Reverting to single-cell biology: The predictions of the atavism theory of cancer.

Cancer or cancer-like phenomena pervade multicellular life, implying deep evolutionary roots. Many of the hallmarks of cancer recapitulate unicellular modalities, suggesting that cancer initiation and progression represent a systematic reversion to simpler ancestral phenotypes in response to a stress or insult. This so-called atavism theory may be tested using phylostratigraphy, which can be used to assign ages to genes. Several research groups have confirmed that cancer cells tend to over-express evolutionary older genes, and rewire the architecture linking unicellular and multicellular gene networks. In addition, some of the elevated mutation rate - a well-known hallmark of cancer - is actually self-inflicted, driven by genes found to be homologs of the ancient SOS genes activated in stressed bacteria, and employed to evolve biological workarounds. These findings have obvious implications for therapy.

Cancer progression as a sequence of atavistic reversions.

It has long been recognized that cancer onset and progression represent a type of reversion to an ancestral quasi-unicellular phenotype. This general concept has been refined into the atavistic model of cancer that attempts to provide a quantitative analysis and testable predictions based on genomic data. Over the past decade, support for the multicellular-to-unicellular reversion predicted by the atavism model has come from phylostratigraphy. Here, we propose that cancer onset and progression involve more than a one-off multicellular-to-unicellular reversion, and are better described as a series of reversionary transitions. We make new predictions based on the chronology of the unicellular-eukaryote-to-multicellular-eukaryote transition. We also make new predictions based on three other evolutionary transitions that occurred in our lineage: eukaryogenesis, oxidative phosphorylation and the transition to adaptive immunity. We propose several modifications to current phylostratigraphy to improve age resolution to test these predictions. Also see the video abstract here: https://youtu.be/3unEu5JYJrQ.

Ancient hot and cold genes and chemotherapy resistance emergence.

We use a microfabricated ecology with a doxorubicin gradient and population fragmentation to produce a strong Darwinian selective pressure that drives forward the rapid emergence of doxorubicin resistance in multiple myeloma (MM) cancer cells. RNA sequencing of the resistant cells was used to examine (i) emergence of genes with high de novo substitution densities (i.e., hot genes) and (ii) genes never substituted (i.e., cold genes). The set of cold genes, which were 21% of the genes sequenced, were further winnowed down by examining excess expression levels. Both the most highly substituted genes and the most highly expressed never-substituted genes were biased in age toward the most ancient of genes. This would support the model that cancer represents a revision back to ancient forms of life adapted to high fitness under extreme stress, and suggests that these ancient genes may be targets for cancer therapy.

Targeting cancer's weaknesses (not its strengths): Therapeutic strategies suggested by the atavistic model.

In the atavistic model of cancer progression, tumor cell dedifferentiation is interpreted as a reversion to phylogenetically earlier capabilities. The more recently evolved capabilities are compromised first during cancer progression. This suggests a therapeutic strategy for targeting cancer: design challenges to cancer that can only be met by the recently evolved capabilities no longer functional in cancer cells. We describe several examples of this target-the-weakness strategy. Our most detailed example involves the immune system. The absence of adaptive immunity in immunosuppressed tumor environments is an irreversible weakness of cancer that can be exploited by creating a challenge that only the presence of adaptive immunity can meet. This leaves tumor cells more vulnerable than healthy tissue to pathogenic attack. Such a target-the-weakness therapeutic strategy has broad applications, and contrasts with current therapies that target the main strength of cancer: cell proliferation.

A physical sciences network characterization of non-tumorigenic and metastatic cells.

To investigate the transition from non-cancerous to metastatic from a physical sciences perspective, the Physical Sciences-Oncology Centers (PS-OC) Network performed molecular and biophysical comparative studies of the non-tumorigenic MCF-10A and metastatic MDA-MB-231 breast epithelial cell lines, commonly used as models of cancer metastasis. Experiments were performed in 20 laboratories from 12 PS-OCs. Each laboratory was supplied with identical aliquots and common reagents and culture protocols. Analyses of these measurements revealed dramatic differences in their mechanics, migration, adhesion, oxygen response, and proteomic profiles. Model-based multi-omics approaches identified key differences between these cells' regulatory networks involved in morphology and survival. These results provide a multifaceted description of cellular parameters of two widely used cell lines and demonstrate the value of the PS-OC Network approach for integration of diverse experimental observations to elucidate the phenotypes associated with cancer metastasis.

Isotropic 3D nuclear morphometry of normal, fibrocystic and malignant breast epithelial cells reveals new structural alterations.

BACKGROUND: Grading schemes for breast cancer diagnosis are predominantly based on pathologists' qualitative assessment of altered nuclear structure from 2D brightfield microscopy images. However, cells are three-dimensional (3D) objects with features that are inherently 3D and thus poorly characterized in 2D. Our goal is to quantitatively characterize nuclear structure in 3D, assess its variation with malignancy, and investigate whether such variation correlates with standard nuclear grading criteria. METHODOLOGY: We applied micro-optical computed tomographic imaging and automated 3D nuclear morphometry to quantify and compare morphological variations between human cell lines derived from normal, benign fibrocystic or malignant breast epithelium. To reproduce the appearance and contrast in clinical cytopathology images, we stained cells with hematoxylin and eosin and obtained 3D images of 150 individual stained cells of each cell type at sub-micron, isotropic resolution. Applying volumetric image analyses, we computed 42 3D morphological and textural descriptors of cellular and nuclear structure. PRINCIPAL FINDINGS: We observed four distinct nuclear shape categories, the predominant being a mushroom cap shape. Cell and nuclear volumes increased from normal to fibrocystic to metastatic type, but there was little difference in the volume ratio of nucleus to cytoplasm (N/C ratio) between the lines. Abnormal cell nuclei had more nucleoli, markedly higher density and clumpier chromatin organization compared to normal. Nuclei of non-tumorigenic, fibrocystic cells exhibited larger textural variations than metastatic cell nuclei. At p<0.0025 by ANOVA and Kruskal-Wallis tests, 90% of our computed descriptors statistically differentiated control from abnormal cell populations, but only 69% of these features statistically differentiated the fibrocystic from the metastatic cell populations. CONCLUSIONS: Our results provide a new perspective on nuclear structure variations associated with malignancy and point to the value of automated quantitative 3D nuclear morphometry as an objective tool to enable development of sensitive and specific nuclear grade classification in breast cancer diagnosis.