The Pq Laboratory of BiomeDx/Rx

Dx to Rx: The Key to Advancing Precision Medicine

We are dedicated to developing novel, feasible, and reliable technologies to address unmet biomedical needs and life science questions, and to properly translate technological advances to clinical use. Through working at the interface of medicine, biomedical engineering, chemical engineering, and electrical engineering, our interdisciplinary and collaborative team aims to develop next generation disease diagnostics and therapeutics. Specifically, we are interested in integrating microfluidics, biomaterials and appropriate sensing technologies to create all-in-one tools for the isolation and detection of body fluid-based biomarkers, such as circulating tumor cells, extracellular vesicles, cell free nucleic acids, and free proteins/peptides. Ultimately, we hope that by working in close partnership with the cellular/molecular biologist and medical practitioners, we can effectively implement these tools in clinical practice. On the other hand, we are also interested in developing methodologies for targeted cancer therapies such as drug delivery vehicles and oncolytic virus.

Cancer Diagnostics: Extracellular Vesicles and Downstream Analyses

​Extracellular vesicles (EVs) are lipid bilayer-enclosed vesicles with sub-micrometer size that are released by cells. EVs contain a tissue-specific signature wherein a variety of proteins and nucleic acids are selectively packaged. Incontestably, growing evidence has shown important biological roles and clinical relevance of EVs in cancers. In particular, recent studies validate that EV can be used for non-invasive repetitive cancer (early) diagnostics, staging, and treatment monitoring. In previous studies, we confirmed the existence of EV DNA. We found EV DNA represents the entire genome, reflects the mutational status, and show identical copy number variation of parental cells. Compared with cell free DNA (cfDNA, average ~160 bp), EV DNA is relatively intact (average ~15 kbp) due to protection of the lipid envelop against DNase. In our cohort study, KRAS and EGFR mutations were identified from plasma EVs isolated from patients with advanced non-small cell lung cancer (NSCLC) and advanced pancreatic cancer. In a pivotal study, we further demonstrated EV DNA is superior to cfDNA for EGFR mutation detection in stage I/II NSCLC. Currently, we are conducting a clinical trial to investigate the role of EV-DNA in early diagnosis of malignant single pulmonary nodule (MSPN). Through the comprehensive investigation of concordance between EV-DNA and tissue DNA, accumulated mutation burden, and mutation hallmark, we would be able to understand the evolution of MSPN. The potential findings including mutation hallmark and sequencing panel could be translated to clinical use for liquid biopsy of MSPN. To further provide a more powerful diagnostic strategy for patients with MSPN, a deep learning artificial intelligence is under development, which can quickly raise a red flag on patients with high risk of MSPN. Subsequently, physicians would recommend these patients take EV-based liquid biopsy. The combination of medical imaging and molecular detection would significantly improve diagnostic accuracy of MSPN with a five-day turnaround time. In contrast, a definitive diagnosis of MSPN generally takes 3 to 12 months, and it heavily relies on follow-up CT scans. The other ongoing project is focusing on the transcriptome of MSPN and its microenvironment. We observed the immunosuppression of major anti-tumor effector cells, such as T cells, B cells, NK cells, and dendritic cells. Moreover, the dynamic changes of the immune cell composition and their molecular characteristics were analyzed as well. Our findings would shed light on the immune evolution from preneoplasia to invasive lung adenocarcinoma. The transcriptome signature of EVs derived from peripheral immune cells could facilitate MSPN screening and early detection.

Nanomedicine: Extracellular Vesicles and EV-mimicking Liposomes for Cancer Therapeutics

In addition to cancer diagnostics, EVs have also been exploited as drug vehicles for drug delivery. Compared to micelles, liposomes, and polymeric nanoparticles, EVs as a natural delivery system can evade phagocytosis, have extended blood half-life, and exhibit optimal biocompatibility without potential long-term safety issues. EVs can fuse with the cell membrane and deliver drugs directly into the cytoplasm. By evading the engulfment by lysosomes, EVs remarkably enhance the delivery efficiency of vulnerable molecules. Additionally, the small size of EVs facilitates their extravasation, translocation through physical barriers, and passage through the extracellular matrix.

Recently, we developed engineered EVs for tumor-targeted drug delivery, which can be massively prepared by mechanical extrusion or sonication. We also used engineered EVs derived from mesenchymal stem cells to promote soft tissue wound healing and skin rejuvenation. Later, we developed genetically engineered universal EVs for concurrent cancer immune checkpoint therapy and chemotherapy. Currently, we are developing the next generation of therapeutic EVs which can specifically bind to receptors on tumor cell membranes and then deliver drugs to the cytosol via highly efficient membrane fusion. Therefore, unprecedentedly high efficacy would be achieved in cancer therapy. 

Overall, given that clinical-grade EVs for cancer treatment have been produced on a large scale under GMP standards, it is highly possible that our engineered EVs can be translated into clinical use in the future. Our lab already filed two patent applications.

Data Mining: Bioinformatics and Meta Analysis

It is a new research direction in our lab. As a rookie, we tentatively explores big data in order to find new diagnostic biomarkers, search new therapeutic targets, and measure the current therapeutic interventions. We extract, analyze, and interpret published clinical data, such as NGS data, efficacy data on the drug treatment, and epidemiological data. Nevertheless, in our finished and ongoing studies we classified lung adenocarcinoma based on gene mutation and immune phenotypes, found potential therapeutic targets for lung cancer patients, demonstrated the significance of statins in treatment of lung cancer. Indeed, based on our findings we are designing relevant clinical trials to further validate the identified biomarker and target for lung cancer treatment. Moreover, we compared the first-line antifungal prophylaxis drugs and determined voriconazole may be the best option for patients. Other data mining related works are not elaborated here.

News

[2021-09] Guosheng's paper is accepted to be published in Clinical and Translational Medicine (with impact factor of 10+). He reported anti-cholesterol therapy could benefit NSCLC patients with wild-type EGFR and low-expression of PD-L1.

[2021-09] We have received notice-of-awards for an R37 grant (MERIT Award) from NCI entitled "liquid biopsy of solitary pulmonary nodule with extracellular vesicles".

[2021-07] Our technical paper is accepted to be published in Bioactive Materials (with impact factor of 10+). The genetically engineered extracellular vesicles can perform concurrent immunotherapy and chemotherapy.

[2019-10] We are excited to publish our first technical paper in Analytical Chemistry.

[2019-08] Miss. Bordenave won the 2nd Place Poster Presentation with "EVs Derived from Cells Cultured in Artificial Microgravity".

[2019-06] The invited News & Views, Enhanced Detection of Tumor-Secreted Vesicles, was published in Nature Biomedical Engineering

[2019-03] Yi's poster got the 1st Prize Poster Award at UNYTE Un-Meeting at University of Rochester on March 13, 2019.

[2018-08] The Pq Lab of BiomeDx/Rx in Binghamton Univeristy-SUNY was established.