RNA-Sequencing Analysis of Adrenocortical Carcinoma, Pheochromocytoma and Paraganglioma from a Pan-Cancer Perspective

Hierarchical classification-based pan-cancer methylation analysis to classify primary cancer

Hierarchical classification offers a more specific categorization of data and breaks down large classification problems into subproblems, providing improved prediction accuracy and predictive power for undefined categories, while also mitigating the impact of poor-quality data. Despite these advantages, its application in predicting primary cancer is rare. To leverage the similarity of cancers and the specificity of methylation patterns among them, we developed the Cancer Hierarchy Classification Tool (CHCT) using the idea of hierarchical classification, with methylation data from 30 cancer types and 8239 methylome samples downloaded from publicly available databases (The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO)). We used unsupervised clustering to divide the classification subproblems and screened differentially methylated sites using Analysis of variance (ANOVA) test, Tukey-kramer test, and Boruta algorithms to construct models for each classifier module. After validation, CHCT accurately classified 1568 out of 1660 cases in the test set, with an average accuracy of 94.46%. We further curated an independent validation cohort of 677 cancer samples from GEO and assigned a diagnosis using CHCT, which showed high diagnostic potential with generally high accuracies (an average accuracy of 91.40%). Moreover, CHCT demonstrates predictive capability for additional cancer types beyond its original classifier scope as demonstrated in the medulloblastoma and pituitary tumor datasets. In summary, CHCT can hierarchically classify primary cancer by methylation profile, by splitting a large-scale classification of 30 cancer types into ten smaller classification problems. These results indicate that cancer hierarchical classification has the potential to be an accurate and robust cancer classification method.

Whole transcriptome analysis of canine pheochromocytoma and paraganglioma

Pheochromocytomas and paragangliomas (PPGLs) are neuroendocrine tumors arising from the chromaffin cells in the adrenal medulla and extra-adrenal paraganglia, respectively. Local invasion, concurrent disorders, and metastases prevent surgical removal, which is the most effective treatment to date. Given the current lack of effective medical treatment, there is a need for novel therapeutic strategies. To identify druggable pathways driving PPGL development, we performed RNA sequencing on PPGLs (n = 19) and normal adrenal medullas (NAMs; n = 10) of dogs. Principal component analysis (PCA) revealed that PPGLs clearly clustered apart from NAMs. In total, 4,218 genes were differentially expressed between PPGLs and NAMs. Of these, 232 had a log2 fold change of >3 or < -3, of which 149 were upregulated in PPGLs, and 83 were downregulated. Compared with NAMs, PPGLs had increased expression of genes related to the cell cycle, tumor development, progression and metastasis, hypoxia and angiogenesis, and the Wnt signaling pathway, and decreased expression of genes related to adrenal steroidogenesis. Our data revealed several overexpressed genes that could provide targets for novel therapeutics, such as Ret Proto-Oncogene (RET), Dopamine Receptor D2 (DRD2), and Secreted Frizzled Related Protein 2 (SFRP2). Based on the PCA, PPGLs were classified into 2 groups, of which group 1 had significantly higher Ki67 scores (p = 0.035) and shorter survival times (p = 0.04) than group 2. Increased expression of 1 of the differentially expressed genes between group 1 and 2, pleiotrophin (PTN), appeared to correlate with a more aggressive tumor phenotype. This study has shed light on the transcriptomic profile of canine PPGL, yielding new insights into the pathogenesis of these tumors in dogs, and revealed potential novel targets for therapy. In addition, we identified 2 transcriptionally distinct groups of PPGLs that had significantly different survival times.

Genetic spectrum in a Canadian cohort of apparently sporadic pheochromocytomas and paragangliomas: New data on multigene panel retesting over time

OBJECTIVE

Pheochromocytomas (PHEOs) and paragangliomas (PGLs), collectively known as PPGLs, are tumours with high heritability. The prevalence of germline mutations in apparently sporadic PPGLs varies depending on the study population. The objective of this study was to determine the spectrum of germline mutations in a cohort of patients with apparently sporadic PPGLs over time.

DESIGN

We performed a retrospective review of patients with apparently sporadic PPGLs who underwent genetic testing at our referral centre from 2005 to 2020.

PATIENTS

We included patients with apparently sporadic PPGLs who underwent genetic testing at our referral center.

MEASUREMENTS

Genetic analysis included sequential gene sequencing by Sanger method or next generation sequencing (NGS) with a multigene panel.

RESULTS

The prevalence of germline mutations was 26.2% (43/164); 40.0% (30/75) in PGLs and 14.6% (13/89) in PHEOs. We identified four novel pathogenic variants (two SDHB and two SDHD). Patients carrying germline mutations were younger (38.7 vs. 49.7 years old) than patients with no identified germline mutations. From 2015 to 2020, we performed NGS with a multigene panel on 12 patients for whom the initial genetic analysis was negative. Germline mutations in previously untested genes were found in four (33.3%) of these patients (two MAX and two SDHA), representing 9.3% (4/43) of the mutation carriers.

CONCLUSION

The prevalence of germline mutations in our cohort of patients with apparently sporadic PPGLs was 26.2%. Genetic re-evaluation over time using multigene sequencing by NGS assay in a subgroup of patients leads to an increase in the detection of mutations.

RNA splicing factors SRRM3 and SRRM4 distinguish molecular phenotypes of castration-resistant neuroendocrine prostate cancer

Neuroendocrine (NE) differentiation in metastatic castration-resistant prostate cancer (mCRPC) is an increasingly common clinical feature arising from cellular plasticity. We recently characterized two mCRPC phenotypes with NE features: androgen receptor (AR)-positive NE-positive amphicrine prostate cancer (AMPC) and AR-negative small cell or neuroendocrine prostate cancer (SCNPC). Here, we interrogated the regulation of RE1-silencing transcription factor (REST), a transcriptional repressor of neuronal genes, and elucidated molecular programs driving AMPC and SCNPC biology. Analysis of prostate cancer (PC) cell lines, mCRPC specimens, and LuCaP patient-derived xenograft models detected alternative splicing of REST to REST4 and attenuated REST repressor activity in AMPC and SCNPC. The REST locus was also hypermethylated and REST expression was reduced in SCNPC. While serine/arginine repetitive matrix protein 4 (SRRM4) was previously implicated in alternative splicing of REST in mCRPC, we detected SRRM3 expression in REST4-positive, SRRM4-negative AMPC and SCNPC. In CRPC cell lines, SRRM3 induced alternative splicing of REST to REST4 and exacerbated the expression of REST-repressed genes. Furthermore, SRRM3 and SRRM4 expression defined molecular subsets of AMPC and SCNPC across species and tumor types. Two AMPC phenotypes and three SCNPC phenotypes were characterized, denoted either by REST attenuation and ASCL1 activity or by progressive activation of neuronal transcription factor programs, respectively. These results nominate SRRM3 as the principal REST splicing factor expressed in early NE differentiation and provide a framework to molecularly classify diverse NE phenotypes in mCRPC.

What Have We Learned from Molecular Biology of Paragangliomas and Pheochromocytomas?

Recent advances in molecular genetics and genomics have led to increased understanding of the aetiopathogenesis of pheochromocytomas and paragangliomas (PPGLs). Thus, pan-genomic studies now provide a comprehensive integrated genomic analysis of PPGLs into distinct molecularly defined subtypes concordant with tumour genotypes. In addition, new embryological discoveries have refined the concept of how normal paraganglia develop, potentially establishing a developmental basis for genotype-phenotype correlations for PPGLs. The challenge for modern pathology is to translate these scientific discoveries into routine practice, which will be based largely on histopathology for the foreseeable future. Here, we review recent progress concerning the cell of origin and molecular pathogenesis of PPGLs, including pathogenetic mechanisms, genetic susceptibility and molecular classification. The current roles and tools of pathologists are considered from a histopathological perspective, including differential diagnoses, genotype-phenotype correlations and the use of immunohistochemistry in identifying hereditary predisposition and validating genetic variants of unknown significance. Current and potential molecular prognosticators are also presented with the hope that predictive molecular biomarkers will be integrated into risk stratification scoring systems to assess the metastatic potential of these intriguing neoplasms and identify potential drug targets.

Pheochromocytoma/paraganglioma: recent updates in genetics, biochemistry, immunohistochemistry, metabolomics, imaging and therapeutic options

Pheochromocytomas and paragangliomas (PPGLs), rare chromaffin/neural crest cell tumors, are commonly benign in their clinical presentation. However, there are a number of cases presenting as metastatic and their diagnosis and management becomes a dilemma because of their rarity. PPGLs are constantly evolving entities in the field of endocrinology brought about by endless research and discoveries, especially in genetics. Throughout the years, our knowledge and perception of these tumors and their genetic background has greatly expanded and changed, and each new discovery leads to advancement in the diagnosis, treatment and follow-up of PPGLs. In this review, we discuss the recent updates in the genetics, biochemistry, immunohistochemistry, metabolomics, imaging and treatment options of PPGLs.

Mutational profile and genotype/phenotype correlation of non-familial pheochromocytoma and paraganglioma

About 30%-40% of patients with pheochromocytoma (PCC) and paraganglioma (PGL) have underlying germline mutations in certain susceptibility genes despite absent family history of these tumors. Here, we present mutational profile of 101 such patients with PCC/PGL (PPGL) from the highly consanguineous population of Saudi Arabia. Results: Of 101 cases with PPGL, 37/101 (36.6%) had germline mutations. Mutations were detected in 30 cases by PCR and direct Sanger sequencing and in 7 additional cases by NGS. The most commonly mutated gene was SDHB (21/101 cases, 20.8%) and the most common SDHB mutation was c.268C>T, p.R90X occurring in 12/21 (57%) cases. Mutations also occurred in SDHC (4/101, 3.96%), SDHD (3/101, 3%), VHL (2/101, 2%) and MAX (2/101, 2%) genes. The following genes were mutated in 1 patient each (1%), RET, SDHA, SDHAF2, TMEM127 and NF1. Metastatic PPGL occurred in 6/21 cases (28.6%) with SDHB mutations and in 1 case with SDHAF2 mutation. Patients and Methods: DNA was isolated from peripheral blood (53 patients) or from non-tumorous formalin fixed paraffin embedded (FFPE) tissue (48 patients). PCR and direct Sanger sequencing of RET, SDHx, VHL, MAX and TMEM127 genes were performed. Cases without mutations were subjected to whole exome sequencing using next generation sequencing (NGS). Conclusion: About 37% of PPGL without family history of such tumors harbor germline mutations. The most commonly mutated gene is SDHB followed by SDHC, SDHD, VHL, MAX and rarely RET, SDHA, SDHAF2, TMEM127 and NF1. SDHB mutations were associated with metastatic PPGL in more than a quarter of cases.

Pheochromocytoma (PHEO) and Paraganglioma (PGL)

This series of 23 articles (17 original articles, six reviews) is presented by international leaders in pheochromocytoma and paraganglioma (PPGL) [...].

Adrenocortical carcinoma - towards genomics guided clinical care

Adrenocortical carcinoma (ACC) is an aggressive and rare neoplasm that originates in the cortex of the adrenal gland. The disease is associated with heterogeneous but mostly poor outcomes and lacks effective pharmaceutical treatment options. Multi-omics studies have defined the landscape of molecular alterations in ACC. Specific molecular signatures can be detected in body fluids, potentially enabling improved diagnostic applications for patients with adrenal tumours. Importantly, pan-molecular data sets further reveal a spectrum within ACC, with three major subgroups that have different disease outcomes. These new subgroups have value as prognostic biomarkers. Research has revealed that the p53-RB and the WNT-β-catenin pathways are common disease drivers in ACC. However, these pathways remain difficult to target by therapeutic interventions. Instead, a unique characteristic of ACC is steroidogenic differentiation, which has emerged as a potential treatment target, with several agents undergoing preclinical or clinical investigations. Finally, a large proportion of ACC tumours have genetic profiles that are associated with promising therapeutic responsiveness in other cancers. All these opportunities now await translation from the laboratory into the clinical setting, thereby offering a real potential of improved survival outcomes and increased quality of life for patients with this serious condition.