Abstract:Insulin-like Growth Factor (IGF)/IGF-1 Receptor (IGF-1R) signaling is known to regulate stem cell pluripotency and differentiation to trigger cell proliferation, organ development, and tissue regeneration during embryonic development. Unbalanced IGF/IGF-1R signaling can promote cancer cell proliferation and activate cancer reprogramming in tumor tissues, especially in the liver. Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related death, with a high incidence and mortality rate in Asia… Show more
“…However, the interplay between YAP and IGF signaling has remained uncertain in HCC sorafenib resistance. We previously illustrated that high expression of IGF-1R correlates with expression of cancer stemness markers (OCT4 and NANOG) and early recurrence [27,28] and with sorafenib resistance properties in HCC [11,66]. In the current study, we found that the underlying mechanism of HCC sorafenib resistance involves a YAP-IGF-1R signaling loop that involves EMT-related proteins and YAP nuclear translocation in vitro and in vivo.…”
The role of a YAP-IGF-1R signaling loop in HCC resistance to sorafenib remains unknown. Method: Sorafenib-resistant cells were generated by treating naïve cells (HepG2215 and Hep3B) with sorafenib. Different cancer cell lines from databases were analyzed through the ONCOMINE web server. BIOSTORM–LIHC patient tissues (46 nonresponders and 21 responders to sorafenib) were used to compare YAP mRNA levels. The HepG2215_R-derived xenograft in SCID mice was used as an in vivo model. HCC tissues from a patient with sorafenib failure were used to examine differences in YAP and IGF-R signaling. Results: Positive associations exist among the levels of YAP, IGF-1R, and EMT markers in HCC tissues and the levels of these proteins increased with sorafenib failure, with a trend of tumor-margin distribution in vivo. Blocking YAP downregulated IGF-1R signaling-related proteins, while IGF-1/2 treatment enhanced the nuclear translocation of YAP in HCC cells through PI3K-mTOR regulation. The combination of YAP-specific inhibitor verteporfin (VP) and sorafenib effectively decreased cell viability in a synergistic manner, evidenced by the combination index (CI). Conclusion: A YAP-IGF-1R signaling loop may play a role in HCC sorafenib resistance and could provide novel potential targets for combination therapy with sorafenib to overcome drug resistance in HCC.
“…However, the interplay between YAP and IGF signaling has remained uncertain in HCC sorafenib resistance. We previously illustrated that high expression of IGF-1R correlates with expression of cancer stemness markers (OCT4 and NANOG) and early recurrence [27,28] and with sorafenib resistance properties in HCC [11,66]. In the current study, we found that the underlying mechanism of HCC sorafenib resistance involves a YAP-IGF-1R signaling loop that involves EMT-related proteins and YAP nuclear translocation in vitro and in vivo.…”
The role of a YAP-IGF-1R signaling loop in HCC resistance to sorafenib remains unknown. Method: Sorafenib-resistant cells were generated by treating naïve cells (HepG2215 and Hep3B) with sorafenib. Different cancer cell lines from databases were analyzed through the ONCOMINE web server. BIOSTORM–LIHC patient tissues (46 nonresponders and 21 responders to sorafenib) were used to compare YAP mRNA levels. The HepG2215_R-derived xenograft in SCID mice was used as an in vivo model. HCC tissues from a patient with sorafenib failure were used to examine differences in YAP and IGF-R signaling. Results: Positive associations exist among the levels of YAP, IGF-1R, and EMT markers in HCC tissues and the levels of these proteins increased with sorafenib failure, with a trend of tumor-margin distribution in vivo. Blocking YAP downregulated IGF-1R signaling-related proteins, while IGF-1/2 treatment enhanced the nuclear translocation of YAP in HCC cells through PI3K-mTOR regulation. The combination of YAP-specific inhibitor verteporfin (VP) and sorafenib effectively decreased cell viability in a synergistic manner, evidenced by the combination index (CI). Conclusion: A YAP-IGF-1R signaling loop may play a role in HCC sorafenib resistance and could provide novel potential targets for combination therapy with sorafenib to overcome drug resistance in HCC.
“…In addition, there is a family of seven high-affinity IGF-binding proteins (IGFBP1 to IGFBP7), which bind and stabilize IGF and regulate its accessibility to its receptors [ 52 ]. Signaling through IGF1R plays an important role in tumorigenesis in the liver and is one of the hallmarks of HCC [ 53 , 54 ]. Over-activation of IGF signaling can be induced by increased levels of IGF1R or excessive IGF, which subsequently leads to prolonged activation of the MAPK/ERK signaling pathway [ 55 ].…”
Section: Mapk/erk Signaling Pathway In Hccmentioning
Hepatocellular carcinoma (HCC) is a major health concern worldwide, and its incidence is increasing steadily. Recently, the MAPK/ERK signaling pathway in HCC has gained renewed attention from basic and clinical researchers. The MAPK/ERK signaling pathway is activated in more than 50% of human HCC cases; however, activating mutations in RAS and RAF genes are rarely found in HCC, which are major genetic events leading to the activation of the MAPK/ERK signaling pathway in other cancers. This suggests that there is an alternative mechanism behind the activation of the signaling pathway in HCC. Here, we will review recent advances in understanding the cellular and molecular mechanisms involved in the activation of the MAPK/ERK signaling pathway and discuss potential therapeutic strategies targeting the signaling pathway in the context of HCC.
“…For this query, the knowledge graph also exhibits top ranked approved/investigative drugs that are targeting core genes associated with HCC (e.g., linsitinib, which is a selective inhibitor of insulin-like growth factor IGF-1R under investigation for the treatment of cancer and solid tumors). Since IGF-1R signaling is critical in tumor formation and activation of cancer stemness, which in turn may lead to tumor recurrence, this investigative drug has been reported in several clinical trials including prostate cancer, NSCLC, and advanced HCC [35].…”
Section: Hcc Query In Crossbar Web-servicementioning
Purpose Computational approaches have been used at different stages of drug development with the purpose of decreasing the time and cost of conventional experimental procedures. Lately, techniques mainly developed and applied in the field of artificial intelligence (AI), have been transferred to different application domains such as biomedicine. Methods In this study, we conducted an investigative analysis via data-driven evaluation of potential hepatocellular carcinoma (HCC) therapeutics in the context of AI-assisted drug discovery/repurposing. First, we discussed basic concepts, computational approaches, databases, modeling approaches, and featurization techniques in drug discovery/repurposing. In the analysis part, we automatically integrated HCC-related biological entities such as genes/proteins, pathways, phenotypes, drugs/compounds, and other diseases with similar implications, and represented these heterogeneous relationships via a knowledge graph using the CROssBAR system. Results Following the system-level evaluation and selection of critical genes/proteins and pathways to target, our deep learning-based drug/compound-target protein interaction predictors DEEPScreen and MDeePred have been employed for predicting new bioactive drugs and compounds for these critical targets. Finally, we embedded ligands of selected HCCassociated proteins which had a significant enrichment with the CROssBAR system into a 2-D space to identify and repurpose small molecule inhibitors as potential drug candidates based on their molecular similarities to known HCC drugs. Conclusions We expect that these series of data-driven analyses can be used as a roadmap to propose early-stage potential inhibitors (from database-scale sets of compounds) to both HCC and other complex diseases, which may subsequently be analyzed with more targeted in silico and experimental approaches.
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