Chemotherapeutic agents for pancreatic ductal adenocarcinoma (PDAC) are highly toxic and induce severe side effects to patients. We wanted to promote minimally invasive precision immuno-oncology interventions by bioinformatics methods, by identifying a pool of biomarkers which would predict the therapeutic efficacy prior to the administration of gemcitabine. Six PDAC patients undergoing gemcitabine treatment were stratified in two groups based on disease progression: stable disease (pre-SD) and progressive disease (pre-PD). Peripheral blood was collected before gemcitabine treatment for all PDAC patients and blood RNA used for gene expression analysis. We filtered 20,356 genes and performed BrB-ArrayTools Class Comparison analysis which allowed the identification of 1489 upregulated genes in the group of pre-SD (downregulated in group pre-PD). These genes were mostly associated to T lymphocytes immune response (Metacore Pathways Maps analysis). We performed a second Geneset Class Comparison Enrichment Analysis; the resultant genes were combined with the genes included in the top Metacore Pathways Maps, and we obtained a pool of highly differentially expressed genes predicting the efficacy of anti-tumor immune response (膵癌・胆道系癌の化学療法剤の奏効性を血液遺伝子発現によって予測する奏効性予測マーカー、及び奏効性予測キット [Translated title: Markers and kits for predicting the response to chemotherapeutic agents for pancreatic and biliary tract cancers by blood gene expression]; Patent number: JP 2021-126107; 2021) [1]. The key biological processes associated to a favorable prognosis (pre-SD group) were related to T cell immunosurveillance, TCR alpha beta signaling pathway, Chemotaxis_CXCR3-A signaling and Cytokines/chemokines and receptors. The creation of a diagnostic kit based on bioinformatics tools for the identification of differentially expressed genes would predict the unresponsiveness to gemcitabine

The pathogenesis of non-alcoholic steatohepatitis (NASH) is still unclear and methods for prevention of the development of hepatocellular carcinoma (HCC) have not been established. We established an atherogenic and high-fat diet mouse model that develops hepatic steatosis, inflammation, fibrosis, and liver tumors at a high frequency. Using two NASH-HCC mouse models, we showed that peretinoin, an acyclic retinoid, significantly improved liver histology and reduced the incidence of liver tumors. We performed a microarray method that can comprehensively evaluate RNA expression using the peretinoin-treated mouse liver tissue. Through MetaCore software, which enables bioinformatic analysis using the expression data obtained by the microarray method, we discovered the possibility of inducing the activity of autophagy, a new physiological function of peretinoin. This was characterized by increased colocalized expression of microtubule-associated protein light chain 3B-II and lysosome-associated membrane protein 2, and increased autophagosome formation and autophagic flux. Among representative autophagy pathways, the autophagy related (Atg) 5-Atg12-Atg16L1 pathway was impaired; especially, Atg16L1 was repressed at both the mRNA and protein level. Decreased Atg16L1 mRNA expression was also found in the liver of patients with NASH according to disease progression. Thus, peretinoin prevents the progression of NASH and the development of HCC through activating the autophagy pathway by increased Atg16L1 expression, which is an essential regulator of autophagy and anti-inflammatory proteins. (Oncotarget, 2017, Vol. 8, (No. 25), pp: 39978-39993).