Should we screen for ovarian cancer? A commentary on the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS) randomized trial

Novel gene signatures for prognosis prediction in ovarian cancer

Ovarian cancer (OV) is one of the leading causes of cancer deaths in women worldwide. Late diagnosis and heterogeneous treatment result to poor survival outcomes for patients with OV. Therefore, we aimed to develop novel biomarkers for prognosis prediction from the potential molecular mechanism of tumorigenesis. Eight eligible data sets related to OV in GEO database were integrated to identify differential expression genes (DEGs) between tumour tissues and normal. Enrichment analyses discovered DEGs were most significantly enriched in G2/M checkpoint signalling pathway. Subsequently, we constructed a multi‐gene signature based on the LASSO Cox regression model in the TCGA database and time‐dependent ROC curves showed good predictive accuracy for 1‐, 3‐ and 5‐year overall survival. Utility in various types of OV was validated through subgroup survival analysis. Risk scores formulated by the multi‐gene signature stratified patients into high‐risk and low‐risk, and the former inclined worse overall survival than the latter. By incorporating this signature with age and pathological tumour stage, a visual predictive nomogram was established, which was useful for clinicians to predict survival outcome of patients. Furthermore, SNRPD1 and EFNA5 were selected from the multi‐gene signature as simplified prognostic indicators. Higher EFNA5 expression or lower SNRPD1 indicated poorer outcome. The correlation between signature gene expression and clinical characteristics was observed through WGCNA. Drug‐gene interaction was used to identify 16 potentially targeted drugs for OV treatment. In conclusion, we established novel gene signatures as independent prognostic factors to stratify the risk of OV patients and facilitate the implementation of personalized therapies.

Ovarian cancer statistics, 2018

In 2018, there will be approximately 22,240 new cases of ovarian cancer diagnosed and 14,070 ovarian cancer deaths in the United States. Herein, the American Cancer Society provides an overview of ovarian cancer occurrence based on incidence data from nationwide population-based cancer registries and mortality data from the National Center for Health Statistics. The status of early detection strategies is also reviewed. In the United States, the overall ovarian cancer incidence rate declined from 1985 (16.6 per 100,000) to 2014 (11.8 per 100,000) by 29% and the mortality rate declined between 1976 (10.0 per 100,000) and 2015 (6.7 per 100,000) by 33%. Ovarian cancer encompasses a heterogenous group of malignancies that vary in etiology, molecular biology, and numerous other characteristics. Ninety percent of ovarian cancers are epithelial, the most common being serous carcinoma, for which incidence is highest in non-Hispanic whites (NHWs) (5.2 per 100,000) and lowest in non-Hispanic blacks (NHBs) and Asians/Pacific Islanders (APIs) (3.4 per 100,000). Notably, however, APIs have the highest incidence of endometrioid and clear cell carcinomas, which occur at younger ages and help explain comparable epithelial cancer incidence for APIs and NHWs younger than 55 years. Most serous carcinomas are diagnosed at stage III (51%) or IV (29%), for which the 5-year cause-specific survival for patients diagnosed during 2007 through 2013 was 42% and 26%, respectively. For all stages of epithelial cancer combined, 5-year survival is highest in APIs (57%) and lowest in NHBs (35%), who have the lowest survival for almost every stage of diagnosis across cancer subtypes. Moreover, survival has plateaued in NHBs for decades despite increasing in NHWs, from 40% for cases diagnosed during 1992 through 1994 to 47% during 2007 through 2013. Progress in reducing ovarian cancer incidence and mortality can be accelerated by reducing racial disparities and furthering knowledge of etiology and tumorigenesis to facilitate strategies for prevention and early detection. CA Cancer J Clin 2018;68:284-296. © 2018 American Cancer Society.

Parenclitic networks for predicting ovarian cancer

Prediction and diagnosis of complex disease may not always be possible with a small number of biomarkers. Modern 'omics' technologies make it possible to cheaply and quantitatively assay hundreds of molecules generating large amounts of data from individual samples. In this study, we describe a parenclitic network-based approach to disease classification using a synthetic data set modelled on data from the United Kingdom Collaborative Trial of Ovarian Cancer Screening (UKCTOCS) and serological assay data from a nested set of samples from the same study. This approach allows us to integrate quantitative proteomic and categorical metadata into a single network, and then use network topologies to construct logistic regression models for disease classification. In this study of ovarian cancer, comprising of 30 controls and cases with samples taken <14 months to diagnosis (n = 30) and/or >34 months to diagnosis (n = 29), we were able to classify cases with a sensitivity of 80.3% within 14 months of diagnosis and 18.9% in samples exceeding 34 months to diagnosis at a specificity of 98%. Furthermore, we use the networks to make observations about proteins within the cohort and identify GZMH and FGFBP1 as changing in cases (in relation to controls) at time points most distal to diagnosis. We conclude that network-based approaches may offer a solution to the problem of complex disease classification that can be used in personalised medicine and to describe the underlying biology of cancer progression at a system level.

Correlation between germline mutations in MMR genes and microsatellite instability in ovarian cancer specimens

A high proportion of ovarian cancers from women who carry germline mutations in mismatch repair (MMR) genes demonstrate microsatellite instability (MSI). The utility of pre-screening ovarian cancer specimens for MSI to identify potential patients for germline screening for MMR mutations is uncertain. 656 women with malignant ovarian cancer underwent both MSI testing and germline mutation testing for large rearrangements in three MMR genes, MLH1, MSH2 and MSH6. Germline DNA sequencing data for the same genes was available. Among the 656 women, only four (0.6%) carried a clearly pathogenic MMR mutation. All four cancers from patients with mutations had loss of two or more microsatellite markers (MSI-high). Eighty-four of 652 (13.0%) women without a mutation had MSI-high ovarian cancers. Using MSI-high as a prescreening criterion, the sensitivity of MSI testing to identify germline MMR gene mutations was 100% and the positive predictive value was 4.5%. Germline mutations in MLH1, MSH2 and MSH6 are rare among unselected cases of ovarian cancer. Patients with germline mutations often will have MSI-positive cancers and pre-screening of ovarian cancer specimens may be an efficient way of identifying patients with Lynch syndrome.

Current and future role of genetic screening in gynecologic malignancies

The world of hereditary cancers has seen exponential growth in recent years. While hereditary breast and ovarian cancer and Lynch syndrome account for the majority of mutations encountered by gynecologists, newly identified deleterious genetic mutations continue to be unearthed with their associated risks of malignancies. However, these advances in genetic cancer predispositions then force practitioners and their patients to confront the uncertainties of these less commonly identified mutations and the fact that there is limited evidence to guide them in expected cancer risk and appropriate risk-reduction strategies. Given the speed of information, it is imperative to involve cancer genetics experts when counseling these patients. In addition, coordination of screening and care in conjunction with specialty high-risk clinics, if available, allows for patients to have centralized management for multiple cancer risks under the guidance of physicians with experience counseling these patients. The objective of this review is to present the current literature regarding genetic mutations associated with gynecologic malignancies as well to propose screening and risk-reduction options for these high-risk patients.

Missed therapeutic and prevention opportunities in women with BRCA-mutated epithelial ovarian cancer and their families due to low referral rates for genetic counseling and BRCA testing: A review of the literature

Answer questions and earn CME/CNE Fifteen percent of women with epithelial ovarian cancer have inherited mutations in the BRCA breast cancer susceptibility genes. Knowledge of her BRCA status has value both for the woman and for her family. A therapeutic benefit exists for the woman with cancer, because a new family of oral drugs, the poly ADP-ribose polymerase (PARP) inhibitors, has recently been approved, and these drugs have the greatest efficacy in women who carry the mutation. For her family, there is the potential to prevent ovarian cancer in those carrying the mutation by using risk-reducing surgery. Such surgery significantly reduces the chance of developing this, for the most part, incurable cancer. Despite these potential benefits, referral rates for genetic counseling and subsequent BRCA testing are low, ranging from 10% to 30%, indicating that these therapeutic and prevention opportunities are being missed. The authors have reviewed the relevant available literature. Topics discussed are BRCA and its relation to ovarian cancer, the rates of referral for genetic counseling/BRCA testing, reasons for these low rates, potential strategies to improve on those rates, lack of effectiveness of current screening strategies, the pros and cons of risk-reducing surgery, other prevention options, and the role and value of PARP inhibitors. CA Cancer J Clin 2017;67:493-506. © 2017 American Cancer Society.

Cost-effectiveness of screening for ovarian cancer amongst postmenopausal women: a model-based economic evaluation

BACKGROUND

The United Kingdom Collaborative Trial of Ovarian Cancer Screening (UKCTOCS) was the biggest ovarian cancer screening trial to date. A non-significant effect of screening on ovarian cancer was reported, but the authors noted a potential delayed effect of screening, and suggested the need for four years further follow-up. There are no UK-based cost-effectiveness analyses of ovarian cancer screening. Hence we assessed the lifetime outcomes associated with, and the cost-effectiveness of, screening for ovarian cancer in the UK, along with the value of further research.

METHODS

We performed a model-based economic evaluation. Effectiveness data were taken from UKCTOCS, which considered strategies of multimodal screening (MMS), ultrasound screening (USS) and no screening. We conducted systematic reviews to identify the remaining model inputs, and performed a rigorous and transparent prospective evaluation of different methods for extrapolating the effect of screening on ovarian cancer mortality. We considered costs to the UK healthcare system and measured effectiveness using quality-adjusted life years (QALYs). We used value of information methods to estimate the value of further research.

RESULTS

Over a lifetime, MMS and USS were estimated to be both more expensive and more effective than no screening. USS was dominated by MMS, being both more expensive and less effective. Compared with no screening, MMS cost on average £419 more (95% confidence interval £255 to £578), and generated 0.047 more QALYs (0.002 to 0.088). The incremental cost-effectiveness ratio (ICER) comparing MMS with no screening was £8864 per QALY (£2600 to £51,576). Alternative extrapolation methods increased the ICER, with the highest value being £36,769 (£13,888 to dominated by no screening). Using the UKCTOCS trial horizon, both MMS and USS were dominated by no screening, as they produced fewer QALYs at a greater cost. The value of research into eliminating all uncertainty in long-term effectiveness was estimated to be worth up to £20 million, or approximately £5 million for four years follow-up.

CONCLUSIONS

Screening for ovarian cancer with MMS is both more effective and more expensive than not screening. Compared to national willingness to pay thresholds, lifetime cost-effectiveness is promising, but there remains considerable uncertainty regarding extrapolated long-term effectiveness.

Ovarian cancer screening effectiveness: A realization from the UK Collaborative Trial of Ovarian Cancer Screening

Effects on survival in the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS) was reported in The Lancet, and demonstrate that reductions in disease-specific mortality in this randomized control trial (RCT) indicate that ovarian cancer screening works. The UKCTOCS was large enough for sufficient accrual and follow-up, using two intervention arms: MMS (a multimodal strategy using the biomarker Ca125 combined with ultrasound as a secondary test) and USS (ultrasound alone) compared against a no-screen control group. MMS and USS performed similarly, showing a statistically significant reduction in mortality that increased with follow-up surveillance (8% reduction in years 0-7 vs 28% in years 7-14). The data led to the estimate that 641 screens are needed to prevent one ovarian cancer death.

Abnormal plasma DNA profiles in early ovarian cancer using a non-invasive prenatal testing platform: implications for cancer screening

BACKGROUND

Non-invasive prenatal testing (NIPT) identifies fetal aneuploidy by sequencing cell-free DNA in the maternal plasma. Pre-symptomatic maternal malignancies have been incidentally detected during NIPT based on abnormal genomic profiles. This low coverage sequencing approach could have potential for ovarian cancer screening in the non-pregnant population. Our objective was to investigate whether plasma DNA sequencing with a clinical whole genome NIPT platform can detect early- and late-stage high-grade serous ovarian carcinomas (HGSOC).

METHODS

This is a case control study of prospectively-collected biobank samples comprising preoperative plasma from 32 women with HGSOC (16 'early cancer' (FIGO I-II) and 16 'advanced cancer' (FIGO III-IV)) and 32 benign controls. Plasma DNA from cases and controls were sequenced using a commercial NIPT platform and chromosome dosage measured. Sequencing data were blindly analyzed with two methods: (1) Subchromosomal changes were called using an open source algorithm WISECONDOR (WIthin-SamplE COpy Number aberration DetectOR). Genomic gains or losses ≥ 15 Mb were prespecified as "screen positive" calls, and mapped to recurrent copy number variations reported in an ovarian cancer genome atlas. (2) Selected whole chromosome gains or losses were reported using the routine NIPT pipeline for fetal aneuploidy.

RESULTS

We detected 13/32 cancer cases using the subchromosomal analysis (sensitivity 40.6 %, 95 % CI, 23.7-59.4 %), including 6/16 early and 7/16 advanced HGSOC cases. Two of 32 benign controls had subchromosomal gains ≥ 15 Mb (specificity 93.8 %, 95 % CI, 79.2-99.2 %). Twelve of the 13 true positive cancer cases exhibited specific recurrent changes reported in HGSOC tumors. The NIPT pipeline resulted in one "monosomy 18" call from the cancer group, and two "monosomy X" calls in the controls.

CONCLUSIONS

Low coverage plasma DNA sequencing used for prenatal testing detected 40.6 % of all HGSOC, including 38 % of early stage cases. Our findings demonstrate the potential of a high throughput sequencing platform to screen for early HGSOC in plasma based on characteristic multiple segmental chromosome gains and losses. The performance of this approach may be further improved by refining bioinformatics algorithms and targeting selected cancer copy number variations.

Validation of a Novel Biomarker Panel for the Detection of Ovarian Cancer

BACKGROUND

Ovarian cancer is the most lethal gynecological malignancy. Our integrated -omics approach to ovarian cancer biomarker discovery has identified kallikrein 6 (KLK6) and folate-receptor 1 (FOLR1) as promising candidates but these markers require further validation.

METHODS

KLK6, FOLR1, CA125, and HE4 were investigated in three independent serum cohorts with a total of 20 healthy controls, 150 benign controls, and 216 ovarian cancer patients. The serum biomarker levels were determined by ELISA or automated immunoassay.

RESULTS

All biomarkers demonstrated elevations in the sera of ovarian cancer patients compared with controls (P < 0.01). Overall, CA125 and HE4 displayed the strongest ability (AUC 0.80 and 0.82, respectively) to identify ovarian cancer patients and the addition of HE4 to CA125 improved the sensitivity from 36% to 67% at a set specificity of 95%. In addition, the combination of HE4 and FOLR1 was a strong predictor of ovarian cancer diagnosis, displaying comparable sensitivity (65%) to the best-performing CA125-based models (67%) at a set specificity of 95%.

CONCLUSIONS

The markers identified through our integrated -omics approach performed similarly to the clinically approved markers CA125 and HE4. Furthermore, HE4 represents a powerful diagnostic marker for ovarian cancer and should be used more routinely in a clinical setting.

IMPACT

The implications of our study are 2-fold: (i) we have demonstrated the strengths of HE4 alone and in combination with CA125, lending credence to increasing its usage in the clinic; and (ii) we have demonstrated the clinical utility of our integrated -omics approach to identifying novel serum markers with comparable performance to clinical markers. Cancer Epidemiol Biomarkers Prev; 25(9); 1333-40. ©2016 AACR.