Maximizing Biomarker Insights: Overcoming Sample Constraints in Oncology Research

In the rapidly evolving field of oncology research, biomarker testing has become a cornerstone for targeted therapy development and personalized treatment. However, a persistent challenge facing the industry is the limited quantity and quality of tumor samples available for comprehensive genomic profiling (CGP). A recent report highlights innovative approaches to maximize data output from minimal samples, potentially accelerating drug development and improving patient outcomes.

The Sample Quality Dilemma

Formalin-fixed paraffin-embedded (FFPE) tissue samples, while standard for specimen preservation, present significant challenges for extracting high-quality DNA and RNA needed for next-generation sequencing (NGS). Dr. Erin Newburn, Director of Field Applications at Labcorp, emphasizes the widespread nature of this issue: "Clinical trial samples from FFPE blocks often have low nucleic acid yields and degradation. This impacts extraction, library preparation and post-sequencing data processing."

Many clinical samples, particularly core needle biopsies, may yield only a few nanograms of usable material, limiting the ability to perform comprehensive genomic analyses. This constraint has hindered the broad adoption of NGS-based approaches that can detect diverse genomic alterations in a single assay.

Innovative Solutions for Sample Optimization

To address these limitations, laboratories are developing standardized workflows and adopting advanced technologies to maximize data output from challenging samples. Labcorp has pioneered automated dual extraction protocols to improve nucleic acid yield and quality from FFPE tissues, significantly reducing the number of quantity not sufficient (QNS) samples.

"Automated, standardized workflows significantly improve nucleic acid yield and quality," says Dr. Newburn. "This enables more successful genomic profiling and ultimately better patient outcomes."

Beyond extraction, quality control (QC) metrics play a crucial role in ensuring high-confidence variant calls. QC tools filter low-confidence data and minimize false results, providing reliable data to drive informed decisions in both clinical and research settings.

Comprehensive Genomic Profiling Strategies

To maximize variant detection from minimal input, researchers are turning to broad genomic solutions such as whole-exome sequencing (WES), whole-transcriptome sequencing (WTS), and large targeted panels. These comprehensive platforms allow biopharma teams to extract maximum data outputs for current and future biomarkers of interest from limited material.

Dr. Newburn adds, "Comprehensive platforms help biopharma teams maximize data outputs for current and future biomarkers of interest from limited material."

Key strategies for optimizing CGP in sample-constrained settings include:

1. Standardized extraction protocols for reproducibility and scalability
2. QC-informed library preparation to improve data quality and reduce rework
3. Advanced sequencing platforms that deliver insights from low-input samples

These approaches not only improve outcomes but also accelerate timelines and reduce costs—critical factors in both clinical and research environments.

As CGP becomes increasingly integral to oncology development, the ability to generate reliable data from limited samples is essential. Through innovations in extraction, sequencing, and analysis, companies like Labcorp are helping to unlock the full potential of precision oncology, one sample at a time. These advancements promise to drive more efficient drug development processes and, ultimately, deliver more targeted therapies to patients in need.