Fibrotic activity quantified in serum by measurements of type III collagen pro-peptides can be used for prognosis across different solid tumor types.
Nicholas WillumsenChristina JensenGeorge GreenNeel I NissenJaclyn NeelyDavid M NelsonRasmus S PedersenPeder FrederiksenInna M ChenMogens K BoisenAstrid Z JohansenDaniel H MadsenInge Marie SvaneAllan LiptonKim LeitzelSuhail M AliJanine T ErlerDaan P HurkmansRon H J MathijssenJoachim AertsMohammed EslamJacob GeorgeClaus ChristiansenMina J BisselMorten A KarsdalPublished in: Cellular and molecular life sciences : CMLS (2022)
Due to activation of fibroblast into cancer-associated fibroblasts, there is often an increased deposition of extracellular matrix and fibrillar collagens, e.g. type III collagen, in the tumor microenvironment (TME) that leads to tumor fibrosis (desmoplasia). Tumor fibrosis is closely associated with treatment response and poor prognosis for patients with solid tumors. To assure that the best possible treatment option is provided for patients, there is medical need for identifying patients with high (or low) fibrotic activity in the TME. Measuring unique collagen fragments such as the pro-peptides released into the bloodstream during fibrillar collagen deposition in the TME can provide a non-invasive measure of the fibrotic activity. Based on data from 8 previously published cohorts, this review provides insight into the prognostic value of quantifying tumor fibrosis by measuring the pro-peptide of type III collagen in serum of a total of 1692 patients with different solid tumor types and discusses the importance of tumor fibrosis for understanding prognosis and for potentially guiding future drug development efforts that aim at overcoming the poor outcome associated with a fibrotic TME.
Keyphrases
- type iii
- poor prognosis
- extracellular matrix
- end stage renal disease
- systemic sclerosis
- chronic kidney disease
- idiopathic pulmonary fibrosis
- long non coding rna
- wound healing
- systematic review
- machine learning
- prognostic factors
- peritoneal dialysis
- tissue engineering
- deep learning
- current status
- liver fibrosis
- electronic health record