Search bioRxiv⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/2022.04.27.489205

Loss of Myosin-1e biases MMTV-PyMT induced breast cancer towards a 4 differentiated and secretory state

Plante, E. L.·Chase, S. E.·De Jong, E. P.·Curtis, T. M.·Garone, M. E.·Krendel, M.
View original source ↗Export metadata ↓

Abstract

Expression of the unconventional myosin, Myosin-1e (Myo1e), has been shown to contribute to tumor progression in the MMTV-PyMT mouse model of mammary tumorigenesis and is associated with poor outcome in breast cancer patients. However, the specific effects of Myo1e expression on the mammary tumor cells remain unidentified. Here, we used Myo1e-KO and wild-type (WT) MMTV-PyMT mice on a pure genetic background to further investigate the molecular and cellular effects of Myo1e expression. Myo1e-WT tumors were characterized by an increased abundance of intra-epithelial macrophages and lower amounts of the extracellular matrix. Transcriptomic profiling of WT and Myo1e-KO tumors identified a pattern of differential expression of tumor suppressor and tumor-promoting genes that was consistent with the observed differences in tumor progression and morphology between the genotypes, and also revealed differential expression of genes associated with secretion and cell-cell adhesion. In agreement with the RNA-seq findings, Myo1e-expressing tumor cells exhibited increased proliferation and elevated nuclear enrichment of YAP1 transcriptional activator compared to Myo1e-KO tumor cells. To investigate tumor cell-autonomous effects of Myo1e expression, we used the epithelial cell line PY-230 derived from the MMTV-PyMT-induced mouse tumor to create Myo1e-depleted cells by Crispr-mediated genome editing. Cells deficient in Myo1e had increased expression of genes encoding milk components compared to the wild-type cells. Electric cell-substrate impedance sensing (ECIS) measurements showed that depletion of Myo1e in PY-230 cells resulted in increased resistance to electrical current indicating enhanced epithelial barrier function. Overall, we find that Myo1e expression biases tumors towards a less-differentiated, pro-tumorigenic state, and that depletion of Myo1e is associated with a pro-secretory, more differentiated state.

Explore related subjects

cancer biologyPreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Plante, E. L., Chase, S. E., De Jong, E. P., Curtis, T. M., Garone, M. E., Krendel, M.. 2022-04-27. Loss of Myosin-1e biases MMTV-PyMT induced breast cancer towards a 4 differentiated and secretory state. https://doi.org/10.1101/2022.04.27.489205

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

BAF complexes cooperate with lineage-restricted transcription factors to establish cell-state-specific regulatory programs

BRG1/BRM-associated factor (BAF) complexes are essential regulators of chromatin organization and cell identity. Genes encoding BAF subunits are among the most frequently mutated in human cancer. Yet, how disruption of a single subunit gives rise to distinct tumor states remains poorly understood. Atypical teratoid rhabdoid tumors (ATRTs) provide a compelling model, as they are uniformly driven by bi-allelic loss of the BAF subunit SMARCB1, yet segregate into distinct molecular subtypes. Using integrated multi-omics profiling of patient-derived ATRT organoids and primary tumor tissues, we show that transcriptional and chromatin accessibility changes upon SMARCB1 reconstitution are directed by subtype- and lineage-specific transcription factor (TF) repertoires. Genome-wide binding and transcriptomic analyses reveal that SMARCB1 reconstitution enables the lineage-specific TF RFX4 to engage regulatory elements and activate neuronal differentiation programs, partially reprogramming ATRT-MYC toward an ATRT-SHH-like identity. Together, these findings demonstrate that SMARCB1 loss disrupts TF-dependent chromatin priming, revealing that the lineage-specific regulatory output of BAF complexes is constrained by the underlying TF repertoire.

cancer biology↗
bioRxiv2026

Curvature-based schedule ordering is preserved in homogeneous and heterogeneous tumors

During treatment, dosing protocols with identical total dose may favor one schedule over another depending on how exposure is distributed over time. In homogeneous cell populations, Jensen's inequality has been shown to predict whether continuous or intermittent high-dose followed by low-dose is favored, based on the curvature of the concentration-effect function. Scheduling ordering can be performed based on curvature only: concave functions favor continuous dosing while convex functions favor intermittent dosing schedules with a high time-variance. However, tumors exhibit heterogeneous drug sensitivities, and treatment preferentially eliminates drug-sensitive cells, progressively shifting the surviving population toward greater drug resistance. Whether this treatment-induced selection can reverse curvature-based schedule ordering remains unclear. We develop a mathematical framework in which phenotypes share a common concentration-effect function but differ by fixed, nonnegative sensitivity scales. We prove that the ordering of equal-mean schedules is administrated solely by the scalar cumulative treatment effect, that is, by the curvature of the effect function alone. Consequently, baseline heterogeneity and treatment-induced selection can alter the magnitude of treatment response and the composition of surviving cells, but cannot reverse the ordering of equal-mean schedules predicted by the curvature of the single-cell concentration-effect function. This preservation holds across different temporal dosing profiles and repeated treatment cycles. Our work uncovers a general principle that curvature-based schedule ordering is preserved in heterogeneous tumors despite treatment-induced selection toward resistance.

cancer biology↗
bioRxiv2026

Enhanced antitumour activity of combined PD-1 blockade and HER2-targeted therapy is associated with reduced epithelial-mesenchymal transition and extracellular matrix-remodelling signatures in gastric cancer

Background The combination of PD-1 blockade, HER2-targeted therapy and chemotherapy improves outcomes in HER2-positive advanced gastric and gastro-oesophageal junction adenocarcinoma. However, chemotherapy can independently alter the tumour microenvironment, making the biological effects of PD-1 and HER2 targeting difficult to distinguish. We therefore investigated how PD-1 and HER2 blockade, alone and in combination, affect tumour growth and associated transcriptional programmes. Methods Immunodeficient NOG mice received human PBMCs by tail-vein injection. Three days later, NCI-N87 gastric cancer cells were implanted subcutaneously. Mice were randomised to vehicle, pembrolizumab, trastuzumab, or combination treatment. Tumour growth was assessed, and bulk RNA sequencing was used to identify treatment-associated changes in gene expression, pathway enrichment, and tumour, stromal, and immune cell-associated signatures. Results Combined treatment produced greater tumour growth control than either monotherapy. Trastuzumab-treated tumours showed enrichment of immune activation, epithelial-mesenchymal transition (EMT), and TGF{beta}-associated signatures, whereas pembrolizumab alone produced a limited transcriptional effect. Combination treatment was associated with reduced proliferation, EMT, and stromal-remodelling signatures, alongside increased cytotoxic immune-associated signatures. Expression of extracellular matrix-associated genes, including VCAN, SPARC, POSTN, collagen genes, and FAP, was lower in combination-treated tumours. Complement-related transcriptional pathways were also enriched. Conclusions In this chemotherapy-free model, combined PD-1 blockade and HER2-targeted therapy was associated with greater tumour growth control, enrichment of cytotoxic immune-associated transcriptional signatures, and reduced EMT and extracellular matrix remodelling signatures. These findings provide hypotheses for further mechanistic validation.

cancer biology↗