The Mclust Analysis of Tumor Budding Unveils the Role of the Collagen Family in Cervical Cancer Progression.

In RNA-seq data analysis, condensing the gene count matrix size is pivotal for downstream investigations, particularly pathway analysis. For this purpose, harnessing machine learning attracts increasing interest, while conventional methodologies depend on p-value comparisons. In this study, 20 tissue samples from real-world cervical cancers were subjected to sequencing, followed by the application of the Mclust algorithm to delineate an optimal cluster. By stratifying tumor budding into high and low groups and quantifying the epithelial-to-mesenchymal transition (EMT) score to scrutinize tumor budding, we discerned 24 EMT-related genes, with 5 showing strong associations with cervical cancer prognosis. Our observations elucidate a biological flow wherein EMT, Matrix Metallopep-tidase 2 (MMP2), and extracellular matrix (ECM) degradation are interconnected, ultimately leading to collagen type VI and exacerbating the prognosis of cervical cancer. The present study underscores an alternative method for selecting useful EMT-related genes by employing an appropriate clustering algorithm, thereby avoiding classical methods while unveiling novel insights into cervical cancer etiology and prognosis. Moreover, when comparing high and low tumor budding, collagen type VI emerges as a potential gene marker for the prognosis of cervical cancer.

Toward Interpretable Cell Image Representation and Abnormality Scoring for Cervical Cancer Screening Using Pap Smears.

Screening is critical for prevention and early detection of cervical cancer but it is time-consuming and laborious. Supervised deep convolutional neural networks have been developed to automate pap smear screening and the results are promising. However, the interest in using only normal samples to train deep neural networks has increased owing to the class imbalance problems and high-labeling costs that are both prevalent in healthcare. In this study, we introduce a method to learn explainable deep cervical cell representations for pap smear cytology images based on one-class classification using variational autoencoders. Findings demonstrate that a score can be calculated for cell abnormality without training models with abnormal samples, and we localize abnormality to interpret our results with a novel metric based on absolute difference in cross-entropy in agglomerative clustering. The best model that discriminates squamous cell carcinoma (SCC) from normals gives 0.908±0.003 area under operating characteristic curve (AUC) and one that discriminates high-grade epithelial lesion (HSIL) 0.920±0.002 AUC. Compared to other clustering methods, our method enhances the V-measure and yields higher homogeneity scores, which more effectively isolate different abnormality regions, aiding in the interpretation of our results. Evaluation using an external dataset shows that our model can discriminate abnormality without the need for additional training of deep models.

Design, synthesis, and evaluation of purine and pyrimidine-based KRAS G12D inhibitors: Towards potential anticancer therapy.

Oncogenic RAS mutations, commonly observed in human tumors, affect approximately 30% of cancer cases and pose a significant challenge for effective cancer treatment. Current strategies to inhibit the KRAS G12D mutation have shown limited success, emphasizing the urgent need for new therapeutic approaches. In this study, we designed and synthesized several purine and pyrimidine analogs as inhibitors for the KRAS G12D mutation. Our synthesized compounds demonstrated potent anticancer activity against cell lines with the KRAS G12D mutation, effectively impeding their growth. They also exhibited low toxicity in normal cells, indicating their selective action against cancer cells harboring the KRAS G12D mutation. Notably, the lead compound, PU1-1 induced the programmed cell death of KRAS G12D-mutated cells and reduced the levels of active KRAS and its downstream signaling proteins. Moreover, PU1-1 significantly shrunk the tumor size in a pancreatic xenograft model induced by the KRAS G12D mutation, further validating its potential as a therapeutic agent. These findings highlight the potential of purine-based KRAS G12D inhibitors as candidates for targeted cancer therapy. However, further exploration and optimization of these compounds are essential to meet the unmet clinical needs of patients with KRAS-mutant cancers.

Improving Tumor-Infiltrating Lymphocytes Score Prediction in Breast Cancer with Self-Supervised Learning.

Tumor microenvironment (TME) plays a pivotal role in immuno-oncology, which investigates the intricate interactions between tumors and the human immune system. Specifically, tumor-infiltrating lymphocytes (TILs) are crucial biomarkers for evaluating the prognosis of breast cancer patients and have the potential to refine immunotherapy precision and accurately identify tumor cells in specific cancer types. In this study, we conducted tissue segmentation and lymphocyte detection tasks to predict TIL scores by employing self-supervised learning (SSL) model-based approaches capable of addressing limited labeling data issues. Our experiments showed a 1.9% improvement in tissue segmentation and a 2% improvement in lymphocyte detection over the ImageNet pre-training model. Using these SSL-based models, we achieved a TIL score of 0.718 with a 4.4% improvement. In particular, when trained with only 10% of the entire dataset, the SwAV pre-trained model exhibited a superior performance over other models. Our work highlights improved tissue segmentation and lymphocyte detection using the SSL model with less labeled data for TIL score prediction.

Profiling of Lymphovascular Space Invasion in Cervical Cancer Revealed PI3K/Akt Signaling Pathway Overactivation and Heterogenic Tumor-Immune Microenvironments.

Lymphovascular space invasion (LVSI) is the presence of tumor emboli in the endothelial-lined space at the tumor body's invasive edge. LVSI is one of three Sedlis criteria components-a prognostic tool for early cervical cancer (CC)-essential for indicating poor prognosis, such as lymph node metastasis, distant metastasis, or shorter survival rate. Despite its clinical significance, an in-depth comprehension of the molecular mechanisms or immune dynamics underlying LVSI in CC remains elusive. Therefore, this study investigated tumor-immune microenvironment (TIME) dynamics of the LVSI-positive group in CC. RNA sequencing included formalin-fixed paraffin-embedded (FFPE) slides from 21 CC patients, and differentially expressed genes (DEGs) were analyzed. Functional analysis and immune deconvolution revealed aberrantly enriched PI3K/Akt pathway activation and a heterogenic immune composition with a low abundance of regulatory T cells (Treg) between LVSI-positive and LVSI-absent groups. These findings improve the comprehension of LSVI TIME and immune mechanisms, benefiting targeted LVSI therapy for CC.

Relationship between Human Papillomavirus Status and the Cervicovaginal Microbiome in Cervical Cancer.

Uterine cervical cancer (CC) is a complex, multistep disease primarily linked to persistent infection with high-risk human papillomavirus (HR-HPV). However, it is widely acknowledged that HR-HPV infection alone cannot account for the formation and progression of CC. Emerging evidence suggests that the cervicovaginal microbiome (CVM) also plays a significant role in HPV-related CC. Certain bacteria, such as Fusobacterium spp., Porphyromonas, Prevotella, and Campylobacter, are currently being considered as potential microbiomarkers for HPV-positive CC. However, the composition of the CVM in CC is inconsistent; thus, further studies are needed. This review comprehensively discusses the complex interplay between HPV and the CVM in cervical carcinogenesis. It is postulated that the dynamic interaction between HPV and the CVM creates an imbalanced cervicovaginal microenvironment that triggers dysbiosis, enhances HPV persistence, and promotes cervical carcinogenesis. Moreover, this review aims to provide updated evidence on the potential role of bacteriotherapy, particularly probiotics, in the treatment of CC.

Deep Learning Prediction of TERT Promoter Mutation Status in Thyroid Cancer Using Histologic Images.

Background and objectives: Telomerase reverse transcriptase (TERT) promoter mutation, found in a subset of patients with thyroid cancer, is strongly associated with aggressive biologic behavior. Predicting TERT promoter mutation is thus necessary for the prognostic stratification of thyroid cancer patients. Materials and Methods: In this study, we evaluate TERT promoter mutation status in thyroid cancer through the deep learning approach using histologic images. Our analysis included 13 consecutive surgically resected thyroid cancers with TERT promoter mutations (either C228T or C250T) and 12 randomly selected surgically resected thyroid cancers with a wild-type TERT promoter. Our deep learning model was created using a two-step cascade approach. First, tumor areas were identified using convolutional neural networks (CNNs), and then TERT promoter mutations within tumor areas were predicted using the CNN-recurrent neural network (CRNN) model. Results: Using the hue-saturation-value (HSV)-strong color transformation scheme, the overall experiment results show 99.9% sensitivity and 60% specificity (improvements of approximately 25% and 37%, respectively, compared to image normalization as a baseline model) in predicting TERT mutations. Conclusions: Highly sensitive screening for TERT promoter mutations is possible using histologic image analysis based on deep learning. This approach will help improve the classification of thyroid cancer patients according to the biologic behavior of tumors.

Enzymatic Process for the Carrageenolytic Bioconversion of Sulfated Polygalactans into ß-Neocarrabiose and 3,6-Anhydro-d-galactose.

Oligosaccharides and anhydro-sugars derived from carrageenan have great potential as functional foods and drugs showing various bioactivities, including antioxidant, anti-inflammatory, antiviral, antitumor, and cytotoxic activities. Although preparation of sulfated carrageenan oligosaccharides by chemical and enzymatic processes has been widely reported, preparation of nonsulfated ß-neocarrabiose (ß-NC2) and the rare sugar 3,6-anhydro-d-galactose (d-AHG) was not reported in the literature. Based on the carrageenan catabolic pathway in marine heterotrophic bacteria, an enzymatic process was designed and constructed with recombinant κ-carrageenase, GH127/GH129 α-1,3 anhydrogalactosidase, and cell-free extract from marine carrageenolytic bacteria Colwellia echini A3T. The process consisted of three successive steps, namely, (i) depolymerization, (ii) desulfation, and (iii) monomerization, by which carrageenan oligosaccharides, ß-NC2, and d-AHG were obtained from κ-carrageenan. Unlike the chemical process, enzymatic hydrolysis yields oligosaccharides with the desired degree of polymerization facilitates specific removal of sulfated groups, free of toxic byproducts, and avoids chemical modifications. The final optimized enzymatic process produced 0.52 g of ß-NC2 and 0.24 g of d-AHG from 1 g of κ-carrageenan. The carrageenolytic process designed for the enzymatic hydrolysis of κ-carrageenan can be scaled up for the mass production of bioactive carrageeno-oligosaccharides.

Immune Pathway and Gene Database (IMPAGT) Revealed the Immune Dysregulation Dynamics and Overactivation of the PI3K/Akt Pathway in Tumor Buddings of Cervical Cancer.

Tumor budding (TB) is a small cluster of malignant cells at the invasive front of a tumor. Despite being an adverse prognosis marker, little research has been conducted on the tumor immune microenvironment of tumor buddings, especially in cervical cancer. Therefore, RNA sequencing was performed using 21 formalin-fixed, paraffin-embedded slides of cervical tissues, and differentially expressed genes (DEGs) were analyzed. Immune Pathway and Gene Database (IMPAGT) was generated for immune profiling. "Pathway in Cancer" was identified as the most enriched pathway for both up- and downregulated DEGs. Kyoto Encyclopedia of Genes and Genomes Mapper and Gene Ontology further revealed the activation of the PI3K/Akt signaling pathway. An IMPAGT analysis revealed immune dysregulation even at the tumor budding stage, especially in the PI3K/Akt/mTOR axis, with a high efficiency and integrity. These findings emphasized the clinical significance of tumor buddings and the necessity of blocking the overactivation of the PI3K/Akt/mTOR pathway to improve targeted therapy in cervical cancer.

Transcriptomic Immune Profiles Can Represent the Tumor Immune Microenvironment Related to the Tumor Budding Histology in Uterine Cervical Cancer.

Tumor budding (TB) histology has become a critical biomarker for several solid cancers. Despite the accumulating evidence for the association of TB histology with poor prognosis, the biological characteristics of TB are little known about in the context related to the tumor immune microenvironment (TIME) in uterine cervical cancer (CC). Therefore, this study aimed to identify the transcriptomic immune profiles related to TB status and further provide robust medical evidence for clinical application. In our study, total RNA was extracted and sequenced from 21 CC tissue specimens. As such, 1494 differentially expressed genes (DEGs) between the high- and low-TB groups were identified by DESeq2. After intersecting the list of DEGs and public immune genes, we selected 106 immune-related DEGs. Then, hub genes were obtained using Least Absolute Shrinkage and Selection Operator regression. Finally, the correlation between the hub genes and immune cell types was analyzed and four candidate genes were identified (one upregulated (FCGR3B) and three downregulated (ROBO2, OPRL1, and NR4A2) genes). These gene expression levels were highly accurate in predicting TB status (area under the curve >80%). Interestingly, FCGR3B is a hub gene of several innate immune pathways; its expression significantly differed in the overall survival analysis (p = 0.0016). In conclusion, FCGR3B, ROBO2, OPRL1, and NR4A2 expression can strongly interfere with TB growth and replace TB to stratify CC patients.

Intratumoral budding: A novel prognostic biomarker for tumor recurrence and a potential predictor of nodal metastasis in uterine cervical cancer.

OBJECTIVE: To evaluate the prognostic and predictive significance of lymphovascular invasion (LVI) and lymph node metastasis of intratumoral budding (ITB) and its correlation with clinicopathological parameters in patients with cervical cancer. METHODS: Total 151 patients with cervical cancer who underwent radical hysterectomy with pelvic and/or paraaortic lymphadenectomy were included. We assessed the status of ITB and peritumoral budding (PTB) in all available hematoxylin and eosin-stained specimens. Univariate and multivariate analyses were performed for ITB, PTB, and other clincopathological parameters as predictors of recurrence. RESULTS: ITBhigh (≥3TB/HPF) was significantly associated with large tumor size, deep stromal invasion, LVI, parametrial invasion, and lymph node metastasis. The numbers of ITBs and PTBs were positively correlated (r2 = 0.754, p < 0.0001). ITBhigh was more frequently observed in squamous cell carcinoma compared with adenocarcinoma and adenosquamous cell carcinoma (p = 0.010). ITBhigh was found to be an independent prognostic factor for tumor recurrence by multivariate analysis (hazard ratio, 1.92; 95% confidence interval [CI], 1.37-9.90; p = 0.026). Multiple logistic regression showed association of LVI (odds ratio [OR], 1.85; 95% CI, 1.11-3.06; p = 0.017) and lymph node metastasis (OR, 1.96; 95% CI, 1.26-4.66; p = 0.019). CONCLUSION: ITBhigh is an independent prognostic factor for tumor recurrence. ITB is a surrogate marker for predicting LVI in cervical cancers. The evaluation of ITB may be readily applied in the clinical setting for improved prognosis and to guide the clinical management of patients with cervical cancer.

Dose-Dependent Effect of Smoking on Risk of Diabetes Remains after Smoking Cessation: A Nationwide Population-Based Cohort Study in Korea.

BACKGROUND: This study aimed to evaluate the dose-dependent effects of smoking on risk of diabetes among those quitting smoking. METHODS: We analyzed clinical data from a total of 5,198,792 individuals age 20 years or older who received health care check-up arranged by the national insurance program of Korea between 2009 and 2016 using the Korean National Health Insurance Service database. Cumulative smoking was estimated by pack-years. Smokers were classified into four categories according to the amount of smoking: light smokers (0.025 to 5 smoking pack-years), medium smokers (5 to 14 smoking pack-years), heavy smokers (14 to 26 smoking pack-years), and extreme smokers (more than 26 smoking pack-years). RESULTS: During the study period, 164,335 individuals (3.2% of the total population) developed diabetes. Compared to sustained smokers, the risk of diabetes was significantly reduced in both quitters (hazard ratio [HR], 0.858; 95% confidence interval [CI], 0.838 to 0.878) and nonsmokers (HR, 0.616; 95% CI, 0.606 to 0.625) after adjustment for multiple risk factors. The risk of diabetes gradually increased with amount of smoking in both quitters and current smokers. The risk of diabetes in heavy (HR, 1.119; 95% CI, 1.057 to 1.185) and extreme smokers (HR, 1.348; 95% CI, 1.275 to 1.425) among quitters was much higher compared to light smokers among current smokers. CONCLUSION: Smoking cessation was effective in reducing the risk of diabetes regardless of weight change. However, there was a potential dose-dependent association between smoking amount and the development of diabetes. Diabetes risk still remained in heavy and extreme smokers even after smoking cessation.

Protective effect of smoking cessation on subsequent myocardial infarction and ischemic stroke independent of weight gain: A nationwide cohort study.

Smoking cessation reduces the cardiovascular risk but increases body weight. We investigated the risk of subsequent myocardial infarction and ischemic stroke according to weight gain after smoking cessation, using a nationwide population based cohort. We enrolled 3,797,572 Korean adults aged over 40 years who participated in national health screenings between 2009 and 2010. Subjects who quit smoking were classified into three subgroups according to the weight change between baseline and 4 years prior. Myocardial infarctions and ischemic strokes were followed until the end of 2015. We compared the hazard ratios among smoking cessation subgroups, non-smokers, and current smokers. The mean changes in weight (1.5 ± 3.9 kg) of the smoking cessation group were higher than those of the other groups (p < 0.0001). A total of 31,277 and 46,811 subjects were newly diagnosed with myocardial infarction and ischemic stroke, respectively. Regardless of weight change, all subgroups of smoking cessation had significantly less risk than current smokers. The subgroup of smoking cessation with weight gain over 4kg showed the lowest risk for myocardial infarctions (hazard ratio 0.646, 95% confidence interval 0.583-0.714, p < 0.0001) and ischemic strokes (hazard ratio 0.648, 95% confidence interval 0.591-0.71, p < 0.0001) after multivariable adjustment. In conclusion, weight gain after smoking cessation did not adversely affect the cardiovascular protective effect.

Association Between Coronary Artery Calcification and the Hemoglobin Glycation Index: The Kangbuk Samsung Health Study.

Context: The hemoglobin glycation index (HGI) is known to be correlated with the risk for cardiovascular disease. Objective: To analyze the association between incident coronary artery calcification (CAC) and the changes in HGI among participants without diabetes, over 4 years. Design, Setting, Participants, and Outcome Measures: A retrospective study of 2052 nondiabetic participants in whom the coronary artery calcium score was measured repeatedly over 4 years, as part of a health checkup program in Kangbuk Samsung Hospital in Korea, and who had no CAC at baseline. The HGI was defined as the difference between the measured and predicted hemoglobin A1c (HbA1c) levels. Results: A total of 201 participants developed CAC after 4 years, and the mean baseline HGI was significantly higher in those patients. The incidence of CAC gradually increased from the first to the fourth quartile groups of baseline HGI. The odds ratio (OR) for incident CAC was the highest among the four groups divided by the quartiles of the baseline HGI and was significant after adjustment for confounding variables (vs first quartile group: OR, 1.632; 95% confidence interval, 1.024 to 2.601). The incidence of and risk for CAC development were significantly higher than in other groups compared with the low-to-low group after adjustment for confounding factors; however, when baseline HbA1c level was included in the model, only participants with a low-to-high HGI over 4 years showed a significantly increased OR for CAC development compared with the low-to-low group (OR, 1.722; 95% confidence interval, 1.046 to 2.833). Conclusions: The participants with a high baseline HGI and consistently high HGI showed a higher risk for incident CAC than those with a low baseline HGI. An increased HGI over 4 years significantly increased the risk for CAC regardless of the baseline HbA1c levels.

Decreased muscle mass in Korean subjects with intracranial arterial stenosis: The Kangbuk Samsung Health Study.

BACKGROUNDS AND AIMS: Intracranial arterial stenosis (ICAS) is a common cause of ischemic stroke in Asians. Decreased muscle mass is one of the major causes of chronic disease in adults. The purpose of this study was to analyze the relationship between muscle mass and ICAS in Korean adults. METHODS: For this study, we selected a total of 10,530 participants (mean age, 43.3 years; 8558 men) in a health screening program, for whom transcranial Doppler (TCD) ultrasound was used to detect >50% ICAS based on criteria modified from the stroke outcomes and neuroimaging of intracranial atherosclerosis trial. Body composition was evaluated by bioelectrical impedance analysis (BIA). Skeletal muscle index (SMI) was calculated with muscle mass/weight (kg) * 100. RESULTS: Among the total patient population, 322 (3.1%) subjects had ICAS. Subjects with ICAS were older, and had higher mean values for fasting glucose, body mass index and blood pressure compared with those without ICAS. Subjects with ICAS had significantly lower muscle mass, SMI and higher percent body fat compared with those without ICAS. In logistic regression analysis, the subjects in the highest tertile of muscle mass had the lowest odds ratio for ICAS with the lowest tertile group of muscle mass as the reference group even after adjusting for age, systolic blood pressure, fasting blood glucose, sex, smoking and exercise (OR 0.650, 95% CI 0.442-0.955). CONCLUSIONS: Subjects with ICAS had significantly decreased muscle mass compared with those without ICAS in Korean adults. The risk for ICAS was lower in subjects with higher muscle mass.