Evidence map›Paper›PMID 27139883›Full record

ArticleGenome biology2016

Application of single-cell RNA sequencing in optimizing a combinatorial therapeutic strategy in metastatic renal cell carcinoma.

Kyu-Tae Kim, Hye Won Lee, Hae-Ock Lee, Hye Jin Song, Da Eun Jeong, Sang Shin, Hyunho Kim, Yoojin Shin, Do-Hyun Nam, Byong Chang Jeong and 3 more

Abstract read
In one paragraph

Article in Genome biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 127 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
127citing 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

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

  1. Pooled it
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  10. Single-cell Technology in Stem Cell Research.Current stem cell research & therapy · 2025
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  20. Application of single-cell RNA sequencing in head and neck squamous cell carcinoma.Chinese journal of cancer research = Chung-kuo yen cheng yen chiu · 2023
    Article

67 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

13 authors.

Kyu-Tae KimSamsung Genome Institute, Samsung Medical Center, Seoul, South Korea.
Hye Won LeeInstitute for Future Medicine, Samsung Medical Center, Seoul, South Korea.
Hae-Ock LeeSamsung Genome Institute, Samsung Medical Center, Seoul, South Korea.
Hye Jin SongDepartments of Anatomy and Cell Biology, Sungkyunkwan University School of Medicine, Seoul, South Korea.
Da Eun JeongDepartment of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences & Technology, Sungkyunkwan University, Seoul, South Korea.
Sang ShinDepartment of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences & Technology, Sungkyunkwan University, Seoul, South Korea.
Hyunho KimSchool of Mechanical Engineering, Korea University, Seoul, South Korea.
Yoojin ShinSchool of Mechanical Engineering, Korea University, Seoul, South Korea.
Do-Hyun NamDepartment of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences & Technology, Sungkyunkwan University, Seoul, South Korea.
Byong Chang JeongDepartments of Urology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.
David G KirschDepartments of Pharmacology and Cancer Biology, Duke University Medical Center, Durham, NC, USA.
Kyeung Min JooDepartments of Anatomy and Cell Biology, Sungkyunkwan University School of Medicine, Seoul, South Korea. kmjoo@skku.edu.
Woong-Yang ParkSamsung Genome Institute, Samsung Medical Center, Seoul, South Korea. woongyang.park@samsung.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIntratumoral heterogeneity hampers the success of marker-based anticancer treatment because the targeted therapy may eliminate a specific subpopulation of tumor cells while leaving others unharmed. Accordingly, a rational strategy minimizing survival of the drug-resistant subpopulation is essential to achieve long-term therapeutic efficacy.

resultsUsing single-cell RNA sequencing (RNA-seq), we examine the intratumoral heterogeneity of a pair of primary renal cell carcinoma and its lung metastasis. Activation of drug target pathways demonstrates considerable variability between the primary and metastatic sites, as well as among individual cancer cells within each site. Based on the prediction of multiple drug target pathway activation, we derive a combinatorial regimen co-targeting two mutually exclusive pathways for the metastatic cancer cells. This combinatorial strategy shows significant increase in the treatment efficacy over monotherapy in the experimental validation using patient-derived xenograft platforms in vitro and in vivo.

conclusionsOur findings demonstrate the investigational application of single-cell RNA-seq in the design of an anticancer regimen. The approach may overcome intratumoral heterogeneity which hampers the success of precision medicine.

Indexed as

AdultAnimalsCarcinoma, Renal CellCells, CulturedGene Expression ProfilingHumansKidney NeoplasmsLung NeoplasmsMaleMiceMolecular Targeted TherapySequence Analysis, RNASingle-Cell AnalysisDrug responsePatient-derived xenograftRenal cell carcinomaSingle cell analysisTumor heterogeneity

Identifiers

PMID27139883
PMCPMC4852434

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.