Dynamic Glycoprotein Hyposialylation Promotes Chemotherapy Evasion and Metastatic Seeding of Quiescent Circulating Tumor Cell Clusters in Breast Cancer.

Most circulating tumor cells (CTC) are detected as single cells, whereas a small proportion of CTCs in multicellular clusters with stemness properties possess 20- to 100-times higher metastatic propensity than the single cells. Here we report that CTC dynamics in both singles and clusters in response to therapies predict overall survival for breast cancer. Chemotherapy-evasive CTC clusters are relatively quiescent with a specific loss of ST6GAL1-catalyzed α2,6-sialylation in glycoproteins. Dynamic hyposialylation in CTCs or deficiency of ST6GAL1 promotes cluster formation for metastatic seeding and enables cellular quiescence to evade paclitaxel treatment in breast cancer. Glycoproteomic analysis reveals newly identified protein substrates of ST6GAL1, such as adhesion or stemness markers PODXL, ICAM1, ECE1, ALCAM1, CD97, and CD44, contributing to CTC clustering (aggregation) and metastatic seeding. As a proof of concept, neutralizing antibodies against one newly identified contributor, PODXL, inhibit CTC cluster formation and lung metastasis associated with paclitaxel treatment for triple-negative breast cancer. SIGNIFICANCE: This study discovers that dynamic loss of terminal sialylation in glycoproteins of CTC clusters contributes to the fate of cellular dormancy, advantageous evasion to chemotherapy, and enhanced metastatic seeding. It identifies PODXL as a glycoprotein substrate of ST6GAL1 and a candidate target to counter chemoevasion-associated metastasis of quiescent tumor cells. This article is featured in Selected Articles from This Issue, p. 1949.

Computational ranking-assisted identification of Plexin-B2 in homotypic and heterotypic clustering of circulating tumor cells in breast cancer metastasis.

Metastasis is the cause of over 90% of all deaths associated with breast cancer, yet the strategies to predict cancer spreading based on primary tumor profiles and therefore prevent metastasis are egregiously limited. As rare precursor cells to metastasis, circulating tumor cells (CTCs) in multicellular clusters in the blood are 20-50 times more likely to produce viable metastasis than single CTCs. However, the molecular mechanisms underlying various CTC clusters, such as homotypic tumor cell clusters and heterotypic tumor-immune cell clusters, are yet to be fully elucidated. Combining machine learning-assisted computational ranking with experimental demonstration to assess cell adhesion candidates, we identified a transmembrane protein Plexin- B2 (PB2) as a new therapeutic target that drives the formation of both homotypic and heterotypic CTC clusters. High PB2 expression in human primary tumors predicts an unfavorable distant metastasis-free survival and is enriched in CTC clusters compared to single CTCs in advanced breast cancers. Loss of PB2 reduces formation of homotypic tumor cell clusters as well as heterotypic tumor-myeloid cell clusters in triple-negative breast cancer. Interactions between PB2 and its ligand Sema4C on tumor cells promote homotypic cluster formation, and PB2 binding with Sema4A on myeloid cells (monocytes) drives heterotypic CTC cluster formation, suggesting that metastasizing tumor cells hijack the PB2/Sema family axis to promote lung metastasis in breast cancer. Additionally, using a global proteomic analysis, we identified novel downstream effectors of the PB2 pathway associated with cancer stemness, cell cycling, and tumor cell clustering in breast cancer. Thus, PB2 is a novel therapeutic target for preventing new metastasis.

Machine learning-assisted elucidation of CD81-CD44 interactions in promoting cancer stemness and extracellular vesicle integrity.

Tumor-initiating cells with reprogramming plasticity or stem-progenitor cell properties (stemness) are thought to be essential for cancer development and metastatic regeneration in many cancers; however, elucidation of the underlying molecular network and pathways remains demanding. Combining machine learning and experimental investigation, here we report CD81, a tetraspanin transmembrane protein known to be enriched in extracellular vesicles (EVs), as a newly identified driver of breast cancer stemness and metastasis. Using protein structure modeling and interface prediction-guided mutagenesis, we demonstrate that membrane CD81 interacts with CD44 through their extracellular regions in promoting tumor cell cluster formation and lung metastasis of triple negative breast cancer (TNBC) in human and mouse models. In-depth global and phosphoproteomic analyses of tumor cells deficient with CD81 or CD44 unveils endocytosis-related pathway alterations, leading to further identification of a quality-keeping role of CD44 and CD81 in EV secretion as well as in EV-associated stemness-promoting function. CD81 is coexpressed along with CD44 in human circulating tumor cells (CTCs) and enriched in clustered CTCs that promote cancer stemness and metastasis, supporting the clinical significance of CD81 in association with patient outcomes. Our study highlights machine learning as a powerful tool in facilitating the molecular understanding of new molecular targets in regulating stemness and metastasis of TNBC.

Better together: circulating tumor cell clustering in metastatic cancer.

Circulating tumor cells (CTCs) are vital components of liquid biopsies for diagnosis of residual cancer, monitoring of therapy response, and prognosis of recurrence. Scientific dogma focuses on metastasis mediated by single CTCs, but advancement of CTC detection technologies has elucidated multicellular CTC clusters, which are associated with unfavorable clinical outcomes and a 20- to 100-fold greater metastatic potential than single CTCs. While the mechanistic understanding of CTC cluster formation is still in its infancy, multiple cell adhesion molecules and tight junction proteins have been identified that underlie the outperforming attributes of homotypic and heterotypic CTC clusters, such as cell survival, cancer stemness, and immune evasion. Future directions include high-resolution characterization of CTCs at multiomic levels for diagnostic/prognostic evaluations and targeted therapies.

ICAM1 initiates CTC cluster formation and trans-endothelial migration in lung metastasis of breast cancer.

Circulating tumor cell (CTC) clusters mediate metastasis at a higher efficiency and are associated with lower overall survival in breast cancer compared to single cells. Combining single-cell RNA sequencing and protein analyses, here we report the profiles of primary tumor cells and lung metastases of triple-negative breast cancer (TNBC). ICAM1 expression increases by 200-fold in the lung metastases of three TNBC patient-derived xenografts (PDXs). Depletion of ICAM1 abrogates lung colonization of TNBC cells by inhibiting homotypic tumor cell-tumor cell cluster formation. Machine learning-based algorithms and mutagenesis analyses identify ICAM1 regions responsible for homophilic ICAM1-ICAM1 interactions, thereby directing homotypic tumor cell clustering, as well as heterotypic tumor-endothelial adhesion for trans-endothelial migration. Moreover, ICAM1 promotes metastasis by activating cellular pathways related to cell cycle and stemness. Finally, blocking ICAM1 interactions significantly inhibits CTC cluster formation, tumor cell transendothelial migration, and lung metastasis. Therefore, ICAM1 can serve as a novel therapeutic target for metastasis initiation of TNBC.

EGFR inhibition blocks cancer stem cell clustering and lung metastasis of triple negative breast cancer.

Triple-negative breast cancer (TNBC) is one of the most aggressive and metastatic breast cancer subtypes lacking targeted therapy. Our recent work demonstrated that circulating tumor cell (CTC) clusters and polyclonal metastasis of TNBC are driven by aggregation of CD44+ cancer stem cells (CSC) and associated with an unfavorable prognosis, such as low overall survival. However, there is no existing therapeutic that can specifically block CTC or CSC cluster formation. Methods: Using patient-derived xenograft (PDX) models, we established an ex vivo tumor cell clustering assay for a pilot screening of blockade antibodies. After identifying EGFR as a target candidate, we modulated the gene expression and inhibited its kinase activity to determine its functional importance in tumor cell clustering and therapeutic inhibition of lung metastasis. We also examined the molecular regulation network of EGFR and a potential connection to CSC marker CD44 and microRNAs, which regulate CTC clustering. Results: We report here that EGFR inhibition successfully blocks circulating CSC (cCSC) clustering and lung metastasis of TNBC. EGFR enhances CD44-mediated tumor cell aggregation and CD44 stabilizes EGFR. Importantly, blocking EGFR by a novel anti-EGFR monoclonal antibody (clone LA1) effectively blocked cell aggregation in vitro and reduced lung metastasis in vivo. Furthermore, our data demonstrated that the tumor suppressor microRNA-30c serves as another negative regulator of cCSC clustering and lung metastasis by targeting CD44 as well as its downstream effector EGFR. Conclusion: Our studies identify a novel anti-EGFR therapeutic strategy to inhibit cCSC aggregation and therefore abolish cCSC cluster-mediated metastasis of TNBC.

Development of novel macrocyclic small molecules that target CTG trinucleotide repeats.

We describe the molecular design, synthesis, and investigation of a series of acridine-triaminotriazine macrocycles that selectively bind to CTG trinucleotide repeats in DNA with minimal nonspecific binding. The limited conformational flexibility enforces the stacking of the triaminotriazine and acridine units. Isothermal titration calorimetry studies and Job plot analyses revealed that the ligands bound to d(CTG) mismatched sites. The acridine and triaminotriazine units were shown to intramolecularly π-stack in aqueous solutions. Compared to a noncyclic analog, the macrocycles showed an almost 10-fold lower cytotoxicity in HeLa cells and up to 4-fold higher transcription inhibition of d(CTG·CAG)74.

Distinct pathological signatures in human cellular models of myotonic dystrophy subtypes.

Myotonic dystrophy (DM) is the most common autosomal dominant muscular dystrophy and encompasses both skeletal muscle and cardiac complications. DM is nucleotide repeat expansion disorder in which type 1 (DM1) is due to a trinucleotide repeat expansion on chromosome 19 and type 2 (DM2) arises from a tetranucleotide repeat expansion on chromosome 3. Developing representative models of DM in animals has been challenging due to instability of nucleotide repeat expansions, especially for DM2, which is characterized by nucleotide repeat expansions often greater than 5,000 copies. To investigate mechanisms of human DM, we generated cellular models of DM1 and DM2. We used regulated MyoD expression to reprogram urine-derived cells into myotubes. In this myogenic cell model, we found impaired dystrophin expression, in the presence of muscleblind-like 1 (MBNL1) foci, and aberrant splicing in DM1 but not in DM2 cells. We generated induced pluripotent stem cells (iPSC) from healthy controls and DM1 and DM2 subjects, and we differentiated these into cardiomyocytes. DM1 and DM2 cells displayed an increase in RNA foci concomitant with cellular differentiation. iPSC-derived cardiomyocytes from DM1 but not DM2 had aberrant splicing of known target genes and MBNL sequestration. High-resolution imaging revealed tight association between MBNL clusters and RNA foci in DM1. Ca2+ transients differed between DM1- and DM2 iPSC-derived cardiomyocytes, and each differed from healthy control cells. RNA-sequencing from DM1- and DM2 iPSC-derived cardiomyocytes revealed distinct misregulation of gene expression, as well as differential aberrant splicing patterns. Together, these data support that DM1 and DM2, despite some shared clinical and molecular features, have distinct pathological signatures.