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The hallmark signatures based on gene expression capture core cancer processes. Through a pan-cancer analysis, we describe the overview of hallmark signatures across tumor types/subtypes and reveal significant relationships between these signatures and genetic alterations. TP53 mutation exerts diverse changes, including increased proliferation and glycolysis, which are closely mimicked by widespread copy-number alterations. Hallmark signature and copy-number clustering identify a cluster of squamous tumors and basal-like breast and bladder cancers with elevated proliferation signatures, frequent TP53 mutation, and high aneuploidy. In these basal-like/squamous TP53-mutated tumors, a specific and consistent spectrum of copy-number alterations is preferentially selected prior to whole-genome duplication. Within Trp53-null breast cancer mouse models, these copy-number alterations spontaneously occur and recapitulate the hallmark signature changes observed in the human condition. Together, our analysis reveals intertumor and intratumor heterogeneity of the hallmark signatures, uncovering an oncogenic program induced by TP53 mutation and select aneuploidy events to drive a worsened prognosis.Significance:Our data demonstrate that TP53 mutation and a resultant selected pattern of aneuploidies cause an aggressive transcriptional program including upregulation of glycolysis signature with prognostic implications. Importantly, basal-like breast cancer demonstrates genetic and/or phenotypic changes closely related to squamous tumors including 5q deletion that reveal alterations that could offer therapeutic options across tumor types regardless of tissue of origin.

Large-scale analyses of genomic data from patients with newly diagnosed multiple myeloma (ndMM) have been undertaken, however, large-scale analysis of relapsed/refractory MM (rrMM) has not been performed. We hypothesize that somatic variants chronicle the therapeutic exposures and clonal structure of myeloma from ndMM to rrMM stages. We generated whole-genome sequencing (WGS) data from 418 tumors (386 patients) derived from 6 rrMM clinical trials and compared them with WGS from 198 unrelated patients with ndMM in a population-based case-control fashion. We identified significantly enriched events at the rrMM stage, including drivers (DUOX2, EZH2, TP53), biallelic inactivation (TP53), noncoding mutations in bona fide drivers (TP53BP1, BLM), copy number aberrations (CNAs; 1qGain, 17pLOH), and double-hit events (Amp1q-ISS3, 1qGain-17p loss-of-heterozygosity). Mutational signature analysis identified a subclonal defective mismatch repair signature enriched in rrMM and highly active in high mutation burden tumors, a likely feature of therapy-associated expanding subclones. Further analysis focused on the association of genomic aberrations enriched at different stages of resistance to immunomodulatory agent (IMiD)–based therapy. This analysis revealed that TP53, DUOX2, 1qGain, and 17p loss-of-heterozygosity increased in prevalence from ndMM to lenalidomide resistant (LENR) to pomalidomide resistant (POMR) stages, whereas enrichment of MAML3 along with immunoglobulin lambda (IGL) and MYC translocations distinguished POM from the LEN subgroup. Genomic drivers associated with rrMM are those that confer clonal selective advantage under therapeutic pressure. Their role in therapy evasion should be further evaluated in longitudinal patient samples, to confirm these associations with the evolution of clinical resistance and to identify molecular subsets of rrMM for the development of targeted therapies.

The acquisition of a multidrug refractory state is a major cause of mortality in myeloma. Myeloma drugs that target the cereblon (CRBN) protein include widely used immunomodulatory drugs (IMiDs), and newer CRBN E3 ligase modulator drugs (CELMoDs), in clinical trials. CRBN genetic disruption causes resistance and poor outcomes with IMiDs. Here, we investigate alternative genomic associations of IMiD resistance, using large whole-genome sequencing patient datasets (n = 522 cases) at newly diagnosed, lenalidomide (LEN)-refractory and lenalidomide-then-pomalidomide (LEN-then-POM)-refractory timepoints. Selecting gene targets reproducibly identified by published CRISPR/shRNA IMiD resistance screens, we found little evidence of genetic disruption by mutation associated with IMiD resistance. However, we identified a chromosome region, 2q37, containing COP9 signalosome members COPS7B and COPS8, copy loss of which significantly enriches between newly diagnosed (incidence 5.5%), LEN-refractory (10.0%), and LEN-then-POM-refractory states (16.4%), and may adversely affect outcomes when clonal fraction is high. In a separate dataset (50 patients) with sequential samples taken throughout treatment, we identified acquisition of 2q37 loss in 16% cases with IMiD exposure, but none in cases without IMiD exposure. The COP9 signalosome is essential for maintenance of the CUL4-DDB1-CRBN E3 ubiquitin ligase. This region may represent a novel marker of IMiD resistance with clinical utility.

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

Purpose:We designed a comprehensive multiple myeloma targeted sequencing panel to identify common genomic abnormalities in a single assay and validated it against known standards.Experimental Design:The panel comprised 228 genes/exons for mutations, 6 regions for translocations, and 56 regions for copy number abnormalities (CNA). Toward panel validation, targeted sequencing was conducted on 233 patient samples and further validated using clinical FISH (translocations), multiplex ligation probe analysis (MLPA; CNAs), whole-genome sequencing (WGS; CNAs, mutations, translocations), or droplet digital PCR (ddPCR) of known standards (mutations).Results:Canonical immunoglobulin heavy chain translocations were detected in 43.2% of patients by sequencing, and aligned with FISH except for 1 patient. CNAs determined by sequencing and MLPA for 22 regions were comparable in 103 samples and concordance between platforms was R2 = 0.969. Variant allele frequency (VAF) for 74 mutations were compared between sequencing and ddPCR with concordance of R2 = 0.9849.Conclusions:In summary, we have developed a targeted sequencing panel that is as robust or superior to FISH and WGS. This molecular panel is cost-effective, comprehensive, clinically actionable, and can be routinely deployed to assist risk stratification at diagnosis or posttreatment to guide sequencing of therapies.

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

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

Lung cancer in never smokers (LCINS) is a common cause of cancer mortality but its genomic landscape is poorly characterized. Here high-coverage whole-genome sequencing of 232 LCINS showed 3 subtypes defined by copy number aberrations. The dominant subtype (piano), which is rare in lung cancer in smokers, features somatic UBA1 mutations, germline AR variants and stem cell-like properties, including low mutational burden, high intratumor heterogeneity, long telomeres, frequent KRAS mutations and slow growth, as suggested by the occurrence of cancer drivers' progenitor cells many years before tumor diagnosis. The other subtypes are characterized by specific amplifications and EGFR mutations (mezzo-forte) and whole-genome doubling (forte). No strong tobacco smoking signatures were detected, even in cases with exposure to secondhand tobacco smoke. Genes within the receptor tyrosine kinase-Ras pathway had distinct impacts on survival; five genomic alterations independently doubled mortality. These findings create avenues for personalized treatment in LCINS.

Emergence of drug resistance to all available therapies is the major challenge to improving survival in myeloma. Cereblon (CRBN) is the essential binding protein of the widely used immunomodulatory drugs (IMiDs) and novel CRBN E3 ligase modulator drugs (CELMoDs) in myeloma, as well as certain proteolysis targeting chimeras (PROTACs), in development for a range of diseases. Using whole-genome sequencing (WGS) data from 455 patients and RNA sequencing (RNASeq) data from 655 patients, including newly diagnosed (WGS, n = 198; RNASeq, n = 437), lenalidomide (LEN)-refractory (WGS, n = 203; RNASeq, n = 176), and pomalidomide (POM)-refractory cohorts (WGS, n = 54; RNASeq, n = 42), we found incremental increases in the frequency of 3 CRBN aberrations, namely point mutations, copy losses/structural variations, and a specific variant transcript (exon 10 spliced), with progressive IMiD exposure, until almost one-third of patients had CBRN alterations by the time they were POM refractory. We found all 3 CRBN aberrations were associated with inferior outcomes to POM in those already refractory to LEN, including those with gene copy losses and structural variations, a finding not previously described. This represents the first comprehensive analysis and largest data set of CBRN alterations in myeloma patients as they progress through therapy. It will help inform patient selection for sequential therapies with CRBN-targeting drugs.

Purpose: We designed a comprehensive multiple myeloma targeted sequencing panel to identify common genomic abnormalities in a single assay and validated it against known standards. Experimental Design: The panel comprised 228 genes/exons for mutations, 6 regions for translocations, and 56 regions for copy number abnormalities (CNA). Toward panel validation, targeted sequencing was conducted on 233 patient samples and further validated using clinical FISH (translocations), multiplex ligation probe analysis (MLPA; CNAs), whole-genome sequencing (WGS; CNAs, mutations, translocations), or droplet digital PCR (ddPCR) of known standards (mutations). Results: Canonical immunoglobulin heavy chain translocations were detected in 43.2% of patients by sequencing, and aligned with FISH except for 1 patient. CNAs determined by sequencing and MLPA for 22 regions were comparable in 103 samples and concordance between platforms was R2 = 0.969. Variant allele frequency (VAF) for 74 mutations were compared between sequencing and ddPCR with concordance of R2 = 0.9849. Conclusions: In summary, we have developed a targeted sequencing panel that is as robust or superior to FISH and WGS. This molecular panel is cost-effective, comprehensive, clinically actionable, and can be routinely deployed to assist risk stratification at diagnosis or posttreatment to guide sequencing of therapies.

Non

Black women across the African diaspora experience more aggressive breast cancer with higher mortality rates than white women of European ancestry. Although inter-ethnic germline variation is known, differential somatic evolution has not been investigated in detail. Analysis of deep whole genomes of 97 breast cancers, with RNA-seq in a subset, from women in Nigeria in comparison with The Cancer Genome Atlas (n = 76) reveal a higher rate of genomic instability and increased intra-tumoral heterogeneity as well as a unique genomic subtype defined by early clonal GATA3 mutations with a 10.5-year younger age at diagnosis. We also find non-coding mutations in bona fide drivers (ZNF217 and SYPL1) and a previously unreported INDEL signature strongly associated with African ancestry proportion, underscoring the need to expand inclusion of diverse populations in biomedical research. Finally, we demonstrate that characterizing tumors for homologous recombination deficiency has significant clinical relevance in stratifying patients for potentially life-saving therapies., Breast cancer heterogeneity and tumour evolutionary trajectories remain largely unknown among women of African ancestry. Here, the authors perform whole genome and transcriptome sequencing of Nigerian breast cancer patients and identify unique evolutionary phenomena.

Black women of African ancestry experience more aggressive breast cancer with higher mortality rates than White women of European ancestry. Although inter-ethnic germline variation is known, differential somatic evolution has not been investigated in detail. Analysis of deep whole genomes of 97 breast tumors, with RNA-seq in a subset, from indigenous African patients in Nigeria in comparison to The Cancer Genome Atlas (n=76) revealed a higher rate of genomic instability and increased intra-tumoral heterogeneity as well as a unique genomic subtype defined by early clonal GATA3 mutations and a 10.5-year younger age at diagnosis. We also found evidence for non-coding mutations in two novel drivers (ZNF217 and SYPL1) and a novel INDEL signature strongly associated with African ancestry proportion. This comprehensive analysis of an understudied population underscores the need to incorporate diversity of genomes as a key parameter in fundamental research with potential to tailor clinical intervention and promote equity in precision oncology care.

Metastatic melanoma carries a poor prognosis despite modern systemic therapies. Understanding the evolution of the disease could help inform patient management. Through whole-genome sequencing of 13 melanoma metastases sampled at autopsy from a treatment naïve patient and by leveraging the analytical power of multi-sample analyses, we reveal evidence of diversification among metastatic lineages. UV-induced mutations dominate the trunk, whereas APOBEC-associated mutations are found in the branches of the evolutionary tree. Multi-sample analyses from a further seven patients confirmed that lineage diversification was pervasive, representing an important mode of melanoma dissemination. Our analyses demonstrate that joint analysis of cancer cell fraction estimates across multiple metastases can uncover previously unrecognised levels of tumour heterogeneity and highlight the limitations of inferring heterogeneity from a single biopsy., Metastatic melanoma is associated with a poor prognosis and understanding the genetic features of metastases may enable better treatment strategies. Here, the authors analyse multiple metastases from individual patients finding high levels of heterogeneity in metastases from different organs.

Identifying causal genes of spermatogenic failure on the male-specific region of Y chromosome (MSY) has been a challenging process. Due to the nonrecombining nature of MSY, haplotype-based approaches have recently been shown to be promising in identifying associated MSY haplogroups. We conducted an MSY analysis of nonobstructive azoospermia (NOA) patients in a case-control setting (N = 278 and 105 respectively) to identify modal haplogroups strongly associated with NOA. Patients with AZF deletions (AZF+) and no AZF deletions (AZF-) were compared with the control group. Given the larger sample set of AZF- NOA patients, we further investigated the association based on histopathological severity, namely Sertoli cell-only syndrome and maturation arrest subtypes. We observed no significant enrichment of MSY haplogroups in AZF- azoospermic patients (or its subtypes). However, we observed a strongly significant association between haplogroup J2a* and AZF+ patients (FDR-corrected p = .0056; OR = 7.02, 95%CI 1.89 to 39.20), a haplogroup which also showed significant enrichment for AZFa/b deletions (p = 4x10-4 ). We conclude that unlike AZF+ patients, AZF- NOA are less likely to have an MSY causative factor with large effect size, thus indicating that the aetiology of AZF- NOA, and to some extent AZFc NOA, is more likely to be based on non-MSY factors.

Studying relationships among gene-product expression profiles is a common approach in systems biology. Many studies have generalized this subject to different levels of the central dogma information flow and assumed correlation of transcript and protein expression levels. All these efforts have updated the signaling network models and expanded the current signaling databases, which include interactions among the gene-products extracted based on either the literature or direct and indirect experiments. In fact, due to unavailability or high-cost of the experiments, most of the studies do not look for the direct interactions (gene-protein or protein-protein) and some of them are contradictory. In addition, it is now a standard practice to undertake enrichment analysis on biological annotations especially in omics research to make claims about the potentially implicated biological pathways in disease. Specifically, upon identifying differentially expressed genes, molecular mechanistic insights are proposed based on statistically enriched biological processes for disease etiology and drug discovery. However, it remains to be demonstrated that expression data may be used as a reliable source to infer causal relationships among gene pairs. In this study, using four common and comprehensive databases i.e. GEO, GDSC, KEGG, and OmniPath, we extracted all relevant gene expression data and all relationships among directly linked gene pairs in order to evaluate the rate of coherency or sign consistency. We illustrated that the signaling network was not more consistent or coherent with the measured expression profile compare to random relationships. Finally, we provided the pieces of evidence and concluded that gene-product expression data, especially at the transcript level, are not reliable or at least insufficient to infer biological relationships among genes and in turn describe cellular behavior.

Introduction: Multiple myeloma (MM) is a genetically heterogeneous disease where risk stratification and outcomes are associated with translocations involving the immunoglobulin (Ig) loci and MYC, copy number abnormalities including gain(1q), del(1p), and del(17p), as well as mutations. Additionally, MM tumors may harbor rare mutations in genes that are targetable in other tumors, such as in IDH1 and IDH2. Therefore, we designed a comprehensive MM targeted sequencing panel to interrogate the common genomic abnormalities in MM and validated it against known standards. Methods: The targeted panel was designed to include the exons of 228 genes which are either frequently mutated, associated with prognosis or risk stratification, clinically actionable, or sites of important copy number abnormalities. Additional targets were added across the genome to identify hyperdiploidy. These targeted regions encompass the mutation detection part of the panel and involve approximately 990 kb. The Ig loci and region surrounding MYC were tiled to capture translocations and copy number changes. In total, this translocation part of the panel involves approximately 4.7 Mb. The mutation and translocation panels are manufactured separately and combined during the assay resulting in a 5:1 sequencing ratio, respectively, which prevents over-sequencing of the large translocation panel. 100 ng DNA extracted from CD138+ bone marrow cells (n=223) and from non-tumor tissue (peripheral blood or saliva) was processed using the HyperCap workflow (KAPA Biosystems). Of the 223, 48 samples were processed in a clinical diagnostic laboratory. Adapter ligated DNA was hybridized with a mixture of the mutation and translocation panel and purified, amplified libraries were sequenced using 75 bp paired end reads. Sequences were aligned to hg19 and mutations and translocations identified using Strelka and Manta. Copy number was determined using the ratio of non-tumor to tumor reads in each targeted region. Data were validated using clinical FISH (translocations, n=116), MLPA (copy number, n=101), known standards (mutations), ddPCR (mutations), and whole genome sequencing (WGS; translocations and copy number, n=122). Results: Canonical IgH translocations were detected in 43.2% of patients by the panel, and all agreed with WGS. FISH detected one additional "variant" t(4;14), but did not detect 4 translocations detected by both sequencing methods. In the remainder of the samples no canonical IgH translocation was detected, agreeing with FISH results. Non-canonical translocations were detected in 14.5% of samples, 43% of which were to the MYC locus. MYC translocations were detected in 37.3% of samples with copy number abnormalities occurring surrounding MYC in 32.7% of samples. Overall, MYC abnormalities were detected in 46.4% of samples. Copy number was determined by panel sequencing and MLPA for 22 regions that were directly comparable between the technologies in 101 patient samples and 13 myeloma cell lines. The copy number concordance between the technologies was 96.9% and 99.6% in patient samples and cell lines, respectively. For the important prognostic regions, the concordance was R 2=0.962 (CDKN2C), R 2=0.986 (CKS1B), and R 2=0.973 (TP53). Panel copy number data were also compared to WGS data and showed complete concordance across the three prognostic regions, which the exception of 2 samples. In these 2 samples a homozygous deletion was detected by the panel but not by WGS. The deletions were 6.2 and 8.0 kb in size, one encompassing the coding sequencing of TP53 and the other exons 1-4 of TP53. A larger homozygous deletion of 36.3 kb was detected by both sequencing methods. Mutation detection validation was performed using Horizon Discovery samples with known variant allele frequencies (VAF) for common mutations. We were able to determine the sequencing VAF for 74 mutations across 5 samples which had a concordance of R 2=0.9849 between the expected and observed frequencies. The minimum detected VAF was 1.3% at an average depth of 891x. We also performed ddPCR on 6 patient samples with the common KRAS, NRAS and BRAF mutations which resulted in a VAF concordance of R 2=0.9983. Conclusion: We have developed a targeted sequencing panel for MM patient samples that is as robust or better than both FISH and WGS. A full protocol for sample processing and analysis is available, and has been used in a clinical diagnostic laboratory. Disclosures Ahsan: Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company. Abu Zaid: Pieris: Current equity holder in publicly-traded company; Incyte: Research Funding; Pharamcyclic: Research Funding; Syndax: Consultancy, Research Funding. Ramasamy: Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Conference registration, Research Funding; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Conference registration, Research Funding; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Conference registration, Research Funding; Celgene (BMS): Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Conference registration, Research Funding; GSK: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncopeptides: Honoraria, Membership on an entity's Board of Directors or advisory committees; Adaptive biotech: Honoraria, Membership on an entity's Board of Directors or advisory committees; Karyopharm: Honoraria, Membership on an entity's Board of Directors or advisory committees; Pfizer oncology: Honoraria, Membership on an entity's Board of Directors or advisory committees; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees. Yong: GSK: Honoraria; Amgen: Honoraria; BMS: Research Funding; Sanofi: Honoraria, Research Funding; Takeda: Honoraria; Autolus: Research Funding; Janssen: Honoraria, Research Funding. Morgan: Takeda: Honoraria. Abonour: Celgene-BMS: Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Research Funding; Jensen: Honoraria, Research Funding; GSK: Consultancy, Honoraria, Research Funding. Flynt: Bristol Myers Squibb: Current Employment. Ansari-Pour: Bristol Myers Squibb: Consultancy. Gooding: Bristol Myers Squibb: Research Funding. Thakurta: Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company. Walker: Bristol Myers Squibb: Research Funding; Sanofi: Speakers Bureau.

Introduction Identification of the causes of, and biomarkers for, drug resistance in myeloma is important for understanding treatment failures, and for future instigation of targeted therapeutics for myeloma. Using the largest set of whole genome sequencing (WGS) of advanced and drug resistant multiple myelomas to date, we reported that even heterozygous loss of the 3p region, which harbours immunomodulatory drug (IMiD) and CRBN E3 ligase modulator drug (CELMoD)-binding protein Cereblon (CRBN), undergoes strong therapeutic selection on lenalidomide (LEN) and/or pomalidomide (POM) treatment (Gooding et al 2021, PMC7893409). We hypothesized that copy loss of other genes required for IMiD activity may also have clinical relevance. Several groups have reported pharmacogenetic screens identifying genes essential for IMiD sensitivity in vitro, particularly genes required for the maintenance of the CUL4-DDB1-CRBN E3 Ubiquitin Ligase, such as members of the COP9 signalosome complex, function of which prevents CRBN protein degradation. However, loss of these genes has hitherto not been reported in myeloma. Methods and results We identified candidate genes whose loss may favor IMiD drug resistance from published pharmacogenetic screens (n=5), and shortlisted genes consistently identified as essential for LEN or POM function in ≥2 screens (n=23). In our WGS dataset of 455 patients (cohorts: newly diagnosed (ND) n = 198, LEN-refractory n = 203; and LEN-then-POM-refractory n = 54), the incidence of mutation of shortlisted LEN/POM-essential genes in drug-refractory cohorts was rare (10% copy loss at the LEN-then-POM-refractory state, plus incidence of copy loss that increased from ND to LEN-then-POM-refractory states by ≥1.5-fold. This delivered 3 copy loss regions for further investigation: a) 3p, which we had already reported; b) 17p, loss of which is known to be strongly selected in myeloma as the site of TP53; and c) 2q, previously unidentified as relevant in myeloma, but whose minimal common region contained two members of the COP9 signalosome (COPS7B, COPS8). Proportion of loss of this region increased between ND (5.5%), LEN-refractory (9.8%) and LEN-then-POM-refractory states (16.6%), p=0.009. Those patients who had lost a copy of these genes also demonstrated a significant reduction in COPS7B/COPS8 gene expression (p In a separate cohort of myeloma patients (n=24) with sequential sample WGS analysis before and after LEN and/or POM resistance acquisition, we traced acquisition of CNA-defined subclones. 5/24 (21%) patients had acquired either clonal or subclonal loss of the 2q region containing COPS7B and COPS8 at IMID resistance, which had been either absent or below limit of detection pre-IMiD exposure. No other CNA newly-emerged in such a high proportion during IMiD treatment. Relative decrease in even one COP9 signalosome gene has been shown to cause CRBN protein level to fall, and reduce LEN efficacy (Sievers et al 2018, PMC6148446). We are now analysing CRBN protein levels in sequential biopsies from these cases. Conclusion Copy number aberrations have not previously been shown to drive a therapy-specific clonal advantage in myeloma in the clinic. We have now identified a second novel CNA, 2q loss, which increases in incidence through LEN- and POM-refractory states to emerge as a marker of dominant clones in advanced, IMiD-resistant disease. Whether these CNAs will mark resistance to novel CELMoDs remains to be seen. The CRBN protein is key to the function of these drugs, and many novel proteolysis targeting chimeras (PROTACs) in development, but whether the kinetics of their CRBN binding are as sensitive to relative CRBN protein loss remains a key question. CNAs may be easily and cost-effectively detected in the clinic by targeted sequencing approaches, and may prove valuable in future therapeutic decision making. Disclosures Gooding: Bristol Myers Squibb: Research Funding. Ansari-Pour: Bristol Myers Squibb: Consultancy. Karagoz: h.: Research Funding. Ortiz Estevez: Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company. Towfic: Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company. Flynt: BMS: Current Employment, Current equity holder in publicly-traded company. Pierceall: BMS: Current Employment, Current equity holder in publicly-traded company. Yong: Sanofi: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; Takeda: Honoraria; GSK: Honoraria; Amgen: Honoraria; BMS: Research Funding; Autolus: Research Funding. Vyas: Astellas: Consultancy, Honoraria; Takeda: Honoraria; Janssen: Honoraria; Novartis: Honoraria; Pfizer: Honoraria; Daiichi Sankyo: Honoraria; Bristol Myers Squibb: Consultancy, Honoraria, Research Funding; Gilead: Honoraria; Jazz: Honoraria; AbbVie: Consultancy, Honoraria. Thakurta: Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company, Patents & Royalties.

Background Accurate measurement of heterogeneity and reconstruction of evolutionary pathways are key to decipher clonal dynamics in tumour origins. Although bulk population genetic sequencing data has been used extensively to understand the life history of tumours, sequencing single cell DNA is likely to provide a much higher resolution of clonal dynamics and yield new insights into competing cellular populations with different genotypes. This is of significant importance when clonal evolution from a benign state to malignant disease is being considered, such as in the clonal evolution of MGUS to multiple myeloma (MM). Methods To this end, we further refined a multiple displacement amplification-based single cell whole-exome sequencing (scWES) protocol and applied it to examine MM cells (2 cases), and in one of these cases, probed evolution from a pre-existing MGUS stage in a paired setting. Single tumour cells were isolated from CD138+CD38+ fluorescence-activated cell sorted populations and CD3+ for T cells as germline controls. We developed a novel computational pipeline to accurately call somatic SNVs/indels and copy number aberration (CNA) events in the form of loss-of-heterozygosity (LOH) and gains in each single cell, identified drivers at the genome-wide level and reconstructed the tumour phylogeny while estimating and accounting for allelic dropout (N=176 single cells, 25× each cell). Results By focusing on the patient that allowed comparison of single cells at pre- and post-malignancy states, we show that pre-malignant subclones can be readily identified, and strikingly that malignant cells arise and expand from one of the MGUS subclones in the combined tumour phylogeny. Conclusions These results suggest that this scWES based method is a pragmatic approach to investigate clonal dynamics by allowing: 1) the analysis of genetic heterogeneity at the genome-wide level (much higher resolution than targeted panels), and 2) at low sequencing costs across large set of cells when compared with whole genome sequencing-based methods.

Metastatic melanoma carries a poor prognosis despite modern systemic therapies. Understanding the evolution of the disease could help inform patient management. Through whole-genome sequencing of 13 melanoma metastases sampled at autopsy from a treatment naïve patient and by leveraging the analytical power of multi-sample analyses, we reveal that metastatic cells may depart the primary tumour very early in the disease course and follow a branched pattern of evolution. Truncal UV-induced mutations that often swamp downstream analyses of heterogeneity, were found to be replaced by APOBEC-associated mutations in the branches of the evolutionary tree. Multi-sample analyses from a further 7 patients confirmed that branched evolution was pervasive, representing an important mode of melanoma dissemination. Our analyses illustrate that combining cancer cell fraction estimates across multiple metastases provides higher resolution phylogenetic reconstructions relative to single sample analyses and highlights the limitations of accurately inferring inter-tumoural heterogeneity from a single biopsy.

Inter-individual variation of drug metabolising enzymes (DMEs) leads to variable efficacy of many drugs and even adverse drug responses. Consequently, it would be desirable to test variants of many DMEs before drug treatment. Inter-ethnic differences in frequency mean that the choice of SNPs to test may vary across population groups. Here we examine the utility of testing representative groups as a way of assessing what variants might be tested. We show that publicly available population information is potentially useful for determining loci for pre-treatment genetic testing, and for determining the most prevalent risk haplotypes in defined groups. However, we also show that the NHS England classifications have limitations for grouping for these purposes, in particular for people of African descent. We conclude: (1) genotyping of hospital patients and people from the hospital catchment area confers no advantage over using samples from appropriate existing ethnic group collections or publicly available data, (2) given the current NHS England Black African grouping, a decision as to whether to test, would have to apply to all patients of recent Black African ancestry to cover reported risk alleles and (3) the current scarcity of available genome and drug effect data from Africans is a problem for both testing and treatment decisions.

Objective Endometriosis is a common complex gynecological disorder that may result in infertility. Macrophage migration inhibitory factor (MIF) is a key pro-inflammatory cytokine that is overexpressed in endometriosis tissues. However, hitherto, no study tested the possible relevancy at genetic level. The aim of this study was to evaluate MIF polymorphisms and possible associations between haplotype of the gene and endometrioma. Study design In this experiment, 115 patients with confirmed endometrioma and 120 of women who were not diagnosed with endometrioma were recruited for this case-control genetic association study. The coding region of MIF was resequenced to detect variations of potential significance. Restriction fragment length polymorphism was used to type the −173 G/C (rs755622) promoter Single nucleotide polymorphism (SNP). Haplotype analyses were then undertaken to assess the effect of genetic variations. Results We detected one functional SNP in promoter (rs755622) and non-functional mutations across the gene including (rs2096525, rs182012324, rs33958703 and rs2070766) in our samples. However, haplotype analysis showed a significant association between MIF and endometrioma where a single haplotype CC carrying only the minor allele at −173 G/C was significantly over-represented in the patients group (P = 0.007) and remained significant even after correction for (Bonferroni adjusted P = 0.028). Conclusion We report a strong linkage between a novel MIF haplotype and endometrioma. This association is consistent with expression data at both transcript and protein levels suggesting the −173C/G promoter as a critical factor.

Phenotypic variation – such as disease susceptibility and differential drug response – has a strong genetic component. Substantial effort has therefore been made to identify causal genomic variants explaining such variation among humans. Point mutations (PMs), which are single nucleotide changes in the genome, have been identified to be the most abundant form of causal genomic variants, making them useful, reliable diagnostic markers. Methods developed to genotype PMs have moved towards solid-phase assays, which not only show greater sensitivity and specificity, but also enable scalability and faster processing time. Most current assays are, however, based on fluorescent probes, which makes them relatively expensive. To develop a more cost-effective label-free genotyping method, we used a porous silicon (PSi) base as an efficient support for DNA biosensing and coupled it with reflectometric interference Fourier transform spectroscopy (RIFTS). To assess the versatility of this approach, we tested both a single nucleotide substitution in VKORC1 (-1639G > A; rs9923231) and a single nucleotide insertion in BRCA1 (5382insC; rs80357906). We demonstrate that the PSi-RIFTS method can efficiently detect both PM types with high sensitivity where hybridization of complementary DNA can be quantifiably differentiated from mismatch and non-complementary hybridization events. In addition, we show that the PSi base with immobilized DNA not only can be re-used to type further samples, but it also remains stable for 14 days, suggesting its potential for high-throughput applications.

The identification of genetic markers (e.g. genes, pathways and subnetworks) for cancer has been one of the most challenging research areas in recent years. A subset of these studies attempt to analyze genome-wide expression profiles to identify markers with high reliability and reusability across independent whole-transcriptome microarray datasets. Therefore, the functional relationships of genes are integrated with their expression data. However, for a more accurate representation of the functional relationships among genes, utilization of the protein-protein interaction network (PPIN) seems to be necessary. Herein, a novel game theoretic approach (GTA) is proposed for the identification of cancer subnetwork markers by integrating genome-wide expression profiles and PPIN. The GTA method was applied to three distinct whole-transcriptome breast cancer datasets to identify the subnetwork markers associated with metastasis. To evaluate the performance of our approach, the identified subnetwork markers were compared with gene-based, pathway-based and network-based markers. We show that GTA is not only capable of identifying robust metastatic markers, it also provides a higher classification performance. In addition, based on these GTA-based subnetworks, we identified a new bonafide candidate gene for breast cancer susceptibility.

Nonsyndromic oral clefting (NSOC) is although one of the most common congenital disorders worldwide, its underlying molecular basis remains elusive. This process has been hindered by the overwhelmingly high level of heterogeneity observed. Given that hitherto multiple loci and genes have been associated with NSOC, and that complex diseases are usually polygenic and show a considerable level of missing heritability, we used a systems genetics approach to reconstruct the NSOC network by integrating human-based physical and regulatory interactome with whole-transcriptome microarray data. We show that the network component contains 53% (23/43) of the curated NSOC-implicated gene set and displays a highly significant propinquity (P

The human Y chromosome has an inevitable role in male fertility because it contains many genes critical for spermatogenesis and the development of the male gonads. Any genetic variation or epigenetic modification affecting the expression pattern of Y chromosome genes may thus lead to male infertility. In this study, we performed isoform-level gene expression profiling of Y chromosome genes within the azoospermia factor (AZF) regions, their X chromosome counterparts, and few autosomal paralogues in testicular biopsies of 12 men with preserved spermatogenesis and 68 men with nonobstructive azoospermia (NOA) (40 Sertoli-cell-only syndrome (SCOS) and 28 premiotic maturation arrest (MA)). This was undertaken using quantitative real-time PCR (qPCR) at the transcript level and Western blotting (WB) and immunohistochemistry (IHC) at the protein level. We profiled the expression of 41 alternative transcripts encoded by 14 AZFa, AZFb, and AZFc region genes (USP9Y, DDX3Y, XKRY, HSFY1, CYORF15A, CYORF15B, KDM5D, EIF1AY, RPS4Y2, RBMY1A1, PRY, BPY2, DAZ1, and CDY1) as well as their X chromosome homologue transcripts and a few autosomal homologues. Of the 41 transcripts, 18 were significantly down-regulated in men with NOA when compared with those of men with complete spermatogenesis. In contrast, the expression of five transcripts increased significantly in NOA patients. Furthermore, to confirm the qPCR results at the protein level, we performed immunoblotting and IHC experiments (based on 24 commercial and homemade antibodies) that detected 10 AZF-encoded proteins. In addition, their localization in testis cell types and organelles was determined. Interestingly, the two missing proteins, XKRY and CYORF15A, were detected for the first time. Finally, we focused on the expression patterns of the significantly altered genes in 12 MA patients with successful sperm retrieval compared to those of 12 MA patients with failed sperm retrieval to predict the success of sperm retrieval in azoospermic men. We showed that HSFY1-1, HSFY1-3, BPY2-1, KDM5C2, RBMX2, and DAZL1 transcripts could be used as potential molecular markers to predict the presence of spermatozoa in MA patients. In this study, we have identified isoform level signature that can be used to discriminate effectively between MA, SCOS, and normal testicular tissues and suggests the possibility of diagnosing the presence of mature sperm cell in azoospermic men to prevent additional testicular sperm extraction (TESE) surgery.

Population-based genetic association studies have proven to be a powerful tool in identifying genes implicated in many complex human diseases that have a huge impact on public health. An essential quality control step in such studies is to undertake Hardy-Weinberg equilibrium (HWE) calculations. Deviations from HWE in the control group may reflect important problems including selection bias, population stratification and genotyping errors. If HWE is violated, the inferences of these studies may thus be biased. We therefore aimed to examine the extent to which HWE calculations are reported in genetic association studies published in Cell Journal(Yakhteh)(Cell J). Using keywords pertaining to genetic association studies, eleven relevant articles were identified of which ten provided full genotypic data. The genotype distribution of 16 single nucleotide polymorphisms (SNPs) was re-analyzed for HWE by using three different methods where appropriate. HWE was not reported in 60% of all articles investigated. Among those reporting, only one article provided calculations correctly and in detail. Therefore, 90% of articles analyzed failed to provide sufficient HWE data. Interestingly, three articles had significant HWE deviation in their control groups of which one highly deviated from HWE expectations (P= 9.8×10(-12)). We thus show that HWE calculations are under-reported in genetic association studies published in this journal. Furthermore, the conclusions of the three studies showing significant HWE in their control groups should be treated cautiously as they may be potentially misleading. We therefore recommend that reporting of detailed HWE calculations should become mandatory for such studies in the future.

About 15% of couples experience difficulty in conceiving a child, of which half of the cases are thought to be male-related. Asthenozoospermia, or low sperm motility, is one of the frequent types of male infertility. Although energy metabolism is suggested to be central to the etiology of asthenozoospermia, very few attempts have been made to identify its underlying metabolic pathways. Here, we reconstructed SpermNet, the first proteome-scale model of the sperm cell by using whole-proteome data and the mCADRE algorithm. The reconstructed model was then analyzed using the COBRA toolbox. Genes were knocked-out in the model to investigate their effect on ATP production. A total of 78 genes elevated ATP production rate considerably of which most encode components of oxidative phosphorylation, fatty acid oxidation, the Krebs cycle, and members of the solute carrier 25 family. Among them, we identified 11 novel genes which have previously not been associated with sperm cell energy metabolism and may thus be implicated in asthenozoospermia. We further examined the reconstructed model by in silico knock out of currently known asthenozoospermia implicated-genes that were not predicted by our model. The pathways affected by knocking out these genes were also related to energy metabolism, confirming previous findings. Therefore, our model not only predicts the known pathways, it also identifies several non-glycolytic genes for deficient energy metabolism in asthenozoospermia. Finally, this model supports the notion that metabolic pathways besides glycolysis such as oxidative phosphorylation and fatty acid oxidation are essential for sperm energy metabolism and if validated, may form a basis for fertility recovery.mCADRE: metabolic context-specificity assessed by deterministic reaction evaluation; ATP: adenosine triphosphate; RNA: ribonucleic acid; FBA: flux balance analysis; FVA: flux variability analysis; DAVID: database for annotation, visualization and integrated discovery; OXPHOS: oxidative phosphorylation; ETC: electron transfer chain; SLC: solute carrier; DLD: dihydrolypoamide dehydrogenase; DLST: dihydrolypoamide S-succinyl transferase; OGDH: oxoglutarate dehydrogenase; CS: citrate synthase; FH: fumarate hydratase; IDH: isocitrate dehydrogenase; SUCLG1: succinate-CoA ligase; SD: succinate dehydrogenase; HADHA: hydroxyacyl-CoA dehydrogenase/3-ketoacyl-CoA thiolase/enoyl-CoA hydratase, subunit A; HADHB: hydroxyacyl-CoA dehydrogenase/3-ketoacyl-CoA thiolase/enoyl-CoA hydratase, subunit B; PPA2: pyrophosphatase (inorganic) 2; PP

Introduction Multiple myeloma (MM) is a heterogeneous disease defined by genetic lesions including translocations, chromosomal copy number aberrations (CNA), and mutations. Large-scale analyses of genomic data from newly-diagnosed patients (ndMM) have defined key oncogenic drivers beyond previously known primary events. In relapsed/refractory MM (rrMM), analyses have been completed on small numbers of patient samples for mutational profiles; however, a large-scale analysis of genomic and transcriptomic data has not been performed. In this initial analysis, we describe the rrMM genomic landscape including prevalence of key translocations, oncogenic/tumor suppressor mutational drivers, and chromosomal CNA. Methods We generated whole genome sequencing (WGS) and whole transcriptome expression (RNA-seq) from 485 rrMM patient samples derived from clinical trials: NCT01712789/CC-4047-MM-010 (N=236), NCT02045017/CC-4047-MM-013 (N=17), NCT02773030/CC-220-MM-001 (N=45) and NCT01421524/CC-122-ST-001MM2 (N=10). Somatic single nucleotide variants (SNVs) and indels were derived from WGS from 308 samples using GATK/MuTect2 and annotated using ANNOVAR. Clonal and subclonal CNA were identified using Sclust. Translocations were determined using Manta. Oncogenic/tumor suppressor drivers were identified using cDriver, which utilizes recurrence and functional consequence and cancer cell fraction (CCF) of each mutation. Results Key translocations included: t(11;14) [76/308 (25%)], t(8;14) [79/308 (25%)], t(4;14) [44/308 (14%)], t(14;16) [24/308 (8%)], t(6;14) CCND3 [18/308 (6%)], t(14;20) [17/308 (5.5%)], and t(6;14) [IRF4 17/308 (5.5%)]. Hyperdiploidy was detected in 140/308 (46%) patients. Key chromosomal CNA included del14q 134/308 (44%), del13q 131/308 (43%), del8p 113/308 (37%), del17p 53/308 (17%), amplification of 1q (≥4 copies) 45/308 (15%), and del1q 31/308 (10%). Compared to samples from ndMM patients, we saw an increase of del17p (17% vs. 8%) and t(11;14) (25% vs. 15%) in rrMM. Further, out of the 53 del17p patients, 45 (85%) were high CCF (>0.55) versus 63/107 (59%) reported in ndMM (Thakurta et al, Blood. 2019) Double Hit patients (biallelic inactivation of TP53 or amplification of 1q on a background of ISS3) was detected in 12% patients which is significantly higher than ndMM (6%, p < 0.05) (Walker et al, Leukemia. 2018) We identified a total of 107 driver genes (FDR Conclusions We have established and analyzed the largest molecular rrMM dataset with associated clinical outcome data. These analyses are revealing the evolution of genetic drivers of resistance to therapy and will assist in identification of subsets of poor prognostic groups (eg, Double Hit) and new molecular subsets of rrMM where novel targeted therapies could be developed. Disclosures Towfic: Celgene Corporation: Employment, Equity Ownership. Ansari-Pour:Celgene Corporation: Consultancy. Ortiz:Celgene Corporation: Employment, Equity Ownership. Gooding:Celgene Corporation: Research Funding. Rozelle:Celgene Corporation: Other: Contractor for Celgene. Zadorozhny:Celgene Corporation: Other: Contractor for Celgene. Mavrommatis:Celgene Corporation: Employment, Equity Ownership. Lata:Celgene Corporation: Employment, Equity Ownership. Stong:Celgene Corporation: Employment, Equity Ownership. Kamalakaran:Celgene Corporation: Employment, Equity Ownership. Tsai:Celgene Corporation: Employment, Equity Ownership. Flynt:Celgene Corporation: Employment, Equity Ownership. Thakurta:Celgene: Employment, Equity Ownership.

Myeloma survival has been significantly improved by novel therapies over the past two decades. Immunomodulatory agents (IMiDs, Lenalidomide (LEN) and Pomalidomide (POM)) are a backbone of current treatment strategies. But myeloma (MM) remains incurable, because patients ultimately relapse. IMiD drug resistance mechanisms are multifactorial, and can be either dependent or independent of IMiDs binding to Cereblon (CRBN) (a component of an E3 ligase) in tumor and immune cells. A small series of relapsed patients demonstrated sub-clonal mutation rates of 12% in CRBN and 10% in other CRBN pathway genes (Kortum et al, Blood 2016), but the clinical implication of this observation is unknown. In contrast, baseline gene expression of CRBN was not associated with clinical outcome to POM-DEX therapy (Qian et al, Leukemia & Lymphoma 2018). An integrated assessment of the burden of different mechanisms of CRBN function loss, the selective pressure for their survival, and their effects on response to CRBN-modulating agents, is lacking. For patients that progress on IMiD-based therapies, there is a need to develop drugs that will overcome their resistance. To appropriately target the right novel agents to the right patients, resistance mechanisms must be understood. A deeper understanding of the mechanistic basis for IMiD-specific resistance mechanisms is critical for differentiating new Cereblon modulating agents (eg CELMoDs) from the IMiDs. Here, we present the largest comprehensive analysis of the burden of CRBN mutation or transcript variants in relapsed refractory myeloma (RRMM) patients. We analysed WGS and RNASeq data from 298 MM samples from 268 patients across 4 clinical trials (CC-4047-MM-010 (N=226), CC-4047-MM-013 (N=17), CC-220-MM-001 (N=45) and CC-122-ST-001MM2 (N=10), for whom outcome data were available. All patients had been exposed to LEN-based therapy and a subset (69/268) were also exposed to POM-based therapy. The overall incidence of single nucleotide variants in CRBN was 17/298 (5.7%). The incidence of at least monoalleleic deletion at the CRBN gene locus was 21/298 (5.5%). CRBN has different transcript isoforms (Gandhi et al, BJHaem 2014). As high levels of isoform ENST00000424814.5, with deletion of exon 10, was previously correlated with poorer survival (Neri et al, Blood 2016), we assessed incidence of a high ratio (>2) of exon 10-deleted CRBN transcript to full length CRBN transcript. 92 samples had sufficient purity (>90% tumor cells) for this analysis. 13/92 samples (14.1%) had a high exon10-deleted transcript ratio. Overall, 43/268 (16.0%) patients had genetic or transcript variants in CRBN. In contrast, 27/514 (5.2%) newly diagnosed myeloma (NDMM) patients from the Myeloma Genome Project had genetic or transcript variants in CBRN; 2/514 (0.4%) had CRBN mutations, 11/514 (2.1%) had CRBN gene deletion and 14/514 (2.7%) had a high exon10-deleted transcript ratio. Thus, there was an increase in CRBN variants from NDMM to RRMM. In patients exposed to LEN but not POM (219/268), there were 5 CRBN mutations, 14 monoallelic CRBN deletions and 13/92 patients with high exon10-deleted transcript ratio. In 69/268 patients exposed to POM (baseline from CC-220-MM-001 (N=35), CC-122-ST-001MM2 (N=10), or follow up samples from CC-4047-MM-010 (N=24)), there were 12 CRBN mutations in 8 patients (11.6%) and 7 CRBN deletions (10.1%), approximately double the incidence seen in the whole cohort. 3 CRBN deletions were homozygous, which was not observed in non-POM-exposed individuals. Sample purity was insufficient to measure transcript ratios. In summary, 16.0% of RRMM patients that received LEN or POM have genetic or transcript variants in CRBN, a higher proportion than in NDMM. The impact of these aberrations on CRBN function, especially related to binding of CRBN-modulating drugs, remains to be ascertained. Analysis of the correlation between CRBN variation and response to therapy, clinical outcomes, and the incidence and effect of mutation or copy loss of CRBN interactors (E3 Ligase members and regulators, CRBN substrates) is underway and will be presented. Disclosures Gooding: Celgene: Research Funding. Ansari-Pour:Celgene Corporation: Consultancy. Towfic:Celgene Corporation: Employment, Equity Ownership. Ortiz:Celgene Corporation: Employment, Equity Ownership. Rozelle:Celgene Corporation: Other: Contractor for Celgene. Zadorozhny:Celgene Corporation: Other: Contractor for Celgene. Amatangelo:Celgene Corporation: Employment, Equity Ownership. Flynt:Celgene Corporation: Employment, Equity Ownership. Tsai:Celgene Corporation: Employment, Equity Ownership. Neri:Celgene, Janssen: Consultancy, Honoraria, Research Funding. Bahlis:AbbVie: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Janssen: Consultancy, Honoraria. Vyas:Novartis: Research Funding, Speakers Bureau; Pfizer: Speakers Bureau; Daiichi Sankyo: Speakers Bureau; Astellas: Speakers Bureau; Abbvie: Speakers Bureau; Celgene: Research Funding, Speakers Bureau; Forty Seven, Inc.: Research Funding. Thakurta:Celgene: Employment, Equity Ownership.

Breast cancer is a heterogeneous disease and the incidence to mortality ratio is highest for women of African ancestry. Paucity of data from non-European ancestry groups limits our understanding of the underlying etiological differences or alternative routes to progression that may explain differential outcomes. To examine the contribution of genomic differences, we performed high-depth whole-genome sequencing on 100 breast tumors (90X) and their paired normal samples (30X) from indigenous African women with breast cancer in Southwest Nigeria and performed comparative analysis with 84 TCGA whole genome sequences of breast tumor/normal pairs (46 White, 30 African American and 8 samples representing other ethnicities). High confidence somatic single nucleotide variants (SNVs) were obtained by using MuTect and Strelka. To analyse intra-tumoral heterogeneity (ITH), Battenberg and DPClust were used to call copy number aberrations (CNA) and cluster somatic SNVs based on cancer cell fraction (CCF) respectively. We find that in the HR-/HER2+ subtype, clonal losses of chromosome 14q are highly enriched in Nigerians (41%) but absent in the Whites even though the proportion of this subtype was comparable between the two groups (42% and 33% respectively). This is an interesting observation since not only 14q loss is known to be an event associated with breast cancer aggressiveness, but HR-/HER2+ has also been reported to be enriched within the relatively younger Nigerian patients with breast cancer. This may in part explain inter-ethnic disparity in survival. Also, somatic SNV clustering analysis showed that Nigerian cancers have a higher level of ITH than Whites, which may explain the pronounced aggressiveness of breast cancer in women of African ancestry. In contrast, early drivers (e.g. TP53 and PIK3CA) and whole genome duplication rates were mostly similar between the groups. Our observations suggest differences in the underlying evolutionary trajectories of breast cancer across ethnic backgrounds. These data underscore the need for larger and more in-depth studies of diverse cancer genomes and, if validated, may translate into clinical intervention opportunities tailored to women of African ancestry and accelerate progress in precision cancer care. Note: This abstract was not presented at the meeting. Citation Format: Naser Ansari-Pour, Jason J. Pitt, Stefan Dentro, Dominic Fitzgerald, Yonglan Zheng, Toshio F. Yoshimatsu, Padma Rajagopal, Andreas Gruber, Ayodele Sanni, Olayiwola Oluwasola, Mustapha Ajani, Abayomi Odetunde, Abiodun Popoola, Adeyinka Falusi, Temidayo Ogundiran, John Obafunwa, Oladosu Ojengbede, Nasiru Ibrahim, Kevin P. White, Dezheng Huo, Peter Van Loo, David C. Wedge, Olufunmilayo Olopade. The life history of breast cancer in Nigerian women: Evidence for ethnic differences in tumor evolution based on whole-genome sequencing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr LB-300.

Objective CYP3A4 expression varies up to 100-fold among individuals, and, to date, genetic causes remain elusive. As a major drug-metabolizing enzyme, elucidation of such genetic causes would increase the potential for introducing personalized dose adjustment of therapies involving CYP3A4 drug substrates. The foetal CYP3A isoform, CYP3A7, is reported to be expressed in ∼10% of European adults and may thus contribute towards the metabolism of endogenous substances and CYP3A drug substrates. However, little is known about the distribution of the variant expressed in the adult. Methods We resequenced the exons, flanking introns, regulatory elements and 3'UTR of CYP3A4 in five Ethiopian populations and incorporated data from the 1000 Genomes Project. Using bioinformatic analysis, we assessed likely consequences of observed CYP3A4 genomic variation. We also conducted the first extensive geographic survey of alleles associated with adult expression of CYP3A7 - that is, CYP3A7*1B and CYP3A7*1C. Results and conclusion Ethiopia contained 60 CYP3A4 variants (26 novel) and more variants (>1%) than all non-African populations combined. No nonsynonymous mutation was found in the homozygous form or at more than 2.8% in any population. Seventy-nine per cent of haplotypes contained 3'UTR and/or regulatory region variation with striking pairwise population differentiation, highlighting the potential for interethnic variation in CYP3A4 expression. Conversely, coding region variation showed that significant interethnic variation is unlikely at the protein level. CYP3A7*1C was found at up to 17.5% in North African populations and in significant linkage disequilibrium with CYP3A5*3, indicating that adult expression of the foetal isoform is likely to be accompanied by reduced or null expression of CYP3A5.

Pinpointing causal genes for spermatogenic failure (SpF) on the Y chromosome has been an ever daunting challenge with setbacks during the past decade. Since complex diseases result from the interaction of multiple genes and also display considerable missing heritability, network analysis is more likely to explicate an etiological molecular basis. We therefore took a network medicine approach by integrating interactome (protein-protein interaction (PPI)) and transcriptome data to reconstruct a Y-centric SpF network. Two sets of seed genes (Y genes and SpF-implicated genes (SIGs)) were used for network reconstruction. Since no PPI was observed among Y genes, we identified their common immediate interactors. Interestingly, 81% (N = 175) of these interactors not only interacted directly with SIGs, but also they were enriched for differentially expressed genes (89.6%; N = 43). The SpF network, formed mainly by the dys-regulated interactors and the two seed gene sets, comprised three modules enriched for ribosomal proteins and nuclear receptors for sex hormones. Ribosomal proteins generally showed significant dys-regulation with RPL39L, thought to be expressed at the onset of spermatogenesis, strongly down-regulated. This network is the first global PPI network pertaining to severe SpF and if experimentally validated on independent data sets can lead to more accurate diagnosis and potential fertility recovery of patients.

Nonsyndromic cleft lip with or without palate (CL/P) is thought to be caused by the interplay of genetic and environmental factors, and this has thus hindered the process of identifying genetic causative factors. Numerous studies in the past decade have implicated IRF6 in CL/P, but this has not often been replicated in other populations. In specific, the only etiologic single-nucleotide polymorphism (SNP) identified in the IRF6 locus (rs642961) has recently been shown not to be associated with CL/P in diverse populations. We therefore used a genewide tagging SNP (tagSNP) haplotyping approach (including rs642961 as a tagSNP) to detect all potential risk-conferring haplotypes and combined this with detailed subphenotyping of CL/P cases ( N = 150) according to severity. We observed a significant overrepresentation of a tagSNP haplotype carrying the rs642961 risk allele in the most severe subphenotype of CL/P (complete bilateral CL/P; P = 0.008, odds ratio = 4.97, 95% confidence interval = 1.33 to 18.46). It was recently shown that >80% of IRF6 mutations in syndromic CL/P occur on the same haplotype background. We therefore suggest that IRF6 is a marker of CL/P severity.

Improved sequencing technologies offer unprecedented opportunities for investigating the role of rare genetic variation in common disease. However, there are considerable challenges with respect to study design, data analysis and replication. Using pooled next-generation sequencing of 507 genes implicated in the repair of DNA in 1,150 samples, an analytical strategy focused on protein-truncating variants (PTVs) and a large-scale sequencing case-control replication experiment in 13,642 individuals, here we show that rare PTVs in the p53-inducible protein phosphatase PPM1D are associated with predisposition to breast cancer and ovarian cancer. PPM1D PTV mutations were present in 25 out of 7,781 cases versus 1 out of 5,861 controls (P = 1.12 × 10(-5)), including 18 mutations in 6,912 individuals with breast cancer (P = 2.42 × 10(-4)) and 12 mutations in 1,121 individuals with ovarian cancer (P = 3.10 × 10(-9)). Notably, all of the identified PPM1D PTVs were mosaic in lymphocyte DNA and clustered within a 370-base-pair region in the final exon of the gene, carboxy-terminal to the phosphatase catalytic domain. Functional studies demonstrate that the mutations result in enhanced suppression of p53 in response to ionizing radiation exposure, suggesting that the mutant alleles encode hyperactive PPM1D isoforms. Thus, although the mutations cause premature protein truncation, they do not result in the simple loss-of-function effect typically associated with this class of variant, but instead probably have a gain-of-function effect. Our results have implications for the detection and management of breast and ovarian cancer risk. More generally, these data provide new insights into the role of rare and of mosaic genetic variants in common conditions, and the use of sequencing in their identification.