Evidence map›Paper›PMID 28977850›Full record

ArticleOncotarget2017

Integrated transcriptomic analysis of distance-related field cancerization in rectal cancer patients.

Honglin Guo, Weigen Zeng, Lin Feng, Xuexin Yu, Ping Li, Kaitai Zhang, Zhixiang Zhou, Shujun Cheng

Open access · diamondAbstract read
In one paragraph

Article in Oncotarget, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed
2.6field-weighted citation impact, top 11% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

34 citing papers in PubMed, 47 citations in OpenAlex.

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  16. Field cancerization in breast cancer.The Journal of pathology · 2022
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 3 institutions in 1 country.

Honglin GuoState Key Laboratory of Molecular Oncology, Department of Etiology and Carcinogenesis, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.
Weigen ZengDepartment of General Surgery, Beijing Chao-Yang Hospital, Capital Medical University, Beijing 100020, China.
Lin FengState Key Laboratory of Molecular Oncology, Department of Etiology and Carcinogenesis, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.
Xuexin YuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Ping LiState Key Laboratory of Molecular Oncology, Department of Etiology and Carcinogenesis, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.
Kaitai ZhangState Key Laboratory of Molecular Oncology, Department of Etiology and Carcinogenesis, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.
Zhixiang ZhouDepartment of Colorectal Surgery, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.
Shujun ChengState Key Laboratory of Molecular Oncology, Department of Etiology and Carcinogenesis, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.
Chinese Academy of Medical Sciences & Peking Union Medical College · CNCapital Medical University · CNHarbin Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Field cancerization (FC) occurs in various epithelial carcinomas, including colorectal cancer, which indicates that the molecular events in carcinogenesis might occur in normal tissues extending from tumors. However, the transcriptomic characteristics of FC in colorectal cancer (CRC) remain largely unexplored. To investigate the changes in gene expression associated with proximity to the tumor, we analyzed the global gene expression profiles of cancer tissues and histologically normal tissues taken at various distances from the tumor (1 cm, 5 cm and the proximal end of the resected sample) from 32 rectal cancer patients. Significantly differentially expressed genes related to the distance from the tumor were screened by linear mixed effects analysis using the lme4 package in R. The distance-related differentially expressed genes that were gradually up-regulated (n=302) or gradually down-regulated (n=568) from normal tissues to the tumor were used to construct protein-protein interaction (PPI) networks. Three subnetworks among the gradually up-regulated genes and four subnetworks among the gradually down-regulated genes were identified using the MCODE plugin in the Cytoscape software program. The most significantly enriched Gene Ontology (GO) biological process terms were "ribosome biogenesis", "mRNA splicing via spliceosome", and "positive regulation of leukocyte migration" for the gradually up-regulated subnetworks and "cellular calcium ion homeostasis", "cell separation after cytokinesis", "cell junction assembly", and "fatty acid metabolic process" for the gradually down-regulated subnetworks. Combined with the previously constructed multistep carcinogenesis model used for the analysis, 50.59% of the genes in the subnetworks (43/85) displayed identical changes in expression from normal colon tissues to adenoma and colon cancer. We focused on the 7 genes associated with fatty acid metabolic processes in the distance-related down-regulated subnetwork. Survival analysis of patients in the CRC dataset from The Cancer Genome Atlas (TCGA) revealed that higher expression of these 7 genes, especially CPT2, ACAA2 and ACADM, was associated with better prognosis (

Indexed as

CPT2CRCfatty acid metabolismfield cancerizationribosome biogenesis

Identifiers

PMID28977850
PMCPMC5617410
OpenAlexW2617184869

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.