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Comprehensive characterization of NK cell-related genes in cutaneous melanoma identified a novel prognostic signature for predicting the prognosis, immunotherapy, and chemotherapy efficacy

Haili Ma, Jian Liu, Huan Jin and 3 more

Discover Oncology · 2025

doi:10.1007/s12672-025-03074-1

References 67

  1. 1.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  2. 2.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  3. 3.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  4. 4.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  5. 5.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  6. 6.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  7. 7.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  8. 8.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  9. 9.
    pRRophetic: An R Package for Prediction of Clinical Chemotherapeutic Response from Tumor Gene Expression Levels · 2014
    No notice
  10. 10.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  11. 11.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  12. 12.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  13. 13.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  14. 14.
    limma powers differential expression analyses for RNA-sequencing and microarray studies · 2015
    No notice
  15. 15.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  16. 16.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  17. 17.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  18. 18.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  19. 19.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  20. 20.
    Time-dependent ROC curve analysis in medical research: current methods and applications · 2017
    No notice
  21. 21.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  22. 22.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  23. 23.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  24. 24.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  25. 25.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  26. 26.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  27. 27.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  28. 28.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  29. 29.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  30. 30.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  31. 31.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  32. 32.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  33. 33.
    Cellular and gene signatures of tumor-infiltrating dendritic cells and natural-killer cells predict prognosis of neuroblastoma · 2020
    No notice
  34. 34.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  35. 35.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  36. 36.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  37. 37.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  38. 38.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  39. 39.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  40. 40.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  41. 41.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  42. 42.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  43. 43.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  44. 44.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  45. 45.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  46. 46.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  47. 47.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  48. 48.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  49. 49.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  50. 50.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  51. 51.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  52. 52.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  53. 53.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  54. 54.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  55. 55.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  56. 56.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  57. 57.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  58. 58.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  59. 59.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  60. 60.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  61. 61.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  62. 62.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  63. 63.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  64. 64.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  65. 65.
    iMLGAM: Integrated Machine Learning and Genetic Algorithm‐driven Multiomics analysis for pan‐cancer immunotherapy response prediction · 2025
    No notice
  66. 66.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

  67. 67.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

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