Citations

AbstractBackground & AimsAlthough transient elastography (TE) is used to determine liver stiffness as a surrogate to hepatic fibrosis, the normal range in children is not well defined. We performed a systematic review and individual participant data (IPD) meta‐analysis to determine the range of liver stiffness in healthy children and evaluate the influence of important biological parameters.MethodsWe pooled data from 10 studies that examined healthy children using TE. We divided 1702 children into two groups: ≥3 years (older group) and < 3 years of age (younger group). Univariate and multivariate linear regression models predicting liver stiffness were conducted.ResultsAfter excluding children with obesity, diabetes, or abnormal liver tests, 652 children were analysed. Among older children, mean liver stiffness was 4.45 kPa (95% confidence interval 4.34‐4.56), and increased liver stiffness was associated with age, sedation status, and S probe use. In the younger group, the mean liver stiffness was 4.79 kPa (95% confidence interval 4.46‐5.12), and increased liver stiffness was associated with sedation status and Caucasian race. In a subgroup analysis, hepatic steatosis on ultrasound was significantly associated with increased liver stiffness. We define a reference range for normal liver stiffness in healthy children as 2.45‐5.56 kPa.ConclusionsWe have established TE‐derived liver stiffness ranges for healthy children and propose an upper limit of liver stiffness in healthy children to be 5.56 kPa. We have identified increasing age, use of sedation, probe size, and presence of steatosis on ultrasound as factors that can significantly increase liver stiffness.

Abstract Purpose: Romidepsin dosing recommendations for patients with malignancy and varying degrees of hepatic dysfunction was lacking at the time of regulatory approval for T-cell lymphoma. We conducted a multicenter phase I clinical trial (ETCTN-9008) via the NCI Organ Dysfunction Working Group to investigate safety, first cycle MTD, and pharmacokinetic profile of romidepsin in this setting. Patients and Methods: Patients with select advanced solid tumors or hematologic malignancies were stratified according to hepatic function. Romidepsin was administered intravenously on days 1, 8, and 15 of a 28-day cycle and escalation followed a 3 + 3 design in moderate and severe impairment cohorts. Blood samples for detailed pharmacokinetic analyses were collected after the first dose. Results: Thirty-one patients received one dose of romidepsin and were evaluable for pharmacokinetic analyses in normal (n = 12), mild (n = 8), moderate (n = 5), and severe (n = 6) cohorts. Adverse events across cohorts were similar, and dose-limiting toxicity occurred in two patients (mild and severe impairment cohorts). The MTD was not determined because the geometric mean AUC values of romidepsin in moderate (7 mg/m2) and severe (5 mg/m2) impairment cohort were 114% and 116% of the normal cohort (14 mg/m2). Conclusions: Data from the ETCTN-9008 trial led to changes in the romidepsin labeling to reflect starting dose adjustment for patients with cancer and moderate and severe hepatic impairment, with no adjustment for mild hepatic impairment.

In 2012, the Norwegian newborn screening program (NBS) was expanded (eNBS) from screening for two diseases to that for 23 diseases (20 inborn errors of metabolism, IEMs) and again in 2018, to include a total of 25 conditions (21 IEMs). Between 1 March 2012 and 29 February 2020, 461,369 newborns were screened for 20 IEMs in addition to phenylketonuria (PKU). Excluding PKU, there were 75 true-positive (TP) (1:6151) and 107 (1:4311) false-positive IEM cases. Twenty-one percent of the TP cases were symptomatic at the time of the NBS results, but in two-thirds, the screening result directed the exact diagnosis. Eighty-two percent of the TP cases had good health outcomes, evaluated in 2020. The yearly positive predictive value was increased from 26% to 54% by the use of the Region 4 Stork post-analytical interpretive tool (R4S)/Collaborative Laboratory Integrated Reports 2.0 (CLIR), second-tier biochemical testing and genetic confirmation using DNA extracted from the original dried blood spots. The incidence of IEMs increased by 46% after eNBS was introduced, predominantly due to the finding of attenuated phenotypes. The next step is defining which newborns would truly benefit from screening at the milder end of the disease spectrum. This will require coordinated international collaboration, including proper case definitions and outcome studies.

Abstract Background: A polygenic hazard score (PHS), the weighted sum of 54 SNP genotypes, was previously validated for association with clinically significant prostate cancer and for improved prostate cancer screening accuracy. Here, we assess the potential impact of PHS-informed screening. Methods: United Kingdom population incidence data (Cancer Research United Kingdom) and data from the Cluster Randomized Trial of PSA Testing for Prostate Cancer were combined to estimate age-specific clinically significant prostate cancer incidence (Gleason score ≥7, stage T3–T4, PSA ≥10, or nodal/distant metastases). Using HRs estimated from the ProtecT prostate cancer trial, age-specific incidence rates were calculated for various PHS risk percentiles. Risk-equivalent age, when someone with a given PHS percentile has prostate cancer risk equivalent to an average 50-year-old man (50-year-standard risk), was derived from PHS and incidence data. Positive predictive value (PPV) of PSA testing for clinically significant prostate cancer was calculated using PHS-adjusted age groups. Results: The expected age at diagnosis of clinically significant prostate cancer differs by 19 years between the 1st and 99th PHS percentiles: men with PHS in the 1st and 99th percentiles reach the 50-year-standard risk level at ages 60 and 41, respectively. PPV of PSA was higher for men with higher PHS-adjusted age. Conclusions: PHS provides individualized estimates of risk-equivalent age for clinically significant prostate cancer. Screening initiation could be adjusted by a man's PHS. Impact: Personalized genetic risk assessments could inform prostate cancer screening decisions.

TPS2573 Background: Brain metastases, most commonly derived from melanoma, lung and breast cancers, are the most common brain tumor, with approximately 200,000 cases diagnosed annually in the United States. Median survival is on the order of months. For patients with clinically symptomatic brain metastases, approximately half succumb due to intracranial progression. In preclinical work, we demonstrated that brain metastases and primary tumors are often genetically distinct with frequent alterations in the CDK and PI3K pathway (Brastianos, Carter et al. Cancer Discovery 2015). Methods: We are currently accruing to a prospective multi-arm phase II study of CDK, PI3K/mTOR, and NTRK/ROS1 inhibitors in patients with brain metastases harboring alterations associated with sensitivity to these inhibitors (abemaciclib, paxalisib and entrectinib), respectively. Patients with new, recurrent or progressive brain metastases are eligible for this trial. Previously obtained tissue from brain metastases and extracranial sites (primary or extracranial metastases) are screened for the presence of these alterations, and if present in both tumor sites, patients will receive the appropriate corresponding targeted treatment. Screening is carried out with the SNaPshot NGS assay, which is a fully validated clinical test designed and developed at the MGH Center for Integrated Diagnostics. The primary endpoint of response rate (RR) in the central nervous system as per RANO criteria will be evaluated separately for each inhibitor, stratified by histology within each arm. There will be 21 evaluable patients assigned to each of the CDK and PI3K inhibitor and tumor type cohorts (breast, lung and other) and 10 patients assigned to the NTRK/ROS1 inhibitor cohort (lung) for a total of 136 evaluable patients. Although current systemic therapy for brain metastases is often ineffective, we hypothesize that targeted therapies will demonstrate efficacy in patients harboring the appropriate mutations. This study represents a novel individualized therapeutic approach in brain metastases, a disease with a critical need for effective therapy. Support: U10CA180821, U10CA180882, https://acknowledgments.alliancefound.org ; Genentech, Kazia Therapeutics Limited, Eli Lilly; Clinical trial information: NCT03994796 .

Abstract Background: It has become increasingly clear that effective treatment of metastatic breast cancer (MBC) requires an in-depth understanding of the molecular differences between primary tumors and metastases. The AURORA US Network was established to collect primary breast cancer-metastasis pairs for multi-platform genomic profiling in order to identify the molecular drivers of metastatic disease. AURORA US has both a retrospective and prospective phase. This is the first report of the retrospective phase. Methods: Archived tissue samples from the primary tumor and at least one distant metastasis were retrospectively collected from 83 MBC patients. Following internal quality assessment, samples from 55 pts, including 105 distinct metastatic lesions, were subject to DNA low pass whole genome and exome sequencing, DNA methylation arrays, and RNA sequencing. Early analyses of these multi-platform data include: DNA methylation, tumor gene expression and microenvironmental signatures, somatic and germline variants, DNA copy number changes, and structural variants between breast primaries and matched metastases. Results: Median age at diagnosis was 49 years (25-76); 32 (58%) were Stage I or II at presentation, 27 (49%) had a family history of breast cancer, and 20 (36%) had a second breast primary. Median disease-free interval before developing MBC was 2 years (range 0-36, 5 patients presented with Stage IV). Median overall survival from initial presentation was 4 years (range 0-37). Median survival after developing MBC was 1 year (range 0-13), with a median of three treatments. Primary tissue samples were banked from 1977-2017 and metastases were banked from 1999-2017. Clinical phenotypes of the primaries included 27 HR+ (49%), 15 triple negative (TNBC, 27%), and 11 HER2+ (20%, 12 missing HER2 status). Intrinsic subtype distribution of the primaries included 17 Basal-like (31%), 17 Luminal A (31%), 7 Normal-like (13%), 5 HER2-enriched (9%), and 1 Luminal B, with 8 pending. All metastases from the Basal-like cases remained Basal-like, while metastases from luminal primaries tended to gain HER2-Enriched subtype features (5/18, p = 0.01). Overall, we identified significant metastasis-enriched alterations in metabolism pathways, an increase in proliferation, and the loss of differentiation signatures and immune infiltrates with progression; the latter being the most pronounced in brain metastases. The most frequent somatic mutations in this cohort were in TP53, NCOR1, and RUNX1. Interestingly, ERBB2, EGFR, and ATM were also mutated in ≥10% of the tumors sequenced. In almost all cases, CpG island hypermethylation was clonally present in the primary tumor and persisted stably in the majority of metastatic lesions. Promoter CpG island hypermethylation was also identified in some metastatic lesions at JAM3, an important cellular adhesion molecule,and this was accompanied by reduced mRNA expression. CONCLUSIONS: Collection of banked primary and metastatic tissue pairs identified a young MBC cohort with a high frequency of breast cancer family history and second breast primaries. Molecular characterization of luminal tumor pairs highlighted acquisition of aggressive traits including increased proliferation and loss of differentiation in the metastases. In contrast, basal-like pairs remained relatively unchanged, except for the loss of immune activation. Ongoing analyses to be presented include clonal heterogeneity and phylogeny, novel metastasis signature discovery, gene fusion, and endogenous retrovirus detection. Citation Format: Tari A King, Minetta C Liu, Marni B McClure, Toshinori Hinoue, Benjamin J Kelly, Chad J Creighton, Jay Bowen, Kristen Leraas, Robyn T Burns, Sara Coppens, Salma Rezk, Amy L Garrett, Justin M Balko, Joel S Parker, Ben H Park, Ian Krop, Carey Anders, Katherine A Hoadley, Julie Gastier-Foster, Mothaffar F Rimawi, Rita Nanda, Nancy U Lin, Claudine Isaacs, P. Kelly Marcom, Anna Maria Storniolo, Fergus J Couch, Elaine R Mardis, Adrian V Lee, Uma Chandran, Peter W Laird, Susan G Hilsenbeck, Larry Norton, Andrea L Richardson, W. Fraser Symmans, Lisa A Carey, Antonio C Wolff, Nancy E Davidson, Charles M Perou, the AURORA US Network. Multiplatform analysis of matched primary and metastatic breast tumors from the AURORA US Network [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr GS3-08.

INTRODUCTION The cerebral cortex underlies our complex cognitive capabilities. Variations in human cortical surface area and thickness are associated with neurological, psychological, and behavioral traits and can be measured in vivo by magnetic resonance imaging (MRI). Studies in model organisms have identified genes that influence cortical structure, but little is known about common genetic variants that affect human cortical structure. RATIONALE To identify genetic variants associated with human cortical structure at both global and regional levels, we conducted a genome-wide association meta-analysis of brain MRI data from 51,665 individuals across 60 cohorts. We analyzed the surface area and average thickness of the whole cortex and 34 cortical regions with known functional specializations. RESULTS We identified 369 nominally genome-wide significant loci ( P < 5 × 10 −8 ) associated with cortical structure in a discovery sample of 33,992 participants of European ancestry. Of the 360 loci for which replication data were available, 241 loci influencing surface area and 66 influencing thickness remained significant after replication, with 237 loci passing multiple testing correction ( P < 8.3 × 10 −10 ; 187 influencing surface area and 50 influencing thickness). Common genetic variants explained 34% (SE = 3%) of the variation in total surface area and 26% (SE = 2%) in average thickness; surface area and thickness showed a negative genetic correlation ( r G = −0.32, SE = 0.05, P = 6.5 × 10 −12 ), which suggests that genetic influences have opposing effects on surface area and thickness. Bioinformatic analyses showed that total surface area is influenced by genetic variants that alter gene regulatory activity in neural progenitor cells during fetal development. By contrast, average thickness is influenced by active regulatory elements in adult brain samples, which may reflect processes that occur after mid-fetal development, such as myelination, branching, or pruning. When considered together, these results support the radial unit hypothesis that different developmental mechanisms promote surface area expansion and increases in thickness. To identify specific genetic influences on individual cortical regions, we controlled for global measures (total surface area or average thickness) in the regional analyses. After multiple testing correction, we identified 175 loci that influence regional surface area and 46 that influence regional thickness. Loci that affect regional surface area cluster near genes involved in the Wnt signaling pathway, which is known to influence areal identity. We observed significant positive genetic correlations and evidence of bidirectional causation of total surface area with both general cognitive functioning and educational attainment. We found additional positive genetic correlations between total surface area and Parkinson’s disease but did not find evidence of causation. Negative genetic correlations were evident between total surface area and insomnia, attention deficit hyperactivity disorder, depressive symptoms, major depressive disorder, and neuroticism. CONCLUSION This large-scale collaborative work enhances our understanding of the genetic architecture of the human cerebral cortex and its regional patterning. The highly polygenic architecture of the cortex suggests that distinct genes are involved in the development of specific cortical areas. Moreover, we find evidence that brain structure is a key phenotype along the causal pathway that leads from genetic variation to differences in general cognitive function. Identifying genetic influences on human cortical structure. ( A ) Measurement of cortical surface area and thickness from MRI. ( B ) Genomic locations of common genetic variants that influence global and regional cortical structure. ( C ) Our results support the radial unit hypothesis that the expansion of cortical surface area is driven by proliferating neural progenitor cells. ( D ) Cortical surface area shows genetic correlation with psychiatric and cognitive traits. Error bars indicate SE. IMAGE CREDITS: (A) K. COURTNEY; (C) M. R. GLASS

8517 Background: An increased risk of SPM in MM pts treated with len has been reported. We performed an IPD metanalysis to estimate the incidence of SPM according to len exposure. Methods: Randomized studies of MM, from PubMed and ASCO/IMW/ASH (after 2000), that met the following criteria, were included: randomization to treatment with len (len-trials); randomization to treatment including new drug but not len (no-len-trials); available SPM data. Primary aim was to estimate cumulative incidence of SPMs by len exposure, corrected for death (competing event). Results: Data from 6,383 pts (3,218 from 8 len-trials, 3,165 from 10 no-len-trials) were analyzed. Median age was 69 years. During follow-up (median=30 mos) 420 (6.6%) SPMs were reported: 188 (2.9%) hematologic and 232 (3.6%) solid cancers. Solid tumors occurred with similar incidence in all groups. Incidence of hematologic SPM was significantly higher in patients receiving len (3.2 vs 1.1, p=0.04), but risk is limited to patients treated with melphalan+len (4.1, 95%CI: 2.4-5.8) with no excess in other combinations (len without melphalan: 1.2, 0.0-2.6; melphalan without len: 1.1, 0.0-2.7) (p=0.003). The cumulative incidence of death for any cause was much higher than the risk of SPM. Conclusions: The risk of hematologic SPMs was higher in pts receiving melphalan+len. The benefit/risk profile of len treatment remains positive. Cumulative incidence (%) of SPMs and death (95%CI). [Table: see text]

Abstract Background The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) creatinine equation is routinely used to assess renal function but exhibits varying accuracy depending on patient characteristics and clinical presentation. The overall aim of the present study was to assess if and to what extent glomerular filtration rate (GFR) estimation based on creatinine can be improved. Methods In a cross-sectional analysis covering the years 2003–17, CKD-EPI was validated against measured GFR (mGFR; using various tracer methods) in patients with high likelihood of chronic kidney disease (CKD; five CKD cohorts, n = 8365) and in patients with low likelihood of CKD (six community cohorts, n = 6759). Comparisons were made with the Lund–Malmö revised equation (LMR) and the Full Age Spectrum equation. Results 7In patients aged 18–39 years old, CKD-EPI overestimated GFR with 5.0–16 mL/min/1.73 m2 in median in both cohort types at mGFR levels &lt;120 mL/min/1.73 m2. LMR had greater accuracy than CKD-EPI in the CKD cohorts (P30, the percentage of estimated GFR within 30% of mGFR, 83.5% versus 76.6%). CKD-EPI was generally the most accurate equation in the community cohorts, but all three equations reached P30 above the Kidney Disease Outcomes Quality Initiative benchmark of 90%. Conclusions None of the evaluated equations made optimal use of available data. Prospects for improved GFR estimation procedures based on creatinine exist, particularly in young adults and in settings where patients with suspected or manifest CKD are investigated.