Reduced Insulin-like Growth Factor Levels in Pre-Menopausal Women with Endometrial Cancer

Abstract

The rising global incidence of uterine cancer has been linked to the escalating prevalence of obesity. Obesity results in insulin resistance which alters the IGF system, thereby driving cancer progression via increased cell proliferation and the inhibition of apoptosis, although the precise mechanisms remain unclear. In a previous study, we compared the levels of IGF1 and IGF2 between fifty endometrial cancer patients (study group) and fifty age-matched non-cancer patients with benign gynaecological conditions (control group), identifying a correlation with menopause. Building on these data, we now report that IGF levels in pre-menopausal women were significantly lower in the study group compared to the control group, a pattern not observed in post-menopausal women. We undertook the receiver operating characteristic (ROC) curve analysis for calculating the potential of IGF1 and IGF2 to effectively distinguish pre-menopausal women with endometrial cancer from those without it. For pre-menopausal women, the area under ROC curve values were 0.966 for IGF1 and 0.955 for IGF2, both with significant p-values, indicating that IGF1 and IGF2 levels have the potential to be diagnostic biomarkers for distinguishing pre-menopausal women with endometrial cancer from those without it. In summary, our findings emphasise the importance of considering menopausal status in the context of IGF level assessments and suggest that IGF1 and IGF2 could play a crucial role in the early diagnosis of endometrial cancer in pre-menopausal women.

1. Introduction

Insulin-like growth factors (IGFs) are potent growth factors with a well-established role in cancer development, as highlighted by numerous epidemiological studies involving colorectal, prostate, breast, liver, and lung cancers [1,2,3,4,5,6,7]. IGFs have been implicated in the development of endometrial cancer, driven by their association with insulin resistance, chronic inflammation, and cancer progression. The dysregulation of the IGF system can occur either by directly enhancing IGF production or by reducing IGF-binding proteins and hence increasing the amount of bio-available free IGF due to prolonged insulin resistance and hyperinsulinemia, referred to as the ‘insulin-IGF hypothesis’ [8]. The IGFs play a pivotal role in the development of various tumours by stimulating cell growth and impeding apoptosis [9,10].

The IGF family encompasses IGF1 and IGF2 polypeptide molecules, alongside their receptors, IGF1 receptor (IGF1R) and IGF2 receptor (IGF2R), as well as six binding proteins known as insulin-like growth factor-binding proteins (IGFBPs) [11]. Typically, more than 90% of the circulating IGFs are bound to IGFBP-3, with less than 1% circulating freely [11]. Additionally, a group of proteases, called IGFBP proteases, are involved in freeing IGF from IGFBPs, as only free IGF can interact with IGF1R. Therefore, IGFBP proteases can be considered a part of the IGF family, as they indirectly regulate IGF activity. IGF1 and IGF2 share about 62% amino acid identity [11]. The downstream effects of the IGF system are mainly mediated through the IGF1R, while the IGF2R solely regulates the availability of circulating IGF2 [10]. Working through various downstream pathways such as phosphatidylinositol-3 kinase/protein kinase (PI3K/Akt) signalling pathway and the rat sarcoma protein/rapidly accelerated fibrosarcoma protein/MAPK-ERK kinase /extra-cellular regulated kinase/(Ras/Raf/MEK/ERK) pathway, the IGFs mediate their proliferative and growth-promoting effects [12]. IGF1 has been recognised for its potent mitogenic and anti-apoptotic roles in humans, promoting tumour growth [11]. The IGF system also contributes to cancer progression through interactions with various factors, including sex steroids, products of tumour suppressor genes, and other growth factors [11]. Specifically, IGF1 has been shown to induce proliferation in a range of cell types, including endometrial and epithelial cells. By acting through the IGF1 receptor (IGF1R), IGF1 stimulates cell cycle growth by enhancing DNA synthesis and promoting the expression of cyclin D1, a key protein that facilitates the transition from the G1 phase to the S phase of the cell cycle [13]. Similarly, IGF2 exhibits anti-apoptotic properties by stimulating the expression of the anti-apoptotic protein Bcl-2 while suppressing the pro-apoptotic protein Bax. This action increases the Bcl-2/Bax heterodimer ratio, thereby regulating apoptosis [14]. Similar to IGF1, IGF2 is recognised for its mitogenic and anti-apoptotic characteristics, further underscoring its significance in cell growth and survival.

However, there is considerable variability among studies regarding the correlation between IGF axis components and endometrial cancer risk. This variability underscores the complexity of this hormonal system and the impact of various factors such as lifestyle, obesity, menopausal status, steroid hormones (oestrogen), growth factors (vascular endothelial growth factor, epidermal growth factor, and fibroblast growth factor), and the expressions of tumour suppressor genes (p53 and BRCA1), among others, on the IGF axis [15].

2. Materials and Methods

2.1. Research Aims and Objectives

This is a prospective observational pilot study, aimed to investigate whether discrepancies in the levels of IGFs between cancer and control groups in relation to menopause could serve as potential diagnostic or risk-prediction markers for endometrial cancer. The primary objectives included comparing the levels of these markers between cancer and control patients, seeking a correlation between the circulating levels of these markers and the menopausal status of the patients, and evaluating the potential of these molecules as predictors of endometrial cancer risk. The secondary objectives included assessing the expression of IGF 1 and 2 and their receptors (IGF1R and IGF2R) in endometrial cancer tissue; seeking a correlation between circulating biomarker levels, measured by ELISA and their expression in endometrial tissue, measured by quantitative polymerase chain reaction (qPCR); and assessing the correlation between the expression of these biomarkers and their receptors in endometrial cancer tissue and the menopausal status of the patient.

2.2. Ethics Approval and Participant Recruitment

Ethics approval for the study was granted by the Health Research Authority and Health and Care Research Wales [Integrated Research Application System (IRAS) ID: 285863; Research Ethics Committee reference: 21/WA/0012; approval date: 27 January 2021]. The populations comprised fifty study patients with endometrial cancer from the gynaecological oncology department, and fifty age-matched control patients with benign gynaecological issues from the benign gynaecology department of the Royal Surrey NHS Foundation Trust.

Demographic data, including age, BMI, and menopausal status, were collected from both groups and presented in depth in our earlier publication [16].

2.3. Sample Collection and Enzyme-Linked Immunosorbent Assay (ELISA)

Details on the blood sample collection and ELISA were as previously published [16]. Briefly, 30 mL of EDTA blood samples were collected from both populations before the commencement of any treatment for either population. The collected blood sample was centrifuged at 2400 g for 10 min to separate the supernatant plasma. Prior to ELISA, an acid–ethanol extraction technique was utilised to release circulating IGF from IGFBP, as IGFs are often bound to IGFBP in plasma. By removing the binding proteins and other interfering substances, the extraction process enhances the sensitivity and specificity of the ELISA, resulting in a more accurate measurement of IGF levels in the plasma sample. The plasma sample was acidified with 37% hydrochloric acid (HCl), which caused the dissociation of IGF from IGFBPs. Thereafter, ethanol was added to the sample, causing proteins (including IGFBPs) to precipitate out of the solution, while IGFs remained in the supernatant. The sample was then centrifuged to separate the precipitated proteins from the supernatant containing the free IGFs. After that, the supernatant was neutralised using 2M Tris buffer (pH 7.6) and reagent diluent (R&D systems, #DY004, NE Minneapolis, MN, USA) before proceeding with the ELISA to ensure that the pH was compatible with the assay conditions. This extraction process is essential to ensure that the ELISA provides an accurate measure of the IGF concentrations in plasma, reflecting the true physiological levels and not being confounded by the presence of IGFBPs.

Following this, ELISA was promptly conducted using kits from R&D Systems (NE Minneapolis, MN, USA), #DY291 for IGF1 (assay range 93.8–6000 pg/mL) and #DY292 for IGF2 (assay range 23.4–1500 pg/mL) adhering to the manufacturer’s instructions. Plasma biomarker concentrations were determined by comparing the absorbance values of each sample against the standard curve generated for each ELISA plate, followed by correction using the appropriate dilution factor. The experiments were carried out in triplicate by the same individual and in a blinded manner to prevent bias.

2.4. Quantitative PCR (qPCR)

Endometrial tumour tissue was collected from 39 patients with endometrial cancer after the initial examination of the hysterectomy specimen by a histopathologist. The RNA expression of IGF 1 and 2 and their receptors were quantified in the endometrial cancer tissues using 5 pooled benign endometrial samples as the calibrator samples. RNA was extracted from the fresh endometrial tissue using the PARIS™ kit (ThermoFischer Scientific, #AM1921, Waltham, MA, USA). The RNA thus extracted was thereafter treated with DNase (Promega, #M6101, Chilworth, Southampton, UK), and cDNA was synthesised with the LunaScript^® RT SuperMix Kit (New England Biolabs, #E3010, Hitchin, UK). RNA amplification and quantitative real-time PCR were performed using Luna^® Universal qPCR Master Mix (New England Biolabs, #M3003) and the Mx3005P Real-Time PCR System (Agilent, Santa Clara, CA, USA). The primers for the qPCR were obtained from Sigma Aldrich (Sofia, Bulgaria). All the qPCR experiments were conducted in triplicate. The results were expressed as fold change relative to the pooled calibrator sample using relative quantification, performed using the 2^−ΔΔCT method [17]. ΔCt values were obtained by comparing each gene’s expression to the housekeeping gene, β-actin. Then, ΔΔCt values were calculated by subtracting the calibrator sample’s ΔCt from each individual sample’s ΔCt. Finally, the fold change in gene expression relative to the reference was calculated using the following formula: fold change = 2^−ΔΔCT.

2.5. Statistical Analysis

Statistical analysis and graphical representations were conducted using the Microsoft Excel (2021 Microsoft Office, version 2409 Build 16.0.18025.20030), GraphPad Prism 9, G*power 3.1.9.7, and R Studio (version 2023.09.0+463) software. A significance level of p < 0.05 was considered statistically significant throughout the study. All the results were normalised by using the formula Y_transformed = log₂(Y + 1).

The study was conducted as an observational pilot study and hence, a total sample number of 50 was decided based on the convenience of recruitment within a short time-period. Nevertheless, a post hoc power calculation was performed using the ‘G-power software’ which indicated that with a moderate effect size (f² = 0.15) and a total sample size of 100, the multivariate linear regression comparing our study group (n = 50) to the control group (n = 50) achieved a high statistical power of 94%. Fischer’s exact test assessed compatibility in the demographic features between the two groups.

A 2-way ANOVA calculation was performed using the functions ‘lm’ and ‘Anova’ from the ‘stats’ and ‘car’ R packages, respectively, to explore the effect of menopausal status on IGF levels between the cancer and control patients.

A receiver operating characteristic (ROC) curve analysis was performed using GraphPad prism to assess the diagnostic capabilities of the pre- or post-menopausal levels of IGFs between the cancer and control patients. This analysis involved plotting the true positive rate (sensitivity) against the false positive rate (1-specificity) at various threshold levels of IGF concentrations, where sensitivity indicates how well the test correctly identifies the cancer patients and specificity indicates the correctly identified control patients. The area under the ROC curve (AUC) was calculated to quantify the overall diagnostic accuracy, with an AUC of 1 indicating perfect discrimination and an AUC of 0.5 representing no diagnostic ability. By comparing the AUCs for the pre- and post-menopausal IGF levels, the analysis will provide insight into the effectiveness of IGFs as biomarkers for cancer detection across different menopausal statuses.

Leave-One-Out Cross-Validation (LOO-CV) was performed alongside the ROC curve to provide a more reliable evaluation of model performance. In LOO-CV, the model is trained on all patients except one, and this process is repeated for each patient. This approach is particularly useful for small datasets, as it maximises the use of available data and provides a less biased estimate of model performance by ensuring every data point is used for both training and testing. The LOO-CV calculations were performed using the ‘pROC’ and ‘glm’ R packages. A logistic regression model was employed to predict the probability of being a cancer patient based on the IGF1 gene expression values within the LOO-CV loop. ROC curves were then generated from the predicted probabilities for the left-out samples, and the AUC was calculated to assess model performance.

The correlation between the blood and tissue levels of the markers was calculated on GraphPad Prism using Spearman’s correlation calculations. The biomarker expression in the tissues was correlated with the menopausal status of the cancer patients to investigate if menopausal status has any bearing on the expression of IGF 1 and 2 and their receptors in the endometrial cancer tissues. This analysis was performed using the functions ‘lm’ and ‘Anova’ from the ‘stats’ and ‘car’ R packages, respectively.

3. Results

3.1. Demographic Characteristics

The demographic characteristics of both groups were previously described [16]. Briefly, the two populations were age-matched by decade, the mean age being 65.7 years in the study population and 66.1 years in the control population. Out of the 50 patients in the cancer group, 39 were menopausal and 11 were pre-menopausal, whereas in the control group, 42 women were menopausal and 8 pre-menopausal. There was no notable difference in the distribution of the menopausal status between the groups (Fisher’s exact test, p = 0.611) (

Table 1. Demographic characteristics of the study and control populations. The study and control populations were compared using Fischer’s exact test, 50 patients in each group Further details were previously described [16].

Parameters				Study Population (n = 50)		Control Population (n = 50)		p-Value
				Number	Percentage	Number	Percentage
Age range (years)			30–39	3	6%	3	6%	1
			40–49	3	6%	3	6%
			50–59	11	22%	11	22%
			60–69	10	20%	10	20%
			70–79	16	32%	16	32%
			80–89	6	12%	6	12%
			90–99	1	2%	1	2%
Menopausal status			Yes	39	78%	42	84%	0.611
			No	11	22%	8	16%

).

3.2. Association between Menopause and IGF Levels in the Two Groups

To investigate the effect of menopausal status on IGF levels between the cancer and control patients, we performed a two-way ANOVA. We observed that in the pre-menopausal women, the levels of IGF1 and IGF2 were significantly higher in the control population (p < 0.0001 and 0.024, respectively). This result is illustrated in Figure 1, which clearly shows that this difference is not present in the post-menopausal women. This finding suggests that IGF levels may be useful in predicting the risk of endometrial cancer in pre-menopausal women.

3.3. Diagnostic Potential of IGF Levels in Pre-Menopausal Women

To evaluate the diagnostic potential of IGFs as a biomarker for separating cancer patients from control patients, an ROC curve analysis was performed. This analysis was performed exclusively for the pre-menopausal women, as the difference in IGF levels between the cancer and control patients was significant only in this group, and not in the post-menopausal women.

The difference in IGF levels between the cancer and control patients in the pre-menopausal women can be demonstrated in the form of a receiver operating characteristic (ROC) curve analysis (Figure 2). AUC for IGF 1 in the pre-menopausal women is 0.966 (p = 0.0007) and for IGF 2 is 0.955 (p = 0.001). These high AUC values indicate that IGF1 and IGF2 have excellent diagnostic accuracy for distinguishing between cancer and control patients in pre-menopausal women. The low p-values suggest that these findings are statistically significant, meaning the observed differences in IGF levels are unlikely due to chance.

The small sample sizes for the cancer and control groups among the pre-menopausal women limit the robustness of the initial ROC curve analysis. To address this limitation, we performed Leave-One-Out Cross-Validation (LOO-CV) combined with the ROC curve analysis. LOO-CV was selected to maximise the use of the available data (n = 19, combining both the cancer and control patients) and provide an unbiased estimate of model performance.

The LOO-CV model was used iteratively, training on 18 patients and testing on the left-out patient. ROC curves were generated from the predicted probabilities of being a cancer patient for the left-out samples, and the AUC was calculated to assess the model performance.

The ROC curve produced through LOO-CV showed good discrimination between the cancer and control groups, with an AUC of 0.864 for IGF1 and 0.852 for IGF2. These values indicate that the model has an 86.4% and 85.2% probability of correctly classifying a randomly chosen patient as cancer or non-cancer based on IGF1 and IGF2 values, respectively.

3.4. Comparison between IGF Expression in Circulation (ELISA) and in Tissues (qPCR)

The study compared the mRNA expression of the IGFs in tissue samples with their levels in plasma to investigate potential correlations. It was noted that IGF1 expression in the cancerous endometrial tissue was about half that in the control endometrium, while IGF2 expression was 1.3 times higher in the cancer tissue compared to the control. However, the baseline plasma levels of IGF1 and IGF2 had demonstrated no significant differences between the cancer patients and the control group (Figure 3). This indicates no direct relationship between the plasma and tissue levels of IGF1 and IGF2. Indeed, on performing Pearson correlation studies, no significant correlation was discovered between the circulating levels of the IGFs and their tissue mRNA expression (Figure 4A).

However, on comparing the circulating levels of the IGFs with the mRNA expression of their receptors in the endometrial cancer tissues using Pearson’s correlation calculations, a significant negative correlation was identified between IGF1R levels in endometrial cancer tissue and plasma IGF1, correlation coefficient r = −0.4 (p = 0.046), and a non-significant negative correlation with plasma IGF2, correlation of r = −0.3 (p = 0.075) (Figure 4B). This suggests a potential clinical significance, indicating that higher tissue IGF1R levels might be associated with lower plasma IGF1 and IGF2 levels and vice versa.

Pearson correlation calculations have been performed and the numbers in the boxes denote Pearson’s r values. The red to the blue end of the scale illustrates a strong negative (r = −1) to strong positive (r = +1) correlation with white indicating no correlation (r = 0).

3.5. Comparison between IGF and IGF Receptor Expression in Endometrial Cancer Tissues (qPCR) and Association with Menopausal Status

We explored the relationship between the expression of IGFs in the endometrial cancer tissue and the menopausal status of the endometrial cancer patients. However, it did not reveal any significant associations, IGF1 (p = 0.572) and IGF2 (p = 0.850). Interestingly, IGF1R expression in the endometrial cancer tissues demonstrated a significant inverse relationship with menopause (p = 0.019), whereby the menopausal women had lower expression of IGF1R in the endometrial cancer tissue than the pre-menopausal women. No such relationship was noted with IGF2R expression (p = 0.618) (Figure 5). Hence, this relationship between the IGF1R expression in the tissues with the menopausal status further substantiates the above finding that circulating IGF levels have a negative association with the tissue IGF1R expression.

X-axis—menopausal status; Y-axis—log₂ [(Fold change/expression of marker) +1]. The 25th and 75th percentiles are represented by the lower and upper boundaries of the rectangles, respectively, while the median is indicated by the horizontal line inside the rectangles. The whiskers extend from the box denoting the minimum and maximum values. The small circles in the plots indicate outliers i.e. observed data points that fall above or below the end of the whiskers.

4. Discussion

Insulin resistance has been inexplicably linked to endometrial cancer [18]. Insulin resistance leads to raised IGF levels due to the structural similarities between insulin and IGFs, and the IGFs function both as a circulating hormone, mediating overall growth, development, and metabolism, and as a local tissue growth factor, encouraging cellular growth, differentiation, and apoptosis, which are important mechanisms by which they can lead to the development of endometrial cancer [19,20].

Our study unveiled intriguing insights into the interplay between both IGF levels and endometrial cancer in relation to menopausal status. A significantly lower level of IGF is noted in the pre-menopausal women among the endometrial cancer population compared to the control group. This pattern was, however, not observed in the post-menopausal women. This suggested that endometrial cancer might exert an influence on IGF levels, particularly in pre-menopausal women. For IGF1 in the pre-menopausal women, an AUC of 0.966 suggests excellent discriminatory ability between the cancer and control groups, with a statistically significant p-value of 0.0007. Similarly, for IGF2, an AUC of 0.955 indicates very good discriminatory ability, also with a statistically significant p-value of 0.001. Thus, these AUC values indicate that both IGF1 and IGF2 levels have strong potential as diagnostic biomarkers for distinguishing between the pre-menopausal women with endometrial cancer and those without it. However, the small size of our study population—11 pre-menopausal women with cancer and 8 controls—limits the generalizability of our findings. To enhance the robustness of the ROC model, we performed Leave-One-Out Cross-Validation (LOO-CV), which produced AUCs of 0.864 for IGF1 and 0.852 for IGF2, reinforcing the potential of these biomarkers for distinguishing between cancer and control groups. Despite the small sample size, the use of LOO-CV ensures a reliable and unbiased estimate of model performance, minimising the risk of overly optimistic results.

Importantly, our findings are notable because, to the best of our knowledge, the potential of IGF levels to predict endometrial cancer risk in pre-menopausal women has not been previously explored. Establishing a threshold below which IGF levels indicate a high risk of endometrial cancer could be invaluable for diagnostic purposes, particularly in pre- or peri-menopausal women.

Further validation in larger, independent cohorts is necessary to confirm these findings. Identifying a predictive threshold for low IGF levels in pre-menopausal women could also streamline monitoring practices for abnormal uterine bleeding in primary care settings. Additionally, large-scale, multi-centre, multi-ethnic longitudinal studies are needed to explore IGF levels as diagnostic markers for endometrial cancer. Our study primarily involved Caucasian women, and while some research suggests that serum IGF1 levels may be influenced by ethnicity, there is no consensus on this matter yet.

Although prior studies have examined the role of IGFs in endometrial cancer, particularly in relation to post-menopausal status, no significant associations have been reported for pre-menopausal women [21,22]. Therefore, to the best of our knowledge, our study represents a novel discovery that warrants further investigation in larger populations.

We explored further the expression of IGF by qPCR in the endometrial cancer patients to investigate if the tissue levels correlated with the circulating plasma levels and whether the tissue level had a better correlation with menopause. We found no correlation between the plasma IGF levels, measured by ELISA and their mRNA expression, in the endometrial cancer tissues. This lack of correlation might indicate that these markers are neither secreted by endometrial cancer tissues nor influenced by their expression or receptor levels in the tissues. Also, while IGF1 and IGF2 show altered expression in the endometrial cancer tissue compared to the control tissue, these changes are not mirrored in the plasma levels where there was not much difference in the expression of IGF 1 and 2 between the cancer and control patients, indicating that tissue-specific alterations in IGF expression may not be detectable through plasma measurements alone. However, both the IGF levels in plasma negatively correlated with IGF1R expression in the endometrial cancer tissue. Both IGF1 and IGF2 act through IGF1R to affect downstream changes in tissues, so there is a potential for the clinical utilisation of this opposing correlation between IGFs in plasma and their receptor IGF1R in the endometrial tissue which needs further corroboration in larger studies. There is a lack of studies that have examined the relationship between the plasma levels and tissue receptor expression of these markers in endometrial tissue, whether benign or cancerous, making it difficult to validate our findings. Notably, the tissue marker expression was unaffected by menopausal status, whereas the circulating levels differed, suggesting that menopausal status may cause metabolic changes that alter circulating IGF levels without affecting tissue expression. However, a significant inverse relationship between IGF1R expression in endometrial cancer tissue and menopausal status, with lower IGF1R expression observed in menopausal women compared to pre-menopausal women aligns with the observed negative correlation between circulating IGF levels and tissue IGF1R expression. This further suggests that IGF1R expression in the endometrial cancer tissues could be responding to the circulating IGF levels in these patients. Consequently, pending further investigation, IGF1R expression in endometrial cancer tissue might serve as a potential biomarker, especially when considered alongside menopausal status.

On a slightly different note, our study population did not include any patients with endometrial hyperplasia among our cohorts. Since endometrial hyperplasia often precedes endometrial cancer, and concurrent endometrial cancer can be present at diagnosis of atypical hyperplasia in >40% of cases [23], it will be interesting to investigate whether IGF levels in pre-menopausal women with endometrial hyperplasia lie on the continuum between non-cancerous and cancerous states. Indeed McCampbell et al. have reported that a significant increase in the expression of IGFIR was noted in biopsies from hyperplastic endometrium compared with benign proliferative endometrium [24]. However, no mention of circulating IGF levels was mentioned in their study and hence this needs further exploration. Also, in addition to regular endometrial evaluations, monitoring IGF levels in pre-menopausal women undergoing conservative management for endometrial hyperplasia could be beneficial. Assessing IGF levels over time may help determine if a decrease in these levels can predict changes in endometrial proliferation status. If a consistent decline in IGF levels during follow-up is found to be indicative of the progression of endometrial hyperplasia to endometrial cancer, these measurements could potentially replace the need for invasive endometrial evaluations during conservative management of endometrial hyperplasia. These insights not only deepen our understanding of the complex relationship between IGFs and endometrial cancer but also provide new directions for future research, potentially leading to improved conservative and non-invasive follow-up techniques for endometrial cancer.

5. Conclusions

In conclusion, our study reveals that pre-menopausal women with endometrial cancer exhibit significantly lower levels of IGF compared to controls, a distinction not observed among post-menopausal women, and there is a high diagnostic potential for both IGF1 and IGF2 in identifying pre-menopausal women with endometrial cancer, although endometrial cancer tissue IGF expression was independent of the circulating levels and the hormonal changes associated with menopause. Hence, identifying a specific threshold of IGFs associated with endometrial cancer in pre-menopausal women could serve as a diagnostic tool for the early diagnosis of endometrial cancer. Furthermore, if a consistent fall in IGF levels from endometrial hyperplasia to cancer development can be established in pre-menopausal women having conservative management of endometrial hyperplasia, it could serve as a valuable adjunct for monitoring such patients, offering a promising direction for future research and clinical practice. Furthermore, a lack of correlation between the plasma IGF levels and their expression in endometrial cancer tissue suggested that IGF alterations in the tumour may not be reflected in circulating levels. However, the negative correlation between the plasma IGF levels and IGF1R expression in cancer tissue, along with the significant inverse relationship between IGF1R expression and menopausal status, indicates a complex interaction where IGF1R in the tissue might respond to circulating IGF levels and could have potential as a biomarker for endometrial cancer, particularly in the context of menopause, though further research is needed to validate this possibility.