Copy number signatures predict chromothripsis and clinical outcomes in newly diagnosed multiple myeloma

A review on trends in development and translation of omics signatures in cancer

The field of cancer genomics and transcriptomics has evolved from targeted profiling to swift sequencing of individual tumor genome and transcriptome. The steady growth in genome, epigenome, and transcriptome datasets on a genome-wide scale has significantly increased our capability in capturing signatures that represent both the intrinsic and extrinsic biological features of tumors. These biological differences can help in precise molecular subtyping of cancer, predicting tumor progression, metastatic potential, and resistance to therapeutic agents. In this review, we summarized the current development of genomic, methylomic, transcriptomic, proteomic and metabolic signatures in the field of cancer research and highlighted their potentials in clinical applications to improve diagnosis, prognosis, and treatment decision in cancer patients.

Cytogenetics in the management of hematological malignancies: An overview of alternative technologies for cytogenetic characterization

Genomic characterization is an essential part of the clinical management of hematological malignancies for diagnostic, prognostic and therapeutic purposes. Although CBA and FISH are still the gold standard in hematology for the detection of CNA and SV, some alternative technologies are intended to complement their deficiencies or even replace them in the more or less near future. In this article, we provide a technological overview of these alternatives. CMA is the historical and well established technique for the high-resolution detection of CNA. For SV detection, there are emerging techniques based on the study of chromatin conformation and more established ones such as RTMLPA for the detection of fusion transcripts and RNA-seq to reveal the molecular consequences of SV. Comprehensive techniques that detect both CNA and SV are the most interesting because they provide all the information in a single examination. Among these, OGM is a promising emerging higher-solution technique that offers a complete solution at a contained cost, at the expense of a relatively low throughput per machine. WGS remains the most adaptable solution, with long-read approaches enabling very high-resolution detection of CAs, but requiring a heavy bioinformatics installation and at a still high cost. However, the development of high-resolution genome-wide detection techniques for CAs allows for a much better description of chromoanagenesis. Therefore, we have included in this review an update on the various existing mechanisms and their consequences and implications, especially prognostic, in hematological malignancies.

Recent Advances in The Definition of the Molecular Alterations Occurring in Multiple Myeloma

Multiple myeloma (MM) is a disorder of the monoclonal plasma cells and is the second most common hematologic malignancy. MM initiation and progression are dependent upon complex genomic abnormalities. The current pathogenic model of MM includes two types of primary events, represented by chromosome translocations or chromosome number alterations resulting in hyperdiploidy. These primary molecular events are observed both in MM and in monoclonal gammopathy, its premalignant precursor. Subsequent genetic events allow the progression of monoclonal gammopathy to MM and, together with primary events, contribute to the genetic complexity and heterogeneity of MM. Newer therapies have considerably improved patient outcomes; however, MM remains an incurable disease and most patients experience multiple relapses. The dramatic progresses achieved in the analysis of the heterogeneous molecular features of different MM patients allowed a comprehensive molecular classification of MM and the definition of an individualized prognostic model to predict an individual MM patient's response to different therapeutic options. Despite these progresses, prognostic models fail to identify a significant proportion of patients destined to early relapse. Treatment strategies are increasingly. Based on disease biology, trials are enriched for high-risk MMs, whose careful definition and categorization requires DNA sequencing studies.

Genomic Classification and Individualized Prognosis in Multiple Myeloma

PURPOSE

Outcomes for patients with newly diagnosed multiple myeloma (NDMM) are heterogenous, with overall survival (OS) ranging from months to over 10 years.

METHODS

To decipher and predict the molecular and clinical heterogeneity of NDMM, we assembled a series of 1,933 patients with available clinical, genomic, and therapeutic data.

RESULTS

Leveraging a comprehensive catalog of genomic drivers, we identified 12 groups, expanding on previous gene expression-based molecular classifications. To build a model predicting individualized risk in NDMM (IRMMa), we integrated clinical, genomic, and treatment variables. To correct for time-dependent variables, including high-dose melphalan followed by autologous stem-cell transplantation (HDM-ASCT), and maintenance therapy, a multi-state model was designed. The IRMMa model accuracy was significantly higher than all comparator prognostic models, with a c-index for OS of 0.726, compared with International Staging System (ISS; 0.61), revised-ISS (0.572), and R2-ISS (0.625). Integral to model accuracy was 20 genomic features, including 1q21 gain/amp, del 1p, TP53 loss, NSD2 translocations, APOBEC mutational signatures, and copy-number signatures (reflecting the complex structural variant chromothripsis). IRMMa accuracy and superiority compared with other prognostic models were validated on 256 patients enrolled in the GMMG-HD6 (ClinicalTrials.gov identifier: NCT02495922) clinical trial. Individualized patient risks were significantly affected across the 12 genomic groups by different treatment strategies (ie, treatment variance), which was used to identify patients for whom HDM-ASCT is particularly effective versus patients for whom the impact is limited.

CONCLUSION

Integrating clinical, demographic, genomic, and therapeutic data, to our knowledge, we have developed the first individualized risk-prediction model enabling personally tailored therapeutic decisions for patients with NDMM.

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.

Scrambling the genome in cancer: causes and consequences of complex chromosome rearrangements

Complex chromosome rearrangements, known as chromoanagenesis, are widespread in cancer. Based on large-scale DNA sequencing of human tumours, the most frequent type of complex chromosome rearrangement is chromothripsis, a massive, localized and clustered rearrangement of one (or a few) chromosomes seemingly acquired in a single event. Chromothripsis can be initiated by mitotic errors that produce a micronucleus encapsulating a single chromosome or chromosomal fragment. Rupture of the unstable micronuclear envelope exposes its chromatin to cytosolic nucleases and induces chromothriptic shattering. Found in up to half of tumours included in pan-cancer genomic analyses, chromothriptic rearrangements can contribute to tumorigenesis through inactivation of tumour suppressor genes, activation of proto-oncogenes, or gene amplification through the production of self-propagating extrachromosomal circular DNAs encoding oncogenes or genes conferring anticancer drug resistance. Here, we discuss what has been learned about the mechanisms that enable these complex genomic rearrangements and their consequences in cancer.

Chromosome instability region analysis and identification of the driver genes of the epithelial ovarian cancer cell lines A2780 and SKOV3

Epithelial ovarian cancer (EOC) is one of the most prevalent gynaecological cancers worldwide. The molecular mechanisms of serous ovarian cancer (SOC) remain unclear and not well understood. SOC cases are primarily diagnosed at the late stage, resulting in a poor prognosis. Advances in molecular biology techniques allow us to obtain a better understanding of precise molecular mechanisms and to identify the chromosome instability region and key driver genes in the carcinogenesis and progression of SOC. Whole-exome sequencing was performed on the normal ovarian cell line IOSE80 and the EOC cell lines SKOV3 and A2780. The single-nucleotide variation burden, distribution, frequency and signature followed the known ovarian mutation profiles, without chromosomal bias. Recurrently mutated ovarian cancer driver genes, including LRP1B, KMT2A, ARID1A, KMT2C and ATRX were also found in two cell lines. The genome distribution of copy number alterations was found by copy number variation (CNV) analysis, including amplification of 17q12 and 4p16.1 and deletion of 10q23.33. The CNVs of MED1, GRB7 and MIEN1 located at 17q12 were found to be correlated with the overall survival of SOC patients (MED1: p = 0.028, GRB7: p = 0.0048, MIEN1: p = 0.0051), and the expression of the three driver genes in the ovarian cell line IOSE80 and EOC cell lines SKOV3 and A2780 was confirmed by western blot and cell immunohistochemistry.

Acquired resistance to a GPRC5D-directed T-cell engager in multiple myeloma is mediated by genetic or epigenetic target inactivation

Bispecific antibodies targeting GPRC5D demonstrated promising efficacy in multiple myeloma, but acquired resistance usually occurs within a few months. Using a single-nucleus multi-omic strategy in three patients from the MYRACLE cohort (ClinicalTrials.gov registration: NCT03807128 ), we identified two resistance mechanisms, by bi-allelic genetic inactivation of GPRC5D or by long-range epigenetic silencing of its promoter and enhancer regions. Molecular profiling of target genes may help to guide the choice of immunotherapy and early detection of resistance in multiple myeloma.

Pan-Cancer Analysis of Copy-Number Features Identifies Recurrent Signatures and a Homologous Recombination Deficiency Biomarker to Predict Poly (ADP-Ribose) Polymerase Inhibitor Response

PURPOSE

Copy-number (CN) features reveal the molecular state of cancers and may have predictive and prognostic value in the treatment of cancer. We sought to apply published CN analysis methods to a large pan-cancer data set and characterize ubiquitous CN signatures across tumor types, including potential utility for treatment selection.

METHODS

We analyzed the landscape of CN features in 260,333 pan-cancer samples. We examined the association of 10 signatures with genomic alterations and clinical characteristics and trained a machine learning classifier using CN and insertion and deletion features to detect homologous recombination deficiency signature (HRDsig) positivity. Clinical outcomes were assessed using a real-world clinicogenomic database (CGDB) of comprehensive genomic profiling linked to deidentified, electronic health record-derived clinical data.

RESULTS

CN signatures were prevalent across cancer types and associated with diverse processes including focal tandem duplications, seismic amplifications, genome-wide loss of heterozygosity (gLOH), and HRD. Our novel HRDsig outperformed gLOH in predicting BRCAness and effectively distinguished biallelic BRCA and homologous recombination-repair wild-type (HRRwt) samples pan-tumor, demonstrating high sensitivity to detect biallelic BRCA in ovarian (93%) and other HRD-associated cancers (80%-87%). Pan-tumor prevalence of HRDsig was 6.4%. HRRwt cases represented a significant fraction of the HRDsig-positive cohort, likely reflecting a population with nongenomic mechanisms of HRD. In ovarian and prostate CGDBs, HRDsig identified more patients than gLOH and had predictive value for poly (ADP-ribose) polymerase inhibitor (PARPi) benefit.

CONCLUSION

Tumor CN profiles are informative, revealing diverse processes active in cancer. We describe the landscape of 10 CN signatures in a large pan-cancer cohort, including two associated with HRD. We trained a machine learning-based HRDsig that robustly identified BRCAness and associated with biallelic BRCA pan-tumor, and was predictive of PARPi benefit in real-world ovarian and prostate data sets.

Daratumumab, Cyclophosphamide, Bortezomib, Lenalidomide, and Dexamethasone as Induction and Extended Consolidation Improves Outcome in Ultra-High-Risk Multiple Myeloma

PURPOSE

The multicenter OPTIMUM (MUKnine) phase II trial investigated daratumumab, low-dose cyclophosphamide, lenalidomide, bortezomib, and dexamethasone (Dara-CVRd) before and after autologous stem-cell transplant (ASCT) in newly diagnosed patients with molecularly defined ultra-high-risk (UHiR) multiple myeloma (NDMM) or plasma cell leukemia (PCL). To provide clinical context, progression-free survival (PFS) and overall survival (OS) were referenced to contemporaneous outcomes seen in patients with UHiR NDMM treated in the recent Myeloma XI (MyeXI) trial.

METHODS

Transplant-eligible all-comers NDMM patients were profiled for UHiR disease, defined by presence of ≥2 genetic risk markers t(4;14)/t(14;16)/t(14;20), del(1p), gain(1q), and del(17p), and/or SKY92 gene expression risk signature. Patients with UHiR MM/PCL were offered treatment with Dara-CVRd induction, V-augmented ASCT, extended Dara-VR(d) consolidation, and Dara-R maintenance. UHiR patients treated in MyeXI with carfilzomib, lenalidomide, dexamethasone, and cyclophosphamide, or lenalidomide, dexamethasone, and cyclophosphamide, ASCT, and R maintenance or observation were identified by mirrored molecular screening. OPTIMUM PFS at 18 months (PFS18m) was compared against MyeXI using a Bayesian framework, and patients were followed up to the end of consolidation for PFS and OS.

RESULTS

Of 412 screened NDMM OPTIMUM patients, 103 were identified as UHiR or PCL and subsequently treated on trial with Dara-CVRd; 117 MyeXI patients identified as UHiR formed the external comparator arm, with comparable clinical and molecular characteristics to OPTIMUM. Comparison of PFS18m per Bayesian framework resulted in a 99.5% chance of OPTIMUM being superior to MyeXI. At 30 months' follow-up, PFS was 77% for OPTIMUM versus 39.8% for MyeXI, and OS 83.5% versus 73.5%, respectively. Extended post-ASCT Dara-VRd consolidation therapy was highly deliverable, with limited toxicity.

CONCLUSION

Our results suggest that Dara-CVRd induction and extended post-ASCT Dara-VRd consolidation markedly improve PFS for UHiR NDMM patients over conventional management, supporting further evaluation of this strategy.

Genetic Abnormalities in Extramedullary Multiple Myeloma

Extramedullary multiple myeloma (or extramedullary disease, EMD) is an aggressive form of multiple myeloma (MM) that occurs when malignant plasma cells become independent of the bone marrow microenvironment. This may occur alongside MM diagnosis or in later stages of relapse and confers an extremely poor prognosis. In the era of novel agents and anti-myeloma therapies, the incidence of EMD is increasing, making this a more prevalent and challenging cohort of patients. Therefore, understanding the underlying mechanisms of bone marrow escape and EMD driver events is increasingly urgent. The role of genomics in MM has been studied extensively; however, much less is known about the genetic background of EMD. Recently there has been an increased focus on driver events for the establishment of distant EMD sites. Generally, high-risk cytogenetic abnormalities and gene signatures are associated with EMD, alongside mutations in RAS signalling pathways. More recently, changes in epigenetic regulation have also been documented, specifically the hypermethylation of DNA promoter regions. Therefore, the focus of this review is to summarize and discuss what is currently known about the genetic background of EMD in MM.

Chromothripsis detection with multiple myeloma patients based on deep graph learning

MOTIVATION

Chromothripsis, associated with poor clinical outcomes, is prognostically vital in multiple myeloma. The catastrophic event is reported to be detectable prior to the progression of multiple myeloma. As a result, chromothripsis detection can contribute to risk estimation and early treatment guidelines for multiple myeloma patients. However, manual diagnosis remains the gold standard approach to detect chromothripsis events with the whole-genome sequencing technology to retrieve both copy number variation (CNV) and structural variation data. Meanwhile, CNV data are much easier to obtain than structural variation data. Hence, in order to reduce the reliance on human experts' efforts and structural variation data extraction, it is necessary to establish a reliable and accurate chromothripsis detection method based on CNV data.

RESULTS

To address those issues, we propose a method to detect chromothripsis solely based on CNV data. With the help of structure learning, the intrinsic relationship-directed acyclic graph of CNV features is inferred to derive a CNV embedding graph (i.e. CNV-DAG). Subsequently, a neural network based on Graph Transformer, local feature extraction, and non-linear feature interaction, is proposed with the embedding graph as the input to distinguish whether the chromothripsis event occurs. Ablation experiments, clustering, and feature importance analysis are also conducted to enable the proposed model to be explained by capturing mechanistic insights.

AVAILABILITY AND IMPLEMENTATION

The source code and data are freely available at https://github.com/luvyfdawnYu/CNV_chromothripsis.

High-grade serous ovarian carcinoma organoids as models of chromosomal instability

High-grade serous ovarian carcinoma (HGSOC) is the most genomically complex cancer, characterized by ubiquitous TP53 mutation, profound chromosomal instability, and heterogeneity. The mutational processes driving chromosomal instability in HGSOC can be distinguished by specific copy number signatures. To develop clinically relevant models of these mutational processes we derived 15 continuous HGSOC patient-derived organoids (PDOs) and characterized them using bulk transcriptomic, bulk genomic, single-cell genomic, and drug sensitivity assays. We show that HGSOC PDOs comprise communities of different clonal populations and represent models of different causes of chromosomal instability including homologous recombination deficiency, chromothripsis, tandem-duplicator phenotype, and whole genome duplication. We also show that these PDOs can be used as exploratory tools to study transcriptional effects of copy number alterations as well as compound-sensitivity tests. In summary, HGSOC PDO cultures provide validated genomic models for studies of specific mutational processes and precision therapeutics.

Optimizing the value of lenalidomide maintenance by extended genetic profiling: an analysis of 556 patients in the Myeloma XI trial

Prediction of individual patient benefit from lenalidomide (Len) maintenance after autologous stem cell transplant (ASCT) remains challenging. Here, we investigated extended molecular profiling for outcome prediction in patients in the National Cancer Research Institute Myeloma XI (MyXI) trial. Patients in the MyXI trial randomized to Len maintenance or observation after ASCT were genetically profiled for t(4;14), t(14;16), t(14;20), del(1p), gain(1q), and del(17p) and co-occurrence of risk markers was computed. Progression-free survival (PFS), subsequent progression (PFS2), and overall survival (OS) were calculated from maintenance randomization, and groups were compared using Cox proportional hazards regression. Of 556 patients, 17% with double-hit multiple myeloma (MM) (≥2 risk markers), 32% with single-hit (1 risk marker), and 51% without risk markers were analyzed. Single-hit MM derived the highest PFS benefit from Len maintenance, specifically, isolated del(1p), del(17p), and t(4;14), with ∼40-fold, 10-fold, and sevenfold reduced risk of progression or death (PFS), respectively, compared with observation. This benefit translated into improved PFS2 and OS for this group of patients compared with observation; median PFS was 10.9 vs 57.3 months for observation vs Len maintenance. Patients with isolated gain(1q) derived no benefit, and double-hit MM limited benefit (regardless or risk lesions involved) from Len maintenance. Extended genetic profiling identifies patients deriving exceptional benefit from Len maintenance and should be considered for newly diagnosed patients to support management discussions along their treatment pathway. This trial was registered at www.isrctn.com/ISRCTN49407852 as # ISRCTN49407852.

Chromosomal Rearrangements and Chromothripsis: The Alternative End Generation Model

Chromothripsis defines a genetic phenomenon where up to hundreds of clustered chromosomal rearrangements can arise in a single catastrophic event. The phenomenon is associated with cancer and congenital diseases. Most current models on the origin of chromothripsis suggest that prior to chromatin reshuffling numerous DNA double-strand breaks (DSBs) have to exist, i.e., chromosomal shattering precedes rearrangements. However, the preference of a DNA end to rearrange in a proximal accessible region led us to propose chromothripsis as the reaction product of successive chromatin rearrangements. We previously coined this process Alternative End Generation (AEG), where a single DSB with a repair-blocking end initiates a domino effect of rearrangements. Accordingly, chromothripsis is the end product of this domino reaction taking place in a single catastrophic event.

Chromothripsis is correlated with reduced cytotoxic immune infiltration and diminished responsiveness to checkpoint blockade immunotherapy

Background: Chromothripsis caused massive, clustered genomic rearrangements is prevalent in cancer and is considered a new paradigm for tumorigenesis and progression. In this study, we investigated the association among chromothripsis, anti-tumor immune responses, and responsiveness to immune checkpoint blockade (ICB). Methods: Quantification of immune cell infiltration and functional enrichment of immune-related signaling pathways were performed in the discovery set (n = 9403) and the validation set (n = 1140). we investigated the association between chromothripsis and anti-tumor immune responses. In the immunotherapy cohort, copy number alteration-based chromothripsis scores (CPSs) were introduced to assess the extent of chromothripsis to evaluate its association with responsiveness to ICB. Results: In the discovery set and the validation set, the ratios of CD8⁺ T cells to Tregs, TAMs, and MDSCs were significantly lower in tumors with chromothripsis (P = 1.5 × 10^-13, P = 5.4 × 10^-8, and P = 1.2 × 10^-4, respectively, TCGA; P = 1.0 × 10^-13, P = 3.6 × 10^-15, and P = 3.3 × 10^-3, respectively, PCAWG). The relevant pathways underlying the antitumor immune effect were significantly enriched in tumors without chromothripsis. Chromothripsis can be used as an independent predictor, and patients with low-CPSs experienced longer overall survival (OS) after immunotherapy [HR, 1.90; 95% confidence interval, 1.10-3.28; P = 0.019]. Conclusions: Our findings highlight the reduced cytotoxic immune infiltration in tumors with chromothripsis and enhanced immunosuppression in the tumor microenvironment. Chromothripsis can thus be used as a potential indicator to help identify patients who will respond to ICB, which could complement established biomarkers.

Genomic profiling for clinical decision making in lymphoid neoplasms

With the introduction of large-scale molecular profiling methods and high-throughput sequencing technologies, the genomic features of most lymphoid neoplasms have been characterized at an unprecedented scale. Although the principles for the classification and diagnosis of these disorders, founded on a multidimensional definition of disease entities, have been consolidated over the past 25 years, novel genomic data have markedly enhanced our understanding of lymphomagenesis and enriched the description of disease entities at the molecular level. Yet, the current diagnosis of lymphoid tumors is largely based on morphological assessment and immunophenotyping, with only few entities being defined by genomic criteria. This paper, which accompanies the International Consensus Classification of mature lymphoid neoplasms, will address how established assays and newly developed technologies for molecular testing already complement clinical diagnoses and provide a novel lens on disease classification. More specifically, their contributions to diagnosis refinement, risk stratification, and therapy prediction will be considered for the main categories of lymphoid neoplasms. The potential of whole-genome sequencing, circulating tumor DNA analyses, single-cell analyses, and epigenetic profiling will be discussed because these will likely become important future tools for implementing precision medicine approaches in clinical decision making for patients with lymphoid malignancies.

A Novel Integrated Approach for Cytogenomic Evaluation of Plasma Cell Neoplasms

Plasma cell neoplasm (PCN) is associated with characteristic chromosomal aberrations of diagnostic and prognostic significance. The presence of a small percentage of neoplastic cells is a drawback in the application of karyotyping and fluorescence in situ hybridization for the evaluation of bone marrow aspirate. The analysis of samples enriched for CD138⁺ cells has improved the detection rate. However, fluorescence in situ hybridization requires several probes and may not be completed due to a limited number of isolated cells. To address the issues experienced with the conventional approach, a novel integrated protocol that consists of whole-genome amplification of DNA isolated from CD138⁺ cells, followed by microarray as well as one fluorescence in situ hybridization assay for balanced IGH gene rearrangements, has been developed. In the present study in a cohort of 56 patients with clinical suspicion for PCN, compared to conventional cytogenetic analysis, this approach provided higher yield in the detection of PCN-related abnormalities, irrespective of the initial percentage of plasma cells. Whole-genome profiling uncovered recurrent chromosomal abnormalities of prognostic value, including unbalanced alterations within the MYC locus, 16q loss, and hypodiploidy, that were not otherwise detectable by conventional methods. The proposed approach is cost-efficient and provides a superior detection rate, required for proper risk stratification and differential diagnosis of PCN regardless of initial plasma cell percentage.

Proceedings from the Blood and Marrow Transplant Clinical Trials Network Myeloma Intergroup Workshop on Immune and Cellular Therapy in Multiple Myeloma

The Blood and Marrow Transplant Clinical Trials Network (BMT CTN) Myeloma Intergroup conducted a workshop on Immune and Cellular Therapy in Multiple Myeloma on January 7, 2022. This workshop included presentations by basic, translational, and clinical researchers with expertise in plasma cell dyscrasias. Four main topics were discussed: platforms for myeloma disease evaluation, insights into pathophysiology, therapeutic target and resistance mechanisms, and cellular therapy for multiple myeloma. Here we provide a comprehensive summary of these workshop presentations.

Signatures of copy number alterations in human cancer

Gains and losses of DNA are prevalent in cancer and emerge as a consequence of inter-related processes of replication stress, mitotic errors, spindle multipolarity and breakage-fusion-bridge cycles, among others, which may lead to chromosomal instability and aneuploidy1,2. These copy number alterations contribute to cancer initiation, progression and therapeutic resistance3-5. Here we present a conceptual framework to examine the patterns of copy number alterations in human cancer that is widely applicable to diverse data types, including whole-genome sequencing, whole-exome sequencing, reduced representation bisulfite sequencing, single-cell DNA sequencing and SNP6 microarray data. Deploying this framework to 9,873 cancers representing 33 human cancer types from The Cancer Genome Atlas6 revealed a set of 21 copy number signatures that explain the copy number patterns of 97% of samples. Seventeen copy number signatures were attributed to biological phenomena of whole-genome doubling, aneuploidy, loss of heterozygosity, homologous recombination deficiency, chromothripsis and haploidization. The aetiologies of four copy number signatures remain unexplained. Some cancer types harbour amplicon signatures associated with extrachromosomal DNA, disease-specific survival and proto-oncogene gains such as MDM2. In contrast to base-scale mutational signatures, no copy number signature was associated with many known exogenous cancer risk factors. Our results synthesize the global landscape of copy number alterations in human cancer by revealing a diversity of mutational processes that give rise to these alterations.

An overview of mutational and copy number signatures in human cancer

The genome of each cell in the human body is constantly under assault from a plethora of exogenous and endogenous processes that can damage DNA. If not successfully repaired, DNA damage generally becomes permanently imprinted in cells, and all their progenies, as somatic mutations. In most cases, the patterns of these somatic mutations contain the tell‐tale signs of the mutagenic processes that have imprinted and are termed mutational signatures. Recent pan‐cancer genomic analyses have elucidated the compendium of mutational signatures for all types of small mutational events, including (1) single base substitutions, (2) doublet base substitutions, and (3) small insertions/deletions. In contrast to small mutational events, where, in most cases, DNA damage is a prerequisite, aneuploidy, which refers to the abnormal number of chromosomes in a cell, usually develops from mistakes during DNA replication. Such mistakes include DNA replication stress, mitotic errors caused by faulty microtubule dynamics, or cohesion defects that contribute to chromosomal breakage and can lead to copy number (CN) alterations (CNAs) or even to structural rearrangements. These aberrations also leave behind genomic scars which can be inferred from sequencing as CN signatures and rearrangement signatures. The analyses of mutational signatures of small mutational events have been extensively reviewed, so we will not comprehensively re‐examine them here. Rather, our focus will be on summarising the existing knowledge for mutational signatures of CNAs. As studying CN signatures is an emerging field, we briefly summarise the utility that mutational signatures of small mutational events have provided in basic science, cancer treatment, and cancer prevention, and we emphasise the future role that CN signatures may play in each of these fields. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Copy number alteration signatures as biomarkers in cancer: a review

Within certain cancers, extensive copy number alterations (CNAs) contribute to a complex and heterogenic genomic profile. This makes it difficult to understand and unravel the distinct molecular dynamics shaping the disease while preventing clinically effective patient stratification. CNA signature analysis represents a novel genomic stratification tool for probing this complexity, offering an intricate framework for deriving CNA patterns at the molecular level. This allows the underlying genomic mechanisms of specific cancers to be revealed, leading to the potential identification of therapeutic targets and prognostic associations. This review outlines the molecular and methodological basis of CNA signatures and focuses on recent advances highlighting their clinical utility, limitations and prospective future as novel diagnostic and prognostic cancer biomarkers.

Systems medicine dissection of chr1q-amp reveals a novel PBX1-FOXM1 axis for targeted therapy in multiple myeloma

Understanding the biological and clinical impact of copy number aberrations (CNAs) on the development of precision therapies in cancer remains an unmet challenge. Genetic amplification of chromosome 1q (chr1q-amp) is a major CNA conferring an adverse prognosis in several types of cancer, including in the blood cancer multiple myeloma (MM). Although several genes across chromosome 1 (chr1q) portend high-risk MM disease, the underpinning molecular etiology remains elusive. Here, with reference to the 3-dimensional (3D) chromatin structure, we integrate multi-omics data sets from patients with MM with genetic variables to obtain an associated clinical risk map across chr1q and to identify 103 adverse prognosis genes in chr1q-amp MM. Prominent among these genes, the transcription factor PBX1 is ectopically expressed by genetic amplification and epigenetic activation of its own preserved 3D regulatory domain. By binding to reprogrammed superenhancers, PBX1 directly regulates critical oncogenic pathways and a FOXM1-dependent transcriptional program. Together, PBX1 and FOXM1 activate a proliferative gene signature that predicts adverse prognosis across multiple types of cancer. Notably, pharmacological disruption of the PBX1-FOXM1 axis with existing agents (thiostrepton) and a novel PBX1 small molecule inhibitor (T417) is selectively toxic against chr1q-amp myeloma and solid tumor cells. Overall, our systems medicine approach successfully identifies CNA-driven oncogenic circuitries, links them to clinical phenotypes, and proposes novel CNA-targeted therapy strategies in MM and other types of cancer.

Insight into the Molecular Basis Underlying Chromothripsis

Chromoanagenesis constitutes a group of events that arise from single cellular events during early development. This particular class of complex rearrangements is a newfound occurrence that may lead to chaotic and complex genomic realignments. By that, chromoanagenesis is thought to be a crucial factor regarding macroevolution of the genome, and consequently is affecting the karyotype revolution together with genomic plasticity. One of chromoanagenesis-type of events is chromothripsis. It is characterised by the breakage of the chromosomal structure and its reassembling in random order and orientation which results in the establishment of derivative forms of chromosomes. Molecular mechanisms that underlie this phenomenon are mostly related to chromosomal sequestration throughout the micronuclei formation process. Chromothripsis is linked both to congenital and cancer diseases, moreover, it might be detected in subjects characterised by a normal phenotype. Chromothripsis, as well as the other chromoanagenetic variations, may be confined to one or more chromosomes, which makes up a non-uniform variety of karyotypes among chromothriptic patients. The detection of chromothripsis is enabled via tools like microarray-based comparative genomic hybridisation, next generation sequencing or authorial protocols aimed for the recognition of structural variations.