Evidence map›Paper›PMID 31343810›Full record

ArticleCancer science2019

A novel pan-cancer biomarker plasma heat shock protein 90alpha and its diagnosis determinants in clinic.

Wei Liu, Jie Li, Ping Zhang, Qiaoyun Hou, Shi Feng, Lisheng Liu, Dawei Cui, Hubing Shi, Yan Fu, Yongzhang Luo

Open access · goldAbstract readMulticenter StudyValidation Study
In one paragraph

Article in Cancer science, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers.

0numbers the graph read from it
0cells of the map it votes in
51citing papers in PubMed
2.7field-weighted citation impact, top 9% 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

51 citing papers in PubMed, 71 citations in OpenAlex.

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  7. Review: Detection of Cancer Biomarkers from a Clinical Perspective.International journal of molecular sciences · 2025
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  19. Investigation ofMicroorganisms · 2024
    Article
  20. MicroRNA-495: a therapeutic and diagnostic tumor marker.Journal of molecular histology · 2023
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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

10 authors at 5 institutions in 1 country.

Wei LiuThe National Engineering Laboratory for Anti-Tumor Protein Therapeutics, Tsinghua University, Beijing, China.
Jie LiBeijing Chest Hospital, Capital Medical University, Beijing, China.
Ping ZhangThe National Engineering Laboratory for Anti-Tumor Protein Therapeutics, Tsinghua University, Beijing, China.
Qiaoyun HouThe National Engineering Laboratory for Anti-Tumor Protein Therapeutics, Tsinghua University, Beijing, China.
Shi FengThe National Engineering Laboratory for Anti-Tumor Protein Therapeutics, Tsinghua University, Beijing, China.
Lisheng LiuClinical Laboratory, Shandong Cancer Hospital, Jinan, China.
Dawei CuiThe National Engineering Laboratory for Anti-Tumor Protein Therapeutics, Tsinghua University, Beijing, China.
Hubing ShiLaboratory of Tumor Targeted and Immune Therapy, Clinical Research Center for Breast, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University and Collaborative Innovation Center, Chengdu, China.
Yan FuThe National Engineering Laboratory for Anti-Tumor Protein Therapeutics, Tsinghua University, Beijing, China.
Yongzhang LuoThe National Engineering Laboratory for Anti-Tumor Protein Therapeutics, Tsinghua University, Beijing, China.ORCID https://orcid.org/0000-0002-2325-2329
Center for Life Sciences · CNTsinghua University · CNCapital Medical University · CNShandong Tumor Hospital · CNSichuan University · CN

Funding

National Key R&D Program of China 2016YFC0906000National Key R&D Program of China 2016YFC0906003Protgen Ltd
6 · The paper itself

Abstract

A sensitive and specific diagnosis biomarker, in principle scalable to most cancer types, is needed to reduce the prevalent cancer mortality. Meanwhile, the investigation of diagnosis determinants of a biomarker will facilitate the interpretation of its screening results in clinic. Here we design a large-scale (1558 enrollments), multicenter (multiple hospitals), and cross-validation (two datasets) clinic study to validate plasma Hsp90α quantified by ELISA as a pan-cancer biomarker. ROC curve shows the optimum diagnostic cutoff is 69.19 ng/mL in discriminating various cancer patients from all controls (AUC 0.895, sensitivity 81.33% and specificity 81.65% in test cohort; AUC 0.893, sensitivity 81.72% and specificity 81.03% in validation cohort). Similar results are noted in detecting early-stage cancer patients. Plasma Hsp90α maintains also broad-spectrum for cancer subtypes, especially with 91.78% sensitivity and 91.96% specificity in patients with AFP-limited liver cancer. In addition, we demonstrate levels of plasma Hsp90α are determined by ADAM10 expression, which will affect Hsp90α content in exosomes. Furthermore, Western blotting and PRM-based quantitative proteomics identify that partial false ELISA-negative patients secret high levels of plasma Hsp90α. Mechanism analysis reveal that TGFβ-PKCγ gene signature defines a distinct pool of hyperphosphorylated Hsp90α at Theronine residue. In clinic, a mechanistically relevant population of false ELISA-negative patients express also higher levels of PKCγ. In sum, plasma Hsp90α is a novel pan-cancer diagnosis biomarker, and cancer diagnosis with plasma Hsp90α is particularly effective in those patients with high expression of ADAM10, but may be insufficient to detect the patients with low ADAM10 and those with hyperphosphorylated Hsp90α.

Indexed as

ADAM10 ProteinAdolescentAdultAmyloid Precursor Protein SecretasesAnimalsBiomarkers, TumorCell Line, TumorChildChild, PreschoolDatasets as TopicEnzyme-Linked Immunosorbent AssayExosomesFalse Negative ReactionsFemaleHSP90 Heat-Shock ProteinsHumansADAM10 ProteinADAM10 protein, humanAmyloid Precursor Protein SecretasesBiomarkers, TumorHSP90AA1 protein, humanHSP90 Heat-Shock ProteinsMembrane ProteinsThreonineADAM10heterogeneityHsp90αpan-cancer biomarkerPKCγ

Identifiers

PMID31343810
PMCPMC6726694
OpenAlexW2963720160

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.