Basic approaches, challenges and opportunities for the discovery of small molecule anti-tumor drugs

Abstract

Chemotherapy is one of the main treatments for cancer, especially for advanced cancer patients. In the past decade, significant progress has been made with the research into the molecular mechanisms of cancer cells and the precision medicine. The treatment on cancer patients has gradually changed from cytotoxic chemotherapy to precise treatment strategy. Research into anticancer drugs has also changed from killing effects on all cells to targeting drugs for target genes. Besides, researchers have developed the understanding of the abnormal physiological function, related genomics, epigenetics, and proteomics of cancer cells with cancer genome sequencing, epigenetic research, and proteomic research. These technologies and related research have accelerated the development of related cancer drugs. In this review, we summarize the research progress of anticancer drugs, the current challenges, and future opportunities.

Keywords: Drug therapy; cancer; comprehensive utilization; inhibitor.

Figure 1

Discovery and development from gene to drug. Small molecules that act on new molecular targets represent therapeutic dependencies and vulnerabilities. There are four main steps of cancer drug discovery: target selection and validation, chemical hit and lead generation, lead optimization to select a clinical candidate, and biology-led clinical trials.

Figure 2

Potential drug targets for targeted therapy. Common proteins upregulated in the majority of tumors were classified in the four functional categories: proteins involved in extracellular matrix (ECM), immune response, cell cycle/DNA replication, and metabolism.

Figure 3

A road map to personalizing targeted cancer therapies using multinomial integration analysis. Multinomial integration analysis approach has been used for personalized targeted therapeutics in a genome profiled patient cohort. Mass spectrometry (MS)-based proteomics can measure global protein abundance and post-translational modifications to provide additional biological insights, which may not be deciphered by genomic analysis alone. The combination of sequencing and MS provides a more comprehensive picture linking cancer genotype to phenotype through functional proteomics and signaling networks. Integrated analyses of genomic, transcriptomic, proteomic, and phosphoproteomic data from tumor and matched non-tumor liver tissues revealed the connection and discordance among multi-omics and alterations in critical signaling and metabolic pathway. Thus, tumor genome analysis for mutation in a cancer-specific gene as a biomarker results in a better outcome in clinical trials.

Figure 4

Status of proteins that participate in the apoptotic pathway in cancer. An overexpression of anti-apoptotic proteins has been reported, as well as a downregulation of pro-apoptotic proteins that participate in the mitochondrial apoptotic pathway and in the TNF receptor pathway. It has been suggested that the dysregulation of these proteins induces resistance to apoptosis in different therapeutic approaches.

Figure 5

Comparison of sources and technologies for anti-cancer compounds. Traditional sources and new technologies that use microbial fermentation, insect and mammalian cell cultures, and transgenic animals have drawbacks in cost, scalability, product safety, and authenticity.