Massively parallel digital high resolution melt for rapid and absolutely quantitative sequence profiling

In clinical diagnostics and pathogen detection, profiling of complex samples for low-level genotypes represents a significant challenge. Advances in speed, sensitivity, and extent of multiplexing of molecular pathogen detection assays are needed to improve patient care. We report the development of an integrated platform enabling the identification of bacterial pathogen DNA sequences in complex samples in less than four hours. The system incorporates a microfluidic chip and instrumentation to accomplish universal PCR amplification, High Resolution Melting (HRM), and machine learning within 20,000 picoliter scale reactions, simultaneously. Clinically relevant concentrations of bacterial DNA molecules are separated by digitization across 20,000 reactions and amplified with universal primers targeting the bacterial 16S gene. Amplification is followed by HRM sequence fingerprinting in all reactions, simultaneously. The resulting bacteria-specific melt curves are identified by Support Vector Machine learning, and individual pathogen loads are quantified. The platform reduces reaction volumes by 99.995% and achieves a greater than 200-fold increase in dynamic range of detection compared to traditional PCR HRM approaches. Type I and II error rates are reduced by 99% and 100% respectively, compared to intercalating dye-based digital PCR (dPCR) methods. This technology could impact a number of quantitative profiling applications, especially infectious disease diagnostics

Prognostic Impact of Modulators of G proteins in Circulating Tumor Cells from Patients with Metastatic Colorectal Cancer

The consequence of a loss of balance between G-protein activation and deactivation in cancers has been interrogated by studying infrequently occurring mutants of trimeric G-protein α-subunits and GPCRs. Prior studies on members of a newly identified family of non-receptor guanine nucleotide exchange factors (GEFs), GIV/Girdin, Daple, NUCB1 and NUCB2 have revealed that GPCR-independent hyperactivation of trimeric G proteins can fuel metastatic progression in a variety of cancers. Here we report that elevated expression of each GEF in circulating tumor cells (CTCs) isolated from the peripheral circulation of patients with metastatic colorectal cancer is associated with a shorter progression-free survival (PFS). The GEFs were stronger prognostic markers than two other markers of cancer progression, S100A4 and MACC1, and clustering of all GEFs together improved the prognostic accuracy of the individual family members; PFS was significantly lower in the high-GEFs versus the low-GEFs groups [H.R = 5, 20 (95% CI; 2,15–12,57)]. Because nucleotide exchange is the rate-limiting step in cyclical activation of G-proteins, the poor prognosis conferred by these GEFs in CTCs implies that hyperactivation of G-protein signaling by these GEFs is an important event during metastatic progression, and may be more frequently encountered than mutations in G-proteins and/or GPCRs