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增强宫颈癌患者对临床现有疗法耐药性的分子机制。

Molecular mechanisms augmenting resistance to current therapies in clinics among cervical cancer patients.

机构信息

School of Biosciences and Technology, Vellore Institute of Technology (VIT), Vellore, Tamil Nadu, 632014, India.

Department of Biochemistry, Centre of Molecular Medicine and Diagnostics (COMManD), Saveetha Dental College & Hospitals, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, 600077, Tamil Nadu, India.

出版信息

Med Oncol. 2023 Apr 15;40(5):149. doi: 10.1007/s12032-023-01997-9.

Abstract

Cervical cancer (CC) is the fourth leading cause of cancer death (~ 324,000 deaths annually) among women internationally, with 85% of these deaths reported in developing regions, particularly sub-Saharan Africa and Southeast Asia. Human papillomavirus (HPV) is considered the major driver of CC, and with the availability of the prophylactic vaccine, HPV-associated CC is expected to be eliminated soon. However, female patients with advanced-stage cervical cancer demonstrated a high recurrence rate (50-70%) within two years of completing radiochemotherapy. Currently, 90% of failures in chemotherapy are during the invasion and metastasis of cancers related to drug resistance. Although molecular target therapies have shown promising results in the lab, they have had little success in patients due to the tumor heterogeneity fueling resistance to these therapies and bypass the targeted signaling pathway. The last two decades have seen the emergence of immunotherapy, especially immune checkpoint blockade (ICB) therapies, as an effective treatment against metastatic tumors. Unfortunately, only a small subgroup of patients (< 20%) have benefited from this approach, reflecting disease heterogeneity and manifestation with primary or acquired resistance over time. Thus, understanding the mechanisms driving drug resistance in CC could significantly improve the quality of medical care for cancer patients and steer them to accurate, individualized treatment. The rise of artificial intelligence and machine learning has also been a pivotal factor in cancer drug discovery. With the advancement in such technology, cervical cancer screening and diagnosis are expected to become easier. This review will systematically discuss the different tumor-intrinsic and extrinsic mechanisms CC cells to adapt to resist current treatments and scheme novel strategies to overcome cancer drug resistance.

摘要

宫颈癌(CC)是全球女性癌症死亡的第四大原因(每年约有 32.4 万人死亡),其中 85%的死亡病例发生在发展中国家,特别是撒哈拉以南非洲和东南亚。人乳头瘤病毒(HPV)被认为是宫颈癌的主要驱动因素,随着预防性疫苗的问世,预计 HPV 相关宫颈癌将很快被消除。然而,接受放化疗的晚期宫颈癌女性患者在完成治疗后两年内复发率很高(50-70%)。目前,化疗失败的 90%发生在与耐药相关的癌症侵袭和转移期间。尽管分子靶向治疗在实验室中显示出了良好的效果,但由于肿瘤异质性导致对这些治疗方法产生耐药性并绕过靶向信号通路,它们在患者中的应用效果并不理想。过去二十年见证了免疫疗法的出现,特别是免疫检查点阻断(ICB)疗法,作为一种有效的转移性肿瘤治疗方法。不幸的是,只有一小部分患者(<20%)从中受益,这反映了疾病的异质性以及随着时间的推移表现出的原发性或获得性耐药。因此,了解导致宫颈癌耐药的机制可以显著提高癌症患者的医疗质量,并为他们提供准确的个体化治疗方案。人工智能和机器学习的兴起也是癌症药物发现的关键因素。随着这项技术的进步,宫颈癌的筛查和诊断有望变得更加容易。本综述将系统地讨论宫颈癌细胞适应现有治疗方法的不同内在和外在机制,并提出克服癌症药物耐药性的新策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9673/10105157/c092894490d5/12032_2023_1997_Fig1_HTML.jpg

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