Novel pedigree analysis implicates DNA repair and chromatin remodeling in multiple myeloma risk

Liquid Biopsies as Non-Invasive Tools for Mutation Profiling in Multiple Myeloma: Application Potential, Challenges, and Opportunities

Over the last decades, the survival of multiple myeloma (MM) patients has considerably improved. However, despite the availability of new treatments, most patients still relapse and become therapy-resistant at some point in the disease evolution. The mutation profile has an impact on MM patients' outcome, while typically evolving over time. Because of the patchy bone marrow (BM) infiltration pattern, the analysis of a single bone marrow sample can lead to an underestimation of the known genetic heterogeneity in MM. As a result, interest is shifting towards blood-derived liquid biopsies, which allow for a more comprehensive and non-invasive genetic interrogation without the discomfort of repeated BM aspirations. In this review, we compare the application potential for mutation profiling in MM of circulating-tumor-cell-derived DNA, cell-free DNA and extracellular-vesicle-derived DNA, while also addressing the challenges associated with their use.

Shared genomic segments analysis identifies MHC class I and class III molecules as genetic risk factors for juvenile idiopathic arthritis

Juvenile idiopathic arthritis (JIA) is a complex rheumatic disease encompassing several clinically defined subtypes of varying severity. The etiology of JIA remains largely unknown, but genome-wide association studies (GWASs) have identified up to 22 genes associated with JIA susceptibility, including a well-established association with HLA-DRB1. Continued investigation of heritable risk factors has been hindered by disease heterogeneity and low disease prevalence. In this study, we utilized shared genomic segments (SGS) analysis on whole-genome sequencing of 40 cases from 12 multi-generational pedigrees significantly enriched for JIA. Subsets of cases are connected by a common ancestor in large extended pedigrees, increasing the power to identify disease-associated loci. SGS analysis identifies genomic segments shared among disease cases that are likely identical by descent and anchored by a disease locus. This approach revealed statistically significant signals for major histocompatibility complex (MHC) class I and class III alleles, particularly HLA-A∗02:01, which was observed at a high frequency among cases. Furthermore, we identified an additional risk locus at 12q23.2-23.3, containing genes primarily expressed by naive B cells, natural killer cells, and monocytes. The recognition of additional risk beyond HLA-DRB1 provides a new perspective on immune cell dynamics in JIA. These findings contribute to our understanding of JIA and may guide future research and therapeutic strategies.

Germline genetic variants in Turkish familial multiple myeloma/monoclonal gammopathy of undetermined significance cases

Multiple myeloma (MM) is a haematological malignancy primarily affecting the elderly, with a striking male predilection and ethnic disparities in incidence. Familial predisposition to MM has long been recognized, but the genetic underpinnings remain elusive. This study aimed to investigate germline variants in Turkish families with recurrent MM cases. A total of 37 MM-affected families, comprising 77 individuals, were included. Targeted next-generation sequencing analysis yielded no previously reported rare variants. Whole exome sequencing analysis in 11 families identified rare disease-causing variants in various genes, some previously linked to familial MM and others not previously associated. Notably, genes involved in ubiquitination, V(D)J recombination and the PI3K/AKT/mTOR pathway were among those identified. Furthermore, a specific variant in BNIP1 (rs28199) was found in 13 patients across nine families, indicating its potential significance in MM pathogenesis. While this study sheds light on genetic variations in familial MM in Turkey, its limitations include sample size and the absence of in vivo investigations. In conclusion, familial MM likely involves a polygenic inheritance pattern with rare, disease-causing variants in various genes, emphasizing the need for international collaborative efforts to unravel the intricate genetic basis of MM and develop targeted therapies.

NTHL1 is a recessive cancer susceptibility gene

In search of novel breast cancer (BC) risk variants, we performed a whole-exome sequencing and variant analysis of 69 Finnish BC patients as well as analysed loss-of-function variants identified in DNA repair genes in the Finns from the Genome Aggregation Database. Additionally, we carried out a validation study of SERPINA3 c.918-1G>C, recently suggested for BC predisposition. We estimated the frequencies of 41 rare candidate variants in 38 genes by genotyping them in 2482-4101 BC patients and in 1273-3985 controls. We further evaluated all coding variants in the candidate genes in a dataset of 18,786 BC patients and 182,927 controls from FinnGen. None of the variants associated significantly with cancer risk in the primary BC series; however, in the FinnGen data, NTHL1 c.244C>T p.(Gln82Ter) associated with BC with a high risk for homozygous (OR = 44.7 [95% CI 6.90-290], P = 6.7 × 10-5) and a low risk for heterozygous women (OR = 1.39 [1.18-1.64], P = 7.8 × 10-5). Furthermore, the results suggested a high risk of colorectal, urinary tract, and basal-cell skin cancer for homozygous individuals, supporting NTHL1 as a recessive multi-tumour susceptibility gene. No significant association with BC risk was detected for SERPINA3 or any other evaluated gene.

Germline rare deleterious variant load alters cancer risk, age of onset and tumor characteristics

Recent studies show that rare, deleterious variants (RDVs) in certain genes are critical determinants of heritable cancer risk. To more comprehensively understand RDVs, we performed the largest-to-date germline variant calling analysis in a case-control setting for a multi-cancer association study from whole-exome sequencing data of 20,789 participants, split into discovery and validation cohorts. We confirm and extend known associations between cancer risk and germline RDVs in specific gene-sets, including DNA repair (OR = 1.50; p-value = 8.30e-07; 95% CI: 1.28-1.77), cancer predisposition (OR = 1.51; p-value = 4.58e-08; 95% CI: 1.30-1.75), and somatic cancer drivers (OR = 1.46; p-value = 4.04e-06; 95% CI: 1.24-1.72). Furthermore, personal RDV load in these gene-sets associated with increased risk, younger age of onset, increased M1 macrophages in tumor and, increased tumor mutational burden in specific cancers. Our findings can be used towards identifying high-risk individuals, who can then benefit from increased surveillance, earlier screening, and treatments that exploit their tumor characteristics, improving prognosis.

Investigation of Rare Non-Coding Variants in Familial Multiple Myeloma

Multiple myeloma (MM) is a plasma cell malignancy whereby a single clone of plasma cells over-propagates in the bone marrow, resulting in the increased production of monoclonal immunoglobulin. While the complex genetic architecture of MM is well characterized, much less is known about germline variants predisposing to MM. Genome-wide sequencing approaches in MM families have started to identify rare high-penetrance coding risk alleles. In addition, genome-wide association studies have discovered several common low-penetrance risk alleles, which are mainly located in the non-coding genome. Here, we further explored the genetic basis in familial MM within the non-coding genome in whole-genome sequencing data. We prioritized and characterized 150 upstream, 5' untranslated region (UTR) and 3' UTR variants from 14 MM families, including 20 top-scoring variants. These variants confirmed previously implicated biological pathways in MM development. Most importantly, protein network and pathway enrichment analyses also identified 10 genes involved in mitogen-activated protein kinase (MAPK) signaling pathways, which have previously been established as important MM pathways.

A germline exome analysis reveals harmful POT1 variants in multiple myeloma patients and families

Observations of inherited susceptibility to multiple myeloma have led to active research in defining predisposing genes to the disease. Here, we analysed 128 plasma cell dyscrasia patients' germline whole-exome sequencing data. Rare dominantly inherited pathogenic or likely pathogenic (P/LP) variant was found in 9.4% of the patients. Among the P/LP variants, CHEK2 (p. Thr410MetfsTer15) was the most prevalent (n = 5, 3.9%). Interestingly, P/LP variants in POT1 were identified in three patients (2.3%). Our findings broaden the spectrum of POT1-related cancers and demonstrate the importance of the germline genetic analysis in hematological malignancies.

Inherited Susceptibility to Hematopoietic Malignancies in the Era of Precision Oncology

As germline predisposition to hematopoietic malignancies has gained increased recognition and attention in the field of oncology, it is important for clinicians to use a systematic framework for the identification, management, and surveillance of patients with hereditary hematopoietic malignancies (HHMs). In this article, we discuss strategies for identifying individuals who warrant diagnostic evaluation and describe considerations pertaining to molecular testing. Although a paucity of prospective data is available to guide clinical monitoring of individuals harboring pathogenic variants, we provide recommendations for clinical surveillance based on consensus opinion and highlight current advances regarding the risk of progression to overt malignancy in HHM variant carriers. We also discuss the prognosis of HHMs and considerations surrounding the utility of allogeneic stem-cell transplantation in these individuals. We close with an overview of contemporary issues at the intersection of HHMs and precision oncology.

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.

Epidemiology, genetics and treatment of multiple myeloma and precursor diseases

Multiple myeloma (MM) is a hematological malignancy caused by the clonal expansion of plasma cells. The incidence of MM worldwide is increasing with greater than 140 000 people being diagnosed with MM per year. Whereas 5-year survival after a diagnosis of MM has improved from 28% in 1975 to 56% in 2012, the disease remains essentially incurable. In this review, we summarize our current understanding of MM including its epidemiology, genetics and biology. We will also provide an overview of MM management that has led to improvements in survival, including recent changes to diagnosis and therapies. Areas of unmet need include the management of patients with high-risk MM, those with reduced performance status and those refractory to standard therapies. Ongoing research into the biology and early detection of MM as well as the development of novel therapies, such as immunotherapies, has the potential to influence MM practice in the future.

Shared genomic segment analysis in a large high-risk chronic lymphocytic leukemia pedigree implicates CXCR4 in inherited risk

AIM

Chronic lymphocytic leukemia (CLL) has been shown to cluster in families. First-degree relatives of individuals with CLL have an ~8 fold increased risk of developing the malignancy. Strong heritability suggests pedigree studies will have good power to localize pathogenic genes. However, CLL is relatively rare and heterogeneous, complicating ascertainment and analyses. Our goal was to identify CLL risk loci using unique resources available in Utah and methods to address intra-familial heterogeneity.

METHODS

We identified a six-generation high-risk CLL pedigree using the Utah Population Database. This pedigree contains 24 CLL cases connected by a common ancestor. We ascertained and genotyped eight CLL cases using a high-density SNP array, and then performed shared genomic segment (SGS) analysis - a method designed for extended high-risk pedigrees that accounts for heterogeneity.

RESULTS

We identified a genome-wide significant region (P = 1.9 × 10^-7, LOD-equivalent 5.6) at 2q22.1. The 0.9 Mb region was inherited through 26 meioses and shared by seven of the eight genotyped cases. It sits within a ~6.25 Mb locus identified in a previous linkage study of 206 small CLL families. Our narrow region intersects two genes, including CXCR4 which is highly expressed in CLL cells and implicated in maintenance and progression.

CONCLUSION

SGS analysis of an extended high-risk CLL pedigree identified the most significant evidence to-date for a 0.9 Mb CLL disease locus at 2q22.1, harboring CXCR4. This discovery contributes to a growing literature implicating CXCR4 in inherited risk to CLL. Investigation of the segregating haplotype in the pedigree will be valuable for elucidating risk variant(s).

Sequencing at lymphoid neoplasm susceptibility loci maps six myeloma risk genes

Inherited genetic risk factors play a role in multiple myeloma (MM), yet considerable missing heritability exists. Rare risk variants at genome-wide association study (GWAS) loci are a new avenue to explore. Pleiotropy between lymphoid neoplasms (LNs) has been suggested in family history and genetic studies, but no studies have interrogated sequencing for pleiotropic genes or rare risk variants. Sequencing genetically enriched cases can help discover rarer variants. We analyzed exome sequencing in familial or early-onset MM cases to identify rare, functionally relevant variants near GWAS loci for a range of LNs. A total of 149 distinct and significant LN GWAS loci have been published. We identified six recurrent, rare, potentially deleterious variants within 5 kb of significant GWAS single nucleotide polymorphisms in 75 MM cases. Mutations were observed in BTNL2, EOMES, TNFRSF13B, IRF8, ACOXL and TSPAN32. All six genes replicated in an independent set of 255 early-onset MM or familial MM or precursor cases. Expansion of our analyses to the full length of these six genes resulted in a list of 39 rare and deleterious variants, seven of which segregated in MM families. Three genes also had significant rare variant burden in 733 sporadic MM cases compared with 935 control individuals: IRF8 (P = 1.0 × 10-6), EOMES (P = 6.0 × 10-6) and BTNL2 (P = 2.1 × 10-3). Together, our results implicate six genes in MM risk, provide support for genetic pleiotropy between LN subtypes and demonstrate the utility of sequencing genetically enriched cases to identify functionally relevant variants near GWAS loci.

Adipose tissue radiodensity: A new prognostic biomarker in people with multiple myeloma

OBJECTIVES

Standard prognostic markers based on individual characteristics of individuals with multiple myeloma (MM) remain scarce. Body-composition features have often been associated with survival outcomes in different cancers. However, the association of adipose tissue radiodensity with MM prognosis has not yet, to our knowledge, been explored.

METHODS

Computed tomography at the third lumbar vertebra was used for body-composition analysis, including adipose tissue radiodensity, in 91 people with MM. Additionally, fludeoxyglucose F 18 (¹⁸F-FDG) positron emission tomography was used to assess adipose tissue ¹⁸F-FDG uptake. Proinflammatory cytokine and adipokine levels were measured.

RESULTS

Event-free survival and overall survival were both shorter in participants with high subcutaneous adipose tissue (SAT) radiodensity. Those in the highest SAT radiodensity tertile had an independently higher risk for both overall survival (hazard ratio, 4.55; 95% confidence interval, 1.26-16.44; P_trend = 0.036) and event-free survival (hazard ratio, 3.08; 95% confidence interval, 1.02-9.27; P_trend = 0.035). Importantly, higher SAT radiodensity was significantly correlated with increased ¹⁸F-FDG adipose tissue uptake and proinflammatory cytokine (tumor necrosis factor and interleukin-6) levels, and with decreased leptin levels.

CONCLUSIONS

SAT radiodensity may serve as a biomarker to predict host-related metabolic and proinflammatory milieu, which ultimately correlates with MM prognosis.

Duo Shared Genomic Segment analysis identifies a genome-wide significant risk locus at 18q21.33 in myeloma pedigrees

AIM

High-risk pedigrees (HRPs) are a powerful design to map highly penetrant risk genes. We previously described Shared Genomic Segment (SGS) analysis, a mapping method for single large extended pedigrees that also addresses genetic heterogeneity inherent in complex diseases. SGS identifies shared segregating chromosomal regions that may inherit in only a subset of cases. However, single large pedigrees that are individually powerful (at least 15 meioses between studied cases) are scarce. Here, we expand the SGS strategy to incorporate evidence from two extended HRPs by identifying the same segregating risk locus in both pedigrees and allowing for some relaxation in the size of each HRP.

METHODS

Duo-SGS is a procedure to combine single-pedigree SGS evidence. It implements statistically rigorous duo-pedigree thresholding to determine genome-wide significance levels that account for optimization across pedigree pairs. Single-pedigree SGS identifies optimal segments shared by case subsets at each locus across the genome, with nominal significance assessed empirically. Duo-SGS combines the statistical evidence for SGS segments at the same genomic location in two pedigrees using Fisher's method. One pedigree is paired with all others and the best duo-SGS evidence at each locus across the genome is established. Genome-wide significance thresholds are determined through distribution-fitting and the Theory of Large Deviations. We applied the duoSGS strategy to eleven extended, myeloma HRPs.

RESULTS

We identified one genome-wide significant region at 18q21.33 (0.85 Mb, P = 7.3 × 10-9) which contains one gene, CDH20. Thirteen regions were genome-wide suggestive: 1q42.2, 2p16.1, 3p25.2, 5q21.3, 5q31.1, 6q16.1, 6q26, 7q11.23, 12q24.31, 13q13.3, 18p11.22, 18q22.3 and 19p13.12.

CONCLUSION

Our results provide novel risk loci with segregating evidence from multiple HRPs and offer compelling targets and specific segment carriers to focus a future search for functional variants involved in inherited risk formyeloma.

Coinherited genetics of multiple myeloma and its precursor, monoclonal gammopathy of undetermined significance

So far, 23 germline susceptibility loci have been associated with multiple myeloma (MM) risk. It is unclear whether the genetic variation associated with MM susceptibility also predisposes to its precursor, monoclonal gammopathy of undetermined significance (MGUS). Leveraging 2434 MM cases, 754 MGUS cases, and 2 independent sets of controls (2567/879), we investigated potential shared genetic susceptibility of MM and MGUS by (1) performing MM and MGUS genome-wide association studies (GWAS); (2) validating the association of a polygenic risk score (PRS) based on 23 established MM loci (MM-PRS) with risk of MM, and for the first time with MGUS; and (3) examining genetic correlation of MM and MGUS. Heritability and genetic estimates yielded 17% (standard error [SE] ±0.04) and 15% (SE ±0.11) for MM and MGUS risk, respectively, and a 55% (SE ±0.30) genetic correlation. The MM-PRS was associated with risk of MM when assessed continuously (odds ratio [OR], 1.17 per SD; 95% confidence interval [CI], 1.13-1.21) or categorically (OR, 1.70; 95% CI, 1.38-2.09 for highest; OR, 0.71; 95% CI, 0.55-0.90 for lowest compared with middle quintile). The MM-PRS was similarly associated with MGUS (OR, 1.19 per SD; 95% CI, 1.14-1.26 as a continuous measure, OR, 1.77, 95%CI: 1.29-2.43 for highest and OR, 0.70, 95%CI: 0.50-0.98 for lowest compared with middle quintile). MM and MGUS associations did not differ by age, sex, or MM immunoglobulin isotype. We validated a 23-SNP MM-PRS in an independent series of MM cases and provide evidence for its association with MGUS. Our results suggest shared common genetic susceptibility to MM and MGUS.

Neurexin 1 variants as risk factors for suicide death

Suicide is a significant public health concern with complex etiology. Although the genetic component of suicide is well established, the scope of gene networks and biological mechanisms underlying suicide has yet to be defined. Previously, we reported genome-wide evidence that neurexin 1 (NRXN1), a key synapse organizing molecule, is associated with familial suicide risk. Here we present new evidence for two non-synonymous variants (rs78540316; P469S and rs199784139; H885Y) associated with increased familial risk of suicide death. We tested the impact of these variants on binding interactions with known partners and assessed functionality in a hemi-synapse formation assay. Although the formation of hemi-synapses was not altered with the P469S variant relative to wild-type, both variants increased binding to the postsynaptic binding partner, leucine-rich repeat transmembrane neuronal 2 (LRRTM2) in vitro. Our findings indicate that variants in NRXN1 and related synaptic genes warrant further study as risk factors for suicide death.

Inherited predisposition to haematopoietic malignancies: overcoming barriers and exploring opportunities

Inherited predisposition to haematopoietic malignancies, due to deleterious germline variants in a variety of genes, is an important clinical entity with implications for the health and management of patients and their family members. Unfortunately, there remain several common misconceptions in this field that can result in patients going unrecognised and/or having incomplete or improper testing including: the impression that inherited haematological malignancy syndromes are rare, that myeloid and lymphoid malignancy predisposition syndromes are mutually exclusive, and that solid tumour predisposition syndromes are unique and distinct from haematopoietic malignancy predisposition syndromes. In the present review, we challenge these ideas with our insights into germline genetic testing for these conditions with the hope that increased awareness and knowledge will overcome barriers and lead to improved diagnosis and management.

The perspectives of interleukin-10 in the pathogenesis and therapeutics of multiple myeloma

Multiple myeloma (MM) is typically featured by the increased levels of inflammatory cytokines in the neoplastic plasma cells (PCs) producing monoclonal immunoglobulin. PCs proliferate in the bone marrow, which will lead to extensive skeletal destruction with osteolytic lesions, osteopenia, or pathologic fractures. The diagnostic biology of MM has progressed from morphology and low-sensitivity protein analysis into multiomics-based high-throughput readout, whereas therapeutics has evolved from single active agent to potential active drug combinations underlying precision medicine. Many studies have focused on the cytokine networks that control growth, progression, and dissemination of the disease. The complexity of cytokines in MM development remains to be elucidated comprehensively. Apart from knowing that interleukin (IL)-6 is important in the pathogenesis of MM, it has been shown that IL-6 is a paracrine factor supplied by the microenvironment comprising of those cells from the myeloid compartment. Due to IL-10 was considered an immunosuppressive cytokine to promote cancer escape from immune surveillance, the role of IL-10 in this regard has been underestimated although recent advances have reported that IL-10 induces both PC proliferation and angiogenesis in MM. In addition, cumulative studies have suggested that IL-10 plays an important role in the induction of chemoresistance in many cancers; a virtual requirement of autocrine IL-10 for MM cells to escape from an IL-6-dependent proliferation loop was implicated. In this review, we summarize the available information to elucidate a new understanding of the molecular and functional roles of IL-10 in MM.

A Journey Through Myeloma Evolution: From the Normal Plasma Cell to Disease Complexity

The knowledge of cancer origin and the subsequent tracking of disease evolution represent unmet needs that will soon be within clinical reach. This will provide the opportunity to improve patient's stratification and to personalize treatments based on cancer biology along its life history. In this review, we focus on the molecular pathogenesis of multiple myeloma (MM), a hematologic malignancy with a well-known multi-stage disease course, where such approach can sooner translate into a clinical benefit. We describe novel insights into modes and timing of disease initiation. We dissect the biology of the preclinical and pre-malignant phases, elucidating how knowledge of the genomics of the disease and the composition of the microenvironment allow stratification of patients based on risk of disease progression. Then, we explore cell-intrinsic and cell-extrinsic drivers of MM evolution to symptomatic disease. Finally, we discuss how this may relate to the development of refractory disease after treatment. By integrating an evolutionary view of myeloma biology with the recent acquisitions on its clonal heterogeneity, we envision a way to drive the clinical management of the disease based on its detailed biological features more than surrogates of disease burden.

Genomic Instability in Multiple Myeloma

Genomic instability (GIN), an increased tendency to acquire genomic alterations, is a cancer hallmark. However, its frequency, underlying causes, and disease relevance vary across different cancers. Multiple myeloma (MM), a plasma cell malignancy, evolves through premalignant phases characterized by genomic abnormalities. Next-generation sequencing (NGS) methods are deconstructing the genomic landscape of MM across the continuum of its development, inextricably linking malignant transformation and disease progression with increasing acquisition of genomic alterations, and illuminating the mechanisms that generate these alterations. Although GIN drives disease evolution, it also creates vulnerabilities such as dependencies on 'superfluous' repair mechanisms and the induction of tumor-specific antigens that can be targeted. We review the mechanisms of GIN in MM, the associated vulnerabilities, and therapeutic targeting strategies.

Family Study Designs Informed by Tumor Heterogeneity and Multi-Cancer Pleiotropies: The Power of the Utah Population Database

BACKGROUND

Previously, family-based designs and high-risk pedigrees have illustrated value for the discovery of high- and intermediate-risk germline breast cancer susceptibility genes. However, genetic heterogeneity is a major obstacle hindering progress. New strategies and analytic approaches will be necessary to make further advances. One opportunity with the potential to address heterogeneity via improved characterization of disease is the growing availability of multisource databases. Specific to advances involving family-based designs are resources that include family structure, such as the Utah Population Database (UPDB). To illustrate the broad utility and potential power of multisource databases, we describe two different novel family-based approaches to reduce heterogeneity in the UPDB.

METHODS

Our first approach focuses on using pedigree-informed breast tumor phenotypes in gene mapping. Our second approach focuses on the identification of families with similar pleiotropies. We use a novel network-inspired clustering technique to explore multi-cancer signatures for high-risk breast cancer families.

RESULTS

Our first approach identifies a genome-wide significant breast cancer locus at 2q13 [P = 1.6 × 10-8, logarithm of the odds (LOD) equivalent 6.64]. In the region, IL1A and IL1B are of particular interest, key cytokine genes involved in inflammation. Our second approach identifies five multi-cancer risk patterns. These clusters include expected coaggregations (such as breast cancer with prostate cancer, ovarian cancer, and melanoma), and also identify novel patterns, including coaggregation with uterine, thyroid, and bladder cancers.

CONCLUSIONS

Our results suggest pedigree-informed tumor phenotypes can map genes for breast cancer, and that various different cancer pleiotropies exist for high-risk breast cancer pedigrees.

IMPACT

Both methods illustrate the potential for decreasing etiologic heterogeneity that large, population-based multisource databases can provide.See all articles in this CEBP Focus section, "Modernizing Population Science."

Genetic predisposition for multiple myeloma

Multiple myeloma (MM) is the second most common blood malignancy. Epidemiological family studies going back to the 1920s have provided evidence for familial aggregation, suggesting a subset of cases have an inherited genetic background. Recently, studies aimed at explaining this phenomenon have begun to provide direct evidence for genetic predisposition to MM. Genome-wide association studies have identified common risk alleles at 24 independent loci. Sequencing studies of familial cases and kindreds have begun to identify promising candidate genes where variants with strong effects on MM risk might reside. Finally, functional studies are starting to give insight into how identified risk alleles promote the development of MM. Here, we review recent findings in MM predisposition field, and highlight open questions and future directions.

Genome-wide significant regions in 43 Utah high-risk families implicate multiple genes involved in risk for completed suicide

Suicide is the 10th leading cause of death in the United States. Although environment has undeniable impact, evidence suggests that genetic factors play a significant role in completed suicide. We linked a resource of ~ 4500 DNA samples from completed suicides obtained from the Utah Medical Examiner to genealogical records and medical records data available on over eight million individuals. This linking has resulted in the identification of high-risk extended families (7-9 generations) with significant familial risk of completed suicide. Familial aggregation across distant relatives minimizes effects of shared environment, provides more genetically homogeneous risk groups, and magnifies genetic risks through familial repetition. We analyzed Illumina PsychArray genotypes from suicide cases in 43 high-risk families, identifying 30 distinct shared genomic segments with genome-wide evidence (p = 2.02E-07-1.30E-18) of segregation with completed suicide. The 207 genes implicated by the shared regions provide a focused set of genes for further study; 18 have been previously associated with suicide risk. Although PsychArray variants do not represent exhaustive variation within the 207 genes, we investigated these for specific segregation within the high-risk families, and for association of variants with predicted functional impact in ~ 1300 additional Utah suicides unrelated to the discovery families. None of the limited PsychArray variants explained the high-risk family segregation; sequencing of these regions will be needed to discover segregating risk variants, which may be rarer or regulatory. However, additional association tests yielded four significant PsychArray variants (SP110, rs181058279; AGBL2, rs76215382; SUCLA2, rs121908538; APH1B, rs745918508), raising the likelihood that these genes confer risk of completed suicide.

DNA damage-induced activation of ATM promotes β-TRCP-mediated ARID1A ubiquitination and destruction in gastric cancer cells

Background

AT-rich interactive domain-containing protein 1A (ARID1A) is a subunit of the mammary SWI/SNF chromatin remodeling complex and a tumor suppressor protein. The loss of ARID1A been observed in several types of human cancers and associated with poor patient prognosis. Previously, we have reported that ARID1A protein was rapidly ubiquitinated and destructed in gastric cancer cells during DNA damage response. However, the ubiquitin e3 ligase that mediated this process remains unclear.

Materials and methods

The interaction between ARID1A and β-TRCP was verified by co-immunoprecipitation (Co-IP) assay. The degron site of ARID1A protein was analyzed by bioinformatics assay. Short hairpin RNAs (shRNAs) were used to knockdown (KD) gene expression.

Results

Here we show that DNA damage promotes ARID1A ubiquitination and subsequent destruction via the ubiquitin E3 ligase complex SCFβ-TRCP. β-TRCP recognizes ARID1A through a canonical degron site (DSGXXS) after its phosphorylation in response to DNA damage. Notably, genetic inactivation of the Ataxia Telangiectasia Mutated (ATM) kinase impaired DNA damage-induced ARID1A destruction.

Conclusions

Our studies provide a novel molecular mechanism for the negative regulation of ARID1A by β-TRCP and ATM in DNA damaged gastric cancer cells.

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.

Lineage: Visualizing Multivariate Clinical Data in Genealogy Graphs

The majority of diseases that are a significant challenge for public and individual heath are caused by a combination of hereditary and environmental factors. In this paper we introduce Lineage, a novel visual analysis tool designed to support domain experts who study such multifactorial diseases in the context of genealogies. Incorporating familial relationships between cases with other data can provide insights into shared genomic variants and shared environmental exposures that may be implicated in such diseases. We introduce a data and task abstraction, and argue that the problem of analyzing such diseases based on genealogical, clinical, and genetic data can be mapped to a multivariate graph visualization problem. The main contribution of our design study is a novel visual representation for tree-like, multivariate graphs, which we apply to genealogies and clinical data about the individuals in these families. We introduce data-driven aggregation methods to scale to multiple families. By designing the genealogy graph layout to align with a tabular view, we are able to incorporate extensive, multivariate attributes in the analysis of the genealogy without cluttering the graph. We validate our designs by conducting case studies with our domain collaborators.