Chapter 1 20 40. Amgad, M. et al. Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group. npj Breast Cancer 6, (2020). 41. Steele, K. E. et al. Measuring multiple parameters of CD8+ tumor-infiltrating lymphocytes in human cancers by image analysis. J. Immunother. Cancer 6, 1–14 (2018). 42. Koelzer, V. H. et al. Digital image analysis improves precision of PD-L1 scoring in cutaneous melanoma. Histopathology 73, 397–406 (2018). 43. Veldman-Jones, M. H. et al. Evaluating robustness and sensitivity of the nanostring technologies ncounter platform to enable multiplexed gene expression analysis of clinical samples. Cancer Res. 75, 2587–2593 (2015). 44. Ayers, M. et al. blockade IFN- γ – related mRNA profile predicts clinical response to PD-1 blockade. J. Clin. Invest. 127, 2930–2940 (2017). 45. Cristescu, R. et al. Pan-tumor genomic biomarkers for PD-1 checkpoint blockade-based immunotherapy. Science (80-. ). 362, (2018). 46. Damotte, D. et al. The tumor inflammation signature (TIS) is associated with anti-PD-1 treatment benefit in the CERTIM pan-cancer cohort. J. Transl. Med. 17, 1–10 (2019). 47. Mints, M. et al. Tumour inflammation signature and expression of S100A12 and HLA class I improve survival in HPV-negative hypopharyngeal cancer. Sci. Rep. 11, 1–11 (2021). 48. Rizvi, H. et al. Molecular determinants of response to anti-programmed cell death (PD)-1 and anti-programmed death-ligand 1 (PD-L1) blockade in patients with non-small-cell lung cancer profiled with targeted next-generation sequencing. J. Clin. Oncol. 36, 633–641 (2018). 49. Hellmann, M. D. et al. Genomic Features of Response to Combination Immunotherapy in Patients with Advanced Non-Small-Cell Lung Cancer. Cancer Cell 33, 843-852.e4 (2018). 50. Bettegowda, C. et al. Detection of circulating tumor DNA in early- and late-stage human malignancies. Sci. Transl. Med. 6, 1–12 (2014). 51. Nikanjam, M., Kato, S. & Kurzrock, R. Liquid biopsy: current technology and clinical applications. J. Hematol. Oncol. 15, 1–14 (2022). 52. Siravegna, G., Marsoni, S., Siena, S. & Bardelli, A. Integrating liquid biopsies into the management of cancer. Nat. Rev. Clin. Oncol. 14, 531–548 (2017). 53. Froudarakis, M. E. Pleural effusion in lung cancer: More questions than answers. Respiration 83, 367–376 (2012). 54. Lin, J. et al. Detection of EGFR mutation in supernatant, cell pellets of pleural effusion and tumor tissues from non-small cell lung cancer patients by high resolution melting analysis and sequencing. Int. J. Clin. Exp. Pathol. 7, 8813–8822 (2014). 55. Liu, D. et al. Malignant pleural effusion supernatants are substitutes for metastatic pleural tumor tissues in egfr mutation test in patients with advanced lung adenocarcinoma. PLOS One 9, 1–5 (2014). 56. Lee, J. S. et al. Liquid biopsy using the supernatant of a pleural effusion for EGFR genotyping in pulmonary adenocarcinoma patients: A comparison between cell-free DNA and extracellular vesicle-derived DNA. BMC Cancer 18, 1–8 (2018). 57. Asaka, S. et al. Rapid point-of-care testing for epidermal growth factor receptor gene mutations in patients with lung cancer using cell-free DNA from cytology specimen supernatants. Int. J. Oncol. 52, 2110–2118 (2018). 58. Kawahara, A. et al. A Combined test using both cell sediment and supernatant cell-free DNA in pleural effusion shows increased sensitivity in detecting activating EGFR mutation in lung cancer patients. Cytopathology 29, 150–155 (2018).
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