Kaur Rajdeep, Suresh P K
Department of Bio-Medical Sciences, School of Biosciences and Technology, VIT University, Vellore, 632014, Tamil Nadu, India.
Appl Biochem Biotechnol. 2024 Jul;196(7):4382-4438. doi: 10.1007/s12010-023-04595-7. Epub 2023 Sep 18.
Globally, lung cancer contributes significantly to the public health burden-associated mortality. As this form of cancer is insidious in nature, there is an inevitable diagnostic delay leading to chronic tumor development. Non-small cell lung cancer (NSCLC) constitutes 80-85% of all lung cancer cases, making this neoplasia form a prevalent subset of lung carcinoma. One of the most vital aspects for proper diagnosis, prognosis, and adequate therapy is the precise classification of non-small cell lung cancer based on biomarker expression profiling. This form of biomarker profiling has provided opportunities for improvements in patient stratification, mechanistic insights, and probable druggable targets. However, numerous patients have exhibited numerous toxic side effects, tumor relapse, and development of therapy-based chemoresistance. As a result of these exacting situations, there is a dire need for efficient and effective new cancer therapeutics. De novo drug development approach is a costly and tedious endeavor, with an increased attrition rate, attributed, in part, to toxicity-related issues. Drug repurposing, on the other hand, when combined with computer-assisted systems biology approach, provides alternatives to the discovery of new, efficacious, and safe drugs. Therefore, in this review, we focus on a comparison of the conventional therapy-based chemoresistance mechanisms with the repurposed anti-cancer drugs from three different classes-anti-parasitic, anti-depressants, and anti-psychotics for cancer treatment with a primary focus on NSCLC therapeutics. Certainly, amalgamating these novel therapeutic approaches with that of the conventional drug regimen in NSCLC-affected patients will possibly complement/synergize the existing therapeutic modalities. This approach has tremendous translational significance, since it can combat drug resistance and cytotoxicity-based side effects and provides a relatively new strategy for possible application in therapy of individuals with NSCLC.
在全球范围内，肺癌对与公共卫生负担相关的死亡率有重大影响。由于这种癌症本质上具有隐匿性，不可避免地会出现诊断延迟，导致肿瘤慢性发展。非小细胞肺癌（NSCLC）占所有肺癌病例的80-85%，使这种肿瘤形成肺癌的一个普遍亚型。基于生物标志物表达谱对非小细胞肺癌进行精确分类是正确诊断、预后和适当治疗的最重要方面之一。这种生物标志物谱分析形式为改善患者分层、机理洞察和可能的可成药靶点提供了机会。然而，许多患者出现了许多毒性副作用、肿瘤复发以及基于治疗的化疗耐药性。由于这些严峻情况，迫切需要高效且有效的新型癌症治疗方法。从头研发药物的方法成本高昂且繁琐，损耗率增加，部分原因是与毒性相关的问题。另一方面，药物重新利用与计算机辅助系统生物学方法相结合，为发现新的、有效且安全的药物提供了替代方案。因此，在本综述中，我们重点比较基于传统治疗的化疗耐药机制与来自三类不同药物——抗寄生虫药、抗抑郁药和抗精神病药——重新用于癌症治疗（主要关注NSCLC治疗）的抗癌药物。当然，将这些新型治疗方法与NSCLC患者的传统药物治疗方案相结合，可能会补充/协同现有的治疗方式。这种方法具有巨大的转化意义，因为它可以对抗耐药性和基于细胞毒性的副作用，并为NSCLC患者的治疗提供一种相对新的可能应用策略。
