Evidence map›Paper›PMID 34474642›Full record

ArticleBioengineered2021

Single-cell RNA-seq reveals invasive trajectory and determines cancer stem cell-related prognostic genes in pancreatic cancer.

Xuechen Ren, Chengliang Zhou, Yu Lu, Fulin Ma, Yong Fan, Chen Wang

Open access · goldAbstract read
In one paragraph

Article in Bioengineered, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
1.7field-weighted citation impact, top 12% 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

16 citing papers in PubMed, 26 citations in OpenAlex.

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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 1 institution in 1 country.

Xuechen RenLanzhou University Second Hospital, Lanzhou, GS, China.
Chengliang ZhouLanzhou University Second Hospital, Lanzhou, GS, China.
Yu LuLanzhou University Second Hospital, Lanzhou, GS, China.
Fulin MaLanzhou University Second Hospital, Lanzhou, GS, China.
Yong FanLanzhou University Second Hospital, Lanzhou, GS, China.
Chen WangLanzhou University Second Hospital, Lanzhou, GS, China.ORCID 0000-0001-7801-833X
Lanzhou University Second Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pancreatic duct adenocarcinoma (PDAC) is an aggressive and lethal malignancy. Pancreatic cancer stem cells (PCSCs) are assumed to contribute to the initiation and invasion of PDAC. In this study, we performed single-cell RNA sequencing (scRNA-seq) analysis of PDAC tumor samples from patients and control pancreas tissues to reveal the transformation process of cancer stem cell (CSC)-like ductal cells into ductal cells with invasive potential and we screened out CSC-related genes (CRGs). Subsequently, we applied LASSO and Cox regression models to identify five CRGs with potential prognostic values and constructed a risk prognostic model using the Cancer Genome Atlas datasets. The risk models were verified using Gene Expression Omnibus datasets. Patients in the high-risk group had a significantly poor overall survival (Pvalue<0.0001), as illustrated by the Kaplan-Meier survival curve, and the area under the curve confirmed the accuracy of predictions by our risk model. Tumor mutation burden variations were used to further explore the differences between the two risk cohorts. In addition, the Human Protein Atlas was used to investigate the protein expression of five hub CRGs. In brief, we utilized scRNA-seq to reveal the invasive trajectory of ductal cells and identified crucial CRGs in PDAC, which may help predict patient survival and provide potential clinical therapeutic targets against CSCs.

Indexed as

Carcinoma, Pancreatic DuctalPancreatic NeoplasmsBiomarkers, TumorFemaleHumansMaleMiddle AgedNeoplastic Stem CellsPancreasPrognosisRNA-SeqSingle-Cell AnalysisTranscriptomeBiomarkers, Tumorcancer stem cellPancreatic cancerscRNA-seqsurvival prognosis

Identifiers

PMID34474642
PMCPMC8806718
OpenAlexW3196498477

What OpenQuestion holds

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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.