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Related Concept Videos

Next-generation Sequencing03:00

Next-generation Sequencing

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The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features....
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RNA-seq03:21

RNA-seq

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RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
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Sanger Sequencing01:57

Sanger Sequencing

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DNA sequencing is a fundamental technique that is routinely used in the biological sciences. This method can be applied to a range of questions at different scales - from the sequencing of a cloned DNA fragment or the study of a mutation in a gene up to whole-genome sequencing. However, despite the widespread use of sequencing today, it was not until 1977 that Fredrick Sanger and his collaborators developed the chain-termination method to decode DNA sequences. It relies on the separation of a...
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Updated: Oct 5, 2025

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
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Computational methods and translational applications for targeted next-generation sequencing platforms.

Anisha Luthra1,2,3, Brooke Mastrogiacomo1,2,3, Shaleigh A Smith1,2

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Genes, Chromosomes & Cancer
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PubMed
Summary

Next-generation sequencing (NGS) is revolutionizing cancer care by enabling molecular subtype classification, biomarker discovery, and treatment monitoring. Computational tools and large datasets enhance the analysis of genomic data for personalized cancer medicine.

Keywords:
AACR GENIEclinical sequencingnext-generation sequencingprecision medicinetargeted sequencing

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Area of Science:

  • Oncology
  • Genomics
  • Bioinformatics

Background:

  • Next-generation sequencing (NGS) has become integral to cancer research and clinical practice over the last decade.
  • NGS applications include patient stratification, biomarker identification for therapy response, hereditary cancer risk assessment, and treatment monitoring.

Purpose of the Study:

  • To highlight the widespread adoption and diverse applications of NGS in clinical oncology.
  • To underscore the importance of computational advancements and data sharing in maximizing the utility of NGS data.

Main Methods:

  • Review of current clinical applications of targeted solid-tissue and blood-based NGS assays.
  • Discussion of the development of algorithms, pipelines, and knowledge bases for NGS data interpretation.
  • Emphasis on cross-institutional collaborations for creating large pooled datasets.

Main Results:

  • NGS facilitates patient stratification into molecular subtypes and identifies biomarkers for targeted therapies.
  • Development of computational tools and knowledge bases aids in linking genomic alterations to treatments and clinical trials.
  • Pooled datasets from collaborations offer insights into the genomics of rare cancers.

Conclusions:

  • NGS technologies are essential for personalized cancer care, improving diagnosis, treatment selection, and monitoring.
  • Advancements in bioinformatics and data sharing are critical for unlocking the full potential of genomic medicine in oncology.
  • Collaborative efforts are crucial for advancing our understanding of cancer genomics, particularly for rare malignancies.