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Related Concept Videos

Targeted Cancer Therapies02:57

Targeted Cancer Therapies

The targeted cancer therapies, also known as “molecular targeted therapies,” take advantage of the molecular and genetic differences between the cancer cells and the normal cells. It needs a thorough understanding of the cancer cells to develop drugs that can target specific molecular aspects that drive the growth, progression, and spread of cancer cells without affecting the growth and survival of other normal cells in the body.
There are several types of targeted therapies against specific...

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Related Experiment Video

Updated: Jul 16, 2026

Comparative Lesions Analysis Through a Targeted Sequencing Approach
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Comparative Lesions Analysis Through a Targeted Sequencing Approach

Published on: November 5, 2019

Off-Target-Based Tumor Fraction Estimation from Targeted Sequencing Shows Concordance with Orthogonal Methods Across

Samantha O Hasenleithner1,2, Shilpa Rao3, Jian Q Yu4

  • 1Division of Oncology, Department of Internal Medicine, Medical University of Graz, 8036 Graz, Austria.

International Journal of Molecular Sciences
|July 15, 2026
PubMed
Summary

Circulating tumor DNA fraction (ctFraction) estimation methods show strong concordance in advanced solid tumors. Fragle off-target offers an efficient strategy using existing targeted sequencing data for ctFraction analysis.

Keywords:
FraglecfDNAcirculating tumor fractionctDNActFractionfragmentomicichorCNAmVAFmean VAFmolecular response

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Testing Targeted Therapies in Cancer using Structural DNA Alteration Analysis and Patient-Derived Xenografts
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Testing Targeted Therapies in Cancer using Structural DNA Alteration Analysis and Patient-Derived Xenografts

Published on: July 25, 2020

Area of Science:

  • Oncology
  • Genomics
  • Biomarker Discovery

Background:

  • Circulating tumor DNA fraction (ctFraction) is a key biomarker for cancer assessment.
  • Accurate ctFraction estimation is crucial for monitoring treatment response.

Purpose of the Study:

  • To compare ctFraction estimates from ichorCNA, Fragle LP-WGS, Fragle off-target, and OTTER algorithms.
  • To evaluate the concordance and correlation of these methods with mean VAF (mVAF).

Main Methods:

  • Plasma samples from 33 patients with advanced solid tumors were analyzed.
  • ctFraction estimates were generated using four different computational methods.
  • Concordance and correlation analyses were performed, including longitudinal data from 20 patients.

Main Results:

  • Fragle off-target showed the highest concordance with Fragle LP-WGS (rho = 0.903).
  • All ctFraction estimates significantly correlated with mVAF, with ichorCNA showing the strongest association (rho = 0.910).
  • Changes in ctFraction (ΔctFraction) strongly correlated with mean ΔVAF for ichorCNA and Fragle off-target.

Conclusions:

  • Copy-number and fragmentomic-based ctFraction estimates are concordant in advanced solid tumors.
  • Fragle off-target provides an efficient method for ctFraction estimation from targeted sequencing data.
  • Further prospective studies are needed to confirm the clinical utility of Fragle off-target for treatment monitoring.