Evidence map›Paper›PMID 27812028›Full record

ArticleScientific reports2016

Biopsy variability of lymphocytic infiltration in breast cancer subtypes and the ImmunoSkew score.

Adnan Mujahid Khan, Yinyin Yuan

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 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
2.1field-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

18 citing papers in PubMed, 36 citations in OpenAlex.

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  15. Spatial Architecture and Arrangement of Tumor-Infiltrating Lymphocytes for Predicting Likelihood of Recurrence in Early-Stage Non-Small Cell Lung Cancer.Clinical cancer research : an official journal of the American Association for Cancer Research · 2019
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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

2 authors at 1 institution in 1 country.

Adnan Mujahid KhanCentre for Evolution and Cancer, The Institute of Cancer Research, London, UK.
Yinyin YuanCentre for Evolution and Cancer, The Institute of Cancer Research, London, UK.
Institute of Cancer Research · GB

Funding

Wellcome Trust
6 · The paper itself

Abstract

The number of tumour biopsies required for a good representation of tumours has been controversial. An important factor to consider is intra-tumour heterogeneity, which can vary among cancer types and subtypes. Immune cells in particular often display complex infiltrative patterns, however, there is a lack of quantitative understanding of the spatial heterogeneity of immune cells and how this fundamental biological nature of human tumours influences biopsy variability and treatment resistance. We systematically investigate biopsy variability for the lymphocytic infiltrate in 998 breast tumours using a novel virtual biopsy method. Across all breast cancers, we observe a nonlinear increase in concordance between the biopsy and whole-tumour score of lymphocytic infiltrate with increasing number of biopsies, yet little improvement is gained with more than four biopsies. Interestingly, biopsy variability of lymphocytic infiltrate differs considerably among breast cancer subtypes, with the human epidermal growth factor receptor 2-positive (HER2+) subtype having the highest variability. We subsequently identify a quantitative measure of spatial variability that predicts disease-specific survival in HER2+ subtype independent of standard clinical variables (node status, tumour size and grade). Our study demonstrates how systematic methods provide new insights that can influence future study design based on a quantitative knowledge of tumour heterogeneity.

Indexed as

Biomarkers, TumorBiopsyBreast NeoplasmsDiagnosis, Computer-AssistedErb-b2 Receptor Tyrosine KinasesFemaleHumansLymphocytes, Tumor-InfiltratingPrognosisTissue Array AnalysisUser-Computer InterfaceBiomarkers, TumorERBB2 protein, humanErb-b2 Receptor Tyrosine Kinases

Identifiers

PMID27812028
PMCPMC5095894
OpenAlexW2548262845

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.