Evidence map›Paper›PMID 27488093›Full record

ArticleScientific reports2016

Predictive Immunohistochemical Markers Related to Drug Selection for Patients Treated with Sunitinib or Sorafenib for Metastatic Renal Cell Cancer.

Xin Ma, Lei Wang, Hongzhao Li, Yu Zhang, Yu Gao, Gang Guo, Kan Liu, Qingyu Meng, Chaofei Zhao, Dianjun Wang and 2 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
2.0field-weighted citation impact, top 13% 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

10 citing papers in PubMed, 19 citations in OpenAlex.

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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

12 authors at 1 institution in 1 country.

Xin MaDepartment of Urology, State Key Laboratory of Kidney Diseases, Chinese PLA General Hospital/Chinese PLA Medical Academy, Beijing, P. R. China.
Lei WangDepartment of Urology, State Key Laboratory of Kidney Diseases, Chinese PLA General Hospital/Chinese PLA Medical Academy, Beijing, P. R. China.
Hongzhao LiDepartment of Urology, State Key Laboratory of Kidney Diseases, Chinese PLA General Hospital/Chinese PLA Medical Academy, Beijing, P. R. China.
Yu ZhangDepartment of Urology, State Key Laboratory of Kidney Diseases, Chinese PLA General Hospital/Chinese PLA Medical Academy, Beijing, P. R. China.
Yu GaoDepartment of Urology, State Key Laboratory of Kidney Diseases, Chinese PLA General Hospital/Chinese PLA Medical Academy, Beijing, P. R. China.
Gang GuoDepartment of Urology, State Key Laboratory of Kidney Diseases, Chinese PLA General Hospital/Chinese PLA Medical Academy, Beijing, P. R. China.
Kan LiuDepartment of Urology, State Key Laboratory of Kidney Diseases, Chinese PLA General Hospital/Chinese PLA Medical Academy, Beijing, P. R. China.
Qingyu MengDepartment of Urology, State Key Laboratory of Kidney Diseases, Chinese PLA General Hospital/Chinese PLA Medical Academy, Beijing, P. R. China.
Chaofei ZhaoDepartment of Urology, State Key Laboratory of Kidney Diseases, Chinese PLA General Hospital/Chinese PLA Medical Academy, Beijing, P. R. China.
Dianjun WangDepartment of Pathology, Chinese PLA General Hospital/Chinese PLA Medical Academy, Beijing, P. R. China.
Zhigang SongDepartment of Pathology, Chinese PLA General Hospital/Chinese PLA Medical Academy, Beijing, P. R. China.
Xu ZhangDepartment of Urology, State Key Laboratory of Kidney Diseases, Chinese PLA General Hospital/Chinese PLA Medical Academy, Beijing, P. R. China.
Chinese PLA General Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Targeted drug decisions in metastatic renal cell carcinoma are exclusively made on the basis of clinical criteria. We investigated whether these biomarkers (HIF-1α, HIF-2α, CAIX, VEGF, VEGFR1, VEGFR2, VEGFR3, PDGFB, PDGFRA, PDGFRB, CD31, CD44, bcl-xL, KIT, p21, CXCR4, PTEN, (CSF)-1R, RET, and FLT-3) can predictive the different effects between sunitinib and sorafenib treatments and are available to guide targeted drug selection. We enrolled all patients who underwent nephrectomy with postoperative sunitinib- or sorafenib-treatment at our institution from 2007 to 2012. Immunohistochemical approach was applied to assess the potential differential effects of immunostainings between sunitinib- and sorafenib-treated groups. We found that patients with high HIF-2α, CD31 expression showed greater relative PFS and OS benefit and patients with high CAIX expression presented greater relative OS benefit from sunitinib than from sorafenib, patients with high VEGFR1 or PDGFRB expression levels exhibited worse relative PFS benefit from sunitinib than from sorafenib. Namely high HIF-2α, CD31, and CAIX expression levels along with low VEGFR1 and PDGFRB expression levels improved the benefit of sunitinib treatment compared with sorafenib treatment. These results can identify whether patients can benefit more from sunitinib or sorafenib for drug selection guidance, eventually with precision medicine.

Indexed as

AdultAntineoplastic AgentsBasic Helix-Loop-Helix ProteinsBiomarkers, TumorCarbonic Anhydrase IXCarcinoma, Renal CellEndothelial PAS Domain-Containing Protein 1FemaleHumansIndolesKidney NeoplasmsMaleMiddle AgedNephrectomyNiacinamidePhenylurea CompoundsAntineoplastic AgentsBasic Helix-Loop-Helix ProteinsBiomarkers, TumorCarbonic Anhydrase IXEndothelial PAS Domain-Containing Protein 1IndolesNiacinamidePDGFRB protein, humanPhenylurea CompoundsPlatelet Endothelial Cell Adhesion Molecule-1PyrrolesReceptor, Platelet-Derived Growth Factor betaSorafenibSunitinibVascular Endothelial Growth Factor Receptor-1

Identifiers

PMID27488093
PMCPMC4973254
OpenAlexW2485554651

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.