Augmented antitumor activity of 5‐fluorouracil by double knockdown of MDM4 and MDM2 in colon and gastric cancer cells

Inactivation of the TP53 tumor suppressor gene is essential during cancer development and progression. Mutations of TP53 are often missense and occur in various human cancers. In some fraction of wild‐type (wt) TP53 tumors, p53 is inactivated by upregulated murine double minute homolog 2 (MDM2) and MDM4. We previously reported that simultaneous knockdown of MDM4 and MDM2 using synthetic DNA‐modified siRNAs revived p53 activity and synergistically inhibited in vitro cell growth in cancer cells with wt TP53 and high MDM4 expression (wtTP53/highMDM4). In the present study, MDM4/MDM2 double knockdown with the siRNAs enhanced 5‐fluorouracil (5‐FU)‐induced p53 activation, arrested the cell cycle at G1 phase, and potentiated the antitumor effect of 5‐FU in wtTP53/highMDM4 human colon (HCT116 and LoVo) and gastric (SNU‐1 and NUGC‐4) cancer cells. Exposure to 5‐FU alone induced MDM2 as well as p21 and PUMA by p53 activation. As p53‐MDM2 forms a negative feedback loop, enhancement of the antitumor effect of 5‐FU by MDM4/MDM2 double knockdown could be attributed to blocking of the feedback mechanism in addition to direct suppression of these p53 antagonists. Intratumor injection of the MDM4/MDM2 siRNAs suppressed in vivo tumor growth and boosted the antitumor effect of 5‐FU in an athymic mouse xenograft model using HCT116 cells. These results suggest that a combination of MDM4/MDM2 knockdown and conventional cytotoxic drugs could be a promising treatment strategy for wtTP53/highMDM4 gastrointestinal cancers

New approach to generating insights for aging research based on literature mining and knowledge integration

<div><p>The proportion of the elderly population in most countries worldwide is increasing dramatically. Therefore, social interest in the fields of health, longevity, and anti-aging has been increasing as well. However, the basic research results obtained from a reductionist approach in biology and a bioinformatic approach in genome science have limited usefulness for generating insights on future health, longevity, and anti-aging-related research on a case by case basis. We propose a new approach that uses our literature mining technique and bioinformatics, which lead to a better perspective on research trends by providing an expanded knowledge base to work from. We demonstrate that our approach provides useful information that deepens insights on future trends which differs from data obtained conventionally, and this methodology is already paving the way for a new field in aging-related research based on literature mining. One compelling example of this is how our new approach can be a useful tool in drug repositioning.</p></div

Heatmap providing an overview of 6,551 aging-related genes.

<p>Heatmaps provide overviews of the relationships between aging-related genes and aging-related causes and/or aging-related diseases. Aging-related causes are marked with an asterisk. Three aging-related causes and 11 aging-related diseases were selected for this paper. Out of our 7,416 aging related genes, 6,551 genes co-occurred with at least one of the 14 terms we selected. The vertical axis consists of all 6,551 genes.</p

Forty-five aging-related terms.

<p>Forty-five aging-related terms.</p

Heatmap providing an overview of sirtuin genes.

<p>The vertical axis consists of sirtuin genes SIRT1-SIRT7. This heatmap shows that SIRT2, SIRT3, and SIRT5, SIRT7, form two separate clusters. SIRT3 and SIRT5 affect the mitochondria, while SIRT 2 and SIRT7 affect the nucleus. Therefore, we can infer that these two clusters may work interchangeably.</p

Heatmap providing an overview of aging-related genes that are related to mitochondria.

<p>Out of our 7,416 aging related genes, only 512 genes are related to mitochondria. The vertical axis consists of the 474 mitochondria-related genes that co-occurred with at least one of 14 terms we selected.</p

Histogram of the 14 terms that were discarded.

<p>The blue bars show the number of genes that are included in the group of 7,416 aging-related genes identified by using 45 aging-related terms. The orange bars show the number of newly identified genes for each term, and the gray line represents the cumulative number of newly identified genes by the terms progressively.</p

Comparison of four public databases.

<p>Comparison of four public databases.</p

An example of a neighbor search.

<p>For the gene names of ALK, the following neighbor search words are generated: anaplastic, lymphoma, and CD246. In the first case (PubMed ID = 7772531), anaplastic and lymphoma occur. Therefore, this occurrence of ALK is considered to be positive. In the second case (PubMed ID = 1522609), none of these neighbor search words appear. Therefore, this occurrence is discarded.</p

Heatmap providing an overview of the top 1,000 genes.

<p>The vertical axis consists of the top 1,000 genes out of 6,551 aging-related genes. Although any number of aging-related genes can be placed on the vertical axis, in this case, 1,000 were chosen. These genes were selected on the basis of their co-occurrences with the aging-related causes and/or diseases on the horizontal axis in the highest number of publications.</p