Evidence map›Paper›PMID 35957894›Full record

ReviewFrontiers in oncology2022

Patient-derived rectal cancer organoids-applications in basic and translational cancer research.

Yumeng Yan, Io Hong Cheong, Peizhan Chen, Xiaoguang Li, Xianli Wang, Hui Wang

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.3field-weighted citation impact, top 41% 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

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Review
  2. Review
  3. 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

6 authors at 2 institutions in 1 country.

Yumeng YanSchool of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Io Hong CheongSchool of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Peizhan ChenSchool of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Xiaoguang LiSchool of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Xianli WangSchool of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Hui WangSchool of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Shanghai Jiao Tong University · CNState Key Laboratory of Oncogene and Related Genes · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Colorectal cancer (CRC) is one of the most commonly diagnosed cancers and among the leading causes of death in both men and women. Rectal cancer (RC) is particularly challenging compared with colon cancer as the treatment after diagnosis of RC is more complex on account of its narrow anatomical location in the pelvis adjacent to the urogenital organs. More and more existing studies have begun to refine the research on RC and colon cancer separately. Early diagnosis and multiple treatment strategies optimize outcomes for individual patients. However, the need for more accurate and precise models to facilitate RC research is underscored due to the heterogeneity of clinical response and morbidity interrelated with radical surgery. Organoids generated from biopsies of patients have developed as powerful models to recapitulate many aspects of their primary tissue, consisting of 3-D self-organizing structures, which shed great light on the applications in both biomedical and clinical research. As the preclinical research models for RC are usually confused with colon cancer, research on patient-derived RC organoid models enable personalized analysis of cancer pathobiology, organizational function, and tumor initiation and progression. In this review, we discuss the various applications of patient-derived RC organoids over the past two years in basic cancer biology and clinical translation, including sequencing analysis, drug screening, precision therapy practice, tumor microenvironment studies, and genetic engineering opportunities.

Indexed as

cancer modelingorganoidspatient-derivedprecision medicinerectal cancertreatment predictiontumor microenvironment

Identifiers

PMID35957894
PMCPMC9360321
OpenAlexW4287877396

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.