Research ArticleExperimental Studies
Open Access

Lysine Methyltransferase 2D Regulates Immune Response and Metastasis in Head and Neck Cancer

JIANCHUN WU, CRYSTAL CHUN, ANGELICA M. LAGUNAS and DAVID L. CROWE
Anticancer Research August 2024, 44 (8) 3231-3242; DOI: https://doi.org/10.21873/anticanres.17141

Abstract

Background/Aim: The most frequently altered epigenetic modifier in head and neck squamous carcinoma (HNSC) is the histone methyltransferase KMT2D. KMT2D catalyzes methylation of histone H3K4 resulting in open chromatin and the activation of target genes. Tumor-associated macrophages (TAMs) promote cancer growth by causing T lymphocyte exhaustion. C-C motif chemokine ligand 2 (CCL2) is a potent TAM chemotactic factor. In HNSC, TAMs have been associated with unfavorable patient outcomes and metastasis. The aim of this study was to determine the role of KMT2D in HNSC using genetically engineered in vivo models. Materials and Methods: KMT2D protein expression was correlated with lymph node metastasis in human HNSC using immunohistochemistry. Genetically engineered KMT2D and CCL2 knockout models of HNSC were created in vivo. HNSC was characterized using qRT-PCR, histopathology, and immunohistochemistry/immunofluorescence microscopy. We also analyzed the effects of KMT2D expression on the proliferation and migration of human HNSC lines. The regulation of the CCL2 gene by KMT2D was characterized using chromatin immunoprecipitation-sequencing assay of transposase accessible chromatin-sequencing, and chromatin conformation capture-sequencing. Results: Human HNSC cases with high KMT2D expression exhibited significantly increased lymph node metastasis. Reduced KMT2D expression in our genetically engineered model correlated with reduced lymph node metastasis, longer latency, and slow tumor growth. CCL2 expression was decreased in KMT2D deficient HNSC, which correlated with a reduced TAM gene expression signature. Genomic experiments demonstrated that KMT2D directly targeted the CCL2 gene. A new genetically engineered in vivo model of CCL2-null HNSC was created, recapitulating the KMT2D deficient phenotype and showing a decreased T lymphocyte exhaustion signature. Conclusion: KMT2D regulates CCL2-mediated immune response and metastasis in HNSC.

Key Words:

Head and neck squamous carcinoma (HNSC) is the one of the most frequent cancers worldwide, with 890,000 cases diagnosed and 450,000 deaths each year (1). The risk factors for HNSC are tobacco and alcohol consumption. A subset of HNSC, primarily of the oropharynx, has been associated with human papillomavirus infection (2). Most patients with HNSC present with advanced tumors and lymph node metastasis. Recurrence after treatment is a frequent clinical problem, and the five-year survival rate for HNSC patients is low. Treatment for advanced tumors consists of concurrent chemoradiation followed by surgery. Epidermal growth factor receptor and immune checkpoint antibodies have been approved for treatment of recurrent HNSC (3).

Genomic studies have revealed that HNSC is a heterogeneous disease at both the molecular and cellular levels (4, 5). The most frequently mutated epigenetic modifier in HNSC is the lysine methyltransferase KMT2D (6-9). KMT2D protein catalyzes methylation of histone H3K4 resulting in open chromatin and activation of target genes (10-12). Fourteen percent of HNSC cases exhibit gain of KMT2D copy number (4, 13-15), and high KMT2D expression predicted tumor recurrence in HNSC (16). Despite the frequency of altered KMT2D expression in HNSC, the mechanism by which this enzyme regulates progression of these cancers is unclear.

Tumor-associated macrophages (TAMs) promote tumor growth by fostering immunosuppression via T lymphocyte exhaustion (17). Unfavorable patient outcomes and metastasis have been associated with increased TAM (18). Macrophages have been phenotypically classified by gene expression signatures which are regulated by different microenvironmental signals (19). Anti-tumor macrophage polarization is stimulated by pro-inflammatory cytokines, while immunosuppressive pro-tumorigenic TAMs are promoted by anti-inflammatory chemokines (20, 21). High levels of TAMs predicted poor immune response (22). Increased TAMs are frequently observed in HNSC and create an immunosuppressive pro-tumorigenic environment (17). C-C motif chemokine ligand 2 (CCL2) is a potent macrophage chemotactic factor (23). Tumors expressing low CCL2 levels exhibit fewer TAMs and improved immune response (24).

Our present study demonstrated that human HNSC cases with high KMT2D expression exhibit significantly increased lymph node metastasis. We created a novel genetically engineered in vivo model of conditional KMT2D inactivation in HNSC. CCL2 expression was decreased in KMT2D deficient HNSC, which correlated with reduced TAM signature and lymph node metastasis. A new genetically engineered in vivo model of CCL2 null HNSC recapitulated the KMT2D deficient phenotype and decreased T lymphocyte exhaustion signature. We concluded that KMT2D regulates immune response and lymph node metastasis in HNSC.

Materials and Methods

Mouse procedures. Mouse procedures were approved by the institutional animal care committee. To characterize the effects of KMT2D deficiency on lymph node metastasis, we created a genetically engineered preclinical model with reduced KMT2D expression in stratified epithelia. Crossing B6N.Cg-Tg(KRT14-cre)1Amc/J with Kmt2dtm1.1Kaig/J mice (The Jackson Laboratories, Bar Harbor, ME, USA) resulted in Cre mediated deletion of KMT2D exons 16-19 in the stratified epithelia of offspring, producing loss of heterozygosity in mucosal epithelium. B6.129S4-Ccl2tm1Rol/J null mutant mice were purchased from The Jackson Laboratories. HNSC induction and tissue processing were performed according to our published protocol (25).

Cell culture and transduction. Human HNSC cell lines SCC9, SCC15, SCC25, SCC71, SCC90, and SCC104 were cultured according to our published protocol (25). Cultures tested negative for mycoplasma contamination using a commercially available kit (MilliporeSigma, St. Louis, MO, USA). SCC15, SCC25, and SCC9 cells were incubated with KMT2D CRISPR-Cas9 or control lentiviruses for 6 h in serum free medium according to manufacturer’s protocol (Horizon Discovery, Lafayette, CO, USA) at 37°C. Puromycin resistant clones were selected and expanded for analysis using western blot, proliferation, and migration experiments. In proliferation experiments, 3×104 cells from control and KMT2D CRISPR-Cas9 clones were plated in triplicate and counted daily for four days. In migration experiments, 2×105 from control and KMT2D CRISPR-Cas9 clones were plated in triplicate in transwell migration chambers for 16 h. Cells which migrated through the membranes were fixed in 70% ethanol, stained with hematoxylin, photographed under light microscopy, and quantitated using digital image analysis (Akoya Biosciences, Marlborough, MA, USA).

qRT-PCR. RNA extraction and reverse transcription were performed according to manufacturer’s instructions (Invitrogen, Carlsbad, CA, USA). cDNA was amplified using mouse primers: KMT2D 5′-AGAACAATGGACGGCCTGAG-3′ and 5′-TCAAGGTATGGG GCCGTTTA-3′, ITGAM 5′-AGCTTGGCTTTTTCAAGCGG-3′ and 5′-CTTACCCACAAGGGTCCCAC-3′, CD33 5′-GGAAA GGACCATCCAGCTCA-3′ and 5′-CAGATGCAGTTGGAGAT AGGCA-3′, CD14 5′-GAAGCAGATCTGGGGCAGTT-3′ and 5′-ACGTTGCGGAGGTTCAAGAT-3′, LY6C 5′-ACCCTTCTCTGA GGATGGACA-3′ and 5′-GATCCCTGATTGGCACACCA-3′, CD80 5′-AGTTTCTCTTTTTCAGGTTGTGAA-3′ and 5′-ACATGATGG GGAAAGCCAGG-3′, CCL2 5′-GACCCCAAGAAGGAATG GGT-3′ and 5′-ACCTTAGGGCAGATGCAGTT-3′, LAG3 5′-AATCCTTCGGGTTACCTGGC-3′ and 5′-CGTACACTGTCGCT CCAAGA-3′, TIM3 5′-GCAGTCAGGATTCGCTCTGA-3′ and 5′-TGGGAGATCCGATCCCTGAA-3′, β-actin 5′-AAAAGCCACCC CCACTCCTAAG-3′ and 5′-TCAAGTCAGTGTACAGG CCAGC-3′. qRT-PCR was performed according to our published protocol (25).

Western blot. Protein extracts from human HNSC lines were separated in 4-20% gradient SDS-PAGE, blotted with Kmt2d or β-actin antibodies, and analyzed according to our published protocol (25).

Histopathology, immunofluorescence, and immunohistochemistry. Human HNSC tissue microarrays were purchased from Tissue Array (Rockville, MD, USA). Formalin fixed mouse and human tumor tissues were processed and analyzed by histopathology, immunofluorescence, and immunohistochemistry according to our published protocol (25).

Cell death analysis. Fixed tumor sections were processed and analyzed for programmed cell death according to manufacturer’s protocol (Roche Applied Sciences, Indianapolis, IN, USA).

Fluorescence activated cell sorting. HNSC were sorted using phycoerythrin conjugated CD14 antibody and analyzed according to our published protocol (25).

Chromatin immunoprecipitation-sequencing. SCC15 cells were formaldehyde cross-linked using 1% formaldehyde. Cells were washed with phosphate buffered saline and resuspended in lysis buffer. The nuclei were collected, resuspended in the immunoprecipitation buffer and sonicated to obtain fragments of 200-300 bp. Chromatin concentrations were determined using spectrophotometry. Immunoprecipitation was performed with 10 μl KMT2D antibody and incubated overnight at 4°C. Protein G beads were added and incubated at 4°C for 2 h. Beads were washed three times and cross-links were reversed overnight at 65°C. Libraries for ChIP-seq were prepared and AmpureXP beads (Beckman Coulter, Indianapolis, IN, USA) were used for size selection. Libraries were quantified and sequenced using Illumina NovaSeq 6000 (San Diego, CA, USA). Reads were de-multiplexed and analyzed for quality control using bcl2fastq and FastQC. FASTQ reads were mapped to the reference genome using Bowtie2. Following conversion using SAMtools, BAM files were indexed and PCR duplicates were excluded using the rmdup function. Occupancy maps were generated using DeepTools and the matrix was used to generate profile plots. BAM files were converted to BigWig format. ComputeMatrix was used to quantify occupancy of reads followed by plotting using plotProfile and plotHeatmap.

Assay of transposase accessible chromatin-sequencing. SCC15 cells were lysed and nuclei were incubated with 12.5 μl of 2X transposase buffer, 2 μl of Tn5 transposase (Illumina, San Diego, CA, USA), and 10.5 μl distilled water at 37°C for 1 h followed by purification. Ten cycles of PCR were performed using Illumina dual index primers followed by purification. Following size selection, library quality and fragment size distribution were analyzed using TapeStation (Agilent, Santa Clara, CA, USA). Libraries were quantified and sequencing was performed on the Illumina NovaSeq 6000. After trimming of adapter sequences, reads were mapped using Bowtie2. Picard was used to remove PCR duplicated and low-quality reads, and MACS2 was used for peak calling.

Chromatin conformation capture-sequencing. One million SCC15 cells were formaldehyde fixed followed by lysis and DpnII digestion (New England BioLabs, Ipswich, MA, USA). PCR amplification was performed, and libraries were sequenced on a NovaSeq 6000 instrument (Illumina). Data were processed using Juicer software and Juicer tools was used to create hic-files. Juicebox was used to view count maps with K-R normalization. For Hi-C map generation, read-pairs of quality ≥30 were used.

Antibodies. Antibodies against p16 (AB241543), H3K9me3 (AB8898) and PCNA (AB92552) were purchased from Abcam (Waltam, MA, USA); The antibody against β-actin (4970) was purchased from Cell Signaling (Danvers, MA, USA); The antibody against KMT2D (HPA035977) was obtained from MilliporeSigma; The antibody against CCL2 (NBP1-07035) was procured from Novus Biologicals (Centennial, CO, USA).

Statistical analysis. Student t-test was used for two groups of parametric data. Fisher exact test was used for categorical data. p-Values <0.05 were considered statistically significant. GraphPad Prism (GraphPad, Boston, MA, USA) was used for the analyses.

Results

Given that KMT2D gain of copy number was detected in HNSC genomic data, we analyzed KMT2D protein expression in human HNSC lines and pathology specimens. KMT2D protein expression was detected in an immortalized mucosal cell line (HOK16B) and at 2-3 fold higher levels in 6 HNSC lines using western blot (Figure 1A). Thirty-one percent (20/64) of human HNSC pathology specimens with low KMT2D expression demonstrated lymph node metastasis (Figure 1B and D). In contrast, 56% (18/32) of human HNSC pathology specimens with high KMT2D expression exhibited lymph node metastasis (Figure 1C and E; p<0.03; Fisher exact test). KMT2D expression did not significantly correlate with patient sex, age, or tumor grade. Our results demonstrate that high KMT2D expression correlates with lymph node metastasis in human HNSC.

Figure 1.
Figure 1.

KMT2D expression correlates with lymph node metastasis in HNSC. (A) Western blot showing KMT2D protein expression in human HNSC cell lines. β-actin expression was used as gel loading control. Molecular mass is shown in kD. Immunohistochemistry showing KMT2D protein expression in human archival HNSC pathology specimens. Representative HNSC cases with low (B,D) and high (C,E) KMT2D protein expression are shown. The fraction of cases with lymph node metastasis in KMT2Dlow and KMT2Dhigh HNSC is shown. p-Value is shown.

To characterize the effects of reduced KMT2D expression on lymph node metastasis, we created a genetically engineered preclinical model with reduced KMT2D expression in stratified epithelia. Crossing B6N.Cg-Tg(KRT14-cre)1Amc/J with Kmt2dtm1.1Kaig/J mice resulted in Cre mediated deletion of KMT2D exons 16-19 in the stratified epithelia of offspring, resulting in loss of heterozygosity in mucosal epithelium. qRT-PCR results showing reduced KMT2D mRNA expression in K14Cre;KMT2D+/f mucosa is shown in Figure 2A. The homozygous null mutant mouse was not viable. We used our published carcinogenesis model to generate 20 K14Cre;KMT2D+/+ and 20 K14Cre;KMT2D+/f HNSC (25). Primary tumor latency was increased in K14Cre;KMT2D+/f compared to K14Cre;KMT2D+/+ HNSC (mean 158 vs. 131 days; p<0.04; Figure 2B; t-test). K14Cre;KMT2D+/f primary tumors exhibited slower growth than K14Cre;KMT2D+/+ HNSC (mean 185 mm3 vs. 240 mm3; p<0.05; Figure 2C). The histopathology of primary tumors from both genotypes are shown in Figure 2D and F. Lymph node metastases were significantly reduced in K14Cre;KMT2D+/f cancers compared to K14Cre;KMT2D+/+ HNSC (16% vs. 62% positive nodes; p<0.0001; Figure 2E, G and H). Our results indicate that reduced KMT2D expression correlated with reduced tumor growth and lymph node metastasis in HNSC.

Figure 2.
Figure 2.

KMT2D deficient HNSC exhibit reduced lymph node metastasis. (A) qRT-PCR showing KMT2D mRNA expression in K14Cre;KMT2D+/+ and K14Cre;KMT2D+/f mucosa. (B) Increased tumor latency in K14Cre;KMT2D+/f compared to K14Cre;KMT2D+/+ HNSC. Percent tumor free mice is shown on the y axis and days latency is shown on the x axis. (C) Reduced tumor growth in K14Cre;KMT2D+/f compared to K14Cre;KMT2D+/+ HNSC. Tumor volume is shown on the y axis and weeks tumor growth is shown on the x axis. Error bars indicate SEM. H&E staining showing the histopathology of K14Cre;KMT2D+/+ primary (D) and metastatic (E) tumors. H&E staining showing the histopathology of K14Cre;KMT2D+/f primary (F) and metastatic (G) tumors. Scale bar=10 μm. Tumor cells are annotated by T, stromal cells are indicated by S, lymphocytes are shown by L, and differentiated tumor cells are shown by diff. (H) Quantitation of lymph node metastases in K14Cre;KMT2D+/+ and K14Cre;KMT2D+/f HNSC. p-Values are shown.

To determine the mechanism for longer latency and reduced growth of KMT2D+/f HNSC, we examined expression of the senescence markers p16 and H3K9me3 in K14Cre;KMT2D+/+ and K14Cre;KMT2D+/f tumor tissue sections. The p16 positive cell fraction was low in both groups (0.1% vs. 0.2%; Figure 3A and B). The H3K9me3 positive cell fraction also was low in both groups (0.3% vs. 0.1%; Figure 3C and D). We then determined the apoptotic cell fraction in K14Cre;KTM2D+/+ and K14Cre;KMT2D+/f HNSC using TUNEL analysis. The apoptotic cell fraction was low in both groups (0.2% vs. 0.3%; Figure 3E and F). Statistical analysis using t-test indicated that there were no statistically significant differences in the number of senescent or apoptotic cells between K14Cre;KMT2D+/+ and K14Cre;KMT2D+/f HNSC. Finally we examined the proliferating cell fraction in K14Cre;KTM2D+/+ and K14Cre;KMT2D+/f HNSC using PCNA immunohistochemistry. The proliferating cell fraction was significantly reduced in K14Cre;KMT2D+/f compared to K14Cre;KMT2D+/+ HNSC (27% vs. 64%; p<0.01, t-test; Figure 3G-I). These results indicate that reduced cellular proliferation correlated with decreased metastasis in K14Cre;KMT2D+/f HNSC.

Figure 3.
Figure 3.

Reduced proliferating cells in K14Cre;KMT2D+/f HNSC. Immunohistochemistry showing expression of the senescence marker p16 in K14Cre;KMT2D+/+ (A) and K14Cre;KMT2D+/f (B) HNSC. Nuclei were counterstained with hematoxylin. Scale bar=10 μm. Immunofluorescence microscopy showing the expression of the senescence marker H3K9me3 in K14Cre;KMT2D+/+ (C) and K14Cre;KMT2D+/f (D) HNSC. Nuclei were counterstained with DAPI. Programmed cell death was determined using TUNEL analysis in K14Cre;KMT2D+/+ (E) and K14Cre;KMT2D+/f (F) HNSC. Proliferation was determined by PCNA expression in K14Cre;KMT2D+/+ (G) and K14Cre;KMT2D+/f (H) HNSC using immunohistochemistry. (I) Quantitation of PCNA+ cells in K14Cre;KMT2D+/+ and K14Cre;KMT2D+/f HNSC. Error bars indicate SEM.

To determine if reduced KMT2D expression directly regulated proliferation and migration of HNSC cells, we transduced SCC15, SCC25, and SCC9 cells with control and KMT2D CRISPR-Cas9 lentiviruses. Reduced KMT2D protein expression in puromycin resistant CRISPR-Cas9 clones is shown in Figure 4A. Control and KMT2D CRISPR-Cas9 clones were then used in proliferation and migration experiments in vitro. Cultured SCC15, SCC25, and SCC9 puromycin resistant control and KMT2D CRISPR-Cas9 clones are shown in Figure 4B, C, F, G, J, and K. Migrated SCC15, SCC25, and SCC9 puromycin resistant control and KMT2D CRISPR-Cas9 clones are shown in Figure 4D, E, H, I, L, and M. Reduced KMT2D expression did not significantly affect proliferation or migration of SCC15 cells (Figure 4N and O; t-test).

Figure 4.
Figure 4.

Reduced KMT2D expression does not inhibit HNSC cell line proliferation or migration. (A) Western blot indicating KMT2D expression in human HNSC lines SCC15, SCC25, and SCC9 in puromycin resistant (puro) control and CRISPR-Cas9 (KO) clones. β-actin expression was used as the gel loading control. Phase contrast microscopy images showing cultured SCC15, SCC25, and SCC9 puromycin resistant (puro) control (B, F, J) and CRISPR-Cas9 (KO) clones (C, G, K). Hematoxylin staining and brightfield microscopy images showing migrating SCC15, SCC25, and SCC9 puromycin resistant (puro) control (D, H, L) and CRISPR-Cas9 (KO) clones (E, I, M). (N) Proliferation time course experiments of SCC15, SCC25, and SCC9 puromycin resistant (puro) control and CRISPR-Cas9 (KO) clones. (O) Quantitation of migrating SCC15, SCC25, and SCC9 puromycin resistant (puro) control and CRISPR-Cas9 (KO) clones. Error bars indicate SEM.

Given that reduced KMT2D expression did not have cell autonomous effects on HNSC proliferation or migration, we investigated the tumor microenvironment in our genetically engineered model of KMT2D deficient HNSC. TAM gene expression signature ITGAM (−2.1 fold), CD33 (−2.8 fold), CD14 (−4 fold), LY6C (−4.3 fold), and CD80 (−4.6 fold) was reduced in K14Cre;KMT2D+/f compared to K14Cre; KMT2D+/+ HNSC (p<0.002; t-test; Figure 5A). We sorted CD14+ TAMs from K14Cre;KMT2D+/+ and K14Cre; KMT2D+/f HNSC using flow cytometry. The CD14+ TAM fraction was significantly reduced in K14Cre;KMT2D+/f HNSC (0.07% vs. 0.2%; p<0.04; t-test; Figure 5B and C) compared to K14Cre;KMT2D+/+ cancers. CCL2, secreted by cancer cells, is a major chemotactic factor for TAMs. CCL2 mRNA (−4.6 fold) and protein expression was significantly reduced in K14Cre;KMT2D+/f compared to K14Cre; KMT2D+/+ HNSC (p<0.002; t-test; Figure 5A, D and E). To determine if KMT2D directly targeted the CCL2 gene, we performed ChIP-seq, ATAC-seq, and HiC genomic studies. Given the limited number of mouse HNSC cells available for these experiments, we used the human HNSC line SCC15 for genomic studies. The human CCL2 gene is located at chr17:34255274. The CCL2 promoter region is located in a micro-compartment domain in SCC15 cells as shown by HiC chromatin conformation capture (Figure 5F), which has been proposed to regulate gene expression (26). KMT2D bound directly to the CCL2 promoter as shown using ChIP-seq which overlapped with open chromatin as shown using ATAC-seq (Figure 5F). These results indicate that KMT2D directly targets the CCL2 gene; KMT2D deficiency in HNSC resulted in decreased CCL2 expression, TAM signature, and cell fraction.

Figure 5.
Figure 5.

Reduced TAM gene expression signature in K14Cre;KMT2D+/f HNSC. (A) qRT-PCR results indicating relative ITGAM, CD33, CD14, LY6C, CD80, and CCL2 expression in KMT2D+/+ and KMT2D+/f HNSC. Error bars indicate SEM. Fluorescence activated cell sorting of CD14+ TAM from K14Cre;KMT2D+/+ (B) and K14Cre;KMT2D+/f (C) HNSC. CD14 log and forward scatter linear scales are shown. Immunohistochemistry showing CCL2 expression in K14Cre;KMT2D+/+ (D) and K14Cre;KMT2D+/f (E) HNSC. Nuclei were counterstained with hematoxylin. Scale bar=10 μm. (F) The CCL2 gene is a direct target of KMT2D. The CCL2 gene is located in a micro-compartment domain as shown by Hi-C analysis. ChIP-seq results showing KMT2D binding to the CCL2 gene which correlated with open chromatin conformation as shown by ATAC-seq. Exon-intron structure of the CCL2 gene is shown.

To determine if reduced CCL2 expression could recapitulate the phenotype of K14Cre;KMT2D+/f cancers, we induced HNSC in 20 CCL2−/− and 20 CCL2+/+ mice. qRT-PCR results indicated reduced CCL2 mRNA expression in CCL2−/− mucosa (Figure 6A). There were no significant differences in primary tumor latency in CCL2−/− compared to CCL2+/+ HNSC (mean 128 vs. 122 days; t-test; Figure 6B). CCL2−/− primary tumors exhibited slower growth than CCL2+/+ HNSC (mean 43 mm3 vs. 225 mm3; t-test; p<0.0006; Figure 6C). The histopathology of primary tumors from both genotypes are shown in Figure 6D and F. Lymph node metastases were significantly reduced in CCL2−/− cancers compared to CCL2+/+ HNSC (19% vs. 56% positive nodes; t-test; p<0.004; Figure 6E, G and H). Our results indicate that reduced CCL2 expression inhibited tumor growth and lymph node metastasis in HNSC.

Figure 6.
Figure 6.

Reduced growth and metastasis of CCL2−/− HNSC. (A) qRT-PCR results showing CCL2 mRNA expression in CCL2+/+ and CCL2−/− mucosa. (B) Tumor latency in CCL2−/− compared to CCL2+/+ HNSC. Percent tumor free mice is shown on the y axis and days latency is shown on the x axis. (C) Reduced tumor growth in CCL2−/− compared to CCL2+/+ HNSC. Tumor volume is shown on the y axis and weeks tumor growth is shown on the x axis. Error bars indicate SEM. H&E staining showing the histopathology of CCL2+/+ primary (D) and metastatic (E) HNSC. H&E staining showing the histopathology of CCL2−/− primary (F) and metastatic (G) HNSC. Scale bar = 10 μm. (H) Quantitation of lymph node metastases in CCL2+/+ and CCL2−/− HNSC. p-Values are shown.

To determine the mechanism for the reduced growth and metastasis of CCL2−/− HNSC, we examined expression of the senescence markers p16 and H3K9me3 in CCL2+/+ and CCL2−/− tumor tissue sections. The p16 positive cell fraction was low in both groups (0.2% vs. 0.2%; Figure 7A and B). The H3K9me3 positive cell fraction also was low in both groups (0.2% vs. 0.3%; Figure 7C and D). We then determined the apoptotic cell fraction in CCL2+/+ and CCL2−/− HNSC using TUNEL analysis. The apoptotic cell fraction was low in both groups (0.3% vs. 0.1%; Figure 7E and F). There were no statistically significant differences in the number of senescent or apoptotic cells between CCL2+/+ and CCL2−/− HNSC. Finally, we examined the proliferating cell fraction in CCL2+/+ and CCL2+/− HNSC using PCNA immunohistochemistry. The proliferating cell fraction was significantly reduced in CCL2−/− compared to CCL2+/+ HNSC (18% vs. 77%; p<0.003; t-test; Figure 7G-I). CCL2−/− HNSC expressed reduced T lymphocyte exhaustion signature (LAG3:−2.6-fold, TIM3: −3.4-fold; p<0.009; t-test; Figure 7J), which correlated with reduced TAM signature. These results indicate that reduced CCL2 expression was associated reduced T lymphocyte exhaustion (improved immune response), decreased proliferating tumor cells, and decreased metastatic HNSC.

Figure 7.
Figure 7.

Reduced cellular proliferation in CCL2−/− HNSC. Immunofluorescence microscopy showing the expression of the senescence marker p16 in CCL2+/+ (A) and CCL2−/− (B) HNSC. Nuclei were counterstained with DAPI. Scale bar=10 μm. Immunofluorescence microscopy showing the expression of the senescence marker H3K9me3 in CCL2+/+ (C) and CCL2−/− (D) HNSC. Programmed cell death was determined using TUNEL analysis in CCL2+/+ (E) and CCL2−/− (F) HNSC. Proliferating cell fraction was determined by PCNA expression CCL2+/+ (G) and CCL2−/− (H) HNSC using immunohistochemistry. Nuclei were counterstained with hematoxylin. (I) Quantitation of PCNA+ cells in CCL2+/+ and CCL2−/− HNSC. (J) Reduced cytotoxic T cell exhaustion gene expression signature in CCL2−/− HNSC. qRT-PCR showing the relative LAG3 and TIM3 mRNA expression in CCL2−/− compared to CCL2+/+ HNSC. Error bars indicate SEM.

Discussion

Our results indicated that KMT2D directly targeted the CCL2 gene in HNSC. CCL2 is a potent chemotactic factor for TAMs, and KMT2D deficiency correlated with reduced TAM gene expression signature in our HNSC model. TAMs have been associated with poor clinical outcome in HNSC (27). CCL2 has been associated with TAM polarization in cancers (28). HNSC with high CCL2 expression correlated with decreased overall patient survival (29). HNSC radiotherapy has been associated with increased CCL2 secretion and induction of an immunosuppressive tumor microenvironment (30). CCL2 was associated with cisplatin sensitivity in head and neck cancer cells (31). CCL2 secretion by pancreatic cancer cells recruited TAMs, which promoted aggressive tumor phenotype (32). CCL2 expression was increased in fibroblasts exposed to tobacco carcinogens (33). Furthermore, it has been shown that uptake of HNSC extracellular vesicles by monocytes resulted in increased CCL2 expression (34).

The immunosuppressive TAM phenotype inhibits cytotoxic T lymphocytes (35). In vivo TAM depletion was shown to reduce cytotoxic T lymphocyte exhaustion gene expression signatures in mouse models of melanoma and mammary tumors (36). Our study demonstrated that CCL2 null HNSC exhibited reduced cytotoxic T cell exhaustion gene expression signature. Exhausted cytotoxic T lymphocytes express plasma membrane bound inhibitory receptors including lymphocyte activation gene 3 (LAG3) and T cell immunoglobulin mucin receptor 3 (TIM3; 37) as shown in our current study. TAMs also produce IL10 and TGFβ which convert CD4+ T lymphocytes to regulatory T cells, which suppress cytotoxic T lymphocyte function (38).

Our study determined that CCL2 null mutation recapitulated reduced proliferation, tumor growth, and metastasis identified in KMT2D deficient HNSC. Reduced KMT2D expression inhibited proliferation and tumor formation by gastric cancer cells (39). Low KMT2D expression correlated with fibrosis in gastric cancer (40). KMT2D was mutated in sinonasal squamous cell carcinomas derived from inverted papillomas (41). KMT2D somatic and germline polymorphisms may also be associated with prostate cancer (42). A small molecule inhibitor of CCR2, the receptor for CCL2, correlated with increased pancreatic patient survival (43). Our future studies will determine how KMT2D regulates TAM polarization and HNSC phenotype using single cell genomics.

Conclusion

KMT2D regulates CCL2 mediated immune response and metastasis in HNSC.

Acknowledgements

The Authors thank Drs. Ke Ma, Zarema Arbieva, Alvaro Hernandez, and Mark Maienschein-Cline (University of Illinois Research Resources Center and Carver Biotechnology Center) for assistance with confocal microscopy, genomics, and bioinformatics.

Footnotes

  • Authors’ Contributions

    J.W., C.C., and A.M.L. performed experiments, analyzed data, and wrote the manuscript. D.L.C. conceived the study, analyzed data, and edited the manuscript. Part of this study was the master’s thesis project of one of the authors (C.C.) and can be found at: indigo.uic.edu.

  • Conflicts of Interest

    The Authors declare no conflicts of interest in relation to this study.

  • Funding

    This study was supported by the University of Illinois Cancer Center.

  • Received May 20, 2024.
  • Revision received June 20, 2024.
  • Accepted June 24, 2024.

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY-NC-ND) 4.0 international license (https://creativecommons.org/licenses/by-nc-nd/4.0).

References

  1. ↵
    1. Chow LQ
    : Head and neck cancer. N Engl J Med 382(1): 60-72, 2020. DOI: 10.1056/NEJMra1715715
    OpenUrlCrossRefPubMed
  2. ↵
    1. Dotto GP,
    2. Rustgi AK
    : Squamous cell cancers: a unified perspective on biology and genetics. Cancer Cell 29(5): 622-637, 2016. DOI: 10.1016/j.ccell.2016.04.004
    OpenUrlCrossRefPubMed
  3. ↵
    1. Leemans CR,
    2. Snijders PJF,
    3. Brakenhoff RH
    : The molecular landscape of head and neck cancer. Nature Rev Cancer 18(5): 269-282, 2018. DOI: 10.1038/nrc.2018.11
    OpenUrlCrossRefPubMed
  4. ↵
    1. Cancer Genome Atlas Network
    : Comprehensive genomic characterization of head and neck squamous cell carcinomas. Nature 517(7536): 576-582, 2015. DOI: 10.1038/nature14129
    OpenUrlCrossRefPubMed
  5. ↵
    1. Farah CS
    : Molecular landscape of head and neck cancer and implications for therapy. Ann Transl Med 9(10): 915, 2021. DOI: 10.21037/atm-20-6264
    OpenUrlCrossRefPubMed
  6. ↵
    1. Martin D,
    2. Abba MC,
    3. Molinolo AA,
    4. Vitale-Cross L,
    5. Wang Z,
    6. Zaida M,
    7. Delic NC,
    8. Samuels Y,
    9. Lyons JG,
    10. Gutkind JS
    : The head and neck cancer cell oncogenome: a platform for the development of precision molecular therapies. Oncotarget 5(19): 8906-8923, 2014. DOI: 10.18632/oncotarget.2417
    OpenUrlCrossRefPubMed
    1. Seiwert TY,
    2. Zuo Z,
    3. Keck MK,
    4. Khattri A,
    5. Pedamallu CS,
    6. Stricker T,
    7. Brown C,
    8. Pugh TJ,
    9. Stojanov P,
    10. Cho J,
    11. Lawrence MS,
    12. Getz G,
    13. Brägelmann J,
    14. DeBoer R,
    15. Weichselbaum RR,
    16. Langerman A,
    17. Portugal L,
    18. Blair E,
    19. Stenson K,
    20. Lingen MW,
    21. Cohen EE,
    22. Vokes EE,
    23. White KP,
    24. Hammerman PS
    : Integrative and comparative genomic analysis of HPV-positive and HPV-negative head and neck squamous cell carcinomas. Clin Cancer Res 21(3): 632-641, 2015. DOI: 10.1158/1078-0432.CCR-13-3310
    OpenUrlAbstract/FREE Full Text
    1. Kalu NN,
    2. Mazumdar T,
    3. Peng S,
    4. Shen L,
    5. Sambandam V,
    6. Rao X,
    7. Xi Y,
    8. Li L,
    9. Qi Y,
    10. Gleber-Netto FO,
    11. Patel A,
    12. Wang J,
    13. Frederick MJ,
    14. Myers JN,
    15. Pickering CR,
    16. Johnson FM
    : Genomic characterization of human papillomavirus-positive and -negative human squamous cell cancer cell lines. Oncotarget 8(49): 86369-86383, 2017. DOI: 10.18632/oncotarget.21174
    OpenUrlCrossRefPubMed
  9. ↵
    1. Shaikh H,
    2. McGrath JE,
    3. Hughes B,
    4. Xiu J,
    5. Brodskiy P,
    6. Sukari A,
    7. Darabi S,
    8. Ikpeazu C,
    9. Nabhan C,
    10. Korn WM,
    11. Wise-Draper TM
    : Genomic and molecular profiling of human papillomavirus associated head and neck squamous cell carcinoma treated with immune checkpoint blockade compared to survival outcomes. Cancers (Basel) 13(24): 6309, 2021. DOI: 10.3390/cancers13246309
    OpenUrlCrossRefPubMed
  10. ↵
    1. Ford DJ,
    2. Dingwall AK
    : The cancer COMPASS: navigating the functions of MLL complexes in cancer. Cancer Genet 208(5): 178-191, 2015. DOI: 10.1016/j.cancergen.2015.01.005
    OpenUrlCrossRefPubMed
    1. Froimchuk E,
    2. Jang Y,
    3. Ge K
    : Histone H3 lysine 4 methyltransferase KMT2D. Gene 627: 337-342, 2017. DOI: 10.1016/j.gene.2017.06.056
    OpenUrlCrossRefPubMed
  12. ↵
    1. Dhar SS,
    2. Lee MG
    : Cancer-epigenetic function of the histone methyltransferase KMT2D and therapeutic opportunities for the treatment of KMT2D-deficient tumors. Oncotarget 12(13): 1296-1308, 2021. DOI: 10.18632/oncotarget.27988
    OpenUrlCrossRefPubMed
  13. ↵
    1. Harbison RA,
    2. Kubik M,
    3. Konnick EQ,
    4. Zhang Q,
    5. Lee SG,
    6. Park H,
    7. Zhang J,
    8. Carlson CS,
    9. Chen C,
    10. Schwartz SM,
    11. Rodriguez CP,
    12. Duvvuri U,
    13. Méndez E
    : The mutational landscape of recurrent versus nonrecurrent human papillomavirus-related oropharyngeal cancer. JCI Insight 3(14): e99327, 2018. DOI: 10.1172/jci.insight.99327
    OpenUrlCrossRef
    1. Haft S,
    2. Ren S,
    3. Xu G,
    4. Mark A,
    5. Fisch K,
    6. Guo TW,
    7. Khan Z,
    8. Pang J,
    9. Ando M,
    10. Liu C,
    11. Sakai A,
    12. Fukusumi T,
    13. Califano JA
    : Mutation of chromatin regulators and focal hotspot alterations characterize human papillomavirus-positive oropharyngeal squamous cell carcinoma. Cancer 125(14): 2423-2434, 2019. DOI: 10.1002/cncr.32068
    OpenUrlCrossRefPubMed
  15. ↵
    1. Osawa Y,
    2. Aoyama KO,
    3. Hosomichi K,
    4. Uchibori M,
    5. Tajima A,
    6. Kimura M,
    7. Ota Y
    : Somatic mutations in oral squamous cell carcinomas in 98 Japanese patients and their clinical implications. Cancer Treat Res Commun 29: 100456, 2021. DOI: 10.1016/j.ctarc.2021.100456
    OpenUrlCrossRefPubMed
  16. ↵
    1. Bunbanjerdsuk S,
    2. Vorasan N,
    3. Saethang T,
    4. Pongrujikorn T,
    5. Pangpunyakulchai D,
    6. Mongkonsiri N,
    7. Arsa L,
    8. Thokanit N,
    9. Pongsapich W,
    10. Anekpuritanang T,
    11. Ngamphaiboon N,
    12. Jinawath A,
    13. Sunpaweravong S,
    14. Pisitkun T,
    15. Suktitipat B,
    16. Jinawath N
    : Oncoproteomic and gene expression analyses identify prognostic biomarkers for second primary malignancy in patients with head and neck squamous cell carcinoma. Mod Pathol 32(7): 943-956, 2019. DOI: 10.1038/s41379-019-0211-2
    OpenUrlCrossRefPubMed
  17. ↵
    1. Bruni D,
    2. Angell HK,
    3. Galon J
    : The immune contexture and Immunoscore in cancer prognosis and therapeutic efficacy. Nature Rev Cancer 20(11): 662-680, 2020. DOI: 10.1038/s41568-020-0285-7
    OpenUrlCrossRefPubMed
  18. ↵
    1. Park MD,
    2. Silvin A,
    3. Ginhoux F,
    4. Merad M
    : Macrophages in health and disease. Cell 185(23): 4259-4279, 2022. DOI: 10.1016/j.cell.2022.10.007
    OpenUrlCrossRefPubMed
  19. ↵
    1. Murray PJ,
    2. Allen JE,
    3. Biswas SK,
    4. Fisher EA,
    5. Gilroy DW,
    6. Goerdt S,
    7. Gordon S,
    8. Hamilton JA,
    9. Ivashkiv LB,
    10. Lawrence T,
    11. Locati M,
    12. Mantovani A,
    13. Martinez FO,
    14. Mege JL,
    15. Mosser DM,
    16. Natoli G,
    17. Saeij JP,
    18. Schultze JL,
    19. Shirey KA,
    20. Sica A,
    21. Suttles J,
    22. Udalova I,
    23. van Ginderachter JA,
    24. Vogel SN,
    25. Wynn TA
    : Macrophage activation and polarization: nomenclature and experimental guidelines. Immunity 41(1): 14-20, 2014. DOI: 10.1016/j.immuni.2014.06.008
    OpenUrlCrossRefPubMed
  20. ↵
    1. Sica A,
    2. Larghi P,
    3. Mancino A,
    4. Rubino L,
    5. Porta C,
    6. Totaro MG,
    7. Rimoldi M,
    8. Biswas SK,
    9. Allavena P,
    10. Mantovani A
    : Macrophage polarization in tumour progression. Semin Cancer Biol 18(5): 349-355, 2008. DOI: 10.1016/j.semcancer.2008.03.004
    OpenUrlCrossRefPubMed
  21. ↵
    1. Jetten N,
    2. Verbruggen S,
    3. Gijbels MJ,
    4. Post MJ,
    5. De Winther MP,
    6. Donners MM
    : Anti-inflammatory M2, but not pro-inflammatory M1 macrophages promote angiogenesis in vivo. Angiogenesis 17(1): 109-118, 2014. DOI: 10.1007/s10456-013-9381-6
    OpenUrlCrossRefPubMed
  22. ↵
    1. Jayasingam SD,
    2. Citartan M,
    3. Thang TH,
    4. Mat Zin AA,
    5. Ang KC,
    6. Ch’ng ES
    : Evaluating the polarization of tumor-associated macrophages into M1 and M2 phenotypes in human cancer tissue: technicalities and challenges in routine clinical practice. Front Oncol 9: 1512, 2020. DOI: 10.3389/fonc.2019.01512
    OpenUrlCrossRefPubMed
  23. ↵
    1. Yang H,
    2. Zhang Q,
    3. Xu M,
    4. Wang L,
    5. Chen X,
    6. Feng Y,
    7. Li Y,
    8. Zhang X,
    9. Cui W,
    10. Jia X
    : CCL2-CCR2 axis recruits tumor associated macrophages to induce immune evasion through PD-1 signaling in esophageal carcinogenesis. Mol Cancer 19(1): 41, 2020. DOI: 10.1186/s12943-020-01165-x
    OpenUrlCrossRefPubMed
  24. ↵
    1. Poh AR,
    2. Ernst M
    : Targeting macrophages in cancer: from bench to bedside. Front Oncol 8: 49, 2018. DOI: 10.3389/fonc.2018.00049
    OpenUrlCrossRefPubMed
  25. ↵
    1. Wu J,
    2. Crowe DL
    : PARP5B is required for nonhomologous end joining during tumorigenesis in vivo. Mol Carcinog 61(1): 85-98, 2022. DOI: 10.1002/mc.23363
    OpenUrlCrossRefPubMed
  26. ↵
    1. Beagan JA,
    2. Phillips-Cremins JE
    : On the existence and functionality of topologically associating domains. Nat Genet 52(1): 8-16, 2020. DOI: 10.1038/s41588-019-0561-1
    OpenUrlCrossRefPubMed
  27. ↵
    1. Evrard D,
    2. Szturz P,
    3. Tijeras-Raballand A,
    4. Astogues-Xerri L,
    5. Abitbol C,
    6. Paradis V,
    7. Raymond E,
    8. Albert S,
    9. Barry B,
    10. Faivre S
    : Macrophages in the microenvironment of head and neck cancer: potential targets for cancer therapy. Oral Oncol 88: 29-38, 2019. DOI: 10.1016/j.oraloncology.2018.10.040
    OpenUrlCrossRefPubMed
  28. ↵
    1. Zhou Y,
    2. Li J,
    3. Han B,
    4. Zhong R,
    5. Zhong H
    : Schwann cells promote lung cancer proliferation by promoting the M2 polarization of macrophages. Cell Immunol 357: 104211, 2020. DOI: 10.1016/j.cellimm.2020.104211
    OpenUrlCrossRefPubMed
  29. ↵
    1. Wang H,
    2. Zhang Q,
    3. Kong H,
    4. Zeng Y,
    5. Hao M,
    6. Yu T,
    7. Peng J,
    8. Xu Z,
    9. Chen J,
    10. Shi H
    : Monocyte chemotactic protein 1 expression as a prognostic biomarker in patients with solid tumor: a meta-analysis. Int J Clin Exp Pathol 7(7): 3876-3886, 2014.
    OpenUrlPubMed
  30. ↵
    1. Sampath S,
    2. Won H,
    3. Massarelli E,
    4. Li M,
    5. Frankel P,
    6. Vora N,
    7. Vora L,
    8. Maghami E,
    9. Kortylewski M
    : Combined modality radiation therapy promotes tolerogenic myeloid cell populations and STAT3-related gene expression in head and neck cancer patients. Oncotarget 9(13): 11279-11290, 2018. DOI: 10.18632/oncotarget.24397
    OpenUrlCrossRefPubMed
  31. ↵
    1. Peltanova B,
    2. Liskova M,
    3. Gumulec J,
    4. Raudenska M,
    5. Polanska HH,
    6. Vaculovic T,
    7. Kalfert D,
    8. Grega M,
    9. Plzak J,
    10. Betka J,
    11. Masarik M
    : Sensitivity to cisplatin in head and neck cancer cells is significantly affected by patient-derived cancer-associated fibroblasts. Int J Mol Sci 22(4): 1912, 2021. DOI: 10.3390/ijms22041912
    OpenUrlCrossRefPubMed
  32. ↵
    1. Tu M,
    2. Klein L,
    3. Espinet E,
    4. Georgomanolis T,
    5. Wegwitz F,
    6. Li X,
    7. Urbach L,
    8. Danieli-Mackay A,
    9. Küffer S,
    10. Bojarczuk K,
    11. Mizi A,
    12. Günesdogan U,
    13. Chapuy B,
    14. Gu Z,
    15. Neesse A,
    16. Kishore U,
    17. Ströbel P,
    18. Hessmann E,
    19. Hahn SA,
    20. Trumpp A,
    21. Papantonis A,
    22. Ellenrieder V,
    23. Singh SK
    : TNF-α-producing macrophages determine subtype identity and prognosis via AP1 enhancer reprogramming in pancreatic cancer. Nature Cancer 2(11): 1185-1203, 2021. DOI: 10.1038/s43018-021-00258-w
    OpenUrlCrossRefPubMed
  33. ↵
    1. Domingo-Vidal M,
    2. Whitaker-Menezes D,
    3. Martos-Rus C,
    4. Tassone P,
    5. Snyder CM,
    6. Tuluc M,
    7. Philp N,
    8. Curry J,
    9. Martinez-Outschoorn U
    : Cigarette smoke induces metabolic reprogramming of the tumor stroma in head and neck squamous cell carcinoma. Mol Cancer Res 17(9): 1893-1909, 2019. DOI: 10.1158/1541-7786.MCR-18-1191
    OpenUrlAbstract/FREE Full Text
  34. ↵
    1. Momen-Heravi F,
    2. Bala S
    : Extracellular vesicles in oral squamous carcinoma carry oncogenic miRNA profile and reprogram monocytes via NF-κB pathway. Oncotarget 9(78): 34838-34854, 2018. DOI: 10.18632/oncotarget.26208
    OpenUrlCrossRefPubMed
  35. ↵
    1. Kloosterman DJ,
    2. Akkari L
    : Macrophages at the interface of the co-evolving cancer ecosystem. Cell 186(8): 1627-1651, 2023. DOI: 10.1016/j.cell.2023.02.020
    OpenUrlCrossRefPubMed
  36. ↵
    1. Kersten K,
    2. Hu KH,
    3. Combes AJ,
    4. Samad B,
    5. Harwin T,
    6. Ray A,
    7. Rao AA,
    8. Cai E,
    9. Marchuk K,
    10. Artichoker J,
    11. Courau T,
    12. Shi Q,
    13. Belk J,
    14. Satpathy AT,
    15. Krummel MF
    : Spatiotemporal co-dependency between macrophages and exhausted CD8(+) T cells in cancer. Cancer Cell 40(6): 624-638.e9, 2022. DOI: 10.1016/j.ccell.2022.05.004
    OpenUrlCrossRefPubMed
    1. van der Leun AM,
    2. Thommen DS,
    3. Schumacher TN
    : CD8(+) T cell states in human cancer: insights from single-cell analysis. Nat Rev Cancer 20(4): 218-232, 2020. DOI: 10.1038/s41568-019-0235-4
    OpenUrlCrossRefPubMed
  38. ↵
    1. Zhu Q,
    2. Wu X,
    3. Wu Y,
    4. Wang X
    : Interaction between Treg cells and tumor-associated macrophages in the tumor microenvironment of epithelial ovarian cancer. Oncol Rep 36(6): 3472-3478, 2016. DOI: 10.3892/or.2016.5136
    OpenUrlCrossRefPubMed
  39. ↵
    1. Li Q,
    2. Wu R,
    3. Wu F,
    4. Chen Q
    : KMT2D promotes proliferation of gastric cancer cells: evidence from ctDNA sequencing. J Clin Lab Anal 35(4): e23721, 2021. DOI: 10.1002/jcla.23721
    OpenUrlCrossRefPubMed
  40. ↵
    1. Numakura S,
    2. Uozaki H
    : Low MLL2 protein expression is associated with fibrosis in early stage gastric cancer. In Vivo 35(1): 603-609, 2021. DOI: 10.21873/invivo.12297
    OpenUrlAbstract/FREE Full Text
  41. ↵
    1. Uchi R,
    2. Jiromaru R,
    3. Yasumatsu R,
    4. Yamamoto H,
    5. Hongo T,
    6. Manako T,
    7. Sato K,
    8. Hashimoto K,
    9. Wakasaki T,
    10. Matsuo M,
    11. Nakagawa T
    : Genomic sequencing of cancer-related genes in sinonasal squamous cell carcinoma and coexisting inverted papilloma. Anticancer Res 41(1): 71-79, 2021. DOI: 10.21873/anticanres.14752
    OpenUrlAbstract/FREE Full Text
  42. ↵
    1. Rocca C,
    2. Rocca G,
    3. Zampieri P,
    4. Dell’atti L,
    5. Bianchi N,
    6. Ippolito C,
    7. Aguiari G
    : Somatic and germline variants affect prognosis and susceptibility in prostate cancer. Anticancer Res 43(7): 2941-2949, 2023. DOI: 10.21873/anticanres.16465
    OpenUrlAbstract/FREE Full Text
  43. ↵
    1. Linehan D,
    2. Noel MS,
    3. Hezel AF,
    4. Wang-Gillam A,
    5. Eskens F,
    6. Sleijfer S,
    7. Desar IME,
    8. Erdkamp F,
    9. Wilmink J,
    10. Diehl J,
    11. Potarca A,
    12. Zhao N,
    13. Miao S,
    14. Deng J,
    15. Hillson J,
    16. Bekker P,
    17. Schall TJ,
    18. Singh R
    : Overall survival in a trial of orally administered CCR2 inhibitor CCX872 in locally advanced/metastatic pancreatic cancer: Correlation with blood monocyte counts. J Clin Oncol 36(5_suppl): 92-92, 2018. DOI: 10.1200/JCO.2018.36.5_suppl.92
    OpenUrlCrossRef
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Lysine Methyltransferase 2D Regulates Immune Response and Metastasis in Head and Neck Cancer
JIANCHUN WU, CRYSTAL CHUN, ANGELICA M. LAGUNAS, DAVID L. CROWE
Anticancer Research Aug 2024, 44 (8) 3231-3242; DOI: 10.21873/anticanres.17141
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