example, we recently found PRO and MES molecular subtypes may derive a comparably greater benefit than DIF and IMM subtypes, in a retrospective study in a randomized controlled phase III trial of primary ovarian cancer with bevacizumab treatment (44). …”

Challenges and Opportunities in Studying the Epidemiology of Ovarian Cancer Subtypes

“…A recent study reported that women with the proliferative and mesenchymal subtypes benefit from experimental treatment (Bevacizumab) over standard chemotherapy [93], which raises the possibility that similar subtype-specific variations in response to other actively developing therapeutics for EOC, such as PARP inhibition and immune therapies [94,95] might exist. For example, immunoreactive tumors may be good candidates for immunotherapy [79]; an open-label single-arm Phase II trial has been initiated to evaluate efficacy and safety of pembrolizumab anti-PD-1 monotherapy in these cases [96].…”

Reparameterization of PAM50 expression identifies novel breast tumor dimensions and leads to discovery of a breast cancer susceptibility locus at 12q15

“…The PAM50 breast intrinsic subtyping assay by RT-qPCR was performed by the Bernard Lab at the Huntsman Cancer Institute for both the LACE/Pathways and pedigree tumors, as previously described (citations [11][12][13]26) For each tumor sample a calibrated log-expression ratio was produced for each gene, producing an expression matrix. Centroid-based algorithms were used to generate quantitative normalized subtype scores for each of the four clinical subtypes plus a subtype characteristic of normal tissue ("Normal-like").…”

“…In particular, characterization of tumor profiles has been used extensively to subtype cancers (4)(5)(6), with breast cancer being a quintessential example (7). While these discoveries have clearly advanced our knowledge of tissue molecular heterogeneity and led to opportunities for improved clinical care (8)(9)(10)(11)(12), a single categorical variable of mutually exclusive subtypes is inadequate to reflect the molecular complexity. We propose that, rather than deconstructing gene expression to one categorical subtypes, the definition of orthogonal dimensions is a more flexible approach that can maintain multiple important expression signals.…”