The CD47/SIRPα axis conveys a 'don't eat me' signal, thereby thwarting the phagocytic clearance of tumor cells. Although blocking antibodies targeting CD47 have demonstrated promising anti-tumor effects in preclinical models, clinical trials involving human cancer patients have not yielded ideal results. Exploring the regulatory mechanisms of CD47 is imperative for devising more efficacious combinational therapies. Here, we report that inhibiting USP2 prompts CD47 degradation and reshapes the tumor microenvironment (TME), thereby enhancing anti-PD-1 immunotherapy. Mechanistically, USP2 interacts with CD47, stabilizing it through deubiquitination. USP2 inhibition destabilizes CD47, thereby boosting macrophage phagocytosis. Single-cell RNA sequencing shows USP2 inhibition reprograms TME, evidenced by increasing M1 macrophages and CD8+ T cells while reducing M2 macrophages. Combining ML364 with anti-PD-1 reduces tumor burden in mouse models. Clinically, low USP2 expression predicts a better response to anti-PD-1 treatment. Our findings uncover the regulatory mechanism of CD47 by USP2 and targeting this axis boosts anti-tumor immunity.

This study reports a simple and rapid aptamer-based sensor platform designed for the sensitive and selective detection of human non-small cell lung cancer (NSCLC) cells. Under standard conditions, gold nanoparticles (AuNPs) remain dispersed and exhibit a characteristic peak at 520 nm. However, the addition of sodium chloride (NaCl) destabilizes the charge of the solution, leading to the aggregation of AuNPs. The AS1411 aptamer can adsorb onto the surface of AuNPs, effectively preventing their aggregation. In the presence of A549 cells, the AS1411 aptamer is induced to form stable G-tetrads, which allows for specific binding to the cells and results in the aggregation of AuNPs in the NaCl solution. This proposed aptasensor platform demonstrates high specificity for A549 cells when compared to other control human normal cells. The method exhibits a dynamic range of 101 to 106 cells per mL, with a detection limit of 7 cells per mL.

Depletion of Stub1 upregulates JAK1. A, Top: immunoblot analysis assessing levels of the indicated proteins in Myc-CaP cells that received distinct siRNAs or sgRNAs targeting Stub1. Nontargeting siRNA or sgRNA was used as control, respectively. Bottom: immunoblot analysis assessing levels of the indicated proteins in the indicated Myc-CaP cells. OE, overexpression. B, Representative images of multiplex immunofluorescence staining for the indicated proteins in UBA1-high and UBA1-low human tumor samples. CK, pan-cytokeratin. Scale bar, 50 µm. C, Schematic showing that UBA1 upregulation in tumor cells facilitates STUB1-mediated proteasomal degradation of a key IFN sensor, JAK1, resulting in low expression of IFN-stimulated genes and thus an immune-cold tumor microenvironment (left). By contrast, inhibition of UBA1 elevates JAK1 and enhances response to IFNs, contributing to the formation of an immune-hot tumor microenvironment (right).

Although N6-methyladenosine (m6A) is a pervasive RNA modification essential for gene regulation, dissecting the functions of individual m6A sites remains technically challenging. To overcome this, we developed functional m6A sites detection by CRISPR-dCas13b-FTO screening (FOCAS), a CRISPR-dCas13b-based platform enabling high-throughput, site-specific functional screening of m6A. Applying FOCAS to four human cancer cell lines identified 4,475 m6A-regulated genes influencing cell fitness via both mRNAs and non-coding RNAs (ncRNAs), many of which are newly linked to cancer and exhibit dynamic developmental expression. FOCAS uncovered context-dependent and reader-specific effects of m6A within the same gene, revealing its intricate regulatory logic. We further uncovered universal and cell-type-specific m6A patterns, with unique sites enriched in ncRNAs and universal ones in transcription-related genes. In SMMC-7721 cells, we identified m6A-regulated transcriptional networks that demonstrated extensive epitranscriptome-transcriptome crosstalk. Overall, this study established a powerful, unbiased approach for the functional dissection of m6A, advancing the understanding of its complexity and therapeutic relevance in cancers.

Objective To investigate the clinical efficacy and prognosis of cross-line immunotherapy for driver gene-negative advanced non-small cell lung cancer(NSCLC).Methods Clinical data of patients with advanced NSCLC in Zhongnan Hospital of Wuhan University from June 2019 to December 2023 were retrospectively analyzed.For first-line treatment for the patients,programmed cell death receptor-1(PD-1)monoclonal antibody combined with platinum-based doublet chemotherapy was adopted,and for second-line treatment,PD-1 monoclonal antibody combined with chemotherapy was used.The Kaplan-Meier method was employed to draw survival curves,and the Log-rank test was used to evaluate the differences in survival.The Cox proportional hazards regression model was used to analyze the risk factors that affect prognosis and subgroup analyses were conducted to explore the impact on patients'prognosis.Results A total of 112 advanced NSCLC patients with negative driver genes were included.The overall response rate(ORR)of cross-line immunotherapy was 20.54％,and the disease control rate(DCR)of cross-line immunotherapy reached 49.11％.The median overall survival(OS)was 26.6 months.The median progression free survival of first-line treatment(PFS-1)was 7.3 months,and that of second-line treatment(PFS-2)was 5.4 months.The subgroup analysis showed that,compared with patients with PFS-1≤10 months,patients with PFS-1＞10 months had longer median OS[44.3 months vs.13.8 months,P＜0.001]and median PFS-2[10.0 months vs.3.5 months,P＜0.01].Patients with BMI＞25 kg/m2 had longer median PFS-2 than those with BMI≤25 kg/m2[10.0 months vs.4.2 months,P＜0.05].Moreover,in contrast to patients with low expression of PD-L1(＜1％PD-L1 on tumor cells or tissues),patients with high expression of PD-L1 had a longer median PFS-2[6.9 months vs.2.5 months,P＜0.01].In the multivariate Cox proportional hazards regression analysis,compared with patients with PFS-1≤10 months,patients with PFS-1＞10 months had a 52％reduction in the risk of progression[HR=0.48,95％CI(0.27,0.87),P＜0.05].Conclusion The benefits of cross-line immunotherapy might not be remarkable for advanced non-small cell lung cancer with negative driver genes.However,patients with PFS-1＞10 months may have a better prognosis.

UBA1 diminishes intratumoral functional CD8+ T cells. A, Left: UMAP of 8,862 cells and the indicated clusters identified among CD45+ cells enriched from the indicated Myc-CaP tumors subjected to scRNA-seq. Right: heatmap showing differentially expressed genes in each of the indicated clusters among T cells. Three representative genes are shown on the right for each cluster. Proportions of T cells derived from the experimental group (Uba1 overexpression) and control group (empty vector) are shown on the top. B and C, The fraction of each T-cell (B) or immune cell (C) subpopulation among all CD45+ immune cells from the indicated groups. D and E, Flow cytometry measuring the absolute numbers of CD8+ T cells (left) or proportions of IFN-γ+, granzyme B+, or Ki67+ cells among CD8+ T cells (right) in the indicated tumors. Middle: representative images showing the proportional change of IFN-γ+ CD8+ T cells by Uba1 overexpression (D) or Uba1 depletion (E). F, Flow cytometry measuring the absolute numbers of CD8+ T cells or proportions of IFN-γ+, granzyme B+, or Ki67+ cells among CD8+ T cells in the indicated tumors. G, Flow cytometry measuring the absolute numbers of CD4+ T cells, IFN-γ+ CD4+ T cells, or Ki67+ CD4+ T cells in the indicated tumors. All data are presented as box and whisker plots, except in B and C (bar graph). Statistics were acquired by the two-tailed Student t test. Data in D–G are pooled from two independent experiments.

UBA1 promotes tumor growth by mediating immune escape. A, Immunoblot analysis assessing levels of the indicated proteins in the indicated cells transduced with empty vector or Uba1 overexpression (OE). B and C, Volumes (left) and weights (right) of subcutaneous tumors derived from Myc-CaP (B) or B16-BL6 (C) cells established in A, in FVB or C57BL/6 mice, respectively (n = 5 mice per group in B; n = 4 mice per group in C). D and E, Volumes (left) and weights (right) of subcutaneous tumors established with injection of the indicated Myc-CaP (D) or B16-BL6 (E) cells to SCID mice (n = 7 mice per group in D; n = 5 mice per group in E). F, Immunoblot analysis assessing levels of the indicated proteins in the indicated cells transfected with nontargeting sgRNA (control) or independent sgRNAs depleting Uba1 (sgUba1 #1 and sgUba1 #2). Quantification of intensity of UBA1 relative to the control is shown. G, Volumes of subcutaneous tumors derived from Myc-CaP (left) or B16-BL6 (right) cells established in F, in the indicated mice (n = 5–7 mice per group). H, Left: immunoblot analysis assessing Uba1 overexpression (OE) in Uba1-depleted Myc-CaP. Right: volumes of subcutaneous tumors derived from Myc-CaP cells established in Left, in FVB mice (n = 5 mice, per group). I, Volumes of subcutaneous tumors established with injection of control or Uba1-depleted Myc-CaP (left) or B16-BL6 (right) cells to the indicated mice, with or without simultaneous depletion of both CD8+ and CD4+ T cells (n = 4–5, per group). Data are representative of two distinct sgRNAs. All data are presented as mean ± SEM. Statistics were acquired by two-way ANOVA in B (left), C (left), D (left), and E (left), and G–I (n.s., not significant), or by the two-tailed Student’s t test in B (right), C (right), D (right), and E (right). Data in B, C, and G are representative of two independent experiments.

UBA1 inactivation upregulates interferon signaling via stabilization of JAK1. A, Hallmark pathways enriched by bulk RNA-seq of tumors with Uba1 depletion (sgUba1) versus control from the B16-BL6 (left) or Myc-CaP (right) subcutaneous tumor models. B, Hallmark pathways enriched by bulk RNA-seq of tumors with Uba1 overexpression (OE) versus control (empty vector) from the Myc-CaP subcutaneous tumor model (left) or of Myc-CaP subcutaneous tumors in TAK-243–treated vs. control mice (right). C, Left: UMAP of pooled CD45+ and CD45− cells from the indicated Myc-CaP tumors subjected to scRNA-seq. Clusters of malignant cells and leukocytes are shown. Right: hallmark pathways enriched by the scRNA-seq (shown in the left) of tumors with Uba1 depletion (sgUba1) versus control or tumors in TAK-243–treated vs. control mice. TAK-243 was administered via intravenous injection in B (right) and C. D, hallmark pathways enriched by bulk RNA-seq of Myc-CaP cells with Uba1 depletion (sgUba1) vs. control, with or without IFN-γ stimulation, or Myc-CaP cells treated with or without 50 nmol/L TAK-243 for 18 hours, and stimulated with or without IFN-γ. IFN-γ or IFN-α response pathways are highlighted in red in A–D. E, Surface expression of MHC-I measured by flow cytometry in Myc-CaP cells with Uba1 depletion (sgUba1) or UBA1 inhibition by 18 hours of 50 nmol/L TAK-243 treatment, in the presence or absence of IFN-γ stimulation. Nontargeting sgRNA or DMSO were used as controls, respectively. Data were acquired from biological triplicates. F, Surface expression of MHC-I measured by flow cytometry in GFP-labeled Myc-CaP tumor cells that were Uba1 depleted or inactivated (n = 4 mice, per group). G, Mass spectrometry measuring protein abundance in Myc-CaP cells treated with 100 nmol/L TAK-243 for 4 hours and subsequently 50 µg/mL of cycloheximide (CHX) for an additional 6 hours. LFC, Log2 fold change. H, CRISPR knockout screens with sgRNAs targeting genes that were robustly upregulated by TAK-243 in G, in Myc-CaP cells that received TAK-243 and IFN-γ co-treatment (left) or TAK-243 and IFN-β co-treatment (right). I, Immunoblot analysis assessing levels of the indicated proteins in Myc-CaP cells with Uba1 depletion (sgUba1) or 18 hours of 50 nmol/L TAK-243 treatment in the presence of IFN-γ stimulation. Nontargeting sgRNA or DMSO were used as controls, respectively. J, Left: immunoblot analysis assessing JAK1 expression in Myc-CaP cells that received knockout of Jak1 (Jak1 KO). Cells receiving nontargeting sgRNA were used as control. Right: surface expression of MHC-I measured by flow cytometry in the indicated cells treated with or without 50 nmol/L TAK-243 and stimulated with or without IFN-γ. Data were acquired from technical triplicates, representative of two independent experiments. K, Volumes of tumors derived from Myc-CaP cells established as in J, in mice treated with or without the combination (combo) of anti-PD-1 and TAK-243 (n = 5 mice, per group). Data in J and K are representative of two independent experiments with two distinct sgRNAs. IFN-γ stimulation was performed at 1 ng/mL for 18 hours. All immunoblot analysis was representative of two independent experiments. Data are presented as mean ± SEM. Statistics were acquired by the two-tailed Student t test in E, F (TAK-243 vs. DMSO), and J, or by two-way ANOVA in F (sgUba1 vs. control) and K. **, P < 0.01; ***, P < 0.001; n.s., not significant. MFI, mean fluorescent index.

High expression of UBA1 is associated with low levels of intratumoral CD8+ T cells and predictive of ICB resistance and poor survival in ICB cohorts. A, Left: Spearman correlation between mRNA expression of IFNG and 614 frequently gained genes in the indicated mCRPC cohort (n = 208). Genes that are significantly negatively correlated with IFNG mRNA expression are listed. Right: Spearman correlation between mRNA expression of the cytotoxic T-lymphocyte signature (CD8A, CD8B, GZMA, GZMB, and PRF1) and the genes listed on the left. SU2C, Stand Up to Cancer; PCF, Prostate Cancer Foundation. B, Spearman correlation between mRNA expression of UBA1 and the indicated gene or gene signature in the indicated cohort. Eff., effector. C, Spearman correlation between UBA1 copy number and mRNA expression in the indicated prostate cancer cohort. Frequency of copy number gain (gain) is shown. Patients with prostate cancer (male) with two or more copies of UBA1 (on the X chromosome) are defined as gain. MCTP, The Michigan Center for Translational Pathology. D, Proportion of UBA1 gain (left) and Spearman correlation between UBA1 copy number and mRNA levels (right) in the indicated cancer types. Data were acquired from The Cancer Genome Atlas (TCGA). ACC, adrenocortical carcinoma; BLCA, bladder urothelial carcinoma; BRCA, breast invasive carcinoma; COADREAD, colorectal adenocarcinoma; CSCC, cervical squamous cell carcinoma; EAC, esophageal adenocarcinoma; HCC, hepatocellular carcinoma; LUAD, lung adenocarcinoma; LUSC, lung squamous cell carcinoma; OV, ovarian serous cystadenocarcinoma; SARC, sarcoma; STAD, stomach adenocarcinoma; UCS, uterine carcinosarcoma. E, Spearman correlation between pretreatment mRNA expression of UBA1 and the indicated gene or signature, in a cohort treated with ICB at the U-M, Ann Arbor (MI-ONCOSEQ ICB cohort). F, Representative images (left) or quantification (Spearman correlation; right) of immunofluorescence assessing the number of CD8+ T cells and the level of UBA1 in a melanoma tissue microarray (TMA). Scale bar, 50 μm. G, Fisher exact test of a combined analysis on four public RNA-seq datasets [Van Allen and colleagues (34); Zhao and colleagues (35); Miao and colleagues (36); and Jung and colleagues (37)] examining the relationship between pretreatment mRNA expression of UBA1 and response to ICB. H, Uniform Manifold Approximation and Projection (UMAP) of malignant cells from scRNA-seq data in an ICB-treated melanoma cohort. Cells with high levels of pretreatment UBA1 mRNA expression are highlighted in pink. PT#, patient number. I, Overall survival of patients with tumors showing high or low pretreatment: UBA1 mRNA levels in the indicated cohorts. ccRCC, clear-cell renal cell carcinoma. Statistics were acquired by two-tailed Student’s t test in H, and by log-rank test in I.

BACKGROUND:Interleukin-6 (IL-6) monoclonal antibodies are commonly acknowledged for their efficacy in managing coronavirus disease 2019 (COVID-19); however, there remains a paucity of comprehensive studies on their potential adverse effects. RESEARCH DESIGN AND METHODS:This is a retrospective pharmacovigilance investigation. We employed FAERS using OpenVigil FDA to detect adverse reactions linked to the interleukin-6 antagonist tocilizumab and sarilumab. RESULTS:Completely 67,976 reports were identified as 'primary suspected (PS)' adverse events (AEs) for tocilizumab, and 12,560 reports for sarilumab. 109 significant disproportionality preferred terms (PTs) of tocilizumab and 158 PTs of sarilumab were retained. A higher incidence of adverse reactions occurred in females aged 45-64 years, with a higher rate of subsequent hospitalization. Both drugs exhibited adverse reactions consistent with previously reported side effects, such as leukopenia, elevated liver enzymes, and hypercholesterolemia. Additionally, there was a strong correlation with gastrointestinal issues. Unexpected significant adverse events, including diabetes, fluctuations in blood pressure, drug ineffectiveness, malignancies, and disorders of the nervous system, were also observed. Gender and age differences existed in AEs signals related to IL-6RAs. CONCLUSION:Our study identified significant new AE signals for interleukin-6 receptor antagonists, potentially supporting clinical monitoring and risk identification for this class of drugs.

Background Lung adenocarcinoma is the most common type of lung cancer, accounting for approximately 40% of all lung cancer cases, and has the highest incidence among lung cancer subtypes. Recent studies have suggested that long non-coding RNAs (lncRNAs) play a crucial role in the initiation and progression of lung adenocarcinoma.Methods Based on integrative analysis through databases, we screened Long intergenic non-protein coding RNA 00839 (LINC00839) as one of the most highly upregulated lncRNAs in lung adenocarcinoma. In vitro and in vivo experiments demonstrated that LINC00839 promotes lung adenocarcinoma proliferation, migration, and invasion and that it is present in exosomes secreted by lung adenocarcinoma cells.Results In the cytoplasm, LINC00839 regulates the Toll-like receptor 4 (TLR4)/NF-κB signaling pathway by acting as a molecular sponge of miR-17-5p, thereby influencing the biological behavior of lung adenocarcinoma cells. LINC00839 binds to Polypyrimidine tract binding protein 1 (PTBP1) in the nucleus to regulate the nuclear translocation of NF-κB p65 molecules and, consequently, the transcription of downstream molecules.Conclusions Our study confirmed that LINC00839 promotes the biological progression of lung adenocarcinoma by performing dual roles in the cytoplasm and nucleus to co-regulate the NF-κB signaling pathway.

Tumor-derived extracellular vesicles (EVs) are potential biomarkers for tumors, but their reliable molecular targets have not been identified. The previous study confirms that ubiquitin-specific protease 22 (USP22) promotes lung adenocarcinoma (LUAD) metastasis in vivo and in vitro. Moreover, USP22 regulates endocytosis of tumor cells and localizes to late endosomes. However, the role of USP22 in the secretion of tumor cell-derived EVs remains unknown. In this study, it demonstrates that USP22 increases the secretion of tumor cell-derived EVs and accelerates their migration and invasion, invadopodia formation, and angiogenesis via EV transfer. USP22 enhances EV secretion by upregulating myosin IB (MYO1B). This study further discovers that USP22 activated the SRC signaling pathway by upregulating the molecule KDEL endoplasmic reticulum protein retention receptor 1 (KDELR1), thereby contributing to LUAD cell progression. The study provides novel insights into the role of USP22 in EV secretion and cell motility regulation in LUAD.

BackgroundBreast cancer is the most common cancer affecting women across the world. Tumor endothelial cells (TECs) and malignant cells are the major constituents of the tumor microenvironment (TME), but their origin and role in shaping disease initiation, progression, and treatment responses remain unclear due to significant heterogeneity.MethodsTissue samples were collected from eight patients presenting with breast cancer. Single-cell RNA sequencing (scRNA-seq) analysis was employed to investigate the presence of distinct cell subsets in the tumor microenvironment. InferCNV was used to identify cancer cells. Pseudotime trajectory analysis revealed the dynamic process of breast cancer angiogenesis. We validated the function of small extracellular vesicles (sEVs)-derived protein phosphatase 1 regulatory inhibitor subunit 1B (PPP1R1B) in vitro experiments.ResultsWe performed single-cell transcriptomics analysis of the factors associated with breast cancer angiogenesis and identified twelve subclusters of endothelial cells involved in the tumor microenvironment. We also identified the role of TECs in tumor angiogenesis and confirmed their participation in different stages of angiogenesis, including communication with other cell types via sEVs. Overall, the research uncovered the TECs heterogeneity and the expression levels of genes at different stages of tumor angiogenesis.ConclusionsThis study showed sEVs derived from breast cancer malignant cells promote blood vessel formation by activating endothelial cells through the transfer of PPP1R1B. This provides a new direction for the development of anti-angiogenic therapies for human breast cancer.

BACKGROUND:Endoplasmic reticulum stress (ERs) is an important cellular self-defence mechanism, which is closely related to tumorigenesis and development. However, the role of endoplasmic reticulum stress state in the development of lung adenocarcinoma (LUAD) has not been clarified.METHODS:The lncRNAs associated with endoplasmic reticulum stress were identified by co-expression analysis in public databases, and by the least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression modelling, we constructed a prognostic model based on endoplasmic reticulum stress-related lncRNAs (ERs-related lncRNAs), performed immune analysis, TME, TMB and clinical drug prediction for model-related risk scores, and performed correlation validation in public databases and at the human tissue level.RESULTS:Five ERs-related lncRNAs were used to construct an ERs-related lncRNA signature (ERs-related LncSig), which can predict the prognosis of LUAD. Patients in the high-risk group had worse survival, and differences existed in immune cell infiltration, immune function, immune checkpoint analysis, tumour microenvironment (TME), tumour mutational burden (TMB), immunotherapy efficacy, and sensitivity to some commonly used chemotherapeutic agents between high and low risk groups.CONCLUSION:Our study demonstrated that ERs-related lncRNA signature can be used for the prognostic evaluation of LUAD patients and may provide new insights into clinical decision-making and personalised medicine for LUAD.

Background Treatment options for pretreated triple-negative breast cancer (TNBC) are limited. This study aimed to evaluate the efficacy and safety of apatinib, an antiangiogenic agent, in combination of etoposide for pretreated patients with advanced TNBC. Methods In this single-arm phase II trial, patients with advanced TNBC who failed to at least one line of chemotherapy were enrolled. Eligible patients received oral apatinib 500 mg on day 1 to 21, plus oral etoposide 50 mg on day 1 to 14 of a 3-week cycle until disease progression or intolerable toxicities. Etoposide was administered up to six cycles. The primary endpoint was progression-free survival (PFS). Results From September 2018 to September 2021, 40 patients with advanced TNBC were enrolled. All patients received previous chemotherapy in the advanced setting, with the median previous lines of 2 (1–5). At the cut-off date on January 10, 2022, the median follow-up was 26.8 (1.6–52.0) months. The median PFS was 6.0 (95% confidence interval [CI]: 3.8–8.2) months, and the median overall survival was 24.5 (95%CI: 10.2–38.8) months. The objective response rate and disease control rate was 10.0% and 62.5%, respectively. The most common adverse events (AEs) were hypertension (65.0%), nausea (47.5%) and vomiting (42.5%). Four patients developed grade 3 AE, including two with hypertension and two with proteinuria. Conclusions Apatinib combined with oral etoposide was feasible in pretreated advanced TNBC, and was easy to administer. Clinical trial registration Chictr.org.cn, (registration number: ChiCTR1800018497, registration date: 20/09/2018)

Dose-response curves of acalabrutinib in four NSCLC cell lines. H1975 and HCC827 cells are EGFR mutant while Calu3 and A549 are EGFR wild-type. Data are presented as the mean {plus minus} standard deviation (SD) of a quadruplet assay. Cells treated with DMSO alone were used as controls, and their values were set as 1. All four cell lines have IC50 > 3 μM for acalabrutinib.

Angiotensin II type 1 receptor-associated protein (ATRAP) is widely expressed in different tissues and organs, although its mechanistic role in breast cancer remains unclear. Here, we show that ATRAP is highly expressed in breast cancer tissues. Its aberrant upregulation promotes breast cancer aggressiveness and is positively correlated with poor prognosis. Functional assays revealed that ATRAP participates in promoting cell growth, metastasis, and aerobic glycolysis, while microarray analysis showed that ATRAP can activate the AKT/mTOR signaling pathway in cancer progression. In addition, ATRAP was revealed to direct Ubiquitin-specific protease 14 (USP14)-mediated deubiquitination and stabilization of Pre-B cell leukemia homeobox 3 (PBX3). Importantly, ATRAP is a direct target of Upstream stimulatory factor 1 (USF1), and that ATRAP overexpression reverses the inhibitory effects of USF1 knockdown. Our study demonstrates the broad contribution of the USF1/ATRAP/PBX3 axis to breast cancer progression and provides a strong potential therapeutic target.

28 Angiotensin II type 1 receptor-associated protein (ATRAP) is widely expressed in different tissues 29 and organs, although its mechanistic role in breast cancer remains unclear. Here, we show that 30 ATRAP is highly expressed in breast cancer tumor tissues. Its aberrant upregulation promotes breast 31 cancer aggressiveness and is positively correlated with poor prognosis. Functional assays revealed 32 that ATRAP participates in promoting cell growth, metastasis, and aerobic glycolysis, while 33 microarray analysis showed that ATRAP can activate the AKT/mTOR signaling pathway in cancer 34 progression. In addition, ATRAP was revealed to direct Ubiquitin-specific protease 14 (USP14)35 mediated de-ubiquitination and stabilization of Pre-B cell leukemia homeobox 3 (PBX3). 36 Importantly, ATRAP is a direct target of Upstream stimulatory factor 1 (USF1), and that ATRAP 37 overexpression reverses the inhibitory effects of USF1 knockdown. Our study demonstrates the 38 broad contribution of the USF1/ATRAP/PBX3 axis to breast cancer progression and provides a 39 strong potential therapeutic target. 40