Evidence map›Paper›PMID 27294005›Full record

ArticleAmerican journal of cancer research2016

The mRNA level of MLH1 in peripheral blood is a biomarker for the diagnosis of hereditary nonpolyposis colorectal cancer.

Hong Yu, Hui Li, Yongan Cui, Wei Xiao, Guihong Dai, Junxing Huang, Chaofu Wang

Abstract read
In one paragraph

Article in American journal of cancer research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
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  5. Review
  6. A NovelBioMed research international · 2018
    Article
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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

7 authors.

Hong YuDepartment of Pathology, Taizhou People's HospitalTaizhou 225300, Jiangsu Province, China; Department of Oncology, Taizhou People's HospitalTaizhou 225300, Jiangsu Province, China.
Hui LiDepartment of Pathology, Shanghai Medical College, Fudan University Shanghai 200032, China.
Yongan CuiDepartment of Oncology, Taizhou People's Hospital Taizhou 225300, Jiangsu Province, China.
Wei XiaoDepartment of Pathology, Taizhou People's Hospital Taizhou 225300, Jiangsu Province, China.
Guihong DaiDepartment of Pathology, Taizhou People's Hospital Taizhou 225300, Jiangsu Province, China.
Junxing HuangDepartment of Oncology, Taizhou People's Hospital Taizhou 225300, Jiangsu Province, China.
Chaofu WangDepartment of Pathology, Ruijin Hospital, Shanghai Jiaotong University School of Medicine Shanghai 200025, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hereditary nonpolyposis colorectal cancer (HNPCC) is caused by functional defects in mismatch repair (MMR) genes, including mutL homolog 1 (MLH1) and mutS homolog 2 (MSH2). This study aimed to assess whether the mRNA expression of MLH1 in peripheral blood could be used as a biomarkers for the diagnosis of HNPCC. The mRNA level of MLH1 was determined in 19 HNPCC families (46 members) using real-time quantitative polymerase chain reaction (qPCR). The mRNA levels of MLH1 in HNPCC were significantly lower than controls (P < 0.001). Receiver operating characteristic (ROC) curve showed a high diagnostic value of the mRNA level of MLH1 for the diagnosis of HNPCC with the area under curve of 0.858. At an optimal cut-off value (0.511), the mRNA level of MLH1 had a sensitivity of 81.3% and a specificity of 86.7% for distinguishing HNPCC from controls. In conclusion, the mRNA expression of MLH1 in peripheral blood may serve as a biomarker for the diagnosis of HNPCC.

Indexed as

diagnosisHereditary nonpolyposis colorectal cancermismatch repair geneMLH1mutation

Identifiers

PMID27294005
PMCPMC4889726

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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.