Evidence map›Paper›PMID 29344893›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2018

Profiling Tumor Infiltrating Immune Cells with CIBERSORT.

Binbin Chen, Michael S Khodadoust, Chih Long Liu, Aaron M Newman, Ash A Alizadeh

Abstract read
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2,764 papers.

0numbers the graph read from it
0cells of the map it votes in
2,764citing papers in PubMed
–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

2,764 citing papers in PubMed.

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  13. Integrative bioinformatic and experimental analysis reveals prognostic and immunological roles of psychological stress-related genes in skin cutaneous melanoma.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
    Article
  14. Article
  15. Immune-stromal dysregulation and senescence in chronic spontaneous urticaria.The journal of allergy and clinical immunology. Global · 2026
    Article
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  17. Public Transcriptomic Data Mining for SCLC: From Candidate Ma rkers to Therapeutic Exploration.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
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2,704 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

5 authors.

Binbin ChenDepartment of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
Michael S KhodadoustDivision of Oncology, Department of Medicine, Stanford Cancer Institute, Stanford University, 875 Blake Wilbur Drive, Stanford, CA, 94305, USA.
Chih Long LiuDivision of Oncology, Department of Medicine, Stanford Cancer Institute, Stanford University, 875 Blake Wilbur Drive, Stanford, CA, 94305, USA.
Aaron M NewmanDivision of Oncology, Department of Medicine, Stanford Cancer Institute, Stanford University, 875 Blake Wilbur Drive, Stanford, CA, 94305, USA. amnewman@stanford.edu.
Ash A AlizadehDivision of Oncology, Department of Medicine, Stanford Cancer Institute, Stanford University, 875 Blake Wilbur Drive, Stanford, CA, 94305, USA. arasha@stanford.edu.

Funding

Leveraging innovative technologies in basic and clinical cancer researchT32CA009302 · NCI · STANFORD UNIVERSITY · PI LAURA D ATTARDI, Aaron M Newman · 1985 to 2026
$19.1M
Modeling the Molecular Determinants of Induced Anti-Tumor Immune Responses in Mantle Cell LymphomaU01CA194389 · NCI · STANFORD UNIVERSITY · PI ALIZADEH, ASH ARASH, DAVIS, MARK MORRIS · 2015 to 2019
$3.1M
Ultrasensitive Quantitation of Circulating Tumor DNAK99CA187192 · NCI · STANFORD UNIVERSITY · PI NEWMAN, AARON M · 2015 to 2016
$342k
NCI NIH HHS K99 CA187192NCI NIH HHS T32 CA009302NCI NIH HHS U01 CA194389
6 · The paper itself

Abstract

Tumor infiltrating leukocytes (TILs) are an integral component of the tumor microenvironment and have been found to correlate with prognosis and response to therapy. Methods to enumerate immune subsets such as immunohistochemistry or flow cytometry suffer from limitations in phenotypic markers and can be challenging to practically implement and standardize. An alternative approach is to acquire aggregative high dimensional data from cellular mixtures and to subsequently infer the cellular components computationally. We recently described CIBERSORT, a versatile computational method for quantifying cell fractions from bulk tissue gene expression profiles (GEPs). Combining support vector regression with prior knowledge of expression profiles from purified leukocyte subsets, CIBERSORT can accurately estimate the immune composition of a tumor biopsy. In this chapter, we provide a primer on the CIBERSORT method and illustrate its use for characterizing TILs in tumor samples profiled by microarray or RNA-Seq.

Indexed as

SoftwareTumor MicroenvironmentGene Expression ProfilingGene Expression Regulation, NeoplasticGenomicsHumansLymphocytes, Tumor-InfiltratingNeoplasmsSupport Vector MachineTranscriptomeCancer immunologyDeconvolutionGene expressionMicroarrayRNA-SeqSupport vector regression (SVR)TCGATumor heterogeneityTumor infiltrating leukocytes (TILs)Tumor microenvironment

Identifiers

PMID29344893
PMCPMC5895181

What OpenQuestion holds

Textmetadata
LicenceTDM
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.