The myeloid SRC family kinase HCK regulates breast cancer growth by activating tumor-associated macrophage-led invasion and inhibiting cytotoxic T cell activity

doi:10.21203/rs.3.rs-4982107/v1

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The myeloid SRC family kinase HCK regulates breast cancer growth by activating tumor-associated macrophage-led invasion and inhibiting cytotoxic T cell activity

https://doi.org/10.21203/rs.3.rs-4982107/v1

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The normal developmental and homeostatic roles of tissue resident macrophages are subverted in tumor-associated macrophages to promote tumor progression. Pro-tumoral macrophage activities include immune evasion and promotion of invasion and metastasis. We show that both activities are regulated by the myeloid Src family kinase HCK, which drives macrophage motility and invasive capacity. Loss of HCK reduced the growth of the aggressively invasive Py8119 mammary tumor by 70–80% while excessive HCK activity increased tumor growth. Consistent with a role for HCK in regulating macrophage invasiveness, plasma membrane-associated Src family kinase activity at the tumor margins was lost in the absence of HCK. Additionally, tumors from HCK-deficient hosts contained increased CD8⁺ T cell numbers and CD8⁺ T cell depletion reduced survival of tumor-bearing mice. However, CD8⁺ T cell-depleted HCK-deficient mice continued to show a significant survival advantage over CD8⁺ T cell-replete control mice, confirming a T cell-independent role for HCK in the promotion of tumor invasion and metastasis. Single cell RNA sequencing confirmed that macrophages comprised more than 40% of tumor mass associated with CSF-1 and IL-34 secretion by Py8119 cells and that loss of HCK activity did not affect macrophage recruitment. Tumor-associated macrophages were clustered into 5 subtypes, immunoregulatory (Folr2^high), inflammatory (H2-Aa^high), interferon-primed, angiogenic and tissue resident, and their relative proportions were not affected by HCK activity. Thus, HCK regulates macrophage invasive capacity and cytotoxic T cell numbers but not macrophage numbers or their subtype distribution to drive Py8119 tumor growth.

tumor associated macrophages

HCK

breast cancer

tumor invasion

cytotoxic T cells

Cells of a myeloid origin, particularly tumor associated macrophages (TAMs), play important roles as determinants of tumor progression and response to therapy in all solid malignancies. Macrophage functional plasticity underpins the ability of TAMs to orchestrate complex and variable responses to tumors as they progress (1). Accordingly, the effects of the local microenvironment on TAMs have been linked to the functional dichotomy between the conventional activation of macrophages to execute their normal homeostatic activities in tissues and the various tumor promoting TAM endotypes that arise from alternative activation cues in tumors (2). Indeed, the latter encompass different functional subsets including those with angiogenic, immune-suppressive, inflammatory and interferon-responsive characteristics (3, 4). Collectively however, TAMs retain the capacity for interstitial migration, normally required by tissue resident macrophages for development and homeostasis, including guiding the formation of the mammary gland ductal network (5, 6). These insights suggest that TAMs may serve as therapeutic targets to help control tumor promotion by either limiting their abundance in the tumor microenvironment, suppressing their polarization toward alternative activated endotypes or blocking a specific tumor promoting behavior.

Therapeutic control of macrophage polarization and associated endotypes has become a major interest for the control of cancer. Several molecules have been identified that appear to play a role at the apex of signaling cascades controlling TAM plasticity and in particular limiting and/or reverting alternative activation. Among those, inhibition of phosphatidyl inositol 3-kinase (PI3K)γ or of the myeloid Src family kinase (SFK) hematopoietic cell kinase (HCK) has attracted interest to convert immune-suppressive to immune-permissive tumor microenvironments (7, 8). Interestingly, both p110δ and HCK are functionally associated with the receptor for colony-stimulating factor-1 (CSF-1R), which not only promotes maturation along the monocyte-macrophage trajectory, but also regulates macrophage motility and associated remodeling of the extracellular matrix (ECM) (9–11). Indeed, selective inhibition of either p110δ or HCK impairs macrophage motility in vitro and, when co-cultured with mammary tumor spheroids, suppresses invasion of tumor cells (9, 12, 13). On the other hand, bone marrow-derived macrophages (BMM) expressing a constitutively active isoform of HCK (Hck^CA) are hyper-motile and promote increased invasion of tumor cells into the surrounding matrix (13). TAMs derived from tumor-bearing Hck^CA hosts also show a pronounced bias towards alternative activation, thereby limiting the anti-tumor immune responses conferred by CD8 and NK effector cells across models of colon, gastric and pancreatic cancer (13–15). This occurs despite myeloid cells contributing a relatively low proportion of cells in these tumors and correlates with suppression of effector cell infiltration and an associated reduction of effector molecules alongside excessive extracellular matrix deposition.

In this study, we show that ablation of HCK activity in a myeloid cell-rich model for chemoresistant mesenchymal-like basal breast cancers confers a significant benefit through suppression of TAM motility in invasive orthotopic Py8119 mammary tumors. This model is renowned for its high expression of CSF-1, recruitment of large numbers of TAMs and aggressively invasive (12, 16). In an allelic series of HCK mutant hosts, we demonstrate that increased HCK activity promotes Py8119 mammary tumor growth and invasion. Conversely, therapeutic inhibition of HCK reduced Py8119 tumor growth in vivo, largely through mechanisms associated with reduced TAM motility. Thus, HCK could provide a myeloid cell-specific therapeutic target to limit tumor progression through complementary cellular mechanisms mediated directly and indirectly by TAMs.

Animal ethics

In vivo mammary tumor growth experiments were carried out strictly according to the ethics requirements of the University of Western Australia, which permitted 4 tumors per mouse and a maximum tumor size of 2 tumors each measuring 10x10mm (RA/3/100/1504, RA/3/100/1540). Hck-deficient (Hck^KO), constitutively active Hck (Hck^CA) and therapeutic RK20449 experiments were carried out at the Olivia Newton John Cancer Research Institute under an ethics approval permitting one tumor per mouse with a maximum tumor volume of 1000mm³ (Austin Health A2021-5746).

Orthotopic mammary tumor models

Female mice aged 10–12 weeks of age were injected with 1x10⁶ Py8119 cells into each of four mammary fat pads (#3 and #4 bilaterally)(ATCC Cat# CRL-3278, RRD: CVCL_AQ09). C57BL/6 mice (RRD:IMSR_JAX:000664) were sourced from the Animal Resources Centre (WA) for inhibitor experiments. Inhibitors were started the day the tumor cells were injected. For HCK inhibition, 30 mg/kg RK20449 (10 mice)(synthesized by Reagency) or vehicle (10 mice)(10% Captisol) was injected twice daily by intraperitoneal (IP) injection. For PI3K p110δ inhibition, mice were treated with 30 mg/kg GS-9820 (9 mice)(Gilead Sciences, Foster City, CA) and compared to the CSF-1R inhibitor GW-2580 (5 mice)(80 mg/kg, Calbiochem, San Diego, CA) or vehicle (9 mice)(0.5% w/v methylcellulose/0.1% Tween 80) twice daily by oral gavage.

Hck-deficient (Hck^KO), constitutively active Hck (Hck^CA) and therapeutic RK20449 experiments were carried out at the Olivia Newton John Cancer Research Institute under an ethics approval that permitted one tumor per mouse. Six female mice aged 10–12 weeks of age per group were injected with 1x10⁶ cells into the right inguinal mammary fat pad (#4) and, if RK20449 or Captisol were administered, treatment was started when tumors were palpable (Day 8). For CD8⁺ T cell and NK cell depletion, female Hck^WT, Hck^KO and Hck^CA mice were given three 200µg doses of either IgG, αCD8 (RRID:AB_322770, JPP Biologics) or αNK1.1 (RRID:AB_630043, JPP Biologics)(5 mice/group) prior to tumor cell inoculation and then continued every three days until the experimental endpoint.

Py8119 tumor processing

Tumors were fixed in 4% paraformaldehyde (PFA, EMS, Hatfield, PA) and paraffin embedded (FFPE) or snap frozen for subsequent RNA or protein extraction. For single cell analyses, tumors were minced with scalpel blades and dissociated in 0.1 mg/ml DNAse 1 (Merck, Bayswater, Vic) and 1.5 mg/ml collagenase type 4 (Worthington, Lakewood, NJ) for 1 hour at 37°C with an additional 0.1 mg/ml of DNAse 1 added for 30 minutes then passed through a 100µM cell strainer followed by red cell lysis. Aliquots of 1x10⁶ cells were stored at -80°C in 50% FCS, 10% DMSO in F12K media.

Macrophage extraction and cell culture

Bone marrow was flushed from the femurs and tibiae of 8–10 week old wild type (WT) or Lyn^-/- mice. Non-adherent mononuclear phagocytic precursor cells were differentiated into mature BMM in increasing doses of CSF-1 as described in Murrey et al. (Murrey et al., 2020). BMM were cultured in 120 ng/ml CSF-1 (kind gift of Dr E.R. Stanley) in α + MEM (Life Technologies, NY) containing 10% fetal calf serum (FCS, Bovogen, Melbourne, Vic) with 10,000U/ml penicillin and streptomycin (Thermo Fisher Scientific, Scoresby, Vic). Py8119 cells were grown in Ham’s F-12K media (Thermo Fisher Scientific) with 5% FCS, 0.1% Mito serum extender (Corning, Clayton, Vic), 50 µg/ml gentamicin and 2.5 µg/ml amphotericin B (Thermo Fisher Scientific).

Quantitative PCR

RNA extraction was carried out using the RNeasy protocol and converted to cDNA using Omniscript reverse transcriptase, according to the manufacturer’s instructions (Qiagen, Clayton, Vic). Mouse oligonucleotide primers were as previously described (10). PCR amplification was carried out using a Bio-Rad iQ5 light cycler using iQ SYBR Green Supermix (Bio‐Rad, Gladesville, NSW). The mRNA expression of individual SFKs was determined relative to RPLPO and GAPDH and corrected for the efficiency of each PCR reaction.

Chemotaxis and invasion assays

BMM were seeded at 2x10⁵ cells in 100µl CSF-1 free media into 0.8µM pore-size transwell chambers (BD Biosciences, Macquarie Park, NSW) and placed into media with 120 ng/ml CSF-1 in the lower chamber. BMM were incubated for 6 hours and migrated cells fixed in 4% paraformaldehyde (PFA) (EMS, Hatfield, PA) then counted (10 fields/insert). To correct for cell loading, 2x10⁴ cells were added to insert-free wells. For the Py8119/BMM invasion assays, 4x10⁴ Py8119 cells +/- 2x10⁴ BMM in 500µl CSF-1-containing media were added to BD Biocoat Matrigel invasion chambers (BD Biosciences) and placed in wells containing 500µl media for 18 hours before processing as above.

Inhibitor Growth curves

Py8119 cells were seeded in 96 well plates at 5x10³ cells per well and four wells per condition. Cells were allowed to settle for one hour prior to treatment with media containing either 10nM RK20449 or 30nM Dasatinib or Captisol/DMSO as control then the assay plates were inserted into an IncuCyte Zoom incubator (RRID:SCR_019874, Essen Bioscience). Four phase-contrast images were taken per well every two hours for 48 hours. Incucyte software measured cell growth as percent confluence. Significance testing was carried out on the doubling times of each condition using a one-way ANOVA, N = 4.

Immunohistochemistry

Dewaxed 5µm thick FFPE tumor sections were subjected to heat mediated antigen retrieval in citrate (pH6) buffer with 0.05% Tween 20. EDTA (pH9) buffer was used for phosphospecific antibodies. After antigen retrieval, sections were incubated with 3% H₂O₂ for 5 minutes to block endogenous peroxidases followed by permeabilization in 0.1% Triton-X 100 in TBS for 10 minutes. Tissue sections were then blocked with 5% BSA in TBS for 30 minutes then incubated with primary antibody diluted in 1% BSA TBS overnight at 4°C. Prediluted EnVision peroxidase system (DAKO/Agilent, Musgrave, Vic) was used with DAB for visualisation (Vector Laboratories, Newark, California). Tissues were counterstained with Gills hematoxylin and mounted in DePeX (BDH Laboratory Supplies, Poole, UK). To compare TAMs in vehicle and drug-treated tumor margins, detect ionized Ca-binding adapter molecule 1 (IBA1)⁺ cells per area of tumor tissue within a 500µm circumference of the tumor edge were quantified using CellProfiler Image Analysis Software (RRID:SCR_007358). To distinguish tumor centers from the margins, the center was measured as the area 1mm from the tumor edge. Areas of necrosis or tissue artifact were eliminated from the analysis.

For multiplex immunofluorescent IHC, antigen retrieval was carried out as above followed by permeabilization with 0.1% Triton-X 100. Tissues were blocked with 5% BSA in TBS with DAPI (Thermo Fisher Scientific) for 30 minutes then incubated with pooled primary antibodies in 1% BSA in TBS for 1 hour, washed and incubated with pooled secondary antibodies for another hour. Tissue autofluorescence was quenched in 10mM CuSO₄ and 50mM (NH₄)₂SO₄ for 10 minutes (17) and mounted in Prolong Diamond (Thermo Fisher Scientific). Slides were imaged on a Nikon A1R confocal microscope with a CFI Plan Apochromat Lambda 20x objective, NA 0.75 using NIS-Elements software (RRID:SCR_014329).

Antibodies

See Supplementary Table 1 for a list of IHC antibodies.

Quantification of pY SFK signal and T cell numbers

Quantification of phospho-SFK staining was carried out using Fiji software (RRID:SCR_002285) (18). Briefly, the auto-threshold function was used to generate a region of interest around Iba1⁺ cells and the mean gray signal of pY-SFK staining recorded within this region. For quantification of (CD3/CD8/Perforin) positive cells, stained cells were counted using the multi-point tool. A minimum of four tumors were imaged per condition and quantification was carried out on at least two fields per tumor.

10x Genomics Chromium library construction, sequencing and analysis

The cryopreserved dissociated tumor cells were recovered according to the Thawing Dissociated Tumor cells for Single Cell RNA Sequencing Demonstrated Protocol (CG000233 Rev A, 10x Genomics). Single cell libraries from three vehicle and three RK20449-treated tumors were constructed according to the Chromium Next GEM Single Cell 3’ Reagent kits v2 in 2018 with approximately 9000 cells captured per sample. Subsequent single cell libraries were constructed from early (3) and late (3) tumors, Hck^WT (3) and Hck^KO (3) tumors, and Hck^WT (2) and Hck^CA (2) tumors according to the Chromium Next GEM Single Cell 3’ Reagent kits v3.1 (Dual Index) User Guide (CG000315 Rev E) with approximately 6000 cells per sample. All 22 single cell libraries were sequenced on the Illumina NovaSeq 6000. The BCL sequencing files were demultiplexed and converted into FASTQ using the bcl2fastq utility of Illumina BaseSpace Sequence Hub (RRID:SCR_015058). FASTQ files were processed using Cell Ranger 7.0.0 (RRID:SCR_017344) using the Cell Ranger-compatible transcriptome refdata-gex-mm10-2020-A reference. Both intronic and exonic reads were counted. Low quality cells were filtered by removing cells that expressed either fewer than 200 genes or more than 10% mitochondrial genes. The data were then integrated using Seurat v.5 (RRID:SCR_016341) as described at the SCTransform workflow using Seurat toolkit (version 5) (https://satijalab.org/seurat/articles/integration_introduction) (19). A clustering resolution of 0.7 was used to produce 25 clusters. After the first integration, hybrid cells expressing mixed genes were removed and the object was re-integrated and re-clustered. Clusters were annotated using marker genes generated by Seurat findallmarkers function and further informed by canonical marker genes based on the literature (20–22). Two-dimensional unified manifold approximation and projections (UMAP) were created using Seurat. Violin plots were created using the scCustomize package (RRID:SCR_024675) (23). Gene set enrichment analysis was carried out using the gProfiler2 package and GOSt function (RRID:SCR_018190) (24). An FDR cutoff of 0.05 was used.

Statistical analysis

GraphPad Prism 9.5 (RRID:SCR_002798) was used to carry out statistical analysis for all in vitro assays and for analysis of tumour weights from animal experiments. Values are displayed as mean +/- SEM or SD. Students T-test (two-tailed, unpaired) was used to compare the means of two groups. For three or more groups, one-way ANOVA was used with Tukeys post-hoc correction. P values < 0.05 were considered significant The DElegate software package was used to convert single cell expression data to a pseudo-bulk data set for analysis of differential gene expression using the EdgeR method. Adjusted P values < 0.05 were considered significant and differentially expressed genes expressed in less than 10% of either condition were excluded.

Inhibition of macrophage motility reduces Py8119 mammary tumor growth

To determine whether HCK activity regulates macrophage motility and associated invasive growth, we took advantage of the fact that HCK becomes activated in response to ligand engagement of the CSF-1R-and resulting stimulation of macrophage motility. Accordingly, we inhibited HCK activity with the pyrrolo-pyrimidine compound RK20449 (25), which we have previously shown to block motility and invasive capacity of both WT and Hck^CA BMM in vitro (10, 13), and to reduce tumor growth in colorectal, gastric and pancreatic cancer in vivo (13–15). Female mice were injected with Py8119 cells and RK20449 injections started immediately, thereby reducing mammary tumor growth by 70% (3.3-fold) (Fig. 1A). We then observed that inhibition of PI3K p110δ with the selective inhibitor GS-9820 (acalisib) reduced tumor size by 35% (1.5-fold) (Fig. 1B) (26).

Figure 1. HCK and PI3K p110δ regulate Py8119 mammary tumor growth. (A) Tumor weights of mice treated prophylactically with the HCK inhibitor RK20449 (RK). (B) Tumor weights of mice treated prophylactically with the PI3K p110δ inhibitor GS9820 (GS) or the CSF-1R inhibitor GW2580 (GW). (C) Tumor weights of mice treated therapeutically with the HCK inhibitor RK20449 (RK). (D) Tumor sections stained for IBA1 + TAMs. (E) Quantification of TAMs at the tumor margin in vehicle and RK20449-treated tumors and at the tumor margin and tumor core in vehicle and GS9820-treated tumors. (F) Tumor weights of Hck^WT and Hck^KO mice. (G) Tumor weights of Hck^WT and Hck^CA mice. Scale bar, 200µm. Mean ± SEM is shown, ns denotes not significant, *p < 0.05, ****p < 0.0001.

In contrast and consistent with previous reports, pan-CSF-1R inhibition by GW-2580 did not reduce tumor growth (Fig. 1B) (27). Finally, therapeutic inhibition of HCK by administration of RK20449 to mice with established (palpable) tumors also reduced tumor growth by 70% (Fig. 1C). To exclude the possibility that RK20449 treatment would directly affect the growth of Py8119 cells, which do not express HCK, we determined their doubling time and found that it was unaffected by RK20449 but suppressed by a pan-SFK inhibitor dasatinib (Supplementary Fig. 1A-D).

Supplementary Fig. 1. Py8119 cell in vitro data. (A,B) Relative expression of SFKs in Py8119 cells. (C,D) Proliferation of Py8119 cells treated with RK20449 or dasatinib, *p < 0.05.

To determine the effect of motility inhibition on TAM numbers in Py8119 tumors, we used immunohistochemistry (IHC) and the macrophage marker IBA1 to monitor the distribution of TAMs across Py8119 tumors. Abundant TAMs were seen, particularly at the tumor edge. While PI3K p110δ inhibition reduced the number of TAMs at the tumor edge, HCK inhibition neither affected their numbers nor their accumulation at the tumor edge (Fig. 1D,E). Taken together, inhibition of CSF-1R-activated macrophage motility but not full CSF-1R blockade reduced Py8119 mammary tumor growth. Moreover, tumor growth inhibition occurred independent of the number of distribution of TAMs.

HCK activity correlates with Py8119 mammary tumor growth

Because HCK inhibition profoundly reduced Py8119 tumor growth and hyper-motile Hck^CA BMM showed increased invasion in Py8119 mammospheres in vitro (13), tumor growth was examined in hosts either deficient in HCK expression (Hck^KO) or expressing constitutively active HCK (Hck^CA). Hck-deficient hosts limited growth by more than 7-fold compared to WT hosts whereas hosts expressing the HCK^CA isoform enabled tumors to grow to 4-fold increased size relative to WT hosts (Fig. 1F,G). Notably, frequent ulceration into overlying skin in Hck^CA mice necessitated sacrifice at smaller tumor size in this experiment.

Loss of HCK activity reduces SFK activity in Py8119 tumor margins

Because HCK activity correlated positively with tumor growth, we used a pY410-specific HCK antibody to examine the distribution of the active isoform of HCK by IHC. Strong nuclear staining in Hck^KO tumors indicated the antibody was not specific for HCK (Supplementary Fig. 2), whereas a pan-pY416-SFK specific antibody demonstrated plasma membrane-associated SFK activity at the margins of Py8119 tumors in treatment-naïve and vehicle-treated Hck^WT hosts (Fig. 2A-C). In contrast, membrane-associated SFK activity was absent at the margins of tumors recovered from Hck^KO and RK20449-treated Hck^WT hosts (Fig. 2A,C,D,F). Membrane-associated SFK activity extended further from the tumor margins in Hck^CA tumors although activity at tumor margins was not measurably increased (Fig. 2B,E). These results indicate that membrane-associated SFK activity is seen in TAMs and other cells at Py8119 mammary tumor margins, particularly in areas associated with invasion, and that much of the pY-SFK signal is due to active HCK in TAMs.

Supplementary Fig. 2. Anti-pHck antibody is non-specific. pY HCK (red) co-localizes with DAPI (blue) in Py8119 tumor nuclei in Hck^KO mice. Iba1⁺ TAMs are shown in green. Scale bar, 200µm.

HCK regulates cytotoxic T cell numbers in Py8119 tumors

We have shown in other tumor models that HCK deletion or inhibition increases cytotoxic T cell recruitment and activation (8, 15). This may account for some of the effect conferred by HCK expression in the host to the growth of Py8119 tumors. Consistent with this, both CD8⁺ T cell abundance and activity (perforin) were increased 4-fold in tumors from Hck^KO hosts and scant CD8⁺ T cells were seen in tumors from Hck^CA hosts (Fig. 3A-D). RK20449 did not change CD8⁺ T cell numbers (Fig. 3E), perhaps due to its known affinity for the T cell-specific SFK member LCK. Thus, HCK activity in TAMs appears to regulate cytotoxic T cell numbers and activity in Py8119 tumors.

An anti-CD8⁺T cell antibody (YTS169) was used to examine the effect of CD8⁺ T cells on Py8119 tumor growth. Hck^WT, Hck^KO and Hck^CA hosts were injected with the antibody prior to, during and after tumor cell inoculation. CD8⁺ T cell depletion reduced survival of tumor-bearing Hck^WT hosts from 25.5 to 20.5 days (p < 0.01), from 41.0 to 34.0 days (p < 0.001) of Hck^KO hosts, and from 15.5 to 14.5 days (p < 0.05) of Hck^CA hosts (Fig. 3F). However, following T cell depletion, Hck^KO hosts survived 14 days longer than Hck^WT hosts lacking cytotoxic T cells (p < 0.0001) and 8.5 days longer than Hck^WT mice treated with an isotype IgG control (p < 0.001). NK cell depletion had little effect on tumor growth in any genotype (Supplementary Fig. 3). These results demonstrate that the effect of HCK inhibition is in part mediated by adaptive immune responses, which is consistent with our findings in MC38 colon and KPC pancreatic tumors (8, 15).

Supplementary Fig. 3. NK cell depletion does not affect Py8119 tumor growth. Survival of Py8119 tumor-bearing Hck^WT, Hck^KO and Hck^CA mice treated with either anti-NK.1 antibody or IgG isotype control.

TAMs comprise more than 40% of Py8119 mammary tumor mass

To further examine the role of HCK in Py8119 tumors, single cell RNA sequencing (scRNA-seq) was carried out on tumors harvested from RK20449-treated, Hck^KO, Hck^CA and matched control hosts. Initially, because the rapid growth and high ulceration rate of tumors in Hck^CA hosts resulted in the recovery of smaller tumors from matched WT hosts (0.206g) than those from WT hosts paired with Hck^KO hosts (1.04g), 10 day (early) and 14 day (late) tumors from WT hosts were characterized to determine whether tumor size affected tumor cellular composition. Transcriptomes of 16,477 cells were sequenced, filtered and normalized to cluster cells in an unbiased manner with annotation based on differentially expressed genes (DEGs) in Seurat and lineage specific markers (Supplementary File 1). TAMs comprised 42.6% of cells in early tumors and 42.1% in terminal volume tumors and tumor cells 43.5% and 39.1% respectively (Table 1) (Fig. 4A).

As tumor stage did not affect Py8119 tumor composition, tumors from all genotypes, treatment groups and stages were then combined (> 103,000 cells), clustered and annotated. Overall, TAMs made up 44.0% of cells compared to 44.4% tumor cells, 5.5% T and NK cells with small clusters of other cell types (Table 1). High Py8119 cell expression of two macrophage chemokines, CSF-1 and interleukin (IL)-34, led to TAM recruitment (Fig. 4B). When the scRNA-seq data were separated by HCK treatment or genotype, consistent with the IHC findings, HCK inhibition and deletion did not reduce TAM numbers (Table 1). In contrast, TAM numbers appeared to be reduced in Hck^CA tumors (Table 1). Also consistent with the IHC findings, HCK deletion doubled T and NK cell numbers (4.6 to 10.6%, p = 0.039) while RK290449 treatment reduced them (6.7 to 2.9%), the latter finding probably reflecting off-target inhibition of LCK in T cells. Finally, scRNA-seq data from tumors from HCK replete hosts confirmed that TAMs and DCs expressed HCK and other myeloid SFKs while T and NK cells expressed LCK and FYN (Fig. 4C). Py8119 cells expressed low levels of the ubiquitous SFKs only (Fig. 4C).

Py8119 tumor TAMs are pro-tumoral and cluster into five subtypes

To examine the role of HCK in the differentiation of TAM phenotypes, we reclustered CD45⁺ immune cells (Fig. 5A). We and others have devised a consensus classification of macrophage subtypes based on single cell data across a range of tumor types to distinguish between angiogenic, immunoregulatory, interferon (IFN)-primed, inflammatory, lipid-associated, tissue resident and proliferating TAMs (3, 4). TAMs in Py8119 tumors consisted of a large immunoregulatory cluster (> 40%, folate receptor beta (Folr2)^high, stabilin (Stab)1^high, F13a1^high), an inflammatory cluster (~ 20%, H2-Aa^high, NLRP3^high, Il1b^high) and smaller clusters of IFN-primed (~ 5%, Isg15 ubiquitin like modifier (Isg15)^high, Cd274^high, Cxcl9), angiogenic (~ 4%, heme oxygenase (Hmox) 1^high, Vegfa^high), and tissue resident (~ 1%, lymphatic vessel endothelial hyaluronan receptor (Lyve)-1^high) macrophages, with proliferating TAMs (Mki67⁺) accounting for 20% (Fig. 5A,B). All Py8119 tumor TAMs showed prominent expression of apolipoprotein E (ApoE)^high, owing to their mammary fat pad origin, and expressed triggering receptor expressed on myeloid cells (TREM2)⁺, secreted phosphoprotein 1 (Spp1)^high), and C1q (Fig. 5C). Finally, HCK was expressed across all TAM subtypes (Fig. 5B), and loss of HCK activity did not induce an inflammatory phenotype in any TAM clusters as determined by lack of expression of inducible nitric oxide synthase (Nos2)⁺ and other classically activated macrophage markers (Supplementary Fig. 4A). Similarly, there was no induction of IL-10, matrix metalloproteinase (Mmp)2 or Mmp9 expression or changes in arginase (Arg)1 expression to indicate a skewing of TAMs towards an alternatively activated phenotype, as we showed previously in several gastrointestinal tumor models (Supplementary Fig. 4B) (13–15).

Gene ontology (GO) analysis of TAM DEGs revealed that metabolic pathways were the most significantly downregulated pathways in Hck^KO TAMs while cytokine production and response pathways were downregulated in RK20449-treated TAMs with cell migration pathways enriched in Hck^CA TAMs (Supplementary File 2). However, no consistent pattern of gene expression changes emerged that could be attributed to HCK activity. Overall, scRNA-seq revealed that TAMs comprised almost half the Py8119 tumor mass and differentiated into 5 main subtypes, the proportions of which were unaffected by HCK activity. Similarly, while GO analysis results were consistent with the regulation of

Supplementary Fig. 4. HCK does not induce a classically activated or an alternatively activated TAM phenotype in Py8119 mammary tumors. (A) Violin plots comparing expression levels of classical activation markers in Py8119 tumor TAMs from control (salmon pink) or HCK mutant/inhibited (teal) mice. (B) Violin plots comparing expression levels of alternative activation markers in Py8119 tumor TAMs from control or HCK mutant/inhibited mice.

macrophage motility by HCK, no clear additional mechanism for the striking effects of HCK activity on tumor growth was revealed. This implicates the loss of HCK-activated phosphotyrosine-based motility signaling downstream of the CSF-1R in all TAM subtypes as the most likely cause.

TAMs are found in many solid tumors and their abundance correlates with poor survival (22, 28). A wealth of clinical and preclinical data has shown that TAMs are of monocytic origin and are recruited to tumors where they promote growth and dissemination through a variety of mechanisms (2). In breast and several other cancers, tumor cells have been shown to secrete CSF-1 to recruit TAMs, which often accumulate in invasive regions (29, 30). Consistent with this observation, primary breast cancers expressing high levels of CSF-1 are more likely to progress to metastasis and cause death (31). The critical role of CSF-1 for invasion and metastasis was highlighted by the observation that CSF-1-deficient PyMT mammary tumors rarely metastasized (32). A subsequent study demonstrated the existence of a paracrine chemokine loop between CSF-1-secreting tumor cells and EGF-secreting TAMs that underpinned PyMT tumor invasion and metastasis (33). However, despite the evidence for CSF-1 in the promotion of invasion and metastasis, clinical trials of CSF-1/CSF-1R inhibitors in several cancer types have shown limited efficacy, apart from tenosynovial giant cell tumors driven by a CSF1 rearrangement (34). Likewise, pan-CSF-1R inhibition also failed to reduce mammary tumor growth in PyMT mice or in our Py8119 model (Fig. 1B) (27).

Hence, attention has shifted to targeting tumor promoting behaviors of TAMs with a focus on changing characteristics of TAMs from a pro-tumoral to an anti-tumoral phenotype (1, 2). As the absence of CSF-1 had a significantly greater effect on metastasis than progression of primary PyMT tumors, we examined whether targeting the CSF-1-activated invasive behavior of TAMs could reduce tumor growth and invasion in a PyMT-derived Py8119 orthotopic mammary tumor model (16). These highly invasive tumors secrete CSF-1 and IL-34 and recruit TAMs to ultimately contribute to over 40% of the total tumor mass. Here we show that targeting CSF-1-activated TAM invasion significantly reduces tumor growth and invasion in a PyMT-derived Py8119 orthotopic mammary tumor model (16).

We have previously shown that Py8119 cells must be in direct contact with macrophages to become invasive and that hyper-motile Hck^CA macrophages increase their invasiveness (10). Similar mechanisms are likely to occur in vivo as TAMs containing active HCK accumulate at the invasive front of Py8119 tumors and, when TAM motility is selectively blocked by either HCK or PI3K p110δ inhibition, Py8119 tumor growth is reduced. Indeed, the profound reduction in Py8119 tumor growth in HCK-deficient hosts combined with the rapid growth and frequent ulceration seen in hosts with constitutively active HCK expression confirmed that HCK regulates tumor growth and invasion.

TAM promotion of invasive growth is consistent with the notion that TAMs recapitulate the behavior of macrophages during tissue development. CSF-1-dependent macrophages remodel the ECM to facilitate terminal end bud outgrowth during mammary ductal morphogenesis (5). In a similar manner, TAMs, which express an array of MMPs and cathepsins, digest collagen and other ECM proteins to facilitate tumor invasion (11). Combined with our observations that macrophages require HCK to dig tunnels through matrix and that Py8119 cells must be in direct contact with TAMs to be invasive, it is likely that the HCK-dependent TAM invasive activity of TAMs contributes to motility and invasion of Py8119 cells (12, 35). This is supported by our observations that profound SFK activity is seen in TAMs located at the margins of Py8119 tumors in HCK-proficient but not HCK-deficient hosts. Consistent with this, membrane-associated SFK activity is associated with reduced survival in triple negative breast cancer (TNBC) (36, 37). Taken together, our results indicate that CSF-1 signaling-dependent HCK activity and associated TAM motility promote invasive growth of these rapidly growing tumors.

Our finding that CD8⁺ T cell depletion reduces survival, irrespective of HCK genotype, indicates that HCK activity in TAMs additionally regulates Py8119 tumor growth by inhibiting CD8⁺ T cell infiltration (8). The mechanism by which TAMs reduce cytotoxic T cell recruitment is unclear but macrophages have been shown to interact with CD8⁺ T cells in normal and cancerous breast tissue (38). Interestingly, mammary ductal macrophages extend highly dynamic branches to routinely survey the ductal epithelium (39). Analogously, TAMs in the tumor margins may extend branches to directly interact with T cells and regulate their behavior. As the pathways controlling these actin-rich extensions are the same as those regulating HCK-dependent macrophage motility, HCK deficiency could limit the dynamic behavior of these branches and increase CD8⁺ T cell recruitment. Consistent with this, we have shown that a combination of HCK and immune checkpoint inhibitors controls tumor growth across a range of otherwise immune cell excluded (“cold”) tumors (8, 15). Nevertheless, Py8119 tumors in CD8⁺ T cell-depleted HCK-deficient hosts grow more slowly than tumors in CD8⁺ T cell-depleted but HCK-proficient hosts. Thus, we speculate that the extent of the contribution of HCK activity to limit T cell-dependent immune control and to promote invasion of tumor cells into the surrounding matrix may differ according to the oncogenic program specific to a particular malignancy or the target organ in which it occurs.

A limitation of our study is that the PyMT tumor-derived Py8119 cell model is orthotopic whereas spontaneous PyMT tumors arise from the mammary ductal epithelium (16, 39, 40). Because TAMs differentiate in response to their local microenvironment, stromal and ductal TAM populations can be discerned in spontaneous PyMT tumors but not in orthotopic tumors (40). However, the majority of TAMs in spontaneous PyMT tumors are equivalent to the immunoregulatory and inflammatory TAM clusters seen in our Py8119 orthotopic model and TAMs arising from normal ductal macrophages were only seen in early spontaneous tumors (40). Other considerations include the aggressively invasive nature of Py8119 tumors and the abundant TAMs that they recruit (12, 16). However, human TNBCs are also highly invasive and recruit significantly higher numbers of TAMs than other, less aggressive breast cancer subtypes (22). Thus, the Py8119 model of breast cancer provides useful insights into the behavior of TAMs in TNBC, particularly motile TAMs at the invasive front of these cancers. The additional role of HCK in the promotion of tumor growth and dissemination via TAM invasive behavior adds to the existing rationale to develop HCK inhibitors to invigorate anti-tumor immune responses.

ApoE, apolipoprotein E; BMM, bone marrow-derived macrophages; CA, constitutively active; CSF-1, colony-stimulating factor-1; CSF-1R, colony-stimulating factor-1 receptor; DEG, differentially expressed genes; ECM, extracellular matrix; Folr2, folate receptor β; GO, Gene Ontology; HCK, hematopoietic cell kinase; Hmox1, heme oxygenase 1; IHC, immunohistochemistry; IFN, interferon; IL, interleukin; KO, knock out;Lyve-1, lymphatic vessel endothelial hyaluronan receptor 1; MMP, matrix metalloproteinase; PI3K, phosphatidyl inositol 3-kinase; PyMT, polyoma middle T antigen; scRNA-seq, single cell RNA sequencing; SFK, Src family kinase; Stab1, stabilin 1; TAM, tumor-associated macrophage; TNBC, triple negative breast cancer; TREM2, triggering receptor expressed on myeloid cells 2.

Ethics approvals

In vivo mammary tumor growth experiments were carried out strictly according to the ethics requirements of the University of Western Australia, which permitted 4 tumors per mouse and a maximum tumor size of 2 tumors each measuring 10x10mm (RA/3/100/1504, RA/3/100/1540). Hck-deficient (Hck^KO), constitutively active Hck (Hck^CA) and therapeutic RK20449 experiments were carried out at the Olivia Newton John Cancer Research Institute under an ethics approval permitting one tumor per mouse with a maximum tumor volume of 1000mm³ (Austin Health A2021-5746).

Consent for publication

Not applicable.

Availability of data and materials

The data generated in this study are publicly available in the Gene Expression Omnibus (GEO) with the accession code GSE272190.

Competing interests

A.R.P. and M.E are inventors on a patent application related to this work filed by the Olivia Newton-John Cancer Research Institute (PCT/AU2021/051073, filed 16 September 2021). All other authors declare that they have no competing interests.

Funding

The project was funded by the Cancer Council of Western Australia (F.J.P. & L.G.E.; APP112230, APP118357, RPG0059), an Australian Research Training Program Scholarship and University of Western Australia Safety Net top-up scholarship (M.W.M), a National Health and Medical Research Council Development and Investigator Grant (M.E.), and a National Health and Medical Research Council Peter Doherty Early Career Fellowship (A.R.P.; GNT1166447). The single cell profiling was supported by a collaborative cancer research grant to A.R.R.F. provided by the Cancer Research Trust (Enabling advanced single-cell cancer genomics in Western Australia), and an enabling grant from the Cancer Council of Western Australia. Sequencing data was generated at the Australian Cancer Research Foundation Centre for Advanced Cancer Genomics and the Australian Genome Research Facility.

Authors’ contributions

Conception and design: FJP, ARP, DAJ and ME. Development of methodology: FJP, MWM, ARD, and LGE. Acquisition of tumor data: MWM, ARP, CR, KAM, ARD. Analysis and interpretation of tumor data: MWM, ARP, JHS, LGE, ME and FJP. Single cell data generation: ARRF, YY, YL, MJ, KPWH, WL and DO’M. Single cell data analysis: MWM, JHS, IK, and ED. Writing, review and/or revision of manuscript: MWM, ARP, JHS, CR, ARRF, LGE, DAJ, ME and FJP.

Acknowledgements

We acknowledge the facilities, and the scientific and technical assistance of Microscopy Australia at the Centre for Microscopy, Characterisation & Analysis, The University of Western Australia, a facility funded by the University, State and Commonwealth Governments. CSF-1 was kindly supplied by E.R. Stanley, Albert Einstein College of Medicine.

Kloosterman DJ, Akkari L. Macrophages at the interface of the co-evolving cancer ecosystem. Cell 2023;186:1627-1651.
Cassetta L, Pollard JW. A timeline of tumour-associated macrophage biology. Nat Rev Cancer 2023;23:238-257.
Ma RY, Black A, Qian BZ. Macrophage diversity in cancer revisited in the era of single-cell omics. Trends Immunol 2022;43:546-563.
Nasir I, McGuinness C, Poh AR, Ernst M, Darcy PK, Britt KL. Tumor macrophage functional heterogeneity can inform the development of novel cancer therapies. Trends Immunol 2023;44:971-985.
Ingman WV, Wyckoff J, Gouon-Evans V, Condeelis J, Pollard JW. Macrophages promote collagen fibrillogenesis around terminal end buds of the developing mammary gland. Dev Dyn 2006;235:3222-3229.
Pixley FJ. Macrophage migration and its regulation by CSF-1. Int J Cell Biol 2012;1-12.
Kaneda MM, Messer KS, Ralainirina N, Li H, Leem CJ, Gorjestani S et al. PI3Kγ is a molecular switch that controls immune suppression. Nature 2016;539:437-442.
Poh AR, Love CG, Chisanga D, Steer JH, Baloyan D, Chopin M et al. Therapeutic inhibition of the SRC-kinase HCK facilitates T cell tumor infiltration and improves response to immunotherapy. Sci Adv 2022;8:eabl7882.
Mouchemore KA, Sampaio NG, Murrey MW, Stanley ER, Lannutti BJ, Pixley FJ. Specific inhibition of PI3K p110delta inhibits CSF-1-induced macrophage spreading and invasive capacity. FEBS J 2013;280:5228-5236.
Dwyer AR, Mouchemore KA, Steer JH, Sunderland AJ, Sampaio NG, Greenland EL et al. Src family kinase expression and subcellular localization in macrophages: implications for their role in CSF-1-induced macrophage migration. J Leukoc Biol 2016;100:163-175.
Murrey MW, Steer JH, Greenland EL, Proudfoot JM, Joyce DA, Pixley FJ. Adhesion, motility and matrix-degrading gene expression changes in CSF-1-induced mouse macrophage differentiation. J Cell Sci 2020;133:1-16.
Dwyer AR, Ellies LG, Holme AL, Pixley FJ. A three-dimensional co-culture system to investigate macrophage-dependent tumor cell invasion. J Biolog Methods 2016;3:e49.
Poh AR, Dwyer AR, Eissmann MF, Chand AL, Baloyan D, Boon L et al. Inhibition of the SRC kinase HCK impairs STAT3-Dependent gastric tumor growth in mice. Cancer Immunol Res 2020;8:428-435.
Poh AR, Love CG, Masson F, Preaudet A, Tsui C, Whitehead L et al. Inhibition of ematopoietic Cell Kinase activity suppresses myeloid cell-mediated colon cancer progression. Cancer Cell 2017;31:563-575.
Poh AR, O’Brien M, Chisanga D, He H, Baloyan D, Traichel J et al. Inhibition of HCK in myeloid cells restricts pancreatic tumor growth and metastasis. Cell Rep 2022;41:111479.
Biswas T, Gu X, Yang J, Ellies LG, Sun LZ. Attenuation of TGF-beta signaling supports tumor progression of a mesenchymal-like mammary tumor cell line in a syngeneic murine model. Cancer Lett 2014;346:129-138.
Zaqout S, Becker LL, Kaindl AM. Immunofluorescence staining of paraffin sections step by step. Front Neuroanat 2020;14:582218.
Schindelin J, Arganda-Carreras I, Frise E et al. Fiji: an open-source platform for biological-image analysis. Nat Methods 2012;9:676-682.
Hao Y, Stuart T, Kowalski MH, Choudhary S, Hoffman P, Hartman A et al. Dictionary learning for integrative, multimodal and scalable single-cell analysis. Nat Biotechnol 2024;42:293-304
Mulder K, Patel AA, Kong WT, Piot C, Halitzki E, Dunsmore G et al. Cross-tissue single-cell landscape of human monocytes and macrophages in health and disease. Immunity 2021;54: 1883-1900.
Sharma A, Seow JJW, Dutertre CA, Pai R, Bleriot C, Mishra A et al. Onco-fetal reprogramming of endothelial cells drives immunosuppressive macrophages in hepatocellular carcinoma. Cell 2020;183:377-394.
Zhao X, Qu J, Sun Y, Wang J, Liu X, Wang F et al. Prognostic significance of tumor-associated macrophages in breast cancer: a meta-analysis of the literature. Oncotarget 2017;8:30576-30586.
Marsh S, Tang M, Kozareva V, Graybuck L. scCustomize: custom visualizations & functions for streamlined analyses of single cell sequencing. R package version 2.1.2. 2024 https://doi.org/10.5281/zenodo.5706431, https://github.com/samuel-marsh/scCustomize
Raudvere U, Kolberg L, Kuzmin I, Arak T, Adler P, Peterson H et al. g:Profiler: a web server for functional enrichment analysis and conversions of gene lists. Nucl Acids Res 2019;47:W191-W198.
Saito Y, Yuki H, Kuratani M, Hashizume Y, Takagi S, Honma T et al. A pyrrolo-pyrimidine derivative targets human primary AML stem cells in vivo. Sci Transl Med 2013;5:181ra52.
Kater AP, Tonino SH, Spiering M, Chamuleau MED, Liu R, Adewoye AH et al. Final results of a phase 1b study of the safety and efficacy of the PI3Kδ inhibitor acalisib (GS-9820) in relapsed/refractory lymphoid malignancies.[letter]. Blood Cancer J 2018;8(2):16.
DeNardo DG, Brennan DJ, Rexhepaj E, Ruffell B, Shiao SL, Madden SF et al. Leukocyte complexity predicts breast cancer survival and functionally regulates response to chemotherapy. Cancer Discov 2011;1:54-67.
Leek RD, Lewis CE, Whitehouse R, Greenall M, Clarke J, Harris AL. Association of macrophage infiltration with angiogenesis and prognosis in invasive breast carcinoma. Cancer Res. 1996;56:4625-4629.
Scholl SM, Pallud C, Beuvon F, Hacene K, Stanley ER, Rohrschneider L et al. Anti-colony-stimulating factor-1 antibody staining in primary breast adenocarcinomas correlates with marked inflammatory cell infiltrates and prognosis. J Natl Cancer Inst 1994;86:120-126.
Kacinski BM. CSF-1 and its receptor in ovarian, endometrial and breast cancer. Ann Med 1995;27:79-85.
Richardsen E, Uglehus RD, Johnsen SH, Busund LT. Macrophage-colony stimulating factor (CSF1) predicts breast cancer progression and mortality. Anticancer Res 2015;35:865-874.
Lin EY, Nguyen AV, Russell RG, Pollard JW. Colony-stimulating factor 1 promotes progression of mammary tumors to malignancy. J Exp Med 2001;193:727-740.
Wyckoff J, Wang W, Lin EY, Wang Y, Pixley F, Stanley ER et al. A paracrine loop between tumor cells and macrophages is required for tumor cell migration in mammary tumors. Cancer Res 2004;64:7022-7029.
Ries CH, Cannarile MA, Hoves S, Benz J, Wartha K, Runza V et al. Targeting tumor-associated macrophages with anti-CSF-1R antibody reveals a strategy for cancer therapy. Cancer Cell 2014;25:846-859.
Cougoule C, Le Cabec V, Poincloux R, Al Saati T, Mege JL, Tabouret G et al. Three-dimensional migration of macrophages requires Hck for podosome organization and extracellular matrix proteolysis. Blood 2010;115:1444-1452.
Elsberger B. Translational evidence on the role of Src kinase and activated Src kinase in invasive breast cancer. Crit Rev Oncol Hematol 2014;89:343-351.
Ortiz MA, Mikhailova T, Li X, Porter BA, Bah A, Kotula L. Src family kinases, adaptor proteins and the actin cytoskeleton in epithelial-to-mesenchymal transition. Cell Commun Signal 2021;19:67-86.
Nalio Ramos R, Missolo-Koussou Y, Gerber-Ferder Y, Bromley CP, Bugatti M, Nunez NG et al. Tissue-resident FOLR2⁺ macrophages associate with CD8⁺ T cell infiltration in human breast cancer. Cell 2022;185:1189-1207.e25.
Dawson CA, Pal B, Vaillant F, Gandolfo LC, Liu Z, Bleriot C et al. Tissue-resident ductal macrophages survey the mammary epithelium and facilitate tissue remodelling. Nat Cell Biol 2020;22:546-558.
Laviron M, Petit M, Weber-Delacroix E, Combes AJ, Arkal AR, Barthelemy S et al. Tumor-associated macrophage heterogeneity is driven by tissue territories in breast cancer. Cell Rep 2022;39:110865.

Table 1 is available in the Supplementary Files section.

Competing interest reported. A.R.P. and M.E are inventors on a patent application related to this work filed by the Olivia Newton-John Cancer Research Institute (PCT/AU2021/051073, filed 16 September 2021). All other authors declare that they have no competing interests.

SuppFig.1.jpg
Supplementary figure 1. Py8119 cell in vitro data. (A,B) Relative expression of SFKs in Py8119 cells. (C,D) Proliferation of Py8119 cells treated with RK20449 or dasatinib, *p < 0.05.
Suppfigure2.jpg
Supplementary figure 2. Anti-pHck antibody is non-specific. pY HCK (red) co-localizes with DAPI (blue) in Py8119 tumor nuclei in Hck^KO mice. Iba1⁺ TAMs are shown in green. Scale bar, 200µm.
Suppfigure3.jpg
Supplementary figure 3. NK cell depletion does not affect Py8119 tumor growth. Survival of Py8119 tumor-bearing Hck^WT, Hck^KO and Hck^CA mice treated with either anti-NK.1 antibody or IgG isotype control.
Suppfig4.jpg
Supplementary figure 4. HCK does not induce a classically activated or an alternatively activated TAM phenotype in Py8119 mammary tumors. (A) Violin plots comparing expression levels of classical activation markers in Py8119 tumor TAMs from control (salmon pink) or HCK mutant/inhibited (teal) mice. (B) Violin plots comparing expression levels of alternative activation markers in Py8119 tumor TAMs from control or HCK mutant/inhibited mice.
SupplementaryTable1.docx
SupplementaryFile1AllTAMSDEGs.xlsx
SupplementaryFile2AllTAMSGO.xlsx
Table1cellnumbers.xlsx

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The myeloid SRC family kinase HCK regulates breast cancer growth by activating tumor-associated macrophage-led invasion and inhibiting cytotoxic T cell activity

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Version 1

Abstract

Figures

Background

Methods

Animal ethics

Orthotopic mammary tumor models

Py8119 tumor processing

Macrophage extraction and cell culture

Quantitative PCR

Chemotaxis and invasion assays

Inhibitor Growth curves

Immunohistochemistry

Antibodies

Quantification of pY SFK signal and T cell numbers

10x Genomics Chromium library construction, sequencing and analysis

Statistical analysis

Results

Inhibition of macrophage motility reduces Py8119 mammary tumor growth

HCK activity correlates with Py8119 mammary tumor growth

Loss of HCK activity reduces SFK activity in Py8119 tumor margins

HCK regulates cytotoxic T cell numbers in Py8119 tumors

TAMs comprise more than 40% of Py8119 mammary tumor mass

Py8119 tumor TAMs are pro-tumoral and cluster into five subtypes

Discussion

Abbreviations

Declarations

References

Table 1

Additional Declarations

Supplementary Files

Status:

Version 1