JP2024039229A - Cancer metastasis inhibitor using Galectin-7 inhibitor - Google Patents

Abstract

[Problem] To provide a method and a drug for suppressing cancer metastasis by elucidating the physiological role of galectin-7 in cancer metastasis, in particular the role that galectin-7 plays in immunosuppression in the tumor microenvironment. [Solution] To provide a cancer metastasis inhibitor containing a galectin-7 inhibitor as an active ingredient, preferably an oligonucleotide having a sequence complementary to galectin-7 messenger RNA (mRNA), and preferably an antibody against galectin-7 protein. [Selected Figure] Figure 3

Description

TECHNICAL FIELD The present invention relates to cancer immunotherapy and medicines used therefor.

Cancer metastasis is the leading cause of cancer-related death worldwide1,2 ^. Squamous cell carcinoma (SCC) includes different types of tumors that occur in the skin, bladder and upper aerodigestive tract. Among upper aerodigestive tract cancers, almost all head and neck cancers (including oral cancer) and more than 80% of esophageal cancers are ^SCC3,4 . These SCCs are caused by the same risk factors, such as smoking, alcohol consumption, and oncogenic viruses, and share close similarities in pathology as well as treatment ^. SCC more frequently involves metastasis to lymph nodes and distant organs than adenocarcinoma. Despite continued advances in comprehensive treatment strategies combining surgery and chemotherapy/radiotherapy, tumors are often resistant to treatment and patient prognosis is ^poor6,7 . An important prognostic factor for somatic cell carcinoma is the presence of metastases, which is significantly correlated with mortality ^6,7 . In reality, recurrence due to metastasis to lymph nodes or distant organs after surgical treatment is often a problem. Thus, it is important to experimentally investigate the basic mechanism of SCC cell metastasis.

Cancer cells are a heterogeneous population, and a small proportion of cells with high metastatic potential (metastatic cells) are clonally selected to contribute to ^{metastasis8,9} . The tumor microenvironment is composed of fibroblasts, endothelial cells, immune/inflammatory cells, and extracellular matrix. Metastatic cells selectively proliferate, invade, and migrate within lymphatics and/or blood vessels through interactions with surrounding cells, i.e., cancer stromal crosstalk, in a specific tumor microenvironment. Earn ^10,11 . Antitumor immunity plays an essential role in tumor eradication. Apoptosis and exhaustion of antitumor immune cells, such as cytotoxic lymphocytes and dendritic cells (DCs), and recruitment of regulatory T cells and myeloid-derived suppressor cells (MDSCs) constitute an immunosuppressive microenvironment, and tumor cells ^12,13 allows the immune system to escape from disseminated immune surveillance12,13. Furthermore, immunosuppression/wasting was associated with the development of a hypoxic environment and ^angiogenesis . However, the molecular mechanisms of how immunosuppression shapes metastasis in the tumor microenvironment remain largely unknown, and this is partially due to the lack of methodology to assess gene expression profiles of the tumor microenvironment in vivo. This is because it is limited.

Galectins are a family of β-galactoside-binding lectins with diverse biological functions, and a total of 16 mammalian galectins have been identified ^16-18 . Galectin-7, the prototype of the galectin family first identified in the human epidermis, is a 15 kDa protein with a single carbohydrate recognition site that forms ^{homodimers19,20} . Galectin-7 expression is mainly found in stratified epithelial cells such as the skin, tongue, esophagus, and thymus21 ^. Galectin-7 functions include cell migration, cell adhesion, apoptosis, and immune regulation22,23 ^. In cancer, galectin-7 was originally identified as a p53-induced gene in apoptotic colon cancer cells. On the other hand, galectin-7 has been reported to have both pro- and anti-tumor roles in cancer, and the same is true for ^SCC25-27 . For example, galectin-7 expression was positively correlated with the well-differentiated status of tumor cells in esophageal and bladder SCCs28,29 ^. Galectin-7 expression is beneficial for the prognosis of cervical SCC patients30-32 ^. On the other hand, high expression of galectin-7 predicts poor prognosis of oral SCC33-37 ^. Additionally, galectin-7 ^was reported to promote tumor metastasis of human head and neck SCC (HNSCC) cells and breast cancer cells in mouse xenograft models. Thus, the physiological role of galectin-7 in cancer metastasis has not yet been elucidated.

1. Sung, H. et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA: A Cancer Journal for Clinicians 71, 209-249, doi:https://doi.org /10.3322/caac.21660 (2021).
2. Mehlen, P. & Puisieux, A. Metastasis: a question of life or death. Nature reviews. Cancer 6, 449-458, doi:10.1038/nrc1886 (2006).
3. Arnold, M., Ferlay, J., van Berge Henegouwen, MI & Soerjomataram, I. Global burden of oesophageal and gastric cancer by histology and subsite in 2018. Gut 69, 1564, doi:10.1136/gutjnl-2020-321600 (2020).
4. Mody, MD, Rocco, JW, Yom, SS, Haddad, RI & Saba, NF Head and neck cancer. The Lancet 398, 2289-2299, doi:10.1016/S0140-6736(21)01550-6 (2021) .
5. Wenig, BM Squamous cell carcinoma of the upper aerodigestive tract: dysplasia and select variants. Modern Pathology 30, S112-S118, doi:10.1038/modpathol.2016.207 (2017).
6. van Hagen, P. et al. Preoperative Chemoradiotherapy for Esophageal or Junctional Cancer. New England Journal of Medicine 366, 2074-2084, doi:10.1056/NEJMoa1112088 (2012).
7. Cramer, JD, Burtness, B., Le, QT & Ferris, RL The changing therapeutic landscape of head and neck cancer. Nature Reviews Clinical Oncology 16, 669-683, doi:10.1038/s41571-019-0227-z ( 2019).
8. Quail, DF & Joyce, JA Microenvironmental regulation of tumor progression and metastasis. Nature medicine 19, 1423-1437, doi:10.1038/nm.3394 (2013).
9. Lawson, DA, Kessenbrock, K., Davis, RT, Pervolarakis, N. & Werb, Z. Tumour heterogeneity and metastasis at single-cell resolution. Nat Cell Biol 20, 1349-1360, doi:10.1038/s41556-018 -0236-7 (2018).
10. Talmadge, JE & Fidler, IJ AACR centennial series: the biology of cancer metastasis: historical perspective. Cancer research 70, 5649-5669, doi:10.1158/0008-5472.Can-10-1040 (2010).
11. Lambert, AW, Pattabiraman, DR & Weinberg, RA Emerging Biological Principles of Metastasis. Cell 168, 670-691, doi:10.1016/j.cell.2016.11.037 (2017).
12. Gonzalez, H., Hagerling, C. & Werb, Z. Roles of the immune system in cancer: from tumor initiation to metastatic progression. Genes Dev 32, 1267-1284, doi:10.1101/gad.314617.118 (2018).
13. Janssen, LME, Ramsay, EE, Logsdon, CD & Overwijk, WW The immune system in cancer metastasis: friend or foe? Journal for ImmunoTherapy of Cancer 5, 79, doi:10.1186/s40425-017-0283-9 (2017 ).
14. Rahma, OE & Hodi, FS The Intersection between Tumor Angiogenesis and Immune Suppression. Clinical Cancer Research 25, 5449-5457, doi:10.1158/1078-0432.CCR-18-1543 (2019).
15. Terry, S., Buart, S. & Chouaib, S. Hypoxic Stress-Induced Tumor and Immune Plasticity, Suppression, and Impact on Tumor Heterogeneity. Frontiers in Immunology 8 (2017).
16. Johannes, L., Jacob, R. & Leffler, H. Galectins at a glance. Journal of Cell Science 131, jcs208884, doi:10.1242/jcs.208884 (2018).
17. Yang, R.-Y., Rabinovich, GA & Liu, F.-T. Galectins: structure, function and therapeutic potential. Expert Reviews in Molecular Medicine 10, e17, doi:10.1017/S1462399408000719 (2008).
18. Si, Y. et al. Human galectin-16 has a pseudo ligand binding site and plays a role in regulating c-Rel-mediated lymphocyte activity. Biochimica et Biophysica Acta (BBA) - General Subjects 1865, 129755, doi:https ://doi.org/10.1016/j.bbagen.2020.129755 (2021).
19. Madsen, P. et al. Cloning, Expression, and Chromosome Mapping of Human Galectin-7 (*). Journal of Biological Chemistry 270, 5823-5829, doi:https://doi.org/10.1074/jbc.270.11 .5823 (1995).
20. Magnaldo, T., Bernerd, F. & Darmon, M. Galectin-7, a human 14-kDa S-lectin, specifically expressed in keratinocytes and sensitive to retinoic acid. Dev Biol 168, 259-271, doi:10.1006 /dbio.1995.1078 (1995).
21. Magnaldo, T., Fowlis, D. & Darmon, M. Galectin-7, a marker of all types of stratified epithelia. Differentiation 63, 159-168, doi:https://doi.org/10.1046/j. 1432-0436.1998.6330159.x (1998).
22. Saussez, S. & Kiss, R. Galectin-7. Cell Mol Life Sci 63, 686-697, doi:10.1007/s00018-005-5458-8 (2006).
23. Sewgobind, NV, Albers, S. & Pieters, RJ Functions and Inhibition of Galectin-7, an Emerging Target in Cellular Pathophysiology. Biomolecules 11, 1720, doi:10.3390/biom11111720 (2021).
24. Polyak, K., Xia, Y., Zweier, JL, Kinzler, KW & Vogelstein, B. A model for p53-induced apoptosis. Nature 389, 300-305, doi:10.1038/38525 (1997).
25. Advedissian, T., Deshayes, F. & Viguier, M. Galectin-7 in Epithelial Homeostasis and Carcinomas. Int J Mol Sci 18, 2760, doi:10.3390/ijms18122760 (2017).
26. Kaur, M., Kaur, T., Kamboj, SS & Singh, J. Roles of Galectin-7 in Cancer. Asian Pacific journal of cancer prevention : APJCP 17, 455-461, doi:10.7314/apjcp.2016.17. 2.455 (2016).
27. St-Pierre, Y., Campion, CG & Grosset, A.-A. A distinctive role for galectin-7 in cancer? FBL 17, 438-450, doi:10.2741/3937 (2012).
28. Zhu, X. et al. Identification of galectin-7 as a potential biomarker for esophageal squamous cell carcinoma by proteomic analysis. BMC Cancer 10, 290-290, doi:10.1186/1471-2407-10-290 (2010).
29. Ostergaard, M. et al. Proteome profiling of bladder squamous cell carcinomas: identification of markers that define their degree of differentiation. Cancer research 57, 4111-4117 (1997).
30. Zhu, H. et al. Roles of galectin-7 and S100A9 in cervical squamous carcinoma: Clinicopathological and in vitro evidence. International Journal of Cancer 132, 1051-1059, doi:https://doi.org/10.1002/ijc .27764 (2013).
31. Zhu, H. et al. Profiling Protein Markers Associated with the Sensitivity to Concurrent Chemoradiotherapy in Human Cervical Carcinoma. Journal of Proteome Research 8, 3969-3976, doi:10.1021/pr900287a (2009).
32. Tsai, CJ et al. Galectin-7 levels predict radiation response in squamous cell carcinoma of the cervix. Gynecologic Oncology 131, 645-649, doi:https://doi.org/10.1016/j.ygyno.2013.04.056 (2013).
33. Guo, J.-P. & Li, X.-G. Galectin-7 promotes the invasiveness of human oral squamous cell carcinoma cells via activation of ERK and JNK signaling. Oncol Lett 13, 1919-1924, doi:10.3892/ ol.2017.5649 (2017).
34. Mesquita, JA et al. Association of immunoexpression of the galectins-3 and -7 with histopathological and clinical parameters in oral squamous cell carcinoma in young patients. European Archives of Oto-Rhino-Laryngology 273, 237-243, doi:10.1007 /s00405-014-3439-y (2016).
35. Alves, PM et al. Significance of galectins-1, -3, -4 and -7 in the progression of squamous cell carcinoma of the tongue. Pathology - Research and Practice 207, 236-240, doi:https:// doi.org/10.1016/j.prp.2011.02.004 (2011).
36. Saussez, S. et al. Identification of matrix metalloproteinase-9 as an independent prognostic marker in laryngeal and hypopharyngeal cancer with opposite correlations to adhesion/growth-regulatory galectins-1 and -7. Int J Oncol 34, 433-439, doi:10.3892/ijo_00000167 (2009).
37. Saussez, S. et al. Galectin 7 (p53-Induced Gene 1): A New Prognostic Predictor of Recurrence and Survival in Stage IV Hypopharyngeal Cancer. Annals of Surgical Oncology 13, 999-1009, doi:10.1245/ASO.2006.08 .033 (2006).
38. Chen, Y.-S. et al. HSP40 co-chaperone protein Tid1 suppresses metastasis of head and neck cancer by inhibiting Galectin-7-TCF3-MMP9 axis signaling. Theranostics 8, 3841-3855, doi:10.7150/thno. 25784 (2018).
39. Demers, M. et al. Overexpression of galectin-7, a myoepithelial cell marker, enhances spontaneous metastasis of breast cancer cells. Am J Pathol 176, 3023-3031, doi:10.2353/ajpath.2010.090876 (2010).
40. Gozgit, JM et al. PARP7 negatively regulates the type I interferon response in cancer cells and inhibits its triggers antitumor immunity. Cancer Cell 39, 1214-1226.e1210, doi:https://doi.org/10.1016/j. ccell.2021.06.018 (2021).
41. Owen, KL et al. Prostate cancer cell-intrinsic interferon signaling regulates dormancy and metastatic outgrowth in bone. EMBO Rep 21, e50162, doi:https://doi.org/10.15252/embr.202050162 (2020).
42. Kumar, V., Patel, S., Tcyganov, E. & Gabrilovich, DI The Nature of Myeloid-Derived Suppressor Cells in the Tumor Microenvironment. Trends Immunol 37, 208-220, doi:10.1016/j.it.2016.01 .004 (2016).
43. Hirakawa, S. et al. VEGF-A induces tumor and sentinel lymph node lymphangiogenesis and promotes lymphatic metastasis. Journal of Experimental Medicine 201, 1089-1099, doi:10.1084/jem.20041896 (2005).
44. Richardson, AM et al. Vimentin Is Required for Lung Adenocarcinoma Metastasis via Heterotypic Tumor Cell-Cancer-Associated Fibroblast Interactions during Collective Invasion. Clin Cancer Res 24, 420-432, doi:10.1158/1078-0432.CCR-17- 1776 (2018).
45. Li, H.-J. et al. ENO1 Promotes Lung Cancer Metastasis via HGFR and WNT Signaling-Driven Epithelial-to-Mesenchymal Transition. Cancer research 81, 4094-4109, doi:10.1158/0008-5472.CAN-20 -3543 (2021).
46. Wang, J. et al. NRP-2 in tumor lymphangiogenesis and lymphatic metastasis. Cancer Letters 418, 176-184, doi:https://doi.org/10.1016/j.canlet.2018.01.040 (2018).
47. Liu, X. et al. Phosphoglycerate Mutase 1 (PGAM1) Promotes Pancreatic Ductal Adenocarcinoma (PDAC) Metastasis by Acting as a Novel Downstream Target of the PI3K/Akt/mTOR Pathway. Oncol Res 26, 1123-1131, doi:10.3727 /096504018X15166223632406 (2018).
48. Bogucka, K. et al. ERK3/MAPK6 controls IL-8 production and chemotaxis. Elife 9, e52511, doi:10.7554/eLife.52511 (2020).
49. Huang, W.-C. et al. A novel miR-365-3p/EHF/keratin 16 axis promotes oral squamous cell carcinoma metastasis, cancer stemness and drug resistance via enhancing β5-integrin/c-met signaling pathway. J Exp Clin Cancer Res 38, 89-89, doi:10.1186/s13046-019-1091-5 (2019).
50. Albini, A., Mirisola, V. & Pfeffer, U. Metastasis signatures: genes regulating tumor-microenvironment interactions predict metastatic behavior. Cancer and Metastasis Reviews 27, 75-83, doi:10.1007/s10555-007-9111-x (2008).
51. Liu, Y. & Cao, X. Immunosuppressive cells in tumor immune escape and metastasis. Journal of Molecular Medicine 94, 509-522, doi:10.1007/s00109-015-1376-x (2016).
52. Campbell, PJ et al. The patterns and dynamics of genomic instability in metastatic pancreatic cancer. Nature 467, 1109-1113, doi:10.1038/nature09460 (2010).
53. Nguyen, B. et al. Genomic characterization of metastatic patterns from prospective clinical sequencing of 25,000 patients. Cell 185, 563-575 e511, doi:10.1016/j.cell.2022.01.003 (2022).
54. Saussez, S. et al. The determination of the levels of circulating galectin-1 and -3 in HNSCC patients could be used to monitor tumor progression and/or responses to therapy. Oral Oncology 44, 86-93, doi:https ://doi.org/10.1016/j.oraloncology.2006.12.014 (2008).
55. Labrie, M., Vladoiu, MC, Grosset, A.-A., Gaboury, L. & St-Pierre, Y. Expression and functions of galectin-7 in ovarian cancer. Oncotarget 5, 7705-7721, doi: 10.18632/oncotarget.2299 (2014).
56. Pham, NTH et al. Perturbing dimer interactions and allosteric communication modulates the immunosuppressive activity of human galectin-7. J Biol Chem 297, 101308-101308, doi:10.1016/j.jbc.2021.101308 (2021).
57. Pape, M. et al. Treatment patterns and overall survival for recurrent esophageal or gastroesophageal junctional cancer: A nationwide European population-based study. Journal of Clinical Oncology 39, 186-186, doi:10.1200/JCO.2021.39.3_suppl. 186 (2021).
58. Matsumoto, G. et al. Cold shock domain protein A (CSDA) overexpression inhibits tumor growth and lymph node metastasis in a mouse model of squamous cell carcinoma. Clinical & Experimental Metastasis 27, 539-547, doi:10.1007/s10585- 010-9343-y (2010).
59. Nagasawa, S. et al. Genomic profiling reveals heterogeneous populations of ductal carcinoma in situ of the breast. Communications Biology 4, 438, doi:10.1038/s42003-021-01959-9 (2021).

The problem to be solved by the present invention is to clarify the physiological role of galectin-7 in cancer metastasis, and in particular, the role that galectin-7 plays in immunosuppression in the tumor microenvironment. The objective is to provide treatments and therapeutic agents.

In this study, we investigated the molecular basis of the metastatic tumor microenvironment by utilizing a syngeneic mouse SCC model. Gene expression profiles of metastatic tumor cells suggested a role for immunosuppression in metastasis. We performed spatial transcriptome analysis and genetically mapped immunosuppressive regions of the primary tumor that share features of downregulated interferon response, antigen presentation, and innate immune responses. Within the immunosuppressive region, we identified tumor cell-derived galectin-7 as a critical mediator of metastasis. Galectin-7 depletion significantly inhibited lymph node and lung metastases without affecting primary tumor growth. Therefore, the present invention has the following configuration.
[Embodiment 1]
A cancer metastasis inhibitor containing a galectin-7 inhibitor as an active ingredient.
[Embodiment 2]
The cancer metastasis inhibitor according to embodiment 1, wherein the galectin-7 inhibitor is an oligonucleotide having a sequence complementary to galectin-7 messenger RNA (mRNA).
[Embodiment 3]
The cancer metastasis suppressor according to embodiment 1, wherein the galectin-7 inhibitor is an antibody against galectin-7 protein.
[Embodiment 4]
A method to determine that the risk of metastasis is high when the concentration of galectin-7 protein in a sample derived from a cancer-bearing patient is higher than a certain number of times compared to a standard control.

By using the medicament of the present invention, it is possible to suppress metastasis of cancer or tumors, particularly cancers or tumors where immunosuppression in the metastatic tumor microenvironment is a problem.

Interferon gene signature is downregulated in metastatic NR-S1M cells. C3H/HeN female mice were subcutaneously implanted with NRS1M cells. a, Tracking the time course of tumor growth and measuring and plotting tumor weight. b, The percentage of mice with LN metastases was calculated and shown as a bar graph 2, 4 and 5 weeks after transplantation. c, The number of metastatic tumor nodules in the lungs is counted and plotted. d, Illustration of the experimental process to isolate metastatic NR-S1M cells. e, Proliferative capacity of parental and metastatic NR-S1M cells cultured in vitro is measured by BrdU incorporation assay, and O.D. values representing proliferating cells are plotted as a bar graph. f, The degree of cell death is evaluated by PI staining, and the percentage (ratio, %) of PI-positive cells is calculated. C3H/HeN female mice were transplanted with parental NR-S1M cells and metastatic NR-S1M cells, respectively. g, Tumor weight was measured 4 weeks after transplantation. h, Calculate the percentage of mice with LN metastases 3 weeks after transplantation. Data are presented as mean ± standard error. *p<0.05. ***p<0.005. Comprehensive gene expression profiles of parental and metastatic NR-S1M cells were determined by RNA-Seq. i, Scatter plot presenting DEGs with applied cutoff values (Q value < 0.05, fold change > 2). j, Gene set enrichment analysis of downregulated DEGs in metastatic NR-S1M cells. Gene sets of interferon response were identified as top hits. k, Expression levels of genes involved in interferon response (adjusted to TPM+1) are shown as a heat map plot. Malignant NR-S1M tumors develop focal areas of immunosuppression. a, Representative cell images of CD3ε and B220 expression on CD45 ⁺ Gr-1 ⁻ cells. The percentage of designated T cells and B cells is calculated and plotted as a bar graph. bc, NR-S1M tumors derived from metastatic cells were immunostained with anti-CD8 or anti-CD11c antibodies. Representative images showing CD8 positive (b) and CD11c positive (c) cells (brown). When the areas in the blue and red frames are strongly enlarged, areas rich in immune cells and areas lacking in immune cells are emphasized, respectively. de, Representative examples of CD8-positive (d) and CD11c-positive (e) cells (brown) in the parental NR-S1M tumor. High magnification of the red-framed area highlights severe deficiencies in immune cells. Spatial transcriptome (ST) analysis of NR‐S1M tumors. a, Visualization of Visium results for NR-S1M tumor tissue (section #3-2). H&E staining (left) and representing a total of 2812 ST spots (right). The entire tissue is classified via unbiased K-Means clustering (k = 9) with different colors. The number of ST spots in each cluster was listed. b, Plot all nine clusters according to the t-SNE algorithm. c–d, Significantly upregulated (c) and downregulated (d) genes in each cluster were determined using Loupe Browser Software and subjected to GO enrichment analysis (Metascape tool). The top five GO terms in each cluster were shown as a bar graph with P values. Identification of immunosuppressive regions with metastatic potential. a-b, ST spots of designated immunocompetent (cluster 6) and immunosuppressive (cluster 4) regions are colored blue and red, respectively. Among these regions, the proportions of CD8-positive (a) and CD11c-positive (b) ST spots (yellow) are calculated and plotted. c, Multi-GO analysis of significantly upregulated genes between immunocompetent and immunosuppressive clusters Expression levels of metastasis-related genes corresponding to GO terms of cellular responses of hypoxia, apoptotic signaling pathway and angiogenesis (Median-Normalized Average) was plotted as a bar graph of d. Data are presented as mean ± SEM. *p<0.05. **p<0.01. Identification of galectin-7 as a potential metastasis-promoting factor. a, Downregulated DEGs (compared to the parental strain, red circles, 470 genes) and immunosuppressive clusters (blue circles, 86 genes compared to the immunocompetent cluster) in metastatic NR-S1M cells were combined; Obtain 21 common genes. b, Merging upregulated DEGs (compared with the parental strain, red circles, 393 genes) and immunosuppressive clusters (blue circles, 20 genes, compared with the immunocompetent cluster) in metastatic NR-S1M cells; Obtain two common genes. c–d, Upregulated expression levels of Lgals7 in metastatic NR-S1M cells (c) and immunosuppressed regions (d) are shown as bar graphs. e, Cell lysates from parental and metastatic NR-S1M cells are subjected to Western blotting. Bands indicate the levels of galectin-7 and GAPDH (internal control), respectively. f, NR-S1M tumor was immunostained using anti-Gal-7 and anti-CD8 antibodies. This is a representative image showing that Gal-7 is highly expressed in a CD8-poor region (area surrounded by a red dotted line). g, Quantitative RT-PCR analysis of Lgals7 expression in metastatic NR-S1M cells with or without 24-h treatment with IFN-γ (100 ng/ml) or TNF-α (100 ng/ml) h, metastatic NR-S1M cells Culture supernatants and plasma from NR-S1M transplanted mice were collected and subjected to ELISA. The content of galectin-7 is quantified and plotted as a bar graph. Data are presented as mean ± SEM. *p<0.05. **p<0.01. ****p<0.001. Removal of galectin-7 in NR-S1M cells alleviates metastasis. C3H/HeN female mice were implanted with control or Gal-7 KO NR-S1M cells for 6 weeks. a, Plasma galectin-7 content was quantified by ELISA. b, Time course of tumor volume was tracked (left) and final tumor weight was measured (right). c, Calculating the percentage of mice with LN metastases after 6 weeks of transplantation. d, Representative images of the macroscopic lungs of mice in each group are shown. The bar indicates 4mm. e, Count and plot the number of metastatic tumor nodules within the lung. f, Lung weights of mice in each group are measured and plotted. Data are presented as mean ± SEM. *p<0.05. **p<0.01. Proportion of CD45 ⁺ Gr-1 ⁺ cells in NR-S1M tumors. Flow cytometry analysis of the percentage of CD45 ⁺ Gr-1 ⁺ cells in tumors derived from parental and metastatic NR-S1M cells Global GO analysis of ST clusters (Intercept #3-2) Multi-GO analysis of significantly up-regulated (left) and down-regulated (right) genes among K-Means classification clusters ST analysis of NR-S1M tumor (section #3-1). a, Visualization of Visium results H&E staining of NR-S1M tumor tissue (#3-1) (left) and representing a total of 2258 ST spots (right). The entire tissue is classified via unbiased K-Means clustering (k = 9) with different colors. The number of ST spots in each cluster was listed. b, Plot all nine clusters according to the t-SNE algorithm. c–d, Significantly upregulated (c) and downregulated (d) genes in each cluster were determined using Loupe Browser Software and subjected to GO enrichment analysis (Metascape tool). The top five GO terms in each cluster were shown as a bar graph with P values. ST analysis of NR-S1M tumor (section #4-3). a, Visualization of Visium results H&E staining of NR-S1M tumor tissue (#4-3) (left) and representing a total of 3774 ST spots (right). The entire tissue is classified via unbiased K-Means clustering (k = 9) with different colors. The number of ST spots in each cluster was listed. b, Plot all nine clusters according to the t-SNE algorithm. c–d, Significantly upregulated (c) and downregulated (d) genes in each cluster were determined using Loupe Browser Software and subjected to GO enrichment analysis (Metascape tool). The top five GO terms in each cluster were shown as a bar graph with P values. ST analysis of NR-S1M tumor (section #4-4). a, Visualization of Visium results H&E staining of NR-S1M tumor tissue (#4-4) (left) and representing a total of 2446 ST spots (right). The entire tissue is classified via unbiased K-means clustering (k = 9) with different colors. The number of ST spots in each cluster was listed. b, Plot all nine clusters according to the t-SNE algorithm. c–d, Significantly upregulated (c) and downregulated (d) genes in each cluster were determined using Loupe Browser Software and subjected to GO enrichment analysis (Metascape tool). The top five GO terms in each cluster were shown as a bar graph with P values. Comparative GO analysis of immunosuppressive regions (section #3-1). In NR-S1M tumor tissue #3-1, ST spots in designated immunocompetent (cluster 2) and immunosuppressive (cluster 3) regions are colored blue and red, respectively. Multi-GO analysis of significantly upregulated genes between immunocompetent and immunosuppressive clusters is shown. Comparative GO analysis of immunosuppressive regions (section #4-3). In NR-S1M tumor tissue #4-3, ST spots in designated immunocompetent (cluster 3) and immunosuppressive (cluster 4) regions are colored blue and red, respectively. Multi-GO analysis of significantly upregulated genes between immunocompetent and immunosuppressive clusters is shown. Comparative GO analysis of immunosuppressive regions (section #4-4). In NR-S1M tumor tissue #4-4, ST spots in designated immunocompetent (cluster 2) and immunosuppressive (cluster 4) regions are colored blue and red, respectively. Multi-GO analysis of significantly upregulated genes between immunocompetent and immunosuppressive clusters is shown.

We found that metastatic cancer cells promote their metastasis by secreting galectin-7 protein extracellularly and achieving immunosuppression in the tumor microenvironment. Therefore, a substance that inhibits the function of galectin-7 at various stages is an active ingredient of the cancer metastasis inhibitor of the present invention. Furthermore, in one embodiment of the present invention, it can be determined that the risk of metastasis is high when the galectin-7 protein concentration in a sample derived from a cancer-bearing patient is higher than a certain number of times compared to a standard control. Examples of the fixed multiple include 1.5 times, 2 times, 3 times, 4 times, 5 times, 8 times, or 10 times.

First, examples of galectin-7 inhibitors include substances that suppress the expression of the galectin-7 gene. More specifically, examples include oligonucleotides (nucleic acid medicines) having a sequence complementary to galectin-7 messenger RNA (mRNA: preferably NCBI Reference Sequence: NM_002307.4). The nucleic acid drug may have a length that is common for nucleic acid drugs, and the portion having a complementary sequence may be 10 to 30, 15 to 25, 18 to 23, or 10, 11, 12, 13, 14, 15. , 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, or 30 nucleotides in length. The complementary sequence is preferably a sequence that is completely complementary to galectin-7 mRNA, but less than 10% or less than 5% (for example, the length of the portion having the complementary sequence is 20 nucleotides). In this case, there may be mismatches of 2 or less places or 1 or less places, respectively. In addition to the portion having a complementary sequence, the nucleic acid drug may have other functional portions (modifying groups, labels, drugs, etc.).

Second, galectin-7 inhibitors include substances that inhibit the function of galectin-7 protein (preferably, NCBI Reference Sequence: NP_002298.1). More specifically, examples include antibodies (antibody drugs) that bind to galectin-7 protein. The antibody drug is preferably a monoclonal antibody, such as a mouse antibody, a chimeric antibody, a humanized antibody, or a fully human antibody.

Third, galectin-7 inhibitors include substances that inhibit the binding of galectin-7 to targets on immune cells in the tumor microenvironment.

Suppression of cancer metastasis, in one aspect, is the prevention of immunosuppression in the metastatic tumor microenvironment. In another embodiment, suppressing cancer metastasis is suppressing apoptosis or exhaustion of anti-tumor immune cells in the metastatic tumor microenvironment, or recruitment of regulatory T cells or myeloid-derived suppressor cells (MDSCs). In another aspect, cancer metastasis inhibition is inhibition of reduced infiltration of anti-tumor immune cells in the metastatic tumor microenvironment. Here, the anti-tumor immune cells are CD8 ⁺ T cells or CD11c ⁺ dendritic cells (DC).

In principle, cancers for which the galectin-7 inhibitor of the present invention is effective are cancers that express galectin-7 and contain cells with high metastatic potential (metastatic cells). Specifically, the galectin-7 inhibitor of the present invention is effective against oral squamous cell carcinoma (SCC). On the other hand, the galectin-7 inhibitor of the present invention is not effective against esophageal SCC, bladder SCC, and cervical SCC.

1. Materials and methods

1.1. Cell culture/tumor metastasis model Mouse oral squamous cell carcinoma cell line NR-S1M was developed by Dr. ⁵⁸ obtained from Matsumoto. Parental NR-S1M cells were cultured in RPMI-1640 medium supplemented with 10% fetal bovine serum at 37°C in the presence of 5% _CO2 . To establish Lgals7 knockout (Gal‐7 KO) NR‐S1M cells, two sgRNA sequences of Lgals7 (Lgals7(AB), CCTCGGGTTAAAGTGCAAGG; Lgals7(AC), GCGATGAGGAGCACTTCAAA) were each cloned into pLentiCRISCRv2 vector. The synthesized pLentiCRISPRv2-sgRNA combined with pMD2.G and psPax2 plasmid was co-transfected into 293FT cells with PEI MAX reagent (Polysciences) to obtain lentivirus. Parental NR-S1M cells were spin-infected with two purified Lgals7 lentiviruses in polybrene (10 μg/ml) and then exposed to puromycin selectin (5 μg/ml) for 1 week. Five-week-old female C3H/HeN mice were purchased from Japan SLC. Mice were inoculated subcutaneously with NR-S1M cells (5×10 ⁶ cells/mouse in 100 μL of DPBS), tumor volumes were measured weekly, and tumor metastasis was assessed after euthanasia. Mice were kept in the animal facility of Akita University Graduate School of Medicine. All animal experiments were conducted in accordance with the Guidelines for the Care and Use of Laboratory Animals published by the National Institutes of Health (NIH Publication No. 85-23, revised in 1996) and approved by the Akita University Ethics Review Committee. Obtained. Metastatic NR-S1M cells were harvested from metastatic LNs of mice 6 weeks after inoculation, pooled, and cultured similarly to the parent strain.

1.2. BrdU incorporation assay 2×10 ⁵ cells/ml of parental and metastatic NR-S1M cells were each seeded in 24-well plates. The next day, BrdU was added to the medium for 6 hours, and proliferating cells were quantified using the BrdU Cell Proliferation ELISA Kit (ab126556, ABCAM).

1.3. Measurement of Cell Death 2×10 ⁵ cells/ml of parental and metastatic NR-S1M cells were each seeded in 24-well plates. The next day, detached cells were suspended in 1× DPBS containing PI staining solution (00-6990-50, eBioscience). The degree of cell death (ratio of PI-positive cells) was evaluated using BD FACSCalibur (BD Biosciences).

1.4. RNA-Seq analysis In triplicate, total RNA was purified from parental or metastatic NR-S1M cells using Direct-zol RNA MicroPrep (Zymo Research). Library construction and high-throughput sequencing were performed by BGI Japan. Differentially expressed genes (DEGs) between groups were selected using the DESeq2 algorithm. Gene set enrichment analysis was performed using Dr.Tom Data Visualization Solution (BGI Japan).

1.5. Flow cytometry
NR‐S1M tumors were excised, minced, and cultured in TESCA buffer containing collagenase IV (2 mg/ml, C5138, Sigma) and DNase I (100 μg/ml, DN25, Sigma) at 37°C for 30 min with shaking. Digested for minutes. The cell suspension was passed through a cell strainer and preincubated with mouse BD Fc block purified rat anti-mouse CD16/CD32 mAb (BD Biosciences) for 15 minutes on ice. Next, APC-conjugated anti-CD45 (30-F11), PE-conjugated anti-CD45R/B220 (RA3-6B2), PerCP/Cy5.5-conjugated anti-CD3ε (145-2C11), and PE/Cy7-conjugated anti-Gr-1 (RB6 -8C5). All antibodies were purchased from BioLegend. Flow cytometry analysis was performed with BD FACSMelody (BD Biosciences), and data were analyzed with FlowJo ver. 10 (Tree Star).

1.6. Immunohistochemistry Formalin-fixed paraffin-embedded NR-S1M tumor tissues were sectioned and then subjected to citrate buffer (pH 6.0) antigen retrieval and endogenous peroxidase quenching. Slides were incubated with primary antibodies against CD8α (4SM15, 1:500, eBioscience), CD11c (#97585, 1:350, Cell Signaling Technology), and Gal-7 (A18059A, 1:500, BioLegend), followed by Simple Detection was performed using StainTM MAX PO (Nichirei Biosciences). Nuclear staining was performed using Mayer's Hematoxylin Solution.

1.7. Spatial transcriptome (ST) analysis (Visium)
Two mice were inoculated with metastatic NR-S1M cells. The primary tumor was excised 3 weeks after inoculation. Each tumor was cut into two pieces, and a total of four tumor tissues were collected and subjected to ST analysis. Fresh tissue was immediately cryopreserved in Tissue-Tek OCT Compound (Sakura Finetek) and processed within 1 week. Frozen tissue blocks were sectioned at a thickness of 10 μm (CM1900, Leica). The RNA quality of the sectioned tissue was confirmed to meet the requirements for ST analysis (RIN >7). The library for Visium was created strictly according to the Visium Spatial Gene Expression User Guide (CG000239 Rev C, 10x Genomics). The tissue was permeabilized for 24 minutes and measured using the Visium Spatial Tissue Optimization Slide & Reagent Kit (10x Genomics). Libraries were sequenced on a NovaSeq 6000 system (Illumina) using the NovaSeq S4 reagent kit (Illumina) to a depth of approximately 350-500 million reads per sample. Raw FASTQ files and histology images were processed using Space Ranger Software (10x Genomics) and then ^visualized on Loupe Browser Software (10x Genomics). A representative tissue section (#3-2) is shown in Figures 3 and 4, and the other three sections are shown in Figures 9-14. All ST spots in each section were classified via K-Means (k = 9) and t-SNE algorithms for non-hierarchical clustering. Significantly upregulated and downregulated genes in each cluster determined by Loupe Browser Software (10x Genomics) were subjected to gene ontology (GO) analysis using Metascape (https://metascape.org). provided.

1.8. Western Blotting Parental and metastatic NR-S1M cells were cultured in RIPA buffer (50mM Tris-Cl, pH 7.5, 150mM NaCl, 1% Triton, 0.5% deoxycol) supplemented with protease inhibitor cocktail (P8340, Sigma). 0.1% sodium dodecyl sulfate). Cell lysates were sonicated and denatured with LDS Sample Buffer (Invitrogen) and β-mercaptoethanol. Samples were loaded onto NuPAGE Bis-Tris Precast Gel (Invitrogen), separated using NuPAGE MES SDS Running Buffer (Invitrogen), and transferred to nitrocellulose membranes (Invitrogen). Membranes were preincubated with 5% skim milk and then stained with anti-Gal-7 (1:1000, A18059A, BioLegend) or anti-GAPDH (#5174, 1:2000, Cell Signaling Technology) antibodies. Blot bands were visualized with ECL reagent (Bio‐Rad) using the ChemiDoc Touch Imaging System (Bio‐Rad).

1.9. Quantitative RT-PCR
cDNA synthesis was performed on the extracted total RNA using PrimeScript RT reagent kit (RR037, Takara Bio). The cDNA product was amplified using gene-specific primers and TB Green Premix Ex Taq II (RR820, Takara Bio) on Thermal Cycler Dice Real Time System III (Takara Bio). The following primers were synthesized and used in this study: Lgals7 Fw, AATTCGAGGCATGGTCCCTGAC; Lgals7 Rv, GGTGTTGAAGACAACCTCGGAAG; gapdh Fw, CTGCACCACCAACTGCTTAG; gapdh Rv, GTCTTCTGGGTGGCAGTGAT.

1.10. Gal-7 ELISA
Cell culture supernatants and plasma from mice inoculated with NR-S1M cells were subjected to mouse galectin-7 DuoSet ELISA (DY1304, R&D Systems) according to the manufacturer's protocol.

1.11. Statistics
Statistical significance between two experimental groups was determined using Student's two-tailed t-test. Comparisons of parameters between three or more groups were performed using one-way analysis of variance, followed by Dunnett's multiple comparison test. P<0.05 was considered significant.

2. Results

2.2. Isolation of metastatic NR-S1M tumor cells from lymph node metastases in a syngeneic murine SCC model
When NR-S1M mouse oral SCC cells were subcutaneously transplanted into C3H/HeN mice, growth of the primary tumor was observed, and the tumor weight reached its maximum value by 6 weeks after inoculation (Figure 1a). Tumor metastasis was observed in regional lymph nodes (LNs) and lungs in a certain percentage of mice 4 weeks after inoculation, and macroscopic pathological images of tumor nodules were observed in all mice 6 weeks after tumor implantation. shown (Fig. 1b,c). To analyze metastatic cells, we dissociated adherent tumor cells from other non-adherent LN cells (mostly lymphocytes) in in vitro culture to analyze the lymph nodes of tumor-bearing mice 6 weeks after inoculation. We isolated cells that had metastasized from (Figure 1d). By repeating this process three times, metastatic NR-S1M cells were established in vitro. In vitro metastatic NR-S1M cells showed no changes in proliferation or cell death from their parent cells (Fig. 1e, f). On the other hand, when mice were inoculated with metastatic NR-S1M cells, tumors of metastatic NR-S1M cells grew and metastasized faster than parental cells, and metastatic NR-S1M cells did not metastasize 3 weeks after transplantation. However, metastasis of the parental cells was confirmed at 6 weeks (Fig. 1g, h). Thus, isolated metastatic NR-S1M cells are enriched for cells with enhanced metastatic potential in the in vivo tumor microenvironment.

2.3. Interferon-activated gene (ISG) expression is downregulated in metastatic NR-S1M cells To investigate the global gene expression profile of metastatic NR-S1M cells, we performed RNA-seq analysis. A total of 863 differentially expressed genes (DEGs) were identified in the comparison between metastatic NR-S1M cells and their parental cells, of which 393 genes were upregulated and 470 genes were downregulated (Fig. 1i ). Gene set enrichment analysis demonstrated that downregulated DEGs were mostly enriched in terms of interferon response (Fig. 1j), whereas upregulated DEGs were only detected for cornification. Representative genes with changed ISGs expression levels are shown in Figure 1k.

2.4. Areas of Focal Immunosuppression in NR-S1M Tumors As dysregulation of ISG expression in tumor cells is known to affect tumor immunity, ^40,41 anti-tumor immunity may be downmodulated in metastatic NR-S1M tumors. I reasoned that it would be rated. When the number of CD3-positive (CD3 ⁺ ) T cells was measured by flow cytometry among cells enzymatically dissociated from tumor tissues, it was found that in tumors of metastatic NR-S1M cells 3 weeks after transplantation, parental cells at the same time point The percentage of CD3 ⁺ T cells was significantly reduced compared to the tumor of origin (Figure 2a). In contrast, the proportion of B220 ⁺ B cells in tumors derived from metastatic cells remained unchanged (Figure 2a). Additionally, Gr-1 ⁺ cells infiltrate more invasively into tumors in metastatic cells, potentially increasing the potential of MDSCs, a subtype of immature myeloid neutrophils and monocytes, to suppress antitumor immune responses. ⁴² (Figure 7). Next, we investigated the distribution of antitumor immune cells in tissue sections of NR-S1M tumors. Immunohistochemistry of metastatic cell tumors 4 weeks after transplantation shows that CD8 ⁺ T cells are not evenly distributed within the tumor, but rather localized heterogeneously. CD8 ⁺ T cells are enriched in some areas of the tumor tissue (blue frame), while sparse CD8 ⁺ T cells are observed in other areas (red frame) (Figure 2b). Consistent with this, CD11c ⁺ DCs also heterogeneously infiltrated NR-S1M tumors (Figure 2c), indicating the heterogeneity of tumor immunity. Interestingly, when the parental NR-S1M cell tumors reached their maximum size and showed metastasis at 6 weeks post-transplant, the parental cell-derived tumors also showed a heterogeneous distribution of CD8 ⁺ T cells and CD11c ⁺ DCs. (Fig. 2d, e), suggesting that malignant NR-S1M tumors develop focal immunosuppressive areas.

2.5. Spatial transcriptome analysis of NR-S1M tumors
Spatial transcriptome (ST) analysis (Visium) was performed to investigate spatial gene expression in the heterogeneous regions of NR-S1M tumors. Three weeks after inoculation, gene expression profiles of 2200 to 3700 barcoded ST spots (55 μm in diameter) per section were obtained for four primary tumors of metastatic NR-S1M cells, with K-Means (k = 9 ) and t-SNE algorithm analysis (Fig. 3a) resulted in unbiased clustering. As a result, ST spots were mainly classified into six clusters based on gene expression patterns, indicating heterogeneity of gene expression in NR-S1M tumors (Fig. 3a, b). For each cluster, significantly upregulated and downregulated genes were subjected to gene ontology (GO) analysis (Figure 8). In section #3-2, GO terms for up-regulated genes and GO terms for down-regulated genes were identified in clusters 1, 3-6 and clusters 1, 3 and 4, respectively (Fig. 3c, d). Importantly, antigen presentation and interferon response gene expression were significantly downregulated in cluster 4 compared to other regions across the section (Figure 3d), whereas interferon response related genes were significantly downregulated in cluster 6. upregulated (Fig. 3c). We therefore interpreted clusters 4 and 6 to map genetically as immunosuppressive and immunocompetent regions, respectively. Consistent with this, the authors detected similar paired clusters corresponding to immunosuppressive and immunocompetent regions in three other sections of the tumor (Figures 9, 10 and 11). When we examined Cd8a or Itgax (Cd11c)-positive puncta in 4 sections of the tumor, we found that both Cd8a ⁺ and Cd11c ⁺ puncta were significantly reduced in the immunosuppressive area compared to the immunocompetent area (Fig. 4a, b ), showed reduced infiltration of antitumor immune cells in immunosuppressed areas. GO analysis was performed between immunocompetent and immunosuppressive regions in section #3-2, and it was confirmed that immunosuppression was significantly associated with upregulation of apoptosis, hypoxic response, and angiogenesis. (Figure 4c). The same gene set was identified in the immunosuppressive regions of the other three sections (Figures 12, 13 and 14). Importantly, genes ^43-48 associated with metastasis, such as Vegfa, Vim and Mapk6, were significantly upregulated in the immunosuppressive region compared to the immunocompetent region (Fig. 4d). These results suggested that the immunosuppressive region is important for metastasis.

2.6 Galectin-7 is a potential pro-metastasis factor that is upregulated in immunosuppressive regions of tumors.
To explore the important metastasis-promoting genes in the immunosuppressive region of NR-S1M tumors, we compared the DEGs in the immunosuppressive region of NR-S1M tumors with in vitro-cultured metastatic NR-S1M cells. Regarding the downregulated compartments, 21 genes were commonly downregulated in both DEGs, most of which were ISGs (Fig. 5a).

Meanwhile, only two genes, Lgals7 and Krt16, were commonly upregulated in both DEGs (Fig. 5b). As Krt16, which encodes Keratin-16, was previously reported to promote OSCC invasion and metastasis, ⁴⁹ we focused on Lgals7, which encodes galectin-7 and whose role in SCC remains unclear. I guessed ^26,27 . Lgals7 was highly expressed in both immunosuppressed tumor areas in vivo and metastatic NR-S1M cells in vitro (Fig. 5c, d). Western blot analysis confirmed that galectin-7 was expressed in metastatic NR-S1M cells in vitro (Figure 5e). Although galectin-7 expression was not observed in parental NR-S1M cells (Fig. 5c, e), immunohistochemical analysis showed that galectin-7 expression was observed in in vivo tumors derived from parental NR-S1M cells. It became clear that it was especially induced in areas lacking CD8 ⁺ T cells (Figure 5f). We also found that when metastatic NR-S1M cells were treated with TNF-α but not IFN-γ, Lgals7 expression was significantly suppressed (Figure 5g), and galectin-7 expression is a pro-inflammatory/immune signal. It was suggested that it is negatively regulated by transmission. Furthermore, although galectin-7 was not detected in the cell culture supernatant of metastatic NR-S1M cells in vitro (Fig. 5c, h), galectin-7 was detected in NR-S1M tumor-bearing mice at 5 to 6 weeks after tumor inoculation. Plasma galectin-7 levels were significantly upregulated (Figure 5h). Thus, galectin-7 expression is induced and enhanced in the immunosuppressive microenvironment and is released extracellularly from tumor cells in vivo during the late stages of tumor development.

2.7. Ablation of galectin-7 suppresses metastasis in NR-S1M cells To investigate whether galectin-7 is involved in tumor metastasis, we generated Lgals7 knockout (Gal-7 KO) NR-S1M cells by using the CRISPR-Cas9 system. Immunohistochemistry did not confirm induction of galectin-7 in tumors of Gal-7 KO cells (not shown), and plasma galectin-7 levels were significantly reduced in mice bearing Gal-7 KO tumors (Fig. 6a). Although the growth rate of primary tumors was unchanged (Fig. 6b, c), the number of LN metastasis-positive mice was significantly reduced in mice inoculated with Gal-7 KO cells compared to mice inoculated with control cells (Fig. 6d). Furthermore, mice implanted with galectin-7-depleted NR-S1M cells had significantly fewer metastatic nodules in the lungs compared to mice implanted with control cells (Fig. 6e, f), and mice implanted with Gal-7 KO cells also had consistently reduced lung weights, indicating reduced tumor burden (Fig. 6g). Thus, depletion of galectin-7 in NR-S1M cells reduces lymph node and lung metastasis.

3. Discussion

Our combined analysis of RNA-seq of metastatic cells and spatial transcriptomics of in vivo tumors identified galectin-7 as a mediator of metastasis. Galectin-7 is highly induced in the immunosuppressive tumor microenvironment. Deletion of galectin-7 specifically suppressed lymph node and lung metastases without affecting primary tumor growth. Thus, galectin-7 plays a specific role in promoting tumor metastasis.

Metastatic NR-S1M cells in vitro exhibited a global alternation in gene expression and downregulation of ISGs compared to parental cells, indicating genetic characteristics imprinted by the specific tumor microenvironment. There could be ⁵⁰ . Indeed, the downregulation ^of tumor cell-intrinsic IFN signaling40,41 ^and the dramatic reduction of antitumor immune cell populations in tumors12 have been shown to be crucial for cancer metastasis. Our ST analysis indicates that malignant NR-S1M tumors are highly heterogeneous and the immunosuppressive sites identified therein may be ^niches for the proliferation and maintenance of metastatic tumor cells. Ta. Early studies on clonal selection of metastatic cells suggested genomic instability in metastatic ^cells52,53 . Genetic and epigenetic selection of tumor cells in immunosuppressive regions may be responsible for selection of metastatic cells and subsequent formation of metastatic nodules in distant organs. Further analysis by single-cell sequencing and/or single-cell ATAC sequencing will be required to elucidate the exact mechanism.

Downregulation of cellular responses to IFN as well as TNF-α in metastatic NR-S1M cells in vitro (Figure 1j) prompted us to examine whether inflammatory/immune signaling is involved in regulating galectin-7 expression. urged. Importantly, treatment with TNF-α dramatically inhibited galectin-7 expression in metastatic cells in vitro, and galectin-7 was highly expressed in immunosuppressive regions of NR-S1M tumors. Thus, a microenvironment with impaired inflammatory/immune signaling appears to enhance galectin-7 expression in tumor cells during tumor progression. On the other hand, the immunosuppressive region of NR-S1M tumors is enriched with apoptotic and hypoxia-responsive gene sets. ^Since galectin-7 expression is induced by p53 activation, it is possible that the hypoxic tumor microenvironment activates p53 in tumor cells, thereby leading to the induction of galectin-7 expression and subsequent release from the cells. be. A previous study showed that nuclear galectin-7 upregulates MMP9 expression and induces metastasis in HNSCC ^. Nevertheless, extracellular galectin-7 was not detected in the blood of HNSCC patients. The present study provides evidence that metastasis is correlated with elevated plasma galectin-7 levels, making it likely that extracellular galectin-7 functions as a specific metastasis-promoting factor. Recombinant galectin-7 has been reported to induce apoptosis in human Jurkat T cells in vitro, ^55,56 but these studies were performed using non-physiologically high concentrations of galectin-7. . Indeed, it was observed that treatment with galectin-7 did not affect the expression of ISGs in mouse splenic DCs (data not shown). Thus, the metastasis-specific effects of extracellular galectin-7 may be exerted through non-immune cells, and further analysis is required.

Galectin-7 expression is associated with cancer heterogeneity and promotes metastasis formation but not primary tumor growth. Although the detailed mechanism awaits further analysis, its metastasis-specific effects are unique. For example, in the treatment of patients with esophageal SCC, neoadjuvant chemotherapy or radiotherapy followed by curative resection of the esophagus is the current standard of care, but certain populations of patients suffer from recurrence of lymph node ^metastases57 . Preoperative treatment induces galectin-7 expression and secretion, thereby inversely promoting tumor metastasis in SCC patients, as induction of galectin-7 expression is associated with cell apoptosis as well as immunosuppression in our tumor model there is a possibility.

Therefore, galectin-7 and other pro-metastasis factors associated with immunosuppression may be potential targets for the development of cancer immunotherapy.

Claims (4)

A cancer metastasis inhibitor containing a galectin-7 inhibitor as an active ingredient. 2. The cancer metastasis suppressor according to claim 1, wherein the galectin-7 inhibitor is an oligonucleotide having a sequence complementary to galectin-7 messenger RNA (mRNA). 2. The cancer metastasis inhibitor according to claim 1, wherein the galectin-7 inhibitor is an antibody against galectin-7 protein. A method to determine that the risk of metastasis is high when the concentration of galectin-7 protein in a sample derived from a cancer-bearing patient is higher than a certain number of times compared to a standard control.