Markers of Predicting Response to Neoadjuvant Chemotherapy in Breast Cancer: New in Molecular Oncology

Abstract

It is known that complete pathomorphological response (pCR) after neoadjuvant therapy (NAC) in patients with breast cancer (BC) correlates with higher rates of recurrence-free and overall survival. In turn, the widespread use of neoadjuvant therapy for the treatment of breast cancer defines the clinical need for prognostic markers of response to ongoing therapy. Currently, some clinicopathological prognostic factors are used to assess the potential benefit of neoadjuvant systemic therapy for female patients, but they have limited applicability. In the era of precision medicine and personalised treatment, a search for new prognostic markers is needed to better tailor patient-specific therapy. To date, novel factors have been proposed to predict response to preoperative treatment in breast cancer patients, but they are either not yet used in routine clinical practice or have limited application. Thus, this review summarises data on both established and proven biomarkers and the latest prognostic factors for response to neoadjuvant treatment in breast cancer patients.

Introduction

Worldwide mortality rates from malignant neoplasms (MN) of various localisations remain at a high level. To date, breast cancer occupies the leading position in the structure of cancer morbidity among women, and predicting the outcome of this oncopathology is still an unsolved problem [1].

The use of chemotherapeutic agents in the preoperative period is a standard treatment option for patients with breast cancer [2-3], especially in aggressive subtypes, such as triple negative breast cancer (TNBC) and HER2+ breast cancer [4-5]. The use of NAC allows to achieve a complete pathomorphological response with a further increase in recurrence-free and overall survival of patients [6-8].

Achieving pCR is one of the main goals for NAC prescription, but it occurs in only a fraction of patients: 30-50% in TNBC, 50-80% in HER2-positive and 5-20% in luminal breast cancer [9]. This is why it is crucial to identify markers for predicting breast cancer patients’ pCR, which will be key to identifying patients to whom NAC can maximise the therapeutic benefit [10-11].

To date, several biomolecular markers are known and actively used to predict the efficacy of NAC in the treatment of breast cancer. First of all, surrogate markers of molecular subtypes of breast cancer: ER (estrogen receptor), PR (progesterone receptor) and HER2 (human epidermal growth factor receptor type 2) markers. They are recommended as mandatory for determining the receptor status of breast cancer in order to select the most effective treatment and improve disease prognosis [12].

Another biomolecular marker widely used in the world literature is Ki-67, which has been used for a long time as an indicator of tumour cell proliferation and is used to predict the response to NAC [5, 13]. In clinical practice, Ki-67 is considered to be a reliable indicator of response to treatment, but there are difficulties in its widespread use due to the estimation of threshold values [14]. The importance of Ki-67 assessment is greatest in luminal A and luminal B HER2- breast cancer [5]. Higher expression of Ki-67 is generally observed in TNBC [13]. However, the data are still controversial. A study by Chinese scientists showed higher Ki-67 expression in patients who achieved a complete pathomorphological response [15]. At the same time, in the work of French colleagues, there was no statistically significant difference in Ki-67 expression between the groups of patients who achieved pCR, which was 68.2%, and those who did not achieve pCR which was 63.85% (p=0.48) [16].

Genomic markers of response to NAC have been described in the literature for a long time [6]. DNA mutations are considered as predictors of prognosis, for example, mutations in the BRCA1 and BRCA2 genes, which contribute to hereditary predisposition to breast cancer [17]. Mutations of these genes are found in 15% of cases in patients with the molecular subtype of TNBC [6, 18]. At the same time, the frequency of pCR in patients with a mutation in TNBC under treatment with standard NAC and platinum drugs ranges from 35 to 70% and to 80% [19].

Somatic mutation of the PIK3CA gene is also one of the widely studied mutations that is frequently found in breast cancer [10]. In a recent study, the impact of this gene mutation on the outcome of TNBC was shown for the first time: patients with PIK3CA mutation receiving platinum and paclitaxel-based NAC had a low relapse-free survival rate compared to patients without the mutation [20].

Some biomarkers of response to NAC are currently known and actively used in clinical practice, but they are effective only for a specific subtype of cancer (Figure 1). or do not have 100% significance in practical application.

Figure 1.

Markers of Response to NAC and Frequency of Complete Pathomorphological Response for Known Molecular Subtypes of Breast Cancer

This is why researchers face the crucial task of finding new biomarkers to predict response to neoadjuvant chemotherapy in breast cancer. The aim of this literature review is to consider potentially useful predictive markers of response to NAC in breast cancer.

The literature search was conducted in PubMed and Google Scholar databases using the keywords “breast cancer”, “neoadjuvant chemotherapy”, “marker of neoadjuvant chemotherapy efficacy in breast cancer”, “markers of response to NAC” in different variations. Full-text articles from 2014 to 2023 were included. The language of the studies was not a barrier to inclusion in this literature review. A total of 69 literature sources were included in the review.

As a result of literature review, we have identified potentially useful candidate markers for predicting response to NAC in breast cancer, with studies nearing the clinical trial stage (Table 1).

Table 1.

Potential Candidate Biomarkers of Response to NAC in Breast Cancer

Biomarker	Research stage	Methodology	Result
CXCL-8	Continued clinical trials are required.	The study included 303 patients with triple negative breast cancer. The NAC regimen included weekly therapy with paclitaxel and carboplatin for all patients. Serum CXCL8 levels were measured at baseline and during surgery using enzyme-linked immunosorbent assay (ELISA). Immunohistochemistry was used to detect CXCR1 and CXCR2 expression in patients with residual tumours after NAC.	Low expression of CXCL8 is associated with a positive response to NAC in TNBC patients [21]. Only four of 103 patients who achieved pCR developed disease relapse [21]. High CXCL8 level is associated with worse outcome in ER/PR+ and HER2+ breast cancer [22]. CXCL8 receptors (CXCR1 and CXCR2) may be a potentially effective therapeutic target. According to phase I clinical trials, reparixin in combination with paclitaxel, targeting CXCR inhibition, reduced tumour metastasis [21].
PD-L1	Continued clinical trials are required.	The presented review discusses the prognostic aspects of PD-L1 testing. The method of immunohistochemical staining was used to assess PD-L1 expression.	PD-L1 expression is found in HER2+ and triple negative breast cancer [23]. Also, PD-L1 can be used as a prognostic marker of the frequency of achieving pCR for TNBC [23].
MELK	Continued clinical trials are required.	A total of 7135 patients with ER+, HER2- and triple negative breast cancer were included. NAC regimens included anthracyclines and taxanes. In order to investigate biological function, groups with low and high MELK expression were compared using gene set enrichment analysis (GSEA) with gene sets from the Molecular Signature Database (MSigDB).	MELK is one of the proliferation markers and is included in clinically used prognostic panels such as MammaPrint and PAM50. When MELK expression is high, achievement of pCR is observed in ER+, HER2- and triple negative breast cancer patients (p < 0.001 and p = 0.027, respectively, with the following NAC regimen: anthracycline and taxane; p = 0.006 + p = 0. 015 for cyclophosphamide, doxorubicin, paclitaxel and 5-fluorouracil; p = 0.003 and p = 0.046, respectively, for cyclophosphamide, doxorubicin, fluorouracil and paclitaxel) [24].
ALDH1	The development stage of therapeutic models.	A total of 40 patients who received 3-6 courses of anthracycline and/or taxane-based NAC were included. Immunohistochemical staining was used to assess ALDH1 expression.	Treatments targeting ALDH1 inhibition may improve the therapeutic outcome of chemotherapy. To date, therapeutic models targeting surface markers, signalling cascades, microenvironment and ABC transporters have been proposed. Also, therapies that induce apoptosis or differentiation for tumour stem cells have been suggested [25].
Deletion 19q13.31–33	Clinical trials NCT02547987 and NCT02124902	Fifty-nine patients with TNBC who received 6 courses of NAC (carboplatin and docetaxel) were included. Whole exome sequencing (WES) was performed to assess the genetic landscape	Proteogenomic analysis of triple negative breast tumours revealed a complex landscape of chemotherapy response associations, including somatic deletion 19q13.31-33 that encodes genes providing lagging DNA strand synthesis (LIG1, POLD1 and XRCC1), which correlate with non-response and selective resistance to carboplatin [26, 27].

We also identified several categories of predictive markers of response to NAC in breast cancer as a result of our literature review.

Biomolecular and biochemical markers

The steroid hormone receptor AR (also known as NR3C4) is prevalent in 90% of all breast cancer cases [28, 29]. However, the question of whether this receptor is a predictive factor for response to NAC in breast cancer and what role it plays in oncogenesis remains open to this day [29]. A recently published study speculated about the nature of this receptor. They found that AR activation has an inhibitory effect on ER. Since ERα is the dominant pathway that promotes tumour growth in ER+ breast cancer, suppression of ERα via AR may slow tumour progression, which may further lead to a positive outcome in patients [30]. AR expression is absent in 80% of TNBC cases. At the same time, TNBC with AR- correlates with a higher rate of achieving complete pathomorphological response than AR+. This proves that AR+ reduces the likelihood of pCR [18]. There is a suggestion that the lower pCR rate for AR-expressing tumours may be due to a lower proliferation rate, making this subgroup more resistant to chemotherapy [13].

For other markers, such as VEGFR2 (vascular endothelial growth factor receptor 2) and VIM (vimetin) in TNBC there is no association with a high probability of achieving pCR [31]. However, FGFR4 (fibroblast growth factor receptor 4), NUP98 (nuclear pore complex protein), Bcl2 (apoptosis regulator 2), ALDH1 (aldehyde dehydrogenase 1), YAP1 (Yes-associated protein 1) and MMP7 (matrix matalloproteinase-7) have been shown to be associated with poor response to NAC in TNBC [13, 31].

To date, the FGFR4 protein is known to contribute to metastasis and chemoresistance in breast cancer, making it a potential target for research [32]. This protein is also resistant to HER2, which is the main reason of inefficient treatment in patients with HER2+ breast cancer [32].

Bcl2 is also involved in oncogenesis and shows resistance to drug therapy [31]. Bcl2 together with VIM is associated with metastasis to axillary lymph nodes [31]. These proteins are considered as potential markers of response to NAC in breast cancer.

In a recently published study, an association between ALDH1 and response to NAC was shown for the first time [25]. It was found that in the group of those patients who had minimal ALDH1 levels after NAC, overall survival was higher [25]. This suggests that treatment aimed at inhibiting aldehyde dehydrogenase 1 may improve the therapeutic outcome of chemotherapy [25]. Based on these findings, various therapeutic models have been proposed, but the study of this biomarker requires more time [25].

In the current literature, microRNAs are increasingly being considered as one of the possible ways not only to distinguish cancer subtypes, but also to predict the response to NAC [33]. It is known that microRNA in luminal B HER2-negative breast cancer can be used as a predictive biomarker of response to NAC, but the results to date remain controversial [34]. In particular, a change in miR-34a-5p expression has been shown with taxane-containing and/or anthracycline-containing NAC regimens. Activation of miR-375 and miR-4516 was also observed after neoadjuvant chemotherapy. A marked decrease in miR-125b-5p expression was found in the group of no response to NAC, while miR-125b-5p levels remained relatively stable in the group with complete and/or partial response to treatment [34]. It was found that decreased levels of miR-21 and miR-195 can also be considered as a potential marker of response prognosis to NAC [33]. Correlation of miR-195 with treatment has been performed previously. There is evidence in the literature that high miR-195 levels correlate with poor response to NAC [35]. Based on the data described above, miRNAs have been evaluated as promising prognostic biomarkers, but they still need further validation [36].

The first experience of identifying differentially methylated genes by whole-genome bisulfite DNA sequencing, which can be used as a marker of breast cancer response to NAC, is presented in the literature. The methylation frequencies of 10 informative genes (SLC9A3, C1QL2, DPYS, IRF4, ADCY8, KCNQ2, TERT, SYNDIG1, SKOR2, and GRIK1) identified in luminal B breast cancer samples differ between patients responding and non-responding to NAC. Three combinations, (1) IRF4 and C1QL2; (2) IRF4, C1QL2 and ADCY8; (3) IRF4, C1QL2 and DPYS had similar ROC characteristics with AUCs of 0.75, 0.78 and 0.74, respectively. The classifier based on IRF4 and C1QL2 met the requirements of the diagnostic panel with a diagnostic accuracy of 0.75 with a sensitivity of 75% and specificity of 75% [37].

Another interesting marker is GBP5 (guanylate binding protein 5). GBP5 may be a useful biomarker for predicting the therapeutic efficacy of taxane-based chemotherapy in relation to TNBC subtypes. Gene Set Enrichment Analysis computer modelling and cell-based assays showed that GBP5 enhances the cytotoxic efficacy of paclitaxel through activation of the Akt/mTOR signalling axis and suppression of autophagy formation in TNBC cells. It is possible to identify an insensitive population even in the BL1 subtype, which is very sensitive to DNA damaging agents, such as doxorubicin, by the level of GBP5 expression [38].

This year, an interesting study on the role of HIF1α, TWIST1 and ITGB1 as predictive markers of response to neoadjuvant chemotherapy in breast cancer was published. In a prospective study of breast cancer patients receiving NAC, the expression of HIF1α, TWIST1, and ITGB1 was evaluated in biopsy material. These markers were shown to be applicable for predicting a good response to NAC (AUC = 0.81, 0.85, 0.79 for HIF1α, TWIST1, ITGB1, respectively) [39].

Circulating biomarkers

Circulating markers include circulating tumour cells, molecules and exosomal nucleic acids useful for diagnosis, prognosis and real-time therapy monitoring with less cost and better compliance than tumour biopsy due to minimal invasiveness [40].

Elevated levels of circulating tumour cells (CTCs) at the initial stage of treatment are an early independent marker for predicting poor survival, while molecular profiling of CTCs provides prognostic information for assessing the risk of relapse and superior prognostic evaluation of therapeutic regimens [41]. However, to date, the identification and evaluation of CTCs for predicting response to NAC is a challenging task and requires further investigation. The global literature data remain contradictory. One recent meta-analysis found no correlation between circulating tumour cells and response to NAC [42]. However, in another meta-analysis, this correlation was clearly observed, and the authors argue that the amount of CTCs is useful in predicting response to NAC [43]. As for the detection of CTCs during and after treatment, their persistence after treatment has been shown to correlate with a worse outcome [44].

Circulating tumour DNA (cDNA) is a new field in monitoring disease and assessment of response to NAC [38]. The presence of cDNA has been found to be an important predictor of poor response to NAC [45].

To date, it is not easy to identify serum biomarkers that can predict response to chemotherapy. PGRN/GP88 (progranulin), an oncogenesis factor (involved in tumour cell proliferation and survival), is one of the promising biomarkers in breast cancer [14]. According to researchers, increased expression of progranulin is observed in TNBC and shows tumour chemosensitivity [46].

To date, it is not easy to identify serum biomarkers that can predict response to chemotherapy. PGRN/GP88 (progranulin), an oncogenesis factor (involved in tumour cell proliferation and survival), is one of the promising biomarkers in breast cancer [14]. According to researchers, increased expression of progranulin is observed in TNBC and shows tumour chemosensitivity [46].

Another serum biomarker used as a potential marker for predicting response to NAC in patients with TNBC is CXCL8 (chemokine ligand 8) [21]. Low expression of CXCL8 was found to be associated with a positive response to NAC [21]. At the same time, out of 103 patients who achieved complete pathomorphological effect, only four patients developed disease relapse [21]. CXCL8 has been shown to be associated with a worse outcome in ER/PR+ and HER2+ breast cancer [22].

Also, attention has been paid to CEA (carcinoembryonic AG) and CA15-3 (tumour-associated AG) antigens as prognostic factors for breast cancer [47]. The National Comprehensive Cancer Network (NCCN) has given a ban on the use of these markers for clinical evaluation before treatment [47]. However, the European Group on Tumour Markers (EGTM) recommended the use of CEA and CA15-3 for prognosis, early treatment, and treatment monitoring of breast cancer [48]. In one study, the association between these biomarkers and NAC was conducted. After NAC, it was found that CEA had prognostic value in HER2- and HER2+ breast cancer, while CA15-3 had value only in HER2+ breast cancer [49].

In 2023, an interesting prospective work was published to evaluate the relationship of FTH1 gene-associated CECs (F-CTC) and their dynamic changes with NAC efficacy in patients with non-metastatic breast cancer. FTH1 gene and EMT markers in CTCs were detected before NAC (T0), after 2 courses of chemotherapy (T1) and before surgery (T2). It was shown that F-CTC in peripheral blood ≥1 at T0 was an independent factor for the incidence of pCR in patients with HER2-positive breast cancer (OR = 0.08, 95%CI 0.01-0.98, p=0.048) [50].

The role of Gal-3 (galectin-3) as a marker of chemotherapy efficacy in breast cancer patients was investigated in a prospective study in 2020. A total of 88 patients with newly diagnosed cancer without prior treatment were included. Gal-3 levels in stroma and plasma were measured in each patient at the time of diagnosis and then throughout treatment. Patients were followed up for 84 months to analyse recurrence-free survival. Elevated plasma (adjuvant) and stromal (neoadjuvant) Gal-3 levels were found to be markers of chemotherapy efficacy. Patients with a chemotherapy-induced increase in extracellular Gal-3 had a longer relapse-free period and a significantly lower relapse rate during the 84-month follow-up in comparison with patients who had unchanged or decreased secretion. The findings support the possibility of using Gal-3 in plasma as a marker of chemotherapy efficacy when residual tumour is not visible on imaging. In addition, stromal levels in any residual tumours after chemotherapy can also be used for predicting long-term prognosis in patients [51].

Immunological markers

Because the tumour is transformed from normal tissues, it induces innate immune responses in order to eliminate nascent tumour cells through immunoreduction [41].

The tumour microenvironment plays an important role in response to ongoing treatment and prognosis in patients with breast cancer and includes immune cells or molecules, blood vessels, fibroblasts, mesenchymal cells, adipocytes and extracellular matrix [52, 53]. Immune cells that contribute to tumour immunoreduction include TILS (tumour infiltrating lymphocytes), TAMS (tumour associated macrophages), Tregs (regulatory T cells), NKT (natural killer cells) and MDSCs (myeloid derived suppressor cells) [54]. The main microenvironmental components can be considered as potential biomarkers of response to antitumour therapy [41].

Infiltrated regulatory T cells have been shown to decline more strongly during chemotherapy than normal T cells, it is suggested that Tregs are more sensitive to the chemotherapy regimen [55].

It was found that in TNBC and HER2+ breast cancer, a high ratio of CD8+/FOXP3+ TILs can be considered as a valuable biomarker for assessing response to NAC [56]. TILs are also prognostic markers for TNBC, where high TIL density is associated with better survival [18]. However, it is essential to take into account TIL density, TIL phenotype and location for consideration of TIL as a prognostic marker [57].

PD-L1 (ligand of programmed cell death receptor-1) has been known to scientists for a long time, as well as its role in oncogenesis. However, only recently scientists have started to actively study the influence of this gene expression on prognosis after neoadjuvant chemotherapy [23]. In breast cancer, PD-L1 expression together with increased TIL density plays an important role in predicting response to NAC in HER2+ and triple negative breast cancer [23]. It is believed that PD-L1 can be used as a prognostic marker of pCR achievement rate for TNBC [23]. Meanwhile, the use of PD-L1+ (positive expression) to predict pathological response to NAC in breast cancer has shown obvious accuracy (OR = 2.01; 95% CI 1.35-3.01; P<0.05) [58].

The expression of immune checkpoint receptors (ICRs) on TILs, where PD-L1, TIM-3 (T-cell immunoglobulin-3), LAG-3 (lymphocyte activating gene 3) and CTLA-4 (cytotoxic T-lymphocyte glycoprotein 4) are included, has long attracted the attention of researchers because of its positive correlation with immunotherapy in breast cancer [57]. It was found that PD-L1, LAG-3 and CTLA-4 were associated with a positive response to chemotherapy among 61 patients with TNBC, most of whom received NAC with anthracyclines and taxanes, whereas TIM-3 expression was associated with a worse response to NAC [59].

Recently, FKBP12 (FK506-binding protein 12) was found to be a prognostic biomarker of anthracycline-based NAC efficacy in TNBC [60]. Deletion of FKBP12 leads to poor prognosis and increased resistance to anthracycline-based chemotherapy [60].

MELK (maternal embryo leucine zip kinase), which plays a significant role in cell cycle and proliferation, has been actively studied since 2021 [24]. At high expression of this gene, it has been observed to achieve complete pathomorphological response during NAC in patients with ER+, HER2- breast cancer and TNBC [24]. In this regard, MELK can also be considered as a potential predictive biomarker.

Tumour stem cells and plasticity markers

Tumour stem cells (TSCs) are undifferentiated cells with drug and radioresistance. According to researchers, TSCs persist after therapy and cause recurrence and metastasis, which makes them a good therapeutic target [61]. At the same time, it is difficult to prove NAC efficacy in relation to TSCs in non-luminal breast cancer, but to date there is evidence that the expression of TSC markers in tumour cells is significantly altered by NAC [62]. For example, ALDH biomarker described above and CD24-/+ are actively used in clinical practice as TSC markers [61]. Today, new stem cell markers are actively searched for to effectively predict the response to NAC [63].

Wright et al. first demonstrated the role of CD133 as a biomarker on cell lines from BRCA1-associated tumours [64]. There are data that CD133+ expression has a positive correlation with poor survival in PR-, ER-, and HER2+ breast cancer [65]. At the same time, this biomarker may be useful in predicting the response to NAC, and its decrease will indicate in favour of NAC efficacy [65].

Amplifications of stemness gene loci are considered as markers of response to NAC in breast cancer patients. According to our own previous studies, ectopic expression of stemness genes (OCT3, SOX2, KLF4, MYC, NOTCH1, NANOG, etc.) is caused by the presence of amplifications in the following chromosomal regions: 3q, 5p, 6p, 7p, 7q, 8q, 13q, 9p, 9q, 10p, 10q21.1, 16p, 18chr, 19p. The occurrence of amplifications in the regions of stemness gene localisation during NAC (22% of cases) in residual tumours was associated with a very high incidence of metastasis (91% of cases). Deletion of tumour clones with stemness gene amplification under NAC (42% of cases) resulted in 100% metastasis-free survival [66]. In other words, elimination of clones with amplifications may be a good measure of NAC efficacy. In the following prospective study, a new strategy of neoadjuvant chemotherapy prescription depending on the presence of stemness gene amplifications in the tumour before treatment was tested.

If there were two or more amplifications, patients were treated with NAC according to a personalised regimen (Group 1); if there was no stemness gene amplification in the tumour, patients were not treated with NAC, and treatment was started with surgery (Group 2). Group 3 served as historical controls. The objective response rate to NAC in Groups 1 and 3 was 79%. Metastatic-free survival was noted in 100% of cases in Group 2 patients. The metastasis rate in Group 1 patients was 10% (4/41), in Group 3 patients it was 47% (14/30). It was shown that NAC treatment was most appropriate in patients with the presence of stemness gene amplifications in the primary tumour, while in the absence of amplification NAC resulted in a sharp decrease in the metastasis-free survival rate [67].

Thus, tumour stem cells and stemness gene amplifications can be useful for predicting the efficacy of NAC.

Conclusions and perspectives

Today, HER2, ER, PR, PD-L1, ALDH, CD44, CD24, as well as CEA and CA15-3 are widely used biomarkers of NAC efficacy in clinical practice. To date, there are a number of agents whose action is related to the need and importance of determining previously identified biomarkers of response to NAC. Anastrazole is one such agent, a non-steroidal compound that reduces estrogen levels and is based on the response of the circulating biomarker CA 15-3. A decrease in CA 15-3 levels indicates a positive therapeutic effect. At the same time, an increase in CA 15-3 concentration during the course of anastrazole therapy, which may be associated with disease progression [68]. Another example is the complex of everolimus (associated with the biomarker FKBP12) and exemestane. Despite the high risk of adverse events, this combination therapy is useful for the treatment of patients with HER2-negative and ER-positive tumours with good tolerability [69, 17]. It should be noted that in the previous chapter, amplifications of stemness gene loci were described, and nowadays they are used to determine the appropriateness of NAC and further personalised treatment of breast cancer. Moreover, interesting results on the newest markers of preoperative treatment efficacy are presented in the literature (Figure 2).

Figure 2.

Markers of Preoperative Treatment Efficacy Presented in the World Literature

However, work aimed at finding potentially useful biomarkers for predicting NAC efficacy in breast cancer is actively ongoing. Many biomarkers are only at the research stage, and only a small proportion of them are close to clinical trials. Response assessment to NAC therapy of the biomarkers presented in this review may be useful for predicting the therapeutic response to different anticancer agents, which may further improve treatment strategies and reduce side effects from ineffective therapy. The prediction of response to NAC in breast cancer still requires continued further study, as most of the work done so far has limited efficacy.

In order to find effective markers of response to NAC, a sufficient number of successful clinical trials leading to a complete pathomorphological response to preoperative treatment and a high survival rate among breast cancer patients should be conducted.

Author Contribution Statement

Writing the text of the article: Ekaterina Kravtsova. Preparation of illustrations, editing of the article text: Matvey Tsyganov. Information search: Irina Tsydenova, Daria Dolgasheva, Ksenia Gaptulbarova. Text correction and final editing of the article: Marina Ibragimova, Nikolai Litviakov. All authors have read and agreed to the published version of the manuscript.