Journal Article

Whole-genome sequencing identifies novel predictors for hematopoietic cell transplant outcomes for patients with myelodysplastic syndrome: a CIBMTR study

Cutler, Corey, Dezern, Amy E., Nazha, Aziz, Spellman, Stephen, Gadalla, Shahinaz M., Bolon, Yung-Tsi, Auer, Paul, Carlson, Karen-Sue, Dong, Jing, Saber, Wael, Deeg, H. Joachim, Zhang, Tao

2023

Overview

Recurrent mutations in TP53, RAS pathway and JAK2 genes were shown to be highly prognostic of allogeneic hematopoietic cell transplant (alloHCT) outcomes in myelodysplastic syndromes (MDS). However, a significant proportion of MDS patients has no such mutations. Whole-genome sequencing (WGS) empowers the discovery of novel prognostic genetic alterations. We conducted WGS on pre-alloHCT whole-blood samples from 494 MDS patients. To nominate genomic candidates and subgroups that are associated with overall survival, we ran genome-wide association tests via gene-based, sliding window and cluster-based multivariate proportional hazard models. We used a random survival forest (RSF) model with build-in cross-validation to develop a prognostic model from identified genomic candidates and subgroups, patient-, disease- and HCT-related clinical factors. Twelve novel regions and three molecular signatures were identified with significant associations to overall survival. Mutations in two novel genes, CHD1 and DDX11 , demonstrated a negative impact on survival in AML/MDS and lymphoid cancer data from the Cancer Genome Atlas (TCGA). From unsupervised clustering of recurrent genomic alterations, genomic subgroup with TP53 /del5q is characterized with the significant association to inferior overall survival and replicated by an independent dataset. From supervised clustering of all genomic variants, more molecular signatures related to myeloid malignancies are characterized from supervised clustering, including Fc-receptor FCGRs, catenin complex CDHs and B-cell receptor regulators MTUS2 / RFTN1 . The RSF model with genomic candidates and subgroups, and clinical variables achieved superior performance compared to models that included only clinical variables.

• Publisher: BioMed Central,BioMed Central Ltd,Springer Nature B.V,BMC
• Subject: Allografts / Analysis / Artificial intelligence / B-cell receptor / Biomarkers / Cancer / Cancer Research / Correspondence / DEAD-box RNA Helicases - genetics / DNA Helicases - genetics / DNA sequencing / Fc receptors / Genes / Genome-Wide Association Study / Genomes / Genomics / Hematology / Hematopoietic Stem Cell Transplantation / Hematopoietic stem cells / Humans / Information sharing / Janus kinase 2 / Leukemia / Lymphocytes B / Malignancy / Medical prognosis / Medical research / Medicine / Medicine & Public Health / Medicine, Experimental / Mutation / Myelodysplastic syndrome / Myelodysplastic syndromes / Myelodysplastic Syndromes - genetics / Nucleotide sequencing / Oncology / p53 Protein / Patient outcomes / Post-transplant survival outcome / Prognosis / Sensitivity analysis / Stem cell transplantation / TP53 / Transplantation / Tumor proteins / WGS / Whole genome sequencing