Comprehensive NGS Solutions for Hemato-Oncology Research and Clinical Applications

Hematologic malignancies are a group of diseases characterized by high heterogeneity, requiring comprehensive analysis integrating morphology, immunology, genetics, and molecular biology for diagnosis and treatment. As a modern molecular biology technology, Next-Generation Sequencing (NGS) offers advantages such as high throughput, high sensitivity, and low cost, making it an essential tool for investigating the molecular pathogenesis of blood tumors and guiding clinical management.

The Value of NGS in Diagnosis and Treatment of Hematologic Malignancies

1. Diagnosis and Classification

NGS-based mutation analysis plays a decisive role in the diagnosis and classification of multiple hematologic malignancies, including acute myeloid leukemia (AML) with recurrent genetic abnormalities, myeloproliferative neoplasms (MPN), myelodysplastic syndromes (MDS), hairy cell leukemia (HCL), and lymphoplasmacytic lymphoma/Waldenström macroglobulinemia (LPL/WM). In other entities, NGS serves as a powerful complementary diagnostic tool.

2. Prognostic Stratification

Genetic mutations form the molecular basis of prognostic assessment across hematologic cancers. NCCN guidelines define mutation-driven risk stratification systems for AML, while prognostic markers have also been established in MDS, MPN, ALL, CLL/SLL, LPL/WM, and LGLL. Ongoing research continues to expand prognostic insights into additional disease subtypes.

3. Therapy Guidance and Precision Medicine

NGS enables the identification of actionable mutations that guide targeted therapy selection. Clinically relevant targets include FLT3, IDH1/2, BRAF, and JAK–STAT pathway alterations.

In addition, mutation profiling informs drug resistance and treatment optimization. For example, TP53 mutations predict poor response to chemotherapy in CLL/SLL, MYD88 and CXCR4 mutations affect ibrutinib efficacy in LPL/WM, and ABL1 kinase domain mutations drive resistance to TKIs in CML and Ph+ ALL.

4. Minimal Residual Disease (MRD) Monitoring

Somatic mutations serve as stable molecular markers for MRD detection. While qPCR and flow cytometry remain standard approaches, deep NGS offers superior sensitivity and scalability for ultra-low–level disease monitoring.

5. Clonal Evolution Tracking

Hematologic malignancies evolve dynamically under therapeutic pressure. Longitudinal NGS monitoring enables detection of emerging clones and mutation shifts, supporting early intervention and adaptive treatment strategies.

Experimental Workflow of NGS in Hematologic Malignancies

From standardized sample collection and high-quality DNA extraction to optimized library preparation, sequencing, and rigorous bioinformatics analysis, a robust NGS workflow is essential to ensure reliable variant detection and clinical interpretation.

 Yeasen’s End-to-End NGS Workflow Solution

Yeasen provides a comprehensive portfolio of NGS reagents designed to support every step of hemato-oncology sequencing workflows, enabling high sensitivity, high uniformity, and reproducible results across diverse applications. 

Case Study: Application in HLA Typing

Item	Description
Application	HLA genotyping
Workflow	Multiplex PCR amplification followed by enzyme-based NGS library preparation
Reagents	Hieff™ NGS Multiplex PCR Master Mix (Cat. No. 17228); Hieff NGS™ OnePot Pro DNA Library Prep Kit V4 (Enzymatic) (Cat. No. 12972ES)
Experimental Conditions	50 ng DNA input; enzymatic reactions at 30 °C for 5–10 min; 5 PCR cycles
Results	Library yields of 1–2 µg, meeting requirements for downstream NGS analysis

(A).                                                               

(B).

Figure 1. Performance of Hieff™ NGS Multiplex PCR Master Mix (17228) and Yeasen Fragmentase-Based Library Prep in HLA sequencing.

(A) Agarose gel of seven HLA amplicons (1–10 kb) from a single multiplex PCR, showing uniform amplification and minimal primer dimers.

(B) Library size distribution after enzymatic fragmentation, demonstrating tight fragment control, high complexity, and optimal insert size.

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