Folate Receptor Alpha Testing: Why Timing Matters in Platinum-Resistant Ovarian Cancer

High-grade serous ovarian carcinoma (HGSOC) frequently expresses folate receptor alpha (FRα), making it a compelling target for antibody-drug conjugates. Mirvetuximab soravtansine (MIRV) received accelerated FDA approval for platinum-resistant HGSOC patients whose tumors exhibit high FRα expression, defined as ≥75% of tumor cells with ≥2+ staining intensity. This approval was based on compelling efficacy data, but the clinical utility hinges entirely on accurate and timely biomarker assessment.^1-3

The drug's mechanism involves a humanized anti-FRα antibody conjugated to a potent microtubule-disrupting agent, DM4. After binding to FRα on the cancer cell surface, the complex internalizes, releasing DM4 to induce mitotic arrest and apoptosis. This targeted delivery aims to reduce systemic toxicity while maximizing anti-tumor activity. The challenge, however, lies in the stability of the target itself.^1,2

The Shifting Target: FRα Expression Over Time

A retrospective study by Neisani, Marrero, and Angeli-Morales, published in Gynecologic Oncology Reports, directly addressed the longitudinal variability of FRα expression.¹ The investigators evaluated paired tumor specimens from a single institution, comparing FRα status at primary diagnosis with that at recurrence, specifically in platinum-resistant disease. This cohort included patients with HGSOC, the primary indication for MIRV.¹

The study enrolled 112 patients with paired samples. The median time between primary diagnosis and recurrence biopsy was 21 months (range, 6-68 months). This interval is clinically relevant, reflecting the typical course of platinum-sensitive disease progressing to platinum resistance. Investigators used a validated immunohistochemistry (IHC) assay, the Ventana FOLR1 (FOLR1-2.1) CDx assay, which is the companion diagnostic for MIRV.¹

The concordance rate for FRα expression between primary and recurrent tumors was 68% (95% CI, 60-76%). This figure, while seemingly moderate, masks critical shifts. Among patients initially classified as FRα-high at primary diagnosis (n=45), 31% (n=14) had lost high FRα expression by the time of recurrence. Conversely, among those initially FRα-low (n=67), 18% (n=12) converted to FRα-high status at recurrence.¹

These numbers are not trivial. Nearly one-third of patients who would have been eligible for MIRV based on their initial biopsy became ineligible, while a substantial minority who were initially ineligible gained eligibility. This dynamic suggests that relying solely on primary tumor biopsy for FRα status in the platinum-resistant setting risks both overtreatment and undertreatment.¹

Implications for Treatment Sequencing and Testing

The MIRASOL trial, a study that was central to the approval of mirvetuximab soravtansine, demonstrated a significant overall survival benefit for patients with FRα-high platinum-resistant ovarian cancer. Patients treated with MIRV had a median overall survival of 16.4 months compared to 12.7 months for those receiving investigator's choice chemotherapy (HR 0.67; 95% CI, 0.50-0.89; P=.0046).² This outcome highlights the importance of accurately identifying the FRα-high population. If FRα status changes, then the benefit observed in MIRASOL would not extend to patients whose tumors have lost expression.²

Liu, Xu, and Ma, in their review of treatment sequencing in platinum-resistant epithelial ovarian cancer, highlighted the critical role of biomarker testing in guiding therapy after trials like MIRASOL.² They emphasize that the market of available therapies, including PARP inhibitors, bevacizumab, and now MIRV, necessitates a precise understanding of tumor biology at each stage of disease progression. The variability in FRα expression directly impacts this precision.²

The ASCO Living Guideline, Version 2026.1.0, for systemic treatment of ovarian cancer recurrence, acknowledges the evolving role of biomarkers.³ While specific recommendations for re-biopsy frequency are still being refined, the guideline emphasizes that treatment decisions for targeted therapies should be based on the most current tumor biology. This implicitly supports re-testing for actionable biomarkers like FRα, especially in a disease where tumor heterogeneity and clonal evolution are well-documented.³

But the practicalities of re-biopsy are not insignificant. Patients with platinum-resistant disease often have a poorer performance status, and repeat invasive procedures carry risks and patient burden. The choice between a new biopsy and relying on archival tissue must weigh these factors against the potential for therapeutic benefit. Still, the data on FRα discordance makes a strong case for re-biopsy.¹

Challenges and Considerations for Clinical Practice

The Neisani study, while informative, has limitations. It was a single-institution retrospective analysis, which inherently carries selection bias. The sample size of 112 paired specimens, while adequate for detecting significant shifts, may not capture the full spectrum of FRα variability across diverse patient populations. The median follow-up time of 21 months between biopsies is also a factor; longer intervals might reveal even greater discordance.¹

Another consideration is the method of FRα assessment. While the Ventana FOLR1 (FOLR1-2.1) CDx assay is standardized, inter-observer variability in IHC interpretation, particularly for a threshold-based biomarker like FRα (≥75% of cells with ≥2+ staining), can exist. This highlights the need for experienced pathologists and robust quality control in clinical laboratories. For clinicians seeking to stay current on these complex diagnostic considerations, the Oxford Handbook of Oncology (4th ed) offers a concise reference.

The mechanism behind FRα expression changes is not fully understood. It could involve clonal selection under chemotherapy pressure, epigenetic modifications, or changes in the tumor microenvironment. Understanding these mechanisms might eventually lead to strategies to stabilize FRα expression or predict its changes. This is similar to the challenges faced in understanding HER2 heterogeneity in gastric cancer, where single-block testing can miss treatment targets. The dynamic nature of biomarkers is a recurring theme in oncology.^1,2

The clinical implications extend beyond just MIRV. As more targeted therapies emerge for ovarian cancer, each with its own biomarker, the need for repeat testing will likely increase. This creates a logistical and financial burden on healthcare systems. Developing less invasive methods for biomarker assessment, such as liquid biopsies, could offer a solution, but these technologies still require extensive validation for FRα.²

The current standard of care for platinum-resistant ovarian cancer often involves single-agent chemotherapy, with modest response rates and progression-free survival. The addition of MIRV for FRα-high patients represents a meaningful improvement. But this benefit is only realized if the patient truly has FRα-high disease at the time of treatment initiation. The data from Neisani and colleagues make a compelling case that this status cannot be assumed from an initial biopsy.^1,2

The ASCO guideline's emphasis on current tumor biology is a pragmatic approach.³ It acknowledges that cancer is not a static disease and that treatment strategies must adapt to its evolution. For FRα, this means accepting the necessity of re-biopsy, despite its challenges, to ensure patients receive the most appropriate and effective targeted therapy. The alternative is to risk administering an expensive, targeted agent to a patient whose tumor no longer expresses the target, or conversely, withholding a beneficial therapy from a patient who has developed the target expression. This is a critical distinction in personalized oncology.^1,3

The ongoing research into treatment sequencing, as discussed by Liu, Xu, and Ma, will continue to refine these strategies.² The integration of new agents like MIRV into existing treatment algorithms requires not only efficacy data but also a deep understanding of biomarker dynamics. The question remains: how frequently should these biomarkers be re-evaluated, and what is the optimal timing for re-biopsy in the context of disease progression and prior therapies?