Evidence map›Paper›PMID 34693378›Full record

ArticlePatterns (New York, N.Y.)2021

Multiplex gene quantification as digital markers for extremely rapid evaluation of chemo-drug sensitivity.

Jiaqi Fan, Yilin Feng, Yifan Cheng, Zitian Wang, Haoran Zhao, Edgar A Galan, Quanxing Liao, Shuzhong Cui, Weijie Zhang, Shaohua Ma

Open access · goldAbstract read
In one paragraph

Article in Patterns (New York, N.Y.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.6field-weighted citation impact, top 35% 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

4 citing papers in PubMed, 7 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Article
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

10 authors at 3 institutions in 1 country.

Jiaqi FanTsinghua University, Shenzhen International Graduate School (SIGS), Shenzhen 518055, China.
Yilin FengTsinghua University, Shenzhen International Graduate School (SIGS), Shenzhen 518055, China.
Yifan ChengTsinghua University, Shenzhen International Graduate School (SIGS), Shenzhen 518055, China.
Zitian WangTsinghua University, Shenzhen International Graduate School (SIGS), Shenzhen 518055, China.
Haoran ZhaoTsinghua University, Shenzhen International Graduate School (SIGS), Shenzhen 518055, China.
Edgar A GalanTsinghua University, Shenzhen International Graduate School (SIGS), Shenzhen 518055, China.
Quanxing LiaoDepartment of Abdominal Surgery, Affiliated Cancer Hospital and Institute of Guangzhou Medical University, Guangzhou 510095, China.
Shuzhong CuiDepartment of Abdominal Surgery, Affiliated Cancer Hospital and Institute of Guangzhou Medical University, Guangzhou 510095, China.
Weijie ZhangDepartment of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China.
Shaohua MaTsinghua University, Shenzhen International Graduate School (SIGS), Shenzhen 518055, China.
Tsinghua–Berkeley Shenzhen Institute · CNGuangzhou Medical University · CNFirst Affiliated Hospital of Zhengzhou University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Current administrations for precision drug uses are limited in evaluation speed. Here, we propose the use of multiplex gene-based digital markers for the extremely rapid personalized prediction of individual sensitivity to cancer drugs. We first screen the transcriptional profiles by applying two to three gene filters and scoring genes by their impact on drug sensitivity and finalize the gene lists by K-nearest neighbors cross-validation. The digital markers are cancer type dependent, are composed of tens to hundreds of gene expressions, and are rapidly quantified by reverse transcription quantitative real-time PCR (qRT-PCR) within 1-3 h after tumor sampling. The area under the receiver operating characteristic curve reached 0.88 when testing the performance of digital markers on organoids derived from colorectal cancer patient tumors. The algorithm and corresponding graphic user interface were developed to demonstrate the promise of digital markers for extremely rapid drug recommendation.

Indexed as

chemo-drugdigital markerextremely rapid evaluationmultiplex gene quantificationpersonalized cancer medicine

Identifiers

PMID34693378
PMCPMC8515010
OpenAlexW3203354670

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.