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Intra-tumoral phenotypic heterogeneity promotes tumor relapse and therapeutic resistance and remains an unsolved clinical challenge. Decoding the interconnections among different biological axes of plasticity is crucial to understand the molecular origins of phenotypic heterogeneity. Here, we use multi-modal transcriptomic data-bulk, single-cell, and spatial transcriptomics-from breast cancer cell lines and primary tumor samples, to identify associations between epithelial-mesenchymal transition (EMT) and luminal-basal plasticity-two key processes that enable heterogeneity. We show that luminal breast cancer strongly associates with an epithelial cell state, but basal breast cancer is associated with hybrid epithelial/mesenchymal phenotype(s) and higher phenotypic heterogeneity. Mathematical modeling of core underlying gene regulatory networks representative of the crosstalk between the luminal-basal and epithelial-mesenchymal axes elucidate mechanistic underpinnings of the observed associations from transcriptomic data. Our systems-based approach integrating multi-modal data analysis with mechanism-based modeling offers a predictive framework to characterize intra-tumor heterogeneity and identify interventions to restrict it., Competing Interests: The authors declare no conflicts of interest., (© 2024 The Author(s).)

Exciting advances in technologies to measure biological systems are currently at the forefront of research. The ability to gather data along an increasing number of omic dimensions has created a need for tools to analyze all of this information together, rather than siloing each technology into separate analysis pipelines. To advance this goal, we introduce a framework called the single-cell multi-modal generative adversarial network (scMMGAN) that integrates data from multiple modalities into a unified representation in the ambient data space for downstream analysis using a combination of adversarial learning and data geometry techniques. The framework's key improvement is an additional diffusion geometry loss with a new kernel that constrains the otherwise over-parameterized GAN. We demonstrate scMMGAN's ability to produce more meaningful alignments than alternative methods on a wide variety of data modalities and that its output can be used to draw conclusions from real-world biological experimental data., Competing Interests: The authors declare no competing interests., (© 2022 The Author(s).)

Abstract: Phenotypic plasticity describes the ability of cancer cells to undergo dynamic, nongenetic cell state changes that amplify cancer heterogeneity to promote metastasis and therapy evasion. Thus, cancer cells occupy a continuous spectrum of phenotypic states connected by trajectories defining dynamic transitions upon a cancer cell state landscape. With technologies proliferating to systematically record molecular mechanisms at single-cell resolution, we illuminate manifold learning techniques as emerging computational tools to effectively model cell state dynamics in a way that mimics our understanding of the cell state landscape. We anticipate that "state-gating" therapies targeting phenotypic plasticity will limit cancer heterogeneity, metastasis, and therapy resistance., Significance: Nongenetic mechanisms underlying phenotypic plasticity have emerged as significant drivers of tumor heterogeneity, metastasis, and therapy resistance. Herein, we discuss new experimental and computational techniques to define phenotypic plasticity as a scaffold to guide accelerated progress in uncovering new vulnerabilities for therapeutic exploitation., (©2022 The Authors; Published by the American Association for Cancer Research.)

Therapies that prevent metastatic dissemination and tumor growth in secondary organs are severely lacking. A better understanding of the mechanisms that drive metastasis will lead to improved therapies that increase patient survival. Within a tumor, cancer cells are equipped with different phenotypic and functional capacities that can impact their ability to complete the metastatic cascade. That phenotypic heterogeneity can be derived from a combination of factors, in which the genetic make-up, interaction with the environment, and ability of cells to adapt to evolving microenvironments and mechanical forces play a major role. In this review, we discuss the specific properties of those cancer cell subgroups and the mechanisms that confer or restrict their capacity to metastasize., Competing Interests: The authors declare no conflict of interest.

Lack of insight into mechanisms governing breast cancer metastasis has precluded the development of curative therapies. Metastasis-initiating cancer cells (MICs) are uniquely equipped to establish metastases, causing recurrence and therapeutic resistance. Using various metastasis models, we discovered that certain primary tumours elicit a systemic inflammatory response involving interleukin-1β (IL-1β)-expressing innate immune cells that infiltrate distant MIC microenvironments. At the metastatic site, IL-1β maintains MICs in a ZEB1-positive differentiation state, preventing MICs from generating highly proliferative E-cadherin-positive progeny. Thus, when the inherent plasticity of MICs is impeded, overt metastases cannot be established. Ablation of the pro-inflammatory response or inhibition of the IL-1 receptor relieves the differentiation block and results in metastatic colonization. Among patients with lymph node-positive breast cancer, high primary tumour IL-1β expression is associated with better overall survival and distant metastasis-free survival. Our data reveal complex interactions that occur between primary tumours and disseminated MICs that could be exploited to improve patient survival.

Carcinoma cells that are induced to suppress their epithelial features and upregulate mesenchymal gene expression programs acquire traits that promote an invasive and metastatic phenotype. This is achieved through the expression of a program termed the epithelial-to-mesenchymal transition (EMT)-a fundamental cell-biological process that plays key roles in embryogenesis and wound healing. Re-activation of the EMT during cancer promotes disease progression and enhances the metastatic phenotype by bestowing upon previously benign carcinoma cell traits such as migration, invasion, resistance to anoikis, chemoresistance and tumour-initiating potential. Herein, we discuss recent insights into the function of the EMT and cancer cell plasticity during cancer progression, with a focus on their role in promoting successful completion of the later stages of the metastatic cascade.

The Notch signalling pathway plays an essential role in the intricate control of cell proliferation and pattern formation in many organs during animal development. In addition, mutations in most members of this pathway are well characterized and frequently lead to tumour formation. The Drosophila imaginal wing discs have provided a suitable model system for the genetic and molecular analysis of the different pathway functions. During disc development, Notch signalling at the presumptive wing margin is necessary for the restricted activation of genes required for pattern formation control and disc proliferation. Interestingly, in different cellular contexts within the wing disc, Notch can either promote cell proliferation or can block the G1-S transition by negatively regulating the expression of dmyc and bantam micro RNA. The target genes of Notch signalling that are required for these functions have not been identified. Here, we show that the Hes vertebrate homolog, deadpan (dpn), and the Enhancer-of-split complex (E(spl)C) genes act redundantly and cooperatively to mediate the Notch signalling function regulating cell proliferation during wing disc development.