Microarray-Based Gene Expression Profile Testing for Multiple Myeloma Risk Stratification

POLICY NUMBER

A.2.04.97

DESCRIPTION

Multiple myeloma is a genetically complex—and invariably fatal—disease. A host of well-characterized factors related to tumor biology, tumor burden, and patient-centered characteristics are used to stratify individuals into high-, intermediate-, and standard-risk categories for prognostic purposes, as well as determining treatment intensity. However, clinical outcomes have varied among individuals in the same risk category who received similar therapy. Thus, more specific methods have been sought to classify multiple myeloma; one such method being proposed is the utilization of a microarray-based gene expression profile (GEP) analysis, which serves to reveal the underlying activity of cellular biologic pathways. This method lends itself to a variety of benefits including the ability to risk-stratify individuals with multiple myeloma, as well as guide treatment decisions.

Multiple Myeloma

Multiple myeloma is a genetically complex—and invariably fatal—neoplasm of plasma cells.

Disease Description

Multiple myeloma is a malignant plasma cell dyscrasia characterized by clonal proliferation of plasma cells derived from B cells in the bone marrow. It accounts for about 1 in every 100 cancers and 13% of hematologic cancers. The American Cancer Society has estimated 35,780 new cases of multiple myeloma will occur in the United States in 2024, and some 12,540 deaths will occur due to the disease. The annual age-adjusted incidence is about 7 cases per 100,000 persons, with a median age-at-diagnosis of about 70 years. Before the advent of current treatment protocols, most patients with multiple myeloma succumbed to their disease within 5 to 10 years; in the pre-chemotherapy era, median survival was less than one year. Among patients who present at an age younger than 60 years, 10-year overall survival with current treatment protocols may now exceed 30%. Black individuals have double the risk of multiple myeloma compared with White individuals and tend to be diagnosed with multiple myeloma at a younger age. Furthermore, Hispanic individuals have a slightly higher incidence rate than White individuals (6.7 per 100,000 vs. 6.2 per 100,100). Recent US Surveillance, Epidemiology, and End Results Program data estimates that the 5-year age-adjusted mortality rate of Black individuals due to multiple myeloma is 6.2 per 100,000, compared with 3.1 per 100,000 White individuals. However, the 5-year relative survival appears to comparable at 53.9% and 51.3% for Black and White individuals in the US, respectively. When treatment is standardized, there is some evidence that Black individuals have superior survival after multiple myeloma diagnosis compared to White individuals, suggesting that Black individuals have a more indolent disease subtype. However, significant disparities in treatment use, access, and referral patterns persist that may impair clinical outcomes.

Criteria for the diagnosis, staging, and response assessment of multiple myeloma developed by the International Myeloma Working Group are in widespread use. The decision to treat is based on criteria set forth in the diagnosis of multiple myeloma, which includes calcium elevation; renal insufficiency; anemia; and bone disease (CRAB). Patients with monoclonal gammopathy of undetermined significance (MGUS) or smoldering myeloma do not require therapy, irrespective of any associated risk factors, except on specifically targeted protocols.

Pathogenesis and Genetic Architecture of Multiple Myeloma

Multiple myeloma is a complex disease that presents itself in distinct clinical phases and risk levels. They include MGUS and smoldering multiple myeloma (also known as asymptomatic myeloma). Monoclonal gammopathy of undetermined significance is a generally benign condition, with a transformation rate to symptomatic plasma cell disorders of about 1% to 2% annually. Smoldering multiple myeloma represents a progression from MGUS to frank multiple myeloma; the risk of the disease transforming to multiple myeloma is about 10% for the first 5 years. Although both of these conditions lack many clinical features of multiple myeloma, they may ultimately share characteristics that necessitate therapy. By contrast, symptomatic multiple myeloma is defined by specific clinical symptoms, accumulation of monoclonal immunoglobulin proteins in the blood or urine, and associated organ dysfunction (including nephropathy and neuropathy). The acronym CRAB reflects the hallmark features of multiple myeloma. Pre-myeloma plasma cells initially require interaction with the bone marrow microenvironment; however, during disease progression, the cells develop the ability to proliferate outside the bone marrow, manifesting as extramedullary myeloma and plasma cell leukemia. These “bone marrow independent” cells represent the end stages in a multistep transformation process from normal to multiple myeloma.

As outlined below, complex genetic abnormalities, commonly identified in multiple myeloma plasma cells, are considered to play major roles in disease initiation, progression and pathogenesis; further, these abnormalities are used in conjunction with laboratory and radiographic studies to stratify patients for therapeutic decisions.

Diagnosis

Cytogenetic and other laboratory tests identify markers to classify newly diagnosed multiple myeloma patients into high, intermediate, and standard clinical risk categories. The level of risk reflects the aggressiveness of the disease, and ultimately dictates the intensity of initial treatment. Thus, a risk-adapted approach provides optimal therapy to patients, ensuring intense treatment for those with aggressive disease. Further, this approach minimizes toxic effects, thereby delivering sufficient, but less-intense therapy for those with lower risk of disease. However, it should be noted that clinical outcomes can vary substantially, using even the most standard methods, among patients with the same estimated risk who undergo a similar intensity of treatment.

Microarray-based gene expression profile (GEP) analysis can be used to estimate the underlying activity of cellular biological pathways, and these pathways control a host of mechanisms such as cell division, cell proliferation, apoptosis, metabolism, or other signaling pathways. Relative over- or under-expression of these pathways is considered to mirror disease aggressiveness, independent of cytogenetics and other laboratory measures. Gene expression profile analysis has been proposed as a means to more finely stratify multiple myeloma patients into risk categories for two purposes: (1) to personalize therapy selection according to tumor biology, and (2) to avoid over- or under-treating patients. Moreover, GEP analysis could be used as a supplement to existing stratification methods, or as a stand-alone test; however, further study is needed to confirm that the analysis has the capability to perform those roles.

The term “gene expression” refers to the process by which the coded information of genes (DNA) is transcribed into messenger RNA (mRNA) and translated into proteins. A GEP assay simultaneously examines the patterns of multiple genes in a single tissue sample; it does this to identify those that are actively producing mRNA or not, ultimately producing proteins or not. By concurrently measuring the cellular levels of mRNA of thousands of genes, a GEP test creates a picture of the rate at which those genes are expressed in a tissue sample.

Gene expression profile tests are not “genetic” tests. Genetic tests measure an individual DNA signature to identify genetic changes or variants that remain constant in the genome. Gene expression tests measure the activity of mRNA in a tissue or bodily fluid at a single point, reflecting an individual’s current disease state (or the likelihood of developing a disease). However, because mRNA levels are dynamic and change as a result of disease processes or environmental signals, dynamic changes in these processes can be studied over time. This information thus reflects the pathogenic process, and in theory, can be used to assess the effects of therapeutic interventions or select therapy based on specifically expressed gene targets.

Gene Expression Analysis of Cancer Using Microarray Technology

Gene expression profile analysis using microarray technology is based on the Watson-Crick pairing of complementary nucleic acid molecules. A collection of DNA sequences, referred to as “probes,” are “arrayed” on a miniaturized solid support (the “microarray”). They are used to determine the concentration of the corresponding complementary mRNA sequences, called ”targets,” isolated from a tissue sample. Laboratory advancements in attaching nucleic acid sequences to solid supports, combined with robotic technology, have allowed investigators to miniaturize the scale of the reactions. As a result of these advances, it is possible to assess the expression of thousands of different genes in a single reaction.

A basic microarray GEP analysis uses mRNA targets that have been both harvested from a patient’s tissue sample and labeled with a fluorescent dye. These samples are hybridized to the DNA probe sequences attached to the microarray medium, then incubated in the presence of mRNA from a different sample labeled with a different fluorescent dye. In a 2 color experimental design, samples can be directly compared with one another or with a common reference mRNA, and their relative expression levels can be quantified. After hybridization, grayscale images corresponding to fluorescent signals are obtained by scanning the microarray with dedicated instruments; the fluorescence intensity corresponding to each gene is quantified by specific software. After normalization, the intensity of the hybridization signals can be compared to detect differential expression by using sophisticated computational and statistical techniques.

Technical variability is a major concern in the use of microarray technologies for clinical management. For example, the source of mRNA is a technical variable that can affect test results. A typical biopsy sample from a solid tumor contains a mixture of malignant and normal (stromal) cells that, in turn, will yield total RNA that reflects all the cells contained in the specimen. To address this, tissue samples may be macro- or microdissected (prior to RNA extraction) to ensure that the specimens contain a sufficiently representative percentage of cancer cells to reflect the disease. For analysis of hematologic cancers, including multiple myeloma, immunomagnetic cell separation technology is used to isolate and enrich cancerous cells from bone marrow aspirates that contain a mixture of cell types.

The instability of mRNA compared to DNA complicates GEP analysis studies, especially when comparing the method with genomic analyses. Two factors that affect RNA quality include pre-analysis storage time and the reagents used to prepare mRNA. Moreover, pH changes in the storage media can trigger mRNA degradation, as can ribonucleases present in cells, which can remain active in the RNA preparation if not stringently controlled.

As noted, Watson-Crick hybridization of complementary nucleic acid moieties in the sequences of mRNA and DNA is the basis of any microarray-based GEP test. This means that sequence selection and gene annotation are among the most important factors that can contribute to analytic variability, hence validity, in results. Different technologic platforms, protocols, and reagents can affect the analytic variability of the results, and therefore affect reproducibility within and across laboratories. Gene expression measures are virtually never used as raw output but undergo sequential steps of mathematical transformation; thus, data preprocessing and analysis may increase variability in results. Moreover, different levels of gene expression can be further processed and combined, according to complex algorithms, to obtain composite summary measurements that are associated with the phenotype(s) under investigation. A statistical analytic technique known as “unsupervised clustering analysis” is applied to the data to produce a visual display, known as a “dendrogram” that shows a hierarchy of similar genes, differentially expressed as mRNA.

International standards have been developed to address the quality of microarray-based GEP analysis. These standards focus on documentation of experimental design, details, and results. Additional topics of interest include interplatform and interlaboratory reproducibility. Quality control efforts emphasize the importance of minimizing the sources of variability in gene expression analysis, thus ensuring that the information derived from such analyses is specific and does not represent accidental associations.

Prognosis and Risk Stratification

Two validated clinical systems are in widespread use to assess prognosis in newly diagnosed multiple myeloma patients: the Durie-Salmon Staging System and the International Staging System. The Durie-Salmon Staging System provides a method to measure multiple myeloma tumor burden, based on multiple myeloma cell numbers and clinical, laboratory, and imaging studies; however,the system hassignificant shortcomings due to its use of observer-dependent studies (e.g., radiographic evaluation of bone lesions), primarily focused on tumor mass, not behavior. The International Staging System, incorporating serum albumin and β2-microglobulin measures, is considered valuable because it permits comparison of outcomes across clinical trials; it is even more reproducible than the Durie-Salmon Staging System. However, the International Staging System is useful only if a diagnosis of multiple myeloma has already been made; it has no role in MGUS, smoldering multiple myeloma, or related plasma cell dyscrasias. Further, the International Staging System does not provide a good estimate of tumor burden, nor is it generally useful for therapeutic risk stratification. In fact, it may not retain prognostic significance in the era of novel drug therapies.

Although multiple myeloma cells may appear morphologically similar across risk levels, the disease exhibits substantial genetic heterogeneity that may change with progression or at relapse. Investigators have used conventional cytogenetic methods (karyotyping) and fluorescence in situ hybridization (FISH) to prognostically stratify multiple myeloma patients according to a host of recurrent chromosomal changes (immunoglobulin heavy chain translocations, chromosome deletions, or amplification). This stratification forms the basis of the Mayo Stratification of Myeloma and Risk-Adapted Therapy, an evidence-based algorithm to facilitate treatment decisions for patients with newly diagnosed multiple myeloma.

Mayo Clinic Stratification of Multiple Myeloma and Risk-Adapted Therapy

FISH: fluorescence in situ hybridization; GEP: gene expression profile.

In addition to the cytogenetic characteristics noted in the table, other findings are typically considered in this model. Although GEP analysis is included in the table, the Mayo Clinic does not currently recommend or routinely perform GEP analysis in a nonresearch setting.

The risk-stratification model outlined in the table is meant to prognosticate and to determine the treatment approach; it is not used to decide whether to initiate therapy (see Therapy Synopsis subsection). Furthermore, therapeutic outcomes among individuals in these categories may vary significantly, to the extent that additional means of subdividing patients into response groups are under investigation. In particular, molecular profiling using microarray-based methods.

Therapy Synopsis

Asymptomatic (smoldering) multiple myeloma and MGUS currently require only ongoing clinical observation (this is because early treatment with conventional chemotherapy has shown no benefit). However, for symptomatic patients diagnosed with multiple myeloma, prompt induction therapy is indicated. Induction therapy generally consists of an immunomodulatory drug (most often lenalidomide), a proteasome inhibitor (eg, bortezomib), and dexamethasone, and may include daratumumab. Eligible patients will then undergo autologous hematopoietic cell transplantation; following transplantation, or induction in transplant-ineligible patients, treatment will typically continue with low-dose maintenance therapy (eg, with lenalidomide).

Gene Expression Profile Test

The MyPRS/MyPRS Plus GEP70 test analyzes the human genome to determine the level of aggressiveness of diagnosed multiple myeloma based on 70 of the most relevant genes involved in cellular signaling and proliferation.

Clinical laboratories may develop and validate tests in-house and market them as a laboratory service; laboratory-developed tests must meet the general regulatory standards of the Clinical Laboratory Improvement Amendments. The MyPRS™/MyPRS Plus™ GEP70 test was acquired by Quest Diagnostics in December 2016.Laboratories that offer laboratory-developed tests must be licensed by the Clinical Laboratory Improvement Amendments for high-complexity testing. To date, the U.S. Food and Drug Administration has chosen not to require any regulatory review of this test.

POLICY

Microarray-based gene expression profile testing for multiple myeloma is considered investigational for all indications.

POLICY EXCEPTIONS

None

POLICY GUIDELINES

The coverage guidelines outlined in the Medical Policy Manual should not be used in lieu of the Member's specific benefit plan language.

According to Mayo Clinic recommendations, a large number of prognostic factors have been validated and categorized into three main groups: tumor biology, tumor burden, and patient-related factors. These factors must be considered to individualize the choice of therapy in individuals with multiple myeloma.

Prognostic Factors in Multiple Myeloma

ECOG: Eastern Cooperative Oncology Group; GEP: gene expression profile.ªThe Mayo Clinic does not currently recommend or routinely perform GEP analysis in a nonresearch setting.

Investigative is defined as the use of any treatment procedure, facility, equipment, drug, device, or supply not yet recognized as a generally accepted standard of good medical practice for the treatment of the condition being treated and; therefore, is not considered medically necessary. For the definition of Investigative, “generally accepted standards of medical practice” means standards that are based on credible scientific evidence published in peer-reviewed medical literature generally recognized by the relevant medical community, and physician specialty society recommendations, and the views of medical practitioners practicing in relevant clinical areas and any other relevant factors. In order for equipment, devices, drugs or supplies [i.e, technologies], to be considered not investigative, the technology must have final approval from the appropriate governmental bodies, and scientific evidence must permit conclusions concerning the effect of the technology on health outcomes, and the technology must improve the net health outcome, and the technology must be as beneficial as any established alternative and the improvement must be attainable outside the testing/investigational setting.

POLICY HISTORY

04/01/2014: Approved by Medical Policy Advisory Committee.

09/03/2014: Policy reviewed; no changes.

07/31/2015: Code Reference section updated for ICD-10.

12/03/2015: Policy description updated regarding multiple myeloma and laboratory testing. Policy statement unchanged. Paragraph regarding criteria for diagnosing multiple myeloma moved from policy guidelines section to the description section. Investigative definition updated in policy guidelines.

06/07/2016: Policy number A.2.04.97 added.

12/14/2017: Policy description updated regarding prognosis and risk stratification. Policy statement unchanged. Policy Guidelines updated to add prognostic factors in multiple myeloma.

10/30/2018: Policy description updated regarding new data for estimated cases of multiple myeloma. Policy statement unchanged.

11/18/2019: Policy reviewed; no changes.

11/19/2020: Policy description updated regarding new multiple myeloma data. Policy statement unchanged.

01/14/2022: Policy description updated regarding new multiple myeloma data. Policy statement unchanged.

12/13/2022: Policy description updated regarding individuals at risk of multiple myeloma. Policy statement unchanged. Policy Guidelines updated.

11/14/2023: Policy description updated regarding multiple myeloma and therapy. Policy statement unchanged.

01/09/2025: Policy description updated regarding new data for multiple myeloma. Policy statement unchanged. Policy description updated.

SOURCE(S)

Blue Cross and Blue Shield Association Policy #2.04.97

CODE REFERENCE

This may not be a comprehensive list of procedure codes applicable to this policy.

Investigational Codes

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