Bioinformatic analysis of the expression profile and identification of RhoGDI2 as a biomarker in imatinib-resistant K562 cells.

OBJECTIVES: Chronic myeloid leukemia (CML) is an aggressive malignancy originating from hematopoietic stem cells. Imatinib (IM), the first-generation tyrosine kinase inhibitor, has greatly improved theliving quality of CML patients. However, owing to the recurrence and treatment failure coming from tyrosine kinase inhibitor (TKIs) resistance, some CML patients still bear poor prognosis. Therefore, we aimed to seek potential signaling pathways and specific biomarkers for imatinib resistance. METHODS: We performed mRNA and miRNA expression profiling in imatinib-sensitive K562 cells (IS-K562) and imatinib-resistant K562 cells (IR-K562). Differentially expressed genes (DEGs) were identified and pathway enrichment analyses were performed to explore the potential mechanism. The protein-protein interaction (PPI) network and miRNA-mRNA regulatory network were constructed to explore potential relationships among these genes. RT-qPCR, western blot and CCK8 were used for further experiments. RESULTS: A total of 623 DEGs and 61 differentially expressed miRNAs were identified. GO revealed that DEGs were mainly involved in cell adhesion, cell migration, differentiation, and inflammatory response. KEGG revealed that DEGs were typically enriched in the Rap1 signaling pathway, focal adhesion, proteoglycans and transcriptional misregulation in cancer, signaling pathways regulating pluripotency of stem cells and some immune-related pathways. The protein-protein interaction (PPI) network and miRNA-mRNA regulatory network revealed a web of diverse connections among genes. Finally, we proved that RHoGDI2 played a critical role in imatinib resistance. CONCLUSION: The dynamic interplay between genes and signaling pathways is associated with TKIs resistance and RHoGDI2 is identified as a biomarker in IR-K562.

P2Y12 receptor involved in the development of chronic nociceptive pain as a sensory information mediator.

Direct or indirect damage to the nervous system (such as inflammation or tumor invasion) can lead to dysfunction and pain. The generation of pain is mainly reflected in the activation of glial cells and the abnormal discharge of sensory neurons, which transmit stronger sensory information to the center. P2Y12 receptor plays important roles in physiological and pathophysiological processes including inflammation and pain. P2Y12 receptor involved in the occurrence of pain as a sensory information mediator, which enhances the activation of microglia and the synaptic plasticity of primary sensory neurons, and reaches the higher center through the ascending conduction pathway (mainly spinothalamic tract) to produce pain. While the application of P2Y12 receptor antagonists (PBS-0739, AR-C69931MX and MRS2359) have better antagonistic activity and produce analgesic pharmacological properties. Therefore, in this article, we discussed the role of the P2Y12 receptor in different chronic pains and its use as a pharmacological target for pain relief.

Molecular subtypes predict therapeutic responses and identifying and validating diagnostic signatures based on machine learning in chronic myeloid leukemia.

Chronic myeloid leukemia (CML) is a hematological tumor derived from hematopoietic stem cells. The aim of this study is to analyze the biological characteristics and identify the diagnostic markers of CML. We obtained the expression profiles from the Gene Expression Omnibus (GEO) database and identified 210 differentially expressed genes (DEGs) between CML and normal samples. These DEGs are mainly enriched in immune-related pathways such as Th1 and Th2 cell differentiation, primary immunodeficiency, T cell receptor signaling pathway, antigen processing and presentation pathways. Based on these DEGs, we identified two molecular subtypes using a consensus clustering algorithm. Cluster A was an immunosuppressive phenotype with reduced immune cell infiltration and significant activation of metabolism-related pathways such as reactive oxygen species, glycolysis and mTORC1; Cluster B was an immune activating phenotype with increased infiltration of CD4 + and CD8 + T cells and NK cells, and increased activation of signaling pathways such as interferon gamma (IFN-γ) response, IL6-JAK-STAT3 and inflammatory response. Drug prediction results showed that patients in Cluster B had a higher therapeutic response to anti-PD-1 and anti-CTLA4 and were more sensitive to imatinib, nilotinib and dasatinib. Support Vector Machine Recursive Feature Elimination (SVM-RFE), Least Absolute Shrinkage Selection Operator (LASSO) and Random Forest (RF) algorithms identified 4 CML diagnostic genes (HDC, SMPDL3A, IRF4 and AQP3), and the risk score model constructed by these genes improved the diagnostic accuracy. We further validated the diagnostic value of the 4 genes and the risk score model in a clinical cohort, and the risk score can be used in the differential diagnosis of CML and other hematological malignancies. The risk score can also be used to identify molecular subtypes and predict response to imatinib treatment. These results reveal the characteristics of immunosuppression and metabolic reprogramming in CML patients, and the identification of molecular subtypes and biomarkers provides new ideas and insights for the clinical diagnosis and treatment.

Splicing factor-mediated regulation patterns reveals biological characteristics and aid in predicting prognosis in acute myeloid leukemia.

BACKGROUND: Alternative splicing (AS) of RNA is a fundamental biological process that shapes protein diversity. Many non-characteristic AS events are involved in the onset and development of acute myeloid leukemia (AML). Abnormal alterations in splicing factors (SFs), which regulate the onset of AS events, affect the process of splicing regulation. Hence, it is important to explore the relationship between SFs and the clinical features and biological processes of patients with AML. METHODS: This study focused on SFs of the classical heterogeneous nuclear ribonucleoprotein (hnRNP) family and arginine and serine/arginine-rich (SR) splicing factor family. We explored the relationship between the regulation patterns associated with the expression of SFs and clinicopathological factors and biological behaviors of AML based on a multi-omics approach. The biological functions of SRSF10 in AML were further analyzed using clinical samples and in vitro experiments. RESULTS: Most SFs were upregulated in AML samples and were associated with poor prognosis. The four splicing regulation patterns were characterized by differences in immune function, tumor mutation, signaling pathway activity, prognosis, and predicted response to chemotherapy and immunotherapy. A risk score model was constructed and validated as an independent prognostic factor for AML. Overall survival was significantly shorter in the high-risk score group. In addition, we confirmed that SRSF10 expression was significantly up-regulated in clinical samples of AML, and knockdown of SRSF10 inhibited the proliferation of AML cells and promoted apoptosis and G1 phase arrest during the cell cycle. CONCLUSION: The analysis of splicing regulation patterns can help us better understand the differences in the tumor microenvironment of patients with AML and guide clinical decision-making and prognosis prediction. SRSF10 can be a potential therapeutic target and biomarker for AML.

Ferroptosis-related molecular patterns reveal immune escape, inflammatory development and lipid metabolism characteristics of the tumor microenvironment in acute myeloid leukemia.

Background: An increasing number of studies have revealed the influencing factors of ferroptosis. The influence of immune cell infiltration, inflammation development and lipid metabolism in the tumor microenvironment (TME) on the ferroptosis of tumor cells requires further research and discussion. Methods: We explored the relationship between ferroptosis-related genes and acute myeloid leukemia (AML) from the perspective of large sample analysis and multiomics, used multiple groups to identify and verify ferroptosis-related molecular patterns, and analyzed the sensitivity to ferroptosis and the state of immune escape between different molecular pattern groups. The single-sample gene set enrichment analysis (ssGSEA) algorithm was used to quantify the phenotypes of ferroptosis-related molecular patterns in individual patients. HL-60 and THP-1 cells were treated with ferroptosis inducer RSL3 to verify the therapeutic value of targeted inhibition of GPX4. Results: Three ferroptosis-related molecular patterns and progressively worsening phenotypes including immune activation, immune exclusion and immunosuppression were found with the two different sequencing approaches. The FSscore we constructed can quantify the development of ferroptosis-related phenotypes in individual patients. The higher the FSscore is, the worse the patient's prognosis. The FSscore is also highly positively correlated with pathological conditions such as inflammation development, immune escape, lipid metabolism, immunotherapy resistance, and chemotherapy resistance and is negatively correlated with tumor mutation burden. Moreover, RSL3 can induce ferroptosis of AML cells by reducing the protein level of GPX4. Conclusions: This study revealed the characteristics of immunity, inflammation, and lipid metabolism in the TME of different AML patients and differences in the sensitivity of tumor cells to ferroptosis. The FSscore can be used as a biomarker to provide a reference for the clinical evaluation of the pathological characteristics of AML patients and the design of personalized treatment plans. And GPX4 is a potential target for AML treatment.

A novel fatty acid metabolism-related signature identifies features of the tumor microenvironment and predicts clinical outcome in acute myeloid leukemia.

BACKGROUND: Acute myeloid leukemia (AML) is the most common malignancy of the hematological system, and there are currently a number of studies regarding abnormal alterations in energy metabolism, but fewer reports related to fatty acid metabolism (FAM) in AML. We therefore analyze the association of FAM and AML tumor development to explore targets for clinical prognosis prediction and identify those with potential therapeutic value. METHODS: The identification of AML patients with different fatty acid metabolism characteristics was based on a consensus clustering algorithm. The CIBERSORT algorithm was used to calculate the proportion of infiltrating immune cells. We used Cox regression analysis and least absolute shrinkage and selection operator (LASSO) regression analysis to construct a signature for predicting the prognosis of AML patients. The Genomics of Drug Sensitivity in Cancer database was used to predict the sensitivity of patient samples in high- and low-risk score groups to different chemotherapy drugs. RESULTS: The consensus clustering approach identified three molecular subtypes of FAM that exhibited significant differences in genomic features such as immunity, metabolism, and inflammation, as well as patient prognosis. The risk-score model we constructed accurately predicted patient outcomes, with area under the receiver operating characteristic curve values of 0.870, 0.878, and 0.950 at 1, 3, and 5 years, respectively. The validation cohort also confirmed the prognostic evaluation performance of the risk score. In addition, higher risk scores were associated with stronger fatty acid metabolisms, significantly higher expression levels of immune checkpoints, and significantly increased infiltration of immunosuppressive cells. Immune functions, such as inflammation promotion, para-inflammation, and type I/II interferon responses, were also significantly activated. These results demonstrated that immunotherapy targeting immune checkpoints and immunosuppressive cells, such as myeloid-derived suppressor cells (MDSCs) and M2 macrophages, are more suitable for patients with high-risk scores. Finally, the prediction results of chemotherapeutic drugs showed that samples in the high-risk score group had greater treatment sensitivity to four chemotherapy drugs in vitro. CONCLUSIONS: The analysis of the molecular patterns of FAM effectively predicted patient prognosis and revealed various tumor microenvironment (TME) characteristics.

Inflammatory response mediates cross-talk with immune function and reveals clinical features in acute myeloid leukemia.

Accumulated genetic mutations are an important cause for the development of acute myeloid leukemia (AML), but abnormal changes in the inflammatory microenvironment also have regulatory effects on AML. Exploring the relationship between inflammatory response and pathological features of AML has implications for clinical diagnosis, treatment and prognosis evaluation. We analyzed the expression variation landscape of inflammatory response-related genes (IRRGs) and calculated an inflammatory response score for each sample using the gene set variation analysis (GSVA) algorithm. The differences in clinical- and immune-related characteristics between high- and low-inflammatory response groups were further analyzed. We found that most IRRGs were highly expressed in AML samples, and patients with high inflammatory response had poor prognosis and were accompanied with highly activated chemokine-, cytokine- and adhesion molecule-related signaling pathways, higher infiltration ratios of monocytes, neutrophils and M2 macrophages, high activity of type I/II interferon (IFN) response, and higher expression of immune checkpoints. We also used the Genomics of Drug Sensitivity in Cancer (GDSC) database to predict the sensitivity of AML samples with different inflammatory responses to common drugs, and found that AML samples with low inflammatory response were more sensitive to cytarabine, doxorubicin and midostaurin. SubMap algorithm also demonstrated that high-inflammatory response patients are more suitable for anti-PD-1 immunotherapy. Finally, we constructed a prognostic risk score model to predict the overall survival (OS) of AML patients. Patients with higher risk score had significantly shorter OS, which was confirmed in two validation cohorts. The analysis of inflammatory response patterns can help us better understand the differences in tumor microenvironment (TME) of AML patients, and guide clinical medication and prognosis prediction.

m6A-related lncRNAs predict prognosis and indicate immune microenvironment in acute myeloid leukemia.

Acute myeloid leukemia (AML) is a complex hematologic malignancy. Survival rate of AML patients is low. N6-methyladenosine (m6A) and long non-coding RNAs (lncRNAs) play important roles in AML tumorigenesis and progression. However, the relationship between lncRNAs and biological characteristics of AML, as well as how lncRNAs influence the prognosis of AML patients, remain unclear. In this study. In this study, Pearson correlation analysis was used to identify lncRNAs related to m6A regulatory genes, namely m6A-related lncRNAs. And we analyzed their roles and prognostic values in AML. m6A-related lncRNAs associated with patient prognosis were screened using univariate Cox regression analysis, followed by systematic analysis of the relationship between these genes and AML clinicopathologic and biologic characteristics. Furthermore, we examined the characteristics of tumor immune microenvironment (TIME) using different IncRNA clustering models. Using LASSO regression, we identified the risk signals related to prognosis of AML patients. We then constructed and verified a risk model based on m6A-related lncRNAs for independent prediction of overall survival in AML patients. Our results indicate that risk scores, calculated based on risk-related signaling, were related to the clinicopathologic characteristics of AML and level of immune infiltration. Finally, we examined the expression level of TRAF3IP2-AS1 in patient samples through real-time polymerase chain reaction analysis and in GEO datasets, and we identified a interaction relationship between SRSF10 and TRAF3IP2-AS1 through in vitro assays. Our study shows that m6A-related lncRNAs, evaluated using the risk prediction model, can potentially be used to predict prognosis and design immunotherapy in AML patients.

m(6)A Modification of lncRNA NEAT1 Regulates Chronic Myelocytic Leukemia Progression via miR-766-5p/CDKN1A Axis.

BACKGROUND: Chronic myeloid leukemia (CML) is an acquired hematopoietic stem malignant disease originating from the myeloid system. Long non-coding RNAs (lncRNAs) have been widely explored in cancer tumorigenesis. However, their roles in CML remain largely unclear. METHODS: The peripheral blood mononuclear cells (PBMCs) and CML cell lines (K562, KCL22, MEG01, BV173) were collected for in vitro research. Real-time quantitative polymerase chain reaction was used to determine the mRNA expression levels. Cell viability and apoptosis were analyzed by cell counting kit 8 and flow cytometry assays. The targeting relationships were predicted using Starbase and TargetScan and ulteriorly verified by RNA pull-down and luciferase reporter assays. Western blotting assay was performed to assess the protein expressions. N6-methyladenosine (m6A) modification sites were predicted by SRAMP and confirmed by Methylated RNA immunoprecipitation (MeRIP) assay. RESULTS: LncRNA nuclear-enriched abundant transcript 1 (NEAT1) expression levels were decreased in the CML cell lines and PBMCs of CML patients. Moreover, METTL3-mediated m6A modification induced the aberrant expression of NEAT1 in CML. Overexpression of NEAT1 inhibited cell viability and promoted the apoptosis of CML cells. Additionally, miR-766-5p was upregulated in CML PBMCs and abrogated the effects of NEAT1 on cell viability and apoptosis of the CML cells. Further, CDKN1A was proved to be the target gene of miR-766-5p and was downregulated in the CML PBMCs. Knockdown of CDKN1A reversed the effects of NEAT1. CONCLUSION: The current research elucidates a novel METTL3/NEAT1/miR-766-5p/CDKN1A axis which plays a critical role in the progression of CML.

Role of TRPM7 in cardiac fibrosis: A potential therapeutic target (Review).

Cardiac fibrosis is a hallmark of cardiac remodeling associated with nearly all forms of heart disease. Clinically, no effective therapeutic drugs aim to inhibit cardiac fibrosis, owing to the complex etiological heterogeneity and pathogenesis of this disease. A two-in-one protein structure, a ubiquitous expression profile and unique biophysical characteristics enable the involvement of transient receptor potential melastatin-subfamily member 7 (TRPM7) in the pathogenesis and development of fibrosis-related cardiac diseases, such as heart failure (HF), cardiomyopathies, arrhythmia and hyperaldosteronism. In response to a variety of stimuli, multiple bioactive molecules can activate TRPM7 and related signaling pathways, leading to fibroblast proliferation, differentiation and extracellular matrix production in cardiac fibroblasts. TRPM7-mediated Ca2+ signaling and TGF-ß1 signaling pathways are critical for the formation of fibrosis. Accumulating evidence has demonstrated that TRPM7 is a potential pharmacological target for halting the development of fibrotic cardiac diseases. Reliable drug-like molecules for further development of high-affinity in vivo drugs targeting TRPM7 are urgently needed. The present review discusses the widespread and significant role of TRPM7 in cardiac fibrosis and focuses on its potential as a therapeutic target for alleviating heart fibrogenesis.

Quantitative Proteomic Analysis of Plasma Exosomes to Identify the Candidate Biomarker of Imatinib Resistance in Chronic Myeloid Leukemia Patients.

BACKGROUND: Imatinib (IM), a tyrosine kinase inhibitor (TKI), has markedly improved the survival and life quality of chronic myeloid leukemia (CML) patients. However, the lack of specific biomarkers for IM resistance remains a serious clinical challenge. Recently, growing evidence has suggested that exosome-harbored proteins were involved in tumor drug resistance and could be novel biomarkers for the diagnosis and drug sensitivity prediction of cancer. Therefore, we aimed to investigate the proteomic profile of plasma exosomes derived from CML patients to identify ideal biomarkers for IM resistance. METHODS: We extracted exosomes from pooled plasma samples of 9 imatinib-resistant CML patients and 9 imatinib-sensitive CML patients by ultracentrifugation. Then, we identified the expression levels of exosomal proteins by liquid chromatography-tandem mass spectrometry (LC-MS/MS) based label free quantification. Bioinformatics analyses were used to analyze the proteomic data. Finally, the western blot (WB) and parallel reaction monitoring (PRM) analyses were applied to validate the candidate proteins. RESULTS: A total of 2812 proteins were identified in plasma exosomes from imatinib-resistant and imatinib-sensitive CML patients, including 279 differentially expressed proteins (DEPs) with restricted criteria (fold change≥1.5 or ≤0.667, p<0.05). Compared with imatinib-sensitive CML patients, 151 proteins were up-regulated and 128 proteins were down-regulated. Bioinformatics analyses revealed that the main function of the upregulated proteins was regulation of protein synthesis, while the downregulated proteins were mainly involved in lipid metabolism. The top 20 hub genes were obtained using STRING and Cytoscape, most of which were components of ribosomes. Moreover, we found that RPL13 and RPL14 exhibited exceptional upregulation in imatinib-resistant CML patients, which were further confirmed by PRM and WB. CONCLUSION: Proteomic analysis of plasma exosomes provides new ideas and important information for the study of IM resistance in CML. Especially the exosomal proteins (RPL13 and RPL14), which may have great potential as biomarkers of IM resistance.

Cetuximab enhances the efficiency of irinotecan through simultaneously inhibiting the MAPK signaling and ABCG2 in colorectal cancer cells.

BACKGROUND: The present study sought to investigate the combined effects of cetuximab and irinotecan on colorectal cancer cells as well as the mechanisms underlying their anti-cancer effects. MATERIAL AND METHODS: High performance liquid chromatography, Hoechst staining assay, and western blotting analysis were used to detect intracellular drug concentrations, cell apoptosis, and protein expression in the presence of cetuximab, irinotecan, and the combination of both. RESULTS: Cetuximab was found to increase intracellular concentrations of irinotecan as well as cytotoxicity by inhibiting the epidermal growth factor receptor and, by extension, the downstream RAS-RAF-MEK-ERK signaling pathway. Cetuximab therefore induced apoptosis and improved the effect of irinotecan in colorectal cancer cells. It was also shown that cetuximab inhibited the drug efflux activity of ABCG2. In combination with irinotecan, cetuximab can both significantly induce cell apoptosis by inhibiting the RAS-RAF-MEK-ERK signaling pathway and improve the effects of irinotecan by decreasing drug efflux through the inhibition of ABCG2. CONCLUSION: These features contribute to its anti-cancer potential.

Catalytic pyrolysis of biomass wastes over Org-CaO/Nano-ZSM-5 to produce aromatics: Influence of catalyst properties.

Catalytic pyrolysis of biomass wastes is a promising way to produce aromatics. Based on the conventional CaO/ZSM-5 system, this study aims to improve the aromatics yields by developing an upgraded system which combined nanosized ZSM-5 with CaO from organic calcium precursors (Org-CaO/NZSM-5). The results showed that the aromatics proportion in bio-oil from pyrolysis of Jatropha de-oiled cake with Org-CaO/NZSM-5 increased to 93%. The corresponding yield of BTX (benzene, toluene and xylene) and naphthalene was around 70% which was almost twice than that with conventional CaO/ZSM-5. Org-CaO showed better thermal cracking ability and deoxygenation with more hydrocarbons intermediates and higher H/Ceff of vapors, contributing to enhanced formation of BTX over NZSM-5. NZSM-5 contained much more mesopores and acid sites on external surface, promoting higher conversion of bulky molecules into naphthalenes. Compared with peanut shell, corncob and bagasse pyrolysis, Jatropha de-oiled cake pyrolysis produced much higher aromatics with Org-CaO/NZSM-5.

H19 contributes to poor clinical features in NSCLC patients and leads to enhanced invasion in A549 cells through regulating miRNA-203-mediated epithelial-mesenchymal transition.

Recent studies have demonstrated that the overexpression of H19 may contribute towards development of tumorigenesis in various types of cancer. To investigate the role of H19 in the development of non-small cell lung cancer (NSCLC), 76 NSCLC tissues samples and their adjacent normal tissue samples were collected. Expression level of H19, and its association with clinicopathological features and overall survival was analyzed. It was found that compared with normal adjacent tissues, H19 expression was elevated in NSCLC tissues along with a decreased miR-203 expression level. It was also found that patients who were in advanced clinical stages had a higher H19 and a lower miR-203 expression compared to normal tissues. The overall survival time of patients with higher H19 expression was shorter compared with the lower H19 expression group. Upregulation of A549 enhanced cell proliferation and promoted invasion. Overexpression of H19 stimulated the epithelial-mesenchymal transition (EMT) process in lung cancer cells and demonstrated typical morphological characteristics of EMT. The level of mesenchymal marker protein, such as Vimentin and SNAI1 increased; while CDH1 protein level decreased. Also, H19 negatively regulated miR-203. Inhibition of H19 attenuated miR-203 induced EMT process. Upregulation of H19 contributes to poor clinical features in patients with NSCLC, induces occurrence of EMT, promotes proliferation and stimulates cell invasion in NSCLC cell line through regulating miRNA-203 mediated EMT.

[Correlation between the genetic polymorphisms of apolipoprotein M with the susceptibility to rheumatic diseases of Chinese Han populastion in Lanzhou].

Objective To investigate the relationship between the genetic polymorphisms of apolipoprotein M (ApoM) and the susceptibility to rheumatoid arthritis (RA), systemic lupus erythematosus (SLE) and ankylosing spondylitis (AS) among Chinese Han population in Lanzhou. Methods Primers for the two single nucleotide polymorphism (SNP) sites (rs805296 and rs805297) in ApoM gene were designed and their genotyping methods of polymerase chain reaction-high resolution melting (PCR-HRM) assay were established. Case-control studies were performed among the 599 cases of RA, 194 cases of SLE, 179 cases of AS and 273 matched healthy controls to analyze the correlations between the two SNPs and the susceptibility to rheumatic diseases. Results The genotype frequencies of rs805296 were AA 87.0%, AG 12.7%, GG 0.3% in RA cases, AA 84.5%, AG 15.0%, GG 0.5% in SLE cases, AA 91.6%, AG 7.3%, GG 1.1% in AS cases, AA 85.0%, AG 15.0%, GG 0% in healthy controls. The ones of rs805297 were GG 38.2%, GT 51.8%, TT 10.0% in RA cases, GG 44.3%, GT 45.4%, TT 10.3% in SLE cases, GG 37.4%, GT 47.5%, TT 15.1% in AS cases, GG 40.7%, GT 46.1%, TT 13.2% in healthy controls. Statistical analyses showed that only the genotype distribution of rs805296 was significantly different between the AS cases and the healthy controls. Under the dominant model, the G allele carriers of rs805296 (AG heterozygote and GG homozygote) were found to significantly decrease the risk for AS development. Conclusion The established PCR-HRM genotyping assays in the present study can successfully achieve the molecular diagnosis of the two SNPs sites (rs805296 and rs805297) from clinical samples, and the study found a significant association between the SNP of rs805296 and the susceptibility to AS among Chinese Han population in Lanzhou.