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Background It is encountering the dilemma of lacking precise biomarkers to predict the response to neoadjuvant chemoimmunotherapy (NACI) and determine whether patients should use immune checkpoint inhibitors (ICIs) in early breast cancer (BC). We aimed to develop a gene signature to predict NACI response for BC patients and identify individuals suitable for adding ICIs.Patients and methods Two I-SPY2 cohorts and one West China Hospital cohort of patients treated with NACI were included. Machine learning algorithms were used to identify key genes. Principal component analysis was used to calculate the ImPredict (IP) score. The interaction effects between biomarkers and treatment regimens were examined based on the logistic regression analysis. The relationship between the IP score and immune microenvironment was investigated through immunohistochemistry (IHC) and multiplex IHC.Results The area under the curves of the IP score were 0.935, 0.865, and 0.841 in the discovery cohort, validation cohort 1, and in-house cohort. Marker-treatment interaction tests indicated that the benefits from immunotherapy significantly varied between patients with high and low IP scores (p for interaction

Abstract Background Kaposiform hemangioendothelioma (KHE) is a rare intermediate vascular tumor with unclear pathogenesis. Recently, three dimensional (3D) cell spheroids and organoids have played an indispensable role in the study of many diseases, such as infantile hemangioma and non-involuting congenital hemangiomas. However, few research on KHE are based on the 3D model. This study aims to evaluate the 3D superiority, the similarity with KHE and the ability of drug evaluation of EOMA spheroids as an in vitro 3D KHE model. Results After two days, relatively uniform morphology and high viability of EOMA spheroids were generated by the rotating cell culture system (RCCS). Through transcriptome analysis, compared with 2D EOMA cells, focal adhesion-related genes such as Itgb4, Flt1, VEGFC, TNXB, LAMA3, VWF, and VEGFD were upregulated in EOMA spheroids. Meanwhile, the EOMA spheroids injected into the subcutaneous showed more obvious KMP than 2D EOMA cells. Furthermore, EOMA spheroids possessed the similar characteristics to the KHE tissues and subcutaneous tumors, such as diagnostic markers (CD31 and LYVE-1), cell proliferation (Ki67), hypoxia (HIF-1α) and cell adhesion (E-cadherin and N-cadherin). Based on the EOMA spheroid model, we discovered that sirolimus, the first-line drug for treating KHE, could inhibit EOMA cell proliferation and downregulate the VEGFC expression. Through the extra addition of VEGFC, the effect of sirolimus on EOMA spheroid could be weakened. Conclusion With a high degree of similarity of the KHE, 3D EOMA spheroids generated by the RCCS can be used as a in vitro model for basic researches of KHE, generating subcutaneous tumors and drug screening.

IntroductionTriple-negative breast cancer (TNBC) is characterized by its aggressive nature and absence of specific therapeutic targets, necessitating the reliance on chemotherapy as the primary treatment modality. However, the drug resistance poses a significant challenge in the management of TNBC. In this study, we investigated the role of DDX58 (DExD/H-box helicase 58), also known as RIG-I, in TNBC chemoresistance.MethodsThe relationship between DDX58 expression and breast cancer prognosis was investigated by online clinical databases and confirmed by immunohistochemistry analysis. DDX58 was knockout by CRISPR-Cas9 system (DDX58-KO), knockdown by DDX58-siRNA (DDX58-KD), and stably over expressed (DDX58-OE) by lentivirus. Western blotting, immunofluorescence and qPCR were used for related molecules detection. Apoptosis was analyzed through flow cytometry (Annexin V/7AAD apoptosis assay) and Caspase 3/7 activity assay.ResultsPatients with lower expression of DDX58 led to lower rate of pathological complete response (pCR) and worse prognosis by online databases and hospital clinical data. DDX58-KD cells showed multiple chemo-drugs resistance (paclitaxel, doxorubicin, 5-fluorouracil) in TNBC cell lines. Similarly, DDX58-KO cells also showed multiple chemo-drugs resistance in a dosage-dependent manner. In the CDX model, tumours in the DDX58-KO group had a 25% reduction in the tumour growth inhibition rate (IR) compared to wild-type (WT) group after doxorubicin (Dox) treatment. The depletion of DDX58 inhibited proliferation and promoted the migration and invasion in MDA-MB-231 cells. The findings of our research indicated that DDX58-KO cells exhibit a reduction in Dox-induced apoptosis both in vivo and in vitro. Mechanistically, Dox treatment leads to a significant increase in the expression of double-stranded RNAs (dsRNAs) and activates the DDX58-Type I interferon (IFN) signaling pathway, ultimately promoting apoptosis in TNBC cells.DiscussionIn the process of TNBC chemotherapy, the deficiency of DDX58 can inhibit Dox-induced apoptosis, revealing a new pathway of chemotherapy resistance, and providing a possibility for developing personalized treatment strategies based on DDX58 expression levels.