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Investigation on the cellular mechanism of Prunetin evidenced through next generation sequencing and bioinformatic approaches against gastric cancer.

ABSTRACT: Gastric cancer is the common type of malignancy positioned at second in mortality rate causing burden worldwide with increasing treatment options. More accurate and reliable diagnostic methods/biomarkers are urgently needed. The application of transcriptomics technologies possesses the high efficiency of identifying key metabolic pathways and functional genes in cancer research. In this study, we performed a transcriptome analysis on Prunetin treated AGS cells. A total of 1,118 differentially expressed (DE) genes on Prunetin treated AGS cancer cells, among which 463 were up-regulated and 655 were down-regulated. Notably, around 40 genes were found to be related with necroptosis, among which 16 genes were found to be in close association with Receptor Interacting Protein Kinase (RIPK) family. Validation of the RIPK genes through GEPIA identified 8 genes (NRP1, MNX1, SSRP1, PRDX2, PLRG1, LGALS4, SNX5 and FXYD3) which are highly expressed in stomach cancer were significantly down-regulated in PRU treated samples. In conclusion, the sequencing data explores the expression of RIPK mediated genes through necroptosis signaling network in treating gastric cancer. The futuristic validations on the 8 genes as candidate biomarkers will offer a treatment approach against gastric cancer using PRU.

SUBMITTER: Vetrivel P

PROVIDER: S-EPMC9279440 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Accurate normalization of the gene expression assays, using housekeeping genes (HKGs), is critically necessary. To do so, selection of a proper set of HKGs for a specific experiment is of great importance. Despite many studies, there is no consensus about the suitable set of HKGs for implementing in the quantitative real-time PCR analyses of chicken tissues. A limited number of HKGs have been widely used. However, wide utilization of a little number of HKGs for all tissues is challenging. The emergence of high-throughput gene expression RNA-seq data has enabled the simultaneous comparison of the stability of multiple HKGs. Therefore, employing the average coefficient of variations of at least three datasets per tissue, we sorted all reliably expressed genes (REGs; with FPKM ≥ 1 in at least one sample) and introduced the top 10 most suitable and stable reference genes for each of the 16 chicken tissues. We evaluated the consistency of the results of five tissues using the same methodology on other datasets. Furthermore, we assessed 96 previously widely used HKGs (WU-HKGs) in order to challenge the accuracy of the previous studies. The New Tuxedo software suite was used for the main analyses. The results revealed novel, different sets of reference genes for each of the tissues with 17 common genes among the top 10 genes lists of 16 tissues. The results did disprove the suitability of WU-HKGs such as Actb, Ldha, Scd, B2m, and Hprt1 for any of the tissues examined. On the contrary, a total of 6, 13, 14, 23, and 32 validated housekeeping genes (V-HKGs) were discovered as the most stable and suitable reference genes for muscle, spleen, liver, heart, and kidney tissues, respectively. Although we identified a few new HKGs usable for multiple tissues, the selection of suitable HKGs is required to be tissue specific. The newly introduced reference genes from the present study, despite lacking experimental validation, will be able to contribute to the more accurate normalization for future expression analysis of chicken genes.

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Investigation on the cellular mechanism of Prunetin evidenced through next generation sequencing and bioinformatic approaches against gastric cancer.

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