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Cancer associated macrophage-like cells in metastatic renal cell carcinoma predicts for poor prognosis and tracks treatment response in real time

Renal Cell Carcinoma (RCC) is a fatal urological cancer, with one third of patients diagnosed with metastasis, resulting in a 5-year survival of only 12%. Recent advancements in therapies have increased survival in mRCC, but lack efficacy in subtypes, due to treatment resistance and toxic side effec...

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Autores principales: Ali, Amama, Adams, Daniel L., Kasabwala, Dimpal M., Tang, Cha-Mei, Ho, Thai H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10310728/
https://www.ncbi.nlm.nih.gov/pubmed/37386095
http://dx.doi.org/10.1038/s41598-023-37671-3
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author Ali, Amama
Adams, Daniel L.
Kasabwala, Dimpal M.
Tang, Cha-Mei
Ho, Thai H.
author_facet Ali, Amama
Adams, Daniel L.
Kasabwala, Dimpal M.
Tang, Cha-Mei
Ho, Thai H.
author_sort Ali, Amama
collection PubMed
description Renal Cell Carcinoma (RCC) is a fatal urological cancer, with one third of patients diagnosed with metastasis, resulting in a 5-year survival of only 12%. Recent advancements in therapies have increased survival in mRCC, but lack efficacy in subtypes, due to treatment resistance and toxic side effects. Currently, white blood cells, hemoglobin, and platelets are limitedly used as blood based biomarkers to help determine RCC prognosis. Cancer associated macrophage-like cells (CAMLs) are a potential mRCC biomarker which have been identified in peripheral blood of patients with malignant tumors and have been shown to predict poor clinical patient outcomes based on their number and size. In this study, blood samples from 40 RCC patients were obtained to evaluate the clinical utility of CAMLs. CAML changes were monitored during treatment regimens to evaluate their ability to predict treatment efficacy. It was observed that patients with smaller CAMLs had better progression free survival (HR = 2.84, 95% CI 1.22–6.60, p = 0.0273) and overall survival (HR = 3.95, 95% CI 1.45–10.78, p = 0.0154) versus patients with larger CAMLs. These findings suggest that CAMLs can be used as a diagnostic, prognostic, and predictive biomarker for patients with RCC which may help improve management of advanced RCC.
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spelling pubmed-103107282023-07-01 Cancer associated macrophage-like cells in metastatic renal cell carcinoma predicts for poor prognosis and tracks treatment response in real time Ali, Amama Adams, Daniel L. Kasabwala, Dimpal M. Tang, Cha-Mei Ho, Thai H. Sci Rep Article Renal Cell Carcinoma (RCC) is a fatal urological cancer, with one third of patients diagnosed with metastasis, resulting in a 5-year survival of only 12%. Recent advancements in therapies have increased survival in mRCC, but lack efficacy in subtypes, due to treatment resistance and toxic side effects. Currently, white blood cells, hemoglobin, and platelets are limitedly used as blood based biomarkers to help determine RCC prognosis. Cancer associated macrophage-like cells (CAMLs) are a potential mRCC biomarker which have been identified in peripheral blood of patients with malignant tumors and have been shown to predict poor clinical patient outcomes based on their number and size. In this study, blood samples from 40 RCC patients were obtained to evaluate the clinical utility of CAMLs. CAML changes were monitored during treatment regimens to evaluate their ability to predict treatment efficacy. It was observed that patients with smaller CAMLs had better progression free survival (HR = 2.84, 95% CI 1.22–6.60, p = 0.0273) and overall survival (HR = 3.95, 95% CI 1.45–10.78, p = 0.0154) versus patients with larger CAMLs. These findings suggest that CAMLs can be used as a diagnostic, prognostic, and predictive biomarker for patients with RCC which may help improve management of advanced RCC. Nature Publishing Group UK 2023-06-29 /pmc/articles/PMC10310728/ /pubmed/37386095 http://dx.doi.org/10.1038/s41598-023-37671-3 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Ali, Amama
Adams, Daniel L.
Kasabwala, Dimpal M.
Tang, Cha-Mei
Ho, Thai H.
Cancer associated macrophage-like cells in metastatic renal cell carcinoma predicts for poor prognosis and tracks treatment response in real time
title Cancer associated macrophage-like cells in metastatic renal cell carcinoma predicts for poor prognosis and tracks treatment response in real time
title_full Cancer associated macrophage-like cells in metastatic renal cell carcinoma predicts for poor prognosis and tracks treatment response in real time
title_fullStr Cancer associated macrophage-like cells in metastatic renal cell carcinoma predicts for poor prognosis and tracks treatment response in real time
title_full_unstemmed Cancer associated macrophage-like cells in metastatic renal cell carcinoma predicts for poor prognosis and tracks treatment response in real time
title_short Cancer associated macrophage-like cells in metastatic renal cell carcinoma predicts for poor prognosis and tracks treatment response in real time
title_sort cancer associated macrophage-like cells in metastatic renal cell carcinoma predicts for poor prognosis and tracks treatment response in real time
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10310728/
https://www.ncbi.nlm.nih.gov/pubmed/37386095
http://dx.doi.org/10.1038/s41598-023-37671-3
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