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A Blood Transcriptional Diagnostic Assay for Septicemic Melioidosis

ABSTRACT: Melioidosis, caused by Gram negative bacteria Burkholderia pseudomallei, is a major type of community-acquired septicemia in Southeast Asia and Northern Australia with high mortality and morbidity rate. More accurate and rapid diagnosis is needed for improving the management of septicemic melioidosis. We previously identified 37-gene candidate signature to distinguish septicemic melioidosis from sepsis due to other pathogens. The aims of this current study were to independently validate our previous biomarker and consolidate gene selection from each of our microarray data set for establishing a targeted assay for the differential diagnosis of melioidosis. Blood samples were collected from patients who presented with severe inflammatory response syndromes from 3 provincial hospitals in Northeast of Thailand during September 2009 and November 2011. Only culture-confirmed sepsis were included in the study (n=166). We generated a new microarray dataset comprising of 29 patients with septicemic melioidosis and 54 patients with sepsis due to other pathogens. Validation of the 37-gene signature using this new dataset demonstrated the prediction accuracy of approximately 80% for detecting type of sepsis. In order to develop a nanoliter-scale high throughput PCR technology, we further identified additional gene signature from this new microarray dataset and by revisiting our published data. Altogether 85 genes including 6 housekeeping genes were selected. Using multi-steps iteration approach we could reduce the number of biomarkers to 12 genes while the performance is comparable to that of the full panel. The high performance (accuracy >70%) of this 12-gene signature could be validated in a second independent set of samples. The 12-gene panel identified by our study provides high performance for the differential diagnosis of septicemic melioidosis. This finding will be useful for improving the management of septicemic melioidosis in term of diagnosis, treatment and follow up.

ORGANISM(S): Homo sapiens

PROVIDER: GSE69528 | GEO | 2015/06/04

SECONDARY ACCESSION(S): PRJNA285800

REPOSITORIES: GEO

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Project description:Melioidosis, caused by Gram negative bacteria Burkholderia pseudomallei, is a major type of community-acquired septicemia in Southeast Asia and Northern Australia with high mortality and morbidity rate. More accurate and rapid diagnosis is needed for improving the management of septicemic melioidosis. We previously identified 37-gene candidate signature to distinguish septicemic melioidosis from sepsis due to other pathogens. The aims of this current study were to independently validate our previous biomarker and consolidate gene selection from each of our microarray data set for establishing a targeted assay for the differential diagnosis of melioidosis. Blood samples were collected from patients who presented with severe inflammatory response syndromes from 3 provincial hospitals in Northeast of Thailand during September 2009 and November 2011. Only culture-confirmed sepsis were included in the study (n=166). We generated a new microarray dataset comprising of 29 patients with septicemic melioidosis and 54 patients with sepsis due to other pathogens. Validation of the 37-gene signature using this new dataset demonstrated the prediction accuracy of approximately 80% for detecting type of sepsis. In order to develop a nanoliter-scale high throughput PCR technology, we further identified additional gene signature from this new microarray dataset and by revisiting our published data. Altogether 85 genes including 6 housekeeping genes were selected. Using multi-steps iteration approach we could reduce the number of biomarkers to 12 genes while the performance is comparable to that of the full panel. The high performance (accuracy >70%) of this 12-gene signature could be validated in a second independent set of samples. The 12-gene panel identified by our study provides high performance for the differential diagnosis of septicemic melioidosis. This finding will be useful for improving the management of septicemic melioidosis in term of diagnosis, treatment and follow up. Total RNA from whole blood obtained from patients with sepsis caused by B.pseudomallei (n=29) or other pathogens (n=54) and uninfected controls (28 healthy and 27 subjects with type 2 diabetes mellitus) were collected. In order to validate the published signature, microarray data were generated from these samples. This dataset was also used for an independent selection of signature for septicemic melioidosis. The same RNA samples were used for validation by a high throughput real-time PCR technique, Fluidigm.

Project description:In cancer management, early and accurate diagnosis of hepatocellular carcinoma (HCC) is important for enhancing survival rate of patients. Currently, serum alpha-fetoprotein (AFP) is the only one biomarker for detection of HCC. However, serum AFP is not satisfactory for diagnosis of HCC due to its low accuracy (about 60-70%). In this study, we collected 109 serum samples (discovery set) from healthy control (HC) and patients with chronic hepatitis B (CHB), liver cirrhosis (LC) and HCC, and analyzed them with custom lncRNA microarray. Profiling analysis shows 181 differentially expressed lncRNAs between HCs and patients with CHB, LC and HCC. Then a 48-lncRNA diagnostic signature was identified with 100% predictive accuracy for all subjects in the discovery set. This diagnostic signature was verified with a cross-validation analysis in the discovery set. To further corroborate the signature, we gathered another 66 serum samples (validation set) and also analyzed them with microarray. The result indicates that the same signature has similar diagnostic accuracy for HC (100%), CHB (73%), LC (88%) and HCC (95%), implying a reproducible diagnostic biomarker for HCC. Receiver operating characteristic (ROC) analysis exhibits that this signature has significantly higher diagnostic accuracy for HCC and non-cancerous subjects (area under curve [AUC]: 0.994) than AFP (AUC: 0.773) in the discovery set and this was also verified in the validation set (0.964 vs 0.792). More importantly, the signature detected small HCC (<3cm) with 100% (13/13) accuracy while AFP with only 61.5% (8/13). Altogether, this study demonstrates that the serum 48-lncRNA signature is not only a powerful and sensitive biomarker for diagnosis of HCC but also a potential biomarker for LC. ***************************************************************** Submitter declares these data are subject to patent number ZL 2016 1 0397094. *****************************************************************

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A Blood Transcriptional Diagnostic Assay for Septicemic Melioidosis

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