Clinical verification of the relationship between serum lipid metabolism and immune activity in breast cancer patients treated with neoadjuvant chemotherapy

doi:10.21203/rs.3.rs-1759677/v2

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Research Article

Clinical verification of the relationship between serum lipid metabolism and immune activity in breast cancer patients treated with neoadjuvant chemotherapy

https://doi.org/10.21203/rs.3.rs-1759677/v2

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Journal Publication

published 02 Jan, 2023

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Background: The have been recent reports that lipid metabolism affects the prognosis and tumor immune activity in cancer patients. However, the effect of lipid metabolism on chemosensitivity in patients with breast cancer treated with neoadjuvant chemotherapy (NAC) remains unclear.

Methods: We examined 327 patients with breast cancer who were treated with NAC followed by curative surgery. The correlations between the serum levels of total cholesterol (TC) and triglyceride (TG) and the clinicopathological features, including the efficacy of NAC, neutrophil-to-lymphocyte ratio (NLR), and absolute lymphocyte count (ALC), were evaluated retrospectively.

Results: Serum TG levels were increased after NAC in all the subtypes, and the rate of change was the highest, especially in triple-negative breast cancer (TNBC) (21.0% → 48.1%). In addition, only TNBC patients with an objective response (OR) had significantly higher TG levels after NAC than those without (P = 0.049). Patients with a high ALC before NAC had significantly higher TG levels after NAC than patients with breast cancer (P = 0.001), HER2-enriched breast cancer (P = 0.021), and TNBC (P = 0.008). Patients with a low NLR before NAC had significantly higher TG levels after NAC only among patients with TNBC (P = 0.025). In patients with human epidermal growth factor receptor 2-enriched breast cancer, the group with normal TC levels before NAC had significantly better OS than those with high TC levels (P = 0.013, log-rank test), and in patients with TNBC, the group with high TC levels after NAC had significantly better OS than those with normal TC levels (P = 0.014, log-rank test).

Conclusions: Good systemic immune activity and chemosensitivity may be associated with lipid metabolism regulated by NAC in TNBC patients.

breast cancer

tumor immune activity

lipid metabolism

neoadjuvant chemotherapy

Neoadjuvant chemotherapy (NAC) is the gold standard treatment for breast cancer and its use has increased the rate of breast-conserving surgery [1, 2]. In addition, the pathological complete response (pCR) after NAC is a predictor of good outcome, and its prognostic value is greatest in aggressive subtypes, human epidermal growth factor receptor 2 (HER2)-enriched, and triple-negative breast cancer (TNBC) [3]. These intrinsic breast cancer subtypes have a high malignancy and immune activity. We have reported previously that immune-related biomarkers, including the neutrophil-lymphocyte ratio (NLR) or tumor-infiltrating lymphocytes in biopsy specimens before NAC, are associated significantly with high pCR rates in these breast cancer subtypes [4].

Immunometabolism has become a relatively new field in cancer immunotherapy, and it has been recognized that the regulation of metabolism can enhance antitumor immunity [5–7]. Chemotherapy enhances antitumor immune responses [17, 18]. Some studies have revealed that changes in the lymphocytic subpopulations after NAC can be used as prognostic markers in patients with breast cancer patients [19–22]. In contrast, other studies have examined the metabolic changes before and after chemotherapy in breast cancer patients and showed significant changes in lipid levels [23, 24]. Furthermore, Tian et al. reported that NAC exerts an adverse effect on lipid levels during chemotherapy [25].

In the case of lipid metabolism, obesity has been shown to be associated positively with breast cancer risk in postmenopausal hormone receptor-positive women [8, 9]. In addition, while epidemiological evidence has shown no association between the use of agents for dyslipidemia, mainly statins, and reduced breast cancer incidence, it supports a protective effect of these drugs on reducing breast cancer recurrence or mortality [10]. Moreover, several basic studies have shown that statins can suppress cancer cell proliferation, exert anti-angiogenic effects, and reduce the invasiveness and metastatic potential of breast cancer cells [11–16]. However, the relationship between lipid metabolism and immune activity has not been investigated sufficiently in clinical practice.

The present study investigated the correlation between lipid metabolism, antitumor immune responses, and chemosensitivity in patients with breast cancer treated with NAC.

Patient Background

Data from the Osaka City University Graduate School of Medicine (Osaka, Japan) between April 2007 and March 2018 were analyzed. In total, 327 patients were diagnosed with breast cancer and treated with NAC. T and N factors and tumor stage were stratified based on the TNM Classification, UICC Seventh Edition [26]. Tumors were classified into intrinsic subtypes according to the immunohistochemical expression of the estrogen receptor (ER), progesterone receptor (PgR), and HER2. We defined ER+ and/or PgR+ and HER2- breast cancer as luminal, ER+ and/or PgR+ and HER2+ breast cancer as luminal-HER2, ER- and PgR-, HER2+ breast cancer as HER2-enriched, and ER-, PgR-, and HER2- breast cancer as TNBC. The antitumor effect was assessed according to the Response Evaluation Criteria in Solid Tumors [27]. The objective response (OR) was calculated as the sum of the clinical partial response and complete response (CR). All the patients underwent mastectomy or breast-conserving surgery after NAC. The pCR was defined as the complete disappearance of the invasive compartment of the lesion with or without intraductal components, including the lymph nodes” [28]. Postoperative adjuvant therapy suitable for each intrinsic breast cancer subtype, and standard postoperative radiotherapy to the remnant breast was administered, if necessary. All the patients underwent physical examinations, blood tests, ultrasonography, computed tomography, and bone scintigraphy scans. Overall survival (OS) was defined as the time from curative surgery to death from any cause, and recurrence-free survival (RFS) was defined as freedom from all locoregional and distant recurrences. The median follow-up time for the assessment of OS was 5.5 years (range, 0.2–12.4 years) and for RFS was 4.9 years (range, 0.1–12.0 years).

Blood Sample Analysis

Peripheral blood samples were obtained at the time of diagnosis, and preoperative blood samples were obtained within a week before surgery. We evaluated the serum lipid levels, including total cholesterol (TC) levels (categorized as low (≤ 149 mg/dl), normal (150–219 mg/dl), and high (≥ 220 mg/dl)) and triglyceride (TG) levels (categorized as low (≤ 49 mg/dl), normal (50–149 mg/dl), and high (≥ 150 mg/dl)). The differential white blood cell counts were analyzed using a Coulter LH 750 Hematology Analyzer (Beckman Coulter, Brea, CA, USA). The neutrophil-to-lymphocyte ratio (NLR) was calculated from the blood samples by dividing the absolute neutrophil count by the absolute lymphocyte count (ALC).

Statistical Analyses

Statistical analyses were performed using the JMP13 software (SAS Institute, Cary, NC, USA). Associations among the variables were analyzed using the χ² or Fisher’s exact test, as appropriate. OS and RFS were estimated using the Kaplan–Meier method and log-rank test. Statistical significance was set at P < 0.05.

Clinicopathological responses of all the breast cancer patients to NAC

The differences in clinicopathological features due to intrinsic breast cancer subtypes are presented in Table 1. A total of 327 patients were included in this study. Among these, 108 (33.0%), 42 (12.9%), 72 (22.0%), and 105 (32.1%) had luminal, luminal-HER2, HER2-enriched, and TNBC, respectively. NAC-related pCR was observed in 121 patients (37.0%). The evaluation based on the clinicopathological features revealed that the pCR rate was significantly higher in HER2-enriched (59.7%, 43/72) and TNBC patients (44.8%, 47/105) (P < 0.001). OR was observed in 295 patients (90.2%). The OR rate was high in all the breast cancer subtypes, and no significant differences were observed (P = 0.070). Other than the HER2-enriched subtype, the number of patients with high TC levels increased after NAC in each breast cancer subtype. Furthermore, patients with TG levels increased after NAC in all subtypes with the rate of change being the highest in TNBC (21.0% → 48.1%).

Table 1

Differences in clinicopathological features due to intrinsic breast cancer subtypes in 327 patients.
Parameters	Intrinsic subtype				p value
Parameters	Luminal (n = 108)	Luminal-HER2 (n = 42)	HER2-enriched (n = 72)	TNBC (n = 105)	p value
Age at operation ≤54 >54	59 (54.6%) 49 (45.4%)	24 (57.1%) 18 (42.9%)	26 (36.1%) 46 (63.9%)	55 (52.4%) 50 (47.6%)	0.054
Menopause Pre- Post-	47 (43.5%) 61 (56.5%)	22 (52.4%) 20 (47.6%)	16 (22.9%) 54 (77.1%)	36 (35.0%) 67 (65.0%)	0.006
BMI ≤22.0 >22.0	48 (44.4%) 60 (55.6%)	21 (50.0%) 21 (50.0%)	42 (58.3%) 30 (41.7%)	53 (50.5%) 52 (49.5%)	0.341
Tumor size ≤2 cm >2 cm	13 (12.0%) 95 (88.0%)	9 (21.4%) 33 (78.6%)	9 (12.5%) 63 (87.5%)	14 (13.3%) 91 (86.7%)	0.528
Lymph node status Negative Positive	27 (25.0%) 81 (75.0%)	22 (52.4%) 20 (47.6%)	26 (36.1%) 46 (63.9%)	30 (28.6%) 75 (71.4%)	0.011
TC (preNAC) Normal High	52 (54.2%) 44 (45.8%)	21 (60.0%) 14 (40.0%)	39 (60.9%) 25 (39.1%)	49 (51.6%) 46 (48.4%)	0.632
TG (preNAC) Normal High	76 (79.2%) 20 (20.8%)	28 (77.8%) 8 (22.2%)	48 (78.7%) 13 (21.3%)	75 (79.0%) 20 (21.0%)	0.999
TC (postNAC) Normal High	35 (37.6%) 58 (62.4%)	15 (50.0%) 15 (50.0%)	36 (62.1%) 22 (37.9%)	33 (38.4%) 53 (61.6%)	0.014
TG (postNAC) Normal High	53 (58.9%) 37 (41.1%)	16 (55.2%) 13 (44.8%)	33 (62.3%) 20 (37.7%)	42 (51.9%) 39 (48.1%)	0.649
Obejective response rate non-ORR ORR	11 (10.2%) 97 (89.8%)	6 (14.3%) 36 (85.7%)	2 (2.8%) 70 (97.2%)	13 (12.4%) 92 (87.6%)	0.070
Pathological response non-pCR pCR	89 (82.4%) 19 (17.6%)	30 (71.4%) 12 (28.6%)	29 (40.3%) 43 (59.7%)	58 (55.2%) 47 (44.8%)	< 0.001
BMI, body mass index. HER2, human epidermal growth factor receptor 2. NAC, neoadjuvant chemotherapy. ORR, objective response rate. pCR, pathological complete response. TC, total-cholesterol. TG, triglyceride. TNBC, triple-negative breast cancer.

In all breast cancer patients, RFS and OS were significantly longer in patients who achieved pCR than in those who did not (P < 0.001 and P = 0.006, log-rank, respectively) (Supplementary Fig. 1a, 2a). Furthermore, these outcomes were also significantly better in patients who achieved OR than in those who did not (P < 0.001 and P = 0.001, log-rank, respectively) (Supplementary Fig. 3a, 4a). Additionally, we investigated the prognostic factors for RFS and OS for each breast cancer subtype. Among patients with luminal cancer, no significant differences were observed in RFS (P = 0.882, P = 0.399, log-rank, respectively) and OS (P = 0.861, P = 0.202, log-rank, respectively) according to the clinicopathological responses, pCRs, and ORs (Supplementary Fig. S1b, 2b, 3b, 4b). In contrast, among the patients with TNBC, RFS (P = 0.005, P < 0.001, log-rank, respectively) and OS (P = 0.003, P < 0.001, log-rank, respectively) were significantly longer in patients who achieved pCR or OR than in those who did not (Supplementary Fig. S1e, 2e, 3e, 4e).

Analysis of relationships between lipid metabolism and chemosensitivity and prognosis.

The relationship between lipid metabolism and chemosensitivity was examined (Table 2). There were no significant correlations between lipid metabolism and the pCRs in any breast cancer subtype. In contrast, only TNBC patients with OR had significantly higher TG levels after NAC than patients without OR (P = 0.049).

Table 2

Relationships between lipid metabolism and chemosensitivity.
	pCR			OR
	Negative	Positive	p-value	Negative	Positive	p-value
All breast cancer (n = 327)
TC (preNAC) Normal High	98 (54.1%) 83 (45.9%)	63 (57.8%) 46 (42.2%)	0.626	13 (44.8%) 16 (55.2%)	148 (56.7%) 113 (43.3%)	0.242
TG (preNAC) Normal High	139 (76.8%) 42 (23.2%)	88 (82.2%) 19 (17.8%)	0.299	24 (80.0%) 6 (20.0%)	203 (78.7%) 55 (21.3%)	0.866
TC (postNAC) Normal High	72 (43.4%) 94 (56.6%)	47 (46.5%) 54 (53.5%)	0.703	11 (44.0%) 14 (56.0%)	108 (44.6%) 134 (55.4%)	0.952
TG (postNAC) Normal High	88 (55.7%) 70 (44.3%)	56 (59.0%) 39 (41.0%)	0.694	15 (62.5%) 9 (37.5%)	129 (56.3%) 100 (43.7%)	0.667
Luminal (n = 108)
TC (preNAC) Normal High	43 (55.1%) 35 (44.9%)	9 (50.0%) 9 (50.0%)	0.795	4 (44.4%) 5 (55.6%)	48 (55.2%) 39 (44.8%)	0.728
TG (preNAC) Normal High	60 (76.9%) 18 (23.1%)	16 (88.9%) 2 (11.1%)	0.347	8 (88.9%) 1 (11.1%)	68 (78.2%) 19 (21.8%)	0.680
TC (postNAC) Normal High	27 (35.5%) 49 (64.5%)	8 (47.1%) 9 (52.9%)	0.415	2 (28.6%) 5 (71.4%)	33 (38.4%) 53 (61.6%)	0.707
TG (postNAC) Normal High	42 (57.5%) 31 (42.5%)	11 (64.7%) 6 (35.3%)	0.785	4 (66.7%) 2 (33.3%)	49 (58.3%) 35 (41.7%)	0.685
Luminal-HER (n = 42)
TC (preNAC) Normal High	14 (58.3%) 10 (41.7%)	7 (63.6%) 4 (36.4%)	0.766	3 (60.0%) 2 (40.0%)	18 (60.0%) 12 (40.0%)	1.000
TG (preNAC) Normal High	17 (68.0%) 8 (32.0%)	11 (100.0%) 0 (0.0%)	0.076	3 (50.0%) 3 (50.0%)	25 (83.3%) 5 (16.7%)	0.109
TC (postNAC) Normal High	10 (50.0%) 10 (50.0%)	5 (50.0%) 5 (50.0%)	1.000	1 (20.0%) 4 (80.0%)	14 (56.0%) 11 (44.0%)	0.330
TG (postNAC) Normal High	9 (45.0%) 11 (55.0%)	7 (77.8%) 2 (22.2%)	0.130	1 (20.0%) 4 (80.0%)	15 (62.5%) 9 (37.5%)	0.144
HER2-enriched (n = 72)
TC (preNAC) Normal High	14 (53.9%) 12 (46.1%)	25 (65.8%) 13 (34.2%)	0.436	1 (50.0%) 1 (50.0%)	38 (61.3%) 24 (38.7%)	0.750
TG (preNAC) Normal High	20 (80.0%) 5 (20.0%)	28 (77.8%) 8 (22.2%)	0.835	2 (100.0%) 0 (0.0%)	46 (78.0%) 13 (22.0%)	0.323
TC (postNAC) Normal High	15 (60.0%) 10 (40.0%)	21 (63.6%) 12 (36.4%)	0.792	2 (100.0%) 0 (0.0%)	34 (60.7%) 22 (39.3%)	0.521
TG (postNAC) Normal High	15 (65.2%) 8 (34.8%)	18 (60.0%) 12 (40.0%)	0.779	1 (50.0%) 1 (50.0%)	32 (62.8%) 19 (37.2%)	0.719
TNBC (n = 105)
TC (preNAC) Normal High	27 (50.9%) 26 (49.1%)	22 (52.4%) 20 (47.6%)	0.889	5 (38.5%) 8 (61.5%)	44 (53.7%) 38 (46.3%)	0.378
TG (preNAC) Normal High	42 (79.3%) 11 (20.7%)	33 (78.6%) 9 (21.4%)	0.936	11 (84.6%) 2 (15.4%)	64 (78.1%) 18 (21.9%)	0.729
TC (postNAC) Normal High	20 (44.5%) 25 (55.6%)	13 (31.7%) 28 (68.3%)	0.270	6 (54.6%) 5 (45.4%)	27 (36.0%) 48 (64.0%)	0.322
TG (postNAC) Normal High	22 (52.4%) 20 (47.6%)	20 (51.3%) 19 (48.7%)	0.921	9 (81.8%) 2 (18.2%)	33 (47.1%) 37 (52.9%)	0.049
HER2, human epidermal growth factor receptor 2. NAC, neoadjuvant chemotherapy. TC, total-cholesterol. TG, triglyceride. TNBC, triple-negative breast cancer.

We also investigated the prognostic value of serum lipid levels before and after NAC for each intrinsic breast cancer subtype. In patients with HER2-enriched breast cancer, those with normal TC levels before NAC had a significantly better OS than those with high TC levels (P = 0.013, log-rank test) (Fig. 1d), and in patients with TNBC, the group with high TC levels after NAC had significantly better OS than those with normal TC levels (P = 0.014, log-rank test) (Fig. 2e).

Analysis of relationships between lipid metabolism and immune activity.

The pre-NAC ALC ranged from 712.8–4446.2 (mean, 1811.0; median, 1749; standard deviation, 613.9), and the pre-NAC NLR ranged from 0.5–10.6 (mean, 2.3; median, 2.0; standard deviation, 1.2). The post-NAC ALC ranged from 285.6–3697.7 (mean, 1122.4; median, 1005.4; standard deviation, 517.0), and the post-NAC NLR ranged from 0.3–15.9 (mean, 2.9; median, 2.4; standard deviation, 1.9). We defined the pre-NAC median as the cutoff value for the ALC and NLR. There were no significant correlations between the systemic immune activity and the effect of NAC in all the breast cancer patients or each of the breast cancer subtypes (Supplementary Table S1).

The relationship between lipid metabolism and systemic immune activity is shown in Table 3. Patients with a high ALC before NAC had significantly higher TG levels after NAC in all the breast cancers (p = 0.001). In addition, among the patients with HER2-enriched breast cancer, high TG levels after NAC were associated significantly with a high ALC before NAC (P = 0.021), and high TG levels before NAC were associated significantly with a high ALC after NAC (P = 0.046). Furthermore, among patients with TNBC, high TG levels after NAC were associated significantly with a high ALC (P = 0.008) and a low NLR (P = 0.025) before NAC, while high TG levels before NAC were associated significantly with a low NLR after NAC (P = 0.034).

Table 3

Relationships between lipid metabolism and immune activity.
	ALC (pre-NAC)			NLR (pre-NAC)			ALC (post-NAC)			NLR (post-NAC)
	Low	High	p-value	Low	High	p-value	Low	High	p-value	Low	High	p-value
All breast cancer (n = 327)
TC (preNAC) Normal High	82 (56.9%) 62 (43.1%)	79 (54.1%) 67 (45.9%)	0.638	76 (53.2%) 67 (46.8%)	85 (57.8%) 62 (42.2%)	0.479	145 (56.2%) 113 (43.8%)	15 (50.0%) 15 (50.0%)	0.564	59 (55.7%) 47 (44.3%)	101 (55.5%) 81 (44.5%)	0.978
TG (preNAC) Normal High	117 (81.8%) 26 (18.2%)	110 (75.9%) 35 (24.1%)	0.249	112 (79.4%) 29 (20.6%)	115 (78.2%) 32 (21.8%)	0.886	205 (80.1%) 51 (19.9%)	20 (66.7%) 10 (33.3%)	0.101	81 (77.1%) 24 (22.9%)	144 (79.6%) 37 (20.4%)	0.655
TC (postNAC) Normal High	60 (47.6%) 66 (52.4%)	59 (41.8%) 82 (58.2%)	0.388	60 (41.1%) 86 (58.9%)	59 (48.8%) 62 (51.2%)	0.219	105 (43.8%) 135 (56.2%)	14 (56.0%) 11 (44.0%)	0.292	51 (50.5%) 50 (49.5%)	68 (41.5%) 96 (58.5%)	0.163
TG (postNAC) Normal High	81 (68.6%) 37 (31.4%)	63 (46.7%) 72 (53.3%)	0.001	73 (52.9%) 65 (47.1%)	71 (61.7%) 44 (38.3%)	0.164	129 (56.8%) 98 (43.2%)	13 (54.2%) 11 (45.8%)	0.803	55 (56.7%) 42 (43.3%)	87 (56.5%) 67 (43.5%)	0.974
Luminal (n = 108)
TC (preNAC) Normal High	25 (58.1%) 18 (41.9%)	27 (50.9%) 26 (49.1%)	0.540	28 (52.8%) 25 (47.2%)	24 (55.8%) 19 (44.2%)	0.838	48 (55.2%) 39 (44.8%)	4 (44.4%) 5 (55.6%)	0.728	16 (50.0%) 16 (50.0%)	36 (56.3%) 28 (43.7%)	0.665
TG (preNAC) Normal High	35 (81.4%) 8 (18.6%)	41 (77.4%) 12 (22.6%)	0.801	41 (77.4%) 12 (22.6%)	35 (81.4%) 8 (18.6%)	0.801	69 (79.3%) 18 (20.7%)	7 (77.8%) 2 (22.2%)	0.915	29 (90.6%) 3 (9.4%)	47 (73.4%) 17 (26.6%)	0.064
TC (postNAC) Normal High	15 (36.6%) 26 (63.4%)	20 (38.5%) 32 (61.5%)	0.853	20 (35.7%) 36 (64.3%)	15 (40.5%) 22 (59.5%)	0.667	31 (37.8%) 51 (62.2%)	4 (36.4%) 7 (63.6%)	0.926	16 (44.4%) 20 (55.6%)	19 (33.3%) 38 (66.7%)	0.380
TG (postNAC) Normal High	25 (64.1%) 14 (35.9%)	28 (54.9%) 23 (45.1%)	0.397	34 (63.0%) 20 (37.0%)	19 (52.8%) 17 (47.2%)	0.386	45 (57.0%) 34 (43.0%)	8 (72.7%) 3 (27.3%)	0.515	22 (62.9%) 13 (37.1%)	31 (56.4%) 24 (43.6%)	0.661
Luminal-HER (n = 42)
TC (preNAC) Normal High	13 (72.2%) 5 (27.8%)	8 (47.1%) 9 (52.9%)	0.176	10 (52.6%) 9 (47.4%)	11 (68.8%) 5 (31.2%)	0.491	19 (65.5%) 10 (34.5%)	1 (20.0%) 4 (80.0%)	0.135	9 (56.3%) 7 (43.7%)	11 (61.1%) 7 (38.9%)	0.774
TG (preNAC) Normal High	14 (73.7%) 5 (26.3%)	14 (82.4%) 3 (17.6%)	0.695	17 (89.5%) 2 (10.5%)	11 (64.7%) 6 (35.3%)	0.114	23 (76.7%) 7 (23.3%)	4 (80.0%) 1 (20.0%)	0.868	13 (81.3%) 3 (18.7%)	14 (73.7%) 5 (26.3%)	0.700
TC (postNAC) Normal High	10 (58.8%) 7 (41.2%)	5 (38.5%) 8 (61.5%)	0.462	8 (57.1%) 6 (42.9%)	7 (43.8%) 9 (56.2%)	0.715	14 (51.9%) 13 (48.1%)	1 (50.0%) 1 (50.0%)	0.960	7 (53.9%) 6 (46.1%)	8 (50.0%) 8 (50.0%)	0.837
TG (postNAC) Normal High	11 (64.7%) 6 (35.3%)	5 (41.7%) 7 (58.3%)	0.274	7 (53.9%) 6 (46.1%)	9 (56.3%) 7 (43.7%)	0.897	15 (57.7%) 11 (42.3%)	0 (0.00%) 2 (100.0%)	0.206	6 (46.2%) 7 (53.8%)	9 (60.0%) 6 (40.0%)	0.705
HER2-enriched (n = 72)
TC (preNAC) Normal High	20 (60.6%) 13 (39.4%)	19 (61.3%) 12 (38.7%)	0.955	16 (61.5%) 10 (38.5%)	23 (60.5%) 15 (39.5%)	0.935	33 (62.3%) 20 (37.7%)	6 (54.6%) 5 (45.4%)	0.738	16 (61.5%) 10 (38.5%)	23 (60.5%) 15 (39.5%)	0.935
TG (preNAC) Normal High	26 (83.9%) 5 (16.1%)	22 (73.3%) 8 (26.7%)	0.363	20 (83.3%) 4 (16.7%)	28 (75.7%) 9 (24.3%)	0.539	42 (84.0%) 8 (16.0%)	6 (54.6%) 5 (45.4%)	0.046	18 (72.0%) 7 (28.0%)	30 (83.3%) 6 (16.7%)	0.349
TC (postNAC) Normal High	16 (66.7%) 8 (33.3%)	20 (58.8%) 14 (41.2%)	0.593	17 (58.6%) 12 (41.4%)	19 (65.5%) 10 (34.5%)	0.787	30 (60.0%) 20 (40.0%)	6 (75.0%) 2 (25.0%)	0.697	16 (72.7%) 6 (27.3%)	20 (55.6%) 16 (44.4%)	0.267
TG (postNAC) Normal High	18 (81.8%) 4 (18.2%)	15 (48.4%) 16 (51.6%)	0.021	14 (53.9%) 12 (46.1%)	19 (70.4%) 8 (29.6%)	0.264	29 (63.0%) 17 (37.0%)	4 (57.1%) 3 (42.9%)	0.766	13 (65.0%) 7 (35.0%)	20 (60.6%) 13 (39.4%)	0.779
TNBC (n = 105)
TC (preNAC) Normal High	24 (48.0%) 26 (52.0%)	25 (55.6%) 20 (44.4%)	0.539	22 (48.9%) 23 (51.1%)	27 (54.0%) 23 (46.0%)	0.683	45 (50.6%) 44 (49.4%)	4 (80.0%) 1 (20.0%)	0.364	18 (56.3%) 14 (43.7%)	31 (50.0%) 31 (50.0%)	0.664
TG (preNAC) Normal High	42 (84.0%) 8 (16.0%)	33 (73.3%) 12 (26.7%)	0.220	34 (75.6%) 11 (24.4%)	41 (82.0%) 9 (18.0%)	0.462	71 (79.8%) 18 (20.2%)	3 (60.0%) 2 (40.0%)	0.287	21 (65.6%) 11 (34.4%)	53 (85.5%) 9 (14.5%)	0.034
TC (postNAC) Normal High	19 (43.2%) 25 (56.8%)	14 (33.3%) 28 (66.7%)	0.382	15 (31.9%) 32 (68.1%)	18 (46.2%) 21 (53.8%)	0.190	30 (37.0%) 51 (63.0%)	3 (75.0%) 1 (25.0%)	0.294	12 (40.0%) 18 (60.0%)	21 (38.2%) 34 (61.8%)	0.870
TG (postNAC) Normal High	27 (67.5%) 13 (32.5%)	15 (36.6%) 26 (63.4%)	0.008	18 (40.0%) 27 (60.0%)	24 (66.7%) 12 (33.3%)	0.025	40 (52.6%) 36 (47.4%)	1 (25.0%) 3 (75.0%)	0.353	14 (48.3%) 15 (51.7%)	27 (52.9%) 24 (47.1%)	0.817
ALC, absolute lymphocyte count. HER2, human epidermal growth factor receptor 2. NAC, neoadjuvant chemotherapy. NLR, neutrophil-to-lymphocyte ratio. TC, total-cholesterol. TG, triglyceride. TNBC, triple-negative breast cancer.

In the present study, NAC increased serum TG levels, particularly in patients with TNBC. Some previous studies showed that serum lipid levels increased significantly after chemotherapy and that the TG levels may be a sensitive biomarker for determining the effect of adjuvant chemotherapy [23, 29]. However, this phenomenon has not yet been fully studied. To the best of our knowledge, our study was the first to analyze the predictive value of lipid metabolism for chemosensitivity of breast cancer patients treated with NAC and to stratify the intrinsic subtypes of breast cancer.

In this study, patients with reduced tumor size had significantly higher TG levels after NAC in only TNBC. Sharma et al. reported that some chemotherapy agents affect serum lipid levels by regulating the expression of genes involved in lipid metabolism in liver cells [30]. Therefore, there is a correlation between the effects of NAC and lipid metabolism in TNBC.

The efficacy of NAC, especially in terms of the pCR, is currently acknowledged as an indicator of good outcomes in patients with TNBC and HER2-enriched breast cancer, which have high immune activity [3, 31, 32]. Hence, it is expected that there will be an association with lipid metabolism and tumor immune activity in TNBC. Recent studies have reported that the regulation of metabolism can affect the tumor immune microenvironment and enhance the antitumor immune response [5–7]. In our study, good systemic immune activity, a high ALC, or low NLR before NAC were associated significantly with high TG levels after NAC in patients with TNBC or HER2-enriched breast cancer.

However, no relationships were observed between the pre-NAC lipid levels and NAC efficacy. In addition, the serum lipid levels before NAC showed no significant relationships with the ALC or NLR. Hence, it was difficult to predict chemosensitivity or systemic immune activity based on serum lipid levels prior to NAC.

In the present study, no significant associations were observed between the systemic immune activity and the effect of NAC. However, in our previous study, we set the cut-off value of pre-NAC NLR to 3.0, in the same breast cancer patients, and the pCR rate was significantly higher in TNBC patients with a good immune status and low NLR [4]. This result suggested that not only the effect of tumor reduction, but also the effect of increasing serum lipid levels is recognized in patients with good systemic immune activity.

Although the TG levels after NAC may be an indicator of chemosensitivity in TNBC, they are not useful predictive markers of recurrence. The reason for this may be that changes in the lipid profiles after NAC are temporary [25]. We presumed that a favorable prognosis may not be based on lipid levels at the time of diagnosis or after NAC, but is induced by the maintenance good lipid metabolism after surgery.

This study has some limitations. First, this was a single-center, retrospective study. Second, in our study, serum TC levels were associated with better OS in patients with HER2-enriched breast cancer or TNBC. However, we did not have detailed data on high-density lipoprotein cholesterol and low-density lipoprotein cholesterol levels. In addition, many factors influence serum lipid levels, including lifestyle and adherence to medication. Considering these limitations, further prospective multicenter studies are needed.

This was the first study to demonstrate the clinical relationships between lipid metabolism, chemosensitivity, and systemic immune activity in patients with breast cancer treated with NAC. The findings of this study indicated that a good systemic immune activity and the effect of NAC may be associated with lipid metabolism regulated by chemotherapy in patients with TNBC.

ALC: absolute lymphocyte count, BMI: body mass index, CR: complete response, ER: estrogen receptor, HER2: human-epidermal growth factor receptor 2, NAC: neoadjuvant chemotherapy, NLR: neutrophil-to-lymphocyte ratio, OR: objective response, ORR: objective response rate, OS: overall survival, pCR: pathological complete response, PgR: progesterone receptor, RFS: recurrence-free survival, TC: total-cholesterol, TG: triglyceride, TNBC: triple-negative breast cancer.

Ethics approval and consent to participate

A written informed consent to participate in the study was obtained from each subject in accordance with the declaration of Helsinki principles. Each patient or the patient’s family was fully informed of the investigational nature of this study and provided their written, informed consent. The study protocol was approved by the Ethics Committee of Osaka City University (approve number #926).

Consent for publication

Not applicable.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Competing interests

The authors declare that they have no competing interests.

Funding

This study was supported in part by Grants-in Aid for Scientific Research (KAKENHI, Nos. 19K18067, 17K10559, and 20K08938) from the Ministry of Education, Science, Sports, Culture and Technology of Japan.

Authors’ contributions

All authors were involved in the preparation of this manuscript. WG collected the data and wrote the manuscript. SK, KT, YA, KO and TM performed the operation and designed the study. WG and SK summarized the data and revised the manuscript. MS, HT, and KM provided a substantial contribution to the study design, performed the operation, and revised the manuscript. All authors read and approved the final manuscript.

Acknowledgements

We thank Tomomi Okawa (Department of Breast Surgical Oncology, Osaka Metropolitan University Graduate School of Medicine) for helpful advice regarding data management.

Author’s information

¹Department of Breast Surgical Oncology, Osaka Metropolitan University Graduate School of Medicine, 1-4-3 Asahi-machi, Abeno-ku, Osaka 545-8585, Japan.

²Department of Gastroenterological Surgery, Osaka Metropolitan University Graduate School of Medicine, 1-4-3 Asahi-machi, Abeno-ku, Osaka 545-8585, Japan.

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No competing interests reported.

SupplementaryFig.S1.tif
Supplement Fig. S1 Recurrence-free survival (RFS) using Kaplan-Meier method in patients based on pCR or non-pCR with different intrinsic breast cancer subtype. All breast cancer (a), Luminal (b), Luminal-human epidermal growth factor receptor 2 (HER2) (c), HER2-enrich (d) and triple-negative breast cancer (e).
SupplementaryFig.S2.tif
Supplement Fig. S2. Overall survival (OS) using Kaplan-Meier method in patients based on pCR or non-pCR with different intrinsic breast cancer subtype. All breast cancer (a), Luminal (b), Luminal-human epidermal growth factor receptor 2 (HER2) (c), HER2-enrich (d) and triple-negative breast cancer (e).
SupplementaryFig.S3.tif
Supplement Fig. S3 Recurrence-free survival (RFS) using Kaplan-Meier method in patients based on OR or non-OR with different intrinsic breast cancer subtype. All breast cancer (a), Luminal (b), Luminal-human epidermal growth factor receptor 2 (HER2) (c), HER2-enrich (d) and triple-negative breast cancer (e).
SupplementaryFig.S4.tif
Supplement Fig. S4 Overall survival (OS) using Kaplan-Meier method in patients based on OR or non-OR with different intrinsic breast cancer subtype. All breast cancer (a), Luminal (b), Luminal-human epidermal growth factor receptor 2 (HER2) (c), HER2-enrich (d) and triple-negative breast cancer (e).
SupplementaryFig.S5.tif
Supplement Fig. S5Recurrence-free survival (RFS) using Kaplan-Meier method in patients based on normal or high-total cholesterol before NAC with different intrinsic breast cancer subtype. All breast cancer (a), Luminal (b), Luminal-human epidermal growth factor receptor 2 (HER2) (c), HER2-enrich (d) and triple-negative breast cancer (e).
SupplementaryFig.S6.tif
Supplement Fig. S6 Recurrence-free survival (RFS) using Kaplan-Meier method in patients based on normal or high-total cholesterol after NAC with different intrinsic breast cancer subtype. All breast cancer (a), Luminal (b), Luminal-human epidermal growth factor receptor 2 (HER2) (c), HER2-enrich (d) and triple-negative breast cancer (e).
SupplementaryFig.S7.tif
Supplement Fig. S7 Recurrence-free survival (RFS) using Kaplan-Meier method in patients based on normal or high-triglyceride before NAC with different intrinsic breast cancer subtype. All breast cancer (a), Luminal (b), Luminal-human epidermal growth factor receptor 2 (HER2) (c), HER2-enrich (d) and triple-negative breast cancer (e).
SupplementaryFig.S8.tif
Supplement Fig. S8Overall survival (OS) using Kaplan-Meier method in patients based on normal or high-triglyceride before NAC with different intrinsic breast cancer subtype. All breast cancer (a), Luminal (b), Luminal-human epidermal growth factor receptor 2 (HER2) (c), HER2-enrich (d) and triple-negative breast cancer (e).
SupplementaryFig.S9.tif
Supplement Fig. S9Recurrence-free survival (RFS) using Kaplan-Meier method in patients based on normal or high-triglyceride after NAC with different intrinsic breast cancer subtype. All breast cancer (a), Luminal (b), Luminal-human epidermal growth factor receptor 2 (HER2) (c), HER2-enrich (d) and triple-negative breast cancer (e).
SupplementaryFig.S10.tif
Supplement Fig. S10Overall survival (RFS) using Kaplan-Meier method in patients based on normal or high-triglyceride after NAC with different intrinsic breast cancer subtype. All breast cancer (a), Luminal (b), Luminal-human epidermal growth factor receptor 2 (HER2) (c), HER2-enrich (d) and triple-negative breast cancer (e).
SupplementatryTableS1.docx

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Clinical verification of the relationship between serum lipid metabolism and immune activity in breast cancer patients treated with neoadjuvant chemotherapy

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Clinicopathological responses of all the breast cancer patients to NAC

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