Your browser doesn't support javascript.
loading
Detection of Single Cancer Cell Multidrug Resistance With Single Cell Bioanalyzer.
Cai, Jun; Fan, Xing-Xing; Li, Run-Ze; Lin, Hong; Li, Min; Song, Qi; Xie, Chun; Wong, Gregory; Liu, Sam Ting-Chung; Cao, Ya-Bing; Leung, Elaine Lai-Han.
Afiliação
  • Cai J; State Key Laboratory of Quality Research in Chinese Medicine, Macau Institute for Applied Research in Medicine and Health, Macau University of Science and Technology, Macau 853, (S.A.R.), China.
  • Fan XX; Faculty of Pharmacy and Food Science, Zhuhai College of Science and Technology, Zhuhai, China.
  • Li RZ; State Key Laboratory of Quality Research in Chinese Medicine, Macau Institute for Applied Research in Medicine and Health, Macau University of Science and Technology, Macau 853, (S.A.R.), China.
  • Lin H; State Key Laboratory of Dampness Syndrome of Chinese Medicine, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine (Guangdong Provincial Hospital of Chinese Medicine), Guangzhou, Guangdong, China.
  • Li M; Breast Surgery, Zhuhai Hospital of Traditional Chinese and Western Medicine, Zhuhai, China.
  • Song Q; Breast Surgery, Zhuhai Hospital of Traditional Chinese and Western Medicine, Zhuhai, China.
  • Xie C; State Key Laboratory of Quality Research in Chinese Medicine, Macau Institute for Applied Research in Medicine and Health, Macau University of Science and Technology, Macau 853, (S.A.R.), China.
  • Wong G; State Key Laboratory of Quality Research in Chinese Medicine, Macau Institute for Applied Research in Medicine and Health, Macau University of Science and Technology, Macau 853, (S.A.R.), China.
  • Liu ST; Macan Biotechnologies Limited, Macau 853 (S.A.R.), China.
  • Cao YB; Macan Biotechnologies Limited, Macau 853 (S.A.R.), China.
  • Leung EL; Department of Oncology, Kiang Wu Hospital, Macau 853 (S.A.R.), China.
Technol Cancer Res Treat ; 22: 15330338231187239, 2023.
Article em En | MEDLINE | ID: mdl-37424497
Objectives: Despite the development of various cancer treatment methods, chemotherapy remains the most common approach for treating cancer. The risk of tumors acquiring resistance to chemotherapy remains a significant hurdle to the successful treatment of various types of cancer. Therefore, overcoming or predicting multidrug resistance in clinical treatment is essential. The detection of circulating tumor cells (CTCs) is an important component of liquid biopsy and the diagnosis of cancer. This study aims to test the feasibility of single-cell bioanalyzer (SCB) and microfluidic chip technology in identifying patients with cancer resistant to chemotherapy and propose new methods to provide clinicians with new choices. Methods: In this study, we used rapidly isolated viable CTCs from the patient blood samples method combined with SCB technology and a novel microfluidic chip, to predict whether patients with cancer are resistant to chemotherapy. SCB and microfluidic chip were used to select single CTCs, and the accumulation of chemotherapy drug was fluorescently measured in real time on these cells in the absence and presence of permeability-glycoprotein inhibitors. Results: Initially, we successfully isolated viable CTCs from the blood samples of patients. Additionally, the present study accurately predicted the response of 4 lung cancer patients to chemotherapeutic drugs. In addition, the CTCs of 17 patients with breast cancer diagnosed at Zhuhai Hospital of Traditional Chinese and Western Medicine were assessed. The results indicated that 9 patients were sensitive to chemotherapeutic drugs, 8 patients were resistant to a certain degree, and only 1 was completely resistant to chemotherapy. Conclusion: The present study indicated that the SCB technology could be used as a prognostic assay to evaluate the CTCs response to available drugs and guide physicians to treatment options that are most likely to be effective.
Assuntos
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article