Neural network-derived multivariate index assay demonstrates effective clinical performance in longitudinal monitoring of ovarian cancer risk.

OBJECTIVE: We recently characterized the clinical performance of a multivariate index assay (MIA3G) to assess ovarian cancer risk for adnexal masses at initial presentation. This study evaluated how MIA3G varies when applied longitudinally to monitor risk during clinical follow-up. METHOD: The study evaluated women presenting with adnexal masses from eleven centers across the US. Patients received an initial blood draw at enrollment and at the standard-of-care follow-up visits. MIA3G was determined for all visits but physicians did not have access to MIA3G scores to determine clinical management. The primary outcome was the relative change value (RCV) of MIA3G over the period of clinical observation. RESULTS: A total of 510 patients of 785 enrolled met study criteria. Of these, 30.8% had a second, 25.4% a third and 22.2% a fourth blood draw following initial collection. The median duration from initial draw was 131 d to second draw, 301.5 d to the third draw and 365.5 d to the fourth draw. MIA3G RCV of >50% was observed in 22-26% patients, whereas 70-75% patients had MIA3G RCV >5%. An empirical baseline RCV of 56% - transformed to 1 in logarithmic scale - was calculated from averaging RCVs of all patients who had no malignancy risk after 210 days. RCV > 1 log was associated with higher incidence of surgical intervention (29.6%) compared to RCV < 1 log (16.9%). CONCLUSIONS: Variation in MI3AG does not change the accuracy of the test for excluding malignancy, while marked changes may be associated with a slightly higher likelihood of surgical intervention. In addition to MIA3G score itself, the MIA3G RCV may be important for clinical management.

Ovarian Cancer surgical consideration is markedly improved by the neural network powered-MIA3G multivariate index assay.

Background: Surgery remains the main treatment option for an adnexal mass suspicious of ovarian cancer. The malignancy rate is, however, only 10-15% in women undergoing surgery. This results in a high number of unnecessary surgeries. A surveillance-based approach is recommended to form the basis for surgical referrals. We have previously reported the clinical performance of MIA3G, a deep neural network-based algorithm, for assessing ovarian cancer risk. In this study, we show that MIA3G markedly improves the surgical selection for women presenting with adnexal masses. Methods: MIA3G employs seven serum biomarkers, patient age, and menopausal status. Serum samples were collected from 785 women (IQR: 39-55 years) across 12 centers that presented with adnexal masses. MIA3G risk scores were calculated for all subjects in this cohort. Physicians had no access to the MIA3G risk score when deciding upon a surgical referral. The performance of MIA3G for surgery referral was compared to clinical and surgical outcomes. MIA3G was also tested in an independent cohort comprising 29 women across 14 study sites, in which the physicians had access to and utilized MIA3G prior to surgical consideration. Results: When compared to the actual number of surgeries (n = 207), referrals based on the MIA3G score would have reduced surgeries by 62% (n = 79). The reduction was higher in premenopausal patients (77%) and in patients ≤55 years old (70%). In addition, a 431% improvement in malignancy prediction would have been observed if physicians had utilized MIA3G scores for surgery selection. The accuracy of MIA3G referral was 90.00% (CI 87.89-92.11), while only 9.18% accuracy was observed when the MIA3G score was not used. These results were corroborated in an independent multi-site study of 29 patients in which the physicians utilized MIA3G in surgical consideration. The surgery reduction was 87% in this cohort. Moreover, the accuracy and concordance of MIA3G in this independent cohort were each 96.55%. Conclusion: These findings demonstrate that MIA3G markedly augments the physician's decisions for surgical intervention and improves malignancy prediction in women presenting with adnexal masses. MIA3G utilization as a clinical diagnostic tool might help reduce unnecessary surgeries.

Restoring and Enhancing the Potency of Existing Antibiotics against Drug-Resistant Gram-Negative Bacteria through the Development of Potent Small-Molecule Adjuvants.

The rapid and persistent emergence of drug-resistant bacteria poses a looming public health crisis. The possible task of developing new sets of antibiotics to replenish the existing ones is daunting to say the least. Searching for adjuvants that restore or even enhance the potency of existing antibiotics against drug-resistant strains of bacteria represents a practical and cost-effective approach. Herein, we describe the discovery of potent adjuvants that extend the antimicrobial spectrum of existing antibiotics and restore their effectiveness toward drug-resistant strains including mcr-1-expressing strains. From a library of cationic compounds, MD-100, which has a diamidine core structure, was identified as a potent antibiotic adjuvant against Gram-negative bacteria. Further optimization efforts including the synthesis of ∼20 compounds through medicinal chemistry work led to the discovery of a much more potent compound MD-124. MD-124 was shown to sensitize various Gram-negative bacterial species and strains, including multidrug resistant pathogens, toward existing antibiotics with diverse mechanisms of action. We further demonstrated the efficacy of MD-124 in an ex vivo skin infection model and in an in vivo murine systemic infection model using both wild-type and drug-resistant Escherichia coli strains. MD-124 functions through selective permeabilization of the outer membrane of Gram-negative bacteria. Importantly, bacteria exhibited low-resistance frequency toward MD-124. In-depth computational investigations of MD-124 binding to the bacterial outer membrane using equilibrium and steered molecular dynamics simulations revealed key structural features for favorable interactions. The very potent nature of such adjuvants distinguishes them as very useful leads for future drug development in combating bacterial drug resistance.

Toward Hydrogen Sulfide Based Therapeutics: Critical Drug Delivery and Developability Issues.

Hydrogen sulfide (H2 S), together with nitric oxide (NO) and carbon monoxide (CO), belongs to the gasotransmitter family and plays important roles in mammals as a signaling molecule. Many studies have also shown the various therapeutic effects of H2 S, which include protection against myocardial ischemia injury, cytoprotection against oxidative stress, mediation of neurotransmission, inhibition of insulin signaling, regulation of inflammation, inhibition of the hypoxia-inducible pathway, and dilation of blood vessels. One major challenge in the development of H2 S-based therapeutics is its delivery. In this manuscript, we assess the various drug delivery strategies in the context of being used research tools and eventual developability as therapeutic agents.