Evidence map›Paper›PMID 31921642›Full record

ReviewFrontiers in oncology2019

Lung Cancer Heterogeneity in Modulation of Th17/IL17A Responses.

Dominique Armstrong, Cheng-Yen Chang, Donald R Lazarus, David Corry, Farrah Kheradmand

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in oncology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
0.5field-weighted citation impact, top 30% 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

10 citing papers in PubMed, 13 citations in OpenAlex.

  1. Review
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  10. Aptamers in Non-Small Cell Lung Cancer Treatment.Molecules (Basel, Switzerland) · 2020
    Review
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 at 1 institution in 1 country.

Dominique ArmstrongDepartment of Medicine, Baylor College of Medicine, Houston, TX, United States.
Cheng-Yen ChangDepartment of Medicine, Baylor College of Medicine, Houston, TX, United States.
Donald R LazarusDepartment of Medicine, Baylor College of Medicine, Houston, TX, United States.
David CorryDepartment of Medicine, Baylor College of Medicine, Houston, TX, United States.
Farrah KheradmandDepartment of Medicine, Baylor College of Medicine, Houston, TX, United States.
Baylor College of Medicine · US

Funding

Training Program in Translational Biology and Molecular MedicineT32GM088129 · NIGMS · BAYLOR COLLEGE OF MEDICINE · PI ROONEY, CLIONA M., VAN DEN VEYVER, IGNATIA B · 2010 to 2019
$3.0M
NIGMS NIH HHS T32 GM088129
6 · The paper itself

Abstract

The interplay between tumors and their immune microenvironment is critical for cancer development and progression. The discovery of tumor heterogeneity has provided a window into a complex interplay between tumors, their secreted products, and host immune responses at the cellular and molecular levels. Tumor heterogeneity can also act as a driving force in promoting treatment resistance and correlates with distinct tumor-mediated acquired immune responses. A prevailing question is how genetic aberrations in solid tumors can shape the immune landscape, resulting in pro-tumor or anti-tumor activities. Here we review evidence for clinical and pathophysiological mechanisms that underlie different types of non-small cell lung cancer (NSCLC) and provide new insights for future immunomodulatory-based therapies. Some of the more common driver mutations in NSCLC heterogeneity includes the opposing immune responses in oncogenic mutations in

Indexed as

IL17Aimmune landscapeimmunotherapylung cancerTh17tumor heterogeneitytumor microenvironment

Identifiers

PMID31921642
PMCPMC6914699
OpenAlexW2996589247

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.