Despite the current pandemic season, reports on pathologic features of coronavirus disease 19 are exceedingly rare at the present time. Here we describe the pathologic features of early lung involvement by Covid-19 in a surgical sample resected for carcinoma from a patient who developed SARS-CoV-2 infection soon after surgery. The main histologic findings observed were pneumocyte damage, alveolar hemorrhages with clustering of macrophages, prominent and diffuse neutrophilic margination within septal vessels, and interstitial inflammatory infiltrates, mainly represented by CD8+ T lymphocytes. These features are similar to those previously described in SARS-CoV-1 infection. Subtle histologic changes suggestive pulmonary involvement by Covid-19 may be accidentally encountered in routine pathology practice, especially when extensive sampling is performed for histology. These findings should be carefully interpreted in light of the clinical context of the patient and could prompt a pharyngeal swab PCR test to rule out the possibility of SARS-CoV-2 infection in asymptomatic patients.

Triple negative breast cancer (TNBC) has an aggressive clinical behaviour, with a poorer prognosis compared to other subtypes. Recently, tumor-infiltrating lymphocytes (TILs) have been proposed as a predictive biomarker for a better clinical outcome and pathological response (pR) after neoadjuvant chemotherapy (NACT) in TNBC. These data confirm the role of the immune system in the neoplastic progression and in the response to therapy. We performed a retrospective analysis of 54 pre-NACT biopsies of TNBC and compared both the percentage of stromal TILs and the degree of PD-L1 expression with the extent of pR to standard NACT. A pathological complete response (pCR) was achieved in 35% of cases. Univariate analysis showed (i) a significant association between PD-L1 expression in ≥25% of neoplastic cells and the achievement of a pCR (p = 0.024); (ii) a significantly higher frequency of pCR in cases showing ≥50% stromal TILs (p < 0.001). However in the multivariate analysis only PD-L1 expression on tumor cells remained significantly associated with pCR (OR = 1,13; 95% CI 1,01–1,27), suggesting that the expression of this biomarker could be associated with a subpopulation of TNBC more likely to respond to chemotherapy. These data need to be confirmed by larger studies.

Purpose The assessment of Programmed death-ligand 1 (PD-L1) expression has become a game changer in the treatment of patients with advanced non-small cell lung cancer (NSCLC). We aimed to investigate the ability of Radiomics applied to computed tomography (CT) in predicting PD-L1 expression in patients with advanced NSCLC. Methods By applying texture analysis, we retrospectively analyzed 72 patients with advanced NSCLC. The datasets were randomly split into a training cohort (2/3) and a validation cohort (1/3). Forty radiomic features were extracted by manually drawing tumor volumes of interest (VOIs) on baseline contrast-enhanced CT. After selecting features on the training cohort, two predictive models were created using binary logistic regression, one for PD-L1 values ≥ 50% and the other for values between 1 and 49%. The two models were analyzed with ROC curves and tested in the validation cohort. Results The Radiomic Score (Rad-Score) for PD-L1 values ≥ 50%, which consisted of Skewness and Low Gray-Level Zone Emphasis (GLZLM_LGZE), presented a cut-off value of − 0.745 with an area under the curve (AUC) of 0.811 and 0.789 in the training and validation cohort, respectively. The Rad-Score for PD-L1 values between 1 and 49% consisted of Sphericity, Skewness, Conv_Q3 and Gray Level Non-Uniformity (GLZLM_GLNU), showing a cut-off value of 0.111 with AUC of 0.763 and 0.806 in the two population, respectively. Conclusion Rad-Scores obtained from CT texture analysis could be useful for predicting PD-L1 expression and guiding the therapeutic choice in patients with advanced NSCLC.

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Objective: To assess evidence on the efficacy of adjuvant human papillomavirus (HPV) vaccination in patients treated for HPV-related disease across different susceptible organ sites. Methods: A systematic review was conducted to identify studies addressing the efficacy of adjuvant HPV vaccination on reducing the risk of recurrence of HPV-related preinvasive diseases. Results were reported as mean differences or pooled odds ratios (OR) with 95% confidence intervals (95% CI). Results: Sixteen studies were identified for the final analysis. Overall, 21,472 patients with cervical dysplasia were included: 4132 (19.2%) received the peri-operative HPV vaccine, while 17,340 (80.8%) underwent surgical treatment alone. The recurrences of CIN 1+ (OR 0.45, 95% CI 0.27 to 0.73; p = 0.001), CIN 2+ (OR 0.33, 95% CI 0.20 to 0.52; p < 0.0001), and CIN 3 (OR 0.28, 95% CI 0.13 to 0.59; p = 0.0009) were lower in the vaccinated than in unvaccinated group. Similarly, adjuvant vaccination reduced the risk of developing anal intraepithelial neoplasia (p = 0.005) and recurrent respiratory papillomatosis (p = 0.004). No differences in anogenital warts and vulvar intraepithelial neoplasia recurrence rate were observed comparing vaccinated and unvaccinated individuals. Conclusions: Adjuvant HPV vaccination is associated with a reduced risk of CIN recurrence, although there are limited data regarding its role in other HPV-related diseases. Further research is warranted to shed more light on the role of HPV vaccination as adjuvant therapy after primary treatment.

Objectives: To investigate the role of quantitative Magnetic Resonance Imaging (MRI) in preoperative assessment of tumor aggressiveness in patients with endometrial cancer, correlating multiple parameters obtained from diffusion and dynamic contrast-enhanced (DCE) MR sequences with conventional histopathological prognostic factors and inflammatory tumour infiltrate. Methods: Forty-four patients with biopsy-proven endometrial cancer underwent preoperative MR imaging at 3T scanner, including DCE imaging, diffusion-weighted imaging (DWI) and intravoxel incoherent motion imaging (IVIM). Images were analyzed on dedicated post-processing workstations and quantitative parameters were extracted: Ktrans, Kep, Ve and AUC from the DCE; ADC from DWI; diffusion D, pseudo diffusion D*, perfusion fraction f from IVIM and tumour volume from DWI. The following histopathological data were obtained after surgery: histological type, grading (G), lympho-vascular invasion (LVI), lymph node status, FIGO stage and inflammatory infiltrate. Results: ADC was significantly higher in endometrioid histology, G1-G2 (low grade), and stage IA. Significantly higher D* were found in endometrioid subptype, negative lymph nodes and stage IA. The absence of LVI is associated with higher f values. Ktrans and Ve values were significantly higher in low grade. Higher D*, f and AUC occur with the presence of chronic inflammatory cells, D * was also able to distinguish chronic from mixed type of inflammation. Larger volume was significantly correlated with the presence of mixed-type inflammation, LVI, positive lymph nodes and stage ≥IB. Conclusions: Quantitative biomarkers obtained from pre-operative DWI, IVIM and DCE-MR examination are an in vivo representation of the physiological and microstructural characteristics of endometrial carcinoma allowing to obtain the fundamental parameters for stratification into Risk Classes. Advances in knowledge: Quantitative imaging biomarkers obtained from DWI, DCE, and IVIM may improve preoperative prognostic stratification in patients with endometrial cancer leading to a more informed therapeutic choice.

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