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PolyADP-ribose polymerase (PARP) inhibitors (PARPis) represent the first clinically approved drugs able to provoke “synthetic lethality” in patients with homologous recombination-deficient (HRD) tumors. Four PARPis have just received approval for the treatment of several types of cancer. Besides, another three additional PARPis underlying the same mechanism of action are currently under investigation. Despite the success of these targeted agents, the increasing use of PARPis in clinical practice for the treatment of different tumors raised the issue of PARPis resistance, and the consequent disease relapse and dismal prognosis for patients. Several mechanisms of resistance have been investigated, and ongoing studies are currently focusing on strategies to address this challenge and overcome PARPis resistance. This review aims to analyze the mechanisms underlying PARPis resistance known today and discuss potential therapeutic strategies to overcome these processes of resistance in the future.

Radiogenomics is a specific application of radiomics where imaging features are linked to genomic profiles. We aim to develop a radiogenomics model based on ovarian US images for predicting germline BRCA1/2 gene status in women with healthy ovaries. From January 2013 to December 2017 a total of 255 patients addressed to germline BRCA1/2 testing and pelvic US documenting normal ovaries, were retrospectively included. Feature selection for univariate analysis was carried out via correlation analysis. Multivariable analysis for classification of germline BRCA1/2 status was then carried out via logistic regression, support vector machine, ensemble of decision trees and automated machine learning pipelines. Data were split into a training (75%) and a testing (25%) set. The four strategies obtained a similar performance in terms of accuracy on the testing set (from 0.54 of logistic regression to 0.64 of the auto-machine learning pipeline). Data coming from one of the tested US machine showed generally higher performances, particularly with the auto-machine learning pipeline (testing set specificity 0.87, negative predictive value 0.73, accuracy value 0.72 and 0.79 on training set). The study shows that a radiogenomics model on machine learning techniques is feasible and potentially useful for predicting g BRCA1/2 status in women with healthy ovaries.

PurposeThe aim was to compare a protocol of uterine artery embolization (UAE) consisting in three digital subtraction angiographies (DSAs)—Group A, with a protocol based on a single DSA—Group B.Materials and MethodsThis is a single-center prospective randomized study enrolling 20 women (mean age 41 years, range 22–55 years) with uterine fibroids treated with UAE, from January 2015 to February 2016. All UAEs were performed by two interventional radiologists using the same angiography machine. Protocol of Group A consisted in three DSA runs (non-selective pelvic view and selective uterine views before and after embolization). Protocol of Group B consisted in 1 DSA run: selective UA angiography before embolization. (Fluoroscopic roadmap was used for UA catheterization; fluoroscopy storage was used as control after embolization.) Each patient was randomized to receive Protocol A in one pelvic side and Protocol B on the other.ResultsAll patients received bilateral UAE. Mean fluoroscopy time for UA catheterization was 11.3 ± 3.7 s. (Protocol A) and 9.93 ± 2.99 s. (Protocol B) (p = 0.19). Fluoroscopy dose for catheterization and embolization was not different between both protocols (p = 0.14). Identification of the UA origin score was similar in both protocols (median error = 0, p = 0.79). Mean dose area product (DAP) was 40859 mGy/cm2 (Protocol A) and 28839 mGy/cm2 (Protocol B) (p = 0.003). Mean effective dose (ED) decreased from Protocol A (14.6 mSv) to Protocol B (9.2 mSv; − 37%). Mean absorbed dose (AD) to ovaries and uterus, respectively, decreased of 53% and 55% from Protocol A to Protocol B.ConclusionReducing the number of DSA runs from 3 to 1 during UAE allows at least a 30% reduction on radiation exposure, without compromising technical outcomes.

The 2022 Delphi revision of the MUSA (Morphological Uterus Sonographic Assessment) criteria for the ultrasound diagnosis of adenomyosis divides the ultrasound signs for diagnosis into direct and indirect ones, considering the presence of at least one direct sign as a mandatory criterion. This study aimed to reclassify the patients referred to the Pelvic Pain specialist outpatient clinic of the Gynecological Clinic of Udine according to the new criteria, evaluating the number of overdiagnoses and the possible correlation between the direct and indirect signs and the patients’ symptoms. 62 patients affected by adenomyosis were retrospectively recruited. The patients were then re-evaluated by ultrasound and clinically. At least one direct sign of adenomyosis was found in 52 patients, while 16% of the population examined did not present any. There was no statistically significant difference between patients presenting direct signs and those presenting none for the symptoms considered. According to the new criteria, 16% of the patients examined were not affected by adenomyosis; applying the new consensus to symptomatic patients could increase false negatives. In a population of symptomatic patients, the diagnosis of adenomyosis is still highly probable even without direct ultrasound signs, given the clinical symptoms and having ruled out other causes of such symptoms.

Objective: To develop and validate magnetic resonance (MR) imaging-based radiomics models for high-risk endometrial cancer (EC) prediction preoperatively, to be able to estimate deep myometrial invasion (DMI) and lymphovascular space invasion (LVSI), and to discriminate between low-risk and other categories of risk as proposed by ESGO/ESTRO/ESP (European Society of Gynaecological Oncology—European Society for Radiotherapy & Oncology and European Society of Pathology) guidelines. Methods: This retrospective study included 96 women with EC who underwent 1.5-T MR imaging before surgical staging between April 2009 and May 2019 in two referral centers divided into training (T = 73) and validation cohorts (V = 23). Radiomics features were extracted using the MODDICOM library with manual delineation of whole-tumor volume on MR images (axial T2-weighted). Diagnostic performances of radiomic models were evaluated by area under the receiver operating characteristic (ROC) curve in training (AUCT) and validation (AUCV) cohorts by using a subset of the most relevant texture features tested individually in univariate analysis using Wilcoxon–Mann–Whitney. Results: A total of 228 radiomics features were extracted and ultimately limited to 38 for DMI, 29 for LVSI, and 15 for risk-classes prediction for logistic radiomic modeling. Whole-tumor radiomic models yielded an AUCT/AUCV of 0.85/0.68 in DMI estimation, 0.92/0.81 in LVSI prediction, and 0.84/0.76 for differentiating low-risk vs other risk classes (intermediate/high-intermediate/high). Conclusion: MRI-based radiomics has great potential in developing advanced prognostication in EC.

A multicenter cross-sectional survey study involving four Italian University Hospitals was performed to test the hypothesis that negative affect and positive affect (affective dimensions) mediate the association between risk perception (perceived risk of infection and death; cognitive dimensions) and the feeling of work exhaustion (WE) among obstetrics healthcare providers (HCPs) during the Coronavirus Disease 2019 (COVID-19) pandemic. Totally, 570 obstetrics HCPs were invited to complete the 104-item IPSICO survey in May 2020. A theoretical model built on the tested hypothesis was investigated by structural equation modelling. The model explained 32.2% of the WE variance. Only negative affect mediated the association between cognitive dimensions and WE and also the association between WE and psychological well-being before the pandemic, experiences of stressful events, female gender, and dysfunctional coping. Non-mediated associations with WE were observed for work perceived as a duty, experience of stressful events, support received by colleagues, and the shift strategy. Only previous psychological well-being, support by colleagues, and shift strategies were inversely associated with WE. Based on study results, monitoring negative than positive affect appears superior in predicting WE, with practical implications for planning psychological interventions in HCPs at the individual, interpersonal, and organizational levels.

PTEN is a tumour suppressor gene, and its loss of function is frequently observed in both heritable and sporadic cancers. It is involved in a great variety of biological processes, including maintenance of genomic stability, cell survival, migration, proliferation and metabolism. A better understanding of PTEN activity and regulation has therefore emerged as a subject of primary interest in cancer research. Gynaecological cancers are variously interested by PTEN deregulation and many perspective in terms of additional prognostic information and new therapeutic approaches can be explored. Here, we present the most significant findings on PTEN in gynaecological cancers (ovarian, endometrial, cervical, vulvar and uterine cancer) focusing on PTEN alterations incidence, biological role and clinical implications.

IOTA ADNEX2 showed an increased risk of malignancy, with highest relative risk either for stage II–IV ovarian cancer or for metastatic cancer to the adnexa (link to the IOTA ADNEX model calculator: https://www.iotagroup.org/sites/default/files/adnexmodel/IOTA-ADNEXmodel.html). [...]the tumor was classified as Ovarian-Adnexal Reporting and Data System (O-RADS) 5.3 At laparoscopy, the presence of the right ovarian mass was confirmed. [...]a right salpingo-oophorectomy and peritoneal biopsies were performed. IOTA ADNEX showed an increased risk of malignancy, with highest relative risk either for stage II–IV ovarian cancer or for metastatic cancer to the adnexa (link to the IOTA ADNEX model calculator: https://www.iotagroup.org/sites/default/files/adnexmodel/IOTA-ADNEXmodel.html). [...]the tumor was classified as O-RADS 5.3 MRI showed bilateral adnexal solid masses of 11 cm (right mass) and 5.5 cm (left mass), respectively; ascites, abdominal and pelvic lymphadenopathy, and nodules in both liver and right adrenal gland were present.

Human papillomavirus (HPV) infection is the recognized cause of almost all cervical cancers. Despite the reduction in incidence due to a wide use of screening programs and a specific vaccine, the prognosis of cervical cancer remains poor, especially for late-stage and relapsed disease. Considering the elevated rates of PD-L1 expression in up to 80% of cervical cancers, a strong rationale supports the use of immunotherapy to restore the immune response against tumor. The aim of this review is to analyze the possible role of immune checkpoint inhibitors in cervical cancer treatment, with a particular focus on the rationale and on the results of phase I and II clinical trials. An overview of ongoing phase III studies with possible future areas of development is also provided.

IntroductionRecurrence of endometrial cancer is an important clinical challenge, with median survival rarely exceeding 12 months. The aim of this study was to analyze patterns of endometrial cancer recurrence and associations of these patterns with clinical outcome.MethodsThe study included patients with endometrial cancer who underwent primary surgical treatment with or without adjuvant treatment between July 2004 and June 2017 at the Gynaecologic Oncology Unit of one of three tertiary hospitals of the Catholic University Network in Italy with complete follow-up data available. Information on the date and pattern of recurrence was retrieved for each relapse. Post-relapse survival was recorded as the time from the date of recurrence to the date of death or last follow-up. Survival probabilities were compared using log rank tests, and associations of clinico-pathological characteristics with post-relapse survival were tested using Cox’s regression models.ResultsA total of 1503 patients were included in the analysis. We identified 210 recurrences (14.0%) and 105 deaths (7.0%) at a median follow-up of 34 months (range 1–162). One hundred and fifty-eight recurrences (78.1%) occurred during the first two years of follow-up. Most recurrences were multifocal (n=121, 57.6%) and involved extrapelvic sites (n=38, 65.7%). Parameters associated with post-relapse survival in the univariate analysis included histotype, grade, time to recurrence, pattern of recurrence, number of relapsing lesions, and secondary radical surgery. Only the pattern of recurrence and secondary radical surgery were independent predictors of post-relapse survival in the multivariate analysis (p=0.025 and p=0.0001, respectively).ConclusionLymph node recurrence and the feasibility of secondary radical surgery were independent predictors of post-relapse survival in patients with recurrent endometrial cancer.