Functional Heterogeneity as an intrinsic property that sets a survival strategy in breast cancer.

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According to clinical evidence, tumor heterogeneity is a critical factor that sets diagnosis and therapeutic outcomes in patients1. As an advance in the field, intratumoral and intertumoral heterogeneity has been described, and considered into therapeutic schemes in several types of cancer2. However, heterogeneity is more than cells with different phenotypes coexisting into a tumor, it manifests a complex interdependence of functional roles. This fact can be observed clearer in a population of isogenic cancer cells and how a plethora of prosurvival functional roles emerge with unique properties that lead to chemoresistance and tumor survival3,4. As part of the disease complexity, the interaction tumor/microenvironment has a strong influence in prognosis, this interaction is established by the spatial organization and the way time shapes the tumoral properties. Moreover, no studies were found available to study functional heterogeneity taking into account three-dimensional organization and time evolution. To address the gap and get the functional heterogeneity basics, we used Multicellular Tumor Spheroids (MCTS) at two-time points of their progression. Under this approximation, we got monoclonal avascular tumor spheroids, which makes them an engaging model to study the heterogeneous functionality of clonal subpopulations at different stages of growth. We used the luminal A breast cancer cell. Therefore we focused the study in the most frequent cancer subtype among women worldwide5,6.

Our study unraveled the functional heterogeneity given the transcriptional landscape of 364 single cells collected at 6 and 19 days of the MCF7 MCTS growth. As a first insight, we believed the major transcriptional differences would arise from the time-point dependency. However, thanks to the integrative data-driven approach combining data analysis and bioinformatic tools, we found that the differences were not about the time but to the time-depending probability of developing a certain function. Surprisingly, we found three conserved subpopulations across samples, each one with their own characteristics. In summary, every subpopulation was associated with a primary function: proliferate, invade and orchestrate immune invasion, and finally to be part of a cellular reservoir. All of them coexist with synergism to develop a survival strategy (Figure 1).  Concordantly with previous reports7, these functions are accompanied by gene expression profiles that pose changes in key gene regulators to supply their metabolic requirements like energy demand. Moreover, we evaluated the possible existence of a master regulation motif to module the subpopulations proportions and which in principle would increase therapeutic proficiency. 

Figure 1:

While the proportion of proliferative and invasive subpopulations proportions shifted with time, the reservoir remained constant. The reservoir subpopulation might be an essential player in generating new tumors because it is intermediate to the others. The functional identity of this last subpopulation was the most challenging aim. However, we consider that its understanding will open new avenues of research with relevant implications in designing new treatments to defeat cancer.

Together, our study highlights that cancer is not a sequence of events but various hallmarks fine-tuned as a whole. We proposed that metastasis can happen even in early cancer stages, and all functional processes have a systemic organization. It seems that heterogeneity maintenance is an intrinsic property that ensures tumor fitness. According to this idea, treatment efficiency will be improved by mixed therapeutic targets that take into account several functional populations in tumors.

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Aarón Vázquez Jiménez

Postdoctoral researcher, INMEGEN, Mexico.

Aarón Vázquez Jiménez is a postdoctoral researcher at the National Institute of Genomic Medicine (INMEGEN) in Mexico City. He has a Ph.D. in Engineer and Biophysics at CINVESTAV. Aarón's expertise is related to system biology and mathematical modeling. From his graduate studies until now, he has focused on regulatory gene circuits, stochastic models and the noise impact in biological systems, information theory, information transmission in cell to cell communication, and computational methods for single-cell data.