Development Of Predictive Strategies Research Articles

Molecular Epidemiology of Acute Myeloid Leukemia (AML): Novel Association of Clinical Epidemiologic Exposures with Unique Mutation Groups on Exome Sequencing of Leukemia DNA in the Mayo Clinic AML Epidemiology Cohort

Background: Clinical epidemiologic risk factors associated with leukemia development are prevalent, and can be identified in over 90% of AML patients. We previously demonstrated an association of clinical exposures with cytogenetic risk group and outcome after therapy, but the molecular impact of such exposures is unclear, and specifically it is not known whether specific epidemiologic exposures are associated with unique genetic lesions. We therefore performed Exome Sequencing in 98 patients from our clinical epidemiology cohort to determine whether there was an association of clinically relevant AML risk factors and exposures with unique deleterious non-synonymous (nonsyn.) mutations.Methods: The Mayo Clinic AML Epidemiology cohort comprises a highly annotated series of n=295 unselected and consecutive patients diagnosed and treated at Mayo Clinic Florida & Arizona [Cancer Epidemiol 39:1084, 2015]. We obtained AML DNA from remnant diagnostic cytogenetic pellets identified in 98 patients in the cohort, and performed Exome Sequencing [ExSeq] using standard techniques. The ~100 million paired-end 100bp reads from each sample were mapped to human genome build hg19 using BWA-MEM 1. The single nucleotide variants (SNVs) and small INDELs in the exome capture regions were identified using Mayo Clinic in-house developed analytic pipeline GenomeGPS 4.0.1 following Broad GATK 2 variant discovery best practices of alignment, realignment and recalibration, haplotype caller, and multi-sample joint genotyping. The variants passed the GATK's Variant Quality Score Recalibration (VQSR) quality control were kept. Since no patient matched normal were sequenced, SNVs and INDELs were filtered using both germline whole exome and whole genome sequencing of ~1200 Mayo Clinic Biobank samples and the public germline variant databases of 1000 genome project, 6500 individuals sequenced in the exome sequencing project (ESP), and HapMap phase 3. The remaining variants were annotated using ANNOVAR 3, and potential functional variants of non-synonymous, truncating, frame-shift, and splice-sites were used in the statistical association analyses. We evaluated the association of unique mutations occurring in 10 or more patients and in TP53, and also gene categories according to algorithm of Lindsley et al (Blood 125:1367, 2015) with relevant clinical and epidemiology exposures identified in our prior analysis. Risk factors and exposures were compared between patients with and without a mutation in different genes of interest using Fisher's exact test.Results: The read quality was excellent, and results from 97 evaluable samples were included in analysis. Results are noted in Table. We found a strong and significant association of prior history of immunosuppressive therapy (IST) or solid organ transplantation (SOT) with RUNX1 mutation (p=0.0001), and of regular Statin use with ASXL1 mutation (p=0.008). Statin use was also associated with mutations in genes involved in DNA methylation (p=0.036) and in Chromatin Modifier genes (p=0.049). We identified a novel inverse association of obesity - the most prevalent AML risk factor - with spliceosome mutation (p=0.010), and of IST/SOT with mutations in Myeloid Transcription Factors (TF, p=0.015) and Activated Signaling pathways [RAS, FLT3, KIT, CBL, NF1] (p=0.026). We confirm the association of secondary AML [sAML] with spliceosome mutation (p=0.018), observed as expected most strongly for Antecedent Hematologic Disorder (p=0.008, not shown). Other borderline associations (p≤0.10) are noted in Table. We did not identify any association of family history [FHx] of hematologic malignancy or of smoking [TOB] with unique mutations, nor did we identify clinical exposures associated with TP53 mutation.Conclusion: For the first time (apart from sAML) we have identified a unique leukemia genotype associated with some common clinical and epidemiologic exposures. Some mutations groups (Cohesin, TP53) were not associated with any clinical exposures, suggesting alternate mechanisms of leukemogenesis. ExSeq was for the first time successfully performed on archived diagnostic cytogenetic cell pellets, we believe a novel source of leukemia DNA. These results will guide a planned prospective study to determine frequency and mechanism of leukemogenesis after exposures, and development of strategies for prediction of leukemia risk and ultimately prevention. [Display omitted] DisclosuresCerhan:Janssen: Other: Scientific Advisory Board (REMICADELYM4001); Janssen: Other: Multiple Myeloma Registry Steering .

A Framework to Assess the Information Dynamics of Source EEG Activity and Its Application to Epileptic Brain Networks.

This study introduces a framework for the information-theoretic analysis of brain functional connectivity performed at the level of electroencephalogram (EEG) sources. The framework combines the use of common spatial patterns to select the EEG components which maximize the variance between two experimental conditions, simultaneous implementation of vector autoregressive modeling (VAR) with independent component analysis to describe the joint source dynamics and their projection to the scalp, and computation of information dynamics measures (information storage, information transfer, statistically significant network links) from the source VAR parameters. The proposed framework was tested on simulated EEGs obtained mixing source signals generated under different coupling conditions, showing its ability to retrieve source information dynamics from the scalp signals. Then, it was applied to investigate scalp and source brain connectivity in a group of children manifesting episodes of focal and generalized epilepsy; the analysis was performed on EEG signals lasting 5 s, collected in two consecutive windows preceding and one window following each ictal episode. Our results show that generalized seizures are associated with a significant decrease from pre-ictal to post-ictal periods of the information stored in the signals and of the information transferred among them, reflecting reduced self-predictability and causal connectivity at the level of both scalp and source brain dynamics. On the contrary, in the case of focal seizures the scalp EEG activity was not discriminated across conditions by any information measure, while source analysis revealed a tendency of the measures of information transfer to increase just before seizures and to decrease just after seizures. These results suggest that focal epileptic seizures are associated with a reorganization of the topology of EEG brain networks which is only visible analyzing connectivity among the brain sources. Our findings emphasize the importance of EEG modeling approaches able to deal with the adverse effects of volume conduction on brain connectivity analysis, and their potential relevance to the development of strategies for prediction and clinical treatment of epilepsy.

Correlation of pretreatment nuclear GLI-1 labeling indices (LIs) with initial SUV (iSUV) in esophageal cancer (EC) patients undergoing trimodality therapy (TMT): A potential pathway to esophageal preservation.

18 Background: For the purpose of understanding clinical behavior of EC, imaging and biomarkers have not been correlated. We attempted to correlate iSUV with a variety of biomarkers (NF-kB, SHH, ALDH1, ABCB1, survivin, and BCRP) including pre-treatment nuclear Gli-1 LIs in patients with EC who had undergone TMT. Methods: 128 patients were analyzed. The iSUV and pre-treatment nuclear Gli-1 LIs were assessed among others. Post-treatment residual cancer status in the resected specimen was also correlated (P0=0% residual cells, P1=1-50% residual cells, and P2=>50% residual cells) with iSUV and nuclear Gli-1 LIs. The Kruskal-Wallis test was performed to find correlations between (1) iSUV and P status; and (2) between nuclear Gli-1 LIs and P status. Results: The Pearson’s correlation coefficient between iSUV and nuclear Gli-1 LIs was 0.21 (p = 0.02). Pre-treatment nuclear Gli-1 LIs were strongly associated with the P status (p<0.0001) but iSUV was not (as has been reported in the literature; PMID: 17532577, 23247658, and 23994746). iSUV, most likely, is not correlative with the P status because of its narrow range compared to that of nuclear Gli-1 LIs.Conclusions: Our data, for the first time, demonstrate that iSUV can be a surrogate for pre-treatment nuclear Gli-1 LIs in EC. This correlation can be exploited in the development of predictive strategies for esophageal preservation. Pre-treatment nuclear Gli-1 is a strong candidate for the biomarker-based predictive model(s). From U. T. M. D. Anderson Cancer Center (UTMDACC), Houston, Texas, USA. Supported by UTMDACC Multidisciplinary Research Grants, CA138671, CA172741, and CA129926 From the NCI (JAA), and Generous Donors. [Table: see text]