Skip to main content
SpringerLink
Log in

Prospective Identification of Prognostic Hot-Spot Mutant Gene Signatures for Leukemia: A Computational Study Based on Integrative Analysis of TCGA and cBioPortal Data

  • Original Paper
  • Published:
Molecular Biotechnology Aims and scope Submit manuscript

Abstract

The advantage of an increasing amount of bioinformatics data on leukemias intrigued us to explore the hot-spot mutation profiles and investigate the implications of those hot-spot mutations in patient survival. We retrieved somatic mutations and their distribution in protein domains through data analysis of The Cancer Genome Atlas and cBioPortal databases. After determining differentially expressed mutant genes related to leukemia, we further conducted principal component analysis and single-factor Cox regression analyses. Moreover, survival analysis was performed for the obtained candidate genes, followed by a multi-factor Cox proportional hazard model method for the impacts of the candidate genes on the survival and prognosis of patients with leukemia. At last, the signaling pathways involved in leukemia were investigated by gene set enrichment analysis. There were 223 somatic missense mutation hot-spots identified with pertinence to leukemia, which were distributed in 41 genes. Differential expression in leukemia was witnessed in 39 genes. We found a close correlation between seven genes and the prognosis of leukemia patients, among which, three genes could significantly influence the survival rate. In addition, among these three genes, CD74 and P2RY8 were highlighted due to close pertinence with survival conditions of leukemia patients. Finally, data suggested that B cell receptor, Hedgehog, and TGF-beta signaling pathways were enriched in low-hazard patients. In conclusion, these data underline the involvement of hot-spot mutations of CD74 and P2RY8 genes in survival status of leukemia patients, highlighting their as novel therapeutic targets or prognostic indicators for leukemia patients.

Graphical Abstract

Summary of Graphical Abstract: We identified 223 leukemia-associated somatic missense mutation hotspots concentrated in 41 different genes from 2297 leukemia patients in the TCGA database. Differential analysis of leukemic and normal samples from the TCGA and GTEx databases revealed that 39 of these 41 genes showed significant differential expression in leukemia. These 39 genes were subjected to PCA analysis, univariate Cox analysis, survival analysis, multivariate Cox regression analysis, GSEA pathway enrichment analysis, and then the association with leukemia survival prognosis and related pathways were investigated.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

Data Availability

The data and materials of the study can be obtained from the corresponding author upon request.

References

  1. Bispo, J. A. B., Pinheiro, P. S., & Kobetz, E. K. (2020). Epidemiology and Etiology of Leukemia and Lymphoma. Cold Spring Harbor Perspectives in Medicine, 10, a034819.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Di Martino, L., Tosello, V., Peroni, E., & Piovan, E. (2021). Insights on Metabolic Reprogramming and Its Therapeutic Potential in Acute Leukemia. International Journal of Molecular Sciences, 22, 8738.

    Article  PubMed  PubMed Central  Google Scholar 

  3. McNeer, N. A., Philip, J., Geiger, H., Ries, R. E., Lavallee, V. P., Walsh, M., Shah, M., Arora, K., Emde, A. K., Robine, N., Alonzo, T. A., Kolb, E. A., Gamis, A. S., Smith, M., Gerhard, D. S., Guidry-Auvil, J., Meshinchi, S., & Kentsis, A. (2019). Genetic mechanisms of primary chemotherapy resistance in pediatric acute myeloid leukemia. Leukemia, 33, 1934–1943.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Arber, D. A., Orazi, A., Hasserjian, R., Thiele, J., Borowitz, M. J., Le Beau, M. M., Bloomfield, C. D., Cazzola, M., & Vardiman, J. W. (2016). The 2016 revision to the World Health Organization classification of myeloid neoplasms and acute leukemia. Blood, 127, 2391–2405.

    Article  CAS  PubMed  Google Scholar 

  5. Cazzola, M. (2016). Introduction to a review series: The 2016 revision of the WHO classification of tumors of hematopoietic and lymphoid tissues. Blood, 127, 2361–2364.

    Article  CAS  PubMed  Google Scholar 

  6. Kantarjian, H., Kadia, T., DiNardo, C., Daver, N., Borthakur, G., Jabbour, E., Garcia-Manero, G., Konopleva, M., & Ravandi, F. (2021). Acute myeloid leukemia: Current progress and future directions. Blood Cancer Journal, 11, 41.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Berman, E. (2022). How I treat chronic-phase chronic myelogenous leukemia. Blood, 139, 3138–3147.

    Article  CAS  PubMed  Google Scholar 

  8. Srivastava, P. K. (2015). Neoepitopes of cancers: Looking Back. Looking Ahead. Cancer Immunol Res., 3, 969–977.

    Article  CAS  PubMed  Google Scholar 

  9. Chang, T. C., Carter, R. A., Li, Y., Li, Y., Wang, H., Edmonson, M. N., Chen, X., Arnold, P., Geiger, T. L., Wu, G., Peng, J., Dyer, M., Downing, J. R., Green, D. R., Thomas, P. G., & Zhang, J. (2017). The neoepitope landscape in pediatric cancers. Genome Med., 9, 78.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Roberts, K. G., & Mullighan, C. G. (2015). Genomics in acute lymphoblastic leukaemia: Insights and treatment implications. Nature Reviews Clinical Oncology, 12, 344–357.

    Article  CAS  PubMed  Google Scholar 

  11. Nemtsova, M. V., Kalinkin, A. I., Kuznetsova, E. B., Bure, I. V., Alekseeva, E. A., Bykov, I. I., Khorobrykh, T. V., Mikhaylenko, D. S., Tanas, A. S., Kutsev, S. I., Zaletaev, D. V., & Strelnikov, V. V. (2020). Clinical relevance of somatic mutations in main driver genes detected in gastric cancer patients by next-generation DNA sequencing. Science and Reports, 10, 504.

    Article  CAS  Google Scholar 

  12. Patel, B. J., Przychodzen, B., Thota, S., Radivoyevitch, T., Visconte, V., Kuzmanovic, T., Clemente, M., Hirsch, C., Morawski, A., Souaid, R., Saygin, C., Nazha, A., Demarest, B., LaFramboise, T., Sakaguchi, H., Kojima, S., Carraway, H. E., Ogawa, S., Makishima, H., … Maciejewski, J. P. (2017). Genomic determinants of chronic myelomonocytic leukemia. Leukemia, 31, 2815–2823.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Buckner, J., Giannini, C., Eckel-Passow, J., Lachance, D., Parney, I., Laack, N., & Jenkins, R. (2017). Management of diffuse low-grade gliomas in adults - use of molecular diagnostics. Nature Reviews. Neurology, 13, 340–351.

    Article  CAS  PubMed  Google Scholar 

  14. Stengel, A., Baer, C., Walter, W., Meggendorfer, M., Kern, W., Haferlach, T., & Haferlach, C. (2021). Mutational patterns and their correlation to CHIP-related mutations and age in hematological malignancies. Blood Advances, 5, 4426–4434.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Maifrede, S., Le, B. V., Nieborowska-Skorska, M., Golovine, K., Sullivan-Reed, K., Dunuwille, W. M. B., Nacson, J., Hulse, M., Keith, K., Madzo, J., Caruso, L. B., Gazze, Z., Lian, Z., Padella, A., Chitrala, K. N., Bartholdy, B. A., Matlawska-Wasowska, K., Di Marcantonio, D., Simonetti, G., … Skorski, T. (2021). TET2 and DNMT3A Mutations Exert Divergent Effects on DNA Repair and Sensitivity of Leukemia Cells to PARP Inhibitors. Cancer Research, 81, 5089–5101.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Kosaki, R., Terashima, H., Kubota, M., & Kosaki, K. (2017). Acute myeloid leukemia-associated DNMT3A p.Arg882His mutation in a patient with Tatton-Brown-Rahman overgrowth syndrome as a constitutional mutation. American Journal of Medical Genetics. Part A, 173, 250–253.

    Article  CAS  PubMed  Google Scholar 

  17. Patel, J. P., Gonen, M., Figueroa, M. E., Fernandez, H., Sun, Z., Racevskis, J., Van Vlierberghe, P., Dolgalev, I., Thomas, S., Aminova, O., Huberman, K., Cheng, J., Viale, A., Socci, N. D., Heguy, A., Cherry, A., Vance, G., Higgins, R. R., Ketterling, R. P., … Levine, R. L. (2012). Prognostic relevance of integrated genetic profiling in acute myeloid leukemia. New England Journal of Medicine, 366, 1079–1089.

    Article  CAS  PubMed  Google Scholar 

  18. Papaemmanuil, E., Gerstung, M., Bullinger, L., Gaidzik, V. I., Paschka, P., Roberts, N. D., Potter, N. E., Heuser, M., Thol, F., Bolli, N., Gundem, G., Van Loo, P., Martincorena, I., Ganly, P., Mudie, L., McLaren, S., O’Meara, S., Raine, K., Jones, D. R., … Campbell, P. J. (2016). Genomic Classification and Prognosis in Acute Myeloid Leukemia. New England Journal of Medicine, 374, 2209–2221.

    Article  CAS  PubMed  Google Scholar 

  19. Kunchala, P., Kuravi, S., Jensen, R., McGuirk, J., & Balusu, R. (2018). When the good go bad: Mutant NPM1 in acute myeloid leukemia. Blood Reviews, 32, 167–183.

    Article  CAS  PubMed  Google Scholar 

  20. Dohner, H., Estey, E., Grimwade, D., Amadori, S., Appelbaum, F. R., Buchner, T., Dombret, H., Ebert, B. L., Fenaux, P., Larson, R. A., Levine, R. L., Lo-Coco, F., Naoe, T., Niederwieser, D., Ossenkoppele, G. J., Sanz, M., Sierra, J., Tallman, M. S., Tien, H. F., … Bloomfield, C. D. (2017). Diagnosis and management of AML in adults: 2017 ELN recommendations from an international expert panel. Blood, 129, 424–447.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Ley, T. J., Miller, C., Ding, L., Raphael, B. J., Mungall, A. J., Robertson, A., Hoadley, K., Triche, T. J., Jr., Laird, P. W., Baty, J. D., Fulton, L. L., Fulton, R., Heath, S. E., Kalicki-Veizer, J., Kandoth, C., Klco, J. M., Koboldt, D. C., Kanchi, K. L., Kulkarni, S., … Cancer Genome Atlas Research. (2013). Genomic and epigenomic landscapes of adult de novo acute myeloid leukemia. New England Journal of Medicine, 368, 2059–2074.

    Article  PubMed  Google Scholar 

  22. Tyner, J. W., Tognon, C. E., Bottomly, D., Wilmot, B., Kurtz, S. E., Savage, S. L., Long, N., Schultz, A. R., Traer, E., Abel, M., Agarwal, A., Blucher, A., Borate, U., Bryant, J., Burke, R., Carlos, A., Carpenter, R., Carroll, J., Chang, B. H.,…Druker, B. J. (2018). Functional genomic landscape of acute myeloid leukaemia. Nature, 562, 526–531.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Cerami, E., Gao, J., Dogrusoz, U., Gross, B. E., Sumer, S. O., Aksoy, B. A., Jacobsen, A., Byrne, C. J., Heuer, M. L., Larsson, E., Antipin, Y., Reva, B., Goldberg, A. P., Sander, C., & Schultz, N. (2012). The cBio cancer genomics portal: An open platform for exploring multidimensional cancer genomics data. Cancer Discovery, 2, 401–404.

    Article  PubMed  Google Scholar 

  24. Nabavizadeh, S. A., Stein, J., & Mohan, S. (2016). Neuroimaging in Leukemia. Hematology/oncology Clinics of North America, 30, 823–842.

    Article  PubMed  Google Scholar 

  25. Porto, L., Kieslich, M., Schwabe, D., Zanella, F. E., & Lanfermann, H. (2004). Granulocytic sarcoma in children. Neuroradiology, 46, 374–377.

    Article  CAS  PubMed  Google Scholar 

  26. Porta-Pardo, E., Garcia-Alonso, L., Hrabe, T., Dopazo, J., & Godzik, A. (2015). A pan-cancer catalogue of cancer driver protein interaction interfaces. PLoS Computational Biology, 11, e1004518.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Bartels, S., Hasemeier, B., Vogtmann, J., Schipper, E., Busche, G., Schlue, J., Kreipe, H., & Lehmann, U. (2020). Feasibility of Combined Detection of Gene Mutations and Fusion Transcripts in Bone Marrow Trephines from Leukemic Neoplasms. The Journal of Molecular Diagnostics, 22, 591–598.

    Article  CAS  PubMed  Google Scholar 

  28. Wan, T. S. (2017). Cancer cytogenetics: An Introduction. Methods in Molecular Biology, 1541, 1–10.

    Article  CAS  PubMed  Google Scholar 

  29. Ganguly, B. B., & Kadam, N. N. (2016). Mutations of myelodysplastic syndromes (MDS): An update. Mutation Research, Reviews in Mutation Research, 769, 47–62.

    Article  CAS  PubMed  Google Scholar 

  30. Huang, M. E., Ye, Y. C., Chen, S. R., Chai, J. R., Lu, J. X., Zhoa, L., Gu, L. J., & Wang, Z. Y. (1988). Use of all-trans retinoic acid in the treatment of acute promyelocytic leukemia. Blood, 72, 567–572.

    Article  CAS  PubMed  Google Scholar 

  31. Weinhold, N., Jacobsen, A., Schultz, N., Sander, C., & Lee, W. (2014). Genome-wide analysis of noncoding regulatory mutations in cancer. Nature Genetics, 46, 1160–1165.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Diederichs, S., Bartsch, L., Berkmann, J. C., Frose, K., Heitmann, J., Hoppe, C., Iggena, D., Jazmati, D., Karschnia, P., Linsenmeier, M., Maulhardt, T., Mohrmann, L., Morstein, J., Paffenholz, S. V., Ropenack, P., Ruckert, T., Sandig, L., Schell, M., Steinmann, A., … Wullenkord, R. (2016). The dark matter of the cancer genome: Aberrations in regulatory elements, untranslated regions, splice sites, non-coding RNA and synonymous mutations. EMBO Molecular Medicine, 8, 442–457.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Mansour, M. R., Abraham, B. J., Anders, L., Berezovskaya, A., Gutierrez, A., Durbin, A. D., Etchin, J., Lawton, L., Sallan, S. E., Silverman, L. B., Loh, M. L., Hunger, S. P., Sanda, T., Young, R. A., & Look, A. T. (2014). Oncogene regulation. An oncogenic super-enhancer formed through somatic mutation of a noncoding intergenic element. Science, 346, 1373–1377.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Aypar, U., Taylor, J., Garcia, J. S., Momeni-Boroujeni, A., Gao, Q., Baik, J., Londono, D., Benayed, R., Sigler, A., Haddadin, M., Penson, A. V., Arcila, M. E., Mullaney, K., Sukhadia, P., Quesada, A. E., Roshal, M., Cullen, N., Lako, A., Rodig, S. J., … Ho, C. (2020). P2RY8-CRLF2Fusion-positive acute myeloid leukemia with myelodysplasia-related changes: Response to novel therapy. JCO Precision Oncology, 4, 152–160.

    Article  PubMed  Google Scholar 

  35. Dou, H., Chen, X., Huang, Y., Su, Y., Lu, L., Yu, J., Yin, Y., & Bao, L. (2017). Prognostic significance of P2RY8-CRLF2 and CRLF2 overexpression may vary across risk subgroups of childhood B-cell acute lymphoblastic leukemia. Genes, Chromosomes & Cancer, 56, 135–146.

    Article  CAS  Google Scholar 

  36. Vesely, C., Frech, C., Eckert, C., Cario, G., Mecklenbrauker, A., Zur Stadt, U., Nebral, K., Kraler, F., Fischer, S., Attarbaschi, A., Schuster, M., Bock, C., Cave, H., von Stackelberg, A., Schrappe, M., Horstmann, M. A., Mann, G., Haas, O. A., & Panzer-Grumayer, R. (2017). Genomic and transcriptional landscape of P2RY8-CRLF2-positive childhood acute lymphoblastic leukemia. Leukemia, 31, 1491–1501.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Pan, C., Chun, J., Li, D., Boese, A. C., Li, J., Kang, J., Umano, A., Jiang, Y., Song, L., Magliocca, K. R., Chen, Z. G., Saba, N. F., Shin, D. M., Owonikoko, T. K., Lonial, S., Jin, L., & Kang, S. (2019). Hsp90B enhances MAST1-mediated cisplatin resistance by protecting MAST1 from proteosomal degradation. The Journal of Clinical Investigation, 129, 4110–4123.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Jin, L., Chun, J., Pan, C., Li, D., Lin, R., Alesi, G. N., Wang, X., Kang, H. B., Song, L., Wang, D., Zhang, G., Fan, J., Boggon, T. J., Zhou, L., Kowalski, J., Qu, C. K., Steuer, C. E., Chen, G. Z., Saba, N. F., … Kang, S. (2018). MAST1 drives cisplatin resistance in human cancers by rewiring cRaf-Independent MEK Activation. Cancer Cell, 34(315–330), e317.

    Google Scholar 

  39. Farr, L., Ghosh, S., & Moonah, S. (2020). Role of MIF Cytokine/CD74 Receptor Pathway in Protecting Against Injury and Promoting Repair. Frontiers in Immunology, 11, 1273.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Barthel, R., Fedorchenko, O., Velmans, T., Rosen, N., Nguyen, P. H., Reinart, N., Florin, A., Herling, M., Hallek, M., & Fingerle-Rowson, G. (2020). CD74 is dispensable for development of chronic lymphocytic leukemia in Emicro-TCL1 transgenic mice. Leukaemia & Lymphoma, 61, 2799–2810.

    Article  CAS  Google Scholar 

  41. Shachar, I., & Haran, M. (2011). The secret second life of an innocent chaperone: The story of CD74 and B cell/chronic lymphocytic leukemia cell survival. Leukaemia & Lymphoma, 52, 1446–1454.

    Article  CAS  Google Scholar 

  42. Zeng, H., Wu, H., Yan, M., Tang, L., Guo, X., & Zhao, X. (2020). Characterization of a 4 lncRNAs-based prognostic risk scoring system in adults with acute myeloid leukemia. Leukemia Research, 88, 106261.

    Article  CAS  PubMed  Google Scholar 

  43. Ma, G. S. (2019). Hydration status and health. Zhonghua Yu Fang Yi Xue Za Zhi, 53, 337–341.

    CAS  PubMed  Google Scholar 

  44. Saika, M., Inoue, D., Nagase, R., Sato, N., Tsuchiya, A., Yabushita, T., Kitamura, T., & Goyama, S. (2018). ASXL1 and SETBP1 mutations promote leukaemogenesis by repressing TGFbeta pathway genes through histone deacetylation. Science and Reports, 8, 15873.

    Article  Google Scholar 

  45. Ten Hacken, E., & Burger, J. A. (2016). Microenvironment interactions and B-cell receptor signaling in Chronic Lymphocytic Leukemia: Implications for disease pathogenesis and treatment. Biochimica et Biophysica Acta, 1863, 401–413.

    Article  PubMed  Google Scholar 

  46. Aberger, F., Hutterer, E., Sternberg, C., Del Burgo, P. J., & Hartmann, T. N. (2017). Acute myeloid leukemia - strategies and challenges for targeting oncogenic Hedgehog/GLI signaling. Cell Communication and Signaling: CCS, 15, 8.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Chen, J., Mu, Q., Li, X., Yin, X., Yu, M., Jin, J., Li, C., Zhou, Y., Zhou, J., Suo, S., Lu, D., & Jin, J. (2017). Homoharringtonine targets Smad3 and TGF-beta pathway to inhibit the proliferation of acute myeloid leukemia cells. Oncotarget, 8, 40318–40326.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Hematology, The First People’s Hospital of Yongkang, Affiliated to Hangzhou Medical College, No. 599, Jinshan West Road, Yongkang, Jinhua City, Zhejiang Province, 321300, People’s Republic of China

    Min Zhang, Xianghua Lang, Xinyi Chen & Yuke Lv

Authors
  1. Min Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xianghua Lang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Xinyi Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yuke Lv
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

MZ designed the study. XHL, XYC and YKL collated the data, carried out data analyses and produced the initial draft of the manuscript. YKL contributed to drafting the manuscript. All authors have read and approved the final submitted manuscript.

Corresponding author

Correspondence to Min Zhang.

Ethics declarations

Conflict of interest

No potential conflict of interest was reported by the authors.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (EPS 703 KB)

Supplementary file2 (DOCX 29 KB)

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, M., Lang, X., Chen, X. et al. Prospective Identification of Prognostic Hot-Spot Mutant Gene Signatures for Leukemia: A Computational Study Based on Integrative Analysis of TCGA and cBioPortal Data. Mol Biotechnol 65, 1898–1912 (2023). https://doi.org/10.1007/s12033-023-00704-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12033-023-00704-3

Keywords

Search

Navigation