Inflammatory Bowel Disease Risk Variants Are Associated with an Increased Risk of Skin Cancer

Background Inflammatory bowel disease is associated with an increased risk of skin cancer. The aims of this study were to determine whether IBD susceptibility variants are also associated with skin cancer susceptibility and if such risk is augmented by use of immune-suppressive therapy. Methods The discovery cohort included participants in the UK Biobank. The validation cohort included participants in the Michigan Genomics Initiative. The primary outcome of interest was skin cancer, subgrouped into nonmelanoma skin cancers (NMSC) and melanoma skin cancers (MSC). Multivariable logistic regression with matched controls (3 controls:1 case) was performed to identify genomic predictors of skin malignancy in the discovery cohort. Variants with P < .05 were tested for replication in the validation cohort. Validated Single nucleotide polymorphisms were then evaluated for effect modification by immune-suppressive medications. Results The discovery cohort included 10,247 cases of NMSC and 1883 cases of MSC. The validation cohort included 7334 cases of NMSC and 3304 cases of MSC. Twenty-nine variants were associated with risk of NMSC in the discovery cohort, of which 5 replicated in the validation cohort (increased risk, rs7773324-A [DUSP22; IRF4], rs2476601-G [PTPN22], rs1847472-C [BACH2], rs72810983-A [CPEB4]; decreased risk, rs6088765-G [PROCR; MMP24]). Twelve variants were associated with risk of MSC in the discovery cohort, of which 4 were replicated in the validation cohort (increased risk, rs61839660-T [IL2RA]; decreased risk, rs17391694-C [GIPC2; MGC27382], rs6088765-G [PROCR; MMP24], and rs1728785-C [ZFP90]). No effect modification was observed. Conclusions The results of this study highlight shared genetic susceptibility across IBD and skin cancer, with increased risk of NMSC in those who carry risk variants in IRF4, PTPN22, CPEB4, and BACH2 and increased risk of MSC in those who carry a risk variant in IL2RA.

Proteomic Signatures of Diffuse and Intestinal Subtypes of Gastric Cancer

Gastric cancer is a leading cause of death from cancer globally. Gastric cancer is classified into intestinal, diffuse and indeterminate subtypes based on histology according to the Laurén classification. The intestinal and diffuse subtypes, although different in histology, demographics and outcomes, are still treated in the same fashion. This study was designed to discover proteomic signatures of diffuse and intestinal subtypes. Mass spectrometry-based proteomics using tandem mass tags (TMT)-based multiplexed analysis was used to identify proteins in tumor tissues from patients with diffuse or intestinal gastric cancer with adjacent normal tissue control. A total of 7448 or 4846 proteins were identified from intestinal or diffuse subtype, respectively. This quantitative mass spectrometric analysis defined a proteomic signature of differential expression across the two subtypes, which included gremlin1 (GREM1), bcl-2-associated athanogene 2 (BAG2), olfactomedin 4 (OLFM4), thyroid hormone receptor interacting protein 6 (TRIP6) and melanoma-associated antigen 9 (MAGE-A9) proteins. Although GREM1, BAG2, OLFM4, TRIP6 and MAGE-A9 have all been previously implicated in tumor progression and metastasis, they have not been linked to intestinal or diffuse subtypes of gastric cancer. Using immunohistochemical labelling of a tissue microarray comprising of 124 cases of gastric cancer, we validated the proteomic signature obtained by mass spectrometry in the discovery cohort. Our findings should help investigate the pathogenesis of these gastric cancer subtypes and potentially lead to strategies for early diagnosis and treatment.

Association between Genetic Variants and Cisplatin-Induced Nephrotoxicity: A Genome-Wide Approach and Validation Study

This study aims to evaluate genetic risk factors for cisplatin-induced nephrotoxicity by investigating not previously studied genetic risk variants and further examining previously reported genetic associations. A genome-wide study (GWAS) was conducted in genetically estimated Europeans in a discovery cohort of cisplatin-treated adults from Toronto, Canada, followed by a candidate gene approach in a validation cohort from the Netherlands. In addition, previously reported genetic associations were further examined in both the discovery and validation cohorts. The outcome, nephrotoxicity, was assessed in two ways: (i) decreased estimated glomerular filtration rate (eGFR), calculated using the Chronic Kidney Disease Epidemiology Collaboration formula (CKD-EPI) and (ii) increased serum creatinine according to the Common Terminology Criteria for Adverse Events v4.03 for acute kidney injury (AKI-CTCAE). Four different Illumina arrays were used for genotyping. Standard quality control was applied for pre- and post-genotype imputation data. In the discovery cohort (n = 608), five single-nucleotide polymorphisms (SNPs) reached genome-wide significance. The A allele in rs4388268 (minor allele frequency = 0.23), an intronic variant of the BACH2 gene, was consistently associated with increased risk of cisplatin-induced nephrotoxicity in both definitions, meeting genome-wide significance (β = −8.4, 95% CI −11.4–−5.4, p = 3.9 × 10−8) for decreased eGFR and reaching suggestive association (OR = 3.9, 95% CI 2.3–6.7, p = 7.4 × 10−7) by AKI-CTCAE. In the validation cohort of 149 patients, this variant was identified with the same direction of effect (eGFR: β = −1.5, 95% CI −5.3–2.4, AKI-CTCAE: OR = 1.7, 95% CI 0.8–3.5). Findings of our previously published candidate gene study could not be confirmed after correction for multiple testing. Genetic predisposition of BACH2 (rs4388268) might be important in the development of cisplatin-induced nephrotoxicity, indicating opportunities for mechanistic understanding, tailored therapy and preventive strategies.

Multiscale heterogeneity in gastric adenocarcinoma evolution is an obstacle to precision medicine

Background Cancer is a somatic evolutionary disease and adenocarcinomas of the stomach and gastroesophageal junction (GC) may serve as a two-dimensional model of cancer expansion, in which tumor subclones are not evenly mixed during tumor progression but rather spatially separated and diversified. We hypothesize that precision medicine efforts are compromised when clinical decisions are based on a single-sample analysis, which ignores the mechanisms of cancer evolution and resulting intratumoral heterogeneity. Using multiregional whole-exome sequencing, we investigated the effect of somatic evolution on intratumoral heterogeneity aiming to shed light on the evolutionary biology of GC. Methods The study comprised a prospective discovery cohort of 9 and a validation cohort of 463 GCs. Multiregional whole-exome sequencing was performed using samples form 45 primary tumors and 3 lymph node metastases (range 3–10 tumor samples/patient) of the discovery cohort. Results In total, the discovery cohort harbored 16,537 non-synonymous mutations. Intratumoral heterogeneity of somatic mutations and copy number variants were present in all tumors of the discovery cohort. Of the non-synonymous mutations, 53–91% were not present in each patient’s sample; 399 genes harbored 2–4 different non-synonymous mutations in the same patient; 175 genes showed copy number variations, the majority being heterogeneous, including CD274 (PD-L1). Multi-sample tree-based analyses provided evidence for branched evolution being most complex in a microsatellite instable GC. The analysis of the mode of evolution showed a high degree of heterogeneity in deviation from neutrality within each tumor. We found evidence of parallel evolution and evolutionary trajectories: different mutations of SMAD4 aligned with different subclones and were found only in TP53 mutant GCs. Conclusions Neutral and non-neutral somatic evolution shape the mutational landscape in GC along its lateral expansions. It leads to complex spatial intratumoral heterogeneity, where lymph node metastases may stem from different areas of the primary tumor, synchronously. Our findings may have profound effects on future patient management. They illustrate the risk of mis-interpreting tumor genetics based on single-sample analysis and open new avenues for an evolutionary classification of GC, i.e., the discovery of distinct evolutionary trajectories which can be utilized for precision medicine.

Immune Profiling of Diagnostic DLBCL Biopsies Dramatically Improves upon Cell-of-Origin Risk Stratification

Background: Diffuse large B cell lymphoma (DLBCL) is an aggressive malignancy of mature B cells. The disease has traditionally been subdivided into cell-of-origin (COO) subtypes - germinal centre B cell-like (GCB) or activated B cell-like (ABC) - as determined by expression profiling or immunohistochemistry of the tumor cells. However the role of the immune microenvironment, and how the tumor and immune system interact to influence patient outcomes, remains to be fully investigated. Methods: In this project, we used mass cytometry (CyTOF) to deeply profile both tumor cell phenotypes and the immune microenvironments, alongside ABC/GCB classification and mutation profiling, in a discovery cohort of 54 DLBCL cases. As well, a validation cohort of 129 DLBCL patients were immunologically profiled by high-dimensional conventional flow cytometry, and their immune profiles alongside ABC/GCB classification, mutation profiling, and RNAseq data, were correlated with patient outcomes as measured by progression-free survival (PFS). Results: Analysis of the CyTOF/discovery cohort demonstrated that DLBCL tumor cells are phenotypically unique to each patient, with a small number of samples displaying distinct sub-clonal structure, often distinguished by differential expression of immune-related proteins like MHC-II. ABC/GCB classifications could be recapitulated based on tumor cell phenotypes, demonstrating that while COO was a robust feature, a great deal of heterogeneity exists within these established subtypes. Immunological profiling of the CyTOF/discovery cohort revealed that DLBCL samples could be divided into three distinct groups which roughly correlated with abundances of naïve, activated, or terminally differentiated T cells, respectively. This profiling schema was extended to the validation cohort of 129 patients which in turn led to identification of a subset of patients with a very high risk of disease progression (5-year PFS; 30% high risk vs. 80% low risk, p<0.0001). This final classifier was based on a combination of ABC-DLBCL designation, combined with the presence of an immune microenvironment dominated by terminally differentiated (CD57+) T cells. We performed a limited series of functional studies using primary DLBCL biopsy samples to characterize further these CD57+ T cells as clonally restricted and incapable of responding to antigenic challenge. Interestingly, traditional immune markers of T cell exhaustion such as PD-1, TIM3, LAG3 and TIGIT were not correlated with patient outcomes. Conclusions: Overall, this study demonstrates the utility of immune profiling in risk stratification based on initial diagnostic biopsy material and highlights a subset of DLBCL patients who may benefit from immune-based therapies to rejuvenate the anti-tumor T cell response. We conclude that T cell senescence, rather than exhaustion, is the more relevant feature in DLBCL disease biology and highlights an alternate target for immunomodulatory therapy. Figure 1 Figure 1. Disclosures Craig: Bayer: Consultancy. Slack: Seagen: Consultancy, Honoraria. Scott: Abbvie: Consultancy; AstraZeneca: Consultancy; Celgene: Consultancy; NanoString Technologies: Patents & Royalties: Patent describing measuring the proliferation signature in MCL using gene expression profiling.; BC Cancer: Patents & Royalties: Patent describing assigning DLBCL COO by gene expression profiling--licensed to NanoString Technologies. Patent describing measuring the proliferation signature in MCL using gene expression profiling. ; Rich/Genentech: Research Funding; Janssen: Consultancy, Research Funding; Incyte: Consultancy. Steidl: Epizyme: Research Funding; Bayer: Consultancy; Curis Inc.: Consultancy; Seattle Genetics: Consultancy; AbbVie: Consultancy; Trillium Therapeutics: Research Funding; Bristol-Myers Squibb: Research Funding.

Pklr Is a Genetic Modifier of Sickle Cell Disease

Background: Acute pain, the most prominent complication of sickle cell disease (SCD), results from vasoocclusion triggered by sickling of deoxygenated red blood cells (RBCs). A key factor influencing HbS oxygenation is the intracellular concentration of 2,3- diphosphoglycerate (2,3-DPG). 2,3-DPG, an intermediate substrate in the glycolytic pathway, decreases oxygen binding and stabilizes the deoxygenated hemoglobin. Pyruvate kinase (gene PKLR, protein PKR) is a rate-limiting enzyme in glycolysis; variants in PKLR may affect PKR activity, 2,3-DPG levels in RBCs, subsequent frequency of sickling and acute pain episodes (APE). There is thus a strong biological basis for exploring PKLR as a candidate gene affecting acute pain in SCD. Methods: The study population for genetic association consists of 2 cohorts: 1) 242 adults with HbSS from King's College Hospital (KCH), London, UK, with complete hospitalisation records over 10 years (2004-2013 inclusive) as the "discovery" cohort; 2) 977 children with HbSS or HbSb 0 thalassemia from the Silent Infarct Transfusion (SIT) trial, with a 3-year history of severe vasoocclusive pain based on hospitalization, as the "validation" cohort. Both studies were approved by the local Institutional Review Boards at KCH and Vanderbilt University Medical Center, respectively. An independent cohort comprises 52 adults with SCD enrolled under 3 protocols - NCT00011648, NCT00081523, and NCT03685721 - approved by the NHLBI Review Board (NIH), for evaluation of imbalance in allele expression. Genome scan for the KCH cohort was performed using llumina's Infinium "MEGA" chip (1.7m markers). The SIT DNA samples were genotyped using Illumina HumanHap650Y array 5 (661K markers) or Illumina Infinium HumanOmni1-Quad array (1.1m markers). The results were quality controlled followed by genotype imputation based on the 1000 Genomes Project phase 3 data. An annualised "hospitalisation rate" as a measure of pain incidence rate, was calculated by dividing the number of hospital admissions for severe acute pain by the number of years of observation for KCH and SIT cohorts (Fig A). We performed association analysis with common SNPs at PKLR locus using data from our genome-wide SNP set and a linear mixed modelling approach incorporating a genetic relatedness matrix to take account of relatedness, plus sex and age as fixed covariates. We corrected for multiple testing after quantifying the linkage disequilibrium (LD) within PKLR and used this to calculate appropriate significance levels. For the PKLR region and hospitalisation rate, the modified significance level was p<0.001268 for the discovery (KCH) cohort. For the allele expression assays, a synonymous variant, rs1052176 (R596R), in exon 11 of PKLR acted as a marker of relative expression levels of the 2 alleles of the gene. Allele specific expression was carried using the Bio-Rad digital droplet PCR system. Results: 7 of 47 variants evaluated in PKLR were associated with hospitalization rate (LnLnHospRate) in the discovery cohort: intron 4 - rs071053, and intron 2 - rs8177970, rs116244351, rs114455416, rs12741350, rs3020781, and rs8177964). All 7 were validated in Fisher's meta-analyses of the KCH and the SIT cohorts using p<0.0071 as threshold to correct for multiple testing (Fig B). We examined the pairwise LD between PKLR variants, and found all the intron 2 variants in tight LD, while R596R belongs to another LD block (Fig C). 52 SCD individuals had the R596R variant, of which 29 were heterozygous and 23 homozygous for the intron 2 haplotype associated with APE in SCD. We performed a Wilcoxon rank sum test and compared the variation in PKLR expression between the 2 alleles in subjects homozygous and heterozygous for the wildtype intron 2 haplotype, using genomic DNA as internal control for each subject. The results reveal a significant deviation from the expected expression ratio in those heterozygous for the intron 2 haplotype (mean 0.2073, +/- SD 0.0135) when compared with to those without the variant (mean 0.1239, +/- SD 0.0682), p=0.0297 (Fig D). Conclusion: Intronic variants of PKLR are associated with hospitalization rate for acute pain episodes in adults and children with SCD. We show that the intronic variants are likely to influence acute pain by affecting expression of the PKLR gene using allele-specific expression analyses, although the causal variant is unclear. These results support PKLR as a genetic modifier of SCD. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

NIMG-63. MACHINE LEARNING USING MRI RADIOMIC ANALYSIS TO PREDICT KI-67 IN WHO GRADE I MENINGIOMAS

PURPOSE Although WHO grade I meningiomas are considered ‘benign’ tumors, an elevated Ki-67 is one crucial factor that has been shown to influence clinical outcomes. In this study, we use standard pre-operative MRI and develop a machine learning (ML) model to predict the Ki-67 in WHO grade I meningiomas. METHODS A retrospective analysis was performed of 306 patients that underwent surgical resection. The mean and median Ki-67 of tumor specimens were 4.84 ± 4.03% (range: 0.3–33.6) and 3.7% (Q1:2.3%, Q3:6%), respectively. Pre-operative MRI was used to perform radiomic feature extraction (N=2,520) followed by ML modeling using least absolute shrinkage and selection operator (LASSO) wrapped with support vector machine (SVM) through nested cross-validation on a discovery cohort (N=230), to stratify tumors based on Ki-67 < 5% and ≥ 5%. A replication cohort (N=76) was kept ‘unseen’ in order to provide insights regarding the generalizability of our predictive model. RESULTS A total of 60 radiomic features extracted from seven different MRI sequences were used in the final model. With this model, an AUC of 0.84 (95% CI: 0.78-0.90), with associated sensitivity and specificity of 84.1% and 73.3%, respectively, were achieved in the discovery cohort. The selected features in the trained predictive model were then applied to the subjects of the replication cohort and the model was applied independently in this cohort. An AUC of 0.83 (95% CI: 0.73-0.94), with a sensitivity of 82.6% and specificity of 85.5% was obtained for this independent testing. Furthermore, the model performed commendably when applied to all skull base and non-skull base tumors in our patient cohort, evidenced by comparable AUC values of 0.86 and 0.83, respectively. CONCLUSION The results of this study may provide enhanced diagnostics to the surgeon pre-operatively such that it can guide surgical strategy and individual patient treatment paradigms.

FAN score comprising fibrosis-4 index, albumin–bilirubin score and neutrophil–lymphocyte ratio is a prognostic marker of urothelial carcinoma patients treated with pembrolizumab

It is important to identify prognostic and predictive markers of metastatic urothelial carcinoma (mUC) treated with immunocheckpoint inhibitors. We sought to establish a prognostic marker for patients with mUC treated with pembrolizumab based on only blood test results. We included 165 patients with mUC in the discovery cohort and 103 with mUC who were treated with pembrolizumab in the validation cohort. Multivariate and Cox regression analyses were used to analyse the data. In the discovery cohort, the fibrosis-4 index (hazard ratio [HR]: 2.13, 95% confidence interval [CI] 1.20–3.76, p = 0.010), albumin–bilirubin score (HR 1.91, 95% CI 1.27–2.88, p = 0.002), and neutrophil–lymphocyte ratio (HR: 1.84, 95% CI 1.22–2.79, p = 0.004) were independent significant prognostic factors. We established a ‘FAN score’ that included these three aforementioned items, which were assigned one point each. We divided patients into the 0–1 point (n = 116) and 2–3 points (n = 49) groups. The FAN score was a significant prognostic marker for cancer-specific survival (CSS) (HR 1.48, 95% CI 1.19–1.83, p < 0.001) along with the Eastern Cooperative Oncology Group Performance Status. The FAN score was also a prognostic factor of progression-free survival (PFS) (HR: 1.25, 95% CI 1.01–1.54, p = 0.036) along with the presence of liver metastasis. In the validation cohort, the FAN score was a significant prognostic factor for CSS (HR: 1.48, 95% CI 1.19–1.85, p = 0.001) and PFS (HR: 1.29, 95% CI 1.02–1.62, p = 0.034). We established the FAN score as a prognostic marker for patients with mUC treated with pembrolizumab.

Validation of GWAS-Identified Variants for Anti-TNF Drug Response in Rheumatoid Arthritis: A Meta-Analysis of Two Large Cohorts

We aimed to validate the association of 28 GWAS-identified genetic variants for response to TNF inhibitors (TNFi) in a discovery cohort of 1361 rheumatoid arthritis (RA) patients monitored in routine care and ascertained through the REPAIR consortium and DANBIO registry. We genotyped selected markers and evaluated their association with response to TNFi after 6 months of treatment according to the change in disease activity score 28 (ΔDAS28). Next, we confirmed the most interesting results through meta-analysis of our data with those from the DREAM cohort that included 706 RA patients treated with TNFi. The meta-analysis of the discovery cohort and DREAM registry including 2067 RA patients revealed an overall association of the LINC02549rs7767069 SNP with a lower improvement in DAS28 that remained significant after correction for multiple testing (per-allele ORMeta=0.83, PMeta=0.000077; PHet=0.61). In addition, we found that each copy of the LRRC55rs717117G allele was significantly associated with lower improvement in DAS28 in rheumatoid factor (RF)-positive patients (per-allele ORMeta=0.67, P=0.00058; PHet=0.06) whereas an opposite but not significant effect was detected in RF-negative subjects (per-allele ORMeta=1.38, P=0.10; PHet=0.45; PInteraction=0.00028). Interestingly, although the identified associations did not survive multiple testing correction, the meta-analysis also showed overall and RF-specific associations for the MAFBrs6071980 and CNTN5rs1813443 SNPs with decreased changes in DAS28 (per-allele ORMeta_rs6071980 = 0.85, P=0.0059; PHet=0.63 and ORMeta_rs1813443_RF+=0.81, P=0.0059; PHet=0.69 and ORMeta_rs1813443_RF-=1.00, P=0.99; PHet=0.12; PInteraction=0.032). Mechanistically, we found that subjects carrying the LINC02549rs7767069T allele had significantly increased numbers of CD45RO+CD45RA+ T cells (P=0.000025) whereas carriers of the LINC02549rs7767069T/T genotype showed significantly increased levels of soluble scavengers CD5 and CD6 in serum (P=0.00037 and P=0.00041). In addition, carriers of the LRRC55rs717117G allele showed decreased production of IL6 after stimulation of PBMCs with B burgdorferi and E coli bacteria (P=0.00046 and P=0.00044), which suggested a reduced IL6-mediated anti-inflammatory effect of this marker to worsen the response to TNFi. In conclusion, this study confirmed the influence of the LINC02549 and LRRC55 loci to determine the response to TNFi in RA patients and suggested a weak effect of the MAFB and CNTN5 loci that need to be further investigated.

Serum Human Epididymis Protein 4 as a Novel Biomarker in Identifying Patients With Interstitial Lung Disease in Rheumatoid Arthritis

Objective: Human epididymis protein 4 (HE4) have been implicated in the pulmonary involvements. We aimed to investigate the clinical utility of HE4 in clinical stratification in patients with rheumatoid arthritis (RA).Methods: This study included a discovery cohort comprising 70 RA patients and 64 healthy controls (HCs), and a validation cohort comprising 98 RA patients and 75 HCs. Human epididymis protein 4 were determined by electrochemical luminescence analyzer.Results: The levels of HE4 were significantly elevated in patients with RA compared to HCs. The positive rates of HE4 in patients with RA and HCs were 50.0% and 0, respectively, in the discovery cohort and 53.1 and 1.3%, respectively, in the validation cohort. When RA patients were subgrouped according to HE4 status, HE4-positive group displayed higher prevalence of interstitial lung disease (ILD) compared to HE4-negative group (28.6 vs. 11.4% in discovery cohort and 57.7 vs. 8.7% in the validation cohort). A positive correlation between the levels of HE4 with the degree of lung impairment was identified. Receiver operating curve (ROC) analysis revealed an optimal cut-off value of 104.3 pmol/L in HE4 for distinguishing RA-ILD from RA-non ILD with the areas under the curve (AUC) of 0.790. Multivariate logistic regression analysis illustrated that high levels of HE4 independently identified patients with RA-ILD (OR, 9.080, p &lt; 0.001).Conclusion: Our findings showed a novel role of HE4 in RA risk stratification, suggest that introducing HE4 to the current RA test panel may serve as an indicator in identifying RA patients for further RA-ILD workups, such as high-resolution computed tomography (HRCT).