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Toward Signaling-Driven Biomarkers Immune to Normal Tissue Contamination.

ABSTRACT: The goal of this study was to discover a minimally invasive pathway-specific biomarker that is immune to normal cell mRNA contamination for diagnosing head and neck squamous cell carcinoma (HNSCC). Using Elsevier's MedScan natural language processing component of the Pathway Studio software and the TRANSFAC database, we produced a curated set of genes regulated by the signaling networks driving the development of HNSCC. The network and its gene targets provided prior probabilities for gene expression, which guided our CoGAPS matrix factorization algorithm to isolate patterns related to HNSCC signaling activity from a microarray-based study. Using patterns that distinguished normal from tumor samples, we identified a reduced set of genes to analyze with Top Scoring Pair in order to produce a potential biomarker for HNSCC. Our proposed biomarker comprises targets of the transcription factor (TF) HIF1A and the FOXO family of TFs coupled with genes that show remarkable stability across all normal tissues. Based on validation with novel data from The Cancer Genome Atlas (TCGA), measured by RNAseq, and bootstrap sampling, the biomarker for normal vs. tumor has an accuracy of 0.77, a Matthews correlation coefficient of 0.54, and an area under the curve (AUC) of 0.82.

SUBMITTER: Stansfield JC

PROVIDER: S-EPMC4750896 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Toward Signaling-Driven Biomarkers Immune to Normal Tissue Contamination.

Stansfield John C JC Rusay Matthew M Shan Roger R Kelton Conor C Gaykalova Daria A DA Fertig Elana J EJ Califano Joseph A JA Ochs Michael F MF

Cancer informatics 20160210

The goal of this study was to discover a minimally invasive pathway-specific biomarker that is immune to normal cell mRNA contamination for diagnosing head and neck squamous cell carcinoma (HNSCC). Using Elsevier's MedScan natural language processing component of the Pathway Studio software and the TRANSFAC database, we produced a curated set of genes regulated by the signaling networks driving the development of HNSCC. The network and its gene targets provided prior probabilities for gene expre ...[more]

PMID: 26884679

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Project description:Background and objectives: Exposure to ionizing radiation (IR) has increased immensely over the past years, owing to diagnostic and therapeutic reasons. However, certain radiosensitive individuals show toxic enhanced reaction to IR, and it is necessary to specifically protect them from unwanted exposure. Although predicting radiosensitivity is the way forward in the field of personalised medicine, there is limited information on the potential biomarkers. The aim of this systematic review is to identify evidence from a range of literature in order to present the status quo of our knowledge of IR-induced changes in protein expression in normal tissues, which can be correlated to radiosensitivity. Methods: Studies were searched in NCBI Pubmed and in ISI Web of Science databases and field experts were consulted for relevant studies. Primary peer-reviewed studies in English language within the time-frame of 2011 to 2020 were considered. Human non-tumour tissues and human-derived non-tumour model systems that have been exposed to IR were considered if they reported changes in protein levels, which could be correlated to radiosensitivity. At least two reviewers screened the titles, keywords, and abstracts of the studies against the eligibility criteria at the first phase and full texts of potential studies at the second phase. Similarly, at least two reviewers manually extracted the data and accessed the risk of bias (National Toxicology Program/Office for Health Assessment and Translation-NTP/OHAT) for the included studies. Finally, the data were synthesised narratively in accordance to synthesis without meta analyses (SWiM) method. Results: In total, 28 studies were included in this review. Most of the records (16) demonstrated increased residual DNA damage in radiosensitive individuals compared to normo-sensitive individuals based on γH2AX and TP53BP1. Overall, 15 studies included proteins other than DNA repair foci, of which five proteins were selected, Vascular endothelial growth factor (VEGF), Caspase 3, p16INK4A (Cyclin-dependent kinase inhibitor 2A, CDKN2A), Interleukin-6, and Interleukin-1β, that were connected to radiosensitivity in normal tissue and were reported at least in two independent studies. Conclusions and implication of key findings: A majority of studies used repair foci as a tool to predict radiosensitivity. However, its correlation to outcome parameters such as repair deficient cell lines and patients, as well as an association to moderate and severe clinical radiation reactions, still remain contradictory. When IR-induced proteins reported in at least two studies were considered, a protein network was discovered, which provides a direction for further studies to elucidate the mechanisms of radiosensitivity. Although the identification of only a few of the commonly reported proteins might raise a concern, this could be because (i) our eligibility criteria were strict and (ii) radiosensitivity is influenced by multiple factors. Registration: PROSPERO (CRD42020220064).

Project description:PurposeTo develop normal tissue complications (NTCP) models for hepatocellular cancer (HCC) patients who undergo liver radiation therapy (RT) and to evaluate the potential role of functional imaging and measurement of blood-based circulating biological markers before and during RT to improve the performance of these models.Methods and materialsThe data from 192 HCC patients who had undergone RT from 2005 to 2014 were evaluated. Of the 192 patients, 146 had received stereotactic body RT (SBRT) and 46 had received conventional RT to a median physical tumor dose of 49.8 Gy and 50.4 Gy, respectively. The physical doses were converted into 2-Gy equivalents for analysis. Two approaches were investigated for modeling NTCP: (1) a generalized Lyman-Kutcher-Burman model; and (2) a generalization of the parallel architecture model. Three clinical endpoints were considered: the change in albumin-bilirubin (ALBI), change in Child-Pugh (C-P) score, and grade ≥3 liver enzymatic changes. Local dynamic contrast-enhanced magnetic resonance imaging portal venous perfusion information was used as an imaging biomarker for local liver function. Four candidate inflammatory cytokines were considered as biological markers. The imaging findings and cytokine levels were incorporated into NTCP modeling, and their role was evaluated using goodness-of-fit metrics.ResultsUsing dosimetric information only, the Lyman-Kutcher-Burman model for the ALBI/C-P change had a steeper response curve compared with grade ≥3 enzymatic changes. Incorporating portal venous perfusion imaging information into the parallel architecture model to represent functional reserve resulted in relatively steeper dose-response curves compared with dose-only models. A larger loss of perfusion function was needed for enzymatic changes compared with ALBI/C-P changes. Increased transforming growth factor-β1 and eotaxin expression increased the trend of expected risk in both NTCP modeling approaches but did not reach statistical significance.ConclusionsThe incorporation of imaging findings and biological markers into NTCP modeling of liver toxicity improved the estimates of expected NTCP risk compared with using dose-only models. In addition, such generalized NTCP models should contribute to a better understanding of the normal tissue response in HCC SBRT patients and facilitate personalized treatment.

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Toward Signaling-Driven Biomarkers Immune to Normal Tissue Contamination.

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Toward Signaling-Driven Biomarkers Immune to Normal Tissue Contamination.

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