Evidence map›Paper›PMID 25720324›Full record

ArticleModern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc2015

Beyond immune density: critical role of spatial heterogeneity in estrogen receptor-negative breast cancer.

Sidra Nawaz, Andreas Heindl, Konrad Koelble, Yinyin Yuan

Erratum issuedAbstract read
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In one paragraph

Article in Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 72 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
72citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

72 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Guideline
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  12. Quantile Index Biomarkers Based on Single-Cell Expression Data.Laboratory investigation; a journal of technical methods and pathology · 2023
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  17. Neoadjuvant Chemotherapy Is Associated with Altered Immune Cell Infiltration and an Anti-Tumorigenic Microenvironment in Resected Pancreatic Cancer.Clinical cancer research : an official journal of the American Association for Cancer Research · 2022
    Article
  18. Article
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  20. Effector memory cytotoxic CD3Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc · 2022
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12 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Sidra Nawaz1] Division of Molecular Pathology, The Institute of Cancer Research, London, UK [2] Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK [3] Centre for Molecular Pathology, Royal Marsden Hospital, London, UK.
Andreas Heindl1] Division of Molecular Pathology, The Institute of Cancer Research, London, UK [2] Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK [3] Centre for Molecular Pathology, Royal Marsden Hospital, London, UK.
Konrad Koelble1] Functional Genomics Laboratory, Institute of Cancer Research, London, UK [2] Department of Histopathology, The Royal Marsden Hospital, London, UK.
Yinyin Yuan1] Division of Molecular Pathology, The Institute of Cancer Research, London, UK [2] Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK [3] Centre for Molecular Pathology, Royal Marsden Hospital, London, UK.

Funding

Wellcome Trust 105104/Z/14/Z
6 · The paper itself

Abstract

The abundance of tumor-infiltrating lymphocytes has been associated with a favorable prognosis in estrogen receptor-negative breast cancer. However, a high degree of spatial heterogeneity in lymphocytic infiltration is often observed and its clinical implication remains unclear. Here we combine automated histological image processing with methods of spatial statistics used in ecological data analysis to quantify spatial heterogeneity in the distribution patterns of tumor-infiltrating lymphocytes. Hematoxylin and eosin-stained sections from two cohorts of estrogen receptor-negative breast cancer patients (discovery: n=120; validation: n=125) were processed with our automated cell classification algorithm to identify the location of lymphocytes and cancer cells. Subsequently, hotspot analysis (Getis-Ord Gi*) was applied to identify statistically significant hotspots of cancer and immune cells, defined as tumor regions with a significantly high number of cancer cells or immune cells, respectively. We found that the amount of co-localized cancer and immune hotspots weighted by tumor area, rather than number of cancer or immune hotspots, correlates with a better prognosis in estrogen receptor-negative breast cancer in univariate and multivariate analysis. Moreover, co-localization of cancer and immune hotspots further stratified patients with immune cell-rich tumors. Our study demonstrates the importance of quantifying not only the abundance of lymphocytes but also their spatial variation in the tumor specimen for which methods from other disciplines such as spatial statistics can be successfully applied.

Indexed as

AlgorithmsBreast NeoplasmsFemaleHumansImage Interpretation, Computer-AssistedKaplan-Meier EstimateLymphocytes, Tumor-InfiltratingProportional Hazards ModelsReceptors, EstrogenReceptors, Estrogen

Identifiers

PMID25720324

What OpenQuestion holds

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Registered trials

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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.