Principal Investigator

Yun
Wu
Awardee Organization

State University Of New York At Buffalo
United States

Fiscal Year
2023
Activity Code
R01
Early Stage Investigator Grants (ESI)
Not Applicable
Project End Date

Lung Cancer Early Detection and Immunotherapy Response Prediction and Monitoring with an Exo-PROS Liquid Biopsy Assay

Lung cancer causes about 25% of all cancer deaths worldwide. Early detection and effective treatment are critical in reducing the mortality. Low-dose computed tomography (CT) is the recommended screening test for lung cancer, however, its high false-positive rate leads to unnecessary biopsy and repeated radiation exposure. Immune checkpoint inhibitors (ICIs) have revolutionized treatment for lung cancer, however, they are only effective for a minority of patients. Predicting and monitoring responses to ICIs by tissue biopsy and imaging are limited by invasive procedure, the lack of effective tumor biomarkers, pseudo progression, and delayed response. Therefore, non-invasive, accurate and affordable methods are urgently needed to detect lung cancer early and to effectively predict and monitor response to ICIs, aiding in improving patient outcomes. Liquid biopsy detects tumor-derived biomarkers in body fluids such as blood, complements imaging and risk factor data, allows sequential monitoring of cancer development, and thus represents a new and non-invasive strategy to address these unmet needs. Exosomes are nano-sized extracellular vesicles secreted by cells. They are actively involved in every step of cancer development and have emerged as promising cancer biomarkers. We hypothesize that tumor-derived exosomes (TEXs) are highly sensitive and specific for lung cancer early detection and treatment response prediction and monitoring, and the combination of TEX markers provides superior diagnostic and predictive performances than single markers alone. A major challenge in developing exosomes-based cancer biomarkers is the separation of TEXs from exosomes released by normal cells, the latter of which can render the test less sensitive or incapable of detecting TEX biomarkers. To overcome this challenge, we have developed an exosome protein RNA one stop (Exo-PROS) biosensor. The Exo-PROS assay first selectively captures TEXs from non-TEXs using canceroverexpressed markers, and then, for the first time, provides one-stop and in-situ quantitation of three types of TEX biomarkers including proteins, microRNAs and carbohydrate antigens. In our pilot study, we demonstrated that combined TEX biomarkers (EGFR, miR-21, LG3BP, miR-210, TF-Ag-α) distinguished lung cancer from normal controls with sensitivity of 1.00 and specificity of 1.00. We also showed that TEX PD-L1, miR-21 and TF-Ag-α successfully predicted the response to anti-PD-1 therapy in lung cancer patients. In this project, we will (1) further develop the Exo-PROS assay and characterize its analytical performances including sensitivity, specificity, linear range and repeatability; (2) determine the diagnostic values of Exo-PROS assay in lung cancer early detection and demonstrate that Exo-PROS assay complements low dose CT and improves the diagnostic accuracy; (3) evaluate Exo-PROS assay in predicting and monitoring response to anti-PD-1 therapy, and demonstrate that Exo-PROS assay is an effective test to complement tissue biopsy and imaging modalities in clinical decision making and patient care.

Publications

  • Hsu CC, Yang Y, Kannisto E, Zeng X, Yu G, Patnaik SK, Dy GK, Reid ME, Gan Q, Wu Y. Simultaneous Detection of Tumor Derived Exosomal Protein-MicroRNA Pairs with an Exo-PROS Biosensor for Cancer Diagnosis. ACS nano. 2023 May 9;17(9):8108-8122. Epub 2023 Apr 27. PMID: 37129374
  • Liu PQ, Miao X, Datta S. Recent Advances in Liquid Metal Photonics: Technologies and Applications. Optical materials express. 2023 Mar 1;13(3):699-727. Epub 2023 Feb 22. PMID: 38249122