Research & Development
NEW BREAKTHROUGH TECHNOLOGY IMMEDIATELY AVAILABLE FOR LICENSING AND JOINT PRODUCT DEVELOPMENT FOR END-USER-DEFINED TARGETED DIAGNOSTIC, PROGNOSTIC, AND IN VIVO SINGLE-CELL IMAGING APPLICATIONS BASED ON DETECTION OF SPECIFIC RNA AND DNA MOLECULES
Technology describes nano-sensors and methods of their design, engineering, and use for detection and discrimination of nucleic acids with a single nucleotide resolution. Best-performing nano-sensors manifest ~200,000-fold enhancement of nano-device’s sensitivity for detection of RNA molecules. World-wide and regional licensing opportunities. US Patent pending. Technology description is available for confidential review upon request (firstname.lastname@example.org; email@example.com).
Recently Issued US Patents
(Up to date list consists of more than 30 applications and is available upon request)
1. US Patent Number 8,349,555 B2
Inventor(s): Gennadi V. Glinskii, M.D., Ph.D.
Title: Methods and compositions for predicting death from cancer and prostate cancer survival using gene expression signatures
Date of Patent: January 08, 2013
2. US Patent Number 7,890,267 B2
Inventor(s): Gennadi V. Glinsky, M.D., Ph.D.
Title: Prognostic and diagnostic methods for cancer therapy
Date of Patent: February 15, 2011
Translational & Functional Genomics Program
Application of genomics to enable practical implementation of the concept of personalized cancer therapy. It is highly desirable to classify cancer patients into high-intensity and low-intensity treatment pools, based on gene expression profiling that predicts aggressive tumor behavior and tumor response to specific chemotherapeutic regimens. Our program is at the forefront of the invention, development, and practical implementation of the concept and principles of the “signature approach” to genome-wide microarray-based gene expression analysis. Our recent work in the mouse/human cross-species translational genomics filed has made a major impact on discovery of the genetic link between “stemness” phenotypes and therapy-resistance phenotypes of human cancer. This discovery facilitated the invention of the gene expression-based cancer therapy outcome predictor (CTOP) algorithm and enabled the retrospective clinical validation of the multi-signature CTOP algorithm for four distinct types of epithelial tumors, including breast, prostate, lung, and ovarian cancers. Prognostic gene signatures that permit therapy outcome classification are derived by algorithms that involve bioinformatics to identify a manageable number of genes of interest that reliably predict clinical behavior of the cancer. We exploited this powerful technique to predict behaviors of multiple human malignancies, including breast and prostate cancer, from an analysis of a panel of about a dozen genes (gene signatures) in tumor specimens from cancer patients with known long-term outcome after therapy. These analytic approaches were derived from tumor banks and retrospective analyses of patient records. We also identified gene expression signatures associated with a “stemness” epigenetic program of embryonic stem cells that appear highly informative in stratification of the early-stage prostate, breast, and lung cancer patients into sub-groups with dramatically distinct likelihood of therapy failure. To date, the retrospective analysis of the prognostic power of individual “stemness” signatures is being extended to more than 3,500 patients diagnosed with 12 distinct types of cancer. Most recently this analysis was extended to discovery of biomarkers suitable for monitoring rare circulating tumor cells at a single cell resolution level. Our inventions are protected by issued patents and pending patent applications.
Application of genomics and related high throughput technologies for identification of genetic and molecular determinants of disease susceptibility and disease predisposition pathways. Recently we initiated an array of novel research projects aimed at investigation of the role of small non-coding RNA (sncRNA) pathways in human diseases. We are exploring the structural-functional relationships of disease-associated SNPs, microRNAs, and transcripts derived from the protein-coding genes in the genomic contexts related to the 24 major human disorders, including Alzheimer’s disease (AD); bipolar disease (BD); rheumatoid arthritis (RA); coronary artery disease (CAD); Crohn's disease (CD); type 1 diabetes (T1D); type 2 diabetes (T2D); obesity (OB); hypertension (HT); ankylosing spondylitis (AS); Graves' disease (autoimmune thyroid disease; AITD); multiple sclerosis (MS); breast cancer (BC); prostate cancer (PC); lung cancer (LC); ovarian cancer (OC); melanoma (MEL); Parkinson’s disease (PD); systemic lupus erythematosus (SLE); vitiligo-associated multiple autoimmune disease (VIT); Huntington?s disease (HD), and ulcerative colitis (UC). Our groundbreaking observations in the area of genomics of common human diseases highlight critically important role of intergenic non-protein-coding regions of human genomes in predisposition to multiple common disorders. Discovery and functional characterization of small non-coding trans-regulatory RNAs (transRNAs) containing intergenic disease-associated SNPs (snpRNAs), which were recently isolated and sequenced in Dr. Glinsky’s laboratory, challenges nearly exclusive, dominant position of the protein-centric dogma in genetic and molecular biology of physiology and pathology of H. sapiens. Dramatic progress in this field is enabling rapid development and translational exploration of genetically-defined color-coded disease predisposition models which are being utilized to carry out robotic screening interfaced with FACS-based indexing to identify small molecule inhibitors of disease-susceptibility pathways Achievement of these milestones would facilitate development and practical implementation of personalized disease chemoprevention programs in targeted high risk populations supported and enabled by efficient point-of-care risk assessment genetic tests.
Most efficient translational exploration of potential practical utility of these discoveries into multitude of clinically-beneficial applications would be greatly enhanced by the convergence with state of the art nanotechnology platforms. One of the most clinically-significant goals which would greatly benefit from the synergistic alliance with implantable chip nanotechnology platform is development of clinically-compatible minimally invasive diagnostic, prognostic, and therapy-selection tests capable of reliably detecting rare events at the micro-scale sensitivity and resolution levels.
Our state-of-the art personalized therapy applications are custom designed based on the GACOR (Gated Access & Controlled On-demand Release) nanotechnology platforms, individual patients genetic and genomic information, and individualized disease models. We use custom-designed RNA-guided diagnostics and therapeutics to improve specificity and decrease toxicity of next-generation nanomedicine. Using these unique for every patient disease models and therapeutic pipelines, therapeutic activity of each specific drug can be verified before administering into patient's body and evidence-based decision can be made whether the individual patient is likely to benefit from the particular treatment.
We are offering a wide range of licensing and collaborative opportunities. Please contact us for details.
GenLight Technologies Corporation, Inc. (GLTCI)