The ratio of lymphocyte/red blood cells and platelets/lymphocytes are predictive biomarkers for lymph node metastasis in patients with breast cancer

Abstract

BACKGROUND:

Axillary lymph node metastasis (LNM) affects the progression of breast cancer. However, it is difficult to preoperatively diagnose axillary lymph node status with high sensitivity. Therefore, we hypothesized that platelets/lymphocytes ratio (PLR) and lymphocytes/ red blood cells ratio (LRR) might help in the prognosis of lymph node metastasis in T1-T2 breast cancer.

METHODS:

166 patients (Chang Ning Maternity & Infant Health Institute) were included in our study, and the associations of PLR and LPR with lymph node metastasis were investigated. Peripheral blood was collected one week before the surgery, and the patients were divided into different categories based on their PLR and LRR.

RESULTS:

The incidence of LNM was significantly increased in the high PLR group ( $p=$ 0.002) compared with the low PLR group; LNM was also significantly increased in the low LRR group ( $p=$ 0.036) compared with the high LPR group. Further, our study revealed that high PLR ( $p<$ 0.001, OR $=$ 4.397, 95% CI $=$ 2.005–9.645), low LRR ( $p=$ 0.017, OR $=$ 0.336, 95%CI $=$ 0.136–0.825) and high clinical T stage ( $p<$ 0.001, OR $=$ 3.929, 95%CI $=$ 1.913–8.071) are independent predictors of LNM.

CONCLUSIONS:

PLR and LRR could be identified as predictors of LNM in patients with T1/T2 breast cancer.

Keywords

Breast cancer lymphocytes platelet red blood cell biomarker

1. Introduction

Breast cancer is the most common cancer in females [1]. According to GLOBOCAN 2020 data, the global age-standardized incidence rate (ASIR) for breast cancer was 47.8 per 100,000, while in China, it stood at 39.1 per 100,000. The worldwide age-standardized mortality rate (ASMR) was 13.6 per 100,000, whereas the ASMR for breast cancer in China was notably lower, at 9.5 per 100,000 [2]. Patients with breast cancer have a high axillary lymph node metastasis rate. Metastasis to axillary lymph nodes is the most significant prognostic factor for patients with breast cancer [3]. In early breast cancer, sentinel lymph node biopsy (SLNB) has been extensively used to evaluate axillary lymph node status [4]. However, some patients undergo axillary lymph node dissection (ALND) irrespective of SLNB results due to concerns over false-negative SLNB. However, no preoperative markers exist that can successfully evaluate axillary lymph node status with high sensitivity and specificity.

Figure 1.

Study design chart. A total of 170 patients with breast cancer diagnosed with cT1/T2N0M0 preoperatively from 2019 to 2021 at the China Chang Ning Maternity & Infant Health Institute. However, 4 patients who showed T3/T4 staged breast cancer after the histological examination were excluded.

Systemic inflammatory response affects cancer progression [5]. Inflammation is divided into two categories: acute and chronic inflammation. Acute inflammatory responses are involved in immune surveillance, whereas chronic inflammatory responses sometimes result in increased tumor growth and metastasis via the release of inflammatory mediators. Persistent chronic inflammation may also induce infiltration of inflammatory cells, which secrete cytokines and chemokines, leading to activation of oncogenes or inactivation of tumor suppressor genes and immune tolerance [6]. Both LRR and PLR are indicators of systemic inflammation [7, 8]. Platelets promote tumor growth by secreting various angiogenic growth factors, including platelet-derived growth factor (PDGF) and transforming growth factor- $\beta$ (TGF- $\beta$ ) [9, 10]. However, lymphocytes are key players in the host immune response and may suppress cancer progression [11]. Previously, the ratios of peripheral blood lymphocytes/red blood cells and platelets/lymphocytes were reported as prognostic indicators of breast cancer [7, 12, 13, 14]. However, most of these studies evaluated the relationship between hematological inflammatory markers and disease-free survival (DFS) or overall survival (OS). These studies included sentinel lymph node status, but there was no detailed report about lymph node metastasis.

Here, we hypothesized that PLR and LRR are differ based on axillary lymph node status in T1-T2 breast cancer and tested whether preoperative PLR and LRR are predictive markers of LNM in breast cancer patients.

2. Materials and methods

2.1 Patients

Patients were enrolled in this study from January 2019 to September 2021 at the China Chang Ning Maternity & Infant Health Institute (Fig. 1). All enrolled patients were devoid of rheumatic or hematological disorders. They had tested negative for nucleic acid 2 days prior to surgery and remained free from coronavirus disease infection for a minimum of 6 months. All patients received breast cancer surgery and axillary lymph node dissection. Immunohistology was used to assess the status of estrogen receptor (ER), progesterone receptor (PR), Ki67, and human epidermal growth factor receptor 2 (HER2). The Immuno-histological expression of estrogen receptor or progesterone receptor was considered positive when $>$ 1% of tumor cells stained positive. Fluorescence in situ hybridization (FISH) was used to measure HER2 positivity (HER2 amplification). Patients with T size $ï ¼ ž$ 5 cm or distant metastasis were excluded from the study. The dye method was used to identify lymph nodes during breast cancer surgery.

Figure 2.

Receiver operating characteristic (ROC) curve analysis. PLR cut-off value for lymph node metastasis was identified as 154.17. Area under curve 0.604, sensitivity 0.645, specificity 0.606 and $p=$ 0.024.

The patient clinical database was evaluated retrospectively, and the data include age, body mass index (BMI), tumor size, pathologic stage, and surgery type. Patients’ peripheral whole blood was collected one week before the surgery with a hemocytometer. Platelet lymphocytes and red blood cells were counted using the Coulter XN-1000 Hematology Analyzer (Sysmex Corporation, JPN) and PLR and LRR were calculated for each patient. Preoperative PLR was calculated as the ratio of the absolute platelet count to the absolute lymphocyte count. Preoperative LRR was calculated as the ratio of the absolute lymphocyte count to the absolute red blood cell count. The PLR cut-off value for predicting axillary lymph node metastasis was set at 154.17. The LRR cut-off value for predicting axillary lymph node metastasis was set at 0.423. Both cut-off values were defined with Receiver-operator curve (ROC) curve analysis (Fig. 2). We stratified the patients into different groups based on their LRR or PLR and analyzed the associations between PLR or LRR levels and axillary lymph node status.

$N=$ 170 patients with T1 or T2 breast cancer were screened. 4 patients who showed T3/T4 staged breast cancer after the histological examination were excluded, and $n=$ 166 patients were finally evaluated retrospectively in the study.

The experiments were undertaken with the understanding and written consent of each subject, and that the study conforms with The Code of Ethics of the World Medical Association (Declaration of Helsinki), printed in the British Medical Journal (18 July 1964). The study was granted approval by the Ethics Management Committee of Shanghai Changning Maternity and Infant Health Hospital.

2.2 Statistical methods

Data were analyzed using the SPSS statistical software (SPSS 26.0, Chicago, IL, USA). Nominal crosstabs were compared using the Chi-square test retrospectively. The student’s paired t-test was used for parametric two-group analyses, and the Mann-Whitney U test was used for non-parametric two-group comparison. ROC analysis was used to identify the cut-off values. PLR and LRR were assessed using univariate, multivariate logistic regression analysis. Multivariate models included age ( $\leqslant$ 50 or $>$ 50), clinical T clinical stage (T1 or T2), ER expression (positive or negative), PR expression (positive or negative), HER2 expression (positive or negative), Ki67 proliferative index ( $\leqslant$ 20 or $>$ 20) and BMI ( $<$ 24 or $\geqslant$ 24) before treatment. For statistical analyses, the p-value was computed based on a two-sided test. A $p$ -value $<$ 0.05 was considered statistically significant.

Table 1
Clinicopathological characteristics of 166 patients

Parameters	Number of patients ( $n=$ 166) (%)
Age, years, mean $\pm$ SD, range	55.32 $\pm$ 10.59 (28–78)
Platelet/lymphocyte ratio, mean $\pm$ SD, range	160.51 $\pm$ 55.83 (49.63–423.9)
Lymphocyte /red blood cell ratio, mean $\pm$ SD, range	0.37 $\pm$ 0.11 (0.14–0.87)
Tumor size, mm, mean $\pm$ SD,	2.077 $\pm$ 1.07 (0.2–5.0)
Clinical T stage
T1	96(57.8%)
T2	70(42.2%)
Estrogen receptor
Negative	46(27.7%)
Positive	120(72.3%)
Progesterone receptor
Negative	63(38.0%)
Positive	103(62.0%)
HER2
Negative	99(59.6%)
Positive	67(40.4%)
Ki67
$\leqslant$ 20%	72(43.4%)
$>$ 20%	94(56.6%)
BMI index
$<$ 24	84(50.6%)
$\geqslant$ 24	82(49.4%)
N stage status
N0	104(62.7%)
N1	62(37.3%)
USG, lymph node status
No	141(84.9%)
Yes	25(15.1%)
Stage
Stage 1	72(43.4%)
Stage 2	94(56.6%)
Primary Cancer Diagnosis, $n$ (%)
Idc	152(91.6%)
Ilc	3(1.8%)
Others	11(6.6%)

HER2, human epidermal growth factor receptor 2; BMI, body mass index; LRR, lymphocyte to red cells ratio; PLR, platelet to lymphocyte ratio.

Table 2

Association between lymph node metastasis and clinicopathological factors

	No metastasis (104 patients 62.7%)	Metastasis (62 patients 37.3%)	$P$ value
Variables	Lymph node
Age, years, mean $\pm$ SD, range	54.39 $\pm$ 10.11 (32–74)	56.87 $\pm$ 11.27(28–78)	0.394
Tumor size, mm, mean $\pm$ SD,	1.845 $\pm$ 0.97(0.2–5)	2.47 $\pm$ 1.10(0.6–5)	$<$ 0.001
Platelet/lymphocyte ratio, mean $\pm$ SD, range	155.61 $\pm$ 60.73(49.63–423.90)	168.75 $\pm$ 45.76(84.52–276.85)	0.025
Lymphocyte/red blood cell ratio, mean $\pm$ SD, range	0.384 $\pm$ 0.121(0.145–0.872)	0.345 $\pm$ 0.089(0.184–0.615)	0.046
Clinical T stage			$<$ 0.001
T1	72	24
T2	32	38
Estrogen receptor			0.134
Negative	33	13
Positive	71	49
Progesterone receptor			0.134
Negative	44	19
Positive	60	43
HER2			0.921
Negative	63	36
Positive	41	26
Ki67			0.208
$\leqslant$ 20%	49	23
$>$ 20%	55	39
BMI index			0.210
$<$ 24	64	32
$\geqslant$ 24	40	30
Platelet to lymphocyte ratio (PLR)			0.002
Low	63	22
High	41	40
Lymphocyte to red cell ratio (LRR)			0.036
Low	72	52
High	32	10

HER2, human epidermal growth factor receptor 2; BMI, body mass index; LRR, lymphocyte to red cells ratio; PLR, platelet to lymphocyte ratio.

3. Results

3.1 Clinical characteristics

166 patients with T1 or T2 breast cancer were included in this study (Table 1). The average age was 55.32 years (range $=$ 28–78 years). 120 patients (72.3%) were ER-positive, 103 patients (62.0%) were PR-positive, 67 patients (40.4%) were HER2-positive, and 94 patients (56.6%) showed Ki67 staining. The metastasis rate of lymph nodes was 37.3% ( $n=$ 62). The mean preoperative PLR was 160.51 (range $=$ 49.36–423.9) an the mean preoperative LRR was 0.37 (range $=$ 0.14–0.87). We divided the patients into the high PLR group ( $n=$ 81, 48.8%) and the high LRR group ( $n=$ 42, 25.3%).

3.2 Association of LRR and PLR with LNM

The relationships of clinicopathological features with LNM are summarised in Table 2. Based on the test for homogeneity, we used the Mann-Whitney U test to evaluate the association of LRP and PLR with LNM. The mean PLR of patients with metastatic lymph nodes was 168.75, and the mean PLR of patients without metastatic lymph nodes was 155.61 ( $p=$ 0.025). The mean LRR of patients with metastatic lymph nodes was 0.345, and the mean LRR of patients without metastatic lymph nodes was 0.384 ( $p=$ 0.046). ROC curve analysis showed that the cutoff value for PLR was 154.17, and the cutoff value for LRR was 0.423. Using the cutoff of PLR, had a sensitivity of 0.645, a specificity of 0.606, and an area under the ROC curve (AUC) of 0.604 (Fig. 2). Using the cutoff of LRR, had a sensitivity of 0.839, a specificity of 0.308, and an area under the ROC curve (AUC) of 0.593 (Fig. 3).

Figure 3.

Receiver operating characteristic (ROC) curve analysis. LRR cut-off value for lymph node metastasis was identified as 0.423. Area under curve 0.593, sensitivity 0.839, specificity 0.308 and $p=$ 0.046.

There were no statistically significant differences in age between the different groups. LNM was significantly associated with tumor size ( $p<$ 0.001), clinical T stage ( $p<$ 0.001), PLR ( $p=$ 0.025), and LRR ( $p=$ 0.046). Among 81 patients with metastatic lymph nodes, 40 were in the high PLR group; among 85 patients without metastatic lymph nodes, 22 were in the low PLR group ( $p=$ 0.002). Among 124 patients with metastatic lymph nodes, 52 were in the low LRR group; among 42 patients without metastatic lymph nodes, 10 were in the high LRR group ( $p=$ 0.036). The associations of LRR, PLR, and LNM are summarized in Table 3. PLR and LRR did not show a significant correlation with other clinicopathological characteristics. Univariate analysis revealed that high PLR ( $p=$ 0.002, OR $=$ 2.794, 95%CI $=$ 1.455–5.363), low LRR ( $p=$ 0.039, OR $=$ 0.433, 95%CI $=$ 0.195–0.958), and high clinical T stage ( $p<$ 0.001, OR $=$ 3.562, 95%CI $=$ 1.843–6.887) were predictors of LNM (Table 3) . Furthermore, multivariate analysis revealed that high PLR ( $p<$ 0.001, OR $=$ 4.397, 95%CI $=$ 2.005–9.645), low LRR ( $p=$ 0.017, OR $=$ 0.336, 95%CI $=$ 0.136–0.825) and high clinical T stage ( $p<$ 0.001, OR $=$ 3.929, 95%CI $=$ 1.913–8.071) are independent predictors of LNM (Table 4).

Table 3

Association between platelet to lymphocyte ratio (PLR), lymphocyte to red cell ratio (LRR) and clinicopathological factors

Variables	PLR			LRR
	Low (85 patients 51.2%)	High (81 patients 48.8%)	$P$ value	Low (124 patients 74.7%)	High (42 patients 25.3%)	$P$ value
Age, years, mean $\pm$ SD, range	55.79 $\pm$ 10.14 (33–74)	54.83 $\pm$ 11.09(28–78)	0.561	55.46 $\pm$ 11.13 (28–78)	54.90 $\pm$ 8.94(33–74)	0.770
Tumour size, mm, mean $\pm$ SD,	2.07 $\pm$ 1.11(0.3–5)	2.08 $\pm$ 1.03(0.2–4.5)	0.775	2.09 $\pm$ 1.08(0.2–5)	2.04 $\pm$ 1.05(0.3–5)	0.840
Clinical T stage			0.562			0.536
T1	51	45		70	26
T2	34	35		54	16
Estrogen receptor			0.616			0.799
Negative	25	21		35	11
Positive	60	60		89	31
Progesterone receptor			0.173			0.982
Negative	28	35		47	16
Positive	57	46		77	26
HER2			0.465			0.141
Negative	53	46		78	21
Positive	32	35		46	21
Ki67			0.558			0.938
$\leqslant$ 20%	35	37		54	18
$>$ 20%	50	44		70	24
BMI index			0.321			0.023
$<$ 24	46	50		78	18
$\geqslant$ 24	39	31		46	24
Clinical lymph node metastasis			0.002			0.036
No	63	41		72	32
Yes	22	40		52	10

HER2, human epidermal growth factor receptor 2; BMI, body mass index; LRR, lymphocyte to red cell ratio; PLR, platelet to lymphocyte ratio.

Table 4

Univariate and multivariate analysis of predictors for lymph node metastasis

Parameters	Univariate analysis			Multivariate analysis
	Odd ratio	95%CI	$p$ -Value	Odd ratio	95%CI	$p$ -Value
Age at surgery (years old)
$\leqslant$ 50 vs. $>$ 50	1.4733	0.755–2.872	0.256
Clinical T stage
T1 vs. T2	3.562	1.843–6.887	$<$ 0.001	3.929	1.913–8.071	$<$ 0.001
Estrogen receptor
Negative vs. positive	1.752	0.838–3.664	0.136
Progesterone receptor
Negative vs. positive	1.660	0.853–3.229	0.136
HER2
Negative vs. positive	1.110	0.585–2.104	0.750
Ki67
$\leqslant$ 20% vs. $>$ 20%	1.511	0.794–2.874	0.209
BMI index
$<$ 24 vs. $\geqslant$ 24	1.500	0.794–2.833	0.211
Platelet to lymphocyte ratio
Low vs. High lymphocyte to red blood cell ratio	2.794	1.455–5.363	0.002	4.397	2.005–9.645	$<$ 0.001
Lymphocyte to red blood cell ratio
Low vs. High	0.433	0.195–0.958	0.039	0.336	0.136–0.825	0.017

HER2, human epidermal growth factor receptor 2.

4. Discussion

Breast cancer is the most prevalent cancer in women worldwide and accounts for 19.5% of newly diagnosed cancer in China [15]. The most significant prognostic factor in invasive breast cancer is axillary lymph node status. Therefore, dissection of suspected metastatic lymph nodes is necessary. 30% of patients with T1-T2 invasive breast cancer show axillary lymph node involvement [16, 17]. In our study, the positivity rate of ALND was 37.3% which is consistent with previous findings. As surgical techniques underwent improvement, SLNB widely replaced ALND [18]. However, some patients worry about false-negative sentinel lymph nodes and opt for ALND.

Our study shows that lymph node metastasis is highly associated with tumor size and clinical T stage, which is similar to previous studies [19, 20]. We found that expressions of ER, PR, and HER2 were not associated with metastasis which is also consistent with other reports [21]. However, KLAR et al. reported that patients with HER-2-positive breast cancer were likely to develop lymph node metastasis [22]. HAN et al. also reported that ER-positive breast cancer tended to metastasize more frequently [23]. These conflicting observations may be due to the differences in race, tumor stage, and tumor size.

Our ultrasound sensitivity result (40.3%) exhibited a lower value in comparison to findings from other studies. This disparity arises from the fact that our research focused on patients in the early stages of breast cancer, where lymph node metastases tend to be more subtle. In contrast, prior studies often concentrated on patients with advanced breast cancer, which could lead to differences in detectability.

PLR and LRR have been established as biomarkers for inflammation [7, 13, 14]. Lymphocytes play an important role in anti-tumor responses and can either directly kill tumor cells or indirectly activate immune responses and induce tumor cell apoptosis. But, the absolute lymphocyte numbers may be affected by nutritional status, infection, and other factors. The complex interaction between tumor cells and the microenvironment has received renewed attention due to the development of molecular biology. Tumor cell-mediated tissue destruction results in chronic inflammation. Inflammatory cells secrete chemokines and cytokines, leading to DNA damage and genomic instability, which may result in the inactivation of cancer suppressor genes or oncogene activation. Inflammatory cells also induce immune tolerance and immune escape and promote tumor progression and metastasis [5, 6]. We previously showed that LRR is an independent prognostic factor for locally advanced breast cancer [7]. In this study, we used red blood cells to reduce variation and showed that pretreatment LRR might be a predictor of axillary lymph nodes metastasis.

An increase in PLR indicates a relative increase in platelets or a decrease in lymphocytes. When a patient experiences inflammation, the release of interleukin 1, interleukin 3, and interleukin 6 increases platelets which are an integral component of blood coagulation and are one of the indicators of the inflammatory response [24]. Platelets secrete immunosuppressive factors, such as TGF- $\beta$ and vascular endothelial growth factor (VEGF), to induce angiogenesis and promote tumor growth and metastasis. Aggregated platelets also negatively regulate immune responses and help tumor cells avoid immune surveillance. Moreover, interleukin 10 and TGF- $\beta$ may inhibit immune function and reduce lymphocyte counts [25, 26].

Recently, higher PLR has been related to worse prognosis in patients with pancreatic carcinoma, stomach cancer, and ovarian carcinoma [27, 28, 29]. An elevated PLR may result from tumor cells mediated destruction of platelets leading to reactive thrombocytosis in breast cancer. Patients with high PLR are more likely to have metastatic lymph nodes and display poor DFS and OS [13, 14]. Our study shows that PLR is also a good bio-predictor of axillary lymph nodes metastasis. TAKADA et al. reported that a high PLR was associated with tumor metastasis to the sentinel lymph node in T1 Breast Cancer [30]. Morkavuk et al. previously also reported that early breast cancer patients with high PLR showed a higher frequency of sentinel axillary lymph node metastasis [31].

Our study has some limitations that are inherent in its retrospective design. The accuracy of prediction may be low because the preoperative PLR and LRR are easily affected by other diseases such as hematopoietic disease and cerebrovascular diseases. The sample size of our study was relatively small. However, we found statistically significant differences in the two biomarkers.

5. Conclusion

In summary, PLR and LRR could be identified as predictors of LNM in patients with T1/T2 breast cancer.

Footnotes

Acknowledgments

We would like to thank the Changning Maternity and Infant Health Hospital and Shanghai Municipal Health Commission for financial support.

Author contributions

Conception: Haofeng Wang.

Interpretation or analysis of data: Haofeng Wang, Jing Cui, Haiyan Zhao.

Preparation of the manuscript: Haofeng Wang, Jinling Yu, Weida Shen.

Revision for important intellectual content: Haofeng Wang, Beimin Gao.

Supervision: Beimin Gao.

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Goto

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31.

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The ratio of lymphocyte/red blood cells and platelets/lymphocytes are predictive biomarkers for lymph node metastasis in patients with breast cancer

Abstract

BACKGROUND:

METHODS:

RESULTS:

CONCLUSIONS:

Keywords

1. Introduction

2.1 Patients

Table 1 Clinicopathological characteristics of 166 patients

3.1 Clinical characteristics

3.2 Association of LRR and PLR with LNM

5. Conclusion

Footnotes

Acknowledgments

Author contributions

References

Table 1
Clinicopathological characteristics of 166 patients