Cancer diagnostics have undergone a major transformation over the past two decades, shifting from late-stage diagnosis and generalized treatment toward earlier detection, molecular stratification, and personalized therapy. With this shift comes the need to detect clinically actionable biomarkers at increasingly low concentrations, while also supporting broader mutational profiling to expand access to molecularly matched therapies, and guide more precise treatment decisions.
As the oncology diagnostics landscape continues to evolve – supporting earlier detection, real-time monitoring, companion diagnostics and decentralized testing – quantitative PCR (qPCR) remains a foundational tool. Its combination of high analytical sensitivity, rapid turnaround time and cost-efficiency makes it uniquely suited for informing therapeutic decision-making at scale, especially in time-sensitive or resource-constrained settings.
What Sets qPCR Apart in Oncology Diagnostics?
qPCR’s strong multiplexing capability allows multiple clinically relevant mutations to be detected in a single reaction, without compromising sensitivity or speed. This makes it particularly well suited for oncology applications where actionable targets span several genes, and sample material is scarce. For example, in non-small cell lung cancer (NSCLC), multiplexed qPCR panels can simultaneously assess alterations in EGFR, KRAS, BRAF and ALK – delivering results faster and using less input material than sequential or panel-based next-generation sequencing (NGS) approaches. Solutions such as Biofidelity’s Aspyre Lung Reagents1 and the AmoyDx® Pan Lung Cancer PCR Panel2 showcase the strong clinical potential of multiplexed qPCR, with ongoing advancements expected to further expand regulatory clearance and clinical adoption. T his makes qPCR an attractive option for labs aiming to expand molecular coverage without the complexity, cost, or turnaround time associated with sequencing platforms. It is especially useful in tissue-limited cases, such as fine needle aspirates or cell-free DNA (cfDNA) from liquid biopsies, where maximizing data from minimal input is critical.
Fast Results with Minimal Infrastructure
Unlike sequencing platforms, which can take days to generate and analyze data, qPCR delivers clinically actionable results within hours. This rapid turnaround is especially valuable in time-sensitive scenarios, such as selecting targeted therapies or enrolling patients into mutation-driven clinical trials where quick decision-making is critical.
qPCR is also highly scalable and automation-friendly, supporting high-throughput testing without the need for significant capital investment or complex infrastructure. Its compatibility with standardized 96- or 384-well formats makes it ideal for a wide range of settings, from centralized reference labs to hospital-based molecular laboratories, and decentralized or resource-limited environments.
In addition, qPCR assays are generally easier to interpret, validate and implement within regulatory frameworks compared to more complex methods like next-generation sequencing (NGS).
Cost-Effective for Scalable Cancer Screening
While sequencing technologies have deepened our understanding of the cancer genome, qPCR remains a significantly more cost-effective option for targeted mutation detection. Test costs typically range from $50 to $200 – substantially less than the $300 to $3,000 price range of NGS.
This affordability makes qPCR especially well-suited for large-scale screening initiatives and routine clinical diagnostics, particularly in resource-conscious healthcare systems. For example, in India, qPCR serves as a cornerstone of HPV-based cervical cancer screening3, while in China, it underpins EGFR mutation testing across both major cancer centers and regional hospitals4.
With its unique combination of speed, cost-efficiency and scalability, qPCR has become a practical and widely deployable tool for population-scale cancer screening – expanding access to precision diagnostics without compromising analytical accuracy.
Key innovations in qPCR Chemistry include:
- Inhibitor Resistance: Next-generation polymerases and buffers are engineered to tolerate PCR inhibitors commonly found in clinical matrices, such as heparinized plasma, whole blood or FFPE-derived nucleic acids.
- Thermal Stability: Enzymes now withstand higher-temperature, faster-cycling protocols without loss of activity – enabling faster run times and greater assay reliability.
- Validate assays using post-COVID sample panels Validation protocols should now include testing with post-COVID clinical samples, especially those from individuals with long COVID or post-acute sequelae. These samples more accurately reflect the current immunological landscape and help developers identify and resolve potential sources of signal distortion that might not have been evident in pre-pandemic populations.
Meridian’s Blocking Solutions: Designed for Today’s Diagnostic Challenges
To support assay developers navigating these post-COVID challenges, Meridian Bioscience offers a range of high-performance immunoassay blockers specifically engineered to reduce interference from rheumatoid factor, HAMA, and other heterophilic antibodies. Meridian’s portfolio includes both traditional blockers—such as highly purified mouse IgG and human anti-mouse antibody blockers—as well as animal-free formulations designed to minimize variability and cross-reactivity. Meridian’s leading proprietary blocker, TRU Block™, is available in three different strengths for HAMA interference reduction. It is widely used in commercial diagnostic kits across ELISA, lateral flow, and chemiluminescent platforms, and can be easily integrated into assay development workflows. Whether you are developing new diagnostics or troubleshooting interference in existing formats, Meridian’s blocker solutions provide a reliable, scalable approach to maintaining assay accuracy in the evolving immune landscape.
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References:
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https://doi.org/10.3390/life13112121
2. Shapiro, S. C. (2021). Biomarkers in rheumatoid arthritis. Cureus, 13(5), e15063.
https://doi.org/10.7759/cureus.15063
3. Wang, E. Y., et al. (2021). Diverse functional autoantibodies in patients with COVID-19. Nature, 595(7866), 283–288.
https://doi.org/10.1038/s41586-021-03631-y
4. Joo, Y. B., et al. (2019). Respiratory viral infections and the risk of rheumatoid arthritis. Arthritis Research & Therapy, 21(1), 199. https://doi.org/10.1186/s13075-019-1977-9
5. Shelef, M., et al. (2024). Polyreactive rheumatoid factors in COVID-19 patients. Journal of Autoimmunity, 112, 102110https://doi.org/10.1016/j.jaut.2024.102110
6. Nayeemuddin, S. N., et al. (2024). Heterophilic interference of rheumatoid factor in TSH immunometric assay: A cross-sectional observational study. Indian Journal of Endocrinology and Metabolism, 28(1), 29–34.
https://doi.org/10.4103/ijem.ijem_99_23
7. Todd, D. J., et al. (2011). Erroneous augmentation of multiplex assay measurements in patients with rheumatoid arthritis due to heterophilic binding by serum rheumatoid factor. Arthritis & Rheumatism, 63(4), 894–903.
https://doi.org/10.1002/art.30213
8. Nakamura, M., et al. (1988). Human monoclonal rheumatoid factor-like antibodies from CD5 (Leu-1)+ B cells are polyreactive. Journal of Immunology, 140, 4180–4186.
9. Burastero, S. E., et al. (1988). Monoreactive high affinity and polyreactive low affinity rheumatoid factors are produced by CD5+ B cells from patients with rheumatoid arthritis. Journal of Experimental Medicine, 168(6), 1979–1992.
https://doi.org/10.1084/jem.168.6.1979
10. Gehin, J. E., et al. (2021). Rheumatoid factor and falsely elevated results in commercial immunoassays: Data from an early arthritis cohort. Rheumatology International, 41(9), 1657–1665.
https://doi.org/10.1007/s00296-021-04865-9
11. Kharlamova, N., et al. (2021). False positive results in SARS-CoV-2 serological tests for samples from patients with chronic inflammatory diseases. Frontiers in Immunology, 12, 666114.
https://doi.org/10.3389/fimmu.2021.666114