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Simple Summary
Small molecule inhibitors and targeted therapy are considered to have significant potential for pancreatic ductal adenocarcinoma therapies. Preclinical studies of novel inhibitors and inhibitor combinations can elucidate their acting mechanisms and provide valuable data for in vivo research and clinical trials. We explored the antitumor efficacy of KRAS inhibitors BI-3406 and sotorasib alone or in combination with the downstream inhibitors trametinib and buparlisib in PDAC cell lines, characterized by different KRAS mutational statuses. The two KRAS inhibitors demonstrated different anti-tumor efficacy and displayed synergistic or additive effects, when combined with downstream pathway inhibitors. These data emphasized the importance of KRAS as a therapeutic target for PDAC and indicate two distinct mechanisms of KRAS inhibition and their interactions with downstream pathway inhibitors.
Abstract
Kirsten rat sarcoma virus (KRAS) mutations are widespread in pancreatic ductal adenocarcinoma (PDAC) and contribute significantly to tumor initiation, progression, tumor relapse/resistance, and prognosis of patients. Although inhibitors against KRAS mutations have been developed, this therapeutic approach is not routinely used in PDAC patients. We investigated the anti-tumor efficacy of two KRAS inhibitors BI-3406 (KRAS::SOS1 inhibitor) and sotorasib (KRAS G12C inhibitor) alone or in combination with MEK1/2 inhibitor trametinib and/or PI3K inhibitor buparlisib in seven PDAC cell lines. Whole transcriptomic analysis of combined inhibition and control groups were comparatively analyzed to explore the corresponding mechanisms of inhibitor combination. Both KRAS inhibitors and corresponding combinations exhibited cytotoxicity against specific PDAC cell lines. BI-3406 enhance the efficacy of trametinib and buparlisib in BXPC-3, ASPC-1 and MIA PACA-2, but not in CAPAN-1, while sotorasib enhances the efficacy of trametinib and buparlisib only in MIA PACA-2. The whole transcriptomic analysis demonstrates that the two triple-inhibitor combinations exert antitumor effects by affecting related cell functions, such as affecting the immune system, cell adhesion, cell migration, and cytokine binding. As well as directly involved in RAF/MEK/ERK pathway and PI3K/AKT pathway affect cell survival. Our current study confirmed inhibition of KRAS and its downstream pathways as a potential novel therapy for PDAC and provides fundamental data for in vivo evaluations.
Genetic Regulation of Liver Metabolites and Transcripts Linking to Biochemical-Clinical Parameters
(2019)
Given the central metabolic role of the liver, hepatic metabolites and transcripts reflect the organismal physiological state. Biochemical-clinical plasma biomarkers, hepatic metabolites, transcripts, and single nucleotide polymorphism (SNP) genotypes of some 300 pigs were integrated by weighted correlation networks and genome-wide association analyses. Network-based approaches of transcriptomic and metabolomics data revealed linked of transcripts and metabolites of the pentose phosphate pathway (PPP). This finding was evidenced by using a NADP/NADPH assay and HDAC4 and G6PD transcript quantification with the latter coding for first limiting enzyme of this pathway and by RNAi knockdown experiments of HDAC4. Other transcripts including ARG2 and SLC22A7 showed link to amino acids and biomarkers. The amino acid metabolites were linked with transcripts of immune or acute phase response signaling, whereas the carbohydrate metabolites were highly enrich in cholesterol biosynthesis transcripts. Genome-wide association analyses revealed 180 metabolic quantitative trait loci (mQTL) (p < 10-4). Trans-4-hydroxy-L-proline (p = 6 × 10-9), being strongly correlated with plasma creatinine (CREA), showed strongest association with SNPs on chromosome 6 that had pleiotropic effects on PRODH2 expression as revealed by multivariate analysis. Consideration of shared marker association with biomarkers, metabolites, and transcripts revealed 144 SNPs associated with 44 metabolites and 69 transcripts that are correlated with each other, representing 176 mQTL and expression quantitative trait loci (eQTL). This is the first work to report genetic variants associated with liver metabolite and transcript levels as well as blood biochemical-clinical parameters in a healthy porcine model. The identified associations provide links between variation at the genome, transcriptome, and metabolome level molecules with clinically relevant phenotypes. This approach has the potential to detect novel biomarkers displaying individual variation and promoting predictive biology in medicine and animal breeding.