Quantifying intrinsic and extrinsic control of single-cell fates in cancer and stem/progenitor cell pedigrees with competing risks analysis

Non-genetic heterogeneity and immune subtyping in breast cancer: Implications for immunotherapy and targeted therapeutics

Breast cancer (BC) is a complex and multifactorial disease, driven by genetic alterations that promote tumor growth and progression. However, recent research has highlighted the importance of non-genetic factors in shaping cancer evolution and influencing therapeutic outcomes. Non-genetic heterogeneity refers to diverse subpopulations of cancer cells within breast tumors, exhibiting distinct phenotypic and functional properties. These subpopulations can arise through various mechanisms, including clonal evolution, genetic changes, epigenetic changes, and reversible phenotypic transitions. Although genetic and epigenetic changes are important points of the pathology of breast cancer yet, the immune system also plays a crucial role in its progression. In clinical management, histologic and molecular classification of BC are used. Immunological subtyping of BC has gained attention in recent years as compared to traditional techniques. Intratumoral heterogeneity revealed by immunological microenvironment (IME) has opened novel opportunities for immunotherapy research. This systematic review is focused on non-genetic variability to identify and interlink immunological subgroups in breast cancer. This review provides a deep understanding of adaptive methods adopted by tumor cells to withstand changes in the tumor microenvironment and selective pressure imposed by medications. These adaptive methods include alterations in drug targets, immune system evasion, activation of survival pathways, and alterations in metabolism. Understanding non-genetic heterogeneity is essential for the development of targeted therapies.

Loss of CDK4/6 activity in S/G2 phase leads to cell cycle reversal

In mammalian cells, the decision to proliferate is thought to be irreversibly made at the restriction point of the cell cycle1,2, when mitogen signalling engages a positive feedback loop between cyclin A2/cyclin-dependent kinase 2 (CDK2) and the retinoblastoma protein3-5. Contrary to this textbook model, here we show that the decision to proliferate is actually fully reversible. Instead, we find that all cycling cells will exit the cell cycle in the absence of mitogens unless they make it to mitosis and divide first. This temporal competition between two fates, mitosis and cell cycle exit, arises because cyclin A2/CDK2 activity depends upon CDK4/6 activity throughout the cell cycle, not just in G1 phase. Without mitogens, mitosis is only observed when the half-life of cyclin A2 protein is long enough to sustain CDK2 activity throughout G2/M. Thus, cells are dependent on mitogens and CDK4/6 activity to maintain CDK2 activity and retinoblastoma protein phosphorylation throughout interphase. Consequently, even a 2-h delay in a cell's progression towards mitosis can induce cell cycle exit if mitogen signalling is lost. Our results uncover the molecular mechanism underlying the restriction point phenomenon, reveal an unexpected role for CDK4/6 activity in S and G2 phases and explain the behaviour of all cells following loss of mitogen signalling.

Toxicity of Orthodontic Brackets Examined by Single Cell Tracking

Subtle toxic effects may be masked in traditional assays that average or summate the response of thousands of cells. We overcome this by using the recent method of single cell tracking in time-lapse recordings. This follows the fate and behavior of individual cells and their progeny and provides unambiguous results for multiple simultaneous biological responses. Further, single cell tracking permits correlation between progeny relationships and cell behavior that is not otherwise possible, including disruption by toxins and toxicants of similarity between paired sister cells. Notably, single cell tracking seems not to have been previously used to study biomaterials toxicity. The culture medium was pre-conditioned by 79 days incubation with orthodontic brackets from seven separate commercial sources. Metal levels were determined by Inductively Coupled Plasma Mass Spectrometry. Metal levels varied amongst conditioned media, with elevated Cr, Mn, Ni, and Cu and often Mo, Pb, Zn, Pd, and Ag were occasionally found. The effect on human dermal fibroblasts was determined by single cell tracking. All bracket-conditioned media reduced cell division (p < 0.05), while some reduced cell migration (p < 0.05). Most bracket-conditioned media increased the rate of asynchronous sister cell division (p < 0.05), a seemingly novel measure for toxicity. No clear effect on cell morphology was seen. We conclude that orthodontic brackets have cytotoxic effects, and that single cell tracking is effective for the study of subtle biomaterials cytotoxicity.

Understanding breast cancer heterogeneity through non-genetic heterogeneity

Intricacy in treatment and diagnosis of breast cancer has been an obstacle due to genotype and phenotype heterogeneity. Understanding of non-genetic heterogeneity mechanisms along with considering role of genetic heterogeneity may fill the gaps in landscape painting of heterogeneity. The main factors contribute to non-genetic heterogeneity including: transcriptional pulsing/bursting or discontinuous transcriptions, stochastic partitioning of components at cell division and various signal transduction from tumor ecosystem. Throughout this review, we desired to provide a conceptual framework focused on non-genetic heterogeneity, which has been intended to offer insight into prediction, diagnosis and treatment of breast cancer.

Cell cycle inertia underlies a bifurcation in cell fates after DNA damage

The G₁-S checkpoint is thought to prevent cells with damaged DNA from entering S phase and replicating their DNA and efficiently arrests cells at the G₁-S transition. Here, using time-lapse imaging and single-cell tracking, we instead find that DNA damage leads to highly variable and divergent fate outcomes. Contrary to the textbook model that cells arrest at the G₁-S transition, cells triggering the DNA damage checkpoint in G₁ phase route back to quiescence, and this cellular rerouting can be initiated at any point in G₁ phase. Furthermore, we find that most of the cells receiving damage in G₁ phase actually fail to arrest and proceed through the G₁-S transition due to persistent cyclin-dependent kinase (CDK) activity in the interval between DNA damage and induction of the CDK inhibitor p21. These observations necessitate a revised model of DNA damage response in G₁ phase and indicate that cells have a G₁ checkpoint.

Analysis of cardiac stem cell self-renewal dynamics in serum-free medium by single cell lineage tracking

Cardiac colony forming unit-fibroblasts (cCFU-F) are a population of stromal cells residing within the SCA1⁺/PDGFRα⁺/CD31^- fraction of adult mouse hearts, and which have functional characteristics akin to bone marrow mesenchymal stem cells. We hypothesise that they participate in cardiac homeostasis and repair through their actions as lineage progenitors and paracrine signaling hubs. However, cCFU-F are rare and there are no specific markers for these cells, making them challenging to study. cCFU can self-renew in vitro, although the common use of serum has made it difficult to identify cytokines that maintain lineage identity and self-renewal ability. Cell heterogeneity is an additional confounder as cCFU-F cultures are metastable. Here, we address these limitations by identifying serum-free medium (SFM) for growth, and by using cCFU-F isolated from Pdgfra^GFP/+ mice to record fate outcomes, morphology and PDGFRα expression for hundreds of single cells over time. We show that SFM supplemented with basic fibroblast growth factor, transforming growth factor-β and platelet-derived growth factor, enhanced cCFU-F colony formation and long-term self-renewal, while maintaining cCFU-F potency. cCFU-F cultured in SFM maintained a higher proportion of PDGFRα⁺ cells, a marker of self-renewing cCFU-F, by increasing Pdgfra-GFP⁺ divisions and reducing the probability of spontaneous myofibroblast differentiation.

Heritable tumor cell division rate heterogeneity induces clonal dominance

Tumors consist of a hierarchical population of cells that differ in their phenotype and genotype. This hierarchical organization of cells means that a few clones (i.e., cells and several generations of offspring) are abundant while most are rare, which is called clonal dominance. Such dominance also occurred in published in vitro iterated growth and passage experiments with tumor cells in which genetic barcodes were used for lineage tracing. A potential source for such heterogeneity is that dominant clones derive from cancer stem cells with an unlimited self-renewal capacity. Furthermore, ongoing evolution and selection within the growing population may also induce clonal dominance. To understand how clonal dominance developed in the iterated growth and passage experiments, we built a computational model that accurately simulates these experiments. The model simulations reproduced the clonal dominance that developed in in vitro iterated growth and passage experiments when the division rates vary between cells, due to a combination of initial variation and of ongoing mutational processes. In contrast, the experimental results can neither be reproduced with a model that considers random growth and passage, nor with a model based on cancer stem cells. Altogether, our model suggests that in vitro clonal dominance develops due to selection of fast-dividing clones.

Tumors consist of numerous cell populations, i.e., clones, that differ with respect to genotype, and potentially with respect to phenotype, and these populations strongly differ in their size. A limited number of clones tend to dominate tumors, but it remains unclear how this clonal dominance arises. Potential driving mechanisms are the presence of cancer stem cells, which either divide indefinitely of differentiate into cells with a limited division potential, and ongoing evolutionary processes within the tumor. Here we use a computational model to understand how clonal dominance developed during in vitro growth and passage experiments with cancer cells. Incorporating cancer stem cells in this model did not result in a match between simulations and in vitro data. In contrast, by considering all cells to divide indefinitely and division rates to evolve due to the combination of division rate variability and selection by passage, our model closely matches the in vitro data.