Evidence map›Paper›PMID 34532488›Full record

ReviewAnnals of translational medicine2021

A narrative review of tumor heterogeneity and challenges to tumor drug therapy.

Liang Zhu, Minlin Jiang, Hao Wang, Hui Sun, Jun Zhu, Wencheng Zhao, Qiyu Fang, Jia Yu, Peixin Chen, Shengyu Wu and 2 more

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Annals of translational medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 84 papers.

0numbers the graph read from it
0cells of the map it votes in
84citing 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

84 citing papers in PubMed.

  1. Article
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  6. Integrating multi-omics data for next-generation cancer research and precision medicine.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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  7. Article
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  11. Transcription-based comparison ofMicrobiology spectrum · 2026
    Article
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  14. Article
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  20. Article

24 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

12 authors.

Liang ZhuTongji University, Shanghai, China.
Minlin JiangTongji University, Shanghai, China.
Hao WangTongji University, Shanghai, China.
Hui SunDepartment of Medical Oncology, Shanghai Pulmonary Hospital, Tongji University Medical School Cancer Institute, Tongji University School of Medicine, Shanghai, China.
Jun ZhuDepartment of Medical Oncology, Shanghai Pulmonary Hospital, Tongji University Medical School Cancer Institute, Tongji University School of Medicine, Shanghai, China.
Wencheng ZhaoDepartment of Medical Oncology, Shanghai Pulmonary Hospital, Tongji University Medical School Cancer Institute, Tongji University School of Medicine, Shanghai, China.
Qiyu FangDepartment of Medical Oncology, Shanghai Pulmonary Hospital, Tongji University Medical School Cancer Institute, Tongji University School of Medicine, Shanghai, China.
Jia YuDepartment of Medical Oncology, Shanghai Pulmonary Hospital, Tongji University Medical School Cancer Institute, Tongji University School of Medicine, Shanghai, China.
Peixin ChenTongji University, Shanghai, China.
Shengyu WuTongji University, Shanghai, China.
Zixuan ZhengTongji University, Shanghai, China.
Yayi HeDepartment of Medical Oncology, Shanghai Pulmonary Hospital, Tongji University Medical School Cancer Institute, Tongji University School of Medicine, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo accurately evaluate tumor heterogeneity, make multidimensional diagnosis according to the causes and phenotypes of tumor heterogeneity, and assist in the individualized treatment of tumors.

backgroundTumor heterogeneity is one of the most essential characteristics of malignant tumors. In tumor recurrence, development, and evolution, tumor heterogeneity can lead to the formation of different cell groups with other molecular characteristics. Tumor heterogeneity can be characterized by the uneven distribution of tumor cell subsets of other genes between and within the disease site (spatial heterogeneity) or the time change of cancer cell molecular composition (temporal heterogeneity). The discovery of tumor targeting drugs has dramatically promoted tumor therapy. However, the existence of heterogeneity seriously affects the effect of tumor treatment and the prognosis of patients.

methodsThe literature discussing tumor heterogeneity and its resistance to tumor therapy was broadly searched to analyze tumor heterogeneity as well as the challenges and solutions for gene detection and tumor drug therapy.

conclusionsTumor heterogeneity is affected by many factors consist of internal cell factors and cell microenvironment. Tumor heterogeneity greatly hinders effective and individualized tumor treatment. Understanding the fickle of tumors in multiple dimensions and flexibly using a variety of detection methods to capture the changes of tumors can help to improve the design of diagnosis and treatment plans for cancer and benefit millions of patients.

Indexed as

diagnosisdrug therapyTumor heterogeneity

Identifiers

PMID34532488
PMCPMC8422119

What OpenQuestion holds

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Registered trials

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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.