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Identification of Potential Biomarkers for Cancer Cachexia and Anti-Fn14 Therapy

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Background: Developing therapies for cancer cachexia has not been successful to date, in part due to the challenges of achieving robust quantitative measures as a readout of patient treatment. Hence, identifying biomarkers to assess the outcomes of treatments for cancer cachexia is of great interest and important for accelerating future clinical trials. Methods: We established a novel xenograft model for cancer cachexia with a cachectic human PC3* cell line, which was responsive to anti-Fn14 mAb treatment. Using RNA-seq and secretomic analysis, genes differentially expressed in cachectic and non-cachectic tumors were identified and validated by digital droplet PCR (ddPCR). Correlation analysis was performed to investigate their impact on survival in cancer patients. Results: A total of 46 genes were highly expressed in cachectic PC3* tumors, which were downregulated by anti-Fn14 mAb treatment. High expression of the top 10 candidates was correlated with low survival and high cachexia risk in different cancer types. Elevated levels of LCN2 were observed in serum samples from cachectic patients compared with non-cachectic cancer patients. Conclusion: The top 10 candidates identified in this study are candidates as potential biomarkers for cancer cachexia. The diagnostic value of LCN2 in detecting cancer cachexia is confirmed in patient samples.


This work was supported by the Australian National Health and Medical Research Council (GNT1117541), Victorian Cancer Agency (Victorian Department of Health and Human Services), Tour de Cure (RSP-147-2020 and RSP-00044-19/20), CASS Foundation and La Trobe University (RFA and DVCR Grants). Biospecimens and data used in this research were obtained from the Victorian Cancer Biobank, Victoria Australia with appropriate ethics approval. The Victorian Cancer Biobank is supported by the Victorian Government. A.M.S is supported by an NHMRC Investigator grant (GNT1177837). I.J.B is supported by the National Imaging Facility (NIF Fellow).


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© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// 4.0/