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The biomarker development field within molecular medicine remains limited by the methods that are available for building predictive models. We developed an efficient method for conservatively estimating confidence intervals for the cross validation-derived prediction errors of biomarker models. This new method was investigated for its ability to improve the capacity of our previously developed method, StaVarSel, for selecting stable biomarkers. Compared with the standard cross validation method, StaVarSel markedly improved the estimated generalisable predictive capacity of serum miRNA biomarkers for the detection of disease states that are at increased risk of progressing to oesophageal adenocarcinoma. The incorporation of our new method for conservatively estimating confidence intervals into StaVarSel resulted in the selection of less complex models with increased stability and improved or similar predictive capacities. The methods developed in this study have the potential to improve progress from biomarker discovery to biomarker driven translational research.

Supplementary figure 5. LncRNAs and mutational signatures. IGV coverage plot of two previously characterised lncRNAs (a) AFAP1-AS1, (b) HNF1A-AS1 upregulated in EAC. Coverage is normalised as counts per million reads. (c) TCGA RNA-seq EAC data was utilised to validate neighbor lncRNA-mRNA pair correlation. Through TCGA alignment of Refseq only 15 of our differentially expressed lncRNAs-gene pairs were available in the TCGA data and then subsequently correlated using the same methods as presented in the main article. (d) SNPs in normal samples were removed from this analysis. All NDBE, LGD and EAC patients were investigated for mutational signatures as described. Only mutations covered by {greater than or equal to}20 reads were used to determine the presence of transcriptional mutation signatures (a) Five signatures were identified, which was used to (e) cluster the patients based on each signatures contribution to the patients mutations.

Esophageal adenocarcinoma (EAC) has one of the fastest increases in incidence of any cancer, along with poor five-year survival rates. Barrett's esophagus (BE) is the main risk factor for EAC; however, the mechanisms driving EAC development remain poorly understood. Here, transcriptomic profiling was performed using RNA-sequencing (RNA-seq) on premalignant and malignant Barrett's tissues to better understand this disease. Machine-learning and network analysis methods were applied to discover novel driver genes for EAC development. Identified gene expression signatures for the distinction of EAC from BE were validated in separate datasets. An extensive analysis of the noncoding RNA (ncRNA) landscape was performed to determine the involvement of novel transcriptomic elements in Barrett's disease and EAC. Finally, transcriptomic mutational investigation of genes that are recurrently mutated in EAC was performed. Through these approaches, novel driver genes were discovered for EAC, which involved key cell cycle and DNA repair genes, such as BRCA1 and PRKDC. A novel 4-gene signature (CTSL, COL17A1, KLF4, and E2F3) was identified, externally validated, and shown to provide excellent distinction of EAC from BE. Furthermore, expression changes were observed in 685 long noncoding RNAs (lncRNA) and a systematic dysregulation of repeat elements across different stages of Barrett's disease, with wide-ranging downregulation of Alu elements in EAC. Mutational investigation revealed distinct pathways activated between EAC tissues with or without TP53 mutations compared with Barrett's disease. In summary, transcriptome sequencing revealed altered expression of numerous novel elements, processes, and networks in EAC and premalignant BE.Implications: This study identified opportunities to improve early detection and treatment of patients with BE and esophageal adenocarcinoma. Mol Cancer Res; 15(11); 1558–69. ©2017 AACR.

Supplementary table 1 describes patient demographics and sample sequencing information Supplementary table 2 describes the top 20 differentially expressed genes, and the 12-gene signature. Supplementary table 3 shows the Discriminative performance of EAC driver genes in predicting the presence of EAC compared to BE with or without dysplasia. Supplementary table 4-5 describes the top 20 differentially expressed lncRNAs and repeat elements, respectively. Supplementary table 6 shows the association of genes in 12-signature with malignancies. Searched Pubmed: "Gene & Cancer" Supplementary table 7 shows the primers for lncRNA expression validation.

Antiretroviral therapy (ART) can attain prolonged undetectable HIV-1 in plasma and cerebrospinal fluid (CSF), but brain injury remains prevalent in people living with HIV-1 infection (PLHIV). We investigated cell-associated (CA)-HIV-1 RNA transcripts in cells in CSF and blood, using the highly sensitive Double-R assay, together with proton Magnetic Resonance Spectroscopy ( 1 H MRS) of major brain metabolites, in sixteen PLHIV. 14/16 CSF cell samples had quantifiable CA-HIV-1 RNA, at levels significantly higher than in their PBMCs (median 9,266 vs 185 copies /106 CD4+ T-cells; p+ CD49d + integrin β7-, CCR5 + CD4 + T-cells were highly enriched in CSF, compared with PBMC (p + T cells from blood, rather than trafficking monocytes. Future research should focus on inhibitors of this transcription to reduce local production of potentially neurotoxic and inflammatory viral products.

Prognostic biomarkers for esophageal adenocarcinoma (EAC) remain elusive but may be helpful in treatment planning, as TNM staging often fails to accurately predict survival. Advanced stage patients are treated by peri-operative chemo/radiotherapy; biomarkers associated with survival are thus likely to represent both true prognostic markers as well as markers of response to chemo/radiotherapy. Here we present first-pass genomic findings for a cohort of optimally staged EAC patients treated by surgery alone. DNA was extracted from fresh frozen EAC and matching normal squamous esophageal tissues obtained at esophagectomy from 65 consenting patients who did not receive any neo- or adjuvant chemo- or radiotherapy due to institutional preference at the time of tissue collection. Library preparation and sequencing for a targeted 600 cancer-associated gene panel designed using the Roche/NimbleGen EZ Choice Library NimbleDesign platform were conducted on Illumina-based platforms followed by analysis with an accredited bioinformatics pipeline. The panel design incorporated the entire coding region plus 10 bp of flanking intron of each gene. Mean age 70 yrs; 88% male. All patients underwent an en bloc esophagectomy (mean 35 lymph nodes). TNM (7th ed.) stages were 61% Stage 3, 18% stage 2, 14% stage 1, 6% stage 4. At median 9.5 years follow-up, 20 (31%) patients remained alive. Copy number changes were common, reflecting chromosomal instability. Less than 8% of patients had high tumour mutational burden (>10mut/MB), associated with mutations in DNA repair genes. Commonest somatic mutations included TP53 (HR: 0.43) and LRP1B (HR: 1.7). Pathways implicated included RTK signalling (PIK3CA, EGFR, KRAS), DNA damage (BRCA1, PALB2, MGMT) and histone remodelling (ARID1A, ARID2, KMT2D). Peri-operative treatment means linking genomic changes independent of stage to clinical outcomes is difficult. Neoadjuvant and/or adjuvant treatment is now standard for T2–4 or node positive EAC. This cohort of 65 patients, most of whom had stage 3 disease and all of whom underwent optimal staging with en bloc esophagectomy, represents a unique opportunity to analyze characteristics of EAC without confounding by peri-operative treatment. An EAC-specific DNA sequencing panel approach offers potential for personalized therapy.