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Introduction Ovarian carcinoma is the leading cause of death from gynecologic malignancies in the Western world [1]. Debulking surgery followed by platinum-based chemotherapy is considered standard of care for patients [...], 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.

Abstract Background Factor 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. Results Two 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. Conclusion Our 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.

This correction notice addresses an error in the original publication of a research article titled "DNA Methylation Alterations in Fractionally Irradiated Rats and Breast Cancer Patients Receiving Radiotherapy." The authors, Radia Tamarat and Susana Constantino Rosa Santos, were accidentally omitted from the list of authors in the published version. They contributed to the research by conducting rat heart irradiation and blood sampling experiments. The correction has been approved by the Academic Editor, and the original publication has been updated to include the missing authors. The authors state that this correction does not affect the scientific conclusions of the study. [Extracted from the article]

Peripheral T-cell lymphomas (PTCL) comprise a heterogeneous group of mature T-cell neoplasms with an unfavorable prognosis; presentation with stage I(E) disease is uncommon. In clinical practice, an abbreviated chemotherapy treatment regimen combined with radiotherapy (combined modality treatment [CMT]) is commonly used, although evidence from clinical trials is lacking. The aim of this nationwide population-based cohort study is to describe first-line treatment and outcome of patients with stage I(E) PTCL. All newly diagnosed patients ≥18 years with stage I(E) anaplastic large cell lymphoma (ALCL), angioimmunoblastic T-cell lymphoma (AITL) and peripheral T-cell lymphoma NOS (PTCL not otherise specified [NOS]) in 1989-2020 were identified in the Netherlands Cancer Registry. Patients were categorized according to treatment regimen, i.e., chemotherapy (CT), radiotherapy (RT), CMT, other therapy and no treatment. The primary endpoint was overall survival (OS). Patients with stage I(E) ALCL, AITL and PTCL NOS (n=576) were most commonly treated with CMT (28%) or CT (29%), 2% underwent SCT. RT only was given in 18%, and 8% received other therapy and 16% no treatment. Overall, the 5-year OS was 59%. According to subtype, 5-year OS was superior for ALCL as compared to PTCL NOS and AITL (68% vs. 55% and 52%, respectively; P=0.03). For patients treated with CMT, 5-year OS was significantly higher (72%) as compared to patients treated with either CT or RT alone (55% and 55%, respectively; P<0.01). In multivariable analysis, age per year increment (hazard ratio [HR] =1.06, 95% confidence interval [CI]: 1.05-1.07), male sex (HR=1.53, 95% CI: 1.23-1.90), and CT, or no treatment (HR=1.64, 95% CI: 1.21-2.21, and HR=1.55, 95% CI: 1.10-2.17, respectively) were associated with a higher risk of mortality. For stage I(E) ALCL, AITL and PTCL NOS, 5-year OS is 59%, comparing favorably to historical outcome in advanced-stage disease. Superior outcome estimates were observed in patients treated with CMT.

Background: In the case of breast cancer (BC), radiotherapy (RT) helps reduce locoregional recurrence and BC-related deaths but can lead to cardiotoxicity, resulting in an increased risk of long-term major cardiovascular events. It is therefore of primary importance to early detect subclinical left ventricular (LV) dysfunction in BC patients after RT and to determine the dose-response relationships between cardiac doses and these events., Methods: Within the frame of the MEDIRAD European project (2017-2022), the prospective multicenter EARLY-HEART study (ClinicalTrials.gov Identifier: NCT03297346) included chemotherapy naïve BC women aged 40-75 years and treated with lumpectomy and adjuvant RT. Myocardial strain analysis was provided using speckle-tracking echocardiography performed at baseline and 6 months following RT. A global longitudinal strain (GLS) reduction >15% between baseline and follow-up was defined as a GLS-based subclinical LV dysfunction. Individual patient dose distributions were obtained using multi-atlas-based auto-segmentation of the heart. Dose-volume parameters were studied for the whole heart (WH) and left ventricle (LV)., Results: The sample included 186 BC women (57.5 ± 7.9 years, 64% left-sided BC). GLS-based subclinical LV dysfunction was observed in 22 patients (14.4%). These patients had significantly higher cardiac exposure regarding WH and LV doses compared to patients without LV dysfunction (for mean WH dose: 2.66 ± 1.75 Gy versus 1.64 ± 0.96 Gy, p = 0.01). A significantly increased risk of subclinical LV dysfunction was observed with the increase in the dose received to the WH [ORs from 1.13 (V 5 ) to 1.74 (D mean ); p < 0.01] and to the LV [ORs from 1.10 (V 5 ) to 1.46 (D mean ); p < 0.01]. Based on ROC analysis, the LV-V 5 parameter may be the best predictor of the short-term onset of subclinical LV dysfunction., Conclusion: These results highlighted that all cardiac doses were strongly associated with the occurrence of subclinical LV dysfunction arising 6 months after BC RT. Whether measurements of GLS at baseline and 6 months after RT combined with cardiac doses can early predict efficiently subclinical events occurring 24 months after RT remains to be investigated., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Locquet, Spoor, Crijns, van der Harst, Eraso, Guedea, Fiuza, Santos, Combs, Borm, Mousseaux, Gencer, Frija, Cardis, Langendijk and Jacob.)

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., (©Valentin Walker, Anne Crijns, Johannes Langendijk, Daan Spoor, Rozemarijn Vliegenthart, Stephanie E Combs, Michael Mayinger, Arantxa Eraso, Ferran Guedea, Manuela Fiuza, Susana Constantino, Radia Tamarat, Dominique Laurier, Jean Ferrières, Elie Mousseaux, Elisabeth Cardis, Sophie Jacob. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 01.10.2018.)

Ovarian cancer ranks the most lethal among gynecologic neoplasms in women. To develop potential biomarkers for diagnosis, we have identified five novel genes (CYP39A1, GTF2A1, FOXD4L4, EBP, and HAAO) that are hypermethylated in ovarian tumors, compared with the non-malignant normal ovarian surface epithelia, using the quantitative methylation-specific polymerase chain reactions. Interestingly enough, multivariate Cox regression analysis has identified hypermethylation of CYP39A1 correlated with an increase rate of relapsing (P=0.032, hazard ratio >1). Concordant hypermethylation in at least three loci was observed in 50 out of 55 (91%) of ovarian tumors examined. The test sensitivity and specificity were assessed to be 96 and 67% for CYP39A1; 95 and 88% for GTF2A1; 93 and 67% for FOXD4L4; 81 and 67% for EBP; 89 and 82% for HAAO, respectively. Our data have identified, for the first time, GTF2A1 alone, or GTF2A1 plus HAAO are excellent candidate biomarkers for detecting this disease. Moreover, the known functions of these gene products further implicate dysregulated transcriptional control, cholesterol metabolism, or synthesis of quinolinic acids, may play important roles in attributing to ovarian neoplasm. Molecular therapies, by reversing the aberrant epigenomes using inhibitory agents or by abrogating the upstream signaling pathways that convey the epigenomic perturbations, may be developed into promising treatment regimens.