Impact of changes in serum lactate dehydrogenase levels on pathological response after neoadjuvant chemotherapy in patients with breast cancer

doi:10.21203/rs.3.rs-4152827/v1

Purpose Serum lactate dehydrogenase (LDH) level is a biomarker associated with the prognosis of breast cancer (BC) patients. However, there are no data on serum LDH levels as a dynamic marker in patients undergoing neoadjuvant chemotherapy (NAC) for BC. In the present study, we compared serum LDH levels at different periods during NAC. We related them to clinicopathologic characteristics and pathologic complete response (pCR) rates in patients with BC.

Patients and methods We retrospectively analyzed the clinicopathological data and pCR rates of 691 non-metastatic BC patients from the Harbin Medical University Cancer Hospital from January 1, 2013, to December 31, 2019. Categorical data were compared using the chi-square test and Fisher's exact test for multivariate data using Logistic regression models. Any predictor variable with P < 0.05 in the univariate analysis was included in the multivariate regression analysis to study the relationship between different serum LDH level groups and pCR.

Results A total of 557 patients were included in the cohort for the analysis. Before BC patients underwent NAC, a total of 510 (91.6%) patients had serum LDH levels below 230 U/L, and after completing half of the chemotherapy cycles, the number of patients with high expression of serum LDH levels gradually increased to about 37.7%. At the end of the complete cycle of chemotherapy for routine preoperative examination, 246 (44.2%) BC patients were in a state of high serum LDH expression. Patients with high expression of serum LDH levels were more likely to achieve pCR. Serum LDH levels in mid-NAC, clinical T-stage, and human epidermal growth factor receptor-2 (HER-2) expression were independent predictors of achieving pCR in patients with BC (P < 0.05).

Conclusion Our findings suggest that serum LDH level is an essential predictor of chemotherapeutic efficacy in BC patients, and we need to pay more attention to this biomarker to individualize treatment, which will help us to treat BC better and provide new targets and blueprints for our clinical treatment.

Breast cancer

Neoadjuvant chemotherapy

Pathologic complete response

Biomarker

Lactate dehydrogenase

By the end of 2020, up to 2.3 million people will be diagnosed with BC globally, an increase of 126,000 from 2019, surpassing lung cancer as the most critical new case in the world ^1,2. BC is a heterogeneous disease with different clinical and biological characteristics ³. The essence of BC is that various oncogenic factors act together on breast epithelial cells, which are stimulated to proliferate abnormally, and the cancer cells are not close to each other and can easily detach. Once the cancer cells are detached, they can metastasize throughout the body by various routes, such as the bloodstream or the lymphatic system ⁴. As BC progresses, it will change certain substances in the bloodstream. The search for appropriate circulating biomarkers can help determine the metastatic status of BC, which is of great significance to the treatment of BC ⁵.

In recent years, increasing serum markers have been identified as prognostic factors for BC, including circulating tumor cells, inflammatory factors, and stem cell markers ^6,7,8. Serum LDH levels are the simplest and least expensive test relative to other biomarkers. LDH is a 140-kDa tetrameric molecule. It is mainly found in the cytoplasm, but experts have also found LDH in the mitochondria and the nucleus. LDH plays a role in the nucleus as a single-stranded binding protein (SSB), which may be involved in DNA replication and transcription ⁹.

Altered energy metabolism has been recognized as one of the hallmarks of cancer and has been associated with cancer metastasis and patient survival ¹⁰. LDH, a key enzyme in glycolysis, converts pyruvate to lactate with the help of nicotinamide adenine dinucleotide (NADH) ¹¹. At the same time, low pH conditions are a hallmark of tumor malignancy. They may influence exosome release and uptake by tumor cells, which play a crucial role in inducing extracellular matrix degradation and angiogenesis ¹². Suppose normal cells are exposed to this environment for a prolonged period. The acidification of the microenvironment will provide a selective growth advantage for cells that have lost their wild-type p53 function, leading to clonal expansion of abnormal cell populations ¹³. In addition, the metabolic activities of the surrounding normal cells are reduced in the hypoxic environment, and the metabolites produced stimulate the growth and proliferation of tumor cells. In the treatment of tumors, hypoxia is also an essential factor affecting the therapeutic effect ¹⁴. Serum LDH levels can reflect the degree of hypoxia in tumor cells and are known markers of hypoxia to assess the degree of proliferation and metastasis of tumor cells ¹⁵.

Experts have found that LDH allows tumor cells to inhibit and evade the immune system by altering the tumor microenvironment and that LDH promotes resistance to chemotherapy and radiation ¹⁶. When patients undergo surgery, serum LDH levels drop rapidly, which is a side effect of the fact that LDH does play a role in tumor formation ¹⁷. Elevated levels of serum LDH also result in a heavier tumor load, and a higher tumor load represents more cancer foci in the body; the tumor size will be bigger, and the number of cancer cells will be more ¹⁸. In addition, we also need to pay attention to the cut-off point of serum LDH level because, in previous studies, the cut-off point of LDH is unclear. Zhang conducted a meta-analysis, and they identified a total of 68 eligible studies, including 31,857 BC patients. The experts found high serum LDH levels were inversely associated with patients' OS, but changes in the serum LDH cut-off did not affect patients' prognosis ¹⁹.

Serum LDH levels are associated with prognosis in patients with a variety of malignant tumors, including lung, cervical, colorectal, gastric, and melanoma ^{20, 21, 22, 23, 24}. In BC, the relationship between serum LDH levels and clinical outcomes has also been extensively studied; however, to the best of our knowledge, the clinical significance of serum LDH levels in patients with BC undergoing NAC remains unknown, and the results of the current study are conflicting. This study aimed to analyze and compare the clinical characteristics, pathological features, molecular subtypes, and therapeutic approaches of different serum LDH level groups in Chinese female patients with non-metastatic BC and to assess the pCR rate of different serum LDH level groups after treatment with NAC.

2.1. Patients and treatments

We conducted a retrospective cohort study, collected from January 1, 2013, to December 31, 2019, in Harbin Medical University cancer hospital treatment of patients after physical examination, imaging examination (ultrasound, X-ray), breast mass hollow needle biopsy confirmed as BC, after communication with patients and their families, agreed to NAC, completed the chemotherapy cycle with our hospital operation. Before the treatment, the personal clinical and pathological data were explained to the patients and their families to be used for clinical research. The patients agreed and signed the informed consent for the medical history data and the secondary use of biological specimens.

2.2. Inclusion and exclusion criteria

A total of 691 patients were obtained for the analysis, and Detailed inclusion criteria include (1) Female patients; (2) Patients who completed NAC before surgery and the cycle is complete; (3) BC was confirmed by pathological confirmation before chemotherapy; (4) Patients with sufficient detailed clinical and pathological data; (5) Patients with T1-T3 tumors according to the American Joint Committee on Cancer (AJCC) TNM stage system. The exclusion criteria include (1) Patients without IHC; (2) Patients with other malignant tumors; (3) Patients without blood tests; (4) Patients with occult BC; (5) Patients without completed treatment. Finally, 557 patients meeting the index were selected for analysis. A flowchart is shown in Fig. 1.

2.3. Clinical and pathological variables

Study variables included serum LDH levels, patient age, menopausal status, body mass index (BMI) value, lymphatic invasion status, estrogen receptor (ER) status, progesterone receptor (PR) status, HER-2 status, KI67 expression, P53 expression, T stage, N stage, molecular subtype, pathological type, and pCR status. Patient information and treatment details were recorded from the beginning of the diagnosis. Serum LDH levels of all BC patients were assessed before NAC, mid-NAC (tested before the third chemotherapy for four-cycle chemotherapy regimens, before the fourth chemotherapy for six-cycle regimens, and before the fifth chemotherapy for eight-cycle regimens), and preoperatively, respectively. The average serum LDH level was 120–230 U/L. A cut-off of 230 U/L was used to divide the patients into two groups. Age was divided into two groups using 40 years as a cut-off. All patients underwent sentinel lymph node biopsy (SLNB). When axillary lymph nodes were abnormal, axillary lymph node dissection (ALND) was performed. BMI values are stratified according to international standards of health: lean, BMI < 18.5; normal, 18.5 ≤ BMI < 24; overweight, 24 ≤ BMI < 30, and obese BMI ≥ 30. Pathologist in our hospital evaluates the hormone receptor (HR) status by immunohistochemistry (IHC). ER and PR nuclear ≥ 1% are defined as positive. When one of ER or PR is positive, HR is positive. KI67 positive nuclear ≥ 15% was defined as high expression, < 15% as low expression. IHC staining 3 + was positive for HER-2, IHC staining 0 or 1 + was negative for HER-2, and when IHC staining was 2 +, Fluorescence in situ hybridization (FISH) was used to detect its status. When Fish is negative, HER-2 is considered negative. Otherwise, it is positive. All patients underwent clinical and radiographic staging. T stage was determined using palpation and ancillary examination measures. N stage was defined as axillary lymph nodes or ultrasound with abnormal lymph nodes. Metastatic disease was assessed by ultrasound and Computed Tomography (CT). We divided the cancer molecular subtype into four types: HR(+)/HER-2(+)、HR(+)/HER-2(-)、HR(-)/HER-2(+)、TNBC.

Miller-Payne (MP) score is currently the most commonly used assessment system in the domestic pathology community, which compares the crude needle puncture specimen before chemotherapy with the surgical specimen after chemotherapy and mainly evaluates the cellular abundance of residual tumors after NAC, divided into five grades. The higher the grading, the better the treatment effect is suggested. Grade 1 (G1): no change or only individual cancer cells have undergone G1: no change or only individual cancer cells are altered, and the number of cancer cells is reduced overall; Grade 2 (G2): the number of cancer cells is mildly reduced, the incremental number is still high, and the number of cancer cells is reduced by < 30%; Grade 3 (G3): the number of cancer cells is reduced by between 30% and 90%; Grade 4 (G4): the number of cancer cells is significantly reduced by > 90%, and only small clusters of scattered or single cancer cells are left; Grade 5 ( G5): no tumor cells remain, but ductal carcinoma in situ may be present. Here, G5 was used as the study endpoint. A residual invasive cancer component in the BC primary tumor and axillary lymph nodes after treatment is called non-pCR.

2.4. Statistical Analysis

Data presented in this paper use the SPSS software version 26.0 (IBM Corporation, New York, USA) for the analysis, stratifying the data in this paper by age. Categorical data are expressed as counts and percentages, basic data of patients were continued when compared and analyzed using the chi-square test, and correlations between clinical case parameters and pCR rates within each subgroup were performed using the chi-square test and the univariate Logistic regression analysis. Statistically, significant variables from the univariate analysis were included in the multivariate analysis. To determine which variables are independent factors of pCR, P < 0.05 was considered statistically significant. The nomogram was established based on the clinicopathologic factors of BC patients. In addition, we analyzed the overall performance of the nomogram by plotting the receiver operating characteristic (ROC) curve and then calculating the AUC of the ROC curves to analyze the overall performance of the nomogram, with the AUC exceeding 0.7 considered that the nomogram provided a reasonable estimation. The above statistical analyses were performed using R4.1.0 software, including the car, rms, pROC, and rmda packages.

3.1 Characteristics of study sample

From January 1, 2013 to December 31, 2019, 691 patients diagnosed with BC were studied at Harbin Medical University Cancer Hospital, 134 patients were excluded (66 patients without blood tests, 36 patients without immunohistochemistry, 15 patients without completed treatment, 6 patients with occult BC, 11 patients with other malignant tumors), and a 557 were included in the study. The clinicopathological characteristics and treatment are shown in Table 1. The age range of this cohort was 23-71 years. 460 (82.6%) patients were older than 40 years. 295 (53.0%) patients had a BMI higher than 24 kg/m². Patients were grouped according to clinical staging: 330 women had early BC (stage I, II), 227 women had locally advanced BC (stage III), and the majority of patients had stage IIb (40.3%, n=225). The most common molecular typing was HR(+)/ HER-2(-) (44.7%, n=249), 72 (12.8%) patients had HR(+)/ HER-2(+), 145 (26.2%) patients had HR(-)/ HER-2(+), and 91 (16.3%) patients had TNBC.

3.2 Analysis of serum LDH levels and clinicopathological features

Before BC patients underwent NAC, a total of 510 (91.6%) patients had serum LDH levels below 230 U/L, and after completing half of the chemotherapy cycles, the number of patients with high expression of serum LDH levels gradually increased to about 37.7%. At the end of the complete cycle of chemotherapy for routine preoperative examination, 246 (44.2%) BC patients were in a state of high serum LDH expression. The differences in age, menopausal status, BMI, clinical N-stage, HER2 expression, and molecular subtype were statistically significant (P < 0.05) for different serum LDH levels. In the present cohort, serum LDH levels were higher in older patients, but this phenomenon was not evident before chemotherapy. Regardless of the period of NAC, menopausal women possessed higher serum LDH levels than non-menopausal women. When the BMI of BC patients was between 24-30 kg/m², they had higher serum LDH levels than other women.

3.3. Association of clinical factors with pCR in the whole group

In the entire cohort, 113 (20.2%) BC patients achieved pCR, and 444 (79.8%) did not. Univariate analysis identified factors affecting the pCR rate after NAC in BC patients. Clinical T stage, ER expression, PR expression, HER-2 expression, KI67 expression, molecular typing, and serum LDH levels (Pre-NAC, Mid-NAC, and Preoperative) were strongly correlated with the pCR rate (P <0.05) (Table 2). However, there was no significant correlation between age, menopausal status, BMI, clinical N stage, lymphatic infiltration, and staging with pCR rate (P > 0.05). Regardless of the stage of treatment, the probability of achieving pCR was higher when patients had high expression of serum LDH levels (Pre-NAC: 31.9% vs. 19.2%, Mid-NAC: 27.6% vs. 15.8%, Preoperative: 24.4% vs. 17.0%, P < 0.05). Patients were more likely to achieve pCR when BC patients had low clinical T stage, negative ER expression, negative PR expression, positive HER-2 expression, and high KI67 expression. Patients were grouped according to molecular typing, and those with HR(-)/HER-2(+) were the most sensitive to chemotherapy (32.4%, n=47), compared to only 8.0% for HR(-)/HER-2(+).

Factors that were statistically significant in the univariate analysis were included in the multivariate analysis. Logistic regression analysis showed that clinical T stage, HER-2 expression, and Mid-NAC serum LDH levels were independent predictors of achieving pCR after NAC in BC patients (P < 0.05) (Table 3). Patients with high serum LDH level expression were more likely to achieve pCR than those with low expression (OR=1.601, CI 95% 1.004-2.552, P = 0.048). Patients with low clinical T stages had better outcomes with chemotherapy (OR=2.281, CI 95% 1.128-4.613, P = 0.022). The probability of obtaining pCR was higher when patients were negative for HER-2 expression (OR=2.114, CI 95% 1.319-3.386, P = 0.002).

3.4. Predictive analysis of BC patients achieving pCR or non-pCR

The receiver operating characteristic (ROC) curve is a commonly used predictive model. We applied the ROC curve to predict the probability of achieving pCR or non-pCR after chemotherapy in BC patients. The clinicopathological characteristics statistically significant in the univariate analysis were selected for analysis (Figure 3 and 4). It was found that the probability of achieving pCR in patients with positive HER-2 expression was 63%, and there was a 57% probability of achieving pCR when the patient's KI67 > 15. After completing half of the cycles of chemotherapy, there was a 58% chance of achieving pCR in patients with serum LDH levels > 230 U/L (Table 4). In addition, we found that when ER and PR expression were positive, patients were insensitive to chemotherapy and less likely to achieve pCR. The difference was statistically significant (P < 0.05) (Table 5).

3.5. Construction of nomogram-based prediction of pCR in patients with BC

A nomogram is built based on logistic regression analysis, which integrates multiple predictors and then employs line segments with scales plotted on the same plane at a specific scale and is thus used to express the interrelationships among variables in the predictive model. We created a column-line graph based on the clinicopathologic characteristics of BC patients to predict the probability of achieving pCR when a BC patient undergoes NAC (Figure 5). HER-2 expression and clinical T stage greatly impacted on the patient's receipt of NAC and serum LDH levels before NAC and in the middle of NAC. We used ROC curves to assess the accuracy of the prediction model. As shown in Figure 6, the AUC was 0.732 (95% CI: 0.608-0.788), indicating that the prediction model had good predictive and judgmental power.

3.6. Evaluate the effect of chemotherapy according to RECIST criteria

Response Evaluation Criteria in Solid Tumors (RECIST) is a standardized method of measuring the response of solid tumors to treatment in clinical studies. Complete Response (CR): the disappearance of all targeted lesions. Partial response (PR): at least 30% reduction in the sum of the diameters of all targeted lesions compared to baseline. Progressed Disease (PD): at least a 20% increase in the sum of the diameters of all targeted lesions; Stable Disease (SD): not achieving PR, nor PD, and in between. Patients with high expression of serum LDH levels of Mid NAC were more likely to achieve CR, with statistically significant differences (P < 0.05).

3.7. Correlation between serum LDH levels and pCR was analyzed by PSM

The propensity score matching (PSM) method matches the two populations based on selected confounders, making the confounders as balanced as possible between the two populations, thus reducing the confounding effect of the confounders on the PSM was used to compare the pCR rate between YWBC and older groups with a matching tolerance of 0.02. Variables included age, menstrual status, ER expression, PR expression, HER-2 expression, clinical T stage, lymphatic infiltration, stage and KI67 expression. We performed PSM based on serum LDH levels at different treatment stages to obtain three separate sets of data (94 patients before NAC, 410 patients in the middle of NAC, and 479 patients in the preoperative period) with no difference in most baseline characteristics (P > 0.05) (Table 7). The pCR rate was significantly higher in patients with high expression of serum LDH levels than in those with low expression, both at any stage of NAC (P < 0.05) (Table 8).

3.8. Association between changes in serum LDH levels and pCR

Previously, we analyzed the effect of serum LDH levels on pCR in different treatment phases, and we went on to analyze whether changes in serum LDH affected the chemotherapeutic outcome of BC patients (Table 9). In this cohort, a total of 294 (52.8%) patients consistently had low expression of serum LDH levels, 30 (5.2%) patients consistently had high expression of serum LDH levels, and 233 (48.0%) patients had a change in serum LDH levels after receiving NAC (Low-to-high: 216 patients, High-to-low: 17 patients). Patients with consistently high expression were more likely to achieve pCR (33.3%), and the pCR rates of patients in the High-to-low and Low-to-high groups were 29.4% and 23.1%, respectively. All three groups were significantly more effective than the consistently low-expression group (16.3%), and the difference was statistically significant (P < 0.05).

A total of 557 female patients with BC were included in this study to investigate whether serum LDH levels at different treatment stages affect the pCR rate of patients. We found that patients were more likely to achieve pCR when they had high expression of serum LDH levels (P < 0.05). Serum LDH levels at mid-NAC, clinical T stage, and HER-2 expression were independent predictors of BC patients' achievement of pCR. We recommend checking serum LDH levels at every stage of NAC (especially mid-NAC). Moreover, according to the serum LDH level, we can better analyze the effect of chemotherapy on patients and adjust patients' treatment decisions appropriately to achieve individualized treatment. However, at the same time, we also need to note that when the serum LDH level does not change during the treatment, it should be combined with other auxiliary examinations before deciding whether the treatment plan needs to be changed.

In the present cohort, there was no significant relationship between the age of diagnosis of the patients and the serum LDH levels. However, as treatment progressed, the older the patient, the higher the serum LDH levels. In the 1970s, Gibson was the first to discover that LDH activity varies regularly during the menstrual cycle and that LDH activity correlates with estrogen levels ²⁵. In the present study, serum LDH levels were significantly higher in menopausal women than in nonmenopausal women, and this continued during chemotherapy.

We found that most patients' serum LDH levels gradually increased with chemotherapy. Elevated serum LDH levels may indicate the effectiveness of treatment because chemotherapeutic agents kill cancer cells, causing these cells to release LDH into the bloodstream, suggesting that the cancer cells have been damaged or have died ²⁶. However, in other cases, elevated serum LDH levels may indicate disease progression or the presence of other complications. Firstly, some patients with BC may have high serum LDH levels prior to treatment, which may be due to a high tumor burden with a large number of cancer cells releasing LDH. Secondly, the chemotherapeutic agents themselves may lead to elevated serum LDH levels, as they can damage the liver and heart, affecting the metabolism and clearance of LDH.

Serum LDH levels are specific for patients with BC malignancies and strongly correlate with clinical TMN staging, but this was not evident in the present cohort. Increased LDH activity increases breast tissue density, which is higher in tumor tissue than in patients with focal asymmetries or structural aberrations, and increases significantly with increasing BI-RADS category ²⁷. Koukourakis found that serum LDH levels in patients with benign breast disease (e.g., fibroadenomas and cystadenomas) were similar to those in patients with cancer ²⁸. Therefore, blood findings should be addressed during the usual physical examination.

PCR after NAC reduces the risk of clinical recurrence in BC. Dennison found that BC patients with high expression of serum LDH levels were the most sensitive to NAC and were independent of established prognostic factors (grading, tumor size) and molecular markers (HR status and PAM50 typing) ²⁹. Lee selected seven target transporter proteins and enzymes involved in glucose metabolism and assessed their association with clinicopathologic factors and outcomes in BC patients receiving NAC. They found that LDH was significantly correlated with pCR (OR = 0.251; p- = 0.016) ³⁰. LDH expression shows a trend for a high SUVmax of primary tumor 18F-FDG PET/CT (OR = 1.797 P = 0.060). Tumor expression of LDH can be considered a pCR predictive marker for NAC.

The prognostic role of LDH in BC has also been studied. BC patients with stable normal serum LDH levels experience longer progression-free survival (PFS) and overall survival (OS). An earlier study found that serum LDH levels were much higher in BC patients than in ordinary women and that when BC patients were operated on for the first week, serum LDH levels were significantly elevated and then gradually decreased over time, which was most likely due to the release of LDH into the circulatory system after the destruction of tumor cells ^{31, 32}. Liu found that the prognostic impact of LDH was more pronounced in stage II and III patients but less so in stage I patients. The possible reason for this is that higher LDH levels imply higher tumor activity and occult metastasis, a situation that is not apparent in stage I patients ³³. Paclitaxel is one of the most effective drugs for treating patients with BC, but the development of resistance after treatment is still an issue that needs to be addressed. Zhou found that LDH expression and activity were increased in paclitaxel-resistant cells and that application of an LDH inhibitor led to paclitaxel-resistant cells being re-sensitized to paclitaxel, which provides valuable information for paclitaxel-resistant BC patients ³⁴. Tas found that serum levels of LDH were significantly associated with the prognosis of small-cell lung cancer. The 1-year OS was 60.2% in patients with normal serum LDH levels compared with 33.1% in patients with higher serum LDH levels (P = 0.0017) ³⁵. Renal failure is a common complication of multiple myeloma, and it has been found that patients with high expression of serum LDH levels have a higher incidence of renal failure (P < 0.002) ³⁶. Mantle cell lymphoma still has no standard prognostic indicators internationally. Hoster analyzed lymphoma patients in 3 clinical trials, and they found that age, birth status, LDH, and white blood cell count were independent risk factors affecting patients' survival, which could be an essential tool for risk-adapted treatment decision-making in patients with advanced mantle cell lymphoma ³⁷. LDH can regulate MMR proteins to promote the proliferation of dMMR and pMMR colorectal tumor cells, and the combination of LDH inhibitors and immune check inhibitors can improve the prognosis of patients with colorectal cancer very well ³⁸. Tomita compared the prognosis of patients with non-Hodgkin's lymphoma with different levels of serum LDH, and the patients with high expression of serum LDH were more likely to have central nervous system involvement when the serum LDH levels reach twofold CNS involvement should be considered for prophylaxis ³⁹. In summary, clinicians need to evaluate patients' serum LDH levels, and LDH is likely an important factor in future cancer research.

There are still many aspects that can be improved in this study. Firstly, this study is a single-centre retrospective analysis, and each patient's treatment is different, which may affect the patient's outcome and therefore lacks uniformity; secondly, the serum LDH threshold applied in this study may be different from other centres, which may have an impact on the results of the study, and we need to confirm its accuracy. Finally, the treatment of BC patients is a long-term process, and we also need to consider non-neoplastic diseases (myocardial infarction, jaundice, diabetes mellitus, rheumatic fever, megaloblastic anaemia, tuberculosis, etc.) occurring in BC patients during the treatment phase that may affect serum LDH levels. In the future, we need further prospective studies to confirm these results.

In summary, serum LDH level at mid-NAC, clinical T stage, and HER-2 expression are independent predictors of achieving pCR in Chinese female BC patients, and patients with high expression of serum LDH level are more likely to achieve pCR. NAC has been widely used in the treatment of BC. It is not enough to detect BC only by imaging. LDH is a cost-effective biomarker with a clear predictive role in some solid tumors and haematological malignancies, which can help physicians make better therapeutic decisions.

ALND, Axillary lymph node dissection

ATP, Adenosine triphosphate

BC, breast cancer

BMI, body mass index

CT, Computed Tomography

ER, estrogen receptor

HER-2, human epidermal growth factor receptor-2

HR, hormone receptor

IHC, immunohistochemistry

LDH, lactate dehydrogenase

NAC, neoadjuvant chemotherapy

NAD, nicotinamide adenine dinucleotide

OS, overall survival

PR, progesterone receptor

pCR, pathologic complete response

PFS, progression free survival

ROC, receiver operating characteristic

SLNB，Sentinel lymph node biopsy

SSB, single-strand binding protein

TNBC, Triple negative breast cancer

Funding

This work was supported by grants from the Natural Science Foundation of China (Grant Number: 81872145).

Competing Interests

The authors have no relevant financial or non-financial interests to disclose

Authors' contributions

All authors contributed to the study conception and design. He Dou, Siyuan Jia and Min Xiao designed research; Danli Luo, Tian Gao, Zhaoting Li, Yuling Ba, Jianan Wang, Pingyang Yu and Youyu Wang performed research; Min Xiao administered the research; Fucheng Li, He Dou, Youyu Wang and Xingyan Chen analyzed the data; He Dou, Siyuan Jia, Danli Luo and Yuling Ba wrote the paper. All authors read and approved the final manuscript.

Data Availability

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

Ethics approval

The study was approved by Harbin Medical University and written informed consent was obtained from all study participants before treatment, and the authors confirmed that all the study was conducted in accordance with the contents of the revised 2013 revised Declaration of Helsinki.

Consent to participate

Informed consent was obtained from all individual participants included in the study.

Consent to publish

Containing any form of personal data (including any personal details, images or videos) has been obtained the consent of the parents or legal guardian of the person or the child. Statements of all case reports have been approved for publication.

Availability of data and materials

The data and materials for this study are authentic and available. All the data can be found in the digital integrated management system of Harbin Medical University Cancer Hospital. Publicly archived datasets analysed or generated during the study may be provided by the corresponding author upon reasonable request.

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Table 1. Descriptive characteristics and treatments of BC patients by serum LDH levels.

Patient characteristic		Pre-NAC LDH (U/L)			Mid-NAC LDH (U/L)			Preoperative LDH (U/L)
		＜230	≥230	P	＜230	≥230	P	＜230	≥230	P
		N (%)	N (%)		N (%)	N (%)		N (%)	N (%)
Total		510 (91.6)	47 (8.4)		347 (62.3)	210 (37.8)		311 (55.8)	246 (44.2)
Age	≤40	92 (18.0)	5 (10.6)	0.200	74 (21.3)	23 (11.0)	0.002	64 (20.6)	33 (13.4)	0.027
	>40	418 (82.0)	42 (89.4)		273 (78.7)	187 (89.0)		247 (79.4)	213 (86.6)
Menstruation	Yes	238 (46.3)	29 (61.7)	0.048	146 (42.0)	121 (57.6)	＜0.001	137 (44.1)	130 (52.8)	0.039
	No	272 (53.7)	18 (38.3)		201 (58.0)	89 (42.4)		174 (55.9)	116 (47.2)
BMI	≤18.5	15 (2.9)	1 (2.1)	0.022	12 (3.5)	4 (1.9)	0.196	13 (4.2)	3 (1.2)	0.001
	18.5-24	234 (45.8)	12 (25.5)		162 (46.7)	84 (40.0)		155 (49.8)	91 (37.0)
	24-30	239 (46.9)	29 (61.7)		159 (45.8)	109 (51.9)		128 (41.2)	140 (56.9)
	≥30	22 (4.4)	5 (10.7)		14 (4.0)	13 (6.2)		15 (4.8)	12 (4.9)
Clinical T stage	1	62 (12.0)	7 (14.8)	0.238	44 (12.6)	25 (11.9)	0.292	41 (13.2)	28 (11.4)	0.598
	2	371 (72.8)	29 (61.7)		242 (69.7)	158 (75.2)		218 (70.1)	182 (74.0)
	3	77 (15.6)	11 (23.5)		61 (17.7)	27 (12.9)		52 (16.7)	36 (14.6)
Clinical N stage	0	66 (12.9)	4 (8.5)	0.419	51 (14.6)	19 (9.0)	0.010	49 (15.8)	21 (8.5)	0.045
	1	278 (54.5)	24 (51.0)		187 (53.8)	115 (54.8)		157 (50.5)	145 (58.9)
	2	67 (13.1)	10 (21.2)		54 (15.8)	23 (11.0)		46 (14.8)	31 (12.6)
	3	99 (19.5)	9 (19.3)		55 (15.8)	53 (25.2)		59 (18.9)	49 (20.0)
Lymphatic infiltration	Yes	368 (72.2)	39 (83.0)	0.110	243 (70.0)	164 (78.1)	0.038	212 (68.2)	195 (79.3)	0.003
	No	142 (27.8)	8 (17.0)		104 (30.0)	46 (21.9)		99 (31.8)	51 (20.7)
ER	Positive	293 (57.5)	24 (51.1)	0.397	203 (58.5)	114 (54.3)	0.330	181 (58.2)	136 (55.3)	0.490
	Negative	217 (42.5)	23 (48.9)		144 (41.5)	96 (45.7)		130 (41.8)	110 (44.7)
PR	Positive	238 (46.7)	16 (34.0)	0.096	162 (46.6)	92 (43.8)	0.509	140 (45.0)	114 (46.3)	0.755
	Negative	272 (53.3)	31 (64.0)		185 (53.4)	118 (56.2)		171 (55.0)	132 (53.7)
HER-2	Positive	198 (38.8)	18 (38.2)	0.944	123 (35.4)	93 (44.3)	0.038	111 (35.7)	104 (42.3)	0.113
	Negative	312 (61.2)	29 (61.8)		224 (64.6)	117 (55.7)		200 (64.3)	142 (57.7)
KI67	≤15	179 (35.1)	14 (29.8)	0.464	128 (36.9)	65 (31.0)	0.154	111 (35.5)	82 (32.8)	0.561
	＞15	331 (64.9)	33 (70.2)		219 (63.1)	145 (69.0)		200 (64.5)	164 (67.2)
Stage	I+II	303 (59.4)	27 (57.4)	0.793	210 (60.1)	120 (57.1)	0.432	182 (58.5)	148 (60.2)	0.695
	III	207 (40.6)	20 (42.6)		137 (39.5)	90 (42.9)		129 (41.5)	98 (39.8)
Molecular subtype	HR+/HER-2+	63 (12.3)	9 (19.1)	0.018	40 (11.5)	32 (15.2)	0.236	40 (12.8)	32 (13.0)	0.381
	HR+/HER-2-	234 (45.9)	15 (32.1)		162 (46.6)	87 (41.4)		143 (46.0)	106 (43.1)
	HR-/HER-2+	136 (26.7)	9 (19.1)		84 (24.2)	61 (29.0)		73 (23.5)	72 (29.3)
	TNBC	77 (15.1)	14 (29.7)		61 (17.7)	30 (14.4)		55 (17.7)	36 (14.6)

Bold values indicate that they are statistically significant at P ≤0.05

Table 2. Univariate analysis between clinical characteristics and pCR.

Patient characteristic		All patients
		pCR （n=113）		Non-pCR （n=444）		χ2	P
		N	%	N	%
Age	≤40	21	18.6	76	17.1	0.156	0.714
	>40	92	81.4	368	82.9
Menstruation	Yes	61	54.0	206	46.4	2.077	0.150
	No	52	46.0	238	54.6
BMI	≤18.5	1	0.8	15	3.4	4.724	0.193
	18.5-24	55	48.7	191	43.0
	24-30	49	43.3	219	49.3
	≥30	8	7.2	19	4.3
Clinical T stage	1+2	102	90.3	367	82.7	3.919	0.048
	3	11	9.7	77	17.3
Clinical N stage	0	20	17.7	50	11.3	3.963	0.265
	1	57	50.4	245	55.2
	2	13	11.5	64	14.4
	3	23	20.4	85	19.1
Lymphatic infiltration	Yes	87	77.0	320	72.1	1.108	0.293
	No	26	23.0	124	27.9
ER	Positive	40	35.4	277	62.3	26.756	＜0.001
	Negative	73	64.6	167	37.7
PR	Positive	28	24.8	226	50.9	24.778	＜0.001
	Negative	85	75.2	218	49.1
HER-2	Positive	68	60.2	148	33.3	27.340	＜0.001
	Negative	45	39.8	296	66.7
KI67	≤15	26	23.0	167	37.6	8.484	0.004
	>15	87	77.0	277	62.4
Stage	I+II	75	66.4	255	57.4	2.981	0.084
	III	38	33.6	189	42.6
Molecular subtype	HR+/HER-2+	21	18.6	51	11.5	42.726	＜0.001
	HR+/HER-2-	20	17.7	229	49.3
	HR-/HER-2+	47	41.6	98	22.1
	TNBC	25	22.1	66	17.1
Pre-NAC LDH	＜230	98	86.7	412	92.8	4.292	0.038
	≥230	15	13.3	32	7.2
Mid-NAC LDH	＜230	55	48.9	292	65.8	11.205	0.001
	≥230	58	51.1	152	34.2
Preoperative LDH	＜230	53	46.9	258	57.8	4.586	0.032
	≥230	60	53.1	186	42.2

Bold values indicate that they are statistically significant at P ≤0.05

Table 3. Multivariate analysis between clinical characteristics and pCR.

Patient characteristic		B	S. E	Wals	OR	CI (95%)	P
Clinical T stage	3	Ref
	1+2	0.825	0.359	5.266	2.281	1.128-4.613	0.022
ER	Positive	Ref
	Negative	0.461	0.335	1.899	1.586	0.823-3.056	0.168
PR	Positive	Ref
	Negative	0.493	0.359	1.881	1.637	0.809-3.310	0.170
HER-2	Negative	Ref
	Positive	0.748	0.240	9.689	2.114	1.319-3.386	0.002
KI67	≤15	Ref
	>15	0.453	0.258	3.089	1.574	0.949-2.609	0.079
Pre-NAC LDH	＜230	Ref
	≥230	0.547	0.361	2.291	1.728	0.851-3.510	0.130
Mid-NAC LDH	＜230	Ref
	≥230	0.471	0.238	3.913	1.601	1.004-2.552	0.048
Preoperative LDH	＜230	Ref
	≥230	0.237	0.234	1.024	1.267	0.801-2.005	0.312

Bold values indicate that they are statistically significant at P ≤0.05

Table 4. Predictive analysis of BC patients achieving pCR

Patient characteristic		AUC	S. E	CI (95%)	P
HER-2	Negative	Ref
	Positive	0.634	0.030	0.576-0.692	＜0.001
KI67	≤15	Ref
	>15	0.573	0.029	0.516-0.630	0.016
Pre-NAC LDH	＜230	Ref
	≥230	0.530	0.319	0.469-0.592	0.319
Mid-NAC LDH	＜230	Ref
	≥230	0.585	0.030	0.526-0.645	0.005
Preoperative LDH	＜230	Ref
	≥230	0.556	0.030	0.497-0.616	0.066

Bold values indicate that they are statistically significant at P ≤0.05

Table 5. Predictive analysis of BC patients achieving Non-pCR

Patient characteristic		AUC	S. E	CI (95%)	P
Clinical T stage	1+2	Ref
	3	0.538	0.029	0.481-0.596	0.211
ER	Negative	Ref
	Positive	0.635	0.029	0.578-0.692	<0.001
PR	Negative	Ref
	Positive	0.631	0.028	0.575-0.686	<0.001

Bold values indicate that they are statistically significant at P ≤0.05

Table 6. Group differences using RECIST as the pathological criteria

Patient characteristic		RECIST				P
Patient characteristic		PD	SD	PR	CR	P
Pre-NAC LDH	＜230	9 (81.8)	75 (92.6)	328 (93.2)	98 (86.7)	0.108
	≥230	2 (18.2)	6 (7.4)	24 (6.8)	15 (13.3)
Mid-NAC LDH	＜230	4 (36.7)	56 (69.1)	232 (65.9)	55 (48.7)	0.001
	≥230	7 (63.3)	25 (30.9)	120 (34.1)	58 (51.3)
Preoperative LDH	＜230	6 (54.5)	54 (66.7)	198 (56.3)	53 (46.9)	0.056
	≥230	5 (45.5)	27 (33.3)	154 (43.7)	60 (53.1)

Bold values indicate that they are statistically significant at P ≤0.05

Table 7. Descriptive characteristics and treatments of BC patients by serum LDH levels after PSM.

Patient characteristic		Pre-NAC LDH (U/L)			Mid-NAC LDH (U/L)			Preoperative LDH (U/L)
		＜230	≥230	P	＜230	≥230	P	＜230	≥230	P
		N (%)	N (%)		N (%)	N (%)		N (%)	N (%)
Total		47 (50.0)	47 (50.0)		200 (48.8)	210 (51.2)		233 (48.6)	246 (51.4)
Age	≤40	9 (19.1)	5 (10.6)	0.247	23 (11.5)	23 (11.0)	0.861	32 (13.7)	33 (13.4)	0.919
	>40	38 (80.9)	42 (89.4)		177 (88.5)	187 (89.0)		201 (86.3)	213 (86.6)
Menstruation	Yes	24 (51.0)	29 (61.7)	0.298	114 (56.9)	121 (57.6)	0.899	116 (49.7)	130 (52.8)	0.503
	No	23 (49.0)	18 (38.3)		86 (43.1)	89 (42.4)		117 (50.3)	116 (47.2)
Clinical T stage	1+2	11 (23.4)	11 (23.4)	1.000	24 (12.0)	27 (12.8)	0.793	36 (15.4)	36 (14.6)	0.803
	3	36 (76.6)	36 (76.6)		176 (82.0)	183 (87.2)		197 (84.6)	210 (85.4)
Lymphatic infiltration	Yes	40 (85.1)	39 (83.0)	0.778	161 (80.5)	164 (78.1)	0.548	185 (79.3)	195 (79.3)	0.972
	No	7 (14.9)	8 (17.0)		39 (19.5)	46 (21.9)		48 (20.7)	51 (20.7)
ER	Positive	23 (48.9)	24 (51.1)	0.397	117 (58.5)	114 (54.3)	0.390	131 (56.3)	136 (55.3)	0.836
	Negative	24 (51.1)	23 (48.9)		83 (41.5)	96 (45.7)		102 (43.7)	110 (44.7)
PR	Positive	17 (36.1)	16 (34.0)	0.829	94 (47.0)	92 (43.8)	0.517	109 (46.7)	114 (46.3)	0.923
	Negative	30 (63.9)	31 (64.0)		106 (53.0)	118 (56.2)		124 (53.3)	132 (53.7)
HER-2	Positive	11 (23.4)	18 (38.2)	0.118	75 (37.5)	93 (44.3)	0.163	85 (36.4)	104 (42.3)	0.195
	Negative	36 (76.6)	29 (61.8)		125 (62.5)	117 (55.7)		148 (63.6)	142 (57.7)
KI67	≤15	15 (31.9)	14 (29.8)	0.823	67 (33.5)	65 (31.0)	0.581	85 (36.4)	82 (32.8)	0.470
	＞15	32 (68.1)	33 (70.2)		133 (63.5)	145 (69.0)		148 (63.6)	164 (67.2)
Stage	I+II	32 (68.0)	27 (57.4)	0.286	123 (61.5)	120 (57.1)	0.369	145 (62.2)	148 (60.2)	0.642
	III	15 (32.0)	20 (42.6)		77 (38.5)	90 (42.9)		88 (37.8)	98 (39.8)

Bold values indicate that they are statistically significant at P ≤0.05

Table 8. Analysis of the correlation between serum LDH level and pCR after PSM.

Patient characteristic		Patients after PSM (Pre-NAC)			Patients after PSM (Mid-NAC)			Patients after PSM (Preoperative)
		pCR	Non-pCR	P	pCR	Non-pCR	P	pCR	Non-pCR	P
		N (%)	N (%)		N (%)	N (%)		N (%)	N (%)
Total		15 (16.0)	79 (84.0)		68 (16.6)	342 (83.4)		82 (17.1)	397 (82.9)
Pre-NAC LDH	＜230	0 (0)	47 (59.5)	＜0.001	55 (80.9)	314 (91.8)	0.006	71 (86.6)	369 (92.9)	0.055
	≥230	15 (100)	32 (40.5)		13 (19.1)	28 (8.2)		11 (13.4)	28 (7.1)
Mid-NAC LDH	＜230	3 (20.0)	57 (72.2)	＜0.001	10 (14.7)	190 (55.6)	＜0.001	37 (45.1)	255 (64.2)	0.001
	≥230	12 (80.0)	22 (27.8)		58 (85.3)	152 (44.4)		45 (54.9)	142 (35.8)
Preoperative LDH	＜230	5 (33.3)	52 (65.8)	＜0.001	27 (39.7)	195 (57.0)	0.009	22 (26.8)	211 (53.1)	＜0.001
	≥230	10 (66.7)	27 (34.2)		41 (60.3)	147 (43.0)		60 (73.2)	186 (46.9)
Age	≤40	1 (6.7)	13 (16.5)	0.329	7 (10.3)	39 (11.4)	0.791	8 (9.8)	57 (14.4)	0.268
	>40	14 (93.3)	66 (83.5)		61 (89.7)	303 (88.6)		74 (91.2)	340 (85.6)
Menstruation	Yes	9 (60.0)	44 (55.7)	0.758	49 (72.1)	186 (54.4)	0.007	53 (64.6)	193 (48.6)	0.008
	No	6 (40.0)	35 (44.3)		19 (27.9)	156 (45.6)		29 (35.4)	204 (51.4)
Clinical T stage	1+2	2 (13.3)	20 (25.3)	0.315	4 (5.9)	47 (13.7)	0.073	8 (9.8)	64 (16.4)	0.142
	3	13 (86.7)	59 (74.7)		64 (94.1)	295 (86.3)		74 (91.2)	333 (83.6)
Lymphatic infiltration	Yes	11 (73.3)	68 (86.1)	0.217	58 (85.3)	267 (78.1)	0.180	72 (87.8)	308 (77.6)	0.037
	No	4 (26.7)	11 (13.9)		10 (14.7)	75 (21.9)		10 (12.2)	89 (22.4)
ER	Positive	6 (40.0)	41 (51.9)	0.398	25 (36.8)	206 (60.2)	＜0.001	25 (30.5)	242 (61.0)	＜0.001
	Negative	9 (60.0)	38 (48.1)		43 (63.2)	136 (39.8)		57 (69.5)	155 (39.0)
PR	Positive	4 (26.7)	29 (36.7)	0.398	17 (25.0)	169 (49.4)	＜0.001	20 (24.4)	203 (51.1)	＜0.001
	Negative	11 (73.3)	50 (63.3)		51 (75.0)	173 (50.6)		62 (75.6)	194 (48.9)
HER-2	Positive	8 (53.3)	21 (26.6)	0.040	47 (69.1)	121 (35.4)	＜0.001	54 (65.9)	135 (34.0)	＜0.001
	Negative	7 (46.7)	58 (73.4)		21 (30.9)	221 (64.6)		28 (34.1)	262 (66.0)
KI67	≤15	2 (13.3)	27 (34.2)	0.109	11 (16.2)	121 (35.4)	0.002	21 (26.5)	146 (36.8)	0.053
	＞15	13 (86.7)	52 (65.8)		57 (83.8)	221 (64.6)		61 (73.5)	251 (63.2)
Stage	I+II	9 (60.0)	50 (63.3)	0.809	43 (63.2)	200 (58.5)	0.466	57 (69.5)	236 (59.4)	0.089
	III	6 (40.0)	29 (36.7)		25 (36.8)	142 (41.5)		25 (30.5)	161 (40.6)

Bold values indicate that they are statistically significant at P ≤0.05

Table 9. Relationship between changes of serum LDH level and pCR after completion of NAC.

LDH Variation	All patients
	pCR （n=113）		Non-pCR （n=444）		χ2	P
	N	%	N	%
Stable low	48	42.5	246	55.4	7.978	0.046
Low-to-high	50	44.2	166	37.4
High-to-low	5	4.4	12	2.7
Stable high	10	8.9	20	4.5

Bold values indicate that they are statistically significant at P ≤0.05

No competing interests reported.

Impact of changes in serum lactate dehydrogenase levels on pathological response after neoadjuvant chemotherapy in patients with breast cancer

Status:

Version 1

Abstract

Figures

1. Introduction

2. Material and methods

2.1. Patients and treatments

2.2. Inclusion and exclusion criteria

2.3. Clinical and pathological variables

2.4. Statistical Analysis

3. Results

4. Discussion

5. Conclusion

Abbreviations

Declarations

References

Tables

Additional Declarations

Status:

Version 1