Breast Cancer Prediction Based on Multiple Machine Learning Algorithms.

INTRODUCTION: The incidence of breast cancer has steadily risen over the years owing to changes in lifestyle and environment. Presently, breast cancer is one of the primary causes of cancer-related deaths among women, making it a crucial global public health concern. Thus, the creation of an automated diagnostic system for breast cancer bears great importance in the medical community. OBJECTIVES: This study analyses the Wisconsin breast cancer dataset and develops a machine learning algorithm for accurately classifying breast cancer as benign or malignant. METHODS: Our research is a retrospective study, and the main purpose is to develop a high-precision classification algorithm for benign and malignant breast cancer. To achieve this, we first preprocessed the dataset using standard techniques such as feature scaling and handling missing values. We assessed the normality of the data distribution initially, after which we opted for Spearman correlation analysis to examine the relationship between the feature subset data and the labeled data, considering the normality test results. We subsequently employed the Wilcoxon rank sum test to investigate the dissimilarities in distribution among various breast cancer feature data. We constructed the feature subset based on statistical results and trained 7 machine learning algorithms, specifically the decision tree, stochastic gradient descent algorithm, random forest algorithm, support vector machine algorithm, logistics algorithm, and AdaBoost algorithm. RESULTS: The results of the evaluation indicated that the AdaBoost-Logistic algorithm achieved an accuracy of 99.12%, outperforming the other 6 algorithms and previous techniques. CONCLUSION: The constructed AdaBoost-Logistic algorithm exhibits significant precision with the Wisconsin breast cancer dataset, achieving commendable classification performance for both benign and malignant breast cancer cases.

HDAC6-dependent deacetylation of NGF dictates its ubiquitination and maintains primordial follicle dormancy.

Rationale: Primordial follicles are limited in number and cannot be regenerated, dormant primordial follicles cannot be reversed once they enter a growth state. Therefore, the length of the female reproductive lifespan depends on the orderly progression and selective activation of primordial follicles, the mechanism of which remains unclear. Methods: We used human ovarian cortical biopsy specimens, granulosa cells from diminished ovarian reserve (DOR) patients, Hdac6-overexpressing transgenic mouse model, and RNA sequencing to analyze the crucial roles of histone deacetylase 6 (HDAC6) in fertility preservation and primordial follicle activation. Results: In the present study, we found that HDAC6 was highly expressed in most dormant primordial follicles. The HDAC6 expression was reduced accompanying reproductive senescence in human and mouse ovaries. Overexpression of Hdac6 delayed the rate of primordial follicle activation, thereby prolonging the mouse reproductive lifespan. Short-term inhibition of HDAC6 promoted primordial follicle activation and follicular development in humans and mice. Mechanism studies revealed that HDAC6 directly interacted with NGF, reducing acetylation modification of NGF and thereby accelerating its ubiquitination degradation. Consequently, the reduced NGF protein level maintained the dormancy of primordial follicles. Conclusions: The physiological significance of the high expression of HDAC6 in most primordial follicles is to reduce NGF expression and prevent primordial follicle activation to maintain female fertility. Reduced HDAC6 expression increases NGF expression in primordial follicles, activating their development and contributing to reproduction. Our study provides a clinical reference value for fertility preservation.

Predicting the prognosis of glioma patients with TERT promoter mutations and guiding the specific immune profile of immune checkpoint blockade therapy.

The telomerase reverse transcriptase promoter (TERTp) is frequently mutated in gliomas. This study sought to identify immune biomarkers of gliomas with TERTp mutations. Data from TCGA were used to identify and validate survival-associated gene signatures, and immune and stromal scores were calculated using the ESTIMATE algorithm. High stromal or immune scores in patients with TERTp-mutant gliomas correlated with shorter overall survival compared to cases with low stromal or immune scores. Among TERTp-mutant gliomas with both high immune and high stromal scores, 213 commonly shared DEGs were identified. Among 71 interacting DEGs representing candidate hub genes in a PPI network, HOXC6, WT1, CD70, and OTP showed significant ability in establishing subgroups of high- and low-risk patients. A risk model based on these 4 genes showed strong prognostic potential for gliomas with mutated TERTp, but was inapplicable for TERTp-wild-type gliomas. TERTp-mutant gliomas with high-risk scores displayed a greater percentage of naïve B cells, plasma cells, naïve CD4 T cells, and activated mast cells than low-risk score gliomas. TIDE analysis indicated that immune checkpoint blockade (ICB) therapy may benefit glioma patients with TERTp mutations. The present risk model can help predict prognosis of glioma patients with TERTp mutations and aid ICB treatment options.

Integrated investigation and experimental validation of PPARG as an oncogenic driver: implications for prognostic assessment and therapeutic targeting in hepatocellular carcinoma.

Peroxisome proliferator-activated receptor gamma (PPARG), a key transcription factor involved in lipid metabolism and glucose homeostasis, has been implicated in various types of cancer. However, its precise role in cancer remains unclear. In this study, we conducted a comprehensive pan-cancer analysis of PPARG expression using various types of cancer obtained from public databases. We observed significant heterogeneity in PPARG expression across different types of cancer. The association between PPARG expression and patient prognosis was investigated using Cox proportional hazards regression models and survival analysis. Clinical features and protein expression levels in the cohort showed that PPARG expression was strongly associated, suggesting its potential as a therapeutic target. We also evaluated the prognostic potential of PPARG by analyzing immune infiltration and genomic stability. We experimentally validated the potential of PPARG as a therapeutic target by analyzing drug sensitivity profiles, molecular docking simulations, and in vitro cell proliferation assays associated with PPARG expression. We identified common expression patterns of PPARG with other genes involved in key carcinogenic pathways. This provides deeper insights into the molecular mechanisms underlying its carcinogenic role. Additionally, functional enrichment analysis revealed significant enrichment of genes related to drug metabolism, cell proliferation, and immune response pathways associated with PPARG. Our findings highlight the importance of PPARG in the broader biology of cancer and suggest its potential as a diagnostic and therapeutic target for specific types of cancer. The results of our study provide strong support for the potential role of PPARG as a promising prognostic biomarker and immunotherapeutic target across various types of cancer.

Reconsideration of interferon treatment for viral diseases: Lessons from SARS, MERS, and COVID-19.

Periodic pandemics of coronavirus (CoV)-related pneumonia have been a major challenging issue since the outbreak of severe acute respiratory syndrome (SARS) in 2002 and Middle East respiratory syndrome (MERS) in 2012. The ongoing pandemic of CoV disease (COVID-19) poses a substantial threat to public health. As for the treatment options, only limited antiviral agents have been approved hitherto, and clinicians mainly focus on currently available drugs including the conventional antiviral interferons (IFNs). In clinical practice, IFNs, when used either alone or in combination with ribavirin and/or lopinavir/ritonavir, have shown promising outcomes, to some extent, in SARS-CoV or MERS-CoV treatment. Although the efficacy and safety of IFNs in COVID-19 treatment remain unclear, their possible use merits further evaluation. We present a review that summarizes current evidence of IFN treatment for COVID-19 and elaborates on other challenges in terms of the timing of IFN treatment initiation, treatment duration, and IFN type to be used. The review findings suggested that IFN acts by directly inhibiting viral replication and activating immune cell subsets. However, there is a lack of well-designed and controlled clinical trials providing firm evidence for the efficacy or safety of IFN therapy for CoVs. Additionally, critically ill patients with multiple immunosuppression-associated comorbidities may not benefit from IFN therapy, necessitating screening of those patients who would most benefit from IFN treatment.

Intracellular angiopoietin-1 promotes TKI-resistance via activation of JAK/STAT5 pathway in chronic myeloid leukemia.

Drug resistance from BCR-ABL tyrosine kinase inhibitors (TKIs) and other chemotherapeutics results in treatment failure and disease progression in chronic myeloid leukemia (CML). However, the mechanism is still uncertain. In this study, we investigated the role of angiopoietin-1 (ANG-1) as a potential prognostic factor for drug resistance in CML. Both intracellular and secretory ANG-1 (iANG-1 and sANG-1) were overexpressed in multidrug-resistant CML samples. The IC50 value was higher in primary CD34+ CD38- cells with more ANG-1. Silencing ANG-1significantly sensitized three TKI-resistant CML cell lines to imatinib (IM) while recombinant human ANG-1 failed to retain cell survival in vitro. This indicated the important role of iANG-1 as opposed to sANG-1 in CML drug resistance. Moreover, a similar effect was observed in xenograft mice models bearing ANG-1-silenced CML cells. Subsequently, pathway analysis and protein validation experiments showed activation of the JAK/STAT pathway and augmentation of STAT5a phosphorylation in ANG-1 restored CML cells. Upstream Src phosphorylation, which plays a crucial role in CML drug resistance, was also upregulated as a key event in iANG-1-related JAK/STAT pathway activation. In conclusion, our study elucidated a new BCR-ABL independent molecular mechanism induced by intracytoplasmic ANG-1 overexpression as a potential strategy for overcoming CML resistance.

JUND/linc00976 promotes cholangiocarcinoma progression and metastasis, inhibits ferroptosis by regulating the miR-3202/GPX4 axis.

Long noncoding RNAs (lncRNAs) are a novel class of noncoding RNAs that have emerged as critical regulators and biomarkers in various cancers. Nevertheless, the expression profile and mechanistic function of lncRNAs in cholangiocarcinoma (CCA) remain unclear. Herein, we examined the expression levels of linc00976 in clinical specimens and cell lines using reverse transcription-quantitative PCR. In total, 50 patients with CCA were enrolled to analyze the correlation between linc00976 expression and clinical characteristics of CCA. Loss- and gain-of-function experiments were performed to investigate the biological effects of linc00976 on proliferation, ferroptosis, migration, and invasion of CCA cells in vitro and in vivo. In situ hybridization, RNA immunoprecipitation, bioinformatic databases, RNA pull-down assay, a dual-luciferase reporter assay, mRNA sequencing, chromatin immunoprecipitation-PCR, and rescue experiments were performed to elucidate the underlying mechanisms of linc00976-induced competitive endogenous RNA regulatory networks. We characterized a novel and abundant lncRNA, linc00976, that functions as a pro-oncogenic regulator of CCA progression. Compared with normal controls, linc00976 was dramatically upregulated in CCA tissue samples and cell lines. Patients with CCA exhibiting high linc00976 expression had a highly advanced clinical stage, substantial lymph node metastasis, and poor overall survival. Knockdown of linc00976 significantly repressed proliferation and metastasis and promoted ferroptosis of CCA cells both in vitro and in vivo, whereas linc00976 overexpression exerted the opposite effect. Mechanistically, linc00976 competitively interacted with miR-3202 to upregulate GPX4 expression, thus contributing to the malignant biological behavior of CCA cells. Moreover, we demonstrated that JUND specifically interacts with the linc00976 promoter and activates linc00976 transcription. Accordingly, JUND promotes linc00976 transcription, and linc00976 plays a crucial role in accelerating CCA tumorigenesis and metastasis and inhibiting ferroptosis by modulating the miR-3202/GPX4 axis. These findings suggest that targeting linc00976 may afford a promising therapeutic strategy for patients with CCA.

A novel immune cell signature for predicting osteosarcoma prognosis and guiding therapy.

Dysregulation of immune cell infiltration in the tumor microenvironment contributes to the progression of osteosarcoma (OS). In the present study, we explored genes related to immune cell infiltration and constructed a risk model to predict the prognosis of and guide therapeutic strategies for OS. The gene expression profile of OS was obtained from TARGET and Gene Expression Omnibus, which were set as the discovery and verification cohorts. CIBERSORT and Kaplan survival analyses were used to analyze the effects of immune cells on the overall survival rates of OS in the discovery cohort. Differentially expressed gene (DEG) analysis and protein-protein interaction (PPI) networks were used to analyze genes associated with immune cell infiltration. Cox regression analysis was used to select key genes to construct a risk model that classified OS tissues into high- and low-risk groups. The prognostic value of the risk model for survival and metastasis was analyzed by Kaplan-Meier survival analyses, receiver operating characteristic curves, and immunohistochemical experiments. Immunological characteristics and response effects of immune checkpoint blockade (ICB) therapy in OS tissues were analyzed using the ESTIMATE and Tumor Immune Dysfunction and Exclusion algorithms, while sensitivity for both targeted and chemotherapy drugs was analyzed using the OncoPredict algorithm. It was demonstrated that the high infiltration of resting dendritic cells in OS tissues was associated with poor prognosis. A total of 225 DEGs were found between the high- and low-infiltration groups of OS tissues, while 94 genes interacted with others. Through COX analyses, among these 94 genes, four genes (including AOC3, CDK6, COL22A1, and RNASE6) were used to construct a risk model. This risk model showed a remarkable prognostic value for survival rates and metastasis in both the discovery and verification cohorts. Even though a high microsatellite instability score was observed in the high-risk group, the ICB response in the high-risk group was poor. Furthermore, using OncoPredict, we found that the high-risk group OS tissues were resistant to seven drugs and sensitive to 25 drugs. Therefore, our study indicates that the resting dendritic cell signature constructed by AOC3, CDK6, COL22A1, and RNASE6 may contribute to predicting osteosarcoma prognosis and thus therapy guidance.

A specific immune signature for predicting the prognosis of glioma patients with IDH1-mutation and guiding immune checkpoint blockade therapy.

Isocitrate dehydrogenase (IDH1) is frequently mutated in glioma tissues, and this mutation mediates specific tumor-promoting mechanisms in glioma cells. We aimed to identify specific immune biomarkers for IDH1-mutation (IDH1mt) glioma. The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) were used to obtain RNA sequencing data and clinical characteristics of glioma tissues, while the stromal and immune scores of TCGA glioma tissues were determined using the ESTIMATE algorithm. Differentially expressed genes (DEGs), the protein-protein interaction(PPI) network, and least absolute shrinkage and selection operator (LASSO) and Cox regression analyses were used to select hub genes associated with stroma and immune scores and the prognoses of patients and to construct the risk model. The practicability and specificity of the risk model in both IDH1mt and IDH1-wildtype (wtIDH1) gliomas in TCGA and CGGA were evaluated. Molecular mechanisms, immunological characteristics and benefits of immune checkpoint blockade therapy in glioma tissues with IDH1mt were analyzed using GSEA, immunohistochemical staining, CIBERSORT, and T-cell dysfunction and exclusion (TIDE) analysis. The overall survival rate for IDH1mt-glioma patients with high stroma/immune scores was lower than that for those with low stroma/immune scores. A total of 222 DEGs were identified in IDH1mt glioma tissues with high stroma/immune scores. Among them, 72 genes had interactions in the PPI network, while three genes, HLA-DQA2, HOXA3, and SAA2, were selected as hub genes and used to construct risk models classifying patients into high- and low-risk score groups, followed by LASSO and Cox regression analyses. This risk model showed prognostic value in IDH1mt glioma in both TCGA and CCGA; nevertheless, the model was not suitable for wtIDH1 glioma. The risk model may act as an independent prognostic factor for IDH1mt glioma. IDH1mt glioma tissues from patients with high-risk scores showed more infiltration of M1 and CD8 T cells than those from patients with low-risk scores. Moreover, TIDE analysis showed that immune checkpoint blockade(ICB) therapy was highly beneficial for IDH1mt patients with high-risk scores. The risk model showed specific potential to predict the prognosis of IDH1mt-glioma patients, as well as guide ICB, contributing to the diagnosis and therapy of IDH1mt-glioma patients.

Discovery of novel IDH1-R132C inhibitors through structure-based virtual screening.

Isocitrate dehydrogenase (IDH) belongs to a family of enzymes involved in glycometabolism. It is found in many living organisms and is one of the most mutated metabolic enzymes. In the current study, we identified novel IDH1-R132C inhibitors using docking-based virtual screening and cellular inhibition assays. A total of 100 molecules with high docking scores were obtained from docking-based virtual screening. The cellular inhibition assay demonstrated five compounds at a concentration of 10 µM could inhibit cancer cells harboring the IDH1-R132C mutation proliferation by > 50%. The compound (T001-0657) showed the most potent effect against cancer cells harboring the IDH1-R132C mutation with a half-maximal inhibitory concentration (IC50) value of 1.311 µM. It also showed a cytotoxic effect against cancer cells with wild-type IDH1 and normal cells with IC50 values of 49.041 µM and >50 µM, respectively. Molecular dynamics simulations were performed to investigate the stability of the kinase structure binding of allosteric inhibitor compound A and the identified compound T001-0657 binds to IDH1-R132C. Root-mean-square deviation, root-mean-square fluctuation, and binding free energy calculations showed that both compounds bind tightly to IDH1-R132C. In conclusion, the compound identified in this study had high selectivity for cancer cells harboring IDH1-R132C mutation and could be considered a promising hit compound for further development of IDH1-R132C inhibitors.

UPLC-MS/MS method for the determination of voriconazole plasma concentration from pediatric patients with hematologic tumors: An application toward personalized therapy.

Untreated invasive fungal infection is one of the important risk factors affecting the prognosis of pediatric patients with hematologic tumors. Voriconazole (VOR) is the first-line antifungal drug for the treatment of Aspergillus infections. In order to reduce the risk of adverse drug reactions while producing an ideal antifungal effect, therapeutic drug monitoring was performed to maintain the VOR plasma concentration in a range of 1,000-5,500 ng/ml. In the present study, a reliable, accurate, sensitive and quick ultra-high performance liquid chromatograph-tandem mass spectrometry (UPLC-MS/MS) method was developed for the determination of the VOR level. Protein precipitation was performed using acetonitrile, and then the chromatographic separation was carried out by UPLC using a C18 column with the gradient mobile phases comprising 0.1% methanoic acid in acetonitrile (A) and 0.1% methanoic acid in water (B). In the selective reaction monitor mode, the mass spectrometric detection was carried out using an TSQ Endura triple quadruple mass spectrometer. The performance of this UPLC-MS/MS method was validated as per the National Medical Products Administration for Bioanalytical Method Validation. Additionally, the plasma concentrations of VOR in pediatric patients with hematologic tumors were detected using this method, and the analyzed results were used for personalized therapy.

Synthesis and bioevaluation of diaryl urea derivatives as potential antitumor agents for the treatment of human colorectal cancer.

The development of inhibitors targeting the PI3K-Akt-mTOR signaling pathway has been greatly hindered by the on-target AEs, such as hyperglycemia and hepatotoxicities. In this study, a series of diaryl urea derivatives has been designed and synthesized based on clinical candidate gedatolisib (6aa), and most of the newly synthesized derivatives showed kinase inhibitory and antiproliferative activities within nanomolar and submicromolar level, respectively. The terminal l-prolineamide substituted derivative 6 ab showed 8.6-fold more potent PI3Kα inhibitory activity (0.7 nM) and 4.6-fold more potent antiproliferative effect against HCT116 cell lines (0.11 µM) compared with control 6aa. The potential antitumor mechanism and efficacy of 6 ab in HCT116 xenograft models have also been evaluated, and found 6 ab showed comparable in vivo antitumor activity with 6aa. The safety investigations revealed that compound 6 ab exhibited more safer profiles in the selectivity of liver cells (selectivity index: >6.6 vs 1.85) and blood glucose regulation than 6aa. In addition, the in vitro stability assays also indicated our developed compound 6 ab possessed good metabolic stabilities.

Synthesis and biological evaluation of cajanonic acid A derivatives as potential PPARγ antagonists.

Four series of cajanonic acid A (CAA) derivatives have been designed and synthesized. The newly prepared compounds have been screened for glucose consumption activity in HepG2 cell lines and PPARγ antagonistic activity in HEK293 cell lines. Compound 26g bearing a tetrahydroisoquinolinone scaffold showed the most potent PPARγ antagonistic and hypoglycemic activities. An oral glucose tolerance test (OGTT) was performed and the results further confirmed that 26g was a potent hypoglycemic agent. In addition, the possible binding modes for compound 26g in the PPARγ protein have been investigated in this study.

Discovery of a Potent and Selective NF-κB-Inducing Kinase (NIK) Inhibitor That Has Anti-inflammatory Effects in Vitro and in Vivo.

The overexpression of NIK plays a critical role in liver inflammatory diseases. Treatment of such diseases with small-molecule NIK inhibitors is a reasonable but underexplored approach. In this paper, we reported the discovery of a potent and selective NIK inhibitor 46 (XT2). 46 inhibited the NIK kinase with an IC50 value of 9.1 nM in vitro, and it also potently suppressed NIK activities in intact cells. In isogenic primary hepatocytes, treatment of 46 efficiently suppressed the expressions of NIK-induced genes. 46 was orally bioavailable in mice with moderate systemic exposure. In a NIK-associated mouse liver inflammation model, 46 suppressed CCl4-induced upregulation of ALT, a key biomarker of acute liver injury. 46 also decreased immune cell infiltration into the injured liver tissue. Overall, these studies provide examples that an NIK inhibitor is able to suppress toxin-induced liver inflammations, which indicates its therapeutic potentials for the treatment of liver inflammatory diseases.

Licochalcone A suppresses the proliferation of sarcoma HT-1080 cells, as a selective R132C mutant IDH1 inhibitor.

IDH1 mutations are closely related to the development and progression of various human cancers, such as glioblastoma, sarcoma, and acute myeloid leukemia. By screening dozens of reported natural compounds using both wild-type and mutant IDH1 enzymatic assays, we discovered Licochalcone A is a selective inhibitor to the R132C-mutant IDH1 with an IC50 value of 5.176 µM, and inhibits the proliferation of sarcoma HT-1080 cells with an IC50 value of 10.75 µM. Suggested by the molecular docking results, Licochalcone A might occupy the allosteric pocket between the two monomers of IDH1 homodimer, and the R132H mutation was unfavorable for the binding of Licochalcone A with the IDH1 protein, as compared to the R132C mutation. Revealed by the RNA-Seq data analysis, the Cell Cycle pathway was the most over-represented pathway for HT-1080 cells treated with Licochalcone A. Consistent with these results, Licochalcone A induced apoptosis and cell cycle arrest of HT-1080 cells, while it showed minimal effect against the proliferation of normal RCTEC cells. The discovery of Licochalcone A as a mutation-selective IDH1 inhibitor can serve as a promising starting point for the development of mutation-selective anti-tumor lead compounds targeting IDH1.