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Table 1 Current status of genomic and related information

From: Integrating cancer genomic data into electronic health records

Technologies Applications Challenges
IHC Measuring gene overexpression Expensive
Flow cytometry Cell surface protein tagging by fluorophores, detects co-expression and loss of expression Limited spectral frequencies of fluorophores
FISH Copy number and rearrangement detection Only works on known targets, cannot detect novel aberrations
Polymerase chain reaction Confirmatory test and detection of minimal residual disease May only be scaled to a limited number of variants
Gene expression panels Production of a single score based on gene expression panel Commercially available products are based on older datasets
NGS panels Detection of somatic variants using mostly full-exon sequencing. NGS panels may vary greatly in size (25–500+ genes) Removing spurious results, identifying VUS, presenting results to clinicians
WES/WGS Sequencing of coding/all DNA, respectively High cost, computational complexity, handling VUS, handling incidental findings
Circulating cell-free tumor DNA Monitoring solid tumor heterogeneity, surveying difficult-to-reach tumors Not yet widely accepted, no consensus on technical approach, slow turnaround, high cost
Washable IHC Measuring protein expression with limited tissue sampling Expensive technique, still experimental
Mass cytometry Protein tagging by metal ion tags, detects co-expression and loss of expression Only applicable in cases with known targets, expensive, still experimental
Methylation panels Determines methylation patterns, which correlate with hypomethylating agent efficacy Slow adoption of these panels
  1. FISH fluorescence in situ hybridization, IHC immunohistochemistry, NGS next-generation sequencing, VUS variants of unknown/uncertain/undetermined significance, WES whole-exome sequencing, WGS whole-genome sequencing