Giant condyloma acuminatum, or Buschke-Löwenstein tumour, is a unique variant of anogenital warts. It is characterized by locally aggressive behaviour but rarely metastasizes. Many treatment strategies such as radical surgery, radiation and chemotherapy have been used to treat it but their efficacy is often poor and the recurrence rates are high. We report a case of 16-year-old girl who was treated with oral retinoid combined with intramuscular interferon-γ. All lesions cleared within three months. During a follow-up period of more than two years, no recurrence has developed. This relatively painless, non-scarring treatment may represent a novel therapeutic option.

Previously it was shown that autophagy contributes to crizotinib resistance in ALK-positive anaplastic large cell lymphoma (ALK + ALCL). We asked if autophagy is equally important in two distinct subsets of ALK + ALCL, namely Reporter Unresponsive (RU) and Reporter Responsive (RR), of which RR cells display stem-like properties. Autophagic flux was assessed with a fluorescence tagged LC3 reporter and immunoblots to detect endogenous LC3 alongside chloroquine, an autophagy inhibitor. The stem-like RR cells displayed significantly higher autophagic response upon crizotinib treatment. Their exaggerated autophagic response is cytoprotective against crizotinib, as inhibition of autophagy using chloroquine or shRNA against BECN1 or ATG7 led to a decrease in their viability. In contrast, autophagy inhibition in RU resulted in minimal changes. Since the differential protein expression of MYC is a regulator of the RU/RR dichotomy and is higher in RR cells, we asked if MYC regulates the autophagy-mediated cytoprotective effect. Inhibition of MYC in RR cells using shRNA significantly blunted crizotinib-induced autophagic response and effectively suppressed this cytoprotective effect. In conclusion, stem-like RR cells respond with rapid and intense autophagic flux which manifests with crizotinib resistance. For the first time, we have highlighted the direct role of MYC in regulating autophagy and its associated chemoresistance phenotype in ALK + ALCL stem-like cells.

Background: Necroptosis is a phenomenon of cellular necrosis resulting from cell membrane rupture by the corresponding activation of Receptor Interacting Protein Kinase 3 (RIPK3) and Mixed Lineage Kinase domain-Like protein (MLKL) under programmed regulation. It is reported that necroptosis is closely related to the development of tumors, but the prognostic role and biological function of necroptosis in lung adenocarcinoma (LUAD), the most important cause of cancer-related deaths, is still obscure.Methods: In this study, we constructed a prognostic Necroptosis-related gene signature based on the RNA transcription data of LUAD patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases as well as the corresponding clinical information. Kaplan-Meier analysis, receiver operating characteristic (ROC), and Cox regression were made to validate and evaluate the model. We analyzed the immune landscape in LUAD and the relationship between the signature and immunotherapy regimens.Results: Five genes (RIPK3, MLKL, TLR2, TNFRSF1A, and ALDH2) were used to construct the prognostic signature, and patients were divided into high and low-risk groups in line with the risk score. Cox regression showed that risk score was an independent prognostic factor. Nomogram was created for predicting the survival rate of LUAD patients. Patients in high and low-risk groups have different tumor purity, tumor immunogenicity, and different sensitivity to common antitumor drugs.Conclusion: Our results highlight the association of necroptosis with LUAD and its potential use in guiding immunotherapy.

Objective. To screen for potential endoplasmic reticulum stress- (ERS-) related biomarkers of periodontitis using machine learning methods and explore their relationship with immune cells. Methods. Three datasets of periodontitis (GSE10334, GES16134, and GES23586) were obtained from the Gene Expression Omnibus (GEO), and the samples were randomly assigned to the training set or the validation set. ERS-related differentially expressed genes (DEGs) between periodontitis and healthy periodontal tissues were screened and analyzed for GO, KEGG, and DO enrichment. Key DEGs were screened by two machine learning algorithms, LASSO regression and support vector machine-recursive feature elimination (SVM-RFE); then, the potential biomarkers were identified through validation. The infiltration of immune cells of periodontitis was calculated using the CIBERSORT algorithm, and the correlation between immune cells and potential biomarkers was specifically analyzed through the Spearman method. Results. We obtained 36 ERS-related DEGs of periodontitis from the training set, from which 11 key DEGs were screened by further machine learning. SERPINA1, ERLEC1, and VWF showed high diagnostic values ( AUC > 0.85 ), so they were considered as potential biomarkers for periodontitis. According to the results of the immune cell infiltration analysis, these three potential biomarkers showed marked correlations with plasma cells, neutrophils, resting dendritic cells, resting mast cells, and follicular helper T cells. Conclusions. Three ERS-related genes, SERPINA1, ERLEC1, and VWF, showed valuable biomarker potential for periodontitis, which provide a target base for future studies on early diagnosis and treatment of periodontitis.