Critical Points in Tumorigenesis: A Carcinogen-Initiated Phase Transition Analyzed via Single-Cell Proteomics

Abstract

A kinetic, single-cell proteomic study of chemically induced carcinogenesis is interpreted by treating the single-cell data as fluctuations of an open system transitioning between different steady states. In analogy to a first-order transition, phase coexistence and the loss of degrees of freedom are observed. The transition is detected well before the appearance of the traditional biomarker of the carcinogenic transformation.

Keywords: carcinogenesis; microfluidics; phase transition; single-cell proteomics; steady state.

Figure 1. The experimental schema and results of colonogenic assay

a. Protocol for the cycles of B[a]P treatment of the MCF 10F cells. b. Time line representing B[a]P dosing, and the 9 (including control) time points for the SCBC analysis. c. Colonogenic assays of cells treated with B[a]P, in complete growth medium under limited cell density. The numbers at the top right of the photographs presents the time point from which the treated cells were used to perform the assay. d. Colonogenic assay for characterizing the anchorage independence (AIG) of MCF-10F cells treated with BaP. e. quantification of colonogenic assay in complete growth medium under limiting cell density (Supporting information text ST 10). Plot shows number of colonies formed from 5000 cell (n=3). f. Quantification of colonogenic assay in reduced growth medium (Supporting information text ST 10; Figure S3). Plot shows number of colonies formed from 20000 cell (n=3). g. Quantification of colonogenic assay in Anchorage Independence assay (Supporting information text ST 10).

Figure 2. Representative results of the SCBC analysis

a. One-dimensional scatter plots of the single cell levels of few representative proteins across the kinetic timeline. b. Protein-protein covariance matrices, extracted from SCBC data of MCF-10F cells treated with BaP, at all the time points in the kinetic study.

Figure 3. Analysis of single cell data through the CiC transition

a. The weight of the steady state term ( ${\lambda }_0$) and the first two constraints ( ${\lambda }_1$and ${\lambda }_2$) plotted, for each cell and color-coded for each time point. b. Number of cells vs. $G_{i0}{\lambda }_0(\mathit{cell},t)$, with different panels shown at different time points shown for the pS6K protein. Comparable distributions are obtained for other measured proteins since $G_{i0}$ are similar (Supplementary figure S7). The distribution (b) at every time point was fitted to either unimodal or Bimodal Gaussian distributions. Bimodal Gaussian distributions appear as the best fitting distribution for the days 12, 15 and 28 (R² >0.95), whereas unimodal Gaussian is the best fit for the control, d57 and d96 (R² >0.95). c. Scatter plots of values ${\lambda }_0$ vs ${\lambda }_1$ at the day 12 and day 28. The unbalanced process ${\lambda }_1$ has higher significance, ${\lambda }_1\ne 0$, (as indicated by ${\lambda }_1>3$ at the day 12 or ${\lambda }_1<-2$ at the day 28) in the cell subpopulations with lower protein abundance, as represented by lower values of ${\lambda }_0$. d. Principle eigenvalues (1 and 2) of the covariance matrix are plotted as a function of t.