Evidence map›Paper›PMID 27086918›Full record

ArticleOncotarget2016

Programmed death-ligand 1 overexpression is a prognostic marker for aggressive papillary thyroid cancer and its variants.

Subrata Chowdhury, Joe Veyhl, Fatima Jessa, Olena Polyakova, Ahmed Alenzi, Christina MacMillan, Ranju Ralhan, Paul G Walfish

Open access · diamondAbstract readComparative Study
In one paragraph

Article in Oncotarget, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 112 papers, 8 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
112citing papers in PubMed, 8 pooled it
13.4field-weighted citation impact, top 1% 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

112 citing papers in PubMed, 8 syntheses or guidelines pooled it, 199 citations in OpenAlex.

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  17. Combination Targeted Therapy with Pembrolizumab and Lenvatinib in Progressive, Radioiodine-Refractory Differentiated Thyroid Cancers.Clinical cancer research : an official journal of the American Association for Cancer Research · 2024
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52 more citing papers are in PubMed but not listed here.

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 2 institutions in 1 country.

Subrata ChowdhuryAlex and Simona Shnaider Research Laboratory in Molecular Oncology, Mount Sinai Hospital, Toronto, Ontario, Canada.
Joe VeyhlAlex and Simona Shnaider Research Laboratory in Molecular Oncology, Mount Sinai Hospital, Toronto, Ontario, Canada.
Fatima JessaAlex and Simona Shnaider Research Laboratory in Molecular Oncology, Mount Sinai Hospital, Toronto, Ontario, Canada.
Olena PolyakovaAlex and Simona Shnaider Research Laboratory in Molecular Oncology, Mount Sinai Hospital, Toronto, Ontario, Canada.
Ahmed AlenziAlex and Simona Shnaider Research Laboratory in Molecular Oncology, Mount Sinai Hospital, Toronto, Ontario, Canada.
Christina MacMillanDepartment of Pathology and Laboratory Medicine, Mount Sinai Hospital, Toronto, Ontario, Canada.
Ranju RalhanAlex and Simona Shnaider Research Laboratory in Molecular Oncology, Mount Sinai Hospital, Toronto, Ontario, Canada.
Paul G WalfishAlex and Simona Shnaider Research Laboratory in Molecular Oncology, Mount Sinai Hospital, Toronto, Ontario, Canada.
Mount Sinai Hospital · CAUniversity of Toronto · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Programmed death-ligand 1(PD-L1) expression on tumor cells is emerging as a potential predictive biomarker in anti-PD-L1 directed cancer immunotherapy. We analyzed PD-L1 expression in papillary thyroid carcinoma (PTC) and its variants and determined its prognostic potential to predict clinical outcome in these patients. This study was conducted at an academic oncology hospital which is a prime referral centre for thyroid diseases. Immunohistochemical subcellular localization (IHC) analyses of PD-L1 protein was retrospectively performed on 251 archived formalin fixed and paraffin embedded (FFPE) surgical tissues (66 benign thyroid nodules and 185 PTCs) using a rabbit monoclonal anti-PD-L1 antibody (E1L3N, Cell Signaling Technology) and detected using VECTASTAIN rapid protocol with diaminobenzidine (DAB) as the chromogen. The clinical-pathological factors and disease outcome over 190 months were assessed; immunohistochemical subcellular localization of PD-L1 was correlated with disease free survival (DFS) using Kaplan Meier survival and Cox multivariate regression analysis. Increased PD-L1 immunostaining was predominantly localized in cytoplasm and occasionally in plasma membrane of tumor cells. Among all combined stages of PTC, patients with increased PD-L1 membrane or cytoplasmic positivity had significantly shorter median DFS (36 months and 49 months respectively) as compared to those with PD-L1 negative tumors (DFS, both 186 months with p < 0.001 and p < 0.01 respectively). Comparison of PD-L1+ and PD-L1- patients with matched staging showed increased cytoplasmic positivity in all four stages of PTC that correlated with a greater risk of recurrence and a poor prognosis, but increased membrane positivity significantly correlated with a greater risk of metastasis or death only in Stage IV patients. In conclusion, PD-L1 positive expression in PTC correlates with a greater risk of recurrence and shortened disease free survival supporting its potential application as a prognostic marker for PTC.

Indexed as

AdolescentAdultAgedAged, 80 and overB7-H1 AntigenBiomarkers, TumorCarcinoma, PapillaryChi-Square DistributionDisease-Free SurvivalDisease ProgressionFemaleGoiter, NodularHumansImmunohistochemistryKaplan-Meier EstimateMaleB7-H1 AntigenBiomarkers, TumorCD274 protein, humanbenign noduleprogrammed death-ligand 1protein biomarkerssubcellular localizationthyroid cancer

Identifiers

PMID27086918
PMCPMC5078015
OpenAlexW2341622444

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.