Evidence map›Paper›PMID 26916442›Full record

ArticleScientific reports2016

An Integrative Pharmacogenomic Approach Identifies Two-drug Combination Therapies for Personalized Cancer Medicine.

Yin Liu, Teng Fei, Xiaoqi Zheng, Myles Brown, Peng Zhang, X Shirley Liu, Haiyun Wang

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 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
2.7field-weighted citation impact, top 11% 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

5 citing papers in PubMed, 16 citations in OpenAlex.

  1. Pharmacogenomic andFrontiers in pharmacology · 2025
    Article
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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

7 authors at 3 institutions in 2 countries.

Yin LiuSchool of Life Science and Technology, Tongji University, Shanghai 200092, China.
Teng FeiDepartment of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA 02115, USA.
Xiaoqi ZhengDepartment of Mathematics, Shanghai Normal University, Shanghai 200234, China.
Myles BrownDepartment of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA 02115, USA.
Peng ZhangDepartment of Thoracic Surgery, Shanghai Pulmonary Hospital of Tongji University School of Medicine, Shanghai 200433, China.
X Shirley LiuDepartment of Biostatistics and Computational Biology, Dana-Faber Cancer Institute and Harvard School of Public Health, Boston, MA 02215, USA.
Haiyun WangSchool of Life Science and Technology, Tongji University, Shanghai 200092, China.
Dana-Farber Cancer Institute · USTongji University · CNShanghai Normal University · CN

Funding

Developing Informatics Technologies to Model Cancer Gene RegulationU01CA180980 · NCI · DANA-FARBER CANCER INST · PI LIU, XIAOLE SHIRLEY · 2013 to 2015
$1.1M
NCI NIH HHS 1U01 CA180980NCI NIH HHS U01 CA180980
6 · The paper itself

Abstract

An individual tumor harbors multiple molecular alterations that promote cell proliferation and prevent apoptosis and differentiation. Drugs that target specific molecular alterations have been introduced into personalized cancer medicine, but their effects can be modulated by the activities of other genes or molecules. Previous studies aiming to identify multiple molecular alterations for combination therapies are limited by available data. Given the recent large scale of available pharmacogenomic data, it is possible to systematically identify multiple biomarkers that contribute jointly to drug sensitivity, and to identify combination therapies for personalized cancer medicine. In this study, we used pharmacogenomic profiling data provided from two independent cohorts in a systematic in silico investigation of perturbed genes cooperatively associated with drug sensitivity. Our study predicted many pairs of molecular biomarkers that may benefit from the use of combination therapies. One of our predicted biomarker pairs, a mutation in the BRAF gene and upregulated expression of the PIM1 gene, was experimentally validated to benefit from a therapy combining BRAF inhibitor and PIM1 inhibitor in lung cancer. This study demonstrates how pharmacogenomic data can be used to systematically identify potentially cooperative genes and provide novel insights to combination therapies in personalized cancer medicine.

Indexed as

Drug Therapy, CombinationMolecular Targeted TherapyPrecision MedicineBiomarkers, TumorCell Line, TumorCell ProliferationChromonesDrug Resistance, NeoplasmDrug SynergismHumansImidazolesLung NeoplasmsMorpholinesProto-Oncogene Proteins B-rafProto-Oncogene Proteins c-pim-1RNA Interference2-(4-morpholinyl)-8-phenyl-4H-1-benzopyran-4-oneBiomarkers, TumorBRAF protein, humanChromonesImidazolesMorpholinesPIM1 protein, humanProto-Oncogene Proteins B-rafProto-Oncogene Proteins c-pim-1RNA, Small InterferingSB-590885

Identifiers

PMID26916442
PMCPMC4768263
OpenAlexW2321815569

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.