Tissue and Genomic Biomarkers in ACC

Precision Medicine and Biomarker Development

Tissue and genomic biomarkers in adrenocortical carcinoma (ACC) are tumor-derived molecular features used to characterize adrenal cortical malignancy beyond conventional morphology. They include somatic genomic alterations, DNA copy-number changes, DNA methylation patterns, gene-expression profiles, non-coding RNAs, protein signatures, and emerging metabolomic or steroid-related tissue phenotypes.¹²³ Within ACC care, these biomarkers are positioned as adjuncts to endocrine pathology and clinical staging rather than replacements for established standards such as expert histopathology, Weiss-based assessment, Ki-67, ENSAT stage, resection status, and hormone secretion phenotype.⁴²⁵

Across platforms, ACC shows reproducible molecular differences from adrenocortical adenoma and normal adrenal cortex, especially in IGF signaling, Wnt/β-catenin and p53/Rb pathway biology, chromosomal instability, CpG methylation, and proliferative transcriptional programs.⁶⁷⁸ These differences have supported development of molecular classifiers for diagnostically difficult adrenal cortical tumors and for postoperative risk stratification, and they have also defined biologic subgroups that may be relevant for trial enrollment and future therapeutic selection.⁹¹⁰¹¹

The evidence base remains limited by the rarity of ACC. Most biomarker data derive from retrospective cohorts, single-center series, public-dataset re-analyses, and assays that are not yet standardized across laboratories or specimen types.¹²¹³¹⁴ As a result, the strongest current use case is prognostic enrichment after diagnosis, whereas predictive treatment selection remains less reliable and is rarely practice-defining outside selected mismatch-repair–altered or trial-matched contexts.¹⁵³¹⁶

Diagnostic context

Biomarker research in ACC largely addresses three clinical tasks: distinguishing carcinoma from adenoma or borderline adrenocortical neoplasms, refining recurrence risk after surgery, and identifying biologic subsets in advanced disease.⁴² The diagnostic task is especially important when morphology is equivocal, because interobserver variability and tumors of uncertain malignant potential can limit confidence in histology alone.¹⁷¹⁸

At a group level, several molecular platforms separate many ACCs from benign adrenocortical tumors more consistently than single-marker immunohistochemistry alone.⁶¹⁹²⁰ However, performance is less certain in borderline lesions, in uncommon functional subtypes, and when assays are transferred from research tissue workflows to routine FFPE material. The practical implication is that biomarkers may strengthen difficult diagnoses, but expert adrenal pathology remains the reference standard.⁴¹⁸²¹

Major biomarker classes

DNA copy-number and mutational biomarkers

Genomic studies show that ACC generally carries a substantially higher burden of chromosomal disruption than adenoma, and recurrent pathway alterations commonly involve Wnt/β-catenin, TP53/Rb, telomere-related mechanisms, and other cell-cycle programs.²²²³⁸ Copy-number architecture and pathway-level alteration patterns have been associated with recurrence and survival, suggesting that DNA-based profiling can add biologic risk information beyond stage alone.¹⁰²⁴²⁵

Historically, limited-probe cytogenetic studies showed numerical chromosomal abnormalities but also illustrated that such findings were not fully specific for carcinoma and could vary by endocrine phenotype.²⁶ More contemporary targeted sequencing is more informative for subclassification and prognostic modeling than for routine targeted-drug selection, because many detected alterations are not clearly actionable in current ACC care.²⁷¹⁶

What appears reliable is that chromosomal instability and recurrent driver-pathway alterations mark aggressive ACC biology. What remains less reliable is the assumption that a detected mutation directly identifies an effective therapy. In practice, sequencing currently contributes mainly to risk stratification, biologic classification, and referral to molecularly informed clinical trials.⁸¹⁵²⁴

DNA methylation and epigenetic classifiers

Epigenetic biomarkers, especially DNA methylation signatures, have shown some of the most reproducible signals in ACC. Hypermethylation affecting IGF2 regulatory regions and broader CpG island methylation phenotypes has demonstrated both diagnostic and prognostic value across multiple cohorts.¹⁹⁹¹⁸ Clinically oriented markers such as G0S2 and PAX5 may further refine survival prediction when added to established clinicopathologic models.²⁸²⁹⁵

These findings are clinically important because methylation classes appear to track relatively stable biologic subtypes and may be less sensitive to sampling variation than some mutation calls. Paired-sample analyses suggest that methylation and chromosome-level patterns are more conserved across primary and metastatic samples than individual somatic mutations.³⁰

What appears most reliable is the prognostic utility of validated methylation classifiers and, in selected settings, their ability to support the adenoma-versus-carcinoma distinction. What is less reliable is universal assay portability, particularly when methods developed in frozen tissue are applied to FFPE samples without analytic validation. The practical implication is that methylation testing is promising for referral centers and retrospective research, but specimen handling and platform harmonization remain critical.²²¹

Transcriptomic and non-coding RNA biomarkers

Gene-expression profiling has repeatedly separated ACC from adenoma and also identified internal ACC subgroups with markedly different outcomes, including prognostic classes reproducible from FFPE tissue.¹⁶³¹¹¹ Across studies, poor-prognosis tumors consistently show enrichment for cell-cycle, mitotic, and chromosome-instability programs, indicating that much of the prognostic signal reflects a recurring high-proliferation phenotype rather than any single dominant transcript.³²³³³⁴

MicroRNA studies have identified recurrent signals, particularly involving miR-483 family members, miR-503, miR-210, miR-195, and miR-335, in tissue-based and some circulating analyses.³⁵³⁶³⁷¹³³⁸ Long non-coding RNAs, circular RNAs, alternative splicing signatures, enhancer RNAs, and RNA-modification models broaden the field but are mostly derived from retrospective computational analyses and remain exploratory in clinical terms.³⁹⁴⁰⁴¹⁴²⁴³⁴⁴

What is relatively reliable is the existence of transcriptomic classes with prognostic relevance and the repeated observation that ncRNA dysregulation accompanies malignant adrenal cortical biology. What is less reliable is the clinical specificity of many single-gene or single-ncRNA candidates, especially when derived mainly from public databases or indirect pan-cancer analyses.¹¹¹⁴⁴⁵ The practical implication is that multigene or class-based expression frameworks are currently more credible than isolated candidate transcripts.

Protein-expression and proteomic studies have identified candidate markers linked to proliferation, angiogenesis, steroid metabolism, metastatic behavior, and survival.⁴⁶⁴⁷⁴⁸⁴⁹ In parallel, tissue metabolomic and steroid-related phenotyping has suggested that ACC may contain clinically relevant biochemical subtypes, including steroid sulfation patterns associated with outcome.⁵⁰⁵¹⁵²

These approaches help bridge molecular classification with endocrine tumor biology, particularly where hormone production and steroid-handling pathways may reflect both lineage and aggressiveness. Even so, most such assays remain specialized and have not been standardized for routine pathology workflows.

What appears reliable is that proteomic and metabolomic methods detect real biologic differences between ACC and comparator tissues. What is less reliable is their immediate readiness for broad clinical implementation. The practical implication is that they are currently best viewed as translational complements to pathology and genomic data rather than stand-alone clinical tests.⁷²

Evidence for prognosis and treatment selection

The literature increasingly supports prognostic use over predictive use. Molecular classifiers based on methylation, transcriptomic subtype, and selected pathway-level DNA alterations may improve estimation of recurrence or survival beyond ENSAT stage and Ki-67 in retrospective cohorts.⁹¹⁰¹¹⁵ This may be most relevant after curative-intent resection, when surveillance intensity, adjuvant mitotane discussions, and trial prioritization depend on estimating residual biologic risk.²⁹²⁴

By contrast, predictive biomarkers in advanced ACC remain less mature. Sequencing can identify potentially actionable alterations, and selected studies suggest possible links between molecular features and mitotane sensitivity, IGF-pathway dependence, immune contexture, or mismatch-repair deficiency, but these associations are not yet robust enough to define standard treatment pathways for most patients.⁵³⁵⁴⁵⁵⁸⁵⁶ Compared with surgery and established systemic therapy algorithms, biomarker data more often inform trial matching or biologic hypothesis generation than routine drug choice.⁵⁷³¹⁶

What is relatively reliable is that integrated molecular data can identify higher-risk ACC subsets and may enrich clinical research populations. What is not yet reliable is broad precision-oncology matching comparable to that seen in more common cancers. The practical implication is that biomarker-directed treatment decisions should usually be regarded as investigational unless supported by disease-specific validation.¹⁵¹⁶

Limitations and future directions

Several limitations recur throughout the ACC biomarker literature: small sample sizes, retrospective design, assay heterogeneity, limited external validation, and repeated reliance on overlapping public datasets.¹²⁵⁸⁵⁹ Intratumor heterogeneity further complicates interpretation, particularly for mutation-based assays, whereas methylation and broad chromosome-based classes may be more stable across disease sites.³⁰

A second limitation is uneven disease specificity. Many recent biomarker claims arise from pan-cancer or purely computational studies that include ACC as a small subset rather than from ACC-focused tissue validation.⁶⁰⁶¹⁶² These analyses may be useful for hypothesis generation, but they do not by themselves establish a clinically deployable ACC biomarker.

The most credible path forward is likely to involve multicenter validation, standardized assays that perform reliably on routine FFPE material, and demonstration that biomarker-informed strategies improve decisions beyond existing clinicopathologic models.³¹¹⁶³ In ACC, clinically useful tissue and genomic biomarkers will likely be those that are analytically robust, additive to standard care pathways, and tied to a clear diagnostic, prognostic, or trial-selection task rather than solely to molecular description.²⁵¹⁶

Included Articles

PMID 9708944: This case series evaluated telomerase activity in resected adrenal tumors and found positivity in both ACC cases and in some lesions initially classified as benign, two of which later developed recurrence or metastases. The findings suggest telomerase assay may help identify malignant potential beyond routine histopathology, though evidence is limited.⁶⁴

PMID 10433067: In a small series of normal and neoplastic adrenal tissues, telomerase activity remained very low in all seven adrenocortical carcinomas and did not reliably distinguish benign from malignant adrenal lesions. The study suggests telomerase activity is not a useful adrenal malignancy biomarker, with only a tentative signal for separating Cushing adenomas from carcinomas requiring larger validation.⁶⁵

PMID 11134136: In sporadic adrenocortical tumors, carcinomas showed higher VEGF-A and lower thrombospondin-1 than adenomas, while recurrent cases had particularly high VEGF-A. IGF-II overexpression correlated with this angiogenic profile, suggesting a biomarker link between molecular alterations, tumor progression, and relapse risk.⁴⁶

PMID 16677799: A preliminary cDNA macroarray study of paraffin-embedded adrenocortical tumors found feasible but low-yield RNA-based profiling, with ACC showing higher HSP-60, cyclin D1, and topoisomerase I expression and lower jun proto-oncogene expression than adenoma. The findings were presented as exploratory candidate diagnostic, prognostic, and therapeutic biomarkers requiring validation.⁶⁶

PMID 17525484: This review summarizes early molecular pathology approaches for distinguishing adrenal cortical adenoma from carcinoma, highlighting that gene-expression profiling and selected biomarkers such as IGF2 and Ki-67 show diagnostic and prognostic promise. It emphasizes that comparative genomic and single-gene tests had limited clinical utility at the time and required further validation.⁴

PMID 18281524: Array comparative genomic hybridization in 25 ACC tumors identified recurrent copy number gains and losses, with specific aberrations linked to worse postoperative survival. The study suggests that cumulative genomic copy number changes may provide investigational prognostic biomarkers and potential leads for targeted therapy development.²²

PMID 18324346: Expression profiling of chromosome 11q13 in adrenocortical tumors identified 25 genes downregulated in ACC, with six RT-PCR-validated candidates showing diagnostic discrimination from benign tumors. A five-gene combination achieved an AUC of 0.89, supporting early biomarker development for ACC diagnosis.⁶⁷

PMID 18794420: Genomewide expression profiling with RT-PCR validation identified 37 dysregulated genes in adrenocortical carcinoma versus benign adrenocortical tumors, with IL13RA2, HTR2B, CCNB2, RARRES2, and SLC16A9 showing the highest diagnostic accuracy for distinguishing malignancy from benign disease.⁶⁸

PMID 19441174: This review summarizes early genome-wide gene-expression profiling in ACC, emphasizing distinct expression signatures between benign and malignant adrenocortical tumors and their potential utility for diagnosis, prognostic assessment, molecular classification, and identification of therapeutic targets.¹

PMID 19519204: This review summarizes how genomic and gene-expression profiling in ACC may improve diagnosis and prognosis beyond histology alone, including signatures involving IGF2, PINK1, DLG7, BUB1B, and Ki-67. It emphasizes marked molecular heterogeneity, adult-pediatric differences, and the need to translate pathway findings into clinically useful biomarkers and therapies.⁶⁹

PMID 19546168: An integrative microRNA and mRNA profiling study in sporadic adrenocortical tumors identified differential miR expression in ACC, including higher miR-184 and miR-503 and lower miR-511 and miR-214 versus other groups. A miR-511 to miR-503 delta Ct measure distinguished ACC from benign adenomas with high sensitivity and specificity, supporting investigational biomarker development.³⁵

PMID 20097573: This review describes how transcriptome analyses can distinguish adrenocortical adenoma from carcinoma and can further separate ACC into prognostically distinct molecular subgroups. It frames gene-expression profiling as a source of diagnostic and prognostic molecular predictors that may outperform standard clinical and pathological tools and aid difficult differential diagnosis.⁶

PMID 21471143: This study found that miR-675, miR-139-3p, and miR-335 were expressed at lower levels in adrenocortical carcinoma than in adenoma, with PCR-based profiling showing potential to help distinguish malignant from benign adrenocortical tumors. Validation data suggested possible utility in lesions with indeterminate malignant potential, although overlap in values remained.⁷⁰

PMID 22112813: Integrated genomic analysis of adrenocortical tumors found substantially greater chromosomal alteration burden in carcinomas than adenomas and developed a six-locus DNA copy-number classifier that distinguished carcinoma from adenoma in an independent cohort. The study also identified chromosome-based prognostic clustering and linked recurrent copy-number changes to expression of tumorigenesis-related genes, including SF-1-associated 9q34 gain in adenomas.²³

PMID 23921203: Ex vivo HRMAS NMR metabolomics showed that ACC forms a distinct biochemical cluster from adrenal adenoma and pheochromocytoma, with higher lactate, acetate, total choline-containing compounds, and fatty acid content. The study suggests metabolomic profiling may aid difficult adrenal tumor discrimination, although evidence is based on a small retrospective tissue series.⁵⁰

PMID 25144458: This study identifies CYP2W1 as highly expressed in normal and neoplastic adrenal tissue and reports that higher CYP2W1 immunoreactivity in ACC is associated with better outcomes and higher response rates among patients treated with mitotane. The findings support CYP2W1 as a potential predictive biomarker and possible future therapeutic target.⁵⁴

PMID 25265426: This study found that microRNA expression profiles can distinguish adrenocortical carcinomas from adenomas and closely track Weiss histopathologic classification. Upregulated miR-503 and combined underexpression of miR-34a and miR-497 showed high diagnostic performance, suggesting potential value in borderline adrenocortical tumors.³⁶

PMID 25346009: This review highlights early ACC genomic biomarker development for diagnostic discrimination, citing tissue IGF-2 profiling with Ki-67 index and miR-483-5p as reported markers with high specificity in the summarized studies. It frames genomic testing as a potentially useful adjunct to improve diagnosis and inform management.¹⁷

PMID 25595289: Focused lncRNA profiling identified distinct expression patterns separating ACC from adenoma and normal adrenal cortex, and found 66 lncRNAs associated with recurrence. Low PRINS expression was validated in an independent ACC cohort and was also associated with metastatic disease at presentation.³⁹

PMID 26454670: In discussion of a small ACC cohort, KCC4 overexpression was associated with nonfunctional tumors but not with stage or survival, with interpretation limited by sample size and tumor heterogeneity. Preliminary non-peer-reviewed cell-line findings suggested KCC overexpression may promote migration and invasion, supporting exploration as a potential molecular target rather than an established biomarker.⁷¹

PMID 26671553: This review summarizes dysregulated tissue and circulating microRNAs in ACC, highlighting candidate biomarkers for distinguishing carcinoma from adenoma and for estimating prognosis. It also describes functional links between specific miRNAs and oncogenic pathways, while noting that larger cohorts are needed for clinical validation.⁷²

PMID 26768118: Preclinical ACC models showed limited response to the vascular disrupting agent ASA404 compared with a neuroendocrine tumor model, alongside overexpression of TNFAIP3/A20 in ACC. In patient cohorts, higher tumor TNFAIP3 expression correlated with overall survival, supporting investigation of TNF-pathway signaling as a biomarker of treatment response and clinical course.⁷³

PMID 26834703: This review summarizes how deregulated tissue and circulating microRNAs in adrenocortical carcinoma may support noninvasive diagnosis, recurrence detection, prognostic stratification, and future therapeutic targeting. It also emphasizes that current evidence is limited by small cohorts, technical variability, and lack of sufficiently powered longitudinal validation.¹²

PMID 26896602: This review argues that advanced ACC has limited benefit from conventional chemotherapy and mitotane, motivating use of genome-wide expression profiling and next-generation sequencing to identify prognostic subgroups and potentially actionable alterations for more individualized therapy selection. It also highlights that targeted agents studied to date have shown mainly modest activity.⁵⁷

PMID 27077147: This review identifies TERT promoter mutations as a potential biomarker of clinically aggressive adrenocortical carcinoma. In the cited data, mutations were seen in a subset of ACC but not adrenocortical adenomas, while the authors emphasize that larger studies are needed to clarify associations with clinical features and survival.⁷⁴

PMID 27535174: This study evaluates DNA methylation patterns in IGF2 regulatory regions as a diagnostic biomarker to distinguish adrenocortical carcinoma from adrenocortical adenoma. Combined methylation signals showed very high diagnostic accuracy in discovery and independent validation cohorts, supporting an objective molecular adjunct to conventional pathology.¹⁹

PMID 27864864: This review summarizes genomic, transcriptomic, and methylation advances in adrenocortical tumors, noting that in ACC genetic derangements already assist prognostic assessment. It highlights investigational uses of circulating mutated DNA and altered-protein-targeted compounds for earlier diagnosis, biomarker development, and future therapeutic selection.⁷⁵

PMID 27967600: In a multicenter validation cohort of 203 ACCs, tumor CpG island methylation measured by a clinically compatible MS-MLPA assay was independently associated with disease-free and overall survival beyond ENSAT stage and, for overall survival, Ki67. A four-gene methylation signature may improve prognostication and support biomarker-driven follow-up and treatment stratification.⁹

PMID 28332880: This review highlights emerging precision-medicine approaches in ACC, including TCGA-defined genomic features involving Wnt and retinoblastoma pathways, whole-genome doubling with telomerase-associated aggressive behavior, methylation signatures with possible treatment relevance, and mass spectrometry steroid profiling to help distinguish malignant from benign adrenal masses.⁷

PMID 28423361: Next-generation sequencing of adrenocortical tissues identified a 15-microRNA signature that distinguished ACC from non-malignant adrenal tissue, with six microRNAs showing at least 95% predictive accuracy in both training and validation sets. The study highlights miR-483-3p, miR-483-5p, and miR-210 as practical candidate biomarkers and suggests potential future noninvasive testing because microRNAs may be detectable in blood.³⁷

PMID 28606737: A metastatic ACC case with more than 11 years of survival after repeat surgery, chemotherapy, and mitotane had whole-genome sequencing showing a DDR2 missense mutation in an otherwise low-mutation tumor. The report suggests genomic profiling in selected advanced or atypical ACC cases may uncover potentially actionable alterations such as DDR2.⁷⁶

PMID 28943972: This sequencing-based analysis compared ACC with adrenocortical adenoma and identified broad small non-coding RNA dysregulation, including 147 miRNAs as well as altered piRNAs, lncRNAs, and sn/snoRNAs. The findings support exploratory biomarker development, highlight p53-related pathway involvement, and note that correlation with tumor grade requires further study.⁷⁷

PMID 29179432: This editorial highlights VAV2 as an SF-1 dosage-dependent molecular marker in ACC, with higher tumor expression associated with shorter progression-free and overall survival across cohorts. It also notes that combining VAV2 assessment with Ki-67 may improve prognostic prediction and frames VAV2-RAC interaction as a potential therapeutic biomarker-driven target.⁷⁸

PMID 29429354: This review summarizes tissue and circulating microRNAs as emerging biomarkers in adrenocortical tumors, highlighting recurrent differential expression of miR-483-5p, miR-503, miR-210, miR-335, and miR-195 between adenoma and carcinoma. It also notes possible prognostic associations and the investigational potential of liquid-biopsy applications, while emphasizing the limitations of small cohorts.⁷⁹

PMID 29444511: In a 10-patient cohort of treatment-refractory metastatic ACC profiled with a 50-gene panel, immunohistochemistry, and FISH, recurrent alterations included CTNNB1, TP53, RB1, APC, frequent p-mTOR and EGFR expression, and occasional PTEN loss. Despite detectable molecular abnormalities, multidisciplinary review found no actionable match for targeted therapy using this platform.²⁷

PMID 29520253: This study evaluates TCF21-related gene expression as a potential molecular biomarker in adrenocortical tumors. In adults, lower TCF21 and its relationship with BUB1B were associated with carcinoma and overall survival, while pediatric findings differed by age group and require external validation.⁸⁰

PMID 29682767: This original study evaluates ghrelin as a potential biomarker of adrenal carcinogenesis, finding markedly higher ghrelin expression in adrenocortical carcinoma than in normal adrenal tissue and higher levels than in adenoma samples. In H295R cells, ghrelin also stimulated proliferation and migration, supporting its possible biologic and diagnostic relevance.⁸¹

PMID 29982598: This study compared tissue and circulating microRNA profiles across adrenal myelolipoma, adrenocortical adenoma, and ACC, showing that ACC-associated miR-483-5p and miR-483-3p were elevated versus adenoma but did not clearly distinguish ACC from myelolipoma. The findings highlight both the promise and diagnostic limits of circulating microRNA biomarkers in adrenal tumor differentiation.⁸²

PMID 30113656: In 107 patients with ACC, targeted molecular profiling of routine FFPE specimens improved prediction of progression-free survival when integrated with stage, resection status, Ki-67, age, and symptoms. The study also identified recurrent potentially targetable alterations and supports clinically applicable molecular prognostication.¹⁰

PMID 30158955: Integrative co-expression and validation analyses identified 12 candidate ACC hub genes linked to tumor grade, stage, survival, and diagnostic discrimination, with enrichment in cell-cycle pathways. The study frames these genes as investigational biomarkers for ACC diagnosis, progression assessment, and prognostic stratification.⁸³

PMID 30519354: An integrated transcriptomic analysis across multiple public datasets identified five overexpressed genes in ACC—TOP2A, NDC80, CEP55, CDKN3, and CDK1—that were associated with worse overall and disease-free survival and with higher pathologic stage and T stage, with limited tissue-level validation supporting TOP2A overexpression.³²

PMID 30527005: This discussion highlights the potential use of pretreatment genetic analysis in ACC to identify dysregulated pathways and potentially predict which patients are more likely to benefit from mitotane. The investigators selected highly modulated genes, using marked expression differences from normal tissue to prioritize candidate targets.⁸⁴

PMID 30691340: This preclinical study developed a monoclonal antibody and derived single-chain antibody variable fragment against DHEA, showing tissue localization in normal adrenal zona reticularis and ACC cells. The authors propose this reagent as a potential biomarker platform for future imaging-based early diagnosis, particularly in pediatric ACC.⁸⁵

PMID 30770352: This study identifies G0S2 hypermethylation and silencing as a clinically feasible biomarker of the CIMP-high ACC subtype, which is associated with rapid recurrence and poor survival. Combining G0S2 methylation with BUB1B-PINK1 further stratified ACC into favorable, intermediate, and uniformly dismal prognostic groups.²⁸

PMID 30816525: Integrated GEO and TCGA expression analyses identified ACC-associated differentially expressed genes enriched in cell-cycle and mitotic programs, with NDC80, CCNB2, and TOP2A emerging as candidate biomarkers linked to overall and recurrence-free survival. Experimental silencing in NCI-H295R cells supported a functional role in tumor cell proliferation.³³

PMID 30886771: Transcriptome-based network analysis linked a stage-associated ACC gene module enriched for cell cycle and DNA replication pathways to four hub genes, TOP2A, TTK, CHEK1, and CENPA. Higher expression of these genes correlated with advanced stage and worse overall survival, supporting their candidacy as investigational prognostic biomarkers.⁸⁶

PMID 31149197: This review highlights circulating extracellular vesicle-associated miR-483-5p as a promising minimally invasive pre-operative biomarker candidate for distinguishing ACC, while noting that larger cohort validation is still needed. It also places this signal within broader ACC genomic and epigenetic alterations that may inform future diagnostic and prognostic biomarker development.⁸⁷

PMID 31321566: A bioinformatics analysis of ACC versus normal adrenal tissue identified 884 differentially expressed genes and several hub genes linked to worse overall survival and stage 4 expression, including FN1, TK1, MCM3, STAT1, and ICAM1. The study frames these transcriptomic candidates as potential biomarkers and therapeutic targets requiring further validation.⁸⁸

PMID 31354635: Integrated gene-expression and DNA-methylation analysis identified seven aberrantly methylated and dysregulated genes in ACC, with expression or methylation status correlating with pathologic stage and overall survival in validation datasets. The study frames these epigenetic alterations as candidate biomarkers and possible therapeutic targets, though clinical applicability remains investigational.⁸⁹

PMID 31492715: High-resolution MALDI mass spectrometry imaging of ACC tissue identified steroid sulfation phenotypes with prognostic associations, including estradiol sulfate, estrone 3-sulfate, SULT2A1 expression, and a poor-survival subset marked by estradiol-17β 3,17-disulfate. The study suggests tissue metabolomic phenotyping may support prognostication and treatment stratification beyond stage alone.⁵¹

PMID 31516579: A TCGA-based weighted gene co-expression analysis in 79 ACC cases identified two gene modules associated with tumor stage and vital status, enriched for cell division and metabolic pathways. High CDK1 and UBC expression correlated with worse overall survival and showed potential diagnostic discrimination between ACC and normal adrenal tissue.⁹⁰

PMID 31572440: An in silico analysis integrating GEO microarray datasets, protein interaction networks, and TCGA validation identified hub-gene expression patterns associated with ACC prognosis. Higher expression of ZWINT, PRC1, CDKN3, CDK1, and CCNA2 was linked to worse disease-free and overall survival, supporting their candidacy as investigational prognostic biomarkers.⁹¹

PMID 31749633: This article describes OSacc, a web-based survival analysis platform that pools seven ACC transcriptomic cohorts with clinical follow-up to assess candidate gene prognostic biomarkers. It highlights both validation of several previously reported markers and identification of CENPF as a potential adverse prognostic biomarker, while noting dataset heterogeneity and limited sample size.³⁴

PMID 32154490: This case report links exceptionally aggressive ACC behavior, including rare leptomeningeal spread, with multiple molecular risk signals beyond standard clinicopathologic markers: a high-proliferative secretory transcriptomic subtype, low BUB1B/PINK1 ratio, marked G0S2 hypermethylation, and TP53 and MEN1 mutations. It highlights the potential value of combining emerging biomarkers with Ki-67 and hormonal status for prognostic stratification.⁹²

PMID 32175564: A TCGA-based analysis of 92 ACC cases linked metastatic status with a ceRNA network and inferred immune-cell composition, identifying H2AFX, hsa-miR-130b-3p, and macrophages M0 as metastasis-associated features. The study also generated prognostic nomograms from ceRNA and immune-cell variables, but findings are computational and exploratory.⁹³

PMID 32207273: A proteomic analysis of 46 ACC cases found cyclin B1, transferrin receptor, and fibronectin overexpressed in metastatic tumors, with cyclin B1 and transferrin receptor, alone and in combinations, adding prognostic information beyond age and ENSAT stage. The study highlights protein-expression biomarkers as a potentially practical prognostic tool, though validation is still needed.⁴⁷

PMID 32319523: Using ACC tumor miRNome and survival data, the article identifies prognostic microRNA clusters on genomic-distance networks: high expression of the Xq27.3 cluster was associated with longer overall survival, whereas high expression of the 14q32.2 cluster was associated with shorter overall survival.⁹⁴

PMID 32414074: This review highlights DNA methylation and broader genomic profiling as emerging ACC biomarkers that may help distinguish adenoma from carcinoma and refine prognostic stratification beyond current clinicopathologic tools. It also emphasizes that molecular and epigenetic classifiers remain promising but are not yet established as guideline-based standard care.²

PMID 32522271: A pilot immunohistochemical study of 26 ACCs found variable FGFR2 expression with a subset showing high nuclear localization, but no clear association with CTNNB1 mutation status or clinical features. The findings suggest FGFR signaling as a potential investigational biomarker and therapeutic target, while underscoring the need for further validation.⁹⁵

PMID 32668404: This multicenter ENSAT validation study found that an IGF2 methylation score from three regulatory regions had high accuracy for distinguishing adrenocortical carcinoma from adenoma, especially when combined with tumor size. The score improved diagnostic objectivity versus Weiss-based uncertainty but did not independently predict metastasis after multivariable analysis.¹⁸

PMID 32698135: This study examined intratumor heterogeneity of DNA-based prognostic markers in ACC across paired primary, recurrent, and metastatic samples. Somatic mutations showed heterogeneity in 31% of patients, whereas chromosome alteration classes and methylation profiles were more stable, suggesting they may be more robust prognostic biomarkers.³⁰

PMID 32725507: This pathology-based biomarker study found predominantly nuclear lncRNA expression in adrenal cortical tissues and reported higher MALAT1 expression in ACC than in adenoma, while PRINS trended lower in ACC. The findings suggest lncRNA in situ hybridization may contribute to tumor classification, though validation was limited by small sample numbers.⁹⁶

PMID 32781574: This review summarizes dysregulated microRNAs and their target networks in ACC, emphasizing their links to aggressive tumor behavior and their potential use as diagnostic biomarkers or future therapeutics. It also highlights isomiR profiling and miRNA-processing abnormalities as investigational avenues whose clinical significance in ACC remains uncertain.⁹⁷

PMID 32919215: Transcriptomic deconvolution and network analysis of ACC datasets identified ERN1 and CEP55 as immune-related hub genes associated with overall survival and progression-free interval. These candidates were linked to immune-cell infiltration patterns and proposed as investigational prognostic and potential immunotherapy biomarkers.⁹⁸

PMID 33075426: Preclinical ACC data identify low filamin A expression as a potential biomarker linked to stronger IGF2-driven proliferation and greater sensitivity to IGF1R or IGF1R/IR inhibitors. The study supports biomarker-based selection within the IGF pathway rather than unselected use of these targeted drugs.⁵⁵

PMID 33101586: A TCGA-based pan-cancer analysis found that ACC showed lower NFE2L2 expression than normal tissue, while higher NFE2L2 expression within ACC was associated with worse overall survival, disease-specific survival, disease-free interval, and progression-free interval, suggesting possible prognostic biomarker value.⁹⁹

PMID 33564960: Targeted tissue sequencing of nine genes identified six genes with higher mutation rates in ACC than adenoma, and the proposed sum of high-risk gene mutations (SHGM) showed potential as an auxiliary biomarker for differentiating ACC from benign adrenocortical adenoma, including some tumors smaller than 5 cm.¹⁰⁰

PMID 33591997: Analysis of TCGA ACC tumors found that high IL-13Rα2 transcript expression was associated with worse overall survival, more frequent new tumor events, and greater excess hormone production. The study presents IL-13Rα2 as a prognostic molecular biomarker and a potential therapeutic target, while noting findings are based on retrospective transcriptomic data.¹⁰¹

PMID 33692753: A TCGA-based study identified differential expression of multiple m6A RNA methylation regulators in ACC and derived a three-gene signature using RBM15, HNRNPC, and FTO that independently predicted overall survival. The risk score also correlated with stage-related clinicopathologic features and was incorporated into a prognostic nomogram.¹⁰²

PMID 33739426: This review suggests steroid sulfation may contribute to ACC biology and biomarker development, highlighting prognostic estrogen sulfate abundance in ACC tissue and the potential of LC-MS/MS and mass spectrometry imaging to characterize sulfated steroid profiles. It also emphasizes that the ACC sulfosteroid metabolome and clinical utility of these markers remain incompletely defined.⁵²

PMID 34177053: A small retrospective single-center study found that preoperative hemocytometer measures including neutrophil and lymphocyte counts, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, RDW, and plateletcrit differed between nonfunctional adrenal adenoma and ACC, but these blood-based parameters did not show prognostic value for recurrence or metastasis in ACC.¹⁰³

PMID 34361082: This review identifies NUCB2/nesfatin-1 as a potential cancer biomarker and notes conflicting ACC-specific evidence, with nesfatin-1 reported to inhibit proliferation of human adrenocortical carcinoma cells. The excerpt frames NUCB2/nesfatin-1 as investigational rather than practice-ready for prognostic or predictive use in ACC.¹⁰⁴

PMID 34410225: Targeted sequencing of 364 ACCs found potentially actionable genomic alterations in 58.5% of tumors and identified mismatch repair pathway alterations in 13.7%, often with higher mutation burden and mismatch repair mutational signatures. These findings support genomic profiling as a strategy to identify biomarker-defined subsets for personalized therapy, including possible immunotherapy candidates.⁸

PMID 34532252: Bioinformatics analysis with limited qPCR validation found TNFSF13B overexpressed in ACC versus normal adrenal tissue and associated with shorter disease-free survival, with inconsistent overall survival validation. The study proposes TNFSF13B as a candidate prognostic biomarker and potential therapeutic target, alongside exploratory links to methylation, miRNA regulation, and SREBP/B-cell receptor pathway enrichment.¹⁰⁵

PMID 34536950: This study identifies ASXL1 copy-number gain and overexpression as a frequent ACC alteration linked to recurrence, worse survival, and reduced sensitivity to etoposide, doxorubicin, and cisplatin. Experimental knockdown impaired ACC cell fitness and increased EDP sensitivity, supporting ASXL1 as a candidate biomarker and investigational therapeutic target.¹⁰⁶

PMID 34669649: This review synthesizes recent ACC genotyping literature, emphasizing that integrated germline, somatic, and epigenetic profiling may refine prognostic stratification beyond clinical models, while predictive utility remains unvalidated. It highlights DNA damage repair alterations and promoter hypermethylation as potential biomarker-defined avenues for future therapeutic repurposing.¹⁵

PMID 34750847: This review synthesizes molecular profiling in sporadic ACC across DNA, RNA, and epigenetic levels, highlighting prognostic and predictive biomarkers and discussing which assays may be practical for routine care. It emphasizes that clinically useful biomarker integration remains incomplete despite promising signals for prognosis, therapy response, and new drug targets.³

PMID 34829730: This systematic review summarizes miRNA biomarker research in ACC, highlighting recurrent diagnostic and prognostic signals such as miR-483-5p upregulation and miR-195 downregulation in tissue and blood. It also emphasizes important limitations, including discordance between tissue and circulating assays and largely preclinical therapeutic data.¹³

PMID 34834449: This preclinical and pilot clinical study suggests intratumoral CXCL12 as a potential biomarker in ACC, with lower expression associated with larger size, higher stage, higher Weiss score, necrosis, mitotic activity, and worse disease-free and progression outcomes. Rosiglitazone increased CXCL12 and reduced CXCR4/CXCR7 in primary ACC models, supporting the CXCL12/CXCR4 axis as a candidate therapeutic-response biomarker and target.¹⁰⁷

PMID 34858850: This study identifies ESM1 as an overexpressed candidate biomarker in ACC, associated with worse overall survival and linked to cell-cycle and DLL4-Notch signaling. Functional experiments in an ACC cell line suggest ESM1 may influence proliferation and could represent an investigational prognostic marker and therapeutic target.¹⁰⁸

PMID 35185794: This study suggests that whole-transcriptome profiling from FFPE adrenocortical tumor samples can reliably approximate fresh frozen results, separate ACC from aldosterone- and cortisol-producing adenomas, and recover known ACC-associated genes such as CCNB2, TOP2A, and MAD2L1. The findings support use of routinely archived tissue for transcriptomic biomarker development in adrenal tumors.³¹

PMID 35205648: This study used RT-qPCR on FFPE adrenocortical tissues and machine learning to derive three tissue miRNA panels that distinguished ACC from adenoma with sensitivity and specificity above 90% in a validation cohort. The authors propose these panels as adjuncts to expert histology and as potential support for preoperative biopsy interpretation.²⁰

PMID 35210821: Using TCGA ACC data with GEO external validation, the study derived a 13-gene immune-related prognostic signature from ssGSEA-defined immune infiltration clusters and built a nomogram with high reported discrimination for 1-, 3-, and 5-year overall survival. It frames immune gene expression profiling as a potential prognostic biomarker approach in ACC.⁵⁸

PMID 35266879: This study shows that 3′ RNA sequencing on FFPE adrenocortical tumor samples can reproduce established transcriptomic classes, distinguish adenoma from carcinoma, and stratify ACC into C1A and C1B prognostic groups. FFPE transcriptome class remained independently prognostic beyond stage and Ki-67, supporting broader routine and retrospective molecular profiling.¹¹

PMID 35462410: In advanced ACC, blood-based ctDNA next-generation sequencing was feasible in 80% of tested patients and showed a genomic alteration profile broadly similar to tissue-based datasets. Nearly half of patients had pathogenic or likely pathogenic alterations in potentially actionable genes, supporting ctDNA as a noninvasive platform for biomarker development and trial matching.¹⁰⁹

PMID 35623010: This review and pilot study suggests that dissected FFPE ACC tissue can yield RNA of sufficient quality for targeted gene expression profiling, enabling transcriptional analysis of morphologically distinct tumor regions. The approach is presented as a practical way to support biomarker discovery in a rare, heterogeneous cancer when frozen tissue is often unavailable.¹¹⁰

PMID 35624283: A pan-cancer TCGA/GTEx analysis reported that taste receptor genes show differential expression, mutations, and copy-number changes across solid tumors, with higher TAS2R14 expression in adrenocortical carcinoma associated with markedly worse survival. The findings position TAS2R14 as a potential prognostic biomarker candidate in ACC, pending further validation.¹¹¹

PMID 35628389: This immunohistochemistry study assessed VEGF and Ang-Tie pathway mediators in adrenocortical tumors and found higher Ang2 expression in ACC, with Tie1 associated with venous invasion and shorter overall survival. Despite these biologic differences, the tested angiogenic markers did not provide a reliable standalone diagnostic biomarker for distinguishing ACC from adenoma.⁴⁸

PMID 35669515: TCGA- and GTEx-based analyses identified m6A-related lncRNA expression patterns in ACC, including a four-lncRNA prognostic risk model associated with overall survival and immune microenvironment differences. The study frames these lncRNAs as investigational biomarkers for prognostic classification and possible future therapeutic stratification.⁴⁰

PMID 35832625: A pan-cancer bioinformatic analysis reported that CSPP1 expression is decreased in adrenocortical carcinoma compared with normal tissue, positioning it as a potential diagnostic biomarker candidate. The study frames CSPP1 dysregulation within broader mechanisms including genetic alteration, methylation, and miRNA effects, but does not provide ACC-specific validation or treatment data.¹¹²

PMID 35883677: This review summarizes dysregulated microRNAs and long non-coding RNAs in ACC, emphasizing circulating and tissue miRNA patterns as potential noninvasive biomarkers for differentiating ACC from adenoma and for prognostic assessment. It also highlights that several candidate ncRNA signals show biologic plausibility but remain incompletely validated for clinical use.¹⁴

PMID 35885996: A pan-cancer computational methylation analysis identified F2RL3 as an ACC-specific GPCR-related DNA methylation biomarker, with higher methylation in ACC than other cancers across training, testing, and GEO validation datasets. The study also linked F2RL3 methylation to predicted sensitivity to BI.2536 and sepantronium bromide, suggesting an investigational biomarker-treatment connection.¹¹³

PMID 35929659: In a 237-patient ACC cohort using FFPE samples, targeted promoter methylation analysis found PAX5 hypermethylation independently associated with worse overall survival after adjustment for S-GRAS. Adding PAX5 methylation status to S-GRAS improved prognostic discrimination for overall, progression-free, and disease-free survival.²⁹

PMID 36077848: This exploratory study profiled circular RNAs in adrenocortical tumors and found that circPHC3 was validated as overexpressed in both ACC and ACA compared with normal adrenal cortex, while not distinguishing carcinoma from adenoma. The findings suggest circRNAs as investigational biomarkers, but their diagnostic relevance in ACC remains unproven.¹¹⁴

PMID 36202651: Integrated analysis of 260 ACC tumors across multiple genomic datasets identified a dysregulated mRNA-miRNA-lncRNA network centered on BIRC5, hsa-miR-335-5p, and PAX8-AS1 that was associated with poor overall survival. The study proposes this network as a candidate prognostic biomarker and potential therapeutic target requiring further validation.¹¹⁵

PMID 36418213: A bioinformatics letter reports that SKA1, SKA2, and SKA3 are overexpressed in ACC versus normal adrenal tissue, correlate with higher T stage, metastatic disease, advanced pathologic stage, and tumor persistence, and are associated with worse overall survival. The study also links higher SKA expression to lower CD8-positive and cytotoxic immune infiltration and identifies trametinib as a candidate drug sensitivity signal.¹¹⁶

PMID 36582114: RNA sequencing of canine cortisol-secreting adrenocortical tumors identified two transcriptomic subtypes with different post-adrenalectomy survival, and higher CYP26B1 expression was associated with outcome in both the canine cohort and a public human cortisol-secreting ACC dataset. The study proposes CYP26B1 as a candidate prognostic biomarker and potential therapeutic target requiring further validation.¹¹⁷

PMID 36583015: This transcriptomic study developed and externally validated a six-gene hypoxia risk score in ACC that independently predicted overall survival alongside tumor stage. Higher scores were associated with a non-inflammatory tumor microenvironment, lower immune checkpoint expression, and lower predicted sensitivity to immune checkpoint inhibitors.¹¹⁸

PMID 36651165: In two ACC transcriptomic cohorts, high SGPL1 expression correlated with reduced overall survival and more aggressive molecular subgroups, while in vitro SGPL1 overexpression promoted proliferation, migration, and metabolic fuel use. These findings position SGPL1 and the sphingolipid pathway as investigational prognostic and therapeutic biomarker candidates.¹¹⁹

PMID 36671489: Immunogenomic profiling identified two reproducible ACC immune subtypes, Immunity-H and Immunity-L, with distinct survival, hormone excess prevalence, genomic instability, CTNNB1 mutation frequency, and pathway enrichment. This framework may help prognostic assessment and future immunotherapy stratification, though it is derived from retrospective multi-cohort transcriptomic analyses.⁵⁹

PMID 36793283: A database-driven ACC study found BRD3 and BRD4 overexpression, with BRD4 correlated with pathologic stage, and higher BRD2/3/4 expression associated with shorter disease-free survival; higher BRD3 and BRD4 also associated with shorter overall survival. The analysis proposes BET-family members and related drug sensitivity signals as investigational prognostic and therapeutic biomarkers.¹²⁰

PMID 36852051: A database-driven ACC study found that SULF2 is overexpressed in tumor tissue versus normal adrenal tissue, and higher expression was associated with worse prognosis, more advanced stage, lymph node involvement, TP53 mutation status, and distinct immune infiltration patterns. The work frames SULF2 as a potential prognostic biomarker and exploratory therapeutic target rather than a validated clinical marker.¹²¹

PMID 36895966: This study proposes an m7G-related four-gene risk signature centered on METTL1 in ACC, associated with prognosis, immune suppression, glycolysis enrichment, and potential differences in response to immune checkpoint blockade and mitotane. Experimental data also support METTL1 as a driver of ACC cell growth, invasion, and altered immune infiltration.¹²²

PMID 36939770: Genome-wide analysis of ACC alternative splicing identified thousands of prognosis-related splicing events and generated multievent risk models associated with clinical outcomes. The study also nominated DDX21 as a potential prognostic biomarker and therapeutic target, supported by TCGA-based analyses and immunohistochemical validation in an external surgical cohort.⁴¹

PMID 36973786: Pan-cancer TCGA-based analysis found that higher SLC31A1 expression in adrenocortical carcinoma was associated with shorter overall and disease-free survival, and SLC31A1 expression also differed across ACC pathological stages. In ACC samples, reported SLC31A1 alterations were copy-number amplifications, supporting investigation of SLC31A1 as a prognostic biomarker candidate.¹²³

PMID 37181234: This study identifies KIF11 as an overexpressed ACC biomarker associated with advanced T, metastasis, pathologic stage, recurrence risk, and shorter survival in TCGA and a small institutional cohort. In vitro, KIF11 inhibition with monastrol reduced NCI-H295R proliferation and invasion, supporting investigational biomarker-target linkage.¹²⁴

PMID 37189849: This study evaluates ZWILCH as a candidate ACC biomarker, showing higher expression in carcinoma than normal adrenal tissue and associations with increased mitotic activity and worse survival. High ZWILCH expression also tracked with proliferation-related transcriptional programs and reduced immune-related gene expression.¹²⁵

PMID 37418996: This review highlights dysregulated tissue and circulating miRNAs in ACC as minimally invasive diagnostic and prognostic biomarker candidates, with particular emphasis on miR-483-5p and miR-139-5p. It also links miRNA profiles to disease progression, recurrence risk, and potential therapeutic targeting, including drug-resistance relevance.³⁸

PMID 37509652: This study evaluates the IGF2 methylation score as a biomarker for adrenocortical tumors with unclear malignant potential and shows that, with the current pyrosequencing method, FFPE tissue is not reliable for this purpose. Fresh frozen resection material is recommended for diagnostic testing and biobanking when this biomarker is being considered.²¹

PMID 37547754: This bioinformatic study identified two ACC m6A methylation modification patterns linked to immune-inflamed versus immune-desert tumor microenvironment phenotypes and different overall survival. A derived m6A score independently predicted prognosis and was associated with copy number variation patterns and putative responsiveness to immune checkpoint blockade.¹²⁶

PMID 37590967: In a two-cohort ACC study using routinely available FFPE tissue, adding two DNA-based biomarkers, Wnt/beta-catenin or Rb/p53 pathway alterations and PAX5 hypermethylation, to the S-GRAS score improved prognostic discrimination for overall, progression-free, and disease-free survival compared with clinical-pathologic factors alone.⁵

PMID 37675289: A pancancer bioinformatics study reported that LEDGF/p75 expression may have prognostic value in adrenocortical carcinoma, while emphasizing broader links to epigenetic regulation, DNA repair, genomic instability, and tumor immunity. The ACC relevance is limited to exploratory biomarker association rather than validated disease-specific biology or treatment guidance.⁶²

PMID 37695690: This study reports that ACC contains a distinct intratumour bacterial DNA profile versus healthy adrenal tissue, with enrichment of Proteobacteria, Pseudomonas, and Serratia. Higher abundance of these taxa was associated with higher mitotane blood levels at 9 months, suggesting a potential investigational biomarker for mitotane responsiveness.¹²⁷

PMID 37852864: This retrospective surgical series evaluated preoperative neutrophil-to-lymphocyte ratio as a simple blood-based biomarker in adrenal tumors. NLR was higher in ACC than non-ACC lesions and showed moderate discriminatory performance at a cutoff of 2.65, but it was not significantly associated with overall survival in ACC.¹²⁸

PMID 37919768: Bioinformatics and limited tissue validation data suggest that SLC7A11 is upregulated in ACC and associated with M stage, poor survival, immune infiltration patterns, immune checkpoint gene expression, tumor mutation burden, and predicted drug sensitivity. The study proposes SLC7A11 as a candidate prognostic and therapeutic biomarker linked to disulfidptosis biology.¹²⁹

PMID 38256114: This study reports that humanin, a mitochondria-derived peptide, is downregulated in ACC tissue at mRNA level and shows reduced tissue protein expression with disease progression, while serum levels were not significantly different from controls. The findings suggest a potential investigational biomarker linked to mitochondrial dysfunction, but clinical utility remains uncertain.¹³⁰

PMID 38277554: This review summarizes microRNAs, long non-coding RNAs, and circular RNAs implicated in ACC pathogenesis and discusses their associations with diagnosis and prognosis. It frames ncRNAs as potential noninvasive biomarkers and future therapeutic targets, while indicating that their clinical application remains investigational.⁴²

PMID 38779454: Patient-derived ACC cell testing showed marked heterogeneity in mitotane sensitivity and identified candidate response-associated features, including CTNNB1 alterations in responders, ZNRF3 alterations in non-responders, lipid-metabolism pathway upregulation, and higher CYP27A1 and ABCA1 expression. The study also highlighted patient-derived cultures as a platform for drug repurposing, with disulfiram, niclosamide, and bortezomib emerging as preliminary leads.⁵⁶

PMID 38806535: A retrospective study using fully automated CT body composition analysis found that ACC showed lower skeletal muscle mass than benign adrenal lesions, with more pronounced sarcopenia in functioning than nonfunctioning ACC. The authors propose automated body composition metrics as a potential imaging-derived biomarker for prognosis and supportive care planning, while noting the need for longitudinal validation.¹³¹

PMID 38868430: This study reports that ACC contains detectable intratumoral bacteria and that microbiome-defined clusters were associated with overall survival. Incorporating microbial signatures improved prognostic performance beyond clinical stage in an immunity-dependent analysis, supporting intratumoral microbiota as an investigational prognostic biomarker linked to host genomic and transcriptomic features.¹³²

PMID 38917236: A simplified targeted NGS panel covering recurrent ACC driver genes showed prognostic value when combined with clinicopathologic data, with NF1 plus TP53 and Wnt/beta-catenin plus Rb/p53 pathway alterations associated with worse progression risk. The signal appeared especially relevant in low-stage disease, supporting molecularly guided risk stratification and more individualized surveillance or treatment planning.²⁴

PMID 39045040: A bioinformatics analysis identified NCAPG, NCAPG2, and NCAPH as overexpressed in ACC versus adenoma and normal adrenal tissue, with associations to advanced stage, poor overall survival, and high ROC discrimination. The study frames these genes as investigational diagnostic and prognostic biomarkers requiring further validation.¹³³

PMID 39081696: This case report and literature review highlight that malignant transformation of an apparently benign nonfunctional adrenal adenoma into ACC is extremely rare but documented, and that current imaging and follow-up rules may miss late transformation. The article emphasizes the unmet need for robust predictive biomarkers, likely including genetic or transcriptomic features, to identify lesions at risk and individualize surveillance.¹³⁴

PMID 39100837: A multi-cohort transcriptomic study identified high ZFHX4-AS1 expression as an independent adverse prognostic biomarker in ACC, with nomogram-based survival prediction and validation in adult and pediatric datasets. In vitro knockdown also reduced ACC cell proliferation and migration, supporting biologic relevance.¹³⁵

PMID 39201408: A preliminary biomarker study found reduced MOTS-c mRNA and tissue protein expression across adrenal tumors, with ACC tissue expression declining in more advanced stages. Tissue MOTS-c showed potential to distinguish ACC from normal adrenal tissue, while serum MOTS-c was not elevated in ACC and had limited discriminatory value versus adenoma.¹³⁶

PMID 39404265: This study identifies AGO2 as a candidate ACC biomarker, showing higher mRNA and protein expression in ACC than in normal adrenal cortex or adrenal adenoma, with high expression associated with markedly worse overall survival. ROC analysis of tissue AGO2 protein suggested potential diagnostic discrimination, supporting further biomarker development and validation.¹³⁷

PMID 39413985: RNA sequencing and co-expression analysis in pediatric adrenocortical tumors identified prognostic hub genes linked to five-year event-free survival and highlighted pathway differences between favorable and unfavorable outcomes. The study also notes enrichment of MAPK, Hedgehog, hormone-signaling, adhesion, and immune-related programs, supporting investigational biomarker development.¹³⁸

PMID 39428280: A TCGA-based retrospective analysis found that pathway-level genomic alterations in WNT, PI3K, and cell cycle signaling were independently associated with recurrence after R0 resection for ACC, while MYC alterations were linked to earlier recurrence. The study frames these signatures as candidate prognostic biomarkers that may help guide future adjuvant or targeted treatment strategies.²⁵

PMID 39778025: This translational study identifies CENPM as an ACC metastasis-associated hub gene that is upregulated in tumors, correlates with metastasis and poor prognosis, and promotes invasion and liver metastasis through physical interaction with FGL1. The findings nominate the CENPM-FGL1 axis as a candidate prognostic biomarker and investigational therapeutic target.¹³⁹

PMID 39788148: Across pediatric and adult ACC cohorts, high YAP1 expression and a YAP1-associated methylation signature were linked to worse survival, supporting YAP1 as a prognostic biomarker candidate. Experimental data also suggest YAP1 inhibition can suppress tumor growth, highlighting its potential as a biomarker-connected therapeutic target.¹⁴⁰

PMID 39802216: A pan-cancer in silico analysis reported reduced ABO mRNA expression in adrenocortical carcinoma compared with normal adrenal tissue and suggested that lower ABO expression may be associated with worse survival in ACC, although significance across cancers was inconsistent. The findings position ABO as a preliminary investigational biomarker rather than a validated ACC-specific marker.¹⁴¹

PMID 39890176: Bioinformatics analysis of TCGA-based datasets found DDX39A mRNA upregulated in ACC relative to normal adrenal tissue, with expression increasing across stages. Higher DDX39A expression was associated with worse overall and disease-free survival, supporting its candidacy as a prognostic biomarker requiring further validation.¹⁴²

PMID 40035383: This study identifies DLK1 as a candidate ACC biomarker with tissue and serum relevance: higher expression was linked to recurrence risk, progression in ENSAT I-II disease, metastatic lesions, and greater disease burden, while preoperative serum DLK1 discriminated ACC from benign adenomas and fell after resection.¹⁴³

PMID 40291702: Transcriptomic analysis of 112 ACC tumors identified bimodally expressed SEMA7A as a candidate prognostic biomarker, with high expression associated with worse survival and enrichment in hormone-producing, higher-stage tumors. The study also shows feasible protein-level assessment by immunohistochemistry and links SEMA7A expression to steroidogenic and integrin-FAK/MAPK pathway gene programs.¹⁴⁴

PMID 40313932: This study proposes VGF as an investigational biomarker in ACC, showing higher tumor than normal adrenal expression and associations with advanced stage, nodal and metastatic disease, residual tumor, and worse overall survival. VGF also correlated with immune infiltration patterns, but the evidence is based mainly on retrospective transcriptomic analysis with small institutional IHC validation.¹⁴⁵

PMID 40574400: This study identifies DTL as a candidate biomarker for ACC, showing higher expression in ACC than in adrenocortical adenoma and adjacent normal cortex, with associations to larger tumors, infiltrative or metastatic features, and shorter survival. The findings support DTL as a potential diagnostic and prognostic marker, pending further validation.¹⁴⁶

PMID 40587033: In a real-world molecular tumor board cohort of rare endocrine neoplasms, adrenocortical carcinoma showed the lowest prevalence of pathogenic alterations on comprehensive genomic profiling at 37.5%, and no ACC cases received genomically guided treatment recommendations. These findings underscore current limits of actionable biomarker discovery for ACC precision oncology.¹⁶

PMID 40647379: A bimodal RNA-seq analysis across TCGA and NCI ACC cohorts identified SEMA7A as a poor-prognosis biomarker, with high expression associated with worse survival and feasible confirmation by immunohistochemistry. Elevated SEMA7A also correlated with steroidogenic gene programs and integrin-FAK-ERK signaling, supporting further biomarker and therapeutic-development study.¹⁴⁷

PMID 40676104: A transcriptomics-based drug repositioning analysis in ACC identified HMMR and other hub genes linked to survival, stage, TP53 mutation status, and immune infiltration, and proposed fluorouracil and epirubicin as candidate drugs targeting HMMR. The study frames these hub genes as potential biomarkers and therapeutic leads, but findings are computational and hypothesis-generating.¹⁴⁸

PMID 40688701: This study identifies CDC20 overexpression as an independent adverse prognostic biomarker in both adult and childhood ACC, supported by transcriptomic analyses, immunohistochemistry, and in vitro functional assays. Higher CDC20 expression was associated with TP53 mutation, lower CD8+ T-cell infiltration, and predicted poorer inferred response to anti-PD-1 immunotherapy.¹⁴⁹

PMID 40693437: Database-driven analyses in ACC found EFNA3 overexpressed versus normal adrenal tissue, associated with pathologic stage, tumor status, primary therapy outcome, and worse survival. Higher EFNA3 expression also correlated with lower CD8-positive T-cell and macrophage infiltration, supporting its candidacy as a prognostic biomarker and investigational therapeutic target.¹⁵⁰

PMID 40876968: TCGA-based GEPIA and UALCAN analyses found that STMN1 mRNA is overexpressed in ACC versus normal adrenal tissue, rises with advancing stage, and is associated with shorter overall survival and disease-free survival. The study positions STMN1 as a candidate prognostic biomarker requiring further validation and mechanistic study.¹⁵¹

PMID 40968257: This study proposes a multimodal Steroid-related Immune Score integrating genomics, digital pathology, and AI to classify ACC into immune- and steroid-linked subgroups with distinct prognosis and potential treatment sensitivity. High SIS was associated with lymphocyte infiltration and better immunotherapy response, whereas low SIS tracked steroid biosynthesis, hormone secretion, and hormone inhibition sensitivity.⁶³

PMID 41166795: Integrative ceRNA analysis of TCGA-ACC and GTEx adrenal tissue identified CKS2 and ACAT2 as upregulated ACC-associated biomarkers with combined diagnostic discrimination and adverse survival associations. The study proposes a coordinated proliferative-metabolic axis, while emphasizing the need for larger cohorts and functional validation before clinical use.¹⁵²

PMID 41172328: A large single-centre cross-sectional study found AgRP is increased in ACC tissue and plasma versus benign adrenal tumors and other malignancies, correlates with RECIST-based tumor burden and metastatic site count, decreases after curative surgery, and independently associates with shorter progression-free and overall survival.¹⁵³

PMID 41181628: This study identifies EFNA3 as a candidate ACC biomarker with associations to worse overall, disease-specific, and progression-free outcomes, diagnostic discrimination, altered methylation, immune infiltration patterns, and differential drug sensitivity signals. In vitro data further support EFNA3 as a potential oncogenic driver and investigational therapeutic target.¹⁵⁴

PMID 41269005: Mass spectrometry-based comparative proteomics identified differential protein signatures separating ACC from normal adrenal tissue and adenomas, with validation in an independent ACC cohort showing high concordance. The study frames these proteomic patterns as a resource for potential biomarkers and therapeutic target discovery in adrenocortical neoplasia.⁴⁹

PMID 41416224: A genome-wide RNAi screen identified chromosome-instability genes whose altered expression correlated with poor survival across several cancers, including adrenocortical carcinoma. The excerpt highlights these candidates as investigational prognostic biomarkers rather than ACC-specific validated markers or therapeutic targets.¹⁵⁵

PMID 41487926: A TCGA-based bioinformatics study found that MCM10 mRNA expression is higher in ACC than in normal adrenal tissue, rises further in stage IV disease, and is associated with shorter overall and disease-free survival. The findings position MCM10 as a candidate prognostic biomarker that requires further validation and mechanistic study.¹⁵⁶

PMID 41500447: In adrenal incidentalomas 4 cm or larger, especially the 4-6 cm indeterminate range, the systemic immune-inflammation index derived from routine blood counts outperformed tumor size as a preoperative discriminator of ACC versus adenoma in a retrospective surgical cohort. The authors position SII as a low-cost adjunctive biomarker that requires prospective external validation before routine use.¹⁵⁷

PMID 41617449: A TCGA-based analysis found ANLN mRNA expression to be higher in ACC than in normal adrenal cortex, highest in stage IV disease, and associated with shorter overall and disease-free survival. The study frames ANLN as a candidate prognostic biomarker requiring further validation for clinical use.¹⁵⁸

PMID 41760253: A TCGA-based in silico study found that YME1L1 mRNA expression was higher in stage IV ACC than in stages I-III and that higher expression correlated with shorter overall survival and disease-free survival. These findings suggest YME1L1 as a candidate prognostic biomarker that requires further validation.¹⁵⁹

PMID 36628237: A pan-cancer TCGA/GTEx analysis reported that ASGR1 expression was associated with prognosis in ACC and correlated across cancers with immune and genomic features such as DNA methyltransferases, mismatch-repair genes, tumor mutational burden, and microsatellite instability. For ACC, the study is best interpreted as exploratory because it was not designed as a disease-specific validation study.⁶⁰

PMID 37543196: A glioma-focused pan-cancer bioinformatic study found SLC10A3 upregulation in ACC and an association between higher SLC10A3 expression and better overall survival in ACC. For ACC, the finding is indirect and exploratory because the analysis was not ACC-focused and did not provide disease-specific validation beyond public transcriptomic datasets.⁶¹

PMID 12352395: A 2002 interphase FISH study of adrenal cortical neoplasms found frequent multi-chromosome tetrasomy in aldosteronism-associated adenomas, fewer abnormalities in Cushing-associated adenomas, and discordant findings across two carcinomas. For ACC, it mainly provides historical context that numerical chromosomal aberrations can be detected but may be endocrine-phenotype-dependent and insufficiently specific when assessed with limited probes.²⁶

PMID 25352177: A prostate cancer study found tumor-suppressive effects of miR-99a and identified FGFR3 as a target in that disease. Its ACC relevance is indirect, resting on the paper’s note that miR-99a had previously been reported as downregulated in childhood adrenocortical tumors rather than on ACC-focused biomarker validation.¹⁶⁰

PMID 24944696: A bladder cancer functional study identified miR-99a as a suppressive microRNA targeting FGFR3 and noted prior reports of miR-99a downregulation in childhood adrenocortical tumors. For ACC, the article is only indirectly relevant and mainly adds cross-cancer context for exploratory microRNA biomarkers rather than disease-specific validation.¹⁶¹

PMID 25078331: A 2014 targeted NGS study of 29 advanced ACC samples found at least one genomic alteration in most tumors and reported potentially actionable alterations in 59%, highlighting sequencing as a source of therapeutic hypotheses in relapsed or metastatic disease rather than proof of routine precision-treatment benefit.⁵³

PMID 34238250: A LUAD-focused eRNA study reported that TBX5-AS1 showed a survival association in pan-cancer analyses that included ACC, but the ACC component was indirect and lacked disease-specific validation. It therefore mainly broadens the list of exploratory non-coding RNA candidates rather than establishing a usable ACC biomarker.⁴³

PMID 34671565: In a hepatocellular carcinoma eRNA study, SPRY4-AS1 showed poor-prognosis associations and was also linked to survival in pan-cancer analyses that included ACC, with correlated SPRY4 expression across several tumor types. Its ACC relevance is therefore indirect and hypothesis-generating rather than disease-specific validation.⁴⁴

PMID 35899496: An erratum to a 2021 ACC transcriptomic-analysis paper corrected figure labels, duplicated images, and the displayed risk-score formula for NDRG4/CKS2 analyses. For this note, it mainly reinforces caution around isolated prognostic gene claims from retrospective expression datasets rather than adding a new biomarker concept.⁴⁵

Quartz 4

Explorer

tissue_and_genomic_biomarkers_in_acc

Tissue and Genomic Biomarkers in ACC

Diagnostic context

Major biomarker classes

DNA copy-number and mutational biomarkers

DNA methylation and epigenetic classifiers

Transcriptomic and non-coding RNA biomarkers

Evidence for prognosis and treatment selection

Limitations and future directions

Included Articles

References

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Table of Contents

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Quartz 4

Explorer

tissue_and_genomic_biomarkers_in_acc

Tissue and Genomic Biomarkers in ACC

Diagnostic context

Major biomarker classes

DNA copy-number and mutational biomarkers

DNA methylation and epigenetic classifiers

Transcriptomic and non-coding RNA biomarkers

Protein, metabolomic, and steroid-related tissue biomarkers

Evidence for prognosis and treatment selection

Limitations and future directions

Included Articles

References

Footnotes

Graph View

Table of Contents

Backlinks