Infections with multiple human papilloma virus (HPV) types have been reported, but their role in cervical carcinogenesis has not been fully elucidated. In this study, 236 cases with multiple HPV infection were examined and compared to 180 cases with single HPV infection. HPV genotyping was performed with cervico-vaginal swab specimens using multiplex (real-time) polymerase chain reaction (PCR). In multiple HPV infection, the most prevalent HPV genotype was HPV 53, followed by HPV 16, 58, 52, and 68. HPV 33, 35, 39, 51, 52, 53, 58, and 68 were high-risk-HPV (HR-HPV) genotypes that were more frequently detected in multiple HPV infection compared to that in single HPV infection. The association between multiple HPV infection and high-grade SIL (HSIL) was significantly stronger compared to that of single HPV infection and HSIL (p = 0.002). Patients with multiple HPV infection displayed persistent and longer duration of the HPV infection compared to patients with single HPV infection. Multiple HPV infections have distinct clinicopathologic characteristics. Since it is associated with persistent HPV infection, HSIL, and different HR-HPV strains in contrast to single HPV infection, the presence of multiple HPV infection should be reported; close follow up is warranted.

We aimed to develop a deep learning (DL) model for predicting high-grade patterns in lung adenocarcinomas (ADC) and to assess the prognostic performance of model in advanced lung cancer patients who underwent neoadjuvant or definitive concurrent chemoradiation therapy (CCRT). We included 275 patients with 290 early lung ADCs from an ongoing prospective clinical trial in the training dataset, which we split into internal–training and internal–validation datasets. We constructed a diagnostic DL model of high-grade patterns of lung ADC considering both morphologic view of the tumor and context view of the area surrounding the tumor (MC3DN; morphologic-view context-view 3D network). Validation was performed on an independent dataset of 417 patients with advanced non-small cell lung cancer who underwent neoadjuvant or definitive CCRT. The area under the curve value of the DL model was 0.8 for the prediction of high-grade histologic patterns such as micropapillary and solid patterns (MPSol). When our model was applied to the validation set, a high probability of MPSol was associated with worse overall survival (probability of MPSol >0.5 vs. <0.5; 5-year OS rate 56.1% vs. 70.7%), indicating that our model could predict the clinical outcomes of advanced lung cancer patients. The subgroup with a high probability of MPSol estimated by the DL model showed a 1.76-fold higher risk of death (HR 1.76, 95% CI 1.16–2.68). Our DL model can be useful in estimating high-grade histologic patterns in lung ADCs and predicting clinical outcomes of patients with advanced lung cancer who underwent neoadjuvant or definitive CCRT.

Background: Prognostic considerations for non-predominant patterns are necessary because most lung adenocarcinomas (ADCs) have a mixed histologic pattern, and the spectrum of actual prognosis varies widely even among lung ADCs with the same most predominant pattern. We aimed to identify prognostic stratification by second most predominant pattern of lung ADC and to more accurately assess prognostic factors with CT imaging analysis, particularly enhancing non-predominant but high-grade pattern. Methods: In this prospective study, patients with early-stage lung ADC undergoing curative surgery underwent preoperative dual-energy CT (DECT) and positron emission tomography (PET)/CT. Histopathology of ADC, the most predominant and second most predominant histologic patterns, and preoperative imaging parameters were assessed and correlated with patient survival. Results: Among the 290 lung ADCs included in the study, 231 (79.7%) were mixed-pathologic pattern. When the most predominant histologic pattern was intermediate-grade, survival curves were significantly different among the three second most predominant subgroups (p = 0.004; low, lepidic; intermediate, acinar and papillary; high, micropapillary and solid). When the second most predominant pattern was high-grade, recurrence risk increased by 4.2-fold compared with the low-grade group (p = 0.005). To predict a non-predominant but high-grade pattern, the non-contrast CT value of tumor was meaningful with a lower HU value associated with the histologic combination of lower grade (low-grade as most predominant and intermediate-grade as second most predominant pattern, OR = 6.15, p = 0.005; intermediate-grade as most predominant and high-grade as second most predominant pattern, OR = 0.10, p = 0.033). SUVmax of the tumor was associated with the non-predominant but high-grade pattern, especially in the histologic combination of intermediate-high grade (OR = 1.14, p = 0.012). Conclusions: The second most predominant histologic pattern can stratify lung ADC patients according to prognosis. Thus, predicting the malignant potential and establishing treatment policies should not rely only on the most predominant pattern. Moreover, imaging parameters of non-contrast CT value and SUVmax could be useful in predicting a non-predominant but high-grade histologic pattern.

Pulmonary emphysema is a destructive inflammatory disease primarily caused by cigarette smoking (CS). Recovery from CS-induced injury requires proper stem cell (SC) activities with a tightly controlled balance of proliferation and differentiation. Here we show that acute alveolar injury induced by two representative tobacco carcinogens, 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone and benzo[a]pyrene (N/B), increased IGF2 expression in alveolar type 2 (AT2) cells to promote their SC function and facilitate alveolar regeneration. Autocrine IGF2 signaling upregulated Wnt genes, particularly Wnt3, to stimulate AT2 proliferation and alveolar barrier regeneration after N/B-induced acute injury. In contrast, repetitive N/B exposure provoked sustained IGF2-Wnt signaling through DNMT3A-mediated epigenetic control of IGF2 expression, causing a proliferation/differentiation imbalance in AT2s and development of emphysema and cancer. Hypermethylation of the IGF2 promoter and overexpression of DNMT3A, IGF2, and the Wnt target gene AXIN2 were seen in the lungs of patients with CS-associated emphysema and cancer. Pharmacologic or genetic approaches targeting IGF2-Wnt signaling or DNMT prevented the development of N/B-induced pulmonary diseases. These findings support dual roles of AT2 cells, which can either stimulate alveolar repair or promote emphysema and cancer depending on IGF2 expression levels. Significance: IGF2-Wnt signaling plays a key role in AT2-mediated alveolar repair after cigarette smoking–induced injury but also drives pathogenesis of pulmonary emphysema and cancer when hyperactivated.

Background: The Korean Society for Cytopathology introduced a digital proficiency test (PT) in 2021. However, many doubtful opinions remain on whether digitally scanned images can satisfactorily present subtle differences in the nuclear features and chromatin patterns of cytological samples.Methods: We prepared 30 whole-slide images (WSIs) from the conventional PT archive by a selection process for digital PT. Digital and conventional PT were performed in parallel for volunteer institutes, and the results were compared using feedback. To assess the quality of cytological assessment WSIs, 12 slides were collected and scanned using five different scanners, with four cytopathologists evaluating image quality through a questionnaire.Results: Among the 215 institutes, 108 and 107 participated in glass and digital PT, respectively. No significant difference was noted in category C (major discordance), although the number of discordant cases was slightly higher in the digital PT group. Leica, 3DHistech Pannoramic 250 Flash, and Hamamatsu NanoZoomer 360 systems showed comparable results in terms of image quality, feature presentation, and error rates for most cytological samples. Overall satisfaction was observed with the general convenience and image quality of digital PT.Conclusions: As three-dimensional clusters are common and nuclear/chromatin features are critical for cytological interpretation, careful selection of scanners and optimal conditions are mandatory for the successful establishment of digital quality assurance programs in cytology.

Despite advances in diagnostic imaging, surgical techniques, and systemic therapy, gastric cancer (GC) is the third leading cause of cancer-related death worldwide. Unfortunately, molecular heterogeneity and, consequently, acquired resistance in GC are the major causes of failure in the development of biomarker-guided targeted therapies. However, by showing promising survival benefits in some studies, the recent emergence of immunotherapy in GC has had a significant impact on treatment-selectable procedures. Immune checkpoint inhibitors (ICIs), widely indicated in the treatment of several malignancies, target inhibitory receptors on T lymphocytes, including the programmed cell death protein (PD-1)/programmed death-ligand 1 (PD-L1) axis and cytotoxic T-lymphocyte-associated protein 4 (CTLA4), and release effector T-cells from negative feedback signals. In this article, we review currently available predictive biomarkers (including PD-L1, microsatellite instability, Epstein–Barr virus, and tumor mutational burden) that affect the ICI treatment response, focusing on PD-L1 expression. We further briefly describe other potential biomarkers or mechanisms for predicting the response to ICIs in GC. This review may facilitate the expansion of the understanding of biomarkers for predicting the response to ICIs and help select the appropriate therapeutic approaches for patients with GC.