High-Risk Multiple Myeloma (MM)

Introduction: Multiple myeloma (MM) is a haematological malignancy characterised by the clonal expansion of malignant plasma cells in the bone marrow.

MM manifests clinically as hypercalcaemia, renal failure, anaemia and bone lesions (known as CRAB features), with a median age of diagnosis of 71 in Ireland.1 MM affects around 384 people in Ireland each year1 and despite advancements in treatments remains incurable in 2024, as patients eventually relapse.

At a genomic level MM is extremely heterogeneous, meaning patients present with a wide range of different genetic abnormalities. As a result, patient outcome and response to treatment also varies. Despite this, personalised treatment plans are still in their infancy relative to those in some of the more common solid cancers, with MM patients generally treated in a similar manner. Treatment of MM normally consists of a combination of two, three or even four drugs from different classes. Treatment approaches vary, depending on patient fitness, co-morbidities, disease features and eligibility for an autologous stem cell transplant (ASCT). Initial treatment in Ireland at present consists of one of the following National Cancer Control Programme (NCCP)-approved

regimens; RVD (bortezomib, lenalidomide, dexamethasone), VMP (bortezomib, melphalan, prednisone), CyBorD (cyclophosphamide, bortezomib, dexamethasone), Rd (lenalidomide, dexamethasone) or most recently D-VTD (daratumumab, bortezomib, thalidomide, dexamethasone).

Notwithstanding significant improvements to patient prognosis as a result of these drug combinations, the median survival of MM patients is currently still low, at around 6 years.2 However, in reality patient outcome varies significantly.

‘High-risk’ MM patients tend to

have a median survival of 2-3 years, whilst for ‘standard-risk’ patients this is 7-10 years.2 There are several methods to identify high-risk patients and, as a result, a major clinical challenge is the lack of standardisation. Ideally, a standardised approach to risk-stratification would aid with streamlined characterisation of patient response in different risk groups, and potentially enable risk-adapted treatment plans in the future. In this article, we will discuss some of the commonly employed methods to identify high-risk MM, with a focus on those related to our own research at the Royal College of Surgeons in Ireland (RCSI) University of Medicine and Health Sciences, Dublin.

Current Risk Classification

Most current classification systems used for MM incorporate common cytogenetic abnormalities as detected by fluorescence in situ hybridisation (FISH). In 2005, the International Myeloma Working Group (IMWG) introduced the International Staging System (ISS) to stratify patients into three prognostic groups. ISS criteria are based on the clinical levels of serum β2 microglobulin and serum albumin. In 2015, this was revised (R-ISS) to include the level of lactate dehydrogenase (LDH) and several cytogenetic abnormalities, specifically high-risk cytogenetic abnormalities t(4;14), t(14;16) or del(17p).3 The R-ISS criteria are shown in Table 1.

Additionally, the Mayo Stratification for Myeloma and Risk-adapted Therapy (mSMART) guidelines use several more genetic factors to guide genetic risk, such as gain(1q), p53 mutation, and gene signatures (Table 2),4

Roughly half of MM patients present with trisomies of odd-numbered chromosomes, and generally this is associated with better prognosis.5 Translocations t(11;14) and t(6;14) are considered to have a neutral effect on prognosis, observed in 15-20% and 2% of patients respectively. t(4;14) is observed in around 10-15% of patients, whilst t(14;16) and t(14;20) are present in only 2-5% and 1% of patients respectively, and all considered to have a detrimental effect on patient outcome. Del(17p) is associated with loss of p53 and is found in around 10% of newly-diagnosed patients.

Gain(1q) is present in around 35-40% of patients, and is often found alongside del(1p), present in around 20% of cases.5 However, del(1p) is currently not included in the above classification systems. chromosome 1 abnormalities are described in more detail later in this article. Additionally, del(13) is found in 50% of patients and predicts poor outcome, however it is also not included in current classification guidelines. This highlights the need for ongoing improvement of risk-stratification systems.

Gene Expression Proflising – MMProfiler SKY92

Gene expression profiling (GEP) has become increasingly popular in MM risk prediction, offering better standardisation and sensitivity than FISH. Accordingly, several gene signatures that can accurately identify molecular subgroups of MM patients and predict prognosis have been identified. To date, two gene signatures have been commercialised – the MyPRS® which detects a 70-gene signature known as GEP-70, and the MMProfiler™ which detects a 92-gene signature known as SKY92.6, 7 Both are commonly incorporated into ongoing clinical trials and have proved to successfully identify high-risk patients. However, the MMProfiler™ is currently the only GEP test with CE-IVD (in vitro diagnostic) approval, meaning it meets European standards to be used in a clinical setting. The MMprofiler™ determines the expression of 92 genes in MM plasma cells from patient bone marrow. Dependent on the way these genes are collectively expressed, a score is calculated and anything equal or above 0.827 is considered high-risk with a predicted survival of less than 2 years.7 Additionally, the MMProfiler™ can detect t(4;14), t(11;14), t(14;16), t(14;20) and gain(1q). Several studies have shown that using MMProfiler™ can overcome the need for FISH and in fact provide additional information often missed by FISH. The MMProfiler™ is already used in private healthcare settings in the UK, and in several NHS clinical trials. We are currently investigating its use in Ireland in newly-diagnosed MM, and our preliminary results show a particularly high proportion of Irish patients are classified as high-risk (>30%). Several trials are also investigating whether MMProfiler™ can predict treatment response, with preliminary results showing it can aid clinical decision making to escalate or deescalate treatment (PROMMIS trial, NCT02911571). It is hoped that these data will ultimately justify incorporation of the MMProfiler™ into routine MM diagnostic and/or treatment workflows in Ireland.

Interestingly, both gene signatures described here include many genes located on chromosome 1. In fact, 30% of genes making up GEP-70 are located on chromosome 1, with most upregulated genes on chromosome 1q, and most downregulated on 1p. Several of the SKY92 genes are also on chromosome 1, such as NUF2 and LBR. From our own analysis, we have identified upregulation of NUF2, located on 1q, as a potential driver of the SKY92 highrisk disease phenotype.

Chromosone 1g

Chromosone 1 instabilities are the most common genomic alterations contributing MM pathogenesis, resulting in gain/amplification of chromosome arm 1q or the loss of regions on the shorter 1p arm. These chromosome 1 cytogenetic abnormalities are indicative of high-risk disease. Various tumour suppressor genes are located on 1p. Downregulation or loss of such genes associate with worse survival. Moreover, 30% of patients present with gain or amplification 1q at diagnosis. Abnormalities of 1q may induce increased genetic instability in MM, and typically manifest with inferior prognosis. Although both copy number variations of chromosome 1q are considered “high-risk”, gain(1q) does not appear to be as detrimental as amp(1q) (Table 3).

As chromosome 1 is the largest human chromosome, a plethora of possible therapeutic candidate genes reside in tow. Interestingly, patients with chromosome 1 alterations have not benefitted from novel treatments as well as other genetic subgroups. To address this, our research team is designing and testing novel therapies for the protein products of the gene F11R which is located on 1q23.3. Additionally, we are investigating the function of NUF2, also on 1q23.3. High expression of either of these genes is associated with inferior outcomes in MM.

F11R encodes the JAM-A protein whose overexpression has been associated with poor patient prognosis in various cancers (breast, lung, glioma) and most recently in MM. JAM-A is found on diverse cell types, where it plays physiological roles in tight junction formation, angiogenesis and leukocyte extravasation. As the pathophysiological overexpression of JAM-A has been linked with various oncogenic traits; it is intriguing to speculate that attenuation of this protein may impair MM progression. Moreover, we have seen an association between high F11R expression and gain(1q) which further supports its exploration as a novel potential target in high-risk MM patients.

The NUF2 gene is part of the SKY92 gene signature, and is upregulated in high-risk MM. Similar to F11R we see a link between high expression and presence of gain(1q). NUF2 facilitates normal chromosomal segregation and centromere microtubule attachment. Abnormal expression of NUF2 leads to mitotic dysregulation and further chromosomal instability associating with reduced survival.

We aim to find novel therapies that may target high NUF2 expression.

Extramedullary Disease

In rare cases, extramedullary disease (EMD) may also occur and is characteristic of high-risk MM. This is a particularly aggressive manifestation of MM whereby the malignant plasma cells have become independent of bone marrow and may infiltrate other organ systems. This occurs in around 7% of MM patients at diagnosis (primary EMD), and up to 20% at the relapsed stage (secondary EMD).8 Prognosis is extremely poor, with survival rates of less than 3 years at diagnosis, and less than 1 year in refractory patients. The incidence of EMD is on the increase, potentially because most novel therapeutics target the bone marrow and thus surviving cells post-treatment have adapted mechanisms to survive outside of this microenvironment.

Regarding the genomic make-up of EMD in MM, definitive studies are currently lacking. However, the few that have been performed generally show an increased rate of high-risk abnormalities in patients presenting with EMD.9 Examples include t(4;14), gain(1q) and del(13). Moreover, t(11;14), which is generally considered standard-risk, is less likely to occur in EMD. Patients classified as GEP-70 high-risk are also five times more likely to experience EMD than standard-risk patients. Of interest, several studies have shown high chromosome 1 instability in EMD patients, namely deletions of 1p and gains of 1q, reinforcing the role chromosome 1 plays in high-risk disease. We currently have an ongoing study investigating the genetics of EMD in Irish MM patients.

Conclusion

High-risk MM represents an aggressive subtype of MM with particularly poor outcome. How high-risk disease is defined can vary, due to the heterogeneity of the disease and varying clinical manifestations. We propose that standardising how it is defined is necessary to understand its underlying disease biology. Currently, there are no personalised therapies that specifically target high-risk MM, and thus research should aim to find novel targets. At RCSI, we are trialling the use of the MMProfiler™ test to aid with risk-classification in Ireland, and are investigating several molecular markers of high-risk disease (JAM-A and NUF2) as

potential new therapeutic targets. Their location on chromosome 1 makes them even more compelling objects of investigation, since chromosome 1 abnormalities are a common occurrence in high-risk MM. Additionally, the presentation of EMD is associated with high-risk disease, and we are currently studying its genetic make-up to better understand its pathogenesis. Ultimately, we hope that identifying and understanding high-risk MM will lead to risk-adapted therapy approaches and improve outcome for this poor prognostic group.

Empowering Patients

In response to a lack of patient-friendly materials on MM research, the MM research group in RCSI recently launched a patient-driven resource discussing MM research in Ireland with the support of the Health Research Charities Ireland, the Health Research Board and Breakthrough Cancer Research. Co-developed by patients, clinicians and researchers, this booklet aims to aid patients and their caregivers in understanding their role in MM research. It is essential to equip patients with knowledge to not only navigate their diagnosis, and treatment options but also to develop an understanding of informed consent and how they may contribute to advancing MM research in Ireland. This booklet can be freely downloaded using the following QR code.

Written by Dr Roisin McAvera (Postdoctoral Researcher RCSI), Miss Niamh McAuley (PhD Student RCSI), Prof Ann Hopkins (Associate Professor RCSI), Prof Siobhan Glavey (Clinician-Scientist Beaumont Hospital/RCSI)

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