Hormonal Crosstalk Between Thyroid and Breast Cancer

Thyroid Hormone Changes Correlate to Combined Breast Cancer with Primary Thyroid Cancer

Background

Breast cancer and thyroid cancer are two prevalent malignancies in women, and a potential association between the two diseases has been suggested.

Methods

This retrospective case-control study was conducted involving 97 patients with breast cancer and thyroid cancer (BC-TC group) and 97 age-matched patients with breast cancer alone (BC group). Thyroid hormone levels, including triiodothyronine (T3), thyroxine (T4), free triiodothyronine (FT3), free thyroxine (FT4) and thyroid-stimulating hormone (TSH), were analyzed in healthy controls, BC patients, and BC-TC patients.

Results

BC-TC patients exhibited a higher rate of estrogen receptor (ER) and progesterone receptor (PR) positivity compared to BC patients. Serum T3 levels were significantly decreased in BC and BC-TC patients compared to healthy controls. However, there was no significant difference in T3 levels between BC and BC-TC patients. Serum TSH levels were significantly higher in BC-TC patients compared to BC patients.

Conclusion

ER positivity, PR positivity, and serum TSH levels greater than 4.45 mU/L were independent risk factors for primary thyroid cancer in breast cancer patients.

The association between thyroid and breast cancers: a bidirectional mendelian randomization study

Background

Thyroid and breast cancers are the two most frequent types of endocrine-related tumors among women worldwide, and their incidence is still on the rise. Observational studies have shown a relationship between thyroid and breast cancers. Nevertheless, many confounders predispose the results to interference. Accordingly, we performed a two-sample Mendelian randomization (MR) study to investigate the causal association between thyroid and breast cancers.

Methods

We acquired breast cancer data from the UK Biobank (13,879 breast cancer cases and 198,523 controls) and the Breast Cancer Association Consortium (BCAC; 122,977 breast cancer cases and 105,974 controls), and thyroid cancer data from FinnGen Biobank (989 thyroid cancer and 217,803 controls). Then, the multiplicative random effects inverse variance weighting (IVW), weight median (WM), and MR Egger methods were executed for MR analysis.

Results

Overall, IVW showed a causal effect of breast cancer on thyroid cancer using the BCAC dataset (odds ratio [OR] = 1.17; 95% confidence interval [CI] = 1.036-1.322; P = 0.011), and this relationship was also supported by the UK Biobank dataset (OR = 23.899; 95% CI = 2.331-245.003; P = 0.007), which showed that breast cancer patients were more likely to be diagnosed with thyroid cancer. On the whole, the reverse MR analysis did not show a causal effect of breast cancer on thyroid cancer. However, IVW showed a causal effect of thyroid cancer on estrogen receptor -negative breast cancer using the BCAC dataset (OR = 1.019; 95% CI = 1.001-1.038; P = 0.043), which suggested that people with thyroid cancer were more likely to develop breast cancer.

Conclusions

Breast cancer represents a possible risk factor for thyroid cancer and thyroid cancer also represents a possible risk factor for ER-negative breast cancer. Future studies using powerful genetic tools to determine the causal relationship between breast and thyroid cancers are required.

Risk Factors for Granulomatous Mastitis and Establishment and Validation of a Clinical Prediction Model (Nomogram)

Background

This study aimed to explore the risk factors and clinical characteristics of granulomatous mastitis (GM) using a case-control study and establish and validate a clinical prediction model (nomogram).

Methods

This retrospective case-control study was conducted in three hospitals in China from June 2017 to December 2021. A total of 1634 GM patients and 186 healthy women during the same period were included and randomly divided into the modeling and validation groups in a 7:3 ratio. To identify the independent risk factors of GM, univariate and multivariate logistic analyses were conducted and used to develop a nomogram. The prediction model was internally and externally validated using the Bootstrap technique and validation cohort. The receiver operating characteristic (ROC) curve and calibration curve were used to evaluate the discrimination and calibration of the prediction model. Decision curve analysis (DCA) and clinical impact curve (CIC) were used to evaluate the clinical significance of the model.

Results

The average age of GM patients was 33.14 years (mainly 20-40). The incidence was high within five years from delivery and mainly occurred in the unilateral breast. The majority of the patients exhibited local skin alterations, while some also presented with systemic symptoms. On multivariate logistic analysis, age, high prolactin level, sex hormone intake, breast trauma, nipple discharge or invagination, and depression were independent risk factors for GM. The mean area under the curve (AUC) in the modeling and validation groups were 0.899 and 0.889. The internal and external validation demonstrated the model's predictive ability and clinical value.

Conclusion

Lactation-related factors are the main risk factors of GM, leading to milk stasis or increased ductal secretion. Meanwhile, hormone disorders could affect the secretion and expansion of mammary ducts. All these factors can obstruct or injure the duct, inducing inflammatory reactions and immune responses. Additionally, blunt trauma, depressed mood, and diet preference can accelerate the process. The nomogram can effectively predict the risk of GM.

The Role of Blood Microbiome in the Development of Thyroid Cancer in Breast Cancer Survivors

Patients diagnosed with breast cancer are likely to be diagnosed with thyroid cancer as a second primary cancer. Similarly, patients with thyroid cancer are likely to develop breast cancer. In this study, we found an association between these two types of cancers in the microbiomes of patients with breast cancer. Blood samples were collected from 96 patients with breast cancer, their bacterial extracellular vesicles were isolated, and their microbiomes were analyzed. After microbiome analysis, researchers performed thyroid function tests, estrogen levels, and thyroid ultrasound results of these patients, and the relationships among these parameters were analyzed. Based on the thyroid ultrasonography results, differences in the microbiome were confirmed in the normal, cyst, nodule, and thyroid lobectomy groups. We investigated the microbiome differences between normal thyroid and thyroid cancer. In particular, the abundance of the genus Bacillus is related to estrogen levels, which could affect thyroid abnormalities and increase thyroid-stimulating hormone levels. This study explains the causes of thyroid cancer in patients with breast cancer using microbiomes and serological tests for thyroid hormones and estrogen. These can be used as basic data for preventing thyroid cancer in patients with breast cancer.

Ectopic thyroid tissue in the breast: A case report

Ectopic thyroid tissue is a rare condition manifested as the appearance of thyroid tissue outside the thyroid gland. Here, we report a case of ectopic thyroid tissue in the breast. A 48-year-old Chinese woman who was diagnosed with breast cancer received modified radical mastectomy. A thyroid tissue was found on subsequent pathological examination. The ectopic thyroid tissue was confirmed by immunohistochemistry staining of thyroid biomarkers, including thyroglobulin, thyroid transcription factor-1, and thyroid peroxidase. Currently, abnormal thyroid anlage descent is the main theory to explain ectopic thyroid tissue, especially lingual thyroid. However, it is far-fetched to explain the pathogenesis of ectopic thyroid tissues existed in organs or tissues far from thyroid such as iris, cardiac, pulmonary, duodenal, adrenal, and vertebral. Here, we reviewed the previous cases of ectopic thyroid tissue in breast and proposed a "entoderm migration" theory to explain distant ectopic thyroid tissues based on embryonic development perspective.

Association between breast cancer and thyroid cancer risk: a two-sample Mendelian randomization study

Background

Breast and thyroid cancer are increasingly prevalent, but it remains unclear whether the observed associations are due to heightened medical surveillance or intrinsic etiological factors. Observational studies are vulnerable to residual confounding, reverse causality, and bias, which can compromise causal inference. In this study, we employed a two-sample Mendelian randomization (MR) analysis to establish a causal link between breast cancer and heightened thyroid cancer risk.

Methods

We obtained the single nucleotide polymorphisms (SNPs) associated with breast cancer from a genome-wide association study (GWAS) conducted by the Breast Cancer Association Consortium (BCAC). The FinnGen consortium's latest and largest accessible GWAS thyroid cancer data at the summary level. We performed four MR analyses, including the inverse-variance-weighted (IVW), weighted median, MR-Egger regression, and weighted mode, to evaluate the potential causal connection between genetically predicted breast cancer and higher risk for thyroid cancer. Sensitivity analysis, heterogeneity and pleiotropy tests were used to ensure the reliability of our findings.

Results

Our study revealed causal relationship between genetically predicted breast cancer and thyroid cancer (IVW method, odds ratio (OR) = 1.135, 95% confidence interval (CI): 1.006 to 1.279, P = 0.038). However, there was no causal association between genetically predicted triple-negative breast cancer and thyroid cancer (OR = 0.817, 95% CI: 0.610 to 1.095, P = 0.177). There was no directional pleiotropy or horizontal pleiotropy in the present study.

Conclusion

This two-sample MR study supports a causal link between ER-positive breast cancer and heightened the risk of thyroid cancer. Our analysis did not reveal a direct correlation between triple-negative breast cancer and thyroid cancer.

Age-dependent changes in the prognostic advantage of papillary thyroid cancer in women: A SEER-based study

BACKGROUND

Papillary thyroid cancer (PTC) is more prevalent in women, and women show a better prognosis than men; however, the factors contributing to this prognostic difference are confounding. Therefore, we aimed to investigate the effect of the interaction between sex and age on the prognosis of PTC.

METHODS

A total of 108,459 patients with PTC were retrospectively analysed, and Cox-regression models were used to assess differences in disease specific survival (DSS) by sex, with inverse probability of treatment weighting (IPTW) to control for between-group differences in prognosis by sex due to age change. Restricted cubic splines were used to analyse prognostic differences between sexes for papillary thyroid microcarcinoma (PTMC) and PTC. Multiple mediation analyses were used to assess the direct or indirect effect of sex on DSS.

RESULTS

The DSS was higher for women than men (98.6% vs. 95.4%, χ²  = 458.57, p < .001). After IPTW adjustment, the DSS of women was better than that of men (HR = 0.67, 0.60-0.76). In the subgroup analysis, women had an advantage in DSS across most age intervals (crude HR = 0.166 [0.082-0.337], p < .001, IPTW-adjusted HR = 0.331 [0.161-0.681], p < .001). The difference between the two gradually narrowed with increasing age, and the prognosis of women was better than that of men in PTMC, while this advantage was not obvious in PTC.

CONCLUSIONS

The overall PTC prognosis of women is better than that of men, but the prognostic advantage of women diminishes with age and tumour growth. These differences in prognosis may be due to some indirect factors caused by different sexes.