MolDX: Genome-Wide Molecular Methodologies for the Detection of Copy Number Alterations and Structural Variants in Hematologic Neoplasms

Title XVIII of the Social Security Act, §1862(a)(1)(A) allows coverage and payment for only those services that are considered to be reasonable and necessary.

42 CFR §410.32(a) Diagnostic x-ray tests, diagnostic laboratory tests, and other diagnostic tests: Conditions

CMS Internet-Only Manual, Pub. 100-02, Medicare Benefit Policy Manual, Chapter 15, §80 Requirements for Diagnostic X-Ray, Diagnostic Laboratory, and Other Diagnostic Tests, §80.1.1 Certification Changes

Reference to specific tests in this LCD does not automatically imply coverage.

Testing by non-Next Generation Sequencing (non-NGS) for the diagnosis of myeloproliferative neoplasms must also fulfill criteria outlined in L39919, MolDX: Non-Next Generation Sequencing Tests for the Diagnosis of BCR-ABL Negative Myeloproliferative Neoplasms.

NGS-based tests must also fulfill criteria outlined in L38047, MolDX: Next-Generation Sequencing Lab-Developed Tests for Myeloid Malignancies and Suspected Myeloid Malignancies.

Testing for response to therapy or minimal residual disease (MRD) is out of scope of this policy and must fulfill criteria outlined in L38779, MolDX: Minimal Residual Disease Testing for Cancer.

Criteria for Coverage

Genome-wide molecular assays for the detection of copy number alterations (CNAs) and structural variants (SVs) in hematologic neoplasms are covered when ALL the following requirements are met:

1. The patient is undergoing workup for a hematopoietic neoplasm AND the results of testing will inform either:
   1. diagnosis in accordance with current expert or professional guidelines (e.g., World Health Organization Classification of Haematolymphoid Tumours (WHO), International Consensus Classification of Myeloid and Lymphoid Neoplasms (ICC)), and other reasonably possible causes have been considered and excluded, as documented in the medical record; OR
   2. clinical management in accordance with current expert or professional guidelines (e.g., National Comprehensive Cancer Network (NCCN)) at the time of initial neoplastic diagnosis made by non-molecular testing (i.e., flow cytometry or morphology) or upon non-molecularly confirmed progression or relapse.
      1. MRD testing is not considered within scope of this LCD.
2. Testing for CNAs and SVs has not already been performed and is not in the process of being performed by another genome-wide molecular methodology or by multiple (>1) other chromosomal and/or molecular methodologies (e.g., chromosome banding analysis, CBA; fluorescence in situ hybridization, FISH; chromosomal microarray, CMA; next generation sequencing, NGS) unless one of the following apply:
   1. A rapid targeted test was performed for PML::RARA to evaluate for acute promyelocytic leukemia (APL) or BCR::ABL to inform initiation of therapy in leukemia, and additional genomic information is necessary.
   2. The patient was confirmed to have a hematologic malignancy by flow cytometry or histology, and a complete genomic workup using standard chromosomal/molecular assays (as above) showed a complete absence of abnormalities.
   3. The patient previously had an oncologic workup for the same indication utilizing standard chromosomal/molecular assays (as above) that was negative, and presents with further signs or symptoms (e.g., worsening blood counts) suggestive of malignancy or progression of malignancy in accordance with expert or professional guidelines (as above) and as documented in the medical record.
3. The test has satisfactorily completed a Technical Assessment (TA) by the Molecular Diagnostic Services Program (MolDX^®) to ensure analytical validity (AV), clinical validity (CV) and clinical utility (CU) standards are met.
   1. The test demonstrates detection accuracy for targeted analytes comparable or superior to current gold standards for testing.
   2. The test demonstrates detection accuracy for targeted analytes comparable or superior to other genome-wide tests that have met coverage criteria under this policy.
   3. The test has been validated in the intended use population and with the intended use sample types.

Background

The identification of chromosomal aberrations is critical to the appropriate evaluation of hematological neoplasms for diagnostic classification and risk stratification as defined by the World Health Organization (WHO) Classification of Haematolymphoid Tumours.¹ Additionally, many professional society and expert consensus guidelines endorse testing for various SVs and CNAs for many hematopoietic malignancies. For example, National Comprehensive Cancer Network^® (NCCN) Guidelines recommend cytogenetics by karyotyping for myelodysplastic syndromes (MDS)², FISH for plasma cell myeloma (PCM)³, and both modalities for acute myeloid leukemia (AML)⁴ and chronic lymphocytic leukemia / small lymphocytic lymphoma (CLL/SLL).⁵ The European Leukemia Network (ELN) has issued similar position statements for AML and ALL.^6,7

Traditional methodologies

CBA, or conventional karyotyping, has been routinely performed for over four decades.⁸ The chief advantage of this approach is the ability to discriminate subclonal architecture based upon microscopic visualization at the single-cell level. However, there are several drawbacks. Cell culture is required, which begets an extended turnaround time (TAT) of over a week yet may still yield elevated specimen adequacy failure rates in less mitotically active conditions. Despite some advances in technology (e.g., automated slide scanning), this technique remains largely manual and low-throughput, consuming time and resources. Result quality may also be operator-dependent, with skill generally increasing directly proportionate to experience. Finally, a fundamental disadvantage is the low resolution of ~5-10 Mb. Results may be incompletely characterized, with “marker” chromosomes of uncertain genetic content, and there is insensitivity for “cryptic” alterations of known clinical importance (e.g., NUP98 and MECOM rearrangements, inv(16) with CBFB-MYH11).

FISH utilizes DNA probes coupled to fluorophores to interrogate specific pre-selected alterations.⁸ TAT can be rapid if expedited on an emergency basis (within 24-36 hours) but is usually in the range of a few days. The resolution (~70 kb – 1 Mb) is approximately 10 times greater than CBA. The main disadvantages of FISH are that the targeted nature requires that the analyte of interest be known in advance and therefore dedicated reagents be available for those loci. While a limited number of markers can potentially be multiplexed, panels are generally required since there are now so many targets needed for complete evaluation. There can be additional limitations based upon probe design; for instance, break-apart probes do not identify the partner locus.

CMA technology, including array-based comparative genomic hybridization (aCGH)⁹ and single nucleotide polymorphism (SNP) arrays, is sometimes utilized to identify CNAs. The resolution is comparable to the lower bound of FISH at ~50-200 kb, and more automated procedures allow for higher throughput. However, a major shortcoming is the restriction to alterations with net gain or loss of genetic material; balanced translocations and inversions cannot be detected.¹⁰

NGS panels are most often applied to inspect for single nucleotide variants (SNVs) and small insertion/deletions (indels). NGS panels are also capable of identifying some CNAs and SVs but have several notable limitations.¹¹ CNA detection is limited to DNA-based NGS, as RNA assays can only quantify relative expression levels, which are influenced by more complex factors than gene copy number. There are also typically size limitations that hinder accurate characterization of large-scale changes (such as full-arm or full-chromosome gains and losses).

SVs can also be quite challenging by short-read NGS. Targeted assays require that at least one partner gene be known at the time of assay design, and data analysis on short-read sequencing platforms may be complicated by pseudogene interference. DNA-based tests may require prohibitively extensive primer tiling across low-complexity intronic regions, while RNA-based assays require that a hybrid fusion transcript be expressed. For example, chromosomal rearrangements involving the IGH gene are highly prevalent in lymphoid disorders, yet extremely difficult to detect by NGS.¹² Breakpoints are often intronic and highly variable, making DNA-based methods insensitive; further, the mechanism of action is placement of an oncogene under control of the active IGH promoter, resulting in increased expression rather than a chimeric RNA product. Similarly, oncogenic abnormalities involving the GATA2 and MECOM loci on chromosome 3q often alter expression levels without a change in mRNA sequence.¹³ Validation of appropriate thresholds for defining aberrant RNA expression is particularly challenging in the setting of variable neoplastic cell content, which may even be undefinable in some conditions such as MDS.

Recent and emerging technologies

To address the various shortcomings of current workflows, efforts have been made to improve CNA and SV detection while also streamlining laboratory operations.

Some of the pitfalls of targeted NGS panels regarding CNAs and SVs can be overcome by whole genome sequencing (WGS), which is well-established in the realm of constitutional genetics as being a single alternative to the combination of whole exome sequencing (WES) and CMA.¹⁴ In a study of 263 patients with myeloid neoplasms, WGS detected all 40 recurrent translocations and 91 copy-number alterations that had been identified by cytogenetic analysis, and also provided new genetic information in almost a quarter of patients, which changed the risk category for 16%.¹⁵ However, the significantly lower depth of coverage translates to decreased sensitivity for sequence variants, which are critical alterations to interrogate (i.e. by NGS); notably, these are not detectable by CBA, FISH or CMA. Limits of detection (LODs) for WGS-based tests are often double or more those of their targeted NGS counterparts (e.g., variant allele fractions, VAFs, of 10% vs. ≤5% for SNVs and 15-20% vs. 5-10% for Indels, respectively). Follow-up studies from the same institution utilizing long-read sequencing showed excellent correlation for CNAs and SVs with short-read WGS, but decreased accuracy for SNVs (96%, with 91% precision) and relatively poor performance for Indels (66%, with 42% precision).¹⁶ Nevertheless, long read WGS did improve upon reclassifying interchromosomal SVs called by standard WGS as intronic insertions near repetitive elements.¹⁶

Unlike any methodology previously discussed, optical genome mapping (OGM) utilizes total isolated ultra-high molecular weight (UHMW) DNA, which allows for spanning of repetitive regions and other regions that are difficult to map by shorter read methods. Nucleotide motifs are enzymatically labeled with fluorescent tags, and DNA is digitally imaged as it is linearized in nanochannel chip arrays; the resulting patterns are constructed into profiles, and CNVs and SVs are identified by bioinformatic comparison to a human refence genome database.¹⁷ OGM does not rely on tissue culture, limiting the possibility of culture artifacts, nor on PCR, preventing false overrepresentation due to amplification bias.¹⁸ Testing can be completed in as few as 4-6 days.¹⁹

Studies have reported robust performance of OGM across a spectrum of myeloid and lymphoid disorders and sample types, such as peripheral blood, bone marrow aspirate, CD-138 isolated cells, and lymph node cell suspensions.^20,21 A wide range of CNAs and SVs have been successfully detected, including not only standard translocations and insertions/deletions, but also unusual karyotypic findings like ring chromosomes, isochromosomes, and markers.²⁰ Additionally, OGM recognizes chromoanagenesis (chromothripsis, chromoanasynthesis, and chromoplexy), an indicator of severe of chromosomal damage.^22,23 Chromoanagenesis is frequently associated with highly complex karyotypes and extensive clonal heterogeneity (known poor prognostic factors), as well as treatment refractoriness in AML.²⁴ This phenomenon is extremely difficult, if not impossible, to detect by some currently used methods (e.g., CBA, FISH).²⁴

The resolution of OGM is dependent upon depth of coverage and type of pipeline assembly (e.g., a de novo assembly has lower sensitivity compared to a rare variant pipeline, but can detect SVs smaller in size), but lower limits of ~500 bp – 5 kb can typically be achieved for insertions and deletions.¹⁹ While limits of detection can differ by the type of alteration under consideration, variant allele frequencies of 5-10% (theoretically translating to ~10-20% neoplastic cell content assuming heterozygosity in all tumor cells) are attainable, demonstrating comparable or superior sensitivity to other available testing methodologies.²⁰ However, molecule alignment can be unreliable in regions concentrated around centromeres and telomeres, and while OGM can identify hyper- and hypodiploidy, it cannot dependably distinguish full or near-full polyploidy (e.g., triploidy, tetraploidy, etc.).^18,19

A single-center study of 101 consecutive newly-diagnosed MDS patients²³ demonstrated that OGM found all clonal abnormalities seen on CBA in 97% of patients. In addition, OGM identified 224 clinically meaningful findings not recognized by CBA (as well as ~50 calls of copy neutral loss of heterozygosity, CN-LOH, not detectable by CBA). OGM results changed the comprehensive cytogenetic scoring system (CCSS) and revised international prognostic scoring system (R-IPSS) risk-groups in 21% and 17% of patients, respectively, though the absolute improvements in prediction of prognosis were not statistically different than those obtained by CBA. However, according to a multivariate analysis, CCSS by OGM independently predicted survival but not CCSS by CBA.²³

Investigators from the same institution subsequently described 159 AML patients (103 newly-diagnosed and 56 relapsed/refractory).²² OGM exhibited >99% sensitivity for detecting abnormalities identified by CBA and FISH when the clone represented ≥20% of cells; as would be expected, the few misses contained 3 instances of tetraploidy. OGM refined 17 fusion events called by CBA/FISH to name the gene(s) involved and reported additional findings in 59 patients including 11 critical MECOM, NUP98, and KMT2A rearrangements. Of significance, OGM also recognized KMT2A partial tandem duplications (PTDs), which cannot be detected by CBA or FISH and are most frequently interrogated by NGS. The authors noted that OGM results would have altered AML classification, risk stratification, and/or clinical trial eligibility in 24 patients (15%).²²

OGM testing in a multi-center cohort of 100 AML patients²⁵ demonstrated 98.4% concordance with sentinel events observed by karyotype at ≥5% allelic fraction and 100% concordance with FISH abnormalities seen at >10% allele frequency; sensitivity fell to 90.1% when CBA findings represented <5% allelic fraction. The authors acknowledge that these limits of detection suggest that OGM may not be suitable for detection of low-level clones, precluding use in the MRD setting. OGM also identified alterations not found by routine testing, but confirmed by orthogonal testing, in 13% of these patients. These additional findings would have changed ELN-2022 classification in five cases, and allowed for eight patients to enroll in clinical trials.²⁵

A Belgian study of diagnostic samples from ALL patients²⁶ investigated performance of OGM vs. routine testing. For 29 B-ALL patients, clonal abnormalities were identified by CBA in 79% and by FISH in 72% (with 93% by combined CBA + FISH) compared to 100% by OGM. Similarly, CBA combined with standard FISH identified at least one clonal abnormality in 8/12=67% of T-ALL patients whereas OGM had finding(s) in all of them. OGM failed to distinguish some subclonal aberrations (of no clinical relevance) seen by CMA/FISH but detected others at equivalent or lower frequencies. Importantly, disease-defining abnormalities were detected in 32 cases by OGM compared to only 23 by the standard testing pathway.²⁶

In a comparison of OGM to FISH in 20 PCM patients²⁷ with a minimum of 10% plasma cells following CD-138 enrichment, there were 100%, 92.5% and 95% accuracies for translocations, deletions, and gains, respectively; the lower values for CNAs were attributed to non-diploidy. Notably, all five canonical IGH translocations, gain of odd-numbered chromosomes, and abnormalities of chromosome 13 were detected by OGM. Additionally, OGM revealed additional prognostic markers in six cases, a 30% increase in yield, though follow-up data were not presented.²⁷

An informative karyotype is unavailable in a substantial proportion of patients with myelofibrosis due to inadequate metaphase mitoses for analysis. In an investigation of 21 myelofibrosis patients in Spain,²⁸ all samples generated successful OGM results (all confirmed by FISH or CMA, except one due to lack of available sample) while only 52% had informative CBA results.

The International Consortium for OGM in Hematologic Malignancies has issued consensus guidance^29,30 focusing on validation, quality control, and analysis and interpretation of variants. OGM has also been incorporated into the American College of Medical Genetics and Genomics (ACMG) Technical Laboratory Standards,³¹ albeit for solid tumors, in which the body of knowledge is less advanced.³² Performing laboratories have suggested that a single-workflow methodology would be more time-, labor-and cost-effective.^27,29

Additional novel technologies are also in various stages of evidence accrual, such as genomic proximity mapping (GPM), an NGS-based approach to capture ultra-long-range contiguity information from conventional short-read sequencing as a function of high-throughput chromosome conformation capture (Hi-C) plus artificial intelligence (AI). The underlying premise is that sequences located closer on a chromosome are more likely to physically interact and be crosslinked, so pairwise frequency of crosslinked sequence interactions can be used to determine the structure of chromosomes, such that proximity ligation signal increases as the genomic distance between any two loci across the genome decreases.³³ A major advantage of GPM is the compatibility with archival (formalin-fixed paraffin-embedded, FFPE) samples. The preservation of chromatin structure and ability to assess 3-dimentional genomic architecture also allows for analysis of epigenetics.³⁴ Similar to OGM, GPM also struggles to identify polyploidy and low-level allele burden.³⁴

A preliminary study of GPM in 48 AML samples indicated 100% concordance with SOC for variants with impact on ELN 2022 risk stratification; GPM identified 39 additional variants, including variants of known clinical impact, not observed by cytogenetics.³⁵ Another group reported that GPM showed complete agreement with all aberrations seen by FISH in samples from 5 newly diagnosed PCM patients, and also found supplemental clinically relevant or known recurrent abnormalities in 4/5.³⁶ A third laboratory performed GPM on a mixture of 18 myeloid and lymphoid neoplasms with a >95% concordance with CBA, FISH, CMA and RNA NGS. GPM successfully detected balanced (and unbalanced) chromosomal rearrangements and CN-LOH, and findings not noted by SOC improved the accuracy of disease classification.³⁷

Recognized and respected authorities on diagnosis and treatment in oncology, such as the WHO,¹ NCCN^2-5 and ELN,^6,7 require that complete pathologic evaluations for almost all hematopoietic neoplasms include assessment of SVs and/or CNVs. Clinical validity and utility of these biomarker classes are rooted in decades of hematologic oncology practice. Unfortunately, reliance on traditional standard of care methodologies often necessitates multiple testing workflows, each with its own pro/con profile, and thus suffers from operational inefficiencies and staggered TATs. The analytical performance of newer approaches has been reproducibly shown to be equivalent or superior to the sum of traditional methodologies in multiple clinical studies spanning many different neoplastic hematologic conditions.^{15,17,18,20-23,25-28,33-37}

In particular, modern technologies (e.g., WGS, OGM, GPM) do not require cell culture, permitting rescue of samples that would be uninformative by CBA. The resolution is also orders of magnitude better, allowing for far greater sensitivity. As opposed to targeted FISH panels, these methods analyze the whole genome, permitting a far larger reportable range. Unlike CMA, these approaches can detect SVs without overall loss of genetic material and may be able to identify CN-LOH.

It is acknowledged that newer approaches have limitations. In comparison to targeted NGS, WGS sacrifices VAF LOD in favor of a broader reportable range, and OGM and GPM are also more compatible with higher disease burdens based upon published LOD values. This concern may not represent significant harm in the setting of high-burden disease, such as would usually be expected at times of initial diagnosis and upon progression, but could be meaningful at lower disease content. Additionally, all bulk genome techniques that rely on normalization of copy number lack the ability to discern changes in ploidy. Nevertheless, complex patterns of aneuploidy and SVs with unusual variant frequencies might be utilized as indicators to suggest that alternate confirmatory analyses may be warranted. Furthermore, since OGM is poor at detecting rearrangements between the centromeres or the telomeres, balanced whole-arm and end-to-end telomere fusions are not identified. This deficiency is more relevant in the constitutional setting (e.g., Robertsonian translocations) and is less concerning for oncology. Overall, the benefits outweigh the weaknesses, and there are not intolerable flaws as yet discovered in WGS, OGM or GPM. Consistent with the ever-expanding and evolving state of science and medicine, it is expected that analogous novel methods are in development and may eventually reach evidentiary thresholds that establish reasonable and necessary standards.

It is understood that newer technologies may not be readily implemented in all care settings; the intent of this coverage determination is not to undermine or preclude traditional testing methodologies, but rather to allow for modernized approaches when/where available. The neoplastic cell content should always be considered when choosing the most suitable assay. Importantly, monitoring for response to therapy or presence of MRD is outside the scope of this policy.

In summary, it has been adequately proven that a single test may provide equivalent or greater clinically valid and useful genetic information as could be achieved by the combination of multiple traditional methodologies (including CBA, FISH, and CMA). Therefore, this contractor concludes that genome-wide molecular testing approaches for CNAs and SVs in hematologic neoplasms are reasonable and necessary when all coverage criteria outlined in this policy are fulfilled. Although the evidence reviewed at this time supports alternatives to traditional testing, data are insufficient regarding augmentation of existing strategies. Therefore, concurrent testing by both innovative and conventional methods, outside the limits outlined in the coverage criteria of this LCD, is considered duplicative and not reasonable or necessary.

Finally, this contractor recognizes that there may be exceptional circumstances in which sequential testing (i.e., use of a genome-wide molecular methodology after multiple (>1) other chromosomal and/or molecular methodologies) may be appropriate for the diagnosis or management of the patient according to the outlined criteria. One such example may include an incomplete interpretation/analysis by multiple other test methodologies (i.e., FISH, CMA, NGS) resulting in the failure to obtain the minimum necessary genomic information required for clinical management. Correspondingly, subsequent testing by an alternate methodology to confirm a suspicious, but not definitive, finding detected by molecular genome-wide analysis should only be undertaken if the original results are not fully validated for the platform (e.g., OGM suggestive of polyploidy) and clarification would impact clinical status. Notably, these situations are expected to be rare, and it is expected that the rationale would be documented in the medical record.

1. Haematolymphoid Tumours. 5th ed. vol 11. WHO Classification of Tumours Editorial Board; 2024.
2. NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines). Myelodysplastic Syndromes. Version 3.2026. https://www.nccn.org/professionals/physician_gls/pdf/mds.pdf. Accessed 7/8/2026.
3. NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines). Multiple Myeloma. Version 5.2026. https://www.nccn.org/professionals/physician_gls/pdf/myeloma.pdf. Accessed 7/8/2026.
4. NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines) Acute Myeloid Leukemia. Version 3.2026. https://www.nccn.org/professionals/physician_gls/pdf/aml.pdf. Accessed 7/8/2026.
5. NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines). Chronic Lymphcytic Leukemia / Small Lymphocytic Lymphoma. Version 2.2026. https://www.nccn.org/professionals/physician_gls/pdf/cll.pdf. Accessed 7/8/2026.
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14. Chung CCY, Hue SPY, Ng NYT, et al. Meta-analysis of the diagnostic and clinical utility of exome and genome sequencing in pediatric and adult patients with rare diseases across diverse populations. Genet Med. 2023;25(9):100896. doi:10.1016/j.gim.2023.100896
15. Duncavage EJ, Schroeder MC, O’Laughlin M, et al. Genome sequencing as an alternative to cytogenetic analysis in myeloid cancers. N Engl J Med. 2021;384(10):924-935. doi:doi:10.1056/NEJMoa2024534
16. Abel HJ, Mahgoub M, Davarapalli N, et al. Evaluation of long-read genome sequencing for genomic profiling of myeloid cancers. J Mol Diagn. 2025;27(12):1242-1254. doi:10.1016/j.jmoldx.2025.09.001
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23. Yang H, Garcia-Manero G, Sasaki K, et al. High-resolution structural variant profiling of myelodysplastic syndromes by optical genome mapping uncovers cryptic aberrations of prognostic and therapeutic significance. Leukemia. 2022;36(9):2306-2316. doi:10.1038/s41375-022-01652-8
24. Wei Q, Hu S, Loghavi S, et al. Chromoanagenesis is frequently associated with highly complex karyotypes, extensive clonal heterogeneity, and treatment refractoriness in acute myeloid leukemia. Am J Hematol. 2025;100(3):417-426. doi:10.1002/ajh.27575
25. Levy B, Baughn LB, Akkari Y, et al. Optical genome mapping in acute myeloid leukemia: a multicenter evaluation. Blood Advances. 2023;7(7):1297-1307. doi:10.1182/bloodadvances.2022007583
26. Rack K, De Bie J, Ameye G, et al. Optimizing the diagnostic workflow for acute lymphoblastic leukemia by optical genome mapping. Am J Hematol. 2022;97(5):548-561. doi:10.1002/ajh.26487
27. Giguere A, Raymond-Bouchard I, Collin V, Claveau JS, Hebert J, LeBlanc R. Optical genome mapping reveals the complex genetic landscape of myeloma. Cancers (Basel). 2023;15(19)doi:10.3390/cancers15194687
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30. Levy B, Kanagal-Shamanna R, Sahajpal NS, et al. A framework for the clinical implementation of optical genome mapping in hematologic malignancies. Am J Hematol. 2024;99(4):642-661. doi:10.1002/ajh.27175
31. Church AJ, Akkari Y, Deeb K, et al. Section E6.7-6.12 of the American College of Medical Genetics and Genomics (ACMG) technical laboratory standards: cytogenomic studies of acquired chromosomal abnormalities in solid tumors. Genet Med. 2024;26(4):101070. doi:10.1016/j.gim.2024.101070
32. Goldrich DY, LaBarge B, Chartrand S, et al. Identification of somatic structural variants in solid tumors by optical genome mapping. J Pers Med. 2021;11(2):142.
33. Fang H, Eacker SM, Wu Y, et al. Evaluation of genomic proximity mapping for detecting genomic and chromosomal structural variants in constitutional disorders. J Mol Diagn. 2025;27(11):1054-1069. doi:10.1016/j.jmoldx.2025.07.005
34. Qiu L. Genomic proximity mapping: a promising next generation cytogenomic assay for comprehensive assessment of acute myeloid leukemia. Haematologica. Published online February 12, 2026. doi:10.3324/haematol.2026.000003
35. Yeung CCS, Eacker SM, Sala-Torra O, et al. Evaluation of acute myeloid leukemia using genomic proximity mapping-based next generation cytogenomics. Haematologica. 2026;doi:10.3324/haematol.2025.288461
36. Kandasamy RK, Hsu JS, Eacker S, et al. Genomic proximity mapping for identification of chromosomal aberrations in multiple myeloma. Am J Hematol. 2026;101(4):899-903. doi:10.1002/ajh.70219
37. Chen X, Fang H, Wu Y, et al. Comprehensive detection of chromosomal and genomic abnormalities via next-generation sequencing-based genomic proximity mapping improves diagnostic classification of hematologic neoplasms. Cancers (Basel). 2025;17(23)doi:10.3390/cancers17233775

• Other (LCD request from laboratory)

• Genome-Wide Molecular Methodologies
• Hematologic Neoplasms