Natural Product Target Network Reveals Potential for Cancer Combination Therapies

Abstract

A body of research demonstrates examples of in vitro and in vivo synergy between natural products and anti-neoplastic drugs for some cancers. However, the underlying biological mechanisms are still elusive. To better understand biological entities targeted by natural products and therefore provide rational evidence for future novel combination therapies for cancer treatment, we assess the targetable space of natural products using public domain compound-target information. When considering pathways from the Reactome database targeted by natural products, we found an increase in coverage of 61% (725 pathways), relative to pathways covered by FDA approved cancer drugs collected in the Cancer Targetome, a resource for evidence-based drug-target interactions. Not only is the coverage of pathways targeted by compounds increased when we include natural products, but coverage of targets within those pathways is also increased. Furthermore, we examined the distribution of cancer driver genes across pathways to assess relevance of natural products to critical cancer therapeutic space. We found 24 pathways enriched for cancer drivers that had no available cancer drug interactions at a potentially clinically relevant binding affinity threshold of < 100nM that had at least one natural product interaction at that same binding threshold. Assessment of network context highlighted the fact that natural products show target family groupings both distinct from and in common with cancer drugs, strengthening the complementary potential for natural products in the cancer therapeutic space. In conclusion, our study provides a foundation for developing novel cancer treatment with the combination of drugs and natural products.

Keywords: antineoplastic drug; cancer; natural product; synergy; therapeutic targets.

Figure 1

Framework for natural product target network evaluation. The targets associated with both NPs and anti-neoplastic drugs were evaluated in different contexts of increasing complexity. Complementary and distinct coverage of protein targets and pathways by the two compound classes were assessed. Target importance and relationships were evaluated in biological contexts, which include protein-protein interaction networks and molecular pathways. Pathway relationships and shared target space were assessed through the construction of a pathway-pathway network and a compound-compound network. Red lines indicate the existence of an edge between nodes in these networks. Two compounds have an edge if they share at least one target, and two pathways have an edge if they share at least one protein (Mahira and Umehara, ; Mykhal, ; Hinemash6, 2010).

Figure 2

Assessment of evidence levels for target and compound-target interactions. CT, Cancer Targetome; NP, Natural Product Target Network. (A) Comparison of interaction distribution by evidence level between NPs and CT drugs. (B) Comparison of interaction distribution at high affinity only (evidence level III exact values in nM). (C) Comparison of maximum target evidence level distribution between NPs and CT drugs. (D) Comparison of maximum target evidence level distribution at high affinity only (evidence level III exact values in nM).

Figure 3

Evaluation of cancer pathway overlap at affinities <100 nM. There is a high level of pathway overlap between those targeted by NPs and CT drugs, but little overlap at the individual target level.

Figure 4

Cancer pathway gene set targeted only by natural products for a cancer driver target. Another Reactome functional interaction network (TP53 Regulates Transcription of Genes Involved in G1 Cell Cycle Arrest) targeted only by NPs at <100 nM (green border). No FDA-approved cancer drugs target this pathway with < 100 nM evidence. Cancer drivers are shown in yellow. In this pathway the NP target is also a cancer driver. Dashed lines are predicted interactions.