Liquid Biopsy - CAM 273

National Cancer Institute (NCI) defines “liquid biopsy” as a test done on a sample of blood for the detection of cancer cells from a tumor that are circulating in the blood or for the detection of cell-free DNA pieces from tumor cells that are in the blood. Liquid biopsies are non-invasive blood tests since circulating tumor cells (CTCs) and cell-free tumor DNA (cfDNA) fragments are shed into the bloodstream from existing tumors and can be detected in blood. The presence of CTCs can be indicative of metastatic disease.

Regulatory Status 
At this time there is only one FDA-approved liquid biopsy test, which is a diagnostic for non-small lung cancer (NSCLC) was approved by the FDA in 2016. The test — cobas EGFR Mutation Test v2 from Roche Diagnostics is purported to detect epidermal growth factor receptor (EGFR) gene mutations in NSCLC patients. The test is intended as a companion diagnostic test for the cancer drug Tarceva (FDA, 2016), and a similar test for the T790M mutation has been produced by the same company. Additionally, many labs have developed specific tests that they must validate and perform in house. These laboratory-developed tests (LDTs) are regulated by the Centers for Medicare & Medicaid Services (CMS) as high-complexity tests under the Clinical Laboratory Improvement Amendments of 1988 (CLIA ’88).  As an LDT, the U.S. Food and Drug Administration has not approved or cleared this test; however, FDA clearance or approval is not currently required for clinical use.

Application of coverage criteria is dependent upon an individual’s benefit coverage at the time of the request

  1. For patients with Stage IIIB/IV non-­small cell lung cancer (NSCLC), liquid biopsy (plasma genotyping) is considered MEDICALLY NECESSARY in either of the following situations:
    1. At diagnosis: ­When results for EGFR single nucleotide variants (SNV) and insertions and deletions (indels); ALK and ROS1 rearrangements; and PD-L1 expression (by immunohistochemistry) are not available AND when tissue-based comprehensive somatic genomic profiling test (CGP) is infeasible (i.e., quantity not sufficient for tissue-based CGP or invasive biopsy is medically contraindicated); OR
    2. At progression: For patients progressing on or after chemotherapy or immunotherapy who have never been tested for EGFR SNVs and indels; and ALK and ROS1 rearrangements, and for whom tissue-­based CGP is infeasible (i.e., quantity not sufficient for tissue-­based CGP); OR For patients progressing on EGFR tyrosine kinase inhibitors (TKIs).

* If no genetic alteration is detected by plasma genotyping, or if circulating tumor DNA (ctDNA) is insufficient/not detected, tissue-based genotyping should be considered.

  1. Liquid biopsy test (plasma genotyping) for PIK3CA and/or for BRCA1/2 mutations is considered MEDICALLY NECESSARY for individuals diagnosed with cancer and being considered for PIK3CA or BRCA1/2 targeted therapy.
  2. Liquid biopsy (plasma genotyping) panel testing (*See Note 1 & Note 2) is considered MEDICALLY NECESSARY for individuals diagnosed with one of the following cancers:
    1. Breast cancer
    2. Colorectal cancer
    3. Non-small cell lung cancer (NSCLC)
  3. Repeat liquid biopsy testing (plasma genotyping) up to once per year is considered MEDICALLY NECESSARY for individuals in the above situations.

The following does not meet coverage criteria due to a lack of available published scientific literature confirming that the test(s) is/are required and beneficial for the diagnosis and treatment of a patient’s illness.

  1. Liquid biopsy testing, including but not limited to the use of cell-free DNA (cfDNA), circulating tumor cells (CTCs), and/or ribonucleoprotein complexes, for screening, detecting and monitoring any other malignancy or tumor is considered NOT MEDICALLY NECESSARY.
  2. Liquid biopsy panel testing (i.e., 5 or more genes) for all other situations is considered NOT MEDICALLY NECESSARY except for Tumor Mutational Burden (TMB) and/or Microsatellite Instability (MSI) testing (Note 2). 
  3. Analysis of PD-L1 by liquid biopsy is considered NOT MEDICALLY NECESSARY.
  4. Urinary liquid biopsy (i.e., use of cell-free DNA (“UcfDNA”) or circulating tumor DNA obtained in a urine sample for the screening, detection, and/or diagnosis of cancer), including but not limited to SelectMDX, is considered NOT MEDICALLY NECESSARY.
  5. Liquid biopsy testing — including but not limited to the use of cell-free DNA (cfDNA), circulating tumor cells (CTCs), and/or ribonucleoprotein complexes — on CSF samples is considered NOT MEDICALLY NECESSARY.
  6. The use of cell capture-enumeration assays of circulating tumor cells, including but not limited to the CELLSEARCH® CTC test, is considered NOT MEDICALLY NECESSARY. 

Note 1: For 5 or more gene tests being run on the same platform, such as multi-gene panel next generation sequencing, please refer to Reimbursement Policy.

Note 2: For guidance concerning Tumor Mutational Burden Testing (TMB) and/or Microsatellite instability (MSI) analysis please refer to the CAM 342 Microsatellite Instability and Tumor Mutational Burden Testing policy.

Table of Terminology




American Association for Clinical Chemistry


Anaplastic lymphoma receptor tyrosine kinase


The Association for Molecular Pathology


Androgen receptor


Androgen receptor splice variant 7


American Society of Clinical Oncology


B-Raf proto-oncogene


Breast cancer type 1 susceptibility gene


Breast cancer type 1/2 susceptibility gene


Breast cancer type 2 susceptibility gene


Cell adhesion molecule


College of American Pathologists




Cell-free tumour deoxyribonucleic acid


Comprehensive somatic genomic profiling

CLIA ’88

Clinical Laboratory Improvement Amendments of 1988


Cellular mesenchymal epithelial transition


Central nervous system


Colorectal cancer


Castration-resistant prostate cancer


Chinese Society of Clinical Oncology


Cerebrospinal fluid


Circulating Tumor Cells in cerebrospinal fluid


Circulating Tumor Cells


Circulating Tumor deoxyribonucleic acid


Cytotoxic T-lymphocyte-associated protein 3


Distal-less 1


Deoxyribonucleic acid


Digital rectal examination


European Association of Urology


Epidermal growth factor receptor


Epithelial cell adhesion molecule


Estrogen receptor-positive metastatic breast cancer


Excision repair cross-complementation group 1


Estrogen receptor-negative circulating tumor cells


European Society for Medical Oncology


European Society of Urogenital Radiology


Extracellular vesicle


Exosome ribonucleic acid


Food and Drug Administration


Formalin-fixed paraffin-embedded


Gastric cancer


Genomic deoxyribonucleic acid


Hierarchical condition category


High-density lipoprotein


Human equilibrative nucleoside transporter 1


Human epidermal growth factor receptor 2


Homeobox C6


International Association for the Study of Lung Cancer




Kallikreins 3


Kirsten rat sarcoma viral oncogene homolog


Lymphocyte-activation gene 3


Leptomeningeal metastasis


Molecular diagnostics


MET Proto-Oncogene


Myotubularin 1


Messenger ribonucleic acid


Microsatellite instability


Microsatellite instability-high


National Academy of Clinical Biochemistry


National Comprehensive Cancer Network


National Cancer Institute


Next-generation sequencing


National Institute of Health


Natural killer


Neuroblastoma rat sarcoma


Non-small cell lung cancer


Polymerase chain reaction


Programmed death-ligand 1


Progression-free survival


Phosphatidylinositol 3-Kinase


Prostate-specific antigen


Rearranged during transfection


Rapid gas quenching


Ribonucleic acid




Ribonucleotide reductase, M1 subunit


Reverse transcriptase polymerase chain reaction


International Society of Geriatric Oncology


Single nucleotide variants


Tissue deoxyribonucleic acid


Tumor-derived exosomes


T cell immunoglobulin and mucin-domain containing-3


Tyrosine kinase inhibitors


Tumor mutational burden


DNA topoisomerase 1


DNA topoisomerase 2 alpha


DNA topoisomerase 2 beta


Tumour protein


Tubulin beta 3 class III


Urinary cell-free deoxyribonucleic acid


Urine-derived tumor deoxyribonucleic acid


X-ray repair cross-complementing 1

The science of noninvasive disease monitoring has advanced greatly since circulating cell-free DNA (cfDNA) was first reported in body fluids by Mandel and Metais. Since then, the evolution of sensitive cfDNA detection technologies has enabled the development of liquid biopsies with many clinical applications. For example, in oncology, the use of liquid biopsy allows for patient stratification, screening, monitoring treatment response and detection of minimal residual disease after surgery or recurrence. Liquid biopsies have grown in importance because the genetic profile of tumors can affect how well patients respond to a certain treatment. However, this characterization is currently achieved through a biopsy despite the inherent problems in procurement of tissue samples and the limitations of tumor analyses. For example, the invasive nature of a biopsy poses a risk to patients and can have a significant cost (Brock, Castellanos-Rizaldos, Hu, Coticchia, & Skog, 2015).

Tumor sampling from some cancer types also remains difficult resulting in inadequate amount of tissue for genetic testing (Brock et al., 2015). In the case of advanced or metastatic non-small cell lung cancers (NSCLC), as many as 69% of cases do not have accessible tissue (J.-Y. Douillard et al., 2009). Even when tissue can be collected, preservation methods such as formalin fixation can cause false positive results for genetic tests (Quach, Goodman, & Shibata, 2004). Finally, due to tumor heterogeneity, biopsies often suffer from sample bias (Bedard, Hansen, Ratain, & Siu, 2013). Liquid biopsies are becoming more popular as they provide an opportunity to genotype in a less invasive and expensive manner. However, the low sensitivity (between 60% – 80%) and higher number of false negative cases compared to traditional tissue biopsy are limitations associated with liquid biopsies (Sequist & Neal, 2020).

Approaches to Liquid Biopsy Analysis

Circulating tumor cells (CTCs)

According to Brock et al. (2015), CTCs are cells shed into the vasculature from a primary tumor and may constitute seeds for subsequent growth of additional tumors (metastasis) in distant organs (Brock et al., 2015). CTCs generally confer the advantage of containing RNA, DNA, and protein from tumor cells including both nuclear and cytoplasmic biomarkers, which is not attainable from ctDNA or exosomes (Yu et al., 2021). They have been detected in various metastatic carcinomas (Mavroudis, 2010) but are extremely rare in healthy subjects and patients with nonmalignant diseases (Brock et al., 2015). Clinical evidence indicates that patients with metastatic lesions are more likely to have CTCs amenable to isolation but their frequency is low, often ~ 1 – 10 CTCs per mL of whole blood (Miller, Doyle, & Terstappen, 2010). As 1 mL of blood contains ~7×106 white blood cells and ~5×109 red blood cells, technologies capable of reproducibly isolating a single CTC from the background of all other blood components are fundamental. While such levels of sensitivity are challenging, there are several novel developments in this area, including positive selection, negative selection, physical properties or even enrichment-free assays to efficiently isolate these rare CTCs (Alix-Panabieres & Pantel, 2013). However, Bettegowda et al. (2014) stated that an advantage of ctDNA is that it can be analyzed from bio-banked biofluids, such as frozen plasma (Bettegowda et al., 2014).

Typically, CTCs are defined as cells with an intact viable nucleus, cytokeratin positive, epithelial cell adhesion molecule (EpCAM) positive and with the absence of CD45 (Brock et al., 2015). Unfortunately, EpCAM and other markers are not always expressed on CTCs (Grover, Cummins, Price, Roberts-Thomson, & Hardingham, 2014). In addition, non-tumor epithelial cells are known to circulate in the blood of patients with prostatitis or patients undergoing surgery (Brock et al., 2015; Murray et al., 2013). The heterogeneity of CTCs is a major challenge from a technical standpoint. This has led to alternative strategies of CTC enrichment such as the CTC-iChip which does not rely on tumor antigen expression (Brock et al., 2015; Karabacak et al., 2014).

Sequencing the genetic material from CTCs has demonstrated that the majority are not cancer cells, even when the isolated cell(s) fit the phenotypic criteria of being a CTC. One study by Marchetti et al. (2014) developed a protocol to recover the CTC enriched samples from the cartridge of the Veridex platform and found that from 37 NSCLC patients, the EGFR mutation allele abundance ranged between 0.02% and 24.79% with a mean of 6.34%. Brock et al. (2014) concluded that the number of CTCs found in the blood is therefore highly dependent on how the platform defines a cell as a CTC (Brock et al., 2015; Marchetti et al., 2014). The CellSearch CTC test, a Food and Drug Administration (FDA) approved actionable CTC test, requires that samples are processed within 96 hours of collection after being drawn into the Cellsave preservative tube. This test does not analyze the molecular genetics of the tumor; rather Cellsave is a platform for CTC numeration. A positive test (more than five detected CTCs for metastatic breast and prostate cancer and more than three CTCs for metastatic colorectal cancer per 7.5 mL of blood) is associated with decreased progression-free survival and decreased overall survival in these patients (C. Aggarwal et al., 2013).

Overall, although CTCs have produced some promising results in evaluating prognosis of patients with varying cancers, further studies are needed to assess the clinical utility of these biomarkers (Adamczyk et al., 2015; Bidard, Proudhon, & Pierga, 2016; Foukakis & Bergh, 2020; Ignatiadis & Dawson, 2014).

Cell-free DNA (cfDNA)

There is currently an intensive research effort to understand the utility of cfDNA in various clinical fields, such as cancer research, non-invasive prenatal testing and transplant rejection diagnostics (Brock et al., 2015). In a systematic review and meta-analysis of 20 studies and 2012 cases covering assessment of EGFR mutational status in NSCLC, Luo, Shen, and Zheng (2014) found a sensitivity of 0.674, a specificity of 0.935, and area under the curve of 0.93. The authors concluded that detection of EGFR mutation by cfDNA is of adequate diagnostic accuracy and cfDNA analysis could be a promising screening test for NSCLC (Luo, Shen, & Zheng, 2014).

In a study, Jiang et al. (2015) observed that most cfDNA in plasma is reportedly fragmented, around 150-180 bp in length with a higher prevalence of tumor associated mutations in the shorter fragments. Per authors, when analyzing the mutation abundance with massively parallel sequencing, a significant correlation was found between mutations and fragments less than 150 bp.  Notably, the size of the majority of cfDNA fragments overlaps well with the size of histone DNA (Jiang et al., 2015)

A direct comparison of mutation detection on cfDNA vs. CTCs showed a higher abundance of the mutation on the cfDNA from the same patient; moreover, recent large studies comparing the effectiveness of cfDNA analysis to tissue biopsy in NSCLC showed the clinical value of the liquid biopsy approach (J. Y. Douillard et al., 2014). This positive result led to an approval to use cfDNA analysis for EGFR mutation analysis for IRESSA in Europe (in patients where a tumor sample was not evaluable), making it the first EGFR tyrosine kinase inhibitor for which cfDNA testing is included in the label. Although promising, challenges remain when using cfDNA to characterize the mutation status of a tumor. In addition to the low copy number of mutant alleles, the median half-life of cfDNA in circulation ranges from 15 minutes to a few hours (Brock et al., 2015).

Brock et al. (2015), in their review, observed that the total concentration of cfDNA in the blood of cancer patients varies considerably with tumor specific mutations ranging from undetectable (less than 1 copy per 5 mL of plasma) to patients with over a hundred thousand copies of the mutation per mL of plasma. The authors note that “the challenge of how to maximize the yield of the cfDNA and pair this with a platform sensitive enough to detect rare variants in the background of wild-type DNA remains. Optimally, the ability to detect mutations in plasma should not be limited to a subpopulation of patients with very high mutant copy numbers in circulation” (Brock et al., 2015). This has been proven to be challenging in early stage cancers (Yu et al., 2021).

While many analytical platforms report the mutation load with an allelic frequency compared to the wild-type DNA platforms relying solely on the allelic frequency without recording the number of mutations have limitations. This is because the allelic frequency of a gene is affected by the amount of wild-type DNA not related to the tumor. Therefore, it is important to consider the processes that affect the amount of wild-type DNA in circulation (Brock et al., 2015). For example, exercise increases cfDNA levels almost 10-fold (Breitbach, Sterzing, Magallanes, Tug, & Simon, 2014). Other pre-analytical variables such as blood collection, the cellular process leading to its release, and extraction protocols affect the amount and size range of cfDNA fragments in a sample (Devonshire et al., 2014).


In the last few years, the exosome field has grown exponentially impacting various areas of research. Studies demonstrating that exosomes are actively released vesicles (carrying RNA, DNA, and protein) and can function as intercellular messengers. Yanez-Mo et al. (2015) highlights these developments in a review outlining the biological properties of exosomes and other extracellular vesicles (EVs). However, Gould and Raposo (2013) observed that the exosome field still lags behind as the standardization of  extracellular vesicle (EV) types are not yet firmly established. The majority of exosomes range in size from 30 – 200 nanometers (nm) in diameter and are isolated from all bio-fluids, including serum, plasma, saliva, urine and cerebrospinal fluid (Brock et al., 2015).

Due to the size of an exosome, on average just over 100 nanometers, the entire transcriptome cannot be packaged inside every vesicle. By way of comparison, retrovirus particles with a similar size can package only around 10 kb, so it is likely that a single vesicle of that size carries only a limited number of transcripts. However, exosomes are extremely abundant (1011 per mL of plasma) and when isolating the vesicle fraction, most of the transcriptome can be detected (Brock et al., 2015). Per Huang et al. (2013), and Kahlert et al. (2014), exosomal RNA can be used for mutation detection as well as global profiling of most types of RNA, and the profile alone (without mutation characterization) can be utilized for diagnostics (Brock et al., 2015). In the study ‘Immune modulation of T-cell and NK (natural killer) cell activities by TEXs (tumor-derived exosomes)’, Whiteside (2013) observed that exosome investigations have focused on the important physiologic and pathophysiologic functions of these vesicles in micro-metastasis, angiogenesis and immune modulation and as a means for detection of tumor specific mutations in bio-fluids (Whiteside, 2013). Consequently, in 2012, interest in this new field increased when the National Institute of Health (NIH) dedicated the large strategic Common Fund to study these new entities of extracellular RNA. The goal of this effort is to better understand how exosomes can be utilized for biomarkers and therapeutics as well as understanding this new mechanism of intercellular communication (NIH, 2017).

Mutation detection and RNA profiling

Analysis of nucleic acids present in bodily fluids can provide a better understanding of the disease, as summarized in Table below.  

Comparison of the analysis capability of CTCs, cfDNA and exosomes from: (Brock et al., 2015)Analysis capability






Point mutations, InDels, amplifications, deletions, translocations




Epigenetic modifications

Methylation patterns




RNA transcription profiles

Levels/activity of mRNA, microRNA, long non-coding RNA, RNA splice variants




Phenotypic studies of cells from the tumor

Cell morphology, protein localization, in vivo studies




Inflammatory response, stromal and other systemic changes

Inflammatory RNA and protein markers




Analysis of RNA as well as DNA and protein profiles from tumor cells

Separate or in combination




Can utilize bio-banked samples

Frozen plasma, urine and other bio-fluids




CTCs, circulating tumor cells; cfDNA, cell-free DNA; InDels, insertions/deletions.

RNA profiling from biofluids is also difficult. However, since exosomes contain RNA, it was possible to separate the fragile RNA from the large amounts of RNases and PCR inhibitors. As cell-free RNA in blood is immediately degraded, RNAs in serum and plasma were either protected inside vesicles, in protein complexes or associated with HDL particles (Brock et al., 2015). The levels of these microRNAs are tightly regulated in normal cells, and dysregulation has been implicated in several human diseases, e.g., cardiovascular (Thum & Condorelli, 2015) and neurological, and is strongly linked to cancer development and progression. However, microRNAs represent only a minor fraction of the transcriptome. By contrast, the nucleic acids in exosomes can be isolated and the entire transcriptome examined (Brock et al., 2015).

The most significant hurdle for all forms of liquid biopsy remains the relative rarity of nucleic acid derived from a tumor against the background of normal material found in most patient samples. In fact, the majority of cell, cell-free nucleic acids, microRNAs and exosomes in a liquid biopsy will have originated from normal cells with numbers fluctuating as a consequence of biological variations (Brock et al., 2015).

Furthermore, although liquid biopsy was first introduced with serum, other liquid media, such as urine and cerebrospinal fluid (CSF), have been used to evaluate other conditions. Cell-free DNA is not necessarily confined to blood, and other media have been proposed.


Urine’s primary advantage over blood is that it is non-invasive, allowing for more convenient testing. Urinary cell-free DNA (UcfDNA) has been proposed as a biomarker for the detection and diagnosis of certain cancers, particularly bladder and prostate cancer (Lu & Li, 2017). An example of this is SelectMDX. SelectMDX evaluates two mRNA cancer-related biomarkers (HOXC6 and DLX1 with KLK3 as a reference gene) to assist a clinician in deciding to continue routine screening or to order a prostate biopsy. This test is considered a “non-invasive urine test” (a liquid biopsy) and reports a binary result of “increased risk” or “very low risk” (MDx, 2018). Van Neste et al. evaluated this test at a 0.90 area under curve in a validation cohort. The authors concluded that the mRNA signature was one of the most significant components of the validation results (Van Neste et al., 2016). Shore et al assessed the effect of SelectMDX results on clinical decision making and found that out of 253 patients SelectMDX evaluated as “negative”, only 12% underwent a biopsy (Shore, 2018).

Xu et al. (2021) assessed the diagnostic value of urinary exosomes for urological tumors. The authors performed a systematic review and meta-analysis of 16 studies with a total of 3224 patients. Diagnostic value was calculated based on the number of true positives, false positives, true negatives, and false negatives. The sensitivity of using urinary exosomes for the diagnosis of urological tumors was 83% and the specificity was 88%. Sensitivity and specificity results were similar regardless of urinary exosome content type and tumor type. The authors conclude that “urinary exosomes may serve as novel non-invasive biomarkers for urological cancer detection” (Xu et al., 2021).

Cerebrospinal Fluid (CSF)

CSF is a colorless, clear liquid produced by the choroid plexus. CSF acts to control flow of molecules to the central nervous system (CNS). Due to the tight control of the CSF, it may play a significant role in assessing several conditions. CSF is traditionally used to evaluate conditions such as meningitis, but it has also been used to assess central nervous system cancers, such as leptomeningeal metastases (Demopoulos, 2020; Johnson, 2019). In addition to widely-known measures of pathology in CSF (opening pressure, total protein, glucose, cell count with differential), circulating tumor cells in CSF have also been proposed as markers for epithelial tumors (Demopoulos, 2020).

Lin et al. (2017) evaluated the diagnostic accuracy of circulating tumor cells in CSF (CSF-CTC) in patients with leptomeningeal metastasis (LM). 30 of 95 total patients were diagnosed with LM based on a combination of CSF cytology and MRI. CSF-CTCs were detected in 43 patients (median 19.3 CSF-CTC/mL). Based on receiver operating curve analysis, the optimal cutoff was found to be 1 CSF-CTC/mL, identifying patients at a rate of 93% sensitivity, 95% specificity, positive predictive value 90%, and negative predictive value 97% (Lin et al., 2017). Diaz et al. (2022) studied the clinical utility of CSF-CTC by evaluating how CSF-CTC quantification was able to predict the outcome of LM. The authors performed a single institution retrospective study of 101 LM patients with solid tumors. The CSF-CTC count significantly predicted survival continuously (p=0.0027). The authors conclude that “CSF-CTCs quantification predicts survival in newly diagnosed LM, and outperforms neuroimaging” and suggest CSF-CTC can be used for LM prognosis and to assess disease burden (Diaz et al., 2022).

Proprietary Testing
FDA approval of use of the Roche Cobas EGFR Mutation Test in plasma was based on evaluation of plasma samples from the ENSURE study (Wu et al., 2015), a multicenter, open-label, randomized, Phase III study of stage IIIB/IV NSCLC patients. 98.6% of the patients enrolled (214/217) had a plasma sample available for testing. The agreement between the Cobas EGFR Mutation Test in plasma and tissue was evaluated for detection of EGFR mutations. In 76.7% of tissue-positive specimens, plasma was also positive for an EGFR mutation. Plasma was negative for EGFR mutation in 98.2% (95.4%, 99.3%) of tissue-negative cases. The patients whose plasma results were positive for exon 19 deletion and/or an L858R mutations treated with erlotinib had improved progression-free survival (PFS) compared to those treated with chemotherapy (FDA, 2016).

Another commercially available test is Guardant360 by Guardant Health Inc. Guardant360 is a gene panel that sequences 74 genes (including 18 amplifications and 6 fusions) associated with NSCLC and reports the percentage of cfDNA (Guardant, 2020, 2022). The manufacturer purports that this genetic test will allow providers to make better treatment decisions based on the mutations present in the patient (Health, 2017). The gene panel was analytically validated, with 99.8% accuracy on 1000 consecutive samples (Lanman et al., 2015).

A third commercially available test is the Liquid GPS by NantHealth Inc. This test assesses both cfDNA and ctDNA, and measures targeted therapy, chemotherapy, and immunotherapy markers. For example, this test evaluates the biomarker AR-V7, which is considered a predictor of prostate cancer treatments. The targeted therapy biomarkers are as follows: EGFR, HER2, AR (or AR-V7), c-MET, ROS1 fusion, ALK fusion, KRAS, BRAF, and NRAS. The chemotherapy markers are as follows: ERCC1, XRCC1, MGMT1, TUBB3, hENT1, TP, TS, RRM1, TOP1, TOP2A, and TOP2B. The immunotherapy markers are as follows: PD-L1, TIM-3, CTLA-3,andLAG-3 (NantHealth, 2018, 2020).

Other proprietary liquid biopsy tests are available to assess genes associated with numerous conditions. OncoBEAM™ has numerous liquid biopsy PCR-based tests for the evaluation of gene mutations, which follow the same principle as other cell-free DNA tests (cells shedding DNA fragments into the circulatory system and into the plasma where it can be easily examined) (Oncobeam, 2018). OncoBEAM™ uses a proprietary method in which the DNA is isolated and amplified with PCR. Then, the wild-type and mutant strains are tagged with separate fluorescent probes, and finally quantified with flow cytometry (Diehl et al., 2008; Oncobeam). OncoBEAM™’s liquid biopsies include assessments for the EGFR, ALK, and ROS1 mutations, and these panels have been observed to detect as low as 0.02% fraction of mutation. OncoBEAM™ offers three separate panels, an 18-gene panel for NSCLC, a 34-gene panel for colorectal cancer, and a 9-gene panel for melanoma (Oncobeam, 2020).

FoundationOne has also created proprietary tests that examine cell-free DNA. Foundation’s test evaluates features like microsatellite instability, specific types of mutations, and 70 commonly altered oncogenes (FoundationOne, 2018). A prior version of this test (covering 62 genes) was evaluated based on 2666 reference samples. The assay reached >99% sensitivity of short variants of allele frequencies of >0.5%, >95% sensitivity of allele frequencies 0.25%-0.5%, and >70% sensitivity of allele frequencies 0.125%-0.25%. Out of 62 healthy volunteers, no false positives were detected (Clark et al., 2018).

Biodesix is another laboratory that offers a liquid biopsy panel. This test, called GeneStrat, tests EGFR, ALK, ROS1, RET, BRAF, and KRAS (Biodesix, 2020). These genes were validated over multiple studies, with sensitivities of 78%-100% for EGFR, ALK, and KRAS (H. Mellert et al., 2017) and detecting over 88% of RET or ROS1-positive patients (H. S. Mellert, Alexander, Jackson, & Pestano, 2018).

Other firms offering liquid biopsy testing include ResolutionBio (ctDX, focuses on actionable genes for lung cancer such as EGFR and ALK), Circulogene (tests BRAF, EGFR, KRAS, ALK, ROS1, PD-L1, and MSI), Admerahealth (Liquidgx, uses next-generation sequencing to evaluate 17 genes including BRAF, EGFR, ROS1, ALK, et al), Inivata (InvisionFirst, 37-gene panel including 10 actionable genes), and Biocept (Target Selector, tests 20 genetic features for targeted therapy). As liquid biopsy is a rapidly emerging field, it is possible that many more tests will find their way into the clinical setting (Admerahealth, 2019; Biocept, 2022; Circulogene, 2018; Inivata, 2022; ResolutionBio, 2021).

Clinical Utility and Validity
Seeberg et al. (2015) conducted a prospective study to assess the prognostic and predictive value of CTCs in 194 patients with colorectal liver metastasis referred to surgery. 153 patients underwent a resection (41 patients had an unresectable tumor), and CTCs were detected in 19.6% of patients. Patients with unresectable tumors had a 46% CTC positivity rate compared to 11.7% for resectable tumors.  Patients with two or more CTCs experienced reduced time to relapse/progression. Two or more CTCs was a strong predictor of progression and mortality in all subgroups of patients. The authors concluded that “CTCs predict nonresectability and impaired survival. CTC analysis should be considered as a tool for decision-making before liver resection in these patients (Seeberg et al., 2015)”.

Groot et al. (2013) performed systematic review and meta-analysis to investigate the prognostic value of CTCs in patients with resectable colorectal liver metastases or widespread metastatic colorectal cancer (CRC). The results of 12 studies representing 1,329 patients were suitable for pooled analysis. The overall survival and progression-free survival were worse in patients with CTCs, with hazard ratios of 2.47 for overall survival rate and 2.07 for progression-free survival. The authors concluded that “the detection of CTCs in peripheral blood of patients with resectable colorectal liver metastases or widespread metastatic CRC is associated with disease progression and poor survival (Groot Koerkamp, Rahbari, Buchler, Koch, & Weitz, 2013).”

Zhang et al. (2012) conducted a meta-analysis of published literature on the prognostic value of CTC in breast cancer. Forty-nine eligible studies enrolling 6,825 patients were identified. The presence of CTC was significantly associated with shorter survival in the total population and the prognostic value of CTC was significant in both early and metastatic breast cancer. The authors concluded that “the detection of CTC is a stable prognosticator in patients with early-stage and metastatic breast cancer. Further studies are required to explore the clinical utility of CTC in breast cancer (Zhang et al., 2012).”

Pinzani et al. (2021) assessed that the clinical validity of CTCs has been demonstrated in cancer screening, prognosis, and monitoring treatment responses. In the original article by Cabel et al. (2017), using the Cellsearch® technique in early non-metastatic cancer has reported low CTC detection rates (5-30% depending on cancer type), with limited specificity since “some circulating epithelial cells can be found in individuals with inflammatory disease or even in some healthy individuals.” However, in the preliminary report of another study, it was found that a CTC count >25 could “distinguish lung cancer from benign lesions in patients with abnormal lung imaging. CTC count was also shown to be an “independent prognostic factor in non-small cell lung cancer and small cell lung cancer;” despite this, CTCs are rare in the non-metastatic setting, and thus cannot be completely utilized as an independent prognostic factor in the localized setting. With respect to the independent cancers, Cabel et al. (2017) summarizes the clinical validity of CTC detection in Figure 1. (Gregory et al., 2013) (Gregory et al., 2013) (Gregory et al., 2013)

On the clinical utility of CTC, Cabel et al. (2017) initially stated “the clinical utility of CTC detection (i.e. does it improve patient outcome) has yet to be demonstrated before it can be implemented in routine clinical practice.” In recent time, it was seen that specific CTC features may have clinical utility in “[predicting] the sensitivity to specific immunotherapies,” and in the case of ER+ MBCs, ER-CTCs can develop and reflect “acquisition of therapy resistance by the primary tumor” (Pinzani et al., 2021).

Oxnard et al. found that: “Sensitivity of plasma genotyping for detection of T790M was 70%. Of 58 patients with T790M-negative tumors, T790M was detected in plasma of 18 (31%). ORR and median PFS were similar in patients with T790M-positive plasma (Objective response rate [ORR], 63%; progression-free survival [PFS], 9.7 months) or T790M-positive tumor (ORR, 62%; PFS, 9.7 months) results. Although patients with T790M-negative plasma had overall favorable outcomes (ORR, 46%; median PFS, 8.2 months), tumor genotyping distinguished a subset of patients positive for T790M who had better outcomes (ORR, 69%; PFS, 16.5 months) as well as a subset of patients negative for T790M with poor outcomes (ORR, 25%; PFS, 2.8 months) (Oxnard et al., 2016).” The authors concluded that “upon availability of validated plasma T790M assays, some patients could avoid a tumor biopsy for T790M genotyping (Oxnard et al., 2016).”

A review by Sacher et al. genotyped 180 patients with NSCLC using plasma droplet PCR (plasma ddPCR). This was done to validate the plasma droplet PCR technique, and the study identified 115 EGFR mutations and 25 KRAS mutations. The plasma ddPCR was measured to have 82% sensitivity for the EGFR 19 del, 74% for L858R, 77% for T790M, and 64% for KRAS. The positive predictive value was 100% for every mutation apart from T790M at 79%. The authors concluded that the technique “detected EGFR and KRAS mutations rapidly with the high specificity needed to select therapy and avoid repeat biopsies”. The authors also noted that this assay “may also detect EGFR T790M missed by tissue genotyping due to tumor heterogeneity in resistant disease (Sacher et al., 2016).”

Kim et al. (2017) evaluated the clinical utility of Guardant360. This study used the Guardant360 panel to detect mutations in patients with metastatic NSCLC and other cancers. Somatic mutations were detected in 59 patients, 25 of which had actionable mutations. Out of the 73-patient NSCLC cohort, 62 were found to have somatic mutations and 34 had actionable mutations. After these genetic findings were identified, molecularly matched therapy was provided to 10 patients with gastric cancer (GC) and 17 with NSCLC. Response rate was 67% in GC and 87% in patients with NSCLC, while disease control rate was 100% for both types (Kim et al., 2017).

Odegaard et al. (2018) validated the Guardant360 cell-free DNA sequencing test and aimed to “demonstrate its clinical feasibility”. The authors found that the test could detect variants down to “0.02% to 0.04% allelic fraction/2.12 copies with ≤0.3%/2.24-2.76 copies”. Clinical validation in a cohort of over 750 patients demonstrated high accuracy and specificity, with positive percent agreement (with PCR) of 92%-100% and negative percent agreement of over 99%. In terms of feasibility, the authors performed the test in 10593 patients and found the technical success rate to be over 99.6% and the clinical sensitivity to be 85.9%. The authors also noted that 16.7% of these mutations were targetable with FDA-approved treatments (with 72% with “treatment or trial recommendations”) with as many as 34.5% of non-small cell cancer samples having a targetable mutation (Odegaard et al., 2018).

Aggarwal et al. (2019) evaluated the utility of plasma-based sequencing in improving mutation detection in patients with non-small cell lung cancer. The authors first performed next-generation sequencing (NGS) on tissue, then plasma-based sequencing. 229 patients had concurrent sequencing, and NGS alone detected 47 targetable mutations. Addition of plasma sequencing brought that number to 82 targetable mutations. Furthermore, 36 of 42 patients that received “plasma next-generation sequencing–indicated therapy” achieved a “complete or a partial response or stable disease”. The authors concluded that “adding plasma next-generation sequencing testing to the routine management of metastatic non–small cell lung cancer appears to increase targetable mutation detection and improve delivery of targeted therapy” (Charu Aggarwal et al., 2019).

Leighl et al. (2019) evaluated the utility of “comprehensive cell-free DNA analysis” to identify genomic biomarkers in patients with newly diagnosed metastatic non-small cell lung cancer (NSCLC). 282 patients were included. Tissue genotyping (current standard of care) identified a guideline-recommended biomarker in 60 patients, whereas cell-free DNA identified a relevant biomarker in 77 patients. Concordance between the two methods was 80% (48 biomarkers detected in both methods). For FDA-approved targets (EGFR, ALK, ROS1, BRAF), concordance was >98.2% with 100% positive predictive value for cell-free DNA. Cell-free DNA was also found to have a faster median turnaround time (9 days compared to 15 for tissue genotyping), and “guideline-complete” (assessment of all eight guideline-recommended biomarkers [EGFR, ALK, ROS1, BRAF, RET, MET amplification and exon 14 skipping, and HER2]), was significantly more likely (268 patients vs 51) (Leighl et al., 2019).

Dudley et al. (2019) have developed a novel high-throughput sequencing method that uses urine-derived tumor DNA (utDNA) known as utDNA CAPP-Seq (uCAPP-Seq) to detect bladder cancer. This technique was used to analyze samples from 118 patients with early-stage bladder cancer and 67 healthy adults. “We detected utDNA pretreatment in 93% of cases using a tumor mutation-informed approach and in 84% when blinded to tumor mutation status, with 96% to 100% specificity (Dudley et al., 2019).” These results show that utDNA can be used to diagnose early-stage bladder cancer with high sensitivity and specificity.

Wang et al. (2018) performed a meta-analysis to determine the diagnostic performance of cell-free DNA (both blood and urine) assays in bladder cancer. 11 studies encompassing 802 patients were included. The authors evaluated cell-free DNA assays at the following statistics: “sensitivity 0.71, specificity 0.78 positive likelihood ratio 3.3, negative likelihood ratio 0.37, diagnostic odds ratio 9, and area under curve 0.80. No publication bias was identified. The authors concluded that “cell-free DNA has a high diagnostic value in bladder cancer” (Wang et al., 2018).

cfDNA can hopefully be used to indicate prognoses of personalized peptide vaccine therapy in patients with NSCLC. Waki et al. (2021) identified that cfDNA integrity “decreased after the first cycle of vaccination” and that those with “high prevaccination cfDNA integrity survived longer than those with low prevaccination integrity (median survival time (MST): 17.9 versus 9.0 months, respectively; hazard ratio (HR): 0.58, p= .0049),” showing that monitoring cfDNA levels could contribute to quantifying treatment success and predicting patient lifespans.

For exosome-based liquid biopsy, Yu et al. (2021) have proposed a synergistic alternative of combining cfDNA and exosomal RNA to “increase the sensivity of mutation detection… the exosome component enables a combination of exosomal RNA, cfDNA, and disease specific proteins… the unique composition of the exosome compartment makes these vesicles particularly amenable for multi-analyte testing, since they carry cancer-informative DNA, RNA, proteins, lipids, oligosaccharides, and metabolites. In one study, a high sensitivity (92%) for EGFR mutations was found for utilizing exosomal RNA and ctDNA together and remained high in a subpopulation that’s been difficult for ctDNA assays to detect (88% sensitivity). ExoRNA and ctDNA combined analyses on BRAF, KRAS, and EGFR mutations in exosomes and respective ctDNA have also better correlated the biomarkers with treatment outcomes when compared to ctDNA alone (Yu et al., 2021).

Lee et al. (2021) analyzed the clinical utility of ctDNA to reliably detect EGFR in ctDNA. The authors compared EGFR analysis results between tissueDNA (tDNA) and ctDNA from 554 NSCLC cases. ctDNA analysis detected EGFR mutation in 57.3% of cases. ctDNA detection correlated with metastatic stage and disease progression (p<0.001). The authors followed up after an average of 41.09 month and found that, “survival analysis revealed ctDNA status and M stage (p < 0.001) to be independent predictors of overall survival in the multivariate analysis.” The authors conclude that ctDNS is clinically useful for EGFR analysis, but note the possibility of false negatives and recommend using tDNA to confirm ctDNA results in some situations (Lee, Han, & Choi, 2021). Syeda et al. (2021) evaluated the use of ctDNA as a biomarker for melanoma. The authors measured changes in ctDNA and survival following “BRAF, MEK, or BRAF plus MEK inhibitor therapy” in patients participating in two clinical trials. The BRAFV600-mutant was measured in ctDNA before and during treatment. “Elevated baseline BRAFV600 mutation-positive ctDNA concentration was associated with worse overall survival outcome.” The authors conclude that BRAFV600-mutation ctDNA analysis can be used as a biomarker to predict clinical outcomes (Syeda et al., 2021).

National Comprehensive Cancer Network (NCCN)
NCCN guidelines for non-small cell lung cancer (NSCLC) strongly advises “broader molecular profiling with the goal of identifying rare driver mutations for which effective drugs may already be available, or to appropriately counsel patients regarding the availability of clinical trials. Broad molecular profiling is a key component of the improvement of care of patients with NSCLC”. Furthermore, the NCCN states that “Data suggest that plasma genotyping (also known as plasma testing or liquid biopsy) may be considered at progression instead of tissue biopsy to detect whether patients have T790M; however, if the plasma biopsy is negative, then tissue biopsy is recommended” (NCCN, 2021h).

However, the NCCN goes on to state that cell-free or circulating tumor DNA testing should not be used in lieu of histologic tissue diagnosis. The NCCN notes that specificity is generally very high for cell-free tumor testing but is lacking in sensitivity (up to 30% false-negative rate) and that standards for testing have not been well established. The use of cell-free or circulating tumor DNA may be considered in specific clinical situations, such as if a patient is medically unfit for an invasive tissue sampling or if there is insufficient material for a molecular analysis following pathologic confirmation of an NSSCLC diagnosis (but only if “follow-up tissue-based analysis is planned for all patients in which an oncogenic driver is not identified”. The NCCN notes that “recent data suggest that plasma cell-free/circulating tumor DNA testing can be used to identify EGFR, ALK, and other oncogenic biomarkers that would otherwise not be identified in patients with metastatic NSCLC” (NCCN, 2021h).

NCCN states that “the clinical use of Circulating Tumor Cells (CTC) or circulating DNA (ctDNA) in metastatic breast cancer is not yet included in the NCCN Guidelines for Breast Cancer (NCCN, 2022b) for disease assessment and monitoring.” However, assessment of the PIK3CA mutation may be performed through liquid biopsy if the tumor is HR-positive, HER2 negative, and if therapy with alpelisib plus fulvestrant is being considered (NCCN, 2022b).

The NCCN states that AR-V7 testing in CTCs “can be considered to help guide selection of therapy in the post-abiraterone/enzalutamide metastatic CRPC setting”. The NCCN does not comment on any particular liquid medium over another (e.g. urine, CSF, serum). However, the NCCN does specify the use of circulating DNA for rucaparib treatment, stating that “the preferred method of selecting patients for rucaparib treatment is somatic analysis of BRCA1 and BRCA2 using a circulating tumor DNA sample” (NCCN, 2022a). SelectMDx is also acknowledged by the NCCN; “the panel believes that SelectMDx score is potentially informative in patients who have never undergone biopsy, and it can therefore be considered in such men” (NCCN, 2021j).

With regards to circulating tumor DNA (ctDNA) in colon cancer, the NCCN “panel believes that there are insufficient data to recommend the use of multigene assays, Immunoscore, or post-surgical ctDNA to estimate risk of recurrence or determine adjuvant therapy” (NCCN, 2021d). NCCN guidelines for small cell lung cancer do not address use of CTCs or ctDNA for patient management (NCCN, 2021k).

For neuroendocrine tumors, NCCN notes that CTCs have been studied as prognostic markers, but state that more research is required. There is no single biomarker available that is satisfactory as a diagnostic, prognostic, or predictive marker (NCCN, 2021g).

For a primary CNS lymphoma, the NCCN remarks that cerebrospinal fluid analysis may “possibly” include gene rearrangement evaluation. For leptomeningeal metastases, the NCCN notes that assessment of CTCs in CSF “increases sensitivity of tumor cell detection and assessment of response to treatment” (NCCN, 2021c).

For pancreatic adenocarcinomas, the NCCN acknowledges that circulating cell-free DNA is being investigated as a biomarker for screening. The NCCN also notes that if tumor tissue is not available, cell-free DNA testing may be considered (NCCN, 2021i).

For esophageal, esophagogastric junction cancers, and gastric cancers, the NCCN states “testing using a validated NGS-based [next generation sequencing] genomic profiling assay performed in a CLIA-approved laboratory may be considered for some patients. A negative result should be interpreted with caution, as this does not exclude the presence of tumor mutations or amplifications. The liquid biopsy platform is in its early phase of development and more research would be necessary before it can be considered standard of care” (NCCN, 2021e). The NCCN does not comment on the usage of liquid biopsies, ctDNA, or CTCs for testing for hepatobiliary cancers (NCCN, 2021f).

For acute myeloid leukemia, the NCCN notes that “morphologically detectable,” circulating leukemic blasts from peripheral blood may be used to detect molecular abnormalities (NCCN, 2021a).

For bladder cancer, the NCCN mentions RT-PCR testing for FGFR2/3 gene alterations but does not specify whether this can be done through a liquid biopsy or cell-free DNA. The only comment made is that the laboratory should be CLIA-approved (NCCN, 2021b).

American Society of Clinical Oncology (ASCO)
In 2016, ASCO published updated recommendations for the use of tumor markers in treatment of metastatic breast cancer. ASCO found that although CTCs may be prognostic, they are not predictive for clinical benefit when used to guide or influence decisions on systemic therapy for metastatic breast cancer. ASCO recommends clinicians to not use these markers as adjunctive assessments (Poznak et al., 2016). Similarly, ASCO recommended against use of CTCs to guide decisions about adjuvant systemic therapy for women with early stage invasive breast cancer (Andre et al., 2019).

In 2019, ASCO stated that clinicians “should not use circulating biomarkers as a surveillance strategy for detection of recurrence in patients who have undergone curative-intent treatment of stage I-III NSCLC or SCLC”. ASCO states that further data is required to validate this approach (Schneider et al., 2019).

In 2018, ASCO and the College of American Pathologists (CAP) released a joint review on “circulating tumor DNA analysis in patients with cancer”. In it, they note that apart from the assays that have received “regulatory appeal”, most assays have “insufficient evidence” for both clinical validity and clinical utility. They note discordant results between circulating DNA assays and tissue genotyping. Furthermore, they remark on the lack of evidence for use in monitoring therapy effectiveness, diagnosing early-stage cancer, or cancer screening.

However, they point to evidence that well-validated assays may support initiation of targeted therapy (Merker et al., 2018).

National Academy of Clinical Biochemistry (NACB), now known as the American Association for Clinical Chemistry (AACC)
In 2010, the NACB issued practice guidelines for the use of tumor markers in liver, bladder, cervical, and gastric cancers. It found that CTCs had “questionable” clinical utility in the assessment of liver cancer and did not recommend their use (C. M. Sturgeon et al., 2010).

The NACB published an updated guideline in 2020. For liver cancer, they note circulating cell-free serum DNA as “undergoing evaluation” for “predictive marker for distant metastasis of hepatitis C virus–related HCC.” The plasma proteasome is also undergoing evaluation for “assessment of early HCC in patients with chronic viral chronic hepatitis; assessment of metastatic potential of HCC.” Finally, circulating methylated DNA is undergoing evaluation for HCC screening, detection, and prognosis. No other circulating tumor markers for bladder, cervical, and gastric cancers were mentioned (Catharine M. Sturgeon et al., 2020).

College of American Pathologists (CAP), the International Association for the Study of Lung Cancer (IASLC), and the Association for Molecular Pathology (AMP)
An expert panel was convened to review and update the CAP-IASLC-AMP Molecular Testing Guideline for Selection of Lung Cancer Patients for EGFR and ALK Tyrosine Kinase Inhibitors. This panel consists of practicing pathologists, oncologists, and a methodologist.

The panel states there is “insufficient evidence to support the use of circulating cell-free plasma DNA (cfDNA) molecular methods for the diagnosis of primary lung adenocarcinoma”. According to the panel, there is also “insufficient evidence to support the use of circulating tumor cell (CTC) molecular analysis for the diagnosis of primary lung adenocarcinoma, the identification of EGFR or other mutations, or the identification of EGFR T790M mutations at the time of EGFR TKI-resistance”(College of American Pathologists, 2018; Lindeman et al., 2018).

However, the panel acknowledges that “In some clinical settings in which tissue is limited and/or insufficient for molecular testing, physicians may use a cell-free plasma DNA (cfDNA) assay to identify EGFR mutations” (Lindeman et al., 2018).

American Society for Clinical Pathology, College of American Pathologists, Association for Molecular Pathology, and American Society of Clinical Oncology
These joint guidelines from these societies were published regarding molecular biomarkers for colorectal cancer. Despite the potential of liquid biopsy for assessment of tumor recurrence and treatment resistance, the technique “awaits robust validation and further studies to determine their clinical utility” (Sepulveda et al., 2017).

European Society for Medical Oncology (ESMO) and Chinese Society of Clinical Oncology (CSCO)
These guidelines state that liquid biopsy can be used as “the initial test for the detection of a T790M mutation [for EGFR in NSCLC], and if tests are negative, a re-biopsy should be attempted if feasible” (Wu et al., 2018).

European Association of Urology (EAU), European Society for Radiotherapy and Oncology (ESTRO), European Society of Urogenital Radiology (ESUR), International Society of Geriatric Oncology (SIOG)
The joint guidelines on prostate cancer  state that “In asymptomatic men with a prostate-specific antigen level between 2–10 ng/mL and a normal digital rectal examination, use one of the following tools for biopsy indication: 

  • risk-calculator;
  • imaging;
  • an additional serum, urine or tissue-based test.”

These joint guidelines acknowledged SelectMDX as a test to select for repeat biopsies, but the guidelines noted SelectMDX as having an “uncertain role” and “probably not cost-effective” (EAU, 2021).

American Society of Colon and Rectal Surgeons (ASCRS)
The ASCRS released clinical practice guidelines for the management of colon cancer. The guidelines state that “the use of multigene assays, CDX2 expression analysis, and ctDNA may be used to complement multidisciplinary decision-making for patients with stage II or III colon cancer” (Vogel et al., 2022).


  1. Adamczyk, L. A., Williams, H., Frankow, A., Ellis, H. P., Haynes, H. R., Perks, C., . . . Kurian, K. M. (2015). Current Understanding of Circulating Tumor Cells - Potential Value in Malignancies of the Central Nervous System. Front Neurol, 6, 174. doi:10.3389/fneur.2015.00174
  2. Admerahealth. (2019). LiquidGX. Retrieved from
  3. Aggarwal, C., Meropol, N. J., Punt, C. J., Iannotti, N., Saidman, B. H., Sabbath, K. D., . . . Cohen, S. J. (2013). Relationship among circulating tumor cells, CEA and overall survival in patients with metastatic colorectal cancer. Ann Oncol, 24(2), 420-428. doi:10.1093/annonc/mds336
  4. Aggarwal, C., Thompson, J. C., Black, T. A., Katz, S. I., Fan, R., Yee, S. S., . . . Carpenter, E. L. (2019). Clinical Implications of Plasma-Based Genotyping With the Delivery of Personalized Therapy in Metastatic Non–Small Cell Lung Cancer. JAMA Oncol, 5(2), 173-180. doi:10.1001/jamaoncol.2018.4305
  5. Alix-Panabieres, C., & Pantel, K. (2013). Circulating tumor cells: liquid biopsy of cancer. Clin Chem, 59(1), 110-118. doi:10.1373/clinchem.2012.194258
  6. Andre, F., Ismaila, N., Henry, N. L., Somerfield, M. R., Bast, R. C., Barlow, W., . . . Stearns, V. (2019). Use of Biomarkers to Guide Decisions on Adjuvant Systemic Therapy for Women With Early-Stage Invasive Breast Cancer: ASCO Clinical Practice Guideline Update—Integration of Results From TAILORx. Journal of Clinical Oncology, 37(22), 1956-1964. doi:10.1200/JCO.19.00945
  7. Bedard, P. L., Hansen, A. R., Ratain, M. J., & Siu, L. L. (2013). Tumour heterogeneity in the clinic. Nature, 501(7467), 355-364. doi:10.1038/nature12627
  8. Bettegowda, C., Sausen, M., Leary, R. J., Kinde, I., Wang, Y., Agrawal, N., . . . Diaz, L. A., Jr. (2014). Detection of circulating tumor DNA in early- and late-stage human malignancies. Sci Transl Med, 6(224), 224ra224. doi:10.1126/scitranslmed.3007094
  9. Bidard, F. C., Proudhon, C., & Pierga, J. Y. (2016). Circulating tumor cells in breast cancer. Mol Oncol, 10(3), 418-430. doi:10.1016/j.molonc.2016.01.001
  10. Biocept. (2022). Target Selector™ Biomarkers. Retrieved from
  11. Biodesix. (2020). GENESTRAT® GENOMIC TEST. Retrieved from
  12. Breitbach, S., Sterzing, B., Magallanes, C., Tug, S., & Simon, P. (2014). Direct measurement of cell-free DNA from serially collected capillary plasma during incremental exercise. J Appl Physiol (1985), 117(2), 119-130. doi:10.1152/japplphysiol.00002.2014
  13. Brock, G., Castellanos-Rizaldos, E., Hu, L., Coticchia, C., & Skog, J. (2015). Liquid biopsy for cancer screening, patient stratification and monitoring. Transl Cancer Res, 4. Retrieved from
  14. Cabel, L., Proudhon, C., Gortais, H., Loirat, D., Coussy, F., Pierga, J.-Y., & Bidard, F.-C. (2017). Circulating tumor cells: clinical validity and utility. International Journal of Clinical Oncology, 22(3), 421-430. doi:10.1007/s10147-017-1105-2
  15. Circulogene. (2018). COMPREHENSIVE LUNG CANCER TESTING. Retrieved from
  16. Clark, T. A., Chung, J. H., Kennedy, M., Hughes, J. D., Chennagiri, N., Lieber, D. S., . . . Lipson, D. (2018). Analytical Validation of a Hybrid Capture-Based Next-Generation Sequencing Clinical Assay for Genomic Profiling of Cell-Free Circulating Tumor DNA. J Mol Diagn, 20(5), 686-702. doi:10.1016/j.jmoldx.2018.05.004
  17. College of American Pathologists, I. A. f. t. S. o. L. C., and the Association for Molecular Pathology. (2018). Updated Molecular Testing Guideline for the Selection of Lung Cancer Patients for Treatment with Targeted Tyrosine Kinase Inhibitors. Retrieved from
  18. Curigliano, G. (2014). Liquid biopsies: Tumour diagnosis and treatment monitoring in a blood test | ESMO. Paper presented at the ESMO 2014.
  19. Demopoulos, A. (2020). Clinical features and diagnosis of leptomeningeal metastases from solid tumors. Retrieved from
  20. Devonshire, A. S., Whale, A. S., Gutteridge, A., Jones, G., Cowen, S., Foy, C. A., & Huggett, J. F. (2014). Towards standardisation of cell-free DNA measurement in plasma: controls for extraction efficiency, fragment size bias and quantification. Anal Bioanal Chem, 406(26), 6499-6512. doi:10.1007/s00216-014-7835-3
  21. Diaz, M., Singh, P., Kotchetkov, I., Skakodub, A., Meng, A., Tamer, C., . . . Ramanathan, L. (2022). Quantitative Assessment of Circulating Tumor Cells in Cerebrospinal Fluid as a Clinical Tool to Predict Survival in Leptomeningeal Metastases.
  22. Diehl, F., Schmidt, K., Choti, M. A., Romans, K., Goodman, S., Li, M., . . . Diaz, L. A., Jr. (2008). Circulating mutant DNA to assess tumor dynamics. Nat Med, 14(9), 985-990. doi:10.1038/nm.1789
  23. Domínguez-Vigil, I. G., Moreno-Martínez, A. K., Wang, J. Y., Roehrl, M. H. A., & Barrera-Saldaña, H. A. (2018). The dawn of the liquid biopsy in the fight against cancer. Oncotarget, 9(2), 2912-2922. doi:10.18632/oncotarget.23131
  24. Douillard, J.-Y., Shepherd, F. A., Hirsh, V., Mok, T., Socinski, M. A., Gervais, R., . . . Kim, E. S. (2009). Molecular Predictors of Outcome With Gefitinib and Docetaxel in Previously Treated Non–Small-Cell Lung Cancer: Data From the Randomized Phase III INTEREST Trial. Journal of Clinical Oncology, 28(5), 744-752. doi:10.1200/JCO.2009.24.3030
  25. Douillard, J. Y., Ostoros, G., Cobo, M., Ciuleanu, T., Cole, R., McWalter, G., . . . McCormack, R. (2014). Gefitinib treatment in EGFR mutated caucasian NSCLC: circulating-free tumor DNA as a surrogate for determination of EGFR status. J Thorac Oncol, 9(9), 1345-1353. doi:10.1097/jto.0000000000000263
  26. Dudley, J. C., Schroers-Martin, J., Lazzareschi, D. V., Shi, W. Y., Chen, S. B., Esfahani, M. S., . . . Diehn, M. (2019). Detection and Surveillance of Bladder Cancer Using Urine Tumor DNA. Cancer Discov, 9(4), 500-509. doi:10.1158/2159-8290.Cd-18-0825
  27. EAU. (2021). Prostate Cancer. Retrieved from
  28. FDA. (2016). Approved Drugs - cobas EGFR Mutation Test v2 (WebContent). Retrieved from from Center for Drug Evaluation and Research
  29. FDA. (2019). Therascreen PIK3CA RGQ PCR Kit. Retrieved from
  30. FDA. (2021). Devices@FDA. Devices@FDA. Retrieved from
  31. Foukakis, T., & Bergh, J. (2020). Prognostic and predictive factors in early, nonmetastatic breast cancer - UpToDate. In D. Hayes (Ed.), UpToDate. Retrieved from;amp;search=gene%20expression%20testing%20breast%20cancer&amp;amp;selectedTitle=4~150&amp;amp;anchor=H103670818&amp;amp;sectionRank=1#H103670818
  32. FoundationOne. (2018). Technical Specifications. Retrieved from
  33. Georgiadis, A., Durham, J. N., Keefer, L. A., Bartlett, B. R., Zielonka, M., Murphy, D., . . . Sausen, M. (2019). Noninvasive Detection of Microsatellite Instability and High Tumor Mutation Burden in Cancer Patients Treated with PD-1 Blockade. Clinical Cancer Research. doi:10.1158/1078-0432.CCR-19-1372
  34. Gould, S. J., & Raposo, G. (2013). As we wait: coping with an imperfect nomenclature for extracellular vesicles. J Extracell Vesicles, 2. doi:10.3402/jev.v2i0.20389
  35. Groot Koerkamp, B., Rahbari, N. N., Buchler, M. W., Koch, M., & Weitz, J. (2013). Circulating tumor cells and prognosis of patients with resectable colorectal liver metastases or widespread metastatic colorectal cancer: a meta-analysis. Ann Surg Oncol, 20(7), 2156-2165. doi:10.1245/s10434-013-2907-8
  36. Grover, P. K., Cummins, A. G., Price, T. J., Roberts-Thomson, I. C., & Hardingham, J. E. (2014). Circulating tumour cells: the evolving concept and the inadequacy of their enrichment by EpCAM-based methodology for basic and clinical cancer research. Ann Oncol, 25(8), 1506-1516. doi:10.1093/annonc/mdu018
  37. Guardant. (2020). Technical Information. Retrieved from
  38. Guardant. (2022). Retrieved from
  39. Haber, D. A., & Velculescu, V. E. (2014). Blood-based analyses of cancer: circulating tumor cells and circulating tumor DNA. Cancer Discov, 4(6), 650-661. doi:10.1158/2159-8290.Cd-13-1014
  40. Health, G. (2017). Guardant360. Retrieved from
  41. Huang, X., Yuan, T., Tschannen, M., Sun, Z., Jacob, H., Du, M., . . . Wang, L. (2013). Characterization of human plasma-derived exosomal RNAs by deep sequencing. BMC Genomics, 14, 319. doi:10.1186/1471-2164-14-319
  42. Ignatiadis, M., & Dawson, S. J. (2014). Circulating tumor cells and circulating tumor DNA for precision medicine: dream or reality? Ann Oncol, 25(12), 2304-2313. doi:10.1093/annonc/mdu480
  43. Inivata. (2022). InvisionFirst Lung. Retrieved from
  44. Jiang, P., Chan, C. W., Chan, K. C., Cheng, S. H., Wong, J., Wong, V. W., . . . Lo, Y. M. (2015). Lengthening and shortening of plasma DNA in hepatocellular carcinoma patients. Proc Natl Acad Sci U S A, 112(11), E1317-1325. doi:10.1073/pnas.1500076112
  45. Johnson, K., Sexton, Daniel. (2019). Cerebrospinal fluid: Physiology and utility of an examination in disease states. Retrieved from
  46. Kahlert, C., Melo, S. A., Protopopov, A., Tang, J., Seth, S., Koch, M., . . . Kalluri, R. (2014). Identification of double-stranded genomic DNA spanning all chromosomes with mutated KRAS and p53 DNA in the serum exosomes of patients with pancreatic cancer. J Biol Chem, 289(7), 3869-3875. doi:10.1074/jbc.C113.532267
  47. Karabacak, N. M., Spuhler, P. S., Fachin, F., Lim, E. J., Pai, V., Ozkumur, E., . . . Toner, M. (2014). Microfluidic, marker-free isolation of circulating tumor cells from blood samples. Nat Protoc, 9(3), 694-710. doi:10.1038/nprot.2014.044
  48. Kim, S. T., Banks, K. C., Lee, S.-H., Kim, K., Park, J. O., Park, S. H., . . . Lee, J. (2017). Prospective Feasibility Study for Using Cell-Free Circulating Tumor DNA–Guided Therapy in Refractory Metastatic Solid Cancers: An Interim Analysis. JCO Precision Oncology, 1(1), 1-15. doi:10.1200/PO.16.00059
  49. Lanman, R. B., Mortimer, S. A., Zill, O. A., Sebisanovic, D., Lopez, R., Blau, S., . . . Talasaz, A. (2015). Analytical and Clinical Validation of a Digital Sequencing Panel for Quantitative, Highly Accurate Evaluation of Cell-Free Circulating Tumor DNA. PLoS One, 10(10), e0140712. doi:10.1371/journal.pone.0140712
  50. Lee, H., Han, J., & Choi, Y.-L. (2021). Real-World Analysis of the EGFR Mutation Test in Tissue and Plasma Samples from Non-Small Cell Lung Cancer. Diagnostics, 11(9), 1695.
  51. Leighl, N. B., Page, R. D., Raymond, V. M., Daniel, D. B., Divers, S. G., Reckamp, K. L., . . . Papadimitrakopoulou, V. A. (2019). Clinical Utility of Comprehensive Cell-Free DNA Analysis to Identify Genomic Biomarkers in Patients with Newly Diagnosed Metastatic Non-Small Cell Lung Cancer. Clinical Cancer Research, clincanres.0624.2019. doi:10.1158/1078-0432.CCR-19-0624
  52. Lin, X., Fleisher, M., Rosenblum, M., Lin, O., Boire, A., Briggs, S., . . . Pentsova, E. I. (2017). Cerebrospinal fluid circulating tumor cells: a novel tool to diagnose leptomeningeal metastases from epithelial tumors. Neuro Oncol, 19(9), 1248-1254. doi:10.1093/neuonc/nox066
  53. Lindeman, N. I., Cagle, P. T., Aisner, D. L., Arcila, M. E., Beasley, M. B., Bernicker, E. H., . . . Yatabe, Y. (2018). Updated Molecular Testing Guideline for the Selection of Lung Cancer Patients for Treatment With Targeted Tyrosine Kinase Inhibitors: Guideline From the College of American Pathologists, the International Association for the Study of Lung Cancer, and the Association for Molecular Pathology. J Mol Diagn, 20(2), 129-159. doi:10.1016/j.jmoldx.2017.11.004
  54. Lu, T., & Li, J. (2017). Clinical applications of urinary cell-free DNA in cancer: current insights and promising future. Am J Cancer Res, 7(11), 2318-2332.
  55. Luo, J., Shen, L., & Zheng, D. (2014). Diagnostic value of circulating free DNA for the detection of EGFR mutation status in NSCLC: a systematic review and meta-analysis. Sci Rep, 4, 6269. doi:10.1038/srep06269
  56. Marchetti, A., Del Grammastro, M., Felicioni, L., Malatesta, S., Filice, G., Centi, I., . . . Buttitta, F. (2014). Assessment of EGFR mutations in circulating tumor cell preparations from NSCLC patients by next generation sequencing: toward a real-time liquid biopsy for treatment. PLoS One, 9(8), e103883. doi:10.1371/journal.pone.0103883
  57. Mavroudis, D. (2010). Circulating cancer cells. Ann Oncol, 21 Suppl 7, vii95-100. doi:10.1093/annonc/mdq378
  58. MDx. (2018). SelectMDx for Prostate Cancer. Retrieved from
  59. Mellert, H., Foreman, T., Jackson, L., Maar, D., Thurston, S., Koch, K., . . . Pestano, G. A. (2017). Development and Clinical Utility of a Blood-Based Test Service for the Rapid Identification of Actionable Mutations in Non-Small Cell Lung Carcinoma. J Mol Diagn, 19(3), 404-416. doi:10.1016/j.jmoldx.2016.11.004
  60. Mellert, H. S., Alexander, K. E., Jackson, L. P., & Pestano, G. A. (2018). A Blood-based Test for the Detection of ROS1 and RET Fusion Transcripts from Circulating Ribonucleic Acid Using Digital Polymerase Chain Reaction. J Vis Exp(134). doi:10.3791/57079
  61. Merker, J. D., Oxnard, G. R., Compton, C., Diehn, M., Hurley, P., Lazar, A. J., . . . Turner, N. C. (2018). Circulating Tumor DNA Analysis in Patients With Cancer: American Society of Clinical Oncology and College of American Pathologists Joint Review. Journal of Clinical Oncology, 36(16), 1631-1641. doi:10.1200/JCO.2017.76.8671
  62. Miller, M. C., Doyle, G. V., & Terstappen, L. W. (2010). Significance of Circulating Tumor Cells Detected by the CellSearch System in Patients with Metastatic Breast Colorectal and Prostate Cancer. J Oncol, 2010, 617421. doi:10.1155/2010/617421
  63. Murray, N. P., Reyes, E., Badinez, L., Orellana, N., Fuentealba, C., Olivares, R., . . . Duenas, R. (2013). Circulating Prostate Cells Found in Men with Benign Prostate Disease Are P504S Negative: Clinical Implications. J Oncol, 2013, 165014. doi:10.1155/2013/165014
  64. NantHealth. (2018). Physician Brochure. Retrieved from
  65. NantHealth. (2020). Liquid GPS. Retrieved from
  66. NCCN. (2021a, November 12). NCCN Clinical Practice Guidelines in Oncology for Acute Myeloid Leukemia version 1.2022. Retrieved from
  67. NCCN. (2021b, July 16). NCCN Clinical Practice Guidelines in Oncology for Bladder Cancer version 6.2021. Retrieved from
  68. NCCN. (2021c, September 11). NCCN Clinical Practice Guidelines in Oncology for Central Nervous System Cancers version 2.2021. Retrieved from
  69. NCCN. (2021d, January 21). NCCN Clinical Practice Guidelines in Oncology for Colon Cancer version 3.2021. Retrieved from
  70. NCCN. (2021e, December 23). NCCN Clinical Practice Guidelines in Oncology for Esophageal and Esophagogastric Junction Cancers version 1.2022. Retrieved from
  71. NCCN. (2021f, August 4). NCCN Clinical Practice Guidelines in Oncology for Hepatobiliary Cancers version 5.2021. Retrieved from
  72. NCCN. (2021g, July 24). NCCN Clinical Practice Guidelines in Oncology for Neuroendocrine and Adrenal Tumors version 4.2021. Retrieved from
  73. NCCN. (2021h, December 15). NCCN Clinical Practice Guidelines in Oncology for Non-Small Cell Lung Cancer version 1.2022. Retrieved from
  74. NCCN. (2021i, October 23). NCCN Clinical Practice Guidelines in Oncology for Pancreatic Adenocarcinoma version 2.2021. Retrieved from
  75. NCCN. (2021j, January 5). NCCN Clinical Practice Guidelines in Oncology for Prostate Cancer Early Detection version 2.2021. Retrieved from
  76. NCCN. (2021k, January 11). NCCN Clinical Practice Guidelines in Oncology for Small Cell Lung Cancer version 2.2022. Retrieved from
  77. NCCN. (2022a, Feburary 2). NCCN Clinical Practice Guidelines for Prostate Cancer version 3.2022. Retrieved from
  78. NCCN. (2022b, January 15). NCCN Clinical Practice Guidelines in Oncology for Breast Cancer version 2.2022. Retrieved from
  79. NIH. (2017). Extracellular RNA Communication - Home | NIH Common Fund. Retrieved from
  80. Odegaard, J. I., Vincent, J. J., Mortimer, S., Vowles, J. V., Ulrich, B. C., Banks, K. C., . . . Talasaz, A. (2018). Validation of a Plasma-Based Comprehensive Cancer Genotyping Assay Utilizing Orthogonal Tissue- and Plasma-Based Methodologies. Clin Cancer Res, 24(15), 3539-3549. doi:10.1158/1078-0432.Ccr-17-3831
  81. Oncobeam. PRINCIPLES OF BLOOD BASED TESTING. Retrieved from
  82. Oncobeam. (2018). PRINCIPLES OF BLOOD BASED TESTING. Retrieved from
  83. Oncobeam. (2020). BEAMing Digital PCR Technology. Retrieved from
  84. Oxnard, G. R., Thress, K. S., Alden, R. S., Lawrance, R., Paweletz, C. P., Cantarini, M., . . . Janne, P. A. (2016). Association Between Plasma Genotyping and Outcomes of Treatment With Osimertinib (AZD9291) in Advanced Non-Small-Cell Lung Cancer. J Clin Oncol, 34(28), 3375-3382. doi:10.1200/jco.2016.66.7162
  85. Pinzani, P., D'Argenio, V., Del Re, M., Pellegrini, C., Cucchiara, F., Salvianti, F., & Galbiati, S. (2021). Updates on liquid biopsy: current trends and future perspectives for clinical application in solid tumors. Clin Chem Lab Med. doi:10.1515/cclm-2020-1685
  86. Poznak, C. V., Somerfield, M. R., Bast, R. C., Cristofanilli, M., Goetz, M. P., Gonzalez-Angulo, A. M., . . . Harris, L. N. (2016). Use of Biomarkers to Guide Decisions on Systemic Therapy for Women With Metastatic Breast Cancer: American Society of Clinical Oncology Clinical Practice Guideline. doi:10.1200/JCO.2015.61.1459
  87. Quach, N., Goodman, M. F., & Shibata, D. (2004). In vitro mutation artifacts after formalin fixation and error prone translesion synthesis during PCR. BMC Clin Pathol, 4(1), 1. doi:10.1186/1472-6890-4-1
  88. ResolutionBio. (2021). Resolution ctDx Lung™. Retrieved from
  89. Sacher, A. G., Paweletz, C., Dahlberg, S. E., Alden, R. S., O'Connell, A., Feeney, N., . . . Oxnard, G. R. (2016). Prospective Validation of Rapid Plasma Genotyping for the Detection of EGFR and KRAS Mutations in Advanced Lung Cancer. JAMA Oncol, 2(8), 1014-1022. doi:10.1001/jamaoncol.2016.0173
  90. Schneider, B. J., Ismaila, N., Aerts, J., Chiles, C., Daly, M. E., Detterbeck, F. C., . . . Altorki, N. (2019). Lung Cancer Surveillance After Definitive Curative-Intent Therapy: ASCO Guideline. Journal of Clinical Oncology, JCO.19.02748. doi:10.1200/JCO.19.02748
  91. Seeberg, L. T., Waage, A., Brunborg, C., Hugenschmidt, H., Renolen, A., Stav, I., . . . Wiedswang, G. (2015). Circulating tumor cells in patients with colorectal liver metastasis predict impaired survival. Ann Surg, 261(1), 164-171. doi:10.1097/sla.0000000000000580
  92. Sepulveda, A. R., Hamilton, S. R., Allegra, C. J., Grody, W., Cushman-Vokoun, A. M., Funkhouser, W. K., . . . Nowak, J. A. (2017). Molecular Biomarkers for the Evaluation of Colorectal Cancer: Guideline From the American Society for Clinical Pathology, College of American Pathologists, Association for Molecular Pathology, and American Society of Clinical Oncology. J Mol Diagn, 19(2), 187-225. doi:10.1016/j.jmoldx.2016.11.001
  93. Sequist, L., & Neal, J. (2020). Personalized, genotype-directed therapy for advanced non-small cell lung cancer - UpToDate. In S. Vora (Ed.), UpToDate. Retrieved from
  94. Shore, N. (2018). SelectMDx Impacts Prostate Biopsy Decision-making in Routine Clinical Practice. Retrieved from
  95. Sturgeon, C. M., Duffy, M. J., Hofmann, B. R., Lamerz, R., Fritsche, H. A., Gaarenstroom, K., . . . Diamandis, E. P. (2020). National Academy of Clinical Biochemistry Laboratory Medicine Practice Guidelines for Use of Tumor Markers in Liver, Bladder, Cervical, and Gastric Cancers. Clin Chem, 56(6), e1-e48. doi:10.1373/clinchem.2009.133124
  96. Sturgeon, C. M., Duffy, M. J., Hofmann, B. R., Lamerz, R., Fritsche, H. A., Gaarenstroom, K., . . . Diamandis, E. P. (2010). National Academy of Clinical Biochemistry Laboratory Medicine Practice Guidelines for use of tumor markers in liver, bladder, cervical, and gastric cancers. Clin Chem, 56(6), e1-48. doi:10.1373/clinchem.2009.133124
  97. Syeda, M. M., Wiggins, J. M., Corless, B. C., Long, G. V., Flaherty, K. T., Schadendorf, D., . . . Polsky, D. (2021). Circulating tumour DNA in patients with advanced melanoma treated with dabrafenib or dabrafenib plus trametinib: a clinical validation study. Lancet Oncol, 22(3), 370-380. doi:10.1016/s1470-2045(20)30726-9
  98. Thum, T., & Condorelli, G. (2015). Long noncoding RNAs and microRNAs in cardiovascular pathophysiology. Circ Res, 116(4), 751-762. doi:10.1161/circresaha.116.303549
  99. Van Neste, L., Hendriks, R. J., Dijkstra, S., Trooskens, G., Cornel, E. B., Jannink, S. A., . . . Schalken, J. A. (2016). Detection of High-grade Prostate Cancer Using a Urinary Molecular Biomarker-Based Risk Score. Eur Urol, 70(5), 740-748. doi:10.1016/j.eururo.2016.04.012
  100. Vogel, J. D., Felder, S. I., Bhama, A. R., Hawkins, A. T., Langenfeld, S. J., Shaffer, V. O., . . . Paquette, I. M. (2022). The American Society of Colon and Rectal Surgeons Clinical Practice Guidelines for the Management of Colon Cancer. Dis Colon Rectum, 65(2), 148-177. doi:10.1097/dcr.0000000000002323
  101. Waki, K., Yokomizo, K., Yoshiyama, K., Takamori, S., Komatsu, N., & Yamada, A. (2021). Integrity of circulating cell-free DNA as a prognostic biomarker for vaccine therapy in patients with nonsmall cell lung cancer. Immunopharmacol Immunotoxicol, 1-14. doi:10.1080/08923973.2021.1872619
  102. Wang, X. S., Zhao, M. Q., Zhang, L., Kong, D. J., Ding, X. Z., Hu, X. C., . . . Gao, S. G. (2018). Cell-free DNA in blood and urine as a diagnostic tool for bladder cancer: a meta-analysis. Am J Transl Res, 10(7), 1935-1948.
  103. Whiteside, T. L. (2013). Immune modulation of T-cell and NK (natural killer) cell activities by TEXs (tumour-derived exosomes). Biochem Soc Trans, 41(1), 245-251. doi:10.1042/bst20120265
  104. Willis, J., Lefterova, M. I., Artyomenko, A., Kasi, P. M., Nakamura, Y., Mody, K., . . . Odegaard, J. I. (2019). Validation of Microsatellite Instability Detection Using a Comprehensive Plasma-Based Genotyping Panel. Clinical Cancer Research. doi:10.1158/1078-0432.CCR-19-1324
  105. Wu, Y. L., Planchard, D., Lu, S., Sun, H., Yamamoto, N., Kim, D. W., . . . Douillard, J. Y. (2018). Pan-Asian adapted Clinical Practice Guidelines for the management of patients with metastatic non-small-cell lung cancer: a CSCO–ESMO initiative endorsed by JSMO, KSMO, MOS, SSO and TOS. Annals of Oncology, 30(2), 171-210. doi:10.1093/annonc/mdy554
  106. Wu, Y. L., Zhou, C., Liam, C. K., Wu, G., Liu, X., Zhong, Z., . . . Zuo, Y. (2015). First-line erlotinib versus gemcitabine/cisplatin in patients with advanced EGFR mutation-positive non-small-cell lung cancer: analyses from the phase III, randomized, open-label, ENSURE study. Ann Oncol, 26(9), 1883-1889. doi:10.1093/annonc/mdv270
  107. Xu, Y., Lou, J., Yu, M., Jiang, Y., Xu, H., Huang, Y., . . . Zhao, A. (2021). Urinary Exosomes Diagnosis of Urological Tumors: A Systematic Review and Meta-Analysis. Front Oncol, 11, 734587. doi:10.3389/fonc.2021.734587
  108. Yanez-Mo, M., Siljander, P. R., Andreu, Z., Zavec, A. B., Borras, F. E., Buzas, E. I., . . . De Wever, O. (2015). Biological properties of extracellular vesicles and their physiological functions. J Extracell Vesicles, 4, 27066. doi:10.3402/jev.v4.27066
  109. Yu, W., Hurley, J., Roberts, D., Chakrabortty, S., Enderle, D., Noerholm, M., . . . Skog, J. (2021). Exosome-based Liquid Biopsies in Cancer: Opportunities and Challenges. Ann Oncol. doi:10.1016/j.annonc.2021.01.074
  110. Zhang, L., Riethdorf, S., Wu, G., Wang, T., Yang, K., Peng, G., . . . Pantel, K. (2012). Meta-analysis of the prognostic value of circulating tumor cells in breast cancer. Clin Cancer Res, 18(20), 5701-5710. doi:10.1158/1078-0432.ccr-12-1587

Coding Section  


Code Description


BRCA1 (BRCA1, DNA repair associated), BRCA2 (BRCA2, DNA repair associated) (eg, hereditary breast and ovarian cancer) gene analysis; full sequence analysis and full duplication/deletion analysis (ie, detection of large gene rearrangements)


BRCA1 (BRCA1, DNA repair associated), BRCA2 (BRCA2, DNA repair associated) (eg, hereditary breast and ovarian cancer) gene analysis; full sequence analysis


BRCA1 (BRCA1, DNA repair associated), BRCA2 (BRCA2, DNA repair associated) (eg, hereditary breast and ovarian cancer) gene analysis; full duplication/deletion analysis (ie, detection of large gene rearrangements)


EGFR (epidermal growth factor receptor) (eg, non-small cell lung cancer) gene analysis, common variants (eg, exon 19 LREA deletion, L858R, T790M, G719A, G719S, L861Q)


PIK3CA (phosphatidylinositol-4, 5-biphosphate 3-kinase, catalytic subunit alpha) (eg, colorectal and breast cancer) gene analysis, targeted sequence analysis (eg, exons 7, 9, 20)


Unlisted molecular pathology procedure


Cell enumeration using immunologic selection and identification in fluid specimen (eg, circulating tumor cells in blood)


Cell enumeration using immunologic selection and identification in fluid specimen (eg, circulating tumor cells in blood); physician interpretation and report, when required


Oncology, prostate cancer, mRNA expression assay of 12 genes (10 content and 2 housekeeping), RT-PCR test utilizing blood plasma and urine, algorithms to predict high-grade prostate cancer risk
Proprietary test: NeoLAB™ Prostate Liquid Biopsy
Lab/Manufacturer: NeoGenomics Laboratories


Oncology (colorectal) screening, cell enumeration of circulating tumor cells, utilizing whole blood, algorithm, for the presence of adenoma or cancer, reported as a positive or negative result
Proprietary test: FirstSightCRC
Lab/Manufacturer: CellMax Life


Oncology (breast cancer), DNA, PIK3CA (phosphatidylinositol-4,5-bisphosphate 3-kinase, catalytic subunit alpha) (eg, breast cancer) gene analysis (ie, p.C420R, p.E542K, p.E545A, p.E545D [g.1635G>T only], p.E545G, p.E545K, p.Q546E, p.Q546R, p.H1047L, p.H1047R, p.H1047Y), utilizing formalin-fixed paraffin-embedded breast tumor tissue, reported as PIK3CA gene mutation status

Proprietary test: therascreen® PIK3CA RGQ PCR Kit

Lab/Manufacturer: QIAGEN


Oncology (breast cancer), DNA, PIK3CA (phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha) gene analysis of 11 gene variants utilizing plasma, reported as PIK3CA gene mutation status
Proprietary test: therascreen® PIK3CA RGQ PCR Kit
Lab/Manufacturer: QIAGEN


Oncology (non-small cell lung cancer), cell-free DNA, targeted sequence analysis of 23 genes (single nucleotide variations, insertions and deletions, fusions without prior knowledge of partner/breakpoint, copy number variations), with report of significant mutation(s)
Proprietary test: Resolution ctDx Lung™
Lab/Manufacturer: Resolution Bioscience


BCAT1 (Branched chain amino acid transaminase 1) or IKZF1 (IKAROS family zinc finger 1) (eg, colorectal cancer) promoter methylation analysis
Proprietary test: Colvera®
Lab/Manufacturer: Clinical Genomics Pathology Inc


Oncology (lung cancer), four-probe FISH (3q29, 3p22.1, 10q22.3, 10cen) assay, whole blood, predictive algorithm-generated evaluation reported as decreased or increased risk for lung cancer
Proprietary test: LungLB®
Lab/Manufacturer: LungLife AI®

Procedure and diagnosis codes on Medical Policy documents are included only as a general reference tool for each policy. They may not be all-inclusive.

This medical policy was developed through consideration of peer-reviewed medical literature generally recognized by the relevant medical community, U.S. FDA approval status, nationally accepted standards of medical practice and accepted standards of medical practice in this community, Blue Cross Blue Shield Association technology assessment program (TEC) and other nonaffiliated technology evaluation centers, reference to federal regulations, other plan medical policies and accredited national guidelines.

"Current Procedural Terminology © American Medical Association. All Rights Reserved" 

History From 2016 Forward     


Annual review, removing "up to 50 genes" from criteria #3, also updating rationale, references and coding. 


Interim review, removing microsatellite instability analysis and tumor mutational burden language as it will migrate to a new policy. Also updating coding, rationale and references. 


Annual review, adding medical necessity statements regarding BRCA1/2. Also updating description, rationale, references and coding. 


Annual review, updating policy verbiage to include additional diagnoses for coverage, microsatellite instability analysis and repeat testing. Also adding more specific criteria regarding testing that is not medically necessary. Also updating coding. 


Interim review to provide verbiage regarding PIK3CA mutation testing, updating medical necessity criteria for Stage IIIb/IV NSCLC testing. Reformatting policy for clarity. 


Annual review, no change to policy intent. Updating coding. 


Interim review of policy to allow for medical necessity criteria related to Guardant360 testing. Also updating description, references and coding. 


Annual review, policy being rewritten entirely to allow for limited indications being medically necessary.


Annual review, no change to policy intent. 


Update review date. No other changes made. No change to policy intent 



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