Frediano Inzani

One biopsy, two tumors: A case report of collision tumor consisting in breast and endometrioid carcinoma detected on bioptic sample of peritoneal carcinomatosis

Collision tumors are rare and very few cases were described in which collision was revealed in a metastatic lesion. Herein we report a case of woman with a peritoneal carcinomatosis underwent to bioptic procedure in correspondence of a nodule of Douglas peritoneum with clinical suspect of ovarian/uterine origin. Histologic examination revealed two different colliding epithelial neoplasms: an endometrioid carcinoma and a ductal breast carcinoma, the latter not suspected at the time of biopsy. Morphology and immunohistochemistry, in particular GATA3 and PAX8, defined clearly the two different colliding carcinomas.

TCGA Molecular Prognostic Groups of Endometrial Carcinoma: Current Knowledge and Future Perspectives

The four TCGA-based molecular prognostic groups of endometrial carcinoma (EC), i.e., POLE-mutant, mismatch repair (MMR)-deficient, p53-abnormal, and “no specific molecular profile” (NSMP), have recently been integrated into ESGO-ESTRO-ESP guidelines. The POLE-mutant and MMR-deficient groups are associated with high mutational load, morphological heterogeneity, and inflammatory infiltration. These groups are frequent in high-grade endometrioid, undifferentiated/dedifferentiated, and mixed histotypes. POLE-mutant ECs show good prognosis and do not require adjuvant treatment, although the management of cases at stage >II is still undefined. MMR-deficient ECs show intermediate prognosis and are currently substratified based on clinicopathological variables, some of which might not have prognostic value. These groups may benefit from immunotherapy. P53-mutant ECs are typically high-grade and often morphologically ambiguous, accounting for virtually all serous ECs, most carcinosarcomas and mixed ECs, and half of clear-cell ECs. They show poor prognosis and are treated with chemoradiotherapy; a subset may benefit from HER2 inhibitors or PARP inhibitors. The NSMP group is the most frequent TCGA group; its prognosis is highly variable and affected by clinicopathological/molecular factors, most of which are still under evaluation. In conclusion, the TCGA classification has improved diagnosis, risk stratification, and management of EC. Further studies are needed to resolve the points of uncertainty that still exist.

Pathological features, immunoprofile and mismatch repair protein expression status in uterine endometrioid carcinoma: focus on MELF pattern of myoinvasion

Microcystic, elongated, and fragmented (MELF) pattern of myoinvasion has been related with increased risk of lympho-vascular space invasion (LVSI) and lymph node metastasis. We analysed a cohort of endometrioid endometrial carcinomas (EECs) to examine the relationships between the MELF pattern of invasion and the clinico-pathological and immunohistochemical features of EEC. 129 EECs were evaluated for the presence of MELF pattern and immunohistochemically tested for Mismatch repair (MMR) proteins, p16, p53 and beta-catenin. We observed 28 MELF + EECs and 101 MELF- EECs. LVSI was observed in 20 MELF + cases and in MELF- tumors. Lymph-node metastases were observed in 7 MELF + cases (2 macrometastases, 3 micrometastases and 2 ITCs). None of the MELF- cases showed micrometastases or ITCs, 18 cases had macrometastatic lymph-nodes. Statistical analysis showed that MELF + tumors carry an increased risk of developing nodal metastasis independent of tumor dimension and LVSI. Loss of MMR proteins expression was observed in 11 MELF + cases and 45 MELF- cases, respectively. Our data showed a higher frequency of immunohistochemical MLH1-PMS2 loss in MELF- pattern of invasion (32.67% of MELF- cases vs 21.43% of MELF + cases) but a higher prevalence of MSH2-MSH6 loss in MELF + pattern (7.14% in MELF + population vs 3.96% of MELF- population) CONCLUSIONS: The morphological recognition of MELF pattern is more reliable than immunohistochemical and molecular signatures of EEC in predicting the risk of nodal involvement. The observed higher prevalence of MSH2-MSH6 loss in MELF + group and MLH1-PMS2 loss in MELF- group may suggest a different molecular signature.

Deep-Learning to Predict BRCA Mutation and Survival from Digital H&E Slides of Epithelial Ovarian Cancer

BRCA 1/2 genes mutation status can already determine the therapeutic algorithm of high grade serous ovarian cancer patients. Nevertheless, its assessment is not sufficient to identify all patients with genomic instability, since BRCA 1/2 mutations are only the most well-known mechanisms of homologous recombination deficiency (HR-d) pathway, and patients displaying HR-d behave similarly to BRCA mutated patients. HRd assessment can be challenging and is progressively overcoming BRCA testing not only for prognostic information but more importantly for drugs prescriptions. However, HR testing is not already integrated in clinical practice, it is quite expensive and it is not refundable in many countries. Selecting patients who are more likely to benefit from this assessment (BRCA 1/2 WT patients) at an early stage of the diagnostic process, would allow an optimization of genomic profiling resources. In this study, we sought to explore whether somatic BRCA1/2 genes status can be predicted using computational pathology from standard hematoxylin and eosin histology. In detail, we adopted a publicly available, deep-learning-based weakly supervised method that uses attention-based learning to automatically identify sub regions of high diagnostic value to accurately classify the whole slide (CLAM). The same model was also tested for progression free survival (PFS) prediction. The model was tested on a cohort of 664 (training set: n = 464, testing set: n = 132) ovarian cancer patients, of whom 233 (35.1%) had a somatic BRCA 1/2 mutation. An area under the curve of 0.7 and 0.55 was achieved in the training and testing set respectively. The model was then further refined by manually identifying areas of interest in half of the cases. 198 images were used for training (126/72) and 87 images for validation (55/32). The model reached a zero classification error on the training set, but the performance was 0.59 in terms of validation ROC AUC, with a 0.57 validation accuracy. Finally, when applied to predict PFS, the model achieved an AUC of 0.71, with a negative predictive value of 0.69, and a positive predictive value of 0.75. Based on these analyses, we have planned further steps of development such as proving a reference classification performance, exploring the hyperparameters space for training optimization, eventually tweaking the learning algorithms and the neural networks architecture for better suiting this specific task. These actions may allow the model to improve performances for all the considered outcomes.

Prognostic role of perineural invasion in vulvar squamous cell carcinoma: A systematic review and meta-analysis

The prognostic role of perineural invasion (PNI) in vulvar squamous cell carcinoma (VSCC) has not been fully established since few studies on this topic are currently available in the literature. In the present study, we conducted a systematic review and metanalysis of literature data in order to determine if PNI could be an independent prognostic predictor of patient's survival in VSCC. Four electronic databases (PubMed, ISI Web of Science, Scopus and Google Scholar) were searched from their inception to December 2021 for all studies assessing the prognostic value of PNI in VSCC. Multivariate hazard ratios (HRs) for overall survival (OS), disease-specific survival (DSS), and progression-free survival (PFS) were pooled. Six studies with 1048 patients were included. PNI was significantly associated with decreased OS (HR = 2.687; p < 0.001), DSS (HR = 2.375; p = 0.014) and PFS (HR = 1.757; p = 0.001), with no statistical heterogeneity among studies and no significant risk of bias across studies. The present meta-analysis highlights that PNI is independently associated with unfavorable prognosis in patients with VSCC. Therefore, PNI should be included in the pathological report of VSCC and considered in combination with other risk factors as a possible criteria for prognostic assessment adjuvant treatment planning inclusion.