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Updated: May 9, 2026
Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies
Published on: April 11, 2016
Technical and implementation issues in using next-generation sequencing of cancers in clinical practice
D Ulahannan1, M B Kovac, P J Mulholland
1Wellcome Trust Centre for Human Genetics, Roosevelt Drive, Oxford OX3 7BN, UK. ulahannandan@yahoo.com
Abstract:
Next-generation sequencing (NGS) of cancer genomes promises to revolutionise oncology, with the ability to design and use targeted drugs, to predict outcome and response, and to classify tumours. It is continually becoming cheaper, faster and more reliable, with the capability to identify rare yet clinically important somatic mutations. Technical challenges include sequencing samples of low quality and/or quantity, reliable identification of structural and copy number variation, and assessment of intratumour heterogeneity. Once these problems are overcome, the use of the data to guide clinical decision making is not straightforward, and there is a risk of premature use of molecular changes to guide patient management in the absence of supporting evidence. Paradoxically, NGS may simply move the bottleneck of personalised medicine from data acquisition to the identification of reliable biomarkers. Standardised cancer NGS data collection on an international scale would be a significant step towards optimising patient care.
Insights
Next-generation sequencing (NGS) offers revolutionary potential in oncology for targeted therapies and tumor classification. Overcoming challenges in data interpretation is key to realizing personalized medicine through reliable biomarkers.
Area of Science:
- Genomic Medicine
- Oncology
- Bioinformatics
Background:
- Next-generation sequencing (NGS) is transforming cancer research and clinical practice.
- NGS enables the identification of somatic mutations for targeted drug development, outcome prediction, and tumor classification.
- The decreasing cost and increasing speed of NGS technologies facilitate broader application in oncology.
Purpose of the Study:
- To review the revolutionary potential of next-generation sequencing (NGS) in oncology.
- To identify the technical challenges and clinical decision-making hurdles associated with NGS data.
- To emphasize the need for standardized data collection and reliable biomarker identification for personalized medicine.
Main Methods:
- Review of current literature on next-generation sequencing in cancer genomics.
- Analysis of technical challenges in sequencing low-quality samples, structural variations, and intratumor heterogeneity.
- Discussion of the clinical utility and potential pitfalls of using NGS data for patient management.
Main Results:
- NGS provides unprecedented capability for identifying clinically significant somatic mutations.
- Technical challenges remain in sample quality, variation identification, and heterogeneity assessment.
- Clinical application of NGS data is complex, risking premature use without robust evidence.
Conclusions:
- NGS holds immense promise for revolutionizing cancer care through personalized medicine.
- Addressing technical and data interpretation challenges is crucial for clinical implementation.
- Standardized, international data collection and reliable biomarker discovery are essential next steps for optimizing patient care.
