Poor overall survival in hyperhaploid multiple myeloma is defined by double-hit bi-allelic inactivation of TP53

Section E6.1-6.6 of the American College of Medical Genetics and Genomics (ACMG) Technical Laboratory Standards: Cytogenomic studies of acquired chromosomal abnormalities in neoplastic blood, bone marrow, and lymph nodes

Cytogenomic analyses of acquired clonal chromosomal abnormalities in neoplastic blood, bone marrow, and/or lymph nodes are instrumental in the clinical management of patients with hematologic neoplasms. Cytogenetic analyses assist in the diagnosis of such disorders and can provide important prognostic information. Furthermore, cytogenetic studies can provide crucial information regarding specific genetically defined subtypes of these neoplasms that may have targeted therapies. At time of relapse, cytogenetic analysis can confirm recurrence of the original neoplasm, detect clonal disease evolution, or uncover a new unrelated neoplastic process. This section deals specifically with the technical standards applicable to cytogenomic studies of acquired clonal chromosomal abnormalities in neoplastic blood, bone marrow, and/or lymph nodes. This updated Section E6.1-6.6 supersedes the previous Section E6 in Section E: Clinical Cytogenetics of the American College of Medical Genetics and Genomics Technical Standards for Clinical Genetics Laboratories.

Chromosomal defects in multiple myeloma

Multiple myeloma is a plasma cell neoplasm driven by primary (e.g. hyperdiploidy; IGH translocations) and secondary (e.g. 1q21 gains/amplifications; del(17p); MYC translocations) chromosomal events. These are important to detect as they influence prognosis, therapeutic response and disease survival. Currently, cytogenetic testing is most commonly performed by interphase fluorescence in situ hybridisation (FISH) on aspirated bone marrow samples. A number of variations to FISH methodology are available, including prior plasma cell enrichment and incorporation of immunophenotypic plasma cell identification. Other molecular methods are increasingly being utilised to provide a genome-wide view at high resolution (e.g. single nucleotide polymorphism (SNP) microarray analysis) and these can detect abnormalities in most cases. Despite their wide application at diagnostic assessment, both FISH and SNP-array have relatively low sensitivity, limiting their use for identification of prognostically significant low-level sub-clones or for disease monitoring. Next-generation sequencing is increasingly being used to detect mutations and new FISH techniques such as by flow cytometry are in development and may address some of the current test limitations. Here we review the primary and secondary cytogenetic aberrations in myeloma and discuss the range of techniques available for their assessment.

Recommendations for the study of monoclonal gammopathies in the clinical laboratory. A consensus of the Spanish Society of Laboratory Medicine and the Spanish Society of Hematology and Hemotherapy. Part I: Update on laboratory tests for the study of monoclonal gammopathies

Monoclonal gammopathies (MG) are characterized by the proliferation of plasma cells that produce identical abnormal immunoglobulins (intact or some of their subunits). This abnormal immunoglobulin component is called monoclonal protein (M-protein), and is considered a biomarker of proliferative activity. The identification, characterization and measurement of M-protein is essential for the management of MG. We conducted a systematic review of the different tests and measurement methods used in the clinical laboratory for the study of M-protein in serum and urine, the biochemistry and hematology tests necessary for clinical evaluation, and studies in bone marrow, peripheral blood and other tissues. This review included literature published between 2009 and 2022. The paper discusses the main methodological characteristics and limitations, as well as the purpose and clinical value of the different tests used in the diagnosis, prognosis, monitoring and assessment of treatment response in MG. Included are methods for the study of M-protein, namely electrophoresis, measurement of immunoglobulin levels, serum free light chains, immunoglobulin heavy chain/light chain pairs, and mass spectrometry, and for the bone marrow examination, morphological analysis, cytogenetics, molecular techniques, and multiparameter flow cytometry.

Cytogenetic Abnormalities in Multiple Myeloma: Incidence, Prognostic Significance, and Geographic Heterogeneity in Indian and Western Populations

Multiple myeloma (MM) is a genetically complex and heterogeneous neoplasm in which cytogenetics is a major factor playing an important role in the risk stratification of disease. High-risk MM based upon cytogenetic classification includes primary IGH translocations t(4;14), t(14;16), t(14;20), and secondary progressive aberrations such as gain/amp(1q), 1p deletion, del(17p), and hypodiploidy. Several studies have proved that interphase FISH can detect primary as well as secondary cryptic aberrations very efficiently in lowest 5-10% abnormal plasma cell population. The present large-scale study was undertaken to evaluate the incidence of cytogenetic abnormalities, to analyse the correlation of conventional karyotyping with FISH, and to seek the geographic heterogeneity in the incidence of primary as well as secondary aberrations in our Indian versus Western populations. We conducted prospective studies of 1,104 patients consecutively referred from the primary, secondary, and tertiary oncology centres from all over India. Interphase FISH was performed on isolated plasma cells. Karyotype analysis was done as per ISCN 2016 and 2020. FISH could detect cytogenetic abnormalities in 67.6% of the cases with an incidence of 59% non-hyperdiploidy. The incidence of IGH translocation was 26% versus literature frequency of 40-50% which was mainly due to a low incidence (6%) of t(11;14) in contrast to 15-20% in other series. Additionally, the association of secondary progressive aberrations in the hyperdiploid group rather than the non-hyperdiploid group in our patients is not a common finding. A biallelic inactivation of TP53 as an ultra-high risk factor was detected in old-aged patients. These observations disclose the novel findings and strongly indicate the racial disparity which leads to geographic heterogeneity. In contrast to FISH, conventional karyotyping could detect MM-related aberrations in 50% of cases, of which 44% revealed highly complex karyotypes with common aberrations of chromosome 1q. Overall, FISH was found to be a novel, easy approach with high success rate and capability of detection of all cytogenetic abnormalities that add valid information for the risk stratification of disease. This, in future, in combination with mutation profile and gene expression profile will help in further refinement of disease and identification of actionable targets.

Myeloma Genome Project Panel is a Comprehensive Targeted Genomics Panel for Molecular Profiling of Patients with Multiple Myeloma

PURPOSE

We designed a comprehensive multiple myeloma targeted sequencing panel to identify common genomic abnormalities in a single assay and validated it against known standards.

EXPERIMENTAL DESIGN

The panel comprised 228 genes/exons for mutations, 6 regions for translocations, and 56 regions for copy number abnormalities (CNA). Toward panel validation, targeted sequencing was conducted on 233 patient samples and further validated using clinical FISH (translocations), multiplex ligation probe analysis (MLPA; CNAs), whole-genome sequencing (WGS; CNAs, mutations, translocations), or droplet digital PCR (ddPCR) of known standards (mutations).

RESULTS

Canonical immunoglobulin heavy chain translocations were detected in 43.2% of patients by sequencing, and aligned with FISH except for 1 patient. CNAs determined by sequencing and MLPA for 22 regions were comparable in 103 samples and concordance between platforms was R2 = 0.969. Variant allele frequency (VAF) for 74 mutations were compared between sequencing and ddPCR with concordance of R2 = 0.9849.

CONCLUSIONS

In summary, we have developed a targeted sequencing panel that is as robust or superior to FISH and WGS. This molecular panel is cost-effective, comprehensive, clinically actionable, and can be routinely deployed to assist risk stratification at diagnosis or posttreatment to guide sequencing of therapies.

Increasing genomic discovery in newly diagnosed multiple myeloma: defining disease biology and its correlation to risk

Our understanding of MM genomics has expanded rapidly in the past 5-10 years as a consequence of cytogenetic analyses obtained in routine clinical practice as well as the ability to perform whole-exome/genome sequencing and gene expression profiling on large patient data sets. This knowledge has offered new insights into disease biology and is increasingly defining high-risk genomic patterns. In this manuscript, we present a thorough review of our current knowledge of MM genomics. The epidemiology and biology of chromosomal abnormalities including both copy number abnormalities and chromosomal translocation are described in full with a focus on those most clinically impactful such as 1q amplification and del(17p) as well as certain chromosome 14 translocations. A review of our ever-expanding knowledge of genetic mutations derived from recent whole-genome/exome data sets is then reviewed including those that drive disease pathogenesis from precursor states as well as those that may impact clinical outcomes. We then transition and attempt to elucidate how both chromosomal abnormalities and gene mutations are evolving our understanding of disease risk. We conclude by offering our perspectives moving forward as to how we might apply whole-genome/exome-level data in addition to routine cytogenetic analyses to improve patient outcomes as well as further knowledge gaps that must be addressed.

How I Treat High-risk Multiple Myeloma

Survival of multiple myeloma (MM) has significantly improved over the last decade; however, a composed group of patients (15-20%), named high-risk (HR) MM, still experience reduced survival. Both tumor biology and suboptimal/absent responses to therapy may underlie HR definition and a clear uniform identification of risk factors is crucial for a proper management of these patients. In biologic-HRMM, MRD negativity attainment and sustain, inside and outside BM, should be the primary goal and therapy should be adapted in patients with frailty to reduce toxicity and improve quality of life. MM treatment has traditionally been tailored on age and more recently frailty or comorbidities, but very rarely on the biology of the disease, mainly because of the lack of a clear benefit derived from a specific drug/combination, inhomogeneity in HR definition and lack of data coming from prospective, properly designed clinical trials. Some attempts have been successfully made recently in this direction. In this review, we are discussing the current different definitions of HR and the need for a consensus, the results of available trials in HR patients and the way through risk-adapted treatment strategies. For this purpose, we are proposing several clinical cases of difficult-to-treat patients throughout different treatment phases.

Genetic Predictors of Mortality in Patients with Multiple Myeloma

Multiple myeloma (MM) is a heterogeneous disease featured by clonal plasma cell proliferation and genomic instability. The advent of next-generation sequencing allowed unraveling the complex genomic landscape of the disease. Several recurrent genomic aberrations including immunoglobulin genes translocations, copy number abnormalities, complex chromosomal events, transcriptomic and epigenomic deregulation, and mutations define various molecular subgroups with distinct outcomes. In this review, we describe the recurrent genomic events identified in MM impacting patients’ outcome and survival. These genomic aberrations constitute new markers that could be incorporated into a prognostication model to eventually guide therapy at every stage of the disease.

TarPan: an easily adaptable targeted sequencing panel viewer for research and clinical use

BACKGROUND

The study of cancer genomics continually matures as the number of patient samples sequenced increases. As more data is generated, oncogenic drivers for specific cancer types are discovered along with their associated risks. This in turn leads to potential treatment strategies that pave the way to precision medicine. However, significant financial and analytical barriers make it infeasible to sequence the entire genome of every patient. In contrast, targeted sequencing panels give reliable information on relevant portions of the genome at a fiscally responsible cost. Therefore, we have created the Targeted Panel (TarPan) Viewer, a software tool, to investigate this type of data.

RESULTS

TarPan Viewer helps investigators understand data from targeted sequencing data by displaying the information through a web browser interface. Through this interface, investigators can easily observe copy number changes, mutations, and structural events in cancer samples. The viewer runs in R Shiny with a robust SQLite backend and its input is generated from bioinformatic algorithms reliably described in the literature. Here we show the results from using TarPan Viewer on publicly available follicular lymphoma, breast cancer, and multiple myeloma data. In addition, we have tested and utilized the viewer internally, and this data has been used in high-impact peer-reviewed publications.

CONCLUSIONS

We have designed a flexible, simple to setup viewer that is easily adaptable to any type of cancer targeted sequencing, and has already proven its use in a research laboratory environment. Further, we believe with deeper sequencing and/or more targeted application it could be of use in the clinic in conjunction with an appropriate targeted sequencing panel as a cost-effective diagnostic test, especially in cancers such as acute leukemia or diffuse large B-cell lymphoma that require rapid interventions.

Reconstructing the evolutionary history of multiple myeloma

Multiple myeloma is the second most common lymphoproliferative disorder, characterized by aberrant expansion of monoclonal plasma cells. In the last years, thanks to novel next generation sequencing technologies, multiple myeloma has emerged as one of the most complex hematological cancers, shaped over time by the activity of multiple mutational processes and by the acquisition of key driver events. In this review, we describe how whole genome sequencing is emerging as a key technology to decipher this complexity at every stage of myeloma development: precursors, diagnosis and relapsed/refractory. Defining the time windows when driver events are acquired improves our understanding of cancer etiology and paves the way for early diagnosis and ultimately prevention.

Germline Risk Contribution to Genomic Instability in Multiple Myeloma

Genomic instability, a well-established hallmark of human cancer, is also a driving force in the natural history of multiple myeloma (MM) - a difficult to treat and in most cases fatal neoplasm of immunoglobulin producing plasma cells that reside in the hematopoietic bone marrow. Long recognized manifestations of genomic instability in myeloma at the cytogenetic level include abnormal chromosome numbers (aneuploidy) caused by trisomy of odd-numbered chromosomes; recurrent oncogene-activating chromosomal translocations that involve immunoglobulin loci; and large-scale amplifications, inversions, and insertions/deletions (indels) of genetic material. Catastrophic genetic rearrangements that either shatter and illegitimately reassemble a single chromosome (chromotripsis) or lead to disordered segmental rearrangements of multiple chromosomes (chromoplexy) also occur. Genomic instability at the nucleotide level results in base substitution mutations and small indels that affect both the coding and non-coding genome. Sometimes this generates a distinctive signature of somatic mutations that can be attributed to defects in DNA repair pathways, the DNA damage response (DDR) or aberrant activity of mutator genes including members of the APOBEC family. In addition to myeloma development and progression, genomic instability promotes acquisition of drug resistance in patients with myeloma. Here we review recent findings on the genetic predisposition to myeloma, including newly identified candidate genes suggesting linkage of germline risk and compromised genomic stability control. The role of ethnic and familial risk factors for myeloma is highlighted. We address current research gaps that concern the lack of studies on the mechanism by which germline risk alleles promote genomic instability in myeloma, including the open question whether genetic modifiers of myeloma development act in tumor cells, the tumor microenvironment (TME), or in both. We conclude with a brief proposition for future research directions, which concentrate on the biological function of myeloma risk and genetic instability alleles, the potential links between the germline genome and somatic changes in myeloma, and the need to elucidate genetic modifiers in the TME.