RESEARCH
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In-depth Genetic and Molecular Characterization of Unilateral Coexisting Adrenal Cortical Adenoma and Carcinoma in the Context of MEN1 Syndrome
Francesca Cioppi1,2(D . Tommaso Orioli3 . Giulia Cantini2,3,4[D . Tonino Ercolino4,5 . Federica Cioppi5 .
Guillaume Assie6D . Anne JouinotiD . Anna Aurora Dedonno2,3 . Raffaella Santi7D . Ronald R. de Krijger8,9[D . Mario Maggi2,3,4,5(D . Matteo Benelli3(D . Letizia Canu2,3,4,5(D . Gabriella Nesi2,4,7 (D . Michaela Luconi2,3,4[D
Received: 14 June 2025 / Accepted: 9 February 2026 @ The Author(s) 2026
Abstract
Adrenal lesions often occur in patients with multiple endocrine neoplasia type 1 (MEN1), mostly adrenal cortical adeno- mas (ACAs), although the frequency of adrenal cortical carcinomas (ACCs) is higher than in the general population. The coexistence of benign and malignant masses has seldom been documented, leaving open the question of ACC progression from benign forms. We report a comprehensive genetic characterization of three adrenal cortical tumor samples obtained from a familial MEN1 patient, operated for the rapid progression of an initially stable nonfunctional adrenal inciden- taloma. Histologically, the tumor consisted of a small ACA contiguous to a large ACC, which subsequently relapsed. Exome sequencing of ACC, ACA and recurrence evidenced a MEN1 loss of heterozygosity (LOH) in ACC but not in ACA, where, however, a second hit driven by alternative mechanisms could not be excluded. The majority of the ACA variants were found to co-occurred in ACC (n=36/42) and were benign, except for two of unknown significance in KANK1 and REN genes, described as associated with renal cancer. Among variants shared between ACC and its recurrence (n=69), 11 were Tier III, while 2 affecting TP53 and NF1 genes were pathogenic. Bioinformatic clonal evolution analysis identified one clone - characterized by TP53 and NF1 mutations - absent in ACA but present in ACC and recurrence, as well as 2 clones shared between ACA and ACC but lost in the recurrence. In conclusion, comparative Whole Exome Sequencing (WES) analysis of three adrenal tumors in a MEN1 patient suggests a possible relationship between malig- nant and benign lesions occurring in MEN1 patients, without, however, demonstrating any causal adenoma-to-carcinoma progression driven by MEN1 LOH. Overall, these data further suggest an increased risk of MEN1 patients to develop adrenocortical malignancy.
Keywords Whole Exome Sequencing . MEN1 . Clonal evolution . ACC and ACA . Somatic mutations . Molecular profiling
Gabriella Nesi and Michaela Luconi contributed equally to this work.
☒ Gabriella Nesi gabriella.nesi@unifi.it
☒ Michaela Luconi michaela.luconi@unifi.it
1 Department of Experimental and Clinical Medicine, University of Florence, Florence 50139, Italy
2 European Network for the Study of Adrenal Tumors (ENSAT) Centre of Excellence, University of Florence, Florence 50139, Italy
3 Department of Experimental and Clinical Biomedical Sciences, University of Florence, Florence 50139, Italy
4 Centro di Ricerca & Innovazione Sulle Patologie Surrenaliche, AOU Careggi, Florence 50134, Italy
5 Azienda Ospedaliero-Universitaria Careggi, (AOUC), Florence 50139, Italy
6 Université Paris Cité, CNRS, INSERM, Institut Cochin, Paris F-75014, France
7 Department of Health Sciences, University of Florence, Florence 50139, Italy
8 Princess Máxima Center for Paediatric Oncology, Utrecht, The Netherlands
9 Department of Pathology, University Medical Center Utrecht, Utrecht 3584 CX, The Netherlands
Introduction
Multiple endocrine neoplasia type 1 (MEN1) is a highly penetrant autosomal dominant disorder caused by germ- line pathogenic variants in the MEN1 gene (11q13.1), and characterized by the occurrence of tumors in two or more endocrine glands, particularly the parathyroids, pancreas and anterior pituitary gland [1]. Although not usually the first manifestation, adrenal lesions are common in MEN1, occurring in 20.4-55% cases in clinical series [2-4], with an even higher prevalence (73%) reported in endoscopic ultrasound series [5]. This is a dramatic increase compared to the general population, where the frequency of inciden- talomas is approximately 3% [6]. Moreover, in MEN1, the ACC prevalence of 4.4-5.4% [2-4] is higher than the 0.4-4% reported in the general population [6], confirming the aggressive clinical behavior of adrenal tumors [7-10].
In the Gatta-Cherfili’s study cohort of 146 MEN1 patients with adrenal involvement, 10 ACCs (9 classified as stage I or II, and 1 as stage IV) were histologically diagnosed in 8 of the 45 patients operated on due to an increase in the size of the mass detected by computed tomography (CT) [2]. Similar results were obtained in a cohort of 89 MEN1 patients with an instrumental diagnosis of adrenal inci- dentaloma, where 2 out of 12 surgically removed masses showed morphological features of ACC (16.7%) [4].
In MEN1 patients, adrenal incidentalomas are most com- monly discovered during routine imaging and are often non-secreting, making active surveillance a clinical chal- lenge due to the limited availability of reliable predictors of tumor behavior and progression. In this context, deter- mining whether a malignant adrenal tumor arises from a pre-existing benign lesion is particularly relevant for patient management. The possibility of malignant transformation versus an independent multifocal origin (collision hypoth- esis) remains a matter of debate in the study of adrenal corti- cal tumors [11, 12].
Whole Exome Sequencing (WES) is a valuable tool for understanding cancer progression from a premalignant lesion and for elucidating the relationships between con- comitant tumors. It enables the detection of low-frequency variants, which can be critical for investigating the clonal origin of tumors [13, 14].
Here, we report a patient with familial MEN1, who underwent surgery for the rapid enlargement of a previously stable, nonfunctional adrenal incidentaloma. Pathology revealed an extended component with malignant features indicative of ACC contiguous to a small peripheral mass exhibiting morphological characteristics of an adrenal cor- tical adenoma (ACA). The patient experienced a relapse in the diaphragmatic bed 2 years later. Tissue availability
from the two coexistent tumors and the recurrence allowed a unique comparative molecular characterization by deep genetic profiling of the three lesions to assess their lineage relationships in the context of MEN1.
Methods
Ethics
This study was designed and conducted in accordance with the Declaration of Helsinki. The study was approved by the local Ethical Committee (Prot. 2011/0020149), and the recruited patient gave informed consent to the study.
Pathological Analysis
Histological diagnosis was carried out by two independent reference pathologists on the tumor tissues removed at sur- gery (ACC, ACA, and recurrence) according to established diagnostic criteria [15]; see Supplementary File 1.
Transcriptome Signature
Transcriptome analysis was performed at Institut Cochin, as previously described [16]; see Supplementary File 1.
Molecular Genetics
Blood DNA and DNA from the frozen recurrence specimen were extracted using DNeasy Blood & Tissue Kit (Qiagen, Germany), according to the manufacturer’s instructions. Tumor DNA was extracted from the FFPE ACA and ACC samples, according to the manufacturer’s instructions. DNA quality and quantity were measured by the Qubit BR assay (ThermoFisher Scientific, USA).
Sanger sequencing was performed to analyze all coding exons along with exon-intron boundaries of the MEN1 gene and to validate the selected variants by Next Generation Sequencing (NGS) analysis.
Targeted NGS panel: the ACC sample was analyzed using a previously validated targeted panel of 10 driver genes in ACC [17].
WES and bioinformatics analysis: patient DNA from different tissues (blood, ACA, ACC, and recurrence) underwent WES. Blood DNA was used to exclude germ- line variants. Exome sequencing was done by Cogentech SRL, using the Twist Exome 2.0 for WES library prepa- ration, Illumina NovaSeq 6000 as a sequencing platform, and requesting a minimum coverage of 100X for blood and 200X for the other samples. Sequences were analysed by the
Sarek workflow from nf-core [18]. Germline variants in the blood sample were detected by HaplotypeCaller-GATK ver- sion 4.5.0.0 [19]. For somatic alterations, Single Nucleotide Variants (SNVs) and small Insertion/Deletions were identi- fied using Mutect2-GATK version 2.2 [19], Strelka version 2.9.10 [20] and VarScan version 2.3.9 [21], and ASCAT ver- sion 2.5.3 for somatic copy-number alteration (CNA) [22]. Cancer Cell Fraction (CCF) was computed as previously reported [23], using tumor purity and CNA from ASCAT.
Somatic variants with allele depth (AD)≥20 and VAF≥5% recomputed by Samtools version 1.20 [24] were considered for downstream analysis. To evaluate potential misclassification of subclonal variants using a 5% VAF threshold, we assessed the reliability of this threshold by comparing VAF with CCF (Fig. S1). Variants were classi- fied according to the 5% cutoff for both measures. Over- all, agreement was 91%, with 10 variants (9%) showing discordance (CCF≥5% but VAF<5%), with borderline CCF values (mean=0.08, range=0.05-0.10). Conse- quently, we used VAF=5%, given its widespread applica- tion. Variants were classified as ACA exclusive (private to ACA), ACA+ACC (shared between ACA and ACC) and ACC+recurrence (shared between ACC and recurrence). To reduce the risk of false positives, a minimum read depth of 250 for the FFPE ACA and ACC samples [25] and 100 for the frozen recurrence was required. Concerning indels, only those called by two or more tools were considered. After annotating variants with VEP version 111, only coding SNVs and indels were considered for downstream analyses and variants were classified according to four tier categories of clinical significance in cancer diagnosis, prognosis and/or therapeutics (Fig. 3a & S3). Clonal analysis was done with PyClone (v.0.13.1) [26], using the final set of mutations and CNA and purity inferred by ASCAT.
Results
Clinical Characterization
We report the case of a woman affected by familial MEN1 syndrome with primary hyperparathyroidism, prolactin- secreting pituitary microadenoma, and multiple pancreatic neuroendocrine tumors (maximum diameter 11 mm). After 9 years, a left adrenal incidentaloma was reported (maxi- mum diameter 12 mm, <10HU) at CT scan. The patient was monitored according to the Guidelines for MEN1 manage- ment [9, 27]. The lesion increased in size to 18 mm over the next 5 years, and reached 50 mm after 5 additional years. An R0 laparoscopic adrenalectomy was carried out, disclos- ing an ACC (ENSAT stage II, Ki67 10%, Weiss score 6)
coexistent with a small peripheral ACA. Two years later, the patient underwent laparoscopic surgery for ACC recurrence in the adrenal bed. Following surgery, mitotane therapy was started, achieving levels≥14 mg/l. Due to a further local recurrence after 4 months, first-line chemotherapy with etoposide, doxorubicin and cisplatin (EDP) was initiated. Chemotherapy was interrupted after the third cycle, while mitotane was continued. After 10 months, the disease had progressed with lymph node and bone metastases, and the patient was administered six cycles of second-line therapy with cisplatin plus nivolumab in addition to radiotherapy to alleviate bone pain. As disease continued to progress, a third-line temozolomide regimen was proposed followed by a fourth-line capecitabine regimen. The patient died 3 years following surgical resection of the recurrent tumor.
Differential Classification of the Three Tumors According to the Histological Oncomarkers
Macroscopic and microscopic features of the adrenal tumor and of the recurrent lesion are shown in Fig. 1.
Grossly, the adrenal lesion was 65×55×50 mm in size and weighed 120 g. On cut section, it consisted of two dis- tinct coexisting nodules: the larger (maximum diameter 50 mm) was light tan in color, with a central area of necro- sis, while the smaller (maximum diameter 15 mm) was golden yellow with no necrotic or hemorrhagic changes. Compressed adrenal cortical tissue was noted at the periph- ery (Fig. 1 upper panel).
On microscopic examination, the larger nodule (Fig. 1) was composed of pleomorphic eosinophilic cells with high nuclear grade, brisk mitotic activity (12 mitoses/10mm2), and a diffuse growth pattern. Necrotic areas and vascular invasion were seen. The smaller nodule (Fig. 1) was con- stituted by clear cells in small nests and chords, resembling the fasciculata zone of the adrenal cortex. Well-consolidated histopathological biomarkers were assessed to further vali- date the differential diagnosis of the two masses [28]. The reticulin framework appeared intact in the smaller nodule, but disrupted in the larger, in line with its previously dem- onstrated diagnostic relevance [29] (Fig. 1). Immunohisto- chemistry revealed SF1 positivity in both lesions as well as in the recurrence, establishing their adrenocortical origin [28] and proliferative characteristics, given that SF1 dosage correlates with increased proliferation in human adrenocor- tical cells and promotes adrenal tumor formation in mice [30]. The larger nodule showed diffuse strong immunore- activity for p53, dot-like paranuclear staining for the para- crine factor Insulin-like Growth Factor 2 (IGF2) (Fig. 1), and a Ki67 labeling index of 10% (Fig. 1 inset), features widely used to differentiate benign from malignant lesions
a
H&E
+
Ki67
a
ACA
b
ACC
C
REC
H&E
d
e
reticulin
g
h
SF-1
j
k
IGF2
m
n
O
p53
p
q
r
ß-catenin
Fig. 1 Pathological features of ACA, ACC and ACC recurrence: Upper panel. Gross morphology of the resected adrenal mass (left) showing a large ACC (black star) adjacent to a small ACA (white star); H&E staining of the two nodules (center) with magnification revealing vari- ation of Ki67 labeling indices in ACC and ACA (right). Lower panel: comparative histochemical and immunohistochemical characterization of ACA (a, d,g, j,m, p), ACC (b, e,h, k,n, q) and ACC recurrence (c, f,i, l,o, r). Panels a-c: Profound cytological and architectural atypia in ACC and ACC recurrence (REC) compared to ACC histology, resembling the normal adrenal zona fasciculata. Panels d-f: Preserved (ACA) vs. disrupted (ACC and ACC recurrence) reticulin framework. Panels g-i: Diffuse nuclear SF1 immunoreactivity in the three lesions. Panels j-l: IGF2 dot-like paranuclear staining was evident in the two malignancies but negative in ACA. Panels m-o: Wild-type p53 reac- tivity in ACA and high p53 expression in ACC and recurrence. Panels p-r: B-catenin expression limited to the cell membrane in the three lesions
of the adrenal cortex [31-33]. In contrast, the smaller lesion displayed a Ki67 labeling index of 2%, no mitotic figures, a wild-type p53 staining pattern, and no IGF2 expression (Fig. 1). Membranous ß-catenin expression was seen in both lesions, with increased intensity in the malignant form (Fig. 1). Based on the described biomarkers, a histological diagnosis of ACA and ACC was established for the smaller and larger lesions, respectively. Tumor recurrence exhibited morphological and phenotypic features consistent with prior ACC (Fig. 1).
Differential Gene Expression in ACC and ACA
To assess if the functional significance of the TP53 variant found is associated with an upregulation of protein expres- sion, described as “gain of function” [34], we explored protein expression by immunohistochemistry. The strong nuclear p53 staining observed in ACC and the recurrence, together with the very low-level staining seen in ACA, sup- ported an altered TP53 pattern in the malignant lesions and a wild-type pattern in ACA (Fig. 1m-o). Increased p53-tar- get ß-catenin was associated with ACC, though positivity was limited to the cell membrane (Fig. 1p-r).
Application of 3’-end RNA sequencing transcriptome technology to FFPE of the primary adrenal tumor samples correctly classified ACC (C1A, Fig. 2) and ACA (C2, Fig. 2) on the basis of a predictive transcriptome model previously developed [16], with a score of 93.3% and 99.1%, respec- tively. According to the model, ACC transcriptome profile was associated with a high risk of recurrence (Fig. 2).
Loss of Function Variant in MEN1
Sanger sequencing identified a heterozygous germline frame- shift mutation in the exon 8 of MEN1 (NM_001370259.2): c.1154del, p.(Ala385GlyfsTer60) (Fig. S2). This variant was novel and was classified as pathogenic, according to the rec- ommendation of the American College of Medical Genetics
and Genomics (ACMG) [35]. MEN1 gene sequencing in the different tumor samples suggested a loss of heterozygosity (LOH) both in ACC and recurrence but not in ACA (Fig. S2).
Targeted NGS Analysis
The targeted NGS panel we recently published [17] identi- fied two somatic variants with strong clinical significance (Tier I) and high frequency (≥70%), Table 1).
Exome Analysis of ACA, ACC and Recurrence
In order to explore the somatic mutational profiles of the three tumors and evaluate possible correlations among the three tumor conditions, we performed parallel WES anal- ysis of patient DNA from blood and tumor tissues, which resulted in a list of somatic tumor-only variants, some in common and some specific of each tumor conditions.
Molecular Characterization of the Tumors
We found 2268 SNVs (Fig. 3) and 1594 indels (Fig. S3). Since all indels were classified as benign/likely benign, and only 2/9 were with unknown significance (Fig. S3), we focused on SNVs. Neither SNVs nor indels co-occurred in ACA and recurrence.
Applying thresholds of VAF≥5% and read depth≥250x in FFPE-ACA tissue, 42 variants remained. Allele fre- quency in the ACC sample was thoroughly established by SAMtools pileup, obtaining a total of 6 ACA-exclusive and 36 ACA/ACC-common variants. Interestingly, all filtered variants were rare. All ACA-exclusive SNVs, consisting of 4 missense and 2 synonymous variants, were classified as Tier IV (benign or likely benign). ACA/ACC-common SNVs in coding regions included 13 missense, 5 synony- mous and 2 stop gain, two classified as Tier III (Fig. 3a). A stop gain variant in KANK1 gene (NM_015158.5: c.3342T>A p.(Cys1114Ter) was present in both ACA and ACC (Table 2).
Regarding filtering of co-occurring SNVs in ACC and recurrence, a threshold of ≥100x read depth was applied to all detected variants with a VAF≥5%, obtaining 69 SNVs. After the exclusion of non-coding ones, 40 missense, 17 synonymous, 4 stop-gain and 2 splicing variants were selected. Among them, 10 variants were classified as Tier III, since all affected genes were found to be associated with cancers (Table 2). The only two variants classified as Tier I, and therefore considered as pathogenic, remained those associated with NF1 and TP53 genes.
To validate the relevance of the mutated genes found in ACA, ACC and recurrence, along with MEN1, we assessed
40 -
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ACC
Transcriptome Class
PC2
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C1A
C1B
C2
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-40
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0
20
40
PC1
| Gene | Transcript | cDNA | Protein | Variant type | Tier | ACMG | Legacy ID (COSMIC) | VAF |
|---|---|---|---|---|---|---|---|---|
| NF1 | NM_000267 | c.4270-1G>C | p .? | splicing | I | Pathogenic | n.a. | 70.85% |
| TP53 | NM 000546 | c.376T>G | p.Tyr126Asp | missense | I | Pathogenic | COSM6024609 | 72.45% |
their frequency in a large independent ACC cohort, query- ing the TCGA-ACC Firehose Legacy [37]. The OncoPlot (Fig. S4) showed the frequency in the TCGA database of each mutated gene, classified according to the presence in ACA, ACC and recurrence, also reporting their association with TP53, NF1 and MEN1 somatic mutations, as found in TCGA. The top 12 most mutated genes in TCGA-ACC samples were found to be wild-type in ACA, suggesting that these genes are not shared with the benign tumoral forms. Among the genes harboring mutations shared between ACA and ACC, FAM47E, SLC26A2, and WDR7 displayed a 2% mutation frequency in the TCGA cohort, whereas somatic mutations in KANK1 gene reached only 1% (Fig. S4).
Notably, 8/12 “driver” genes with malignant potential, exclusively present in ACC and recurrence, showed pre- dicted protein interactions centered in TP53, according to the STRING analysis of protein-protein interaction net- works (Fig. 4a). Figure 4b reports gene ontology enrichment analysis, which clusters mutated genes according to their molecular functions in the three conditions (ACA exclusive, ACA+ACC common, or ACC+REC common). Cluster distribution showed that all functional clusters common
to ACA and ACC were also maintained in the recurrence, as well as three additional classes, corresponding to tran- scriptional regulators, molecular function regulators and molecular transducers emerged as being shared by ACC and recurrence, but not by ACA.
To integrate the information derived from SNV and indel analysis for tracing common or unique somatic alterations of ACC, ACA and recurrence, we also analyzed duplica- tions and deletions of genes across the chromosomes. Copy number alteration (CNA) analysis of the 3 tumor samples (Fig. 5) revealed no alteration in ACA (Fig. 5a), while ACC (Fig. 5b) and recurrence (Fig. 5c) showed pervasive arm- level copy number changes.
CNA patterns were concordant between ACC and the recurrent tumor, with both exhibiting MEN1 LOH. Con- trariwise, no alterations at the MEN1 locus (11q13) were detectable in ACA (Fig. 5d), as indicated by WES analysis and Sanger sequencing.
The curated set of SNVs (n=111) were used to infer clonal populations and potential relationships across sam- ples (Supplementary File 2.xlsx). PyClone analysis identi- fied four distinct clones (Fig. 6a). Two clones (clones 1 and
4) were shared between ACC and the recurrence. Clone 1, which included all Tier III-classified variants along with pathogenic TP53 and NF1 mutations, was the most preva- lent, suggesting a relevant role in disease progression. Clone 4 displayed increased clonality in the recurrence compared to ACC. Two additional clones, comprising 37 Tier IV vari- ants (clone 3) and two Tier III variants in KANK1 and REN (clone 2), were shared between ACA and ACC but were not detected in the recurrence, which may be consistent with a divergent evolutionary pattern compared to clones 1 and 4. No clones were specific to ACA. These results were sup- ported by CCF analysis, showing comparable trends across the different clones (Fig. S5).
Discussion
In this study, the unique simultaneous presentation of ipsi- lateral ACA and ACC, along with the availability of a subse- quent recurrence, enabled the morphological and molecular comparison of the three tumors to investigate: (i) the pro- gression versus collision hypothesis of ACA and ACC in the context of MEN1 syndrome; (ii) the identification of driver clones with malignant potential.
The coexistence of ACC and ACA, so far only rarely reported-with limited genetic characterization [12, 39, 40] and all but one outside the context of MEN1-suggests tumor collision as the most likely scenario. A recent paper summarized sporadic cases of malignant transformation of adrenal incidentalomas, likely ACAs, into ACCs [41]. However, in these cases, the diagnosis of benign lesions was based exclusively on imaging, without histopathologi- cal confirmation. The strongest evidence against a stepwise progression from ACA to carcinoma lies in the striking dis- crepancy between the high prevalence of adenomas and the rarity of ACCs. Nonetheless, in MEN1, the frequency of incidentalomas increases together with that of carcinomas, implying a greater risk of malignancy in MEN1.
In our case, WES analysis revealed significant arm-level copy number changes in ACC and its recurrence, in line with previous reports [37, 42, 43], with largely overlapping CNA patterns between the two malignant lesions. In contrast, ACA exhibited a neutral copy-number profile, suggesting that CNAs may contribute to adrenocortical malignancy.
Concerning SNVs and indels, we applied stringent fil- tering criteria to identify a reliable set of somatic variants, which were classified into four Tier categories based on their clinical impact. SNVs shared between ACC and the recurrence, but not detected in ACA, are in keeping with a clonal relationship between the two malignant lesions and support their interpretation as a true relapse. Samtools
pileup and filtering by ≥2 somatic variant calling tools applied to SNVs and indels yielded a reduced, high-confi- dence variant set, comprising six SNVs exclusive to ACA, 36 shared between ACA and ACC, and 69 shared between ACC and the recurrence. No variants were identified in genes previously reported to predispose to ACA [44], and all ACA-exclusive SNVs were classified as benign. Among ACA-ACC shared mutations, two were classified as Tier III and affected KANK1 and REN genes. KANK1 is a candidate tumor suppressor gene for renal cell carcinoma [45, 46] and has been reported as mutated in the TCGA-ACC cohort, albeit at a low frequency of approximately 1%. A potential involvement of KANK1 haploinsufficiency in centrosome aberrations has been documented in tumorigenesis [47]. The relatively high number of SNVs shared between ACA and ACC, compared with the limited number of ACA-exclusive variants, is compatible with a possible relationship between the two lesions.
Of the 69 SNVs shared between ACC and the recurrence, 10 variants were of unknown significance (Tier III) and 2 of strong clinical significance (Tier I), including those in the TP53 and NF1 genes, which are frequently mutated in ACC [17]. Immunohistochemistry demonstrated strong p53 overexpression confined to ACC and retained in the recur- rence. As extensively shown in ovarian cancer, many mis- sense mutations in TP53, specifically in the DNA-binding domain, not only result in loss of tumor suppression activity of the protein, but are also associated with protein overex- pression and gain-of-function (GOF) properties that sustain the tumorigenic process [34, 48] and confer chemoresis- tance [49]. In colorectal cancer, TP53 GOF mutations spe- cifically activate the Wnt-ß-catenin oncogenic signaling by increasing ß-catenin protein levels through decreased deg- radation and enhanced synthesis [50]. Additionally, beyond acquiring a TP53 mutation in one allele, most tumors lose the second allele by deletion or copy neutral LOH [51]. In keeping with these findings, increased ß-catenin immuno- reactivity was associated with p53 overexpression in ACC and, to an even greater extent, in the recurrence, whereas ACA showed a very low-level wild-type p53 staining pat- tern, supporting a GOF effect of the identified TP53 muta- tion. LOH of MEN1 may further contribute to dysregulation of Wnt-ß-catenin oncogenic signaling, as menin has been shown to suppress cell proliferation through direct interac- tion with ß-catenin [52]. Notably, in a large series of ovarian serous carcinomas, all NF1-mutated tumors also harbored a missense TP53 mutation, suggesting a possible link between the two mutational events [53]. In ACC, the co-occurrence of TP53 and NF1 mutations has been reported to correlate with poorer overall and progression-free survival [17].
Although not recognized as ACC driver genes, the remaining 10 affected genes shared between ACA and ACC
a
Total SNVs (n=2268)
ACA exclusive (n=169)
ACA+ ACC (n=99)
ACC exclusive (n=1893)
Recurence exclusive (n=34)
ACC+ recurrence (n=81)
Samtools mpileup
Samtools mpileup
VAF ≥5% Read depth ≥250X (n=42)
VAF ≥5% Read depth ≥100X (n=69)
6 non-coding variants filtered out
VAF <5% in ACC
VAF ≥5% in ACC
☐ Missense (n=40)
☐ Synonymous (n=17)
ACA exclusive (n=6)
Common ACA+ACC (n=36)
☐ Stop gain (n=4)
☐ Splicing (n=2)
16 non-coding variants filtered out
☐ Missense (n=13)
Tier IV (n=51)
Tier III (n=10)
Tier I (n=2)
☐ Missense (n=4)
☐ Synonymous (n=2)
☐ Synonymous (n=5)
☐ Stop gain (n=2)
Tier IV
Tier IV (n=18)
Tier III (n=2)
Genes: ATG12 CALM2
Genes: NF1 TP53
Genes: KANK1 REN
EXT1 GABRB3 IRF7 LCK
MAP4K1 PDK4 SATB2 SYNPO2L
ACA
ACC
Recurrence
n=36
n=69
n=6
n=1893*
n=34*
b
Fig. 3 SNVs filtering with final retained variants in relevant genes. Panel a: Flowchart illustrating the number of total and prioritized vari- ants in the different tumor samples after the variant filtering approach. Red color indicates affected genes by variants of unknown signifi- cance or pathogenic. SNVs: Single Nucleotide Variants; Tier IV: vari- ants classified as likely benign/benign; Tier III: variants of unknown clinical significance; Tier I: variants with strong clinical significance; VAF: Variant Allele Frequency. Panel b: Venn diagram showing the final number of exclusive or shared SNVs in different tumor samples. *indicates variants not checked by SAMtools pileup
were also found to be mutated in the TCGA-ACC cohort, albeit at a low frequency. According to STRING analysis, 6 of them (ATG12, GABRB3, IRF7, LCK, MAP4K1, SATB2) are part of a predicted protein-protein interaction network
centered in TP53, suggesting a potential role in the develop- ment of malignancy.
Clonal evolution analysis based on validated somatic variants identified four clonal populations in ACA, ACA+ACC, and ACC + recurrence. Clones 2 and 3, shared between ACA and ACC, corresponded to variants present in both lesions. Of note, clone 3 included two Tier III variants affecting KANK1 and REN. Neither of these two clones was detected in the recurrence, consistently with the absence of ACA-ACC shared variants at this stage. Conversely, mutations in clones 1 and 4, which were shared between ACC and the recurrence, were not detected in ACA. Clone 1 included pathogenic variants in TP53
| Gene | Locus | HGVS | VAF in ACA | VAF in ACC (%) | VAF in recur- rence (%) | ACMG | Tier | cBIO Portal | Gene-associated cancer* |
|---|---|---|---|---|---|---|---|---|---|
| (%) | |||||||||
| ATG12 | 5q22.3 | NM_004707.4:c.416G>A p.(Trp139Ter) | 0 | 36.1 | 29.2 | VUS | III | Pancreatic cancer | Liver, ovary, kidney, thyroid |
| CALM2 | 2p21 | NM_001743.6:c.73G>T p.(Asp25Tyr) | 0 | 60 | 55,1 | VUS | III | n.a. | breast, colorectal, liver, pancreas, kidney |
| EXT1 | 8q24.11 | NM_000127.3:c.1031 C>G p.(Ser344Cys) | 0 | 35.6 | 30.8 | P | IV | n.a. | Lung |
| GABRB3 | 15q12 | NM_000810.4:c.409 A>G p.(Asn137Asp) | 0 | 38 | 36.8 | LP | III | n.a. | Prostate adenocarcinoma |
| IRF7 | 11p15.5 | NM_001572.5:c.1252 C>T p.(Arg418Trp) | 0 | 68.3 | 54.9 | VUS | III | n.a. | Liver, urothelial |
| KANK1 | 9p24.3 | NM_015158.5:c.3342T>A p.(Cys1114Ter) | 5 | 7.54 | 0 | LP | III | n.a. | Kidney |
| LCK | 1p35.2 | NM_005356.5:c.373G>A p.(Glu125Lys) | 0 | 34.5 | 37.5 | VUS | III | Glioma Melanoma | T-cell acute lympho- blastic leukemia |
| MAP4K1 | 19q13.2 | NM_001042600.3:c.865G>C p.(Asp289His) | 0,7 | 43.1 | 33 | VUS | III | n.a. | Lymphoma |
| NF1 | 17q11.2 | NM_001042492.3:c.4333-1G>C p .? | 0 | 65.9 | 56.9 | P | I | Bladder cancer | Breast |
| PDK4 | 7q21.3 | NM_002612.4:c.625G>C p.(Glu209Gln) | 0 | 38.7 | 31.7 | VUS | III | n.a. | Kidney, Thyroid |
| REN | 1q32.1 | NM_000537.4:c.995 C>A p.(Pro332His) | 8.61 | 6.85 | 0 | VUS | III | n.a. | Kidney |
| SATB2 | 2q33.1 | NM_001172509.2:c.1547G>A p.(Trp516Ter) | 0 | 69.4 | 53.6 | LP | III | n.a. | Bowel |
| SYNPO2L | 10q22.2 | NM_001114133.3:c.235 C>T p.(Gln79Ter) | 0 | 34.9 | 37.8 | LP | III | n.a. | Breast, Head and Neck and Prostate. |
| TP53 | 17p13.1 | NM_000546.6:c.376T>G p.(Tyr126Asp) | 0 | 67.3 | 47.4 | P | I | 18 cancer types# | Breast, colorectal, lung, sarcoma, pros- tate, adrenal cortical, glioma, Spitzoid tumor, multiple other tumor types |
*based on cancer specificity/prognostic for cancers (italic form) according to Human Protein Atlas. esophagogastric cancer, colorectal cancer, glioma, non-small cell lung cancer, breast cancer, hepatobiliary cancer, pancreatic cancer, soft tissue sarcoma, renal cell carcinoma, prostate cancer, myelodysplastic syndrome, melanoma, liver cancer, head and neck cancer, gastrointestinal neuroendocrine tumor, endometrial cancer, mature B-cell neoplasms, esophageal-stomach cancer
a
b
ACA exclusive: 5 genes 6 SNV
MAP4K1
25%
binding (GO:0005488)
50%
catalytic activity (GO:0003824).
molecular function regulator (GO:0098772)
25%
LCK
ACA + ACC common: 29 genes 36 SNV
13%
NF1
IRF7
binding (GO:0005488)
7%
catalytic activity (GO:0003824).
TP53
20%
translation regulator activity (GO:0045182).
60%
transporter activity (GO:0005215)
ATG12
SATB2
ACC+REC common: 69 genes 2% 69 SNV
binding (GO:0005488)
4%
6%
catalytic activity (GO:0003824).
6%
36%
molecular function regulator (GO:0098772)
6%
molecular transducer activity (GO:0060089)
GABRB3
transcription regulator activity (GO:0140110)
40%
translation regulator activity_(GO:0045182)
transporter activity (GO:0005215)
and NF1, and its restriction to ACC and the recurrence suggests an association with the malignant phenotype and persistence during disease evolution. All selected genes affected by Tier III variants mapped to clone 1, indicating that this clone encompassed the variants with the highest predicted clinical relevance. Functional enrichment analysis of proteins encoded by genes mutated and shared between ACC and the recurrence revealed additional functional categories that were not observed among genes mutated in both ACA and ACC.
The absence of demonstrable biallelic MEN1 inacti- vation in the adenoma is a major limitation of this study. Whole-exome and Sanger sequencing demonstrated LOH at the MEN1 locus in ACC and the recurrence, while exclud- ing classical coding alterations in the adenoma. However,
(https://functionome.geneontology.org). GO-PANTHER software shows the distribution of the molecular function protein clusters cor- responding to the mutated genes in the three tumor conditions: ACA exclusive genes, ACA+ACC common genes, and ACC+recurrence common genes. Molecular functional classes according to Go-Panther ontology are indicated to the right, and their percentage distribution inside the pie graphs
the occurrence of alternative second-hit mechanisms, such as large genomic rearrangements, mutations in promoter or untranslated regions, or epigenetic alterations not detect- able by WES, cannot be ruled out in ACA, particularly in the absence of informative menin immunohistochemistry. Consequently, a causal role for MEN1 inactivation at the adenoma stage cannot be established.
An additional limitation is that this study is based on a single patient, which restricts the generalizability of the findings to the broader MEN1 patient population. Nonethe- less, the spectrum of mutations identified is consistent with those reported in the TCGA-ACC dataset, supporting the biological relevance of these findings.
In conclusion, comprehensive molecular profiling of the ACA, ACC and recurrence occurring in a MEN1
chr1
chr2
chr3
chr4
chrS
chr6
chr7
chr8
chr9
chr10
chr11
chr12
chr13
chr14
chr15
chr16
chr17
chr18
chr19
chr20
chr21
chr22
chrX
chrY
a
chr1
chr2
chr3
chr4
chr5
chr6
chr7
chr8
chr9
chr10
chr11
chr12
chr13
chr14
chr15
chr16
chr17
chr18
chr19
chr20
chr21
chr22
chrX
chrY
b
U
F
chr1
chr2
chr3
chr4
chr5
chr6
chr7
chr8
chr9
chr10
chr11
chr12
chr13
chr14
chr15
chr16
chr17
chr18
chr19
chr20
chr21
chr22
chrX
chrY
C
T
E
E
d
Copy number variation
ACA
2
0
-2.
-4.
ACC
2
0
LogR
-2.
-4.
Recurrence
2
0
MEN1
-2.
-4
i
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
2 1 22
x
Y
Chromosome
E
L
1
a
b
1.00
Clone 1:
NF1
Blood
TP53
SYNPO2L
IRF7
GABRB3
MAP4K1
Clone 4:
0.75
LCK
FCSK
Cellular prevalence (in %)
SATB2
KNG1
ACA
CALM2
CPEB2
ATG12
PDK4
Clone
EXT1
Clone 1 (n= 66)
…
0.50
- Clone 2 (n= 37)
ACC
Clone 3:
- Clone 3 (n= 5)
HNRNPF
Clone 4 (n= 3)
ZDHHC8P1
SLC26A2’
0.25
SLC26A22
Recurrence
HLA-G
Clone 2:
REN
KANK1
Cellular prevalence (in %)
…
1
0.00
0.5
Blood
ACA
ACC
Recurrence
Conditions
0
patient has provided insight into the possible relationship between benign and malignant adrenocortical lesions in this context. Clonal evolution analysis identified distinct clonal populations across lesions, highlighting variants potentially relevant to malignant behavior and disease relapse. Although the clonal architecture and the number of variants shared between ACA and ACC are compat- ible with a clonal relationship between the two lesions, the lack of unequivocal evidence for MEN1 inactivation in ACA precludes definitive conclusions regarding a step- wise adenoma-carcinoma progression versus independent multifocal tumor development within the same organ. Nonetheless, these findings support careful clinical con- sideration of the potential risk of ACC when managing MEN1 patients with adrenal lesions.
1 and 2, which are the most interesting as bearing the highest number of mutations, are indicated in the boxes; clone 3 bears 2 different muta- tions on the same gene. * Clone 3 contains two mutations in SLC26A2. Panel b. Cellular prevalence of each clone is summarized in a single hexagon where each cell represents a set of mutations and the relative abundance in the four conditions. Hexagon created with supraHex R package (v.1.10.1) [38]
Supplementary Information The online version contains supplementary material available at https://doi.org/10.1007/s12022-026-09908-0.
Acknowledgements The authors are grateful to Dr. Luisa Candita (Azienda Ospedaliero-Universitaria Careggi) for valuable advice on genetic aspects, and to Sven van Kempen (University Medical Center Utrecht, Utrecht, The Netherlands), Gianna Baroni and Monica Pepi (University of Florence, Florence, Italy) for expert technical assis- tance.
Author Contributions ML: conceptualization, research coordination; ML and FrC: study design, data analysis and interpretation; ML, FC and GN: manuscript writing; FC and TE: NGS and genetic analysis and genetic sequencing ; TO and MB: bioinformatic analysis, WES data interpretation, bioinformatic analysis description; FeC and LC: clinical management of the patient; GC: data collection and manage- ment; RRdK and MM: project supervision; RS and GN: immunohis- tochemical and pathology analysis; GA, AJ and AAD: transcriptomic profile. ML and MB: secured funds. All authors reviewed and ap- proved the final version of the manuscript.
Funding Open access funding provided by Università degli Studi di Firenze within the CRUI-CARE Agreement. This research has been funded by EU Horizon Europe EU4H-2024-PJ-03-4 (Support of Personalized medicine Approaches in Cancer-SPARC project n. 101232874), by the Italian Ministry of the University and Research (Progetti di Ricerca di Interesse Nazionale -PRIN 20222KAYY5, PNRR M4.C2.1.1 - Next Generation EU funded by the European Community to M.L.) and by Associazione Italiana per la Ricerca sul Cancro AIRC (grants IG17691 to M.L. and IG27036 to M.B.). The work has also been supported by European Cooperation in Science & Technology (COST) Action CA20122 Harmonisation, and A.A.D. received a Short Term Scientific Missions grant inside the CA20122.
Data Availability The curated set of SNVs are reported as Supplemen- tary File 2.xlsx
Declarations
Competing interests The authors declare no competing interests.
Disclosures The authors have no competing interests to declare that are relevant to the content of this article. Ronald R. de Krijger is an editorial board member of Endocrine Pathology. Part of the data of the manuscript has been presented as posters at the Endocrine Society’s Annual Meeting ENDO2025 (San Francisco CA, USA, July 12-15, 2025) and at the Joint 24th ENS@T Scientific Meeting & 4th Harmo- nis@tion Meeting (Belgrade, Serbia, September 4-5, 2025).
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.o rg/licenses/by/4.0/.
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