Melissa C. Larson

High-Dose Vincristine Sulfate Liposome Injection for Advanced, Relapsed, and Refractory Adult Philadelphia Chromosome–Negative Acute Lymphoblastic Leukemia

PURPOSE Relapsed adult acute lymphoblastic leukemia (ALL) is associated with high reinduction mortality, chemotherapy resistance, and rapid progression leading to death. Vincristine sulfate liposome injection (VSLI), sphingomyelin and cholesterol nanoparticle vincristine (VCR), facilitates VCR dose-intensification and densification plus enhances target tissue delivery. We evaluated high-dose VSLI monotherapy in adults with Philadelphia chromosome (Ph) -negative ALL that was multiply relapsed, relapsed and refractory to reinduction, and/or relapsed after hematopoietic cell transplantation (HCT). PATIENTS AND METHODS Sixty-five adults with Ph-negative ALL in second or greater relapse or whose disease had progressed following two or more leukemia therapies were treated in this pivotal phase II, multinational trial. Intravenous VSLI 2.25 mg/m(2), without dose capping, was administered once per week until response, progression, toxicity, or pursuit of HCT. The primary end point was achievement of complete response (CR) or CR with incomplete hematologic recovery (CRi). RESULTS The CR/CRi rate was 20% and overall response rate was 35%. VSLI monotherapy was effective as third-, fourth-, and fifth-line therapy and in patients refractory to other single- and multiagent reinduction therapies. Median CR/CRi duration was 23 weeks (range, 5 to 66 weeks); 12 patients bridged to a post-VSLI HCT, and five patients were long-term survivors. VSLI was generally well tolerated and associated with a low 30-day mortality rate (12%). CONCLUSION High-dose VSLI monotherapy resulted in meaningful clinical outcomes including durable responses and bridging to HCT in advanced ALL settings. The toxicity profile of VSLI was predictable, manageable, and comparable to standard VCR despite the delivery of large, normally unachievable, individual and cumulative doses of VCR.

Obesity and risk of ovarian cancer subtypes: evidence from the Ovarian Cancer Association Consortium

Whilst previous studies have reported that higher BMI increases a womans risk of developing ovarian cancer, associations for the different histological subtypes have not been well defined. As the prevalence of obesity has increased dramatically, and classification of ovarian histology has improved in the last decade, we sought to examine the association in a pooled analysis of recent studies participating in the Ovarian Cancer Association Consortium. We evaluated the association between BMI (recent, maximum and in young adulthood) and ovarian cancer risk using original data from 15 case-control studies (13 548 cases and 17 913 controls). We combined study-specific adjusted odds ratios (ORs) using a random-effects model. We further examined the associations by histological subtype, menopausal status and post-menopausal hormone use. High BMI (all time-points) was associated with increased risk. This was most pronounced for borderline serous (recent BMI: pooled OR=1.24 per 5 kg/m(2); 95% CI 1.18-1.30), invasive endometrioid (1.17; 1.11-1.23) and invasive mucinous (1.19; 1.06-1.32) tumours. There was no association with serous invasive cancer overall (0.98; 0.94-1.02), but increased risks for low-grade serous invasive tumours (1.13, 1.03-1.25) and in pre-menopausal women (1.11; 1.04-1.18). Among post-menopausal women, the associations did not differ between hormone replacement therapy users and non-users. Whilst obesity appears to increase risk of the less common histological subtypes of ovarian cancer, it does not increase risk of high-grade invasive serous cancers, and reducing BMI is therefore unlikely to prevent the majority of ovarian cancer deaths. Other modifiable factors must be identified to control this disease.

Germline Mutation in BRCA1 or BRCA2 and Ten-Year Survival for Women Diagnosed with Epithelial Ovarian Cancer

Purpose: To analyze the effect of germline mutations in BRCA1 and BRCA2 on mortality in patients with ovarian cancer up to 10 years after diagnosis. Experimental Design: We used unpublished survival time data for 2,242 patients from two case–control studies and extended survival time data for 4,314 patients from previously reported studies. All participants had been screened for deleterious germline mutations in BRCA1 and BRCA2. Survival time was analyzed for the combined data using Cox proportional hazard models with BRCA1 and BRCA2 as time-varying covariates. Competing risks were analyzed using Fine and Gray model. Results: The combined 10-year overall survival rate was 30% [95% confidence interval (CI), 28%–31%] for non-carriers, 25% (95% CI, 22%–28%) for BRCA1 carriers, and 35% (95% CI, 30%–41%) for BRCA2 carriers. The HR for BRCA1 was 0.53 at time zero and increased over time becoming greater than one at 4.8 years. For BRCA2, the HR was 0.42 at time zero and increased over time (predicted to become greater than 1 at 10.5 years). The results were similar when restricted to 3,202 patients with high-grade serous tumors and to ovarian cancer–specific mortality. Conclusions: BRCA1/2 mutations are associated with better short-term survival, but this advantage decreases over time and in BRCA1 carriers is eventually reversed. This may have important implications for therapy of both primary and relapsed disease and for analysis of long-term survival in clinical trials of new agents, particularly those that are effective in BRCA1/2 mutation carriers. Clin Cancer Res; 21(3); 652–7. ©2014 AACR.

Clinical Characteristics of Ovarian Cancer Classified by BRCA1, BRCA2, and RAD51C Status

We evaluated homologous recombination deficient (HRD) phenotypes in epithelial ovarian cancer (EOC) considering BRCA1, BRCA2, and RAD51C in a large well-annotated patient set. We evaluated EOC patients for germline deleterious mutations (n = 899), somatic mutations (n = 279) and epigenetic alterations (n = 482) in these genes using NGS and genome-wide methylation arrays. Deleterious germline mutations were identified in 32 (3.6%) patients for BRCA1, in 28 (3.1%) for BRCA2 and in 26 (2.9%) for RAD51C. Ten somatically sequenced patients had deleterious alterations, six (2.1%) in BRCA1 and four (1.4%) in BRCA2. Fifty two patients (10.8%) had methylated BRCA1 or RAD51C. HRD patients with germline or somatic alterations in any gene were more likely to be high grade serous, have an earlier diagnosis age and have ovarian and/or breast cancer family history. The HRD phenotype was most common in high grade serous EOC. Identification of EOC patients with an HRD phenotype may help tailor specific therapies.

Epigenome-wide ovarian cancer analysis identifies a methylation profile differentiating clear-cell histology with epigenetic silencing of the HERG K+ channel

Ovarian cancer remains the leading cause of death in women with gynecologic malignancies, despite surgical advances and the development of more effective chemotherapeutics. As increasing evidence indicates that clear-cell ovarian cancer may have unique pathogenesis, further understanding of molecular features may enable us to begin to understand the underlying biology and histology-specific information for improved outcomes. To study epigenetics in clear-cell ovarian cancer, fresh frozen tumor DNA (n = 485) was assayed on Illumina Infinium HumanMethylation450 BeadChips. We identified a clear-cell ovarian cancer tumor methylation profile (n = 163) which we validated in two independent replication sets (set 1, n = 163; set 2, n = 159), highlighting 22 CpG loci associated with nine genes (VWA1, FOXP1, FGFRL1, LINC00340, KCNH2, ANK1, ATXN2, NDRG21 and SLC16A11). Nearly all of the differentially methylated CpGs showed a propensity toward hypermethylation among clear-cell cases. Several loci methylation inversely correlated with tumor gene expression, most notably KCNH2 (HERG, a potassium channel) (P = 9.5 × 10(-7)), indicating epigenetic silencing. In addition, a predicted methylation class mainly represented by the clear-cell cases (20 clear cell out of 23 cases) had improved survival time. Although these analyses included only 30 clear-cell carcinomas, results suggest that loss of expression of KCNH2 (HERG) by methylation could be a good prognostic marker, given that overexpression of the potassium (K(+)) channel Eag family members promotes increased proliferation and results in poor prognosis. Validation in a bigger cohort of clear-cell tumors of the ovary is warranted.

Assessment of Hepatocyte Growth Factor in Ovarian Cancer Mortality

Background: Invasive ovarian cancer is a significant cause of gynecologic cancer mortality. Methods: We examined whether this mortality was associated with inherited variation in approximately 170 candidate genes/regions [993 single-nucleotide polymorphisms (SNPs)] in a multistage analysis based initially on 312 Mayo Clinic cases (172 deaths). Additional analyses used The Cancer Genome Atlas (TCGA; 127 cases, 62 deaths). For the most compelling gene, we immunostained Mayo Clinic tissue microarrays (TMA, 326 cases) and conducted consortium-based SNP replication analysis (2,560 cases, 1,046 deaths). Results: The strongest initial mortality association was in HGF (hepatocyte growth factor) at rs1800793 (HR = 1.7, 95% CI = 1.3–2.2, P = 2.0 × 10−5) and with overall variation in HGF (gene-level test, P = 3.7 × 10−4). Analysis of TCGA data revealed consistent associations [e.g., rs5745709 (r2 = 0.96 with rs1800793): TCGA HR = 2.4, CI = 1.4–4.1, P = 2.2 × 10−3; Mayo Clinic + TCGA HR = 1.6, CI = 1.3–1.9, P = 7.0 × 10−5] and suggested genotype correlation with reduced HGF mRNA levels (P = 0.01). In Mayo Clinic TMAs, protein levels of HGF, its receptor MET (C-MET), and phospho-MET were not associated with genotype and did not serve as an intermediate phenotype; however, phospho-MET was associated with reduced mortality (P = 0.01) likely due to higher expression in early-stage disease. In eight additional ovarian cancer case series, HGF rs5745709 was not associated with mortality (HR = 1.0, CI = 0.9–1.1, P = 0.87). Conclusions: We conclude that although HGF signaling is critical to migration, invasion, and apoptosis, it is unlikely that HGF genetic variation plays a major role in ovarian cancer mortality. Furthermore, any minor role is not related to genetically-determined expression. Impact: Our study shows the utility of multiple data types and multiple data sets in observational studies. Cancer Epidemiol Biomarkers Prev; 20(8); 1638–48. ©2011 AACR.

Xenobiotic-metabolizing gene polymorphisms and ovarian cancer risk

Because selected xenobiotic‐metabolizing enzymes process pro‐carcinogens that could initiate ovarian carcinogenesis, we hypothesized that single nucleotide polymorphisms (SNPs) in the genes encoding xenobiotic‐metabolizing enzymes are associated with risk of ovarian cancer. Cases with invasive epithelial ovarian cancer (N = 1,571 including 956 of serous sub‐type) and controls (N = 2,046) from three studies were genotyped at 11 SNPs in EPHX1, ADH4, ADH1A, NQO2, NAT2, GSTP1, CYP1A1, and NQO1, following an initial SNP screen in a subset of participants. Logistic regression analysis of genotypes obtained via Illumina GoldenGate and Sequenom iPlex technologies revealed the following age‐ and study‐adjusted associations: EPHX1 rs1051740 with increased serous ovarian cancer risk [per‐allele odds ratio (OR) 1.17, 95% confidence interval (95% CI) 1.04–1.32, P = 0.01), ADH4 r1042364 with decreased ovarian cancer risk (OR 0.90, 95% CI: 0.81–1.00, P = 0.05), and NQO1 rs291766 with increased ovarian cancer risk (OR 1.11, 95% CI: 1.00–1.23, P = 0.04). These findings are consistent with prior studies implicating these genes in carcinogenesis and suggest that this collection of variants is worthy of follow‐up in additional studies.

Integrative genomic analysis identifies epigenetic marks that mediate genetic risk for epithelial ovarian cancer

BackgroundBoth genetic and epigenetic factors influence the development and progression of epithelial ovarian cancer (EOC). However, there is an incomplete understanding of the interrelationship between these factors and the extent to which they interact to impact disease risk. In the present study, we aimed to gain insight into this relationship by identifying DNA methylation marks that are candidate mediators of ovarian cancer genetic risk.MethodsWe used 214 cases and 214 age-matched controls from the Mayo Clinic Ovarian Cancer Study. Pretreatment, blood-derived DNA was profiled for genome-wide methylation (Illumina Infinium HumanMethylation27 BeadArray) and single nucleotide polymorphisms (SNPs, Illumina Infinium HD Human610-Quad BeadArray). The Causal Inference Test (CIT) was implemented to distinguish CpG sites that mediate genetic risk, from those that are consequential or independently acted on by genotype.ResultsControlling for the estimated distribution of immune cells and other key covariates, our initial epigenome-wide association analysis revealed 1,993 significantly differentially methylated CpGs that between cases and controls (FDR, q < 0.05). The relationship between methylation and case-control status for these 1,993 CpGs was found to be highly consistent with the results of previously published, independent study that consisted of peripheral blood DNA methylation signatures in 131 pretreatment cases and 274 controls. Implementation of the CIT test revealed 17 CpG/SNP pairs, comprising 13 unique CpGs and 17 unique SNPs, which represent potential methylation-mediated relationships between genotype and EOC risk. Of these 13 CpGs, several are associated with immune related genes and genes that have been previously shown to exhibit altered expression in the context of cancer.ConclusionsThese findings provide additional insight into EOC etiology and may serve as novel biomarkers for EOC susceptibility.

Kernel canonical correlation analysis for assessing gene–gene interactions and application to ovarian cancer

Although single-locus approaches have been widely applied to identify disease-associated single-nucleotide polymorphisms (SNPs), complex diseases are thought to be the product of multiple interactions between loci. This has led to the recent development of statistical methods for detecting statistical interactions between two loci. Canonical correlation analysis (CCA) has previously been proposed to detect gene–gene coassociation. However, this approach is limited to detecting linear relations and can only be applied when the number of observations exceeds the number of SNPs in a gene. This limitation is particularly important for next-generation sequencing, which could yield a large number of novel variants on a limited number of subjects. To overcome these limitations, we propose an approach to detect gene–gene interactions on the basis of a kernelized version of CCA (KCCA). Our simulation studies showed that KCCA controls the Type-I error, and is more powerful than leading gene-based approaches under a disease model with negligible marginal effects. To demonstrate the utility of our approach, we also applied KCCA to assess interactions between 200 genes in the NF-κB pathway in relation to ovarian cancer risk in 3869 cases and 3276 controls. We identified 13 significant gene pairs relevant to ovarian cancer risk (local false discovery rate <0.05). Finally, we discuss the advantages of KCCA in gene–gene interaction analysis and its future role in genetic association studies.

Risk of ovarian cancer and inherited variants in relapse-associated genes.

Background We previously identified a panel of genes associated with outcome of ovarian cancer. The purpose of the current study was to assess whether variants in these genes correlated with ovarian cancer risk. Methods and Findings Women with and without invasive ovarian cancer (749 cases, 1,041 controls) were genotyped at 136 single nucleotide polymorphisms (SNPs) within 13 candidate genes. Risk was estimated for each SNP and for overall variation within each gene. At the gene-level, variation within MSL1 (male-specific lethal-1 homolog) was associated with risk of serous cancer (p = 0.03); haplotypes within PRPF31 (PRP31 pre-mRNA processing factor 31 homolog) were associated with risk of invasive disease (p = 0.03). MSL1 rs7211770 was associated with decreased risk of serous disease (OR 0.81, 95% CI 0.66–0.98; p = 0.03). SNPs in MFSD7, BTN3A3, ZNF200, PTPRS, and CCND1A were inversely associated with risk (p<0.05), and there was increased risk at HEXIM1 rs1053578 (p = 0.04, OR 1.40, 95% CI 1.02–1.91). Conclusions Tumor studies can reveal novel genes worthy of follow-up for cancer susceptibility. Here, we found that inherited markers in the gene encoding MSL1, part of a complex that modifies the histone H4, may decrease risk of invasive serous ovarian cancer.