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Discov Oncol
Discov Oncol
Discover Oncology
2730-6011
Springer US New York

39217596
1269
10.1007/s12672-024-01269-6
Analysis
Causality between autoimmune diseases and breast cancer: a two-sample Mendelian randomization study in a European population
Zhang Hengheng 12
Shen Guoshuang 2
Yang Ping 12
Wu Meijie 12
Li Jinming 12
Li Zitao 2
Zhao Fuxing 2
Liang Hongxia 2
Da Mengting 2
Wang Ronghua 2
Zhang Chengrong 12
Zhao Jiuda jiudazhao@126.com

2
Zhao Yi zywm0001@163.com

2
1 https://ror.org/05h33bt13 grid.262246.6 0000 0004 1765 430X Qinghai University, Xining, China
2 https://ror.org/04cgmg165 grid.459326.f The Center of Breast Disease Diagnosis and Treatment of Affiliated Hospital of Qinghai University & Affiliated Cancer Hospital of Qinghai University, Xining, 810000 China
1 9 2024
1 9 2024
12 2024
15 39610 1 2024
23 8 2024
© The Author(s) 2024
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
Background

The incidence of autoimmune diseases and breast cancer is significantly higher in women compared to men. Previous observational studies have not conclusively determined the relationship between these two conditions. This study utilizes the Mendelian randomization approach to investigate the genetic association between autoimmune diseases and breast cancer.

Method

Two-sample Mendelian randomization was conducted on a European population using the GWAS database. The inverse variance-weighted method served as the primary analytical approach. The MR-PRESSO test was applied to detect horizontal pleiotropy. To ensure result robustness, the FDR correction method was used.

Result

The study revealed that Sjögren’s syndrome lowers the overall risk of breast cancer (OR 0.96, 95% CI [0.93–0.99], p = 0.011). Idiopathic inflammatory myopathy shows a protective effect against overall breast cancer (OR 0.98, 95% CI [0.97–0.99], p = 0.035). An association was identified between rheumatoid arthritis and overall breast cancer (OR 0.98, 95% CI [0.96–1.00], p = 0.050). No causal link was found between systemic lupus erythematosus, systemic sclerosis, and overall breast cancer. The study also suggests that Sjögren’s syndrome, rheumatoid arthritis, and idiopathic inflammatory myopathy might reduce the risk of developing HER + breast cancer. Specifically, Sjögren’s syndrome (OR = 0.90, 95% CI [0.83–0.98], p = 0.02), rheumatoid arthritis (OR = 0.94, 95% CI [0.91–0.98], p = 0.006), and idiopathic inflammatory myopathy (OR = 0.96, 95% CI [0.93–0.99], p = 0.036). Additionally, systemic lupus erythematosus was found to lower the risk of HER- breast cancer (OR = 0.95, 95% CI [0.91–0.99], p = 0.046). The study did not establish a causal relationship between these five autoimmune diseases and ER + or ER- breast cancer.

Conclusion

This study found that autoimmune diseases may act as protective factors against breast cancer risk.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12672-024-01269-6.

Keywords

Autoimmune diseases
Breast cancer
Mendelian randomization
Causality
European population
Central Government Guiding Local Scientific and Technological Development Funds for Qinghai Province in China2022ZY009 issue-copyright-statement© Springer Science+Business Media, LLC 2024
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pmcIntroduction

Breast cancer ranks as one of the most common malignant tumors in women, exhibiting the highest incidence and mortality rates among female cancers [1]. Current data show about 2.26 million new cases of breast cancer diagnosed globally each year [1, 2]. Breast cancer can be categorized into four subtypes based on hormone receptor (estrogen receptor, progesterone receptor) and human epidermal growth factor receptor 2 (HER2) status: HR + /HER2-, HR-/HER2-, HR + /HER2 + , and HR-/HER2 + . These subtypes are clinically important as receptor expression directly impacts treatment strategies [3]. Additionally, breast cancer is a highly heterogeneous disease. The molecular characteristics of breast cancer subtypes do not appear to be fixed but rather represent a dynamic entity that can change during tumor progression and metastasis. This presents a challenge for clinicians. Further research into the etiology of breast cancer and its subtypes will provide effective management strategies for disease prevention and treatment [4–6]. This presents a challenge for clinicians. Further research into the etiology of breast cancer and its subtypes will provide effective management strategies for disease prevention and treatment [7]. Studies have identified a clear link between diet, alcohol intake, and the development of breast cancer. Furthermore, there is a proposed connection between chronic inflammation and the progression of breast cancer [8–10].

Autoimmune diseases (ADs) are the most common chronic inflammatory conditions [11]. ADs occur when the immune system mistakenly attacks healthy cells, tissues, or organs, causing inflammatory damage [12]. As research delves into the molecular aspects of diseases, increasing attention is being paid to the relationship between autoimmune diseases and malignant tumors [13]. Nonetheless, the association between autoimmune diseases and breast cancer remains controversial. Some studies suggest that autoimmune diseases may increase the risk of breast cancer, while others indicate a possible reduction in this risk. For example, research by S. Bernatsky indicates a decreased risk of breast cancer among patients with SLE [14]. Similarly, Warren David Raymond’s findings align with this perspective, showing reduced odds of colorectal, breast, and skin cancers but higher rates of hematologic malignancies in SLE patients [15]. Meanwhile, Wenjie Li et al.’s research reports no causal relationship between SLE and overall breast cancer, ER + breast cancer, or ER- breast cancer in European cohorts, with a lower risk of breast cancer in East Asian SLE patients [16].

To better understand the relationship between autoimmune diseases and breast cancer, this study employed Mendelian randomization (MR) to investigate potential genetic correlations. MR is a causal inference method that uses genetic variations to study causal relationships, helping to reduce the influence of confounding factors [17]. Additionally, MR can lessen the chance of reverse causation since genetic variations are generally not affected by disease onset or progression [18]. This study considered five common autoimmune diseases as potential exposures and evaluated breast cancer and its various subtypes as outcome variables.

Methods

Study design

This study conducted two-sample Mendelian randomization (MR) analyses using summarized genetic data and IEU OpenGWAS database to evaluate the potential causal relationship between autoimmune diseases (ADs) and breast cancer risk. The instrumental variables (IVs) in this analysis adhered to three criteria: First, IVs had a strong association with ADs. Second, IVs were independent of potential confounders between ADs and cancer. Third, IVs influenced cancer risk solely through ADs without interference from other factors. Figure 1 illustrates this process.Fig. 1 Flow diagram for study

GWAS data source for autoimmune diseases (ADs)

The study examined five common autoimmune diseases: Sjögren’s syndrome, rheumatoid arthritis, systemic lupus erythematosus, systemic sclerosis, and idiopathic inflammatory myopathy. Genetic data for these diseases were obtained from the IEU OpenGWAS database (https://gwas.mrcieu.ac.uk/). Instrumental variables were selected based on a genome-wide significance threshold of p < 5 × 10–8, with an LD threshold of (LD r2 < 0.001, kb = 10,000) to ensure effective linkage disequilibrium [19]. For idiopathic inflammatory myopathy and systemic sclerosis, a significance level of p < 1 × 10–6 was used, with an LD r2 < 0.01 criterion. These standards are consistent with previous studies [20]. To reduce bias from weak instrumental variables, the study calculated R2 to determine the proportion of phenotypic variance each instrumental variable explained. The R2 formula: R2 = [2 × EAF × (1-EAF) × (β)^2]/[(2 × EAF × (1-EAF) × (β)^2) + (2 × EAF × (1-EAF) × N × se (β)^2)], where EAF is the effect allele frequency, β the effect size, N the sample size, and se(β) the standard error of the genetic effect [18]. F-statistics were then computed to assess the strength of each instrumental variable, using the formula: F = [r2 × (N-k-1)]/[(1- R2) × k], where k is the number of instrumental variables [21]. SNPs with an F-value < 10 were deemed weak and excluded from further analysis. For comprehensive details on the genetic instruments selected for each autoimmune disease, see Table 1. Table 1 Information on the dataset for breast cancer

GWAS ID	Trait	Year	Consortium	N. cases	N. controls	Sample size	Number of SNPs	
ebi-a-GCST90018799	Breast cancer	2021	NA	17,389	240,341	257,730	24,133,589	
finn-b-C3_BREAST_HERPLUS	HER + breast cancer	2021	NA	4,263	119,039	NA	16,379,780	
finn-b-C3_BREAST_HERNEG	HER- breast cancer	2021	NA	3,092	115,947	NA	16,379,675	
ieu-a-1127	ER + breast cancer	2017	BCAC	69,501	105,974	175,475	10,680,257	
ieu-a-1136	ER- breast cancer	2017	BCAC	7,333	42,892	50,225	10,680,257	
BCAC Breast Cancer Association Consortium, NA not available

GWAS data source for breast cancer

For breast cancer data, this study used statistical information on European populations from the IEU OpenGWAS database (https://gwas.mrcieu.ac.uk/) and previous studies. Data were mainly derived from the Breast Cancer Association Consortium (BCAC) GWAS, which included 228,951 European women, 122,977 of whom had breast cancer and 105,974 were controls [22]. Furthermore, GWAS data from Saori Sakaue's study, involving 17,389 breast cancer patients and 240,341 controls, were also incorporated [23]. Detailed information about the GWAS data for breast cancer is presented in Table 2. Table 2 Information on the datasets for exposures

GWAS ID	Trait	Year	Consortium	N. cases	N. controls	Sample size	Number of SNPs	
ebi-a-GCST90018920	Sjogren's syndrome	2021	NA	1,296	482,717	484,013	24,197,329	
ebi-a-GCST90013534	Rheumatoid arthritis	2020	NA	14,361	43,923	58,284	13,108,512	
ebi-a-GCST90011866	Systemic lupus erythematosus	2021	NA	4,222	8,431	12,653	5,691,661	
finn-b-M13_POLYMYO	Idiopathic Inflammatory Myopathy	2021	NA	119	213,145	NA	16,380,450	
ebi-a-GCST003566	Systemic Sclerosis	2016	NA	4888	10,395	15,283	7,910,365	
NA not available

Statistical analysis

The statistical analysis in this research focused on determining the causal relationship between ADs and breast cancer, and we performed MR analyses using inverse variance weighting (IVW), weighted median, simple modal, weighted modal, and MR Egger methods. IVW is the primary MR analysis method, which includes the MR effects of individual snp to derive an overall weighted effect [24]. We used the other four methods as complementary methods to test for possible violations of the MR second and third hypotheses. When the Egger-intercept of linear regression approaches 0, there is no directional pleiotropy in IVs and the exclusion hypothesis can be considered valid [25]. The hypothesis can be considered valid. The analysis by the above method can make our results more robust.

We used the MR-PRESSO method to detect and remove outliers and then generated inverse variance-weighted estimates [26]. After removing the outliers, we calculated the inverse variance-weighted estimates again and used the P-value of the MR-PRESSO distortion test to assess whether the difference between the estimates before and after removal was significant. We then performed a sensitivity analysis on the remaining SNPs [27].

We searched the LDlink database (https://ldlink.nih.gov/?tab=home) for potentially causal SNPs to verify whether the instrumental variables (IVs) met the independence assumption [28]. The results of the search showed that seven SNPs were confounders, so we removed them when performing the MR analysis (Supplementary Table 1). In addition, we used Cochrane’s Q-test and MR multivariate residual sums to assess heterogeneity, thus increasing the reliability of our findings. egger_intercept of P_value and MR-egger intercept derived P_value greater than 0.05 did not heterogeneity existed [29]. Leave-One-Out (LOO) analysis validated the MR estimates’ robustness and identified any SNP-driven associations.

Statistical analyses were conducted using R software version 4.3.1, with TwoSampleMR and MR-PRESSO packages. To ensure conclusion reliability, the study applied False Discovery Rate (FDR) correction, using q-values to manage the FDR. The FDR-corrected threshold was set at 0.05, allowing for up to 5% of positive findings to be false positives.

Results

Association between autoimmune diseases and overall breast cancer risk

The study conducted a two-sample MR analysis using European population-based breast cancer GWAS data from Saori Sakaue's study to explore the link between autoimmune diseases and overall breast cancer risk. According to Fig. 2, results from the Inverse Variance Weighted (IVW) method indicated a significant reduction in overall breast cancer risk for patients with Sjögren’s syndrome(OR 0.96, 95% CI [0.93–0.99], p = 0.011) and idiopathic inflammatory myopathy (OR 0.98, 95% CI [0.97–0.99], p = 0.035).Additionally, rheumatoid arthritis was found to have a correlated risk of breast cancer (OR 0.98, 95% CI [0.96–1.00], p = 0.050). The findings remained consistent after applying the FDR correction. The MR-Egger and Weighted Median method estimates aligned with the IVW results.Fig. 2 Forest plot of OR values between five autoimmune diseases and overall breast cancer

We analyzed exposure factors with breast cancer one by one. Two SNPs, rs3129962, rs3132487, were found to have palindromic sequences when analyzing desiccation syndrome with breast cancer, and we deleted them. No SNPs with horizontal pleiotropy were found when MR-PRESSO test was performed. rs3129767, rs9272305, two SNPs with palindromic sequences were found when analyzing idiopathic myositis myopathy with breast cancer, and we deleted them but did not find the presence of SNPs with horizontal pleiotropy. Analyzing the relationship between rheumatoid arthritis and overall breast cancer, we identified three SNPs, rs1858037, rs34536443, and rs7278257, contained palindromic sequences and therefore decided to remove them. In addition, when performing the MR-PRESSO test, we identified two SNPs, rs1950897 and rs3025669, as having horizontal pleiotropy, and therefore excluded them as well. Finally, the data after removing the SNPs were analyzed to obtain the above results.

Figures 3, 4 and 5 include a scatter plot illustrating the relationship between autoimmune diseases and overall breast cancer, as well as a leave-one-out method analysis plot. The information on heterogeneity and MR-PRESSO test for autoimmune diseases and overall breast cancer in Table 3. We provide SNP data for the analysis of exposure factors with breast cancer in Supplementary Tables 2–6.Fig. 3 Scatter plot of association between five autoimmune diseases and overall breast cancer

Fig. 4 A forest plot illustrating ‘leave-one-out’ sensitivity analysis, showcasing individual SNP influences on results

Fig. 5 Scatter plot and Leave-one-out analysis of the causal relationship between systemic lupus erythematosus and overall breast cancer

Table 3 The information on heterogeneity and MR-PRESSO test for autoimmune diseases and overall breast cancer

Exposure	Outcome	Cochran’s Q derived p value	MRPRESSO global test derived p value	Egger_intercept	MR-egger intercept derived p value	
MR Egger	Inverse variance weighted	
Sjogren’s syndrome	Overall breast cancer	0.568089161	0.620239177	0.673	0.568089161	0.620239177	
Rheumatoid arthritis	Overall breast cancer	0.0001845	0.00023908	 < 0.001	– 0.000412295	0.8758976	
Systemic lupus erythematosus	Overall breast cancer	0.136516792	0.145738383	0.124	0.005411465	0.4489015	
Polymyositis	Overall breast cancer	0.885359	0.568738925	0.576	0.03014041	0.2276465	
Multiple sclerosis	Overall breast cancer	7.33307E-07	6.56256E-07	0.796	0.00127764	0.7860478	
NA not available

Autoimmune diseases and HER- and HER + breast cancer risk

Research indicates a strong link between human epidermal growth factor receptor (HER) expression status in breast cancer and patient prognosis. Utilizing data from the Breast Cancer Association Consortium (BCAC) GWAS, this study explored the potential causal relationship between autoimmune diseases and HER- and HER + breast cancer. According to Fig. 6, analysis via the Inverse Variance Weighted (IVW) method suggests that Sjögren's syndrome, rheumatoid arthritis, and idiopathic inflammatory myopathy might reduce the risk of developing HER + breast cancer. Specifically, Sjögren’s syndrome showed an odds ratio (OR) of 0.90(95% CI [0.83–0.98], p = 0.02), indicating a significant reduction in risk. Rheumatoid arthritis had an OR of 0.94 (95% CI [0.91–0.98], p = 0.006), suggesting a lower likelihood of HER + breast cancer in individuals with this condition. Idiopathic inflammatory myopathy was associated with a reduced risk (OR 0.96, 95% CI [0.93–0.99], p = 0.036). Additionally, systemic lupus erythematosus was linked to a slightly decreased risk of HER- breast cancer (OR 0.95, 95% CI [0.91–0.99], p = 0.046). After applying False Discovery Rate (FDR) corrections, the results indicated significant causal relationships between rheumatoid arthritis, idiopathic inflammatory myopathy, and HER + breast cancer, but not between Sjögren’s syndrome and HER + breast cancer. Also, a significant causal link was found between systemic lupus erythematosus and a reduced risk of HER- breast cancer.Fig. 6 Forest plot of OR values between five autoimmune diseases and breast cancer subtype

When analyzing exposure factors with HER + breast cancer, a palindrome sequence was found in the SNP (rs34536443) analyzed for rheumatoid arthritis with HER + breast cancer, which was removed. Also when we analyzed dry syndrome and idiopathic inflammatory myopathy with HER + breast cancer, no palindromic sequences were found. There was no horizontal pleiotropy when MR-presso test was performed (P_value > 0.05).

The association between systemic lupus erythematosus (SLE) and HER-breast cancer was investigated. We found that rs11185603 was associated with Fasting glucose, and rs5749502 with Red blood cell traits, while rs4844538 was associated with type 2 diabetes. These SNPs may have confounding effects and were therefore excluded from the analysis. In addition, we found the presence of palindromic sequences for rs11059928 and rs11185603, which were also excluded for analytical accuracy considerations. Horizontal pleiotropy was not present at MR-presso test (P_value = 0.763).

Leave-One-Out analysis revealed that no instrumental variables significantly influenced the causal relationship between autoimmune diseases and HER + and HER- breast cancer. Supplementary Tables 7–10, we also provide SNP data that provide an analysis of exposure factors with HER + /HER- breast cancer.

Autoimmune diseases and ER- and ER + breast cancer risk

Other studies have highlighted differences in prognosis among breast cancer patients based on estrogen receptor (ER) expression status. This study reanalyzed data from the Breast Cancer Association Consortium (BCAC) GWAS dataset for ER + and ER- breast cancer. However, the analysis using the Inverse Variance Weighted (IVW) method found no causal relationship between the five autoimmune diseases and ER + or ER- breast cancer in Fig. 6.

Supplementary Figs. 1 to 2 (eFig.1–2) include a scatter plot illustrating the relationship between autoimmune diseases and breast cancer subtype, as well as a leave-one-out method analysis plot. The information on heterogeneity and MR-PRESSO test for autoimmune diseases and breast cancer subtype in Supplementary Table 11 to 14 (eTable.11–14).

Discussion

Breast cancer is a major health challenge for women worldwide, and its etiology is complex and diverse [2]. Currently, clinical therapeutic strategies are mainly based on the classification of estrogen receptor (ER) and human epidermal growth factor receptor 2 (HER2) status [6]. The classification of breast cancer subtypes is closely related to the expression of ER and HER2 receptors, and it is important to explore the pathogenic factors of breast cancer subtypes for clinical prevention and treatment. Autoimmune diseases such as dry syndrome, rheumatoid arthritis and systemic lupus erythematosus have a high prevalence in women, while breast cancer is the most common malignant tumor in women [30, 31]. To investigate whether there is a correlation between the two, we conducted the present study.

The findings indicate a reduced risk of breast cancer in patients with Sjögren’s syndrome, idiopathic inflammatory myopathy, and rheumatoid arthritis, showing odds ratios(OR) of 0.96 (95% CI [0.93–0.99], p = 0.011), 0.98 (95% CI [0.97–0.99], p = 0.035), and 0.98 (95% CI [0.96–1.00], p = 0.050), respectively. The observed protective effect of Sjögren's syndrome on breast cancer risk corroborates Jian Deng's research findings [32].

Moreover, the study delved into the association between autoimmune diseases and breast cancer across different HER and ER expression states. It revealed that systemic lupus erythematosus significantly reduces the risk of HER- breast cancer (OR = 0.95, 95% CI [0.91–0.99], p = 0.046). Idiopathic inflammatory myopathy significantly lowered the risk of HER + breast cancer (OR = 0.96, 95% CI [0.93–0.99], p = 0.036). Sjögren's syndrome and rheumatoid arthritis also appeared to act as protective factors against HER + breast cancer, with statistically significant differences observed (Sjögren's syndrome, OR = 0.90, 95% CI [0.83–0.98], p = 0.02; Rheumatoid arthritis, OR = 0.94, 95% CI [0.91–0.98], p = 0.006).

Notably, the analysis on the correlation between systemic sclerosis and HER- breast cancer yielded a p-value close to 0.05 (p = 0.06), suggesting a non-significant statistical difference. However, this trend might still indicate a protective effect in patients with HER- breast cancer. The relationship between systemic sclerosis and breast cancer warrants further exploration in future studies as the database expands and more data become available.

According to the results of this study, autoimmune diseases may reduce the risk of developing breast cancer. We believe that the specific mechanisms are as follows. Firstly, the “immunosurveillance” hypothesis proposes that autoimmune diseases are due to an increase in immune tone, which improves immunosurveillance [33].

Immune surveillance refers to the immune system's process of recognizing and eliminating abnormal cells, such as cancer cells, which includes the phases of elimination, equilibrium, and escape [34]. Research indicates that tumors can be recognized by the immune system and controlled or prevented through immune surveillance processes [35]. The specificity of tumor immune responses lies in the recognition of tumor antigens. The immune system identifies and clears nascent tumors by recognizing tumor-specific neoantigens expressed on tumor cells, similar to allograft rejection, thus maintaining tissue homeostasis in complex multicellular organisms [34, 36]. In clinical settings, the restoration of immune surveillance is considered a measure of the effectiveness of chemotherapy, targeted therapy, and radiotherapy in breast cancer patients [37].

Supporting this, studies have shown that individuals with broad autoantibody specificity can decrease their risk of breast cancer by 60% [38]. Additionally, research has reported a decreased risk of breast cancer in patients with systemic lupus erythematosus (SLE), which may be associated with anti-DNA antibodies. These antibodies exert direct anti-cancer effects on cells with DNA repair deficiencies [38]. This aligns with findings that systemic lupus erythematosus significantly lowers breast cancer risk, which is consistent with the results of this study [39]. Further mechanistic studies have revealed that a cell-penetrating lupus autoantibody (3E10) is synthetically lethal to BRCA2-deficient human cancer cells and can enhance the effectiveness of low doses of doxorubicin, thereby improving chemotherapy outcomes [40]. Additionally, James Gardner Thorpe's study reported that lupus-associated anti-ribosome P autoantibodies could directly induce apoptosis in cancer cells [41]. From the treatment perspective of autoimmune diseases, certain studies have noted that using non-steroidal anti-inflammatory drugs or aspirin can boost tumor immune surveillance and lower cancer risk [42, 43]. On the contrary, glucocorticoid use may disrupt immune surveillance and elevate cancer risk [44].

Previous studies on Sjögren’s syndrome (SS) have consistently reported a decreased incidence of breast cancer, which aligns with our findings. Hemminki et al. compared 1516 Swedish SS patients with the general population, noting a standardized incidence ratio (SIR) for breast cancer of 0.46 (95% confidence interval: 0.26–0.75) [45]. Several factors may explain the lower risk of breast cancer in SS patients. SS primarily affects exocrine glands, especially the lacrimal and salivary glands, which share anatomical, histological, and immunological similarities with the breast. SS patients display different immune patterns in breast-associated mucosal tissues, with higher proportions of CD4 + T cells. This suggests a distinct immune response to local antigens, such as tumor cells, potentially establishing a more robust mucosal immune system dynamic that may reduce breast cancer incidence [45, 46]. Additionally, studies have identified lower estrogen levels in SS patients, which significantly contribute to reducing breast cancer incidence [47]. Estrogen is a known risk factor for breast cancer development, so lower estrogen levels may provide protective effects against the disease.

Our findings suggest that rheumatoid arthritis may reduce the risk of developing HER + breast cancer. It has been shown that rheumatoid arthritis (RA) may reduce breast cancer risk, which is consistent with our findings [48]. The mechanisms may include the following: Firstly, the peak incidence of female RA often occurs during menopause, characterized by decreased hormone secretion, including estrogen. Lower estrogen levels are known to reduce breast cancer risk. Furthermore, studies have demonstrated significant differences in luteinizing hormone (LH) and follicle-stimulating hormone (FSH) levels between RA patients and healthy individuals. These hormones are crucial in regulating reproductive function and sex hormone levels, and their fluctuations may further influence breast cancer risk [49]. In cohorts of patients with idiopathic inflammatory myopathies, reports indicate that individuals with breast and ovarian cancers often carry anti-synthetase antibodies, which possess anticancer properties [50, 51]. These observations suggest a complex interplay between autoimmunity and cancer incidence, necessitating further exploration through in vivo and in vitro studies. Overall, these findings highlight the significant role of the immune system and autoimmune diseases in regulating breast cancer risk.

However, to date, no significant link between ER + and ER- breast cancer and autoimmune diseases has been established in genome-wide association studies (GWAS) using European population samples. Future updates to these databases may provide opportunities for more in-depth exploration of this relationship. This study has several strengths: Primarily, it is the first to utilize Mendelian Randomization (MR) to investigate potential causality between autoimmune diseases and breast cancers with varying HER and ER states. MR methodology significantly minimizes the effects of confounding factors and reverse causation. Compared to traditional observational studies, the analysis of single nucleotide polymorphisms (SNPs) reduces the impact of multiple potential confounders, offering more robust research evidence.

Nonetheless, there are limitations to this study. First, the sample predominantly consisted of the European population. Whether these findings are applicable to other regions and populations remains uncertain, necessitating further validation in diverse populations and regions. Secondly, the potential for pleiotropy is an issue that cannot be entirely ruled out in MR studies and requires additional investigation and discussion. Furthermore, due to variations in data collection times, disease progression stages, and treatment phases in GWAS data, our study has some limitations. These factors may affect the research outcomes to a certain extent, but we can still derive valuable SNP data analysis results from them. Further, our study is based on genome-wide association study (GWAS) data, revealing potential genetic factors in relation to disease. However, these findings are limited to statistical associations and do not provide direct mechanistic causality. Therefore, our findings need to be validated by in vivo experiments in future studies to further reveal the underlying biological mechanisms.

Conclusion

The Mendelian Randomization (MR) analysis in this study indicates that autoimmune diseases may act as protective factors against breast cancer risk. Based on studies in European populations, there is a potential genetic correlation between desiccation syndrome, rheumatoid arthritis, idiopathic inflammatory myopathies and HER + breast cancer. In addition, we observed a potential genetic correlation between systemic lupus erythematosus and HER-breast cancer as well.

Supplementary Information

Additional file 1.

Additional file 2.

Additional file 3.

Additional file 4.

Additional file 5.

Additional file 6.

Acknowledgements

We are grateful to the investigators who shared the GWAS data. At the same time, I would like to thank the Central Government of Qinghai Province to guide the local Science and Technology Development Fund (approval number: 2022ZY009).

Author contributions

H.h.Z and Y.Z orchestrated the conception and design of the study. Data collection and analysis were spearheaded by C.r.Z. R.h.w and J.m.L The initial manuscript was drafted by H.h.Z and M.j.Wu, M.t.D, H.x.L, P.Y and G.h.S significantly contributed to data analysis and interpretation. F.x.Z, Z.t.L, Y.Z and J.d.Z meticulously revised the manuscript. H.h.Z Drawing.Every author actively participated in writing the article and endorsed the final version submitted for publication. Furthermore, all authors have thoroughly reviewed and approved the published manuscript.

Funding

This study was supported by Central Government Guiding Local Scientific and Technological Development Funds for Qinghai Province in China (Grant ID: 2022ZY009).

Availability of data and materials

The data used in this study was obtained from public databases and previous studies. Data sources and handing of these data were described in the Materials and Methods. Further information is available from the corresponding author upon request. All data involved in this study are available in the public database. For further information, please contact the corresponding authors. Data is provided in a manuscript or supplementary information file where our data is available.

Declarations

Ethics approval and consent to participate

Not needed.

Informed consent

The consent of the patients was not required because the informed consent had already been given in the original study.

Competing interests

On behalf of all authors, the corresponding author states that there is no conflict of interest.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Hengheng Zhang, Guoshuang Shen, Ping Yang have contributed equally (Co-first authors).
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References

1. Giaquinto AN Sung H Miller KD Kramer JL Newman LA Minihan A Siegel RL Breast cancer statistics, 2022 CA A Cancer J Clin 2022 72 6 524 541 10.3322/caac.21754
Giaquinto AN, Sung H, Miller KD, Kramer JL, Newman LA, Minihan A, Siegel RL. Breast cancer statistics, 2022. CA A Cancer J Clin. 2022;72(6):524–41. 10.3322/caac.21754.10.3322/caac.21754
2. Arnold M Morgan E Rumgay H Mafra A Singh D Laversanne M Soerjomataram I Current and future burden of breast cancer: global statistics for 2020 and 2040 Breast 2022 66 15 23 10.1016/j.breast.2022.08.010 36084384
Arnold M, Morgan E, Rumgay H, Mafra A, Singh D, Laversanne M, Soerjomataram I. Current and future burden of breast cancer: global statistics for 2020 and 2040. Breast. 2022;66:15–23. 10.1016/j.breast.2022.08.010.36084384 10.1016/j.breast.2022.08.010
3. Howlader N Altekruse SF Li CI Chen VW Clarke CA Ries LAG Cronin KA US incidence of breast cancer subtypes defined by joint hormone receptor and HER2 status JNCI J Natl Cancer Inst 2014 10.1093/jnci/dju055 24777111
Howlader N, Altekruse SF, Li CI, Chen VW, Clarke CA, Ries LAG, Cronin KA. US incidence of breast cancer subtypes defined by joint hormone receptor and HER2 status. JNCI J Natl Cancer Inst. 2014. 10.1093/jnci/dju055.24777111 10.1093/jnci/dju055
4. Priedigkeit N Hartmaier RJ Chen Y Vareslija D Basudan A Watters RJ Lee AV Intrinsic subtype switching and acquired ERBB2/HER2 amplifications and mutations in breast cancer brain metastases JAMA Oncol 2017 3 5 666 671 10.1001/jamaoncol.2016.5630 27926948
Priedigkeit N, Hartmaier RJ, Chen Y, Vareslija D, Basudan A, Watters RJ, Lee AV. Intrinsic subtype switching and acquired ERBB2/HER2 amplifications and mutations in breast cancer brain metastases. JAMA Oncol. 2017;3(5):666–71. 10.1001/jamaoncol.2016.5630.27926948 10.1001/jamaoncol.2016.5630
5. Garcia-Recio S Thennavan A East MP Parker JS Cejalvo JM Garay JP Perou CM FGFR4 regulates tumor subtype differentiation in luminal breast cancer and metastatic disease J Clin Investig 2020 130 9 4871 4887 10.1172/JCI130323 32573490
Garcia-Recio S, Thennavan A, East MP, Parker JS, Cejalvo JM, Garay JP, Perou CM. FGFR4 regulates tumor subtype differentiation in luminal breast cancer and metastatic disease. J Clin Investig. 2020;130(9):4871–87. 10.1172/JCI130323.32573490 10.1172/JCI130323
6. Jordan NV Bardia A Wittner BS Benes C Ligorio M Zheng Y Haber DA HER2 expression identifies dynamic functional states within circulating breast cancer cells Nature 2016 537 7618 102 106 10.1038/nature19328 27556950
Jordan NV, Bardia A, Wittner BS, Benes C, Ligorio M, Zheng Y, Haber DA. HER2 expression identifies dynamic functional states within circulating breast cancer cells. Nature. 2016;537(7618):102–6. 10.1038/nature19328.27556950 10.1038/nature19328
7. Turner KM Yeo SK Holm TM Shaughnessy E Guan J-L Heterogeneity within molecular subtypes of breast cancer Am J Physiol Cell Physiol 2021 321 2 C343 C354 10.1152/ajpcell.00109.2021 34191627
Turner KM, Yeo SK, Holm TM, Shaughnessy E, Guan J-L. Heterogeneity within molecular subtypes of breast cancer. Am J Physiol Cell Physiol. 2021;321(2):C343–54. 10.1152/ajpcell.00109.2021.34191627 10.1152/ajpcell.00109.2021
8. Campbell NJ Barton C Cutress RI Copson ER Impact of obesity, lifestyle factors and health interventions on breast cancer survivors Proc Nutr Soc 2023 82 1 47 57 10.1017/S0029665122002816 36426642
Campbell NJ, Barton C, Cutress RI, Copson ER. Impact of obesity, lifestyle factors and health interventions on breast cancer survivors. Proc Nutr Soc. 2023;82(1):47–57. 10.1017/S0029665122002816.36426642 10.1017/S0029665122002816
9. De Visser KE Eichten A Coussens LM Paradoxical roles of the immune system during cancer development Nat Rev Cancer 2006 6 1 24 37 10.1038/nrc1782 16397525
De Visser KE, Eichten A, Coussens LM. Paradoxical roles of the immune system during cancer development. Nat Rev Cancer. 2006;6(1):24–37. 10.1038/nrc1782.16397525 10.1038/nrc1782
10. Papadimitriou N Markozannes G Kanellopoulou A Critselis E Alhardan S Karafousia V Tsilidis KK An umbrella review of the evidence associating diet and cancer risk at 11 anatomical sites Nat Commun 2021 12 1 4579 10.1038/s41467-021-24861-8 34321471
Papadimitriou N, Markozannes G, Kanellopoulou A, Critselis E, Alhardan S, Karafousia V, Tsilidis KK. An umbrella review of the evidence associating diet and cancer risk at 11 anatomical sites. Nat Commun. 2021;12(1):4579. 10.1038/s41467-021-24861-8.34321471 10.1038/s41467-021-24861-8
11. Furman D Campisi J Verdin E Carrera-Bastos P Targ S Franceschi C Slavich GM Chronic inflammation in the etiology of disease across the life span Nat Med 2019 25 12 1822 1832 10.1038/s41591-019-0675-0 31806905
Furman D, Campisi J, Verdin E, Carrera-Bastos P, Targ S, Franceschi C, Slavich GM. Chronic inflammation in the etiology of disease across the life span. Nat Med. 2019;25(12):1822–32. 10.1038/s41591-019-0675-0.31806905 10.1038/s41591-019-0675-0
12. Zhernakova A Van Diemen CC Wijmenga C Detecting shared pathogenesis from the shared genetics of immune-related diseases Nat Rev Genet 2009 10 1 43 55 10.1038/nrg2489 19092835
Zhernakova A, Van Diemen CC, Wijmenga C. Detecting shared pathogenesis from the shared genetics of immune-related diseases. Nat Rev Genet. 2009;10(1):43–55. 10.1038/nrg2489.19092835 10.1038/nrg2489
13. Hemminki K Liu X Ji J Försti A Sundquist J Sundquist K Effect of autoimmune diseases on risk and survival in female cancers Gynecol Oncol 2012 127 1 180 185 10.1016/j.ygyno.2012.07.100 22819787
Hemminki K, Liu X, Ji J, Försti A, Sundquist J, Sundquist K. Effect of autoimmune diseases on risk and survival in female cancers. Gynecol Oncol. 2012;127(1):180–5. 10.1016/j.ygyno.2012.07.100.22819787 10.1016/j.ygyno.2012.07.100
14. Bernatsky S Ramsey-Goldman R Foulkes WD Gordon C Clarke AE Breast, ovarian, and endometrial malignancies in systemic lupus erythematosus: a meta-analysis Br J Cancer 2011 104 9 1478 1481 10.1038/bjc.2011.115 21487409
Bernatsky S, Ramsey-Goldman R, Foulkes WD, Gordon C, Clarke AE. Breast, ovarian, and endometrial malignancies in systemic lupus erythematosus: a meta-analysis. Br J Cancer. 2011;104(9):1478–81. 10.1038/bjc.2011.115.21487409 10.1038/bjc.2011.115
15. Raymond WD Preen DB Keen HI Inderjeeth CA Nossent JC Cancer development in patients hospitalized with systemic lupus erythematosus: a population-level data linkage study Int J Rheum Dis 2023 26 8 1557 1570 10.1111/1756-185X.14784 37338061
Raymond WD, Preen DB, Keen HI, Inderjeeth CA, Nossent JC. Cancer development in patients hospitalized with systemic lupus erythematosus: a population-level data linkage study. Int J Rheum Dis. 2023;26(8):1557–70. 10.1111/1756-185X.14784.37338061 10.1111/1756-185X.14784
16. Exploring the causality and pathogenesis of systemic lupus erythematosus in breast cancer based on Mendelian randomization and transcriptome data analyses—PubMed. (n.d.). https://pubmed.ncbi.nlm.nih.gov/36726984/. Accessed 27 Jul 2024.
17. Davey Smith G Ebrahim S ‘Mendelian randomization’: can genetic epidemiology contribute to understanding environmental determinants of disease?* Int J Epidemiol 2003 32 1 1 22 10.1093/ije/dyg070 12689998
Davey Smith G, Ebrahim S. ‘Mendelian randomization’: can genetic epidemiology contribute to understanding environmental determinants of disease?*. Int J Epidemiol. 2003;32(1):1–22. 10.1093/ije/dyg070.12689998 10.1093/ije/dyg070
18. Boef AGC Dekkers OM Le Cessie S Mendelian randomization studies: a review of the approaches used and the quality of reporting Int J Epidemiol 2015 44 2 496 511 10.1093/ije/dyv071 25953784
Boef AGC, Dekkers OM, Le Cessie S. Mendelian randomization studies: a review of the approaches used and the quality of reporting. Int J Epidemiol. 2015;44(2):496–511. 10.1093/ije/dyv071.25953784 10.1093/ije/dyv071
19. Papadimitriou N Dimou N Gill D Tzoulaki I Murphy N Riboli E Tsilidis KK Genetically predicted circulating concentrations of micronutrients and risk of breast cancer: a Mendelian randomization study Int J Cancer 2021 148 3 646 653 10.1002/ijc.33246 32761610
Papadimitriou N, Dimou N, Gill D, Tzoulaki I, Murphy N, Riboli E, Tsilidis KK. Genetically predicted circulating concentrations of micronutrients and risk of breast cancer: a Mendelian randomization study. Int J Cancer. 2021;148(3):646–53. 10.1002/ijc.33246.32761610 10.1002/ijc.33246
20. Chen F Wen W Long J Shu X Yang Y Shu X Zheng W Mendelian randomization analyses of 23 known and suspected risk factors and biomarkers for breast cancer overall and by molecular subtypes Int J Cancer 2022 151 3 372 380 10.1002/ijc.34026 35403707
Chen F, Wen W, Long J, Shu X, Yang Y, Shu X, Zheng W. Mendelian randomization analyses of 23 known and suspected risk factors and biomarkers for breast cancer overall and by molecular subtypes. Int J Cancer. 2022;151(3):372–80. 10.1002/ijc.34026.35403707 10.1002/ijc.34026
21. Brion M-JA Shakhbazov K Visscher PM Calculating statistical power in Mendelian randomization studies Int J Epidemiol 2013 42 5 1497 1501 10.1093/ije/dyt179 24159078
Brion M-JA, Shakhbazov K, Visscher PM. Calculating statistical power in Mendelian randomization studies. Int J Epidemiol. 2013;42(5):1497–501. 10.1093/ije/dyt179.24159078 10.1093/ije/dyt179
22. Michailidou K Lindström S Dennis J Beesley J Hui S Kar S Easton DF Association analysis identifies 65 new breast cancer risk loci Nature 2017 551 7678 92 94 10.1038/nature24284 29059683
Michailidou K, Lindström S, Dennis J, Beesley J, Hui S, Kar S, Easton DF. Association analysis identifies 65 new breast cancer risk loci. Nature. 2017;551(7678):92–4. 10.1038/nature24284.29059683 10.1038/nature24284
23. Sakaue S Kanai M Tanigawa Y Karjalainen J Kurki M Koshiba S Okada Y A cross-population atlas of genetic associations for 220 human phenotypes Nat Genet 2021 53 10 1415 1424 10.1038/s41588-021-00931-x 34594039
Sakaue S, Kanai M, Tanigawa Y, Karjalainen J, Kurki M, Koshiba S, Okada Y. A cross-population atlas of genetic associations for 220 human phenotypes. Nat Genet. 2021;53(10):1415–24. 10.1038/s41588-021-00931-x.34594039 10.1038/s41588-021-00931-x
24. Bowden J Spiller W Fabiola Del Greco M Sheehan N Thompson J Minelli C Smith GD Improving the visualization, interpretation and analysis of two-sample summary data Mendelian randomization via the Radial plot and Radial regression Int J Epidemiol 2018 47 6 2100 10.1093/ije/dyy265 30423109
Bowden J, Spiller W, Fabiola Del Greco M, Sheehan N, Thompson J, Minelli C, Smith GD. Improving the visualization, interpretation and analysis of two-sample summary data Mendelian randomization via the Radial plot and Radial regression. Int J Epidemiol. 2018;47(6):2100. 10.1093/ije/dyy265.30423109 10.1093/ije/dyy265
25. Bowden J Davey Smith G Burgess S Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression Int J Epidemiol 2015 44 2 512 525 10.1093/ije/dyv080 26050253
Bowden J, Davey Smith G, Burgess S. Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression. Int J Epidemiol. 2015;44(2):512–25. 10.1093/ije/dyv080.26050253 10.1093/ije/dyv080
26. Evaluating the potential role of pleiotropy in Mendelian randomization studies—PubMed. (n.d.). https://pubmed.ncbi.nlm.nih.gov/29771313/. Accessed 27 Jul 2024.
27. Verbanck M Chen C-Y Neale B Do R Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases Nat Genet 2018 50 5 693 698 10.1038/s41588-018-0099-7 29686387
Verbanck M, Chen C-Y, Neale B, Do R. Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases. Nat Genet. 2018;50(5):693–8. 10.1038/s41588-018-0099-7.29686387 10.1038/s41588-018-0099-7
28. Machiela MJ Chanock SJ LDassoc: an online tool for interactively exploring genome-wide association study results and prioritizing variants for functional investigation Bioinformatics 2018 34 5 887 889 10.1093/bioinformatics/btx561 28968746
Machiela MJ, Chanock SJ. LDassoc: an online tool for interactively exploring genome-wide association study results and prioritizing variants for functional investigation. Bioinformatics. 2018;34(5):887–9. 10.1093/bioinformatics/btx561.28968746 10.1093/bioinformatics/btx561
29. Burgess S Thompson SG Interpreting findings from Mendelian randomization using the MR-Egger method Eur J Epidemiol 2017 32 5 377 389 10.1007/s10654-017-0255-x 28527048
Burgess S, Thompson SG. Interpreting findings from Mendelian randomization using the MR-Egger method. Eur J Epidemiol. 2017;32(5):377–89. 10.1007/s10654-017-0255-x.28527048 10.1007/s10654-017-0255-x
30. Qin B Wang J Yang Z Yang M Ma N Huang F Zhong R Epidemiology of primary Sjögren’s syndrome: a systematic review and meta-analysis Ann Rheum Dis 2015 74 11 1983 1989 10.1136/annrheumdis-2014-205375 24938285
Qin B, Wang J, Yang Z, Yang M, Ma N, Huang F, Zhong R. Epidemiology of primary Sjögren’s syndrome: a systematic review and meta-analysis. Ann Rheum Dis. 2015;74(11):1983–9. 10.1136/annrheumdis-2014-205375.24938285 10.1136/annrheumdis-2014-205375
31. Association between comorbidities and extraglandular manifestations in primary Sjögren’s syndrome: a multicenter cross-sectional study—PubMed. (n.d.). https://pubmed.ncbi.nlm.nih.gov/32146615/. Accessed 27 Jul 2024.
32. Deng J Liu M Xiao R Wang J Liao X Ye Z Sun Z Risk, incidence, and mortality of breast cancer in primary sjögren’s syndrome: a systematic review and meta-analysis Front Immunol 2022 13 904682 10.3389/fimmu.2022.904682 35844507
Deng J, Liu M, Xiao R, Wang J, Liao X, Ye Z, Sun Z. Risk, incidence, and mortality of breast cancer in primary sjögren’s syndrome: a systematic review and meta-analysis. Front Immunol. 2022;13:904682. 10.3389/fimmu.2022.904682.35844507 10.3389/fimmu.2022.904682
33. Pol J Paillet J Plantureux C Kroemer G Beneficial autoimmunity and maladaptive inflammation shape epidemiological links between cancer and immune-inflammatory diseases OncoImmunology 2022 11 1 2029299 10.1080/2162402X.2022.2029299 35070497
Pol J, Paillet J, Plantureux C, Kroemer G. Beneficial autoimmunity and maladaptive inflammation shape epidemiological links between cancer and immune-inflammatory diseases. OncoImmunology. 2022;11(1):2029299. 10.1080/2162402X.2022.2029299.35070497 10.1080/2162402X.2022.2029299
34. Schreiber RD Old LJ Smyth MJ Cancer immunoediting: integrating immunity’s roles in cancer suppression and promotion Science 2011 331 6024 1565 1570 10.1126/science.1203486 21436444
Schreiber RD, Old LJ, Smyth MJ. Cancer immunoediting: integrating immunity’s roles in cancer suppression and promotion. Science. 2011;331(6024):1565–70. 10.1126/science.1203486.21436444 10.1126/science.1203486
35. Finn OJ Immuno-oncology: understanding the function and dysfunction of the immune system in cancer Ann Oncol 2012 23 viii6 viii9 10.1093/annonc/mds256 22918931
Finn OJ. Immuno-oncology: understanding the function and dysfunction of the immune system in cancer. Ann Oncol. 2012;23:viii6–9. 10.1093/annonc/mds256.22918931 10.1093/annonc/mds256
36. Ribatti D The concept of immune surveillance against tumors: the first theories Oncotarget 2017 8 4 7175 7180 10.1863/oncotarget.12739 27764780
Ribatti D. The concept of immune surveillance against tumors: the first theories. Oncotarget. 2017;8(4):7175–80. 10.1863/oncotarget.12739.27764780 10.1863/oncotarget.12739
37. Zitvogel L Galluzzi L Smyth MJ Kroemer G Mechanism of action of conventional and targeted anticancer therapies: reinstating immunosurveillance Immunity 2013 39 1 74 88 10.1016/j.immuni.2013.06.014 23890065
Zitvogel L, Galluzzi L, Smyth MJ, Kroemer G. Mechanism of action of conventional and targeted anticancer therapies: reinstating immunosurveillance. Immunity. 2013;39(1):74–88. 10.1016/j.immuni.2013.06.014.23890065 10.1016/j.immuni.2013.06.014
38. Shah AA Igusa T Goldman D Li J Casciola-Rosen L Rosen A Petri M Association of systemic lupus erythematosus autoantibody diversity with breast cancer protection Arthritis Res Ther 2021 23 1 64 10.1186/s13075-021-02449-3 33632283
Shah AA, Igusa T, Goldman D, Li J, Casciola-Rosen L, Rosen A, Petri M. Association of systemic lupus erythematosus autoantibody diversity with breast cancer protection. Arthritis Res Ther. 2021;23(1):64. 10.1186/s13075-021-02449-3.33632283 10.1186/s13075-021-02449-3
39. Bernatsky S Ramsey-Goldman R Labrecque J Joseph L Boivin J-F Petri M Clarke AE Cancer risk in systemic lupus: an updated international multi-centre cohort study J Autoimmunity 2013 42 130 135 10.1016/j.jaut.2012.12.009 23410586
Bernatsky S, Ramsey-Goldman R, Labrecque J, Joseph L, Boivin J-F, Petri M, Clarke AE. Cancer risk in systemic lupus: an updated international multi-centre cohort study. J Autoimmunity. 2013;42:130–5. 10.1016/j.jaut.2012.12.009.23410586 10.1016/j.jaut.2012.12.009
40. Hansen JE Chan G Liu Y Hegan DC Dalal S Dray E Glazer MP Targeting cancer with a lupus autoantibody Sci Transl Med 2012 10.1126/scitranslmed.3004385 23100628
Hansen JE, Chan G, Liu Y, Hegan DC, Dalal S, Dray E, Glazer MP. Targeting cancer with a lupus autoantibody. Sci Transl Med. 2012. 10.1126/scitranslmed.3004385.23100628 10.1126/scitranslmed.3004385
41. Gardner-Thorpe J Ito H Ashley SW Whang EE Autoantibody-mediated inhibition of pancreatic cancer cell growth in an athymic (Nude) mouse model Pancreas 2003 27 2 180 189 10.1097/00006676-200308000-00012 12883268
Gardner-Thorpe J, Ito H, Ashley SW, Whang EE. Autoantibody-mediated inhibition of pancreatic cancer cell growth in an athymic (Nude) mouse model. Pancreas. 2003;27(2):180–9. 10.1097/00006676-200308000-00012.12883268 10.1097/00006676-200308000-00012
42. Castoldi F Humeau J Martins I Lachkar S Loew D Dingli F Pietrocola F Autophagy-mediated metabolic effects of aspirin Cell Death Discov 2020 6 1 129 10.1038/s41420-020-00365-0 33298861
Castoldi F, Humeau J, Martins I, Lachkar S, Loew D, Dingli F, Pietrocola F. Autophagy-mediated metabolic effects of aspirin. Cell Death Discov. 2020;6(1):129. 10.1038/s41420-020-00365-0.33298861 10.1038/s41420-020-00365-0
43. Zhang Y Chen H Chen S Li Z Chen J Li W The effect of concomitant use of statins, NSAIDs, low-dose aspirin, metformin and beta-blockers on outcomes in patients receiving immune checkpoint inhibitors: a systematic review and meta-analysis OncoImmunology 2021 10 1 1957605 10.1080/2162402X.2021.1957605 34377596
Zhang Y, Chen H, Chen S, Li Z, Chen J, Li W. The effect of concomitant use of statins, NSAIDs, low-dose aspirin, metformin and beta-blockers on outcomes in patients receiving immune checkpoint inhibitors: a systematic review and meta-analysis. OncoImmunology. 2021;10(1):1957605. 10.1080/2162402X.2021.1957605.34377596 10.1080/2162402X.2021.1957605
44. Yang H Xia L Chen J Zhang S Martin V Li Q Ma Y Stress–glucocorticoid–TSC22D3 axis compromises therapy-induced antitumor immunity Nat Med 2019 25 9 1428 1441 10.1038/s41591-019-0566-4 31501614
Yang H, Xia L, Chen J, Zhang S, Martin V, Li Q, Ma Y. Stress–glucocorticoid–TSC22D3 axis compromises therapy-induced antitumor immunity. Nat Med. 2019;25(9):1428–41. 10.1038/s41591-019-0566-4.31501614 10.1038/s41591-019-0566-4
45. Goulabchand R Malafaye N Jacot W Witkowski Durand Viel P Morel J Lukas C Guilpain P Cancer incidence in primary Sjögren’s syndrome: data from the French hospitalization database Autoimmun Rev 2021 20 12 102987 10.1016/j.autrev.2021.102987 34718160
Goulabchand R, Malafaye N, Jacot W, Witkowski Durand Viel P, Morel J, Lukas C, Guilpain P. Cancer incidence in primary Sjögren’s syndrome: data from the French hospitalization database. Autoimmun Rev. 2021;20(12):102987. 10.1016/j.autrev.2021.102987.34718160 10.1016/j.autrev.2021.102987
46. Goulabchand R Hafidi A Millet I Morel J Lukas C Humbert S Guilpain P Mastitis associated with Sjögren’s syndrome: a series of nine cases Immunol Res 2017 65 1 218 229 10.1007/s12026-016-8830-x 27561784
Goulabchand R, Hafidi A, Millet I, Morel J, Lukas C, Humbert S, Guilpain P. Mastitis associated with Sjögren’s syndrome: a series of nine cases. Immunol Res. 2017;65(1):218–29. 10.1007/s12026-016-8830-x.27561784 10.1007/s12026-016-8830-x
47. McCoy SS Sampene E Baer AN Association of Sjögren’s syndrome with reduced lifetime sex hormone exposure: a case-control study Arthritis Care Res 2020 72 9 1315 1322 10.1002/acr.24014
McCoy SS, Sampene E, Baer AN. Association of Sjögren’s syndrome with reduced lifetime sex hormone exposure: a case-control study. Arthritis Care Res. 2020;72(9):1315–22. 10.1002/acr.24014.10.1002/acr.24014
48. Incidence of malignancy in adult patients with rheumatoid arthritis: a meta-analysis—PubMed. (n.d.). https://pubmed.ncbi.nlm.nih.gov/26271620/. Accessed 27 Jul 2024.
49. Cevik R Em S Gur A Nas K Sarac AJ Çolpan L Sex and thyroid hormone status in women with rheumatoid arthritis: are there any effects of menopausal state and disease activity on these hormones?: Sex and thyroid hormone status in women with RA Int J Clin Pract 2004 58 4 327 332 10.1111/j.1368-5031.2004.00005.x 15161114
Cevik R, Em S, Gur A, Nas K, Sarac AJ, Çolpan L. Sex and thyroid hormone status in women with rheumatoid arthritis: are there any effects of menopausal state and disease activity on these hormones?: Sex and thyroid hormone status in women with RA. Int J Clin Pract. 2004;58(4):327–32. 10.1111/j.1368-5031.2004.00005.x.15161114 10.1111/j.1368-5031.2004.00005.x
50. Oldroyd AGS Allard AB Callen JP Chinoy H Chung L Fiorentino D Aggarwal R A systematic review and meta-analysis to inform cancer screening guidelines in idiopathic inflammatory myopathies Rheumatology 2021 60 6 2615 2628 10.1093/rheumatology/keab166 33599244
Oldroyd AGS, Allard AB, Callen JP, Chinoy H, Chung L, Fiorentino D, Aggarwal R. A systematic review and meta-analysis to inform cancer screening guidelines in idiopathic inflammatory myopathies. Rheumatology. 2021;60(6):2615–28. 10.1093/rheumatology/keab166.33599244 10.1093/rheumatology/keab166
51. Mecoli CA Igusa T Chen M Wang X Albayda J Paik JJ Shah AA Subsets of idiopathic inflammatory myositis enriched for contemporaneous cancer relative to the general population Arthr Rheumatol 2023 75 4 620 629 10.1002/art.42311 35878018
Mecoli CA, Igusa T, Chen M, Wang X, Albayda J, Paik JJ, Shah AA. Subsets of idiopathic inflammatory myositis enriched for contemporaneous cancer relative to the general population. Arthr Rheumatol. 2023;75(4):620–9. 10.1002/art.42311.35878018 10.1002/art.42311
