Phaeochromocytomas and paragangliomas (PPGLs) are tumours of the adrenal medulla and
extra-adrenal sympathetic nervous system, respectively, that often secrete
catecholamines(1). The tumours are derived from the neural crest and approximately 50%
are caused by a germline variant. Because of the strong heritability, genetic testing is
recommended in all patients with PPGLs (2-5). Most PPGLs are non-malignant (defined as
non-metastatic) tumours and respond well to surgical treatment. Approximately 15% of
PPGLs are metastatic and incurable by currently available therapies(1). The latest WHO
Blue Book classifies all PPGLs as possibly malignant due to their unpredictable
behaviour(6).
PPGLs are very heterogeneous tumours predisposed by more than 20 distinct genes(1). In
two thirds of the tumours a germline or somatic variant can be identified and thus PPGLs
have been divided into distinct biological subgroups on the basis of these variants(1). A
consensus statement from 2017 stated the necessity for a targeted gene panel
(Next-Generation Sequencing, NGS) in all PPGL patients and testing of tumour DNA if
possible to identify potential future targets for drug therapies(2). Furthermore,
epigenetic changes in PPGLs and other endocrine tumours have been shown to be associated
with the risk of metastatic disease(7-11) and future research should be focused on
understanding both epigenetic and genetic changes in PPGLs as this will open
opportunities for targeted molecular therapies and personalized medicine(11,12). It has
been demonstrated that DNA methylation-based tumour classification is a valuable asset
for clinical decision making(13).
Many histopathological predictive risk factors for poor prognosis have been proposed and
scoring systems have been developed to identify those PPGLs that have a metastatic
potential. The PASS (Pheochromocytoma of the Adrenal Gland Scaled Score) and GAPP
(Grading system for Adrenal Phaeochromocytoma and Paraganglioma) scores are the most
well-known (1,14-18). In a recent meta-analysis the algorithms were evaluated and it was
concluded that both algorithms had a low positive predictive value but a high negative
predictive value for PPGLs which indicated that the models were relevant for ruling out
metastatic potential for both tumour types rather than identifying cases with an
increased risk of disseminated disease. This could most probably be attributed to
subjective assessment of criteria involved in these scoring systems. The authors
concluded that the inclusion of NGS data and an overall molecular approach is needed to
accurately pinpoint cases at risk for future metastases(19). Furthermore, there is a need
for an algorithm based on objective measurements to ensure objectivity in the
pathological diagnosis of PPGLs, similar to algorithms for adrenocortical carcinomas like
the Helsinki Score and the Reticulin Algorithm(19-21). To this end computer-assisted
techniques have shown promising results(11,20).
Correctly identifying PPGLs with a future risk of metastatic disease is a clinical
challenge which impacts not only the physicians but also the patients and their family
members. Today's clinical guidelines are based on 'rule all in' methods which have a
costly impact on the healthcare resources and the quality of life of the patients. An
algorithm based on histopathological, genetic, epigenetic, and clinical variables may be
helpful in stratifying patients into risk categories with different needs for clinical
follow-up.
Pilot Study: Patients followed at Copenhagen University Hospital, Copenhagen have been
part of a pilot study on the effect of genetic screening of family members with SDHX
variants on the clinical presentation of cases. Variants of the SDHX (SDHA, -AF2, -B, -C,
-D) genes are a frequent cause of familial PPGLs. The investigators found distinct
differences in the clinical and histopathological characteristics between genetic
variants in SDHB. Family screening for SDHB variants resulted in earlier detection of
tumours in two families. Patients with SDHA, SDHC and SDHD variants also had severe
phaenotypes, underlining the necessity for a broad genetic screening of the proband. The
study corroborated previous findings of poor prognostic markers and found that the
genetic variants and clinical phenotype are linked and therefore useful in the decision
of clinical follow-up. This study has been presented as master thesis at the University
of Copenhagen 2019 (Grade A) and the manuscript has been published(22). The study
corroborates the feasibility of the current project.
Process of the study.Part 1: Description of the genotype-phaenotype association in a nation-wide cohort of
approximately 400 patients with PPGLs or germ-line genetic variants predisposing to PPGLs
using clinical data, biochemical variables, tumour characteristics and imaging results.
This national cohort will provide characterization of patients making it possible to
identify a metastatic and non-metastatic clinical course, respectively.
Part 2: Identification of novel prognostic biomarkers using formalin-fixed
paraffin-embedded tumor tissue samples for genetic testing (NGS for somatic variants),
DNA methylation, PASS scoring, and immunohistochemical markers. Twenty patients with a
poor prognosis (proof of metastases) and 20 patients with a good prognosis
(non-metastatic) will be included from the Capital Region of Denmark. The results will be
used to develop a new algorithm for clinical prognosis.
Part 3: Validation of the new algorithm in a second subcohort of patients with tumor
tissue specimens selected at random from the national cohort. Tumor specimens will be
subjected to investigation of the same novel prognostic biomarkers identified in part 2.
Results will be entered into the new algorithm to test whether the clinical course can be
accurately predicted.
Dissemination Positive, negative or inconclusive results will be published in
peer-reviewed international journals and presented at scientific meetings and in relevant
patient fora. The study group members are affiliated to ENDO-ERN (European Reference
Network on Rare Endocrine Conditions), a European collaboration of highly specialized
centres treating rare endocrine conditions through which results can be disseminated
(https://endo-ern.eu/).
To ensure completeness and transparency in the reporting of results the investigators
will use the STROBE reporting guidelines relevant to cohort studies.
Patient involvement:
Patients with lived experiences contribute additional expertise and give valuable, novel
insights and thus improve the effectiveness of the study. Furthermore, the patient
perspective is essential in the presentation of the results. Relevant patients with the
disease in question from our outpatient clinic will be invited to participate in the
Steering Committee.
Safety and ethical considerations Treatment of personal data: General Data Protection
Regulation will be strictly adhered to. Approval by the Ethics Committee for the Capital
Region has been granted (H-20065699, 19th of February 2021).
Database: The database will be established under RedCap, which is accessible nation-wide
and managed centrally by the data protection unit of The Capital Region.
Statistics: Based on previous studies which have developed similar algorithms (20,21) the
investigators will need approximately 200 patients to achieve statistical power in
relation to validation of the algorithm in the larger cohort. Study population
characteristics will be presented using descriptive statistics. Group differences will be
tested primarily using non-parametric tests (Mann-Whitney, Wilcoxon) or t-test.
Associations between the genotype and phaenotype will be analysed by ANOVA (analysis of
variance) and regression analysis controlling for relevant confounders, i.e. age and sex,
where appropriate. The sensitivity and specificity of the algorithm to predict poor or
good outcome will be determined using multiple regression analyses, Chi2 and ROC
(Receiver Operating Characteristics). The investigators will seek help from professional
statisticians at Copenhagen University at Statistical Advisory Service for PhD-students
and students at the Faculty of Health Sciences.
