Anne Crijns

Survival-related profile, pathways, and transcription factors in ovarian cancer.

Background Ovarian cancer has a poor prognosis due to advanced stage at presentation and either intrinsic or acquired resistance to classic cytotoxic drugs such as platinum and taxoids. Recent large clinical trials with different combinations and sequences of classic cytotoxic drugs indicate that further significant improvement in prognosis by this type of drugs is not to be expected. Currently a large number of drugs, targeting dysregulated molecular pathways in cancer cells have been developed and are introduced in the clinic. A major challenge is to identify those patients who will benefit from drugs targeting these specific dysregulated pathways.The aims of our study were (1) to develop a gene expression profile associated with overall survival in advanced stage serous ovarian cancer, (2) to assess the association of pathways and transcription factors with overall survival, and (3) to validate our identified profile and pathways/transcription factors in an independent set of ovarian cancers. Methods and Findings According to a randomized design, profiling of 157 advanced stage serous ovarian cancers was performed in duplicate using ∼35,000 70-mer oligonucleotide microarrays. A continuous predictor of overall survival was built taking into account well-known issues in microarray analysis, such as multiple testing and overfitting. A functional class scoring analysis was utilized to assess pathways/transcription factors for their association with overall survival. The prognostic value of genes that constitute our overall survival profile was validated on a fully independent, publicly available dataset of 118 well-defined primary serous ovarian cancers. Furthermore, functional class scoring analysis was also performed on this independent dataset to assess the similarities with results from our own dataset. An 86-gene overall survival profile discriminated between patients with unfavorable and favorable prognosis (median survival, 19 versus 41 mo, respectively; permutation p-value of log-rank statistic = 0.015) and maintained its independent prognostic value in multivariate analysis. Genes that composed the overall survival profile were also able to discriminate between the two risk groups in the independent dataset. In our dataset 17/167 pathways and 13/111 transcription factors were associated with overall survival, of which 16 and 12, respectively, were confirmed in the independent dataset. Conclusions Our study provides new clues to genes, pathways, and transcription factors that contribute to the clinical outcome of serous ovarian cancer and might be exploited in designing new treatment strategies.

Modest effect of p53, EGFR and HER-2/neu on prognosis in epithelial ovarian cancer: a meta-analysis

Background:P53, EGFR and HER-2/neu are the most frequently studied molecular biological parameters in epithelial ovarian cancer, but their prognostic impact is still unequivocal. We performed a meta-analysis to more precisely estimate their prognostic significance.Methods:Published studies that investigated the association between p53, EGFR and HER-2/neu status and survival were identified. Meta-analysis was performed using a DerSimonian–Laird model. Publication bias was investigated using funnel plots and sources of heterogeneity were identified using meta-regression analysis.Results:A total of 62 studies were included for p53, 15 for EGFR and 20 for HER-2/neu. P53, EGFR and HER-2/neu status had a modest effect on overall survival (pooled HR 1.47, 95% CI 1.33–1.61 for p53; HR 1.65, 95% CI 1.25–2.19 for EGFR and HR 1.67, 95% CI 1.34–2.08 for HER-2/neu). Meta-regression analysis for p53 showed that FIGO stage distribution influenced study outcome. For EGFR and HER-2/neu, considerable publication bias was present.Conclusions:Although p53, EGFR and HER-2/neu status modestly influences survival, these markers are, by themselves, unlikely to be useful as prognostic markers in clinical practice. Our study highlights the need for well-defined, prospective clinical trials and more complete reporting of results of prognostic factor studies.

The ErbB signalling pathway: protein expression and prognostic value in epithelial ovarian cancer

Ovarian cancer is the most frequent cause of death from gynaecological cancer in the Western world. Current prognostic factors do not allow reliable prediction of response to chemotherapy and survival for individual ovarian cancer patients. Epidermal growth factor receptor (EGFR) and HER-2/neu are frequently expressed in ovarian cancer but their prognostic value remains unclear. In this study, we investigated the expression and prognostic value of EGFR, EGFR variant III (EGFRvIII), HER-2/neu and important downstream signalling components in a large series of epithelial ovarian cancer patients. Immunohistochemical staining of EGFR, pEGFR, EGFRvIII, Her-2/neu, PTEN (phosphatase and tensin homologue deleted on chromosome 10), total and phosphorylated AKT (pAKT) and phosphorylated ERK (pERK) was performed in 232 primary tumours using the tissue microarray platform and related to clinicopathological characteristics and survival. In addition, EGFRvIII expression was determined in 45 tumours by RT–PCR. Our results show that negative PTEN immunostaining was associated with stage I/II disease (P=0.006), non-serous tumour type (P=0.042) and in multivariate analysis with a longer progression-free survival (P=0.015). Negative PTEN staining also predicted improved progression-free survival in patients with grade III or undifferentiated serous carcinomas (P=0.011). Positive pAKT staining was associated with advanced-stage disease (P=0.006). Other proteins were expressed only at low levels, and were not associated with any clinicopathological parameter or survival. None of the tumours were positive for EGFRvIII. In conclusion, our results indicate that tumours showing negative PTEN staining could represent a subgroup of ovarian carcinomas with a relatively favourable prognosis.

Factors influencing p53 expression in ovarian cancer as a biomarker of clinical outcome in multicentre studies

The prognostic impact of p53 immunostaining in a large series of tumours from epithelial ovarian cancer patients in a two-centre study was analysed. The study population (n=476) comprised of a retrospective series of 188 patients (Dutch cohort) and a prospective series of 288 patients (Scottish cohort) enrolled in clinical trials. P53 expression was determined by immunohistochemistry on tissue microarrays. Association with progression-free survival (PFS) and overall survival (OS) was analysed by univariate and multivariate Cox regression analysis. Aberrant p53 overexpression was significantly associated with PFS in the Dutch and Scottish cohorts (P=0.001 and 0.038, respectively), but not with OS in univariate analysis. In multivariate analysis, when the two groups were combined and account taken of clinical factors and country of origin of the cohort, p53 expression was not an independent prognostic predictor of PFS or OS. In this well-powered study with minimal methodological variability, p53 immunostaining is not an independent prognostic marker of clinical outcome in epithelial ovarian cancer. The data demonstrate the importance of methodological standardisation, particularly defining patient characteristics and survival end-point data, if biomarker data from multicentre studies are to be combined.

Validation and Modification of a Prediction Model for Acute Cardiac Events in Patients With Breast Cancer Treated With Radiotherapy Based on Three-Dimensional Dose Distributions to Cardiac Substructures

Purpose A relationship between mean heart dose (MHD) and acute coronary event (ACE) rate was reported in a study of patients with breast cancer (BC). The main objective of our cohort study was to validate this relationship and investigate if other dose-distribution parameters are better predictors for ACEs than MHD. Patients and Methods The cohort consisted of 910 consecutive female patients with BC treated with radiotherapy (RT) after breast-conserving surgery. The primary end point was cumulative incidence of ACEs within 9 years of follow-up. Both MHD and various dose-distribution parameters of the cardiac substructures were collected from three-dimensional computed tomography planning data. Results The median MHD was 2.37 Gy (range, 0.51 to 15.25 Gy). The median follow-up time was 7.6 years (range, 0.1 to 10.1 years), during which 30 patients experienced an ACE. The cumulative incidence of ACE increased by 16.5% per Gy (95% CI, 0.6 to 35.0; P = .042). Analysis showed that the volume of the left ventricle receiving 5 Gy (LV-V5) was the most important prognostic dose-volume parameter. The most optimal multivariable normal tissue complication probability model for ACEs consisted of LV-V5, age, and weighted ACE risk score per patient (c-statistic, 0.83; 95% CI, 0.75 to 0.91). Conclusion A significant dose-effect relationship was found for ACEs within 9 years after RT. Using MHD, the relative increase per Gy was similar to that reported in the previous study. In addition, LV-V5 seemed to be a better predictor for ACEs than MHD. This study confirms the importance of reducing exposure of the heart to radiation to avoid excess risk of ACEs after radiotherapy for BC.

Prognostic factors in ovarian cancer : current evidence and future prospects

Abstract In ovarian cancer, translational research on the prognostic impact of molecular biological factors has until now not led to clinical implementation of any of these factors. This is partly due to the often conflicting results of different prognostic factor studies on the same molecular biological factor. We have performed meta-analyses on studies in ovarian cancer on four putative prognostic molecular biological factors, epidermal growth factor-receptor (EGFR), HER-2/neu, glutathione-S-transferase (GST)-pi and p53. Odds ratios were estimated for the increase in death at 1 and 5 years for patients with ovarian cancer, harbouring aberrant EGFR, HER-2/neu, GST-pi and p53, respectively. Patients with aberrant Her2/neu or p53 in their tumours had significantly worse odds of surviving 1 and 5 years, respectively. Patients with aberrant EGFR in their tumours only had a significantly greater risk of mortality at 5 years, while there seemed to be a trend for a decreased probability of 5-year survival for patients with aberrant GST-pi in their tumours. Despite inevitable flaws (such as small individual study sizes, publication bias, etc.) our meta-analysis confirms that therapeutic drugs targeted at EGFR, HER-2/neu, GSTpi and p53 may have therapeutic potential. Since ovarian cancer is a relatively rare disease, international collaboration to increase the number of patients to be analysed is critical for progress in translational research on the prognostic impact of molecular biological factors and on innovative treatment in ovarian cancer. In addition it is important to reach a consensus about guidelines for the design, conduct and analysis of translational studies in ovarian cancer.

A biological question and a balanced (orthogonal) design: the ingredients to efficiently analyze two-color microarrays with Confirmatory Factor Analysis

BackgroundFactor analysis (FA) has been widely applied in microarray studies as a data-reduction-tool without any a-priori assumption regarding associations between observed data and latent structure (Exploratory Factor Analysis).A disadvantage is that the representation of data in a reduced set of dimensions can be difficult to interpret, as biological contrasts do not necessarily coincide with single dimensions. However, FA can also be applied as an instrument to confirm what is expected on the basis of pre-established hypotheses (Confirmatory Factor Analysis, CFA). We show that with a hypothesis incorporated in a balanced (orthogonal) design, including SelfSelf hybridizations, dye swaps and independent replications, FA can be used to identify the latent factors underlying the correlation structure among the observed two-color microarray data. An orthogonal design will reflect the principal components associated with each experimental factor. We applied CFA to a microarray study performed to investigate cisplatin resistance in four ovarian cancer cell lines, which only differ in their degree of cisplatin resistance.ResultsTwo latent factors, coinciding with principal components, representing the differences in cisplatin resistance between the four ovarian cancer cell lines were easily identified. From these two factors 315 genes associated with cisplatin resistance were selected, 199 genes from the first factor (False Discovery Rate (FDR): 19%) and 152 (FDR: 24%) from the second factor, while both gene sets shared 36. The differential expression of 16 genes was validated with reverse transcription-polymerase chain reaction.ConclusionOur results show that FA is an efficient method to analyze two-color microarray data provided that there is a pre-defined hypothesis reflected in an orthogonal design.

Radiation-induced fibrosis in the boost area after three-dimensional conformal radiotherapy with a simultaneous integrated boost technique for early-stage breast cancer: A multivariable prediction model

BACKGROUND AND PURPOSEnTo develop a multivariable prediction model for the risk of grade⩾2 fibrosis in the boost area after breast conserving surgery (BCS) followed by three-dimensional conformal radiotherapy (RT) with a simultaneous integrated photon boost (3D-CRT-SIB), five years after RT.nnnMATERIAL AND METHODSnThis prospective cohort study included 1,030 patients treated with RT for breast cancer (stage 0-III), after BCS. Data regarding physician-rated fibrosis and dose-volume parameters were available in 546 patients. A multivariable logistic regression model for grade⩾2 fibrosis was generated.nnnRESULTSnAt 5years, grade⩾2 fibrosis was observed in 13.4% of the patients. The multivariable analysis resulted in a prediction model for grade⩾2 fibrosis in the boost area including three independent variables: patient age, breast volume receiving⩾55Gy (V55 CTV breast) and the maximum radiation dose in the breast (Dmax).nnnCONCLUSIONSnA multivariable prediction model was developed including age, V55 CTV breast and Dmax for grade⩾2 fibrosis in the boost area after breast cancer RT using a 3D-CRT-SIB technique. This model can be used to estimate the risk of fibrosis and to optimize dose distributions aiming at reducing this risk.

Early Detection of Cardiovascular Changes After Radiotherapy for Breast Cancer: Protocol for a European Multicenter Prospective Cohort Study (MEDIRAD EARLY HEART Study)

Background Breast cancer is the most common cancer among women, and radiotherapy plays a major role in its treatment. However, breast cancer radiotherapy can lead to incidental irradiation of the heart, resulting in an increased risk for a variety of heart diseases arising many years after radiotherapy. Therefore, identifying breast cancer patients at the highest risk for radiation-induced cardiac complications is crucial for developing strategies for primary and secondary prevention, which may contribute to healthy aging. There is still a need for precise knowledge on the relationship between radiation dose to specific cardiac structures and early subclinical cardiac changes and their occurrence over time that could finally lead to cardiac complications. Objective The MEDIRAD EARLY HEART study aims to identify and validate new cardiac imaging and circulating biomarkers of radiation-induced cardiovascular changes arising within first 2 years of breast cancer radiotherapy and to develop risk models integrating these biomarkers combined with precise dose metrics of cardiac structures based on three-dimensional dosimetry. Methods The EARLY HEART study is a multicenter, prospective cohort study in which 250 women treated for breast cancer and followed for 2 years after radiotherapy will be included. Women treated with radiotherapy without chemotherapy for a unilateral breast cancer and aged 40-75 years meet the inclusion criteria. Baseline and follow-up data include cardiac measurements based on two-dimensional speckle-tracking echocardiography, computed tomography coronary angiography, cardiac magnetic resonance imaging, and a wide panel of circulating biomarkers of cardiac injury. The absorbed dose will be evaluated globally for the heart and different substructures. Furthermore, the dose-response relationship will allow modeling the radiation-induced occurrence and evolution of subclinical cardiac lesions and biomarkers to develop prediction models. Results This study details the protocol of the MEDIRAD EARLY HEART study and presents the main limits and advantages of this international project. The inclusion of patients began in 2017. Preliminary results are expected to be published in 2019, and complete analysis should be published in 2021. Conclusions The MEDIRAD EARLY HEART study will allow identifying the main cardiac imaging and blood-based determinants of radiation-induced cardiac injuries to better propose primary and secondary preventive measures in order to contribute to enhanced patient care and quality of life. Trial Registration ClinicalTrials.gov NCT03297346; https://clinicaltrials.gov/ct2/show/NCT03297346 (Archived by WebCite at http://www.webcitation.org/72KS7MIUU) Registered Report Identifier RR1-10.2196/9906

Is the coronary artery calcium score associated with acute coronary events in breast cancer patients treated with radiotherapy

BACKGROUND AND PURPOSEnThe main objective of this study was to test whether pre-treatment coronary artery calcium (CAC) was associated with the cumulative incidence of acute coronary events (ACE) among breast cancer (BC) patients treated with postoperative radiotherapy (RT).nnnMATERIAL AND METHODSnThe study population consisted of 939 consecutive female BC patients treated with RT. The association between CAC and ACE was tested using Cox-proportional hazard models. Known risk factors for ACE and the mean heart dose (MHD), collected from three-dimensional computed tomography planning data, were tested for confounding.nnnRESULTSnCAC scores varied from 0 to 2,859 (mean 27.3). The 9-year cumulative incidence of ACE was 3.2%, this was significantly associated with the pre-treatment CAC score. After correction for confounders, age, history of ischemic heart disease, diabetes, Body Mass Index ≥30, MHD, hypercholesterolemia and hypertension, the hazard ratio for ACE for the low and the combined intermediate and high CAC score category were 1.42 (95%CI: 0.49-4.17; pu202f=u202f0.519) and 4.95 (95%CI: 1.69-14.53; pu202f=u202f0.004) respectively, compared to the CAC zero category.nnnCONCLUSIONSnHigh pre-treatment CAC is associated with ACE in BC patients treated with postoperative RT, even after correction for confounding factors such as MHD.