Predictive value of CA-153, CA-125 and Apo A for ocular metastasis in menopausal female patients with breast cancer.

● AIM: To establish a meaningful standard for diagnosing ocular metastasis (OM) in menopausal breast cancer (BC) women, and explore the relationship between CA-153, CA-125, apolipoprotein A, and OM. ● METHODS: A total of 1362 menopausal female BC patients with OM volunteered to take part in this study between July 2012 and July 2022. Women with BC who are menopausal were found to have an OM incidence of 1.6%. Furthermore, CA-153, CA-125, and apolipoprotein A (Apo A) all contributed to OM in women with BC who are postmenopausal according to binary logistic regression. Receiver operating curve (ROC) analysis was used to assess the diagnostic value of OM in patients with BC. ● RESULTS: Both CA-153 and CA-153+CA-125 showed a higher sensitivity of 95.45%, whereas CA-153+Apo A illustrated the highest specificity of 99.02%. Moreover, CA-153 and CA-153+CA-125 had higher areas under the curve (AUC) of 0.973. ● CONCLUSION: The data indicate that the serum concentrations of CA-153 exhibited the most significant predictors of the diagnosis of OM in menopausal women with BC. The current study researches the utility of risk factors in predicting of OM in menopausal BC women and put forward the latest suggestions on their clinical application. ● KEYWORDS: menopausal female patients; breast cancer; ocular metastasis; CA-125; CA-153; apolipoprotein A DOI:10.18240/ijo.2024.12.15 Citation: Liu QC, Ling Q, Zeng YM, Chen C, Wei H, Hu JY , Zou J, Wang XY , Chen X, Shao Y . Predictive value of CA-153, CA-125 and Apo A for ocular metastasis in menopausal female patients with breast cancer. Int J Ophthalmol 2024;17(12):2265-2275

B reast cancer (BC) is now the most prevalent form of malignant tumor in women [1] . In 2018, 32.4% of women were diagnosed with BC, according to data from the World Cancer Research Fund International [2] . Furthermore, 31% of all tumors in women worldwide are BC, which are the most common malignant tumors in women. It is characterized by high recurrence rate, high mortality rate, and unfavorable prognoses [3] . Also, this disease affected 1.7 million women worldwide in 2012, making it a global priority [4] . Therefore, it is no exaggeration to say that there are probably more studies on BC than any other malignant tumor. During menopause, ovary function ceases, reproductive hormone production ceases, and fertility is irreversibly lost, which is a natural part of aging reproductive organs [5] . Menopause is an important transition in the reproductive life cycle of women, as it signals the end of fertility [6] . Menopause is also an important determinant of future BC risk [7] . Ovarian degeneration and estrogen reduction are closely related to menopause and are considered to be risk factors for BC [8] . 2266 However, much evidence also shows that the external influence factors of BC are lack of physical exercise [9] , high-fat diet [10] , mutagenic and carcinogenic compounds in food [11] , and drinking [12] . Heredity also can increase BC predisposition [13] . Excessive drinking has been linked to BC risk in previous studies, but whether light drinking has adverse effects on the human body is still unclear [14] . Based on the review of Scoccianti et al [14] , we selected drinking more than 15 g per day as one criterion and divided the sample into two groups, to compare the relationship between drinking and ocular metastasis (OM) in BC and assess the histopathological features caused by drinking. In addition, after several years from the occurrence of primary BC, the probability of distant metastasis of patients is higher than that of local recurrence [15] . And any part of the body can be affected by BC, including the eyes (only 3%–10% of cases) [16] . In the study of Demirci et al [17] , all BC patients with OM, regardless of their treatment history, had a poor systemic prognosis, with survival rates of 65% after one year and 24% after five years, with survival rates of 65% at 1-year follow-up and 24% at 5-year follow-up. This shows that early diagnosis can bring early treatment which can significantly improve the prognosis of patients with distant metastasis [15] . Although diagnostic imaging examination (e.g., magnetic resonance imaging, ultrasonography, mammography, and other scientific and effective imaging methods) may contribute to reduced morbidity and mortality [1] , they are either expensive or need a high level of technical support. Thus, in the current study, we adopted a simple, inexpensive, routine hematological examination to establish a universally accepted diagnostic standard for BC by detecting biomarkers in the serum. Tumor markers exist in the blood tissue of patients and are substances synthesized and released by tumor cells during the occurrence and development of tumors. The more vigorously the tumor grows, the higher the number of corresponding markers, which can also be a type of substance produced by other tissues or cells. The elevation of tumor markers may indicate the occurrence of a tumor or the recurrence and metastasis of a previous tumor. The normal reference range for tumor markers is the normal range calculated by epidemiological investigations and statistics for most healthy individuals [18] . Their presence or quantity changes can indicate the nature of the tumor, in order to understand its tissue development, cell differentiation, and cell function, and to assist in the diagnosis, classification, prognosis, and treatment guidance of tumors. In addition, some benign diseases such as inflammation, liver and kidney dysfunction, skin diseases, endometriosis, etc. may be accompanied by abnormal elevation of tumor markers. Normal physiological changes such as pregnancy and menstruation can affect some tumor markers. In addition, unhealthy lifestyle habits such as drinking alcohol, smoking, and staying up late may also lead to abnormal tumor markers [19] . Abnormal elevation of CA153 is commonly seen in breast malignant tumors, and mild abnormalities are occasionally observed in benign diseases such as breast adenomas [20] . The positive rate of CA153 in BC patients was significantly higher than that in healthy people. The level of CA153 in BC patients is closely related to the treatment effect. Detection of CA153 can be used to monitor the treatment effect of BC patients and determine whether there is metastasis after surgery. When there is metastasis, the positive rate of CA153 is as high as 60% to 80% [21] . Abnormal increase of CA125 is common in gynecological malignancies, such as BC, ovarian cancer, endometrial cancer, cervical cancer, fallopian tube cancer, etc. It may also be slightly increased in some gynecological benign diseases [22] . Apolipoprotein A (Apo A) is a special type of lipoprotein, and abnormal elevation is mainly caused by genetic factors. Patients with high lipoprotein A often have more than one family member with similar blood lipid abnormalities [23] . Although the lipid composition of Apo A is similar to low-density lipoprotein (LDL), the concentration of Lipoprotein a (LPA) is not affected by gender, age, weight, and cholesterol lowering drugs, making it difficult to adjust for abnormally elevated levels of this lipoprotein. Previous studies have found that the level of apolipoprotein A in the blood of patients with diagnosed BC is significantly higher than that of benign breast tumors and healthy controls (physical examination population), suggesting that there may be a certain relationship between lipoprotein a and the occurrence of BC [24] . In the our study, a correlation was also examined between serum biomarker levels CA-153, CA-125, and Apo A, and OM in menopausal BC patients in the Jiangxi Province. We aimed to establish a meaningful standard for diagnosing OM in menopausal BC women, and explore the relationship between CA-153, CA-125, Apo A, and OM. PARTICIPANTS AND METHODS Ethical Approval The First Affiliated Hospital of Nanchang University’s medical research ethics committee, Nanchang, Jiangxi Province, China approved the study. All participants in the study gave informed consent. All procedure was carried out in compliance with the principles outlined in the Declaration of Helsinki. Study Design In this retrospective study, between July 2012 and July 2022, a total of 1362 menopausal women with BC were evaluated and subdivided into OM and non- ocular metastasis (NOM) groups. The OM were assessed through ophthalmic B-type ultrasound, fundus photography, indocyanine green angiography (ICGA) and fundus fluorescein angiography (FFA; Figure 1). The diagnosis of Risk factors of breast cancer in ocular metastasis 2267 Int J Ophthalmol, Vol. 17, No. 12, Dec. 18, 2024 www.ijo.cn Tel: 8629-82245172 8629-82210956 Email: [email protected] OM was validated through the application of both computed tomography (CT) and magnetic resonance imaging (MRI). Inclusion criteria of OM: 1) BC patients with OM; 2) heart function is normal, kidney function is normal, and imaging can be performed; 3) no metal implants, MRI can be performed. Exclusion criteria: 1) presence of primary malignant and benign ocular tumors; 2) presence of comorbidities; 3) presence of other metastatic cancers; 4) mental illness. Inclusion criteria of NOM: 1) patients with BC; 2) heart function is normal, kidney function is normal, and imaging can be performed; 3) no metal implants, MRI can be performed. Exclusion criteria: 1) presence of comorbidities; 2) metastasis to other organs or lymph nodes; 3) mental illness. All medical records were up-to-date and basic demographic and clinical data were collected in a timely manner. Data Collection Diagnostic records of patients were analyzed to determine serum levels of relevant biomarkers (e.g., age, histopathological types, and drinking habits). Several biomarkers were then compared between the two groups, which contained calcium, alkaline phosphatase (ALP), total cholesterol, CA-153, CA-125, CA-199, carcinoembryonic antigen (CEA), triglyceride (TG), LDL, high density lipoprotein (HDL), Apo A, Apo B, lipoprotein(a) [Lp(a)], and hemoglobin (HB). All medical records were obtained during the initial diagnosis of BC, biomarkers were tested by the Laboratory Department of our hospital, the test sample was the patient’s blood. Statistical Analysis The differences in histopathological type and age between the OM and NOM groups were evaluated using Chi-squared tests and Student’s t-tests. An investigation of single OM risk factors was conducted using binary logistic regression models. Receiver operating characteristic (ROC) curves showed the differences in sensitivities, specificities, and areas under the curve (AUCs) of CA-125, CA-153, and Apo A. OM diagnosis accuracy was evaluated by the AUCs in menopausal patients with BC. P <0.05 was considered statistically significant. Statistical analysis was carried out through Microsoft Office Excel 2016 (Microsoft Corp, USA), SPSS version 17.0 software (SPSS Inc., Chicago, IL, USA), and MedCalc 18.6.0 statistical software (MedCalc, Ostend, Belgium). Continuous data were represented as mean±standard deviation (SD).

Demographics and Clinical Characteristics The analysis was conducted on 22 individuals with OM and 1340 individuals with NOM. Demographic data are presented in Table 1. Figure 2 shows typical images of the hematoxylin-eosin (HE) and Immunohistochemistry (IHC) staining of specimens from the OM portion of BC. The average age of the OM and NOM groups was 54.0±3.0 and 59.5±2.5y, respectively (all ages of menopausal patients with BC>45y). No significant differences (P>0.05) were observed in the histopathological types between the OM and NOM groups (Table 1). Furthermore, Table 2 shows that no notable histopathological type (P >0.05) had been observed in most menopausal patients with BC and OM. No significant differences (P>0.05) in histopathological types were observed between the drinking and non-drinking groups (Table 1). Radical surgery was used on all patients. Tables 1 and 2 shows the details of all menopausal women with BC. Figure 3 shows the proportion of drinkers and non-drinkers in two groups. Clinical Data and Risk Factors Related to Ocular Metastasis The analysis of serum biomarker data acquired from patient records revealed that the concentrations of CA-125, CA-153, TG, HDL, Apo B, and Lp(a) in the NOM group were significantly lower than those in the OM group Figure 1 An example of breast cancer patients with OM A: Ophthalmic B-type ultrasound; B: Fundus photography; C: Fundus fluorescein angiography; D: Indocyanine green angiography. OM: Ocular metastasis. Figure 2 The HE and IHC staining images of OM in breast cancer patients A: CD56; B: HE; C: SYN; D: TTF-1. HE: Hematoxylin-eosin staining; IHC: Immunohistochemistry; OM: Ocular metastasis; SYN: Synaptophysin; TTF: Thyroid transcription factor. 2268 (P<0.05). Conversely, the NOM group exhibited elevated levels of ALP, calcium, total cholesterol, LDL, Apo A, and HB (P0.05). The results of these analyses are presented in Tables 3 and 4. Moreover, CA-153, CA- 125, and Apo A were identified as independent risk factors which associated with OM in an analysis of binary logistic regression (Table 5). In medicine, cutoff values [25] are positive judgment values, diagnostic thresholds for diseases, or

values that affect medical behavior. The criteria for selecting appropriate cutoff values come from the optimal solution of diagnostic or decision-making performance. Generally speaking, the examination results themselves are only objective quantitative indicators, and cutoff values can help diagnose positive examination results and clarify the physiological/pathological value of the detection indicators [26] . Sensitivity, also known as true positive rate or detection rate, reflects the ability of a test to detect patients. The higher the sensitivity, the lower the missed diagnosis rate [27] . Specificity, also known as true negative rate, the higher the specificity, the lower the misdiagnosis rate [28] . The AUC reflects the value of the diagnostic test [29] . The larger the area and the closer it is to 1.0, the higher the accuracy of the diagnosis; The closer it is to 0.5, the lower the accuracy of the diagnosis; When it is equal to 0.5, there is no diagnostic value. AUC=0.5-0.7, low accuracy; AUC=0.7-0.9, with certain accuracy; AUC>0.9, high accuracy [30] . Table 6 shows some risk factors for BC metastases [31-43] . Performance of CA-125, CA-153, and Apo A in Diagnosing OM It can be seen in Table 5 that CA-153, CA-125, and Apo A exhibit critical values of 19.30 U/mL, 61.35 U/mL, and 1.12 g/L, respectively. The AUC of CA-153 as a single risk factor yielded the highest value of 0.973. We later examined these risk factors both pairwise and as a whole. Figure 4 illustrates the ROC curves for CA-153, CA-125, and Apo A as single factors as well as their combinations. We found that CA-153 showed the highest AUC values with relatively high sensitivity and specificity, which were 0.973, 95.45%, and 97.38%, respectively. Among the indicators under investigation, there was the greatest sensitivity in CA-153 and CA-153+CA-125 (95.45%), whereas CA-153+Apo A showed the highest specificity (99.02%). There was statistical significance to all of these findings (P<0.05). Table 1 Clinical characteristics of menopausal female patients with breast cancer n (%) Patient characteristics OM groupa (n=22) NOM group (n=1340) P Mean agec 54.0±3.0 59.5±2.5 <0.001c Histopathological type 0.898 Ductal carcinoma 1 (4.5) 55 (4.1) Invasive ductal carcinoma 13 (59.1) 746 (55.7) Lobular carcinoma 0 36 (2.7) Squamous cell carcinoma 0 2 (0.1) Adenocarcinoma 0 54 (4.0) Others 8 (36.4) 447 (33.4) aOcular metastasis including intraocular metastasis and eyelid metastasis; bChi-squared test, cStudent’s t-test for comparison between the OM and NOM groups. P<0.05 denoted statistical significance. OM: Ocular metastasis; NOM: Non-ocular metastasis. Table 2 Histopathological types of menopausal female patients with breast cancer with drinking or non-drinking n (%) Histopathological type Drinking (n=296) Non-drinking (n=1066) Pa Ductal carcinoma 15 (5.1) 41 (3.8) 0.611 Invasive ductal carcinoma 157 (53.1) 602 (56.6) Lobular carcinoma 9 (3.0) 27 (2.5) Squamous cell carcinoma 0 2 (0.2) Adenocarcinoma 9 (3.0) 45 (4.2) Others 106 (35.8) 349 (32.7) aChi-square test was used for comparison between OM group and NOM group. P<0.05 represented statistically significant. Figure 3 The drinking and non-drinking proportion of menopausal female breast cancer patients with OM or NOM OM: ocular metastasis; NOM: Non-ocular metastasis. Figure 4 ROC curves of single risk factors and the combinations of risk factors for detecting OM in menopausal female patients with breast cancer ROC curves of CA-125, CA-153 and apolipoprotein A as single risk factor and the combination of CA-125, CA-153 and apolipoprotein A to detected OM in menopausal female patients with breast cancer. ROC: Receiver operating characteristic; AUC: Area under curve; OM: Ocular metastasis. Risk factors of breast cancer in ocular metastasis 2269 Int J Ophthalmol, Vol. 17, No. 12, Dec. 18, 2024 www.ijo.cn Tel: 8629-82245172 8629-82210956 Email: [email protected]

In both developed and less-developed countries, BC is the most prevalent type of cancer among women [44] . However, the epidemiological features of BC differ in developing countries from those in western countries [45] . More than 6 million women worldwide live with a diagnosis of BC [6] . The incidence of BC continues to be extremely high. However, overall BC mortality has shown a rapid decline by 39% per year from 1989 to 2015 [46] . Menopause can increase the incidence of BC by influencing estrogen levels. Based on the studies of Wang et al [47] and Ekwueme et al [48] , we selected menopausal individuals with BC, who were older than 45 years old. Moreover, the World Cancer Research Fund International and American Cancer Society recommend limiting alcohol consumption and changing lifestyles to reduce the risk of BC by 25% to 30% in spite of their controversial recommendations [44] , even though these recommendations are controversial. In the study of Scoccianti et al [49] , the intake of alcoholic beverages has been linked to the incidence of female BC, exhibiting a linear dose-response relationship. The impact of excessive alcohol consumption has been acknowledged for a long time, and even moderate drinking is linked to a higher risk of BC [49] . However, in the study of the Collaborative Group on Hormonal Factors Table 3 Differences in the concentration of various tumor biomarkers between menopausal female breast cancer patients with and without OM Tumor biomarkers OM group NOM group t-test P ALP (U/L) 107.50±46.50 123.00±64.00 -8.390 <0.001 Calcium (mmol/L) 2.12±0.00 2.21±0.18 -4.929 <0.001 Total cholesterol (mmol/L) 3.68±0.64 4.49±0.86 -17.733 <0.001 CEA (ng/mL) 1.92±0.36 14.99±12.36 -0.796 0.426 CA-125 (U/mL) 18.50±2.50 9.90±0.07 -12.601 <0.001 CA-199 (U/mL) 9.44±2.87 14.90±3.81 -2.893 0.004 CA-153 (U/mL) 75.55±56.46 35.69±21.82 53.182 <0.001 TG (mmol/L) 2.19±0.23 1.12±0.41 -27.917 <0.001 HDL (mmol/L) 1.73±1.03 1.27±0.13 18.545 <0.001 LDL (mmol/L) 1.18±0.35 2.89±0.82 -40.514 <0.001 Apolipoprotein A (g/L) 1.22±0.28 1.59±0.19 -79.998 <0.001 Apolipoprotein B (g/L) 1.16±0.48 0.75±0.12 -7.320 <0.001 Lipoprotein-a (mg/L) 159.50±26.50 146.00±100.00 -10.342 <0.001 HB (g/L) 101.50±1.50 119.50±12.50 -36.093 <0.001 Independent sample t-test. P<0.05 denoted statistical significance. OM: Ocular metastasis; NOM: Non-ocular metastasis; ALP: Alkaline phosphatase; CEA: Carcinoembryonic antigen; TG: Triglyceride; HDL: High-density lipoprotein; LDL: Low-density lipoprotein; HB: Hemoglobin. Table 4 Risk factors of OM in menopausal female patients with breast cancer Factors B Exp(B) OR (95%CI) P ALP (U/L) -0.002 0.998 -38.042- -23.633 <0.001 Calcium (mmol/L) -1.610 0.200 -0.313- -0.135 <0.001 Total cholesterol (mmol/L) -0.466 0.627 -1.981- -1.586 <0.001 CA-125 (U/mL) <0.001 1.000 -661.751- -483.600 <0.001 CA-153 (U/mL) 0.011 1.011 61.819-66.550 <0.001 TG (mmol/L) -1.203 0.300 -2.584- -2.245 <0.001 HDL (mmol/L) 0.128 1.136 1.117-1.381 <0.001 LDL (mmol/L) -2.549 0.078 -2.609- -2.368 <0.001 Apolipoprotein A (g/L) -8.591 <0.001 -0.915- -0.871 <0.001 Apolipoprotein B (g/L) -0.237 0.789 -0.282 - -0.163 <0.001 Lipoprotein-a (mg/L) -0.002 0.998 -81.122- -55.271 <0.001 HB (g/L) -0.045 0.956 -15.643- -14.032 <0.001 Binary logistic regression analysis. P<0.05 denoted statistical significance. B: Coefficient of regression; OR: Odds ratio; CI: Confidence interval; OM: Ocular metastasis; ALP: Alkaline phosphatase; TG: Triglyceride; HDL: High-density lipoprotein; LDL: Low-density lipoprotein; HB: Hemoglobin. 2270 in BC, there was no material difference in BC based on alcohol consumption [50] . Research has shown that exposure to alcohol induces the expression of aldehyde dehydrogenase 2 (ALDH2), which stabilizes PD-L1 protein expression by physically interacting with the intracellular portion of PD-L1 and inhibiting proteasome dependent degradation mediated by the E3 ubiquitin ligase speckle type POZ protein [51] . Importantly, inhibiting ALDH2 reduces the PD-L1 protein in cells and promotes the infiltration of tumor infiltrating T cells. These findings highlight the crucial role of ALDH2 in promoting alcohol mediated tumor escape from immune surveillance and facilitating tumor progression. Epidemiological evidence suggests that excessive alcohol consumption is associated with immune suppression, thereby eliminating immune surveillance against tumor formation. According to reports, alcohol can impair the function and activation of T cells, and induce T cell apoptosis. In addition, it was found that ALDH2 can promote the stability of PD-L1 protein. Importantly, it has been demonstrated that the combination of ALDH2 inhibition and PD-1/PD-L1 checkpoint inhibitors can enhance the anti- tumor activity of effector immune cells. In summary, the research findings indicate that alcohol consumption can induce ALDH2 and subsequently upregulate PD-L1 expression, thereby sparing it from immune surveillance [52] . Researchers have found that alcohol has always had harmful effects on patients. Gastric cancer patients who drink excessively are more likely to have high levels of BRF1 expression and MPO positive inflammatory cell filtration. Alcoholics are more likely to experience abnormal range of BRCA1 in non-tumor tissues. Previous studies have found a similar association between BRF1 levels and alcohol intake in patients with BC [53] and liver cancer [54] . In addition, the tumor marker AFP is also elevated in long-term heavy drinkers [55] , which may be due to the continuous repair of liver cells caused by the stimulation of alcohol on liver cells. It is known that alcohol can cause adverse health effects due to the presence of ethanol, which is carcinogenic to humans and can cause several cancers. Studies show that even moderate consumption of alcohol (drink once a day) can cause adverse health effects due to the presence of ethanol, which is carcinogenic to humans and can lead to multiple types of Table 5 Cut-off value, sensitivity, specificity, and AUC of single risk factors for the prediction of OM in menopausal female breast cancer patients Factor Cut-off value Sensitivity (%) Specificity (%) AUC P CA-125 19.30 81.82 79.70 0.808 <0.001 CA-153 61.35 95.45 97.38 0.973 <0.001 Apolipoprotein A 1.12 77.27 95.67 0.896 <0.001 CA-125 +CA-153 - 95.45 96.84 0.973 <0.001 CA-125+apolipoprotein A - 77.27 95.34 0.896 <0.001 CA-153 +apolipoprotein A - 81.82 99.02 0.927 <0.001 CA-125+CA-153 +apolipoprotein A - 81.82 98.87 0.918 <0.001 Sensitivity and specificity were acquired at the cut-off value. P<0.05 denoted statistical significance. AUC: Area under the curve. Table 6 Risk factors for metastases of breast cancer Author Year Histopathological type Metastatic sites Risk factor da Silva et al[31] 2016 Invasive ductal carcinoma Axillary lymph node Age Zhou et al[32] 2017 Triple-negative carcinoma Lymph node ANXA3 Li et al[33] 2017 NS Bone Marrow adiposity Wang et al[34] 2017 Invasive carcinoma Lymph node ECT2 Pestalozzi et al[35] 2008 HER2-positive carcinoma CNS Negative steroid receptor Takalkar et al[36] 2016 Invasive ductal carcinoma NS Increasing age, low parity and obesity Altundag et al[37] 2007 Invasive ductal carcinoma CNS Lung metastasis Zhang et al[38] 2013 Invasive ductal carcinoma Axillary lymph node CCR5 Friesenhengst et al[39] 2018 Ductal carcinoma Lymph node CYP19A1 Salamanna et al[40] 2018 NS Bone Estrogen Coleman[41]] 2002 NS Bone N-telopeptide and C-telopeptide Lei et al[42] 2017 MBC Axillary lymph node PR Cummings et al[43] 2014 NS Liver Age<49y ANXA3: Annexin A3; ECT2: Epithelial cell transforming sequence 2; CNS: Central nervous system; CCR5: Investigate chemotactic factor receptor 5; CYP19A1: A kind of aromatase; MBC: Mucinous breast cancer; PR: Progesterone receptor; NS: Not specific. Risk factors of breast cancer in ocular metastasis 2271 Int J Ophthalmol, Vol. 17, No. 12, Dec. 18, 2024 www.ijo.cn Tel: 8629-82245172 8629-82210956 Email: [email protected] cancers (oral cavity, pharynx, larynx). Thus, based on the study of Scoccianti et al [14] , we conducted a single-center trial at our hospital using the standard for drinking as more than 15 g per day. We concluded that drinking was associated with OM in BC. Moreover, most cancer-associated deaths occur due to metastasis [56] , distant metastases of BC usually occur several years after the primary BC [15] . In addition to distant metastases occurring in the bone, lung, and liver, BC can spread almost anywhere in the body, including the eyes (only 3%–10%) [50] and pituitary gland [57] . Intraorbital metastases of BC are rarely diagnosed, even though pathological reports suggest an incidence of up to 30% [50] . However, once OM occurs, the prognosis of BC is poor. In the study of Demirci et al [17] , 93% of cases, in which patients presenting with visual symptoms due to uveal metastases from BC, the prognosis was unfavorable, with survival rates of 65% and 24% after one year and five years of follow-up, respectively. BC may affect the eye and orbit by metastatic neoplastic infiltration through blood and lymph; the uvea is the most common site of presentation [58] . In addition, most metastatic orbital tumors originate from the lung, followed by the breast, liver, adrenal gland, and stomach. Furthermore, OM from BC affects female patients alone [59] . Reports have also shown that adenocarcinoma of the breast can manifest as OM [60] , and at other times, it is indicative of nonpalpable primary breast carcinoma [61] . Dieing et al [16] reported two cases of intraorbital extraocular metastases of BC. Both patients had been diagnosed with metastatic BC for several years, and both had been stable. Due to often minimal or absent symptoms, diagnosing the condition was challenging [16] . However, once diagnosed, individuals with initial BC, advanced localized conditions, or regional recurrence can achieve a cure through contemporary combined therapies, including surgery, radiation, drug therapy [14] , immunotherapy [4] , and targeted treatments with biological drugs [4] . Patients with metastatic disease are treated with palliative intent to alleviate symptoms and prolong survival [14] . In Germany, the five-year survival rate of BC is 87%, which shows that the chances of a complete recovery are even higher for patients with early BC [14] . Thus, the establishment of standardized diagnostic criteria for OM in BC are necessary. OM can sometimes be missed by conventional diagnostic methods, such as CT and MRI. For example, standard cerebral MRI failed to detect any cerebral or ocular tumors in the first patient of the study of Dieing et al [16] . Currently, better treatment decisions could be made by identifying BC biomarkers-molecules that identify precancerous cells that are likely to progress to invasive cancer [4] through advances in genomics [50] . Although treatment

[4,62] have shown progress, simpler, convenient diagnostic methods with strong feasibility have not been established. Hematological evaluation is a routine diagnostic process for various diseases. Therefore, we were keen to identify a diagnostic indicator, based on our detection of serum biomarkers. We found an interesting phenomenon regarding the HDL concentration in the OM group, which was higher than that in the NOM group (P <0.05); whereas the LDL concentration was lower (P<0.05). Some studies suggest that the relationship between HDL and menopause is complex, because higher HDL-C may indicate dysfunctional HDL metabolism [63] , and lower LDL may be related to early atherosclerosis during menopause [64] . Table 3 shows selected risk factors and various combinations of such factors for the detection of OM in menopausal patients with BC. In the current study, our laboratory conducted an analysis of patient serum samples to quantify the concentrations of ALP, calcium, total cholesterol, CEA, CA-125, CA-199, CA- 153, TG, HDL, LDL, Apo A, Apo B, Lp(a), and HB. Based on previous findings that total cholesterol, TG, Lp(a), and increased Apo B are associated with aging in women and menopause [65-66] ; ALP is a risk factor for bone metastases in lung cancer [67-68] ; and we selected CA-125, CA-153, and Apo A as individual risk factors because calcium and HB are susceptible to other factors (P <0.01, P<0.01, and P <0.01, respectively). AUC, sensitivity, and specificity for each of these biomarkers are presented in Table 5. Furthermore, CA-153 alone is effective for diagnosing OM in BC patients who have undergone menopause based on our findings. With these ROC curves as a guide, it is possible to develop reliable clinical tests. The presence of CA-125, CA-153, and Apo A concentrations higher than 19.30 U/mL, 61.35 U/mL, and 1.12 g/L represent critical blood levels for the presence of OM in BC patients who have reached menopause. Consequently, there are other diagnostic techniques that can be used (e.g., CT and MRI imaging of the eye) to provide more detailed information. Another point that deserves attention is the highest specificity of the combination of CA-153+Apo A (99.02%), which was also accurate in predicting OM. CA153 was initially discovered to be a tumor antigen that can be recognized by two monoclonal antibodies, DF3 and 115D8, simultaneously. Monoclonal antibody DF3 can recognize the core protein of mucin 1 (MUC1 or CD227), while monoclonal antibody 115D8 recognizes a portion of the polysaccharide chain on MUC1. Previous studies have shown that MUC1 can mediate the production of growth factors such as connective tissue growth factor, platelet-derived growth factor-A, and platelet-derived growth factor-B, which can promote the activation of MAPK and PI3K/Akt pathways, enhance the 2272 proliferation and survival ability of tumor cells [69] . MUC1 can also regulate the expression, stability, and activity of hypoxia inducible factor-1 alpha (HIF-1α). HIF-1α can regulate the expression of enzymes in the glycolytic pathway, which is the preferred metabolic pathway for cancer cell proliferation. CA153, as a soluble form of MUC1, also participates in many processes of tumor occurrence and development. In addition, CA153 can reduce the interactions between cells and between cells and matrix, and decrease its adhesion. Meanwhile, overexpression of CA153 can promote the separation of tumor cells from peripheral stromal cells, normal cells, and so on. The serum CA153 level in BC was abnormally elevated, and its level was positively correlated with TNM stage, histological grade, and lymph node metastasis [70] . CA125 is a large transmembrane glycoprotein derived from the epithelial cells of the body cavity (pericardium, pleura, and peritoneum) and Mullerian tubes (fallopian tubes, endometrium, and cervical endometrium). Under normal circumstances, due to the intercellular connections and the blocking effect of the basement membrane, CA125 cannot enter the serum, so CA125 cannot be detected or has a very low concentration in normal human serum [71] . When the tissue undergoes malignant transformation, the synthesized CA125 in the cell concentrates at the edge of the cell, causing depolarization of the local cell membrane and transporting CA125 antigen; Invasive tumor cells can damage tissue structure, and the secretion of CA125 after the disruption of intercellular connections and basement membrane can be released into the bloodstream. Its functions are as follows: under physiological conditions, CA125 forms a polysaccharide rich barrier to protect epithelial cells from pathogen invasion, and under pathological conditions, CA125 can protect cancer cells from surveillance by inhibiting natural killer cells (its potential mechanism may be that the highly glycosylated tandem repeat domain of CA125 can bind to an immunosuppressive protein - galectin-1). CA125 can induce tumor cell movement by reducing the expression of calcium binding protein E and increasing epithelial mesenchymal transition; It can also enhance the invasion ability of tumor cells and promote tumor tissue invasion into the serosa by binding to mesothelin (a glycoprotein expressed by peritoneal mesothelial cells) [72] . As a clinical doctor, it is necessary to understand the appropriate items and latest developments of tumor markers. Therefore, clinical doctors need to constantly learn new knowledge and skills, and understand the latest developments in testing projects. Multidisciplinary collaboration in interpreting tumor markers, mutual understanding between clinical departments and laboratory departments, can better promote the rational application of tumor markers. In addition, it is necessary to understand the impact of the pre- and post testing stages on the application of tumor markers, such as the correlation between the results of many testing items and the physiological state of the patient at the time of blood collection: the whole blood white blood cell count of the same patient may be different in the morning and afternoon [73] , the sex hormone test values may be different during the physiological period and pre physiological period [74] , the antral follicle count and CA125 are related to the menstrual period [75] , and the AFP of pregnant individuals may also be different from usual [76] . Compared with diagnostic methods such as imaging examination and pathological biopsy, tumor marker detection is very convenient and economical, suitable for cancer screening. However, there are numerous tumor markers, and the sensitivity or specificity of a single marker is often low, which cannot meet clinical requirements. In theory and practice, it is advocated to simultaneously measure multiple markers to improve sensitivity and specificity. In addition, tumor markers are not the only basis for tumor diagnosis. In clinical practice, it is necessary to consider other

such as clinical symptoms and imaging examinations comprehensively. The diagnosis of tumors must be based on tissue or cellular pathology. Unlike diagnostic methods such as imaging and biopsy, due to individual differences in patients, specific clinical conditions, and other factors, the analysis of tumor markers needs to be combined with clinical conditions and compared from multiple perspectives in order to draw

and true conclusions. Certain tumor markers can also be abnormally elevated in certain physiological conditions or benign diseases, and attention should be paid to differentiation. Moreover, there are also limitations associated with the current research. There were several problems with the study, including the exclusive evaluation of transient data from the time of primary diagnosis, a small sample size derived from a single medical center, and the absence of tumor classification. If the research sample comes from only one center, it may

in selection bias and cannot represent a wider population or patient group, as patients in a specific center may have specific characteristics or disease spectrum. Geopolitical bias may also occur, as samples from a single center only reflect unique environmental, genetic, or lifestyle factors that may differ in other regions. In addition, large centers may have more medical resources and technology, which may affect the diagnosis, treatment, and prognosis of patients, which may not be available in small or different types of medical centers, resulting in resource limitation bias. Thus, more medical centers need to be included in the sample size in order to conduct a valid study. In addition, previous studies [77] have found that perimenopausal syndrome has an impact on tumor markers, positively correlated with AFP, CA125, CA153, but Risk factors of breast cancer in ocular metastasis 2273 Int J Ophthalmol, Vol. 17, No. 12, Dec. 18, 2024 www.ijo.cn Tel: 8629-82245172 8629-82210956 Email: [email protected] not correlated with CEA. Menopausal status is negatively correlated with CA125. Different treatment plans may also have an impact on tumor markers. These confounding factors may lead to confounding bias. In this study, we balanced confounding factors through random allocation and ensured that cases and controls were similar in certain potential confounding factors through matching. In the future, we will further improve the research plan, limit the perimenopausal time and treatment methods of the research subjects, and use statistical models (such as regression analysis and propensity score analysis) to adjust for the influence of confounding factors, in order to reduce their impact. In conclusion, CA-153 predicts the incidence of OM more accurately than other risk factors, as evidenced by its high sensitivity, specificity, and AUC. CA-153 shows superior predictive value, owing to its high sensitivity, specificity, and AUC, among various risk factors for OM. Menopausal women with BC who drink alcohol are at a greater risk of developing OM. The present findings need to be verified prospectively and high-quality screening, diagnosis, and treatment needs to be provided to all segments of the affected population [78] .

Data Availability: The datasets generated during and/or analysed during the current study are accessible via the PubMed. Upon reasonable request, the corresponding author will make available the datasets generated and/or analyzed as part of this study. All the data generated or analysed during the course of this study are comprehensively contained within this published article (and its supplementary information files). Foundations: Supported by National Natural Science Foundation of China (No.82160195; No.82460203); Jiangxi Key R&D Program of Jiangxi Province (No.20223BBH80014); Science and Technology Project of Jiangxi Province Health Commission of Traditional Chinese Medicine (No.2022B258); Science and Technology Project of Jiangxi Health Commission (No.202210017). Conflicts of Interest: Liu QC, None; Ling Q, None; Zeng YM, None; Chen C, None; Wei H, None; Hu JY, None; Zou J, None; Wang XY, None; Chen X, None; Shao Y, None.

1 Kolak A, Kamińska M, Sygit K, Budny A, Surdyka D, Kukiełka-Budny B, Burdan F. Primary and secondary prevention of breast cancer. Ann Agric Environ Med 2017;24(4):549-553. 2 Ghoncheh M, Pournamdar Z, Salehiniya H. Incidence and mortality and epidemiology of breast cancer in the world. Asian Pac J Cancer Prev 2016;17(S3):43-46. 3 Wilkinson L, Gathani T. Understanding breast cancer as a global health concern. Br J Radiol 2022;95(1130):20211033. 4 Woolston C. Breast cancer: 4 big questions. Nature 2015; 527(7578):S120. 5 Davis SR, Pinkerton J, Santoro N, Simoncini T. Menopause-Biology, consequences, supportive care, and therapeutic options. Cell 2023;186(19):4038-4058. 6 Cohen PA, Brennan A, Marino JL, Saunders CM, Hickey M. Managing menopausal symptoms after breast cancer–a multidisciplinary approach. Maturitas 2017;105:4-7. 7 Collaborative Group on Hormonal Factors in Breast Cancer. Menarche, menopause, and breast cancer risk: individual participant meta-analysis, including 118 964 women with breast cancer from 117 epidemiological studies. Lancet Oncol 2012;13(11):1141-1151. 8 Brown SB, Hankinson SE. Endogenous estrogens and the risk of breast, endometrial, and ovarian cancers. Steroids 2015;99(pt a):8-10. 9 Ferrini K, Ghelfi F, Mannucci R, Titta L. Lifestyle, nutrition and breast cancer: facts and presumptions for consideration. Ecancermedicalscience 2015;9:557. 10 Shield KD, Soerjomataram I, Rehm J. Alcohol use and breast cancer: a critical review. Alcohol Clin Exp Res 2016;40(6):1166-1181. 11 Lewandowska AM, Rudzki M, Rudzki S, Lewandowski T, Laskowska B. Environmental risk factors for cancer - review paper. Ann Agric Environ Med 2019;26(1):1-7. 12 Schwartz AL, de Heer HD, Bea JW. Initiating Exercise Interventions to Promote Wellness in Cancer Patients and Survivors. Oncology (Williston Park) 2017;31(10):711-717. 13 Jatoi I, Benson JR. Management of women with a hereditary predisposition for breast cancer. Future Oncol 2016;12(19):2277-2288. 14 Scoccianti C, Straif K, Romieu I. Recent evidence on alcohol and cancer epidemiology. Future Oncol 2013;9(9):1315-1322. 15 Toguchi M, Matsuki M, Numoto I, Tsurusaki M, Imaoka I, Ishii K, Yamashita R, Inada Y , Monzawa S, Kobayashi H, Murakami T. Imaging of metastases from breast cancer to uncommon sites: a pictorial review. Jpn J Radiol 2016;34(6):400-408. 16 Dieing A, Schulz CO, Schmid P, Roever AC, Lehenbauer-Dehm S, Jehn C, Flath B, Possinger K. Orbital metastases in breast cancer: report of two cases and review of the literature. J Cancer Res Clin Oncol 2004;130(12):745-748. 17 Demirci H, Shields CL, Chao AN, Shields JA. Uveal metastasis from breast cancer in 264 patients. Am J Ophthalmol 2003;136(2):264-271. 18 Lin DF, Shen LS, Luo M, Zhang K, Li JF, Yang Q, Zhu FF, Zhou D, Zheng S, Chen YD, Zhou JJ. Circulating tumor cells: biology and clinical significance. Signal Transduct Target Ther 2021;6(1):404. 19 Geng SK, Fu SM, Zhang HW, Fu YP. Predictive nomogram based on serum tumor markers and clinicopathological features for stratifying lymph node metastasis in breast cancer. BMC Cancer 2022;22(1):1328. 20 Tarighati E, Keivan H, Mahani H. A review of prognostic and predictive biomarkers in breast cancer. Clin Exp Med 2023;23(1):1-16. 21 Seale KN, Tkaczuk KHR. Circulating biomarkers in breast cancer. Clin Breast Cancer 2022;22(3):e319-e331. 22 Li JX, Liu LY , Feng ZW, Wang X, Huang YB, Dai HJ, Zhang LW, Song FF, Wang DZ, Zhang PY , Ma BS, Li HX, Zheng H, Song 2274 FJ, Chen KX. Tumor markers CA15-3, CA125, CEA and breast cancer survival by molecular subtype: a cohort study. Breast Cancer 2020;27(4):621-630. 23 Fogacci F, Di Micoli V , Avagimyan A, Giovannini M, Imbalzano E, Cicero AFG. Assessment of apolipoprotein(a) isoform size using phenotypic and genotypic methods. Int J Mol Sci 2023;24(18):13886. 24 Wang C, Chen S, Zhang R, Chen M, Yang X, He Y , Shangguan Z, Mao Q, Zhang Z, Ying S. Apolipoprotein A-1 downregulation promotes basal-like breast cancer cell proliferation and migration associated with DNA methylation. Oncol Lett 2024;28(1):295. 25 Liu L, Lewandrowski K. Establishing optimal cutoff values for high- sensitivity cardiac troponin algorithms in risk stratification of acute myocardial infarction. Crit Rev Clin Lab Sci 2024;61(1):1-22. 26 Torasawa M, Horinouchi H, Nomura S, Igawa S, Asai M, Ishii H, Wakui H, Ushio R, Asao T, Namba Y , Koyama R, Hayakawa D, Katayama I, Matsuda H, Sasaki S, Takahashi K, Hosomi Y , Naoki K, Ohe Y . Reconsidering the cutoff value for sensitive and refractory relapses in extensive-stage SCLC in the era of immunotherapy. J Thorac Oncol 2024;19(2):325-336. 27 Monaghan TF, Rahman SN, Agudelo CW, Wein AJ, Lazar JM, Everaert K, Dmochowski RR. Foundational statistical principles in medical research: sensitivity, specificity, positive predictive value, and negative predictive value. Medicina 2021;57(5):503. 28 Binney N, Hyde C, Bossuyt PM. On the origin of sensitivity and specificity. Ann Intern Med 2021;174(3):401-407. 29 Çorbacıoğlu ŞK, Aksel G. Receiver operating characteristic curve analysis in diagnostic accuracy studies: a guide to interpreting the area under the curve value. Turk J Emerg Med 2023;23(4):195-198. 30 Muschelli J. ROC and AUC with a binary predictor: a potentially misleading metric. J Classif 2020;37(3):696-708. 31 da Silva BB, Sousa-Esteves FC, Martins RS, Salha CP, Paiva-Melo BN, Moura CS, Alves-Ribeiro FA. Clinical and epidemiological profile of women with breast cancer managed in a public referral hospital in northeastern Brazil. Eur J Gynaecol Oncol 2016;37(6):814-816. 32 Zhou T, Li Y , Yang L, Tang TT, Zhang LN, Shi JJ. Annexin A3 as a prognostic biomarker for breast cancer: a retrospective study. Biomed Res Int 2017;2017:2603685. 33 Li GW, Xu Z, Zhuang A, Chang SX, Hou LM, Chen YS, Polat M, Wu DM. Magnetic resonance spectroscopy-detected change in marrow adiposity is strongly correlated to postmenopausal breast cancer risk. Clin Breast Cancer 2017;17(3):239-244. 34 Wang HK, Liang JF, Zheng HX, Xiao H. Expression and prognostic significance of ECT2 in invasive breast cancer. J Clin Pathol 2018;71(5):442-445. 35 Pestalozzi BC, Francis P, Quinaux E, Dolci S, Azambuja E, Gelber RD, Viale G, Balil A, Andersson M, Nordenskjöld B, Gnant M, Gutierrez J, Láng I, Crown JPA, Piccart-Gebhart M. Is risk of central nervous system (CNS) relapse related to adjuvant taxane treatment in node- positive breast cancer? Results of the CNS substudy in the intergroup phase III BIG 02-98 trial. Ann Oncol 2008;19(11):1837-1841. 36 Takalkar UV , Asegaonkar SB, Kulkarni U, Saraf M, Advani S. Clinicopathological profile of breast cancer patients at a tertiary care hospital in marathwada region of westen India. Asian Pac J Cancer Prev 2016;17(4):2195-2198. 37 Altundag K, Bondy ML, Mirza NQ, Kau SW, Broglio K, Hortobagyi GN, Rivera E. Clinicopathologic characteristics and prognostic factors in 420 metastatic breast cancer patients with central nervous system metastasis. Cancer 2007;110(12):2640-2647. 38 Zhang Y , Meng FY , Li WL, Zhou CX, Guan Z, Fan HY . Association of chemotactic factor receptor 5 gene with breast cancer. Genet Mol Res 2013;12(4):5289-5300. 39 Friesenhengst A, Pribitzer-Winner T, Miedl H, Pröstling K, Schreiber M. Elevated aromatase (CYP19A1) expression is associated with a poor survival of patients with estrogen receptor positive breast cancer. Horm Cancer 2018;9(2):128-138. 40 Salamanna F, Borsari V , Contartese D, Nicoli Aldini N, Fini M. Link between estrogen deficiency osteoporosis and susceptibility to bone metastases: a way towards precision medicine in cancer patients. Breast 2018;41:42-50. 41 Coleman RE. The clinical use of bone resorption markers in patients with malignant bone disease. Cancer 2002;94(10):2521-2533. 42 Lei L, Chen ZZ, Zheng YB, Chen B, Wang X, Wang XJ. Clinical features and risk factors for recurrence in mucinous breast cancer. Zhonghua Zhong Liu Za Zhi 2017;39(4):274-279. 43 Cummings MC, Simpson PT, Reid LE, Jayanthan J, Skerman J, Song S, McCart Reed AE, Kutasovic JR, Morey AL, Marquart L, O’Rourke P, Lakhani SR. Metastatic progression of breast cancer: insights from 50y of autopsies. J Pathol 2014;232(1):23-31. 44 Harvie M, Howell A, Evans DG. Can diet and lifestyle prevent breast cancer: what is the evidence? Am Soc Clin Oncol Educ Book 2015:e66-73. 45 Corbex M, Bouzbid S, Boffetta P. Features of breast cancer in developing countries, examples from North-Africa. Eur J Cancer 2014;50(10):1808-1818. 46 DeSantis CE, Ma JM, Goding Sauer A, Newman LA, Jemal A. Breast cancer statistics, 2017,racial disparity in mortality by state. CA Cancer J Clin 2017;67(6):439-448. 47 Wang M, Hu RY , Wang H, Gong WW, Wang CM, Xie KX, Chen ZM, Guo Y , Yu M, Li LM. Age at natural menopause and risk of diabetes in adult women: Findings from the China Kadoorie Biobank study in the Zhejiang area. J Diabetes Investig 2018;9(4):762-768. 48 Ekwueme DU, Allaire BT, Parish WJ, Thomas CC, Poehler D, Guy GP Jr, Aldridge AP, Lahoti SR, Fairley TL, Trogdon JG. Estimation of breast cancer incident cases and medical care costs attributable to alcohol consumption among insured women aged <45y in the U.S. Am J Prev Med 2017;53(3S1). 49 Scoccianti C, Lauby-Secretan B, Bello PY , Chajes V , Romieu I. Female breast cancer and alcohol consumption: a review of the literature. Am J Prev Med 2014;46(3 Suppl 1):S16-S25. Risk factors of breast cancer in ocular metastasis 2275 Int J Ophthalmol, Vol. 17, No. 12, Dec. 18, 2024 www.ijo.cn Tel: 8629-82245172 8629-82210956 Email: [email protected] 50 Merino Bonilla JA, Torres Tabanera M, Ros Mendoza LH. Breast cancer in the 21st century: from early detection to new therapies. Radiologia 2017;59(5):368-379. 51 Rumgay H, Murphy N, Ferrari P, Soerjomataram I. Alcohol and cancer: epidemiology and biological mechanisms. Nutrients 2021;13(9):3173. 52 Macke AJ, Petrosyan A. Alcohol and prostate cancer: time to draw conclusions. Biomolecules 2022;12(3):375. 53 Starek-Świechowicz B, Budziszewska B, Starek A. Alcohol and breast cancer. Pharmacol Rep 2023;75(1):69-84. 54 Mackowiak B, Fu Y , Maccioni L, Gao B. Alcohol-associated liver disease. J Clin Invest 2024;134(3):e176345. 55 Pinto TAM, Saito HPA, Nourani CL, Ataide EC, Boin IFSF, Lourenco GJ, Lima CSP. Clinicopathological aspects and inflammation-immune markers in alcohol and/or hepatitis C virus-induced hepatocellular carcinoma patients treated with sorafenib. Gastroenterology Res 2024;17(1):23-31. 56 Gerstberger S, Jiang QW, Ganesh K. Metastasis. Cell 2023;186: 1564-1579. 57 Magalhães JF, Bacchin RP, Costa PS, Alves GM, Fraige Filho F, Stella LC. Breast cancer metastasis to the pituitary gland. Arq Bras Endocrinol Metabol 2014;58(8):869-872. 58 Amichetti M, Caffo O, Minatel E, Roncadin M, Valli MC, Lozza L, Panizzoni G. Ocular metastases from breast carcinoma: a multicentric retrospective study. Oncol Rep 2000;7(4):761-765. 59 Amemiya T, Hayashida H, Dake Y . Metastatic orbital tumors in Japan: a review of the literature. Ophthalmic Epidemiol 2002;9(1):35-47. 60 Glazer LC, Harris GJ, Simons KB. Orbital metastasis as the presenting sign of adenocarcinoma of the breast. Ophthalmic Plast Reconstr Surg 1991;7(4):252-255. 61 Reeves D, Levine MR, Lash R. Nonpalpable breast carcinoma presenting as orbital infiltration: case presentation and literature review. Ophthalmic Plast Reconstr Surg 2002;18(1):84-88. 62 McCaffery S, Simon EM, Fischbein NJ, Rowley HA, Shimikawa A, Lin S, O’Brien JM. Three-dimensional high-resolution magnetic resonance imaging of ocular and orbital malignancies. Arch Ophthalmol 2002;120(6):747-754. 63 El Khoudary SR. HDL and the menopause. Curr Opin Lipidol 2017;28(4):328-336. 64 Gentile M, Panico S, Mattiello A, Ubaldi S, Iannuzzo G, de Michele M, Iannuzzi A, Rubba P. Association between small dense LDL and early atherosclerosis in a sample of menopausal women. Clin Chim Acta 2013;426:1-5. 65 Anagnostis P, Stevenson JC, Crook D, Johnston DG, Godsland IF. Effects of gender, age and menopausal status on serum apolipoprotein concentrations. Clin Endocrinol 2016;85(5):733-740. 66 Bruera MG, Benedetto MM, Guido ME, Degano AL, Contin MA. Glial cell response to constant low light exposure in rat retina. Vis Neurosci 2022;39:E005. 67 Lang J, Zhao Q, He Y , Yu X. Bone turnover markers and novel biomarkers in lung cancer bone metastases. Biomarkers 2018;23(6):518-526. 68 Zhang L, Gong ZX. Clinical characteristics and prognostic factors in bone metastases from lung cancer. Med Sci Monit 2017;23:4087-4094. 69 Fan Y , Chen XY , Li HJ. Clinical value of serum biomarkers CA153, CEA, and white blood cells in predicting sentinel lymph node metastasis of breast cancer. Int J Clin Exp Pathol 2020;13(11):2889-2894. 70 Jia L, Li GH, Ma N, Zhang AM, Zhou YL, Ren L, Dong D. Soluble POSTN is a novel biomarker complementing CA153 and CEA for breast cancer diagnosis and metastasis prediction. BMC Cancer 2022;22(1):760. 71 Zhang MH, Cheng SS, Jin Y , Zhao YQ, Wang Y . Roles of CA125 in diagnosis, prediction, and oncogenesis of ovarian cancer. Biochim Biophys Acta BBA Rev Cancer 2021;1875(2):188503. 72 Huo Q, Xu C, Shao Y , Yu Q, Huang L, Liu Y , Bao H. Free CA125 promotes ovarian cancer cell migration and tumor metastasis by binding Mesothelin to reduce DKK1 expression and activate the SGK3/FOXO3 pathway. Int J Biol Sci 2021;17(2):574-588. 73 Eimonte M, Paulauskas H, Daniuseviciute L, Eimantas N, Vitkauskiene A, Dauksaite G, Solianik R, Brazaitis M. Residual effects of short- term whole-body cold-water immersion on the cytokine profile, white blood cell count, and blood markers of stress. Int J Hyperthermia 2021;38(1):696-707. 74 Shen LP, Zhang W, Yuan Y , Zhu WP, Shang AQ. Vaginal microecological characteristics of women in different physiological and pathological period. Front Cell Infect Microbiol 2022;12:959793. 75 Selcuk S, Kucukbas M, Koc N, Cam C, Ozkaya E, Eser A, Karateke A. Tumour markers and histopathologic features of ovarian endometriotic cysts. J Obstet Gynaecol 2021;41(5):763-768. 76 Głowska-Ciemny J, Szmyt K, Kuszerska A, Rzepka R, von Kaisenberg C, Kocyłowski R. Fetal and placental causes of elevated serum alpha- fetoprotein levels in pregnant women. J Clin Med 2024;13(2):466. 77 Matevossian K, Carpinello O. Polycystic ovary syndrome: menopause and malignancy. Clin Obstet Gynecol 2021;64(1):102-109. 78 DeSantis C, Siegel R, Bandi P, Jemal A. Breast cancer statistics, 2011. CA Cancer J Clin 2011;61(6):409-418.