Quantifying the Role of Heterogeneity and Clonal Diversity on Cell Population Samples in an in silico Spatio-temporal Model

How does heterogeneity and/or clonal diversity in the true population affect the amount of information we obtain from samples of the true population?

It is currently unknown how statistically representative the biopsy is of the full tumor or tumors present and how biopsy representativeness changes as a function of features of the biopsy or the cancer itself. Agent-based models (ABMs) present an opportunity to provide the necessary data to answer this question.

Data Information

The data for this project is from ARCADE v2.2 POPULATION_HETEROGENEITY simulations, produced in November 2019. Simulations conditions include context, population mixture, population heterogeneity, and background heterogeneity.

More information on ARCADE can be found at the ARCADE GitHub repository and the paper.

Data Description

• Simulations of all possible permutations of four populations (X, A, B, C) under colony and tissue context with different levels of parameter heterogeneity (0, 0.1, 0.2, 0.3, 0.4, and 0.5).
  • See POPULATION_HETEROGENEITY_C.xml for colony context setup
  • See POPULATION_HETEROGENEITY_CH.xml for tissue context setup
    • For tissue context, the healthy cell populations also varies parameter heterogeneity independent of the cancerous cell populations.
• Each condition is run for 15 days (21600 ticks) with 20 replicates (random seeds 0 - 19).
• Cells are introduced to the center of the constant source environment after a 1 day delay.
• Snapshots are taken every 0.5 days (720 ticks).

AWS Data Stoage Information

• The `data/` folder contains `.tar.xz` compressed replicate sets.
• The `data.param/` folder contains `.tar.xz` compressed replicate sets for `.PARAM` output.
• The `results/` folder contains `.pkl` files of data parsed into arrays.

File Naming Conventions

Simulations are labeled as: `[context]_[populations]_[population heterogeneity]_[background heterogeneity]`

• `[context]`
  • `C` = colony context, cancerous cell populations only
  • `CH` = tissue context, cancerous cell populations and healthy cells
• `[populations]`
  • `X` = cancerous cell population with basal parameters
  • `A` = cancerous cell population with `max_height` x 1.5
  • `B` = cancerous cell population with `meta_pref` x 1.5
  • `C` = cancerous cell population with `migra_threshold` x 0.5
• `[population heterogeneity]`
  • `##` = heterogeneity value for cancerous cell populations (`##`/10)
• `[background heterogeneity]`
  • `##` = heterogeneity value for healthy cell population (`##`/10)

Data Analysis

For data analysis, this project analyze data from simulation with varied cell line permutation and heterogeneity levels across the two contxt.

Features

Below, we describe the specific features we looked at in the data. Namely, discrete and continuous features.

Heterogeneity

Heteoreneity is an intrinsic property of biological systems, even within clonal populations. In our model, all internal cell parameters are drawn from a normal distribution where mean (µ) = parameter value and standard deviation (σ) = heterogeneity (H) · µ. There are 5 intracellular heterogeneity levels varied at 0, 10, 20, 30, 40, and 50%.