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Molecular Drivers of Potential Immunotherapy Failure in Adrenocortical Carcinoma.

ABSTRACT: Adrenocortical carcinoma (ACC) is a rare, highly aggressive cancer, often insensitive to conventional chemotherapeutics agents. Early diagnosis, followed by radical surgical resection plus/minus adjuvant mitotane therapy, is nowadays the only valuable option. Unfortunately, one out of four patients has metastatic disease at diagnosis and most of radically resected ACC patients are destined to recur with local or metastatic disease. Numerous efforts aimed at identifying molecular alterations crucial for ACC pathogenesis have been extensively conducted, with the hope to develop new treatments. Indeed, multiple genes and pathways have been identified as potentially targetable in ACC patients; however, despite the strong preclinical rationale, translational findings to clinical trials led to date to disappointing results. The immunotherapeutic intervention targeting T-cell checkpoint molecules has been proposed as well, but results obtained in early studies indicate that ACC patients would be unlikely to benefit from immunotherapy. Genetic alterations of different pathways involved in ACC carcinogenesis are also known substrates of resistance to immunotherapy. Among them, ?-catenin gene CTNNB1 and TP53 gene are frequently mutated in ACC samples. Overactivation of the ?-catenin pathway and loss of p53 protein function are potential tumor-intrinsic factors that, impacting on the ability of ACC cells to recruit dendritic cells, leading to T-cell exclusion, put this tumor among those that are potentially resistant to immunotherapy. Moreover, the steroid phenotype, which implies glucocorticoids hypersecretion in a subset of ACC, contributes to generating an immunosuppressive microenvironment. Here, we review clinical results of immunotherapy in ACC and we highlight molecular mechanisms driving immunotherapy failure in ACC, suggesting possible approaches to overcome resistance.

SUBMITTER: Fiorentini C

PROVIDER: S-EPMC6463568 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Molecular Drivers of Potential Immunotherapy Failure in Adrenocortical Carcinoma.

Fiorentini Chiara C Grisanti Salvatore S Cosentini Deborah D Abate Andrea A Rossini Elisa E Berruti Alfredo A Sigala Sandra S

Journal of oncology 20190401

Adrenocortical carcinoma (ACC) is a rare, highly aggressive cancer, often insensitive to conventional chemotherapeutics agents. Early diagnosis, followed by radical surgical resection plus/minus adjuvant mitotane therapy, is nowadays the only valuable option. Unfortunately, one out of four patients has metastatic disease at diagnosis and most of radically resected ACC patients are destined to recur with local or metastatic disease. Numerous efforts aimed at identifying molecular alterations cruc ...[more]

PMID: 31057613

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Project description:Despite progress in understanding the biology of adrenocortical carcinoma (ACC), treatment options have not dramatically changed in the last three decades, nor have we learned how to avoid some of its long-term side effects. Our goal was to improve the understanding of immune pathways that may include druggable targets to enhance immune responses of patients with ACC, focusing on immune evasion and the activation of immune cells against ACC. Our strategy was aimed at improving insight regarding gene expression without steroid interference. Using approaches based on high and low steroid phenotypes (HSP and LSP, respectively), we characterized immune pathways using The Cancer Genome Atlas (TCGA) ACC cohort data. Although previous studies have suggested that patients with ACC receive minimal benefit from immunotherapy, high expression of immune modulators was noted in patients with LSP, suggesting the activation of these biomarkers may be an important adjuvant therapy target after clearance of excess glucocorticoids. In addition, patients with LSP ACC had higher immune cell infiltration than patients with HSP ACC and other cancer subtypes. Our findings can be summarized as follows (1): we confirmed and improved the definition of two immune response pathways to ACC (HSP and LSP) based on in silico transcriptome analysis (2), we demonstrated the steroid profile should be considered, otherwise analyses of ACC immune characteristics can generate confounding results (3), among the overexpressed immunotherapy targets, we demonstrated that LSP was rich in PDCD1LG2 (PD-L2) and both HSP and LSP overexpressed CD276 (B7-H3), which was associated with resistance to anti-PD1 therapy and may have accounted for the modest results of previous clinical trials, and (4) identification of patients with LSP or HSP ACC can be used to help determine whether immunotherapy should be used. In conclusion, we highlighted the differences between LSP and HSP, drawing attention to potential therapeutic targets (CD276, PDCD1, and PDCD1LG2). Treatments to reduce immune evasion, as well as the use of other natural and pharmacological immune activators, should include prior pharmacological inhibition of steroidogenesis. Attempts to combine these with tumor cell proliferation inhibitors, if they do not affect cells of the immune system, may produce interesting results.

Project description:Objective: Adrenocortical carcinoma (ACC) is a rare but aggressive malignant cancer that has been attracting growing attention over recent decades. This study aims to integrate protein interaction networks with gene expression profiles to identify potential biomarkers with prognostic value in silico. Methods: Three microarray data sets were downloaded from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) according to the normalization annotation information. Enrichment analyses were utilized to describe biological functions. A protein-protein interaction network (PPI) of the DEGs was developed, and the modules were analyzed using STRING and Cytoscape. LASSO Cox regression was used to identify independent prognostic factors. The Kaplan-Meier method for the integrated expression score was applied to analyze survival outcomes. A receiver operating characteristic (ROC) curve was constructed with area under curve (AUC) analysis to determine the diagnostic ability of the candidate biomarkers. Results: A total of 150 DEGs and 24 significant hub genes with functional enrichment were identified as candidate prognostic biomarkers. LASSO Cox regression suggested that ZWINT, PRC1, CDKN3, CDK1 and CCNA2 were independent prognostic factors in ACC. In multivariate Cox analysis, the integrated expression scores of the modules showed statistical significance in predicting disease-free survival (DFS, P = 0.019) and overall survival (OS, P < 0.001). Meanwhile, ROC curves were generated to validate the ability of the Cox model to predict prognosis. The AUC index for the integrated genes scores was 0.861 (P < 0.0001). Conclusion: In conclusion, the present study identifies DEGs and hub genes that may be involved in poor prognosis and early recurrence of ACC. The expression levels of ZWINT, PRC1, CDKN3, CDK1 and CCNA2 are of high prognostic value, and may help us understand better the underlying carcinogenesis or progression of ACC. Further studies are required to elucidate molecular pathogenesis and alteration in signaling pathways for these genes in ACC.

Project description:ImportanceThe risk stratification of adrenocortical carcinoma (ACC) based on tumor proliferation index and stage is limited. Adjuvant therapy after surgery is recommended for most patients. Pan-genomic studies have identified distinct molecular groups closely associated with outcome.ObjectiveTo compare the molecular classification for prognostic assessment of ACC with other known prognostic factors.Design, setting, and participantsIn this retrospective biomarker analysis, ACC tumor samples from 368 patients who had undergone surgical tumor removal were collected from March 1, 2005, to September 30, 2015 (144 in the training cohort and 224 in the validation cohort) at 21 referral centers with a median follow-up of 35 months (interquartile range, 18-74 months). Data were analyzed from March 2016 to March 2018.ExposuresMeta-analysis of pan-genomic studies (transcriptome, methylome, chromosome alteration, and mutational profiles) was performed on the training cohort. Targeted biomarker analysis, including targeted gene expression (BUB1B and PINK1), targeted methylation (PAX5, GSTP1, PYCARD, and PAX6), and targeted next-generation sequencing, was performed on the training and validation cohorts.Main outcomes and measuresDisease-free survival. Cox proportional hazards regression and C indexes were used to assess the prognostic value of each model.ResultsOf the 368 patients (mean [SD] age, 49 [16] years), 144 were in the training cohort (100 [69.4%] female) and 224 were in the validation cohort (142 [63.4%] female). In the training cohort, pan-genomic measures classified ACC into 3 molecular groups (A1, A2, and A3-B), with 5-year survival of 9% for group A1, 45% for group A2, and 82% for group A3-B (log-rank P < .001). Molecular class was an independent prognostic factor of recurrence in stage I to III ACC after complete surgery (hazard ratio, 55.91; 95% CI, 8.55-365.40; P < .001). The combination of European Network for the Study of Adrenal Tumors (ENSAT) stage, tumor proliferation index, and molecular class provided the most discriminant prognostic model (C index, 0.88). In the validation cohort, the molecular classification, determined by targeted biomarker measures, was confirmed as an independent prognostic factor of recurrence (hazard ratio, 5.96 [95% CI, 1.81-19.58], P = .003 for the targeted classifier combining expression, methylation, and chromosome alterations; and 2.61 [95% CI, 1.31-5.19], P = .006 for the targeted classifier combining methylation, chromosome alterations, and mutational profile). The prognostic value of the molecular markers was limited for patients with stage IV ACC.Conclusions and relevanceThe findings suggest that in localized ACC, targeted classifiers may be used as independent markers of recurrence. The determination of molecular class may improve individual prognostic assessment and thus may spare unnecessary adjuvant treatment.

Dataset Information

Molecular Drivers of Potential Immunotherapy Failure in Adrenocortical Carcinoma.

Publications

Molecular Drivers of Potential Immunotherapy Failure in Adrenocortical Carcinoma.

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