Liu, Jianjun

Background: Thyroid eye disease (TED) is a debilitating autoimmune disorder linked to thyroid dysfunction. There is limited knowledge of TED in Asian populations. This multicenter study characterizes the clinical features and treatment response of TED in a large Chinese cohort. Methods: A retrospective multicenter study included 4157 patients with TED from nine Chinese hospitals from February 2016 to July 2023. Disease severity and activity were evaluated according to the European Group on Graves’ Orbitopathy standards. We examined associations of variables including sex, age, smoking status, I 131 treatment, consultation department, and geographical region with clinical outcomes. Logistic regression and nomogram models were developed to examine associations with sight-threatening TED and, in a subgroup analysis ( n = 126), patients’ responsiveness to intravenous glucocorticoid (IVGC) therapy. Results: We included 4157 patients with mean age and standard deviation (SD) 45.96 ± 16.44 years. Of these, 63.6% ( n = 2644) were females. Over half (55.6%, n = 2310) of participants were in the inactive phase, with a mean clinical activity score of 2.19 ± 1.61 (SD) for all patients. TED severity was categorized as mild (9.3%, n = 385), moderate-to-severe (82.5%, n = 3428), and sight-threatening (8.2%, n = 344). The average degree of exophthalmos was 20.04 ± 5.27 mm, and 48.8% ( n = 2029) of patients had diplopia. Patients treated with I 131 had higher disease activity (47.5%, n = 468, vs. 43.5%, n = 1379, p < 0.05). Coastal region patients exhibited more severe TED (sight-threatening cases: 10.1%, n = 195, vs. 7.2%, n = 147) and higher diplopia scores (1.00 ± 1.10 vs. 0.86 ± 1.09, p < 0.001) than inland counterparts. TED severity was also greater in patients treated in Ophthalmology departments (mild cases: 6.0%, n = 213; moderate-to-severe cases: 85.6%, n = 3055) compared with Endocrinology departments (mild cases: 29.3%, n = 172; moderate-to-severe cases: 63.5%, n = 373). Nomograms had an area under the receiver operating curve of 0.742 (confidence interval [CI] 0.716–0.768) for sight-threatening TED and 0.759 (CI 0.674–0.843) for IVGC therapy responsiveness. Conclusions: We characterized the clinical features and treatment response of TED in a large Chinese cohort. These findings offer valuable insights informing TED risk stratification in Asian patients and forming a foundation for future prospective studies.

Abstract Background Lung adenocarcinoma in never-smokers is a major public health burden, especially among East Asian women. Polygenic risk scores (PRSs) are promising for risk stratification but are primarily developed in European-ancestry populations. We aimed to develop and validate single- and multi-ancestry PRSs for East Asian never-smokers to improve lung adenocarcinoma risk prediction. Methods PRSs were developed using genome-wide association study summary statistics from East Asian (8002 cases; 20 782 controls) and European (2058 cases; 5575 controls) populations. Single-ancestry models included a PRS with 25 single nucleotide variants (PRS-25), PRS clumping and thresholding (CT), and LDpred2; multi-ancestry models included LDpred2 plus European PRS-128, PRS-CSx, and clumping and thresholding, super learning, empirical Bayes (CT-SLEB). Performance was evaluated in independent East Asian data from the Female Lung Cancer Consortium and externally validated in the Nanjing Lung Cancer Cohort. We assessed predictive accuracy via area under the curve operating procedure (AUC), with 10-year and (ages 30-80 years) absolute risks estimates. Results The best multi-ancestry PRS, using East Asian and European data via CT-SLEB, outperformed the best East Asian-only (LDpred2; AUC = 0.629, 95% confidence interval [CI] = 0.618 to 0.641), achieving an AUC of 0.640 (95% CI = 0.629 to 0.653) and odds ratio of 1.71 (95% CI = 1.61 to 1.82) per standard deviation increase. Nanjing Lung Cancer Cohort validation confirmed robust performance (AUC = 0.649, 95% CI = 0.623 to 0.676). The top 20% PRS group had a 3.92-fold higher lung adenocarcinoma risk than the bottom 20%. Further, the top 5% PRS group reached a 6.69% lifetime absolute risk. Notably, this group reached the average population 10-year lung adenocarcinoma risk at age 50 years (0.42%) by age 41 years, 9 years earlier. Conclusions Multi-ancestry PRS approaches enhance lung adenocarcinoma risk stratification in East Asian never-smokers, with consistent external validation, suggesting future clinical utility.

Summary Among individuals of European Ancestry (EA), genome‐wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) and polygenic risk scores (PRSs) associated with non‐Hodgkin lymphoma (NHL) risk. We evaluated subtype‐specific PRSs, based on established EA‐SNPs, in Israeli Jews (IJ) and Palestinian Arabs (PA) and performed a GWAS in the combined ethnic groups to identify new loci. We included three common pathologically confirmed subtypes: diffuse large B‐cell (DLBCL), follicular (FL) and marginal zone (MZL) lymphomas. Controls were frequency matched to cases by age and sex. Among 752 IJ (201—DLBCL; 130—FL; 54—MZL/367—controls) and 593 PA (203—DLBCL; 41—FL/349‐controls), we computed PRSs weighted by EA‐derived effect estimates and used logistic regression models adjusted for confounders. In the combined ethnic groups of IJ and PA, subtype‐specific PRSs were significantly associated with the corresponding subtype, with a 1.69‐fold, 2.21‐fold and 2.26‐fold risk for DLBCL, FL and MZL, respectively; however, these effect sizes were attenuated compared to those reported in EA and varied by ethnicity. In the GWAS of the combined ethnic groups, two novel SNPs in the 6p21.32 locus were associated with DLBCL risk. Additional GWAS studies are needed among Jewish and Arab populations to improve genetic risk prediction for NHL in these ethnic groups.

Across multiancestry groups, we analyzed Human Leukocyte Antigen (HLA) associations in over 176,000 individuals with Parkinson’s disease (PD) and Alzheimer’s disease (AD) versus controls. We demonstrate that the two diseases share the same protective association at the HLA locus. HLA-specific fine-mapping showed that hierarchical protective effects of HLA-DRB1 *04 subtypes best accounted for the association, strongest with HLA-DRB1 *04:04 and HLA-DRB1 *04:07, and intermediary with HLA-DRB1 *04:01 and HLA-DRB1 *04:03. The same signal was associated with decreased neurofibrillary tangles in postmortem brains and was associated with reduced tau levels in cerebrospinal fluid and to a lower extent with increased Aβ42. Protective HLA-DRB1 *04 subtypes strongly bound the aggregation-prone tau PHF6 sequence, however only when acetylated at a lysine (K311), a common posttranslational modification central to tau aggregation. An HLA-DRB1 *04-mediated adaptive immune response decreases PD and AD risks, potentially by acting against tau, offering the possibility of therapeutic avenues.

Abstract Background Mendelian randomization (MR) studies are susceptible to metadata errors (e.g. incorrect specification of the effect allele column) and other analytical issues that can introduce substantial bias into analyses. We developed a quality control (QC) pipeline for the Fatty Acids in Cancer Mendelian Randomization Collaboration (FAMRC) that can be used to identify and correct for such errors. Methods We collated summary association statistics from fatty acid and cancer genome-wide association studies (GWAS) and subjected the collated data to a comprehensive QC pipeline. We identified metadata errors through comparison of study-specific statistics to external reference data sets (the National Human Genome Research Institute-European Bioinformatics Institute GWAS catalogue and 1000 genome super populations) and other analytical issues through comparison of reported to expected genetic effect sizes. Comparisons were based on three sets of genetic variants: (i) GWAS hits for fatty acids, (ii) GWAS hits for cancer and (iii) a 1000 genomes reference set. Results We collated summary data from 6 fatty acid and 54 cancer GWAS. Metadata errors and analytical issues with the potential to introduce substantial bias were identified in seven studies (11.6%). After resolving metadata errors and analytical issues, we created a data set of 219 842 genetic associations with 90 cancer types, generated in analyses of 566 665 cancer cases and 1 622 374 controls. Conclusions In this large MR collaboration, 11.6% of included studies were affected by a substantial metadata error or analytical issue. By increasing the integrity of collated summary data prior to their analysis, our protocol can be used to increase the reliability of downstream MR analyses. Our pipeline is available to other researchers via the CheckSumStats package (https://github.com/MRCIEU/CheckSumStats).

PURPOSE Antitumor activity in preclinical models and a phase I study of patients with dedifferentiated liposarcoma (DD-LPS) was observed with selinexor. We evaluated the clinical benefit of selinexor in patients with previously treated DD-LPS whose sarcoma progressed on approved agents. METHODS SEAL was a phase II-III, multicenter, randomized, double-blind, placebo-controlled study. Patients age 12 years or older with advanced DD-LPS who had received two-five lines of therapy were randomly assigned (2:1) to selinexor (60 mg) or placebo twice weekly in 6-week cycles (crossover permitted). The primary end point was progression-free survival (PFS). Patients who received at least one dose of study treatment were included for safety analysis (ClinicalTrials.gov identifier: NCT02606461 ). RESULTS Two hundred eighty-five patients were enrolled (selinexor, n = 188; placebo, n = 97). PFS was significantly longer with selinexor versus placebo: hazard ratio (HR) 0.70 (95% CI, 0.52 to 0.95; one-sided P = .011; medians 2.8 v 2.1 months), as was time to next treatment: HR 0.50 (95% CI, 0.37 to 0.66; one-sided P < .0001; medians 5.8 v 3.2 months). With crossover, no difference was observed in overall survival. The most common treatment-emergent adverse events of any grade versus grade 3 or 4 with selinexor were nausea (151 [80.7%] v 11 [5.9]), decreased appetite (113 [60.4%] v 14 [7.5%]), and fatigue (96 [51.3%] v 12 [6.4%]). Four (2.1%) and three (3.1%) patients died in the selinexor and placebo arms, respectively. Exploratory RNA sequencing analysis identified that the absence of CALB1 expression was associated with longer PFS with selinexor compared with placebo (median 6.9 v 2.2 months; HR, 0.19; P = .001). CONCLUSION Patients with advanced, refractory DD-LPS showed improved PFS and time to next treatment with selinexor compared with placebo. Supportive care and dose reductions mitigated side effects of selinexor. Prospective validation of CALB1 expression as a predictive biomarker for selinexor in DD-LPS is warranted.

Introduction: Selinexor is a novel, oral selective inhibitor of nuclear export (SINE) which forces nuclear retention and activation of tumor suppressor proteins. Selinexor plus low dose dexamethasone (Sel-dex) was recently approved in the United States based on data from the STORM study wherein, Sel-dex induced an overall response rate (ORR) of 26.2% in patients with penta-exposed, triple-class refractory multiple myeloma. The presence of high-risk cytogenetic abnormalities is known to have a poor prognosis in multiple myeloma, with transient responses. We performed post-hoc analyses to determine the outcomes in patients with relapsed/refractory myeloma treated with Sel-dex based on the baseline cytogenetic abnormalities. Methods: STORM was a phase 2b, open-label study which enrolled patients with relapsed and refractory myeloma. Selinexor 80 mg in combination with dexamethasone 20 mg was administered orally, twice weekly. The primary endpoint was ORR. For this analysis, we pooled 78 patients (48 quad-refractory and 30 penta-refractory) from STORM, part 1 and 122 patients (penta-exposed and triple class refractory) from STORM, part 2 to compare outcomes between high-risk and standard risk cytogenetics groups. High-risk cytogenetics was defined as having at least 1 of the following abnormalities by fluorescence in-situ hybridization (FISH) at baseline: del(17p), t(4;14), t(14;16), and gain(1q) in >5% of screened plasma cells. The FISH analyses were performed at a central laboratory and used to assess cytogenetic risk status. Results: Of the 200 patients, 122 (61%) had high-risk disease (del(17p): 36%, t(4;14): 18%, t(14;16): 5%, and gain(1q): 36%). The ORR in high-risk patients was 20.5% (very good partial response [VGPR)]: 5.7% and partial response [PR]: 14.8%) and the ORR was 29.5 % (complete response [CR]: 2.6%, VGPR: 3.8%, and PR: 23.1%) in standard-risk patients. The clinical benefit rate (CBR) was 35.2% in high-risk patients compared with 38.5% in standard-risk patients. Median duration of clinical benefit (DOCB) was 4.4 and 6.2 months in the high-risk and standard-risk patients respectively. Median progression-free survival (PFS) was 3.8 and 4.2 months and overall survival (OS) was 8.6 and 9.4 months in the high-risk and standard-risk patients, respectively. Efficacy by specific cytogenetic abnormality is presented in Table 1 below (Due to the small sample size (n=11), data for the t(14;16) subgroup are not presented separately). Conclusions: Sel-dex demonstrated a similar CBR in patients with high risk and standard risk disease and preserved clinical benefit in heavily pre-treated patients who had rapidly proliferative disease and high-risk cytogenetics at baseline. The benefit was maintained across cytogenetic risk subgroups with a higher ORR in the t(4;14) and gain(1q) subgroups. The DOR and OS was similar across all the subgroups. These analyses support the use of Sel-dex in patients with high-risk cytogenetics and warrant further evaluation of selinexor in combination with other anti-myeloma therapies in high-risk disease. Disclosures Nooka: GSK: Honoraria, Other: advisory board participation; Amgen: Honoraria, Other: advisory board participation; BMS: Honoraria, Other: advisory board participation; Janssen: Honoraria, Other: advisory board participation; Spectrum pharmaceuticals: Honoraria, Other: advisory board participation; Adaptive technologies: Honoraria, Other: advisory board participation; Celgene: Honoraria, Other: advisory board participation; Takeda: Honoraria, Other: advisory board participation. Yee:Adaptive: Consultancy; Karyopharm: Consultancy; Takeda: Consultancy; Bristol-Myers Squibb: Consultancy, Research Funding; Amgen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding. Huff:Karyopharm, Sanofi, MiDiagnostics: Consultancy; Member of Safety Monitoring Board for Johnson and Johnson: Membership on an entity's Board of Directors or advisory committees. Vogl:Karyopharm Therapeutics: Consultancy; Takeda: Consultancy; Celgene: Consultancy; Amgen: Consultancy; Janssen: Consultancy; Active Biotech: Consultancy. Chari:Novartis Pharmaceuticals: Research Funding; GlaxoSmithKline: Research Funding; Array Biopharma: Research Funding; Karyopharm: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Millennium/Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol-Myers Squibb: Consultancy; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Membership on an entity's Board of Directors or advisory committees; Seattle Genetics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Pharmacyclics: Research Funding; Oncoceutics: Research Funding. Moreau:Celgene: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria. Dingli:Karyopharm: Research Funding; Rigel: Consultancy; Millenium: Consultancy; alexion: Consultancy; Janssen: Consultancy. Lonial:Genentech: Consultancy; Karyopharm: Consultancy; Takeda: Consultancy, Research Funding; Amgen: Consultancy; BMS: Consultancy; Janssen: Consultancy, Research Funding; GSK: Consultancy; Celgene Corporation: Consultancy, Research Funding. Dimopoulos:Sanofi Oncology: Research Funding. Vij:Takeda: Honoraria, Research Funding; Sanofi: Honoraria; Karyopharm: Honoraria; Janssen: Honoraria; Genentech: Honoraria; Celgene: Honoraria, Research Funding; Bristol-Myers Squibb: Honoraria, Research Funding. Tuchman:Karyopharm: Honoraria; Celgene: Honoraria, Research Funding, Speakers Bureau; Amgen: Research Funding; Merck: Research Funding; Prothena: Research Funding; Roche: Research Funding; Sanofi: Research Funding; Alnylam: Honoraria, Research Funding. Biran:Bristol Meyers Squibb: Research Funding; Amgen: Consultancy, Honoraria, Research Funding; Merck: Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria; Takeda: Consultancy, Honoraria. Siegel:Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Bristol-Myers Squibb Company: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau. Richardson:Karyopharm: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Sanofi: Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Research Funding; Oncopeptides: Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding. Liu:Karyopharm Therapeutics: Employment, Equity Ownership. Joshi:Karyopharm Therapeutics: Employment, Equity Ownership. Shah:Karyopharm Therapeutics: Employment, Equity Ownership. Shacham:Karyopharm Therapeutics Inc: Employment, Equity Ownership, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties. Kauffman:Karyopharm Therapeutics Inc: Employment, Equity Ownership, Membership on an entity's Board of Directors or advisory committees. Jagannath:Medicom: Speakers Bureau; Multiple Myeloma Research Foundation: Speakers Bureau; BMS: Consultancy; Celgene: Consultancy; Novartis: Consultancy; Merck: Consultancy.

Abstract Familial studies were among the first to indicate that breast cancer prognosis has a heritable component. Subsequently many variants associated with prognosis have been identified using a range of techniques including genome-wide association studies (GWAs). Despite these advances, much of the heritability remains unexplained. In young women, breast cancer is characterised by a higher incidence of adverse pathological features, unique tumour gene expression profiles and worse survival. In addition, the association of risk with conventional epidemiological exposures is less clear in women with early onset. We hypothesise that some of these difference between early and late onset could be influenced by germline variation. To identify additional variants that influence breast cancer prognosis we conducted a two stage meta-analysis of four GWAs consisting of 6,042 patients from the UK (POSH), Finland (HEBCS), Germany (SUCCESS-A) and Australia (ABCFS). Cox-regression analyses were used to investigate overall survival (OS, n=1,101 events) and disease-free survival (DFS, n=1,316 events) with correction for oestrogen status (ER). These survival analyses were repeated in a subset of patients with early onset (aged ≤40 at diagnosis, n=2,315 patients, OS n=604 events, DFS n=716 events). Meta-analysis identified two intronic SNPs in ADAMTSL1 that were associated exclusively with early onset DFS, rs715212 (Pmeta=3.54x10-5) and rs10963755 (Pmeta=3.91x10-4) without heterogeneity between cohorts. Multivariable Cox-regression demonstrated that the effect of these SNPs were independent of the classical prognostic factors. Most importantly, rs715212 reached genome-wide significance (Pmultivariate=5.37x10-8) in the multivariate model. ADAMTSL1 encodes a glycoprotein that forms part of the extracellular matrix (ECM) and may function in cell-cell or cell-matrix interactions or may regulate other ADAMTS proteases. Previous studies have shown that ADAMTSL1 is hypermethylated in ER positive breast cancer tumours. Using GTEx to perform eQTL analysis, we found that rs715212 is associated with the expression of several biologically relevant genes AREG (P=0.035), TNF (P=0.015), FASLG (P=0.0031) and EGF (P=0.0018) in breast mammary tissue. Interestingly, separate studies have shown that AREG is overexpressed in ER-positive breast tumours from pre-menopausal women versus post-menopausal women. Furthermore, AREG is differentially expressed between parous and non-parous mammary glands and is persistently downregulated by parity, which suggests it may contribute to the susceptibility of the nulliparous gland to breast cancer. We conclude that rs715212 is associated with an increased risk of disease progression in patients with early onset and speculate that this could be due to an interaction with the expression of AREG. Note: This abstract was not presented at the meeting. Citation Format: Latha Kadalayil, Sofia Khan, Heli Nevanlinna, Peter A. Fasching, Fergus J. Couch, John Hopper, Jianjun Liu, Tom Maishman, Lorraine Durcan, Carl Bloomqvist, Andy Collins, Dianna Eccles, William Tapper. A meta-analysis of genome-wide association studies identifies novel loci that influence breast cancer prognosis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1322. doi:10.1158/1538-7445.AM2017-1322