PCDHGC3 hypermethylation as a potential biomarker of intestinal neuroendocrine carcinomas

Neuroendocrine neoplasms (NENs) encompass tumors arising from neuroendocrine cells in various organs, including the gastrointestinal tract, pancreas, adrenal gland, and paraganglia. Despite advancements, accurately predicting the aggressiveness of gastroenteropancreatic (GEP) NENs based solely on pathological data remains challenging, thereby limiting optimal clinical management. Our previous research unveiled a crucial link between hypermethylation of the protocadherin PCDHGC3 gene and neuroendocrine tumors originating from the paraganglia and adrenal medulla. This epigenetic alteration was associated with increased metastatic potential and succinate dehydrogenase complex (SDH) dysfunction. Expanding upon this discovery, the current study explored PCDHGC3 gene methylation within the context of GEP‐NENs in a cohort comprising 34 cases. We uncovered promoter hypermethylation of PCDHGC3 in 29% of GEP‐NENs, with a significantly higher prevalence in gastrointestinal (GI) neuroendocrine carcinomas (NECs) compared with both pancreatic (Pan) NECs and neuroendocrine tumors (NETs) of GI and Pan origin. Importantly, these findings were validated in one of the largest multi‐center GEP‐NEN cohorts. Mechanistic analysis revealed that PCDHGC3 hypermethylation was not associated with SDH mutations or protein loss, indicating an SDH‐independent epigenetic mechanism. Clinically, PCDHGC3 hypermethylation emerged as a significant prognostic factor, correlating with reduced overall survival rates in both patient cohorts. Significantly, whereas PCDHGC3 hypermethylation exhibited a strong correlation with TP53 somatic mutations, a hallmark of NEC, its predictive value surpassed that of TP53 mutations, with an area under the curve (AUC) of 0.95 (95% CI 0.83–1.0) for discriminating GI‐NECs from GI‐NETs, highlighting its superior predictive performance. In conclusion, our findings position PCDHGC3 methylation status as a promising molecular biomarker for effectively stratifying patients with GI‐NENs. This discovery has the potential to advance patient care by enabling more precise risk assessments and tailored treatment strategies. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

According to the 2022 WHO Classification of Neuroendocrine Neoplasms, GEP-NENs are classified into two main categories: well-differentiated neuroendocrine tumors (GEP-NETs) and poorly differentiated neuroendocrine carcinomas (GEP-NECs) [3].NETs are further categorized as G1, G2, and G3 based on proliferation rate and Ki67 index, whereas NECs are inherently high grade with a high proliferation rate.
Clinically, distinguishing between GEP-NECs and GEP-NETs is crucial for accurate prognostication and optimal management of patients [4][5][6][7].The WHO Classification of Endocrine and Neuroendocrine Tumors (2022) highlights TP53 and RB1 mutations as primary molecular markers for NEC.Nevertheless, there is a possibility of these mutations being present in a small proportion of G3 NETs as well [8].MEN1, DAXX, and ATRX are the most frequently mutated genes in NETs [9], although more recent data suggest that their occurrence is lower than expected [10].These findings indicate that NETs and NECs represent distinct malignancies on the molecular level, and that additional molecular characteristics may be used to differentiate and classify NECs from NETs when morphology is not sufficient.
Recent studies suggested that several adhesion molecules may play a key role in GEP-NEN tumorigenesis, although their involvement in tumor progression is less understood.For example, loss of E-cadherin expression has been identified as a key step in the development of Pan-NENs [11,12].Cadherin-17 has also been shown to be involved in the proliferation and invasion of Pan-NENs [13].Meanwhile, the role of cadherin-6 is still being explored, with preliminary evidence suggesting that it may promote tumor growth and invasion in GI-NENs [14,15].The functions of other cadherins, such as the protocadherins, in GEP-NENs have not been previously explored.
Clustered protocadherins (cPCDHs) are cell adhesion molecules that belong to the cadherin family of adhesion proteins.They consist of 58 cell surface homophilic-adhesion molecules organized into three gene subclusters named alpha, beta, and gamma: PCDHA@, PCDHB@, and PCDHG@, respectively, located on human chromosome 5q31 [16].The expression of cPCDHs is tightly regulated by complex mechanisms that involve stochastic promoter choice and DNA methylation [17].These molecules are primarily expressed in the central nervous system, where they play crucial roles in various neurobiological processes [18].However, some other tissues also maintain cPCDH.
Dysregulation of PCDH expression has been linked to several types of cancer, highlighting the broader relationship between cadherin-mediated cell adhesion and oncogenesis [19][20][21][22][23][24][25].Our previous research revealed that PCDHGC3, a member of the PCDHG family, is silenced through epigenetic mechanisms and may function as a tumor suppressor gene in paraganglioma and pheochromocytoma [25].Its involvement in tumor progression has also been observed in colorectal cancer [21].We have demonstrated that PCDHGC3 has the potential to serve as a biomarker for identifying individuals with paragangliomas and pheochromocytomas carrying mutations in the succinate dehydrogenase B (SDHB) gene and having an increased risk of developing metastasis.However, the role of PCDHGC3 in cancer, apart from colorectal cancer and paragangliomas or pheochromocytomas, remains largely unexplored.Therefore, in this current study, we aimed to expand upon previous findings by investigating PCDHGC3 methylation in GEP-NENs.Our findings indicate that hypermethylation of PCDHGC3 is present in GEP-NECs and is associated with a decreased overall survival rate.These results underscore the potential significance of investigating epigenetic alterations in neuroendocrine tumors and offer possibilities for a novel biomarker in the context of GEP-NENs.

Tumor samples
Tumor tissues were obtained from 34 patients with GEP-NENs, diagnosed and treated between 2003 and 2017 at the Hospital Universitario Central de Asturias (Spain).Tumor samples included 34 primary tumors.In 12 cases, adjacent non-tumoral samples were available.Informed consent was obtained from each patient and the study was approved by the ethical committee of the hospital.The methods were carried out in accordance with the approved guidelines and the principles expressed in the Declaration of Helsinki.Clinical data were collected from patients' medical reports.Every tumor sample was reviewed by two qualified pathologists.Selected cases were studied applying tumor grading (G) according to the WHO classification of neuroendocrine neoplasms [3] and tumor staging (TNM) according to the Union for International Cancer Control/American Joint Committee on Cancer (UICC/AJCC), eighth edition [26].

Immunohistochemistry
FFPE human tumor tissue blocks were sectioned into 4-μm slices and collected on poly-L-lysine-coated slides.To deparaffinize, rehydrate, and retrieve antigens, a high pH EnVision™ FLEX target retrieval solution was used for 20 min at 95 C in a Dako PT link platform (Dako Denmark A/S, Glostrup, Denmark).Staining was performed using the Dako EnVision™ (Dako Denmark A/S) FLEX detection system with primary antibody against SDHB (rabbit anti-SDHB polyclonal, HPA002868, diluted 1:500; Sigma-Aldrich, St Louis, MO, USA) or p53 PCDHGC3 hypermethylation in neuroendocrine carcinomas (FLEX Monoclonal Mouse Anti-Human p53 Protein Clone DO-7, Ready-to-Use; Agilent Dako, Santa Clara, CA, USA).To reduce assessment variability, immunohistochemistry for p53 was categorized as either 'pathogenic' (suggestive of TP53 mutations) or 'non-pathogenic' (suggestive of wild-type TP53).More precisely, staining was considered 'pathogenic' in cases of negative or widespread overexpression in most cells, while sporadically weakly stained cells were interpreted as 'non-pathogenic' [27,28].

DNA methylation analysis
The DNA methylation level of CpGs in the PCDHGC3 gene was evaluated using bisulfite DNA modification, DNA amplification, and pyrosequencing.The DNA from tumor and normal tissues was extracted using the QIAamp DNA Kit (QIAGEN, Hilden, Germany).Bisulfite modification of the samples was performed using the EZ DNA Methylation-Gold™ Kit (Zymo Research, Irvine, CA, USA).Amplification of the region of interest was conducted with specific primers (5'-GGGATGAGGTAGAGATTGAATAG-3'; 5'-CCTCC AAACCTCTAAAACCATCTCA-3').Pyrosequencing was carried out using the PyroMark Q24 Advanced System ® (QIAGEN) with a specific primer (5'-GAGGTAGAGATTGAATAGT-3').Primers were designed using the PyroMark assay designer (QIAGEN), focusing on the promoter region of the PCDHGC3 gene TSS200 = 0-200 bases upstream of the transcription start site.
For data validation, we used a GEP-NEN cohort that had been previously published and analyzed using the Infinium MethylationEPIC BeadChip (Illumina, San Diego, CA, USA) [31].We used Illumina GenomeStudio software (version 2011.1) and retrieved AVG beta values for each CpG site, which ranged from 0 (unmethylated) to 1 (methylated).Our focus was on the promoter region of PCDHGC3, defined here as the genomic region located 200 bases upstream of the transcription start site of PCDHGC3.

Statistical analyses
Statistical analyses were performed using R version 3.5.2(R Foundation for Statistical Computing, Vienna, Austria).ROC curves were used to evaluate the ability of the diagnostic test to distinguish between NETs and NECs.ROC curves were constructed by plotting the true-positive rate (sensitivity) against the false-positive rate (specificity) across various threshold values of the test results.The area under the ROC curve (AUC) was computed as a measure of the overall discriminative capacity of the test.Statistical analyses for the impact of PCDHGC3 de novo methylation on overall survival were performed using Kaplan-Meier analysis (log-rank analysis for statistical significance).We defined overall survival as the time that elapsed from the date of diagnosis to the date of death from any cause or last contact, whichever occurred first.p < 0.05 was defined as statistically significant.
Interestingly, our study unveiled significant differences in the PCDHGC3 methylation levels between NET and NEC.Specifically, PCDHGC3 methylation was notably more prevalent in NEC cases, with 9 out of 14 cases (64%) exhibiting hypermethylation, than in NET cases, with only 1 out of 20 (5%) cases displaying hypermethylation ( p < 0.0001).Further stratification by primary site revealed that this methylation pattern was present in 9 out of 19 (47%) GI-NENs and 1 out of 15 (6.6%)Pan-NENs (p = 0.0009) (Figure 1 and Table 1).Furthermore, our analysis within the subset of GI-NEC cases revealed no preferential hypermethylation across different anatomical locations, encompassing the stomach, colon, or ileum.In MINENs, PCDHGC3 hypermethylation was detected in two of the three tumors.The molecular-clinical associations remained consistent when these tumors were excluded from the analysis.
No relationship was observed between PCDHGC3 hypermethylation levels and sex, tumor size, or lymph node metastasis (Table 1).While PCDHGC3 hypermethylation demonstrated a significant association with distant metastases (p = 0.024), the analysis yielded  PCDHGC3 hypermethylation in neuroendocrine carcinomas 421 no statistical significance when confined to NEC or NET cases (p = 0.5 and p = 0.437, respectively).

Validation of de novo hypermethylation of PCDHGC3 in GI-NECs
Significantly, our findings underwent independent validation using a previously reported large-scale cohort that included 23 GI-NECs and 40 Pan-NENs (comprising 28 NET and 12 NEC cases).The data confirmed the prevailing presence of PCDHGC3 hypermethylation (with beta values exceeding 40%) in NEC cases (10 out of 35 cases, 29%) in contrast with NET cases (1 out of 28 cases, 3.6%) ( p = 0.009).Additionally, a higher incidence, albeit not statistically significant, was observed in GI-NEC cases (8 out of 23 cases, 34.8%) compared with Pan-NEC cases (2 out of 12, 16%).However, given that our exploratory and validation datasets are enriched in gastrointestinal tumors, it remains uncertain whether PCDHGC3 methylation truly distinguishes between GI-NEC and Pan-NEC cases.
Our prior study documented the methylation-driven upregulation of the SOX2 transcription factor, recognized for its involvement in neuroendocrine differentiation within GEP-NECs.Upon evaluating the hypermethylation status of both SOX2 and PCDHGC3 in the validation cohort, a significant correlation was observed (r = 0.390, p = 0.002) (Figure 2).Nonetheless, it is important to note that not all tumors exhibiting SOX2 methylation displayed concurrent PCDHGC3 methylation, implying the involvement of both shared and distinct epigenetic regulatory mechanisms.

PCDHGC3 methylation is not associated with genetic loss of function of SDH genes
Targeted exome sequencing of SDH genes showed that there were no mutations in SDHB, SDHC, SDHD, SDHA, and SDHAF2 in any of the GEP-NENs.SDH-deficient tumors have also been associated with the epigenetic silencing of the SDHC gene through promoter hypermethylation.However, upon analyzing the DNA promoter methylation of the SDHC gene in tumors

422
T Cubiella et al carrying PCDHGC3 methylation, we found no evidence of SDHC hypermethylation.Additionally, SDHB immunohistochemistry indicated the presence of an intact SDH complex (Figure 3).It is essential to note that the loss of SDHB protein serves as an indicator of inactivating mutations or deletions in any of the SDH genes.Consequently, based on these findings, we can conclude that PCDHGC3 methylation in GEP-NENs is not associated with SDH loss of function, as observed in paraganglioma and pheochromocytoma.
PCDHGC3 methylation is associated with TP53 mutations in GEP-NENs TP53 sequencing analysis identified inactivating mutations in 21% (7 out of 32) of the analyzed tumors.In line with previous reports, TP53 mutations were significantly associated with NEC originating in the GI tract.Specifically, all (7 out of 7) TP53-mutated GEP-NENs were of GI origin, and six of them had been diagnosed as NEC (p = 0.015, Table 1).The data were corroborated by immunohistochemical analysis of p53 (Figure 4).Among the cases with p53 overexpression, all had TP53 non-synonymous mutations, whereas the only case with the absence of p53 immunostaining had a TP53 deletion.
As expected, PCDHGC3 hypermethylation was significantly associated with TP53 mutation ( p = 0.001) or positive p53 immunostaining ( p = 0.034) (Figure 4 and Table 1).This association aligns with the knowledge that TP53 mutation is predominantly found in NEC.Nevertheless, among cases with PCDHGC3 methylation, the absence of TP53 mutations or negative p53 immunostaining was found in 40% and 55% of cases, respectively.In addition, PCDHGC3 hypermethylation was not associated with TP53 mutations in our validation cohort (p = 0.109).Collectively, these data suggest that dysfunction of p53 is not casually related to PCDHGC3 hypermethylation.

Relationships between PCDHGC3 methylation and overall survival
We collected follow-up data from 30 patients with a median follow-up of 55.5 months.Among them, 14 patients (41.2%) died of the disease after a median time of 38.7 ± 35.6 months from diagnosis.Kaplan-Meier survival curve analysis revealed no significant differences in survival time between patients with GI-NENs and Pan-NENs (p = 0.793).Patients with NETs exhibited a more favorable overall survival (OS) compared with those with NEC ( p = 0.037).
Furthermore, our analysis revealed that patients with PCDHGC3 methylation had a significantly shorter OS in comparison to those without methylation (median 106 versus 29.6 months, p = 0.002), as depicted in Figure 5. Similarly, patients with TP53 mutation showed a reduced OS compared with those without mutations (median 110 versus 24 months; p < 0.0001).Exclusion of MINENs from the analysis did not significantly modify the results (p < 0.0001 for both PCDHGC3 hypermethylation and TP53 mutation).Furthermore, these associations remained consistent in the validation cohort as well, with PCDHGC3 hypermethylation and TP53 mutations both being correlated with shorter overall survival ( p = 0.011 and p = 0.012, respectively).
Evaluating the diagnostic potential of PCDHGC3 hypermethylation and TP53 mutations in GEP-NECs versus GEP-NETs Given the higher prevalence of both PCDHGC3 methylation and TP53 mutations in GEP-NECs compared with GEP-NETs, we assessed their predictive value for distinguishing these tumor entities.PCDHGC3 methylation exhibited a sensitivity of 64.3%, a specificity of 95%, and a positive predictive value of 90% in distinguishing GEP-NECs from GEP-NETs.In contrast, TP53 mutations demonstrated a sensitivity of 46.2%, a specificity of 94.7%, and a positive predictive

Discussion
In this study, we uncovered the presence of PCDHGC3 promoter hypermethylation in GEP-NENs.Notably, PCDHGC3 hypermethylation is rarely encountered in GEP-NETs from any location and in pancreatic NEC.These findings may hold significant implications for the diagnosis, prognosis, and treatment of affected patients.
The distinction between NETs and NECs can be a complex and challenging process when relying solely on histopathology [6][7][8].This distinction is of paramount significance because these two tumor types are associated with differing prognoses and treatment benefits.To address this, the WHO classification aims to incorporate molecular parameters.In this context, our study highlights the significance of PCDHGC3 promoter hypermethylation as a defining feature in approximately 40% of all GI-NECs, providing a clear demarcation from NETs.While mutations or inactivation of the TP53 gene have been considered a hallmark of NECs [32], absent in NETs, our data now provide a more valuable tool than TP53 for distinguishing between these entities.Notably, we found that PCDHGC3 hypermethylation outperforms TP53 mutations in effectively differentiating GI-NECs from GI-NETs.This epigenetic modification can enhance the categorization of challenging NEN cases, leading to improved patient management and more informed treatment decisions.However, since the most pressing need is to differentiate between NET G3 and NEC and considering that our cohort includes only one patient with G3-NET, further studies are warranted to fully evaluate the diagnostic potential of this epigenetic trait.
In this study, we observed that PCDHGC3 hypermethylation predominantly occurred in NECs of gastrointestinal origin, while only a minority of Pan-NECs exhibited this alteration.This observation aligns with previous studies implicating aberrant DNA methylation as a crucial mechanism in GI-NEC progression [31,33].However, it is important to acknowledge that this result may be biased due to the higher prevalence of GI-NENs (78%) compared with Pan-NENs (29%) in the patient cohorts.Therefore, further investigations with larger sample sizes and diverse cohorts are warranted to confirm our findings and explore potential tissue-specific differences in PCDHGC3 methylation patterns.
Mechanistically, we found that SDH deficiency is largely absent in GEP-NENs, suggesting that it is not a contributing factor to PCDHGC3 methylation in NEC, in contrast to paraganglioma and pheochromocytoma [25].We also explored the possibility that PCDHGC3 promoter methylation may be part of a broader hypermethylation pattern affecting genes involved in neuroendocrine differentiation.In the validation cohort used in this study, hypermethylation of SOX2, a transcription factor linked to neuroendocrine differentiation, had been found in GEP-NEC cases [31].However, despite the correlation between these two epigenetic alterations, there is no distinct overlap between SOX2 and PCDHGC3 methylation patterns in these samples.Taken together, these results suggest that PCDHGC3 methylation possesses shared features as well as distinctive attributes, setting it apart as a unique epigenetic alteration in GI-NEC.
While our study has limitations due to the relatively small sample size of the discovery cohort, the findings were substantiated by the inclusion of a significantly larger validation cohort.Furthermore, our results align with previous research, including our own, underscoring PCDHGC3 hypermethylation in neuroendocrine carcinomas 425 the significance of PCDHGC3 methylation in cancer progression [22,25,34].We have previously reported the epigenetic silencing of PCDHGC3 in two other types of neuroendocrine tumors, paraganglioma and pheochromocytoma [25].Notably, this epigenetic trait was progressively amplified during the transition from benign to metastatic tumor cells, leading to increased cell proliferation and migration.Furthermore, Dallosso et al have suggested that PCDHGC3 promoter hypermethylation may serve as a pivotal driver in the colorectal adenomacarcinoma transition [22].Significantly, PCDHGC3 methylation has been linked to the activation of druggable target pathways, such as mTOR and WNT signaling [22,35].These collective findings are particularly relevant due to their potential to transform treatment approaches for specific types of cancers.Traditionally, the treatment decisions for GEP-NENs have largely relied on histopathological and clinical features.Our results may contribute to the development of tailored therapies based on the unique epigenetic profile of each GEP-NEN, with the potential to enhance treatment efficacy while minimizing adverse effects.
In conclusion, our study underscores the clinical relevance of PCDHGC3 hypermethylation as a distinguishing feature of GEP-NECs, signaling their more aggressive nature compared with NETs.This insight opens exciting avenues for personalized, molecularly-driven therapies in the challenging landscape of GI-NECs, offering hope for improved outcomes and more effective treatment strategies.

Figure 1 .
Figure 1.PCDHGC3 promoter methylation in GEP-NENs.Graphic representations of the percentages of PCDHGC3 promoter methylation in tumoral (T) and non-tumoral (N) samples (left) or in GEP-NENs, stratified as NET or NEC, and categorized according to the tissue of origin.

Figure 2 .
Figure 2. Validation of PCDHGC3 methylation data.(A) Heatmap representation of the transcription start site (TSS) and exon 1 sequences of PCDHGC3 (left) and the TSS of SOX2 (right).Each column represents a probe set from the validation cohort, and each row represents a sample.(B) Scatterplot depicting the correlation between methylation levels of the PCDHGC3 and SOX2 genes within the validation cohort.Median beta values of each probe situated in the TSS regions of the specified genes were used.Methylation data are displayed on a scale of 0 (no methylation) to 100 (full methylation).

Figure 3 .
Figure 3. Immunohistochemistry for SDHB as a marker of SDHA, SDHB, SDHC, and SDHD gene mutations.Representative immunohistochemical images of SDHB in two GEP-NEN samples.Both samples exhibit granular and intense staining, irrespective of high PCDHGC3 methylation levels (left) or the absence of such methylation (right).Scale bars: 50 μm.

Figure 4 .
Figure 4. Relationship between PCDHGC3 methylation and TP53 mutation.(A) Representative images of p53 immunohistochemistry (a, b, d, f) and hematoxylin staining (c, e) in two independent NEC tumors that carry either a non-synonymous Tyr205Asp TP53 mutation (a-d) or a frameshift Asp48Argfs*76 TP53 mutation (e, f).(B) Bar chart displaying the relationship between TP53 mutations and the presence (met) or absence (unmet) of PCDHGC3 methylation.(C) Characteristics of the cohort of tumors and identified PCDHGC3 methylation status and TP53 somatic mutations.***p < 0.001.

424T
Cubiella et al © 2024 The Authors.The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.www.pathsoc.org

Figure 5 .
Figure 5. Prognostic value of PCDHGC3 methylation and TP53 mutation.Kaplan-Meier curves for overall survival according to levels of PCDHGC3 hypermethylation and TP53 mutation.The PCDHGC3 data were divided as low and high according to their mean values (16.4%).p values were calculated using the Kaplan-Meier test.

Figure 6 .
Figure 6.Receiver operating characteristic (ROC) curve analysis for PCDHGC3 and TP53 in NEC versus NET prediction.(A and B) ROC curves assessing the predictive performance of PCDHGC3 methylation and TP53 mutations for distinguishing between GEP-NETs and GEP-NECs (A) and between GI-NETs and GI-NECs (B).

Table 1 .
Relationships between PCDHGC3 hypermethylation and TP53 mutations and clinicopathological variables.