Extracellular matrix mediates circulating tumor cell clustering in triple-negative breast cancer metastasis

Domain: neuroscience
Published: 2026-02-06
Editorial outcome: major_revision

Abstract
Metastatic tumor cell dissemination is the leading cause of cancer-related deaths. Clustered circulating tumor cells (CTCs) possess higher metastatic potential than single CTCs. Epithelial adherens junction (AJ) proteins typically mediate stable cell-cell interactions; however, these proteins are frequently lost in highly aggressive triple-negative breast cancers (TNBCs), raising the question of how CTCs from such tumors cluster. Here we show that the extracellular matrix (ECM) component hyaluronan (HA) mediates AJ-independent CTC clustering in TNBCs. HA is necessary and sufficient to drive clustering of tumor cells expressing its receptor CD44. Mechanistically, HA initiates contact between neighboring cells through actin-based membrane protrusions. As cells are pulled closer, these initial interactions expand to membrane-membrane contact and are subsequently stabilized by desmosomes. CTC-derived HA also acts as a docking platform to promote heterotypic cluster formation by recruiting non-CTCs, including immune cells. Thus, this ECM–receptor interaction enables CTC clustering and survival under shear stress, enhancing TNBC metastasis.

Introduction
Metastatic spreading of tumor cells to secondary sites remains the major cause of cancer-related deaths. Circulating tumor cells (CTCs) represent an intermediate stage of metastasis and travel through the blood as single cells or as clusters. The latter can be composed solely of CTCs, or exist as heterotypic clusters that include other cell types, such as white blood cells, platelets, or cancer-associated fibroblasts. CTC clusters can arise from collective migration of tumor cells from the primary tumor or by clustering of single CTCs near the vasculature. Compared to single CTCs, clustered CTCs possess significantly higher metastatic potential, highlighting how multi-cell cooperation can overcome natural barriers against metastasis.

Previous studies have shown that stable cell-cell contacts in CTC clusters can be mediated through direct interactions between epithelial adherens junction (AJ) proteins, but these proteins are often lowly expressed or completely absent in the aggressive triple negative breast cancer (TNBC) subtype. These TNBCs, which are highly metastatic and mesenchymal in nature, tend to express alternative adhesion proteins that primarily facilitate cell migration rather than stable cell-cell contacts. Alternatively, TNBC CTCs have been reported to cluster through homotypic interactions of the cell surface receptor CD44. However, CD44 is broadly expressed across most cell types present in the bloodstream, including immune cells, erythrocytes, and platelets. It is thus unlikely that a clustering mechanism solely based on CD44 expression can be utilized in the bloodstream, as it would result in the formation of cell aggregates and emboli in circulation.

In addition to being mediated directly by cell surface proteins, cell-cell interactions can, in principle, also occur through extracellular matrix (ECM) components, allowing neighboring cells to interact by binding to the same ECM molecules. The ECM is a network of macromolecules that represents a key non-cellular component of tissues. It provides structural and mechanical support and acts as a dynamic signaling hub to actively shape the behavior of resident cells. Surprisingly, although CTCs do not reside in a tissue, recent studies have shown that several ECM components are upregulated in breast and pancreatic CTCs. While extensive ECM reorganization affects every stage of the metastatic cascade, most studies focused on ECM remodeling at primary tumor sites and the metastatic niche. Accordingly, if and how ECM components shape tumor cell behavior during circulation and whether the ECM can mediate cell-cell interactions in the bloodstream remains largely unknown.

Here, we show that cells lacking typical epithelial cell-cell adhesion molecules can utilize the ECM component hyaluronan (HA) to form stable cell-cell interactions in a cell-ECM-cell fashion. This interaction is subsequently strengthened through desmosome formation. Furthermore, HA-based mechanism enables TNBC CTCs to form highly metastatic CTC clusters and facilitates seamless incorporation of non-tumor cells into the cluster, thereby further enhancing their metastatic potential.

Results
ECM-associated changes in TNBC include upregulation of HAS2
To determine the cellular components that drive the aggressiveness of TNBCs, we compared TNBC and non-TNBC tumors from The Cancer Genome Atlas (TCGA) breast cancer (BRCA) dataset. Gene ontology (GO) analysis revealed that ECM and plasma membrane genes are enriched in TNBCs compared to non-TNBCs (Fig. 1a), as well as in tumors expressing low levels of E-cadherin, a key component of epithelial AJs (Supplementary Fig. 1a). This suggests that altered ECM dynamics could play a role in promoting the aggressive behavior of TNBCs. Further examination of individual ECM components implicated in breast cancer progression showed a consistent pattern across three independent breast cancer datasets, where hyaluronan synthase 2 (HAS2) was one of the top two most enriched ECM-related genes in the basal-like subtype of tumors, which are predominantly TNBCs (Fig. 1b and Supplementary Fig. 1b–c).

HAS2 encodes an integral membrane protein that synthesizes the major ECM component HA by polymerizing monosaccharides and extruding the growing polysaccharide chain directly into the extracellular space. While HAS1 and HAS3 can also produce HA, HAS2 is the major HA-producing enzyme in breast cancer. Gene set enrichment analysis (GSEA) of HAS2-correlated genes in TCGA-BRCA dataset revealed positive enrichment of ECM-receptor interactions, cancer-associated signaling pathways (Supplementary Fig. 1d), and aggressive tumor signatures, including epithelial-to-mesenchymal transition (EMT), breast cancer metastasis, claudin-low characteristic, and cancer stem cells (Fig. 1c and Supplementary Fig. 1e). These results are consistent with previous studies showing that elevated HA deposition or increased HAS2 expression is associated with poor survival and metastatic status in breast cancer patients. Despite these earlier publications, the direct mechanism by which HA promotes tumor progression has remained elusive.

Since metastases originate from CTCs, we examined the localization of HA in CTCs from the well-established metastatic TNBC mouse model MDA-MB-231-LM2 (LM2). Immunofluorescence (IF) staining revealed that HA coated the surface of LM2 CTCs, indicating that HA remains stably associated with CTCs as they travel through the bloodstream (Fig. 1d). Notably, HA specifically localized to cell-cell interaction sites within CTC clusters (Fig. 1d), raising the possibility that HA enhances the metastatic potential of CTCs by enabling stable CTC-CTC connection in clusters.

Metastatic TNBC cells form clusters and express elevated levels of HAS2
To investigate whether HA indeed facilitates stable cell-cell interactions in clusters, we developed an in vitro tumor cell cluster assay to examine whether tumor cells can form clusters that remain intact while encountering physiological levels of shear stress. In this assay, freshly detached single cells are rotated on an orbital shaker at a frequency of 200 rpm (Supplementary Fig. 1f), which creates approximately 9 dyn/cm2 shear stress. This resembles shearing forces that CTC clusters encounter in larger arteries and smaller veins. Clustering ability was assessed by quantifying the number and size of tumor cell clusters as well as the number of remaining single cells.

Exposing the metastatic TNBC cell line LM2 to this experimental setup resulted in rapid assembly of hundreds of multicellular clusters within one minute (Fig. 1e and Supplementary Fig. 1g). Circulation time of CTCs has been reported to range from minutes to several hours, which prompted us to extend the cluster assay to 1 h and examine the stability of these rapidly formed clusters. We found that LM2 tumor cell clusters remain intact even after 1 h exposure to shear stress and are bigger and tighter (Supplementary Fig. 1g). Similarly, the metastatic TNBC cell lines BT549, WHIM12, and MDA-MB-231 formed highly stable clusters when subjected to the cluster assay (Fig. 1f, g and Supplementary Fig. 1h–j). In contrast, non-metastatic breast tumor cell lines MCF7, BT474, and SKBR3, as well as the non-tumor breast cell lines HMLE and MCF10A, failed to cluster and instead remained as single cells (Fig. 1f, g and Supplementary Fig. 1h–i).

Characterization of stable LM2 tumor cell clusters via electron microscopy (EM) revealed that the cell membranes of connected cells interacted across a maximum length of 3.5 μm with a median gap of 18.6 nm between opposing membranes (Fig. 1h-i and Supplementary Fig. 1k). This gap size is similar to the 10-20 nm reported for AJs; however, these interactions are not mediated by AJs, as the cluster-forming metastatic cell lines lack expression of the crucial AJ component E-cadherin (Supplementary Fig. 1l). Interestingly, all metastatic tumor cells capable of clustering express HAS2, and its expression correlated positively with the number of clusters and negatively with the number of remaining single cells (Fig. 1j and Supplementary Fig. 1m). Together with the specific enrichment of HA at the cell-cell interaction sites inside CTC clusters (Fig. 1d), this suggests that HA produced by HAS2 mediates cell clustering.

HA is required for CTC cluster formation
We developed an IF method to examine HA localization in three-dimensional (3D) cell clusters formed in the cluster assay. IF analysis of LM2 and WHIM12 3D tumor cell clusters revealed that HA is present on the cell surface of clustered tumor cells and is enriched at the cell-cell junctions (Fig. 1k and Supplementary Fig. 1n), which closely resembles the HA localization in CTC clusters isolated from tumor-bearing mice (Fig. 1d). Quantification of HA compared to membrane staining further confirmed the enrichment of HA at cell junctions (Supplementary Fig. 1o). These results reveal that tumor cell clusters formed in the in vitro assay recapitulate aspects of CTC clusters in vivo.

To directly test whether HA facilitates TNBC tumor cell clustering, we treated LM2 cells with the enzyme hyaluronidase (HAse) to degrade HA (Fig. 2a). In contrast to control cells, HAse-treated cells failed to form stable clusters and remained single in the cluster assay (Fig. 2b and Supplementary Fig. 2a). Similar results were obtained when HA was depleted using two independent shRNAs to knockdown (KD) HAS2 (Supplementary Fig. 2b–e) and when treating two additional TNBC cell lines with HAse: PDX-derived WHIM12 and BT549 (Supplementary Fig. 2f). Together, these results support the notion that HA is necessary for TNBC cell clustering.

HA molecules can exist in different sizes and can elicit distinct cellular responses. To assess what form of HA facilitates tumor cell clustering, we treated LM2 HAS2 KD cells for 1 h with increasing concentrations of two different sizes of HA molecules, a low molecular weight (130–150 kDa) HA and a high molecular weight (750–1000 kDa) HA. Incubation with exogenous high molecular weight HA reconstituted clustering capabilities of LM2 HAS2 KD cells in a dose-dependent manner, whereas low molecular weight HA failed to rescue clustering (Supplementary Fig. 2g). These results are consistent with HAS2’s function in producing HA molecules of higher molecular weight and suggest that large HA molecules are required to mediate tumor cell clustering, likely by providing enough interaction sites for HA receptors on two or more tumor cells to stably interact with the same HA moiety.

HA-CD44 interaction is sufficient to induce tumor cell clustering
The above results suggest that metastatic tumor cells rely on HA to connect and form clusters. This prompted us to investigate whether HA binding to its cell surface receptor is required. We knocked out (KO) the major HA receptor CD44 in LM2 cells (Supplementary Fig. 2h) and found that CD44 KO cells failed to cluster (Supplementary Fig. 2i), similar to a previous report. Interestingly, the surface of CD44 KO cells is not coated by HA (Supplementary Fig. 2j), suggesting that CD44 is necessary to retain HA on the cell surface. Importantly, CD44 alone is not sufficient to drive tumor cell clustering, as the TNBC cell line SUM159, which expresses CD44 at levels comparable to that of LM2 (Supplementary Fig. 2k), failed to cluster (Fig. 2c, d). Since SUM159 cells almost completely lack HAS2 expression (Supplementary Fig. 2l) and have no HA coat (Fig. 2e and Supplementary Fig. 2m), we ectopically expressed HAS2 cDNA (Supplementary Fig. 2n). The HAS2-expressing SUM159 cells established an HA coat (Fig. 2f) and acquired the ability to form stable clusters under shear stress (Fig. 2g). These results suggest that HA is sufficient to induce TNBC cell clustering through its receptor CD44.

Our results predict that HA-based cell clustering is mediated through direct interactions between HA and CD44. To test this directly, we performed a reconstitution experiment using non-clustering 293FT cells, which lack endogenous HAS2 and CD44 expression (Supplementary Fig. 2o, p) and co-expressed HAS2 with either wild type CD44 (CD44 WT) or its mutant CD44 R41A (Supplementary Fig. 2q, r). The CD44 R41A mutation disrupts the hydrogen bond interactions between the Arginine residue R41 of CD44 and the polysaccharide sugar chain of HA, thereby abolishing the CD44-HA interaction without affecting CD44 protein conformation (Fig. 2h). 293FT cells co-expressing HAS2 and wild type CD44, but not CD44 R41A, readily formed clusters (Fig. 2i). In contrast to the clear HA coat in CD44 WT expressing cells, only intracellular HA was detected in CD44 R41A expressing cells despite proper surface localization of CD44 R41A (Fig. 2j). These results indicate that the HA-CD44 interaction is both essential and sufficient for cluster formation. Supporting this finding, treatment with the CD44 monoclonal antibody IM7, which blocks the interaction between HA and CD44, significantly reduced tumor cell clustering in LM2, WHIM12 PDX, and HAS2-overexpressing SUM159 cells (Fig. 2k). Thus, HA facilitates stable TNBC cell clustering through interactions with its receptor CD44.

To further generalize our findings in other cancer cell types, we performed the cluster assay using the prostate PC-3, the pancreatic PANC-1, and the glioblastoma DAOY cell lines. All three cell lines express HAS2 and CD44 at similar levels (Supplementary Fig. 2s), formed clusters under shear stress, and lost clustering ability upon HAse treatment (Fig. 2l-m). Together, these results support the notion that the HA-based clustering mechanism is employed by many metastatic cancer types in addition to TNBC cells.

Actin-based cellular protrusions are required for tumor cell clustering
IF analysis of LM2 cells in 3D suspension revealed numerous CD44-positive cellular protrusions. These protrusions radiated outwards from the main cell body with a maximum length of 0.25-0.3 μm, showed a specific enrichment of HA at their tips (Fig. 3a), and their lengths were not affected by HA levels or CD44 expression (Fig. 3b). By greatly expanding the cell surface area, these protrusions likely serve as initial points of contact between neighboring cells, and HA’s localization at their distal tips optimally positions it to initiate cellular interactions. Indeed, when analyzing early cell-cell interaction events in freshly detached cells, we observed that cells formed connections via protrusions that were tightly associated with HA across their full length (Fig. 3c). Interestingly, CD44 and HA staining of neighboring cells grown in 2D also revealed interacting protrusions (Supplementary Fig. 3a).

To understand the cytoskeletal basis of these protrusions, we co-stained LM2 cells in suspension for CD44 and two major cytoskeletal components, actin and tubulin. Actin staining showed a clear overlap with the CD44-marked protrusions (Fig. 3d), whereas tubulin localized just beneath the cell membrane (Supplementary Fig. 3b). Treatment of LM2 cells with the actin depolymerizing drug Latrunculin A, but not the microtubule polymerization inhibitor colchicine, eliminated protrusions and increased cell size (Supplementary Fig. 3c). In addition, cell surface staining of CD44, and especially HA, was markedly reduced in Latrunculin A treated cells (Supplementary Fig. 3c) suggesting that actin is required to properly position CD44, and thereby also HA at the cell surface. Consistent with HA being required for TNBC tumor cell clustering (Fig. 2 and Supplementary Fig. 2), Latrunculin A treatment abolished cluster formation, whereas clustering remained largely unaffected by colchicine (Fig. 3e and Supplementary Fig. 3d). Together, these results suggest that actin is essential for the formation of tumor cell clusters, likely through the formation of cellular protrusions that help organize HA localization (Figs. 2j and 3a).

Cellular protrusions facilitate HA-dependent tumor cell clustering
To investigate whether cellular protrusions play a physical role in the initiation and maturation of cell contacts, we analyzed early cell clustering events using live cell imaging. We found that neighboring cells initiate contact through cellular protrusions, and they subsequently move closer to each other, gradually expanding their contact interface (Fig. 3f, Supplementary Fig. 3e and Supplementary Movies 1–3). Within 30–45 min, this process resulted in the formation of a mature connection, with cells adhering across a large membrane area, similar to the cell-cell interaction sites observed in the EM images (Fig. 1h) and CTC clusters (Fig. 1d).

We also conducted live imaging of mixed LM2 control and CD44 KO cells, as the latter fail to establish an HA coat (Supplementary Fig. 2j). We labeled actin to visualize protrusions and CD44 to distinguish between control (yellow) and CD44 KO (red) cells. Protrusions of neighboring control cells readily initiated contact and ultimately formed tight clusters (Fig. 3g, cyan arrows and Supplementary Movie 4). In contrast, CD44 KO cells failed to establish stable cell contacts with either control or other CD44 KO cells despite being in close proximity (Fig. 3g, yellow arrows and Supplementary Movie 4). During up to 2.5 h of live imaging, the distance between neighboring control cells rapidly decreased as they clustered, whereas neighboring KO cells remained separated by at least 0.5 μm (Fig. 3h), which corresponds to approximately twice the average length of the longest protrusions (Fig. 3b). Collectively, these results suggest that the HA-CD44 interaction is crucial to connect actin-based protrusions of neighboring cells and ultimately enable the formation of tumor cell clusters.

Sliding of protrusions alongside each other enables maturation of cell connections
The above data suggest that once cell-cell contact is initiated at the level of protrusions, cells are gradually pulled closer until they form stable interactions across a large cell surface area (Fig. 3f–h, Supplementary Fig. 3e and Supplementary Movies 1–4). This maturation process could be a consequence of retraction of Head-to-Head connected protrusions, or the result of attached protrusions sliding alongside each other until they finally connect to the opposite cell body. To evaluate these possibilities, we analyzed protrusion attachment types in early cell-cell interactions using EM (Fig. 3i–k and Supplementary Fig. 3f). We observed a clear relationship between the distance separating neighboring cells and the number of their cell-cell connections (Fig. 3j), suggesting that once initial contact is established by a few long protrusions, additional protrusions are progressively recruited during the maturation process.

We identified five categories of protrusion interactions (Fig. 3i and Supplementary Fig. 3f). (1) Head-to-Head, (2) Head-to-Side, (3) Side-to-Side, (4) direct protrusion-membrane interaction, and (5) broad membrane-membrane contacts. Quantifying these interaction types relative to the distance between cells revealed a clear pattern. Long-distance interactions were predominantly Head-to-Head, which transitioned to Head-to-Side and Side-to-Side interactions as cells drew closer, finally culminating in direct membrane-membrane contacts (Fig. 3k). These observations indicate that cells progressively increase their contact area during the maturation of the cell-cell interaction site, ultimately resulting in direct membrane-membrane contacts. These results suggest that the maturation process involves protrusion-guided sliding of cells closer to each other, and not retraction of Head-to-Head connected protrusions. Intriguingly, this HA-mediated clustering mechanism parallels the E-cadherin-mediated AJ formation process (see “Discussion”).

HA promotes cluster stability
The above analysis of the maturation process revealed that cells strive to maximize the surface contact area between neighbors to form stable HA-based cell-cell connections. As shown in Fig. 2, HA is required for tumor cells to establish stable multicellular clusters under shear stress. However, HA has previously been reported to be dispensable for tumor cell aggregation in an assay where cells settle in a low-attachment plate. These seemingly contradictory findings can be reconciled if HA is dispensable for unperturbed cluster formation but required for stable clusters that are capable of withstanding physiological levels of shear stress.

To test this, we formed tumor cell aggregates of LM2 control and HAse-treated cells in a low-attachment plate and subsequently subjected them to increasing amounts of shear stress (Fig. 4a). In agreement with the previous report, LM2 control and HAse-treated cells showed similar numbers of clusters and single cells in the absence of shear stress (Fig. 4a and Supplementary Fig. 4a–c, “no shear stress”). However, cell aggregates formed in the absence of HA were only stable at very low rotational speeds. When subjected to physiological levels of shear stress, HAse-treated aggregates rapidly dissociated into single cells, while control clusters remained largely intact, supporting the notion that HA is required to form stable connections (Fig. 4a and Supplementary Fig. 4a–c, “shear stress”). Similarly, WHIM12 PDX tumor cells required HA to form functional cell clusters capable of withstanding shear stress (Supplementary Fig. 4d–f).

To gain mechanistic insight into how HA stabilizes cell clusters, we next used EM to compare shear stress-free cell aggregates formed in the presence or absence of HA. Cell-free spaces in HAse-treated LM2 cell aggregates were approximately two-fold higher compared to the LM2 control aggregates (Fig. 4b, c and Supplementary Fig. 4g), indicating that cells in HAse-treated aggregates are only loosely associated. Moreover, the interconnectivity between cells in aggregates formed in the absence of HA was limited and control cell aggregates formed a network that was significantly more densely connected (Figs. 4b, d and Supplementary Fig. 4g). Tightly packed cells in control aggregates were mostly cobblestone shaped, whereas HAse-treated cells retained the predominantly round morphology of single cells (Fig. 4b and Supplementary Fig. 4g). Collectively, these findings suggest that HA is required to form stable cell clusters that can withstand physiological levels of shear stress. This stability is achieved by strengthening individual cell-cell contacts through interactions across a larger membrane surface area and by increasing the overall interconnectivity of cells within the cluster. These results show that while HA is dispensable for TNBC cell cluster formation in the absence of shear stress, it is critically required to form functional tumor cell clusters that can withstand the shear stress encountered by CTC clusters in the bloodstream.

Examining the E-cadherin-positive MCF7 cell lines revealed that although they failed to cluster under shear stress (Fig. 1f, g), MCF7 cells can efficiently form clusters when left unperturbed in a low-attachment plate (Supplementary Fig. 4h). Subsequent addition of shear stress did not break apart the clusters, in line with the reported strength of AJ-dependent cell-cell interactions (Supplementary Fig. 4h). This suggests that AJ-dependent clusters likely form under no-shear stress conditions in the tumor bed and shed as intact clusters.

Desmosomes stabilize HA-mediated clusters
The tight interactions observed in fully formed clusters prompted us to investigate whether HA-based clustering recruits additional components to strengthen the cell-cell connection during the maturation of the interaction site. Desmosomes are specialized intercellular junctions that connect to intermediate filaments to stably link neighboring cells together. Desmoglein-2 (DSG2) and Desmocollin-2 (DSC2) are desmosomal cadherins that mediate adhesive binding between adjacent cells, while Desmoplakin (DSP) is the intracellular scaffold protein that anchors these cadherins to intermediate filament of the cytoskeleton. Interestingly, recent reports showed that elevated DSG2 expression increased prevalence of CTC clusters and metastasis and that DSC2 and DSP were associated with increased cluster formation and CTC survival in breast and lung cancer cells.

These findings prompted us to investigate whether desmosomes are involved in HA-based clustering of tumor cells as LM2 cells express DSG2, DSC2, and DSP (Supplementary Fig. 4i). Assessing their localization in clustered LM2 cells, we found all three desmosome proteins localized to the fully established cell-cell interaction sites, indicating that they mechanically couple neighboring cells in mature clusters (Fig. 4e). In contrast, in early cell-cell interactions where cell morphology is still largely round and cell membrane contacts are limited to a small area, only HA, but not DSG2, DSC2 or DSP, is enriched at the cell contact site (Supplementary Fig. 4j). This suggests that desmosomes are established after large areas of the cell membranes are brought into close proximity via HA-based interactions.

To determine whether desmosomes promote HA-based clustering by strengthening cell-cell interactions, we knocked down DSG2, DSC2, and DSP individually in LM2 cells (Supplementary Fig. 4i). Next, we performed cell clustering experiments with gradually increasing levels of rotational speed. All three KD cell lines formed clusters at 200 rpm, but they rapidly dissociated at higher shear forces, indicating reduced stability compared to control cell clusters (Fig. 4f, g). Of note, control cell clusters started to break into smaller clusters at ~350 rpm (Fig. 4f), which was not the case when cell-cell interactions were established in the absence of shear stress over a period of 24 h (Fig. 4a). Taken together, these results suggest that HA-mediated initial cell contacts enable the subsequent assembly of desmosomes, which effectively lock in these interactions and mechanically stabilize the clusters.

HA-based clustering increases cell survival under shear stress
Shear stress not only challenges cluster stability but also poses a threat for CTC survival. To examine the impact of HA on tumor cell survival under shear stress, we analyzed cell death in a time course experiment. HA depletion decreased cell survival, showing significant differences from 16 h onwards. At 24 h, only 20–25% of the HAse-treated or HAS2 KD LM2 cells were alive, compared to 65% of the control cells (Supplementary Fig. 5a–c). Similarly, HAse treatment reduced survival of WHIM12 PDX cells (Supplementary Fig. 5b, right), suggesting that HA-mediated clustering reduces shear force-induced cell death.

Shear stress induces the production of reactive oxygen species (ROS), which in turn triggers cell death. Since cell clustering can limit ROS production, we tested whether oxidative stress contributes to the increased shear stress-induced cell death in HA-lacking cells. Compared to untreated wild type cells, shear stress exposure elevated ROS levels in both control and HAse-treated LM2 cells at 12 h (Supplementary Fig. 6a, b), a time point preceding extensive cell death of HAse treated cells (Supplementary Fig. 5a). However, the ROS levels were more than two-fold higher in single HAse-treated cells compared to clustered control (Supplementary Fig. 6a), suggesting that HA-mediated clustering promotes CTC survival by limiting shear stress-induced ROS production. Indeed, addition of the antioxidant N-acetylcysteine (NAC) to repress ROS partially rescued cell death of HAse-treated single cells (Supplementary Fig. 6c). These results indicate that HA-mediated clustering at least partially shields tumor cells from shear stress-induced cell death.

HA is required for CTC clustering and metastasis in vivo
Increased HA synthesis, HAS2 expression, and cell-surface bound HA have all been linked to increased metastatic potential in breast and melanoma cancers, whereas loss of HAS2 is correlated with reduced metastasis. Despite these observations, the direct mechanism of how lack of HA production negatively impacts the complex metastatic process remains elusive. Our finding that HA is required for the formation of stable TNBC cell clusters has therefore the potential to provide a mechanistic explanation for these observations.

Based on our in vitro results, we hypothesized that HA-lacking CTCs may have reduced metastatic colonization ability as they are more susceptible to shear stress-induced cell death (Supplementary Figs. 5–6). To test this hypothesis, we injected LM2 control and HAS2 KD cells via tail vein in female NSG mice and examined their lungs for the presence of GFP-positive tumor cells 24 h later. Indeed, HAS2 KD tumor cells were present in fewer numbers in the lungs compared to control cells (Supplementary Fig. 7a). Additionally, a Matrigel-based in vitro invasion assay revealed that HA-lacking single cells have reduced invasive capacity compared to clustered control cells (Supplementary Fig. 7b). Together, these results indicate that HA-mediated clustering protects tumor cells from shear-stress induced cell death and promotes invasion to enhance metastatic colonization and outgrowth.

To determine the role of HA in spontaneous CTC clustering and metastasis in vivo, we injected LM2 control and HAS2 KD cells into the mammary fat pad of female NSG mice (Fig. 5a). Tumors were collected 8 weeks after injection and continued HAS2 KD was verified (Supplementary Fig. 7c). Histological analysis of the lungs revealed that HAS2 KD led to a more than 5-fold decrease in lung metastasis (Fig. 5b, c). Importantly, this difference is not a consequence of reduced tumor outgrowth as HAS2 KD did not significantly alter primary tumor growth in mice (Fig. 5d-e and Supplementary Fig. 7d), consistent with their similar in vitro growth rates (Supplementary Fig. 7e) and an unaltered Ki67-based proliferation index in vivo (Supplementary Fig. 7f). Analysis of blood samples (Fig. 5f) showed that HAS2 KD resulted in a drastic reduction in total CTC numbers (Fig. 5g), with 75-fold and 82-fold reduction of single and clustered CTCs, respectively (Fig. 5h and Supplementary Fig. 7g). CTC clusters were detected in all 5 control mice, compared to only 4 out of 7 mice in the HAS2 KD group. Moreover, while control CTC clusters ranged in size from 2 to 22 CTCs per cluster, all observed CTC clusters in HAS2 KD mice were limited to only 2 CTCs per cluster (Fig. 5i). IF staining of CTC clusters from control mice revealed strong HA accumulation at CTC interaction sites (Fig. 5j and Supplementary Fig. 7h, i), consistent with our previous observations (Figs. 1d, k and Supplementary Fig. 1n, o). These results indicate that HA is essential for CTC clustering, which in turn enhances TNBC metastatic potential.

To determine whether the reduced metastasis of HAS2 KD TNBC cells is a consequence of their inability to form functional HA-mediated CTC clusters, we utilized the experimental metastasis model by injecting LM2 control and HAS2 KD cells via the tail vein. By avoiding potential confounding effects of HAS2 KD on the primary tumor microenvironment, tumor cell migration, and intravasation, this experiment allowed us to assess the stability of tumor cell clusters in the bloodstream more directly. LM2 control and HAS2 KD cells were allowed to form aggregates overnight without shear force and similar-sized clusters containing 5–10 tumor cells each were injected into the tail veins of female NSG mice (Fig. 5k). While similar numbers of both control and HAS2 KD cells reached the lung vasculature upon injection (Fig. 5k, l Day 0), clear differences in metastatic lung signal are detectable from one week onwards (Fig. 5k, l and Supplementary Fig. 7j). At the experimental endpoint of 4 weeks, the HAS2 KD group exhibited a significant decrease in lung metastasis by more than 4-fold. Histological analysis of the lungs revealed reduced tumor burden in the HAS2 KD group (Fig. 5m), consistent with our findings from the spontaneous metastasis model (Fig. 5b, c). Ki67 staining of the metastatic lungs was the same between LM2 control and HAS2 KD tumor cells (Supplementary Fig. 7k), indicating that the decreased lung metastasis was not a consequence of altered tumor cell growth. Instead, as shown earlier (Supplementary Figs. 5 and 6), the HAS2 KD cells likely arrived in the lungs in a worse condition and failed to invade (Supplementary Fig. 7a, b), resulting in reduced initial colonization. Analysis of blood samples showed that CTCs were present in 6 out of 7 control mice, but only in 2 out of 7 in the HAS2 KD group (Supplementary Fig. 7l), with one of the two KD mice having barely any CTCs (Fig. 5n). HAS2 KD resulted in greater than a 100-fold reduction in CTC numbers (Fig. 5n), including both clustered and single CTCs (Fig. 5o and Supplementary Fig. 7m). Consistent with the spontaneous metastasis experiment, HAS2 KD drastically decreased CTC cluster numbers and size. Control CTC clusters were detected in 6 out of 7 mice, with the cluster size ranging from 2 to 18 CTCs per cluster. In contrast, only 1 out of 7 mice in HAS2 KD group had clusters, which were limited in size to 2–4 CTCs per cluster (Fig. 5p). Noticeably, a small amount of HA was detectable at cell-cell interaction sites in HAS2 KD CTC clusters (Supplementary Fig. 7n), suggesting that their formation could be mediated by residual HA.

The significance of HA in CTC clustering was further supported by IF staining of CTCs from control mice. Several key features identified in our in vitro cluster assay (Figs. 2 and 3) were recapitulated in these CTC clusters: HA was enriched at the cell-cell interaction sites (Fig. 5q, r), and we detected both early interaction events involving HA-tipped protrusions (Fig. 5q, Supplementary Fig. 7o, p and Supplementary Movie 5) as well as fully matured connections in large clusters (Fig. 5r and Supplementary Fig. 7q). Looking at early CTC clustering in 3D revealed two cells connected at a small membrane region, which was surrounded by interlocked protrusions of varying lengths. Reminiscent of our in vitro results (Fig. 3f–k and Supplementary Fig. 3e, f), these protrusions appeared to be sliding alongside each other to bring both CTCs closer together and expand and stabilize the contacting area (Supplementary Movie 5). As HA localized to both interacting protrusions and the directly contacting areas of CTCs, these results suggest that HA enhances TNBC metastasis in vivo by enabling the formation of stable CTC clusters.

HA facilitates interactions between CTCs and non-CTCs
Tumor heterogeneity is a key feature that enables tumors to adapt to new environments and develop therapeutic resistance. Accordingly, CTC clusters can be composed of highly diverse CTCs. Although HA-deficient cells are unable to cluster on their own, the HA coat of one CTC could, in principle, serve as a docking site to recruit HA-lacking cells that express an HA receptor. Such a mechanism would enable the formation of heterogeneous CTC clusters, where HA-producing and HA-lacking tumor cells combine their respective capabilities to increase the metastatic potential of the whole CTC cluster.

To test this hypothesis, we mixed RFP-tagged LM2 cells with GFP-tagged HAS2 KD LM2 cells in a 1:1 ratio. Even though HAS2 KD cells were unable to cluster on their own, 60% of them readily integrated into clusters with control cells (Fig. 6a and Supplementary Fig. 8a). In a similar experimental setup, LM2 CD44 KO cells failed to integrate into control cell clusters (Fig. 6b and Supplementary Fig. 8b), emphasizing the necessity of an HA receptor for inclusion into HA-mediated clusters. IF analysis of early cell-cell interactions between LM2 control and HAS2 KD cells revealed a partial translocation of HA from the control cells toward the HAS2 KD cells (Fig. 6c and Supplementary Fig. 8c). Upon full maturation of the cell-cell interaction site in mixed clusters, an enrichment of HA from control cells at the interactions sites between control and HAS2 KD cells is apparent (Fig. 6d and Supplementary Fig. 8d). These results reveal that the HA coat presented by CTCs can recruit HA-lacking CTCs that express the HA receptor CD44 into CTC clusters.

To evaluate this process in vivo, we pre-formed cell aggregates of RFP-tagged control and GFP-tagged HAS2 KD LM2 cells mixed at a 1:1 ratio and injected them into the tail vein of female NSG mice (Fig. 6e). After 4 weeks, we analyzed the number of CTCs originating from control and HAS2 KD cells in each mouse and observed a 4-to 12-fold reduction of CTCs originating from HAS2 KD cells (Fig. 6f). Furthermore, 64.4% of CTC clusters were composed solely of control LM2 cells, 31.4% contained a mixture of both control and HAS2 KD cells, and the remaining 4.2% consisted exclusively of HAS2 KD cells (Fig. 6g). Analysis of the individual mixed clusters revealed that the majority of CTCs in each mixed cluster were control cells (Fig. 6h). In accordance with our observations for mixed in vitro clusters (Fig. 6d), HA derived from control CTCs was enriched at their cell interaction sites where they connected to HAS2 KD CTCs (Fig. 6i).

We next analyzed HA localization in blood specimens from five TNBC patients. CTCs from patient blood were identified using a cocktail of the gold standard CTC markers (Pan-Cytokeratin, EpCAM, and EGFR). CTC clusters were detected in three of the TNBC patients. These CTCs displayed a prominent HA coat, and a clear HA enrichment was found at CTC-CTC contact sites, both in clusters where all CTCs produced HA (Supplementary Fig. 8e) and when only one CTC provided the HA necessary for the interaction (Fig. 6j). One TNBC patient had HA-coated CTCs, but no CTC clusters were detected, and the last TNBC patient only had single CTCs without an HA coat. These results reiterate the importance of HA in TNBC CTC clustering and also show that HA-coated CTCs are capable of recruiting HA-lacking CTCs into CTC clusters.

In addition to heterogeneous CTC clusters, we also observed HA enrichment in heterotypic clusters consisting of CTCs and non-CTCs in mice (Fig. 6k–m and Supplementary Fig. 8f–i). CD44 staining revealed that a small number of protrusions from non-CTCs interacted with HA-tipped CTC protrusions during early interactions (Fig. 6k, left, Fig. 6l and Supplementary Fig. 8f). This example further supports the notion that neighboring cells can attach to CTCs by binding to the same HA moiety. The distinct localization pattern of HA often shifted from a widespread HA coat covering an unattached single cell (Fig. 2a) to a concentrated accumulation at the cell-cell interaction sites (Supplementary Fig. 8g), indicating that CTC-produced HA mediates the interactions with non-CTCs. Some of these non-CTCs expressed the mouse neutrophil marker Ly6G (Fig. 6k, right, 6m and Supplementary Fig. 8h, i), indicating that neutrophils, which are known to be part of heterotypic CTC clusters, can be recruited to CTC clusters via HA. Moreover, HA enrichment at interaction sites between CTCs and non-CTCs was also observed in metastatic TNBC patient blood specimens (Fig. 6n). Thus, HA-based clustering can facilitate the formation of heterotypic CTC clusters.

Methods
Ethics
All animal procedures were performed with approval from the Institutional Animal Care and Use Committee at Baylor College of Medicine (Protocol number AN-7145). For human sample analysis, de-identified blood samples from breast cancer patients were obtained after receiving their informed consent as per the institutional review board (IRB) at Baylor College of Medicine.

Cell lines and transfection
All cell lines were maintained at 37 °C in 5% CO2 and passaged every 2–3 days. Base medium for all cell lines was supplemented with penicillin and streptomycin. MDA-MB-231, LM2, MCF7, 293FT, PANC-1, and DAOY cells were cultured in DMEM supplemented with 10% FBS. BT474 cells were cultured in RPMI 1640 supplemented with 10% FBS. SKBR3 cells were cultured in McCoy’s 5A supplemented with 10% FBS. BT549 cells were cultured in RPMI 1640 supplemented with 10% FBS and 10 μg/mL insulin. SUM159 cells were cultured in F12 supplemented with 5% FBS, 10 mM HEPES, 5 μg/mL insulin, and 1 μg/mL hydrocortisone (HC). MCF10A were cultured in DMEM supplemented with 5% horse serum, 20 ng/mL EGF, 0.5 μg/mL HC, 100 ng/mL cholera toxin, and 10 μg/mL insulin. WHIM12 cells were cultured in DMEM/F12 (1:1) supplemented with 10% FBS, 0.1X ITS-X (Thermo Fisher 51500056), 10 ng/mL EGF, 50 ng/mL 3,3’,5-triiodo-L-thyronine, and 10 ng/mL HC. PC-3 cells were cultured in RPMI 1640 supplemented with 10% FBS, L-glutamine, and 10 mM HEPES. MDA-MB-231 and its derivative LM2 were obtained from Dr. Yibin Kang. HMLE from Dr. Jing Yang, MCF10A from Dr. Alexander Minella, BT474 from Dr. Charles V. Clevenger, SUM159 from Dr. Robert Weinberg, WHIM12 from Dr. Matthew Ellis, MCF7 from Dr. Marcus Peter, SKBR3 from Dr. Vince Cryns, PC-3 from Dr. Raymond Bergan, and DAOY from Dr. Richard Hurwitz. 293FT and BT549 were purchased from ATCC. PANC-1 was purchased from BCM Molecular and Cellular Biology Tissue Culture Core Laboratory.

For HA depletion experiments, cells were treated with 500 U/mL of crude Hyaluronidase from bovine testes (Sigma H4272) or 1.5 U/mL of purified Hyaluronidase from Streptomyces hyalurolyticus (Sigma H1136). For exogenous HA treatment, cells were pre-incubated for 1 h with the indicated concentration and size of HA (Sigma 75043 and 53163) in a low-attachment plate prior to clustering. To inhibit cytoskeletal dynamics, attached cells were treated for 1.5 h with 5 μM of Latrunculin A (Sigma 428026) or with 10 μM of Colchicine (Sigma C9754).

For transient expression, 293FT cells were transfected using the X-tremeGENE™ HP DNA Transfection Reagent (Roche 6366236001) and analyzed after 48 h. Retroviral or lentiviral infections were performed for generation of stable cell lines. Plasmids used for HAS2 expression (pLX304-HAS2) or shRNA-mediated HAS2 knockdown #1 (pLKO.1-shHAS2 #1) were described previously. The plasmid for shRNA-mediated HAS2 knockdown #2 (targeting sequence: 5′-GCCATGCTTATGTGGGTTAT-3′) was cloned into pLKO.1 backbone using AgeI and EcoRI restriction enzymes. shHAS2 #1 was used for experiments unless otherwise specified. The plasmids for DSG2 knockdown (targeting sequence: 5′-GCTCAAACTAACGAAGGAATT-3′), DSC2 knockdown (targeting sequence: 5′-TAGCAGTGGCATAAGGTATAA-3′), and DSP knockdown (targeting sequence: 5′-GCAGAATGATTCACAAGCAAT-3′) were cloned in the same manner. EFS-GFP was a gift from Michael Lewis (Addgene plasmid #110834). pWPT-RFP was kindly provided by Xiang Zhang. These two plasmids were used to tag LM2 cells with GFP or RFP. pBRIT-CD44-HA was used to express CD44 in 293FT cells. The R41 residue of CD44 was mutated to Alanine using the Quick Protocol for Q5® Site-Directed Mutagenesis Kit (NEB E0554) according to the manufacturer’s instructions. Lentiviral CRISPR/Cas9 was used to generate LM2 CD44 KO cells with a gRNA targeting exon 1 of CD44 (fwd: 5′-CACCGAGTTTTGGTGGCACGCAGCC-3′; rev: 5′-AAACGGCTGCGTGCCACCAAAACTC-3′).

Antibodies and other reagents
For immunofluorescence, the following antibodies were used: CD44-IM7 (Santa Cruz Biotechnology sc-18849; 1:100), DSG2 (Proteintech 21880; 1:100), DSC2 (ABclonal A10211; 1:100), DSP (ABclonal A7635; 1:100), Tubulin (Proteintech 11224-1-AP; 1:100), Ki67 (eBioscience 14-5698-82; 1:100), GFP (Abcam ab13970; 1:100), RFP (Rockland 600-401-379; 1:100), Ly6G-AF594 (Biolegend 127636; 1:50), Pan-cytokeratin (Santa Cruz Biotechnology sc-8018; 1:100), Cytokeratin 19 (Invitrogen MA5-12663; 1:100), EpCAM-AF488 (Cell Signaling 5198S; 1:50), and EGFR-AF488 (Biolegend 352908; 1:50). Biotinylated HA binding protein (Millipore 385911; 2 μg/mL) was used to detect HA and AF568-coupled phalloidin (Thermo Fisher A12380; 1:100) to detect actin. For immunoblotting, the following antibodies were used: CD44 (R&D BBA10; 1:1000), HA tag (Cell Signaling 3724S; 1:1000), E-cadherin (Cell Signaling 3195S; 1:2000), HAS2 (Santa Cruz Biotechnology sc-514737; 1:500), DSG2 (Proteintech 21880; 1:1000), DSC2 (ABclonal A10211; 1:1000), DSP (ABclonal A7635; 1:1000), GAPDH (Millipore MAB374; 1:3000), and β-actin (Sigma A1978; 1:3000).

Bioinformatics analysis
The TCGA BRCA RNAseq expression dataset was downloaded from the GDC portal (https://portal.gdc.cancer.gov). METABRIC breast cancer expression dataset was downloaded from the cBioPortal (https://www.cbioportal.org). CCLE expression dataset was downloaded from Broad Institute’s DepMap Portal (https://depmap.org/portal). Each dataset’s internal PAM50 classification was used to divide tumor samples by subtype. For the heatmaps, z-score normalization was performed for each gene across all samples and plotted. Differential gene expression analysis of TNBC vs. non-TNBC tumors was conducted using DESeq2 performed on genes with at least 5 counts present in at least half of the samples. To determine the differential gene expression of tumors expressing low vs. high levels of E-cadherin, the bottom 10% (E-cadherin_low) and top 10% (E-cadherin_high) of all breast cancer samples based on their E-cadherin expression were compared. To characterize the cancer processes associated with HAS2, we first filtered out low abundance genes that have less than 5 reads across half of the samples in TCGA BRCA. We then applied log2-tranformed counts per million (CPM) normalization and the trimmed mean of M-values (TMM) adjustment on the count matrix, after which correlation coefficient of HAS2 expression with each gene was calculated using Pearson correlation. GSEA was performed with our in-house script, using fgsea on genes ranked by log2FC with 1000 gene set level permutations and considering gene sets of size 15–500 genes. Gene ontology (GO) cellular component analysis and GSEA KEGG pathway analysis were both conducted using WebGestalt (https://www.webgestalt.org) with the default settings. For GO analysis, the top 500 upregulated genes were uploaded. For GSEA, the correlation coefficient of the whole transcriptome to HAS2 gene expression was used to pre-rank the genes. We utilized our own curated signatures as well as metastasis signature derived from the C2 collection in MSigDB (https://www.gsea-msigdb.org/gsea/msigdb).

Cluster assay
Cells were detached using TrypLE Express (Gibco 12605010) and resuspended in fresh growth media to obtain a single cell suspension. 100K cells were transferred to 500 μL of growth media in a 12 well plate, which was immediately placed on an orbital shaker at 37 °C in 5% CO2. Alternatively, 50K cells were placed in 250 μL of growth media in a 24 well plate, keeping the ratio of number of cells to total volume consistent. The plate was agitated at 200 rpm for 1 h. Afterwards, each entire well was scanned using the IncuCyte® S3 live imaging system (Sartorius). ImageJ (v1.54.f) was used to quantify the number and size of single cells and clusters. Particles between 1 and 100 pixels2 were categorized as single cells, while particles greater than 700 pixels2 (roughly representing a cluster of 5–10 or more cells) were categorized as clusters.

For no shear stress condition, 50K cells were seeded in 250 μL of growth media in a low-attachment 24 well plate and allowed to aggregate for 24 h. Plates were scanned using IncuCyte as described above to quantify no shear stress, or 0 rpm, clustering. Next, these plates were placed on an orbital shaker and agitated at increasing speeds in 50 rpm increments, from 100 rpm to 350 rpm. For desmosome knockdowns, stability of clustering cells was examined by first inducing cluster formation for 30 min at 200 rpm, followed by agitation at increasing speeds in 50 rpm increments from 250 rpm to 350 rpm. For each speed, plates were agitated for 15 min, imaged using IncuCyte to measure changes in clustering, and subsequently placed back on the shaker at the next speed. Alternatively, after 6 h of aggregation in low-attachment plates and imaging, cells were agitated at 200 rpm for 1 h and imaged.

HA-CD44 interaction blocking assay
Cells were seeded in a 6 well plate and allowed to grow to 70% confluency for two days. At this point, the old media was replaced with 1 mL of fresh growth media containing 10 μg/mL of Rat IgG control (BioXcell BE0089) or CD44-IM7 (BioXcell BE0039) antibody. After 3 h of antibody treatment, cells were detached to perform the cluster assay.

Quantitative RT-PCR
RNA was extracted using the E.Z.N.A Total RNA Kit I (Omega Bio-Tek), and cDNA was generated using GoScript Reverse Transcription System (Promega). qRT-PCR was performed using GoTaq qPCR Master Mix (Promega). For every biological replicate, mRNA expression of two technical replicates was averaged and normalized to mRNA expression of TATA-binding protein (TBP). The following primers were used: HAS2 (fwd: 5′-AGAGCACTGGGACGAAGTGT-3′; rev: 5′-ATGCACTGAACACACCCAAA-3′), CD44 (fwd: 5’-TACTGATGATGACGTGAGCA-3’; rev: 5’-GAATGTGTCTTGGTCTCTGGT-3’) and TBP (fwd: 5′-GGAGAGTTCTGGGATTGTAC7-3′; rev: 5′-CTTATCCTCATGATTACCG-CAG-3′).

Immunoblotting
Cells were harvested in RIPA lysis buffer (2% NP-40, 1% Sodium Deoxycholate, 0.2% SDS supplemented with 1x protease inhibitor cocktail in PBS) and lysed for 30 min on ice. Lysates were cleared via centrifugation, and protein concentration was measured using Bradford protein assay (Bio-Rad 500-0006). For the HAS2 blot, instead of loading equal amounts of protein, lysates derived from the same amount of cells were not cleared through centrifugation but directly boiled in SDS sample buffer and loaded in equal volumes. Samples were boiled in SDS sample buffer, and 20 μg of protein per sample was subjected to electrophoresis by 4–20% SDS-PAGE (Genscript) and transferred to a methanol activated PVDF membrane (GE 10600023). Membranes were blocked with 5% milk in TBST for 30 min at room temperature (RT) and then incubated in primary antibodies overnight at 4 °C. The next day, membranes were washed thrice in TBST and incubated in the corresponding HRP-conjugated secondary antibodies for 1 h at RT. After final TBST washes, membranes were imaged using a ChemiDoc (Bio-Rad) with Immobilon Western Chemiluminescent HRP Substrate (Millipore).

Immunofluorescence
Cells were either grown and fixed on glass coverslips or detached using TrypLE Express (Gibco 12605010) and fixed directly in solution as single cells or subjected to the clustering assay for 15–90 min. For membrane staining, 1000x dye stock solution of CellBrite® Fix 555 Membrane Stain (Biotium 30088) was added at a 1:400 dilution for the last 15 min of the clustering assay. Tumor cell clusters were transferred into a μ Slide 8 well Glass Bottom (Ibidi 80827), and after 5 min of settling onto the slide, liquid was carefully removed while observing the chamber under a light microscope. This results in spreading of the clusters across the glass bottom when surrounding liquid disappears. Before fixation, remaining liquid was allowed to evaporate for 5–10 min.

For all staining, fixation was performed for 10 min at RT in PBS containing 4% Paraformaldehyde (Fisher Scientific AA433689M) and 0.1% Glutaraldehyde (Electron Microscopy Sciences 16019). When required, samples were permeabilized for 10 min in PBS/0.1% Triton and endogenous biotin was masked using Avidin/Biotin Blocking Solution (Sakura #10-0039). Cells were blocked for at least 1 h in PBS/2% Bovine Serum Albumin (VWR 0332-25G) and incubated in primary antibody and biotinylated HA binding protein (Millipore 385911) overnight at 4 °C. Following three washes in PBS, samples were incubated in PBS containing the respective Alexa Fluor (AF)-coupled secondary antibodies and/or Streptavidin AF647 (Molecular Probes S21374) for 1 h at RT. After three additional washes in PBS, samples were mounted in ProLong™ Diamond Antifade Mountant with DAPI (Thermo Fisher P36971). For staining with any primary AF-conjugated antibodies, samples were incubated at RT for 2 h. Note: to keep the structure of IF images consistent throughout the manuscript, green pseudocolor was chosen for HA, despite it being imaged in the far-red channel using Alexa Fluor 647-coupled streptavidin. For presentation purposes, pseudo green and red colors were also used in samples that included GFP-/RFP-positive cells.

Microscopy and image analysis
Images were acquired using a GE Healthcare DeltaVision LIVE High Resolution Deconvolution Microscope and were deconvolved using softWoRx Explorer or an Olympus IX83 epifluorescence deconvolution microscope. Images of fixed cells were taken as 50–65 z stacks of 0.2 μM increments using a 100× oil immersion objective. Quantification of signal intensities was performed using Fiji. Enrichment of HA/CD44 was quantified by averaging signal intensities of five different areas across the cell-cell interaction site (“cell junction”) or five different areas that are not in contact with neighboring cells (“non-junction”). For enrichment of HA/total Membrane, an equal number of “cell junction” and “non-junction” regions were quantified for HA and membrane signal, and HA signal divided by membrane signal. Protrusion length was determined by averaging the lengths of the five largest protrusions per cell.

Time-lapse imaging was performed with 25 z stacks of 0.4 μM increments using a 60× oil immersion objective and a time-lapse of 5 min. Cells were detached as described for the cluster assay and transported as a single cell solution to the microscope. There, cells were transferred to a μ Slide 8 well Glass Bottom (Ibidi 80827) and the imaging run was initiated.

Electron microscopy
Cells were detached as described for the cluster assay and either placed in 6-well low-attachment plates and treated with DMSO or HAse for 16 h to induce gravity-based cell aggregation or clustered in the cluster assay for 5, 10, and 20 min to capture early-to-mid clustering events. Formed clusters were transferred into tubes and spun down at 500g for 5 min. Pelleted clusters were placed in scintillator vials with 2.5% Paraformaldehyde and 2% Glutaraldehyde in 0.1M Sodium Cacodylate buffer and placed on a rotator in a cold room overnight. The next day the cell pellets were processed inside a Ted Pella Bio Wave Vacuum Microwave and cells were re-pelleted after initial reagent changes. Samples were fixed again for 1 min at 650 watts, followed by 3 rinses with 0.1M Sodium Cacodylate buffer for 40 seconds at 150 watts. Pellets were post-fixed at 100 watts for two 2-min on-off-on cycles of 1% buffered Osmium Tetroxide. Pellets were then rinsed thrice with Millipore water at 150 watts for 40s. Aqueous Ethanol concentrations from 25 to 100% were used as the initial dehydration series for 40s each at 150 watts, followed with 3 Propylene Oxide changes as a final dehydrant for 40s at 150 watts each. Samples were gradually infiltrated using a graded series of Propylene Oxide and Embed 812 resin for 3 min each at 250 watts. Finally, the samples were infiltrated with 3 changes of pure resin at 250 watts for 3 min each under vacuum. Samples were allowed to infiltrate further in pure resin overnight on a rotator at RT. The samples were embedded into regular Beem capsules and cured in the oven at 62 °C for 3 days. The polymerized samples were sectioned into 50–55 nm silver sections. Blocks were thin sectioned at 50–55 nm silver sections on a Leica UC7 Ultra-microtome and placed on formvar coated copper slot grids. Sections were stained with 1% Uranyl Acetate for 13 min and Lead Citrate for 2 min. Micrographs were taken on a JEOL 1400Plus TEM with a mid-mount AMTR16 TEM camera.

Proliferation assay
25K LM2 control and HAS2 KD cells were seeded per well in 24 well plates in normal growth media. Plates were scanned using IncuCyte® S3 live imaging system every 4 h for 2 days. Cell confluency was analyzed at each time point to generate a cell proliferation curve.

Cell survival assay
Cells were detached using TrypLE Express and resuspended in DMEM supplemented with 0.5% FBS. 100K cells in 500 μL of DMEM supplemented with 0.5% FBS and either DMSO or HAse were seeded in each well of a 24 well plate, which was immediately placed on an orbital shaker at 37 °C in 5% CO2. Cells were agitated at 200 rpm for 6, 16, or 24 h. For each condition, cells from 3 wells were combined to obtain enough material for analysis. For the rescue experiment, cells were treated with 5 mM N-acetylcysteine (NAC; Sigma A9165) during the 24 h of agitation. At the end of the time point, cells were first manually counted with a Hemocytometer to determine the remaining number of cells in each sample. Then, they were spun down in flow tubes at 500g for 5 min. Pellets were resuspended into a single cell suspension in PBS and stained with Propidium Iodide (PI; BD Pharmingen 556463, 1:250 dilution) for 15 min at RT in the dark. Samples were immediately run on CytoFLEX benchtop flow cytometer (Beckman Coulter CytExpert v2.4.0.28) to assess PI staining and FlowJo v10 was used to quantify cell viability.

For ROS measurement, cells were prepared similarly, but they were agitated for 12 h. At the same time, a portion of the detached cells (“wild type”) was placed in a low-attachment plate without any agitation to use for signal normalization. At the end of the time point, cells were incubated in PBS containing ROS Deep Red dye (Abcam ab186029; 1:1000) for 30 min at 37 °C in the dark. CytoFLEX benchtop flow cytometer and FlowJo were used to determine ROS levels.

Matrigel invasion assay
LM2 cells were starved in serum-free DMEM for 24 h prior to this assay. To generate tumor cell clusters, 25K of the starved LM2 control cells were placed in a low-attachment 24 well plate in serum-free DMEM and subjected to the clustering assay for 1 h at 200 rpm. For the HAse condition, 25K of the starved LM2 cells were incubated in suspension with HAse in serum-free DMEM for 1 h at 37 °C, without any shear force. Next, control clusters and HAse-treated single cells were transferred to Matrigel invasion chambers (Corning 354480), which had been equilibrated for 2–4 h at 37 °C in serum-free DMEM. At the same time, DMEM supplemented with 10% FBS was added as a chemoattractant to the wells of the 24-well plate containing the Matrigel chambers. Cells were allowed to invade through the Matrigel to the exterior of the chamber. After 24 h, cells from the interior of the chamber were removed using a cotton swab, while cells on the exterior were stained using crystal violet dye. Invading cells were imaged using a light microscope and quantified via ImageJ (v1.54.f).

Mice
Mice were housed in a 14:10 h light/dark cycle at an ambient temperature of 20–23 °C. Humidity was maintained between 30-70%. NSG mice (NOD.Cg-Prkdcscid Il2rgtm1Wjl/SzJ) were originally obtained from Jackson Laboratory. Female mice were utilized in this study as breast cancer primarily occurs in females. For spontaneous metastasis experiments, 10K LM2 control and HAS2 KD cells were injected with Matrigel (Corning 354230) into the fourth mammary fat pad of 6–9 weeks old NSG female mice. Primary tumors were monitored twice a week and measured using a caliper. Tumor volumes were calculated as half of length × width2. The maximum permitted tumor size of 1.5 cm was not exceeded. After 58 days, mice were euthanized, and blood was collected via heart puncture into EDTA tubes. Primary tumors were removed and weighed individually. Additionally, lungs were collected after perfusion with 10% neutral buffered formalin (NBF) and fixed for H&E or immunofluorescent staining. To obtain WHIM12 PDX primary tumor cells for in vitro studies, 6–8 weeks old NSG female mice were implanted with a 1–2 mm2 tumor chunk (only passaged in mice) in the fourth mammary fat pad. Tumors were collected prior to reaching 800 mm2 and dissociated into single cells.

For tail vein experiments, 100K LM2 control and HAS2 KD cells were injected as aggregates into 6–8 weeks old NSG female mice by tail vein. Within 20 min of the injection, baseline cell amount in the lungs was quantified using Luciferin (Gold Biotechnology LUCK-100) injection and IVIS spectrum imaging (Caliper Life Science). Lung metastasis BLI signal was monitored every week. After 4 weeks, mice were euthanized, and blood and lungs were collected and processed as described above. For the short-term 24 h tail vein experiment, 1×106 LM2 control and HAS2 KD cells were injected as aggregates, and lungs were collected and processed as described above. ImageJ (v1.54.f) was used to quantify the percentages of tumor cells in lungs. For each mouse, average tumor cell percentages from 12 random locations are reported.

For CTC analysis, whole blood was centrifuged at 700×g for 15 min to deplete plasma. Pellets were resuspended in ACK lysing buffer (Thermo Fisher A1049201) and incubated for 3–5 min to lyse red blood cells. Samples were diluted with PBS and centrifuged at 700×g for 5 min to obtain pellets containing white blood cells and CTCs. Pellets were resuspended in PBS, spread onto slides coated with Poly-L-Lysine (Electron Microscopy Sciences 19320-A), and allowed to attach for 30-60 min at 37 °C. Slides were fixed and imaged using a CyteFinder® instrument (RareCyte) to quantify GFP- or RFP-labeled CTCs. For each mouse, CTC numbers quantified from a portion of the pellet were extrapolated to determine total CTCs per mL of blood.

Patient CTC samples
Breast cancer primarily occurs in females, so human samples from female breast cancer patients were utilized in this study. For CTC analysis, blood was obtained from de-identified patients with metastatic TNBCs after receiving their informed consent as per institutional review board (IRB) protocol at Baylor College of Medicine. 6–8 mL of peripheral blood was collected into EDTA vacutainers. The blood was centrifuged at 700×g for 15 min to deplete plasma. The pellet was resuspended in PBS, and peripheral blood mononuclear cells (PBMCs) were isolated using LymphoprepTM density gradient medium (STEMCELL Technologies 07851) and ACK lysing buffer. PBMCs were resuspended in Transfer Fluid (RareCyte) and spread onto slides. After fixation with 10% NBF for 20 min, immunofluorescent staining was performed as described above. CTCs were detected using a cocktail of four antibodies consisting of Pan-Cytokeratin, Cytokeratin 19, EpCAM, and EGFR. Slides were scanned using a CyteFinder® instrument (RareCyte) to identify CTCs.

Statistics and reproducibility
GraphPad Prism was used to perform all statistical tests as described in the figure legends. P-value<0.05 was considered statistically significant. P=<0.05 (*), P=<0.01 (**), P=<0.001 (***), P=<0.0001 (****) were indicated with exact values provided in the figure legends when possible. Additional statistical metrics, including confidence intervals, are provided in the Source Data file. Each experiment was replicated and successfully reproduced at least three times. All microscopy images and western blots represent results from these biological replicates. No statistical method was used to predetermine sample size for in vitro experiments. Mouse experiments were performed with groups of 7–8 mice based on pilot experiments and to account for any mortality prior to the completion of the experiment. No data was excluded except in the event of animal mortality prior to completion of the experiment. Mice and cell line samples were randomly allocated into groups to minimize bias. Investigators were blinded to group allocations during both data collection and data analysis for all mouse experiments and when possible, for in vitro experiments.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "Overall impression:\nThis well-written manuscript provides an interesting and useful extension of prior research documenting the importance of\nCD44 in TNBC metastasis by providing compelling evidence that the main ligand of this cell surface receptor, hyaluronan\n(HA), plays an important role in cluster formation. While the evidence for CD44 and HA in cluster formation is extensive and\nconvincing, the importance of this interaction in promoting metastasis is less clear.\nMajor points:\n1. The authors state that “While similar numbers of both control and HAS2 KD cells reached the lungs upon injection, clear\ndifferences in metastatic lung signal are detectable from one week onwards (Fig. 5k-l and Extended Data Fig. 5h).” At the\nsame time, the authors show that both control and HAS2 KD cells exhibit the same level of proliferation and Ki67 staining of\nthe metastatic lungs was the same between LM2 control and HAS2 KD tumor cells (Extended Data Fig. 5i). Why would there\nbe a difference in lung metastasis over time if cells’ ability to colonize the lungs and their proliferation rate was the same?\nWeek 1-4 typically represents outgrowth of cells that have successfully colonized the lungs. Shouldn’t there be a difference\nin ability to colonize the lungs given that HAse-treated cells exhibit a 2-fold increase in ROS levels compared to control\ncells? In fact, the authors’ in vitro results show that “HA depletion decreased cell survival, with significant differences being\ndetected at 16 hrs. At 24 hrs, only 20-25% of the HAse-treated or HAS2 KD LM2 cells were alive, compared to 65% of the\ncontrol cells (Fig. 4e-f).”\n2. In Figure 6f, the authors analyzed the number of CTCs originating from control and HAS2 KD cells in each mouse and\nobserved a 4- to 12-fold reduction of CTCs originating from HAS2 KD cells. Why was a 4-week time-point chosen? Again,\none would expect there to be a significant decrease in CTCs within 24 h based on the author’s in vitro data and previously\npublished work (see PMID: 31485072, which the authors failed to cite in this manuscript).\nIn addition, the authors need to rule out the possibility that even though HA is crucial for cluster formation, the final cell-cell\ncontacts might be mediated by an additional cell-cell adhesion mechanism.\n3. The authors state that “gap size is similar to the 10-20 nm reported for AJs; however, the cluster-forming metastatic cell\nlines lack the crucial AJ component E-cadherin.” Later, they also state that “LM2 control and HAse-treated cells showed\nsimilar numbers of clusters and single cells in the absence of shear stress (Fig. 4a and Extended Data Fig. 4a-c, “no shear\nstress”).” Although the evidence for the crucial involvement of HA in cluster formation is compelling, the authors have not\nruled out the possibility that after HA-mediated cell attachment occurs, the final cell aggregates are held together most tightly\nby an alternative cell adhesive mechanism besides HA, even though E-cadherin is missing. Have the authors checked the\nexpression level of other AJ components in LM2 cells? The data presented strongly suggests that another AJ component is\ninvolved in cell clustering. What happens if that component is knocked down? Can cells still form cell clusters effectively in\nresponse to shear stress?\nMinor points:\n1. An interesting observation is that freshly detached MCF7 cells fail to cluster when rotated on an orbital shaker. MCF7 cells\nexpress high levels of E-cadherin and form strong cell-cell contacts in the absence of shear force. If MCF7 cells are allowed\nto cluster and are then subjected to shear force, do they remain together as clusters? How strong is this interaction\ncompared to HA-mediated cell clustering exhibited by LM2 cells? How do LM2 cells form clusters more readily in response\nto shear stress than MCF7 cells? Does HA act like a ‘glue’ making it more likely for colliding cells to interact with each\nother? Do E-cadherin based clusters take a long time to form whereas HA-CD44 form more quickly?\n2. Increased HA intensity at cell-cell junctions may be due to the presence of more plasma membrane. For example, CAAX-\nGFP and GPI-GFP intensity is typically greater at cell-cell junctions. A better measure of HA intensity at cell-cell junctions\nwould be to normalize the signal by the total amount of plasma membrane (i.e., HA/plasma membrane staining).\n3. Have the authors performed an outlier test for Extended Figure 3d? If the abnormally low data point for colchicine is\nremoved, there is likely a significant increase in the number of single cells relative to control. Is the amount of CD44 on the\nplasma membrane altered when the microtubule network is dismantled? Perhaps the amount of HA on the plasma\nmembrane is reduced?\n4. Line 84: Has hyaluronan been identified previously among ECM components reported to be upregulated in CTCs?\n5. Lines 236-237: The evidence presented does not show conclusively that “actin filaments provide the protrusive force for\nthe formation of these structures” but instead that actin is necessary for their maintenance.\nWording:\n1. Line 75: Typo: emboli rather than embolies\n2. Line 232: The “remarkable overlap” is not surprising because protrusions are normally filled with actin, so actin should\noverlap with any cell surface or matrix component on the outside of protrusions.\n3. Line 482: The wording appears too general: the non-tumor cells also need to be CD44-expressing.", "reviewer_2": "This manuscript by Bobkov et al, identified a previously unrecognized HA-mediated mechanism that enables stable CTC\ncluster formation in triple-negative breast cancer (TNBC). The study is well designed, integrating both in vitro and in vivo\nassays with human samples and mouse models. The data are convincing, and the findings are both novel and highly clinic\nrelevant. The results expand the current paradigm of CTC cluster biology and may provide new possibilities for treating\nmetastatic TNBC patients. Some comments are shown below to improve the manuscript:\nMajor comments:\n1. In most of the images showing cell clustering (e.g., Fig. 1f, Fig. 2b, 2g, etc.), the non-clustered groups have less cells than\nthe clustered groups. It would be better to show full images of the entire culture to demonstrate that each group started with a\nsimilar number of cells.\n2. Please carefully double-check all image labels. For example, in Fig. 5k, the signal based on the bar shown should be\nbetween 150–2,000 on Day 0, but the y-axis is labeled as 10⁴ in Fig.5i. In addition, the Week 4 raw signal appears to be\nbetween 2,000–20,000(Fig.5K), so it is unclear how the “signal (relative to Day 0)” can be ~1,000 (fig.5i).\n3. The inclusion of patient-derived CTCs is a strength, but the sample size is not specified. In addition, including CTCs from\nother breast cancer subtypes for comparison, if feasible, would further enhance the translational relevance of the findings.\n4. In addition to the RT-PCR data, the knockdown efficiency of HAS2 should be validated by Western blot. Since the pooled\npopulation contain residual HAS2, and the remaining HA can mediate cell clustering in HAS2 knockdown cells (as shown in\nExtended Data Fig. 5l). Providing this additional validation would strengthen the conclusions regarding HAS2’s role.\n5. In the conclusion, it is stated that: “The formation of this coat is likely a consequence of HA’s unique mode of production.\nHA is synthesized at the plasma membrane, and while the growing HA chain extrudes out into the extracellular space, it is\nimmediately captured and bound by its receptor CD44. This enables the formation of an HA-rich pericellular coat.” Could the\nauthors provide citation to support this statement? Otherwise, additional experiments would be needed to validate it.\n6. It is known that CTC clustering can promote cell survival, and HA has also been reported to support cell survival.\nTherefore, the cell survival data may be considered to remove or move to the supplemental data, as it is not central to the\nfocus of the manuscript. In addition, the reactive oxygen species (ROS) data is weak. If these data are kept, the authors\ncould strengthen this aspect by performing rescue experiments—for example, testing whether antioxidants can prevent\nthe death of HAse-treated cells.\nMinor comments:\n1. Since SKBR3 cells are used in Fig. 1g, it would be more appropriate for the representative image in Fig. 1f to also show\nSKBR3 cells, rather than BT474 cells. This would help maintain consistency between the panels.\n2. In the text, it is stated that “CTC clusters were detected in all 6 control mice”. However, only 5 mice are shown in fig.5h&\n5i.\n3. Since the tumor cells were labeled with GFP, it is unclear whether the GFP signal will be preserved during IF staining,\nespecially given that HA is also detected using a green fluorophore. Could the authors clarify how these signals are\ndistinguished in the images?", "reviewer_3": "In this manuscript, Bobkov and Patel et al. propose a novel role for hyaluronan in circulating tumor cell (CTC) clustering\nduring TNBC metastasis. They show that CTCs express HAS2, which synthesizes HA, and that HA interacts with CD44 on\ncancer cells to function as adherent junctions, which is very interesting and novel. Overall, the data are clear and well\npresented. However, some of the results sections are somewhat lengthy and would be better reorganizing or moving parts\ninto the discussion. It is intriguing that HA appears to show such a strong effect as a mediator of cell-cell interactions, the\ndata overall support this hypothesis well. Detailed comments are as below:\n1. HA is a well-known serum marker for several cancers, including breast, prostate, and gastrointestinal cancers. Elevated\nserum HA levels have been correlated with a worse prognosis and increase risk of metastasis, which supports the findings\nof this study. However, this also indicates that HA is already abundant in the bloodstream of patients with cancer or tumor-\nbearing mice, suggesting that CTCs may not be the primary source of HA. Moreover, HA is highly accumulated in the\nprimary tumor, raising the possibility that HA-coated cancer cells could detach from the primary tumor, intravasate, and form\nclusters. According to this study, endogenous HAS2 expression is crucial for HA-mediated CTC clustering (HAS2\noverexpression and knockdown experiments). In the context of rich HA in the bloodstream or culture media, CTCs can form\nclusters independently of HAS2 expression? Can you also compare HAS2 expression or HA intensity in LM2 clusters\ncompared to LM2 single cells?\n2. Metastatic tumors often lose adherens junction expression as they undergo epithelial-to-mesenchymal transition. This\ntransition is a very important process in metastasis. In this study, EpCAM-negative cancer cells show high HAS2 expression,\nwhereas EpCAM-positive cancer cells exhibit little to no HAS2 expression (Fig. 1j and extended Fig.1l). Is there any\nevidence linking the HAS2 or HAS2-HA -CD44 axis to epithelial-to-mesenchyamal phenotypic changes? And could this\ntransition also be associated with CTC clustering or cell-cell interactions?\n3. While this study primarily focused on the TNBC metastasis, it would be important to clarify whether similar observations\nare found in other aggressive or malignant cancer types.\n4. HA exists in both high-molecular weight and low-molecular weight forms, which are known to play distinct roles in\npathophysiology. The authors should determine the size of HA to better understand the novel function of HA.\n5. The authors suggest that tumor cells express HAS, which synthesize HA, and that this HA interacts with CD44 on cancer\ncells, forming a kind of autocrine loop. This axis mediates cell-cell interactions and promotes CTC clustering. The HA-CD44\ninteraction has been extensively studied in cancer biology. Do HA-coated CTC clusters also contribute to extravasation,\ncancer cell migration, or invasion, at later step of metastasis? In vivo data suggest that HA-mediated CTC clustering plays\nan important role in TNBC lung metastasis (Fig.5). Given that HA-CD44 is important for CTC survival, what is the\ndownstream pathway of HA-CD44 in CTCs clustering?\n6. It is quite surprising that HA-coated CTC clustering is prominent under shear stress. How does HA uniquely contribute\nunder these conditions? What is the mechanism of HAS2-HA upregulation in CTCs? What upstream signals stimulate\nHAS2 to synthesize HA? or, metastatic TNBC cells constitutively express HAS2? Since clustering occurs very rapidly, in a\nminute, is it possible that shear stress can quickly induce HA secretion? In addition, given that HA-CD44 is involved in cell-\ncell interaction, this could be involved in cell-cell interactions in the primary tumor. What distinguishes HA in the blood\nstream from HA at the primary tumor site from HA? Additionally, how do cancer cells sense shear stress and respond to\ncluster formation via HA?\n7. As authors stated in the Introduction, CD44 is expressed by many cell types, including immune cells. In Fig. 6, authors\nsuggest that HA facilitates interactions between CTCs and non-CTCs. Any chance to work in heterotypic clusters with\nimmune cells or CAFs? HA is also expressed by cancer cells and cancer-associated fibroblasts.\n8. Non-metastatic cell lines, such as MCF7 and BT474, hardly express HAS2 (Fig. 1j), but they highly express EPCAM\n(extended Fig. 1l), showing almost no clustering (Fig. 1f). Given that EPCAM is also known to mediate cell-cell interactions,\nit is somewhat surprising that HA appears to have a stronger effect that EpCAM in promoting cluster formation. In addition,\nthe HA-CD44 axis appears to act as a master regulator of CTC clustering, rather than functioning as an AJ-independent\npathway. In Fig.2 and extended Fig.2, HAse treatment, HAS2 KD, or CD44 KO nearly abolishes all CTC clustering. This\nraises the question of whether HA-CD44 plays roles beyond just mediating cell-cell interactions.\n9. The authors used 293FT cell line to investigate the role of HA-CD44 in TNBC clustering (Extended Fig.2). While it is\nunderstandable that they chose this line because it lacks both HAS2 and CD44, it is not a breast cancer cell line. It would be\nbetter if the authors could replicate these experiments in breast cancer cell line.\n10. According to the literature, CD44 is known to be important for homophilic CTC clustering. However, Fig. 2c-d suggests\nCD44 function is impaired in the absence of HA. To directly test whether HA-CD44 interaction is crucial for TNBC CTC\nclustering, authors should consider block this interaction using a specific antagonist.", "reviewer_4": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature\nCommunications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career\nResearchers who co-review manuscripts."}, "author_response": "We thank Reviewer 1 for raising this point and apologize for the confusion. We measured\nluciferase signals of each mouse immediately after tumor cell injection to ensure that the same\nnumber of tumor cells reached the lungs at time of injection. This number does not represent\ncomparable lung colonization, as metastasis is an incredibly inefficient process. Studies have\nshown that most tumor cells that reach an organ fail to initiate macrometastases and instead\neither die or stay dormant (PMID: 9736035). As the Reviewer correctly pointed out, the in vivo cell\nproliferation rate is comparable between control and HAS2 KD cells (Extended Data Fig. 5f and\n5k), indicating that the difference in metastasis is not a consequence of reduced outgrowth.\nInstead, initial lung colonization by HAS2 KD cells was likely impaired because HA-lacking cells\nare more susceptible to shear stress (revised Extended Data Fig. 4k-n).\nWe now present additional results to compare the lung colonization capability. We\nexamined the lungs from mice 24 hrs after tail vein injection of LM2 control and HAS2 KD cells\nand detected a significantly lower number of HAS2 KD cells in the lungs compared to that of\ncontrol (Fig. R1a and revised Extended Data Fig. 5a). Additionally, we performed in vitro invasion\nassay and found that HA-lacking cells have reduced invasion capability (Fig. R1b-c and revised\nExtended Data Fig. 5b). Taken together, these results reveal that HAS2 KD cells are likely more\nsusceptible to the harmful effects of shear stress exposure, as the Reviewer suggested (see also\nReviewer 3, point 5).\nWe have described the new results on page 16. It reads: “Based on our in vitro results, we\nhypothesized that HA-lacking CTCs may have reduced metastatic colonization ability as they are\nmore susceptible to shear stress-induced cell death (Extended Data Fig. 4k-n). To test this\nhypothesis, we injected LM2 control and HAS2 KD cells via tail vein in female NSG mice and\nexamined their lungs for the presence of GFP-positive tumor cells 24 hrs later. Indeed, HAS2 KD\n1\ntumor cells were present in fewer numbers in the lungs compared to control cells (Extended Data\nFig. 5a). Accordingly, a Matrigel-based in vitro invasion assay revealed that HA-lacking single\ncells have reduced invasive capacity compared to clustered control cells (Extended Data Fig. 5b).\nTogether, these results indicate that HA-mediated clustering protects tumor cells from shear-\nstress induced cell death and promotes invasion to enhance metastatic colonization and\noutgrowth.”\nFig. R1. HAS2 KD perturbs tumor cell infiltration. (a) Percentage of LM2 Ctrl and HAS2 KD cells that\nreside inside the lung 24 hrs right after tail vein injection. (b) Representative images showing Matrigel-\ninvasion of LM2 Ctrl and HAse-treated cells after 24 hrs. (c) Quantification of the images shown in b.\n2. In Fig. 6f, the authors analyzed the number of CTCs originating from control and HAS2\nKD cells in each mouse and observed a 4- to 12-fold reduction of CTCs originating from HAS2\nKD cells. Why was a 4-week time-point chosen? Again, one would expect there to be a significant\ndecrease in CTCs within 24 h based on the author’s in vitro data and previously published work\n(see PMID: 31485072, which the authors failed to cite in this manuscript).\nIn addition, the authors need to rule out the possibility that even though HA is crucial for cluster\nformation, the final cell-cell contacts might be mediated by an additional cell-cell adhesion\nmechanism.\nResponse:\nWe thank the Reviewer for pointing out this important paper. We had cited it in an earlier\nversion of the manuscript and accidentally deleted it. We have rectified this in the revised\nmanuscript and now cite it as reference 71 in the discussion on page 19. It reads: “Highly\naggressive TNBCs often exhibit mesenchymal features and downregulate epithelial AJ molecules\nto increase their invasive and migratory properties15-18. While this promotes dissemination, the\nlack of classical AJ-mediated interactions can prevent the formation of CTC clusters71.”\nAfter tumor cell injection, CTCs are thought to get trapped in the capillaries and thus\nrapidly cleared from circulation (PMID: 26114035, 23166151). CTCs re-emerge in our system ~4\nweeks post injection once lung lesions have been established and begin shedding cells. This is\nwhy we analyzed this specific time point. We tried to accommodate the Reviewer’s request and\nchecked for CTCs 24 hrs after injection, but could not detect any CTCs. Of note, the publication\nreferred by the Reviewer also quantifies CTC number only after a primary tumor has been fully\nestablished in a mammary fat pad spontaneous metastasis model. Our experimental setup shown\nin revised Fig. 5k-p is comparable to those in this published paper.\nReviewer and now include data derived from lungs collected 24 hrs after tail vein injection, where\nwe see reduced HAS2 KD tumor cells compared to control. Regarding the involvement of\nadditional cell-cell adhesion molecules, we now include exciting new data showing that\ndesmosomes help stabilize HA-based tumor cell clusters (see response to the next comment).\n3. The authors state that “gap size is similar to the 10-20 nm reported for AJs; however, the\ncluster-forming metastatic cell lines lack the crucial AJ component E-cadherin.” Later, they\nalso state that “LM2 control and HAse-treated cells showed similar numbers of clusters and single\ncells in the absence of shear stress (Fig. 4a and Extended Data Fig. 4a-c, “no shear stress”).”\nAlthough the evidence for the crucial involvement of HA in cluster formation is compelling, the\nauthors have not ruled out the possibility that after HA-mediated cell attachment occurs, the final\ncell aggregates are held together most tightly by an alternative cell adhesive mechanism besides\nHA, even though E-cadherin is missing. Have the authors checked the expression level of other\nAJ components in LM2 cells? The data presented strongly suggests that another AJ component\nis involved in cell clustering. What happens if that component is knocked down? Can cells still\nform cell clusters effectively in response to shear stress?\nResponse:\nWe thank the Reviewer for raising the question concerning alternative cell adhesive\nmechanisms working in concert with HA. Two recent papers investigating CTCs showed an\nupregulation of the desmosomal cadherins Desmoglein-2 (DSG2) and Desmocollin-2 (DSC2), as\nwell as Desmoplakin (DSP), which anchors these cadherins to intermediate filaments (PMID:\n33431674, 34586853). Inspired by Reviewer 1’s question, we analyzed desmosomal proteins in\nour experimental system.\nWe found that all three proteins localize to mature, but not early cell-cell interaction sites\n(Fig. R2a-b, revised Fig. 4e, and revised Extended Data Fig. 4j). We further show that depletion\nof any of these desmosomal proteins (Fig. R2c and revised Extended Data Fig. 4i) does not\nabolish clustering per se, but affects their stability as clusters rapidly dissociate when experiencing\nhigher shear stress (Fig. R2d-e and revised Fig. 4f-g). Together, this new set of experiments\nshows that desmosomes are established at the interaction site to further strengthen and stabilize\nHA-dependent clusters.\nWe added a new section named “Desmosomes stabilize HA-mediated clusters” on page 14\nof the revised manuscript to present the desmosome data. It reads “The tight interactions\nobserved in fully formed clusters (Fig. 1h-i, 4b-d and Extended Data Fig. 1k, 4g) prompted us to\ninvestigate whether HA-based clustering recruits additional components to strengthen the cell-\ncell connection during the maturation of the interaction site. Desmosomes are specialized\nintercellular junctions that connect to intermediate filaments, thereby providing strong mechanical\ncoupling between neighboring cells53. Desmoglein-2 (DSG2) and Desmocollin-2 (DSC2) are\ndesmosomal cadherins that mediate adhesive binding between adjacent cells, while Desmoplakin\n(DSP) is the intracellular scaffold protein that anchors these cadherins to intermediate filament of\nthe cytoskeleton. Interestingly, recent reports showed that high expression of DSG2 in CTCs\nincreased prevalence of CTC clusters and metastasis54 and that DSC2 and DSP was associated\nwith increased cluster formation and CTC survival in breast and lung cancer cells55.\nThese findings prompted us to investigate whether desmosomes are involved in HA-based\nclustering of tumor cells as LM2 cells express DSG2, DSC2, and DSP (Extended Data Fig. 4i).\nAssessing their localization in clustered LM2 cells, we found all three desmosome proteins\nlocalized to the fully established cell-cell interaction sites, indicating that they mechanically couple\nneighboring cells in mature clusters (Fig. 4e). In contrast, in early clustering interactions where\n3\ncell morphology is still largely round and cell membrane contacts are limited to a small area,\nonly\nHA, but not DSG2, DSC2 or DSP, is enriched at the cell contact site (Extended Data Fig. 4j),\nsuggesting that desmosomes are established after large areas of the cell membranes are brought\ninto close proximity via HA-based interactions.\nTo determine whether desmosomes promote HA-based clustering by strengthening cell-cell\ninteractions, we knocked down DSG2, DSC2, and DSP individually in LM2 cells (Extended Data\nFig. 4i). Next, we performed cell clustering experiments with gradually increasing levels of\nrotational speed. All three KD cell lines formed clusters at 200rpm, but they rapidly dissociated at\nhigher shear forces, indicating reduced stability compared to control cells (Fig. 4f-g). Of note,\ncluster stability in control cells was not as high as in Fig. 4a, as they started to fragment into\nsmaller clusters at ~350 rpm (Fig. 4f). This suggests that while desmosome formation under shear\nstress is possible, it is less efficient than only challenging desmosome stability after they were\nfully established in the absence of shear stress. Taken together, these results suggest that the\ninitial connection of cells through HA enables the subsequent assembly of desmosomes, which\neffectively lock in these interactions and mechanically stabilize the clusters.”\nFig. R2. Desmosomes stabilize HA-based cell-cell interactions. (a-b) Localization of DSG2, DSC2, and\nDSP in fully formed clusters (a) and early (b) clusters. Cells were stained for HA (green) and\nDesmosome components (red). DAPI served as a nuclear counterstain. (c) WB analysis showing the\nKD of DSG2, DSC2, and DSP. (d-e) Representative images of LM2 cell clusters (d) and quantification of\nthe number of single cells (e) in Ctrl or Desmosome KD cells after clustering at various speeds (n=3).\nCells were clustered for 30 min at 200rpm and then sequentially agitated for 15 min at each higher\nspeed.\nFurthermore, we also discuss the similarities between desmosomes formed following\nestablishment of AJ- or HA-dependent cell-cell interactions on page 21: “The similarities further\nextend to the formation of desmosomes, which occurs only after initial membrane contacts have\nbeen established through AJs or HA. These similarities ultimately result in comparable structural\nfeatures such as gap sizes between interacting cells and the stable connection of cells across a\nlarge membrane area39,40.\nstabilize the HA-mediated cell-cell interaction greatly strengthens our study.\nMinor points:\n1. An interesting observation is that freshly detached MCF7 cells fail to cluster when\nrotated on an orbital shaker. MCF7 cells express high levels of E-cadherin and form strong cell-\ncell contacts in the absence of shear force. If MCF7 cells are allowed to cluster and are then\nsubjected to shear force, do they remain together as clusters? How strong is this interaction\ncompared to HA-mediated cell clustering exhibited by LM2 cells? How do LM2 cells form clusters\nmore readily in response to shear stress than MCF7 cells? Does HA act like a ‘glue’ making it\nmore likely for colliding cells to interact with each other? Do E-cadherin based clusters take a long\ntime to form whereas HA-CD44 form more quickly?\nResponse:\nIndeed, the Reviewer’s reasoning completely aligns with our own interpretation of the two\nclustering processes. The formation of adherens junctions is a complex interaction that involves\nmultiple proteins, requiring hours to fully establish (PMID: 24659804). This is likely the reason\nwhy MCF7 cells fail to cluster when they briefly encounter each other in a highly volatile\nenvironment (revised Fig. 1f-g). In contrast, the simplicity of the HA-CD44 interaction enables\ndynamic interactions that can facilitate clustering even under shear stress, and subsequent\nassembly of desmosomes fully stabilize the interaction (see reply to previous comment).\nAccording to the Reviewer’s question, we assessed the clustering capabilities of MCF7 cells\nunder no shear stress conditions and found that MCF7 cells form clusters (Fig. R3 and revised\nExtended Data Fig. 4h). Once established, these clusters are stable and can withstand shear\nforce (see also Reviewer 3, point 8).\nWe included this new result on page 13. It reads: “Examining the E-cadherin-positive MCF7\ncell lines revealed that although they failed to cluster under shear stress (Fig. 1f-g), MCF7 cells\ncan efficiently form clusters when left unperturbed in a low-attachment plate (Extended Data Fig.\n4h). Subsequent addition of shear stress did not break apart the clusters, in line with the reported\nstrength of AJ-dependent cell-cell interactions51 (Extended Data Fig. 4h). These results show that\nwhile HA is dispensable for TNBC cell cluster formation in the absence of shear stress, it is\ncritically required to form functional tumor cell clusters that can withstand the shear stress\nencountered by CTC clusters in the bloodstream.”\nFig. R3 MCF7 cells can form highly stable tumor cell clusters under no-shear stress conditions. (a)\nRepresentative picture of MCF7 clusters formed under no-shear stress (0 rpm) condition and tested for\nstability at higher rotational speeds (250 rpm and 350 rpm). (b) Quantification of pictures shown in\na.(n=4). Cells were settled for 24 hrs in a low-attachment plate (0rpm) and then agitated sequentially at\neach speed for 15 min.\n5\n2. Increased HA intensity at cell-cell junctions may be due to the presence of more plasma\nmembrane. For example, CAAX-GFP and GPI-GFP intensity is typically greater at cell-cell\njunctions. A better measure of HA intensity at cell-cell junctions would be to normalize the signal\nby the total amount of plasma membrane (i.e., HA/plasma membrane staining).\nResponse:\nFollowing the Reviewer’s excellent suggestion, we examined HA intensity compared to\ntotal amount of plasma membrane signal by staining cell membranes using Cellbrite® Fix\nMembrane. As seen in Fig. R4a-b and Extended Data Fig. 1o, HA is indeed significantly enriched\nat the interaction site.\nWe included this new data on page 7 as follows: “Importantly, quantification of HA\ncompared to membrane staining further confirmed the enrichment of HA at cell junctions\n(Extended Data Fig. 1o).”\nFig. R4 HA is enriched at the cell-cell interaction site. (a) Maximum intensity projection of fixed LM2\ncluster stained for HA (green) and membrane (red). Memb represents Membrane stain in RGB picture.\n(b) HA signal divided by the corresponding membrane signal from quantifications of pictures shown in a.\nn= 125 cell junction and 125 non-junction sites.\n3. Have the authors performed an outlier test for Extended Fig. 3d? If the abnormally low\ndata point for colchicine is removed, there is likely a significant increase in the number of single\ncells relative to control. Is the amount of CD44 on the plasma membrane altered when the\nmicrotubule network is dismantled? Perhaps the amount of HA on the plasma membrane is\nreduced?\nResponse:\nAs per the Reviewer’s suggestion, we have performed outlier analysis using ROUT\n(Q=1%) in GraphPad Prism and no samples were marked for exclusion. Nonetheless, we decided\nto remove this particular replicate, as it also produced the outlier-like data point for number of\nclusters. Results comparing before and after removal of this replicate are shown in Fig. R5a vs.\nR5b). The new plots are included in revised Fig. 3e and revised Extended Data Fig. 3d).\nWe thank the Reviewer for raising the question concerning CD44 and HA levels in treated\ncells, as it uncovered a surprising phenotype. Both CD44 and surface-bound HA were almost\ncompletely absent in Latrunculin A-treated cells, whereas colchicine didn’t show any effect (Fig.\nR5c and revised Extended Data Fig. 3c). We have updated our description to accommodate this\nnew finding on page 10 as follows: “Treatment of LM2 cells with the actin depolymerizing drug\nand increased cell size45 (Extended Data Fig. 3c). In addition, cell surface staining of CD44, and\nespecially HA, was markedly reduced in Latrunculin A treated cells (Extended Data Fig. 3c)\nsuggesting that actin is required to properly position CD44, and thereby also HA at the cell surface.\nConsistent with HA being required for TNBC tumor cell clustering (Fig. 2 and Extended Data Fig.\n2), Latrunculin A treatment abolished cluster formation, whereas clustering remained largely\nunaffected by colchicine (Fig. 3e and Extended Data Fig. 3d). Together, these results suggest that\nactin is essential for the formation of tumor cell clusters, likely through the formation of cellular\nprotrusions that help organize HA localization (Fig. 2j and 3a).”\nFig. R5 Latrunculin A treatment perturbs CD44 and HA cell surface localization and ultimately abolishes\ntumor cell clustering. (a) Old graphs including the fourth replicate showing that Latrunculin A treatment\ndisrupts TNBC tumor cell clustering. Number of clusters (left) and number of single cells (right) are\nshown. (b) Updates graphs of the data shown in a. (c) Maximum projection of fixed single cells in\nsuspension. Control (left), Latrunculin A (middle) and Colchicine (right) treated cells are shown. Cells\nare stained for HA (green) and CD44 (red). CD44 single color channel is additionally displayed in gray\nto show presence/absence of protrusions. High CD44 exposure of Latrunculin A was used to show\nsmooth, protrusion-free cell body.\n4. Line 84: Has hyaluronan been identified previously among ECM components reported to be\nupregulated in CTCs?\nResponse:\nTo our knowledge, hyaluronan (HA) has not been previously identified to be upregulated\nin CTCs. This is likely due to multiple factors. First, there is no direct measure for HA in RNA-seq\ndatasets as it is a polysaccharide. Second, HA levels are dynamically regulated by multiple\nsynthases and degradation factors called hyaluronidases. These proteins are variably expressed\nacross tissues, making HA level prediction difficult. Third, HA synthases are not structural ECM\ncomponents and thus may not necessarily be classified as such in bioinformatic analyses. Lastly,\nCTCs are an extremely rare population and may become damaged during isolation. These\nchallenges might have limited the discovery of HA’s association with CTCs.\n5. Lines 236-237: The evidence presented does not show conclusively that “actin filaments\nprovide the protrusive force for the formation of these structures” but instead that actin is\nnecessary for their maintenance.\nWe agree with the Reviewer’s comment and have removed this statement as Latrunculin\nA treatment cannot distinguish whether maintenance or formation of the protrusions is affected.\nIn addition, our finding that CD44 and HA cell surface localization is perturbed by the treatment\nmakes it likely that the failure to cluster is a direct consequence of the altered HA localization and\nnot necessarily the perturbed protrusions. On page 10, the revised manuscript reads as follows:\n“Consistent with HA being required for TNBC tumor cell clustering (Fig. 2 and Extended Data Fig.\n2), Latrunculin A treatment abolished cluster formation, whereas clustering remained largely\nunaffected by colchicine (Fig. 3e and Extended Data Fig. 3d). Together, these results suggest that\nactin is essential for the formation of tumor cell clusters, likely through the formation of cellular\nprotrusions that help organize HA localization (Fig. 2j and 3a).”\nWording:\n1. Line 75: Typo: emboli rather than embolies\nResponse:\nWe now use the correct word “emboli”.\n2. Line 232: The “remarkable overlap” is not surprising because protrusions are normally\nfilled with actin, so actin should overlap with any cell surface or matrix component on the outside\nof protrusions.\nResponse:\nThis wording was chosen in comparison to the microtubule staining. We rewrote this\nstatement in line with the Reviewer’s comment to avoid making the overlap sound like something\nextraordinaire. The revised manuscript now reads on page 10: “Actin staining showed a clear\noverlap with the CD44-marked protrusions (Fig. 3d), whereas tubulin localized just beneath the\ncell membrane (Extended Data Fig. 3b).”\n3. Line 482: The wording appears too general: the non-tumor cells also need to be CD44-\nexpressing.\nResponse:\nWe agree with the Reviewer and now emphasize the requirement of the HA receptor\nCD44. The sentence read: “Using TNBC patient samples and mouse models, we also show that\nHA can serve as a landing pad to enable integration of non-tumor cells that express the HA\nreceptor CD44 into heterotypic CTC clusters.” in the Line on page 20 that corresponds to Line\n482 of the initial manuscript.\nReviewer #2 (Remarks to the Author):\nThis manuscript by Bobkov et al, identified a previously unrecognized HA-mediated mechanism\nthat enables stable CTC cluster formation in triple-negative breast cancer (TNBC). The study is\nwell designed, integrating both in vitro and in vivo assays with human samples and mouse models.\nThe data are convincing, and the findings are both novel and highly clinic relevant. The results\nexpand the current paradigm of CTC cluster biology and may provide new possibilities for treating\nmetastatic TNBC patients. Some comments are shown below to improve the manuscript:\n1. In most of the images showing cell clustering (e.g., Fig. 1f, Fig. 2b, 2g, etc.), the non-\nclustered groups have less cells than the clustered groups. It would be better to show full images\nof the entire culture to demonstrate that each group started with a similar number of cells.\nResponse:\nWe fully acknowledge the concern raised by the Reviewer and explored options to add\nthe full overview images. As can be seen in Figure R6a, the full image is too large to allow\nvisualization of individual cells. To accommodate the Reviewer’s request, we now show a large\nfield of cells to reflect that equal amount of cells were used (Fig. R6b and Extended Data Fig. 2a).\nFig. R6 Overview pictures showing the clustering assay was performed with the same amount of cells.\n(a) Full scan image of the whole well. (b) Large overview section of Ctrl and HAse treated cells were\nclusters/single cells can still be recognized. Black box indicates position of the 3x enlarged inset.\n2. Please carefully double-check all image labels. For example, in Fig. 5k, the signal based\non the bar shown should be between 150–2,000 on Day 0, but the y-axis is labeled as 10⁴ in\nFig.5i. In addition, the Week 4 raw signal appears to be between 2,000–20,000(Fig.5K), so it is\nunclear how the “signal (relative to Day 0)” can be ~1,000 (fig.5i).\nResponse:\nWe thank the Reviewer for pointing this out. The IVIS picture shown in original Fig. 5k are\nnot directly comparable to the quantified tumor burden shown in original Fig.5l. The representative\nimages for d0 (Fig. R7a and revised Fig. 5k) include a heatmap to visualize bioluminescence\nsignal intensity per pixel. The scale bars of 35-600 (Day 0) and 200-2k (Week 4) depict the range\n9\nof minimum and maximum signal intensity per pixel. In the revised Fig. 5l, combined total radiance\nsignal of the lungs is shown. Therefore, the numbers in the bar plots in revised Fig. 5l reflect the\n“total normalized signal” and are thus not directly comparable to the “signal/pixel” shown in the\nheatmap in revised Fig. 5k. Additionally, we accidentally showed representative images of mice\nfrom the pilot experiment in Fig. 5k and have now replaced them with the ones used in the final\nexperiment. The revised Fig. 5k and 5l are shown in Fig. R7.\nFig. R7 HAS2 KD reduces lung metastasis signal after tail vein injection. (a) Left: schematic depicting\ntail vein injection of GFP-tagged LM2 control or HAS2 KD cell aggregates in immunocompromised mice\n(n=7 per group). Right: representative images of lung tumor burden measured via bioluminescent\nimaging in these mice at time of injection (Day 0) and upon experimental endpoint at Week 4. (b)\nQuantification of lung metastasis signal at time of injection (Day 0) and Weeks 1, 2 and 4. Data is\nnormalized to lung signal at time of injection.\n3. The inclusion of patient-derived CTCs is a strength, but the sample size is not specified.\nIn addition, including CTCs from other breast cancer subtypes for comparison, if feasible, would\nfurther enhance the translational relevance of the findings.\nResponse:\nAccording to the Reviewer’s request, the updated manuscript now includes the sample\nsize and reads on page 19: “We next analyzed HA localization in blood specimens from five TNBC\npatients. CTCs from patient blood were identified using a cocktail of the gold standard CTC\nmarkers (Pan-Cytokeratin, EpCAM and EGFR). CTC clusters were detected in three of the TNBC\npatients. These CTCs displayed a prominent HA coat, and a clear HA enrichment was found at\nCTC-CTC contact sites, both in clusters where all CTCs produce HA (Extended Data Fig. 6e) or\nwhen only one CTC provides the HA necessary for the interaction (Fig. 6j). One TNBC patient\nhad HA-coated CTCs, but no CTC clusters were detected, and the last TNBC patient only had\nsingle CTCs without an HA coat. These results reiterate the importance of HA in TNBC CTC\nclustering and also show that HA-coated CTCs are capable of recruiting HA-lacking CTCs into\nCTC clusters.”\nWe further analyzed CTC clusters from blood specimens of four ER⁺/PR⁺/HER2⁻ patients\nusing previously banked slides known to contain CTC clusters. As expected, none of the CTCs\nshowed cell-surface HA staining, indicating that these clusters likely form through a different\nmechanism. We predict that they are mediated by E-cadherin. We elected to omit these data from\nthe final manuscript, since this study does not otherwise focus on E-cadherin–dependent\nclustering and we were unable to stain for E-cadherin due to limited availability of patient slides.\nWe chose not to include the non-TNBC patient data in order to keep the study focused and\n10\nminimize potential confusion for readers. Nonetheless, we\nwould be happy to include these data in the revised\nmanuscript if requested.\n4. In addition to the RT-PCR data, the knockdown\nefficiency of HAS2 should be validated by Western blot.\nSince the pooled population contain residual HAS2, and\nthe remaining HA can mediate cell clustering in HAS2\nFig. R8 Western blot showing the\nknockdown cells (as shown in Extended Data Fig. 5l).\nknockdown of HAS2 to supplement\nProviding this additional validation would strengthen the\nRNA (qPCR) and functional\nconclusions regarding HAS2’s role.\nconsequence (IF) data shown in\nExtended Data 2a. GAPDH served\nResponse:\nAs a loading control.\nFollowing the Reviewer’s suggestion, we now include a WB showing the knockdown\nefficiency of HAS2 on the protein level (Fig. R8 and revised Extended Data Fig. 2c) to supplement\nour original qPCR and HA IF data (revised Extended Data Fig. 2b,d).\n5. In the conclusion, it is stated that: “The formation of this coat is likely a consequence of\nHA’s unique mode of production. HA is synthesized at the plasma membrane, and while the\ngrowing HA chain extrudes out into the extracellular space, it is immediately captured and bound\nby its receptor CD44. This enables the formation of an HA-rich pericellular coat.” Could the\nauthors provide citation to support this statement? Otherwise, additional experiments would be\nneeded to validate it.\nResponse:\nWe agree with the Reviewer that a citation is\nwarranted at this place and now cite a\ncomprehensive review about HA synthases that\ndescribes the unique production method of this\nmajor ECM component in detail (PMID: 17981795 –\nReference 32 in revised manuscript) and an\nFig. R9/revised Extended Data Fig. 2h The\nadditional review that examines the Golgi-driven formation of a membrane-associated HA coat\nsecretion of other ECM macromolecules (PMID:\nrequires CD44. (a) Left: Western blot\n35023559 – Reference 70 in revised manuscript).\nshowing CD44 protein levels of LM2 control\nThe notion that HA is bound by CD44 at the cell and CD44 KO cell lines. GAPDH served as a\nsurface is further supported by the fact that cell- loading control. Right: maximum intensity\nmembrane associated HA is lost in CD44 KO cells projection of LM2 Ctrl and CD44 KO cells\nfixed in suspension, permeabilized and\n(Fig. R9a and revised Extended Data Fig. 2h, j).\nstained for HA (green).\n6. It is known that CTC clustering can promote cell survival, and HA has also been reported\nto support cell survival. Therefore, the cell survival data may be considered to remove or move to\nthe supplemental data, as it is not central to the focus of the manuscript. In addition, the reactive\noxygen species (ROS) data is weak. If these data are kept, the authors could strengthen this\naspect by performing rescue experiments—for example, testing whether antioxidants can prevent\nthe death of HAse-treated cells.\nWe thank the Reviewer for these\nsuggestions. We included this experiment to\nshow that specifically the HA-mediated clusters\ncan enhance cell survival. As per the Reviewer’s\nsuggestion, both the cell survival and ROS\nexperiment data have now been moved to the\nsupplemental data (Fig. R10a and revised\nExtended Data Fig. 4k-n). Additionally, we have\nperformed the suggested rescue experiment Fig. R10 Shear stress induces cell death\nthrough ROS (a) Relative ROS production in\nand found that the antioxidant N-acetylcysteine\nLM2 Ctrl or HAse-treated cells after 12 hrs of\n(NAC) can partially rescue the cell death\nshear stress exposure (n=4). Data normalized to\nphenotype of both clustered control and single\nwild type (WT) cells not exposed to shear stress.\nHAse-treated cells (Fig. R10b and revised\n(b) Percentage of viable LM2 Ctrl or HAse-\nExtended Data Fig. 4n), suggesting that HA- treated cells after 24 hrs of shear stress\nmediated clusters partially protect tumor cells exposure, with or without 5 mM of the antioxidant\nagainst shear stress-induced cell death.\nN-acetylcysteine.\nThe updated text in the revised manuscript can be found on page 15 and reads “Since cell\nclustering can limit ROS production59, we tested whether oxidative stress contributes to the\nincreased shear stress-induced cell death in HA-lacking cells (Extended Data Fig. 4k-l).\nCompared to untreated wild type cells, shear stress exposure elevated ROS levels in both control\nand HAse-treated LM2 cells at 12 hrs (Extended Data Fig. 4m), a timepoint preceding extensive\ncell death of HAse treated cells (Extended Data Fig. 4k). However, the ROS levels were more\nthan two-fold higher in single HAse-treated cells compared to clustered control (Extended Data\nFig. 4m), suggesting that HA-mediated clustering promotes CTC survival by limiting shear stress-\ninduced ROS production. Addition of the antioxidant N-acetylcysteine (NAC) to repress ROS\nmoderately rescued cell death of HAse-treated single cells (Extended Data Fig. 4n). suggesting\nthat HA-mediated clustering at least partially shields tumor cells from shear stress-induced cell\ndeath.”\nMinor comments:\n1. Since SKBR3 cells are used in Fig. 1g, it would be more appropriate for the\nrepresentative image in Fig. 1f to also show SKBR3 cells, rather than BT474 cells. This would\nhelp maintain consistency between the panels.\nResponse:\nWe thank the Reviewer for catching this. We have adapted the Figures according to the\nReviewer’s suggestion.\n2. In the text, it is stated that “CTC clusters were detected in all 6 control mice”. However,\nonly 5 mice are shown in fig.5h& 5i.\nResponse:\nWe thank the Reviewer for catching this. The discrepancy between the text and Figure\nwas a typo and has been corrected.\n12\n3. Since the tumor cells were labeled with GFP, it is unclear whether the GFP signal will\nbe preserved during IF staining, especially given that HA is also detected using a green\nfluorophore. Could the authors clarify how these signals are distinguished in the images?\nResponse:\nWe apologize for the confusion; HA was stained in the far-red channel, and not in the\ngreen channel. The green color was only chosen as a pseudo-color. For presentation purposes,\nwe kept all HA signals in green throughout the manuscript. To avoid any confusion, we have now\nedited the figure legends and also included a clarification in the method section. The Figure\nlegends read “For visualization, HA staining was assigned a green pseudo-color. GFP signal is\nshown in grey in the Extended Data Fig. 5/6”. We have further indicated wherever a pseudo\nred/green color was used (if imaged cells express RFP or GFP respectively) by changing the\ndescription from “stained for HA (green)” to “stained for HA (green pseudo color)” to prevent future\nconfusion.\nReviewer #3 (Remarks to the Author):\nIn this manuscript, Bobkov and Patel et al. propose a novel role for hyaluronan in\ncirculating tumor cell (CTC) clustering during TNBC metastasis. They show that CTCs express\nHAS2, which synthesizes HA, and that HA interacts with CD44 on cancer cells to function as\nadherent junctions, which is very interesting and novel. Overall, the data are clear and well\npresented. However, some of the results sections are somewhat lengthy and would be better\nreorganizing or moving parts into the discussion. It is intriguing that HA appears to show such a\nstrong effect as a mediator of cell-cell interactions, the data overall support this hypothesis well.\nDetailed comments are as below:\n1. HA is a well-known serum marker for several cancers, including breast, prostate, and\ngastrointestinal cancers. Elevated serum HA levels have been correlated with a worse prognosis\nand increase risk of metastasis, which supports the findings of this study. However, this also\nindicates that HA is already abundant in the bloodstream of patients with cancer or tumor-bearing\nmice, suggesting that CTCs may not be the primary source of HA. Moreover, HA is highly\naccumulated in the primary tumor, raising the possibility that HA-coated cancer cells could detach\nfrom the primary tumor, intravasate, and form clusters. According to this study, endogenous HAS2\nexpression is crucial for HA-mediated CTC clustering (HAS2 overexpression and knockdown\nexperiments). In the context of rich HA in the bloodstream or culture media, CTCs can form\nclusters independently of HAS2 expression? Can you also compare HAS2 expression or HA\nintensity in LM2 clusters compared to LM2 single cells?\nResponse:\nWe thank the Reviewer for their recognition of our work. We have also edited the manuscript\nto make it more concise.\nFollowing the Reviewer’s suggestion, we tested whether exogenous HA in the culture media\ncan facilitate tumor cell clustering and found that high molecular weight (HMW; 750-1000kDa),\nbut not low molecular weight (LMW; 130-150kDa) HA can rescue the clustering defect of LM2\nHAS2 KD cells in a dosage dependent manner (Fig. R11 and revised Extended Data Fig. 2g).\nThis new data is shown on page 7-8 of the revised manuscript and reads “HA molecules can\nexist in different sizes and can elicit distinct cellular responses. To assess what form of HA\nfacilitates tumor cell clustering, we treated LM2 HAS2 KD cells for 1 hr with increasing\n13\nconcentrations of two different sizes of HA\nmolecules, a low molecular weight (130-150\nkDa) HA and a high molecular weight (750-\n1000 kDa) HA. Incubation with exogenous\nhigh molecular weight HA reconstituted\nclustering capabilities of LM2 HAS2 KD cells\nin a dose-dependent manner, whereas low\nmolecular weight HA failed to rescue\nclustering (Extended Data Fig. 2g). These\nresults are consistent with HAS2's function Fig. R11 Exogenous HMW HA can rescue tumor cell\nin producing HA molecules of higher clustering in HAS2 KD cells. (a) Quantification of\nnumbers of clusters formed by LM2 HAS2 KD cells\nmolecular weight41 and suggest that large\nafter treatment with low-molecular weight (130-150\nHA molecules are required to mediate tumor\nkDa) and high-molecular weight (750-1000 kDa) HA\ncell clustering, likely by providing enough\n(n=3). Cells were pre-incubated with the exogenous\ninteraction sites for HA receptors on two or\nHA for 1 hr prior to clustering for 1 hr. Concentrations\nmore tumor cells to stably interact with the in µg/mL indicated on the x-axis.\nsame HA moiety.”\nWhile these results suggest that high abundance of exogenous HA of the appropriate size\ncan mediate CTC clustering, such conditions are unlikely to occur in vivo. HA in the tumor\nmicroenvironment is thought to be a mixture of various sizes and is likely skewed towards LMW\nHA due to increased degradation by hyaluronidases and the resulting pro-tumorigenic effects\n(PMID: 31134064, 26106384). Although HA levels can be elevated in the bloodstream of breast\ncancer patients, they generally remain low in absolute concentration (PMID: 2394505, 26686298,\n26082778). Moreover, serum LMW HA (<50 kDa), but not total HA, was found to be correlated\nwith breast cancer metastasis (PMID: 25550464), suggesting that elevated serum HA is\ninsufficient to facilitate CTC clustering. Together, these factors help explain why HAS2 KD tumor\ncells in our in vivo experiments couldn’t compensate for their lack of HA by utilizing stromal HA to\nform CTC clusters.\nRegarding the last question, the HA intensity is not altered in clustered and single LM2\ncells, but the localization of HA shifts during the maturation of the cell-cell interaction, where it\ntransforms from an even coating of the cell surface (Fig. R12a and revised Fig. 6c) to enrichment\nat the interaction sites (Fig. R12b and revised Extended Data Fig. 6g).\nFig. R12 HA localization shifts during the maturation of the cell-cell interaction site (a) Maximum\nintensity projection of fixed early-interacting LM2 control (top) and HAS2 KD (bottom) cells stained for\nHA (green pseudo color) and CD44 (red). (b) Maximum intensity projections of fixed, heterotypic LM2\nCTC clusters containing one CTC and one non-tumor cell. Cells were stained for HA (green) and\nCD44 (red pseudo color). White arrowhead indicates the site of HA enrichment at the CTC and non-\nCTC interaction site.\n14\n2. Metastatic tumors often lose adherens junction expression as they undergo epithelial-\nto-mesenchymal transition. This transition is a very important process in metastasis. In this study,\nEpCAM-negative cancer cells show high HAS2 expression, whereas EpCAM-positive cancer\ncells exhibit little to no HAS2 expression (Fig. 1j and extended Fig.1l). Is there any evidence\nlinking the HAS2 or HAS2-HA -CD44 axis to epithelial-to-mesenchyamal phenotypic changes?\nAnd could this transition also be associated with CTC clustering or cell-cell interactions?\nResponse:\nWe thank the Reviewer for raising the important question whether HAS2 is linked to EMT\nphenotypic changes. The connection between HAS2 and EMT has indeed been documented by\nmultiple publications, such as HAS2 being required for TGFb induced EMT (PMID: 23108409), a\nZEB1/HAS2 positive feedback loop that promotes EMT in breast cancer (PMID: 28086235) and\nour previous work showing that depletion of HAS2 abolishes the effect of CD44s on promoting\nthe mesenchymal phenotype (PMID: 28533273). EMT traits highly correlate with HA-based CTC\nclustering (revised Fig. 1c), as cells undergoing EMT downregulate cell-cell interaction molecules\nand instead upregulate adhesion molecules focused on cell-ECM interactions (PMID: 24556840,\n15688013, 22778267, 23165231). We have now included the connection of HAS2/HA to EMT as\nwell as their connection to CTC clustering in Discussion. In our study, we measured E-Cadherin\n(Extended Data Fig. 1l) and interpreted the “EpCAM” mentioned in the comment as a referral to\nE-cadherin.\n3. While this study primarily focused on the TNBC metastasis, it would be important to\nclarify whether similar observations are found in other aggressive or malignant cancer types.\nResponse:\nWe thank the Reviewer for this great suggestion. We assessed the clustering capabilities\nof three different cell lines from other aggressive cancer types: the pancreatic PANC-1, the\nprostate PC3, and the glioblastoma DAOY. All three cell lines exhibit similar HAS2 and CD44\nexpression (Fig. R13a and revised Extended Data Fig. 2s). Consistent with the HA-based\nclustering mechanism identified in TNBC tumor cells, all three lines rapidly form clusters when\nsubjected to our cluster assay, and HAse treatment abolishes cluster formation (Fig. R13b-c and\nrevised Fig. 2l-m). These results show that the HA-based clustering mechanism is a feature\nshared by other aggressive and malignant cancer types.\nFig. R13 HA-based tumor cell clustering is a shared feature of multiple aggressive cancer types. (a)\nqRT-PCR analysis of HAS2 and CD44 mRNA expression in non-TNBC cancer cell lines. Data is\nnormalized to TBP. (n=3). (b-c) Representative pictures (b) and quantification of cluster number (c) of\nCtrl and HAse treated PC-3, PANC-1 and DAOY cells after 1 hr of clustering.\ncancer cell types, we performed the clustering assay using the prostate PC-3, the pancreatic\nPANC-1, and the glioblastoma DAOY cell lines. All three cell lines express HAS2 and CD44 at\nsimilar levels (Extended Data Fig. 2s), formed clusters under shear stress, and HAse treatment\nabolished clustering Fig. 2l-m). Together, these results support the notion that the HA-based\nclustering mechanism is employed by many metastatic cancer types in addition to TNBC tumor\ncells.”\n4. HA exists in both high-molecular weight and low-molecular weight forms, which are\nknown to play distinct roles in pathophysiology. The authors should determine the size of HA to\nbetter understand the novel function of HA.\nResponse:\nPlease see our response to Reviewer 3 Comment 1. We determined the size of HA and\nfound high-molecular weight HA to be required for the clustering process.\n5. The authors suggest that tumor cells express HAS, which synthesize HA, and that this\nHA interacts with CD44 on cancer cells, forming a kind of autocrine loop. This axis mediates cell-\ncell interactions and promotes CTC clustering. The HA-CD44 interaction has been extensively\nstudied in cancer biology. Do HA-coated CTC clusters also contribute to extravasation, cancer\ncell migration, or invasion, at later step of metastasis? In vivo data suggest that HA-mediated CTC\nclustering plays an important role in TNBC lung metastasis (Fig.5). Given that HA-CD44 is\nimportant for CTC survival, what is the downstream pathway of HA-CD44 in CTCs clustering?\nResponse:\nWe thank the Reviewer for this question. Accordingly, we performed an in vitro invasion\nassay to determine whether HA-coated CTC clusters also contribute to invasion. Our results\nshown in Fig. R1b and revised Extended Data Fig. 5b are now included on page 14. It reads:\n“Additionally, a Matrigel-based in vitro invasion assay revealed that HA-lacking single cells have\nreduced invasive capacity compared to clustered control cells (Extended Data Fig. 5b).”\nAdditionally, we performed a 24 hrs tail vein experiment to examine differences in lung\ncolonization between pre-aggregated LM2 control and HAS2 KD cells. The resulting increased\ncolonization by control cells further suggests that HA-coated clusters have enhanced ability to\nsurvive shear stress, extravasate and/or colonize metastatic sites. The results are shown in\nresponse to Reviewer 1 Comment 1.\nRegarding the downstream signaling pathways induced by CD44-HA interaction, we and\nothers have shown that CD44-HA interaction activates the PI3K-Akt signaling pathway (PMID:\n28533273, 33024087, 11408591, 12145277). This survival advantage of HA-dependent CTC\nclusters is further supported by our results shown in the revised Extended Data Fig. 4k-n.\n6. It is quite surprising that HA-coated CTC clustering is prominent under shear stress.\nHow does HA uniquely contribute under these conditions? What is the mechanism of HAS2-HA\nupregulation in CTCs? What upstream signals stimulate HAS2 to synthesize HA? or, metastatic\nTNBC cells constitutively express HAS2? Since clustering occurs very rapidly, in a minute, is it\npossible that shear stress can quickly induce HA secretion? In addition, given that HA-CD44 is\ninvolved in cell-cell interaction, this could be involved in cell-cell interactions in the primary tumor.\nWhat distinguishes HA in the blood stream from HA at the primary tumor site from HA?\nAdditionally, how do cancer cells sense shear stress and respond to cluster formation via HA?\nThese are a set of great questions. We found that HAS2 is upregulated in highly metastatic\nTNBC cells and constitutively expressed (revised Fig. 1b, 1j), which enables TNBC CTCs to form\nHA-dependent clusters. Our previous study (PMID: 28533273) showed that CD44/HA interaction\nelicits a positive-feedback loop that stimulates PI3K/Akt, resulting in inhibition of FOXO1, a\ntranscription repressor of HAS2. In turn, this results in upregulation of HAS2, producing HA. We\nagree with the Reviewer that HA-CD44-mediated cell-cell interactions can occur in the primary\ntumor, although as discussed in our response to Reviewer 3, Comment 1, the molecular weight\nof the HA present in the tumor microenvironment and the bloodstream is likely of LMW and thus\nnot able to induce tumor cell clustering. Instead, our results suggest that tumor-derived HA is key\nfor the clustering process (revised Fig. 5, 6, and revised Extended Data Fig. 5, 6). How cancer\ncells sense shear stress and respond to cluster formation via HA is an excellent question. As it is\nout of the scope of current study, we will investigate it in the future.\n7. As authors stated in the Introduction, CD44 is expressed by many cell types, including\nimmune cells. In Fig. 6, authors suggest that HA facilitates interactions between CTCs and non-\nCTCs. Any chance to work in heterotypic clusters with immune cells or CAFs? HA is also\nexpressed by cancer cells and cancer-associated fibroblasts.\nResponse:\nAs shown in revised Fig. 6k-n and revised Extended data Fig. 6f-i, we show that immune\ncells can indeed be recruited into heterotypic CTC clusters. Importantly, CTC-bound HA\nmolecules translocate to the interaction site with the HA-lacking immune cells, supporting the\nnotion that HA from CTCs promotes the interaction between CTCs and immune cells. We thank\nthe Reviewer for bringing up CAFs, as they have been shown to form heterotypic clusters with\nCTCs (PMID: 34216317), and we now cite it as reference 8 in the revised manuscript. It reads on\npage 3: “Metastatic spreading of tumor cells to secondary sites remains the major cause of\ncancer-related deaths. Circulating tumor cells (CTCs) represent an intermediate stage of\nmetastasis and travel through the blood as single cells or as clusters. The latter can be composed\nsolely of CTCs, or exist as heterotypic clusters that include other cell types, such as white blood\ncells1-4, platelets5,6, or cancer-associated fibroblasts7,8.”\n8. Non-metastatic cell lines, such as MCF7 and BT474, hardly express HAS2 (Fig. 1j), but\nthey highly express EPCAM (extended Fig. 1l), showing almost no clustering (Fig. 1f). Given that\nEPCAM is also known to mediate cell-cell interactions, it is somewhat surprising that HA appears\nto have a stronger effect that EpCAM in promoting cluster formation. In addition, the HA-CD44\naxis appears to act as a master regulator of CTC clustering, rather than functioning as an AJ-\nindependent pathway. In Fig.2 and extended Fig.2, HAse treatment, HAS2 KD, or CD44 KO nearly\nabolishes all CTC clustering. This raises the question of whether HA-CD44 plays roles beyond\njust mediating cell-cell interactions.\nResponse:\nWe believed the Reviewer meant E-cadherin and not EpCAM, as we did not discuss\nEpCAM in the manuscript. The Reviewer is correct that E-Cadherin can facilitate cell clustering\n(PMID: 26831077). Please see also our response to Reviewer 1, Minor point 1. We have now\nstreamlined our description and added new data to support our conclusion. We show that the E-\ncadherin-positive MCF7 cells fail to form clusters under shear stress but can form clusters under\nno-stress conditions (Fig. R3 and revised Extended Data Fig. 4h). Once formed, these clusters\nare highly stable and capable of withstanding shear stress (Fig. R3 and revised Extended Data\nFig. 4h).\n17\n9. The authors used 293FT cell line to investigate the role of HA-CD44 in TNBC clustering\n(Extended Fig.2). While it is understandable that they chose this line because it lacks both HAS2\nand CD44, it is not a breast cancer cell line. It would be better if the authors could replicate these\nexperiments in breast cancer cell line.\nResponse:\nWe thank the Reviewer for their comment. The purpose of using 293FT cells was to\ndemonstrate that a CD44-negative and HAS2-negative non-clustering cell line can acquire\nclustering ability upon introduction of CD44 and HAS2 expression, and that the CD44-R41A\nmutant, which cannot bind HA, fails to confer this clustering ability (revised Fig. 2h-j and revised\nExtended Data Fig. 2o-r). Similarly, we also transformed the non-clustering TNBC line SUM159\ninto a clustering one by inducing the formation of an HA coat through the ectopic expression of\nHAS2. In line with the Reviewer’s suggestion, we updated the title of the respective paragraph on\npage 8 from “HA-CD44 interaction is sufficient to induce TNBC cell clustering” to “HA-CD44\ninteraction is sufficient to induce tumor cell clustering”. This broader title further allows inclusion\nof the newly added data showing that non-breast cancer metastatic cell lines can cluster through\nHA (Fig. R13 and revised Fig. 2l-m) into the paragraph (see Reviewer 3, comment 3).\n10. According to the literature, CD44 is known to be important for homophilic CTC\nclustering. However, Fig. 2c-d suggests CD44 function is impaired in the absence of HA. To\ndirectly test whether HA-CD44 interaction is crucial for TNBC CTC clustering, authors should\nconsider block this interaction using a specific antagonist.\nResponse:\nThe Reviewer is correct that CD44 has\nbeen reported to be important for homophilic\nCTC clustering (PMID: 30361447). We\nrecapitulated previous results showing CD44 is\nrequired for clustering in a no-shear stress\nsetting. We specifically addressed the\ndifferences between our results and the earlier Fig. R14 Quantification of the number of clusters\npaper in Fig. 4. In short, homophilic CD44 formed by IgG-treated or CD44 blocking antibody\nIM7-treated LM2, WHIM12, and SUM159 HAS2\ninteraction alone can facilitate loose tumor cell\nOE cells after 1 hr of clustering (n=3).\naggregation under no-stress conditions. In the\nabsence of HA, however, these clusters are\nnot functional as they rapidly dissociate under physiological levels of shear stress (revised Fig.\n4a-d and revised Extended Data Fig. 4a-g). The presence of HA enables tumor cell clusters to\nwithstand shear stress CTC clusters encounter in the bloodstream.\nTo show HA-CD44 interaction is crucial, we performed two sets of experiments. First, in\nline with the Reviewer’s comment, we used a CD44 antibody as a specific antagonist and showed\nthat it abolished tumor cell clustering (Fig. R14a and revised Fig. 2k). Moreover, we used the\nCD44 R41A mutant that prevents its interaction with HA and demonstrated that the HA-CD44\ninteraction is crucial for cell clustering (revised Fig. 2h-j and revised Extended Data Fig. 2o-r). We\nthank the Reviewer for their comments.\nReviewer #4, ECR co-reviewing with Reviewer #1(Remarks to the Author):\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is\npart of the Nature Communications initiative to facilitate training in peer review and to provide\nappropriate recognition for Early Career Researchers who co-review manuscripts.\nReviewer #1 (Remarks to the Author):\nIn this resubmitted manuscript, the authors have responded conscientiously and directly to the\nconcerns of the reviewers. The new Matrigel invasion results are interesting and support the\ninterpretation of increased invasive metastasis. However, there seems to be a puzzle. This\ntransfilter assay is thought to measure single-cell invasion, whereas the CTC clusters are\ntighter. Do the authors have some idea or speculation on how to reconcile these apparent\ncontradictions? For example, does HA increase both cell-cell adhesion in suspension and individual cell\ninvasiveness when exposed to a matrix?\nResponse:\nWe thank the Reviewer for this thoughtful comment. Previous studies have shown that TNBC cell\nclusters can traverse capillary-sized constrictions of 5 um by dynamically rearranging the cluster\nstructure. Tumor cells within the original cluster remain connected while passing through the\nconstriction in a single-file fashion, and reform into clusters upon exiting. This work was discussed\nin the Discussion section of the manuscript (Ref. 74). Although the pore size of transwell would\nprimarily permit the passage of single cells or very small clusters, HA-mediated clusters may\nsimilarly transverse the transwell in a single-file configuration. While unlikely, we cannot exclude\nthe possibility that clustered cells migrate through adjacent pores as individual cells, which would\nsuggest that HA directly enhances cell invasion. Nonetheless, even under this scenario, the\nfindings remain consistent with a contribution of HA to promote metastatic processes.\nReviewer #2 (Remarks to the Author):\nThe authors have addressed all my concerns.\nReviewer #3 (Remarks to the Author):\nThe authors have adequately addressed all reviewer comments in the revised manuscript.\nReviewer #4 (Remarks to the Author):\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is\npart of the Nature Communications initiative to facilitate training in peer review and to provide\nappropriate recognition for Early Career Researchers who co-review manuscripts."}]

Decision letter