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Expression Patterns of HOX Gene Family Defines Tumor Microenvironment and Immunotherapy in Hepatocellular Carcinoma

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Abstract

Hepatocellular carcinoma (HCC) pathophysiology is prevalently related with HOX genes. However, the study on associations of extensive HOX genes with tumor microenvironment and drug sensitivity of HCC remains scarce. The data sets of HCC were downloaded from TCGA, ICGC, and GEO by bioinformatics method and analyzed. Based on a computational frame, HCC samples were divided into a high and a low HOXscore group, and significantly shorter survival time in the high HOXscore was observed relative to low HOXscore group using survival analysis. Gene set enrichment analysis (GSEA) revealed that the high HOXscore group was more likely to be enriched in cancer-specific pathways. Furthermore, the high HOXscore group was involved in the infiltration of inhibitory immune cells. In response to anti-cancer drugs, the high HOXscore group was more sensitive to mitomycin and cisplatin. Importantly, the HOXscore was associated with the therapeutic efficacy of PD-L1 blockade, suggesting that the development of potential drugs targeting these HOX genes to aid the clinical benefits of immunotherapy is needed. In addition, RT-qPCR and immunohistochemistry showed 10 HOX genes mRNA expression was higher in HCC compared to the normal tissues. This study provides a comprehensive analysis of HOX genes family in HCC and revealed the potential function of these HOX genes family in tumor microenvironment (TME) and identified their therapeutic liability in targeted therapy and immunotherapy. Eventually, this work highlights the cross-talk and potential clinical utility of HOX genes family in HCC therapy.

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Data Availability

The main datasets of LIHC were collected from TCGA (https://portal.gdc.cancer.gov/), ICGC (https://icgc.org/), and GEO database. The raw microarray data is available at GEO: GSE76427. The datasets used and/or analyzed during the current study are available from the corresponding author on request.

References

  1. Siegel, R. L., Miller, K. D., & Jemal, A. (2020). Cancer statistics, 2020. CA: A Cancer Journal for Clinicians, 70, 7–30. https://doi.org/10.3322/caac.21590

    Article  PubMed  Google Scholar 

  2. Villanueva, A. (2019). Hepatocellular Carcinoma. New England Journal of Medicine, 380, 1450–1462. https://doi.org/10.1056/NEJMra1713263

    Article  CAS  PubMed  Google Scholar 

  3. Forner, A., Reig, M., & Bruix, J. (2018). Hepatocellular carcinoma. Lancet, 391, 1301–1314. https://doi.org/10.1016/s0140-6736(18)30010-2

    Article  PubMed  Google Scholar 

  4. Hartke, J., Johnson, M., & Ghabril, M. (2017). The diagnosis and treatment of hepatocellular carcinoma. Seminars in Diagnostic Pathology, 34, 153–159. https://doi.org/10.1053/j.semdp.2016.12.011

    Article  PubMed  Google Scholar 

  5. Grandhi, M. S., Kim, A. K., Ronnekleiv-Kelly, S. M., Kamel, I. R., Ghasebeh, M. A., & Pawlik, T. M. (2016). Hepatocellular carcinoma: From diagnosis to treatment. Surgical Oncology, 25, 74–85. https://doi.org/10.1016/j.suronc.2016.03.002

    Article  PubMed  Google Scholar 

  6. Gao, D., Xu, X., Liu, L., Liu, L., Zhang, X., Liang, X., Cen, L., Liu, Q., Yuan, X., & Yu, Z. (2023). Combination of peglated-H1/HGFK1 nanoparticles and TAE in the treatment of hepatocellular carcinoma. Applied Biochemistry and Biotechnology, 195, 505–518. https://doi.org/10.1007/s12010-022-04153-7

    Article  CAS  PubMed  Google Scholar 

  7. Kudo, M., Kawamura, Y., Hasegawa, K., Tateishi, R., Kariyama, K., Shiina, S., Toyoda, H., Imai, Y., Hiraoka, A., Ikeda, M., Izumi, N., Moriguchi, M., Ogasawara, S., et al. (2021). Management of hepatocellular carcinoma in Japan: JSH Consensus Statements and Recommendations 2021 Update. Liver Cancer., 10, 181–223. https://doi.org/10.1159/000514174

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Piñero, F., Dirchwolf, M., & Pessôa, M. G. (2020). Biomarkers in hepatocellular carcinoma: diagnosis, prognosis and treatment response assessment. Cells, 9. https://doi.org/10.3390/cells9061370.

  9. Schlachterman, A., Craft, W. W., Jr., Hilgenfeldt, E., Mitra, A., & Cabrera, R. (2015). Current and future treatments for hepatocellular carcinoma. World Journal of Gastroenterology, 21, 8478–8491. https://doi.org/10.3748/wjg.v21.i28.8478

    Article  PubMed  PubMed Central  Google Scholar 

  10. Amudha, P., Jayalakshmi, M., Vidya, R., & Poojitha, B. N. (2022). Chemopreventive and therapeutic efficacy of enhalus acoroides against diethylnitrosamine induced hepatocellular carcinoma in Wistar Albino rats. Applied Biochemistry and Biotechnology. https://doi.org/10.1007/s12010-022-03832-9

    Article  PubMed  Google Scholar 

  11. Seethy, A., Pethusamy, K., Chattopadhyay, I., Sah, R., Chopra, A., Dhar, R., & Karmakar, S. (2021). TETology: Epigenetic mastermind in action. Applied Biochemistry and Biotechnology, 193, 1701–1726. https://doi.org/10.1007/s12010-021-03537-5

    Article  CAS  PubMed  Google Scholar 

  12. Bhatlekar, S., Fields, J. Z., & Boman, B. M. (2014). HOX genes and their role in the development of human cancers. Journal of Molecular Medicine (Berlin, Germany), 92, 811–823. https://doi.org/10.1007/s00109-014-1181-y

    Article  CAS  PubMed  Google Scholar 

  13. Paço, A., Aparecida de Bessa Garcia, S., Leitão Castro, J., Costa-Pinto, A. R., & Freitas, R. (2020). Roles of the HOX proteins in cancer invasion and metastasis. Cancers (Basel), 13. https://doi.org/10.3390/cancers13010010.

  14. Fantini, S., Salsi, V., & Zappavigna, V. (2018). HOX cluster-embedded micro-RNAs and cancer. Biochimica et Biophysica Acta - Reviews on Cancer, 1869, 230–247. https://doi.org/10.1016/j.bbcan.2018.03.002

    Article  CAS  PubMed  Google Scholar 

  15. Shah, N., & Sukumar, S. (2010). The Hox genes and their roles in oncogenesis. Nature Reviews Cancer, 10, 361–371. https://doi.org/10.1038/nrc2826

    Article  CAS  PubMed  Google Scholar 

  16. Contarelli, S., Fedele, V., & Melisi, D. (2020). HOX Genes family and cancer: a novel role for homeobox B9 in the resistance to anti-angiogenic therapies. Cancers (Basel), 12. https://doi.org/10.3390/cancers12113299.

  17. Grinchuk, O. V., Yenamandra, S. P., Iyer, R., Singh, M., Lee, H. K., Lim, K. H., Chow, P. K., & Kuznetsov, V. A. (2018). Tumor-adjacent tissue co-expression profile analysis reveals pro-oncogenic ribosomal gene signature for prognosis of resectable hepatocellular carcinoma. Molecular Oncology, 12, 89–113. https://doi.org/10.1002/1878-0261.12153

    Article  CAS  PubMed  Google Scholar 

  18. Robinson, M. D., & Oshlack, A. (2010). A scaling normalization method for differential expression analysis of RNA-seq data. Genome Biology, 11, R25. https://doi.org/10.1186/gb-2010-11-3-r25

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Wilkerson, M. D., & Hayes, D. N. (2010). ConsensusClusterPlus: A class discovery tool with confidence assessments and item tracking. Bioinformatics, 26, 1572–1573. https://doi.org/10.1093/bioinformatics/btq170

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Simon, N., Friedman, J., Hastie, T., & Tibshirani, R. (2011). Regularization paths for Cox’s proportional hazards Model via coordinate descent. Journal of Statistical Software, 39, 1–13. https://doi.org/10.18637/jss.v039.i05

    Article  PubMed  PubMed Central  Google Scholar 

  21. David, C. C., & Jacobs, D. J. (2014). Principal component analysis: A method for determining the essential dynamics of proteins. Methods in Molecular Biology, 1084, 193–226. https://doi.org/10.1007/978-1-62703-658-0_11

    Article  CAS  PubMed  Google Scholar 

  22. Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., & Mesirov, J. P. (2005). Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles. Proceedings of the National Academy of Sciences USA, 102, 15545–15550. https://doi.org/10.1073/pnas.0506580102

    Article  CAS  Google Scholar 

  23. Barbie, D. A., Tamayo, P., Boehm, J. S., Kim, S. Y., Moody, S. E., Dunn, I. F., Schinzel, A. C., Sandy, P., Meylan, E., Scholl, C., Fröhling, S., Chan, E. M., Sos, M. L., et al. (2009). Systematic RNA interference reveals that oncogenic KRAS-driven cancers require TBK1. Nature, 462, 108–112. https://doi.org/10.1038/nature08460

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Bindea, G., Mlecnik, B., Tosolini, M., Kirilovsky, A., Waldner, M., Obenauf, A. C., Angell, H., Fredriksen, T., Lafontaine, L., Berger, A., Bruneval, P., Fridman, W. H., Becker, C., et al. (2013). Spatiotemporal dynamics of intratumoral immune cells reveal the immune landscape in human cancer. Immunity, 39, 782–795. https://doi.org/10.1016/j.immuni.2013.10.003

    Article  CAS  PubMed  Google Scholar 

  25. Lu, C., Rong, D., Zhang, B., Zheng, W., Wang, X., Chen, Z., & Tang, W. (2019). Current perspectives on the immunosuppressive tumor microenvironment in hepatocellular carcinoma: Challenges and opportunities. Molecular Cancer, 18, 130. https://doi.org/10.1186/s12943-019-1047-6

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Guichard, C., Amaddeo, G., Imbeaud, S., Ladeiro, Y., Pelletier, L., Maad, I. B., Calderaro, J., Bioulac-Sage, P., Letexier, M., Degos, F., Clément, B., Balabaud, C., Chevet, E., et al. (2012). Integrated analysis of somatic mutations and focal copy-number changes identifies key genes and pathways in hepatocellular carcinoma. Nature Genetics, 44, 694–698. https://doi.org/10.1038/ng.2256

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. de Bessa Garcia, S. A., Araújo, M., Pereira, T., Mouta, J., & Freitas, R. (2020). HOX genes function in breast cancer development. Biochimica et Biophysica Acta - Reviews on Cancer, 1873, 188358. https://doi.org/10.1016/j.bbcan.2020.188358

    Article  CAS  PubMed  Google Scholar 

  28. Hammoud, S. S., Nix, D. A., Zhang, H., Purwar, J., Carrell, D. T., & Cairns, B. R. (2009). Distinctive chromatin in human sperm packages genes for embryo development. Nature, 460, 473–478. https://doi.org/10.1038/nature08162

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Kapur, R. P., Gershon, M. D., Milla, P. J., & Pachnis, V. (2004). The influence of Hox genes and three intercellular signalling pathways on enteric neuromuscular development. Neurogastroenterology and Motility, 16(Suppl 1), 8–13. https://doi.org/10.1111/j.1743-3150.2004.00467.x

    Article  PubMed  Google Scholar 

  30. Pinto, P. B., Espinosa-Vázquez, J. M., Rivas, M. L., & Hombría, J. C. (2015). JAK/STAT and Hox dynamic interactions in an organogenetic gene cascade. PLoS Genet., 11, e1005412. https://doi.org/10.1371/journal.pgen.1005412

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Memic, F., Knoflach, V., Morarach, K., Sadler, R., Laranjeira, C., Hjerling-Leffler, J., Sundström, E., Pachnis, V., & Marklund, U. (2018). Transcription and signaling regulators in developing neuronal subtypes of mouse and human enteric nervous system. Gastroenterology, 154, 624–636. https://doi.org/10.1053/j.gastro.2017.10.005

    Article  CAS  PubMed  Google Scholar 

  32. Domsch, K., Papagiannouli, F., & Lohmann, I. (2015). The HOX-apoptosis regulatory interplay in development and disease. Current Topics in Developmental Biology, 114, 121–158. https://doi.org/10.1016/bs.ctdb.2015.07.014

    Article  CAS  PubMed  Google Scholar 

  33. Li, B., Huang, Q., & Wei, G. H. (2019). he role of HOX transcription factors in cancer predisposition and progression. Cancers (Basel), 11. https://doi.org/10.3390/cancers11040528.

  34. Tang, B., Qi, G., Sun, X., Tang, F., Yuan, S., Wang, Z., Liang, X., Li, B., Yu, S., Liu, J., Huang, Q., Wei, Y., Zhai, R., et al. (2016). HOXA7 plays a critical role in metastasis of liver cancer associated with activation of Snail. Molecular Cancer, 15, 57. https://doi.org/10.1186/s12943-016-0540-4

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Yang, L., Peng, X., Li, Y., Zhang, X., Ma, Y., Wu, C., Fan, Q., Wei, S., Li, H., & Liu, J. (2019). Long non-coding RNA HOTAIR promotes exosome secretion by regulating RAB35 and SNAP23 in hepatocellular carcinoma. Molecular Cancer, 18, 78. https://doi.org/10.1186/s12943-019-0990-6

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Guo, Y., Peng, Y., Gao, D., Zhang, M., Yang, W., Linghu, E., Herman, J. G., Fuks, F., Dong, G., & Guo, M. (2017). Silencing HOXD10 by promoter region hypermethylation activates ERK signaling in hepatocellular carcinoma. Clinical Epigenetics, 9, 116. https://doi.org/10.1186/s13148-017-0412-9

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Xu, F., Jin, T., Zhu, Y., & Dai, C. (2018). Immune checkpoint therapy in liver cancer. Journal of Experimental & Clinical Cancer Research, 37, 110. https://doi.org/10.1186/s13046-018-0777-4

    Article  CAS  Google Scholar 

  38. Wu, Q., Zhou, W., Yin, S., Zhou, Y., Chen, T., Qian, J., Su, R., Hong, L., Lu, H., Zhang, F., Xie, H., Zhou, L., & Zheng, S. (2019). Blocking triggering receptor expressed on myeloid cells-1-positive tumor-associated macrophages induced by hypoxia reverses immunosuppression and anti-programmed cell death ligand 1 resistance in liver cancer. Hepatology, 70, 198–214. https://doi.org/10.1002/hep.30593

    Article  CAS  PubMed  Google Scholar 

  39. Jain, V., Gupta, A., Pawar, V. K., Asthana, S., Jaiswal, A. K., Dube, A., & Chourasia, M. K. (2014). Chitosan-assisted immunotherapy for intervention of experimental leishmaniasis via amphotericin B-loaded solid lipid nanoparticles. Applied Biochemistry and Biotechnology, 174, 1309–1330. https://doi.org/10.1007/s12010-014-1084-y

    Article  CAS  PubMed  Google Scholar 

  40. ( 2017). Comprehensive and integrative genomic characterization of hepatocellular carcinoma. Cell, 169, 1327-41.e23https://doi.org/10.1016/j.cell.2017.05.046

  41. Mantovani, A., Allavena, P., Sica, A., & Balkwill, F. (2008). Cancer-related inflammation. Nature, 454, 436–444. https://doi.org/10.1038/nature07205

    Article  CAS  PubMed  Google Scholar 

  42. Bronte, V., Brandau, S., Chen, S. H., Colombo, M. P., Frey, A. B., Greten, T. F., Mandruzzato, S., Murray, P. J., Ochoa, A., Ostrand-Rosenberg, S., Rodriguez, P. C., Sica, A., Umansky, V., et al. (2016). Recommendations for myeloid-derived suppressor cell nomenclature and characterization standards. Nature Communications, 7, 12150. https://doi.org/10.1038/ncomms12150

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Chaubey, N., & Ghosh, S. S. (2015). Overexpression of granulocyte macrophage colony stimulating factor in breast cancer cells leads towards drug sensitization. Applied Biochemistry and Biotechnology, 175, 1948–1959. https://doi.org/10.1007/s12010-014-1373-5

    Article  CAS  PubMed  Google Scholar 

  44. Fridman, W. H., Pagès, F., Sautès-Fridman, C., & Galon, J. (2012). The immune contexture in human tumours: Impact on clinical outcome. Nature Reviews Cancer, 12, 298–306. https://doi.org/10.1038/nrc3245

    Article  CAS  PubMed  Google Scholar 

  45. Fridman, W. H., Zitvogel, L., Sautès-Fridman, C., & Kroemer, G. (2017). The immune contexture in cancer prognosis and treatment. Nature Reviews. Clinical Oncology, 14, 717–734. https://doi.org/10.1038/nrclinonc.2017.101

    Article  CAS  PubMed  Google Scholar 

  46. Chen, X., & Zhang, L. (2023). Integrative analysis revealed LINC00847 as a potential target of tumor immunotherapy. Applied Biochemistry and Biotechnology. https://doi.org/10.1007/s12010-023-04387-z

    Article  PubMed  Google Scholar 

  47. Zhang, Y. L., Li, J., Mo, H. Y., Qiu, F., Zheng, L. M., Qian, C. N., & Zeng, Y. X. (2010). Different subsets of tumor infiltrating lymphocytes correlate with NPC progression in different ways. Molecular Cancer, 9, 4. https://doi.org/10.1186/1476-4598-9-4

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Tosolini, M., Kirilovsky, A., Mlecnik, B., Fredriksen, T., Mauger, S., Bindea, G., Berger, A., Bruneval, P., Fridman, W. H., Pagès, F., & Galon, J. (2011). Clinical impact of different classes of infiltrating T cytotoxic and helper cells (Th1, th2, treg, th17) in patients with colorectal cancer. Cancer Research, 71, 1263–1271. https://doi.org/10.1158/0008-5472.Can-10-2907

    Article  CAS  PubMed  Google Scholar 

  49. Winerdal, M. E., Marits, P., Winerdal, M., Hasan, M., Rosenblatt, R., Tolf, A., Selling, K., Sherif, A., & Winqvist, O. (2011). FOXP3 and survival in urinary bladder cancer. BJU International, 108, 1672–1678. https://doi.org/10.1111/j.1464-410X.2010.10020.x

    Article  CAS  PubMed  Google Scholar 

  50. Shiraki, T., Takayama, E., Magari, H., Nakata, T., Maekita, T., Enomoto, S., Mori, Y., Shingaki, N., Moribata, K., Deguchi, H., Ueda, K., Inoue, I., Mizuno-Kamiya, M., et al. (2011). Altered cytokine levels and increased CD4+CD57+ T cells in the peripheral blood of hepatitis C virus-related hepatocellular carcinoma patients. Oncology Reports, 26, 201–208. https://doi.org/10.3892/or.2011.1258

    Article  CAS  PubMed  Google Scholar 

  51. Mantovani, A. (2011). B cells and macrophages in cancer: Yin and yang. Nature Medicine, 17, 285–286. https://doi.org/10.1038/nm0311-285

    Article  CAS  PubMed  Google Scholar 

  52. Olkhanud, P. B., Damdinsuren, B., Bodogai, M., Gress, R. E., Sen, R., Wejksza, K., Malchinkhuu, E., Wersto, R. P., & Biragyn, A. (2011). Tumor-evoked regulatory B cells promote breast cancer metastasis by converting resting CD4+ T cells to T-regulatory cells. Cancer Research, 71, 3505–3515. https://doi.org/10.1158/0008-5472.Can-10-4316

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. DiLillo, D. J., Yanaba, K., & Tedder, T. F. (2010). B cells are required for optimal CD4+ and CD8+ T cell tumor immunity: Therapeutic B cell depletion enhances B16 melanoma growth in mice. The Journal of Immunology, 184, 4006–4016. https://doi.org/10.4049/jimmunol.0903009

    Article  CAS  PubMed  Google Scholar 

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Authors and Affiliations

  1. Department of Interventional Radiology, Cancer Hospital of Shantou University Medical College, Shantou, China

    Changhong Yi

  2. Department of Interventional, Jingzhou Hospital Affiliated to Yangtze University, Jingzhou, China

    Wei Wei, Maolin Wan, Ya Chen, Bo Zhang & Wenze Wu

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  1. Changhong Yi
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  2. Wei Wei
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  4. Ya Chen
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Contributions

Changhong Yi, Wei Wei, and Wenze Wu: conceived and designed the experiments; performed the experiments; analyzed and interpreted the data; contributed reagents, materials, analysis tools, or data; and wrote the paper. Maolin Wan and Ya Chen: conceived and designed the experiments; analyzed and interpreted the data; and wrote the paper. Bo Zhang and Benhong Zhou: analyzed and interpreted the data and wrote the paper.

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Correspondence to Wenze Wu.

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Yi, C., Wei, W., Wan, M. et al. Expression Patterns of HOX Gene Family Defines Tumor Microenvironment and Immunotherapy in Hepatocellular Carcinoma. Appl Biochem Biotechnol 195, 5072–5093 (2023). https://doi.org/10.1007/s12010-023-04443-8

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