YY1: a key regulator inhibits gastric cancer ferroptosis and mediating apatinib-resistance.

OBJECTIVE: Gastric cancer (GC) stands as a prevalent and deadly global malignancy. Despite its role as a preoperative neoadjuvant therapy, Apatinib's effectiveness is curtailed among GC patients exhibiting elevated YY1 expression. YY1's connection to adverse prognosis, drug resistance, and GC metastasis is established, yet the precise underlying mechanisms remain elusive. This study aims to unravel potential pathogenic pathways attributed to YY1. DESIGN: Utilizing bioinformatics analysis, we conducted differentially expressed genes, functional annotation, and pathway enrichment analyses, and further validation through cellular and animal experiments. RESULTS: Higher YY1 expression correlated with diminished postoperative progression-free survival (PFS) and disease-specific survival (DSS) rates in TCGA analysis, identifying YY1 as an independent DSS indicator in gastric cancer (GC) patients. Notably, YY1 exhibited significantly elevated expression in tumor tissues compared to adjacent normal tissues. Bioinformatics analysis revealed noteworthy differentially expressed genes (DEGs), transcriptional targets, factors, and co-expressed genes associated with YY1. LASSO Cox analysis unveiled Transferrin as a prospective pivotal protein regulated by YY1, with heightened expression linked to adverse DSS and PFS outcomes. YY1's role in governing the p53 signaling pathway and ferroptosis in GC cells was further elucidated. Moreover, YY1 overexpression dampened immune cell infiltration within GC tumors. Additionally, YY1 overexpression hindered GC cell ferroptosis and mediated Apatinib resistance via the p53 pathway. Remarkably, IFN-a demonstrated efficacy in reversing Apatinib resistance and immune suppression in GC tissues. CONCLUSIONS: Our findings underscore the pivotal role of YY1 in driving GC progression and influencing prognosis, thus pinpointing it as a promising therapeutic target to enhance patient outcomes.

Identification of 14 glutathione S-transferase genes from Lasioderma serricorne and characterization of LsGSTe1 involved in lambda-cyhalothrin detoxification.

In insects, glutathione S-transferases (GSTs) play a pivotal role in the detoxification of a wide range of pesticides. The cigarette beetle, Lasioderma serricorne, is an economically important pest insect of stored products. Recently, pyrethroid insecticides have been used to control this pest. However, little is known concerning the responses and functions of GSTs in L. serricorne under pyrethroid exposure. In this study, transcriptome sequencing was performed on L. serricorne, and a total of 14 GSTs were identified by retrieving the unigene dataset. Of these, 13 predicted GSTs fell into six cytosolic classes, namely, delta, epsilon, omega, sigma, theta, and zeta, and one was assigned to an "unclassified" group. The GST genes were differentially expressed in various larval tissues and at different developmental stages. Exposure to the pyrethroid insecticide lambda-cyhalothrin (LCT) caused oxidative stress in L. serricorne larvae and led to significantly elevated expression levels of six genes, among which LsGSTe1 was the most upregulated. Recombinant LsGSTE1 protein displayed LCT-metabolizing activity. Furthermore, LsGSTE1 protects cells against oxidative stress. Moreover, knockdown of LsGSTe1 by RNA interference dramatically increased the susceptibility of L. serricorne larvae to LCT treatment. The results from this study provide sequence resources and expression data for GST genes in L. serricorne. Our findings indicate that LsGSTE1 plays a dual role in LCT detoxification by metabolizing the pesticide and by preventing LCT-induced oxidative stress. Thus, the LsGSTe1 gene could be used as a potential target for sustainable management of the cigarette beetle.

Splicing factor SRSF1 promotes breast cancer progression via oncogenic splice switching of PTPMT1.

BACKGROUND: Intensive evidence has highlighted the effect of aberrant alternative splicing (AS) events on cancer progression when triggered by dysregulation of the SR protein family. Nonetheless, the underlying mechanism in breast cancer (BRCA) remains elusive. Here we sought to explore the molecular function of SRSF1 and identify the key AS events regulated by SRSF1 in BRCA. METHODS: We conducted a comprehensive analysis of the expression and clinical correlation of SRSF1 in BRCA based on the TCGA dataset, Metabric database and clinical tissue samples. Functional analysis of SRSF1 in BRCA was conducted in vitro and in vivo. SRSF1-mediated AS events and their binding motifs were identified by RNA-seq, RNA immunoprecipitation-PCR (RIP-PCR) and in vivo crosslinking followed by immunoprecipitation (CLIP), which was further validated by the minigene reporter assay. PTPMT1 exon 3 (E3) AS was identified to partially mediate the oncogenic role of SRSF1 by the P-AKT/C-MYC axis. Finally, the expression and clinical significance of these AS events were validated in clinical samples and using the TCGA database. RESULTS: SRSF1 expression was consistently upregulated in BRCA samples, positively associated with tumor grade and the Ki-67 index, and correlated with poor prognosis in a hormone receptor-positive (HR+) cohort, which facilitated proliferation, cell migration and inhibited apoptosis in vitro and in vivo. We identified SRSF1-mediated AS events and discovered the SRSF1 binding motif in the regulation of splice switching of PTPMT1. Furthermore, PTPMT1 splice switching was regulated by SRSF1 by binding directly to its motif in E3 which partially mediated the oncogenic role of SRSF1 by the AKT/C-MYC axis. Additionally, PTPMT1 splice switching was validated in tissue samples of BRCA patients and using the TCGA database. The high-risk group, identified by AS of PTPMT1 and expression of SRSF1, possessed poorer prognosis in the stage I/II TCGA BRCA cohort. CONCLUSIONS: SRSF1 exerts oncogenic roles in BRCA partially by regulating the AS of PTPMT1, which could be a therapeutic target candidate in BRCA and a prognostic factor in HR+ BRCA patient.

Profiles of alternative splicing landscape in breast cancer and their clinical significance: an integrative analysis based on large-sequencing data.

BACKGROUND: Alternative splicing (AS) is closely correlated with the initiation and progression of carcinoma. The systematic analysis of its biological and clinical significance in breast cancer (BRCA) is, however, lacking. METHODS: Clinical data and RNA-seq were obtained from the TCGA dataset and differentially expressed AS (DEAS) events between tumor and paired normal BRCA tissues were identified. Enrichment analysis was then used to reveal the potential biological functions of DEAS events. We performed protein-protein interaction (PPI) analysis of DEAS events by using STRING and the correlation network between splicing factors (SFs) and AS events was constructed. The LASSO Cox model, Kaplan-Meier and log-rank tests were used to construct and evaluate DEAS-related risk signature, and the association between DEAS events and clinicopathological features were then analyzed. RESULTS: After strict filtering, 35,367 AS events and 973 DEAS events were detected. DEAS corresponding genes were significantly enriched in pivotal pathways including cell adhesion, cytoskeleton organization, and extracellular matrix organization. A total of 103 DEAS events were correlated with disease free survival. The DEAS-related risk signature stratified BRCA patients into two groups and the area under curve (AUC) was 0.754. Moreover, patients in the high-risk group had enriched basel-like subtype, advanced clinical stages, proliferation, and metastasis potency. CONCLUSIONS: Collectively, the profile of DEAS landscape in BRCA revealed the potential biological function and prognostic value of DEAS events.

Splicing factors: Insights into their regulatory network in alternative splicing in cancer.

More than 95% of all human genes are alternatively spliced after transcription, which enriches the diversity of proteins and regulates transcript and/or protein levels. The splicing isoforms produced from the same gene can manifest distinctly, even exerting opposite effects. Mounting evidence indicates that the alternative splicing (AS) mechanism is ubiquitous in various cancers and drives the generation and maintenance of various hallmarks of cancer, such as enhanced proliferation, inhibited apoptosis, invasion and metastasis, and angiogenesis. Splicing factors (SFs) play pivotal roles in the recognition of splice sites and the assembly of spliceosomes during AS. In this review, we mainly discuss the similarities and differences of SF domains, the details of SF function in AS, the effect of SF-driven pathological AS on different hallmarks of cancer, and the main drivers of SF expression level and subcellular localization. In addition, we briefly introduce the application prospects of targeted therapeutic strategies, including small-molecule inhibitors, siRNAs and splice-switching oligonucleotides (SSOs), from three perspectives (drivers, SFs and pathological AS). Finally, we share our insights into the potential direction of research on SF-centric AS-related regulatory networks.

Establishment and validation of a novel autophagy-related gene signature for patients with breast cancer.

BACKGROUND: There exists considerable evidence conforming that autophagy may play an important role in the biological process of breast cancer. This study aimed to construct and evaluate a novel autophagy-related gene signature as a potential prognostic factor and therapeutic target in breast cancer patients based on high-throughput sequencing datasets. MATERIALS & METHODS: Autophagy-related genes obtained from the Human Autophagy Database and high-sequencing data obtained from The Cancer Genome Atlas (TCGA) were analyzed to identify differential expressed genes (DEGs) between tumor and normal tissues. Then GO and KEGG analysis were performed to explore potential biological and pathological functions of DEGs. Autophagy-related prognostic genes were identified by univariate COX regression analysis. Subsequently stepwise model selection using the Alkaike information criterion (AIC) and multivariate COX regression model was performed to construct autophagy-related gene signature. Then patients were divided into high- and low-risk groups based on the risk score identified by the autophagy-related gene signature. Multivariate COX regression model and stratification analysis were used to specify the prognostic value of this gene signature in whole cohort and various subgroups. T-test and ANOVA analysis were used to compare the expression differences of continuous variables (5 prognostic genes and risk score) in binary and multiple category groups respectively. Kaplan-Meier analysis, log-rank tests and the area under receiver operating characteristic (ROC) curve (AUC) were conducted to validate the accuracy and precise of the autophagy-related gene signature based on GSE20685 and GSE21653 datasets. RESULTS: We profiled autophagy-related DEGs in normal and breast tumor tissues. GO and KEGG analysis indicated that autophagy-related DEGs might participate in breast cancer occurrence, development and drug resistance. Then we identified five autophagy-related genes (EIF4EBP1, ATG4A, BAG1, MAP1LC3A and SERPINA1) that had significantly prognostic values for breast cancer. Autophagy-related gene signature was constructed and patients were divided into high- and low- risk groups based on their risk score. Patients in the high-risk group tended to have shorter overall survival (OS) and relapse-free survival (RFS) times than those in the low-risk group (OS: HR = 1.620, 95%CIs: 1.345-1.950; P < 0.001; RFS: HR = 1.487, 95%CIs: 1.248-1.771, P < 0.001). Autophagy-related gene signature had significant prognostic value in stratified subgroups especially in advanced breast cancer subgroups (T3-4; N2-3; stage III-IV). Its prognostic value was further confirmed in two GEO validation datasets (GSE20685: P = 6.795e-03; GSE21653: P = 1.383e-03). Finally, association analysis between clinicopathological factors and gene signature showed the risk score was higher in patients with ER/PR negative, higher clinical stage or T stage (P < 0.01). CONCLUSION: We established and confirmed a novel autophagy-related gene signature for patients with breast cancer that had independent survival prognostic value especially in advanced breast cancer subgroups. Our research might promote the molecular mechanism study of autophagy-related genes in breast cancer.

EDNRB isoform 3 confers Temozolomide resistance in A375 melanoma cells by modulating membrane potential, reactive oxygen species and mitochondrial Ca2.

BACKGROUND: The role of endothelin receptor type B (EDNRB) isoform 3 involved in Temozolomide (TMZ)-induced melanoma cell death has not yet been elucidated. METHODS: The subcellular localization of EDNRB isoform 3 was determined by confocal and immunoblotting assays. Silencing EDNRB isoform 3 was performed by CRISPR/Cas9. Apoptosis was assessed by annexin V/propium iodide staining and caspases 3/7/9 activity. Mitochondrial membrane potential, reactive oxygen species and mitochondrial Ca2+ were measured by flow cytometry. Apoptosis protein array was applied. RESULTS: Confocal and immunoblot analyses indicate mitochondrial localization of EDNRB isoform 3 and the first N-terminal (1-22) amino acids are sufficient for its mitochondrial targeting. EDNRB isoform 3 depleted A375 cells significantly confers chemoresistance with mitochondrial depolarization, reduced reactive oxygen species, enhanced mitochondrial Ca2+ uptake and decreased caspase 9 activation. Additionally, apoptosis array shows that lack of EDNRB isoform 3 has relatively lower expression of phosphorylation of p53 at S392 and a slightly higher expression of Paraoxonase 2. CONCLUSION: Our findings raise the possibility of targeting EDNRB isoform 3 as a new therapeutic strategy in combination with TMZ for melanoma treatment.

Prognostic alternative mRNA splicing signature in hepatocellular carcinoma: a study based on large-scale sequencing data.

Most genes are alternatively spliced and increasing number of evidences show that alternative splicing (AS) is modified and related to tumor progression. Systematic profiles of AS signature in hepatocellular carcinoma (HCC) is absent and urgently needed. Here, differentially spliced AS transcripts between HCC and non-HCC tissues were compared, prognosis-associated AS events by using univariate Cox regression analysis were selected. Our gene functional enrichment analysis demonstrated the potential pathways enriched by survival-associated AS. Prognostic AS signatures were then constructed for HCC prognosis prediction by Lasso regression model. We also analyzed splicing factors (SFs) regulating underlying mechanisms by Pearson correlation and then built corresponding regulatory networks. In addition, we explored the performance of AS signature in the mutated HCC samples. Genome-wide AS events in 377 HCC patients from TCGA were profiled. Among 34 163 AS events in 8985 genes, 3950 AS events in 2403 genes associated with overall survival (OS) significantly for HCC were detected. In addition, computational algorithm results showed that metabolic and ribosome pathways may be the potential molecular mechanisms regulating the poor prognosis. More importantly, survival-associated AS signatures revealed high performance in predicting HCC prognosis. The area under curve for AS signature was 0.806 in all HCC and 0.944 in TP53 mutated HCC samples at 2000 days of OS. We submitted prognostic SFs to build the AS regulatory network, from which we found prognostic AS events were significantly enriched in metabolism-related pathways. A robust AS signature for HCC patients and revealed the regulatory splicing networks contributing to the potential significantly enriched metabolism-related pathways.

Binding of organic ligands with Al(III) in dissolved organic matter from soil: implications for soil organic carbon storage.

The binding characteristics of organic ligands with Al(III) in soil dissolved organic matter (DOM) is essential to understand soil organic carbon (SOC) storage. In this study, two-dimensional (2D) FTIR correlation spectroscopy was developed as a novel tool to explore the binding of organic ligands with Al(III) in DOM present in soils as part of a long-term (21-year) fertilization experiment. The results showed that while it is a popular method for characterizing the binding of organic ligands and metals, fluorescence excitation-emission matrix-parallel factor analysis can only characterize the binding characteristics of fluorescent substances (i.e., protein-, humic-, and fulvic-like substances) with Al(III). However, 2D FTIR correlation spectroscopy can characterize the binding characteristics of both fluorescent and nonfluorescent (i.e., polysaccharides, lipids, and lignin) substances with Al(III). Meanwhile, 2D FTIR correlation spectroscopy demonstrated that the sequencing/ordering of organics binding with Al(III) could be modified by the use of long-term fertilization strategies. Furthermore, 2D FTIR correlation spectroscopy revealed that the high SOC content in the chemical plus manure (NPKM) treatment in the long term fertilization experiment can be attributed to the formation of noncrystalline microparticles (i.e., allophane and imogolite). In summary, 2D FTIR correlation spectroscopy is a promising approach for the characterization of metal-organic complexes.

[Meta-analysis of dapoxetine on demand in the treatment of premature ejaculation].

OBJECTIVE: To assess the efficacy of dapoxetine on demand for premature ejaculation and provide evidence for clinical decision-making. METHODS: We searched PubMed, Embase, BIOSIS Previews, Cochrane Library, CNKI Database and Wanfang Database for literature on dapoxetine on demand for premature ejaculation. We performed meta-analysis on the identified publications and evaluated its therapeutic efficacy based on the intravaginal ejaculatory latency time (IELT), patient-reported global impression of change (PGI), and composite PRO criteria for clinical benefit (CCCB). RESULTS: Four relevant studies were included involving 6 081 cases of premature ejaculation. Compared with the placebo controls, the patients treated with dapoxetine on demand showed significant improvement in IELT (WMD = 1.39, 95% CI [1.23, 1.55], P < 0.000 01), PGI (OR = 2.59, 95% CI [2.21, 3.04], P < 0. 000 01), and CCCB (OR = 2.59, 95% CI [1.98, 3.39], P < 0.000 01). There were significant differences between the 60 mg and 30 mg dapoxetine groups in IELT (WMD = 0.46, 95% CI [0.19, 0.74], P = 0.001 0) and PGI (OR = 1.32, 95% CI [1.06, 1.64], P = 0.01), but not in CCCB (OR = 1.39, 95% CI [0.90, 2.15], P = 0.13). CONCLUSION: Dapoxetine on demand can prolong IELT and improve PGI and CCCB, either at the dose of 60 mg or 30 mg, and has an even better efficacy in prolonging IELT and improving PGI at 60 mg.

Fluorescence excitation-emission spectroscopy with regional integration analysis for assessment of compost maturity.

Composting of animal manures is believed as an alternative way for directly recycling them in farms, and therefore assessment of compost maturity is crucial for achieving high quality compost. Fluorescence excitation-emission matrices (EEMs) combined with regional integration analysis is presented to assess compost maturity. The results showed that the EEM contours of water-extract organic matter (WEOM) from immature composts exhibited four peaks at excitation/emission (Ex/Em) of 220/340nm, 280/340nm, 220/410nm, and 330/410nm, whereas EEM contour of WEOM from mature composts had only two peaks at Ex/Em of 230/420nm and 330/420nm. Pearson correlation demonstrated that peaks intensity rather than their ratios had a significantly correlation with the common indices assessing compost maturity, whereas the normalized excitation-emission area volumes (Φ(i,n)s) from regional integration analysis had a stronger correlation with the common indices assessing compost maturity than peaks intensity. It is concluded that the Φ(i,n)s from regional integration analysis are more suitable to assess the maturity of compost than the intensities of peaks. Therefore, the fluorescence spectroscopy combined with regional integration analysis can be used as a valuable industrial and research tool for assessing compost maturity, given its high sensitivity and selectivity.

[Serum ferritin in donors with regular plateletpheresis].

This study was aimed to evaluate the impact of regular donating platelets on serum ferritin (SF) of donors. A total of 93 male blood donors including 24 initial plateletpheresis donors and 69 regular plateletpheresis donors were selected randomly. Their SF level was measured by ELISA. The results showed that the SF level of initial plateletpheresis donors and regular plateletpheresis donors were 91.08 ± 23.38 µg/L and 57.16 ± 35.48 µg/L respectively, and all were in normal levels, but there was significant difference between the 2 groups (p < 0.05). The SF level decreased when the donation frequency increased, there were no significant differences between the groups with different donation frequency. Correlation with lifetime donations of platelets was not found. It is concluded that regular plateletpheresis donors may have lower SF level.

PARAFAC modeling of fluorescence excitation-emission spectra for rapid assessment of compost maturity.

Assessment of compost maturity is crucial for achieving high quality compost in order to guarantee its marketability. In this context, a novel technique that combines fluorescence excitation-emission matrices (EEMs) with parallel factor (PARAFAC) analysis to assess compost maturity is presented. A total of 60 fluorescence EEMs of composts were successfully decomposed into a three-factor model using PARAFAC analysis. Components 1 [excitation/emission (Ex/Em) wavelengths=(230, 330)/410] and 2 [Ex/Em wavelengths=(250, 350)/450] were attributable to humic-like and fulvic-like substances, whereas component 3 [Ex/Em wavelengths=(220, 280)/340] belonged to protein-like substances. Pearson correlation analysis between the common maturity indices and log scores of three components demonstrated that components 1 and 3 are more suitable to assess compost maturity than component 2. These results reveal that EEM-PARAFAC could be applied as a valuable tool for assessing compost maturity, given its high sensitivity and selectivity.