The partnership facilitates and supports collaborative research projects between CCNY and MSKCC investigators. The partnership has a robust translational portfolio research in health disparities, biomedical engineering, computer science/medical imaging, and basic science research.
U54 Funded Projects
PIs: David Rumschitzki (CCNY) / Richard White (MSK)
How Tumor Ensemble Models with Two Experimental Models Predict Tumor Dormancy & Reactivation in Cancers with Gender and/or Ethnic Disparities
The project posits a new type (population balance) of mathematical model for the dynamics of a large ensemble (from one or many patients) of tumors of all sizes subject to mitosis, cell death (immunity, chemo or immunotherapy, necrosis, etc.) and metastasis…. This proposal intimately integrates this new mathematical model with the BALB/c murine breast cancer and the clear, stripeless zebrafish melanoma systems that both allow live non-invasive monitoring of tumor numbers and sizes as a function of time without animal sacrifice. Our model fits existing human hepatocellular carcinoma and immune-suppressed & competent fish melanoma data extremely well with only 3 parameters. The investigators plan new fish experiments to control/tune the level of immunity so as to access and test parameters predicted to yield dormancy and recurrence. They will carry out detailed experiments on the mouse breast cancer system, which may exhibit dormancy & recurrence naturally, and use it to test our model. They will also attempt to modulate its immunity to access and test parameters predicted to yield dormancy & recurrence. Since these cancers show both ethnic and gender disparities, they will use melanoma cell with snps that recapitulate ethnicity-specific genetics and segregate (fish) data by gender so as to see if parameters show ethnic and/or gender specificity; this would carry over to dormancy and recurrence. Time and funds permitting, the investigators will look at the effect of tumor shape on its parameters’ tumor size dependences.
Specific aims of the proposal are:
1. Modulate (with steroids) zebrafish immunity to adjust its tumor growth & regression parameter balance into a model-predicted dormancy and recurrence (d&r) regime. They have tested our model on male and female immune competent and fully suppressed fish and found excellent model agreement; strong gender differences only for fish immunity parameters; and a fish immune system too strong to admit recurrence. Modulating its immune response, by combining chemotherapy and/or partial immune suppression, to a model-predicted recurrence regime will allow the investigators to test this model prediction, to potentially create the first unambiguous animal model for cancer d&r and to predict & test time to recurrence (t → r).
2. Carry out similar experiments on immune-compromised and -competent BALB/c mice with triple-negative breast cancer to find model parameters with natural and suppressed immunity, chemotherapy, e.g., doxorubicin, paclitaxel, 5-FU, etc., and immunity+chemo; to predict disease progression for these parameters and various initial tumor size distributions. To predict and achieve parameter values that indicate d&r, to realize them and to test for predicted d&r.
3. Repeat SA1 experiments with tumor cell lines that recapitulate aspects of ethnicity- specific genetic traits; to see if these data imply ethnicity- and/or gender specific model parameters; if so, to use them to find testable ethnicity-specific difference predictions as in SA1 for d&r and t → r; and to test them.
PIs: Bao Vuong (CCNY) / Jayanta Chaudhuri (MSK):
Characterizing the Role of ATM and MSH2 in Genome Stability
Cancer cells have mutations that alter when they will grow and die. The cells acquire these mutations through DNA damage. Normally, when a cell experiences DNA damage, DNA repair proteins are recruited to correct the damaged or mutated DNA. If the damage is not corrected, a cell death pathway is activated that kills the cell. However, mistakes in the DNA damage response can occur, resulting in the survival of cells with mutated DNA that can give rise to cancer. People who are born with mutations in genes involved in DNA repair are predisposed to developing cancer and many people not born with these mutations who develop cancer have been found to have acquired mutations in DNA repair genes in their tumors. To study how cells repair DNA damage, the investigators use mouse B cells as a model system. To generate antibodies that recognize and eliminate pathogens, B cells are genetically programmed to mutate and delete antibody coding genes. The B cells carefully coordinate their DNA damage and DNA repair pathways to avoid triggering a cell death pathway. ATM (ataxia telangiectasia mutated) and MSH2 (MutS homologue 2) are proteins that are essential for two distinct DNA repair pathways. Mice engineered to lack either ATM or MSH2 display defects in antibody production and have a similar cancer predisposition as people born with mutations in these DNA repair genes. However, mice that lack both ATM and MSH2 are not viable (unpublished data). The investigators hypothesize that the combined loss of ATM and MSH2 causes the accumulation of genomic DNA damage that prevents mouse development. They propose experiments to characterize the mechanism by which ATM and MSH2 cooperatively regulate genome stability and experiments to determine if these unique molecular pathways can be exploited therapeutically in cancer.
PIs: Robert Alfano (CCNY) / Jason Koutcher (MSK)
Early Detection of Breast Cancer Subtypes by Raman Spectroscopy with Heavy Water Labeling and MultiPhoton Microscopy
The goals of the project are to are to use resonance Raman spectroscopy (RRS) and heavy water labeling as a metabolic fingerprinting tool to distinguish different subtypes of breast cancer, and to use multiphoton fluorescence microscopy to detect native fluorescence signals from critical metabolic molecules (collagen, tryptophan, NADH, flavin, etc.) in aggressive and less aggressive tumors. We will further explore the mechanism for the differences in metabolism by studying tumor metabolism by in vivo measurements of glycolytic changes, a critical metabolic pathway in tumors, and tumor perfusion. The latter is critical since changes in perfusion will lead to alterations in nutrient and oxygen delivery which will alter tumor metabolism (balance between glycolysis and oxidative phosphorylation) and may explain differences in the resonance Raman spectra and multiphoton microscopy that occur between different tumor models. This collaborative effort is scientifically sound since the data derived at each institution is complementary and critical to addressing the issue of detecting breast tumors by optical techniques, and understanding the mechanism behind these findings.
PIs: Susannah Fritton (CCNY) / John Healey (MSK)
Development of Mechanical Interventions to Enhance Drug Delivery to Bone Tumors
The objective of this study is to develop and validate clinically translatable mechanical interventions that can be used to enhance drug delivery to cancerous bone tumors. In preliminary work, the City College of New York (CCNY) and Memorial Sloan Kettering Cancer Center (MSKCC) investigative team has demonstrated that delivery of an intravenous drug can be significantly enhanced in mechanically loaded tumor-bearing rat tibiae. Based on the promising preliminary results, this study will collect important pre-clinical data that will test two different mechanical interventions in a rat model and then translate the results to develop a clinical protocol to enhance drug delivery to bone tumors. Two different approaches of applying mechanical intervention will be used to enhance tumor drug delivery in a rat model of metastatic bone cancer to assess their potential applicability to human patients.
Specific Aim 1 will simulate how exercise would be used in the clinic to enhance drug delivery to bone tumors.
Specific Aim 2 will utilize very low-magnitude mechanical vibration that could also be delivered easily in a clinical setting.
Specific Aim 3 will build upon the findings from the pre- clinical rat studies to design a clinical IRB protocol that would target patients most likely to benefit from mechanical intervention during cancer drug administration. The long-term goal of this work is to establish a clinical treatment that uses load-bearing exercise or low-intensity vibration to enhance tumor delivery of therapeutic drugs. This low-risk and easy-to-implement approach may enhance a drug’s uptake and therapeutic effect in the most clinically relevant skeletal areas while potentially decreasing systemic drug dosage and unwanted side effects.
PIs: Deidre Anglin (CCNY) / Rosario Costas-Muñiz (MSK) / Wendy Lichtenthal (MSK)
Cultural Adaptation of EMPOWER for Latinx Family Caregivers in Intensive Care Units in the Context of COVID-19
The Bronx, NY, home to one of the poorest congressional districts in the nation and the largest percentage of non-Whites (91% racial and ethnic minorities), has the highest death rate in NY due to COVID-19 (274.49 per 100,000). This project aims to examine the mental health impact of the coronavirus pandemic and the degree to which cancer-promoting health risk behaviors have increased among Black and Latinx adolescents and their parents/caregivers in the Bronx, New York. Specifically, it will examine how the collective trauma and losses from this pandemic influenced minority-related stress, psychological distress (i.e., stress sensitivity), post-traumatic symptoms (i.e., anxiety, depression), and cancer-related lifestyle risk behaviors (i.e., smoking/vaping, substance and alcohol abuse, unhealthy eating habits, physical inactivity) among Black and Latinx youth and their parents. Using a mixed-methods design, the project aims to capture the extent to which living in a community with substantial social and economic inequities has shaped the psychological impact of the coronavirus pandemic and risk for unhealthy behaviors linked to cancer. Using Photovoice, a qualitative method that uses photos to reflect personal and community strengths and challenges, and quantitative measures of mental health functioning and health-risk behaviors, the team aims to give voice to the collective trauma and loss and its sequelae, as well as indicators of resilience that occur through parental support and coping and community-level supports. The findings will inform the construction of future multilevel, intergenerational interventions designed to improve psychological health and reduce cancer risk in vulnerable and underserved communities.
PIs: Lucas Parra (CCNY) / Sarah Eskreis-Winkler (MSK)
Precision Medicine Using Racially-Unbiased Artificial Intelligence to Optimize the Use of Preoperative Breast MRI and Reduce Disparities in Outcomes
The long-term goal of this project is to develop and clinically implement an objective data-driven tool to optimize the use of preoperative MRIs to decrease unnecessary healthcare costs and reduce healthcare disparities. Although over 300,000 women are diagnosed and treated for breast cancer each year, there are still significant gaps in knowledge about which groups of patients will benefit from a breast MRI as part of their cancer workup. In 85 percent of breast cancer patients referred for preoperative MRI, MRI does not change management, and only increases medical costs, anxiety, unnecessary biopsies and time to surgery. But we do not know, a priori, in which cases the MRI will be helpful. As a result, practice patterns vary and are subjective. Black women are more likely to have positive margins at surgery compared to white
women and therefore are more likely to potentially benefit from preoperative MRI, and yet they are less likely to receive preoperative MRI compared to white women. There is, therefore, an urgent unmet clinical need for a racially-unbiased data-driven tool to optimize use of preoperative MRIs to decrease unnecessary healthcare costs and reduce healthcare disparities.
We hypothesize that the mammogram itself, along with clinical data, can predict the likelihood that a subsequent MRI will reveal additional disease. To test this hypothesis, we will leverage our MSK breast imaging dataset of ~6,000 mammograms and preoperative MRIs from recently diagnosed breast cancer patients.
Aim 1: Establish the healthcare costs and healthcare disparities that occur due to suboptimal use of preoperative breast MRI. We will establish the significance of this problem by calculating the healthcare costs and will test the hypothesis that preoperative MRI is underutilized in some racial groups more than others. We will not assume that preoperative MRI rates should be the same across racial groups but instead seek to develop a new metric to optimize preoperative MRI rates in a race-specific way.
Aim 2: Build an automatic racially unbiased breast MRI recommendation system based on mammograms, clinical and demographic information. We will build a deep learning-based recommendation system to predict which newly diagnosed breast cancer patients would benefit from preoperative MRI. We will test the hypothesis that mammograms carry information about not only mammographically-visible cancers, but about cancer occult to the human eye (traditionally seen only on MRI). To ensure a racially-unbiased model, we will evaluate performance with racial subgroup testing and do focused retraining to correct any disparities in performance prior to final network testing.
Aim 3: Compare performance of breast MRI automatic recommendation system to current standard of care referral patterns. We will evaluate whether the model developed in Aim 2 is better than current methods at optimizing preoperative MRI use. We will perform subgroup analysis across racial subgroups.
PIs: Ryan Williams (CCNY) / Dianna Ng (MSK)
Rapid Diagnostic Evaluation of Estrogen Receptor Status in Fine Needle Aspiration Biopsies
Breast cancer outcomes are disproportionately poor in low- and middle-income countries (LMICs) compared to high-income countries. Low breast cancer survival rates in LMICs are primarily attributable to advanced stage presentation and limited diagnostic and treatment capacity. Although national clinical practice guidelines for breast cancer in Tanzania recommend that all breast cancer patients receive estrogen receptor (ER) testing, current pathology capacity is unable to meet this need. Pathologic diagnosis, including ER testing, is critical to determining the presence of cancer, extent of the disease, and planning treatment. However, ER testing is currently expensive, requires highly trained technical personnel, and not widely available. As a result, only a subset of eligible women receiving ER testing, with long turnaround times, and only a few receive life-prolonging, affordable, and widely available endocrine therapy.
To reduce this evidence-to-practice gap, we propose to develop rapid, inexpensive optical nanosensors that interrogate the estrogen receptor status of cells in fine needle aspirate biopsies (FNAB). First, we will design a fluorescent single-walled carbon nanotube sensor that quantifies the presence of ER using in vitro ER-positive breast cancer cell lines. Then, we will evaluate the function of the ER nanosensor in FNABs obtained from clinical mastectomy samples. Parallel validation of ER status and disease state will be performed via conventional testing.
We hypothesize that the development of this technology has the potential to increase the proportion of patients who are able to receive ER testing and guideline-concordant endocrine therapy, resulting in improved cancer care, quality of life, and overall short term survival of patients.
- Full: Gerardo Blumenkrantz (CCNY) / Abraham Aragones (MSK): Social Marketing and Technology to Increase HPV Vaccination Rates Among Mexican American Children: A Randomized Controlled Trial
- Full: Marom Bikson (CCNY) / Prasad Adusumilli (MSK): Preclinical Evaluation, Clinical Trial Preparation, and a Prospective Clinical Trail of Intraoperative Real-time Tissue Oxygenation Monitoring by Wireless Pulse Oximetry (WiPOX)
- Full: Bao Vuong (CCNY) / Jayanta Chaudhuri (MSK): Molecular Function of ATM in Class Switch Recombination
- Full: Marom Bikson (CCNY) / Govindarajan Srimathveeravalli (MSK): Framework for Non-Invasive Low Voltage Electroporation for Drug and Gene Delivery to Brain Tumors
- Pilot: Jie Wei (CCNY) / Guang Li (MSK): Developing an Accurate and Reliable Method for Tumor Motion Monitoring
- Pilot: Tiffany Floyd (CCNY) / Katherine DuHamel (MSK): Salon-Based Intervention to Promote Colonoscopy Screening among African-American Women
- Pilot: Sihong Wang (CCNY) / Sihong Jiang (MSK) / Carlos Meriles (CCNY): Differentiating Cancer Cells by their Thermal Properties via NV Centers in Nanodiamonds
- Pilot: Pengfei Zhang (CCNY) / Jennifer Leng (MSK): TaxI Particulate matter Study (TIPS)
- Pilot: David Rumschitzki (CCNY) / Richard White (MSK): Theory & Experiment for Tumor Growth Regression and Metastasis
- Pilot: Lingyan Shi (CCNY) / Robert Alfano (CCNY) /Jason Koutcher (MSK): Early Diagnosis of Triple Negative Breast Cancer by Raman Spectroscopy and Multiphoton Microscopy
- Pilot: Itzhak Mano (CCNY) / Xuejun Jiang (MSK): Molecular Mechanisms of Regulated Necrosis in Brain Cancer: Ferroptosis & Excitotoxicity
- Pilot: Hernan Makse (CCNY) / Andrei Holodny (MSK): Graph Theoretical Analysis of Pre-operative fMRI Data in Bilingual Patients with Brain Tumors and Multiphoton Microscopy