Phase 1b study of mirvetuximab soravtansine, a folate receptor alpha (FRα)-targeting antibody-drug conjugate, in combination with carboplatin and bevacizumab in patients with platinum-sensitive ovarian cancer.

OBJECTIVE: Evaluate the antitumor activity and safety profile of the triplet combination of mirvetuximab soravtansine (MIRV), carboplatin, and bevacizumab in recurrent, platinum-sensitive ovarian cancer. METHODS: Participants with recurrent, platinum-sensitive epithelial ovarian, fallopian tube, or primary peritoneal cancer (1-2 prior lines of therapy) received MIRV (6 mg/kg adjusted ideal body weight), carboplatin (AUC5), and bevacizumab (15 mg/kg) once every 3 weeks. Carboplatin could be discontinued after 6 cycles per investigator discretion; continuation of MIRV+bevacizumab as maintenance therapy was permitted. Eligibility included folate receptor alpha (FRα) expression by immunohistochemistry (≥50% of cells with ≥2+ intensity; PS2+ scoring); prior bevacizumab was allowed. Tumor response, duration of response (DOR), progression-free survival (PFS), and adverse events (AEs) were assessed. RESULTS: Forty-one participants received triplet therapy, with a median of 6, 12, and 13 cycles of carboplatin, MIRV, and bevacizumab, respectively. The confirmed objective response rate was 83% (9 complete and 25 partial responses). The median DOR was 10.9 months; median PFS was 13.5 months. AEs (any grade) occurred as expected, based on each agent's safety profile; most common were diarrhea (83%), nausea (76%), fatigue (73%), thrombocytopenia (71%), and blurred vision (68%). Most cases were mild to moderate (grade ≤2), except for thrombocytopenia, for which most drug-related discontinuations occurred, and neutropenia. CONCLUSIONS: This triplet regimen (MIRV+carboplatin+bevacizumab) was highly active, with a tolerable AE profile in participants with recurrent, platinum-sensitive, FRα-expressing ovarian cancer. Thrombocytopenia was the primary cause of dose modifications. These outcomes compare favorably to historical data reported for platinum-based chemotherapy plus bevacizumab regimens in similar patient populations.

A phase II study of Mirvetuximab Soravtansine in triple-negative breast cancer.

Folate receptor alpha (FRα) has been reported to be expressed in up to 80% of triple-negative breast cancers (TNBC) with limited expression in normal tissues, making it a promising therapeutic target. Mirvetuximab soravtansine (mirvetuximab-s) is an antibody drug conjugate which has shown promise in the treatment of FRα-positive solid tumors in early phase clinical trials. Herein, are the results of the first prospective phase II trial evaluating mirvetuximab-s in metastatic TNBC. Patients with advanced, FRα-positive TNBC were enrolled on this study. Mirvetuximab-s was administered at a dose of 6.0 mg/kg every 3 weeks. 96 patients with advanced TNBC consented for screening. FRα staining was performed on tumor tissue obtained from 80 patients. The rate of FRα positivity by immunohistochemistry was 10.0% (8/80). Two patients were treated on study, with best overall responses of stable disease in one and progressive disease in the other. Adverse events were consistent with earlier studies. The study was terminated early due to the low rate of FRα positivity in the screened patient population and lack of disease response in the two patients treated. The observed rate of FRα positivity was considerably lower than previously reported and none of the patients had a partial or complete response. Treatment with mirvetuximab-s should only be further explored in TNBC if an alternate biomarker strategy is developed for patient selection on the basis of additional preclinical data.

Folate Receptor α-Targeted 89Zr-M9346A Immuno-PET for Image-Guided Intervention with Mirvetuximab Soravtansine in Triple-Negative Breast Cancer.

Folate receptor α (FRα) is a well-studied tumor biomarker highly expressed in many epithelial tumors such as breast, ovarian, and lung cancers. Mirvetuximab soravtansine (IMGN853) is the antibody-drug conjugate of FRα-binding humanized monoclonal antibody M9346A and cytotoxic maytansinoid drug DM4. IMGN853 is currently being evaluated in multiple clinical trials, in which the immunohistochemical evaluation of an archival tumor or biopsy specimen is used for patient screening. However, limited tissue collection may lead to inaccurate diagnosis due to tumor heterogeneity. Herein, we developed a zirconium-89 (89Zr)-radiolabeled M9346A (89Zr-M9346A) as an immuno-positron emission tomography (immuno-PET) radiotracer to evaluate FRα expression in triple-negative breast cancer (TNBC) patients, providing a novel means to guide intervention with therapeutic IMGN853. In this study, we verified the binding specificity and immunoreactivity of 89Zr-M9346A by in vitro studies in FRαhigh cells (HeLa) and FRαlow cells (OVCAR-3). In vivo PET/computed tomography (PET/CT) imaging in HeLa xenografts and TNBC patient-derived xenograft (PDX) mouse models with various levels of FRα expression demonstrated its targeting specificity and sensitivity. Following PET imaging, the treatment efficiencies of IMGN853, pemetrexed, IMGN853 + pemetrexed, paclitaxel, and saline were assessed in FRαhigh and FRαlow TNBC PDX models. The correlation between 89Zr-M9346A tumor uptake and treatment response using IMGN853 in FRαhigh TNBC PDX model suggested the potential of 89Zr-M9346A PET as a noninvasive tool to prescreen patients based on the in vivo PET imaging for IMGN853-targeted treatment.

Breast cancer molecular subtypes respond differently to preoperative chemotherapy.

PURPOSE: Molecular classification of breast cancer has been proposed based on gene expression profiles of human tumors. Luminal, basal-like, normal-like, and erbB2+ subgroups were identified and were shown to have different prognoses. The goal of this research was to determine if these different molecular subtypes of breast cancer also respond differently to preoperative chemotherapy. EXPERIMENTAL DESIGN: Fine needle aspirations of 82 breast cancers were obtained before starting preoperative paclitaxel followed by 5-fluorouracil, doxorubicin, and cyclophosphamide chemotherapy. Gene expression profiling was done with Affymetrix U133A microarrays and the previously reported "breast intrinsic" gene set was used for hierarchical clustering and multidimensional scaling to assign molecular class. RESULTS: The basal-like and erbB2+ subgroups were associated with the highest rates of pathologic complete response (CR), 45% [95% confidence interval (95% CI), 24-68] and 45% (95% CI, 23-68), respectively, whereas the luminal tumors had a pathologic CR rate of 6% (95% CI, 1-21). No pathologic CR was observed among the normal-like cancers (95% CI, 0-31). Molecular class was not independent of conventional cliniocopathologic predictors of response such as estrogen receptor status and nuclear grade. None of the 61 genes associated with pathologic CR in the basal-like group were associated with pathologic CR in the erbB2+ group, suggesting that the molecular mechanisms of chemotherapy sensitivity may vary between these two estrogen receptor-negative subtypes. CONCLUSIONS: The basal-like and erbB2+ subtypes of breast cancer are more sensitive to paclitaxel- and doxorubicin-containing preoperative chemotherapy than the luminal and normal-like cancers.

Gene expression profiles predict early relapse in ovarian cancer after platinum-paclitaxel chemotherapy.

PURPOSE: Women with advanced epithelial ovarian cancer are routinely treated with platinum-paclitaxel chemotherapy following cytoreductive surgery, yet only approximately 20% achieve long-term disease-free survival. We hypothesized that differences in gene expression before treatment could distinguish patients with short versus long time to recurrence after administration of platinum-paclitaxel combination chemotherapy. EXPERIMENTAL DESIGN: To test this hypothesis, gene expression profiling of 79 primary surgically resected tumors from women with advanced-stage, high-grade epithelial ovarian cancer was done using cDNA microarrays containing 30,721 genes. Supervised learning algorithms were applied in an effort to develop a binary classifier that could discriminate women at risk for early (< or =21 months) versus late (>21 months) relapse after initial chemotherapy. RESULTS: A 14-gene predictive model was developed using a set of training samples (n = 51) and subsequently tested using an independent set of test samples (n = 28). This model correctly predicted the outcome of 24 of the 28 test samples (86% accuracy) with 95% positive predictive value for early relapse. CONCLUSIONS: Predictive markers for early recurrence can be identified for platinum-paclitaxel combination chemotherapy in primary ovarian carcinoma. The proposed 14-gene model requires further validation.

Comparison of the predictive accuracy of DNA array-based multigene classifiers across cDNA arrays and Affymetrix GeneChips.

We examined how well differentially expressed genes and multigene outcome classifiers retain their class-discriminating values when tested on data generated by different transcriptional profiling platforms. RNA from 33 stage I-III breast cancers was hybridized to both Affymetrix GeneChip and Millennium Pharmaceuticals cDNA arrays. Only 30% of all corresponding gene expression measurements on the two platforms had Pearson correlation coefficient r >or= 0.7 when UniGene was used to match probes. There was substantial variation in correlation between different Affymetrix probe sets matched to the same cDNA probe. When cDNA and Affymetrix probes were matched by basic local alignment tool (BLAST) sequence identity, the correlation increased substantially. We identified 182 genes in the Affymetrix and 45 in the cDNA data (including 17 common genes) that accurately separated 91% of cases in supervised hierarchical clustering in each data set. Cross-platform testing of these informative genes resulted in lower clustering accuracy of 45 and 79%, respectively. Several sets of accurate five-gene classifiers were developed on each platform using linear discriminant analysis. The best 100 classifiers showed average misclassification error rate of 2% on the original data that rose to 19.5% when tested on data from the other platform. Random five-gene classifiers showed misclassification error rate of 33%. We conclude that multigene predictors optimized for one platform lose accuracy when applied to data from another platform due to missing genes and sequence differences in probes that result in differing measurements for the same gene.

Gene expression profiles obtained from fine-needle aspirations of breast cancer reliably identify routine prognostic markers and reveal large-scale molecular differences between estrogen-negative and estrogen-positive tumors.

PURPOSE: The purpose of this study was to determine whether comprehensive transcriptional profiles (TPs) can be obtained from single-passage fine-needle aspirations (FNAs) of breast cancer and to explore whether profiles capture routine clinicopathological parameters. EXPERIMENTAL DESIGN: Expression profiles were available on 38 patients with stage I-III breast cancer who underwent FNA at the time of diagnosis. [(33)P]dCTP-labeled cDNA probes were generated and hybridized to cDNA membrane microarrays that contained 30,000 human sequence clones, including 10,890 expressed sequence tags. RESULTS: The median total RNA yield from the biopsies was 2 micro g (range, 1-25 micro g). The cellular composition of each biopsy was examined and, on average, 79% of the cells were cancer cells. TP was successfully performed on all 38 of the biopsies. Unsupervised complete-linkage hierarchical clustering with all of the biopsies revealed an association between estrogen receptor (ER) status and gene expression profiles. There was a strong correlation between ER status determined by TP and measured by routine immunohistochemistry (P = 0.001). A similar strong correlation was seen with HER-2 status determined by fluorescent in situ hybridization (P = 0.0002). Using the first 18 cases as the discovery set, we established a cutoff of 2.0 and 18.0 for ER and HER-2 mRNA levels, respectively, to distinguish clinically-negative from -positive cases. We also identified 105 genes (excluding the ER gene) the expression of which correlated highly with clinical ER status. Twenty tumors were used for prospective validation. HER-2 status was correctly identified in all 20 of the cases, based on HER-2 mRNA content detected by TP. ER status was correctly identified in 19 of 20 cases. When the marker set of 105 genes was used to prospectively predict ER status, TP-based classification correctly identified 9 of 10 of the ER-positive and 7 of 10 of the ER-negative tumors. We also explored supervised cluster analysis using various functional categories of genes, and we observed a clear separation between ER-negative and ER-positive tumors when genes involved in signal transduction were used for clustering. CONCLUSIONS: These results demonstrate that comprehensive TP can be performed on FNA biopsies. TPs reliably measure conventional single-gene prognostic markers such as ER and HER-2. A complex pattern of genes (not including ER) can also be used to predict clinical ER status. These results demonstrate that needle biopsy-based diagnostic microarray tests may be developed that could capture conventional prognostic information but may also contain additional clinical information that cannot currently be measured with other methods.

Breast cancer biomarkers and molecular medicine: part II.

In this second part of the two-part review of breast cancer biomarkers and molecular medicine, the first section will consider additional breast cancer prognostic factors, including oncogenes, tumor suppressor genes, cell adhesion molecules, invasion-associated proteins and proteases, hormone receptor proteins, drug resistance proteins, apoptosis regulators, transcription factors, telomerase, DNA repair and methylation and transcriptional profiling using high-density genomic microarrays. The second section will consider the prediction of therapy response using the techniques of pharmacogenetics and pharmacogenomics.

Breast cancer biomarkers and molecular medicine.

The first part of this two-part review of established and emerging breast cancer biomarkers and molecular diagnostics considers breast cancer predisposition, screening tests for diagnosis, diagnosis using small specimens and metastatic lesions, micrometastatic disease and breast cancer prognosis assessment. Prognostic factors covered in this review include: cytogenetic markers, DNA ploidy and S phase determination, cell proliferation markers, cell cycle regulators and growth factor measurements including epithelial growth factor receptor, HER-2/neu and a variety of other relevant molecules controlling proliferation, differentiation and angiogenesis. The first section of part two will continue the consideration of breast cancer prognostic factors including oncogenes, tumor suppressor genes, cell adhesion molecules, invasion-associated proteins and proteases, hormone receptor proteins, drug resistance proteins, apoptosis regulators, transcription factors, telomerase, DNA repair and methylation and transcriptional profiling using high-density genomic microarrays. The second section of part two will consider the prediction of therapy response using the techniques of pharmacogenetics and pharmacogenomics.

DNA ploidy and cell cycle analysis in breast cancer.

During the past 10 years there has been considerable interest in the application of new technologies to identify human malignancy and predict disease outcome. Markers of cell proliferation and the technologies of flow cytometry and image analysis for the determination of DNA total content in human tumor cells have been studied in breast cancer for 20 years. In this review, the uses and limitations of these technologies for the determination of ploidy status are discussed. This review also considers the prognostic significance and potential clinical utility of ploidy measurements, S phase calculation, and individual cell cycle regulatory biomarker expression levels.