Evidence map›Paper›PMID 23390614›Full record

ArticleFrontiers in oncology2013

Single-cell protein secretomic signatures as potential correlates to tumor cell lineage evolution and cell-cell interaction.

Minsuk Kwak, Luye Mu, Yao Lu, Jonathan J Chen, Kara Brower, Rong Fan

Abstract read
In one paragraph

Article in Frontiers in oncology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Enhanced TLR2 responses in multiple sclerosis.Clinical and experimental immunology · 2018
    Article
  6. Review
  7. Review
  8. Article
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

6 authors.

Minsuk KwakDepartment of Biomedical Engineering, Yale University New Haven, CT, USA.
Luye Mu
Yao Lu
Jonathan J Chen
Kara Brower
Rong Fan

Funding

The Cell-Of-Origin of Human CancersU54CA143798 · NCI · SLOAN-KETTERING INST CAN RESEARCH · PI MICHOR, FRANZISKA · 2009 to 2014
$11.2M
Integrated Microchips for Informative Diagnosis of Cancer-immune InteractionsR00CA136759 · NCI · YALE UNIVERSITY · PI FAN, RONG · 2010 to 2012
$707k
NCI NIH HHS R00 CA136759NCI NIH HHS U54 CA143798
6 · The paper itself

Abstract

Secreted proteins including cytokines, chemokines, and growth factors represent important functional regulators mediating a range of cellular behavior and cell-cell paracrine/autocrine signaling, e.g., in the immunological system (Rothenberg, 2007), tumor microenvironment (Hanahan and Weinberg, 2011), or stem cell niche (Gnecchi etal., 2008). Detection of these proteins is of great value not only in basic cell biology but also for diagnosis and therapeutic monitoring of human diseases such as cancer. However, due to co-production of multiple effector proteins from a single cell, referred to as polyfunctionality, it is biologically informative to measure a panel of secreted proteins, or secretomic signature, at the level of single cells. Recent evidence further indicates that a genetically identical cell population can give rise to diverse phenotypic differences (Niepel etal., 2009). Non-genetic heterogeneity is also emerging as a potential barrier to accurate monitoring of cellular immunity and effective pharmacological therapies (Cohen etal., 2008; Gascoigne and Taylor, 2008), but can hardly assessed using conventional approaches that do not examine cellular phenotype at the functional level. It is known that cytokines, for example, in the immune system define the effector functions and lineage differentiation of immune cells. In this article, we hypothesize that protein secretion profile may represent a universal measure to identify the definitive correlate in the larger context of cellular functions to dissect cellular heterogeneity and evolutionary lineage relationship in human cancer.

Indexed as

immunomonitoringintra-tumor heterogeneityprotein secretion profilesingle-cell analysistumor microenvironment

Identifiers

PMID23390614
PMCPMC3565185

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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.