Hallazgos radiológicos y biomarcadores asociados con mortalidad en pacientes con cáncer
Palabras clave:
Detección precoz del cáncer, biomarcadores de tumor, diagnóstico por imagen, mortalidad.Resumen
El cáncer es un problema de salud pública prioritario en todo el mundo. Se caracteriza por células en desorden que proliferan de forma anormal, lo que resulta en la formación de agregados que afectan a tejidos vecinos; asimismo, es un grupo de patologías que cuentan con un origen variable. En el año 2020 se reportaron 19,3 millones de casos nuevos y 10 millones de muertes. En este contexto, la tomografía computarizada (TC) combinada con biomarcadores séricos se ha convertido en una herramienta clave para predecir resultados como la mortalidad o la progresión tumoral. El uso conjunto de radiología, biomarcadores y herramientas como la inteligencia artificial está mejorando la precisión del pronóstico y la individualización del tratamiento.
Descargas
Referencias
1. Sánchez NC. Conociendo y comprendiendo la célula cancerosa: fisiopatología del cáncer. Rev Med Clin Condes. 2013;24(4):553-62.
2. Binnewies M, Roberts EW, Kersten K, Chan V, Fearon DF, Merad M, et al. Understanding the tumor immune microenvironment (TIME) for efective therapy. Nat Med. 2018;24:541–50.
3. Baci D, Bosi A, Gallazzi M, Rizzi M, Noonan DM, Poggi A, et al. The ovarian cancer Tumor Immune Microenvironment (TIME) as target for therapy: a focus on innate immunity cells as therapeutic efectors. Int J Mol Sci. 2020;21:3125.
4. Yang C, Xia B-R, Zhang Z-C, Zhang Y-J, Lou G, Jin W-L. Immunotherapy for ovarian cancer: adjuvant, combination, and neoadjuvant. Front Immunol. 2020;11:577869.
5. Reschke R, Gajewski TF. CXCL9 and CXCL10 bring the heat to tumors. Sci Immunol. 2022;7:eabq6509.
6. Karin N. CXCR3 Ligands in cancer and autoimmunity, chemoattraction of efector T cells, and beyond. Front Immunol. 2020;11:976.
7. Bergamaschi C, Pandit H, Nagy BA, Stellas D, Jensen SM, Bear J, et al. Heterodimeric IL-15 delays tumor growth and promotes intratumoral CTL and dendritic cell accumulation by a cytokine network involving XCL1, IFN-γ, CXCL9 and CXCL10. J Immunother Cancer. 2020;8:e000599.
8. Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021;71(3):209–49.
9. Lin Y, Zhang Q, Chen H, Liu S, Peng K, Wang X, et al. Multi-cancer early detection based on serum surface-enhanced Raman spectroscopy with deep learning: a large-scale case-control study. BMC Med. 2025;23(1):97. doi: 10.1186/s12916-025-03887-5.
10. Wu H, Liu J, Jing Z, Qi Z, Ma X, Zhao J, et al. Value of serum LncRNA KIF9-AS1 combined with CT signs in the diagnosis of benign and malignant early pulmonary nodules and its correlation with prognosis. J Cardiothorac Surg. 2025 20(1):228. doi: 10.1186/s13019-025-03438-2.
11. Ahmad WKM, Bedau T, Wang Y, Michels S, Rasokat A, Wolf J, Heldwein M, Schallenberg S, Quaas A, Büttner R, Tolkach Y. Development and clinical validation of a prognostic algorithm for stroma-tumor ratio quantification in non-small cell lung cancer. Lung Cancer. 2025 205:108613. doi: 10.1016/j.lungcan.2025.108613.
12. Hao Wen, Dongling Zou. Chinese guidelines for maintenance treatment of epithelial ovarian cancer (2021 edition). Chin J Prac Gynecol Obstet. 2021;37(6):640–9.
13. Torre LA, Trabert B, DeSantis CE, Miller KD, Samimi G, Runowicz CD, et al. Ovarian cancer statistics, 2018. CA Cancer J Clin. 2018;68:284–96.
14. Xia LY, Cao XC, Yu Y. Effect of HER2-low expression on the efficacy of neoadjuvant chemotherapy in triple-negative breast cancer. Sci Rep. 2025:19595. doi: 10.1038/s41598-025-03487-6.
15. Bleyer A, Welch HG. Efect of three decades of screening mammography on breast-cancer incidence. N Engl J Med. 2012;367(21):1998–2005.
16. Nishihara R, Wu K, Lochhead P, Morikawa T, Liao X, Qian ZR, et al. Longterm colorectal-cancer incidence and mortality after lower endoscopy. N Engl J Med. 2013;369(12):1095–105.
17. Huang KL, Wang SY, Lu WC, Chang YH, Su J, Lu YT. Efects of lowdose computed tomography on lung cancer screening: a systematic review, meta-analysis, and trial sequential analysis. BMC Pulm Med. 2019;19(1):126.
18. Zhang Y, Chen H, Lin D, Lin Z, Shi J, Gao H, et al. Comparison of [99mTc]Tc-FAPI SPECT/CT and [18F]FDG PET/CT as predictive biomarkers for immunotherapy response in gastrointestinal cancer. Sci Rep. 2025:16674. doi: 10.1038/s41598-025-01577-z.
19. Saba A, Ishaqi MSQ, Khan MS, Manzoor A, Ali SA. The Predictive Model of Suboptimal Primary Debulking Surgery among Women with Ovarian Cancer Using Pre-Operative Computerized Tomography, Tumor Markers and Comparison with the Intraoperative Findings: An Experience in Tertiary Care Hospital of Pakistan. Asian Pac J Cancer Prev. 2025;26(5):1671-1679. doi: 10.31557/APJCP.2025.26.5.1671.
20. Wright AA, Bohlke K, Armstrong DK, Bookman MA, Cliby WA, Coleman RL, et al. Neoadjuvant chemotherapy for newly diagnosed, advanced ovarian cancer: Society of Gynecologic Oncology and American Society of Clinical Oncology clinical practice guideline. Gynecol Oncol. 2016;143(1):3-15. https://doi.org/10.1016/j. ygyno.2016.05.022.
21. Janco JM, Glaser G, Kim B, McGree ME, Weaver AL, Cliby WA, et al. Development of a prediction model for residual disease in newly diagnosed advanced ovarian cancer. Gynecol Oncol. 2015;138(1):70-7. https://doi.org/10.1016/j. ygyno.2015.04.013.
22. Jung DC, Kang S, Kim SC, Kim JW, Nam JH, Ryu SY, et al. Use of complex surgical procedures, patterns of tumor spread, and CA-125 predicts a risk of incomplete cytoreduction: a Korean Gynecologic Oncology Group study (KGOG-3022). Gynecol Oncol. 2013;131(2):336-40. https://doi.org/10.1016/j.ygyno.2013.07.110.
23. Naik R, Suchitra R, Naik B. Comparative study of pre-operative CT scan and per-operative findings in carcinoma ovary. Int J Reprod Contracept Obstet Gynecol. 2015;4(5):1367-73. https://doi.org/10.18203/2320-1770. ijrcog20150713
24. Rumgay H, Arnold M, Ferlay J, et al. Global burden of primary liver cancer in 2020 and predictions to 2040. J Hepatol. 2022;77:1598–606.
25. Jin ZL, Zhao LJ. Construction of a nomogram for predicting the risk of primary liver cancer occurrence in patients with liver cysts using CT imaging features combined with alpha-fetoprotein. Medicine (Baltimore). 2025:e42719. doi: 10.1097/MD.0000000000042719.
26. Hanif H, Ali MJ, Susheela AT, et al. Update on the applications and limitations of alpha-fetoprotein for hepatocellular carcinoma. World J Gastroenterol. 2022;28:216–29. doi: 10.3748/wjg.v28.i2.216
27. Ruch B, Wagler J, Kumm K, et al. Hepatocellular carcinoma, alpha fetoprotein, and liver allocation for transplantation: past, present and future. Curr Oncol. 2022;29:7537–51. doi: https://doi.org/10.3390/curroncol29100593
28. Belot A, Velten M, Grosclaude P, Bossard N, Launoy G, Remontet L, et al. (2008). Estimation nationale de l’incidence et de la mortalité par cancer en France entre 1980 et 2005. Institut de veille sanitaire Saint-Maurice (France) 56:159.
29. Alberg AJ, Brock MV, Ford JG, Samet JM, Spivack SD (2013). Epidemiology of lung cancer: diagnosis and management of lung cancer, 3rd ed: American College of Chest Physicians evidence-based clinical practice guidelines. Chest 143(Suppl 5):e1S–e29S
30. Bouvier A-M, Jooste V, Launoy G, Bouvier V, Cariou M, Lecoffre C et al. (2020). Survie des personnes atteintes de cancer en France métropolitaine.
31. Sancho-Garnier H, Villet R, Rouëssé J, Dubois G, Laredo JD, Triboulet JP (2021). Rapport 21-02. Le dépistage du cancer du poumon par scanner thoracique faible dose (STFD) reste non justifié, mais peut être utile pour un bilan de santé des fumeurs. Bull Acad Natl Méd 205:441–447
32. Anderson CM, Burns DM, Dodd KW, Feuer EJ (2012). Chapter 2: birth-cohortspecific estimates of smoking behaviors for the U.S. population. Risk Anal 32(Suppl 1):S14–S24.
33. Guilbert P, Gautier A, Beck F, Peretti-Watel P, Wilquin J-L, Léon C, et al. (2005). Tabagisme: estimation de la prévalence déclarée, baromètre santé, France, 2004-2005. Bull Épidémiol Hebd 22:9798.
34. Leleu H, Berkovitch Q, Bonastre J, Caramella C, Giroux-Leprieur É, Lefèvre L, et al. Efficacy and cost-effectiveness of lung cancer screening in France with low-dose computed tomography. Eur J Cancer Prev. 2025. doi: 10.1097/CEJ.0000000000000973.
35. Meza R, Jeon J, Toumazis I, ten Haaf K, Cao P, Bastani M, et al. (2021). Evaluation of the benefits and harms of lung cancer screening with low-dose computed tomography: modeling study for the US Preventive Services Task Force. JAMA 325:988–997.
36. Rockall AG, Qureshi M, Papadopoulou I, Saso S, Butterfield N, Thomassin-Naggara I, et al. Role of imaging in fertility-sparing treatment of gynecologic malignancies. Radiographics. 2016;36(7):2214-33. https:// doi.org/10.1148/rg.2016150254.
37. Wu H, Tong H, Du X, et al. Vascular habitat analysis based on dynamic susceptibility contrast perfusion MRI predicts IDH mutation status and prognosis in high-grade gliomas. Eur Radiol. 2020;30(6):3254–65.
38. Zeng D, Song Z, Liu Q, Huang J, Wang X, Tang Z. Radiomics analysis of dual-layer detector spectral CT-derived iodine maps for predicting Ki-67 PI in pancreatic ductal adenocarcinoma. BMC Med Imaging. 2025;25(1):124. doi: 10.1186/s12880-025-01664-7.
39. Rizzo S, Botta F, Raimondi S, Origgi D, Fanciullo C, Morganti AG, et al. Radiomics: the facts and the challenges of image analysis. Eur Radiol Exp. 2018;2(1):36. doi:10.1186/s41747-018-0068-z
40. Wu H, Liu J, Jing Z, Qi Z, Ma X, Zhao J, Huang L. Value of serum LncRNA KIF9-AS1 combined with CT signs in the diagnosis of benign and malignant early pulmonary nodules and its correlation with prognosis. J Cardiothorac Surg. 2025;20(1):228. doi: 10.1186/s13019-025-03438-2.
41. Wang Y, Jing L, Liang C, Liu J, Wang S, Wang G. Comparison of the safety and effectiveness of the four-hook needle and Hook wire for the preoperative positioning of localization ground glass nodules. J Cardiothorac Surg. 2024;19(1):35. Larici AR, Farchione A, Franchi P, Ciliberto M, Cicchetti G, Calandriello L et al. Lung nodules: size still matters. Eur Respir Rev. 2017;26(146).
42. Larici AR, Farchione A, Franchi P, Ciliberto M, Cicchetti G, Calandriello L et al. Lung nodules: size still matters. Eur Respir Rev. 2017;26(146).
43. Sicular S, Alpaslan M, Ortega FA, Keathley N, Venkatesh S, Jones RM et al. Reevaluation of missed lung cancer with artificial intelligence. Respir Med Case Rep. 2022;39:101733.
44. Grunnet M, Sorensen JB. Carcinoembryonic antigen (CEA) as tumor marker in lung cancer. Lung Cancer. 2012;76(2):138–43.
45. Zhang X, Han L, Nie F, Zhang H, Li L, Liang R. Development of a radiomic model to predict CEACAM1 expression and prognosis in ovarian cancer. Sci Rep. 2025;15(1):15259. doi: 10.1038/s41598-025-99625-1.
46. Wang X, Xing Y, Zhou X, Wang C, Han S, Zhao S. Radiomics Signatures Based on Computed Tomography for Noninvasive Prediction of CXCL10 Expression and Prognosis in Ovarian Cancer. Cancer Rep (Hoboken). 2024:e70030. doi: 10.1002/cnr2.70030.
47. Gu R, Tan S, Xu Y, Pan D, Wang C, Zhao M, et al. CT radiomics prediction of CXCL9 expression and survival in ovarian cancer. J Ovarian Res. 2023 Aug 180. doi: 10.1186/s13048-023-01248-5.
48. Xia C, Dong X, Li H, Cao M, Sun D, He S, et al. Cancer statistics in China and United States, 2022: profles, trends, and determinants. Chin Med J (Engl). 2022;135:584–90.
49. Yang L, Xie HJ, Li YY, Wang X, Liu XX, Mai J. Molecular mechanisms of platinum-based chemotherapy resistance in ovarian cancer (Review). Oncol Rep. 2022;47:82.
50. Brandt EF, Baues M, Wirtz TH, et al., “Chemokine CXCL10 Modulates the Tumor Microenvironment of Fibrosis-Associated Hepatocellular Carcinoma,” International Journal of Molecular Sciences. 2022; 23(15): 8112. https://doi.org/10.3390/ijms23158112.
51. Salbas A, Koc AM, Coskun M, Horoz EM, Sengul A, Gelal MF. Temporal evolution of MRI findings and survival outcomes in patients with brain metastases after stereotactic radiosurgery. BMC Med Imaging. 2025; 161. doi: 10.1186/s12880-025-01713-1.
52. Li Q, Li W, Wang J, Li X, Ji Y, Wu M. Non-invasive prediction of DCE-MRI radiomics model on CCR5 in breast cancer based on a machine learning algorithm. Cancer Biomark. 2025 18758592251332852. doi: 10.1177/18758592251332852.
53. Siegel RL, Giaquinto AN, Jemal A. Cancer statistics, 2024. CA Cancer J Clin 2024; 74: 12–49. Crossref. PubMed. Web of Science.
54. Loibl S, Poortmans P, Morrow M, et al. Breast cancer. Lancet (London, England) 2021; 397: 1750–1769. Crossref. Web of Science.
Descargas
Publicado
Número
Sección
Licencia
Derechos de autor 2026 Ana Sofía Araujo-Aguirre
Esta obra está bajo una licencia internacional Creative Commons Atribución 4.0.
La Revista Salutem Scientia Spiritus usa la licencia Creative Commons de Atribución – No comercial – Sin derivar: Los textos de la revista son posibles de ser descargados en versión PDF siempre que sea reconocida la autoría y el texto no tenga modificaciones de ningún tipo.
