Research Paper Volume 14, Issue 18 pp 7470—7504

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

Wen-Liang Yu1,2, , Zi-Chun Hua1,2,3, ,

  • 1 School of Biopharmacy, China Pharmaceutical University, Nanjing 211198, China
  • 2 Changzhou High-Tech Research Institute of Nanjing University and Jiangsu TargetPharma Laboratories Inc., Changzhou 213164, China
  • 3 School of Life Sciences, Nanjing University, Nanjing 210023, China

Received: April 26, 2022       Accepted: August 31, 2022       Published: September 19, 2022
How to Cite

Copyright: © 2022 Yu and Hua. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


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.


ALL: Acute lymphoblastic leukemia; AML: Acute myeloid leukemia; B-ALL: B cell acute lymphoblastic leukemia; BM: Bone marrow; BP: Biological processes; CAR T: Chimeric antigen receptors T; cBioPortal: cBio Cancer Genomics Portal; CC: Cellular components; C-index: Concordance index; CIBERSORTx: Cell-type Identification by Estimating Relative Subsets of RNA Transcripts x; CI: Confidence interval; DCs: dendritic cells; DEGs: Differentially expressed genes; ESTIMATE: Estimation of stromal and immune cells in malignant tumours using expression data; GEO: Gene Expression Omnibus; GO: Gene ontology; HR: Hazard ratio; HSPCs: Hematopoietic stem cells and progenitor cells; ISCIRG: Immune/stromal cell infiltration-related gene; KEGG: Kyoto encyclopedia of gene and genomes; KM: Kaplan-Meier; LASSO: Least absolute shrinkage and selection operator; ssGSEA: single-sample gene set-enrichment analysis; MF: Molecular functions; MPAL: Mixed-phenotype acute leukemia; NK: Natural killer; OS: Overall survival; PCA: Principal component analysis; PPI: Protein–protein interaction; T-ALL: T cell acute lymphoblastic leukemia; TARGET: Therapeutically applicable research to generate effective treatments; TCGA: The cancer genome atlas; t-SNE: t-distributed stochastic neighbor embedding.