Lycorine attenuated proliferation and induced apoptosis on imatinib-resistant K562 cell by inhibiting autophagy.

BACKGROUND: Tyrosine kinase inhibitor (TKI) resistance is a significant factor exacerbating the burden on chronic myeloid leukemia (CML) patients and impacting clinical efficacy. The main goal is to offer new insights into overcoming drug resistance in treating CML. METHODS: Imatinib (IM) resistant K562/IM cells were generated using gradient induction. Responses to IM, lycorine, and autophagy modulators were assessed using CCK-8. Protein expression of Beclin-1, Atg5, LC3, Caspase-3, P62, Bax, Bcl-2, and P-gp was detected using Western blot. Lycorine-induced apoptosis and cell cycle changes were evaluated through flow cytometry, while autophagy alterations were detected using monodansylcadaverine (MDC) staining. In the K562/IM mice model, non-obese diabetic severe combined immunodeficent (NOD-SCID) mice were subcutaneously inoculated with K562/IM cells. After 17 days of lycorine injection, assessments included tumor size, hematoxylin-eosin (HE) staining, and Ki67 expression. RESULTS: After 72 h of IM treatment, K562/IM cells showed a 55.86-fold increase in drug resistance compared to K562 cells. Lycorine treatment for 24 h inhibited cell proliferation and induced G0/G1 phase cell cycle arrest and apoptosis in both K562 and K562/IM cells. MDC staining indicated reduced autophagy in K562/IM cells, mitigated by lycorine. In vivo experiments demonstrated reduced tumor size and Ki67 proliferation index in the lycorine treatment group (K562+L, K562/IM+L) compared to the control group, particularly in the drug-resistant group. However, no significant change in Ki67 was observed in the K562 group after lycorine treatment. CONCLUSION: In summary, K562/IM cells displayed heightened autophagy levels compared to K562 cells. Lycorine effectively impeded the proliferation of K562/IM cells through diverse mechanisms, including reduced autophagy, enhanced apoptosis, and induced cell cycle arrest.

Effects of immune cells in mediating the relationship between gut microbiota and myelodysplastic syndrome: a bidirectional two-sample, two-step Mendelian randomization study.

BACKGROUND: The definitive establishment of a causal relationship between gut microbiota and myelodysplastic syndrome (MDS) has not been achieved. Furthermore, the involvement of immune cells in mediating the connection between gut microbiota and MDS is presently unclear. METHODS: To elucidate the bidirectional correlation between gut microbiota and MDS, as well as to investigate the mediating role of immune cells, a bidirectional two-sample, two-step Mendelian randomization (MR) study was conducted. Summary statistics were obtained from genome-wide association studies (GWAS), including MDS (456,348 individuals), gut microbiota (18,340 individuals), and 731 immune cells signatures (3757 individuals). RESULTS: Genetically predicted eight gut microbiota traits were significantly associated with MDS risk, but not vice versa. Through biological annotation of host-microbiome shared genes, we found that immune regulation may mediate the impact of gut microbiota on MDS. Subsequently, twenty-three immunophenotypes that exhibited significant associations with MDS risk and five of these immunophenotypes were under the causal influence of gut microbiota. Importantly, the causal effects of gut microbiota on MDS were significantly mediated by five immunophenotypes, including CD4 +T cell %leukocyte, CD127 on CD45RA - CD4 not regulatory T cell, CD45 on CD33 + HLA DR + WHR, CD33 on basophil, and Monocyte AC. CONCLUSIONS: Gut microbiota was causally associated with MDS risk, and five specific immunophenotypes served as potential causal mediators of the effect of gut microbiota on MDS. Understanding the causality among gut microbiota, immune cells and MDS is critical in identifying potential targets for diagnosis and treatment.

Exploring the causal relationship between gut microbiota and multiple myeloma risk based on Mendelian randomization and biological annotation.

Introduction: The microbial genome-wide association studies (mbGWAS) have highlighted significant host-microbiome interactions based on microbiome heritability. However, establishing causal relationships between particular microbiota and multiple myeloma (MM) remains challenging due to limited sample sizes. Methods: Gut microbiota data from a GWAS with 18,340 participants and MM summary statistics from 456,348 individuals. The inverse variance-weighted (IVW) method was used as the main bidirectional Mendelian randomization (MR) analysis. To assess the robustness of our results, we further performed supplementary analyses, including MR pleiotropy residual sum and outlier (MR-PRESSO) test, MR-Egger, Weighted median, Simple mode, and Weighted mode. Moreover, a backward MR analysis was conducted to investigate the potential for reverse causation. Finally, gene and gene-set-based analyses were then conducted to explore the common biological factors connecting gut microbiota and MM. Results: We discovered that 10 gut microbial taxa were causally related to MM risk. Among them, family Acidaminococcaceae, Bacteroidales family S24-7, family Porphyromonadaceae, genus Eubacterium ruminantium group, genus Parabacteroides, and genus Turicibacter were positively correlated with MM. Conversely, class Verrucomicrobia, family Verrucomicrobiaceae, genus Akkermansia, and order Verrucomicrobiales were negatively correlated with MM. The heterogeneity test revealed no Heterogeneity. MR-Egger and MR-PRESSO tests showed no significant horizontal pleiotropy. Importantly, leave-one-out analysis confirmed the robustness of MR results. In the backward MR analysis, no statistically significant associations were discovered between MM and 10 gut microbiota taxa. Lastly, we identified novel host-microbiome shared genes (AUTS2, CDK2, ERBB3, IKZF4, PMEL, SUOX, and RAB5B) that are associated with immunoregulation and prognosis in MM through biological annotation. Discussion: Overall, this study provides evidence supporting a potential causal relationship between gut microbiota and MM risk, while also revealing novel host-microbiome shared genes relevant to MM immunoregulation and clinical prognosis.

Role of lipid metabolism gene KLF4 in osteoarthritis.

INTRODUCTION: Osteoarthritis (OA) is a common degenerative disease of joints, which can appear in almost any joint of the body. Therefore, the widespread occurrence of this disease has a huge impact on the lives of patients around the world. As an important part of metabolism, lipid metabolism is closely related to the occurrence and development of osteoarthritis. METHOD: We screened UGCG and KLF4 based on weighted co-expression network analysis (WGCNA) and SVM-REF analysis. The data from Gene Expression Omnibus (GEO) and single-cell data verified the expression of these two genes. We analyzed KLF4-related genes and established a diagnosis model of OA related to lipid metabolism through the least absolute shrinkage and selection operator (LASSO) analysis. RT-PCR was used to verify the expression of KLF4 in osteoarthritis. RESULTS: Ten important lipid metabolism related genes (LMRGs) in OA were obtained. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that they are involve in the formation of immune microenvironment in osteoarthritis. CIBERSORT analysis revealed that there were significant differences in the immune microenvironment between osteoarthritis patients and normal controls. RT-PCR results showed that the expression of KLF4 in OA samples was lower than that in normal samples. The diagnostic model can be used to diagnose OA patients well. CONCLUSIONS: Overall, we demonstrated the potential relationship between the abnormal lipid metabolism and the pathological process of OA. Finally, we identified KLF4 as our significant LMRG and constructed a KLF4-related scoring model to accurately diagnose OA. In conclusion, therapy strategies targeting on regulating lipid metabolism may become a key factor in treating OA. Key Points (a) We identified the significant LMRG KLF4 and constructed a novel KLF4-related scoring model for the accuracy diagnosis of OA. (b) The potential relationship between lipid metabolism and the immune microenvironment in OA was demonstrated in our research. (c) The relationship of lipid metabolism and OA has been further improved in our research and provided novel insight for the diagnosis and therapy for OA patients.

Deubiquitinating enzyme USP10 promotes osteosarcoma metastasis and epithelial-mesenchymal transition by stabilizing YAP1.

BACKGROUND: Osteosarcoma (OS) is a fatal adolescent tumor, which is susceptible to remote metastases at an early stage, and its treatment remains a major challenge. ubiquitin-specific protease 10 (USP10) is primarily located in the cytoplasm and can therefore deubiquitinate various cytoplasmic proteins. However, the expression and mechanism of USP10 in OS remain ambiguous. The aim of this study was to explore how USP10 affects Yes-associated protein1 (YAP1) to influence the metastasis and epithelial-mesenchymal transition (EMT). METHODS: Western blotting, qRT-PCR, and immunohistochemical (IHC) analyses were performed to evaluate USP10 and YAP1 levels. Using wound healing and transwell tests, the roles and molecular pathways of USP10 and YAP1 ability to migrate and invade of OS were investigated, and cell morphological alterations were examined using phalloidin staining. RESULTS: Our results indicated that USP10, a new type of deubiquitinating protease, is increased in OS tissues and cells contrasted with adjacent healthy tissues. Overexpression of USP10 correlated with tumor size, distant metastasis, and TNM stage, and was an independent factor of poor prognosis in OS patients. Also, USP10 expression is closely connected with the incident of OS metastasis and tumor size. Functional assays revealed that USP10 knockdown suppressed cell migrating and invading ability and inhibited the EMT of OS cells in vivo and in vitro. In addition, we showed that USP10 knockdown decreased the levels of YAP1, which is an important positive regulator of migration and invasion in many cancers. We also found a significant positive correlation between USP10 and YAP1 levels, further demonstrating that USP10-induced migration and EMT are based on YAP1 in OS cells. In a mechanistic way, USP10 stabilizes the expression of YAP1 by mediating its deubiquitination in OS cells. CONCLUSION: Together, this study showed that USP10 can directly interact with YAP1 to reduce ubiquitinated YAP1, thereby stabilizing its protein levels and affecting EMT and distant metastasis in OS cells.

Osteosarcoma subtypes based on platelet-related genes and tumor microenvironment characteristics.

Background: Osteosarcoma is a common metastatic tumor in children and adolescents. Because of its easy metastasis, patients often show a poor prognosis. Recently, researchers have found that platelets are closely related to metastasis of a variety of malignant tumors, but the role of platelets related characteristics in osteosarcoma is still unknown. The purpose of this study is to explore the characteristics of platelet-related subtypes and cell infiltration in tumor microenvironment. Methods: We collected osteosarcoma cohorts from TCGA and GEO databases, and explored the molecular subtypes mediated by platelet-related genes and the related TME cell infiltration according to the expression of platelet-related genes in osteosarcoma. In addition, we also explored the differentially expressed genes (DEGs) among different molecular subtypes and established a protein-protein interaction network (PPI). Then we constructed a platelet scoring model by Univariate cox regression and least absolute shrinkage and selection operator (Lasso) cox regression model to quantify the characteristics of platelet in a single tumor. RT-PCR was used to investigate the expression of six candidate genes in osteosarcoma cell lines and normal osteoblast lines. Finally, we also predicted potential drugs with therapeutic effects on platelet-related subtypes. Results: We found that platelet-related genes (PRGs) can distinguish osteosarcoma into two different platelet-related subtypes, C1 and C2. And the prognosis of the C2 subtype was significantly worse than that of C1 subtype. The results of ESTIMATE analysis and GO/KEGG enrichment showed that the differences between different subtypes were mainly concentrated in immune response pathways, and the immune response of C2 was inhibited relative to C1. We further studied the relationship between platelet-related subtypes and immune cell infiltration. We found that the distribution of most immune cells in C1 subtype was higher than that in C2 subtype, and there was a correlation between C1 subtype and more immune cells. Finally, we screened the PRGs related to the prognosis of osteosarcoma through Univariate Cox regression, established independent prognostic platelet characteristics consisting of six genes to predict the prognosis of patients with OS, and predicted the drugs that may be used in the treatment of osteosarcoma. RT-PCR was used to verify the expression of candidate genes in osteosarcoma cells. Conclusion: Platelet scoring model is a significant biomarker, which is of great significance to determine the prognosis, molecular subtypes, characteristics of TME cell infiltration and therapy in patients with OS.

Circular RNA circPRMT5 is upregulated in breast cancer and is required for cell proliferation and migration.

BACKGROUND: To evaluate the role of cyclic protein arginine methyltransferase 5 (circPRMT5) in the occurrence and development of breast cancer (BC). METHODS: A total of 90 BC patients who underwent radical mastectomy and 40 age-matched healthy female controls were recruited in the Second People's Hospital of China Three Gorges University, Yichang Second People's Hospital from 2017 to 2020. Quantitative reverse transcription polymerase chain reaction (RT-qPCR) was used to detect the expression levels of circPRMT5 in BC tissues, serum, normal breast cell line (MCF-10A), and BC cell line (T47D, MCF-7, BT549, Hs-578T, and MDA-MB-231, MDAMB-468). The associations between circPRMT5 expression level and age, tumor size, degree of differentiation, TNM stage, distant metastasis, estrogen receptor (ER) or progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) status were analyzed. BC cell lines with circPRMT5 knockdown or overexpression were subject to CCK-8 cell proliferation assay, and transwell cell invasion/migration assay. RESULTS: CircPRMT5 expression in BC tissue was higher than that in adjacent normal breast tissue. Consistently, the expression level of circPRMT5 was also elevated in serum samples collected from BC patients when compared with healthy controls. And in multiple breast cancer cell lines, circPRMT5 was upregulated as compared to normal breast epithelial MCF-10A cells. CircPRMT5 expression level was correlated with tumor size, TNM stage, lymph node metastasis distant metastasis, but no correlation was observed with ER, PR, HER2 status. Overexpression of circPRMT5 promoted the proliferation, invasion, and migration of MCF7 cells; while the knockdown of circPRMT5 inhibited cell proliferation, invasion, and migration. DISCUSSION: CircPRMT5 seems to act as an oncogene in the progression of BC. Our data suggest that CircPRMT5 may be used as a biomarker for the diagnosis, prognosis evaluation, and targeted therapy of breast cancer.

The roles of glycolysis in osteosarcoma.

Metabolic reprogramming is of great significance in the progression of various cancers and is critical for cancer progression, diagnosis, and treatment. Cellular metabolic pathways mainly include glycolysis, fat metabolism, glutamine decomposition, and oxidative phosphorylation. In cancer cells, reprogramming metabolic pathways is used to meet the massive energy requirement for tumorigenesis and development. Metabolisms are also altered in malignant osteosarcoma (OS) cells. Among reprogrammed metabolisms, alterations in aerobic glycolysis are key to the massive biosynthesis and energy demands of OS cells to sustain their growth and metastasis. Numerous studies have demonstrated that compared to normal cells, glycolysis in OS cells under aerobic conditions is substantially enhanced to promote malignant behaviors such as proliferation, invasion, metastasis, and drug resistance of OS. Glycolysis in OS is closely related to various oncogenes and tumor suppressor genes, and numerous signaling pathways have been reported to be involved in the regulation of glycolysis. In recent years, a vast number of inhibitors and natural products have been discovered to inhibit OS progression by targeting glycolysis-related proteins. These potential inhibitors and natural products may be ideal candidates for the treatment of osteosarcoma following hundreds of preclinical and clinical trials. In this article, we explore key pathways, glycolysis enzymes, non-coding RNAs, inhibitors, and natural products regulating aerobic glycolysis in OS cells to gain a deeper understanding of the relationship between glycolysis and the progression of OS and discover novel therapeutic approaches targeting glycolytic metabolism in OS.