Nerve Bundle Density and Expression of NGF and IL-1β Are Intra-Individually Heterogenous in Subtypes of Endometriosis

Endometriosis is a gynecological disorder associated with local inflammation and neuroproliferation. Increased nerve bundle density has been attributed to increased expression of nerve growth factor (NGF) and interleukin–1β (IL-1β). Immunohistochemical analysis was carried out on 12 patients presenting with all three anatomic subtypes of endometriosis (deep, superficial peritoneal, endometrioma) at surgery, with at least two surgically excised subtypes available for analysis. Immunolocalization for nerve bundle density around endometriosis using protein gene product 9.5 (PGP9.5), as well as NGF and IL-1β histoscores in endometriosis epithelium/stroma, was performed to evaluate differences in scores between lesions and anatomic subtypes per patient. Intra-individual heterogeneity in scores across lesions was assessed using the coefficient of variation (CV). The degree of score variability between subtypes was evaluated using the percentage difference between mean scores from one subtype to another subtype for each marker. PGP9.5 nerve bundle density was heterogenous across multiple subtypes of endometriosis, ranging from 50.0% to 173.2%, where most patients (8/12) showed CV ≥ 100%. The percentage difference in scores showed that PGP9.5 nerve bundle density and NGF and IL-1β expression were heterogenous between anatomic subtypes within the same patient. Based on these observations of intra-individual heterogeneity, we conclude that markers of neuroproliferation in endometriosis should be stratified by anatomic subtype in future studies of clinical correlation.


Introduction
Endometriosis is a common gynecological disorder characterized by the presence of endometrial-like glandular epithelial cells (GECs) and stromal cells (SCs) outside of the uterus, which may present with symptoms of dysmenorrhea, chronic pelvic pain, dyspareunia, and infertility in addition to other co-morbidities [1,2].Endometriosis can be classified into three anatomic subtypes: deep endometriosis (DE), superficial peritoneal (SUP), and endometrioma (OMA).The severity of endometriosis can be described by the #Enzian classification system and can also be described by the revised American Society for Reproductive Medicine classification into four stages based on size of the lesion, anatomic location, and extent of adhesion: Stage I: mild; Stage II: moderate; Stage III: severe; and Stage IV: extensive [3][4][5].
Biomolecules 2024, 14, 583 2 of 13 The extent of disease and severity of pain does not seem to be correlated in endometriosis, and the stage may not provide the most robust explanation of the patients' pain symptoms [6].The concept of neuroproliferation in association with dyspareunia in endometriosis has been described as a quantitative increase in nerve fiber bundles around the endometriotic lesion, which may amplify pain signaling to the central nervous system when contacted [7].The nerve growth factor family of neurotrophins have been implicated in increased local neuroproliferation and pain, specifically with nerve growth factor (NGF) as the primary neurotrophin of interest [8][9][10][11][12][13][14][15][16][17].
A pathway of local neuroproliferation may be triggered or amplified by simultaneous local inflammation.The inflammatory cytokine interleukin-1β, (IL-1β) has been proposed to directly influence NGF and BDNF expression in endometriotic SC, which in turn stimulates nerve bundle growth identified using the pan-neuronal specific ubiquitin carboxyl-terminal hydrolase isoenzyme, protein-gene-product 9.5 (PGP9.5)[16,[18][19][20][21][22][23].Local inflammation may be further amplified by the resulting neuroproliferation, leading to a positive feedback loop between neuroproliferation and pain [7].Recently, studies have begun to explore the IL-1β-NGF pathway to pain in relation to endometriosis phenotypes [18].Previously, we proposed a model of endometriosis-related pain phenotyping based on potential peripheral pain mechanisms, specifically local inflammation and neuroproliferation [5,6].However, studies have produced variable results in correlating local inflammation and neuroproliferation with anatomic subtype and pain symptoms [10,11,14,24].
A factor that may confound the clinical correlation of local neuroproliferation and inflammation in endometriosis is the issue of multiple anatomic subtypes and multiple lesions per subtype in a single patient.In this study, we describe twelve patients undergoing surgery for endometriosis with additional immunohistochemical testing for NGF, IL-1β, and nerve bundle density using PGP9.5.The objective of this study is to characterize the intra-individual heterogeneity of these markers amongst patients with endometriosis, which may guide future clinical correlation studies for neuroproliferation in endometriosis.

Study Description
Twelve patients were selected from a cohort of 122 patients from the BC Centre for Pelvic Pain and Endometriosis that had previously been described in an earlier study that included the methodology for PGP9.5 nerve bundle density (Table 1) [25].This study was approved by the Research Ethics Board of the University of British Columbia (ENDOONC study; REB H11-00536 and H14-03040).Clinical data were collected as part of a linked prospective registry at the center (EPPIC registry, https://clinicaltrials.gov #NCT02911090 (accessed on 6 October 2023), REB H11-02882 and H16-00264).Informed consent was received from all study subjects for the ENDOONC study and EPPIC data registry.
The 12 patients in this study were surgically diagnosed with all three anatomic subtypes at the time of an index surgery that took place between 1 December 2013 and 31 December 2017.Formalin-fixed paraffin-embedded tissue specimens from sites of suspected endometriosis were preserved for pathology at the time of surgery.Samples were screened for tissue quality (i.e., adequate endometriotic glandular epithelial cells (GECs) and stromal cells (SCs)) using hematoxylin and eosin staining prior to selection for analysis.Cases were selected based on the availability of samples from at least two anatomic subtypes eligible for immunolocalization.These 12 patients were selected for a demonstration of intra-individual variation in NGF, IL-1β, and nerve bundle density by PGP9.5 (Figure 1).
PGP9.5 nerve bundle density was calculated as the number of PGP9.5-positive nerve bundles at a 200× magnification divided by the total number of high-powered fields observed (fiber bundles/HPF) (Figure 2).Histoscores were calculated for NGF and IL-1β in HPF fields of endometriosis at a 200× magnification as previously described [26].Briefly, the intensity of NGF and IL-1β immunostaining was categorized (0 = negative; 1 = weak; 2 = moderate; 3 = strong) in glandular epithelial cells and stromal cells, and the percentage of stained cells in each of the 4 categories was visually estimated for the specific cell type (epithelial or stromal).The histoscore was then calculated for each cell type in each of the three random fields as follows: Histoscores of each sample were calculated as the mean of the histoscores from the three random scored fields.
2 × %     + 3 × %     Histoscores of each sample were calculated as the mean of the histoscores from the three random scored fields.

Statistical Analysis
Overall, five variables were considered: PGP9.5 nerve bundle density around endometriosis, NGF histoscores in endometriosis GEC and SC, and IL−1β histoscores in endometriosis GEC and SC.These variables were examined across anatomic subtypes within each patient and presented as the median and interquartile range, with intra-individual heterogeneity displayed by the coefficient of variation (mean divided by standard

Statistical Analysis
Overall, five variables were considered: PGP9.5 nerve bundle density around endometriosis, NGF histoscores in endometriosis GEC and SC, and IL-1β histoscores in endometriosis GEC and SC.These variables were examined across anatomic subtypes within each patient and presented as the median and interquartile range, with intra-individual heterogeneity displayed by the coefficient of variation (mean divided by standard deviation).As well, PGP9.5 nerve bundle density and NGF and IL-1β histoscores, were compared between anatomic subtypes within the same patient.The relative magnitude of difference between subtypes within each patient for each marker was calculated as follows: Histoscore avg × 100% For patients with more than one lesion for an anatomic subtype (e.g., DE), the average nerve density and histoscore were used.The analysis was performed using Microsoft Excel 2019 (Microsoft Corporation, Redmond, WA, USA), IBM SPSS 28.0 (IBM Corporation, Armonk, NY, USA) and GraphPad Prism 9 software (GraphPad Software, San Diego, CA, USA).

Intra-Individual Variation in Nerve Bundle Density, NGF, and IL-1β
Immunohistochemistry and analysis for protein gene product 9.5 (PGP 9.5) nerve bundle density, NGF GEC, NGF SC, IL-1β GEC, and IL-1β SC were performed in the following lesions across the twelve patients (Table 2, Figure S1).

Nerve Bundle Density and Expression of NGF and IL-1β Vary between Anatomic Subtypes
The mean difference in scores between anatomic subtypes was used to evaluate the degree of variation for PGP9.5 nerve bundle density and for NGF and IL-1β expression.The percentage difference (PD) in scores was used to determine the relative magnitude of the differences in mean scores between anatomic subtypes.

Discussion
In this study, we present the intra-individual heterogeneity in PGP9.5 nerve bundle density and associated biomarkers of neuroproliferation (NGF, IL-1β), amongst patients who had all three anatomic subtypes of endometriosis at surgery and where at least two subtypes were available for analysis.Coefficients of variation (CV) for PGP9.5 nerve bundle density and histoscores for the other biomarkers were examined in each patient.Most CVs were less than 100% (i.e., standard deviation less than mean), but the CV was highest for PGP9.5 nerve bundle density, being at times higher than 100%.For PGP9.5 nerve bundle density and the other biomarker histoscores, there were wide differences in terms of the relative expression levels between anatomic subtypes within the same patient.
The lower CV for NGF GEC, NGF SC, IL-1β GEC, and IL-1β SC (Table 3) could suggest that it may be plausible to sample one lesion in a patient as a reflection of expression for the patient.However, there were differences in level of expression between each anatomic subtypes in the same patient (Figures 2-4).Therefore, it is recommended that each anatomic subtype be sampled separately within a patient, as expression in one subtype cannot be assumed to reflect expression in another subtype.
These observations may guide future studies attempting a clinical correlation of PGP9.5 nerve bundle density and associated neuroproliferative biomarkers.In a patient with multiple anatomic subtypes present, it is not possible to correlate one anatomic subtype to pain symptoms.Instead, all available anatomic subtypes should be sampled per patient.For statistical analyses, we propose that correlations with pain severity be carried out by anatomic subtype.For example, in a cohort, the PGP9.5 nerve bundle density amongst DE lesions in the cohort can be analyzed for an association with deep dyspareunia; then, the PGP9.5 nerve bundle density amongst SUP lesions and the OMA lesions can be studied separately for associations with deep dyspareunia.This would reflect three overlapping non-mutually exclusive sub-cohorts within the total cohort, since each patient can have more than one anatomic subtype.
Another observation in this study is the complex relationship between PGP9.5 nerve bundle density and NGF and IL-1β histoscores in each patient.While these variables have been found to be correlated in prior studies [11,18,19], there remains irregularity with certain biomarkers being higher in one subtype and other biomarkers being higher in another subtype, within the same patient.In other words, patterns observed for NGF cannot be extrapolated to IL-1β, and vice versa.Therefore, we recommend that each biomarker be examined separately in future studies.As well, there are multiple other factors to be involved, including other cells in the endometriosis microenvironment (e.g., mast cells) and other neuroproliferative factors (e.g., BDNF and Trk receptors) that can confound these correlations [14,27].
A strength of this study is an in-depth look at the intra-individual variation in markers of local neuroproliferation, including across anatomic subtypes, which would not be possible in studies that only sample one lesion or anatomic subtype per patient [10,[12][13][14][15]19,21,28].The limitations are the sample size, such that descriptions are provided but statistical analyses of observed trends and correlations to patient-reported pain scores were not possible.We did not have sufficient cases with multiple lesions of each subtype (e.g., two OMAs) and thus could not examine the issue of heterogeneity within a single subtype in the same patient.
Further research will involve the clinical correlation of PGP9.5 nerve bundle density and associated biomarkers with an adjustment for hormonal treatment.Given that local neuroproliferation is just one of multiple pain generators in endometriosis from peripheral to central [7], this type of analysis will be complex.It will likely be necessary to control for pain comorbidities that are common in endometriosis, such as visceral pain conditions (irritable bowel syndrome and painful bladder syndrome) and somatic pain conditions (abdominal wall myofascial trigger points and pelvic floor myalgia) [29].As such, studies will need to be standardized with rigorous pain phenotyping, and an adequate sample size will be required to control for potential confounders.

Conclusions
This case report highlights the intra-individual heterogeneity in nerve bundle density and NGF and IL-1β expression between anatomic subtypes of endometriosis in patients with greater disease burden.These observations should guide future studies that correlate these factors with clinical presentation.

Figure 3 .
Figure 3.The difference in PGP9.5 nerve bundle density and IL−1β and NGF expression betwee DE and SUP per patient.A difference of >0% or >0 indicates a higher score in DE; a difference <0% or <0 indicates a higher score in SUP.(A) Distribution of difference in PGP9.5 nerve bund density.(B) Distribution of difference in NGF GEC histoscore.(C) Distribution of difference in NG SC histoscore.(D) Distribution of difference in IL−1β GEC histoscore.(E) Distribution of differen in IL−1β SC histoscore.PGP9.5: protein gene product 9.5; NGF: nerve growth factor; IL−1β: inte leukin−1β; GEC: glandular epithelial cells; SC: stromal cells.

Figure 3 .
Figure 3.The difference in PGP9.5 nerve bundle density and IL-1β and NGF expression between DE and SUP per patient.A difference of >0% or >0 indicates a higher score in DE; a difference of <0% or <0 indicates a higher score in SUP.(A) Distribution of difference in PGP9.5 nerve bundle density.(B) Distribution of difference in NGF GEC histoscore.(C) Distribution of difference in NGF SC histoscore.(D) Distribution of difference in IL-1β GEC histoscore.(E) Distribution of difference in IL-1β SC histoscore.PGP9.5: protein gene product 9.5; NGF: nerve growth factor; IL-1β: interleukin-1β; GEC: glandular epithelial cells; SC: stromal cells.

Figure 4 .
Figure 4.The difference in PGP9.5 nerve bundle density and IL−1β and NGF expression between DE and OMA per patient.A difference of >0% or >0 indicates a higher score in DE; a difference o <0% or <0 indicates a higher score in OMA.(A) Distribution of difference in PGP9.5 nerve bundle density.(B) Distribution of difference in NGF GEC histoscore.(C) Distribution of difference in NGF SC histoscore.(D) Distribution of difference in IL−1β GEC histoscore.(E) Distribution of difference

Figure 5 .
Figure 5.The difference in PGP9.5 nerve bundle density and IL-1β and NGF expression between SUP and OMA per patient.A difference of >0% or >0 indicates a higher score in SUP; a difference of <0% or <0 indicates a higher score in OMA.(A) Distribution of difference in PGP9.5 histoscore.(B) Distribution of difference in NGF GEC histoscore.(C) Distribution of difference in NGF SC histoscore.(D) Distribution of difference in IL-1β GEC histoscore.(E) Distribution of difference in IL-1β SC histoscore.PGP9.5: protein gene product 9.5; NGF: nerve growth factor; IL-1β: interleukin-1β; GEC: glandular epithelial cells; SC: stromal cells.

Table 1 .
Patient and sample characteristics describing the findings at intake and at the index surgery.* Deep dyspareunia within 3 months of index surgery: N = 11.

Table 2 .
Anatomic subtype and location of endometriosis selected for immunohistochemistry in patients presenting with all three anatomic subtypes.Cells marked with "N/A" represent samples which were unavailable or had insufficient endometriosis for analysis.R: right; L: left; ns: laterality not specified; DE: deep endometriosis; SUP: superficial peritoneal endometriosis; OMA: endometrioma.