Recently, we reported a chemical approach to generate pluripotent stem cells from mouse fibroblasts. However, whether chemically induced pluripotent stem cells (CiPSCs) can be derived from other cell types remains to be demonstrated. Here, using lineage tracing, we first verify the generation of CiPSCs from fibroblasts. Next, we demonstrate that neural stem cells (NSCs) from the ectoderm and small intestinal epithelial cells (IECs) from the endoderm can be chemically reprogrammed into pluripotent stem cells. CiPSCs derived from NSCs and IECs resemble mouse embryonic stem cells in proliferation rate, global gene expression profile, epigenetic status, self-renewal and differentiation capacity, and germline transmission competency. Interestingly, the pluripotency gene Sall4 is expressed at the initial stage in the chemical reprogramming process from different cell types, and the same core small molecules are required for the reprogramming, suggesting conservation in the molecular mechanism underlying chemical reprogramming from these diverse cell types. Our analysis also shows that the use of these small molecules should be fine-tuned to meet the requirement of reprogramming from different cell types. Together, these findings demonstrate that full chemical reprogramming approach can be applied in cells of different tissue origins and suggest that chemical reprogramming is a promising strategy with the potential to be extended to more initial types.
Altered metabolism is one of the hallmarks of cancers. Deregulation of ribose-5-phosphate isomerase A (RPIA) in the pentose phosphate pathway (PPP) is known to promote tumorigenesis in liver, lung, and breast tissues. Yet, the molecular mechanism of RPIA-mediated colorectal cancer (CRC) is unknown. Our study demonstrates a noncanonical function of RPIA in CRC. Data from the mRNAs of 80 patients' CRC tissues and paired nontumor tissues and protein levels, as well as a CRC tissue array, indicate RPIA is significantly elevated in CRC. RPIA modulates cell proliferation and oncogenicity via activation of β-catenin in colon cancer cell lines. Unlike its role in PPP in which RPIA functions within the cytosol, RPIA enters the nucleus to form a complex with the adenomatous polyposis coli (APC) and β-catenin. This association protects β-catenin by preventing its phosphorylation, ubiquitination, and subsequent degradation. The C-terminus of RPIA (amino acids 290 to 311), a region distinct from its enzymatic domain, is necessary for RPIA-mediated tumorigenesis. Consistent with results in vitro, RPIA increases the expression of β-catenin and its target genes, and induces tumorigenesis in gut-specific promotor-carrying RPIA transgenic zebrafish. Together, we demonstrate a novel function of RPIA in CRC formation in which RPIA enters the nucleus and stabilizes β-catenin activity and suggests that RPIA might be a biomarker for targeted therapy and prognosis. Author summaryThe pentose phosphate pathway generates NADPH, pentose, and ribose-5-phosphate by RPIA for nucleotide synthesis. Deregulation of RPIA is known to promote tumorigenesis in liver, lung, and breast tissues; however, the molecular mechanism of RPIA-mediated CRC is unknown. Here, we demonstrate a role of RPIA in CRC formation distinct from its role in these other tissues. We showed that RPIA is significantly elevated in CRC. RPIA increased cell proliferation and oncogenicity via activation of β-catenin, with RPIA entering the nucleus to form a complex with APC and β-catenin. Further investigation suggested that RPIA protects β-catenin by preventing its phosphorylation, ubiquitination, and subsequent degradation. In addition, the C-terminus of RPIA (amino acids 290 to 311), a portion of the protein not previously characterized, is necessary for RPIA-mediated tumorigenesis. Finally, we observed that transgenic expression of RPIA increases the expression of β-catenin and its target genes and induces tumorigenesis. Our findings suggest that RPIA can enter the nucleus and associate with APC/β-catenin, and suggest precise treatment of human CRC by targeting its nonenzymatic domain.
The primary type of liver cancer, hepatocellular carcinoma (HCC), has been associated with nonalcoholic steatohepatitis, diabetes, and obesity. Previous studies have identified some genetic risk factors, such as hepatitis B virus X antigens, overexpression of SRC oncogene, and mutation of the p53 tumor suppressor gene; however, the synergism between diet and genetic risk factors is still unclear. To investigate the synergism between diet and genetic risk factors in hepatocarcinogenesis, we used zebrafish with four genetic backgrounds and overfeeding or high-fat-diet-induced obesity with an omics-based expression of genes and histopathological changes. The results show that overfeeding and high-fat diet can induce obesity and nonalcoholic steatohepatitis in wild-type fish. In HBx, Src (p53-) triple transgenic zebrafish, diet-induced obesity accelerated HCC formation at five months of age and increased the cancer incidence threefold. We developed a global omics data analysis method to investigate genes, pathways, and biological systems based on microarray and next-generation sequencing (NGS, RNA-seq) omics data of zebrafish with four diet and genetic risk factors. The results show that two Kyoto Encyclopedia of Genes and Genomes (KEGG) systems, metabolism and genetic information processing, as well as the pathways of fatty acid metabolism, steroid biosynthesis, and ribosome biogenesis, are activated during hepatocarcinogenesis. This study provides a systematic view of the synergism between genetic and diet factors in the dynamic liver cancer formation process, and indicate that overfeeding or a high-fat diet and the risk genes have a synergistic effect in causing liver cancer by affecting fatty acid metabolism and ribosome biogenesis.
In head and neck squamous cell carcinoma (HNSCC), the incidence of mutation, which is the major cause of cetuximab resistance, is relatively rare compared with the other types of cancers, and the mechanism mediating acquired resistance is unclear compared with the driver gene mutation-mediated resistance. Here, we investigated the driver gene mutation-independent mechanism for cetuximab resistance in HNSCC. We used the -selected and-selected cetuximab-resistant sublines of HNSCC cell lines for investigating the mechanism of acquired resistance to cetuximab. Zebrafish model was applied for evaluating the synergistic effect of combinatory drugs for overcoming cetuximab resistance. The cetuximab-resistant HNSCC cells undergo a Snail-induced epithelial-mesenchymal transition. Mechanistically, Snail induces the expression of lymphotoxin-β (LTβ), a TNF superfamily protein that activates NF-κB, and protein arginine methyltransferase 1 (PRMT1), an arginine methyltransferase that methylates EGFR. LTβ interacts with methylated EGFR to promote its ligand-binding ability and dimerization. Furthermore, LTβ activates the NF-κB pathway through a LTβ receptor-independent mechanism. Combination of an EGFR tyrosine kinase inhibitor and a NF-κB inhibitor effectively suppressed cetuximab-resistant HNSCC and interfering with the EGFR-LTβ interaction reverses resistance. Our findings elucidate the mechanism of driver gene mutations-independent mechanism of acquired resistance to cetuximab in HNSCC and also provide potential strategies for combating cetuximab resistance. .
Background: Lymphovascular invasion (LOI), a key pathological feature of head and neck squamous cell carcinoma (HNSCC), is predictive of poor survival; however, the associated clinical characteristics and underlying molecular mechanisms remain largely unknown. Methods: We performed weighted gene co-expression network analysis to construct gene co-expression networks and investigate the relationship between key modules and the LOI clinical phenotype. Functional enrichment and KEGG pathway analyses were performed with differentially expressed genes. A protein-protein interaction network was constructed using Cytoscape, and module analysis was performed using MCODE. Prognostic value, expression analysis, and survival analysis were conducted using hub genes; GEPIA and the Human Protein Atlas database were used to determine the mRNA and protein expression levels of hub genes, respectively. Multivariable Cox regression analysis was used to establish a prognostic risk formula and the areas under the receiver operating characteristic curve (AUCs) were used to evaluate prediction efficiency. Finally, potential small molecular agents that could target LOI were identified with DrugBank.
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