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Background: The accurate discrimination of uterine leiomyosarcomas and leiomyomas in a pre-operative setting remains a current challenge. To date, the diagnosis is made by a pathologist on the excised tumor. The aim of this study was to develop a machine learning algorithm using radiomic data extracted from contrast-enhanced computed tomography (CECT) images that could accurately distinguish leiomyosarcomas from leiomyomas. Methods: Pre-operative CECT images from patients submitted to surgery with a histological diagnosis of leiomyoma or leiomyosarcoma were used for the region of interest identification and radiomic feature extraction. Feature extraction was conducted using the PyRadiomics library, and three feature selection methods combined with the general linear model (GLM), random forest (RF), and support vector machine (SVM) classifiers were built, trained, and tested for the binary classification task (malignant vs. benign). In parallel, radiologists assessed the diagnosis with or without clinical data. Results: A total of 30 patients with leiomyosarcoma (mean age 59 years) and 35 patients with leiomyoma (mean age 48 years) were included in the study, comprising 30 and 51 lesions, respectively. Out of nine machine learning models, the three feature selection methods combined with the GLM and RF classifiers showed good performances, with predicted area under the curve (AUC), sensitivity, and specificity ranging from 0.78 to 0.97, from 0.78 to 1.00, and from 0.67 to 0.93, respectively, when compared to the results obtained from experienced radiologists when blinded to the clinical profile (AUC = 0.73 95%CI = 0.62–0.84), as well as when the clinical data were consulted (AUC = 0.75 95%CI = 0.65–0.85). Conclusions: CECT images integrated with radiomics have great potential in differentiating uterine leiomyomas from leiomyosarcomas. Such a tool can be used to mitigate the risks of eventual surgical spread in the case of leiomyosarcoma and allow for safer fertility-sparing treatment in patients with benign uterine lesions.

Background: Current prognostic models lack the use of pre-operative CT images to predict recurrence in endometrial cancer (EC) patients. Our study aimed to investigate the potential of radiomic features extracted from pre-surgical CT scans to accurately predict disease-free survival (DFS) among EC patients. Methods: Contrast-Enhanced CT (CE-CT) scans from 81 EC cases were used to extract the radiomic features from semi-automatically contoured volumes of interest. We employed a 10-fold cross-validation approach with a 6:4 training to test set and utilized data augmentation and balancing techniques. Univariate analysis was applied for feature reduction leading to the development of three distinct machine learning (ML) models for the prediction of DFS: LASSO-Cox, CoxBoost and Random Forest (RFsrc). Results: In the training set, the ML models demonstrated AUCs ranging from 0.92 to 0.93, sensitivities from 0.96 to 1.00 and specificities from 0.77 to 0.89. In the test set, AUCs ranged from 0.86 to 0.90, sensitivities from 0.89 to 1.00 and specificities from 0.73 to 0.90. Patients classified as having a high recurrence risk prediction by ML models exhibited significantly worse DSF (p-value < 0.001) across all models. Conclusions: Our findings demonstrate the potential of radiomics in predicting EC recurrence. While further validation studies are needed, our results underscore the promising role of radiomics in forecasting EC outcomes.

BRCA testing is recommended in all Ovarian Cancer (OC) patients, but the optimal approach is debated. The landscape of BRCA alterations was explored in 30 consecutive OC patients: 6 (20.0%) carried germline pathogenic variants, 1 (3.3%) a somatic mutation of BRCA2, 2 (6.7%) unclassified germline variants in BRCA1, and 5 (16.7%) hypermethylation of the BRCA1 promoter. Overall, 12 patients (40.0%) showed BRCA deficit (BD), due to inactivation of both alleles of either BRCA1 or BRCA2, while 18 (60.0%) had undetected/unclear BRCA deficit (BU). Regarding sequence changes, analysis performed on Formalin-Fixed-Paraffin-Embedded tissue through a validated diagnostic protocol showed 100% accuracy, compared with 96.3% for Snap-Frozen tissue and 77.8% for the pre-diagnostic Formalin-Fixed-Paraffin-Embedded protocol. BD tumors, compared to BU, showed a significantly higher rate of small genomic rearrangements. After a median follow-up of 60.3 months, the mean PFS was 54.9 ± 27.2 months in BD patients and 34.6 ± 26.7 months in BU patients (p = 0.055). The analysis of other cancer genes in BU patients identified a carrier of a pathogenic germline variant in RAD51C. Thus, BRCA sequencing alone may miss tumors potentially responsive to specific treatments (due to BRCA1 promoter methylation or mutations in other genes) while unvalidated FFPE approaches may yield false-positive results.

Uterine sarcomas are rare cancers, sometimes diagnosed in women of childbearing age. Hysterectomy is the standard treatment in early stages. The option of lesion removal to save fertility is described in the literature, but it is still considered experimental. The objective of this systematic review is to report on the available evidence on the reproductive and oncological outcomes of fertility-sparing treatment in women with uterine sarcomas. PubMed, Scopus and Cochrane Central Register of Controlled Trials were searched between 1 January 2011 and 21 June 2021 for publications in English about women with uterine sarcoma treated with a fertility-sparing intervention. Thirty-seven studies were included for a total of 210 patients: 63 low-grade endometrial stromal sarcomas, 35 embryonal rhabdomyosarcomas of the cervix, 19 adenosarcomas, 7 leiomyosarcomas and 2 uterine tumors resembling an ovarian sex cord. Conservative treatment ensured pregnancy in 32% of cases. In terms of oncological outcomes, relapse was related to histology and the worst prognosis was reported for leiomyosarcoma, followed by low-grade endometrial stromal sarcoma, which relapsed in 71% and 54% of cases, respectively. The highest death rate was associated with leiomyosarcoma (57.1%). This study demonstrated that fertility-sparing treatments may be employed in selected cases of early stage uterine sarcoma.

According to our systematic literature review (PRISMA guidelines), only 37 vulvar squamous cell carcinomas (VSCCs) were diagnosed during pregnancy (age range: 17–41 years). The tumor size range was 0.3–15 cm. The treatment was performed after (14/37, 38%), before (10/37, 27%), or before-and-after delivery (11/37, 30%). We found that 21/37 (57%) cases were stage I, 2 II (5%), 11 III (30%), and 3 IVB (8%). HPV-related features (condylomas/warts; HPV infection; high-grade squamous intraepithelial lesion) were reported in 11/37 (30%) cases. We also found that 9/37 (24%) patients had inflammatory conditions (lichen sclerosus/planus, psoriasis, chronic dermatitis). The time-to-recurrence/progression (12/37, 32%) ranged from 0 to 36 (mean 9) months. Eight women died of disease (22%) 2.5–48 months after diagnosis, 2 (5%) were alive with disease, and 23 (62%) were disease-free at the end of follow-up. Pregnant patients must be followed-up. Even if they are small, newly arising vulvar lesions should be biopsied, especially in women with risk factors (HPV, dermatosis, etc.). The treatment of VSCCs diagnosed in late third trimester might be delayed until postpartum. Elective cesarean section may prevent vulvar wound dehiscence. In the few reported cases, pregnancy/fetal outcomes seemed to not be affected by invasive treatments during pregnancy. However, clinicians must be careful; larger cohorts should define the best treatment. Definite guidelines are lacking, so a multidisciplinary approach and discussion with patients are mandatory.

The collaborative Cancer Genome Atlas (TCGA) project identified four distinct prognostic groups of endometrial carcinoma (EC) based on molecular alterations: (i) the ultramutated subtype that encompasses POLE mutated (POLE) cases; (ii) the hypermutated subtype, characterized by MisMatch Repair deficiency (MMRd); (iii) the copy-number high subtype, with p53 abnormal/mutated features (p53abn); (iv) the copy-number low subtype, known as No Specific Molecular Profile (NSMP). Although the prognostic value of TCGA molecular classification, NSMP carcinomas present a wide variability in molecular alterations and biological aggressiveness. This study aims to investigate the impact of ARID1A and CTNNB1/β-catenin alterations by targeted Next-generation sequencing (NGS) and immunohistochemistry (IHC) in a consecutive series of 125 molecularly classified ECs. NGS and IHC were used to assign surrogate TCGA groups and to identify molecular alterations of multiple target genes including POLE, PTEN, ARID1A, CTNNB1, TP53. Associations with clinicopathologic parameters, molecular subtypes, and outcomes identified NSMP category as the most heterogeneous group in terms of clinicopathologic features and outcome. Integration of surrogate TCGA molecular classification with ARID1A and β-catenin analysis showed NSMP cases with ARID1A mutation characterized by the worst outcome with early recurrence, while NSMP tumors with ARID1A wild-type and β-catenin alteration had indolent clinicopathologic features and no recurrence. This study indicates how the identification of ARID1A and β-catenin alterations in EC represents a simple and effective way to characterize NSMP tumor aggressiveness and metastatic potential.

Background: Although the use of adjuvant chemotherapy (AC) appears to be increasing over the past few years, several clinical trials and previous meta-analyses failed to determine whether AC could improve clinical outcomes in uterine leiomyosarcoma (uLMS). The aim of this systematic review and meta-analysis was to compare AC (with or without radiotherapy) versus observation (obs) after primary surgery in early stage uLMS. Materials and Methods: Randomized controlled (RCTs) and non-randomized studies (NRSs) were retrieved. Outcomes of interest were as follows: distant recurrence rate, locoregional recurrence rate and overall recurrence rate. Results about distant recurrence rate, locoregional recurrence rate and overall recurrence rate were compared by calculating odds ratios (ORs) with 95% confidence intervals (CIs); ORs were combined with Mantel–Haenszel method. Results: Nine studies were included in the analysis, involving 545 patients (AC: 252, obs: 293). Compared with obs, AC did not reduce locoregional and distant recurrence rate, with a pooled OR of 1.36 and 0.63, respectively. Similarly, administration of AC did not decrease overall recurrence rate in comparison to obs. Conclusion: According to our results, AC (with or without radiotherapy) did not decrease recurrence rate in early stage uLMS; thus, the role of AC in this setting remains unclear.

BRAF exon 15 mutations are the most common molecular alterations found in papillary thyroid carcinoma (PTC). To date, there is no information regarding BRAF alterations in the thyroid parenchyma surrounding the tumor. To explore the early events associated with the development of PTC, we used massively parallel sequencing to investigate BRAF exon 15 in 30 PTCs and in 100 samples from the thyroid parenchyma surrounding the tumor. BRAF p.V600E was identified in 19/30 PTCs (63.3%). BRAF p.V600E mutations were identified in the tissue adjacent the PTC only in samples containing psammoma bodies. The other samples were either BRAF wild type (WT) or carried BRAF non p.V600E mutations. Specifically, BRAF p.G593D, -p.A598T, -p.V600M, -p.R603Q, -p.S607F, and -p.S607P were identified in 4 of 36 (11.1%) samples with follicular cell atypia, in 2 of 16 (12.5%) with follicular cell hyperplasia, and in 1 of 33 (3.0%) histologically normal samples—Only in tissue surrounding BRAF p.V600E mutated PTCs. These mutations are predicted to affect protein function in silico but, in vitro, have kinase activity and BRAF phosphorylation levels similar to BRAF WT. No BRAF exon 15 mutations were identified in samples adjacent to PTCs that were BRAF WT. A mutagenic process affecting BRAF exon 15 occurs in a subset of thyroid glands that develop BRAF p.V600E mutated PTCs.

It is unclear whether the site of origin of papillary thyroid microcarcinoma (mPTC) with respect to the thyroid surface has an influence on clinicopathologic parameters. The objectives of the study were to: (i) Accurately measure the mPTC distance from the thyroid surface; (ii) analyze whether this distance correlates with relevant clinicopathologic parameters; and (iii) investigate the impact of the site of origin of the mPTC on risk stratification. Clinicopathologic features and BRAF mutational status were analyzed and correlated with the site of origin of the mPTC in a multicenter cohort of 298 mPTCs from six Italian medical institutions. Tumors arise at a median distance of 3.5 mm below the surface of the thyroid gland. Statistical analysis identified four distinct clusters. Group A, mPTC: size ≥ 5 mm and distance of the edge of the tumor from the thyroid capsule = 0 mm; group B, mPTC: size ≥ 5 mm and distance of the edge of the tumor from the thyroid capsule > 0 mm; group C, mPTC: size < 5 mm and distance of the edge of the tumor from the thyroid capsule = 0 mm; and group D, mPTC: size < 5 mm and distance of the edge of the tumor from the thyroid capsule > 0 mm. Univariate analysis demonstrates significant differences between the groups: Group A shows the most aggressive features, and group D the most indolent ones. By multivariate analysis, group A tumors are characterized by tall cell histotype, BRAF V600E mutation, tumor fibrosis, aggressive growth with invasive features, vascular invasion, lymph node metastases, and intermediate ATA risk. The mPTC clinicopathologic features vary according to the tumor size and distance from the thyroid surface. A four-group model may be useful for risk stratification and to refine the selection of nodules to be targeted for fine needle aspiration.