Haematologic malignancies, such as leukaemia, lymphoma, and myeloproliferative disorders, represent a diverse group of cancers originating in the blood and bone marrow. Accurate diagnosis and timely monitoring are critical, not only for initiating appropriate therapy but also for predicting prognosis and guiding personalised treatment strategies. Over the past decade, molecular testing has transformed this landscape, offering unparalleled precision in detecting the genetic abnormalities that drive these diseases. 

Why molecular testing matters 

Traditional diagnostic approaches — morphology, immunophenotyping, and cytogenetics — remain foundational. However, they often lack the sensitivity to detect minimal residual disease (MRD) or subtle genetic changes that influence treatment response. Molecular assays bridge this gap by identifying specific gene fusions, mutations, and expression profiles that define disease subtypes. For instance: 

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Polymerase chain reaction (PCR) remains the workhorse for detecting known mutations and translocations. Quantitative PCR (qPCR) allows for the monitoring of disease burden, particularly in CML, where BCR–ABL1 transcript levels guide therapy adjustments. 

Next-generation sequencing (NGS) has expanded our capabilities, enabling the simultaneous analysis of multiple genes and the discovery of novel mutations. NGS panels for haematologic malignancies now include genes involved in epigenetic regulation, RNA splicing, and signalling pathways, offering a comprehensive view of disease biology. 

Digital PCR and droplet-based technologies further enhance sensitivity, making MRD detection possible at levels previously unattainable. This is crucial for early relapse prediction and treatment optimisation. 

Monitoring: beyond diagnosis 

Molecular monitoring is now standard in many haematologic cancers. In CML, achieving and maintaining a deep molecular response correlates with long-term remission. Similarly, MRD assessment in ALL influence decisions on therapy intensification or consideration of stem cell transplantation. 

The challenge lies in harmonising methodologies across laboratories to ensure consistent and reproducible results. International guidelines, such as those from the European LeukemiaNet (ELN), provide frameworks for standardisation, but effective implementation requires robust quality assurance. 

The future: AI and digital transformation 

Artificial intelligence (AI) is poised to revolutionise haematology. Machine learning algorithms can analyse complex genomic datasets, identify patterns, and predict outcomes with remarkable accuracy. 

AI-driven platforms may soon assist in: 

Moreover, AI can enhance NGS analysis by accelerating data processing and improving the detection of low-frequency variants. Combined with cloud-based solutions, this will enable real-time collaboration and decision-making across global networks. 

Conclusion 

The integration of molecular diagnostics into routine haematology practice has redefined standards of care. As technologies evolve — from PCR to NGS and AI-driven analytics — the future promises even greater precision, efficiency, and personalisation. For clinicians, laboratories, and patients alike, these advances translate into improved outcomes and a new era of targeted therapy. 

The journey ahead is exciting. Molecular testing is no longer merely a diagnostic tool; it is the cornerstone of modern haematology and a gateway to the future of cancer care.