CAM 167

General Genetic Testing, Somatic Disorders

Category:Medicine   Last Reviewed:April 2021
Department(s):Medical Affairs   Next Review:April 2022
Original Date:April 2017    

Somatic mutation refers to a genetic alteration in DNA that occurs after conception and is often linked to the development of cancer. Somatic mutations can occur in any of the cells of the body except the germ cells (reproductive) and, therefore, are not passed on to offspring.

Genetic testing is a type of diagnostic testing that identifies changes in chromosomes, genes or proteins. Genetic testing is used to confirm or rule out a suspected genetic condition or to help determine likelihood of developing or passing on a genetic disorder (National Institutes of Health, 2017). 

Several methods can be used for genetic testing (National Institutes of Health, 2017): 

  • Molecular genetic tests (or gene tests) study single genes or short lengths of DNA to identify variations or mutations. This may include tests for monitoring minimal residual disease (e.g., RNA tests). 
  • Chromosomal genetic tests analyze whole chromosomes or long lengths of DNA to see if there are large genetic changes, such as an extra copy of a chromosome, that cause a cancer (e.g., chronic myelogenous leukemia).

Somatic mutation testing is done with the goal of providing information on prognosis, disease classification and treatment. Somatic mutation testing typically involves testing of a sample of the patient’s tumor and/or blood to assess for somatic mutation. Genetic germline testing might also be indicated, as well, as part of the overall analysis.

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

This policy addresses the general use of somatic (tumor) genetic testing and applies to all tests for which a policy addressing a specific clinical condition is not available. 

  1. Genetic testing for a specific genetic mutation or mutations that have documented clinical utility is MEDICALLY NECESSARY for diagnosis, selection of therapy, or prognostication when there is a documented benefit based on the presence of such mutations in the tumor, or neoplastic cells.
  2. Repeat testing may be MEDICALLY NECESSARY for recurrence monitoring, OR
  3. Repeat testing may be MEDICALLY NECESSARY when there is the possibility of further genetic alterations in the hematologic malignancy, primary tumor or metastasis AND knowledge of these changes would result in the addition, elimination or alteration of non-investigational therapies.
  4. MSI testing for all soilid tumors is considered MEDICALLY NECESSARY for individuals being considered for pembrolizmab (Keytruda) therapy.
  5. TMB testing for all solid tumors may be MEDICALLY NECESSARY for individuals being considered for pembrolizumab (Keytruda) therapy.

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. Testing with a gene panel containing genes that do not meet the criteria in item 1 above is considered NOT MEDICALLY NECESSARY.

Note: For 5 or more gene tests being run on a tumor specimen (i.e. non-liquid biopsy) on the same platform, such as multi-gene panel next generation sequencing, please refer to AHS-R2162 Reimbursement Policy.

Policy Guidelines 
Changes in genes that are not inherited (somatic mutations) in individuals have been associated with multiple types of cancer. Testing for these gene alterations in a tumor sample can help with determining official diagnosis, prognosis and treatment options.

The National Comprehensive Cancer Network and other professional societies have issued criteria on when this testing could be useful to patients (The National Comprehensive Cancer Network (NCCN) provides extensive guidelines for the diagnosis, treatment and monitoring of cancers by site:

Only somatic mutation testing that can lead to appropriate diagnosis, prognosis and non-investigational treatment is considered medically necessary.

Information about specific genetic disorders, rare disorders research and genomic medicine research activities can be found here:

Gene mutations are referred to as “somatic” if they are not within the germline (i.e. within gametes); therefore, these mutations are not passed on from parent to offspring. Somatic mutations may arise de novo or later in life and are very common in neoplasms. There are many different types of somatic mutations, including single nucleotide polymorphisms (SNPs); structural variations such as deletions, inversions, or translocations, and smaller chromosomal abnormalities such as short tandem repeats or gene fusions. Most mutations do not result in disease.

SNPs are the most common type of genetic mutation, including missense mutations. These mutations are single base-pair changes where one nucleotide replaces a different nucleotide. More than 65% of the diseases caused by genetic mutations are due to SNPs (B. Raby, 2020). Estimates based on whole genome sequencing have placed the average amount of SNPs in any given individual at 2.8 to 3.9 million. Insertion/deletion (indel) polymorphisms are often a single nucleotide but may be up to four nucleotides. SNPs often lead to frameshift mutations that can cause premature stop codons and the failure of the allele.

Structural variations are usually classified as larger than 1,000 base pairs. These include deletions, duplications, inversions, translocations, or ring chromosome formations. Due to the large number of genes affected, these variations commonly lead to severe genetic abnormalities; for example, a major cause of chronic myeloid leukemia is due to the translocation between chromosomes 9 and 22, resulting in a fused gene. The most common structural variation is the copy number variant (CNV), referring to a differing number of DNA segment copies in different individuals. For example, one person may have three copies of a particular segment whereas another may only have two. These variations may lead to dysregulation, gain-of-function, or loss-of-function of the affected genes (B. Raby, 2020). The sensitive genes that require or produce precise quantities of a protein product tend to suffer more from these variations (Bacino, 2019).

Any size mutation may be pathogenic and must be categorized as to how likely the mutation is to cause disease. The American College of Medical Genetics (ACMG) has classified mutations in five categories, which are as follows: pathogenic, likely pathogenic, uncertain significance, likely benign, and benign. The “likely pathogenic” and “likely benign” refer to weaker evidence than their respective pathogenic and benign categories, and “uncertain significance” refers to evidence that does not meet criteria for benignity or pathogenicity or has conflicting evidence from both sides. Prediction algorithms have been used to interpret variants and to predict whether a variant will affect the gene function or splicing of the gene. These algorithms are publicly available but have a tendency of predicting the harmful impact of a variant. The specificity of these databases has been estimated at 60-80%.

Due to the enormous number of variants, as well as the rate that variants are discovered, comprehensive databases of genetic variants have been published and are easily available. For example, the Genome-Wide Repository of Associations Between SNPs and Phenotypes (GRASP) database includes information from over 2,000 studies and over one million variant-related results. Databases focusing on cancer-specific variants, reference sequences, and the general population are all available publicly.

Spontaneous mutations accumulate in somatic cells over a lifetime. Early somatic mutations can cause developmental disorders while the accumulation of mutations throughout life can lead to cancer and contribute to aging (Martincorena & Campbell, 2015). Molecular profiles of tumors have clinical utility in guiding the clinical management of cancer patients, providing diagnostic or prognostic information, or identifying a potential treatment regimen. Increasingly, somatic mutations are being identified in diseases other than cancer, such as neurodevelopmental diseases.

A malignant neoplasm is another term for cancer, which may encompass many types including breast, prostate, skin, lung, rectum, colon, and brain. Gastrointestinal stromal tumors (GISTs) are considered rare neoplasms with approximately 95% of these cancers non-hereditary; GISTs are mainly identified by KIT protein expression with typical mutations in the KIT or platelet-derived growth factor receptor alpha (PDGFRA) genes. These GISTs are the most common mesenchymal tumor of the gastrointestinal tract that originate from the cell of Cajal (Comandini, Damiani, & Pastorino, 2017). Primary prostate and lung tumors have been associated with different types of GISTs such as gastric and small bowel; genetic analysis of one patient found “that the gastric GIST and abdominal tumors were characterized by two different c-KIT mutations.” Extragastrointestinal stromal tumors (EGISTs) are another type of rare neoplasm which also arise in the gastrointestinal tract. Liu et al. (2014) report that an EGIST was identified in the prostate of a male patient. “The results of immunohistochemical staining showed positive immunoreactivity for cluster of differentiation (CD)117 (c-kit), CD34 and DOG1 in the tumor. On mutation analysis, loss of heterozygosity of the c-kit gene was observed in the prostatic EGIST; however, the platelet-derived growth factor receptor-α (PDGFRA) gene was considered to be normal.” Due to the rarity of EGIST of the prostate, immunohistochemistry analysis is important to confirm a diagnosis.

Mutations of the KIT and PDGFRA genes in small cell neuroendocrine carcinoma (SCNEC) of the prostate have been researched by Terada (2012). A total of 706 malignant prostate tumors were identified, and four of these tumors were classified as SCNEC. Of these four tumors, three tumors were positive for KIT, and PDGFRA, among other genes. Molecular genotyping via PCR showed no KIT or PDGFRA mutations (Terada, 2012). Another study completed by McCabe, Spyropoulos, Martin, and Moreno (2008) noted that homeobox C6 (HOXC6) is overexpressed in prostate cancers and completed an analysis of prostate cancer cells to identify which promoters are bound by HOXC6. “We show that HOXC6 directly regulates expression of bone morphogenic protein 7, fibroblast growth factor receptor 2, insulin-like growth factor binding protein 3, and platelet-derived growth factor receptor alpha (PDGFRA) in prostate cells.” The researchers also note that PDGFRA is able to reduce the proliferation of prostate cancer cells, and that if HOXC6 is overexpressed, the effects of PDGFRA inhibition may be overcome. The fusion gene FIP1L1-PDGFRA has also been associated with chronic eosinophilic leukemia.

Clinical biomarkers are widely used for making personalized and actionable decisions for cancer treatment. Tumor mutational burden (TMB), the number of somatic mutations per mega base of the DNA in cancer cells, is an emerging biomarker associated with predicting the response to immunotherapy treatment (NCI, 2021). A high TMB value indicates better treatment outcomes, which is observed in patients with melanoma on CTLA-4 inhibitors and patients with melanoma, non-small-cell lung carcinoma, bladder cancer, microsatellite instability cancers, and pan-tumors on PD-1/PD-L1 inhibitors. High TMB has also been associated with improved outcomes in patients on a combination of PD-1/PD-L1 and CTLA-4 inhibitors. TMB was originally measured with whole-exome sequencing (WES), but this method has limited clinical utility due to a 6–8-week sequencing period and expensive costs. Alternatively, targeted NGS panels can reliably estimate TMB from a subset of the exome with reduced sequencing time and increased clinical application. Two FDA-approved products for calculating TMB include the FoundationOne CDx assay (Foundation Medicine Inc.) and MSK-IMPACT (Memorial Sloan Kettering Cancer Center). Both of these tests, referred to as comprehensive genomic profiling (CGP), can identify all types of "molecular alterations (i.e., single nucleotide variants, small and large insertionā€deletion alterations, copy number alterations, and structural variants) in cancerā€related genes, as well as genomic signatures such as microsatellite instability (MSI), loss of heterozygosity, and TMB." Studies show that TMB calculation from CGP has high concordance with TMB measured from WES. On June 16, 2020, the FDA approved pembrolizumab for the treatment of adult and pediatric patients with a TMB value of greater than 10 mutations per mega base as determined by the FoundationOne CDx assay.

Clinical Validity and Utility
Advancements in technology and availability of sequencing, previously constrained by limitations of sequential single-gene testing on limited patient samples, have led to significant strides in our understanding of the genetic basis of inherited and somatic conditions. Variants detected by genetic testing include inherited germline variants and somatic mutations; next generation sequencing (NGS) has allowed for superior detection of these mutations. The accuracy of NGS varies depending on how many genes are sequenced; fewer genes tends to result in higher accuracy since there will be more “probe-template overlap.” Although Sanger sequencing remains the most accurate at >99.99% accuracy, it cannot sequence a large amount of genes in a timely fashion and is best used for sequencing of a specific gene.

NGS has been used to identify several types of somatic mutations associated with cancer and may help to single out therapeutic targets. Genetic mutations in BRCA1 & 2 are associated with breast and ovarian cancer. Kowalik et al. (2019) have identified somatic genetic mutations in BRCA1 & 2 for ovarian cancer prognostic purposes using NGS. Ovarian cancer tissue samples were used for the analysis. A total of 3% of mutations (6/201) were identified as somatic; with only 24% (49/201) of samples identified with a pathogenic mutation overall (Kowalik et al., 2019). The other 35 mutations were of germline origin. This is similar to the report by Nagahashi et al. (2019) which states that approximately 2.5% of BRCA1 & 2 mutations are somatic.

The clinical validity of a genetic test depends primarily on the expressivity and penetrance of a given phenotype. Penetrance refers to the likelihood of developing a disease when the pathogenic mutation is present, and expressivity refers to the variations in the way the disease is expressed. For example, virtually any mutation in the APC gene will cause symptoms of familial adenomatous polyposis, thereby increasing the clinical validity of an APC assessment. Some conditions may not clinically manifest at all despite a mutated genotype.

The clinical utility of a genetic test generally relies on available treatments for a condition. Conditions such as Huntington’s Disease that do not have many options for treatment will have limited clinical utility compared to another condition even though the actual test is highly valid. Factors such as severity of the disease and management options affect the clinical utility of a genetic test.

Hayano et al. (2016); McCabe et al. (2008) noted that homeobox C6 (HOXC6) is overexpressed in prostate cancers and completed an analysis of prostate cancer cells to identify which promoters are bound by HOXC6.

In a multi-cohort, open-label, non-randomized study to establish the relationship between TMB and pembrolizumab treatment response, 790 patients were tested for TMB with the FoundationOne CDx assay. 102/790 patients had high TMB (≥10 mutations per mega base) in solid tumors of anal, biliary, cervical, endometrial, mesothelioma, neuroendocrine, salivary, small cell lung, thyroid, and vulvar cancers. The overall response rate (ORR) in patients with a high TMB was 29%, with a 4% complete response rate and 25% partial response rate compared to an ORR of 6% in patients with a low TMB. The overall response rate was nearly 5-fold in patients with a high TMB. The authors conclude “TMB could be a novel and useful predictive biomarker for response to pembrolizumab monotherapy in patients with previously treated recurrent or metastatic advanced solid tumours.”

Woodhouse et al. (2020) evaluated the analytical performance of FoundationOne Liquid CDx assay to detect genomic alterations in cancer patients. The assay was evaluated across more than 30 different cancer types in over 300 genes and greater than 30,000 gene variants. "Results demonstrated a 95% limit of detection of 0.40% variant allele fraction for select substitutions and insertions/deletions, 0.37% variant allele fraction for select rearrangements, 21.7% tumor fraction (TF) for copy number amplifications, and 30.4% TF for copy number losses. The false positive variant rate was 0.013% (approximately 1 in 8,000). Reproducibility of variant calling was 99.59%0" In comparison to in situ hybridization and immunohistochemistry, FoundationOne had an overall 96.3% positive percent agreement and > 99.9% negative percent agreement. "These study results demonstrate that FoundationOne Liquid CDx accurately and reproducibly detects the major types of genomic alterations in addition to complex biomarkers such as microsatellite instability, blood tumor mutational burden, and tumor fraction."

Association for Molecular Pathology (AMP), American Society of Clinical Oncology (ASCO), and College of American Pathologists (CAP)
The Joint Commission recommended that somatic variants be categorized by and reported based on their impact on clinical care. The Joint Commission notes that somatic variants include indels, SNVs, fusion genes from genomic rearrangements, and CNVs and should focus on their impact on clinical care. Any variant may be considered a biomarker if it predicts response to therapy, influences prognosis, diagnosis, treatment decisions, or the gene function itself. The Joint Commission proposes four levels for these biomarkers which are as follows:

“1. Level A, biomarkers that predict response or resistance to US FDA-approved therapies for a specific type of tumor or have been included in professional guidelines as therapeutic, diagnostic, and/or prognostic biomarkers for specific types of tumors;

2. Level B, biomarkers that predict response or resistance to a therapy based on well-powered studies with consensus from experts in the field, or have diagnostic and/or prognostic significance of certain diseases based on well-powered studies with expert consensus;

3. Level C, biomarkers that predict response or resistance to therapies approved by FDA or professional societies for a different tumor type (i.e., off-label use of a drug), serve as inclusion criteria for clinical trials, or have diagnostic and/or prognostic significance based on the results of multiple small studies;

4. Level D, biomarkers that show plausible therapeutic significance based on preclinical studies, or may assist disease diagnosis and/or prognosis themselves or along with other biomarkers based on small studies or multiple case reports with no consensus.”

The Joint Commission also includes variants in different tiers based on the amount of evidence there is to support its significance. For example, tier 1 variants include significance of levels A and B and tier 2 includes significance of levels C and D. Tier 3 is variants of unknown significance (VUS), such as variants in cancer genes that have not been reported in any other cancers. These variants are not typically seen in significant frequencies in the general population. When evaluating these variants, the type of mutation and gene function should be considered. Tier 4 is benign variants or likely benign variants. These alleles are often observed in significant amounts in general populations. Tier 3 variants should be reported while ensuring that the most important information is communicated to the patient.

National Comprehensive Cancer Network (NCCN)
Multiple somatic mutations have been incorporated into the diagnostic workups recommended by the NCCN. Furthermore, the NCCN has several guidelines which recommend that gene expression profiling, or multiple gene testing, may be helpful, more efficient and/or cost-effective for selected patients. Please see the individual policies.

American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP)
The ACMG and AMP released criteria on the types and severity of mutations, which are as follows:

  • Very strong evidence of pathogenicity: Null variants (nonsense, frameshifts, canonical +/- 1-2 splice sites, initiation codon, exon deletions) in a gene where loss of function (LOF) is a known mechanism of disease. The guidelines note to use caution in genes where LOF is not a mechanism, if LOF variants are at the 3’ end, if exon skipping occurs, and if multiple transcripts are present.
  • Strong: Amino acid change to a pathogenic version, de novo mutations, established studies supporting a damaging gene or gene product, or if the prevalence of the variant is increased in affected individuals compared to healthy controls. The guidelines note to be careful of changes impacting splicing and if only the paternity has been confirmed.
  • Moderate: Located in a mutational hot spot or well-established functional domain (e.g., active site of an enzyme) without a benign variation, absent from controls in Exome Sequencing Project, 1000 Genomes Project, or Exome Aggregation Consortium, detected in trans with pathogenic variants for a recessive disorder, protein length changes, novel missense changes where a different missense change has been pathogenic before, and a possible de novo mutation.
  • Supporting: Cosegregation with disease in multiple affected family members in a gene definitively known to cause the disease, missense variant in a gene with low rate of benign missense variation, if the mutation has evidence that it is deleterious, if the patient’s phenotype is highly specific for disease with a single genetic cause.

The guidelines also list criteria for benign gene variants.

  • Stand-alone evidence of benignity: Allele frequency is >5% in Exome Sequencing Project, 1000 Genomes Project, or Exome Aggregation Consortium
  • Strong: Allele frequency is greater than expected for disorder, observed in healthy adult with full penetrance at early age, lack of segregation in affected family members (although pathogenic variants may masquerade as nonsegregated), or well-established studies that show no damaging effect on protein production.
  • Supporting: Missense variant of a gene for which truncating mutations are pathogenic, indels in repetitive region of unknown function, silent variants, variants of unknown significance, or a trans version of a cis mutation (Richards et al., 2015).

American College of Medical Genetics (ACMG)
The ACMG has released a list of genes for which secondary findings should be disclosed. Secondary findings refer to incidental findings unrelated to why a genetic test was originally ordered but are of significant clinical value to the patient. The portion of the table containing the conditions, the associated genes, and which variants should be reported is listed below:



Variants to Report

Breast/ovarian cancer


KP (known pathogenic),

EP (expected pathogenic)

Li-Fraumeni syndrome



Peutz-Jeghers syndrome



Juvenile polyposis



PTEN hamartoma syndrome



Lynch syndrome



Familial adenomatous polyposis



MYH-associated polyposis



Von Hippel Lindau syndrome






Tuberous sclerosis complex



Wilms tumor



Multiple endocrine neoplasia 1 or 2

MEN1 (1), RET (2)


Familial medullary thyroid cancer



Hereditary paraganglionoma-pheochromocytoma syndrome


KP, EP for all but SDHAF2 (KP only)

Neurofibromatosis type 2



Hypertrophic or dilated cardiomyopathy


KP, EP for LMNA, GLA, MYBPC3, TNNT2, KP only for MYH7, TNNI3, MYL2

Catacholamenergic polymorphic ventricular tachycardia



Arrhythmogenic right ventricular cardiomyopathy


KP, EP for all but DSP (KP only)

Romano-Ward Long QT syndromes, Brugada syndrome


KP, EP for all

Familial hypercholesterolemia


KP, EP for LDLR, KP only for APOB and PCSK9

Ehlers Danlos syndrome



Marfan syndrome, Loeys-Dietz syndrome, familial thoracic aortic aneurysms and dissections


KP, EP for all

Malignant hyperthermia sensitivity


KP only

Wilson disease (copper metabolism)



Ornithine transcarbamylase deficiency (urea cycle)



American Society of Clinical Oncology (ASCO)
The ASCO published guidelines regarding genetic and genomic testing for cancer susceptibility. These guidelines state that the “ASCO recognizes that concurrent multigene testing (i.e., panel testing) may be efficient in circumstances that require evaluation of multiple high-penetrance genes of established clinical utility as possible explanations for a patient’s personal or family history of cancer. Depending on the specific genes included on the panel employed, panel testing may also identify mutations in genes associated with moderate or low cancer risks and mutations in high-penetrance genes that would not have been evaluated on the basis of the presenting personal or family history… ASCO affirms that it is sufficient for cancer risk assessment to evaluate genes of established clinical utility that are suggested by the patient’s personal and/or family history.”

ASCO released guidelines regarding somatic tumor testing for ovarian cancer. ASCO recommends that “Women diagnosed with clear cell, endometrioid, or mucinous ovarian cancer should be offered somatic tumor testing for mismatch repair deficiency (dMMR).  Somatic tumor testing for BRCA1 and BRCA2 pathogenic or likely pathogenic variants may be reserved for time of recurrence for women who have completed upfront therapy and are currently in observation, as presence of these mutations qualifies the patient for FDA-approved treatments (Konstantinopoulos et al., 2020).”

European Society for Medical Oncology (ESMO)
The ESMO recommends that “Mutational analysis inclusion in the diagnostic work-up of all GISTs should be considered standard practice [II, A] (with the possible exclusion of < 2 cm non-rectal GISTs).” The article also states that “Mutational analysis for known mutations involving KIT and PDGFRA can confirm the diagnosis of GIST, if doubtful (particularly in rare CD117/DOG1-negative suspect GIST). Mutational analysis has a predictive value for sensitivity to molecular-targeted therapy and to prognostic value. Its inclusion in the diagnostic work-up of all GISTs should be considered standard practice.”

The ESMO Translational Research and Precision Medicine Working Group released clinical practice guidelines to define best practice for homologous recombination deficiency (HRD) testing in high-grade serous ovarian, fallopian tube and peritoneal carcinoma (HGSC). ESMO recommends that “pathological evaluation of the tumour tissue specimens used for assessment of somatic molecular alterations is essential.” Regarding homologous recombination repair (HRR) tests, BRCA germline and somatic mutation tests are recommended as they consistently identify the subgroup of ovarian cancer patients who benefit the most from poly-ADP ribose inhibitors (PARPi) therapy. There is insufficient evidence to determine the clinical validity of a panel of non-BRCA HRR genes and BRCA1 or RAD51C promoter methylation to predict PARPi benefit. “In the first-line maintenance setting, germline and somatic BRCA mutation testing is routinely recommended to identify HGSC patients who should receive a PARPi.”

European Society for Medical Oncology (ESMO) Precision Medicine Working Group (2020)
ESMO released clinical practice guidelines on the use of NGS to evaluate patients with metastatic cancers. Overall, ESMO suggests that NGS should be used routinely in patients with metastatic cancers including advanced lung adenocarcinoma, prostate cancer, ovarian cancer, and cholangiocarcinoma. For colon cancer, NGS can be an alternative option to PCR if it does not incur additional costs.

ESMO also recommends that “based on the KN158 trial”, tumor mutational burden (TMB) should be tested in cervical cancers, salivary cancers, thyroid cancers, well- or moderately- differentiated neuroendocrine tumors, and vulvar cancers. ESMO notes that this trial found that pembrolizumab was effective for TMB-high cases of these cancer types.

Patients with other cancers may decide with their physician to order NGS on a large gene panel,  if  "pending no extra cost for the public health care system, and if the patient is informed about the low likelihood of benefit." ESMO states that more evidence is still needed to improve understanding on how to use NGS to treat patients based on precision biomarkers.

Recommendations according to cancer type are summarized below. Recommendations were provided based on the ESCAT scale ranking that calculates the number of patients that would need to be tested with NGS to identify one patient who could be matched to an effective drug. Level I means that the match between drug and genomic alterations has been validated in clinical trials and should drive treatment decision in daily practice. Level II means that alteration has been associated with phase I/phase II trials. Level III means that genome alteration has been validated in another cancer, but not for that specific one. Level IV are hypothetically targetable alterations based on preclinical data.

Cancer Type


Lung Adenocarcinoma

“Tumour multigene NGS to assess level I alterations. Larger panels can be used only on the basis of specific agreements with payers taking into account the overall cost of the strategy (drug included) and if they report accurate ranking of alterations. NGS can either be done on RNA or DNA, if it includes level I fusions in the panel.

Squamous cell lung cancer

No current indication for tumour multigene NGS

Breast cancer

No current indication for tumour multigene NGS

Colon cancer

Multigene tumour NGS can be an alternative option to PCR if it does not result in additional cost

Prostate cancer

Multigene tumour NGS to assess level I alterations. Larger panels can be used only on the basis of specific agreements with payers taking into account the overall cost of the strategy and if they report accurate ranking of alterations.

Gastric cancer

No current indication for tumour multigene NGS

Pancreatic cancer

No current indication for tumour multigene NGS

Hepatocellular carcinoma

No current indication for tumour multigene NGS


Multigene tumour NGS could be recommended to assess level I alterations. Larger panels can be used only on the basis of specific agreements with payers taking into account the overall cost of the strategy (drug included) and if they report accurate ranking of alterations. RNA-based NGS can be used.


Tumour multigene NGS can be used in ovarian cancers to determine somatic BRCA1/2 mutations. In this latter case, larger panels can be used only on the basis of specific agreements with payers taking into account the overall cost of the strategy (drug included) and if they report accurate ranking of alterations. Large panel NGS can be used in carcinoma of unknown primary.

It is recommended to determine TMB in cervical cancer, salivary cancer, thyroid cancers, well-to-moderately differentiated neuroendocrine tumours, vulvar cancer, pending drug access (and in TMB-high endometrial and SCL [small-cell lung cancer] cancers if anti-PD1 antibody is not available otherwise) (Mosele et al., 2020).”

British Sarcoma Group (BSG)
The BSG has published guidelines on the management of GIST and state that the majority of GIST cases are associated with a KIT or PDGFRA mutation. The guidelines recommend the following:

  • “The diagnosis should be made by a pathologist experienced in the disease and include the use of immunohistochemistry and mutational analysis, which should be performed by an accredited laboratory.
  • If neoadjuvant treatment with imatinib is planned, it is vital to confirm the diagnosis, since there is a wide differential. It may be necessary to perform a percutaneous core needle biopsy if the tumour is inaccessible to endoscopic ultrasound-guided biopsy. Mutational analysis is obligatory, since some GISTs are insensitive to imatinib (e.g. those with D842V mutation in exon 18 of PDGFRA).”


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  20. Marabelle, A., Fakih, M., Lopez, J., Shah, M., Shapira-Frommer, R., Nakagawa, K., . . . Bang, Y.-J. (2020). Association of tumour mutational burden with outcomes in patients with advanced solid tumours treated with pembrolizumab: prospective biomarker analysis of the multicohort, open-label, phase 2 KEYNOTE-158 study. The Lancet Oncology, 21(10), 1353-1365. doi:10.1016/S1470-2045(20)30445-9
  21. Martincorena, I., & Campbell, P. J. (2015). Somatic mutation in cancer and normal cells. Science, 349(6255), 1483-1489. doi:10.1126/science.aab4082
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  24. Miller, R. E., Leary, A., Scott, C. L., Serra, V., Lord, C. J., Bowtell, D., . . . Yates, L. R. (2020). ESMO recommendations on predictive biomarker testing for homologous recombination deficiency and PARP inhibitor benefit in ovarian cancer. Annals of Oncology, 31(12), 1606-1622. doi:10.1016/j.annonc.2020.08.2102
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Coding Section 

Code Numer Description
CPT  81168 (effective 01/01/2021)  CCND1/IGH (t(11;14)) (eg, mantle cell lymphoma) translocation analysis, major breakpoint, qualitative and quantitative, if performed 
  81175  ASXL1 (additional sex combs like 1, transcriptional regulator) (eg, myelodysplastic syndrome, myeloproliferative neoplasms, chronic myelomonocytic leukemia) gene analysis; full gene sequence 
  81176  ASXL1 (additional sex combs like 1, transcriptional regulator) (eg, myelodysplastic syndrome, myeloproliferative neoplasms, chronic myelomonocytic leukemia) gene analysis; targeted sequence analysis (eg, exon 12) 
  81191 (effective 01/01/2021)  NTRK1 (neurotrophic receptor tyrosine kinase 1) (eg, solid tumors) translocation analysis 
  81192 (effective 01/01/2021)   NTRK2 (neurotrophic receptor tyrosine kinase 2) (eg, solid tumors) translocation analysis 
  81193 (effective 01/01/2021)   NTRK3 (neurotrophic receptor tyrosine kinase 3) (eg, solid tumors) translocation analysis 
  81194 (effective 01/01/2021)   NTRK (neurotrophic-tropomyosin receptor tyrosine kinase 1, 2, and 3) (eg, solid tumors) translocation analysis 
  81204 (effective 01/01/2019) AR (androgen receptor) (eg, spinal and bulbar muscular atrophy, Kennedy disease, X chromosome inactivation) gene analysis; characterization of alleles (eg, expanded size or methylation status)
  81233  BTK (Bruton's tyrosine kinase) (eg, chronic lymphocytic leukemia) gene analysis, common variants (eg, C481S, C481R, C481F) 
  81236  BTK (Bruton's tyrosine kinase) (eg, chronic lymphocytic leukemia) gene analysis, common variants (eg, C481S, C481R, C481F) 
  81261  IGH@ (Immunoglobulin heavy chain locus) (eg, leukemias amd lymphomas, B-cell), gene rearrangement analysis to detect abnormal clonal population(s); amplified methodology (eg, polymerase chain reaction) 
  81262 direct probe methodology (eg, Southern blot)
  81263 IGH@ (Immunoglobulin heavy chain locus) (eg, leukemias and lymphoma, B-cell), variable region somatic mutation analysis
  81264 IGK@ (Immunoglobulin kappa light chain locus) (eg, leukemia and lymphoma, B-cell) gene-rearrangement analysis, evaluation to detect abnormal clonal population(s)

Comparative analysis using Short Tandem Repeat (STR) makers; patient and comparative specimen (eg, pre-transplant recipient and donor germline testing, post-transplant non-hematopoietic recipient germline [eg, buccal swab or other germline tissue sample] and donor testing, twin zygosity testing, or maternal cell contamination of fetal cells)

  81266 each additional specimen )eg, additional cord blood donor, additional fteal samples from different cultures, or additional zygosity in multiple birth pregnancies) [List separately in addition to code for primary procedure]
  81267  Chimerism (engraftment) analysis, post transplantation specimen (eg, hematopoietic stem cell), includes comparison to previously performed baseline analyses; without cell selection 
  81268  Chimerism (engraftment) analysis, post transplantation specimen (eg, hematopoietic stem cell), includes comparison to previously performed baseline analyses; with cell selection (eg, CD3, CD33), each cell type 
  81277 Cytogenomic neoplasia (genome-wide) microarray analysis, interrogation of genomic regions for copy number and loss-of-heterozygosity variants for chromosomal abnormalities 
  81278 (effective 01/01/2021)  IGH@/BCL2 (t(14;18)) (eg, follicular lymphoma) translocation analysis, major breakpoint region (MBR) and minor cluster region (mcr) breakpoints, qualitative or quantitative 
  81301  Microsatellite instability analysis (eg, hereditary non-polyposis colorectal cancer, Lynch syndrome) of markers for mismatch repair deficiency (eg, BAT25, BAT26), includes comparison of neoplastic and normal tissue, if performed
  81305 (effective 01/01/2019)  MYD88 (myeloid differentiation primary response 88) (eg, Waldenstrom's macroglobulinemia, lymphoplasmacytic leukemia) gene analysis, p.Leu265Pro (L265P) variant 
  81314  PDGFRA (platelet-derived growth factor receptor, alpha polypeptide) (eg, gastrointestinal stromal tumor [GIST]), gene analysis, targeted sequence analysis (eg, exons 12, 18) 
  81315 PML/RARalpha, (t(15;17)), (promyelocytic leukemia/retinoic acid receptor alpha) (eg, promyelocytic leukemia) translocation analysis; common breakpoints (eg, intron 3 and intron 6), qualitative or quantitative
  81316 single breakpoint (eg, intron 3, intron 6 or exon 6), qualitative or quantitative
  81340 TRB@ (T cell antigen receptor, beta) (eg, leukemia and lymphoma), gene rearrangement analysis to detect abnormal clonal population(s); using amplification methodology (eg, polymerase chain reaction)
  81341 using direct probe methodology (eg, Southern blot)
  81342 TRG@ ((T cell antigen receptor, gamma) (eg, leukemia and lymphoma), gene rearrangement analysis, evaluation to detect abnormal clonal population(s)
  81347 (effective 01/01/2021)  SF3B1 (splicing factor [3b] subunit B1) (eg, myelodysplastic syndrome/acute myeloid leukemia) gene analysis, common variants (eg, A672T, E622D, L833F, R625C, R625L) 
  81348 (effective 01/01/2021)  SRSF2 (serine and arginine-rich splicing factor 2) (eg, myelodysplastic syndrome, acute myeloid leukemia) gene analysis, common variants (eg, P95H, P95L) 
  81357 (effective 01/01/2021)  U2AF1 (U2 small nuclear RNA auxiliary factor 1) (eg, myelodysplastic syndrome, acute myeloid leukemia) gene analysis, common variants (eg, S34F, S34Y, Q157R, Q157P) 
  81360 (effective 01/01/2021)   ZRSR2 (zinc finger CCCH-type, RNA binding motif and serine/arginine-rich 2) (eg, myelodysplastic syndrome, acute myeloid leukemia) gene analysis, common variant(s) (eg, E65fs, E122fs, R448fs) 
  81370 HLA Class I and II typing, low resolution (eg, antigen equivalents); HLA-A, -B, -C, -DRB1/3/4/5, and -DQB1
  81371 HLA-A, -B, and -DRB1 (eg, verification typing)
  81372 HLA Class I typing, low resolution (eg, antigen equivalents); complete (ie, HLA-A, -B, -C) **Note: When performing both Class I and Class II low resolution typing for HLA-A, -B, -C, -DRB/1/3/4/5 and -DQB1, use 81370

one locus (eg, HLA-A, -B, and - C) each

**Note: when performing a complete Class I (HLA-A, -B, and -C) low resolution HLA typing, use 81372


one antigen equivalent (eg, B*27), each

**Note: When testing for the presence or absence of more than 2 antigen equivalents at a locus, use 81372 for each locus tested
  81375 HLA Class II typing, low resolution (eg, antigen equivalents; HLA-DRB1/3/4/5 and -DQB1

one locus (eg,HLA-DRB1, -DRB 3/4/5, -DQB1, -DQA1, -DPB1, or -DPA1), each

 **Note: When low resolution typing is performed for HLADRB1/3/4/5/ AND -DQB1, use 81375

one antigen equivalent, each

**Note: when testing for more than 2 antigen equivalents at a locus, use 81376 for each locus
  81378 HLA Class I and Class II typing, high resolution (ie, alleles or allele groups), HLA-A, -B, -C, and -DRB1
  81379 HLAClass I typing, high resolution (ie, alleles or allele groups), complete (ie, HLA-A, -B, and -C)
  81380 one locus (ie, HLA-A, -B, or -C) each
  81381 one allele or allele group (eg, B*57:01P), each
  81382 HLA Class Typing II, high resolution (ie, alleles or allele groups), one locus (eg, HLA-DRB1, -DRB3/4/5, -DQB1, -DQA1, DPB1, or -DPA1, each
  81383 one allele or allele group (eg, HLA-DQB1*06:02P), each
  81400 Molecular pathology procedure, Level 1 (eg, identification of single germline variant (eg, SNP) by techniques such as restrictive enzyme digestion or melt curve analysis
  81401 Molecular pathology procedure, Level 2 (eg, 2-10 SNPs, 1 methylated variant, or 1 somatic variant (typically using nonsequencing target variant analysis), or detection of a dynamic mutation disorder/triple repeat
  81402 Molecular pathology procedure, Level 3 (eg, >10 SNPs, 2-10 methylated variants, or 2-10 somatic variants [typically using non-sequencing target variant analysis], immunoglobulin and T-cell receptor gene rearrangements, duplication/deletion variants of 1 exon, loss of heterozygosity [LOH], uniparental disomy [UPD])
  81403 Molecular pathology procedure, Level 4 (eg, analysis of single exon by DNA sequence analysis, analysis of >10 amplicons using multiplex PCR in 2 or more independent reactions, mutation scanning or duplication/deletion variants of 205 exons)
  81405  Molecular pathology procedure, Level 6 (eg, analysis of 6-10 exons by DNA sequence analysis, mutation scanning or duplication/deletion variants of 11-25 exons, regionally targeted cytogenomic array analysis) 
  81479 Unlisted molecular pathology procedure
  81599 Unlisted multianalyte assay with algorithmic analysis
  88237 Tissue culture for neoplastic disorders; bone marrow, blood cells
  88239 Solid tumor
  88240 Cryopreservation, freezing and storage of cells, each cell line
  88241 Thawing and expansion of frozen cells, each aliquot
  88269 Chromosome analysis, in situ for amniotic fluid cells, count cells from 6-12 colonies, 1 karotype with banding
  88271 Molecular cytogenetics; DNA probe, each (eg, FISH)
  88272 chromosomal in situ hybridization, analyze 3-5 cells (eg, for derivatives and markers)
  88273 chromosomal in situ hybridization, analyze 10-30 cells (eg, for microdeletions)
  88274 interphase in situ hybridization, analyze 25-99 cells
  88275 interphase in situ hybridization, analyze 100-300 cells
  88280 Chromosome analysis; additional karyotypes, each study
  88283 additional specialized banding technique (eg, NOR, C-banding)
  88285 additional cell counted, each study
  88289 additional high resolution study
  88291 Cytogenetics and molecular cytogenetics, interpretation and report
  88299 Unlisted cytogenetic study
  96040 Medical genetics & genetic counseling services
HCPCS  S0265 Genetic counseling, under physician supervision, each 15 minutes
ICD-10 CM C00.0 - C14.8 Malignant neoplasms of lip, oral cavity and pharynx
  C15.3 - C26.9 Malignant neoplasms of digestive organs
  C30.0 - C39.9 Malignant neoplasms of respiratory and intrathoracic organs
  C40.00 - C41.9 Malignant neoplasms of bone and articular cartilage
  C43.0 - C4A.9 Melanoma and other malignant neoplasms of skin
  C45.0 - C49.A9 Malignant neoplasms of mesothelial and soft tissue
  C50.011 - C50.929 Malignant neoplasms of breast
  C51.0 - C58 Malignant neoplasms of female genital organs
  C60.0 - C63.9 Malignant neoplasms of male genital organs
  C64.1 - C68.9 Malignant neoplasms of urinary tract
  C69.00 - C72.9 Malignant neoplasms of eye, brain and other parts of central nervous system
  C73 - C75.9 Malignant neoplasms of thyroid and other endocrine glands
  C76-C80.2  Malignant neoplasms of ill-defined, other secondary and unspecified sites 
  C7A.00 - C7A.8 Malignant neuroendocrine tumors
  C7B.00 - C7B.8 Secondary neuroendocrine tumors
  D75.89 Other specified diseases of blood and blood-forming organs
  Z13.7 Encounter for other screening for genetic and chromosomal anomalies
  Z85.79 Personal history of other malignant neoplasms of lymphoid, hematopoietic and related tissues
  All Z94 Codes Transplanted organ and tissue status  

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 and Blue Shield Association technology assessment program (TEC) and other non-affiliated 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 2017 Forward     


Annual review, adding statement related to Keytruda therapy. Also updating rationale and references. 


 Updating Coding Section with 2021 codes. 


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


Interim review to remove the word "hematologic" from the first medical necessity statement.


Annual review, adding 4th policy statement regarding microsatellite testing for all solid tumors for individuals being considered for pembrolizumab (Keytruda). No other changes to policy intent. Also updating coding. 


Updating with additional 2019 codes.  


Updating with 2019 codes.  


Annual review, no change to policy intent. 


New Policy

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