SUMMARY RNA-binding proteins (RBPs) play critical roles in regulating gene expression by modulating splicing, RNA stability, and protein translation. Stimulus-induced alterations in RBP function contribute to global changes in gene expression, but identifying which RBPs are responsible for the observed changes remains an unmet need. Here, we present Transite, a computational approach that systematically infers RBPs influencing gene expression through changes in RNA stability and degradation. As a proof of principle, we apply Transite to RNA expression data from human patients with non-small-cell lung cancer whose tumors were sampled at diagnosis or after recurrence following treatment with platinum-based chemotherapy. Transite implicates known RBP regulators of the DNA damage response and identifies hnRNPC as a new modulator of chemotherapeutic resistance, which we subsequently validated experimentally. Transite serves as a framework for the identification of RBPs that drive cell-state transitions and adds additional value to the vast collection of publicly available gene expression datasets.

RNAi approaches have been widely combined with platinum-based anticancer agents to elucidate cellular responses and to target gene products that mediate acquired resistance. Recent work has demonstrated that platination of siRNA prior to transfection may negatively influence RNAi efficiency based on the position and sequence of its guanosine nucleosides. Here, we used detailed spectroscopic characterization to demonstrate rapid formation of Pt-guanosine adducts within 30 min after coincubation of oxaliplatin [OxaPt(II)] or cisplatin [CisPt(II)] with either guanosine monophosphate or B-cell lymphoma 2 (BCL-2) siRNA. After 3 h of exposure to these platinum(II) agents, >50% of BCL-2 siRNA transcripts were platinated and unable to effectively suppress mRNA levels. Platinum(IV) analogues [OxaPt(IV) or CisPt(IV)] did not form Pt-siRNA adducts but did display decreased in vitro uptake and reduced potency. To overcome these challenges, we utilized biodegradable methoxyl-poly(ethylene glycol)-block-poly(ε-caprolactone)-block-poly(l-lysine) (mPEG-b-PCL-b-PLL) to generate self-assembled micelles that covalently conjugated OxaPt(IV) and/or electrostatically complexed siRNA. We then compared multiple strategies by which to combine BCL-2 siRNA with either OxaPt(II) or OxaPt(IV). Overall, we determined that the concentrations of siRNA (nM) and platinum(II)-based anticancer agents (μM) that are typically used for in vitro experiments led to rapid Pt-siRNA adduct formation and ineffective RNAi. Coincorporation of BCL-2 siRNA and platinum(IV) analogues in a single micelle enabled maximal suppression of BCL-2 mRNA levels (to <10% of baseline), augmented the intracellular levels of platinum (by ∼4×) and the numbers of resultant Pt-DNA adducts (by >5×), increased the cellular fractions that underwent apoptosis (by ∼4×), and enhanced the in vitro antiproliferative activity of the corresponding platinum(II) agent (by 10-100×, depending on the cancer cell line). When combining RNAi and platinum-based anticancer agents, this generalizable strategy may be adopted to maximize synergy during screening or for therapeutic delivery.

RNA-binding proteins (RBPs) play critical roles in regulating gene expression by modulating splicing, RNA stability, and protein translation. In response to various stimuli, alterations in RBP function contribute to global changes in gene expression, but identifying which specific RBPs are responsible for the observed changes in gene expression patterns remains an unmet need. Here, we present Transite a multipronged computational approach that systematically infers RBPs influencing gene expression changes through alterations in RNA stability and degradation. As a proof of principle, we applied Transite to public RNA expression data from human patients with non-small cell lung cancer whose tumors were sampled at diagnosis, or after recurrence following treatment with platinum-based chemotherapy. Transite implicated known RBP regulators of the DNA damage response and identified hnRNPC as a new modulator of chemotherapeutic resistance, which we subsequently validated experimentally. Transite serves as a generalizable framework for the identification of RBPs responsible for gene expression changes that drive cell-state transitions and adds additional value to the vast wealth of publicly-available gene expression data.

Objective: Trauma-induced coagulopathy (TIC) is provoked by multiple mechanisms and is perceived to be one driver of massive transfusions (MT). Single laboratory values using prothrombin time (INR) or thrombelastography (TEG) are used to clinically define this complex process. We used a proteomics approach to test whether current definitions of TIC (INR, TEG, or clinical judgment) are sufficient to capture the majority of protein changes associated with MT. Methods: Eight level I trauma centers contributed blood samples from patients available early after injury. TIC was defined as INR >1.5 (INR-TIC), TEG maximum amplitude <50 mm (TEG-TIC), or clinical judgment (Clin-TIC) by the trauma surgeon. MT was defined as >10 units of red blood cells in 24 hours or >4 units RBC/hour during the first 4 hours. SomaLogic proteomic analysis of 1305 proteins was performed. Pathways associated with proteins dysregulated in patients with each TIC definition and MT were identified. Results: Patients (n = 211) had a mean injury severity score of 24, with a MT and mortality rate of 22% and 12%, respectively. We identified 578 SOMAscan analytes dysregulated among MT patients, of which INR-TIC, TEG-TIC, and Clin-TIC patients showed dysregulation only in 25%, 3%, and 4% of these, respectively. TIC definitions jointly failed to show changes in 73% of the protein levels associated with MT, and failed to identify 26% of patients that received a massive transfusion. INR-TIC and TEG-TIC patients showed dysregulation of proteins significantly associated with complement activity. Proteins dysregulated in Clin-TIC or massive transfusion patients were not significantly associated with any pathway. Conclusion: These data indicate there are unexplored opportunities to identify patients at risk for massive bleeding. Only a small subset of proteins that are dysregulated in patients receiving MT are statistically significantly dysregulated among patients whose TIC is defined based solely on laboratory measurements or clinical assessment.