2024 Canary CREST Program Projects

Mentor: Christina Curtis, PhD, MSc

Type of Research: Dry lab

Possible Project:

Recently, we developed a mutation agnostic diagnostic method to detect clonal hematopoiesis of indeterminate potential (CHIP) using whole peripheral blood and fluctuating methylation clocks. We are interested in whether this same technique can be used as a prognostic indicator for the development of therapy-related myeloid neoplasms (tMN) in patients undergoing chemotherapy and/or radiation for a primary malignant disease prior to beginning the course of treatment. We will explore this through a combination of bioinformatics analysis of methylation data, mechanistic mathematical modeling, and statistical analysis to evaluate the usefulness of FMCs as an early detector of tMN risk.

Lab Profile: https://med.stanford.edu/curtislab.html

PIJeremy Dahl, PhD

Type of Research: Combination of wet and dry lab

Possible Project:

Ultrasound molecular imaging (UMI) is a promising tool that can provide noninvasive, non-ionizing, real-time, freehand breast cancer tumor assessment at the point of care. UMI uses targeted ultrasound contrast agents (UCAs) to differentiate between benign and malignant lesions and has the potential to reduce false positive rates and overdiagnosis. However, poor UMI image quality has led researchers to trade the benefits of real-time and freehand imaging for better image quality, resulting in longer exam times, higher UCA dosage, and potentially missed targets.

This project focuses on ultrasound molecular imaging for early cancer detection.  This project is multidisciplinary, involving concepts in ultrasound image reconstruction, data/computer science, microbubble formulation, preclinical cancer models, cancer biomarkers, and protein engineering.  In this project, we are developing a high-sensitivity, high-specificity, ultrasound molecular imaging system that involves real-time non-destructive imaging of targeted microbubbles and the development of clinically viable B7-H3 and PD-L1 targeted microbubbles for cancer detection.  Technical developments on the imaging side include developing a deep learning models to reconstruct molecular imaging signals from noisy raw ultrasound data. The student may be involved in technical tasks such as developing, programming, or executing large-scale physics simulations of ultrasound imaging of cancer-bound microbubbles, developing deep learning models to reconstruct ultrasound molecular images from raw ultrasound data, and perform imaging of preclinical models of breast or kidney cancer.  Computer programming skills (e.g., Python, MATLAB, or julia) are a prerequisite for technical aspects to this project. Students may also engage in microbubble fabrication and design, involving the use of microfluidics systems, protein engineering, phantom fabrication, and other chemistry or life science laboratory skills.

Lab Profile: http://med.stanford.edu/ultrasound

PI: Utkan Demirci, PhD

Type of Research: Combination of wet and dry lab

Possible Project:

The general research in BAMM lab is focused on identifying the exosome derived biosignatures of various cancers, infectious diseases, and brain related diseases. We are exploring the exosomal markers of Alzheimer's, brain tumors, HIV, and COVID-19 diseases to bioengineer new diagnostic optical technologies. We do translational research by combining engineering, medicine, and biology know-how to address the important clinical challenges using spectroscopy, proteomics, and genomics techniques. Based on their interest, the intern will be involved in biology and/or engineering aspects of the project and learn the main exosome isolation, characterization, detection techniques and/or mass and Raman spectroscopy data collection and analysis techniques using machine learning. The intern is expected to provide intellectual contribution to their project of interest and will be mentored to learn basic research principles as well as dry and wet lab procedures.

Lab Profile: https://bammlabs.stanford.edu/people/dr-utkan-demirci

PIGozde Durmus, PhD

Type of Research: Combination of wet and dry lab

Possible Project:

Capturing and Subtyping of Exosomes from Plasma Using Microfluidic Magnetic Levitation: Exosomes, extracellular vesicles in the size of 30-150 nm, can carry molecules that are essential for cell-to-cell communication, including DNA, RNA, and metabolites. Tumor cells are thought to secrete exosomes into bodily fluids such as plasma to facilitate angiogenesis and metastasis, and to make space for migration and proliferation while deactivating tumor suppressors. However, their small size makes the isolation and subtyping of exosomes extremely difficult using traditional methods. A simple method of isolating and subtyping exosomes will be beneficial to better understand disease progression and identify tumor-associated biomarkers. In this project, we will develop a rapid, cost-effective, and straightforward method to capture and subtype exosomes from plasma. We will develop a multiplexed subtyping platform where the beads decorated with antibodies will act as mobile assay surfaces for each subtype when mixed with plasma. The beads of different subtypes will be sorted out at different outlets with the microfluidic magnetic levitation platform and subjected to downstream analysis for further characterization.

Lab Profile: https://gdurmus.people.stanford.edu/

PI: Olivier Gevaert, PhD

Type of Research: Dry lab

Possible Project:

My lab focuses on biomedical data fusion: the development of machine learning methods for biomedical decision support using multi-scale biomedical data. Previously we pioneered data fusion work using Bayesian and kernel methods studying breast and ovarian cancer. Additionally, we developed computational algorithms for the identification of driver genes using multi-omics data. Furthermore, we are working on multi-scale biomedical data fusion methods, bridging the molecular using omics data, cellular using pathology data and tissue using medical imaging data.

Lab Profile: http://med.stanford.edu/gevaertlab.html

Instructor: Sharon Hori, PhD  

Type of Research: Combination of wet and dry lab

Possible Project:

Most cancers can be more effectively treated if they are discovered early. The Hori Lab is improving the detection of early-stage cancers using secreted cancer-specific biomarkers, which are proteins or other molecules released from tumor cells into the blood. The purpose of this internship is to learn to develop innovative strategies to detect small, early-stage cancers from a routine blood sample. This involves learning how to design and conduct molecular and cellular biology experiments, utilize novel molecular imaging techniques, and integrate these experimental results with computational models to study the relationship between a growing tumor and the amount of biomarker it secretes. Cancers of the prostate, lung, breast, pancreas and colon will be the primary focus.

The applicant should be highly motivated with a basic background in molecular/cellular biology and/or mathematics (single-variable calculus), and have a strong desire to learn and integrate biological and computational modeling techniques. Computer programming, mathematical modeling, and machine learning skills are preferred but not required. The student may have the opportunity to learn how to culture cancer cells, perform assays to assess cell viability and measure secreted biomarker levels, image live cancer cells using fluorescence and bioluminescence techniques, study cell properties using flow cytometry, develop basic mathematical/computational models for tumor growth and biomarker secretion, and/or use mathematical modeling and machine learning approaches to make predictions about cancer presence and aggressiveness. This summer research program will provide a unique opportunity to gain hands-on experience in biological and computational research, and is ideal for students interested in cancer research, molecular/cellular biology, medicine, anatomy/physiology, computational and systems biology, computer science, biomedical engineering and related fields. Minimum 40 hr/week required.

PI: Ramasamy Paulmurugan, PhD

Type of Laboratory Research: Combination of wet and dry lab

Possible Projects:

Cellular Pathway Imaging Laboratory (CPIL):

Our research group focuses on developing new imaging assays for studying cellular signal transduction networks in cancer and cellular other diseases. Specifically, we apply our extensive experience in molecular biology to develop several in vivo imaging assays for monitoring basic cellular processes and post-translational modifications of proteins, such as methylation, phosphorylation, sumoylation, and many more. We have developed split-reporter protein complementation systems for various reporter proteins (luciferases, fluorescent proteins, and thymidine kinase) and use them for designing various sensors to study cellular signaling processes. Some of the main applications of these assays include imaging the tumor microenvironment, as well as immune cytokine signaling in cancer and infectious diseases. Other applications where we are currently applying these assays include studying protein-protein interactions involved in estrogen receptor signaling, Nrf2-mediated antioxidant signaling in chemoresistance, p53-sumoylation mediated chemotherapy responses in cancer, NFkB mediated cytokine signaling in cancer, and signaling mechanisms associated with APP and Tau protein sumoylations in Alzheimer’s disease.

In cancer therapy, we are establishing microRNA-based reprogramming approaches to sensitizing drug-resistant cancers (breast cancer, hepatocellular carcinoma, and glioma) to commonly used chemotherapies. We mainly target oncogenic and tumor suppressor microRNAs (miR-21, miR-10b, miR-122, and miR-100) that are dysregulated in cancers to improve cancer therapy. To deliver intact miRNAs in vivo, we load miRNAs in PLGA-PEG nanoparticles and use ultrasound-microbubble (US-MB) triggered drug delivery strategies for locoregional enhancement of microRNAs in the tumor bed to improve cancer therapy. We evaluate miRNA delivery strategies in small animal models (mice and rats) and optimize US parameters (cavitation, PRF, mechanical energy, and delivery efficiency) in large animal models (pigs and dogs) to address clinical translational feasibilities. We have shown tremendous progress in this area of research with a number of publications in high impact journals. We recently identified five sense and antisense miRNAs (miR-203, miR-218, antimiR-10b, antimiR-19b, and antimiR-21) through a rigorous analysis of miRNA expression data available in TCGA (GDC) and GEO using a biological basis-driven workflow, where these microRNAs target multiple hallmarks of cancer to improve chemo- and immunotherapies in cancer.

In synthetic biology, we recently invented the application of high-pressure microfluidic system in the reconstruction of biomolecules derived from cells (proteins and lipids) along with synthetic sources (phospholipids, polymers, and surfactants) to develop self-assembled nano- and micro-structures that mimic biological membranes for drug delivery applications. As part of this process, we developed biomimetic microbubbles (biMBs) and nanobubbles (biNBs) using tumor cell derived exosomes (TDEs) for cancer immunotherapy applications. In this grant, we apply this novel technology to exploit the natural accumulation of biMBs in the immune organs (LNs, lungs, and spleen) while TDE -targeted biNBs accumulation in the tumor to achieve cancer immunotherapy.

In addition, we also work on developing novel intranasal vaccine for Covid-19 and other respiratory diseases. As part of this project, we have developed gold nanostar-coated DNA vaccine for SARS-CoV2 disease by activating mucosal immunity. We also extend this platform delivery system for lung cancer gene therapy applications using suicide gene therapy along tumor suppressor microRNAs as a combination treatment.

Specific Research Topics of the lab:

  • Developing multiplex-imaging assays to simultaneously measure histone methylations in various lysine marks of histone proteins (H3K9, H3K27, H3K36, H3K79, and H4K20).
  • Developing FDA approved polymer nanoparticles to co-deliver therapeutic sense- and antisense- microRNAs for cancer therapy.
  • Studying estrogen receptor (ER) α and β cross-talk in breast cancer.
  • Nrf2-Keap1 antioxidant mechanism in drug resistance and chemotherapy in cancers.
  • Studying the stemness of cancer cells and cancer stem cells in cancer and targeting Wnt-Beta catenin and NFkB-Nrf2 signaling to improve cancer chemotherapy.
  • Covid-19 intranasal vaccine for controlling different variants of SARS-CoV2.
  • Ultrasound-Microbubble mediated targeted delivery of cancer therapies (MicroRNAs and Biomimetic immunotherapies).


Lab Profile: https://med.stanford.edu/mips/research/cpil.html

PI: Sharon Pitteri, PhD

Type of Research: Combination of wet and dry lab

Possible Project:

The Pitteri Laboratory is focused on the discovery and validation of proteins and other types of molecules in the blood that can be used as indicators of risk, diagnosis, progression, and recurrence of cancer. We specialize in molecular analysis of clinical and biological samples to detect cancer and understand biology. We utilize state-of-the art technologies including liquid chromatography and mass spectrometry to identify, quantify, and characterize proteins and other molecules of interest.

We are looking for highly motivated undergraduate students looking for an opportunity to work on a summer research project focused on cancer early detection. The Canary CREST program is well-suited for students with interests in chemistry, biochemistry, biology, applied physical science, and/or medical research. You will gain hands-on experience with biochemistry and analytical chemistry techniques, and data analysis. Possible projects include analysis of clinical samples and/or cancer cell lines. A positive attitude, willingness to learn and contribute, and meticulous attention to details are a must.

Lab Profile: http://med.stanford.edu/pitterilab/lab-members.html