Reply to “A commentary on macrophage morphology and distribution are strong predictors of prognosis in resected colorectal liver metastases: results from an external retrospective observational study”

Dear Editor, We appreciate the thoughtful comments[1] from our colleagues regarding our article “Macrophage morphology and distribution are strong predictors of prognosis in resected colorectal liver metastases: results from an external retrospective observational study”[2]. We welcome the opportunity to address their concerns and provide further clarification on our methodology and findings. Regarding the clinicopathological baseline statistics, we acknowledge the importance of liver status and systemic inflammation in modulating macrophage morphology and function. In our cohort, all patients underwent liver resection for colorectal liver metastases (CLM). It is important to note that patients with relevant underlying liver diseases impairing liver function were excluded from the study, as they would not have been deemed suitable candidates for liver resection. This selection criterion helps to ensure a more homogeneous patient population in terms of liver function. Moreover, we assessed and considered previous chemotherapy, which may lead to liver damage[3]. This approach allowed us to account for potential chemotherapy-induced liver injuries that could influence our findings. Regarding systemic inflammation markers, we did collect data on neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and lymphocyte-to-monocyte ratio (LMR) in our published series. Median NLR was 2 (range, 0.63–6), median PLR was 141 (range, 41.15–392) and median LMR was 4 (1.6–9): none of these ratios were associated with TAMs’ morphology on univariate analysis. While these markers provide some insight into the systemic inflammatory status of our patient cohort, we agree that including more detailed liver function indicators could provide additional valuable insights. For future studies, we plan to incorporate more comprehensive liver function tests and potentially expand our analysis of systemic inflammation markers to address potential confounding factors more thoroughly. We acknowledge the concerns raised regarding the potential heterogeneity in TAMs’ distribution within the peritumoral tissue and the consequent importance of determining section zones to mitigate selection bias. To minimize this risk, as detailed in the methods section of the article, for each CD163-stained slide, the three noncontiguous, nonoverlapping microscopic areas in the invasive margin of the tumor, were selected by an expert pathologist, which was blinded to the study. Additionally, we conducted a sub-analysis comparing high-risk (n = 6, recurrence within 3 months post-surgery) and low-risk patients (n = 6, no recurrence after 48 months post-surgery). This last analysis examined the entire 500-μm wide peritumoral area along the tumor’s contour, generating density maps (Figure 3 of the article) for the distribution of large TAMs (L-TAMs) and small TAMs (S-TAMs). These maps revealed distinct distribution patterns of the two populations between the patient groups, corroborating our findings from the section-based analysis. This sub-analysis was designed to address potential selection bias by constructing density maps along the entire tumor contour without any selective sampling. Finally, we concur with the observation emphasizing the significance of characterizing TAMs in the primary tumor. This approach would indeed contribute substantially to elucidating the pathophysiological mechanisms underlying colorectal cancer (CRC) cell extravasation and their role in the metastatic process[4]. Concurrently, we maintain that evaluating TAMs as potential therapeutic targets is of paramount importance. In this context, our focus on stage IV patients, for whom systemic therapy is a cornerstone of treatment[5,6], represents a logical starting point from a translational perspective. This approach aligns with the objective of bridging fundamental research with clinical applications, potentially leading to novel therapeutic strategies for advanced CRC. We appreciate the constructive feedback and agree that larger-scale, rigorous cohort studies are necessary to further validate our findings. It is important to note that our study already represents an external validation of a previous findings in this area[7]. As such, it serves as a crucial step in confirming the role of TAM morphology in colorectal cancer prognosis and provides a solid foundation for future research. We are committed to advancing our understanding of TAM morphology’s role in colorectal cancer prognosis and believe that our work contributes significantly to this field. We thank our colleagues for their insightful comments, which will undoubtedly contribute to improving future research in this important area of study.

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International Journal of Surgery Open
Published
2024-10-15
DOI
https://doi.org/10.1097/io9.0000000000000219
Primary Topic
Radiomics and Machine Learning in Medical Imaging
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article
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article

Reply to “A commentary on macrophage morphology and distribution are strong predictors of prognosis in resected colorectal liver metastases: results from an external retrospective observational study”

Matteo Donadon, Guido Costa, Guido Torzilli
International Journal of Surgery Open
Radiomics and Machine Learning in Medical Imaging
article

Reply to “A commentary on macrophage morphology and distribution are strong predictors of prognosis in resected colorectal liver metastases: results from an external retrospective observational study”

Matteo Donadon, Guido Costa, Guido Torzilli
article en

Abstract

Dear Editor, We appreciate the thoughtful comments[1] from our colleagues regarding our article “Macrophage morphology and distribution are strong predictors of prognosis in resected colorectal liver metastases: results from an external retrospective observational study”[2]. We welcome the opportunity to address their concerns and provide further clarification on our methodology and findings. Regarding the clinicopathological baseline statistics, we acknowledge the importance of liver status and systemic inflammation in modulating macrophage morphology and function. In our cohort, all patients underwent liver resection for colorectal liver metastases (CLM). It is important to note that patients with relevant underlying liver diseases impairing liver function were excluded from the study, as they would not have been deemed suitable candidates for liver resection. This selection criterion helps to ensure a more homogeneous patient population in terms of liver function. Moreover, we assessed and considered previous chemotherapy, which may lead to liver damage[3]. This approach allowed us to account for potential chemotherapy-induced liver injuries that could influence our findings. Regarding systemic inflammation markers, we did collect data on neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and lymphocyte-to-monocyte ratio (LMR) in our published series. Median NLR was 2 (range, 0.63–6), median PLR was 141 (range, 41.15–392) and median LMR was 4 (1.6–9): none of these ratios were associated with TAMs’ morphology on univariate analysis. While these markers provide some insight into the systemic inflammatory status of our patient cohort, we agree that including more detailed liver function indicators could provide additional valuable insights. For future studies, we plan to incorporate more comprehensive liver function tests and potentially expand our analysis of systemic inflammation markers to address potential confounding factors more thoroughly. We acknowledge the concerns raised regarding the potential heterogeneity in TAMs’ distribution within the peritumoral tissue and the consequent importance of determining section zones to mitigate selection bias. To minimize this risk, as detailed in the methods section of the article, for each CD163-stained slide, the three noncontiguous, nonoverlapping microscopic areas in the invasive margin of the tumor, were selected by an expert pathologist, which was blinded to the study. Additionally, we conducted a sub-analysis comparing high-risk (n = 6, recurrence within 3 months post-surgery) and low-risk patients (n = 6, no recurrence after 48 months post-surgery). This last analysis examined the entire 500-μm wide peritumoral area along the tumor’s contour, generating density maps (Figure 3 of the article) for the distribution of large TAMs (L-TAMs) and small TAMs (S-TAMs). These maps revealed distinct distribution patterns of the two populations between the patient groups, corroborating our findings from the section-based analysis. This sub-analysis was designed to address potential selection bias by constructing density maps along the entire tumor contour without any selective sampling. Finally, we concur with the observation emphasizing the significance of characterizing TAMs in the primary tumor. This approach would indeed contribute substantially to elucidating the pathophysiological mechanisms underlying colorectal cancer (CRC) cell extravasation and their role in the metastatic process[4]. Concurrently, we maintain that evaluating TAMs as potential therapeutic targets is of paramount importance. In this context, our focus on stage IV patients, for whom systemic therapy is a cornerstone of treatment[5,6], represents a logical starting point from a translational perspective. This approach aligns with the objective of bridging fundamental research with clinical applications, potentially leading to novel therapeutic strategies for advanced CRC. We appreciate the constructive feedback and agree that larger-scale, rigorous cohort studies are necessary to further validate our findings. It is important to note that our study already represents an external validation of a previous findings in this area[7]. As such, it serves as a crucial step in confirming the role of TAM morphology in colorectal cancer prognosis and provides a solid foundation for future research. We are committed to advancing our understanding of TAM morphology’s role in colorectal cancer prognosis and believe that our work contributes significantly to this field. We thank our colleagues for their insightful comments, which will undoubtedly contribute to improving future research in this important area of study.

International Journal of Surgery OpenVol. 62(6)
Università degli Studi del Piemonte Orientale “Amedeo Avogadro” (IT), Humanitas University (IT), Azienda Ospedaliero Universitaria Maggiore della Carita (IT), IRCCS Humanitas Research Hospital (IT)
Openalex Percentile: Top 56%
Radiomics and Machine Learning in Medical Imaging
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