Multiplex Approach in Classification, Diagnosis, and Prognostication in Acute Myeloid Leukemia: An Experience from Tertiary Cancer Center in South India

Exploring the relationship between immune heterogeneity characteristic genes of rheumatoid arthritis and acute myeloid leukemia

BACKGROUND

People with autoimmune diseases are prone to cancer, and there is a close relationship between rheumatoid arthritis (RA) and acute myeloid leukemia (AML). The bone marrow (BM) is affected throughout the course of RA, with a variety of hematologic involvement. Hopes are pinned on rheumatoid arthritis research to obtain BM biomarkers for AML.

METHODS

Synovial transcriptome sequencing data for RA and osteoarthritis (OA), and single-cell sequencing data for RA and controls were obtained from the GEO database.Bone marrow sequencing data for AML patients and normal subjects were obtained from the UCSC Xena database. The final immune heterogeneity characteristics of RA were determined through ssGSEA analysis, gene differential expression analysis, fuzzy c-means clustering algorithm, and XGboost algorithm. Random Ferns classifiers (RFs) are used to identify new bone marrow markers for AML.

RESULTS

SELL, PTPRC, IL7R, CCR7, and KLRB1 were able to distinguish leukemia cells from normal cells well, with AUC values higher than 0.970.

CONCLUSION

Genes characterizing the immune heterogeneity of RA are associated with AML, and KLRBA may be a potential target for AML treatment.

Molecular Profiling of Kenyan Acute Myeloid Leukemia Patients

Acute myeloid leukemia (AML) is an infrequent disease, and it is associated with high morbidity and mortality. It harbors a unique configuration of cytogenetic abnormalities and molecular mutations that can be detected using microscopic and molecular methods respectively. These genetic tests are core elements of diagnosis and prognostication in high-income countries. They are routinely incorporated in clinical decision making, allowing for the individualization of therapy. However, these tests are largely inaccessible to most patients in Kenya and therefore no data has been reported on this group of patients. The main purpose of this study is to describe the cytogenetic and molecular abnormalities of acute myeloid leukemia patients seen at the hemato-oncology unit of Kenyatta National Hospital. A cross-sectional descriptive study was carried out over a 3-month period on ten patients with a diagnosis of AML. Social demographics and clinical data were collected through a study proforma. A peripheral blood sample was collected for conventional metaphase G-banding technique and next generation sequencing. Particularly, targeted DNA sequencing (Illumina myeloid panel) and whole exome sequencing (WES) were performed. Cytogenetic analysis failed in 10/10 cases. Targeted sequencing was successfully obtained in 8 cases, whereas WES in 7. Cytogenetic studies yielded no results. There were 20 mutations detected across 10 commonly mutated genes. All patients had at least one clinically relevant mutation. Based on ELN criteria, NGS identified three patients with high-risk mutations, affecting TP53 (n = 2) and RUNX1 (n = 1). One patient was classified as favorable (PML-RARA) while 4 were standard risk. However, WT1 mutations associated with unfavorable prognosis were recorded in additional 2 cases. WES showed concordant results with targeted sequencing while unveiling more mutations that warrant further attention. In conclusion, we provide the first molecular profiling study of AML patients in Kenya including application of advanced next generation sequencing technologies, highlighting current limitations of AML diagnostics and treatment while confirming the relevance of NGS in AML characterization.