Marker and application thereof in predicting adverse reaction of neoadjuvant chemotherapy of breast cancer

Abstract

The invention discloses a marker for predicting the adverse reaction of breast cancer neoadjuvant chemotherapy in the field of biomedical detection, the marker is a site rs4670814, and the marker can predict the adverse reaction of breast cancer neoadjuvant chemotherapy, so that a certain reference is provided for accurate prevention and treatment of breast cancer.

Description

Technical Field

[0001] The present invention belongs to the field of biomedical detection, and particularly relates to a marker and its application in predicting adverse reactions of neoadjuvant chemotherapy for breast cancer. Background Art

[0002] Breast cancer (BC) is one of the most common malignant tumors in women. Clinically, for patients with a pathologically confirmed breast cancer, doctors will tailor treatments based on their physical condition, disease type, and pathological findings to minimize the risk of metastasis and recurrence. These treatments include: surgical removal of the breast tumor; radiation therapy to reduce the risk of tumor recurrence in the breast and surrounding tissues; and targeted medications (including hormone therapy, chemotherapy, or targeted biological therapy) to kill cancer cells and prevent their spread.

[0003] Neoadjuvant chemotherapy (NAC) is increasingly being used in the treatment of breast cancer, particularly in reducing the size of primary breast lesions. Neoadjuvant chemotherapy, also known as preoperative chemotherapy, refers to systemic chemotherapy administered before local treatment. NAC can reduce the size of primary tumors to a level suitable for surgery, thereby increasing surgical access and success rates for patients with advanced or inoperable BC. It also achieves the goals of downstaging tumors and conserving the breast and axilla, significantly improving patient outcomes. Clinicians can also assess chemotherapy efficacy by observing changes in tumor size or maximum diameter before and after NAC using imaging modalities. Generally, the response of BC patients to NAC is categorized as either pathologic complete response (pCR) or non-pathologic complete response (non-pCR). Multiple studies have shown that individuals who achieve a pCR are more responsive to chemotherapy, significantly improving disease-free survival (DFS) and overall survival (OS), and also leading to better treatment outcomes and a lower risk of complications.

[0004] However, not all BC patients achieve pCR after neoadjuvant chemotherapy. Individuals who are not sensitive to chemotherapy may not only benefit little from treatment and chemotherapy regimens, but may also experience further disease progression and worsening, and even a series of harmful consequences such as metastasis and recurrence, increasing the risk of adverse outcomes in BC patients. Furthermore, even among patients with the same course of disease, the degree of pathological complete remission can vary significantly, even with the same treatment regimen, medication type, dosage, and duration of treatment. Therefore, individual differences are the primary factor contributing to varying therapeutic outcomes among patients with the same course of disease treated with the same treatment regimen.

[0005] Therefore, it is extremely important to conduct prognostic research on breast cancer patients, divide chemotherapy-sensitive populations, and find biomarkers that can effectively predict therapeutic efficacy, so as to achieve precise treatment of cancer while taking into account the principle of economic efficiency. Summary of the Invention

[0006] The present invention aims to provide a marker for predicting adverse reactions to neoadjuvant chemotherapy for breast cancer, thereby predicting the adverse reactions to neoadjuvant chemotherapy for breast cancer and providing a certain reference for the precise prevention and treatment of breast cancer.

[0007] In this study, a marker for predicting adverse reactions to neoadjuvant chemotherapy for breast cancer is identified at rs4670814. The gene sequence is [GATTTCTCCTACTTAACTGGGGGGA[C / G]GCTGTAGTCACAGCGAAGGGAATAT].

[0008] Furthermore, the genotype of locus rs4670814 was CC.

[0009] Furthermore, the neoadjuvant chemotherapy is ET regimen neoadjuvant chemotherapy.

[0010] On the other hand, the applicant found through adverse reaction analysis that breast cancer patients carrying the CC genotype of rs4670814 had a significantly increased risk of bone marrow suppression (homozygous model OR = 4.397, 95% CI = 1.177-16.424, P = 0.028, recessive model OR = 2.149, 95% CI = 1.115-4.144, P = 0.022). Therefore, the applicant requests protection for the application of the site rs4670814 in predicting adverse reactions to neoadjuvant chemotherapy for breast cancer.

[0011] Furthermore, the adverse reaction of neoadjuvant chemotherapy for breast cancer is the risk of bone marrow suppression in breast cancer patients after neoadjuvant chemotherapy.

[0012] Furthermore, when predicting the risk of bone marrow suppression in breast cancer patients after neoadjuvant chemotherapy, the genotype of the rs4670814 locus of the breast cancer patient is detected. When the CC genotype is detected, the patient has a higher risk of bone marrow suppression after neoadjuvant chemotherapy.

[0013] Furthermore, the site rs4670814 is used in products related to predicting the risk of bone marrow suppression in breast cancer patients after neoadjuvant chemotherapy.

[0014] Furthermore, the product is a reagent, kit, chip, test paper capable of detecting the CC genotype of the rs4670814 site in breast cancer patients, or an assessment system that can automatically output the patient's bone marrow suppression risk based on the input genotype test results of the rs4670814 site.

[0015] Furthermore, the evaluation system includes:

[0016] An input unit is provided to obtain data to be processed, wherein the data to be processed includes a genotype detection result of the site rs4670814 in the sample;

[0017] an evaluation unit, inputting the data to be processed into a bone marrow suppression evaluation model to obtain a bone marrow suppression evaluation result of the data to be processed, wherein the bone marrow suppression evaluation model is a pre-trained model, and the bone marrow suppression evaluation result includes a correlation between the genotype of the site rs4670814 and the risk of bone marrow suppression after neoadjuvant chemotherapy in breast cancer patients;

[0018] The output unit outputs the bone marrow suppression risk assessment result of the data to be processed. When the detection result is the CC genotype of the site rs4670814, the output result is that the patient has an increased risk of bone marrow suppression.

[0019] Since breast cancer patients carrying the CC genotype at rs4670814 have a significantly increased risk of bone marrow suppression (homozygous model OR = 4.397, 95% CI = 1.177-16.424, P = 0.028, recessive model OR = 2.149, 95% CI = 1.115-4.144, P = 0.022), the CC genotype at rs4670814 can be used to screen therapeutic drugs for bone marrow suppression. Specifically, the CC genotype at rs4670814 is used as a target for therapeutic drugs for bone marrow suppression to verify the therapeutic effect of candidate drugs on bone marrow suppression. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 Figure 2 is the rs4670814 genotyping test results. DETAILED DESCRIPTION

[0021] The following is further described in detail through specific implementation methods:

[0022] 1. Materials and Methods

[0023] 1.1 Bioinformatics

[0024] 1.1.1 SNP Acquisition

[0025] The NCBI database (https: / / www.ncbi.nlm.nih.gov / ) was searched and the region range of the CYP1B1 gene and its upper and lower 5 kb flanking regions was obtained as "Chr2:38294746-38303323". Then, the EnSembl database (https: / / www.ensembl.org / index.html) was logged in. In the "Region Lookup" field, the region range obtained in NCBI was entered. The vcf file format was selected for download to obtain all SNPs in the CYP1B1 gene and its upper and lower 5 kb flanking regions.

[0026] 1.1.2 SNP functional annotation

[0027] Using the 3DSNP integrated database (v2.0, https: / / omic.tech / 3dsnpv2 / ), we scored each SNP based on its six functional annotations: "interacting genes," "enhancer status," "promoter status," "transcription factor binding sites," "motif changes," and "conservation score." We used RegulomeDB (v2.1, https: / / regulomedb.org), leveraging databases such as the DNA Element Encyclopedia Project and the NCBI Sequence Database, to perform functional analysis of SNPs in noncoding regions. By entering the CYP1B1 gene and its upper and lower 5 kb flanking regions (Chr2:38294746-38303323) into the search boxes of 3DSNP and RegulomeDB, respectively, we obtained functional scores for each SNP. We also performed gene-based functional annotation, focusing on whether the SNPs caused protein-coding changes, using ANNOVAR software.

[0028] 1.1.3 SNP screening

[0029] According to the 1000 Genomes Project (http: / / www.1000genomes.org), we excluded functional SNPs with a minor allele frequency (MAF) < 0.05 in the Han population and finally screened out possible functional SNPs.

[0030] 1.1.4 Results

[0031] Using the NCBI and EnSembl databases, we identified a total of 2439 single-nucleotide polymorphisms (SNPs) within the CYP1B1 gene and its upper and lower 5 kb flanking regions. After annotation using 3DSNP, ANNOVAR, and RegulomeDB, we predicted 312 SNPs to have biological functions. We then included SNPs with a MAF > 0.05 in southern Han Chinese individuals, yielding a total of 25 SNPs. We ultimately selected the potentially functional locus, rs4670814 (see Table 1 for functional prediction information).

[0032] Table 1 Detailed information of possible functional genetic loci

[0033]

[0034] Note: b Prediction results based on 3DSNP, ANNOVAR, and RegulomeDB.

[0035] 1.2 Research subjects

[0036] Patients with primary breast cancer pathologically confirmed at the Affiliated Hospital of Zunyi Medical University between March 2020 and March 2023 and receiving neoadjuvant ET chemotherapy were enrolled in this study. The study was approved by the Medical Ethics Committee of Zunyi Medical University (approval number: 2019-1-032). All participants who voluntarily participated in this study provided written informed consent. Specific inclusion and exclusion criteria were as follows:

[0037] Subjects meeting the inclusion criteria:

[0038] 1) Patients diagnosed with primary breast cancer by pathology;

[0039] 2) Patients were treated with ET regimen NAC for 4-6 cycles, with the initial chemotherapy dose of no less than 75 mg / m2 of epirubicin in the first cycle. 2 and docetaxel 75 mg / m 2 ;

[0040] 3) Tumor assessment was performed before chemotherapy and every 2 cycles after the start of chemotherapy, and the efficacy evaluation was in accordance with RECIST criteria;

[0041] 4) Patients received radical breast cancer surgery after NAC, and the Miller and Payne grading system was used to evaluate the efficacy of the patients.

[0042] Exclusion criteria:

[0043] 1) History of metastatic cancer or other cancers;

[0044] 2) history of radiotherapy or chemotherapy before blood collection;

[0045] 3) Male.

[0046] 1.3 Collection of research subject data

[0047] Medical records of the study subjects were collected. General demographic information included age, smoking, alcohol consumption, and menstrual history. Clinicopathological data included tumor size, lymph node metastasis, distant metastasis, TNM stage, efficacy, and adverse reactions. Short-term efficacy, myelosuppression, and gastrointestinal toxicity were assessed according to RECIST criteria and Common Terminology Criteria for Adverse Events (CTCAE) Version 5.0.

[0048] 1.4 Estimating Sample Size Power

[0049] Based on a review of relevant literature, the pCR rate for breast cancer patients was 20%. The study had an expected OR of 2, a two-sided test level of α = 0.05, and a power of β = 0.10. The calculated sample size was n = 278. A total of 513 BC patients were included, indicating a sufficient sample size. The sample size calculation formula is as follows:

[0050]

[0051] 1.5 Collection of blood samples and isolation and purification of genomic DNA

[0052] 1.5.1 Collection of blood samples

[0053] After the subjects signed the informed consent form, 2 ml of peripheral blood was collected using an EDTA vacutainer. The tubes were gently inverted and mixed five times, and then stored in a -20°C freezer within 1 hour. If not used for an extended period, the tubes should be transferred to a -80°C freezer for long-term storage. Repeated freezing and thawing should be avoided during storage.

[0054] 1.5.2 Main reagents and instruments for the experiment

[0055] 1.5.2.1 Main experimental reagents

[0056]

[0057] 1.5.2.2 Main experimental instruments

[0058]

[0059] 1.5.3 Genomic DNA Isolation and Purification Steps

[0060] A blood genomic DNA extraction kit was used to isolate and purify DNA from peripheral blood samples. The specific steps were as follows: (1) blood samples were taken out of the −20°C refrigerator and thawed in a 4°C refrigerator overnight;

[0061] (2) Lysis of red blood cells, the specific contents are as follows:

[0062]

[0063] (3) Lysis of leukocytes and proteins, the specific contents are as follows:

[0064]

[0065] (4) DNA separation, the details are as follows:

[0066]

[0067] (5) Washing and desalting

[0068] Prepare 70% ethanol and add 1 ml of ethanol to the DNA pellet. Invert the tube 50 times to wash the DNA thoroughly. Centrifuge at 12,000 rpm for 2 minutes, discard the supernatant, and repeat the previous step for 2 washes.

[0069] (6) Dissolving DNA. The specific contents are as follows:

[0070]

[0071] (7) DNA solution concentration determination and quantitative dilution, the specific contents are as follows:

[0072]

[0073] 1.6 Genotyping

[0074] The selected SNP is rs4670814, and the probe primer sequences are shown in Table 2 below:

[0075] Table 2 Probe primer sequences

[0076]

[0077] 1.6.1 Main experimental reagents for genotyping

[0078] 1.6.1.1 Main experimental reagents

[0079]

[0080] 1.6.1.2 Main experimental instruments

[0081]

[0082] 1.6.2 Specific steps of genotyping

[0083] 1.6.2.1 Taqman OpenArray Chip Typing

[0084] (1) Sample preparation:

[0085] 1) Prepare the DNA sample, vortex, and centrifuge at 1000 rpm for 1 minute. Set aside. Equilibrate the Taqman OpenArray chip at room temperature half an hour in advance.

[0086] 2) Importing sample layout information: Samples included in the study were placed in a 96-well plate. A table was created using Excel. The samples were transferred to the 96-well plate, sealed with aluminum foil tape, and stored at -80°C. Sample Tracker software was used to import the sample information into a 384-well export layout file for sample transfer.

[0087] (2) PCR reaction system configuration: Add 2.5 μl of TaqMan OpenArray Genotyping Master Mix to the sample plate according to the exported file, then use a pipette to draw 2.5 μl of DNA sample into the corresponding sample well, centrifuge at 1000 rpm for 1 min, and place it into the sample slot of the automatic sampler;

[0088] (3) Preparation of the chip: After the chip has been balanced for 30 minutes, remove the cap of the prepared oil-containing syringe and replace it with a gun tip. Place the Taqman OpenArray chip in the chip slot of the automatic sample injector. Turn on the automatic sample injector and inject the DNA sample onto the OpenArray chip. After the injection is completed, remove the OpenArray chip and seal the plate. Use the prepared syringe to inject oil into the chip. It is best to complete it within 60 seconds. The injection process should be continuous and not too fast to avoid affecting subsequent experiments. Wipe the outside of the OpenArray chip clean with alcohol.

[0089] (4) PCR reaction: Tear off the protective film on the surface of the chip and place the sealed OpenArray plate into the QuantStudio TM For the 12KFlex System, set the following reaction conditions:

[0090]

[0091] (5) Genotyping: After the reaction is completed, TM The results were read by 12K Flex software and typing was performed based on fluorescence intensity.

[0092] 1.7 Statistical methods

[0093] Data were analyzed using SPSS 29.0 statistical software. t-tests were used to analyze intergroup differences in continuous data. Unconditional logistic regression was used to analyze the association between the rs4670814 genetic variant and NAC efficacy, adverse reactions (bone marrow suppression, gastrointestinal toxicity), and long-term breast cancer prognostic indicators (tumor size, lymph node metastasis, etc.). Odds ratios (ORs) and 95% confidence intervals (95% CIs) were used to estimate the strength of the association. All tests were two-sided, and calculated P values ​​were adjusted for age, menopausal status, and smoking and alcohol use. P < 0.05 was considered statistically significant.

[0094] 2. Results

[0095] 2.1 Basic Information of Research Subjects

[0096] A total of 513 patients with pathologically confirmed primary BC who underwent neoadjuvant ET were included in this study. The basic information of the subjects is shown in Table 3. The mean age of the patients was 49.90 ± 9.719 years. Among them, 9 patients (1.75%) smoked, 2 patients (0.39%) drank alcohol, 276 patients (53.80%) were premenopausal, 371 patients (72.32%) were in TNM stage I-II, 427 patients (83.24%) had tumor size ≤5 cm before receiving NAC, 313 patients (61.01%) had lymph node metastasis, and 35 patients (6.82%) had distant metastasis; after receiving NAC, among 513 BC patients, 231 patients (45.03%) had varying degrees of bone marrow suppression, 22 patients (4.29%) had gastrointestinal toxicity, and 413 patients (80.51%) were effective to NAC.

[0097] Table 3 Basic information of 513 BC patients

[0098]

[0099] Note: pathologic complete response (pCR): pathologic complete response; complete response (CR): complete response; partial response (PR): partial response; stable disease (SD): no response; progressive disease (PD): disease worsening.

[0100] 2.2rs4670814 genotyping results

[0101] This study successfully completed the rs4670814 locus typing test for 513 breast cancer patients ( Figure 1 ), and the genotype distribution was in accordance with Hardy-Weinberg genetic equilibrium (P=0.215).

[0102] 2.3 Association analysis between rs4670814 genetic variation and NAC efficacy in breast cancer

[0103] As shown in Table 4, breast cancer patients who achieved pCR, CR, or PR after NAC were classified as the effective group, while those who achieved SD or PD were classified as the ineffective group. The mean age of the ineffective and effective groups was 50.40 years (±9.930) and 49.78 years (±9.675), respectively, with no statistically significant difference in age between the two groups (P = 0.567). After adjusting for age, menopausal status, smoking, and alcohol consumption, the results of a logistic regression model showed that the association between the rs4670814 genetic variant and NAC efficacy in breast cancer was not statistically significant (dominant model OR = 0.854, 95% CI = 0.533-1.369, P = 0.512; additive model OR = 0.996, 95% CI = 0.653-1.518, P = 0.983).

[0104] Table 4 Association of rs4670814 genetic variation with NAC efficacy in breast cancer

[0105]

[0106] 2.4 Analysis of the association between rs4670814 genetic variation and breast cancer toxicity

[0107] As shown in Table 5, we analyzed the association between the candidate SNP rs4670814 and adverse reactions to NAC in breast cancer. The results showed that rs4670814 was significantly associated with the occurrence of myelosuppression in breast cancer patients with NAC, and individuals carrying the CC gene had an increased risk of myelosuppression (homozygous model OR = 4.397, 95% CI = 1.177-16.424, P = 0.028; recessive model OR = 2.149, 95% CI = 1.115-4.144, P = 0.022). No association was found between rs4670814 and gastrointestinal toxicity in breast cancer patients with NAC, and neither the additive nor the dominant model was statistically significant (additive model OR = 0.841, 95% CI = 0.348-2.030, P = 0.700; dominant model OR = 0.915, 95% CI = 0.350-2.388, P = 0.856).

[0108] Table 5 Association of rs4670814 genetic variation with NAC toxicity in breast cancer

[0109]

[0110]

[0111] From the above results, it can be seen that the rs4670814 site, especially its CC genotype, is associated with bone marrow suppression in neoadjuvant chemotherapy for breast cancer in the population, and can be used as a prognostic marker for the toxic and side effects of neoadjuvant chemotherapy for breast cancer, providing a reference for personalized treatment of breast cancer.

[0112] In this article, the CC genotype sequence of rs4670814 is as follows:

[0113] GATTTCTCCTACTTAACTGGGGGGA[C / C]GCTGTAGTCACAGCGAAGGGAATAT.

[0114] The GG genotype sequence of rs4670814 is as follows:

[0115] GATTTCTCCTACTTAACTGGGGGGA[G / G]GCTGTAGTCACAGCGAAGGGAATAT.

[0116] The GC genotype sequence of rs4670814 is as follows:

[0117] GATTTCTCCTACTTAACTGGGGGGA[C / G]GCTGTAGTCACAGCGAAGGGAATAT.

[0118] The above is only an embodiment of the present invention, and the common knowledge such as the specific structure and characteristics of the scheme is not described in detail here. It should be pointed out that for those skilled in the art, without departing from the structure of the present invention, several variations and improvements can be made, which should also be regarded as the scope of protection of the present invention, and these will not affect the effect of the implementation of the present invention and the practicality of the patent. The scope of protection required by this application shall be based on the content of its claims, and the specific implementation methods and other records in the specification can be used to interpret the content of the claims.

Claims

1. A marker for predicting adverse reactions to neoadjuvant chemotherapy for breast cancer, characterized by: The marker is site rs4670814.

2. The marker according to claim 1, characterized in that: The genotype of locus rs4670814 was CC.

3. The marker according to claim 2, characterized in that: The neoadjuvant chemotherapy is ET regimen neoadjuvant chemotherapy.

4. Use of the marker according to any one of claims 1 to 3 in predicting adverse reactions to neoadjuvant chemotherapy for breast cancer.

5. The use according to claim 4, characterized in that: The adverse reaction of neoadjuvant chemotherapy for breast cancer is the risk of bone marrow suppression in breast cancer patients after neoadjuvant chemotherapy.

6. The use according to claim 5, characterized in that: When predicting the risk of bone marrow suppression in breast cancer patients after neoadjuvant chemotherapy, the genotype of the rs4670814 locus of breast cancer patients is detected. When the CC genotype is detected, the patient has a higher risk of bone marrow suppression after neoadjuvant chemotherapy.

7. The use according to claim 5, characterized in that: Application of the locus rs4670814 in predicting the risk of bone marrow suppression in breast cancer patients after neoadjuvant chemotherapy.

8. The use according to claim 7, characterized in that: The product is a reagent, a kit, a chip, a test paper capable of detecting the CC genotype of the rs4670814 site in breast cancer patients, or an assessment system that can automatically output the patient's bone marrow suppression risk based on the input genotype detection results of the site rs4670814.

9. The use according to claim 8, characterized in that: The evaluation system comprises: An input unit is provided to obtain data to be processed, wherein the data to be processed includes a genotype detection result of the site rs4670814 in the sample; an evaluation unit, inputting the data to be processed into a bone marrow suppression evaluation model to obtain a bone marrow suppression evaluation result of the data to be processed, wherein the bone marrow suppression evaluation model is a pre-trained model, and the bone marrow suppression evaluation result includes a correlation between the genotype of the site rs4670814 and the risk of bone marrow suppression after neoadjuvant chemotherapy in breast cancer patients; The output unit outputs the bone marrow suppression risk assessment result of the data to be processed. When the detection result is the CC genotype of the site rs4670814, the output result is that the patient has an increased risk of bone marrow suppression.

10. Use of the marker according to claim 2 in screening drugs for treating myelosuppression.

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