Sequence-based RNA Fluorescence Assay to Measure Latent HIV Reservoirs

Jan Biotech, Inc., Ithaca NY

Investigators

Abstract

Project Summary/Abstract Public Health Problem. The CDC estimates that in the U.S., 1,144,500 people aged 13 years and older are living with HIV infection, with approximately 180,900 (15.8%) others infected but undiagnosed. For most HIV-positive individuals, available drugs can only control HIV infection and delay progression to AIDS. HIV cure treatments in active development require validated biomarkers for HIV clearance from infected individuals. Issues with Current Solutions & How Product Meets Unmet Needs. Current methods of quantifying the HIV reservoir include the quantitative viral outgrowth assay (QVOA), PCR and RT-PCR. QVOA is a time and resource intensive procedure while RT-PCR can be used to detect viral RNA to 20-50 virus particles per mL and thus reduces the time to result of QVOA and is generally applicable for measuring viral load, but does not directly detect replication-competent HIV-infected cells. Fluorescence-activated cell sorting (FACS) using combined antibody and probe hybridizations requires multiple steps with significant loss of signal. In Jan Biotech’s assay, all RNA molecules are counted, whereas q and ddPCR are limited by the efficiency of reverse transcription. The capability of Jan Biotech’s sequence-based latent HIV assay to detect down to the single HIV-infected cell level would provide a high throughput, scalable assay critically needed to monitor latent HIV reservoirs. Summary of Approach. Jan Biotech’s assay employs sequence-specific fluorogenic probes with a high signal amplification to directly detect HIV RNA species. It will be evaluated for correlation with RT-ddPCR Transcriptional Profiling and QVOA. A statistical correlation of >0.6 with both comparison assays will be the milestone to move forward to Phase II validation testing and assessment of the predictive value of the assay for time to viral rebound after treatment interruption. Software analytics will be developed and shared open source. Collaborators and Unique Resources. Jan Biotech, Inc., with expertise in molecular diagnostic development, will collaborate with Dr. Steven Yukl, MD, UCSF/SFVAMC, for Transcriptional Profiling, with Michael Busch, MD, PhD, and Mars Stone, PhD, for the use of the RAVEN sample panels, and with Jonathan Li, MD, MMSc Associate Professor of Medicine at Harvard Medical School and Brigham and Women’s Hospital, Harris A. Gelbard, MD, PhD, of University of Rochester Medical School, and John Mellors, MD, of University of Pittsburgh Medical School, for ATCG sample testing. Fast-Track Specific Aims Specific Aim 1 (Phase I): Assay correlation to Transcriptional Profiling and QVOA orthogonal assays Comparison testing will be performed between Jan Biotech’s RNAamp assay and Dr. Yukl’s transcriptional profiling RT-ddPCR assays and QVOA. The Critical Phase I milestone will be a statistical correlation of 0.6 or better of RNAamp to both RT-ddPCR transcriptional profiling or QVOA values. Specific Aim 2 (Phase II): Assay validation using RAVEN Evaluation Panel and QVOA Samples Given successful completion of Phase I comparison testing between RNAamp and RT-ddPCR transcriptional profiling and achievement of the Phase I metric, in Aim 2, Jan Biotech will validate RNAamp using the Reservoir Assay Validation and Evaluation Network (RAVEN) Evaluation Panel. Specific Aim 3 (Phase II): Evaluation of clinical relevance to HIV reservoir activation This Aim will evaluate these novel biomarkers for prediction of time to HIV rebound, which is crucial to prioritize promising treatments to determine those participants likely to benefit from novel HIV remission strategies. Specific Aim 4 (Phase II): Software development and integration for assay analytics In Aim 4, we will build Bayesian software to analyze and share the data from the HIV reservoir RNAamp assay. Market after Phase II Completion. The end result of the project will be a validated sequence-based, quantitative HIV reservoir diagnostic assay and computational software that will enable us to proceed to the FDA approval process, including additional preclinical and clinical evaluation leading towards 510(k) approval, clinical trials, and commercialization of an accurate, high-throughput HIV reservoir assay.