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Lysine lactylation (Kla) might be a novel therapeutic target for breast cancer

BMC Medical Genomics volume 16, Article number: 283 (2023) Cite this article

Abstract

Background

Histone lysine lactylation (Kla) is a newly identified histone modification, which plays a crucial role in cancer progression. Hence, we determined the prognostic value of Kla in breast cancer (BC).

Methods

We obtained RNA expression profiles of BC from The Cancer Genome Atlas (TCGA), following screening out Kla-specific genes. Furthermore, we determined the prognostic value of Kla by constructing a cox model based on Kla-specific genes. Subsequently, we identified expression of lactate accumulation-related genes and prognostic Kla-specific genes through Human Protein Atlas (HPA), and further performed a correlation analysis based on their expression. Meanwhile, we explored the effects of Kla on BC tumor microenvironment (TME), drug therapy and immunotherapy. Moreover, we predicted the pathways influenced by Kla via gene set enrichment analysis (GSEA).

Results

A total of 1073 BC samples and 112 normal controls were obtained from TCGA, and 23 tumor samples were removed owing to inadequate clinical information. We identified 257 differentially expressed Kla-specific genes (DEKlaGs) in BC. A cox model involved with CCR7, IGFBP6, NDUFAF6, OVOL1 and SDC1 was established, and risk score could be visualized as an independent biomarker for BC. Meanwhile, Kla was remarkably associated with BC immune microenvironment, drug therapy and immunotherapy. Kla was identified to be related to activation of various BC-related KEGG pathways.

Conclusion

In conclusion, Kla contributes to drug resistance and undesirable immune responses, and plays a crucial role in BC prognosis, suggesting that Kla was expected to be a new therapeutic target for BC.

Peer Review reports

Introduction

Breast cancer (BC) is a heterogeneous disease with high level of mortality, and it is the fifth leading reason of cancer-associated death [1]. BC has surpassed lung cancer as the most prevalent malignancy in 2020 [2], and it is characterized by local recurrence, distant metastasis and chemotherapy resistance, which are the major causes that lead to the high mortality of BC patients [3]. Although advances in BC prevention, diagnosis and personalized therapy in accordance with molecular classification [4, 5], therapeutic targets for BC are still lacking, which contributes to unfavorable prognosis. Therefore, it is crucial to determine more effective therapeutic targets for improving the overall survival of BC patients.

Histone posttranslational modifications have been identified to play a vital role in cancer progression, antitumor immunity and therapy [6,7,8]. Feng et al. indicated that histone posttranslational modifications can contribute to maintaining genome stability, transcription, DNA repair, and chromatin modulation in BC [9]. Recently, Zhao et al. identified a new histone posttranslational modification type, called histone lysine lactylation (Kla) [10], which could stimulate or inhibit gene transcription from chromatin directly. Lactate is predominantly derived from aerobic glycolysis, a characteristic of cancer cells [11], and always accumulates in the tumor microenvironment (TME). Studies showed that lactate could promote cancer local invasion, metastasis [12], and inhibit immune response [13]. Lactate in TME promoted the development of myeloid-derived suppressor cells (MDSCs) [13] and modulated dendritic cell activation, which might remarkably contribute to tumor escape [14]. Moreover, lactate derived from tumor could inhibit tumor surveillance by T and NK cells, which led to tumor immune escape [15]. Recently, the roles of Kla on malignancies have attracted more attention since identified by Zhao et al [16]. Majority of researches showed that aberrant Kla level was associated with tumorigenesis and malignant progression [17, 18]. In addition, inhibition of histone Kla could impair the tumorigenicity of cancer stem cells [19]. BC is characterized by activation of aerobic glycolysis [20, 21], leading to accumulation of lactate in the TME. However, there is no study to evaluate the carcinogenic role of Kla in BC.

In our study, we downloaded gene expression profiles from The Cancer Genome Atlas (TCGA), following screening out differentially expressed Kla-specific genes (DEKlaGs). Subsequently, DEKlaGs were enrolled in univariate and multivariate cox regression analyses to build a risk model. Furthermore, we evaluated the prognostic value of Kla-specific genes, and then determined the contribution of Kla to BC TME, drug therapy and immunotherapy. Finally, gene set enrichment analysis (GSEA) revealed the potential mechanisms of Kla in BC.

Materials and methods

Data preparation

In 2019, Zhao et al. identified the newly posttranslational modification histone Kla, and then determined the Kla-specific genes via ChIP-seq. Hence, we downloaded all of the Kla-specific genes from Zhao’s study [10]. BC RNA expression profiles and their corresponding clinical data were downloaded from TCGA (https://portal.gdc.cancer.gov/), including 1073 BC samples and 112 normal controls. All of the IHC image data were obtained from Human Proteins Atlas (HPA) database (Table S1) (https://www.proteinatlas.org/).

To identify prognostic value on Kla

The expression levels of Kla-specific genes were extracted, following differentially expressed analysis in R software limma package, with the cut-off criteria |log2(Fold-Change)| >=1 and p-value < 0.05. To identify the prognostic value of Kla, univariate cox analysis was used to screen prognostic genes, following constructing cox model via multivariate cox analysis according to prognostic Kla-specific genes. According to cox model, BC patients were divided into high- and low-risk groups on basis of risk score median. And we further validated the accuracy of cox formula via survival analysis and independent prognostic analysis. In addition, the prognostic value of genes enrolled in cox model was also determined.

Correlation analysis between lactate accumulation related genes and Kla specific genes

According to previous study, E1A binding protein p300 (P300) was regarded as a writer of Kla. In addition, Zhao et al. indicated that lactate dehydrogenase A (LDHA), lactate dehydrogenase B (LDHB) and hypoxia inducible factor 1 subunit alpha (HIF1A) also played a crucial role in Kla process. Therefore, we evaluated the expression of these four genes, and the correlation analyses between these four genes and prognostic Kla-specific genes were determined in BC.

Tumor microenvironment (TME) analysis

Firstly, immune cells’ levels of BC patients were calculated via “CIBERSORT” in R software. The correlations between prognostic Kla-specific genes and immune cells were performed. In addition, immune scores of BC patients in TCGA were gained through single sample gene set enrichment analysis (ssGSEA) in packages “GVSA” and “GSEAbase” of R software. Then, we further explored the relationship of immune cell scores, immune function and Kla-specific genes. Subsequently, we downloaded the stemness score data according to DNA methylation (DNAss) and RNA (RNAss) from UCSC Xena database (http://xena.ucsc.edu/). Stemness score correlation analysis was further determined.

Tumor mutation burden (TMB) correlation analysis

Tumor mutation burden (TMB), the number of mutations which exist in a tumor and are related to the emergence of neoantigens that trigger antitumor immunity, is identified as a new indicator for prediction of response to immunotherapy [22]. Hence, we downloaded the TMB data from UCSC Xena (https://xena.ucsc.edu/), and then explored the relevance between TMB and Kla-specific genes in BC.

Immunotherapy and immune checkpoint analysis

To further explore the relationship between Kla and immunotherapy, we obtained the immunotherapy data from the TCIA database (https://tcia.at/home). Subsequently, we analyzed the correlation between prognostic Kla-specific genes and immunotherapy in BC. In addition, we acquired the immune checkpoint data from previous publications [23], and then we explored the relevance of Kla and checkpoints.

Drug susceptibility analysis

Drug susceptibility data were downloaded from the CellMiner database (https://discover.nci.nih.gov/cellminer/home.do). Furthermore, the effects of Kla on BC drug therapy were evaluated via correlation analysis.

Gene set enrichment analysis (GSEA)

To evaluate the potential mechanism of Kla in BC, we explored the potential KEGG pathways influenced by Kla-specific genes via Gene Set Enrichment Analysis (GSEA), and the top 3 pathways of each prognostic Kla-specific gene were listed.

Statistical analysis

The software SPSS (Version 23.3, IBM) was used to perform statistical analyses. Pearson’s Correlation Tests, Student’s T-test and long-rank p test were carried out in this study. Significance difference was considered at p < 0.0001****; p < 0.001***; p < 0.01 **; p < 0.05 *.

Results

Identification of prognostic value

According to differentially expressed analysis, we screened out 257 differentially expressed Kla-specific genes (DEKlaGs) with the cut-off criteria |log2FC| >=1 and p-value < 0.05 (Fig. 1A, Table S2) in BC. To explore the prognostic value of DEKlaGs, we selected prognostic Kla-specific genes via univariate cox analysis (Table 1), and then built a cox model through multivariate cox regression analysis (Fig. 1B). Furthermore, risk score of each patient was calculated based on C-C Chemokine Receptor 7 (CCR7), insulin like growth factor binding protein 6 (IGFBP6), NADH: ubiquinone oxidoreductase complex assembly factor 6 (NDUFAF6), ovo like transcriptional repressor 1 (OVOL1) and syndecan 1 (SDC1) expression level, following dividing into low- and high-risk groups on basis of risk median, respectively. Survival analysis showed that high-risk patients had unsatisfied overall survival compared to low-risk group (Fig. 1C, Figure S1). In addition, prognostic value analysis indicated that risk score in accordance with Kla might be an independent prognostic biomarker for BC (Fig. 1D, E). Risk score combined with gene expression profiles, survival time were visualized in R (Fig. 1F, G, H). Furthermore, the prognostic value of Kla-specific genes enrolled in cox formula was also identified (Fig. 1I-M).

Fig. 1
figure 1

Identification prognostic value of Kla-specific genes. A, Differentially expressed Kla-specific genes (DEKlaGs) in BC, with the cut-off criteria |log2FC|>=1, p-value < 0.05. B, Cox regression model in accordance with DEKlaGs. C, Survival analysis according to risk score calculated by Kla-specific genes expression. D;E, Independent prognostic analysis of risk score. T represents the tumor size in tumor TNM classification, N represents the lymph node metastasis in TNM classification, and M represents distant metastasis in TNM classification. F, Visualization of risk level combined with gene expression. Heatmap represents the prognostic gene expression profiles. Blue stands for low expression, while red stands for high expression. The type means risk level. G, Distribution of each risk score according to Kla-specific genes. Green represents low-risk group, while red represents high-risk group. H, Visualization of survival time and risk score. Patients with high-risk score tend to have shorter survival time. I-M, Survival analysis of prognostic Kla-specific genes. FC, Foldchange

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Table 1 Prognostic Kla-specific genes in BRCA
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Identification of Kla-specific genes expression

According to Kla-specific genes enrolled in cox model, we further evaluated their RNA and protein expression in BC. As the results shown, CCR7 RNA expression level in TCGA was overexpressed in tumor samples. However, the protein expression based on IHC in HPA was opposite (Fig. 2A). And patients with high CCR7 expression had favorable overall survival (Fig. 1G). The potential mechanism should be further explored. The RNA levels of IGFBP6, a tumor suppressor gene in BC, were downregulated in BC samples. Meanwhile, the protein expression of IGFBP6 was nearly not detected in tumor tissues (Fig. 2B). NDUFAF6, OVOL1 and SDC1, as oncogenes, were all upregulated in BC samples (Fig. 2C, D, E).

Fig. 2
figure 2

Identification of Kla-specific genes expression. RNA and protein expression of CCR7 (A), IGFBP6 (B), NDUFAF6 (C), OVOL1 (D) and SDC1 (E) in BC were obtained from TCGA and HPA database, respectively

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Identification of lactate-related genes in BC

Zhao et al. indicated that the 4 genes P300, LDHA, LDHB and HIF1A were related to lactate accumulation and Kla modification [10]. Therefore, we explored the expression of these 4 genes in BC. The results showed that P300, LDHA and LDHB were all overexpressed in tumor samples (Fig. 3A, B, C). Although RNA level had no significance between normal controls and BC patients, HIF1A protein was significantly upregulated in BC (Fig. 3D).

Fig. 3
figure 3

Identification of lactate accumulation related genes in BC. The expression of P300 (A), LDHA (B), LDHB (C) and HIF1A (D) in BC cases

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Correlation analysis between lactate accumulation-related genes and Kla -specific genes

Lactate accumulation-related genes were all identified to overexpression in BC. We further explored the relevance between lactate accumulation-related genes and prognostic Kla-specific genes. As the figure shown, P300 was positively related to NDUFAF6 and OVOL1, and negatively related to tumor suppress gene IGFBP6 (Fig. 4A). HIF1A was associated with CCR7, IGFBP6 and SDC1 (Fig. 4B). LDHA, overexpression in BC, was positively relevant to oncogenes NDUFAF6, OVOL1 and SDC1, while negatively relevant to CCR7 and IGFBP6 (Fig. 4C). LDHB only played a promoted role in CCR7 expression, and played an inhibited role in other 4 genes (Fig. 4D). Taken together, the expression of tumor suppressor gene IGFBP6 in BC was negatively associated with Kla production, suggesting that IGFBP6 might be a crucial Kla target for BC.

Fig. 4
figure 4

Correlation between Kla-specific genes and lactate accumulation related genes. Correlation between P300 (A), LDHA (B), LDHB (C), HIF1A (D) and Kla-specific genes including CCR7, IGFBP6, NDUFAF6, OVOL1 and SDC1.

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Kla was associated with immunity in BC TME

To evaluate the role of Kla on immunity, we determined the relevance between Kla-specific genes and various immune cells. CCR7 expression was significantly related to majority of immune cells level. The most positively and negatively relevant immune cell type were T cell CD8 and Macrophage M2 which was identified to contribute to cancer progression, respectively (Fig. 5A). And IGFBP6 expression was most positively related to Mast cells resting, and negatively related to T cells CD4 memory activated (Fig. 5B). NDUFAF6, OVOL1 and SDC1, as oncogenes in BC, were all positively related to Macrophage M2, while negatively related to NK cells activated (Fig. 5C, D, E). Furthermore, according to the immune cell scores and immune function from ssGSEA, we determined the difference between high and low expression group of there 5 genes (Figure S2). In addition, NDUFAF6, OVOL1 and SDC1 were positively related, while CCR7 and IGFBP6 were negatively related to stemness score in BC (Fig. 5F).

Fig. 5
figure 5

Correlation between Kla-specific genes and immune microenvironment. CCR7 (A), IGFBP6 (B), NDUFAF6 (C), OVOL1 (D) and SDC1 (E) expression were correlated with immune cells level in BC. (F), Heatmap of correlation between Kla and stemness. DNAss: DNA methylation-based, EREG-METHss: Epigenetically regulated DNA methylation-based, DMPss: Differentially methylated probes-based, ENHss: Enhancer Elements/DNAmethylation-based; RNAss: RNA expression-based, EREG.EXPss: Epigenetically regulated RNA expression-based

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Kla was related to BC TMB

TMB was regarded as a new indicator for the response to immunotherapy. Therefore, we explored the relationship between TMB and Kla. As the results shown, CCR7 had no effect on TMB in BC (Fig. 6A), while high IGFBP6 expression always meant low level of TMB (Fig. 6B). Oncogenes NDUFAF6, OVOL1 and SDC1 were all positively related to TMB level in BC (Fig. 6C, D, E), indicating that Kla might play a crucial role in BC immunotherapy.

Fig. 6
figure 6

Correlation between Kla and TMB. High CCR7 (A) and IGFBP6 (B) level meant lower TMB in BC. High NDUFAF6 (C), OVOL1 (D) and SDC1 (E) meant high TMB level

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Kla was related to BC immunotherapy

To further determine the role of Kla on BC immunotherapy, we downloaded the immunotherapy information of BC samples from TCIA. The results showed that BC patients with high CCR7 and IGFBP6 expression had more favorable immunotherapy response than low expression (Fig. 7A, B). Conversely, as oncogenes, NDUFAF6, OVOL1 and SDC1 played an inhibited role in immunotherapy process (Fig. 7C, D, E). Furthermore, we explored the correlation between Kla-specific genes and immune checkpoints. The results showed that CCR7 and IGFBP6 were positively relevant to nearly all checkpoints, while NDUFAF6, OVOL1 and SDC1 were opposite (Fig. 7F).

Fig. 7
figure 7

Immunotherapy analysis on basis of Kla. A-E, CCR7 and IGFBP6 were positively related to immunotherapy response, while NDUFAF6, OVOL1 and SDC1 were opposite. F, the correlation between Kla and immune checkpoint expression

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Drug susceptibility analysis

To determine the effects of Kla on BC drug therapy, we obtained drug susceptibility data, and then analyzed the correlation between drug susceptibility and prognostic Kla-specific genes (Tables 2, 3, 4, 5 and 6). High CCR7 presented high susceptibility in majority of drugs, such as Nelarabine and Chelerythrine (Fig. 8A). Similarly, tumor suppressor gene IGFBP6 was also associated with the response of drug therapy (Fig. 8B). NDUFAF6, as an oncogene, was positively related to drug susceptibility (Fig. 8C). The potential mechanism was unclear. OVOL1 and SDC1 displayed a remarkably inhibited role in BC drug therapy, such as Carboplatin, Cisplatin, Nilotinib, Imexon, etc. (Fig. 8D, E).

Table 2 Drug susceptibility analysis according to CCR7
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Table 3 Drug susceptibility analysis according to IGFBP6
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Table 4 Drug susceptibility analysis according to NDUFAF6
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Table 5 Drug susceptibility analysis according to OVOL1
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Table 6 Drug susceptibility analysis according to SDC1
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Fig. 8
figure 8

Drug susceptibility analysis. The role of CCR7 (A), IGFBP6 (B), NDUFAF6 (C), OVOL1 (D) and SDC1 (E) on BC drug resistance

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Enrichment pathway of prognostic kla-specific genes

To explore the potential KEGG pathways influenced by Kla, we carried out GSEA, and showed that CCR7 was related to immune response pathways, such as B cell receptor signaling pathway. And it also played a negative role in BC cancer cell oxidative phosphorylation process (Fig. 9A). IGFBP6 inhibited the activity of cell cycle and alanine aspartate and glutamate metabolism pathways. But as a tumor suppressor gene, IGFBP6 was associated with activation of MAPK signaling pathway (Fig. 9B). NDUFAF6 played a crucial role in the activation of cell cycle and oxidative phosphorylation (Fig. 9C). OVOL1 and SDC1 were also related to activation of several cancer related pathways, such as NOTCH, WNT signaling pathways and focal adhesion (Fig. 9D, E).

Fig. 9
figure 9

Gene set enrichment analysis. KEGG pathways influenced by CCR7 (A), IGFBP6 (B), NDUFAF6 (C), OVOL1 (D) and SDC1 (E) in BC. The horizontal axis represents the sequenced genes, while the vertical axis represents the corresponding running enrichment score (ES). The peak is the ES of this gene set. The black vertical lines are the target genes in the gene set. The genes before the peak were the core genes in the gene set, indicating the genes that contributed the most to the final ES of the pathway. The red meant bigger logFC, while blue is opposite

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Discussion

Normal cells always produce energy via mitochondrial oxidative phosphorylation, while cancer cells, owing to massive energy demands, are characterized by reprogramming metabolic pathways such as aerobic glycolysis [12]. Activation of aerobic glycolysis plays a crucial role in BC tumorigenesis and progression [24, 25]. Chen et al. indicated that aerobic glycolysis was associated with drug resistance of BC [26]. Generally, aerobic glycolysis leads to accumulation of lactate in the TME, which is related to histone Kla and plays a vital role in cancer progression and tumor immunity [27, 28]. However, whether lactate produced by aerobic glycolysis and histone Kla play a carcinogenic role in BC is unclear. Therefore, we determined the role of Kla in BC.

In present study, we built a cox model to predict BC patient prognosis, and the risk score in accordance with prognostic Kla-specific genes could be regarded as an independent prognostic biomarker. 2 tumor suppressor genes including CCR7, IGFBP6 and 3 oncogenes including NDUFAF6, OVOL1, SDC1 were involved in cox model. CCR7 was one of chemokine receptors identified be upregulated in BC. Signals mediated by CCR7 can activate T and B lymphocytes, and regulate the migration of immune cells to inflamed tissue [29]. In 2001, A Müller et al. demonstrated that CCR7 was upregulated in BC and played a vital role in determining the metastatic destination of tumor cell [30]. In addition, in a BC mouse model, downregulation of CCR7 might impair the tumor cell proliferation and invasive properties, indicating that CCR7 might promote distant metastasis via promoting tumor cell proliferation and invasion at the metastatic site [31]. Philippe A Cassier et al. demonstrated that CCR7 was expressed by spindle shaped stromal cells in BC, but its expression showed no difference on patient overall survival [32]. Taken together, although studies suggest that CCR7 seems to reliably predict the lymph node metastases of BC, it is unclear whether CCR7 can be associated with BC patient survival. In our study, RNA expression of CCR7 was elevated in TCGA BC samples. However, patients with high CCR7 expression had favorable prognosis. High CCR7 expression always meant high immune cell and immune function scores. Patients with high CCR7 level had better responses to drug therapy and immunotherapy. The potential mechanism is unclear. More studies, of course, should be carried out to explore the function of CCR7 in BC. In the future, it will be important to correlate the types of cells that express CCR7 in BC with stage of progression. IGFBP6 was associated with cell migration and positive regulation of stress-activated MAPK cascade [33]. IGFBP6 was regarded as a biomarker of BC [34]. Knockdown of IGFBP6 was more resistant to apoptosis and increased the proliferation of cancer cells. Meanwhile, BC with low IGFBP6 expression had a high probability of metastasis due to a more efficient invasion of tumor cells [35]. In our study, we identified IGFBP6 as a tumor suppressor gene, which played a positive role in BC drug therapy and immunotherapy. BC patients with high IGFBP6 expression always meant lower risk level and high overall survival rate. It was also found that upregulation of IGFBP6 was positively related to high immune cell scores, such as NK cells and TILs. Elevation of IGFBP6 also promoted the immune process, especially Type-II-IFN response, and responses to immunotherapy, suggesting that IGFBP6 might be a candidate immunotherapeutic target for BC. We identified that Kla production was negatively related to IGFBP6 expression, but Lucia Longhitano et al. indicated that lactate could enhance the expression of IGFBP6, and then induce the microglia M2 polarization in glioblastoma [36], and IGFBP6 induced by lactate promoted glioblastoma cells migration and colony formation. Meanwhile, stimulation with lactate in BC cells led to upregulation of IGFBP6, which was controversial with our study. IGFBP6 could also induce expression of various genes related to mitochondrial biogenesis, and then promote cancer cell proliferation [37], which was controversial with previous studies [35, 38]. Moreover, Shkurnikov MY showed that IGFBP6 could correctly predict the emergence of BC relapse with sensitivity of more than 80%, and poor prognosis was related to low expression IGFBP6 [39, 40]. In conclusion, the role of IGFBP6 in BC was controversial, and more studies should be performed to evaluate its biological function and effect on drug therapy and immunotherapy. NDUFAF6 is relevant to assembly of complex I (NADH-ubiquinone oxidoreductase) in the mitochondrial respiratory chain via regulation of subunit ND1 biogenesis [41]. Recently, Lu HJ et al. indicated that NDUFAF6 was identified as a potential prognostic gene in hepatocellular carcinoma (HCC) via bioinformatics analysis, and showed promise to be a new therapeutic target. In BC, Lu et al. suggested that NDUFAF6, as a lactate metabolism gene, was most related to BC prognosis, and played a crucial role in NK cells activation [42], which was similar to our study. We also suggested that NDUFAF6 contributed to cell cycle and oxidative phosphorylation in BC. NDUFAF6 might inhibit the function of various immune cells and immune responses. Meanwhile, overexpression of NDUFAF6 was associated with high TMB level and undesirable immunotherapy response. NDUFAF6 was also negatively related to various immune checkpoint expression in BC, indicating that it showed promise to be an immunotherapy target for BC. OVOL1 was identified to overexpression in BC, and related to activation of several BC-related pathways, such as NOTCH and WNT signaling pathways [43, 44]. However, Drug susceptibility analysis showed that it correlated with drug response, such as Elesclomol and SR16157. Fan CN et al. identified that OVOL1 could impair TGF-β/SMAD signaling and maintain the epithelial identity of BC cells [45]. Therefore, OVOL1 might act as a tumor suppressor gene in BC, and it is necessary to carry out more studies to further explore its effect on BC immunotherapy. SDC1, an integral membrane protein, participates in cell proliferation, cell migration and cell-matrix interactions through its receptor for extracellular matrix proteins [46]. Yang et al. suggested that targeting SDC1 might be a new opportunity for cancer therapy [46]. In pancreatic ductal adenocarcinoma (PDAC), serum SDC1 level was remarkably elevated, and receiver operating characteristic (ROC) analysis area under the curve was 0.847 [47], suggesting that serum SDC1 served as a promising novel biomarker for PDAC early diagnosis. It was found that SDC1 was associated with malignant tumor metastasis and drug resistance [48]. In our study, we identified that SDC1 contributed to focal adhesion of BC, and negatively correlated with immune responses, especially Type-II-IFN response. Meanwhile, high SDC1 level meant high Macrophage M2 and low NK cell activation, which all played a crucial role in BC metastasis and immunotherapy [49,50,51]. Our further TMB correlation analysis, drug susceptibility and immunotherapy analysis validated the results, which were similar to previous studies [52]. In addition, Juliana Maria Motta et al. indicated that SDC1 showed promise to be a candidate target for therapeutic strategies against BC [53]. However, fewer studies focused on SDC1 to explore its mechanism and effect on BC immunotherapy. In conclusion, these Kla-specific genes were associated with the initiation and progression of BC, and also played a crucial role in BC TME, drug therapy and immune process, indicating that histone Kla might be a potential therapeutic target for BC.

Conclusion

In present study, we investigated the prognostic value of Kla in BC by cox regression analysis, and showed that Kla might be a potential independent prognostic biomarker for BC. It was also found that Kla production was associated unfavorable prognosis of BC patients, and played a crucial role in BC TME, drug resistance and immunotherapy responses. Finally, we suggested Kla production might induce the activation of various BC-accociated KEGG pathways. These findings showed that Kla was expected to be a new therapeutic target for BC.

Data Availability

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

Abbreviations

Kla:

Lysine lactylation

BC:

Breast cancer

TCGA:

The Cancer Genome Atlas

HPA:

Human Protein Atlas

TME:

Tumor microenvironment

GSEA:

Gene set enrichment analysis

DEKlaGs:

Differentially expressed Kla-specific genes

MDSCs:

Myeloid-derived suppressor cells

LDHA:

Lactate dehydrogenase A

LDHB:

Lactate dehydrogenase B

HIF1A:

Hypoxia inducible factor 1 subunit alpha

SsGSEA:

Single sample gene set enrichment analysis

TMB:

Tumor mutation burden

DEGs:

Differentially expressed genes

CCR7:

C- Chemokine Receptor 7

IGFBP6:

Insulin like growth factor binding protein 6

NDUFAF6:

Ubiquinone oxidoreductase complex assembly factor 6

OVOL1:

Ovo like transcriptional repressor 1

SDC1:

Syndecan 1

HCC:

Hepatocellular carcinoma

PDAC:

Pancreatic ductal adenocarcinoma

ROC:

Receiver operating characteristic

KEGG:

Kyoto Encyclopedia of Genes and Genomes

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Authors and Affiliations

  1. Department of Thyroid Breast Surgery, The Second Affiliated Hospital, Hengyang Medical School, University of South China, No. 35 Jiefang Avenue. Hengyang, Hengyang, 421001, China

    Jian Deng

  2. Department of Anesthesiology, West China Hospital, Sichuan University, Chengdu, China

    Xinyi Liao

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Deng, J., Liao, X. Lysine lactylation (Kla) might be a novel therapeutic target for breast cancer. BMC Med Genomics 16, 283 (2023). https://doi.org/10.1186/s12920-023-01726-1

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BMC Medical Genomics

ISSN: 1755-8794

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