Erianin inhibits the progression of triple-negative breast cancer by suppressing SRC-mediated cholesterol metabolism.

Triple-negative breast cancer (TNBC) is highly malignant and lacks effective biotherapeutic targets. The development of efficient anticancer drugs with low toxicity and few side effects is a hotspot in TNBC treatment research. Although erianin is known to have potent antitumor activity, its regulatory mechanism and target in TNBC have not been fully elucidated, hampering further drug development. This study showed that erianin can significantly inhibit TNBC cell proliferation and migration, promote cell apoptosis, and inhibit the growth of transplanted tumors in mice. Mechanistically, through network pharmacology analysis, molecular docking and cellular thermal shift assays, we preliminarily identified SRC as the cellular target of erianin. Erianin potently inhibited the expression of SRC, which mediated the anticancer effect of erianin in TNBC. Moreover, erianin can downregulate the expression of genes related to cholesterol synthesis and uptake by targeting SRC, interfering with cholesterol levels in TNBC, thereby inhibiting the progression of TNBC in vivo and in vitro. Taken together, our results suggest that erianin may inhibit the progression of TNBC by suppressing SRC-mediated cholesterol metabolism, and erianin has the great potential to be an effective treatment for TNBC patients.

Application of Novel Transcription Factor Machine Learning Model and Targeted Drug Combination Therapy Strategy in Triple Negative Breast Cancer.

Transcription factors (TFs) have been shown to play a key role in the occurrence and development of tumors, including triple-negative breast cancer (TNBC), with a worse prognosis. Machine learning is widely used for establishing prediction models and screening key tumor drivers. Current studies lack TF integration in TNBC, so targeted research on TF prognostic models and targeted drugs is beneficial to improve clinical translational application. The purpose of this study was to use the Least Absolute Shrinkage and Selection Operator to build a prognostic TFs model after cohort normalization based on housekeeping gene expression levels. Potential targeted drugs were then screened on the basis of molecular docking, and a multi-drug combination strategy was used for both in vivo and in vitro experimental studies. The machine learning model of TFs built by E2F8, FOXM1, and MYBL2 has broad applicability, with an AUC value of up to 0.877 at one year. As a high-risk clinical factor, its abnormal disorder may lead to upregulation of the activity of pathways related to cell proliferation. This model can also be used to predict the adverse effects of immunotherapy in patients with TNBC. Molecular docking was used to screen three drugs that target TFs: Trichostatin A (TSA), Doxorubicin (DOX), and Calcitriol. In vitro and in vivo experiments showed that TSA + DOX was able to effectively reduce DOX dosage, and TSA + DOX + Calcitriol may be able to effectively reduce the toxic side effects of DOX on the heart. In conclusion, the machine learning model based on three TFs provides new biomarkers for clinical and prognostic diagnosis of TNBC, and the combination targeted drug strategy offers a novel research perspective for TNBC treatment.

Integrating Single-cell RNA-seq to construct a Neutrophil prognostic model for predicting immune responses in non-small cell lung cancer.

Non-small cell lung cancer (NSCLC) is the most widely distributed tumor in the world, and its immunotherapy is not practical. Neutrophil is one of a tumor's most abundant immune cell groups. This research aimed to investigate the complex communication network in the immune microenvironment (TIME) of NSCLC tumors to clarify the interaction between immune cells and tumors and establish a prognostic risk model that can predict immune response and prognosis of patients by analyzing the characteristics of Neutrophil differentiation. Integrated Single-cell RNA sequencing (scRNA-seq) data from NSCLC samples and Bulk RNA-seq were used for analysis. Twenty-eight main cell clusters were identified, and their interactions were clarified. Next, four subsets of Neutrophils with different differentiation states were found, closely related to immune regulation and metabolic pathways. Based on the ratio of four housekeeping genes (ACTB, GAPDH, TFRC, TUBB), six Neutrophil differentiation-related genes (NDRGs) prognostic risk models, including MS4A7, CXCR2, CSRNP1, RETN, CD177, and LUCAT1, were constructed by Elastic Net and Multivariate Cox regression, and patients' total survival time and immunotherapy response were successfully predicted and validated in three large cohorts. Finally, the causes of the unfavorable prognosis of NSCLC caused by six prognostic genes were explored, and the small molecular compounds targeted at the anti-tumor effect of prognostic genes were screened. This study clarifies the TIME regulation network in NSCLC and emphasizes the critical role of NDRGs in predicting the prognosis of patients with NSCLC and their potential response to immunotherapy, thus providing a promising therapeutic target for NSCLC.

Gain of function in the mouse model of a recurrent mutation p53N236S promotes the formation of double minute chromosomes and the oncogenic potential of p19ARF.

The mutation p53N236S (p53S) has been identified as one of the recurrent mutations in human cancers by TCGA database. Our in vitro data revealed the oncogenic gain of function of p53S. To understand the function of p53S in vivo, we generated the p53S knock-in mouse. The p53S/S mice manifested highly invasive lymphomas and metastatic sarcomas with dramatically increased double minute chromosomes. The survival curve, the incidence of tumors and the tumor spectrum of p53S/S mice is very similar to the p53R172H mouse model. The p53S/+ mice showed delayed onset of tumorigenesis and a high metastasis rate (40%) and low loss of heterozygosity rate (2/16). The activation of CDKN2A pathway in p53S/S MEF and tumors, and the accumulation of p19ARF protein in tumor tissues suggested p19ARF might contribute to the accumulation of mutant p53S protein in the tumor and promote tumorigenesis. The high expression of p19ARF correlated with mutant p53 accumulation and tumor progression, suggesting a dual role of p19ARF in tumor promotion or suppression that might depend on the p53 mutation status in tumor cells. The oncogenic gain of function of this recurrent mutation p53S prompts the reconsideration of p53 mutations function that occurs at a low frequency.

Comparison of clinical outcomes of patients with non-small-cell lung cancer harbouring epidermal growth factor receptor exon 19 or exon 21 mutations after tyrosine kinase inhibitors treatment: a meta-analysis.

PURPOSE: Exon 19 deletion and exon 21 L858R mutation were the most common epidermal growth factor receptor (EGFR) mutations. We examined the clinical impact of these two mutations in patients with non-small-cell lung cancer (NSCLC) after EGFR tyrosine kinase inhibitor (TKI) treatment. METHODS: The outcomes of interest were progression-free survival (PFS), overall survival (OS) and objective response rates (ORR), network meta-analysis and direct meta-analysis were conducted to calculate the efficacy of EGFR-TKIs between these two mutations. We also investigated the association between EGFR mutation types and clinical characteristics. RESULTS: A total of 4835 patients from 26 trials were assessed. EGFR-TKIs, compared with chemotherapy, significantly prolonged PFS and OS in both exon 19 deletion and exon 21 L858R mutation based on 8 trials. Network meta-analysis revealed that treatment with EGFR-TKIs had greater benefit in exon 19 deletion than in exon 21 L858R mutation. Furthermore, direct meta-analysis from 12 studies showed the similar result; patients with exon 19 deletion had a significantly longer PFS compared with exon 21 L858R mutation (HR, 0.69; 95 % CI, 0.57­0.82; P < 0.001). There were also greater benefit on OS (HR, 0.61; 95 % CI, 0.43­0.86; P = 0.005) and higher ORR (OR, 2.14; 95 % CI, 1.63­2.81; P < 0.001). Additionally, we found that a significant association between the type of mutation and age (P < 0.001) or smoking status (P = 0.022), but no other significant differences were detected in sex, histologic subtype and performance status between these two mutations. CONCLUSIONS: Patients with NSCLC and EGFR exon 19 deletion had a longer PFS, OS and higher response rates after EGFR-TKI therapy compared with exon 21 L858R mutation.

Polymorphism of MDM2 promoter 309 (rs 2279744) and the risk of PCOS.

This study aimed at evaluating possible association between MDM2 SNP309 polymorphism (rs 2279744) and polycystic ovary syndrome (PCOS). One hundred and twenty-five women with PCOS and two hundred and fifty women without PCOS were collected from the department of reproductive medicine of college hospital in this case-control study. Peripheral blood samples were collected from all participants and DNA was extracted, MDM2 SNP309 polymorphism (rs 2279744) was determined from the 125 cases and 250 controls. Women were grouped into PCOS (n = 125) group and control group (n = 250). Odds ratios (OR) and 95% confidence intervals (CI) were used to evaluate the association between MDM2 SNP309 polymorphism (rs 2279744) and PCOS. The distribution of T allele was significant higher in PCOS cases than controls. MDM2 SNP 309 T allele is associated with PCOS.

Association of longevity with TNF-α G308A and IL-6 G174C polymorphic inflammatory biomarkers in Caucasians: a meta-analysis.

BACKGROUND: Mutations in genes encoding tumor necrosis factor (TNF)-α and interleukin (IL)-6 were previously shown to affect mortality. Single nucleotide polymorphisms (SNPs) in the functional promoter regions of TNF-α (G308A) and IL-6 (G174C) are among the most widely studied. OBJECTIVES: To determine whether TNF-α G308A and IL-6 G174C SNPs confer susceptibility to longevity, we performed a meta-analysis to comprehensively estimate the association between these SNPs and longevity in long-lived individuals (LLI, aged ≥ 80 years). MATERIALS AND METHODS: Studies addressing the role of TNF-α and IL-6 SNPs in longevity were identified from the PubMed database. Pooled ORs with 95 % confidence intervals (CIs) were used to assess the association between SNPs and longevity. RESULTS: The meta-analysis was based on four studies of TNF-α G308A and nine of IL-6 G174C, covering a total of 2945 LLI individuals and 2992 controls. Overall, no significantly increased risks were observed for G308A [A vs. G (additive model): OR = 0.98, 95 % CI = 0.79-1.22, p = 0.852; AA + AG vs. GG (dominant model): OR = 0.97, 95 % CI = 0.75-1.24, p = 0.791] or for G174C [C vs. G (additive model): OR = 1.07, 95 % CI = 0.94-1.22, p = 0.293; CC + CG vs. GG (dominant model): OR = 1.09, 95 % CI = 0.93-1.28, p = 0.299]. There was no change in the significance when a cutoff age of ≥ 90 years was introduced. CONCLUSIONS: We found no evidence that the TNF-α G308A and IL-6 G174C SNPs affected the probability of reaching an advanced age in Caucasians, and that they have little effect on delaying the onset and progression of age-related diseases, but this does not rule out the possibility of population-specific effects caused by different genes and/or environmental factors and their interactions.

Paraoxonase (PON1) polymorphisms Q192R and L55M are not associated with human longevity: A meta-analysis.

BACKGROUND: Genetic mutations in the paraoxonase 1 (PON1) encoding gene have been considered to affect mortality and of these the functional promoter region polymorphisms Q192R and L55M are among the most widely studied. OBJECTIVE: The aim of this study was to determine whether the Q192R and L55M polymorphisms of PON1 can increase susceptibility to longevity. A meta-analysis was performed to obtain a comprehensive estimation of the association between Q192R and L55M and longevity in long-lived individuals (LLIs) aged 80 years or more. MATERIAL AND METHODS: A search was carried out in the PubMed database (from January 2001 to May 2014) to obtain data on the role of PON1 polymorphisms in longevity and a pooled odds ratio (OR) with a 95% confidence interval (CI) was used to assess the associations. RESULTS: The meta-analysis was based on 9 studies of PON1 Q192R and 5 studies of PON1 L55M that covered a total of 5086 LLIs and 4494 controls. Overall, significantly increased risks were not observed for either Q192R or L55M. The results of the statistical calculations were as follows: R vs. Q (additive model): OR = 1.080, 95% CI = 0.989-1.179, p = 0.088 and RR + RQ vs. QQ (dominant model): OR = 1.099, 95% CI = 0.975-1.240, p = 0.124; M vs. L (additive model): OR = 0.946, 95% CI = 0.862-1.039, p = 0.245 and MM + ML vs. LL (dominant model): OR = 0.951, 95% CI = 0.836-1.081, p = 0.442 for Q192R and L55M, respectively. The results did not change with an age cut-off among the LLIs of ≥ 93 years. CONCLUSION: No evidence that the Q192R and L55M polymorphisms of PON1 impacted on the probability of reaching extreme ages was found although this cannot be completely ruled out; however, the possibility of population-specific effects due to the influence of and interaction between different genes or environmental factors could not be ruled out.

Milk, yogurt, and lactose intake and ovarian cancer risk: a meta-analysis.

Inconclusive information for the role of dairy food intake in relation to ovarian cancer risk may associate with adverse effects of lactose, which has been hypothesized to increase gonadotropin levels in animal models and ecological studies. Up to now, several studies have indicated the association between dairy food intake and risk of ovarian cancer, but no identified founding was reported. We performed this meta-analysis to derive a more precise estimation of the association between dairy food intake and ovarian cancer risk. Using the data from 19 available publications, we examined dairy food including low-fat/skim milk, whole milk, yogurt and lactose in relation to risk of ovarian cancer by meta-analysis. Pooled odds ratio (OR) with 95% confidence interval (CI) were used to assess the association. We observed a slightly increased risk of ovarian cancer with high intake of whole milk, but has no statistical significance (OR = 1.228, 95% CI = 1.031-1.464, P = 0.022). The results of other milk models did not provide evidence of positive association with ovarian cancer risk. This meta-analysis suggests that low-fat/skim milk, whole milk, yogurt and lactose intake has no associated with increased risk of ovarian cancer. Further studies with larger participants worldwide are needed to validate the association between dairy food intake and ovarian cancer.

Folate metabolism gene polymorphisms MTHFR C677T and A1298C and risk for preeclampsia: a meta-analysis.

OBJECTIVES: MTHFR C677T and A1298C have been associated with the risk of preeclampsia (PE), but with conflicting results. We performed this meta-analysis to derive a more precise estimation of the association between MTHFR polymorphisms and PE. STUDY DESIGN: An electronic search of PubMed and Chinese Biomedicine database was conducted to select studies for meta-analysis. 54 case controlled studies containing MTHFR C677T and A1298C gene polymorphisms were chosen, and odds ratio (OR) with confidence interval (CI) was used to assess the strength of this association. RESULT: These studies evaluated 7398 cases and 11230 controls for MTHFR C677T. The overall results suggested that MTHFR C677T was associated with the risk of PE. (T vs. C: OR = 1.157, 95% CI: 1.057-1.266, p = 0.002; TT + CT vs. CC: OR = 1.165, 95% CI : 1.049-1.293, P = 0.004; TT vs. CT + CC: OR = 1.371, 95% CI: 1.153-1.63, p < 0.001). We also evaluated 1103 cases and 988 controls for MTHFR A1298C but could not demonstrate an increased risk of PE for this polymorphism (p = 0.667). A symmetric funnel plot, the Egger's test (p = 0.819) suggested a lack of publication bias. CONCLUSION: This meta-analysis supports the idea that MTHFR C677T genotype is associated with increased risk for PE, especially in the case of Asians and Caucasians.

The prognosis of MGMT promoter methylation in glioblastoma patients of different race: a meta-analysis.

O(6)-Methylguanine-DNA methyltransferase (MGMT) is a DNA repair gene. Epigenetic silencing of the MGMT promoter methylation compromises DNA repair and has been associated with longer survival in patients with glioblastoma (GBM) who receive alkylating agents. But the prognostic of MGMT promoter methylation in GBM patients of different race is still ambiguous. Based on an univariate or multivariate analysis between different race (Caucasian and Asian), a meta-analysis of the effects of MGMT promoter methylation on both progression-free survival (PFS) and overall survival (OS) among GBM patients was conducted. A total of 6,309 patients from 50 studies were involved in the analysis. Random effect models were applied to estimate the pooled hazard ratio (HR) with 95 % confidence intervals (CIs) for GBM patients of different race prognosis, the Chi square-based Q test was used to test heterogeneity. Begg's (funnel plot method) and Egger's linear regression tests were adopted to check publication bias (a bias with regard to what is likely to be published, among what is available to be published). The HR value estimated for OS was 0.524 (95 % CI 0.428-0.640) by univariate analysis and 0.427 (95 % CI 0.355-0.513) by multivariate analysis in Caucasian. The HR value estimated for OS was 0.892 (95 % CI 0.469-1.698) by univariate analysis and 0.562 (95 % CI 0.394-0.804) by multivariate analysis in Asian. The HR value estimated for PFS was 0.526 (95 % CI 0.372-0.743) by univariate analysis and 0.437 (95 % CI 0.356-0.537) by multivariate analysis in Caucasian. The HR value estimated for PFS was 0.132 (95 % CI 0.006-3.027) by multivariate analysis in Asian. This data revealed that GBM patients with MGMT promoter methylation had longer OS and PFS by univariate or multivariate analysis in Caucasian regardless of therapeutic intervention. However, GBM patients with MGMT promoter methylation only had longer OS by multivariate analysis in Asian.

The molecular mechanism of HOTAIR in tumorigenesis, metastasis, and drug resistance.

Long non-coding RNAs have been reported to play an important role in cellular metabolism and development. Homeobox transcript antisense intergenic RNA (HOTAIR), a long non-coding RNA, is pervasively over-expressed in most human cancers compared with non-cancerous adjacent tissues. Although many articles have reported that HOTAIR is closely associated with metastasis, epithelial-mesenchymal transition, advanced pathological stage, drug resistance, and poor prognosis, the role of HOTAIR in gene regulation and tumor development is largely unknown, and the potential molecular mechanisms are not completely clear yet. In this review, we summarized the recent progress in the study of the major functions of HOTAIR. miR-331-3p, miR-130a, miR-7, miR-141, HER2, c-MYC, WIF-1, RBM38, PTEN, and Col-1 are involved in the HOTAIR regulation network. We tried to elucidate the molecular mechanisms of HOTAIR in the aspects of tumorigenesis, metastasis, drug resistance, and regulation.

Identification of potential drug targets for allergic diseases from a genetic perspective: A mendelian randomization study.

BACKGROUND: Allergic diseases typically refer to a heterogeneous group of conditions primarily caused by the activation of mast cells or eosinophils, including atopic dermatitis (AD), allergic rhinitis (AR), and asthma. Asthma, AR, and AD collectively affect approximately one-fifth of the global population, imposing a significant economic burden on society. Despite the availability of drugs to treat allergic diseases, they have been shown to be insufficient in controlling relapses and halting disease progression. Therefore, new drug targets are needed to prevent the onset of allergic diseases. METHOD: We employed a Mendelian randomization approach to identify potential drug targets for the treatment of allergic diseases. Leveraging 1798 genetic instruments for 1537 plasma proteins from the latest reported Genome-Wide Association Studies (GWAS), we analyzed the GWAS summary statistics of Ferreira MA et al. (nCase = 180,129, nControl = 180,709) using the Mendelian randomization method. Furthermore, we validated our findings in the GWAS data from the FinnGen and UK Biobank cohorts. Subsequently, we conducted sensitivity tests through reverse causal analysis, Bayesian colocalization analysis, and phenotype scanning. Additionally, we performed protein-protein interaction analysis to determine the interaction between causal proteins. Finally, based on the potential protein targets, we conducted molecular docking to identify potential drugs for the treatment of allergic diseases. RESULTS: At Bonferroni significance (p < 3.25 × 10-5), the Mendelian randomization analysis revealed 11 significantly associated protein-allergic disease pairs. Among these, the increased levels of TNFAIP3, ERBB3, TLR1, and IL1RL2 proteins were associated with a reduced risk of allergic diseases, with corresponding odds ratios of 0.82 (0.76-0.88), 0.74 (0.66-0.82), 0.49 (0.45-0.55), and 0.81 (0.75-0.87), respectively. Conversely, increased levels of IL6R, IL1R1, ITPKA, IL1RL1, KYNU, LAYN, and LRP11 proteins were linked to an elevated risk of allergic diseases, with corresponding odds ratios of 1.04 (1.03-1.05), 1.25 (1.18-1.34), 1.48 (1.25-1.75), 1.14 (1.11-1.18), 1.09 (1.05-1.12), 1.96 (1.56-2.47), and 1.05 (1.03-1.07), respectively. Bayesian colocalization analysis suggested that LAYN (coloc.abf-PPH4 = 0.819) and TNFAIP3 (coloc.abf-PPH4 = 0.930) share the same variant associated with allergic diseases. CONCLUSIONS: Our study demonstrates a causal association between the expression levels of TNFAIP3 and LAYN and the risk of allergic diseases, suggesting them as potential drug targets for these conditions, warranting further clinical investigation.

Cervical cancer subtype identification and model building based on lipid metabolism and post-infection microenvironment immune landscape.

Background: As the second most common gynecological cancer, cervical cancer (CC) seriously threatens women's health. The poor prognosis of CC is closely related to the post-infection microenvironment (PIM). This study investigated how lipid metabolism-related genes (LMRGs) affect CC PIM and their role in diagnosing CC. Methods: We analyzed lipid metabolism scores in the CC single-cell landscape by AUCell. The differentiation trajectory of epithelial cells to cancer cells was revealed using LMRGs and Monocle2. Consensus clustering was used to identify novel subgroups using the LMRGs. Multiple immune assessment methods were used to evaluate the immune landscape of the subgroups. Prognostic genes were determined by the LASSO and multivariate Cox regression analysis. Finally, we perform molecular docking of prognostic genes to explore potential therapeutic agents. Results: We revealed the differentiation trajectory of epithelial cells to cancer cells in CC by LMRGs. The higher LMRGs expression cluster had higher survival rates and immune infiltration expression. Functional enrichment showed that two clusters were mainly involved in immune response regulation. A novel LMR signature (LMR.sig) was constructed to predict clinical outcomes in CC. The expression of prognostic genes was correlated with the PIM immune landscape. Small molecular compounds with the best binding effect to prognostic genes were obtained by molecular docking, which may be used as new targeted therapeutic drugs. Conclusion: We found that the subtype with better prognosis could regulate the expression of some critical genes through more frequent lipid metabolic reprogramming, thus affecting the maturation and migration of dendritic cells (DCs) and the expression of M1 macrophages, reshaping the immunosuppressive environment of PIM in CC patients. LMRGs are closely related to the PIM immune landscape and can accurately predict tumor prognosis. These results further our understanding of the underlying mechanisms of LMRGs in CC.

Triterpenes from the aerial parts of Cimicifuga yunnanensis and their antiproliferative effects on p53(N236S) mouse embryonic fibroblasts.

Nine new triterpene derivatives, yunnanterpenes A-F (1-6), 15,16-seco-cimiterpenes A and B (7, 8), and cimilactone C (9), and 15 known analogues (10-24) were isolated from the aerial parts of Cimicifuga yunnanensis. The new structures were established using a combination of MS, NMR, and single-crystal X-ray diffraction techniques. WT MEFs (wild-type mouse embryonic fibroblasts) and tumorigenic cell lines p53(-/-)+H-RasV12 and p53(-/-)+p53(N236S)+H-RasV12 were used for evaluating active structures, targeting p53(N236S) (corresponding to p53(N239S) in humans) mutation. Compound 5 showed nonselective activities against these cell lines, with IC50 values of 5.8, 8.6, and 6.0 µM, respectively. Compound 4 exhibited greater selectivity against the p53(-/-)+p53(N236S)+H-RasV12 cells (IC50 5.5 µM) than against the WT MEFs cells (IC50 14.3 µM).

[The regulation of anoikis in tumor invasion and metastasis].

As a barrier to metastasis of cancer, cells that lost contact with the neighbouring cells or extracellular matrix(Extracellular matrix, ECM) will be subjected to apoptosis. This cell death process has been termed "anoikis". When normal epithelial cells or solid tumor cells without metastatic potential detach from the primary site, and then enter into the circulatory system, the anoikis mechanism will be activated. The significance of anoikis is to prevent the shedding cells from growing and implanting into other inappropriate sites. Tumor cells, especially several malignant cells that is prone to transfer to distant sites, have properties of anti-anoikis, which facilitates metastasis as well as invasion of tumor cells. The studies found that tumor cells can resist anoikis through multiple mechanisms: the pro-survival pathways are activated by cells autocrine growth factors and paracrine factors derived from neighboring cells; cells change the pattern of integrin expression so that they can receive survival signals from new environment; reactive oxygen species (ROS) activates growth factor receptors in a ligand-independent way to avoid apoptosis; and epithelial-mesenchymal transformation(EMT) is activated etc.. All of these mechanisms lead to activation of survival signals and inhibition of apoptotic pathways, and ultimately cause resistance to anoikis as well as metastasis. This paper summarizes the key mechanisms of the current studies on metastasis, which also suggest important targets for cancer therapy.

Widely targeted metabolomics reveals the antioxidant and anticancer activities of different colors of Dianthus caryophyllus.

Carnation is edible flower that has potent antioxidant properties and is used in traditional Chinese medicinal system and food industry. The phytochemicals responsible for these various proprieties, however, are not fully understood. Thus, in order to recognize metabolite diversity and variability in carnation flowers of different colors and to discover key metabolites that contribute to the differences in antioxidant and anticancer activities, widely targeted LC-MS/MS-based metabolomics analysis was conducted on purple, green, yellow, and white carnation flowers. We identified and chemically categorized 932 metabolites. Metabolic compounds varied significantly with flower color. Several flavonoids, organic acids, phenolic acids, and nucleotides and their derivatives were found to be specific differential metabolites in purple flowers. A total of 128 key differential metabolites were screened. The purple flowers were found to have the highest antioxidant and anticancer activities compared to the other colored flowers. Correlation analysis revealed that the 6-hydroxykaempferol-3,6-O-diglucoside, 6-hydroxykaempferol-7-O-glucoside, quercetin-3-O-sophoroside, and 2'-deoxyguanosine were found to be the major constituents of the antioxidant and anticancer activities. 2'-Deoxyguanosine has effective antiproliferative activity against A549 and U2OS cells for the first report. At the same time, the combination of 2'-deoxyguanosine with 6-hydroxykaempferol-3, 6-O-diglucoside, or quercetin-3-O-sophoroside have also been found to increase the antitumor activity of 2'-deoxyguanosine. These discoveries enrich information on the phytochemical composition of carnation of different colors and provide resources for the overall use and improvement of carnation flowers quality.

Stemness signature and targeted therapeutic drugs identification for Triple Negative Breast Cancer.

Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer and carries the worst prognosis, characterized by the lack of progesterone, estrogen, and HER2 gene expression. This study aimed to analyze cancer stemness-related gene signature to determine patients' risk stratification and prognosis feature with TNBC. Here one-class logistic regression (OCLR) algorithm was applied to compute the stemness index of TNBC patients. Cox and LASSO regression analysis was performed on stemness-index related genes to establish 16 genes-based prognostic signature, and their predictive performance was verified in TCGA and METABERIC merged data cohort. We diagnosed the expression level of prognostic genes signature in the tumor immune microenvironment, analyzed the TNBC scRNA-seq GSE176078 dataset, and further validated the expression level of prognostic genes using the HPA database. Finally, the small molecular compounds targeted at the anti-tumor effect of predictive genes were screened by molecular docking; this novel stemness-based prognostic genes signature study could facilitate the prognosis of patients with TNBC and thus provide a feasible therapeutic target for TNBC.

Single-cell and bulk RNA-sequencing analysis to predict the role and clinical value of CD36 in lung squamous cell carcinoma.

The majority of patients with lung squamous cell carcinoma are diagnosed at an advanced stage, which poses a challenge to the efficacy of chemotherapy. Therefore, the search for an early biomarker needs to be addressed. CD36 is a scavenger receptor expressed in various cell types. It has been reported that it is closely related to the occurrence and development of many kinds of tumours. However, its role in lung squamous cell carcinoma has not been reported. Our research aims to reveal the role of CD36 in lung squamous cell carcinoma by integrating single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing data. We used bioinformatics methods to explore the potential carcinogenicity of CD36 by analysing the data from the cancer genome map (TCGA), gene expression comprehensive map (GEO), human protein map (HPA) comparative toxicology genomics database (CTD) and other resources. Our study dissected the relationship between CD36 and prognosis and gene correlation, functional analysis, mutation of different tumours, infiltration of immune cells and exploring the interaction between CD36 and chemicals. The results showed that the expression of CD36 was heterogeneous. Compared with normal patients, the expression was low in lung squamous cell carcinoma. In addition, CD36 showed early diagnostic value in four kinds of tumours (LUSC, BLCA, BRCA and KIRC) and was positively or negatively correlated with the prognosis of different tumours. The relationship between CD36 and the tumour immune microenvironment was revealed by immunoinfiltration analysis, and many drugs that might target CD36 were identified by the comparative toxicological genomics database (CTD). In summary, through pancancer analysis, we found and verified for the first time that CD36 may play a role in the detection of lung squamous cell carcinoma. In addition, it has high specificity and sensitivity in detecting cancer. Therefore, CD36 can be used as an auxiliary index for early tumour diagnosis and a prognostic marker for lung squamous cell carcinoma.

Association of p53 Arg72Pro polymorphism with gastric cancer: a meta-analysis.

BACKGROUND: p53 tumor suppressor gene Arg72Pro polymorphism has been associated with gastric cancer. However, results were inconsistent. We performed this meta-analysis to estimate the association between p53 Arg72Pro polymorphism and gastric cancer. METHODS: An electronic search of PubMed was conducted to select studies. Studies containing available genotype frequencies of Arg72Pro were chosen, and the association was assess by pooled odds ratio (ORs) with 95% confidence interval (CIs). RESULTS: The meta-analysis suggested that the p53 Arg72Pro was associated with the gastric cancer risk (Additive model: OR = 1.149, 95% CI = 1.045-1.263, p = 0.004; Dominant model: OR = 1.18, 95% CI = 1.049-1.328, p = 0.006; Recessive model: OR = 1.202, 95% CI = 1.013-1.427, p = 0.035) in Asian subgroup. CONCLUSION: This meta-analysis suggests that p53 Arg72Pro polymorphism is associated with increased risk of gastric cancer in Asians.