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. 2024 Jun 4;10(11):e32360.
doi: 10.1016/j.heliyon.2024.e32360. eCollection 2024 Jun 15.

High peripheral neutrophil and monocyte count distinguishes renal cell carcinoma from renal angiomyolipoma and predicts poor prognosis of renal cell carcinoma

Affiliations

High peripheral neutrophil and monocyte count distinguishes renal cell carcinoma from renal angiomyolipoma and predicts poor prognosis of renal cell carcinoma

Jiajia Sun et al. Heliyon. .

Abstract

Background: The presence of peripheral inflammatory cells has been linked to the prognosis of cancer. This study aims to investigate the distinct roles of absolute neutrophil count (ANC) and absolute monocyte count (AMC) in differentiating renal cell carcinoma (RCC) from renal angiomyolipoma (RAML), as well as their prognostic significance in RCC.

Methods: We conducted a comprehensive analysis of peripheral immune cell data, clinicopathological data, and tumor characteristics in patients diagnosed with RCC or RAML from January 2015 to December 2021. Receiver operating characteristic (ROC) curves, as well as univariate and multivariate analyses, were employed to assess the diagnostic utility of AMC and ANC in differentiating between RCC and RAML. Kaplan-Meier curve analysis was used to study the survival of RCC patients with different AMC and ANC. The prognostic value of AMC and ANC in RCC was investigated using COX univariate and multivariate analysis. The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were used for bioinformatic correlation analysis.

Results: A total of 1120 eligible patients were included in the study. The mean preoperative AMC and ANC in patients with RCC were found to be significantly higher compared to those in patients with RAML (P = 0.001 and P < 0.001, respectively). High preoperative AMC and ANC significantly correlated with smoking history, tumor length, gross hematuria, and high T Stage, N stage, and pathological grade. In multivariate analyses, an ANC> 3.205 *10^9/L was identified to be independently associated with the presence of RCC (HR = 1.618, P = 0.008). High AMC and ANC were significantly associated with reduced OS and PFS (P < 0.05), and ANC may be an independent prognostic factor. Public database analysis showed that signature genes of tumor-associated macrophages (TAMs) and tumor-associated neutrophils (TANs) were highly expressed in ccRCC.

Conclusions: Elevated preoperative ANC and AMC can distinguish RCC from RAML and predict poor prognosis in patients with RCC. Furthermore, the signature genes of TAMs and TANs exhibit high expression levels in clear cell RCC.

Keywords: AMC; ANC; RAML; RCC; TAMs; TANs.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1
Fig. 1
Inclusion and exclusion criteria for screening 1120 patients with RAML or RCC who underwent surgery in this study. RAML, renal angiomyolipoma; RCC, renal cell carcinoma; ccRCC, clear cell renal cell carcinoma; pRCC, papillary renalcell carcinoma; ChRCC, chromophobe renal cell carcinoma.
Fig. 2
Fig. 2
Levels of AMC, ANC, MLR, and NLR in RAML and RCC. (A) AMC; (B) ANC; (C) MLR level; (D) NLR level. Diagnostic value of (E) AMC, (F) ANC, (G) MLR, and (H) NLR for distinguishing RCC from RAML by ROC analysis. (I) The following table shows the data of ROC curves. (J) Line correlations between AMC and ANC. (K) Line correlations between MLR and NLR. RAML, renal angiomyolipoma; RCC, renal cell carcinoma; AMC, absolute monocyte count; ANC, absolute neutrophil count; MLR, monocyte-to-lymphocyte ratio; NLR, neutrophil to lymphocyte ratio; ROC, receiver-operating characteristic; AUC, area under curve; YI, Youden Index; PPV, positive predictive value; NPV, negative predictive value; TRR, True Positive Rate; FPR, False Positive Rate; ***P < 0.001.
Fig. 3
Fig. 3
Diagnostic value of clinicopathological variables in distinguishing RCC from RAML. ROC curves for determination of cutoff value of (A) age and (B) tumor length regarding distinguishing RCC from RAML. (C) Data table for ROC curves. (D) Univariate and (E) multivariate analysis of preoperative variables on prediction of RCC. RAML, renal angiomyolipoma; RCC, renal cell carcinoma; AMC, absolute monocyte count; ANC, absolute neutrophil count; ROC, receiver-operating characteristic; AUC, area under curve; YI, Youden Index; PPV, positive predictive value; NPV, negative predictive value; TRR, True Positive Rate; FPR, False Positive Rate; HR, hazard ratio; CI, confidence interval.
Fig. 4
Fig. 4
AMC and ANC in RCC subgroups. Comparison of AMC levels among different (A) T stage, (B) pathologic stage, and (C) histologic grade. Diagnostic value of AMC for (D) high T stage, (E) high pathologic stage, and (F) high histologic grade. Comparison of ANC levels among different (G) T stage, (H) pathologic stage, and (I) histologic grade. Diagnostic value of ANC for (J) high T stage, (K) high pathologic stage, and (L) high histologic grade. RCC, renal cell carcinoma; AMC, absolute monocyte count; ANC, absolute neutrophil count; TRR, True Positive Rate; FPR, False Positive Rate; *P < 0.05, **P < 0.01, ***P < 0.001.
Fig. 5
Fig. 5
Survival analysis of RCC patients with different AMC and ANC levels. Kaplan-Meier curve analysis based on AMC or ANC effect for overall survival (OS) (A, AMC; C, ANC) and progression-free survival (PFS) (B, AMC; D, ANC) of RCC, according to the 50th percentile of AMC or ANC level. Univariate and multivariate Cox regression analysis to investigate the independent prognostic value of AMC and ANC (E, OS; F, PFS). (G) Nomogram model for predicting survival rates of RCC patients at 3, 5, and 7 years. RCC, renal cell carcinoma; AMC, absolute monocyte count; ANC, absolute neutrophil count; OS, overall survival; PFS, progression free survival; HR, hazard ratio.
Fig. 6
Fig. 6
TANs and TAMs signature gene expressions in ccRCC. (A) Expression of TANs (left panel) and TAMs (right panel) signature genes in normal and ccRCC tumor tissues based on TCGA database. (B) Expression of TANs (left panel) and TAMs (right panel) signature genes in tumor and adjacent normal tissue in ccRCC patients based on TCGA database. (C) Representative heatmap of TANs and TAMs signature genes using GSE15641 data (left panel). Bar graph showing the fold difference of all signature genes between ccRCC tumor and normal tissues (right panel). (D) Correlation analyses between the expression of TANs and TAMs signature gene expression in ccRCC based on TCGA database. TANs, tumor-associated neutrophils; TAMs, tumor-associated macrophages; ccRCC, clear cell renal cell carcinoma; *P < 0.05, **P < 0.01, ***P < 0.001.

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References

    1. Jonasch E.A.-O., Walker C.L., Rathmell W.A.-O. Clear cell renal cell carcinoma ontogeny and mechanisms of lethality. Nat. Rev. Nephrol. 2021;17(4):245–261. - PMC - PubMed
    1. Yong C., Stewart G.D., Frezza C. Oncometabolites in renal cancer. Nat. Rev. Nephrol. 2020;16(3):156–172. - PMC - PubMed
    1. Capitanio U., Montorsi F. Identifying patients for adjuvant therapy after nephrectomy. Lancet. 2022;400(10358):1080–1081. - PubMed
    1. Sendur M.A.N. Adjuvant immunotherapy for renal cell carcinoma. Lancet Oncol. 2022;23(9):1110–1111. - PubMed
    1. Díaz-Montero C.M., Rini B.I., Finke J.H. The immunology of renal cell carcinoma. Nat. Rev. Nephrol. 2020;16(12):721–735. - PubMed

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