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Comprehensive Genomic Profiling

Bring cancer into focus with comprehensive genomic profiling

Simultaneously assess multiple biomarkers from numerous tumor types in a single NGS assay

1. Detect Multiple Biomarkers in a Single Assay

NGS-based CGP assays provide nucleotide-level resolution of DNA or RNA across multiple genes, enabling identification of numerous types of genomic variants without a priori knowledge of specific mutations. Many of these variants include biomarkers associated with approved and developing therapies across multiple tumor types:

  • Single-nucleotide variants (SNVs) and insertions or deletions (indels)
  • Gene fusions and RNA splice variants
  • Copy-number variants (CNVs)
  • Tumor mutational burden (TMB)
  • Microsatellite Instability (MSI)

2. Consolidate Testing to Save Time and Precious Samples

CGP consolidates biomarker detection into a single multiplex assay, eliminating the need for sequential testing. With a single test, you can assess the most prevalent as well as rare biomarkers. By assessing all biomarkers at once, you may increase chances of finding a positive biomarker. This potentially provides faster results, limits the input of precious biopsy samples, and may reduce the need for rebiopsy1-3.

3. Identify Actionable Alterations

CGP can offer actionable results to help identify more effective therapeutic paths for cancer patients. When tissue biopsies are unavailable, CGP from liquid biopsy may provide helpful information about a tumor's genomic make-up. CGP using tissue and liquid biopsy together may reveal more insights into a tumor's composition.

Modeling studies have shown that by acquiring critical information with higher efficiency, CGP has demonstrated potential cost savings and shorter time to test result 2.

It is important for CGP to include DNA and RNA targets. RNA fusions are very important in some cancers, and you need to see the exact RNA fusion

Professor Xiaoyan Zhou
Reference LabLeader of Molecular Pathological Lab
Shanghai Cancer Center, Fudan University

Professor Andrew Beggs Discusses CGP

Professor Andrew Beggs of the University of Birmingham shares his point of view on comprehensive genomic profiling as an approach for assessing biomarkers for therapy selection and clinical trial enrollment.

How CGP Compares to Other NGS Methods

CGP vs Single Gene Assays

Single gene assays are limited to a single biomarker. Many times these assays do not cover the entire gene sequence, with the risk of missing important gene alterations.

CGP vs Targeted Panels

Targeted panels typically offer hotspot coverage of genes instead of the entire coding sequence. As a result they can miss important alterations.

A comprehensive single assay that assesses a wide range of biomarkers increases the chances of obtaining relevant information vs. targeted panels.

CGP vs Exome Sequencing

CGP can yield TMB results comparable to whole-exome sequencing at a lower cost.

Because whole-exome sequencing may be cost-prohibitive when developing a personalized medicine approach, there is interest in obtaining accurate TMB assessment with less sequencing.

There are a lot of very impressive novel therapies coming on the market with new fusions that we need to detect.

Ludovic Lacroix
Department of Medical Biology and Pathology
Institut de Cancerologie Gustave Roussy

Pan-Cancer Coverage

Comprehensive genomic profiling provides tumor-agnostic testing for hundreds of relevant biomarkers in a single assay, offering significant savings in sample, time, and cost.

Gene content is typically designed to be relevant across multiple tumor types, in contrast to older single-marker or hotspot assays that are often cancer-type specific.

Relevant Biomarkers for CGP Test Inclusion per Guidelines

Pan-Cancer Biomarkers      NTRK1        NTRK2        NTRK3        MSI        TMB
Lung Melanoma Colon Ovarian Breast Gastric Bladder Sarcoma
AKT1 BRAF AKT1 BRAF AKT1 BRAF MSH5 ALK
ALK CTNNB1 BRAF BRCA1 AR KIT PMS2 APC
BRAF GNA11 HRAS BRCA2 BRCA1 KRAS TSC1 BRAF
DDR2 GNAQ KRAS KRAS BRCA2 MET   CDK4
EGFR KIT MET PDGFRA ERBB2 MLH1   CTNNB1
ERBB2 MAP2K1 MLH1 FOXL2 FGFR1 PDGFRA   ETV6
FGFR1 NF1 MSH2 TP53 FGFR2 TP53   EWSR1
FGFR3 NRAS MSH6   PIK3CA     FOXO1
KRAS PDGFRA NRAS   PTEN     GLI1
MAP2K1 PIK3CA PIK3CA         KJT
MET PTEN PMS2         MDM2
NRAS TP53 PTEN         MYOD1
PIK3CA   SMAD4         NAB2
PTEN   TP53         NF1
RET             PAX3
TP53             PAX7
              PDGFRA
              PDGFRB
              SDHB
              SDHC
              SMARCB1
              TFE3
              WT1

The genes shown here are not an exhaustive list.

Consult with an expert to learn more about CGP

Featured Webinars & Podcasts

Enabling CGP from Liquid Biopsy Samples

Learn about critical workflow and bioinformatics considerations when consolidating biomarker testing into a panel that enables CGP from liquid biopsy samples in clinical trials.

Comprehensive Genomic Profiling

In this podcast episode, Dr. Brian Piening of the Providence Cancer Institute explains how NGS is changing the standard of care in oncology.

Enabling Scalable CGP from FFPE Samples

Experts discuss why they decided to implement in-house CGP, share analytical performance data, and provide details about their end-to-end workflow.

Molecular profiling for precision cancer therapies

 

Genomic and transcriptomic profiling expands precision cancer medicine: the WINTHER trial

 

Feasibility and utility of a panel testing for 114 cancer-associated genes: A hospital-based study

 

Related Solutions

ctDNA Sequencing

NGS offers the sensitivity researchers need to analyze low levels of circulating tumor DNA (ctDNA) in the bloodstream.

Immuno-Oncology Research

See how NGS can provide insights into immunotherapy response factors and tumor immune evasion mechanisms.

Cancer Whole-Genome Sequencing

Get a base-by-base view of the unique mutations and genomic alterations present in cancer tissue.

Cancer Exome Sequencing

Focus on assessing coding regions, which frequently contain mutations that affect tumor progression.

References
  1. Pennel AP, Mutebi A, Zheng-Yi Z, et al. Economic Impact of Next-Generation Sequencing Versus Single-Gene Testing to Detect Genomic Alterations in Metastatic Non–Small-Cell Lung Cancer Using a Decision Analytic Model. JCO Precis Oncol. 2019. doi.org/10.1200/PO.18.00356.
  2. National Comprehensive Cancer Network. https://www.nccn.org/professionals/physician_gls/default.aspx. Accessed March 25, 2019.
  3. Lindeman NI, et al. Guideline from the college of American pathologists, the international association for the study of lung cancer, and the association of molecular pathology: updated molecular testing guideline for the selection of lung cancer patients for treatment with targeted tyrosine kinase inhibitors. J Thor Onc. 2017;13(3):323-358.