Prognostic Significance of Amino Acid Metabolism-Related Genes in Prostate Cancer Retrieved by Machine Learning

前列腺癌 表观遗传学 癌症 前列腺 疾病 医学 生物信息学 生物标志物 溶质载体族 生物 癌症研究 内科学 肿瘤科 基因 遗传学 运输机
作者
Ivana Samaržija,Koraljka Gall Trošelj,Paško Konjevoda
出处
期刊:Cancers [MDPI AG]
卷期号:15 (4): 1309-1309
标识
DOI:10.3390/cancers15041309
摘要

Prostate cancer is among the leading cancers according to both incidence and mortality. Due to the high molecular, morphological and clinical heterogeneity, the course of prostate cancer ranges from slow growth that usually does not require immediate therapeutic intervention to aggressive and fatal disease that spreads quickly. However, currently available biomarkers cannot precisely predict the course of a disease, and novel strategies are needed to guide prostate cancer management. Amino acids serve numerous roles in cancers, among which are energy production, building block reservoirs, maintenance of redox homeostasis, epigenetic regulation, immune system modulation and resistance to therapy. In this article, by using The Cancer Genome Atlas (TCGA) data, we found that the expression of amino acid metabolism-related genes is highly aberrant in prostate cancer, which holds potential to be exploited in biomarker design or in treatment strategies. This change in expression is especially evident for catabolism genes and transporters from the solute carrier family. Furthermore, by using recursive partitioning, we confirmed that the Gleason score is strongly prognostic for progression-free survival. However, the expression of the genes SERINC3 (phosphatidylserine and sphingolipids generation) and CSAD (hypotaurine generation) can refine prognosis for high and low Gleason scores, respectively. Therefore, our results hold potential for novel prostate cancer progression biomarkers.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
ZK999完成签到,获得积分10
刚刚
clay_park完成签到,获得积分10
1秒前
顺利紫山完成签到,获得积分10
1秒前
898完成签到 ,获得积分20
1秒前
SYLH应助金色热浪采纳,获得10
1秒前
2秒前
kiki完成签到 ,获得积分10
2秒前
金丝铁线完成签到,获得积分10
2秒前
爱听歌的冷安完成签到,获得积分10
3秒前
欧欧欧导发布了新的文献求助10
3秒前
4秒前
热情醉冬完成签到,获得积分10
4秒前
5秒前
JamesPei应助四毛采纳,获得10
5秒前
Majinheng完成签到,获得积分10
6秒前
Lee发布了新的文献求助10
6秒前
鱼柒完成签到 ,获得积分10
7秒前
7秒前
SYLH应助满意的契采纳,获得10
7秒前
xx完成签到,获得积分10
7秒前
泡泡鱼完成签到 ,获得积分10
7秒前
8秒前
爆米花应助默默月光采纳,获得10
8秒前
绝不延毕完成签到,获得积分10
8秒前
领导范儿应助邵恒采纳,获得10
9秒前
朴素的书琴完成签到,获得积分20
9秒前
超级李包包完成签到,获得积分10
9秒前
MeiLing完成签到,获得积分10
9秒前
xx发布了新的文献求助30
10秒前
10秒前
111完成签到,获得积分10
10秒前
Agernon应助柔弱的麦片采纳,获得10
11秒前
山月鹿发布了新的文献求助10
12秒前
调皮的勒完成签到,获得积分10
12秒前
cmq完成签到 ,获得积分10
12秒前
jzhou88完成签到,获得积分10
12秒前
dogsday完成签到,获得积分10
13秒前
CHyaa完成签到,获得积分10
13秒前
学术小白发布了新的文献求助10
14秒前
xml发布了新的文献求助10
14秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Mechanistic Modeling of Gas-Liquid Two-Phase Flow in Pipes 2500
Structural Load Modelling and Combination for Performance and Safety Evaluation 800
Conference Record, IAS Annual Meeting 1977 610
Virulence Mechanisms of Plant-Pathogenic Bacteria 500
白土三平研究 500
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3556269
求助须知:如何正确求助?哪些是违规求助? 3131813
关于积分的说明 9393417
捐赠科研通 2831860
什么是DOI,文献DOI怎么找? 1556519
邀请新用户注册赠送积分活动 726691
科研通“疑难数据库(出版商)”最低求助积分说明 716012