Cargando…

Identification of immune and stromal cell infiltration-related gene signature for prognosis prediction in acute lymphoblastic leukemia

Acute lymphoblastic leukemia (ALL) is a common and life-threatening hematologic malignancy, its occurrence and progression are closely related to immune/stromal cell infiltration in the bone marrow (BM) microenvironment. However, no studies have described an immune/stromal cell infiltration-related...

Descripción completa

Detalles Bibliográficos
Autores principales: Yu, Wen-Liang, Hua, Zi-Chun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9550239/
https://www.ncbi.nlm.nih.gov/pubmed/36126190
http://dx.doi.org/10.18632/aging.204292
_version_ 1784805836391972864
author Yu, Wen-Liang
Hua, Zi-Chun
author_facet Yu, Wen-Liang
Hua, Zi-Chun
author_sort Yu, Wen-Liang
collection PubMed
description Acute lymphoblastic leukemia (ALL) is a common and life-threatening hematologic malignancy, its occurrence and progression are closely related to immune/stromal cell infiltration in the bone marrow (BM) microenvironment. However, no studies have described an immune/stromal cell infiltration-related gene (ISCIRG)-based prognostic signature for ALL. A total of 444 patients involving 437 bulk and 7 single-cell RNA-seq datasets were included in this study. Eligible datasets were searched and reviewed from the database of TCGA, TARGET project and GEO. Then an integrated bioinformatics analysis was performed to select optimal prognosis-related genes from ISCIRGs, construct a nomogram model for predicting prognosis, and assess the predictive power. After LASSO and multivariate Cox regression analyses, a seven ISCIRGs-based signature was proved to be able to significantly stratify patients into high- and low-risk groups in terms of OS. The seven genes were confirmed that directly related to the composition and status of immune/stromal cells in BM microenvironment by analyzing bulk and single-cell RNA-seq datasets. The calibration plot showed that the predicted results of the nomogram were consistent with the actual observation results of training/validation cohort. This study offers a reference for future research regarding the role of ISCIRGs in ALL and the clinical care of patients.
format Online
Article
Text
id pubmed-9550239
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Impact Journals
record_format MEDLINE/PubMed
spelling pubmed-95502392022-10-11 Identification of immune and stromal cell infiltration-related gene signature for prognosis prediction in acute lymphoblastic leukemia Yu, Wen-Liang Hua, Zi-Chun Aging (Albany NY) Research Paper Acute lymphoblastic leukemia (ALL) is a common and life-threatening hematologic malignancy, its occurrence and progression are closely related to immune/stromal cell infiltration in the bone marrow (BM) microenvironment. However, no studies have described an immune/stromal cell infiltration-related gene (ISCIRG)-based prognostic signature for ALL. A total of 444 patients involving 437 bulk and 7 single-cell RNA-seq datasets were included in this study. Eligible datasets were searched and reviewed from the database of TCGA, TARGET project and GEO. Then an integrated bioinformatics analysis was performed to select optimal prognosis-related genes from ISCIRGs, construct a nomogram model for predicting prognosis, and assess the predictive power. After LASSO and multivariate Cox regression analyses, a seven ISCIRGs-based signature was proved to be able to significantly stratify patients into high- and low-risk groups in terms of OS. The seven genes were confirmed that directly related to the composition and status of immune/stromal cells in BM microenvironment by analyzing bulk and single-cell RNA-seq datasets. The calibration plot showed that the predicted results of the nomogram were consistent with the actual observation results of training/validation cohort. This study offers a reference for future research regarding the role of ISCIRGs in ALL and the clinical care of patients. Impact Journals 2022-09-19 /pmc/articles/PMC9550239/ /pubmed/36126190 http://dx.doi.org/10.18632/aging.204292 Text en Copyright: © 2022 Yu and Hua. https://creativecommons.org/licenses/by/3.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/3.0/) (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Paper
Yu, Wen-Liang
Hua, Zi-Chun
Identification of immune and stromal cell infiltration-related gene signature for prognosis prediction in acute lymphoblastic leukemia
title Identification of immune and stromal cell infiltration-related gene signature for prognosis prediction in acute lymphoblastic leukemia
title_full Identification of immune and stromal cell infiltration-related gene signature for prognosis prediction in acute lymphoblastic leukemia
title_fullStr Identification of immune and stromal cell infiltration-related gene signature for prognosis prediction in acute lymphoblastic leukemia
title_full_unstemmed Identification of immune and stromal cell infiltration-related gene signature for prognosis prediction in acute lymphoblastic leukemia
title_short Identification of immune and stromal cell infiltration-related gene signature for prognosis prediction in acute lymphoblastic leukemia
title_sort identification of immune and stromal cell infiltration-related gene signature for prognosis prediction in acute lymphoblastic leukemia
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9550239/
https://www.ncbi.nlm.nih.gov/pubmed/36126190
http://dx.doi.org/10.18632/aging.204292
work_keys_str_mv AT yuwenliang identificationofimmuneandstromalcellinfiltrationrelatedgenesignatureforprognosispredictioninacutelymphoblasticleukemia
AT huazichun identificationofimmuneandstromalcellinfiltrationrelatedgenesignatureforprognosispredictioninacutelymphoblasticleukemia