Biology Direct最新文献

Gliomas represent a highly aggressive class of tumors located in the brain. Despite the availability of multiple treatment modalities, the prognosis for patients diagnosed with glioma remains unfavorable. Therefore, further exploration of new biomarkers is crucial to enhance the prognostic assessment of glioma and to investigate more effective treatment options. In this research, we utilized multiple machine learning techniques to assess the significance of genes related to angiogenesis and epithelial-mesenchymal transition (EMT) in the context of prognosis and treatment for glioma patients. The random forest algorithm highlighted the significance of CALU, and further analysis indicated that the effect of CALU on glioma progression may be regulated by MYC. Different machine learning approaches were employed in our investigation to uncover crucial genes associated with angiogenesis and EMT in glioma. Our findings verify the connection between these genes and the prognosis of patients with glioma, as well as the results of immunotherapeutic interventions. Notably, through experimental verification, we identified CALU as a new prognostic marker for glioma, and inhibiting the expression of CALU can impede the progression of glioma.

Precise regulation of gene expression is crucial to development. Enhancers, the core of gene regulation, determine the spatiotemporal pattern of gene transcription. Since many disease-associated mutations are characterized in enhancers, the research on enhancer will provide clues to precise medicine. Rapid advances in high-throughput sequencing technology facilitate the characterization of enhancers at genome wide, but understanding the functional mechanisms of enhancers remains challenging. Herein, we provide a panorama of enhancer characteristics, including epigenetic modifications, enhancer transcripts, and enhancer-promoter interaction patterns. Furthermore, we outline the applications of high-throughput sequencing technology and functional genomics methods in enhancer research. Finally, we discuss the role of enhancers in human disease and their potential as targets for disease prevention and treatment strategies.

Endoplasmic reticulum (ER) stress has been shown to play a pivotal role in the pathogenesis of asthma. DEPTOR (DEP Domain Containing MTOR Interacting Protein) is an endogenous mTOR inhibitor that participates in various physiological processes such as cell growth, apoptosis, autophagy, and ER homeostasis. However, the role of DEPTOR in the pathogenesis of asthma is still unknown. In this study, an ovalbumin (OVA)-induced mice model and IL-13 induced 16HBE cells were used to evaluate the effect of DEPTOR on asthma. A decreased DEPTOR expression was shown in the lung tissues of OVA-mice and IL-13 induced 16HBE cells. Upregulation of DEPTOR attenuated airway goblet cell hyperplasia, inhibited mucus hypersecretion, decreased the expression of mucin MUC5AC, and suppressed the level of inflammatory factors IL-4 and IL-5, which were all induced by OVA treatment. The increased protein expression of ER stress markers GRP78, CHOP, unfolded protein response (UPR) related proteins, and apoptosis markers in OVA mice were also inhibited by DEPTOR overexpression. In IL-13 induced 16HBE cells, overexpression of DEPTOR decreased IL-4, IL-5, and MUC5AC levels, preventing ER stress response and UPR process. Furthermore, from the proteomics results, we identified that SOD1 (Cu/Zn Superoxide Dismutase 1) may be the downstream factor of DEPTOR. Similar to DEPTOR, upregulation of SOD1 alleviated asthma progression. Rescue experiments showed that SOD1 inhibition abrogates the remission effect of DEPTOR on ER stress in vitro. In conclusion, these data suggested that DEPTOR attenuates asthma progression by suppressing endoplasmic reticulum stress through SOD1.

Background: Hepatocellular carcinoma (HCC) is one of the most common as well as leading causes of mortality worldwide, and sorafenib is the first-line treatment in HCC patients. Unfortunately, drug resistance to sorafenib often develops. However, the underlying mechanism remains unclear. Here, we reveal the important role of macrophage extracellular traps (METs)-mediated crosstalk between macrophages and tumor cells in sorafenib resistance.

Methods: METs in HCC tumor tissues were detected using immunofluorescence. The concentrations of MPO-DNA, elastase and cytokines were measured using ELISA. The mRNA expression levels of genes were confirmed by qRT-PCR. The siRNAs were conducted to knock ARHGDIG in Hepa1-6 and Hep3B cells. Western Blot assay was performed to determine protein expression of Rho GDP dissociation inhibitor gamma (ARHGDIG, or RHOGDI-3), PADI2, and PADI4. Cell viability and migration were evaluated by CCK-8 assay and transwell assay, respectively. Cell ferroptosis was assessed by measurement of Fe²⁺ concentration, flow cytometry assay of lipid ROS, and western blot assay of GPX4. The functions of sorafenib, DNase I, IL4 neutralization antibody and GPX4 in tumor growth were explored through in vivo experiments.

Results: Sorafenib induced MET formation in M2 macrophages rather than M1 macrophages derived from both human and mice. In Hepa1-6 HCC mice, METs clearance by DNase I improved response to sorafenib therapy, detected by tumor weight, tumor growth curve, tumor volume, and survival. By screening candidate cytokines that affect macrophage function, we found that sorafenib-promoting IL4 secretion by HCC cells plays a crucial role in sorafenib-induced MET formation. Understanding the critical role of IL4 in sorafenib-induced MET formation led us to find that IL4 neutralization significantly improved the efficiency of sorafenib in HCC models. Mechanistically, we discovered that sorafenib increased the expression of ARHGDIG in HCC cells, which led to the release of IL4. In M2 macrophages, IL4 triggered MET formation by elevating the mRNA and protein expression of peptidyl arginine deiminase 4 (PADI4) rather than PADI2. In HCC models, GSK484 inhibition of PADI4 could consistently weaken sorafenib resistance and improve sorafenib efficiency. Importantly, we discovered that METs contribute to sorafenib resistance by inhibiting the ferroptosis of HCC cells. Meanwhile, PADI4 inhibition or DNase I could reverse the sorafenib resistance caused by METs-inhibiting ferroptosis of HCC cells.

Conclusion: Our study concludes that sorafenib-induced METs inhibit the ferroptosis of tumor cells, suggesting that targeting the IL4/PADI4/METs axis in HCC could reduce or prevent sorafenib resistance.

Background: MicroRNAs (miRNAs) are critical regulators of cancer progression, prompting our investigation into the specific function of miR-630 in pancreatic cancer stem cells (PCSCs). Analysis of miRNA and mRNA expression data in PCSCs revealed downregulation of miR-630 and upregulation of PRKCI, implying a potential role for miR-630 in PCSC function and tumorigenicity.

Results: Functional assays confirmed that miR-630 directly targets PRKCI, leading to the suppression of the Hedgehog signaling pathway and consequent inhibition of PCSC self-renewal and tumorigenicity in murine models. This study unveiled the modulation of the PRKCI-Hedgehog signaling axis by miR-630, highlighting its promising therapeutic potential for pancreatic cancer (PC) treatment.

Conclusions: MiR-630 emerges as a pivotal regulator in PCSC biology, opening up new avenues for targeted interventions in PC. The inhibitory effect of miR-630 on PCSC behavior underscores its potential as a valuable therapeutic target, offering insights into innovative treatment strategies for this challenging disease.

Chlamydomonas reinhardtii, a model organism for unicellular green microalgae, is widely used in basic and applied research. Nonetheless, proceeding towards synthetic biology requires a full set of manipulation techniques for inserting, removing, or editing genes. Despite recent advancements in CRISPR/Cas9, still significant limitations in producing gene knock-outs are standing, including (i) unsatisfactory genome editing (GE) efficiency and (ii) uncontrolled DNA random insertion of antibiotic resistance markers. Thus, obtaining efficient gene targeting without using marker genes is instrumental in developing a pipeline for efficient engineering of strains for biotechnological applications. We developed an efficient DNA-free gene disruption strategy, relying on phenotypical identification of mutants, to (i) precisely determine its efficiency compared to marker-relying approaches and (ii) establish a new DNA-free editing tool. This study found that classical CRISPR Cas9-based GE for gene disruption in Chlamydomonas reinhardtii is mainly limited by DNA integration. With respect to previous results achieved on synchronized cell populations, we succeeded in increasing the GE efficiency of single gene targeting by about 200 times and up to 270 times by applying phosphate starvation. Moreover, we determined the efficiency of multiplex simultaneous gene disruption by using an additional gene target whose knock-out did not lead to a visible phenotype, achieving a co-targeting efficiency of 22%. These results expand the toolset of GE techniques and, additionally, lead the way to future strategies to generate complex genotypes or to functionally investigate gene families. Furthermore, the approach provides new perspectives on how GE can be applied to (non-) model microalgae species, targeting groups of candidate genes of high interest for basic research and biotechnological applications.

Introduction: Dysregulated androgen receptor (AR) activity is central to various diseases, particularly prostate cancer (PCa), in which it drives tumour initiation and progression. Consequently, antagonising AR activity via anti-androgens is an indispensable treatment option for metastatic PCa. However, despite initial tumour remission, drug resistance occurs. Therefore, the AR signalling pathway has been intensively investigated. However, the role of AR protein stability in AR signalling and therapy resistance has not yet been deciphered. Therefore, this study aimed to investigate the role of AR protein changes in transactivity and assess its mechanism as a possible target in PCa.

Methods: LNCaP, C4-2, and 22Rv1 cells were treated with R1881, enzalutamide, cycloheximide, and Rocaglamide. Mass spectrometry analyses were performed on LNCaP cells to identify the pathways enriched by the treatments. Western blotting was performed to investigate AR protein levels and localisation changes. Changes in AR transactivity were determined by qPCR.

Results: Mass spectrometry analyses were performed on LNCaP cells to decipher the molecular mechanisms underlying androgen- and antiandrogen-induced alterations in the AR protein. Pathway analysis revealed the enrichment of proteins involved in different pathways that regulate translation. Translational and proteasome inhibitor experiments revealed that these AR protein changes were attributable to modifications in translational activity. Interestingly, the effects on AR protein levels in castration-resistant PCa (CRPC) cells C4-2 or enzalutamide-resistant cells 22Rv1 were less prominent and non-existent. This outcome was similarly observed in the alteration of AR transactivation, which was suppressed in hormone-sensitive prostate cancer (HSPC) LNCaP cells by translational inhibition, akin to the effect of enzalutamide. In contrast, treatment-resistant cell lines showed only a slight change in AR transcription.

Conclusion: This study suggests that in HSPC, AR activation triggers a signalling cascade that increases AR protein levels by enhancing its translation rate, thereby amplifying AR activity. However, this mechanism appears to be dysregulated in castration-resistant PCa cells.

Background: Biosynthesis of 17β-estradiol (E2) is a crucial ovarian function in mammals, which is essential for follicular development and pregnancy outcome. Exploring the epigenetic regulation of E2 synthesis is beneficial for maintaining ovary health and the optimal reproductive traits. NORFA is the first validated sow fertility-associated long non-coding RNA (lncRNA). However, its role on steroidogenesis is elusive. The aim of this study is to investigate the regulation and underlying mechanism of NORFA to E2 synthesis in sow granulosa cells (GCs).

Results: Through Pearson correlation analysis and comparative detection, we found that NORFA expression was positively correlated with the levels of pregnenolone (PREG) and E2 in follicles, which also exhibited similar alteration patterns during follicular atresia. ELISA was conducted and indicated for the first time that NORFA induced the synthesis of PREG and E2 in sow GCs in a dose- and time-dependent manner. RNA-seq, GSEA and quantitative analyses results validated that CYP11A1, the coding gene of P450SCC which is the first step rate-limiting enzyme of E2 synthesis, was a positive functional target of NORFA. Mechanistically, NORFA promotes SF-1 expression by stabilizing NR5A1 mRNA through directly interacting with its 3'-UTR, and also tethers SF-1 to shuttle into nucleus. Additionally, SF-1 in the nucleus activates CYP11A1 transcription by directly binding to its promoter, which ultimately induces E2 synthesis and inhibits GC apoptosis.

Conclusion: Our findings highlight that NORFA, a multifunctional lncRNA, induces E2 synthesis and inhibits GC apoptosis through the SF-1/CYP11A1 axis in a ceRNA-independent manner, which provide valuable clues and potential targets for follicular atresia inhibition and female fertility improvement.

The expression of TRIM47, a member of the TRIM protein and E3 ubiquitin ligase families, is elevated in various cancers, such as non-small cell lung cancer and colorectal cancer, and is linked to poor prognosis. This study aimed to investigate the role of TRIM47 in gastric cancer development. Using The Cancer Genome Atlas-Stomach Adenocarcinoma (TCGA-STAD) dataset and analysis of 20 patient samples from our center, TRIM47 was found to be significantly up-regulated in gastric cancer tissues and associated with advanced N-stage and poor prognosis. We constructed stable TRIM47 knockdown and overexpressing gastric cancer cell lines. CCK8, EDU, colony formation, wound healing, and Transwell tests were used to evaluate the effects on cell proliferation, invasion, and migration. The results showed that TRIM47 knockdown inhibited the proliferation, migration and invasion of gastric cancer cells, while TRIM47 overexpression promoted these behaviors. These results were further confirmed in vivo. In the mechanism part, we found that TRIM47 interacts with CYLD protein. Moreover, TRIM47 promotes K48-linked ubiquitination, leading to the degradation of CYLD by the proteasome, thereby activating the NF-κB pathway and regulating the biological behavior of gastric cancer cells. Taken together, our study demonstrated that TRIM47 is involved in the proliferation and metastasis of gastric cancer through the CYLD/NF-κB pathway.

Background: Accurately identifying effective biomarkers and translating them into clinical practice have significant implications for improving clinical outcomes in hepatocellular carcinoma (HCC). In this study, our objective is to explore appropriate methods to improve the accuracy of biomarker identification and investigate their clinical value.

Methods: Concentrating on the N6-methyladenosine (m6A) modification regulators, we utilized dozens of multi-omics HCC datasets to analyze the expression patterns and genetic features of m6A regulators. Through the integration of big data analysis with function experiments, we have redefined the biological roles of m6A regulators in HCC. Based on the key regulators, we constructed m6A risk models and explored their clinical value in estimating prognosis and guiding personalized therapy for HCC.

Results: Most m6A regulators exhibit abnormal expression in HCC, and their expression is influenced by copy number variations (CNV) and DNA methylation. Large-scale data analysis has revealed the biological roles of many key m6A regulators, and these findings are well consistent with experimental results. The m6A risk models offer significant prognostic value. Moreover, they assist in reassessing the therapeutic potential of drugs such as sorafenib, gemcitabine, CTLA4 and PD1 blockers in HCC.

Conclusions: Our findings suggest that the mutual validation of big data analysis and functional experiments may facilitate the precise identification and definition of biomarkers, and our m6A risk models may have the potential to guide personalized chemotherapy, targeted treatment, and immunotherapy decisions in HCC.