Association of METTL14 expression with prognosis and immunotherapy in breast cancer

Introduction

Breast cancer (BC) has emerged as a leading contributor to rising global morbidity and mortality rates in the field of cancer, and is a major public health challenge, maintaining its status as the most commonly diagnosed malignancy in women (1). Statistics demonstrate that annually, there are more than 1.3 million newly diagnosed cases of BC, leading to approximately 500,000 deaths on a global scale (2). In recent years, there has been a marked improvement in the survival rates of patients diagnosed with BC. This enhancement can be attributed to the introduction of treatment options, including surgery, hormonal therapy, chemotherapy, radiation therapy, and targeted therapy (3-5). Notwithstanding the above advancements, there remains a paucity of evidence to support the efficacy of these therapies, particularly in cases of advanced BC and triple-negative BC (TNBC). Consequently, there is an immediate and pressing necessity to identify new therapeutic targets and prognostic biomarkers that could improve outcomes for individuals diagnosed with BC. Additionally, it is essential to recognize that the immune system is pivotal in the progression of cancer. The immune system is not only involved in the body’s defense against tumors but also influences how cancer cells grow and spread. Understanding the intricate relationship between the immune response and cancer can provide valuable insights into potential therapeutic approaches. Although BC is generally recognized as a tumor with lower levels of immune reactivity, numerous clinical studies have pointed out that patients exhibiting elevated levels of immune cell infiltration are more likely to demonstrate favorable prognoses and responses to treatment. This trend is particularly evident in cases of TNBC and human epidermal growth factor receptor 2 (HER2)-positive BC (6,7). Researches have indicated that immunotherapy can effectively modulate both innate and adaptive immune responses of BC patients (8,9). While antibodies targeting programmed death-1 (PD-1), programmed cell death-ligand 1 (PD-L1), and cytotoxic T-lymphocyte-associated protein 4 (CTLA4) are being explored for clinical applications, the challenge of immune evasion by tumor cells poses a significant hurdle for effective cancer immunotherapy. Considering that BC displays distinct features regarding immune cell infiltration and the immune response when compared to other types of cancer, it is crucial to conduct additional research to pinpoint immune-related genes that are prognostically significant for BC patients and can potentially serve as targets for immunotherapeutic strategies.

N⁶-methyladenosine (m⁶A) is identified as the most prevalent reversible modification observed in various types of RNA within human cells (10-12). Two main types of proteins significantly facilitate the process of m⁶A modification, playing essential roles in this biochemical mechanism. The first category comprises key proteins, including methyltransferase-like 3 (METTL3), METTL14, and WILMS tumor 1 associative protein (WTAP). These proteins function in a collaborative manner to facilitate the biochemical process of adding multiple methyl groups to RNA molecules. Their coordinated action constitutes a vital post-transcriptional modification that can affect RNA stability, translation efficiency, and interactions with other biomolecules, thereby impacting gene expression and overall cellular activity. The second category encompasses fat mass and obesity-associated protein (FTO), along with alkB homolog 5 (ALKBH5). These proteins function as demethylases, which are enzymes that remove methyl groups from various substrates. These proteins can reverse the methylation process, thereby regulating the amounts of m⁶A modification found in RNA (13). m⁶A regulatory factors are considered to be involved in a variety of biological processes, including tumor growth, invasion, and metastasis (14,15). In the context of pancreatic and colorectal cancers, the levels of m⁶A regulatory factors correlate with the infiltration of tumor-infiltrating immune cells, offering specific insights into immune checkpoint inhibitor (ICI) responses (16,17). As a central methyltransferase in m⁶A modification, METTL14 is found to be abnormally expressed across numerous tumors (18). Ma et al. demonstrated that elevated METTL14 levels were linked to enhanced outcomes from immunotherapy in patients with endometrial cancer (19). Moreover, the impairment of METTL14 promotes the CD8⁺ T-cells activation and improves the effectiveness of immunotherapy directed against PD-1, which correlates with the m⁶A modification of HSD17B6 in lung cancer (20). Nevertheless, the exploration of METTL14’s impact on the immune microenvironment in BC remains insufficient.

In our preliminary study, an exploratory investigation was conducted into the expression levels of METTL14 and its relationship with a range of clinicopathological characteristics, along with the prognostic significance for BC patients. Our results demonstrated a significant link between METTL14 levels and the clinical characteristics of the disease. Additionally, we found that the overexpression of METTL14 (oe-METTL14) significantly contributes to suppressing the growth, movement, and invasion of BC cells, thereby emphasizing its possible significance as a therapeutic candidate. Moreover, we explored the relationship between METTL14 expression and the immune microenvironment by employing the Tumor Immune Estimation Resource (TIMER) algorithms alongside the Tumor-Immune System Interaction Database (TISIDB). We also examined the immune cell types present in breast tissues using multiplex immunofluorescence (mIF) techniques.

Finally, we conducted an evaluation of the response to immunotherapy among distinct groups characterized by varying expressions of METTL14, employing the Tumor Immune Dysfunction and Exclusion (TIDE) method as our analytical framework. The findings from this evaluation underscore the critical role of METTL14, indicating its promise as a prognostic biomarker as well as an important therapeutic target. By focusing our efforts on targeting METTL14, we are confident that enhancing the effectiveness of immunotherapy for BC treatment is achievable, potentially resulting in improved outcomes for patients. We present this article in accordance with the MDAR reporting checklist (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1331/rc).

Methods

Patients and samples

The raw RNA sequencing reads for breast carcinoma were obtained, along with matched paracancerous tissues, from The Cancer Genome Atlas (TCGA) database, which is accessible at https://portal.gdc.cancer.gov/. This dataset included corresponding clinical information for a total of 96 patients. In addition to these data, fresh BC tissues and adjacent non-tumorous tissues were also collected from the Maternal and Children Health Hospital of Hubei Province in 2020. It is noteworthy that these patients had not received any preoperative treatments such as radiotherapy or chemotherapy. This approach was crucial in maintaining the integrity of the tissue samples, allowing for more accurate analysis and research outcomes. Following surgical resection, the tissues were promptly frozen in liquid nitrogen to preserve their molecular composition and were subsequently stored until needed for analysis. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Ethics Committees of Maternal and Children Health Hospital of Hubei Province {No. [2020] IEC(LW041)} and informed consent was obtained from all patients.

Gene expression data mining and survival outcome analysis

The expression profile of mRNA was constructed utilizing the Illumina Hiseq 2000 RNA sequencing platform. This advanced technology allows for high-throughput sequencing, enabling researchers to obtain comprehensive insights into gene expression levels across various conditions. To accurately quantify the transcriptomic data obtained from this sequencing, the fragments per kilobase of transcript per million mapped reads (FPKM) were employed (21,22). In order to assess the overall survival rates of BC patients, the Kaplan-Meier plotter was employed. This statistical tool is widely recognized for its effectiveness in estimating survival functions from lifetime data, which can be accessed at the following website: http://kmplot.com/analysis. In this examination, individuals were methodically divided into two separate categories according to their levels of METTL14 expression. The threshold for these categories was specifically established using the median expression level of METTL14.

Estimate tumor immune cell infiltration, immune subtype

The study investigated how somatic copy number alterations (SCNA) of METTL14 relate to immune infiltration levels in patients with BC, utilizing the Tumor Immunity Evaluation Online database known as TIMER (https://cistrome.shinyapps.io/timer/). Additionally, TIMER2.0 (http://timer.cistrome.org/) was employed to evaluate the relationship between METTL14 expression levels and the various types of immune cells present in patients with BC. The TISIDB (http://cis.hku.hk/tisidb/) was used to assess the distribution of METTL14 expression in various immune cell subtypes. This assessment sought to provide insights into how METTL14 is distributed among different immune cell types, with the potential to reveal its function in immune responses and associated biological processes.

Assessment of immunotherapy response

Genes that are linked to human leukocyte antigen (HLA) and immune checkpoints play a vital role in regulating immune responses. In this study, we specifically examined the expression levels of six classical HLA genes, namely HLA-A, HLA-B, HLA-C, HLA-DQA1, HLA-DQB1, and HLA-DRB1. Additionally, we analyzed the expression of four key immune checkpoints: PD-1, PD-L1, T cell immunoglobulin and mucin-containing molecule 3 (TIM3), and lymphocyte activation gene 3 (LAG3). These assessments were conducted across various groups differentiated by their levels of METTL14 expression. This comparative analysis aims to shed light on how variations in METTL14 expression might influence the immune landscape, particularly in relation to HLA gene and immune checkpoint expression. The TIDE algorithm is a bioinformatic method that has been developed for the purpose of predicting the probability of a response to immunotherapy (23).

mIF

The mIF staining was conducted at Abcarta Medtech Co., Ltd. (Suzhou, China). Two panels comprising a total of eight markers were analyzed: panel 1 included CD4, CD8, CD63, and CD68, while panel 2 contained PD-1, LAG3, TIM3, and PD-L1. Multiple images were obtained from serial sections derived from the same block for each patient, stained with 4',6-diamidino-2-phenylindole (DAPI) alongside four markers from panel 1 or panel 2. Detection of each panel was based on a 4-µm-thick slide cutting from formalin-fixed paraffin-embedded (FFPE) breast tissues. Tissue samples were subjected to a baking process at 60 ℃ for 1 hour. Following this step, the samples underwent deparaffinization using two applications of a de-waxing solution (Abcarta, PS000) at 65 ℃ for 1 minute each, and were then rinsed five times with pure ethanol. Antigen retrieval was carried out using the pH 9.0 ethylenediaminetetraacetic acid (EDTA) solution (1×) (Abcarta, PS900) at a temperature of 100 ℃ for a duration of 20 minutes. Following these initial preparations, the slides were incubated with a single clone of either CD4, CD8, ,CD63, CD68, PD1, LAG3, TIM3, or PD-L1 primary antibodies. This was succeeded by the application of polymeric horseradish peroxidase (HRP)-conjugated secondary antibodies. To facilitate visualization, an appropriate Opal fluorophore-conjugated tyramide signal amplification (TSA) reagent was then added to the slides at a dilution of 1:100. After each application, the slides were thoroughly rinsed with a washing buffer to ensure proper washing between each step. Following the deposition of the TSA, the slides underwent another round of HIER, which served to strip the tissue-bound primary and secondary antibody complexes, thus preparing the slides for the labeling of subsequent markers. This meticulous process was repeated until all four markers had been successfully labeled on the slides, culminating in the addition of spectral DAPI. This step was crucial for enhancing the visibility of the cellular structures under examination. Subsequently, the slides were mounted with an anti-fixation medium to preserve the stained samples and ensure their integrity for further analysis. Once prepared, the stained slides were scanned and imaged utilizing the Heidstar automatic digital fluorescence scanning system (version 23.10.30). This advanced imaging technology allowed for high-resolution capture of the fluorescence signals, facilitating detailed observation and analysis of the stained specimens.

Immunohistochemistry

The obtained samples for immunochemical staining included 20 normal breast tissues alongside 82 specimens of BC. The process began with deparaffinization in xylene, followed by hydration through a series of graded alcohols. Antigen retrieval from the paraffin sections was achieved using heat-mediated techniques at a pH of 9.0, with EDTA serving as the buffer solution. Subsequently, 100 µL of the primary antibody directed against METTL14 (supplied by Sigma, St. Louis, MO, USA; product code HPA038002-100UL, diluted at 1:100) was applied to the sections. After being thoroughly washed, the sections were treated using the EnVision/horseradish HRP kit in conjunction with a substrate kit containing 3,3'-diaminobenzidine (Dako, Agilent Technologies, Santa Clara, CA, USA) at room temperature for 15 minutes. Once counterstained with hematoxylin, the specimens underwent dehydration and were subsequently mounted. The assessment of METTL14 immunohistochemical staining adhered to the procedures outlined in previous studies (24). The intensity scores were categorized in this manner: a score of 0 indicates the absence of staining; a score of 1 reflects weak positivity; a score of 2 indicates positivity; and a score of 3 represents strong positivity.

Western blotting

The process of extracting proteins utilized the RIPA lysis and extraction buffer from the Magna RZP Kit (Millipore, Billerica, MA, USA). After the extraction, a 10% sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) gel was employed to separate the proteins based on their molecular weight. Upon completion of the separation, the proteins were transferred onto a polyvinylidene fluoride (PVDF) membrane (GE Healthcare, Chicago, IL, USA). Subsequently, the membranes were subjected to a blocking procedure with a 5% nonfat milk solution, which was permitted to occur for 1 hour at ambient temperature. Subsequently, the membranes were treated with distinct antibodies that specifically recognize METTL14, diluted to 1:300 (HPA038002, Sigma), along with actin antibodies at a dilution of 1:1,000 (Proteintech, Rosemont, IL, USA). This incubation was conducted overnight at 4 ℃. Following the incubation process with secondary antibodies, which were diluted to a ratio of 1:5,000, the subsequent band signal was successfully identified utilizing the Odyssey imaging system developed by LI-COR Biosciences​ (Lincoln, NE, USA). This imaging system is known for its advanced capabilities in detecting and analyzing protein bands, thereby providing reliable results for further research and analysis. The careful dilution of the secondary antibodies ensures optimal binding and signal amplification, which is crucial for accurate detection in various experimental setups.

Cell culture and plasmid transfection

The plasmid for the oe-METTL14 was obtained from Miaoling Biotechnology (Wuhan, China) to enhance METTL14 levels. The human BC cell line MDA-MB-231 obtained from the China Center for Type Culture Collection was routinely maintained in McCoy’s 5A medium, a specialized growth medium provided by Gibco (Grand Island, NY, USA). The cells were incubated at a temperature of 37 ℃ within a controlled environment that included a mixture of 5% carbon dioxide. To support optimal growth and proliferation, the medium was enriched with 10% fetal bovine serum (FBS), which provides essential nutrients and growth factors. In addition, a 1% solution of penicillin and streptomycin, also sourced from Gibco, was included to prevent bacterial contamination during the culture process. This careful combination of conditions ensures the viability and health of the MDA-MB-231 cells during experimentation. The cells were sourced from Pumei Biotechnology Co., Ltd. (Wuhan, China). After a 24-hour incubation at 70% confluence, transfection was performed using either oe-METTL14 or a control vector plasmid, employing Lipofectamine 3000 (ThermoFisher, Carlsbad, CA, USA) as per the instructions provided by the manufacturer.

Migration and invasion assays

Transwell assays serve to assess the migratory and invasive properties of BC cells through the use of transwell chambers (Corning Inc., Corning, NY, USA). Invasion tests were conducted utilizing matrigel-coated transwell chambers (BD Biosciences, Franklin Lakes, NJ, USA). Matrigel was excluded from the migration experiments. Transfer 200 µL of Dulbecco’s modified Eagle medium (DMEM) that is free of FBS, which includes 4.0×10⁴ transfected cells, into the upper section of the transwell chamber. In the lower section, introduce 500 µL of DMEM enriched with 20% FBS to serve as a chemoattractant. Following a 24-hour incubation period at 37 ℃ in a 5% CO₂ environment, the subsequent step involved the removal of non-invading cells by using cotton swabs. Thereafter, the cells attached to the lower surface were subjected to a washing procedure with phosphate-buffered saline (PBS) to eliminate any residual substances. After washing, the cells were fixed using paraformaldehyde, a common fixative that preserves cellular structures for examination. Finally, the cells were subjected to staining with crystal violet for a duration of 20 minutes, which allows for enhanced visualization of the cells under a microscope, facilitating subsequent analysis and evaluation. Cells that were invaded were tallied in six random areas using a light microscope.

Wound-healing experiment

A total of 5.0×10⁴ MDA-MB-231 cells that had been transfected were placed into two wells of a 12-well plate arranged in a two-chamber configuration. After 24 hours, remove the mold, change the culture medium to serum-free DMEM, and take a picture of the “gap area (0 hour)”. After 24 hours, a photo of the “rest area (24 hours)” will be taken. According to the calculation formula “cutting area (0 hour) − cutting area (24 hours)/cutting area (0 hour)”, the relative wound area was measured using ImageJ software.

Cell proliferation assays

The rates of cell proliferation were assessed using the cell counting kit-8 (CCK-8) assay. For this assay, 2.0×10³ transfected MDA-MB-231 cells were distributed into a 96-well plate, ensuring that there were five replicate wells for each group. Subsequent to the seeding process, the degree of absorption was evaluated at a wavelength of 450 nm, at intervals of 0, 24, 48, and 72 hours, in adherence to the manufacturer’s guidelines.

Statistical analysis

The data are presented in a format that includes the mean value along with the standard error of the mean (SEM). In conducting the statistical analysis, comparisons between two groups were made using Student’s t-tests, whereas one-way analysis of variance (ANOVA) was applied to evaluate multiple comparisons by examining the mean of each column in relation to the means of all other columns. To determine correlations, Pearson correlation coefficients (r) were computed, and the significance of these correlations was evaluated through two-tailed t-tests with r set at 0. Additionally, the scores from the immunohistochemistry staining of METTL14 in both benign breast tissues and BC samples were statistically analyzed using χ² tests. The software GraphPad Prism 5.0 was utilized for generating graphs. Data analysis was performed with SPSS (version 16.0), where a P value <0.05 signifies a statistically significant difference.

Results

A low level of METTL14 suggests a negative outlook for individuals diagnosed with BC

An examination of the TCGA database showed that the expression level of METTL14 was lower in 96 BC samples when compared to nearby normal tissues (Figure 1A). We additionally examined METTL14 expression levels in patients classified according to varying statuses of estrogen receptor (ER), progesterone receptor (PR), and HER2. Our research indicates that the expression levels of METTL14 were markedly reduced in individuals diagnosed with TNBC when compared to those with ER⁺/PR⁺/HER2⁺ and ER⁺/PR⁺/HER2⁻ statuses. The observed variation of METTL14 levels in patients exhibiting ER⁺/PR⁺/HER2⁺ and those exhibiting ER⁺/PR⁺/HER2⁻ was consistent with the differences seen in individuals with ER⁻/PR⁻/HER2⁺ (Figure 1B). In addition, findings from Western blotting and immunohistochemistry revealed a significant reduction in METTL14 protein levels within TNBC tissue samples (Figure 1C-1F). To investigate the relationships between METTL14 expression and different clinicopathological characteristics, we categorized BC tissues into two categories according to high and low levels of METTL14 expression, utilizing the median expression level as the threshold. The analysis revealed that lower METTL14 levels correlated with reduced tumor differentiation and elevated Ki67 proliferation index (Table 1). The survival analysis conducted using the Kaplan-Meier method indicated that patients with BC who displayed low METTL14 levels experienced worse recurrence-free survival (RFS) outcomes (Figure 1G).

Figure 1 METTL14 low level indicated poor prognosis in BC. (A,B) Expression levels of METTL14 were analyzed in breast tumor tissues in comparison to adjacent normal tissues (n=96) and also across various categories of breast tumor tissues classified by their ER, PR, and HER2 statuses: ER⁻/PR⁻/HER2⁻ (n=8), ER⁻/PR⁻/HER2⁺ (n=4), and ER⁺/PR⁺/HER2⁻ (n=32), and ER⁺/PR⁺/HER2⁺ (n=14). Additionally, (C) Western blot analyses were performed for METTL14 expression in patients diagnosed with TNBC (n=4). (D) The quantification of western blotting results was carried out using ImageJ. Furthermore, (E) the assessment of immunohistochemistry staining was performed on normal breast tissues (n=21) and TNBC tissues (n=47). (F) The staining gradations of METTL14 for both normal breast tissues and TNBC tissues were shown. Finally, (G) the online bioinformatics tool Kaplan-Meier plotter was utilized to depict the survival curves for RFS, which are determined by the expression levels of METTL14 in BC. *, P<0.05; **, P<0.01; ns, no significant difference. BC, breast cancer; CI, confidence interval; ER, estrogen receptor; HER2, human epidermal growth factor receptor 2; HR, hazard ratio; METTL14, methyltransferase-like 14; N, normal; PR, progesterone receptor; RFS, recurrence-free survival; T, tumor; TNBC, triple-negative breast cancer.

METTL14 modulates the malignant proliferation and invasion of TNBC cells

As the above data showed that METTL14 expression was linked to the proliferation index and tumor differentiation of patients with BC, we then went on to conduct experiments to see if METTL14 was associated with BC progression. To confirm this, an experiment was conducted in which the METTL14 gene was overexpressed in the TNBC cell line MDA-MB-231, while the control group was treated with the empty pcDNA3.1 vector. As observed in the CCK-8 assay, METTL14 overexpression significantly suppressed the proliferative capacities of tumor cells (Figure 2A). The influence of METTL14 on the migration of BC cells was evaluated using both wound healing and transwell migration assays. Collectively, these findings demonstrate that the increased levels of METTL14 diminished the migratory abilities of MDA-MB-231 (Figure 2B-2E). Furthermore, the heightened expression of METTL14 contributed to a decline in the invasiveness of MDA-MB-231 (Figure 2D,2E).

Figure 2 METTL14 modulated the malignant proliferation and invasion of TNBC cell. (A) The proliferation of MDA-MB-231 cells transfected with a plasmid for METTL14 overexpression is illustrated by the growth curves obtained from the CCK-8 assay (n=4). (B) Migration capacity of breast cells upon METTL14 overexpression was determined by wound-healing assays in MDA-MB-231. Scale bar, 200 µm. (C) Percent wound healing area quantified in histogram (n=3). (D) Migration and invasion capabilities of MDA-MB-231 cells were detected by transwell assays and crystal violet staining. Scale bar, 200 µm. (E) Quantify the relative numbers of migrating and invading cells in histograms (n=3). *, P<0.05; **, P<0.01; ***, P<0.001. CCK-8, cell counting kit-8; METTL14, methyltransferase-like 14; NC, negative control; OD, optical density; oe, overexpression; TNBC, triple-negative breast cancer.

The association of METTL14 expression in breast carcinoma and the infiltration of immune cells within the tumor immune microenvironment

The presence of immune cells plays a vital role in shaping the evolution and advancement of tumors, significantly impacting the outcomes for patients diagnosed with cancer. Consequently, the association between METTL14 levels and the infiltration of 20 different immune cell types was investigated by utilizing the TIMER database within the framework of BC. An analysis conducted using the TIMER database indicates a significantly positive relationship between the expression levels of METTL14 and the infiltration of various immune cell types, specifically CD8⁺ T cells, CD4⁺ T cells, macrophages, and mast cells. Among these immune cell types, the most pronounced correlation was found in relation to the infiltration of CD4⁺ T cells (r=0.492, P<0.001). Conversely, there was a negative correlation with regulatory T cells (Tregs), myeloid-derived suppressor cells (MDSCs), natural killer (NK) cells, and follicular helper T cells (Figure 3A). Furthermore, the module focused on SCNAs emphasized the relationship between the infiltration of immune cells and the variations in somatic copy numbers linked to METTL14. As illustrated in Figure 3B, varying copy numbers of METTL14 considerably influenced the immune infiltration levels in BC. A further examination of the group with low METTL14 expression indicated significantly elevated ESTIMATEScore and ImmuneScore, and the StromalScore showed no difference between different METTL14 expression groups (Figure 3C-3E). In summary, these findings imply that different expressions of METTL14 result in distinct characteristics of tumor microenvironment (TME) infiltration.

Figure 3 The association of METTL14 expression in breast carcinoma and the infiltration of immune cells within the tumor immune microenvironment. (A) Examination of immune cell infiltration utilizing the TIMER dataset. (B) In the TIMER database, varying levels of immune cell infiltration related to different METTL14 copy number levels were observed. The relationship between the expression levels of METTL14 and the (C) StromalScore, (D) ESTIMATEScore, and (E) ImmuneScore in both the low and high METTL14 groups in BC. *, P<0.05; **, P<0.01; ***, P<0.001. BC, breast cancer; BRCA, breast cancer; MDSC, myeloid-derived suppressor cells; METTL14, methyltransferase-like 14; NK, natural killer; TIMER, Tumor Immune Estimation Resource; TPM, transcripts per million.

The proportion of immune cells in BC

To enhance our comprehension of how METTL14 interacts with immune cells in relation to BC, we first performed a multiplex immunohistochemistry analysis. This analysis employed four specific immune cell markers, which included the T cell markers CD4 and CD8, the macrophage marker CD68, and the mast cell marker CD63. By utilizing this comprehensive approach, we aimed to elucidate the potential interactions between METTL14 and various immune cell populations within the TME. In comparison to normal tissue, there was a notable decrease in the proportion of CD4⁺ cells within the tumor tissue. No differences were observed in the immune cells CD8, CD68, and CD63. Interestingly, the proportion of CD8⁺ cells within the tumor tissue exhibited a tendency to be lower, although these results did not reach statistical significance (Figure 4).

Figure 4 The proportion of immune cells in BC. (A) The upper panel presents a typical multi-color immunofluorescence image depicting CD4⁺ (green), CD8⁺ (red), CD63⁺ (cyan), and CD68⁺ (yellow) immune cells in a normal breast tissue sample. In contrast, the lower panel illustrates a representative multi-color immunofluorescence image of these immune cells in a breast tumor sample. (B) An analysis of the ratio of CD4⁺ immune cells found in normal breast tissue samples (n=3) compared to those from tumor samples (n=7). (C) A comparison of the percentage of CD8⁺ immune cells in healthy breast tissue samples (n=3) versus those obtained from tumor specimens (n=7). (D) A comparison of the fraction of CD63⁺ immune cells between normal breast samples (n=3) and tumor samples (n=7). (E) An analysis of the occurrence of CD68⁺ immune cells in healthy breast tissue samples (n=3) versus those from tumors (n=7). *, P<0.05; ns, no significant difference. BC, breast cancer.

The proportion of CD4+ cell in different METTL14 expression samples

We examined the percentage of CD4⁺ immune cells under different METTL14 expression levels in BC. The METTL14 lower expression group demonstrated a greater decline in the proportion of CD4⁺ immune cells (4.117%±1.297% vs. 10.31%±1.917%, P=0.06), though this decline did not reach statistical significance (Figure 5).

Figure 5 The proportion of CD4⁺ cell in different METTL14 expression samples. (A) The top section showcases a typical immunofluorescence image depicting CD4⁺ (green) immune cells from the group with low METTL14 expression, whereas the bottom section presents an image of CD4⁺ (green) immune cells from the group exhibiting high METTL14 expression. (B) A comparison was performed on the ratio of CD4⁺ immune cells between the group exhibiting high levels of METTL14 expression (n=4) and the group demonstrating low expression levels (n=3). METTL14, methyltransferase-like 14.

METTL14 is related to immunosuppressive signature in BC

We performed an analysis comparing the expression levels of genes relevant to immune checkpoints and HLA genes among groups with low and high expression of METTL14. In the cohort with low levels of METTL14, a rise in the expression of genes associated with HLA was noted. In terms of immune checkpoints, a significant negative relationship was identified between the levels of PDCD1 (also known as PD-1) and LAG3 and those of METTL14. In contrast, hepatitis A virus cellular receptor (HAVCR2, also known as TIM3) exhibited a positive association with the expression of METTL14 (Figure 6A). Consequently, we conducted mIF to assess the expression of PD-1, LAG3, TIM3, and PD-L1 on paraffin sections collected from eight BC patients. The results revealed that PD-1 expression was significantly higher in the low METTL14 group, whereas TIM3 expression was significantly lower in the same group. Additionally, there was no significant difference in LAG3 and PD-L1 expression between the low and high METTL14 groups (Figure 6B-6D).

Figure 6 METTL14 is related to immunosuppressive signature in BC. (A) A boxplot illustrating the variation in HLA expression alongside immune checkpoint genes across various METTL14 expression groups. (B) A comparison was performed on the ratio of PD-1⁺, TIM3⁺, LAG3⁺, and PD-L1⁺ immune cells between the group exhibiting low levels of METTL14 expression (n=4) and the group demonstrating high expression levels (n=4). (C,D) Representative images of multiplex immunohistochemistry for PD-1 (yellow), LAG3 (cyan), and TIM3 (magenta) from the group with low METTL14 expression in BC (C) and the group with high METTL14 expression in BC (D). *, P<0.05; **, P<0.01; ****, P<0.0001; ns, no significant difference. BC, breast cancer; HAVCR2, hepatitis A virus cellular receptor 2; HLA, human leukocyte antigen; LAG3, lymphocyte activation gene 3; METTL14, methyltransferase-like 14; PD-1, programmed death-1; PD-L1, programmed cell death-ligand 1; TIM3, T cell immunoglobulin and mucin-containing molecule 3.

Role of METTL14 in immunotherapy

We investigated the potential role of METTL14 in predicting immunotherapy outcomes for patients with BC. Our analysis utilizing the TIDE algorithm indicated a positive association between METTL14 expression and TIDE scores. It was observed that the group exhibiting low levels of METTL14 had notably reduced TIDE scores when contrasted with the group characterized by high METTL14 expression (Figure 7A). Additionally, the response rate among individuals categorized within the low METTL14 expression group was found to be significantly higher than that of their counterparts in the high METTL14 expression group (Figure 7B,7C). We further investigated how METTL14 expression correlates with various immune subtypes in BC. The results revealed notable variations in METTL14 expression among the six identified immune subtypes. The wound healing (C1) subtype had the lowest METTL14 expression, whereas the levels in the interferon-γ (IFN-γ) dominant (C2), inflammatory (C3), lymphocyte depleted (C4), and transforming growth factor-β (TGF-β) dominant (C6) subtypes were higher compared to C1 (Figure 7D).

Figure 7 Role of METTL14 in immunotherapy. (A) An analysis of TIDE among distinct METTL14 expression categories. (B,C) The distribution and proportion of immunotherapy responses within the expression groups of BC patients. (D) The comparative expression levels of METTL14 across different immune subtypes. BC, breast cancer; BRCA, breast cancer; CPM, counts per million; IFN-γ, interferon-γ; METTL14, methyltransferase-like 14; TGF-β, transforming growth factor-β; TIDE, Tumor Immune Dysfunction and Exclusion.

Discussion

A substantial body of research has emerged that validates the indispensable role of the immune system in response to conventional therapies and long-term survival of BC patients (25). BCs characterized by HER2 positivity and TNBC exhibit a greater presence of stromal tumor-infiltrating lymphocytes (TILs) at the time of diagnosis compared to luminal breast tumors. Furthermore, the amount of stromal TILs is directly correlated with clinical outcomes (25,26).

In this research, we thoroughly examined the expression, prognostic significance, and immunomodulatory impact of METTL14 in BC, as well as its role in the TME, which presents a potential strategy for immunotherapy in BC.

A thorough examination of the TCGA BC cohort revealed that the expression of METTL14 in BC samples was notably reduced, particularly in TNBC, when compared to other molecular subtypes. In addition, the result was confirmed in clinical BC samples by immunoblotting and immunohistochemistry. Furthermore, a significant association was detected between reduced levels of METTL14 protein and BC prognosis, tumor stage, as well as Ki67 proliferation. The previous study suggests that decreased METTL14 facilitates tumor metastasis in colorectal cancer (27). It has also been reported that METTL14 suppresses gastric cancer progression by regulating miR-30c-2-3p/AKT1S1 axis (28). The experimental results of wound healing, CCK-8, and transwell migration assay are consistent with previous studies, showing that upregulation of METTL14 can suppress both the migration and proliferation of MDA-MB-231 cells in vitro. The results indicate that METTL4 acts as a BC tumor suppressor.

Currently, studies investigating the function of METTL14 in tumor development mainly emphasize the dysregulation of tumor immunity (29,30). Nonetheless, there is a scarcity of research concerning the immune modulation by METTL14 in BC, leading to a deficient understanding in this area. Consequently, a thorough exploration was conducted into the association between METTL14 and immune regulation in BC. By utilizing the TIMER online tool, we found that lower levels of METTL14 were significantly linked to the infiltration of immune cells, showing positive associations with CD8⁺ T cells, CD4⁺ T cells, macrophages, and mast cells, while demonstrating negative relationships with Tregs, MDSCs, NK cells, and follicular helper T cells. Additionally, the somatic copy number alteration of METTL14 displayed a significant correlation with CD8⁺ T cells, macrophages, and dendritic cells. Through mIF analysis, we examined four categories of immune cells, including CD8⁺ T cells, CD4⁺ T cells, macrophages, and mast cells. Our findings indicated a notable decrease in the proportion of CD4⁺ T cells within the tumor samples. While a pattern was noted, no meaningful statistical difference was found between the groups with high and low METTL14 expression, possibly because of the small sample size. CD4⁺ T cells serve a complex function and are frequently regarded as a double-edged sword within the field of immunology, as they are essential for both starting and sustaining the immune response against cancer (30-32). Schroeder et al. showed that CD4⁺ cells were associated with better outcomes in dedifferentiated liposarcoma (33). A different research investigation indicates that non-alcoholic fatty liver disease (NAFLD) results in a targeted reduction of CD4⁺ T lymphocytes and facilitates the development of hepatocarcinoma (34). However, further prospective studies are necessary to more precisely validate our hypothesis, particularly regarding the connection between METTL14 and CD4⁺ T cells.

Immunotherapy has made great progress in clinical practice in recent years and has become increasingly effective after surgery, radiation, chemotherapy, and destination treatment. The variability in HLA expression results in varied reactions to immunotherapy. The progression of cancer and its ability to evade the immune system can be linked to the downregulation, loss of heterozygosity (LOH), and total absence of HLAs (35,36). Immune checkpoints represent a category of immunosuppressive molecules capable of modulating T cell function via various pathways, including signals for co-suppression or co-stimulation, which enhance the immune response against tumors (37). An increased level of the ICI gene is associated with the creation of a microenvironment that is capable of inhibiting the immune response and facilitating the evasion of tumors by the immune system. This research found that METTL14 exhibited a predominantly negative correlation with HLA, suggesting that groups with reduced METTL14 expression could potentially gain advantages from immunotherapy. Additionally, it was observed that the expression levels of PDCD1 were significantly elevated in the group with reduced METTL14 expression. Recent research suggests that using a combination of anti-PD-1 monoclonal antibodies along with anti-LAG3 monoclonal antibodies shows promising outcomes for treating individuals with advanced melanoma (38). The scatter plot demonstrated an inverse relationship between the METTL14 levels and TIDE score within the TCGA cohort, suggesting that individuals with lower levels of METTL14 could have an increased likelihood of benefiting from immunotherapy. Recently, six immune types have been discovered for the first time through extensive immunogenomic analysis of 33 different types of cancer: C1 (wound healing), C2 (IFN-γ-dominated), C3 (inflammation), C4 (lymphocyte depleted), C5 (immunologically quiet), and C6 (TGF-β dominant) (39). The novel immune subtype has the capability to distinguish between various heterogeneous tumors, which could prove advantageous for the targeted immune therapy in cancer patients. During our research, we noted that the levels of METTL14 expression varied significantly among various immune subtypes associated with BC. This evidence suggests that METTL14 could be essential in the realm of cancer immunotherapy, emphasizing its possible importance in creating targeted therapies for BC.

Conclusions

This research clarifies the link between reduced METTL14 expression levels and the aggressive traits linked to BC, as well as its connection to a poorer patient prognosis. Moreover, METTL14 could function as a biomarker for anticipating the impacts of immunotherapy, as its expression levels seem to align with immunotherapy-related signature status. Consequently, these factors could potentially serve as valuable biomarkers in forecasting ICI response for BC. Nonetheless, a key limitation of this research is the necessity for additional experimental validation.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the MDAR reporting checklist. Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1331/rc

Data Sharing Statement: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1331/dss

Peer Review File: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1331/prf

Funding: This work was supported by the National Natural Science Foundation of China (No. 82001423) and the Hubei Provincial Health Commission (No. WJ2021M185).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1331/coif). All authors report that this work was supported by the National Natural Science Foundation of China (No. 82001423) and the Hubei Provincial Health Commission (No. WJ2021M185). The authors have no other conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Ethics Committees of Maternal and Children Health Hospital of Hubei Province {No. [2020] IEC(LW041)} and informed consent was obtained from all patients.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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