# Project 1: How tumor ensemble models with two experimental models predict tumor dormancy & reactivation in cancers with gender and/or ethnic disparities

> **NIH NIH U54** · CITY COLLEGE OF NEW YORK · 2021 · $149,846

## Abstract

Cancer is one of the world's major health problems. After chemotherapy or surgery, some cancers, e.g.,
breast cancer and melanoma, by a still mysterious mechanism persist, apparently dormant, for years before
distant metastases appear and tumors reactivate and grow. Latent tumor cells may survive by their microenvi-
ronment partially excluding T-cells that would attack them. Transplant studies indicate that, rather than static
quiescence, these cells and the immune system are in dynamic equilibrium and periodic bursts of cell division
and elimination sometimes transform unobservable micrometastases that accumulate genetic, epigenetic and
proteomic changes into macrometastases. Details and a complete mechanism are lacking.
 There is a paucity of experimental or theoretical models that recapitulate latency or its reactivation. One
mouse breast cancer model exhibits short-term latency & recurrence. Mathematical cancer models typically
describe single tumor growth and/or metastasis generation or the probability of several mutations, but not dor-
mancy. We posit a new mathematical population 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, necro-
sis, etc.) and metastasis. Ensembles naturally incorporate response variations of similar tumors. Predictions
are probabilistic, proportional to the expected tumor number of each size and time from any initial size distribu-
tion. Smaller tumors often respond better to chemotherapy than larger ones, likely due to the latter's more ac-
cumulated mutations; tumor-size-dependent parameters model this most simply. Our model finds a surprising
interaction among these size-dependent processes in an ensemble that generates intriguing new unexpected
qualitative behavior, e.g., diffusion in tumor size space that for the first time predicts dormancy & recurrence.
 This proposal intimately integrates this new mathematical model with the BALB/c murine breast cancer and
the clear, stripeless zebrafish melanoma systems; both allow live non-invasive monitoring of tumor numbers
and sizes vs time without animal sacrifice. Our model fits existing human hepatocellular carcinoma and im-
mune-suppressed & competent fish melanoma histograms at many times extremely well with only 3 parame-
ters. We plan new fish experiments to control/tune the level of immunity so as to access and test parameters
predicted to yield dormancy & recurrence. We shall carry out detailed experiments on the mouse breast cancer
system, which may exhibit dormancy & recurrence naturally, and use it to test our model. We shall also attempt
to modulate its immunity to access and test parameters predicted to yield dormancy & recurrence. Since both
these cancers show both ethnic and gender disparities, we shall use melanoma cell with snps that recapitulate
ethnicity-specific genetics and segregate (fish) data by gender so as to see if parameters show et...

## Key facts

- **NIH application ID:** 10260495
- **Project number:** 5U54CA132378-13
- **Recipient organization:** CITY COLLEGE OF NEW YORK
- **Principal Investigator:** DAVID Sheldon RUMSCHITZKI
- **Activity code:** U54 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $149,846
- **Award type:** 5
- **Project period:** 2008-09-26 → 2024-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10260495

## Citation

> US National Institutes of Health, RePORTER application 10260495, Project 1: How tumor ensemble models with two experimental models predict tumor dormancy & reactivation in cancers with gender and/or ethnic disparities (5U54CA132378-13). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10260495. Licensed CC0.

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