RESUMEN
Homologous recombination (HR) plays a key role in maintaining genomic stability, and the efficiency of the HR system is closely associated with tumor response to chemotherapy. Our previous work reported that CK2 kinase phosphorylates HIV Tat-specific factor 1 (HTATSF1) Ser748 to facilitate HTATSF1 interaction with TOPBP1, which in turn, promotes RAD51 recruitment and HR repair. However, the clinical implication of the CK2-HTATSF1-TOPBP1 pathway in tumorigenesis and chemotherapeutic response remains to be elucidated. Here, we report that the CK2-HTATSF1-TOPBP1 axis is generally hyperactivated in multiple malignancies and renders breast tumors less responsive to chemotherapy. In contrast, deletion mutations of each gene in this axis, which also occur in breast and lung tumor samples, predict higher HR deficiency scores, and tumor cells bearing a loss-of-function mutation of HTATSF1 are vulnerable to poly(ADP-ribose) polymerase inhibitors or platinum drugs. Taken together, our study suggests that the integrity of the CK2-HTATSF1-TOPBP1 axis is closely linked to tumorigenesis and serves as an indicator of tumor HR status and modulates chemotherapy response.
Asunto(s)
Proteínas Portadoras , Quinasa de la Caseína II , Proteínas de Unión al ADN , Transducción de Señal , Humanos , Proteínas de Unión al ADN/metabolismo , Proteínas de Unión al ADN/genética , Transducción de Señal/efectos de los fármacos , Quinasa de la Caseína II/metabolismo , Quinasa de la Caseína II/genética , Proteínas Portadoras/metabolismo , Proteínas Portadoras/genética , Animales , Femenino , Ratones , Línea Celular Tumoral , Proteínas Nucleares/metabolismo , Proteínas Nucleares/genética , Antineoplásicos/farmacología , Antineoplásicos/uso terapéutico , Neoplasias de la Mama/metabolismo , Neoplasias de la Mama/tratamiento farmacológico , Neoplasias de la Mama/genética , Neoplasias de la Mama/patología , Neoplasias/metabolismo , Neoplasias/tratamiento farmacológico , Neoplasias/genética , Neoplasias/patologíaRESUMEN
With the advancement of sequencing technology, cell separation, and whole-genome amplification techniques, single cell technology for genome sequencing is emerging gradually. In comparison to traditional genome sequencing at the multi-cellular level, single-cell sequencing can not only measure the gene expression level more accurately but also can detect a small amount of gene expression or rare noncoding RNA. This technology has garnered increasing interest among researchers engaged in single-cell studies in recent years. Here, we developed a reproducible computational workflow for scRNA-seq data analysis which including tasks like quality control, normalization, data correction, pseudotime analysis, copy number analysis, etc. We illustrate the application of these steps using publicly available datasets and provide practical recommendations for their implementation. This study serves as a comprehensive tutorial for researchers keen on single-cell data analysis, aiding users in constructing and refining their own analysis pipelines.