Staying current on the rapidly evolving therapeutic landscape in oncology is challenging for clinicians. This commentary discusses exciting practice‐changing data specific to ovarian cancer.

Background

Applying directed acyclic graph (DAG) models to proteogenomic data has been shown effective for detecting causal biomarkers of complex diseases. However, there remain unsolved challenges in DAG learning to jointly model binary clinical outcome variables and continuous biomarker measurements.

Results

In this paper, we propose a new tool, DAGBagM, to learn DAGs with both continuous and binary nodes. By using appropriate models, DAGBagM allows for either continuous or binary nodes to be parent or child nodes. It employs a bootstrap aggregating strategy to reduce false positives in edge inference. At the same time, the aggregation procedure provides a flexible framework to robustly incorporate prior information on edges.

Conclusions

Through extensive simulation experiments, we demonstrate that DAGBagM has superior performance compared to alternative strategies for modeling mixed types of nodes. In addition, DAGBagM is computationally more efficient than two competing methods. When applying DAGBagM to proteogenomic datasets from ovarian cancer studies, we identify potential protein biomarkers for platinum refractory/resistant response in ovarian cancer. DAGBagM is made available as a github repository at https://github.com/jie108/dagbagM .

Objective

To determine whether a non‑platinum chemotherapy doublet improves overall survival (OS) among patients with recurrent/metastatic cervical carcinoma.

Methods

Gynecologic Oncology Group protocol 240 is a phase 3, randomized, open-label, clinical trial that studied the efficacy of paclitaxel 175 mg/m² plus topotecan 0.75 mg/m² days 1-3 (n = 223) vs cisplatin 50 mg/m² plus paclitaxel 135 or 175 mg/m² (n = 229), in 452 patients with recurrent/metastatic cervical cancer. Each chemotherapy doublet was also studied with and without bevacizumab (15 mg/kg). Cycles were repeated every 21 days until progression, unacceptable toxicity, or complete response. The primary endpoints were OS and the frequency and severity of adverse effects. We report the final analysis of OS.

Results

At the protocol-specified final analysis, median OS was 16.3 (cisplatin-paclitaxel backbone) and 13.8 months (topotecan-paclitaxel backbone) (HR 1.12; 95% CI, 0.91-1.38; p = 0.28). Median OS for cisplatin-paclitaxel and topotecan-paclitaxel was 15 vs 12 months, respectively (HR 1.10; 95% CI,0.82-1.48; p = 0.52), and for cisplatin-paclitaxel-bevacizumab and topotecan-paclitaxel-bevacizumab was 17.5 vs 16.2 months, respectively (HR 1.16; 95% CI, 0.86-1.56; p = 0.34). Among the 75% of patients in the study population previously exposed to platinum, median OS was 14.6 (cisplatin-paclitaxel backbone) vs 12.9 months (topotecan-paclitaxel backbone), respectively (HR 1.09; 95% CI, 0.86-1.38;p = 0.48). Post-progression survival was 7.9 (cisplatin-paclitaxel backbone) vs 8.1 months (topotecan-paclitaxel backbone) (HR 0.95; 95% CI, 0.75-1.19). Grade 4 hematologic toxicity was similar between chemotherapy backbones.

Conclusions

Topotecan plus paclitaxel does not confer a survival benefit to women with recurrent/metastatic cervical cancer, even among platinum-exposed patients. Topotecan-paclitaxel should not be routinely recommended in this population. NCT00803062.

Poly-(ADP-ribose) polymerase (PARP) inhibitors (PARPis) selectively kill BRCA1/2-deficient cells, but their efficacy in BRCA-deficient patients is limited by drug resistance. Here, we used derived cell lines and cells from patients to investigate how to overcome PARPi resistance. We found that the functions of BRCA1 in homologous recombination (HR) and replication fork protection are sequentially bypassed during the acquisition of PARPi resistance. Despite the lack of BRCA1, PARPi-resistant cells regain RAD51 loading to DNA double-stranded breaks (DSBs) and stalled replication forks, enabling two distinct mechanisms of PARPi resistance. Compared with BRCA1-proficient cells, PARPi-resistant BRCA1-deficient cells are increasingly dependent on ATR for survival. ATR inhibitors (ATRis) disrupt BRCA1-independent RAD51 loading to DSBs and stalled forks in PARPi-resistant BRCA1-deficient cells, overcoming both resistance mechanisms. In tumor cells derived from patients, ATRis also overcome the bypass of BRCA1/2 in fork protection. Thus, ATR inhibition is a unique strategy to overcome the PARPi resistance of BRCA-deficient cancers.

To isolate circulating tumor cells (CTC) from women with advanced cervical cancer and estimate the impact of CTCs and treatment on overall survival and progression-free survival (PFS). A total of 7.5 mL of whole blood was drawn pre-cycle 1 and 36 days post-cycle 1 from patients enrolled on Gynecologic Oncology Group 0240, the phase III randomized trial that led directly to regulatory approval of the antiangiogenesis drug, bevacizumab, in women with recurrent/metastatic cervical cancer. CTCs (defined as anti-cytokeratin⁺/anti-CD45^- cells) were isolated from the buffy coat layer using an anti-EpCAM antibody-conjugated ferrofluid and rare earth magnet, and counted using a semiautomated fluorescence microscope. The median pre-cycle 1 CTC count was 7 CTCs/7.5 mL whole blood (range, 0-18) and, at 36 days posttreatment, was 4 (range, 0-17). The greater the declination in CTCs between time points studied, the lower the risk of death [HR, 0.87; 95% confidence interval (CI), 0.79-0.95)]. Among patients with high (≥ median) pretreatment CTCs, bevacizumab treatment was associated with a reduction in the hazard of death (HR, 0.57; 95% CI, 0.32-1.03) and PFS (HR, 0.59; 95% CI, 0.36-0.96). This effect was not observed with low (< median) CTCs. CTCs can be isolated from women with advanced cervical cancer and may have prognostic significance. A survival benefit conferred by bevacizumab among patients with high pretreatment CTCs may reflect increased tumor neovascularization and concomitant vulnerability to VEGF inhibition. These data support studying CTC capture as a potential predictive biomarker.

Ovarian cancer is the fifth leading cause of cancer death in women. Ovarian cancers display a high degree of complex genetic alterations involving many oncogenes and tumor suppressor genes. Analysis of the association between genetic alterations and clinical endpoints such as survival will lead to improved patient management via genetic stratification of patients into clinically relevant subgroups. In this study, we aim to define subgroups of high-grade serous ovarian carcinomas that differ with respect to prognosis and overall survival. Genome-wide DNA copy number alterations (CNAs) were measured in 72 clinically annotated, high-grade serous tumors using high-resolution oligonucleotide arrays. Two clinically annotated, independent cohorts were used for validation. Unsupervised hierarchical clustering of copy number data derived from the 72 patient cohort resulted in two clusters with significant difference in progression free survival (PFS) and a marginal difference in overall survival (OS). GISTIC analysis of the two clusters identified altered regions unique to each cluster. Supervised clustering of two independent large cohorts of high-grade serous tumors using the classification scheme derived from the two initial clusters validated our results and identified 8 genomic regions that are distinctly different among the subgroups. These 8 regions map to 8p21.3, 8p23.2, 12p12.1, 17p11.2, 17p12, 19q12, 20q11.21 and 20q13.12; and harbor potential oncogenes and tumor suppressor genes that are likely to be involved in the pathogenesis of ovarian carcinoma. We have identified a set of genetic alterations that could be used for stratification of high-grade serous tumors into clinically relevant treatment subgroups.

Objective

Gynecologic Oncology Group (GOG) 177 demonstrated that addition of paclitaxel to a backbone of adriamycin/cisplatin improves overall survival (OS) and progression-free survival (PFS) for patients with advanced or recurrent endometrial cancer. Using patient specimens from GOG-177, our objective was to identify potential mechanisms underlying the improved clinical response to taxanes. Stathmin (STMN1) is a recognized poor prognostic marker in endometrial cancer that functions as a microtubule depolymerizing protein, allowing cells to transit rapidly through mitosis. Therefore, we hypothesized that one possible mechanism underlying the beneficial effects of paclitaxel could be to counter the impact of stathmin.

Methods

We analyzed the expression of stathmin by immunohistochemistry (IHC) in 69 specimens from patients enrolled on GOG-177. We also determined the correlation between stathmin mRNA expression and clinical outcomes in The Cancer Genome Atlas (TCGA) dataset for endometrial cancer.

Results

We first established that stathmin expression was significantly associated with shorter PFS and OS for all analyzed cases in both GOG-177 and TCGA. However, subgroup analysis from GOG-177 revealed that high stathmin correlated with poor PFS and OS particularly in patients who received adriamycin/cisplatin only. In contrast, there was no statistically significant association between stathmin expression and OS or PFS in patients treated with paclitaxel/adriamycin/cisplatin.

Conclusions

Our findings demonstrate that high stathmin expression is a poor prognostic marker in endometrial cancer. Paclitaxel may help to negate the impact of stathmin overexpression when treating high risk endometrial cancer cases.

Objectives

The ability to stratify a patient's risk of metastasis and survival permits more refined care. A proof of principle study was undertaken to investigate the relationship between single nucleotide polymorphisms (SNPs) in literature based candidate cancer genes and the risk of nodal metastasis and clinical outcome in endometrioid endometrial cancer (EEC) patients.

Methods

Surgically-staged EEC patients from the Gynecologic Oncology Group or Washington University School of Medicine with germline DNA available were eligible. Fifty-four genes represented by 384 SNPs, were evaluated by Illumina Custom GoldenGate array. Association with lymph node metastases was the primary outcome. Progression-free survival (PFS) and overall survival (OS) was also evaluated.

Results

361 SNPs with high quality genotype data were evaluated in 337 patients with outcome data. Five SNPs in CXCR2 had an odds ratio (OR) between 0.68 and 0.70 (p-value ≤ 0.025). The A allele rs946486 in ABL had an OR of 1.5 (p-value = 0.01) for metastasis. The G allele in rs7795743 in EGFR had an OR for metastasis of 0.68 (p-value = 0.02) and hazard ratio (HR) for progression of 0.66 (p-value = 0.004). Importantly, no SNP met genome wide significance after adjusting for multiple test correcting and clinical covariates. The A allele in rs2159359 SNP in NME1 and the G allele in rs13222385 in EGFR were associated with worse OS. Both exhibited genome wide significance; rs13222385 remained significant after adjusting for prognostic clinical variables.

Conclusion

SNPs in cancer genes including rs2159359 SNP in NME1 and rs13222385 in EGFR may stratify risk in EEC and are prioritized for further investigation.

Purpose

Increasing measures of adiposity have been correlated with poor oncologic outcomes and a lack of response to anti-angiogenic therapies. Limited data exists on the impact of subcutaneous fat density (SFD) and visceral fat density (VFD) on oncologic outcomes. This ancillary analysis of GOG-218, evaluates whether imaging markers of adiposity were predictive biomarkers for bevacizumab (bev) use in epithelial ovarian cancer (EOC).

Patients and methods

There were 1249 patients (67%) from GOG-218 with imaging measurements. SFD and VFD were calculated utilizing Hounsfield units (HU). Proportional hazards models were used to assess the association between SFD and VFD with overall survival (OS).

Results

Increased SFD and VFD showed an increased HR for death (HR per 1-SD increase 1.12, 95% CI:1.05-1.19 p = 0.0009 and 1.13, 95% CI: 1.05-1.20 p = 0.0006 respectively). In the predictive analysis for response to bev, high VFD showed an increased hazard for death in the placebo group (HR per 1-SD increase 1.22, 95% CI: 1.09-1.37; p = 0.025). However, in the bev group there was no effect seen (HR per 1-SD increase: 1.01, 95% CI: 0.90-1.14) Median OS was 45 vs 47 months in the VFD low groups and 36 vs 42 months in the VFD high groups on placebo versus bev, respectively.

Conclusion

High VFD and SFD have a negative prognostic impact on patients with EOC. High VFD appears to be a predictive marker of bev response and patients with high VFD may be more likely to benefit from initial treatment with bev.

Objective

This study evaluated single nucleotide polymorphisms (SNPs) associated with progression free (PFS) and overall survival (OS) in patients with advanced stage serous EOC.

Methods

Patients enrolled in GOG-172 and 182 who provided specimens for translational research and consent were included. Germline DNA was evaluated with the Illumina's HumanOMNI1-Quad beadchips and scanned using Illumina's iScan optical imaging system. SNPs with allele frequency>0.05 and genotyping rate>0.98 were included. Analysis of SNPs for PFS and OS was done using Cox regression. Statistical significance was determined using Bonferroni corrected p-values with genomic control adjustment.

Results

The initial GWAS analysis included 1,124,677 markers in 396 patients. To obtain the final data set, quality control checks were performed and limited to serous tumors and self-identified Caucasian race. In total 636,555 SNPs and 289 patients passed all the filters. The pre-specified statistical level of significance was 7.855e^-08. No SNPs met this criteria for PFS or OS, however, two SNPs were close to significance (rs10899426 p-2.144e^-08) (rs6256 p-9.774e^-07) for PFS and 2 different SNPs were identified (rs295315 p-7.536e^-07; rs17693104 p-7.734e^-07) which were close to significance for OS.

Conclusions

Using the pre-specified level of significance of 1×10^-08, we did not identify any SNPs of statistical significance for OS or PFS, however several were close. The SNP's identified in this GWAS study will require validation and these preliminary findings may lead to identification of novel pathways and biomarkers.