Liver cancer treatment with cisplatin is often hindered by drug resistance. This study aimed to identify key genes associated with cisplatin resistance in liver cancer and develop targeted inhibitors. Using genome-wide CRISPR-Cas9 screening, ATOX1 was identified as a critical gene for cisplatin resistance. ATOX1 was highly expressed in liver cancer tissues and associated with poor prognosis. Knockdown of ATOX1 in liver cancer cells enhanced cisplatin sensitivity in vitro and in vivo. Molecular dynamics simulation and virtual screening identified compound 8 as a potent ATOX1 inhibitor with high affinity (Kd = 12.5 μM) and exhibited synergistic effects with cisplatin on liver cancer cell growth. Mechanistically, compound 8 inhibits the activity of ATOX1, leading to intracellular copper accumulation. The elevated copper levels subsequently promote increased DNA methylation at the NOTCH1 promoter, resulting in suppression of the NOTCH1/HES1 signaling pathway and enhancing the sensitivity of liver cancer cells to cisplatin. In conclusion, ATOX1 is crucial for cisplatin resistance in liver cancer and linked to poor prognosis. Targeting ATOX1 with compound 8 may be a novel therapeutic strategy for overcoming cisplatin resistance.

The classical sequential workflow-individual compound screening, followed by stepwise design-synthesis-purification of derivatives-makes lead compound discovery time-consuming and cost-prohibitive. Herein, we developed Affinity Selection Thin-Layer Chromatography (AS-TLC) as a method for high-throughput screening (HTS), enabling efficient and cost-effective screening of compound mixtures. Furthermore, we integrated activity assays with AS-TLC to minimize target protein consumption and lower the false positive rate, through which we identified a YTH domain-containing protein 1 (YTHDC1) inhibitor, fragment YD, with a half-maximal inhibitory concentration (IC50) of 20.01 ± 3.30 µm. Building on this hit, we applied copper(I)-catalyzed azide-alkyne cycloaddition (CuAAC) click chemistry for rapid structural modification and compound library construction, ultimately obtaining LC-YD03 with significantly enhanced inhibitory activity (IC50 = 41.98 ± 6.24 nm). The interaction mode between LC-YD03 and YTHDC1 was further clarified via X-ray crystallographic analysis. This study demonstrates that the AS-TLC-activity assay platform enables efficient hit screening from compound mixtures; subsequent click chemistry-based combinatorial library technology accelerates lead compound optimization. Collectively, this workflow significantly reduces the time and cost associated with lead compound discovery.

Non-small-cell lung cancer (NSCLC) is one of the most prevalent cancer types and accounts for the majority of cancer-related deaths worldwide. Tanshinone and its derivatives exhibit diverse biological activities, and their prominent antitumor potential has been well documented. In this study, we rationally designed a series of tanshinone derivatives with a scaffold-hopping strategy. Thirty-five tanshinone derivatives were synthesized, and their cytotoxic activities against the NSCLC cell lines A549 and H838 were investigated. Concurrently, their safety profile was assessed in BEAS-2B cells. The results showed that compounds S2-1, S2-4, and S2-8 exhibited superior inhibitory activity against A549 cells compared with the positive control, β-lapachone. Meanwhile, compounds S2-1, S2-3, S2-4, S2-8, S2-13, and S2-14 exhibited similar or increased antiproliferation activity against H838 cells. Compounds S2-4 (0.58 ± 0.07 μM) and S2-8 (0.42 ± 0.04 μM) demonstrated the greatest potency towards H838 cells; compounds S2-13 (1.28 ± 0.13 μM) and S2-14 (1.80 ± 0.24 μM) exhibited potent and selective activity towards H838 cells. Molecular docking studies of S2-4/NLRP3 and S2-14/STAT3, combined with the structure–activity relationship (SAR) analysis, indicated that the benzofuran core containing an ortho-quinone, along with an amide linkage and a 1,2,3-triazole group introduced at the C-2 position of the furan ring, is an effective chemical scaffold for enhancing the anti-NSCLC activity of tanshinone derivatives.

The overexpression of the transcriptional enhanced associate domain (TEAD), which regulates gene transcription linked to cell growth, drives the proliferation in cases of hepatocellular carcinoma (HCC). In order to discover novel TEAD inhibitors that are more effective and have better efficacy and pharmacokinetic properties for treating HCC, this study employed a cyclization strategy to generate a novel indole-based scaffold of TEAD inhibitors. A comprehensive and systematic structure-activity relationship (SAR) analysis identified the most promising compound: LC-TD-05, a non-covalent, partial TEAD inhibitor with selective activity against TEAD1, TEAD2 and TEAD4, but reduced potency against TEAD3. LC-TD-05 exhibits good potency against TEAD1/2/4 (TEAD1 IC50 = 116.6 ± 21.7 nM, TEAD2 IC50 = 168.7 ± 17.1 nM, TEAD4 IC50 = 68.3 ± 18.2 nM), demonstrates favorable oral bioavailability (F = 53.7%), and exhibits significant anti-tumor activity in HCC LM3 models in vitro (LM3 cell IC50 = 248 ± 27.9 nM) and in vivo (TGI = 75%). Overall, this study provides a novel scaffold for TEAD inhibitors, enabling more effective interventions against HCC.

Hepatocellular carcinoma (HCC) is the common malignancy in digestive system, characterized by glucose metabolic reprogramming, which supplies the necessary nutrients and energy to sustain significantly increased cell proliferation and metastasis. However, the underlying mechanistic connections between glycolysis and HCC cells have not been comprehensively elucidated. Herein, through whole-gene CRISPR library screen, Calpain S1 (CAPNS1) was considered a key gene that significantly promotes cell proliferation under conditions where cells rely solely on glycolytic metabolism. Higher CAPNS1 levels were found in HCC tissues, correlating with increased glycolysis level, advanced tumor stage, and shorter survival days. CAPNS1 overexpression enhanced glycolysis, proliferation, and metastasis of HCC cells, whereas CAPNS1 knockdown produced inverse effects. CAPNS1 interacted with calpain 2 to form heterodimers, bound to Dicer, and cleaved Dicer at the arginine 1910 site, thereby suppressing the maturation of various microRNAs, such as miR-200a-3p and miR-122-5p, which targeting enzymes of glycolysis. The lactate produced from glycolysis increased H3K27 acetylation at the promoter region of CAPNS1, thereby enhancing CAPNS1 transcription. Taken together, the CAPNS1/Dicer feedback loop facilitated glycolysis, proliferation, and metastasis in HCC cell by inhibiting the maturation of the microRNA pool. Consequently, CAPNS1 may represent as a remarkable biomarker and therapic target for HCC.

Relapsed/refractory (R/R) acute myeloid leukemia (AML) remains difficult to treat due to limited actionable targets and frequent drug resistance. Integrated analyses of multiple AML cohorts identified S100A9 as a candidate factor associated with disease aggressiveness and suboptimal therapeutic response in R/R AML. We combined genetic perturbation of S100A9 with mitochondrial Ca2+ measurements to define its functional role in AML cells. A structure-guided virtual screening strategy was then used to identify small molecules with direct affinity for S100A9, followed by biochemical validation and anti-leukemic profiling in AML cell lines, primary patient samples, normal hematopoietic cells, and xenograft models. Transcriptomic (RNA-seq) and protein assays were performed to characterize pathway changes induced by the lead compound. S100A9 modulation altered mitochondrial Ca2+ homeostasis and AML cell fitness. We identified B2, a novel S100A9-binding small molecule that reduces S100A9 abundance and is associated with increased mitochondrial Ca2+ accumulation. RNA-seq and immunoblotting demonstrated concomitant attenuation of survival signaling, including reduced STAT5 and AKT activation. B2 preferentially impaired S100A9-high AML cell lines and primary samples with minimal toxicity to normal hematopoietic cells, and significantly reduced leukemia burden in xenograft models. These findings establish S100A9 as a regulator of mitochondrial Ca2+ homeostasis in AML and support B2 as a translational candidate that targets mitochondrial vulnerabilities and downstream survival pathways in R/R AML.

Celecoxib, a selective COX-2 inhibitor, has demonstrated anti-liver cancer effects in various preclinical models and clinical traits. However, prolonged use of celecoxib can lead to drug resistance, necessitating higher doses to maintain efficacy, which often results in severe side effects, limiting its clinical application. This study aimed to identify strategies to overcome celecoxib resistance in liver cancer. CRISPR/Cas9 screening revealed that liver cancer cells compensated for celecoxib treatment by upregulating ALOX and CYP enzymes, facilitating AA metabolism to produce alternative downstream products. STAT6 was identified as a key regulator of ALOX15, ALOX12, and CYP2E1, acting as a resister to celecoxib. Celecoxib stimulation leaded to increased phosphorylation of STAT6, enhanced binding to the promoters of target genes such as ALOX15, and upregulation of downstream gene expression. Knockdown of STAT6 significantly enhanced celecoxib sensitivity in vitro and in vivo by blocking AA shunting mediated by these enzymes. Furthermore, AS1517499, a STAT6 inhibitor, showed strong synergy with celecoxib in liver cancer cells by inhibiting AA shunting. In conclusion, targeting STAT6 enhances the efficacy of celecoxib in liver cancer by suppressing AA shunting. The combination of AS1517499 and celecoxib holds promise as a novel therapeutic strategy for liver cancer.

Angiopoietin 1 (ANGPT1) is a key regulator in the tumor microenvironment (TME), influencing tumor progression, immune modulation, and therapy response. However, a systematic pan-cancer analysis of ANGPT1’s role is lacking. In this study, we performed a comprehensive bioinformatics analysis using datasets from multiple databases to explore ANGPT1’s prognostic significance, its interaction with immune cells in the TME, and its potential as a therapeutic target across various cancers. We examined ANGPT1’s association with tumor prognosis, mutation load, microsatellite instability, immune cell infiltration, immune checkpoint genes, and drug sensitivity. Additionally, we analyzed ANGPT1 expression in acute myeloid leukemia (AML) patients, comparing complete remission (CR) versus no response (NR) groups, and investigated its effect on AML cell proliferation through loss-of-function assays. Our results showed significant heterogeneity in ANGPT1 mRNA expression across 10 of 33 cancer types, with high expression in glioblastoma multiforme and kidney chromophobe, and lower expression in other tumors. High ANGPT1 immunohistochemical scores were significantly associated with poor prognosis in six cancers. Furthermore, ANGPT1 expression correlated with immune-related markers, tumor mutational burden, microsatellite instability, and immune regulation. Drug sensitivity predictions revealed that ANGPT1 expression influenced tumor sensitivity to various drugs. Importantly, ANGPT1 was significantly upregulated in AML patients, with higher levels in the NR group compared to the CR group, and it promoted AML cell proliferation. These findings highlight ANGPT1 as a pivotal regulator in the TME, influencing immune responses and drug sensitivity, making it a potential prognostic biomarker and therapeutic target in cancer immunotherapy.

INTRODUCTION:The incidence of breast cancer has steadily risen over the years owing to changes in lifestyle and environment. Presently, breast cancer is one of the primary causes of cancer-related deaths among women, making it a crucial global public health concern. Thus, the creation of an automated diagnostic system for breast cancer bears great importance in the medical community. OBJECTIVES:This study analyses the Wisconsin breast cancer dataset and develops a machine learning algorithm for accurately classifying breast cancer as benign or malignant. METHODS:Our research is a retrospective study, and the main purpose is to develop a high-precision classification algorithm for benign and malignant breast cancer. To achieve this, we first preprocessed the dataset using standard techniques such as feature scaling and handling missing values. We assessed the normality of the data distribution initially, after which we opted for Spearman correlation analysis to examine the relationship between the feature subset data and the labeled data, considering the normality test results. We subsequently employed the Wilcoxon rank sum test to investigate the dissimilarities in distribution among various breast cancer feature data. We constructed the feature subset based on statistical results and trained 7 machine learning algorithms, specifically the decision tree, stochastic gradient descent algorithm, random forest algorithm, support vector machine algorithm, logistics algorithm, and AdaBoost algorithm. RESULTS:The results of the evaluation indicated that the AdaBoost-Logistic algorithm achieved an accuracy of 99.12%, outperforming the other 6 algorithms and previous techniques. CONCLUSION:The constructed AdaBoost-Logistic algorithm exhibits significant precision with the Wisconsin breast cancer dataset, achieving commendable classification performance for both benign and malignant breast cancer cases.

The telomerase reverse transcriptase promoter (TERTp) is frequently mutated in gliomas. This study sought to identify immune biomarkers of gliomas with TERTp mutations. Data from TCGA were used to identify and validate survival-associated gene signatures, and immune and stromal scores were calculated using the ESTIMATE algorithm. High stromal or immune scores in patients with TERTp-mutant gliomas correlated with shorter overall survival compared to cases with low stromal or immune scores. Among TERTp-mutant gliomas with both high immune and high stromal scores, 213 commonly shared DEGs were identified. Among 71 interacting DEGs representing candidate hub genes in a PPI network, HOXC6, WT1, CD70, and OTP showed significant ability in establishing subgroups of high- and low-risk patients. A risk model based on these 4 genes showed strong prognostic potential for gliomas with mutated TERTp, but was inapplicable for TERTp-wild-type gliomas. TERTp-mutant gliomas with high-risk scores displayed a greater percentage of naïve B cells, plasma cells, naïve CD4 T cells, and activated mast cells than low-risk score gliomas. TIDE analysis indicated that immune checkpoint blockade (ICB) therapy may benefit glioma patients with TERTp mutations. The present risk model can help predict prognosis of glioma patients with TERTp mutations and aid ICB treatment options.

Background: The heterogeneity of prognosis and treatment benefits among patients with gliomas is due to tumor microenvironment characteristics.However, biomarkers that reflect microenvironmental characteristics and predict the prognosis of gliomas are limited.Therefore, we aimed to develop a model that can effectively predict prognosis, differentiate microenvironment signatures, and optimize drug selection for patients with glioma.Materials and Methods: The CIBERSORT algorithm, bulk sequencing analysis, and single-cell RNA (scRNA) analysis were employed to identify significant cross-talk genes between M2 macrophages and cancer cells in glioma tissues.A predictive model was constructed based on cross-talk gene expression, and its effect on prognosis, recurrence prediction, and microenvironment characteristics was validated in multiple cohorts.The effect of the predictive model on drug selection was evaluated using the OncoPredict algorithm and relevant cellular biology experiments.Results:A high abundance of M2 macrophages in glioma tissues indicates poor prognosis, and cross-talk between macrophages and cancer cells plays a crucial role in shaping the tumor microenvironment.Eight genes involved in the cross-talk between macrophages and cancer cells were identified.Among them, periostin (POSTN), chitinase 3 like 1 (CHI3L1), serum amyloid A1 (SAA1), and matrix metallopeptidase 9 (MMP9) were selected to construct a predictive model.The developed model demonstrated significant efficacy in distinguishing patient prognosis, recurrent cases, and characteristics of high inflammation, hypoxia, and immunosuppression.Furthermore, this model can serve as a valuable tool for guiding the use of trametinib.Conclusions: In summary, this study provides a comprehensive understanding of the interplay between M2 macrophages and cancer cells in glioma; utilizes a crosstalk gene signature to develop a predictive model that can predict the differentiation of patient prognosis, recurrence instances, and microenvironment characteristics; and aids in optimizing the application of trametinib in glioma patients.

Aberrant activation or mutation of the EGFR-PI3K-Akt-mTOR signaling pathway has been implicated in a wide range of human cancers, especially non-small-cell lung cancer (NSCLC). Thus, dual inhibition of EGFR and PI3K has been investigated as a promising strategy to address acquired drug resistance resulting from the use of tyrosine kinase inhibitors. A series of dual EGFR/PI3K alpha inhibitors was synthesized using pharmacophore hybridization of the third-generation EGFR inhibitor olmutinib and the PI3K alpha selective inhibitor TAK-117. The optimal compound 30k showed potent kinase inhibitory activities with IC50 values of 3.6 and 30.0 nM against EGFRL858R/T790M and PI3K alpha, respectively. Compound 30k exhibited a significant antiproliferative effect in NCIH1975 cells with a higher selectivity profile than olmutinib. The potential antitumor mechanism, molecular binding modes, and in vitro metabolic stability of compound 30k were also clarified.

The PD-1/PD-L1 pathway is considered as one of the most promising immune checkpoints in tumour immunotherapy. However, researchers are faced with the inherent limitations of antibodies, driving them to pursue PD-L1 small molecule inhibitors. Virtual screening followed by experimental validation is a proven approach to discover active compounds. In this study, we employed multistage virtual screening methods to screen multiple compound databases to predict new PD-1/PD-L1 ligands. 35 compounds were proposed by combined analysis of fitness scores, interaction pattern and MM-GBSA binding affinities. Enzymatic assay confirmed that 10 out of 35 ligands were potential PD-L1 inhibitors, with inhibitory rate higher than 50% at the concentration of 30 mu M. Among them, ZDS20 was identified as the most effective inhibitor with low micromolar activity (IC50 = 3.27 mu M). Altogether, ZDS20 carrying novel scaffold was identified and could serve as a lead for the development of new classes of PD-L1 inhibitors.

Rationale: Primordial follicles are limited in number and cannot be regenerated, dormant primordial follicles cannot be reversed once they enter a growth state. Therefore, the length of the female reproductive lifespan depends on the orderly progression and selective activation of primordial follicles, the mechanism of which remains unclear. Methods: We used human ovarian cortical biopsy specimens, granulosa cells from diminished ovarian reserve (DOR) patients, Hdac6-overexpressing transgenic mouse model, and RNA sequencing to analyze the crucial roles of histone deacetylase 6 (HDAC6) in fertility preservation and primordial follicle activation. Results: In the present study, we found that HDAC6 was highly expressed in most dormant primordial follicles. The HDAC6 expression was reduced accompanying reproductive senescence in human and mouse ovaries. Overexpression of Hdac6 delayed the rate of primordial follicle activation, thereby prolonging the mouse reproductive lifespan. Short-term inhibition of HDAC6 promoted primordial follicle activation and follicular development in humans and mice. Mechanism studies revealed that HDAC6 directly interacted with NGF, reducing acetylation modification of NGF and thereby accelerating its ubiquitination degradation. Consequently, the reduced NGF protein level maintained the dormancy of primordial follicles. Conclusions: The physiological significance of the high expression of HDAC6 in most primordial follicles is to reduce NGF expression and prevent primordial follicle activation to maintain female fertility. Reduced HDAC6 expression increases NGF expression in primordial follicles, activating their development and contributing to reproduction. Our study provides a clinical reference value for fertility preservation.

Peroxisome proliferator-activated receptor gamma (PPARG), a key transcription factor involved in lipid metabolism and glucose homeostasis, has been implicated in various types of cancer. However, its precise role in cancer remains unclear. In this study, we conducted a comprehensive pan-cancer analysis of PPARG expression using various types of cancer obtained from public databases. We observed significant heterogeneity in PPARG expression across different types of cancer. The association between PPARG expression and patient prognosis was investigated using Cox proportional hazards regression models and survival analysis. Clinical features and protein expression levels in the cohort showed that PPARG expression was strongly associated, suggesting its potential as a therapeutic target. We also evaluated the prognostic potential of PPARG by analyzing immune infiltration and genomic stability. We experimentally validated the potential of PPARG as a therapeutic target by analyzing drug sensitivity profiles, molecular docking simulations, and in vitro cell proliferation assays associated with PPARG expression. We identified common expression patterns of PPARG with other genes involved in key carcinogenic pathways. This provides deeper insights into the molecular mechanisms underlying its carcinogenic role. Additionally, functional enrichment analysis revealed significant enrichment of genes related to drug metabolism, cell proliferation, and immune response pathways associated with PPARG. Our findings highlight the importance of PPARG in the broader biology of cancer and suggest its potential as a diagnostic and therapeutic target for specific types of cancer. The results of our study provide strong support for the potential role of PPARG as a promising prognostic biomarker and immunotherapeutic target across various types of cancer.

As companies continue to generate merchandise sales, the data is important for their marketing planning, market analysis, and logistics planning, so it is important to accurately predict merchandise sales. This paper combines a recently proposed attention mechanism multiple time series regression model, the CNN-BiLSTM-Attention model, to predict product sales for the next three months. The model can fix the overfitting problem, and can accurately predict the sales volume of products with high accuracy.

Periodic pandemics of coronavirus (CoV)-related pneumonia have been a major challenging issue since the outbreak of severe acute respiratory syndrome (SARS) in 2002 and Middle East respiratory syndrome (MERS) in 2012. The ongoing pandemic of CoV disease (COVID-19) poses a substantial threat to public health. As for the treatment options, only limited antiviral agents have been approved hitherto, and clinicians mainly focus on currently available drugs including the conventional antiviral interferons (IFNs). In clinical practice, IFNs, when used either alone or in combination with ribavirin and/or lopinavir/ritonavir, have shown promising outcomes, to some extent, in SARS-CoV or MERS-CoV treatment. Although the efficacy and safety of IFNs in COVID-19 treatment remain unclear, their possible use merits further evaluation. We present a review that summarizes current evidence of IFN treatment for COVID-19 and elaborates on other challenges in terms of the timing of IFN treatment initiation, treatment duration, and IFN type to be used. The review findings suggested that IFN acts by directly inhibiting viral replication and activating immune cell subsets. However, there is a lack of well-designed and controlled clinical trials providing firm evidence for the efficacy or safety of IFN therapy for CoVs. Additionally, critically ill patients with multiple immunosuppression-associated comorbidities may not benefit from IFN therapy, necessitating screening of those patients who would most benefit from IFN treatment.

Long noncoding RNAs (lncRNAs) are a novel class of noncoding RNAs that have emerged as critical regulators and biomarkers in various cancers. Nevertheless, the expression profile and mechanistic function of lncRNAs in cholangiocarcinoma (CCA) remain unclear. Herein, we examined the expression levels of linc00976 in clinical specimens and cell lines using reverse transcription-quantitative PCR. In total, 50 patients with CCA were enrolled to analyze the correlation between linc00976 expression and clinical characteristics of CCA. Loss- and gain-of-function experiments were performed to investigate the biological effects of linc00976 on proliferation, ferroptosis, migration, and invasion of CCA cells in vitro and in vivo. In situ hybridization, RNA immunoprecipitation, bioinformatic databases, RNA pull-down assay, a dual-luciferase reporter assay, mRNA sequencing, chromatin immunoprecipitation-PCR, and rescue experiments were performed to elucidate the underlying mechanisms of linc00976-induced competitive endogenous RNA regulatory networks. We characterized a novel and abundant lncRNA, linc00976, that functions as a pro-oncogenic regulator of CCA progression. Compared with normal controls, linc00976 was dramatically upregulated in CCA tissue samples and cell lines. Patients with CCA exhibiting high linc00976 expression had a highly advanced clinical stage, substantial lymph node metastasis, and poor overall survival. Knockdown of linc00976 significantly repressed proliferation and metastasis and promoted ferroptosis of CCA cells both in vitro and in vivo, whereas linc00976 overexpression exerted the opposite effect. Mechanistically, linc00976 competitively interacted with miR-3202 to upregulate GPX4 expression, thus contributing to the malignant biological behavior of CCA cells. Moreover, we demonstrated that JUND specifically interacts with the linc00976 promoter and activates linc00976 transcription. Accordingly, JUND promotes linc00976 transcription, and linc00976 plays a crucial role in accelerating CCA tumorigenesis and metastasis and inhibiting ferroptosis by modulating the miR-3202/GPX4 axis. These findings suggest that targeting linc00976 may afford a promising therapeutic strategy for patients with CCA.

The development of inhibitors targeting the PI3K-Akt-mTOR signaling pathway has been greatly hindered by the on-target AEs, such as hyperglycemia and hepatotoxicities. In this study, a series of diaryl urea derivatives has been designed and synthesized based on clinical candidate gedatolisib (6aa), and most of the newly synthesized derivatives showed kinase inhibitory and antiproliferative activities within nanomolar and submicromolar level, respectively. The terminal l-prolineamide substituted derivative 6 ab showed 8.6-fold more potent PI3Kα inhibitory activity (0.7 nM) and 4.6-fold more potent antiproliferative effect against HCT116 cell lines (0.11 μM) compared with control 6aa. The potential antitumor mechanism and efficacy of 6 ab in HCT116 xenograft models have also been evaluated, and found 6 ab showed comparable in vivo antitumor activity with 6aa. The safety investigations revealed that compound 6 ab exhibited more safer profiles in the selectivity of liver cells (selectivity index: >6.6 vs 1.85) and blood glucose regulation than 6aa. In addition, the in vitro stability assays also indicated our developed compound 6 ab possessed good metabolic stabilities.

Drug resistance from BCR - ABL tyrosine kinase inhibitors (TKIs) and other chemotherapeutics results in treatment failure and disease progression in chronic myeloid leukemia (CML). However, the mechanism is still uncertain. In this study, we investigated the role of angiopoietin-1 (ANG-1) as a potential prognostic factor for drug resistance in CML. Both intracellular and secretory ANG-1 (iANG-1 and sANG-1) were overexpressed in multidrug-resistant CML samples. The IC 50 value was higher in primary CD34 + CD38 – cells with more ANG-1. Silencing ANG-1significantly sensitized three TKI-resistant CML cell lines to imatinib (IM) while recombinant human ANG-1 failed to retain cell survival in vitro. This indicated the important role of iANG-1 as opposed to sANG-1 in CML drug resistance. Moreover, a similar effect was observed in xenograft mice models bearing ANG-1-silenced CML cells. Subsequently, pathway analysis and protein validation experiments showed activation of the JAK/STAT pathway and augmentation of STAT5a phosphorylation in ANG-1 restored CML cells. Upstream Src phosphorylation, which plays a crucial role in CML drug resistance, was also upregulated as a key event in iANG-1-related JAK/STAT pathway activation. In conclusion, our study elucidated a new BCR - ABL independent molecular mechanism induced by intracytoplasmic ANG-1 overexpression as a potential strategy for overcoming CML resistance.