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STATE-OF-THE-ART REVIEW IN ENDOCRINOLOGY
Updates on WHO 5th edition classification, molecular characteristics and tumor microenvironment of adrenocortical carcinomas
Yuto Yamazaki1) (D, Yuta Tezuka2), Yoshikiyo Ono2), Fumitoshi Satoh1), Hironobu Sasano1) and Takashi Suzuki1)
1) Department of Pathology, Tohoku University Graduate School of Medicine, Sendai 980-8575, Japan
2) Department of Diabetes, Metabolism and Endocrinology, Tohoku University Hospital, Sendai 980-8575, Japan
Abstract. Discerning malignancy in adrenocortical tumors is clinically pivotal in the management of patients but has also been one of the most difficult areas in both clinical and pathology settings. The recently published WHO 5th edition “Endocrine and Neuroendocrine Tumours” recommends a diagnostic algorithm employing not only one but several proposed histopathological criteria-including the Weiss criteria and its revision and the Helsinki criteria-in addition to the Reticulin algorithm, the Ki-67 proliferative index, and others depending upon their histopathological features. On the other hand, the risk classification proposed by ENSAT (European Network of Study for Adrenal Tumors) in 2018 was primarily based on the Ki-67 proliferative index of carcinoma cells, especially focusing on whether or not postoperative or adjuvant chemotherapy could be administered. The recently reported results of the ADIUVO study, although preliminary, discuss the necessity of postoperative therapy with mitotane in patients with low-grade adrenocortical carcinomas (ACCs) after complete resection. In addition, recently reported comprehensive genetic analyses attempted to classify ACCs into four major molecular subtypes: (i) the Wnt/-catenin pathway, (ii) the p53/Rb1 pathway, (iii) the chromosomal maintenance/chromatin remodeling pathway, and (iv) the MMR (Mismatch repair) pathway. Among those, groups (i) and (ii) are more commonly detected in high-grade ACCs but it is also true that specific therapeutic targets based on the molecular characteristics of tumors have remained limited. In addition, possible effects of glucocorticoid excess in functional ACCs on the tumor microenvironment have also been examined, and the utility of immune checkpoint inhibitors is being explored at this juncture.
Key words: Weiss, Ki-67, Glucocorticoid, Adrenocortical carcinoma, Tumor microenvironment
Introduction
Adrenocortical carcinoma (ACC) is an extremely rare tumor, accounting for approximately 0.5% of all malig- nant tumors, and its annual incidence is 0.7-2 cases per million [1]. The gender difference in male to female ratio is 45:55 [1]. In addition, the age distribution is bimodal, with the great majority of cases occurring in the pediatric and middle-aged population in their 40s to 50s [1]. In pediatric cases, ACCs are frequently associated with some hereditary tumor syndromes, including Li-Fraumeni, Beckwith-Wiedemann, McCune-Albright, MEN (multi- ple endocrine neoplasia), and Lynch [1]. Therefore, it is
pivotal to explore the possibility of such genetic back- ground based on family history and clinical findings con- cerning non-adrenal issues when seeing pediatric patients with ACCs.
More than 90% of previously reported ACCs were 6.5 cm or larger and weighed 50 g or more [1], but adrenal tumors measuring more than 4 cm in their great- est dimension are at present considered worthwhile in clinically pursuing the differential diagnosis of ACC [2]. However, it is also true that discerning malignancy in adrenocortical tumors has remained challenging for both clinicians and pathologists. The recently published WHO 5th edition. classification first classifies histo- pathological diagnostic criteria into “essential” and “desirable” [3]. “Essential diagnostic criteria” comprises histological parameters required in appropriately employ- ing the multi-scoring systems including those applicable to special subtypes of ACCs such as oncocytic or pedi- atric tumors [3].
E-mail: yuto.yamazaki.c7@tohoku.ac.jp
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On the other hand, ACCs are well known to harbor enormously distinctive intra-tumoral heterogeneity at the levels of both histology and endocrine function, such as in the status of biologically active corticosteroids. In par- ticular, ACCs have a unique status of steroidogenesis termed “disorganized steroidogenesis” or “combined steroidogenesis” compared to that of normal adrenal cor- tex or adrenocortical adenomas [4, 5]. The disorganized steroidogenesis is due to disorganized or extremely het- erogenous intra-tumoral distribution of the steroidogenic enzymes required for biologically active steroids [4]. Due to this disorganized steroidogenesis, carcinoma cells cannot produce and secrete biologically active steroids because of the lack of all steroidogenic enzymes required in the same tumor cells, which usually results in excessive production and secretion of biologically inactive precur- sor steroids [4]. Of particular interest, this complicated but unique status of steroidogenesis in ACCs has recently also been reported to possibly influence tumor immunity and make it difficult to predict the efficacy of immune checkpoint inhibitors [6]. Therefore, these unique aspects of ACCs definitively merit further investigation in terms of clinical benefits for patients.
The genetic characterization of ACCs has recently been relatively well explored but the potential therapeu- tic targets based on those features have been markedly limited. However, it is of interest that a proposal has been made to use these genetic alterations as risk stratifi- cation and/or prognostic factors for ACCs [7].
Herein we review the recent updates regarding the histopathological diagnosis of ACCs based on the WHO 5th edition. classification and then summarize the poten- tial clinical significance of molecular characteristics and the influence of steroid production on ACC tumor micro- environments.
1. Histopathological Diagnosis of ACCs: From the Past to the Present (WHO 5th edition Classification)
The history of previously proposed histopathological criteria for evaluating adrenocortical malignancy is sum- marized in Fig. 1. The Weiss criteria was first proposed in 1984 and is still widely used as the gold standard, and diagnosis as ACC is determined by the presence of 3 or more points [8]. However, since the criteria consists of 9 morphological findings (nuclear atypia, mitotic figures, atypical mitotic figures, coagulative necrosis, capsular invasion, sinusoidal invasion, venous invasion, eosinophilic cytoplasm, and diffuse architecture) [8, 9], interobserver variance has been sometimes reported.
Therefore, Weiss himself revised his criteria in 2002 [10]; then in 2009, the reticulin algorithm was also pro-
posed [11], followed by the Helsinki score in 2015 [12]. The Ki-67 proliferative index was first incorporated into the diagnostic criteria of the Helsinki score, and those with a score of 8.5 or more are currently diagnosed as ACC [12]. In addition, a subsequent validation study demonstrated that Weiss criteria had a sensitivity of 100% and specificity of 90.2%, its revised criteria 100% and 96.9%, and the Helsinki score 100% and 99.4% [11-13]. However, it is also pivotal to note that these diagnostic algorithms were established mainly by com- paring the findings between those harboring the lesions of metastasis and those that did not: i.e., early clinical stages of ACCs without any distant metastases were not included in the analysis. Therefore, their accuracy has been disputed, especially when diagnosing cases of low- grade malignancy harboring 3-4 Weiss points, myxoid type, and pediatric cases. In particular, Weiss criteria has been considered “gold standard” and therefore widely been used since its proposal. However, it is also true that marked interobserver variance is unavoidable due to its subjective nature and thus modified Weiss criteria was introduced although still depending on subjective mor- phological findings [3, 8-10]. In addition, myxoid vari- ants are often underestimated and oncocytic variants or pediatric cases are overestimated [13]. In those subtypes of ACC, reticulin algorism is considered useful contain- ing the significant morphological findings incorporated in Weiss criteria [3, 11] but actually reticulin staining has not been necessarily performed because of its complex technical procedures of identifying reticulin structure by rather complicated or rarely used and not standardized histochemical methods in the great majority of diagnostic pathology laboratories. In addition, those aforementioned criteria do not necessarily incorporate Ki-67 proliferative index, the most widely used immunohistochemical marker to differentiate benign and malignant neoplasms in addi- tion to predicting clinical prognosis of the patients. On the other hand, Helsinki score firstly incorporated Ki-67 proliferative index into its scoring system and resulted in high sensitivity and specificity for not only diagnosis but also prediction of prognosis or clinical outcome of the patients, although the methodologies of obtaining Ki-67 proliferative index have not necessarily been standard- ized [12, 13].
Since the introduction of the previous WHO 4th edi- tion classification, myxoid, oncocytic and sarcomatoid variant has been established as distinct subtypes of ACC. Myxoid variants often harbor mild cytological atypia with abundant myxoid change in intervening stroma positive for alcian-blue [3, 13]. This histological subtype is fre- quently underestimated by conventional Weiss criteria [3, 13]. Oncocytic variants were composed of more than 90% of eosinophilic cells and often overestimated by Weiss
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Weiss criteria
Weiss revised criteria
Reticulin algorithm
Helsinki Score
Histological findings
Histopathological findings
Nuclear atypia (Fuhrman G3/G4)
Reticulin framework Disruption +
Histological findings
Mitosis >5/50HPF
Mitosis >5/50HPF
Mitosis>5/50HPF
Atypical mitosis
Histopathological findings (Any of the following)
Coagulation necrosis
Atypical mitosis
Eosinophilic cytoplasm>75%
Ki-67 labeling index
Eosinophilic cytoplasm>75%
Capsular invasion
Mitosis>5/50HPF
Diffuse architecture
Coagulation necrosis
Necrosis
(HS)
Capsular invasion
(WRS)
Venous invasion
=3 x mitotic rate (>5/50 high-power fields)
Sinusoidal invasion
= 2 x mitotic rate
+ 5 x necrosis
Venous invasion
+ 2 x cytoplasm
+ Ki-67 (hot spot)
Coagulation necrosis
+ atypical mitoses
+ necrosis
≥8.5pts : Malignant
+ capsular invasion
<8.5pts : Benign
≥3pts : Malignant
<3pts : Benign
≥3pts : Malignant <3pts : Benign
ACC diagnostic criteria of WHO 5Th classification
Essential: Morphologic and/or immunohistochemical evidence of adrenal cortical differentiation, and evidence of malignancy usually based on a multiparameter scoring system *; mitotic tumour grading and Ki67 immunohistochemistry
Desirable: Confirmation of the adrenal cortical differentiation using SF1, and application of prognostic biomarkers
*Fulfills one of the established multiparameter scoring systems for malignancy, including: Conventional adrenal cortical neoplasms in adults (one of the followings):
-Weiss score ≥3, Modified Weiss score ≥3, Helsinki score >8.5, Reticulin algorithm
Oncocytic adrenal cortical neoplasms (one of the followings):
-Lin-Weiss-Bisceglia (any major criterion); Helsinki score >8.5, Reticulin algorithm
Paediatric adrenal cortical neoplasms: -Wieneke/AFIP criteria score ≥4
The Weiss criteria was first proposed in 1984 and consisted of nine morphological findings. Subsequently, in 2002, the Weiss revised criteria was proposed, calculating as = 2 × mitotic rate + 2 × cytoplasm + atypical mitoses + necrosis + capsular invasion. The reticulin algorithm specifically focused on the reticulin framework for evaluation of histological architecture with the additional presence of one or more findings of necrosis, mitosis >5/50HPF, and venous invasion. The Helsinki criteria first adapted the Ki-67 index, calculating as = 3 x mitotic rate (>5/50 high-power fields) + 5 x necrosis + Ki-67 (hotspot). Cases with 8.5 pts or more are diagnosed as malignant. The WHO 5th edition classification currently recommends making a definite diagnosis, employing at least one or more scoring systems [3]. The description of diagnostic criteria was cited from [3]. In addition, in special subtypes like oncocytic or pediatric cases, optimized scoring systems such as the Lin-Weiss-Bisceglia or Wieneke criteria should be used in combination for diagnosis.
criteria. Therefore, WHO 5th edition classification recommends Li-Weiss-Bisceglia criteria, the specific diagnostic algorism for oncocytic adrenocortical tumors when evaluating the degree of malignancy in oncocytic adrenocortical tumors, although their great majority is benign [3, 13]. Sarcomatoid variants are sometimes diffi- cult to be distinguished from high grade sarcoma or other sarcomatoid carcinomas which requires SF-1 immuno- histochemistry to identify the adrenocortical origin in those tumor cells [13]. However, universally applicable diagnostic criteria including those characteristic ACC
subtypes have not yet to be established at this juncture.
Therefore, the WHO 5th edition classification newly defines the “essential” and “desirable” histopathological criteria as summarized in Fig. 1 [3]. The “essential” cri- teria contain the histological evidence of malignancy based on at least one of multiparameter scoring diagnos- tic systems (Weiss, Modified Weiss, Helsinki, Reticulin), in addition to that of adrenocortical origin, Ki-67 and mitotic figure counts. In addition, “desirable” criteria contain the confirmation of adrenocortical origin by SF-1 immunohistochemistry and application of the prognostic
biomarkers [3]. The representative histological images of various types of ACCs including low and high grade are illustrated in Fig. 2.
Of particular note, the WHO 5th edition classification also emphasized the significance of recognizing the foci of lymphovascular invasion, and recommended employ- ing platelet markers such as CD61 in immunohisto- chemical identification of vascular invasion as well as immunohistochemical detection of circumscribing tumor nests within blood vessels [3]. This particular usage of platelet markers is considered reasonable because lym- phovascular invasion of carcinoma cells usually results in injury to the endothelial cells recruiting the platelets at the relevant areas. In addition, the status of IGF-2 over- expression in carcinoma cells was also proposed as a useful immunohistochemical marker in differentiating benign from malignant tumors with a positive perinu- clear dot-like intracellular localization of IGF-2 specific for ACCs but its evaluation remains in dispute in actual clinical practice [3, 13]. On the other hand, the Ki-67 proliferative index is considered a clinically important marker not only for differentiating between benign and malignant adrenocortical tumors but also for predicting clinical outcome or prognosis of ACC patients [3]. How- ever, it is also true that its cutoff value between high- grade and low-grade tumors remains controversial. In 2018 The ENSAT (European Network for the Study of Adrenal Tumors) guidelines proposed setting the cutoff value for the Ki-67 proliferative index at 10%, with those lower than 10% in Stage I and II with complete resection classified as low or intermediate grade [14]. A proposal has been made to clinically determine postoperative adjuvant mitotane therapy according to this grade of ACC [14]. ENSAT practice guidelines recommended treatment with mitotane alone instead of the combination of mitotane and EDP in the high-risk group with a Ki-67 of 10% or greater [14]. Since the FIRM-ACT phase III ran- domized trial reported in 2012, etoposide, doxorubicin and cisplatin combined with mitotane (EDP-M) has been the first-line treatment strategy for metastatic ACC [15]. However, there is still much controversy on the clinical or therapeutic benefits of chemotherapy, especially for ACC patients with low performance status as well as the combination of other therapeutic agents including immune-checkpoint inhibitors [16]. Recently, based on the preliminary results of the ADIUVO study published by Terzolo et al. in 2023 studying completely resected cases of low-grade ACC, the survival rate in the mitotane-treated group tended to be slightly higher than that in non-treated, but the survival curve displayed no significant differences [17]. However, it should be noted when interpreting the results above that the recruited number in the ADIVUO study was rather small [17].
The ENSAT guideline clearly states that the Ki-67 prolif- erative index should be obtained after careful review of the entire specimen in all ACC cases, evaluating the highest areas of positive carcinoma cells or hotspots, and preferably using the image analysis system [14]. In con- trast, the WHO 5th edition classification sets the cutoff value for the Ki-67 proliferative index at 15%, and it is necessary to perform a comprehensive evaluation in con- junction with the count of mitotic figures (cutoff is 20 pieces/10 mm2) [3]. However, consensus is yet to be re- ported regarding the cutoff value and the standardization of methodology [3, 14, 18]. In addition, based on our previous reports, the Ki-67 proliferative index in ACCs differed enormously in values between evaluating hotspots and the average of the whole tumor, and values also dra- matically changed when image analysis was used [19]. Therefore, further investigation is definitively warranted for the standardization of the Ki-67 proliferative index when determining the cutoff value in ACC patients.
In addition to these potential drawbacks, not only dif- ferentiation between benign and malignant, but also risk stratification of high-grade ACCs has been extensively examined. The ENSAT group proposed the S-GRAS score as a representative and practical stratification index, which was composed of S: ENSAT stage; G: grade (Ki-67 labeling rate); R: resection surgical margin; A: age at diagnosis; and S: presence or absence of symptoms [20].
The risk stratification of ACCs including the factors of various genotypes and phenotypes has also been studied in the last decade using divergent comprehensive analyti- cal approaches of omics as mentioned as follows, but there has been no consensus on reliable risk stratification of patients reported at this juncture.
2. Molecular Profiles of ACCs and Their Clinical Significance
Several studies of comprehensive genetic analyses of ACCs have been reported in the last decade and they provided a wide variety of genetic alterations. Their clin- ical significance is summarized in Fig. 3. In addition, genome-wide approaches including transcriptome, SNP array, and methylome and miRome analyses have also been reported over the last decade and succeeded in identifying new genetic and epigenetic alterations, which further enabled clustering of ACCs into subgroups asso- ciated with different prognosis for stratification.
2-1. DNA genomic mutations in ACCs
Based on the recent development of comprehensive genetic analysis, the four major genotype clusters have been proposed in ACCs as summarized in Fig. 3: (i) Wnt/B-catenin signaling pathway (CTNNB1 mutation
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A) Hematoxylin and eosin (H&E)-stained section, B) Alcian-blue stained section of myxoid ACC: although the cytological atypia is not marked, myxoid change stained by alcian-blue was detected in intervening stroma. This histological subtype is frequently underestimated by conventional Weiss criteria.
C) H&E-stained section of oncocytic ACC: tumor cells have abundant eosinophilic or oncocytic cytoplasm with nuclear pleomorphism. These tumors should be evaluated by multiple scoring systems including the Lin-Wiess-Bisceglia criteria. In contrast to other endocrine organs, the WHO 5th edition classification does not define the category of adrenal oncocytoma because of insufficient characterization. Adrenal oncocytoma was previously determined as a non-functional tumor with frequent absence of SF-1 immunoreactivity. This category is required for further molecular clarification.
D) H&E-stained section, E) Ki-67 IHC section of low-grade ACC: monotonous proliferation of ovoid tumor cells with eosinophilic cytoplasms with low-intermediate cytological atypia. Ki-67 proliferative index is less than 10%.
F) H&E-stained section, G) Ki-67 IHC section of high-grade ACC: tumor cells with severe cytological atypia proliferate in high cellular density with broad area of coagulative necrosis. Ki-67 proliferative index is higher than 20%. Scale bar: 300 um
Wnt/B-catenin
Chromosome/ Chromatin remodeling
p53/Rb1
MMR
| Genotype clusters | Genes |
|---|---|
| (i) Wnt/ß-catenin pathway | ZNRF3, APC, CTNNB1 etc. |
| (ii) p53/Rb1 pathway | CDKN2A, TP53, Rb1, CDK4, MDM2 etc. |
| (iii) Chromosome/Chromatin remodeling pathway | MEN1, DAXX, ATRX, TERT, TERF2 etc. |
| (iv) MMR (Mismatch repair) pathway | MLH1, MSH2, MSH6, PMS2 etc. |
| Authors | Year | N | Analytical method | Detected gene alteration | Clinical significance |
|---|---|---|---|---|---|
| Ross JS et al. [23] | 2014 | 29 | 3,320 exons from 236 cancer-related genes and 47 introns of 19 genes by NGS. | TP53 (34%), MEN1 (14%) CTNNB1 (10%), APC (7%), DAXX (7%), KDM5C (7%), LRP1B (7%), MSH2 (7%) and RB1 (7%). | 59% had genetic alteration associated with an available therapeutic or a clinical trial. |
| Assié G et al. [21] | 2014 | 45 | Integrated genomic analysis | ZNRF3 (21%), CTNNB1 (16%), TP53 (16%), CDKN2A (11%), Rb1 (7%), MEN1 (7%), DAXX (6%), TERT (6%), MED12 (5%) and APC (2%). | Numerous mutations and DNA methylation alterations: Poor outcome: |
| 335,765 exons from 20,975 genes and SNP array by NGS. | Specific deregulation of two miRNA clusters: Good prognosis | ||||
| Juhlin CC et al. [25] | 2015 | 41 | WES by NGS (paired with normal). | TP53 (19.5%), TERT (14.6%), CTNNB1 (9.8%), ZNRF3 (9.8%), KREMEN1 (7.3%). | NA |
| Pinto EM et al. [26] | 2015 | 31 (Pediatric) | WGS or WES. | 11p LOH (91%), Chr17 loss (76%), TP53 (68%), ATRX (13%), CTNNB1 (8%). | Germline TP53 and somatic ATRX mutations : failure of standard chemotherapy. |
| Zheng S et al. [27] | 2016 | 91 | WES and RNA sequencing and genome wide copy number analysis by NGS. | TP53 (21%), ZNRF3 (19%), CDKN2A (15%), CTNNB1 (16%), TERT (14%), PRKAR1A (11%), MDM2 (6.8%), CDK4 (6.8%), Rb1 (6.8%), MEN1 (6.8%), CCNE1 (5.7%), APC (3.3%). | Three-grade integrated molecular classification reflects patients' outcomes. |
| Lippert J et al. [28] | 2018 | 107 | Targeted sequencing of 160 genes and pyrosequencing of 4 genes by NGS, using FFPE. | TP53 (22%), CTNNB1 (17%), NF1 (11%), APC (8.4%), ZNRF3 (8.4%), MEN1 (7.4%), GNAS (6.5%), and ATRX (6.5%). NOTCH1, CIC, KDM6A, BRCA1, and BRCA2 (all >2.8%). | Integrated score (somatic mutation in Wnt/b-catenin and p53 pathways, high methylation pattern and clinical/histopathological parameters) reflects PFS. |
| Vatorano S et al. [24] | 2018 | 62 | Targeted sequencing and copy number variation analyses for 18 genes, by NGS, using FFPE. | Wnt/ß-catenin alterations (40%), p53/Rb (28%), mismatch repair (18%), chromatin-remodeling (14%) | p53/Rb1 pathway: High risk Oncocytic type: lowest mutation burden Conventional and myxoid type: Rb1 and CDK4 high prevalence. |
| Pozdeyev N et al. [22] | 2021 | 364 | Targeted sequencing by FoundationOne CDx. | TP53: 38%, CTNNB1: 28%, ZNRF3: 17%, MMR gene alteration: 13.7%, CDKN2A: 13%, RB1: 12%, MEN1: 12%, ATRX: 11%, TERT promoter: 10%, APC: 10%, NF1: 9%, LRP1B: 8%, IL7R: 6%, FRS2: 4%, ARID1A1 4%, KRAS: 3%. | More than 50% have potentially actionable genomic alterations. |
| Lippert J et al. [29] | 2022 | 237 | Targeted pyrosequencing (methylation) by NGS, using FFPE. | Hypermethylation in PAX5 (27.9%), GSTP1 (13.9%), PTCARD (49%), PAX6 (49%), and GOS2 (25.3%). | PAX5 hypermethylation was associated with OS. |
| Nazha B et al. [30] | 2022 | 122 | Guardant 360, using blood samples. | TP53 (52%), EGFR (23%), CTNNB1 (18%), MET (18%), and ATM (14%). | 47% had pathogenic and/or likely pathogenic mutations in therapeutically relevant genes. |
Fig. 3 Summary of genetic alteration in ACCs ACCs are classified into four major genotypes, and the individual pathways with relevant genes are summarized. Several major comprehensive genetic analyses published in the last decade and their findings on gene mutations are listed. Abbreviation: WES: whole exome sequencing, WGS: whole genome sequencing, NGS: next generation sequencing
and ZNRF3 deletion); (ii) p53/Rb1 cell cycle regulation pathway (TP53, RB1, MDM2, CDK4, and CDKN2A mutations); (iii) chromosomal maintenance/chromatin remodeling pathway (DAXX, ATRX, MEN1, TERT muta- tion, and TERF2 amplification, etc.); and (iv) MMR (mismatch repair) pathway (MLH1, MSH2, MSH6, and PMS2 mutation, etc.). In addition to these four genotype clusters, the PKA (protein kinase A) pathway (PRKAR1A mutations, etc.) was also reported as a cause of ACC associated with Carney’s complex [21-30].
Pozdeyev et al. analyzed 364 adult ACCs and reported the prevalence of genetic alterations, including TP53: 38%; CTNNB1: 28%; ZNRF3: 17%; MMR gene alter- ation: 13.7%; CDKN2A: 13%; RB1: 12%; MEN1: 12%; ATRX: 11%; TERT promoter: 10%; APC: 10%; NF1: 9%; LRP1B: 8%; IL7R: 6%; FRS2: 4%; ARID1A1: 4%; and KRAS: 3% [22]. Gara et al. performed whole-exome sequencing in 33 ACC cases with distant metastasis and compared the genetic profiles between primary and metastatic lesions. They reported that 37-57% of gene mutations overlapped but a higher mutation rate was detected in those associated with metastasis [31].
In the WHO 5th edition classification, high-grade adult ACCs frequently harbored ß-catenin nuclear transloca- tion and/or p53 aberrant expression (overexpression or loss) [3]. Therefore, such genetic alteration is reasonably postulated to be associated with poor prognosis but is by no means to serve as an independent marker. The genetic profiles of special histological subtypes-including myx- oid, oncocytic, and sarcomatoid-have been examined, and the lowest mutation burden was reported in the oncocytic type, whereas the highest, with a prevalence of Rb1 and CDK4, was reported in the conventional and myxoid types [24]. However, a consensus has not yet been obtained at this juncture and further investigations are required for clarification.
Microsatellite instability (MSI) is a pattern of hyper- mutation that occurs at genomic microsatellites due to defects in the mismatch repair system, and could be a cause of Lynch syndrome. The MMR deficiency subgroup was detected in approximately 5-15% of ACCs [22, 32]. On the other hand, the prevalence of Lynch syndrome among ACC patients was reported as 3.2% [33]. MSI is both a prognostic and a predictive factor of response to immunotherapy in various cancers, and frequently har- bors a high status of tumor mutation burden (TMB). According to the study of pan-cancer by Bonneville et al., the prevalence of MSI-H in ACCs was the fifth highest (4.3%) among 39 cancers, and MSI-high ACCs had a higher average mutational burden than those that were microsatellite-stable [32]. However, compared with other malignancies, ACCs are generally considered as those that are TMB-low, which could be one of the reasons for
developing therapeutic resistance to cancer-immunotherapy in ACCs [34].
In pediatric ACCs, Pinto et al. analyzed 31 pediatric cases, and detected the genetic alteration as 11p LOH (91%), Chromosome 17 loss (76%), TP53 (68%), ATRX (13%), and CTNNB1 (8%) [26]. TP53 gene mutations have been much more frequently detected in pediatric cases than in those of adults [26]. Wasserman et al. specifically examined TP53 mutation in both germline and somatic levels in 88 pediatric ACC cases with subse- quent functional validation by in vitro study, and they detected the germline variant in 50%, not necessarily corresponding to those previously detected within the hotspots [35]. In particular, they also reported pediatric ACCs with alleles encoding TP53 protein with higher functionality were less likely to have a strong family his- tory of cancer, whereas those with greater loss of func- tion had multiple primary malignancies and/or a positive family history, and the prevalence of TP53 mutations declined with age [35].
2-2. Chromosomal abnormalities in ACCs
Based on studies on copy number variation (CNV) analyses, CNVs were distributed broadly across the ACC genome. Large-scale amplification of chromosome 19 was detected in 63%, and was associated with stage III/IV disease [36].
Lippert et al. evaluated somatic CNVs in 107 ACC cases. Most frequent CN gains were detected in CDK4 (43%), STK11 (31%), NOTCH1 (19%), TERT (12%), FGFR3 (12%), GNA11 (17%), and MDM2 genes (7.4%), with CN losses at RB1 (5.6%) [28].
ACCs are frequently hypodiploid compared with other cancer types. However, more than 60% of cases had copy number gains and losses, which could be associated with whole genome doubling (WGD) reflecting poor clinical outcomes [27].
2-3. Epigenetic alterations in ACC (methylome and miRtome analysis)
In addition, epigenetic alterations including methyla- tion status, as well as miRNA profiles in ACCs have also been recently studied.
Jouinot et al. reported that combined risk stratification of hypermethylated status of 4 genes (PAX5, GSTP1, PYCARD, and PAX6), high value of the Ki-67 prolifera- tive index and advanced stage of ENSAT staging was the most significant clinical marker predicting overall sur- vival (OS), disease-free survival (DFS), after they per- formed methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA) in 50 training and 203 validated ACC cases [37]. Xiao et al. screened and identi- fied 92 differentially expressed genes and 802 abnormally
methylated genes and found seven aberrantly methylated genes. Among these seven genes (six hypermethylated genes: KCNQ1, PTGER4, HOXA5, CD14, NR2F1, and CYP11B1, and one hypomethylated gene: ESM1), the expression or methylation status was significantly corre- lated with different pathological stages and overall rates of survival of those ACC patients [38]. Mohan et al. reported the clinical significance of GOS2 hypermethyla- tion in ACCs characterized by upregulation of cell cycle and DNA damage response programs, which could inde- pendently predict shorter DFS and OS in median 14 and 17 months, respectively. They also proposed the prog- nostic stratification of ACCs scaled by GOS2 hypermeth- ylation combined with the validated molecular markers (BUB1B-PINK1) which could classify the ACC patients into three groups [39]. Lippert et al. subsequently used FFPE samples and performed targeted pyrosequencing in 237 ACCs, resulting in hypermethylation within genes of PAX5 (27.9%), GSTP1 (13.9%), PYCARD (49%), PAX6 (49%), and G0S2 (25.3%), which was associated with both PFS and OS with hazard ratios between 1.4 and 2.3 [29]. Among them, only hypermethylation of PAX5 revealed significant association with OS in multivariable analysis. The authors then proposed a modified S-GRAS model for risk stratification including PAX5 methylation status, which could more precisely evaluate the progno- sis of patients with ACCs compared to S-GRAS alone [29].
As for miRNA profiling in ACCs, many previous studies have been published, which mainly evaluated the potential diagnostic of clinical value of miRNA profiles for differentiating between benign and malignant tumors. Among those, miR-483-5p and miR-483-3p were the most validated miRNAs upregulated, while miR-195 and miR-335 were downregulated in ACCs compared with normal adrenal glands and/or adenomas [40, 41]. Wang et al. reported that miR-483-3p was overexpressed in 68% (17 of 25) of ACCs, as opposed to 12% (3 of 25) of adenomas [42], which was further validated by serum specimens of ACC patients by examining circulating miRNAs [43]. Increased expression of miR-483-5p was associated with significantly poor prognosis in ACC patients and is further correlated with high IGF2 expres- sion levels [44, 45]. In contrast, low miR-195 expression level is significantly associated with poor OS in both adults and pediatric ACCs [44, 46] due to the fact that the miR-195 locus was within chromosome 17, which was frequently deleted in the pediatric ACCs described above [40].
In addition to the aforementioned miRNAs, upregu- lated miRNAs following the validation in ACCs com- pared to normal adrenal glands and/or adenomas were: miR-10-5p, miR-21-3p, miR-21-5p, miR-22-3p, miR-
34b-5p, miR-128, miR-139-5p, miR-146a, miR-148b-3p, miR-184, miR-210, miR-340, miR-410, miR-421, miR- 424-3p, miR-424-5p, miR-503, miR-506-3p, miR-506-5p, miR-508-3p, miR-509-3p, miR-509-5p, miR-542-3p, miR-542-5p, and miR-598-whereas downregulated miRNAs were: miR-7, miR-34a, miR-100, miR-125b, miR-139-3p, miR-214, miR-335, miR-375, miR-485-3p, miR-497, miR-511, miR-675, miR-1974, and others [40-50]. Some of those miRNAs above were functional but miRNA expression profiles did not necessarily have disease or tissue specificity, which markedly limited the clinical utility or validity of those findings. Further in- vestigations for the discovery of new surrogate biomark- ers are expected in this field.
2-4. Transcriptomic characterization in ACCs
According to several previous transcriptome analyses, ACCs were generally classified into three subgroups based on mRNA expression profile: the adenoma group and the aggressive and indolent carcinoma groups [21, 51, 52]. In previous divergent mRNA profiling, several specific mRNA markers, including BUB1B and PINK1, have been ascertained as those indicating improved prog- nosis for ACCs [53]. In addition, Xiao et al. reported that ACCs with higher expression levels of TOP2A, CDK1, NDC80, CDKN3, and CEP55 represented shorter OS and DFS [54]. The latest comprehensive transcriptome analy- sis performed by Sun-Zhang et al. identified 3,903 sig- nificant differentially expressed genes when comparing ACCs and adrenocortical adenomas, among which 461 of 3,903 genes significantly impacted survival rate. The five transcripts of PBK, CCNB2, CDK1, ASPM, and PTTG1 with the highest absolute fold changes impacted on worse survival rate [54]. They also reported that expression levels of 25 genes regulating cell differentia- tion, steroidogenic enzymes, cholesterol transporters, and their transcriptional regulator, such as SF1 (NR5A1), were not necessarily correlated with the results of the Weiss criteria and the presence of TP53 mutation, but rather were associated with the presence of Wnt signal- related gene mutation (high expression) and sarcomatoid variant tumors (low expression) [55].
The great majority of the previous studies on tran- scriptome analyses used frozen tissue specimens but Jouinot et al. analyzed 131 adrenocortical tumors and profiled by transcriptome analysis using formalin-fixed paraffin embedded (FFPE) tissue specimens [56]. In addition, they also validated the prognostic value of FFPE transcriptome and demonstrated it as an indepen- dent prognostic factor in a multivariable model including tumor stage and Ki-67 proliferative index [56]. In partic- ular, oncocytic tumors did not necessarily form any spe- cific clusters regardless of their malignant potential [56].
As for fusion-genes, several uncommon fusion genes have been detected but no significantly frequent or pathological genes have been reported at this juncture [27]. More data is required to ascertain their possible roles in the pathogenesis of ACCs.
Considering the genetic characteristics of ACCs men- tioned above, the ENSAT group proposed a modified S-GRAS prognostic prediction scoring system, including the aforementioned high-risk group genotypes (Wnt/ B-catenin signal, p53/Rb1 pathway, and PAX5 hyper- methylation) as summarized in Fig. 4, which could further stratify the prognosis and more accurately charac- terize high-risk ACCs [7].
However, it is also important to note that these gene mutations related to the prediction of clinical outcome for patients yielded hardly any possible therapeutic tar- gets. Numerous genetic profiles have been identified at this juncture as mentioned above, but the genetic charac- teristics of ACC cases who underwent gene panel testing that could be proposed for treatment was extremely lim- ited in Japan. In addition, it is difficult to routinely per- form genetic analysis in actual clinical practice, and its clinical utility is still limited in Japan. The data accumu- lation of these surrogate markers, which potentially have not only diagnostic value but which may also become possible therapeutic targets in ACCs, is expected in the near future.
3. Endocrine Function (Steroid Production) and Tumor Microenvironment
As described above, ACCs not only have the charac- teristics of a malignant tumor, but also have the charac- teristics of endocrine tumors associated with steroid hormone excess in the case of functional tumors, harbor- ing remarkably unique or characteristic intratumoral heterogeneity [4]. Approximately 60% of ACCs are functional, and two-thirds of these functional tumors have clinical symptoms associated with excessive hor- mone production represented by Cushing’s manifestation and/or virilization [6, 57]. The most frequently produced hormone is cortisol, but approximately 30% of functional ACCs produce multiple hormones including steroid hor- mone precursors. ACCs frequently display unique steroid hormone production named “disorganized steroidogene- sis” and/or “combined steroidogenesis” [4, 5, 57].
3-1. In situ glucocorticoid production and TILs (tumor-infiltrating lymphocytes)
In recent years, an association has been reported between in situ steroidogenesis and the tumor microenvi- ronment: especially for the profile of tumor-infiltrating lymphocytes (TILs) and for determining the usefulness and response prediction of immune checkpoint inhibitors and their possible mechanisms in ACCs.
Landwehr et al. reported that CD4+ T-lymphocytes were significantly lower in ACCs with glucocorticoid
| S-GRAS | |
| (S) ENSAT Staging | Opt: Stage 1,2 |
| 1pt: Stage 3 | |
| 2pts: Stage 4 | |
| (G) Grading Ki-67 | Opt: 0-9% |
| 1pt: 10-19% | |
| 2pts: ≥20% | |
| (R) R | 0pt: R0 |
| 1pt: RX | |
| 2pts: R1 | |
| 3pts: R2 | |
| (A) Age at diagnosis | Opt: < 50 y.o |
| 1pt: >50 y.o | |
| (S) Symptoms (Hormone, tumor etc) | Opt: No |
| 1pt: Yes |
S-GRAS: 0-1
Genetic alterations in
2-3
1pt: Wnt/B-catenin
+
1pt: Rb/p53 pathways
4-5
6-9
1pt: hypermethylated PAX5
Fig. 4 Modified S-GRAS scoring systems
The ENSAT group proposed a modified S-GRAS scoring system combined with the molecular characteristics of hypermethylation in the PAX5 gene and/or mutations within the Wnt signaling pathway and/or mutations within p53/Rb1 signaling pathways.
excess, resulting in poor prognosis or adverse clinical outcome for patients [58]. We also recently analyzed the profiles of steroidogenic synthases (particularly cortisol synthases CYP17A and CYP11B1) and TILs, selecting multiple areas within tumors in order to circumvent or overcome the potential intratumoral heterogeneity [6]. Results demonstrated that the number of CD8+ T lym- phocytes increased in areas with high expression of CYP17A, whereas the number of CD4+ T lymphocytes decreased in areas with high expression of CYP11B1. Of particular interest, the localization of cortisol synthases (CYP17A and CYP11B1) was not necessarily mutually concordant, which possibly reflected the status of disor- ganized steroidogenesis in ACCs. Therefore, in situ steroidogenesis in ACCs could be considered in a more complex manner, and the effects of disorganized in situ steroid production on the tumor microenvironment was considered to be more complex [6]. Based on the results above, the tumor microenvironment may be modulated in cases of functional ACCs, including glucocorticoid excess, which should make it rather difficult to interpret the pathophysiology and to predict the response of immune checkpoint inhibitors in ACCs.
Several past studies indicated that a small population of a particular subgroup of ACCs benefitted from immune checkpoint inhibitors, and their clinical out- comes were rather heterogeneous with an objective response rate (ORR) between 6% and 33% [59-62]. In addition, factors predicting the clinical response to immunotherapy are still controversial. Recently, an asso- ciation has been examined in ACCs between the efficacy of immune checkpoint inhibitors and their predictive fac- tors, such as anti-PD-1 and anti-PD-ligand-1 (PD-L1) antibodies, and anti-cytotoxic-T-lymphocyte-associated- antigen 4 (anti-CTLA-4) [63, 64]. Studies reported the heterogeneous expression of PD1, PD-L1, and CTLA-4 in ACCs, possibly resulting in the heterogeneous out- comes of the immunotherapy. However, PD-1 expression was a strong prognostic biomarker of immunotherapy in ACCs in the same fashion as other malignant solid tumors, which can easily be applied in routine histo- pathological assessment [63, 64]. Remde et al. reported a retrospective study on clinical outcomes of immunother- apy in 54 advanced ACC cases [65]. They reported that positive tissue staining for programmed cell death ligand 1 (PD-L1) was associated with a longer progression-free survival. Adjusted for concomitant mitotane use, treat- ment with nivolumab was associated with lower risk of progression [65].
Previously reported studies suggest that patients with ACCs received minimal benefits from cancer- immunotherapy but a high expression level of immune modulators was detected in patients with low steroid pro-
duction, possibly indicating that activation of these biomarkers may be a potential target for adjuvant therapy after clearance of excessive glucocorticoids. In addi- tion, ACCs with low steroid production have higher immune cell infiltration than those with abundant steroid production [66, 67]. In addition, as illustrated in Fig. 5, glucocorticoids have also been reported to act on adja- cent tumor cells via glucocorticoid receptors (GR) in a paracrine-like manner. Wu et al. reported that ACCs with glucocorticoid overproduction have significantly lower expression of GR and fewer CD4+ and CD8+ T lymphocytes [68]. Furthermore, there are genes down- stream of GRE (GR responsive element) that are involved in the maturation, proliferation, and migration of these T lymphocytes. They reported that the expres- sion of these genes is also decreased, indicating that immune checkpoint inhibitors were less effective in cases of ACCs with glucocorticoid excess because of down- regulation of GR [68]. These findings could also indicate the limit of mitotane effects. In contrast, mitotane pre-treatment before immune checkpoint inhibitors to inhibit in situ glucocorticoid production could possibly modulate tumor immunity and might enhance its efficacy. However, the effects of steroid pro- duction on the tumor microenvironment are still largely unknown and further investigation is expected in the future.
3-2. In situ glucocorticoid production and cell senescence
In addition, we also proposed a possible association of in situ glucocorticoid excess with cellular senescence in cortisol-producing adenomas [69]. Cellular senescence is defined as a form of durable persistent/irreversible cell cycle arrest that maintains homeostasis of cellularity (to prevent tumorigenesis), and is induced by a variety of potentially oncogenic stimuli or stress [70, 71]. Cellular senescence has been reported to cause cellular or organ dysfunction and to be associated with various neoplastic, inflammatory, degenerative, and even endocrinological diseases [70, 71]. Previous in vitro studies also reported that chronic exposure to excessive glucocorticoid levels could lead to stressful stimuli or even cell line damage, resulting in an irreversible status of cell cycle arrest (cell senescence) [69, 72]. The International Cell Senescence Association (ICSA) recommendation proposed a work- flow to determine the senescent cells in human bodies [73]. The representative biomarkers for cellular senes- cence screening are the SA-ß-galactosidase and the lipo- fuscin granules [73]. In addition, p16 and p21 are additional markers for verification. It has been reported that p21 is the marker of initiation and p16 is the marker of sustenance of cellular senescence [73].
A
T-cell differentiation T-cell activation T-cell proliferation Chemokine Lymphocytes migration
Cortisol
GR
GR GR
GC excess(-) ACC
PD-L1
CD4/CD8 T-lymphocytes
PD-L1
PD-L1
B
Cortisol ît
T-cell differentiation T-cell activation T-cell proliferation Chemokine Lymphocytes migration
Cortisol 1
GF R
Cortisol ît
GC excess(+) ACC
CD4/CD8 T-lymphocytes
PD-L10
C
Cortisol 1
??
GC excess(+) with disorganized steroidogenesis ACC
T-cell differentiation T-cell activation T-cell proliferation Chemokine Lymphocytes migration
GR
??
Precursor 1
??
Precursor 1
??
CD4/CD8 T-lymphocytes
??
PD-L10
Tumor cells of cortisol-producing adenomas fre- quently harbor abundant lipofuscin granules and accom- pany lymphocyte aggregation in intervening stroma [69]. The results of our previous study indicated that these
markers, including p16, p21, and SA-ß-galactosidase, were abundantly expressed in tumor cells in cortisol- producing adenomas rather than in aldosterone-producing cells, leading to senescent-associated secretory phenotype
Hormonal activity
· Disorganized / Combined steroidogenesis
· In situ glucocorticoid excess on tumor microenvironment
Genetics
· Risk stratification
1) Wnt/catenin pathway
· Therapeutic targets
2) p53/Rb1 pathway
3) Chromosomal remodeling
4) MMR
+
Chromosomal abnormalities, methylation, miRNA, transcriptome,
Histopathology
·WHO 5th ed. Classification
Comprehensive diagnosis: Weiss, Weiss revisited, Reticulin algorithm, Helsinki+Ki-67, mitotic count, etc.
Graphical Abstract
(SASP) accompanying lymphocyte aggregation [69, 74]. However, the situation could be different with ACCs compared to adenomas because of the nature of malig- nant cells accumulating DNA damage towards immortal- ization, particularly in the case of frequent genetic alteration of CDNK2A, which encodes p16, and has also been reported by comprehensive genetic analyses of ACCs, as described in the section above [14, 26]. Further investigations are also required to clarify a possible mechanism of in situ glucocorticoid excess to influence the tumor microenvironment of ACCs.
Conclusion
Histopathological diagnosis of adrenocortical tumors currently requires not only determining whether the tumor is benign or malignant, but also stratifying its bio- logical or clinical behavior, especially in high-grade ACCs. For the last decade, comprehensive molecular analyses including whole genome sequencing, transcrip- tome, miRome, methylome, and others have provided detailed molecular characterization as well as a phenotype-genotype association in ACCs, and these genetic alterations could partially contribute to the strati- fication of the degree of malignancy or predict the clini- cal outcome of ACC patients. However, it is also true that no therapeutic targets have been identified by those analyses above compared to those for other malignan- cies. In addition, excessive steroid production, especially
GC, in functional ACCs could modulate the tumor microenvironment resulting in the development of thera- peutic resistance to immune checkpoint inhibitors. The status of disorganized steroidogenesis, the hallmark of hormonal features of ACC, could also result in a more complicated pathophysiology of ACCs. Mitotane pre- treatment before immune checkpoint inhibitors to elimi- nate in situ glucocorticoid production could possibly optimize subsequent immunotherapy, but further data accumulation and other potential therapeutic targets are definitively required in order to understand the compli- cated pathophysiology of functional ACCs as well as to overcome the poor clinical outcomes. The integrated and comprehensive characterization of these genetic, histo- pathological and hormonal features of ACC are indeed expected for risk stratification in order to overcome poor outcome as well as limited therapeutic options of ACC patients summarized in Graphical Abstract.
Acknowledgments
This work was supported by JSPS KAKENHI (grant no. 22K16406) and Health Labour Sciences Research Grant (No. 23FC1041).
Disclosures
Nothing to disclose.
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