Abstract Introduction: The Know Your Tumor (KYT) pancreas cancer program enables molecular analysis of both tumor DNA and mRNA to characterize tumor phenotypes and guide potential treatment options. The primary objective of the current study was to develop and apply criteria to establish treatment response from real-world clinical data and to characterize the matching molecular and immunologic features of the pancreatic ductal adenocarcinoma (PDAC) tumor biopsies to identify tumor phenotypes that associate with treatment response. Experimental Procedures: Formalin-fixed, paraffin-embedded tumor samples and related clinical data were collected from n=240 patients diagnosed with PDAC and treated at medical centers in the United States. Samples underwent retrospective mutation analysis using the Tempus xT targeted panel of 648 genes and whole transcriptome RNA-sequencing also from Tempus. To identify molecular profiles associated with tumor treatment response, the duration of first therapy and CA19-9 levels taken after the start of first therapy were analyzed to establish consensus responder and non-responder criteria. Mutation associations using Fisher exact tests and differential gene expression and immune signature analysis using Wilcoxon tests were performed on all FOLFIRINOX-treated subjects that meet consensus responder (n = 12) or non-responder (n = 10) definitions to identify molecular underpinnings of FOLFIRINOX resistance. Gene expression analysis initially focused on tumor intrinsic genes (TIGs) because the expression of these genes may specifically reflect PDAC tumor biology. Differentially expressed TIGs with an unadjusted p-value < 0.05 were submitted for gene set enrichment analysis (GSEA) and manual investigation. Results: No association between DNA mutations and response to FOLFIRINOX was observed in this small dataset. In contrast, results from RNA-based gene expression analysis suggested that differences in tumor biology may contribute to response. GSEA and manual interrogation of differentially expressed TIGs revealed non-responder tumors may have high expression of apoptosis-related genes and genes associated with energetics. GSEA of all differentially expressed genes (unadjusted p-value < 0.05) refined this interpretation and corroborated initial findings by suggesting non-responders may have high expression of hypoxia, glycolysis- and apoptosis-related genes and low expression of SMAD4 and its associated target genes. Summary and Conclusions: These results support the testable hypothesis that FOLFIRINOX non-responders evade apoptosis through hypoxia adaptations and autophagic flux. These hypotheses may warrant further investigation with preclinical models such as cell culture, PDX or organoid models. Finally, the analysis plan provides a roadmap for using the KYT cohort and other real-world datasets to generate hypotheses about molecular mechanisms of treatment response. Citation Format: James M. Davison, Greg Mayhew, Kirk Beebe, Joel R. Eisner, Dennis Ladnier, Eric A. Collisson, Lynn M. Matrisian. Initial retrospective analysis of mechanisms of FOLFIRINOX resistance using clinical and molecular data from the Know Your Tumor (KYT) pancreatic ductal adenocarcinoma (PDAC) cohort [abstract]. In: Proceedings of the AACR Virtual Special Conference on Pancreatic Cancer; 2021 Sep 29-30. Philadelphia (PA): AACR; Cancer Res 2021;81(22 Suppl):Abstract nr PO-002.
Peroxisome proliferator-activated receptor-alpha (PPARalpha) agonists such as fenofibrate are used to treat dyslipidemia. Although fenofibrate is considered safe in humans, it is known to cause hepatocarcinogenesis in rodents. To evaluate untargeted metabolic profiling as a tool for gaining insight into the underlying pharmacology and hepatotoxicology, Fischer 344 male rats were dosed with 300 mg/kg/day of fenofibrate for 14 days and the urine and plasma were analyzed on days 2 and 14. A combination of liquid and gas chromatography mass spectrometry returned the profiles of 486 plasma and 932 urinary metabolites. Aside from known pharmacological effects, such as accelerated fatty acid beta-oxidation and reduced plasma cholesterol, new observations on the drug's impact on cellular metabolism were generated. Reductions in TCA cycle intermediates and biochemical evidence of lactic acidosis demonstrated that energy metabolism homeostasis was altered. Perturbation of the glutathione biosynthesis and elevation of oxidative stress markers were observed. Furthermore, tryptophan metabolism was up-regulated, resulting in accumulation of tryptophan metabolites associated with reactive oxygen species generation, suggesting the possibility of oxidative stress as a mechanism of nongenotoxic carcinogenesis. Finally, several metabolites related to liver function, kidney function, cell damage, and cell proliferation were altered by fenofibrate-induced toxicity at this dose.
Cigarette smoking is well-known to associate with accelerated skin aging as well as cardiovascular disease and lung cancer, in large part due to oxidative stress. Because metabolites are downstream of genetic variation, as well as transcriptional changes and post-translational modifications of proteins, they are the most proximal reporters of disease states or reversal of disease states. In this study, we explore the potential effects of commonly available oral supplements (containing antioxidants, vitamins and omega-3 fatty acids) on the metabolomes of smokers (n = 11) compared to non-smokers (n = 17). At baseline and after 12 weeks of supplementation, metabolomic analysis was performed on serum by liquid and gas chromatography with mass spectroscopy (LC-MS and GC-MS). Furthermore, clinical parameters of skin aging, including cutometry as assessed by three dermatologist raters blinded to subjects' age and smoking status, were measured. Long-chain fatty acids, including palmitate and oleate, decreased in smokers by 0.76-fold (P = 0.0045) and 0.72-fold (P = 0.0112), respectively. These changes were not observed in non-smokers. Furthermore, age and smoking status showed increased glow (P = 0.004) and a decrease in fine wrinkling (P = 0.038). Cutometry showed an increase in skin elasticity in smokers (P = 0.049) but not in non-smokers. Complexion analysis software (VISIA) revealed decreases in the number of ultraviolet spots (P = 0.031), and cutometry showed increased elasticity (P = 0.05) in smokers but not non-smokers. Additional future work may shed light on the specific mechanisms by which long-chain fatty acids can lead to increased glow, improved elasticity measures and decreased fine wrinkling in smokers' skin. Our study provides a novel, medicine-focused application of available metabolomic technology to identify changes in sera of human subjects with oxidative stress, and suggests that oral supplementation (in particular, commonly available antioxidants, vitamins and omega-3 fatty acids) affects these individuals in a way that is unique (compared to non-smokers) on a broad level.
Abstract Although cancer is well recognised as a genetic disease, there is an emerging awareness that many of these genetic mutations promote an established hallmark of tumour cells – metabolic reprogramming. And while the connection between oncogenic signalling and the metabolic reprogramming of tumour cells (in hindsight) is highly intuitive, how to expand on this knowledge and capitalise on it for therapeutic gain is yet to be fully actualised. An emerging opportunity to expand this possibility involves taking advantage of the fact that diverse genetic alterations in tumour cells converge to the shared features of metabolic reprogramming. Therefore, these features could offer a common means to target the tumour irrespective of the mutational status. However, in all likelihood, the most selective and efficacious treatments will emerge from combining data to specifically define the genetic and metabolic features of a tumour with modern genomic and metabolomic technologies. Conceptually, genotyping and metabotyping can be combined in an effort to define efficacious first line dual‐targeted combinations. Although there are many practical considerations and challenges to achieve this end, the premise will be described through a number of preclinical examples that begin to offer an illustration of this possibility. Key Concepts: Oncogenes and tumour suppressors directly regulate metabolic reprogramming. Metabolic reprogramming supports tumour energetics, biosynthesis and survival. Metabolic targets present viable options for therapeutic development. Global metabolite profiling provides knowledge into tumour signalling pathway dysregulation. Metabolic reprogramming contributes to therapeutic resistance/sensitivity. Understanding malignant cell metabolism affords greater insight into optimal drug combination strategies. Metabolomics combined with genotyping offers an opportunity to advance personalised cancer medicine.
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