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Construction of a novel gene-based model for prognosis prediction of clear cell renal cell carcinoma.
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Abstract:
Background:Clear cell renal cell carcinoma (ccRCC) comprises the majority of kidney cancer death worldwide, whose incidence and mortality are not promising. Identifying ideal biomarkers to construct a more accurate prognostic model than conventional clinical parameters is crucial. Methods:Raw count of RNA-sequencing data and clinicopathological data were acquired from The Cancer Genome Atlas (TCGA). Tumor samples were divided into two sets. Differentially expressed genes (DEGs) were screened in the whole set and prognosis-related genes were identified from the training set. Their common genes were used in LASSO and best subset regression which were performed to identify the best prognostic 5 genes. The gene-based risk score was developed based on the Cox coefficient of the individual gene. Time-dependent receiver operating characteristic (ROC) and Kaplan-Meier (KM) survival analysis were used to assess its prognostic power. GSE29609 dataset from GEO (Gene Expression Omnibus) database was used to validate the signature. Univariate and multivariate Cox regression were performed to screen independent prognostic parameters to construct a nomogram. The predictive power of the nomogram was revealed by time-dependent ROC curves and the calibration plot and verified in the validation set. Finally, Functional enrichment analysis of DEGs and 5 novel genes were performed to suggest the potential biological pathways. Results:PADI1, ATP6V0D2, DPP6, C9orf135 and PLG were screened to be significantly related to the prognosis of ccRCC patients. The risk score effectively stratified the patients into high-risk group with poor overall survival (OS) based on survival analysis. AJCC-stage, age, recurrence and risk score were regarded as independent prognostic parameters by Cox regression analysis and were used to construct a nomogram. Time-dependent ROC curves showed the nomogram performed best in 1-, 3- and 5-year survival predictions compared with AJCC-stage and risk score in validation sets. The calibration plot showed good agreement of the nomogram between predicted and observed outcomes. Functional enrichment analysis suggested several enriched biological pathways related to cancer. Conclusions:In our study, we constructed a gene-based model integrating clinical prognostic parameters to predict prognosis of ccRCC well, which might provide a reliable prognosis assessment tool for clinician and aid treatment decision-making in the clinic.
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Cancer Cell International
CANCER CELL INT
| 最新影响因子：6.429 | 期刊ISSN：1475-2867 | CiteScore：3.36 |
| 出版周期：Irregular | 是否OA：YES | 出版年份：2001 |
| 自引率：1.60% | 研究方向：ONCOLOGY- |
| 出版地区：ENGLAND |
SCI期刊coverage：Science Citation Index Expanded（科学引文索引扩展）
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Cancer Cell International 期刊简介
英文简介：
Cancer Cell International publishes articles on all aspects of cancer cell biology, originating largely from, but not limited to, work using cell culture techniques. The journal focuses on cancer studies reporting data from biological experiments performed on cells grown in vitro, in two- or three-dimensional systems, and/or in vivo (animal experiments). These types of experiments have provided crucial data in many fields, from cell proliferation and transformation, to epithelial-mesenchymal interaction, to apoptosis, and host immune response to tumors. Cancer Cell International also considers manuscripts reporting translational cancer research studies where in vitro discoveries are bridged to the clinic. As such, Cancer Cell International is interested in laboratory and animal studies reporting on novel biomarkers of tumor progression and response to therapy and on their applicability to human cancers. As an established journal, Cancer Cell International publishes many interesting articles from all over the world. It serves a particular need where wide communication of data is required, especially from countries that have a lower profile than many Western countries in biomedical publishing.
中文简介：（来自Google、百度翻译）
《癌细胞国际》发表了有关癌细胞生物学各个方面的文章，主要来源于但不限于使用细胞培养技术的工作。 该杂志关注癌症研究，报告了在体外、二维或三维系统和/或体内（动物实验）生长的细胞的生物学实验数据。这些类型的实验在许多领域提供了重要的数据，从细胞增殖和转化，到上皮间充质相互作用，到细胞凋亡，以及宿主对肿瘤的免疫反应。 《癌细胞国际》还考虑了报告转化性癌症研究的手稿，在这些研究中，体外发现被桥接到了临床。因此，国际癌症细胞组织（Cancer Cell International）对实验室和动物研究感兴趣，这些研究报告了肿瘤进展和治疗反应的新生物标志物，以及它们对人类癌症的适用性。 《癌细胞国际》作为一本公认的杂志，发表了许多来自世界各地的有趣文章。在需要广泛的数据交流的地方，特别是在生物医学出版方面，比许多西方国家的知名度要低的国家，它满足了特殊的需要。
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Cancer Cell International 期刊中科院评价数据
最新中科院分区
| 大类(学科) | 小类(学科) | 学科排名 |
| 医学 |
ONCOLOGY (肿瘤学) 3区 |
74/223 |
最新公布的期刊年发文量
| 年度总发文量 | 年度论文发表量 | 年度综述发表量 |
| 118 | 108 | 10 |
总被引频次：2825
特征因子：0.005500
影响因子趋势图
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Cancer Cell International 期刊CiteScore评价数据
最新CiteScore值
3.36
=
引文计数(2018)
文献(2015-2017)
=
1207次引用
359篇文献
文献总数（2014-2016）：359
被引比率：81%
SJR：1.13
SCLmago期刊等级衡量经过加权后的期刊受引用次数，引用次数的加权值由施引期刊的学科领域和声望(SJR)决定。
SNIP：0.912
每篇文章中来源出版物的标准化影响将实际受引用情况对照期刊所属学科领域中预期的受引用情况进行衡量。
CiteScore排名
| 序号 | 类别 | 排名 | 百分位 |
| 1 |
大类(学科)：Medicine
小类(学科)：Oncology
|
#82/325
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|
|
| 2 |
大类(学科)：Biochemistry, Genetics and Molecular Biology
小类(学科)：Genetics
|
#88/310
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|
|
| 3 |
大类(学科)：Biochemistry, Genetics and Molecular Biology
小类(学科)：Cancer Research
|
#69/191
点击查看排名表
|
|
CiteScore趋势图
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liting7111
审稿时间： 2个月内 接受率： 中等（50%命中）
投稿后，竟然分配了6个审稿人审稿。2020-05-11 -
liting7111
研究方向：肿瘤 乳腺癌
审稿时间： 2个月内 接受率： 中等（50%命中）
10月21号投稿，修了一次，12月10号就接收了，效率还是可以的，就是国人投稿很多。2020-03-01 -
liting7111
研究方向：肿瘤
审稿时间： 3个月内 接受率： 一般容易（75%命中）
我是在6月份投稿的，10月份要求修改，因为其他事情耽误了下，到一月接受了，交完费就出版了，后期速度很快。2020-02-16 -
liting7111
投稿到接受只花了两个月时间，感觉还可以啊。2020-01-28 -
liting7111
接受率： 中等（50%命中）
投稿后初审一个月，小修不到一周就接收了，杂志很给力！2020-01-25 -
liting7111
研究方向：妇科肿瘤
审稿时间： 2个月内 接受率： 中等（50%命中）
因为是英国杂志，要求很严，也很严谨。版面费要1270英镑，挺贵的。投稿后严格按照审稿人意见修改，由于补实验速度比较慢，导致投回时间很长，前后十个月，大修两次补了五个实验，小修五次。2019-07-03 -
liting7111
研究方向：肿瘤
投稿后一审一个月时间，给了小修，修回去意见两个月了，就没消息了，状态一直显示reviews completed，希望能快点接受。2019-06-05
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