Chemoresistance in acute myeloid leukemia: An alternative single-cell RNA sequencing approach.

Our previous study demonstrated that myc, mitochondrial oxidative phosphorylation, mTOR, and stemness are independently responsible for chemoresistance in acute myeloid leukemia (AML) cells. This study aimed to identify potential mechanisms of chemoresistance of the "7 + 3" induction in AML by using a single-cell RNA sequencing (scRNA-seq) approach. In the present study, 13 untreated patients with de novo AML were enrolled and stratified into two groups: complete remission (CR; n = 8) and non-CR (n = 5). Single-cell RNA sequencing was used to analyze genetic profiles of 28,950 AML cells from these patients; results were validated using a previously published bulk RNA-seq dataset. Our study results showed chemoresistant AML cells had premature accumulation during early hematopoiesis. Hematopoietic stem cell-like cells from the non-CR group expressed more leukemic stem cell markers (CD9, CD82, IL3RA, and IL1RAP) than those from the CR group. Chemoresistant progenitor cells had impaired myeloid differentiation owing to early arrest of hematopoiesis. Notably, AML cells analyzed by scRNA-seq and bulk RNA-seq harbored a comparable myeloid lineage cell fraction, which internally validated our results. Using the TCGA database, our analysis demonstrated that patients with AML with higher expression of chemoresistant genetic markers (IL3RA and IL1RAP) had a worse overall survival (p < 0.01 for IL3RA; p < 0.05 for IL1RAP). In conclusion, AML cells responsive and resistant to the "7 + 3" induction were derived from a diverse cancerous hematopoietic stem cell population, as indicated by the specific genetic biomarkers obtained using scRNA-seq approach. Furthermore, arrest of hematopoiesis was shown to occur earlier in chemoresistant AML cells, furthering the current understanding of chemoresistance in AML.

A Novel Quality-Control Procedure to Improve the Accuracy of Rare Variant Calling in SNP Arrays.

Background: Single-nucleotide polymorphism (SNP) arrays are an ideal technology for genotyping genetic variants in mass screening. However, using SNP arrays to detect rare variants [with a minor allele frequency (MAF) of <1%] is still a challenge because of noise signals and batch effects. An approach that improves the genotyping quality is needed for clinical applications. Methods: We developed a quality-control procedure for rare variants which integrates different algorithms, filters, and experiments to increase the accuracy of variant calling. Using data from the TWB 2.0 custom Axiom array, we adopted an advanced normalization adjustment to prevent false calls caused by splitting the cluster and a rare het adjustment which decreases false calls in rare variants. The concordance of allelic frequencies from array data was compared to those from sequencing datasets of Taiwanese. Finally, genotyping results were used to detect familial hypercholesterolemia (FH), thrombophilia (TH), and maturity-onset diabetes of the young (MODY) to assess the performance in disease screening. All heterozygous calls were verified by Sanger sequencing or qPCR. The positive predictive value (PPV) of each step was estimated to evaluate the performance of our procedure. Results: We analyzed SNP array data from 43,433 individuals, which interrogated 267,247 rare variants. The advanced normalization and rare het adjustment methods adjusted genotyping calling of 168,134 variants (96.49%). We further removed 3916 probesets which were discordant in MAFs between the SNP array and sequencing data. The PPV for detecting pathogenic variants with 0.01%10,000 are available. The results demonstrated our procedure could perform correct genotype calling of rare variants. It provides a solution of pathogenic variant detection through SNP array. The approach brings tremendous promise for implementing precision medicine in medical practice.