Prognostic and predictive biomarkers for immunotherapy in advanced renal cell carcinoma.
Matteo RoselliniAndrea MarchettiVeronica MollicaAlessandro RizzoMatteo SantoniFrancesco MassariPublished in: Nature reviews. Urology (2022)
The therapeutic algorithm of renal cell carcinoma has been revolutionized by the approval of immunotherapy agents by regulatory agencies. However, objective and durable responses are still not observed in a large number of patients, and prognostic and predictive biomarkers for immunotherapy response are urgently needed. Prognostic models used in clinical practice are based on clinical and laboratory factors (such as hypercalcaemia, neutrophil count or Karnofsky Performance Status), but, with progress in molecular biology and genome sequencing techniques, new renal cell carcinoma molecular features that might improve disease course and outcomes prediction have been highlighted. An implementation of current models is needed to improve the accuracy of prognosis in the immuno-oncology era. Moreover, several potential biomarkers are currently under evaluation, but effective markers to select patients who might benefit from immunotherapy and to guide therapeutic strategies are still far from validation.
Keyphrases
- renal cell carcinoma
- end stage renal disease
- clinical practice
- chronic kidney disease
- newly diagnosed
- ejection fraction
- machine learning
- healthcare
- peritoneal dialysis
- palliative care
- type diabetes
- prognostic factors
- deep learning
- genome wide
- transcription factor
- gene expression
- adipose tissue
- metabolic syndrome
- quality improvement
- insulin resistance
- weight loss
- glycemic control
- high throughput sequencing