Progressive, multi-organ, and multi-layered nature of cancer cachexia.

Cancer cachexia is a complex, multifaceted condition that negatively impacts the health, treatment efficacy, and economic status of cancer patients. The management of cancer cachexia is an essential clinical need. Cancer cachexia is currently defined mainly according to the severity of weight loss and sarcopenia (i.e., macrosymptoms). However, such macrosymptoms may be insufficient to give clinicians clues on how to manage this condition as these symptoms appear at the late stage of cancer. We need to understand earlier events during the progression of cancer cachexia so as not to miss a clinical opportunity to control this complex syndrome. Recent research indicates that cancer-induced changes in the host are much wider than previously recognized, including disruption of liver function and the immune system. Furthermore, such changes are observed before the occurrence of visible distant metastases (i.e., in early, localized cancers). In light of these findings, we propose to expand the definition of cancer cachexia to include all cancer-induced changes to host physiology, including changes caused by early, localized cancers. This new definition of cancer cachexia can provide a new perspective on this topic, which can stimulate the research and development of novel cancer cachexia therapies.

Time-series blood cytokine profiles correlate with treatment responses in triple-negative breast cancer patients.

BACKGROUND: Triple-negative breast cancer (TNBC) is the most heterogeneous breast cancer subtype. Partly due to its heterogeneity, it is currently challenging to stratify TNBC patients and predict treatment outcomes. METHODS: In this study, we examined blood cytokine profiles of TNBC patients throughout treatments (pre-treatment, during chemotherapy, pre-surgery, and 1 year after the surgery in a total of 294 samples). We analyzed the obtained cytokine datasets using weighted correlation network analyses, protein-protein interaction analyses, and logistic regression analyses. RESULTS: We identified five cytokines that correlate with good clinical outcomes: interleukin (IL)-1α, TNF-related apoptosis-inducing ligand (TRAIL), Stem Cell Factor (SCF), Chemokine ligand 5 (CCL5 also known as RANTES), and IL-16. The expression of these cytokines was decreased during chemotherapy and then restored after the treatment. Importantly, patients with good clinical outcomes had constitutively high expression of these cytokines during treatments. Protein-protein interaction analyses implicated that these five cytokines promote an immune response. Logistic regression analyses revealed that IL-1α and TRAIL expression levels at pre-treatment could predict treatment outcomes in our cohort. CONCLUSION: We concluded that time-series cytokine profiles in breast cancer patients may be useful for understanding immune cell activity during treatment and for predicting treatment outcomes, supporting precision medicine. TRIAL REGISTRATION: The study has been registered with the University Hospital Medical Information Network Clinical Trials Registry ( http://www.umin.ac.jp/ctr/index-j.htm ) with the unique trial number UMIN000023162. The association Japan Breast Cancer Research Group trial number is JBCRG-22. The clinical outcome of the JBCRG-22 study was published in Breast Cancer Research and Treatment on 25 March 2021. https://doi.org/10.1007/s10549-021-06184-w .