Evidence map›Paper›PMID 26820133›Full record

ArticleTumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine2016

Use of two gene panels for prostate cancer diagnosis and patient risk stratification.

Kefeng Xiao, Jinan Guo, Xuhui Zhang, Xiaoyan Feng, Heqiu Zhang, Zhiqiang Cheng, Heather Johnson, Jenny L Persson, Lingwu Chen

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In one paragraph

Article in Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.5field-weighted citation impact, top 30% 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

9 citing papers in PubMed, 16 citations in OpenAlex.

  1. Article
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  5. A 23-Gene Classifier urine test for prostate cancer prognosis.Clinical and translational medicine · 2021
    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

9 authors at 5 institutions in 3 countries.

Kefeng XiaoDepartment of Urology, Jinan University School of Medicine and Shenzhen People's Hospital, No. 1017, Dongmen Road North, Luo Hu District, Shenzhen, 518020, China.
Jinan GuoDepartment of Urology, Jinan University School of Medicine and Shenzhen People's Hospital, No. 1017, Dongmen Road North, Luo Hu District, Shenzhen, 518020, China.
Xuhui ZhangDepartment of Bio-Diagnosis, Institute of Basic Medical Sciences, 27, Taiping Road, Beijing, 100850, China.
Xiaoyan FengDepartment of Bio-Diagnosis, Institute of Basic Medical Sciences, 27, Taiping Road, Beijing, 100850, China.
Heqiu ZhangDepartment of Bio-Diagnosis, Institute of Basic Medical Sciences, 27, Taiping Road, Beijing, 100850, China.
Zhiqiang ChengDepartment of Pathology, Jinan University School of Medicine and Shenzhen People's Hospital, No. 1017, Dongmen Road North, Luo Hu District, Shenzhen, 518020, China.
Heather JohnsonOlympia Diagnostics, Inc., 640 W. California Ave, Suite 210, Sunnyvale, CA, 94086, USA.
Jenny L PerssonDepartment of Translational Medicine, Lund University, 205 02, Malmö, Sweden. jenny_l.persson@med.lu.se.
Lingwu ChenDepartment of Urology, The First Affiliated Hospital of Sun Yat-Sen University, No. 58 Zhongshan Er'Lu, Guangzhou, 510080, Guangdong Province, China. chenlingwu@hotmail.com.
Institute of Basic Medical Sciences of the Chinese Academy of Medical SciencesJinan University · CNLund University · SEOlympia Diagnostics (United States) · USSun Yat-sen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Currently, no ideal prostate cancer (PCa) diagnostic or prognostic test is available due to the lack of biomarkers with high sensitivity and specificity. There is an unmet medical need to develop combinations of multiple biomarkers which may have higher accuracy in detection of PCa and stratification of aggressive and indolent cancer patients. The aim of this study was to test two biomarker gene panels in distinguishing PCa from benign prostate and high-risk, aggressive PCa from low-risk, indolent PCa, respectively. We identified a five-gene panel that can be used to distinguish PCa from benign prostate. The messenger RNA (mRNA) expression signature of the five genes was determined in 144 PCa and benign prostate specimens from prostatectomy. We showed that the five-gene panel distinguished PCa from benign prostate with sensitivity of 96.59 %, specificity of 92.86 %, and area under the curve (AUC) of 0.992 (p < 0.0001). The five-gene panel was further validated in a 137 specimen cohort and showed sensitivity of 84.62 %, specificity of 91.84 %, and AUC of 0.942 (p < 0.0001). To define subtypes of PCa for treatment guidance, we examined mRNA expression signature of an eight-gene panel in 87 PCa specimens from prostatectomy. The signature of the eight-gene panel was able to distinguish aggressive PCa (Gleason score >6) from indolent PCa (Gleason score ≤6) with sensitivity of 90.28 %, specificity of 80.00 %, and AUC of 0.967 (p < 0.0001). This panel was further validated in a 158 specimen cohort and showed significant difference between aggressive PCa and indolent PCa with sensitivity of 92.57 %, specificity of 70.00 %, and AUC of 0.962 (p < 0.0001). Our findings in assessing multiple biomarkers in combination may provide new tools to detect PCa and distinguish aggressive and indolent PCa for precision and personalized treatment. The two biomarker panels may be used in clinical settings for accurate PCa diagnosis and patient risk stratification for biomarker-guided treatment.

Indexed as

Gene Expression ProfilingGenes, NeoplasmAdenocarcinomaAgedArea Under CurveBiomarkers, TumorDatasets as TopicDiagnosis, DifferentialHumansMaleMiddle AgedNeoplasm GradingNeoplasm InvasivenessNeoplasm ProteinsProstateProstatic HyperplasiaBiomarkers, TumorNeoplasm ProteinsRNA, MessengerRNA, NeoplasmAggressive prostate cancerIndolent prostate cancerProstate cancerProstate cancer biomarkersProstate cancer diagnosisProstate cancer prognosis

Identifiers

PMID26820133
OpenAlexW2291104978

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.