A Next-Generation Sequencing Strategy for Evaluating the Most Common Genetic Abnormalities in Multiple Myeloma

Advancements in Multiple Myeloma Research: High-Throughput Sequencing Technologies, Omics, and the Role of Artificial Intelligence

Multiple myeloma is a complex and challenging type of blood cancer that affects plasma cells in the bone marrow. In recent years, the development of advanced research techniques, such as omics approaches-which involve studying large sets of biological data like genes and proteins-and high-throughput sequencing technologies, has allowed researchers to analyze vast amounts of genetic information rapidly and gain new insights into the disease. Additionally, the advent of artificial intelligence tools has accelerated data analysis, enabling more accurate predictions and improved treatment strategies. This review aims to highlight recent research advances in multiple myeloma made possible by these novel techniques and to provide guidance for researchers seeking effective approaches in this field.

Liquid biopsy for molecular characterization of diffuse large B-cell lymphoma and early assessment of minimal residual disease

Circulating tumour DNA (ctDNA) allows genotyping and minimal residual disease (MRD) detection in lymphomas. Using a next-generation sequencing (NGS) approach (EuroClonality-NDC), we evaluated the clinical and prognostic value of ctDNA in a series of R-CHOP-treated diffuse large B-cell lymphoma (DLBCL) patients at baseline (n = 68) and after two cycles (n = 59), monitored by metabolic imaging (positron emission tomography combined with computed tomography [PET/CT]). A molecular marker was identified in 61/68 (90%) ctDNA samples at diagnosis. Pretreatment high ctDNA levels significantly correlated with elevated lactate dehydrogenase, advanced stage, high-risk International Prognostic Index and a trend to shorter 2-year progression-free survival (PFS). Valuable NGS data after two cycles of treatment were obtained in 44 cases, and 38 achieved major molecular response (MMR; 2.5-log drop in ctDNA). PFS curves displayed statistically significant differences among those achieving MMR versus those not achieving MMR (2-year PFS of 76% vs. 0%, p < 0.001). Similarly, more than 66% reduction in ΔSUVmax by PET/CT identified two subgroups with different prognosis (2-year PFS of 83% vs. 38%; p < 0.001). Combining both approaches MMR and ΔSUVmax reduction, a better stratification was observed (2-year PFS of 84% vs. 17% vs. 0%, p < 0.001). EuroClonality-NDC panel allows the detection of a molecular marker in the ctDNA in 90% of DLBCL. ctDNA reduction at two cycles and its combination with interim PET results improve patient prognosis stratification.

Targeted single-cell proteomic analysis identifies new liquid biopsy biomarkers associated with multiple myeloma

Multiple myeloma (MM) is accompanied by alterations to the normal plasma cell (PC) proteome, leading to changes to the tumor microenvironment and disease progression. There is a great need for understanding the consequences that lead to MM progression and for the discovery of new biomarkers that can aid clinical diagnostics and serve as targets for therapeutics. This study demonstrates the applicability of utilizing the single-cell high-definition liquid biopsy assay (HDSCA) and imaging mass cytometry to characterize the proteomic profile of myeloma. In our study, we analyzed ~87,000 cells from seven patient samples (bone marrow and peripheral blood) across the myeloma disease spectrum and utilized our multiplexed panel to characterize the expression of clinical markers for PC classification, additional potential therapeutic targets, and the tumor microenvironment cells. Our analysis showed BCMA, ICAM3 (CD50), CD221, and CS1 (SLAMF7) as the most abundantly expressed markers on PCs across all myeloma stages, with BCMA, ICAM3, and CD221 having significantly higher expression levels on disease versus precursor PCs. Additionally, we identify significantly elevated levels of expression for CD74, MUM1, CD229, CD44, IGLL5, Cyclin D1, UBA52, and CD317 on PCs from overt disease conditions compared to those from precursor states.

Genetic Alterations in Members of the Proteasome 26S Subunit, AAA-ATPase (PSMC) Gene Family in the Light of Proteasome Inhibitor Resistance in Multiple Myeloma

For the treatment of Multiple Myeloma, proteasome inhibitors are highly efficient and widely used, but resistance is a major obstacle to successful therapy. Several underlying mechanisms have been proposed but were only reported for a minority of resistant patients. The proteasome is a large and complex machinery. Here, we focus on the AAA ATPases of the 19S proteasome regulator (PSMC1-6) and their implication in PI resistance. As an example of cancer evolution and the acquisition of resistance, we conducted an in-depth analysis of an index patient by applying FISH, WES, and immunoglobulin-rearrangement sequencing in serial samples, starting from MGUS to newly diagnosed Multiple Myeloma to a PI-resistant relapse. The WES analysis uncovered an acquired PSMC2 Y429S mutation at the relapse after intensive bortezomib-containing therapy, which was functionally confirmed to mediate PI resistance. A meta-analysis comprising 1499 newly diagnosed and 447 progressed patients revealed a total of 36 SNVs over all six PSMC genes that were structurally accumulated in regulatory sites for activity such as the ADP/ATP binding pocket. Other alterations impact the interaction between different PSMC subunits or the intrinsic conformation of an individual subunit, consequently affecting the folding and function of the complex. Interestingly, several mutations were clustered in the central channel of the ATPase ring, where the unfolded substrates enter the 20S core. Our results indicate that PSMC SNVs play a role in PI resistance in MM.

NGS-Based Molecular Karyotyping of Multiple Myeloma: Results from the GEM12 Clinical Trial

Simple Summary

Multiple Myeloma (MM) is considered an incurable chronic disease, which prognosis depends on the presence of different genomic alterations. To accomplish a complete molecular diagnosis in a single essay, we have designed and validated a capture-based NGS approach to reliably identify pathogenic mutations (SNVs and indels), genomic alterations (CNVs and chromosomic translocations), and IGH rearrangements. We have observed a good correlation of the results obtained using our capture panel with data obtained by both FISH and WES techniques. In this study, the molecular classification performed using our approach was significantly associated with the stratification and outcome of MM patients. Additionally, this panel has been proven to detect specific IGH rearrangements that could be used as biomarkers in patient follow-ups through minimal residual disease (MRD) assays. In conclusion, we think that MM patients could benefit from the use of this capture-based NGS approach with a more accurate, single-essay molecular diagnosis.

Abstract

Next-generation sequencing (NGS) has greatly improved our ability to detect the genomic aberrations occurring in multiple myeloma (MM); however, its transfer to routine clinical labs and its validation in clinical trials remains to be established. We designed a capture-based NGS targeted panel to identify, in a single assay, known genetic alterations for the prognostic stratification of MM. The NGS panel was designed for the simultaneous study of single nucleotide and copy number variations, insertions and deletions, chromosomal translocations and V(D)J rearrangements. The panel was validated using a cohort of 149 MM patients enrolled in the GEM2012MENOS65 clinical trial. The results showed great global accuracy, with positive and negative predictive values close to 90% when compared with available data from fluorescence in situ hybridization and whole-exome sequencing. While the treatments used in the clinical trial showed high efficacy, patients defined as high-risk by the panel had shorter progression-free survival (p = 0.0015). As expected, the mutational status of TP53 was significant in predicting patient outcomes (p = 0.021). The NGS panel also efficiently detected clonal IGH rearrangements in 81% of patients. In conclusion, molecular karyotyping using a targeted NGS panel can identify relevant prognostic chromosomal abnormalities and translocations for the clinical management of MM patients.

Genome Instability in Multiple Myeloma: Facts and Factors

Multiple myeloma (MM) is a malignant neoplasm of terminally differentiated immunoglobulin-producing B lymphocytes called plasma cells. MM is the second most common hematologic malignancy, and it poses a heavy economic and social burden because it remains incurable and confers a profound disability to patients. Despite current progress in MM treatment, the disease invariably recurs, even after the transplantation of autologous hematopoietic stem cells (ASCT). Biological processes leading to a pathological myeloma clone and the mechanisms of further evolution of the disease are far from complete understanding. Genetically, MM is a complex disease that demonstrates a high level of heterogeneity. Myeloma genomes carry numerous genetic changes, including structural genome variations and chromosomal gains and losses, and these changes occur in combinations with point mutations affecting various cellular pathways, including genome maintenance. MM genome instability in its extreme is manifested in mutation kataegis and complex genomic rearrangements: chromothripsis, templated insertions, and chromoplexy. Chemotherapeutic agents used to treat MM add another level of complexity because many of them exacerbate genome instability. Genome abnormalities are driver events and deciphering their mechanisms will help understand the causes of MM and play a pivotal role in developing new therapies.

RNA-Sequencing-Based Transcriptomic Score with Prognostic and Theranostic Values in Multiple Myeloma

Multiple myeloma (MM) is the second most frequent hematological cancer and is characterized by the clonal proliferation of malignant plasma cells. Genome-wide expression profiling (GEP) analysis with DNA microarrays has emerged as a powerful tool for biomedical research, generating a huge amount of data. Microarray analyses have improved our understanding of MM disease and have led to important clinical applications. In MM, GEP has been used to stratify patients, define risk, identify therapeutic targets, predict treatment response, and understand drug resistance. In this study, we built a gene risk score for 267 genes using RNA-seq data that demonstrated a prognostic value in two independent cohorts (n = 674 and n = 76) of newly diagnosed MM patients treated with high-dose Melphalan and autologous stem cell transplantation. High-risk patients were associated with the expression of genes involved in several major pathways implicated in MM pathophysiology, including interferon response, cell proliferation, hypoxia, IL-6 signaling pathway, stem cell genes, MYC, and epigenetic deregulation. The RNA-seq-based risk score was correlated with specific MM somatic mutation profiles and responses to targeted treatment including EZH2, MELK, TOPK/PBK, and Aurora kinase inhibitors, outlining potential utility for precision medicine strategies in MM.

Next-Generation Biomarkers in Multiple Myeloma: Understanding the Molecular Basis for Potential Use in Diagnosis and Prognosis

Multiple myeloma (MM) is considered to be the second most common blood malignancy and it is characterized by abnormal proliferation and an accumulation of malignant plasma cells in the bone marrow. Although the currently utilized markers in the diagnosis and assessment of MM are showing promising results, the incidence and mortality rate of the disease are still high. Therefore, exploring and developing better diagnostic or prognostic biomarkers have drawn global interest. In the present review, we highlight some of the recently reported and investigated novel biomarkers that have great potentials as diagnostic and/or prognostic tools in MM. These biomarkers include angiogenic markers, miRNAs as well as proteomic and immunological biomarkers. Moreover, we present some of the advanced methodologies that could be utilized in the early and competent diagnosis of MM. The present review also focuses on understanding the molecular concepts and pathways involved in these biomarkers in order to validate and efficiently utilize them. The present review may also help in identifying areas of improvement for better diagnosis and superior outcomes of MM.

Defining the undetectable: The current landscape of minimal residual disease assessment in multiple myeloma and goals for future clarity

Multiple Myeloma, the second most prevalent hematologic malignancy, yet lacks an established curative therapy. However, overall response rate to modern four-drug regimens approaches 100%. Major efforts have thus focused on the measurement of minute quantities of residual disease (minimal residual disease or MRD) for prognostic metrics and therapeutic response evaluation. Currently, MRD is assessed by flow cytometry or by next generation sequencing to track tumor-specific immunoglobulin V(D)J rearrangements. These bone marrow-based methods can reach sensitivity thresholds of the identification of one neoplastic cell in 1,000,000 (10-6). New technologies are being developed to be used alone or in conjunction with established methods, including peripheral blood-based assays, mass spectrometry, and targeted imaging. Data is also building for MRD as a surrogate endpoint for overall survival. Here, we will address the currently utilized MRD assays, challenges in validation across labs and clinical trials, techniques in development, and future directions for successful clinical application of MRD in multiple myeloma.

Application of Next-Generation Sequencing for the Genomic Characterization of Patients with Smoldering Myeloma

Genomic analysis could contribute to a better understanding of the biological determinants of the evolution of multiple myeloma (MM) precursor disease and an improved definition of high-risk patients. To assess the feasibility and value of next-generation sequencing approaches in an asymptomatic setting, we performed a targeted gene mutation analysis and a genome-wide assessment of copy number alterations (CNAs) by ultra-low-pass whole genome sequencing (ULP-WGS) in six patients with monoclonal gammopathy of undetermined significance and 25 patients with smoldering MM (SMM). Our comprehensive genomic characterization highlighted heterogeneous but substantial values of the tumor fraction, especially in SMM; a rather high degree of genomic complexity, in terms of both mutations and CNAs, and inter-patient variability; a higher incidence of gene mutations and CNAs in SMM, confirming ongoing evolution; intraclonal heterogeneity; and instances of convergent evolution. ULP-WGS of these patients proved effective in revealing the marked genome-wide level of their CNAs, most of which are not routinely investigated. Finally, the analysis of our small SMM cohort suggested that chr(8p) deletions, the DNA tumor fraction, and the number of alterations may have clinical relevance in the progression to overt MM. Although validation in larger series is mandatory, these findings highlight the promising impact of genomic approaches in the clinical management of SMM.

Genomic profiling of multiple myeloma: New insights and modern technologies

Advances in technologies for genomic profiling, primarily with next generation sequencing, have lead to a better understanding of the complex genomic landscape in multiple myeloma. Integrated analysis of whole genome, exome and transcriptome sequencing has lead to new insights on disease drivers including translocations, copy number alterations, somatic mutations, and altered gene expression. Disease progression in multiple myeloma is largely driven by structural variations including the traditional immunoglobulin heavy chain (IGH) translocations and hyperdiploidy which are early events in myelomagenesis as well as more complex events spanning over multiple chromosomes and involving amplifications and deletions. In this review, we will discuss recent insights on the genomic landscape of multiple myeloma and their implications for disease progression and personalized treatment. We will review how sequencing assays compare to current clinical methods and give an overview of modern technologies for interrogating genomic aberrations.

The combination of WGS and RNA-Seq is superior to conventional diagnostic tests in multiple myeloma: Ready for prime time?

The diagnosis and risk stratification of multiple myeloma (MM) is based on clinical and cytogenetic tests. Magnetic CD138 enrichment followed by interphase FISH (fluorescence in situ hybridisation) is the gold standard to identify prognostic translocations and copy number alterations (CNA). Although clinical implications of gene expression profiling (GEP) or panel based sequencing results are evident, those tests have not yet reached routine clinical application. We set up a single workflow to analyse MM of 211 patients at first diagnosis by whole genome sequencing (WGS) and RNA-Seq and validate the results by FISH analysis. We observed a 96% concordance of FISH and WGS results when assessing translocations involving the IGH locus and an overall concordance of FISH and WGS of 92% when assessing CNA. WGS analysis resulted in the identification of 17 additional MYC-translocations that were missed by FISH analysis. RNA-Seq followed by supervised clustering grouped patients in their expected genetically defined subgroup and prompted the assessment of WGS data in cases that were not congruent with FISH. This allowed the identification of additional IGH-translocations and hyperdiploid cases. We show the reliability of WGS an RNA-Seq in a clinical setting, which is a prerequisite for a novel routine diagnostic test.

Mate pair sequencing outperforms fluorescence in situ hybridization in the genomic characterization of multiple myeloma

Fluorescence in situ hybridization (FISH) is currently the gold-standard assay to detect recurrent genomic abnormalities of prognostic significance in multiple myeloma (MM). Since most translocations in MM involve a position effect with heterogeneous breakpoints, we hypothesize that FISH has the potential to miss translocations involving these regions. We evaluated 70 bone marrow samples from patients with plasma cell dyscrasia by FISH and whole-genome mate-pair sequencing (MPseq). Thirty cases (42.9%) displayed at least one instance of discordance between FISH and MPseq for each primary and secondary abnormality evaluated. Nine cases had abnormalities detected by FISH that went undetected by MPseq including 6 tetraploid clones and three cases with missed copy number abnormalities. In contrast, 19 cases had abnormalities detected by MPseq that went undetected by FISH. Seventeen were MYC rearrangements and two were 17p deletions. MPseq identified 36 MYC abnormalities and 17 (50.0% of MYC abnormal group with FISH results) displayed a false negative FISH result. MPseq identified 10 cases (14.3%) with IgL rearrangements, a recent marker of poor outcome, and 10% with abnormalities in genes associated with lenalidomide response or resistance. In summary, MPseq was superior in the characterization of rearrangement complexity and identification of secondary abnormalities demonstrating increased clinical value compared to FISH.

The future of myeloma precision medicine: integrating the compendium of known drug resistance mechanisms with emerging tumor profiling technologies

Multiple myeloma (MM) is a hematologic malignancy that is considered mostly incurable in large part due to the inability of standard of care therapies to overcome refractory disease and inevitable drug-resistant relapse. The post-genomic era has been a productive period of discovery where modern sequencing methods have been applied to large MM patient cohorts to modernize our current perception of myeloma pathobiology and establish an appreciation for the vast heterogeneity that exists between and within MM patients. Numerous pre-clinical studies conducted in the last two decades have unveiled a compendium of mechanisms by which malignant plasma cells can escape standard therapies, many of which have potentially quantifiable biomarkers. Exhaustive pre-clinical efforts have evaluated countless putative anti-MM therapeutic agents and many of these have begun to enter clinical trial evaluation. While the palette of available anti-MM therapies is continuing to expand it is also clear that malignant plasma cells still have mechanistic avenues by which they can evade even the most promising new therapies. It is therefore becoming increasingly clear that there is an outstanding need to develop and employ precision medicine strategies in MM management that harness emerging tumor profiling technologies to identify biomarkers that predict efficacy or resistance within an individual's sub-clonally heterogeneous tumor. In this review we present an updated overview of broad classes of therapeutic resistance mechanisms and describe selected examples of putative biomarkers. We also outline several emerging tumor profiling technologies that have the potential to accurately quantify biomarkers for therapeutic sensitivity and resistance at genomic, transcriptomic and proteomic levels. Finally, we comment on the future of implementation for precision medicine strategies in MM and the clear need for a paradigm shift in clinical trial design and disease management.

Two Cases of γ-Heavy Chain Disease and a Review of the Literature

Gamma heavy chain disease (γ-HCD) is a rare lymphoproliferative disorder characterised by the production of a truncated immunoglobulin heavy chain. Fewer than 200 cases have been reported in the literature. In some cases, γ-HCD occurs with other lymphoid neoplasms. This study reports clinical, biochemical, haematological, and histological findings in two cases of γ-HCD. We describe newer biochemical diagnostic tools (HevyLite measurement, capillary electrophoresis, and immunotyping) that can aid in the characterisation of γ-HCD. The first case is an 88-year-old woman with γ-HCD. The second case is an 81-year-old woman who developed γ-HCD during treatment for Waldenstrom's macroglobulinemia. In the second patient, histopathology identified a separate clone responsible for the secretion of the gamma heavy chain. Studies on the clonal evolution of the disease may provide insight into therapeutic implications and the genomic complexity of the disease.

Chromothripsis 18 in multiple myeloma patient with rapid extramedullary relapse

Background

Catastrophic chromosomal event known as chromothripsis was proven to be a significant hallmark of poor prognosis in several cancer diseases. While this phenomenon is very rare in among multiple myeloma (MM) patients, its presence in karyotype is associated with very poor prognosis.

Case presentation

In our case, we report a 62 year female patient with rapid progression of multiple myeloma (MM) into extramedullary disease and short overall survival (OS = 23 months). I-FISH investigation revealed presence of gain 1q21 and hyperdiploidy (+ 5,+ 9,+ 15) in 82% and 86%, respectively, while IgH rearrangements, del(17)(p13) and del(13)(q14) were evaluated as negative.Whole-genome profiling using array-CGH showed complex genomic changes including hyperdiploidy (+ 3,+ 5,+ 9,+ 11, + 15,+ 19), monosomy X, structural gains (1q21-1q23.1, 1q32-1q44, 16p13.13-16p11.2) and losses (1q23.1-1q32.1; 8p23.3-8p11.21) of genetic material and chromothripsis in chromosome 18 with 6 breakpoint areas. Next-generation sequencing showed a total of 338 variants with 1.8% (6/338) of pathological mutations in NRAS (c.181C > A; p.Gln61Lys) or variants of unknown significance in TP53, CUX1 and POU4F1.

Conclusions

Our findings suggest that presence of chromothripsis should be considered as another important genetic hallmark of poor prognosis in MM patients and utilization of genome-wide screening techniques such as array-CGH and NGS improves the clinical diagnostics of the disease.

Decitabine and Melphalan Fail to Reactivate p73 in p53 Deficient Myeloma Cells

(1) Background: TP53 deficiency remains a major adverse event in Multiple Myeloma (MM) despite therapeutic progresses. As it is not possible to target TP53 deficiency with pharmacological agents, we explored the possibility of activating another p53 family member, p73, which has not been well studied in myeloma. (2) Methods: Using human myeloma cell lines (HMCLs) with normal or abnormal TP53 status, we assessed TP73 methylation and expression. (3) Results: Using microarray data, we reported that TP73 is weakly expressed in 47 HMCLs and mostly in TP53 wild type (TP53^wt) HMCLs (p = 0.0029). Q-RT-PCR assays showed that TP73 was expressed in 57% of TP53^wt HMCLs (4 out of 7) and 11% of TP53 abnormal (TP53^abn) HMCLs (2 out of 18) (p = 0.0463). We showed that TP73 is silenced by methylation in TP53^abn HMCLs and that decitabine increased its expression, which, however, remained insufficient for significant protein expression. Alkylating drugs increased expression of TP73 only in TP53^wt HMCLs but failed to synergize with decitabine in TP53^abn HMCLs. (4) Conclusions: Decitabine and melphalan does not appear as a promising combination for inducing p73 and bypassing p53 deficiency in myeloma cells.

Standardisation of minimal residual disease in multiple myeloma

The assessment of the effectiveness of chemotherapy in oncology cannot disregard the concept of minimal residual disease (MRD). In fact, the efforts of numerous scientific groups all over the world are currently focusing on this issue, with the sole purpose of defining sensitive, effective assessment criteria that are, above all, able to give acceptable, easily repeatable results worldwide. Regarding this issue, especially with the advent of new drugs, multiple myeloma is one of the haematologic malignancies for which a consensus has not yet been reached. In this review, we analyse various techniques that have been used to improve the sensitivity of response, aimed at reducing the cut-off values previously allowed, as well as serological values like serum-free light chain, or immunophenotypic tools on bone marrow or peripheral blood, like multi-parameter flow cytometry, or molecular ones such as allele-specific oligonucleotide (ASO)-qPCR and next-generation/high-throughput sequencing technologies (NGS). Moreover, our discussion makes a brief reference to promising techniques, such as mass spectrometry for identifying Ig light chain (LC) in peripheral blood, and the assessment of gene expression profile not only in defining prognostic risk at the diagnosis but also as a tool for evaluation of response.

Precision Medicine in Myeloma: Challenges in Defining an Actionable Approach

Recently, large sequencing studies have provided insights into the mutational landscape of multiple myeloma (MM), identifying actionable mutations and giving a precious opportunity for exploring new targeted therapies. The main goal of precision medicine, matching patients with the right drug, seems to be closer than ever. However, no targeted therapies in MM are approved yet. Several clinical trials testing targeted drugs and enrolling patients with MM are currently ongoing and will provide predictive biomarkers that might support clinical decision making. In this review, we evaluate the evidence supporting the implementation of precision medicine in MM and we discuss the challenges that should be dealt with in this imminent and promising new era.

Utilizing next-generation sequencing in the management of multiple myeloma

INTRODUCTION

Multiple myeloma (MM) is a bone marrow plasma cell malignancy characterized by wide clinical presentation and heterogeneous genetic background. Despite the recent advances in patient outcome, new markers are needed for improving risk prediction and choice of a more appropriate therapy. In this perspective, the genetic makeup of MM cells is being better characterized by means of next-generation sequencing (NGS) technologies. Areas covered: The authors discuss how the application of NGS has improved our knowledge of MM biology by discovering its mutational landscape, identifying the operating mutational processes, and revealing the clonal composition of tumors and the dynamics of its evolution; and how this can have important clinical implications in terms of prognostication, therapeutic choices, and response assessment. Finally, the authors provide a quick outlook of future applications of these technologies that could help in the management of the disease in the next years. Expert commentary: The clinical exploitation of NGS-based characterization of MM patients has as its ultimate goal the precision medicine. Considerable obstacles to its implementation in myeloma management exist; therefore, the concerted effort of all involved stakeholders is mandatory to ensure that it will become a reality in routine clinical practice in the next future.

MYC Deregulation in Primary Human Cancers

MYC regulates a complex biological program by transcriptionally activating and repressing its numerous target genes. As such, MYC is a master regulator of many processes, including cell cycle entry, ribosome biogenesis, and metabolism. In cancer, the activity of the MYC transcriptional network is frequently deregulated, contributing to the initiation and maintenance of disease. Deregulation often leads to constitutive overexpression of MYC, which can be achieved through gross genetic abnormalities, including copy number alterations, chromosomal translocations, increased enhancer activity, or through aberrant signal transduction leading to increased MYC transcription or increased MYC mRNA and protein stability. Herein, we summarize the frequency and modes of MYC deregulation and describe both well-established and more recent findings in a variety of cancer types. Notably, these studies have highlighted that with an increased appreciation for the basic mechanisms deregulating MYC in cancer, new therapeutic vulnerabilities can be discovered and potentially exploited for the inhibition of this potent oncogene in cancer.