Evidence map›Paper›PMID 35831404›Full record

ArticleScientific reports2022

Single-cell transcriptional pharmacodynamics of trifluridine in a tumor-immune model.

Tove Selvin, Erik Fasterius, Malin Jarvius, Mårten Fryknäs, Rolf Larsson, Claes R Andersson

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 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 48% 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, 3 citations in OpenAlex.

  1. Article
  2. Review
  3. 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

6 authors at 3 institutions in 1 country.

Tove SelvinDepartment of Medical Sciences, Uppsala University, 75185, Uppsala, Sweden. tove.selvin@medsci.uu.se.
Erik FasteriusNational Bioinformatics Infrastructure Sweden (NBIS), Stockholm University, Stockholm, Sweden.
Malin JarviusDepartment of Medical Sciences, Uppsala University, 75185, Uppsala, Sweden.
Mårten FryknäsDepartment of Medical Sciences, Uppsala University, 75185, Uppsala, Sweden.
Rolf LarssonDepartment of Medical Sciences, Uppsala University, 75185, Uppsala, Sweden.
Claes R AnderssonDepartment of Medical Sciences, Uppsala University, 75185, Uppsala, Sweden. claes.andersson@medsci.uu.se.
Uppsala University · SEScience for Life Laboratory · SEStockholm University · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding the immunological effects of chemotherapy is of great importance, especially now that we have entered an era where ever-increasing pre-clinical and clinical efforts are put into combining chemotherapy and immunotherapy to combat cancer. Single-cell RNA sequencing (scRNA-seq) has proved to be a powerful technique with a broad range of applications, studies evaluating drug effects in co-cultures of tumor and immune cells are however scarce. We treated a co-culture comprised of human colorectal cancer (CRC) cells and peripheral blood mononuclear cells (PBMCs) with the nucleoside analogue trifluridine (FTD) and used scRNA-seq to analyze posttreatment gene expression profiles in thousands of individual cancer and immune cells concurrently. ScRNA-seq recapitulated major mechanisms of action previously described for FTD and provided new insight into possible treatment-induced effects on T-cell mediated antitumor responses.

Indexed as

Colorectal NeoplasmsFrontotemporal DementiaHumansLeukocytes, MononuclearPyrrolidinesSingle-Cell AnalysisThymineTrifluridinePyrrolidinesThymineTrifluridine

Identifiers

PMID35831404
PMCPMC9279337
OpenAlexW4285394522

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.