Survival prediction in second primary breast cancer patients with machine learning: An analysis of SEER database.

BACKGROUND: Studies have found that first primary cancer (FPC) survivors are at high risk of developing second primary breast cancer (SPBC). However, there is a lack of prognostic studies specifically focusing on patients with SPBC. METHODS: This retrospective study used data from Surveillance, Epidemiology and End Results Program. We selected female FPC survivors diagnosed with SPBC from 12 registries (from January 1998 to December 2018) to construct prognostic models. Meanwhile, SPBC patients selected from another five registries (from January 2010 to December 2018) were used as the validation set to test the model's generalization ability. Four machine learning models and a Cox proportional hazards regression (CoxPH) were constructed to predict the overall survival of SPBC patients. Univariate and multivariate Cox regression analyses were used for feature selection. Model performance was assessed using time-dependent area under the ROC curve (t-AUC) and integrated Brier score (iBrier). RESULTS: A total of 10,321 female FPC survivors with SPBC (mean age [SD]: 66.03 [11.17]) were included for model construction. These patients were randomly split into a training set (mean age [SD]: 65.98 [11.15]) and a test set (mean age [SD]: 66.15 [11.23]) with a ratio of 7:3. In validation set, a total of 3,638 SPBC patients (mean age [SD]: 66.28 [10.68]) were finally enrolled. Sixteen features were selected for model construction through univariate and multivariable Cox regression analyses. Among five models, random survival forest model showed excellent performance with a t-AUC of 0.805 (95 %CI: 0.803 - 0.807) and an iBrier of 0.123 (95 %CI: 0.122 - 0.124) on testing set, as well as a t-AUC of 0.803 (95 %CI: 0.801 - 0.807) and an iBrier of 0.098 (95 %CI: 0.096 - 0.103) on validation set. Through feature importance ranking, the top one and other top five key predictive features of the random survival forest model were identified, namely age, stage, regional nodes positive, latency, radiotherapy, and surgery. CONCLUSIONS: The random survival forest model outperformed CoxPH and other machine learning models in predicting the overall survival of patients with SPBC, which was helpful for the monitoring of high-risk populations.

The Value of CEUS LI-RADS combined with AFP in early diagnosis of hepatocellular carcinoma in low- and high-risk patients.

BACKGROUND: We found that the occurrence of hepatocellular carcinoma (HCC) has increased significantly in non-cirrhotic individuals, with HCC being frequently overlooked or misdiagnosed. Contrast-enhanced ultrasound (CEUS) Liver Imaging Reporting and Data System (LI-RADS) is known to have a high diagnostic quality in high-risk HCC patients. Therefore, we aimed to compare the detection accuracy of CEUS LI-RADS for HCC between low- and high-risk individuals, to confirm its value in low-risk patients at increased risk of HCC, but not yet included in the high-risk groups of LI-RADS. In addition, since CEUS LR-4 and LR-M categories contain a relatively high proportion of HCC, and serum alpha-fetoprotein (AFP) is the most commonly used biomarker for HCC, and the clinically valid, we attempted to further improve the early diagnostic capability of CEUS LI-RADS for HCC in the low-risk and high-risk patients by combining CEUS LR-4 and LR-M categories with AFP. METHODS: We defined high-risk groups (HR)-included in the high-risk patients of LI-RADS, low-risk groups (LR)-not included in the high-risk patients of LI-RADS and enrolled 189 HCC patients with LR and HR settings in a retrospective study. All lesions were confirmed histopathologically. The CEUS LI-RADS accuracy for detecting HCC in these two patients was compared. In addition, the diagnostic algorithm in our study was proposed (for CEUS LR-4 and LR-M patients with AFP>20 ng/ml). we analyzed the ability of CEUS LI-RADS as a valid method of establishing the early diagnosis of HCC in LR and HR patients by combining LR-4 and LR-M categories with AFP. RESULTS: Through comparative analysis, the specificity of the CEUS LR-5 category for HCC in the HR group was 78.4%, whereas in the LR group, it was 94.2%. Meanwhile, the sensitivity (63.2% vs. 63.0%) and positive predictive value (PPV) (75.0% vs. 88.7%) did not differ between the LR and HR groups ( P = 0.990, P = 0.299). It is noteworthy that there were the high proportion of HCC in CEUS LR-4 and LR-M categories in our cases and when we combined CEUS LR-4 and LR-M categories with AFP significantly improved the sensitivity by 21.0% (84.2%) in the LR group, and by 16.0% (79.0%) in the HR group, with statistically difference in sensitivity after combination in the HR group ( P = 0.014). CONCLUSIONS: The CEUS LR-5 category has real meaningful utility in the diagnosis of HCC in both LR and HR patients. The early detection power of the CEUS LI-RADS category for HCC patients was further increased when the CEUS LR-4 and LR-M categories were combined with elevated AFP.

Associations Between Metabolic Obesity Phenotypes and Pathological Characteristics of Papillary Thyroid Carcinoma.

OBJECTIVE: The association between obesity, metabolic dysregulation, and the aggressive pathological traits of papillary thyroid carcinoma (PTC) continues to be a contentious issue. To date, no investigations have examined the impact of metabolic status on the malignant pathological features of PTC in relation to obesity. METHODS: This research involved 855 adult patients with PTC from Shandong Provincial Hospital, classified into 4 groups based on metabolic and obesity status: metabolically healthy nonobese, metabolically unhealthy nonobese (MUNO), metabolically healthy obese, and metabolically unhealthy obese. We employed logistic regression to investigate the relationship between these metabolic obesity phenotypes and PTC's pathological characteristics. Mediation analysis was also performed to determine metabolic abnormalities' mediating role in the nexus between obesity and these characteristics. RESULTS: Relative to metabolically healthy nonobese individuals, the metabolically unhealthy obese group was significantly associated with an elevated risk of larger tumor sizes and a greater number of tumor foci in PTC. Mediation analysis indicated that obesity directly influences tumor size, whereas its effect on tumor multifocality is mediated through metabolic dysfunctions. Specifically, high-density lipoprotein cholesterol levels were notably associated with tumor multifocality within obese subjects, serving as a mediator in obesity's impact on this trait. CONCLUSION: The concurrent presence of obesity and metabolic dysregulation is often connected to more aggressive pathological features in PTC. The mediation analysis suggests obesity directly affects tumor size and indirectly influences tumor multifocality via low high-density lipoprotein cholesterol levels.

Characterization and application of in situ curcumin/ZNP hydrogels for periodontitis treatment.

BACKGROUND: Periodontitis is a chronic inflammatory disease that occurs in tooth-supporting tissues. Controlling inflammation and alleviating periodontal tissue destruction are key factors in periodontal therapy. This study aimed to develop an in situ curcumin/zinc oxide (Cur/ZNP) hydrogel and investigate its characteristics and effectiveness in the treatment of periodontitis. METHODS: Antibacterial activity and cytotoxicity assays were performed in vitro. To evaluate the effect of the in situ Cur/ZNP hydrogel on periodontitis in vivo, an experimental periodontitis model was established in Sprague‒Dawley rats via silk ligature and inoculation of the maxillary first molar with Porphyromonas gingivalis. After one month of in situ treatment with the hydrogel, we examined the transcriptional responses of the gingiva to the Cur/ZNP hydrogel treatment and detected the alveolar bone level as well as the expression of osteocalcin (OCN) and osteoprotegerin (OPG) in the periodontal tissues of the rats. RESULTS: Cur/ZNPs had synergistic inhibitory effects on P. gingivalis and good biocompatibility. RNA sequencing of the gingiva showed that immune effector process-related genes were significantly induced by experimental periodontitis. Carcinoembryonic antigen-related cell adhesion molecule 1 (Ceacam1), which is involved in the negative regulation of bone resorption, was differentially regulated by the Cur/ZNP hydrogel but not by the Cur hydrogel or ZNP hydrogel. The Cur/ZNP hydrogel also had a stronger protective effect on alveolar bone resorption than both the Cur hydrogel and the ZNP hydrogel. CONCLUSION: The Cur/ZNP hydrogel effectively inhibited periodontal pathogenic bacteria and alleviated alveolar bone destruction while exhibiting favorable biocompatibility.

CYP1B1 affects the integrity of the blood-brain barrier and oxidative stress in the striatum: An investigation of manganese-induced neurotoxicity.

AIMS: Excessive influx of manganese (Mn) into the brain across the blood-brain barrier induces neurodegeneration. CYP1B1 is involved in the metabolism of arachidonic acid (AA) that affects vascular homeostasis. We aimed to investigate the effect of brain CYP1B1 on Mn-induced neurotoxicity. METHOD: Brain Mn concentrations and α-synuclein accumulation were measured in wild-type and CYP1B1 knockout mice treated with MnCl2 (30 mg/kg) and biotin (0.2 g/kg) for 21 continuous days. Tight junctions and oxidative stress were analyzed in hCMEC/D3 and SH-SY5Y cells after the treatment with MnCl2 (200 µM) and CYP1B1-derived AA metabolites (HETEs and EETs). RESULTS: Mn exposure inhibited brain CYP1B1, and CYP1B1 deficiency increased brain Mn concentrations and accelerated α-synuclein deposition in the striatum. CYP1B1 deficiency disrupted the integrity of the blood-brain barrier (BBB) and increased the ratio of 3, 4-dihydroxyphenylacetic acid (DOPAC) to dopamine in the striatum. HETEs attenuated Mn-induced inhibition of tight junctions by activating PPARγ in endothelial cells. Additionally, EETs attenuated Mn-induced up-regulation of the KLF/MAO-B axis and down-regulation of NRF2 in neuronal cells. Biotin up-regulated brain CYP1B1 and reduced Mn-induced neurotoxicity in mice. CONCLUSIONS: Brain CYP1B1 plays a critical role in both cerebrovascular and dopamine homeostasis, which might serve as a novel therapeutic target for the prevention of Mn-induced neurotoxicity.

Inhibition of RhoGEF/RhoA alleviates regorafenib resistance and cancer stemness via Hippo signaling pathway in hepatocellular carcinoma.

Patients with hepatocellular carcinoma (HCC) are vulnerable to drug resistance. Although drug resistance has been taken much attention to HCC therapy, little is known of regorafenib and regorafenib resistance (RR). This study aimed to determine the drug resistance pattern and the role of RhoA in RR. Two regorafenib-resistant cell lines were constructed based on Huh7 and Hep3B cell lines. In vitro and in vivo assays were conducted to study RhoA expression, the activity of Hippo signaling pathway and cancer stem cell (CSC) traits. The data showed that RhoA was highly expressed, Hippo signaling was hypoactivated and CSC traits were more prominent in RR cells. Inhibiting RhoA could reverse RR, and the alliance of RhoA inhibition and regorafenib synergistically attenuated CSC phenotype. Furthermore, inhibiting LARG/RhoA increased Kibra/NF2 complex formation, prevented YAP from shuttling into the nucleus and repressed CD44 mRNA expression. Clinically, the high expression of RhoA correlated with poor prognosis. LARG, RhoA, YAP1 and CD44 show positive correlation with each other. Thus, inhibition of RhoGEF/RhoA has the potential to reverse RR and repress CSC phenotype in HCC.

The survival of periodontally treated molars in long-term maintenance: A systematic review and meta-analysis.

AIM: This systematic review and meta-analysis aimed to determine the survival of periodontally treated molars during maintenance care and identify the risk factors associated with molar loss among patients with periodontitis who received professional periodontal therapy and maintenance. MATERIALS AND METHODS: Longitudinal studies with a minimum follow-up duration of 5 years published until 28 August 2023 were retrieved from the following databases: the Cochrane Library, Embase, MEDLINE and Web of Science. All included studies reported data on molar retention. Meta-analysis was performed using Review Manager 5.4. A modified version of the Newcastle-Ottawa Scale was used to evaluate the study quality. Statistical results of analyses of the overall survival rate and molar loss are presented as estimated standardized mean differences, whereas the results of the analyses of risk factors are presented as risk ratios with 95% confidence intervals (95% CIs). RESULTS: From among the 1323 potentially eligible reports, 41 studies (5584 patients, 29,908 molars retained at the beginning of maintenance therapy, mean follow-up duration of 14.7 years) were included. The pooled survival rate of the molars during maintenance therapy was 82% (95% CI: 80%-84%). The average loss of molars was 0.05 per patient per year (95% CI: 0.04-0.06) among the patients receiving long-term periodontal maintenance (PM) therapy. Fifteen factors were examined in this meta-analysis. Six patient-related factors (older age, lack of compliance, smoking, bruxism, diabetes and lack of private insurance) and five tooth-related factors (maxillary location, high probing pocket depth, furcation involvement, higher mobility and lack of pulpal vitality) were identified as risk factors for molar loss during maintenance therapy. CONCLUSIONS: The findings of the present study suggest that the long-term retention of periodontally compromised molars can be achieved. The average number of molars lost per decade was <1 among the patients receiving long-term PM therapy. Older age, noncompliance, smoking, bruxism, diabetes, lack of private insurance coverage, maxillary location, furcation involvement, higher mobility, increase in the probing pocket depth and loss of pulpal vitality are strong risk factors for the long-term prognosis of molars.

Development of interpretable machine learning models associated with environmental chemicals to predict all-cause and specific-cause mortality：A longitudinal study based on NHANES.

Limited information is available on potential predictive value of environmental chemicals for mortality. Our study aimed to investigate the associations between 43 of 8 classes representative environmental chemicals in serum/urine and mortality, and further develop the interpretable machine learning models associated with environmental chemicals to predict mortality. A total of 1602 participants were included from the National Health and Nutrition Examination Survey (NHANES). During 154,646 person-months of follow-up, 127 deaths occurred. We found that machine learning showed promise in predicting mortality. CoxPH was selected as the optimal model for predicting all-cause mortality with time-dependent AUROC of 0.953 (95%CI: 0.951-0.955). Coxnet was the best model for predicting cardiovascular disease (CVD) and cancer mortality with time-dependent AUROCs of 0.935 (95%CI: 0.933-0.936) and 0.850 (95%CI: 0.844-0.857). Based on clinical variables, adding environmental chemicals could enhance the predictive ability of cancer mortality (P < 0.05). Some environmental chemicals contributed more to the models than traditional clinical variables. Combined the results of association and prediction models by interpretable machine learning analyses, we found urinary methyl paraben (MP) and urinary 2-napthol (2-NAP) were negatively associated with all-cause mortality, while serum cadmium (Cd) was positively associated with all-cause mortality. Urinary bisphenol A (BPA) was positively associated with CVD mortality.

A feedback loop of PPP and PI3K/AKT signal pathway drives regorafenib-resistance in HCC.

BACKGROUND: Hepatocellular carcinoma (HCC) is a principal type of liver cancer with high incidence and mortality rates. Regorafenib is a novel oral multikinase inhibitor for second-line therapy for advanced HCC. However, resistance to regorafenib is gradually becoming a dilemma for HCC and the mechanism remains unclear. In this study, we aimed to reveal the metabolic profiles of regorafenib-resistant cells and the key role and mechanism of the most relevant metabolic pathway in regorafenib resistance. METHODS: Metabolomics was performed to detect the metabolic alteration between drug-sensitive and regorafenib-resistant cells. Colony formation assay, CCK-8 assay and flow cytometry were applied to observe cell colony formation, cell proliferation and apoptosis, respectively. The protein and mRNA levels were detected by western blot and RT-qPCR. Cell lines of Glucose-6-phosphate dehydrogenase(G6PD) knockdown in regorafenib-resistant cells or G6PD overexpression in HCC cell lines were stably established by lentivirus infection technique. G6PD activity, NADPH level, NADPH/NADP+ ratio, the ratio of ROS positive cells, GSH level, and GSH/GSSG ratio were detected to evaluate the anti-oxidative stress ability of cells. Phosphorylation levels of NADK were evaluated by immunoprecipitation. RESULTS: Metabonomics analysis revealed that pentose phosphate pathway (PPP) was the most relevant metabolic pathway in regorafenib resistance in HCC. Compared with drug-sensitive cells, G6PD enzyme activity, NADPH level and NADPH/NADP+ ratio were increased in regorafenib-resistant cells, but the ratio of ROS positive cells and the apoptosis rate under the conditions of oxidative stress were decreased. Furthermore, G6PD suppression using shRNA or an inhibitor, sensitized regorafenib-resistant cells to regorafenib. In contrast, G6PD overexpression blunted the effects of regorafenib to drug-sensitive cells. Mechanistically, G6PD, the rate-limiting enzyme of PPP, regulated the PI3K/AKT activation. Furthermore, PI3K/AKT inhibition decreased G6PD protein expression, G6PD enzymatic activity and the capacity of PPP to anti-oxidative stress possibly by inhibited the expression and phosphorylation of NADK. CONCLUSION: Taken together, a feedback loop of PPP and PI3K/AKT signal pathway drives regorafenib-resistance in HCC and targeting the feedback loop could be a promising approach to overcome drug resistance.