Prognostic and therapeutic TILs of cervical cancer—Current advances and future perspectives

Autor: Anne X.J. Zhang, Wenyi Gu, Guangyu Chen, Ying Tang, Yanheng Wu
Rok vydání: 2021
Předmět:
Zdroj: Molecular Therapy Oncolytics
Molecular Therapy: Oncolytics, Vol 22, Iss, Pp 410-430 (2021)
ISSN: 2372-7705
DOI: 10.1016/j.omto.2021.07.006
Popis: Cervical cancer is a top lethal cancer for women worldwide. Although screening and vaccination programs are available in many countries, resulting in the decline of new cases, this is not true for developing countries where there are many new cases and related deaths. Cancer immunotherapy through adaptive cell therapy (ACT) has been applied in clinics, but now much attention is focused on autogenic tumor-infiltrating lymphocyte (TIL)-based therapy, which has shown more specificity and better ability to inhibit tumor growth. Data from melanoma and cervical cancers confirm that tumor-specific T cells in TILs can be expanded for more specific and effective ACT. Moreover, TILs are derived from individual patients and are ready to home back to kill tumor cells after patient infusion, aligning well with personalized and precision medicine. In addition to therapy, TIL cell types and numbers are good indicators of host immune response to the tumor, and thus they have significant values in prognosis. Because of the special relationship with human papillomavirus (HPV) infection, cervical cancer has some specialties in TIL-based prognosis and therapy. In this review, we summarize the recent advances in the prognostic significance of TILs and TIL-based therapy for cervical cancer and discuss related perspectives.
Graphical abstract
Tumor-infiltrating lymphocytes (TILs) of cervical cancer can be isolated and expanded as a personalized and precision medicine to specifically treat heterogeneous (multi-target) tumor cells of the patient. Furthermore, the phenotype and number of TILs or infiltrating immune cells (such as macrophages) have a significant value in predicting cancer progression and prognosis.
Databáze: OpenAIRE