Altered tissue mechanics and metabolism have gained significant attention as drivers of tumorigenesis, and mechanoresponsive metabolism has been implicated in migration and metastasis. However, heterogeneity in cell populations makes it difficult to link changes in behavior with metabolism, as individual cell behaviors are not necessarily reflected in population-based measurements. As such, the impact of increased collagen deposition, a tumor-associated collagen signature, on metabolism remains ambiguous. Here, we utilize a wide range of collagen densities to alter migration ability and study the bioenergetics of individual cells over time. Sorting cells based on their level of motility revealed energetics are a function of collagen density only for highly motile cells, not the entire population or cells with low motility. Changes in migration with increasing collagen density were correlated with cellular energetics, where matrix conditions most permissive to migration required less energy usage during movement and migrated more efficiently. These findings reveal a link between matrix mechanics, migratory phenotype, and bioenergetics and suggest that energetic costs are determined by the extracellular matrix and influence cell motility.

Cell migration during many fundamental biological processes including metastasis requires cells to traverse tissue with heterogeneous mechanical cues that direct migration as well as determine force and energy requirements for motility. However, the influence of discrete structural and mechanical cues on migration remains challenging to determine as they are often coupled. Here, we decouple the pro-invasive cues of collagen fiber alignment and tension to study their individual impact on migration. When presented with both cues, cells preferentially travel in the axis of tension against fiber alignment. Computational and experimental data show applying tension perpendicular to alignment increases potential energy stored within collagen fibers, lowering requirements for cell-induced matrix deformation and energy usage during migration compared to motility in the direction of fiber alignment. Energy minimization directs migration trajectory, and tension can facilitate migration against fiber alignment. These findings provide a conceptual understanding of bioenergetics during migration through a fibrous matrix.

Approximately 70% of advanced breast cancer patients will develop bone metastases, which accounts for ∼90% of cancer-related mortality. Breast cancer circulating tumor cells (CTCs) establish metastatic tumors in the bone after a close interaction with local bone marrow cells including pericytes and osteoblasts, both related to resident mesenchymal stem/stromal cells (BM-MSCs) progenitors. In vitro recapitulation of the critical cellular players of the bone microenvironment and infiltrating CTCs could provide new insights into their cross-talk during the metastatic cascade, helping in the development of novel therapeutic strategies. Human BM-MSCs were isolated and fractionated according to CD146 presence. CD146+ cells were utilized as pericyte-like cells (PLCs) given the high expression of the marker in perivascular cells, while CD146− cells were induced into an osteogenic phenotype generating osteoblast-like cells (OLCs). Transwell migration assays were performed to establish whether primary breast cancer cells (3384T) were attracted to OLC. Furthermore, proliferation of 3384T breast cancer cells was assessed in the presence of PLC- and OLC-derived conditioned media. Additionally, conditioned media cultures as well as transwell co-cultures of each OLCs and PLCs were performed with 3384T breast cancer cells for gene expression interrogation assessing their induced transcriptional changes with an emphasis on metastatic potential. PLC as well as their conditioned media increased motility and invasion potential of 3384T breast cancer cells, while OLC induced a dormant phenotype, downregulating invasiveness markers related with migration and proliferation. Altogether, these results indicate that PLC distinctively drive 3384T cancer cells to an invasive and migratory phenotype, while OLC induce a quiescence state, thus recapitulating the different phases of the in vivo bone metastatic process. These data show that phenotypic responses from metastasizing cancer cells are influenced by neighboring cells at the bone metastatic niche during the establishment of secondary metastatic tumors.

Background/Objectives: Cancer cell migration is a hallmark of cancer and is associated with metastasis. While large-scale functional screens have identified regulators of migration, less is known about how intrinsic transcriptional heterogeneity drives highly migratory phenotypes within individual cancer models or whether these transcriptional changes are conserved across different models of varying tissues of origin. This study aims to define shared and cell line-specific transcriptional programs associated with cancer cell migration and analyze their relevance to patient datasets. Methods: Five cancer cell lines across three cancer types (breast, colorectal, and melanoma) were subjected to transwell-based migratory sorting to isolate highly and weakly migratory subpopulations. Bulk RNA sequencing, differential gene expression analysis, Gene Ontology (GO) enrichment, and upstream regulator prediction were performed. Public tumor datasets were analyzed to evaluate gene expression and its association with patient survival. Results: EVA1A was consistently upregulated in all highly migratory (HM) subpopulations. Multiple GO terms were enriched across all cell lines, often driven by distinct gene signatures, indicating convergence at the level of biological processes despite transcriptional divergence. TEAD4 was predicted as an upstream regulator, and increased TEAD4 nuclear localization was observed in four of the five HM subpopulations. EVA1A and TEAD4 expression were elevated in tumors relative to normal tissues, with cancer type-dependent survival outcomes. Conclusions: Migratory selection was accompanied by extensive transcriptional change within each model, yet across five models spanning three tissue types these changes converged on shared biological processes rather than shared genes. Migration-associated phenotypes may therefore be better defined by pathway-level than single-gene analyses, and the clinical relevance of regulatory nodes such as TEAD4 appears conditional on cancer type.