C-myc expression in adrenocortical tumours

Advances in translational research of the rare cancer type adrenocortical carcinoma

Adrenocortical carcinoma is a rare malignancy with an annual worldwide incidence of 1-2 cases per 1 million and a 5-year survival rate of <60%. Although adrenocortical carcinoma is rare, such rare cancers account for approximately one third of patients diagnosed with cancer annually. In the past decade, there have been considerable advances in understanding the molecular basis of adrenocortical carcinoma. The genetic events associated with adrenocortical carcinoma in adults are distinct from those of paediatric cases, which are often associated with germline or somatic TP53 mutations and have a better prognosis. In adult primary adrenocortical carcinoma, the main somatic genetic alterations occur in genes that encode proteins involved in the WNT-β-catenin pathway, cell cycle and p53 apoptosis pathway, chromatin remodelling and telomere maintenance pathway, cAMP-protein kinase A (PKA) pathway or DNA transcription and RNA translation pathways. Recently, integrated molecular studies of adrenocortical carcinomas, which have characterized somatic mutations and the methylome as well as gene and microRNA expression profiles, have led to a molecular classification of these tumours that can predict prognosis and have helped to identify new therapeutic targets. In this Review, we summarize these recent translational research advances in adrenocortical carcinoma, which it is hoped could lead to improved patient diagnosis, treatment and outcome.

Origin and Therapies of Osteosarcoma

Simple Summary

Osteosarcoma is the most common malignant bone tumor in children, with a 5-year survival rate ranging from 70% to 20% depending on the aggressiveness of the disease. The current treatments have not evolved over the past four decades due in part to the genetic complexity of the disease and its heterogeneity. This review will summarize the current knowledge of OS origin, diagnosis and therapies.

Abstract

Osteosarcoma (OS) is the most frequent primary bone tumor, mainly affecting children and young adults. Despite therapeutic advances, the 5-year survival rate is 70% but drastically decreases to 20–30% for poor responders to therapies or for patients with metastasis. No real evolution of the survival rates has been observed for four decades, explained by poor knowledge of the origin, difficulties related to diagnosis and the lack of targeted therapies for this pediatric tumor. This review will describe a non-exhaustive overview of osteosarcoma disease from a clinical and biological point of view, describing the origin, diagnosis and therapies.

MicroRNAs and Long Non-Coding RNAs in Adrenocortical Carcinoma

Non-coding RNAs (ncRNAs) are a type of genetic material that do not encode proteins but regulate the gene expression at an epigenetic level, such as microRNAs (miRNAs) and long non-coding RNAs (lncRNAs). The role played by ncRNAs in many physiological and pathological processes has gained attention during the last few decades, as they might be useful in the diagnosis, treatment and management of several human disorders, including endocrine and oncological diseases. Adrenocortical carcinoma (ACC) is a rare and aggressive endocrine cancer, still characterized by high mortality and morbidity due to both endocrine and oncological complications. Despite the rarity of this disease, recently, the role of ncRNA has been quite extensively evaluated in ACC. In order to better explore the role of the ncRNA in human ACC, this review summarizes the current knowledge on ncRNA dysregulation in ACC and its potential role in the diagnosis, treatment, and management of this tumor.

Identifying New Potential Biomarkers in Adrenocortical Tumors Based on mRNA Expression Data Using Machine Learning

Simple Summary

Using a visual-based clustering method on the TCGA RNA sequencing data of a large adrenocortical carcinoma (ACC) cohort, we were able to classify these tumors in two distinct clusters largely overlapping with previously identified ones. As previously shown, the identified clusters also correlated with patient survival. Applying the visual clustering method to a second dataset also including benign adrenocortical samples additionally revealed that one of the ACC clusters is more closely located to the benign samples, providing a possible explanation for the better survival of this ACC cluster. Furthermore, the subsequent use of machine learning identified new possible biomarker genes with prognostic potential for this rare disease, that are significantly differentially expressed in the different survival clusters and should be further evaluated.

Abstract

Adrenocortical carcinoma (ACC) is a rare disease, associated with poor survival. Several “multiple-omics” studies characterizing ACC on a molecular level identified two different clusters correlating with patient survival (C1A and C1B). We here used the publicly available transcriptome data from the TCGA-ACC dataset (n = 79), applying machine learning (ML) methods to classify the ACC based on expression pattern in an unbiased manner. UMAP (uniform manifold approximation and projection)-based clustering resulted in two distinct groups, ACC-UMAP1 and ACC-UMAP2, that largely overlap with clusters C1B and C1A, respectively. However, subsequent use of random-forest-based learning revealed a set of new possible marker genes showing significant differential expression in the described clusters (e.g., SOAT1, EIF2A1). For validation purposes, we used a secondary dataset based on a previous study from our group, consisting of 4 normal adrenal glands and 52 benign and 7 malignant tumor samples. The results largely confirmed those obtained for the TCGA-ACC cohort. In addition, the ENSAT dataset showed a correlation between benign adrenocortical tumors and the good prognosis ACC cluster ACC-UMAP1/C1B. In conclusion, the use of ML approaches re-identified and redefined known prognostic ACC subgroups. On the other hand, the subsequent use of random-forest-based learning identified new possible prognostic marker genes for ACC.

Interferon Regulatory Factor 4 Regulates the Development of Polymorphonuclear Myeloid-Derived Suppressor Cells Through the Transcription of c-Myc in Cancer

The accumulation of myeloid-derived suppressor cells (MDSCs) is one of the major obstacles to achieve an appropriate anti-tumor immune response and successful tumor immunotherapy. MDSCs in tumor-bearing hosts are primarily polymorphonuclear (PMN-MDSCs). However, the mechanisms regulating the development of MDSCs remain poorly understood. In this report, we showed that interferon regulatory factor 4 (IRF4) plays a key role in the development of PMN-MDSCs, but not monocytic MDSCs. IRF4 deficiency caused a significant elevation of PMN-MDSCs and enhanced the suppressive activity of PMN-MDSCs, increasing tumor growth and metastasis in mice. Mechanistic studies showed that c-Myc was up-regulated by the IRF4 protein. Over-expression of c-Myc almost abrogated the effects of IRF4 deletion on PMN-MDSCs development. Importantly, the IRF4 expression level was negatively correlated with the PMN-MDSCs frequency and tumor development but positively correlated with c-Myc expression in clinical cancer patients. In summary, this study demonstrated that IRF4 represents a novel regulator of PMN-MDSCs development in cancer, which may have predictive value for tumor progression.

TRIP13 promotes lung cancer cell growth and metastasis through AKT/mTORC1/c-Myc signaling

BACKGROUND

Lung adenocarcinoma (LUAD) is a primary cause of cancer-patient mortality throughout the world. Thyroid hormone receptor interactor 13 (TRIP13) is a gene that expresses a protein involved in cell division, including tumorigenesis. Its expression is high in various human tumors; however, its role in LUAD cells remains undetermined.

OBJECTIVE

To investigate the TRIP13's role in the development of LUAD.

METHODS

Bioinformation analysis was used to analyze the expression of TRIP13 in LUAD tissues and the impact on the prognosis of LUAD; CRISPR/Cas9 was used to construct the cell lines; CCK-8 was used to explore the cell proliferation; Transwell assays was applied to exam the cell migration and cell invasion abilities; Western blot and immunoprecipitation was used to explore the relation between TRIP13 and AKT/mTORC1/c-Myc signaling pathway.

RESULTS

By analyzing LUAD data from The Cancer Genome Atlas and the Gene Expression Omnibus databases, we determined that TRIP13 is highly expressed in LUAD tissues and that this expression level has a negative impact on the patient mortality. TRIP13 has also proved to promote LUAD cell proliferation, migration, and invasion. In this study, we demonstrated that TRIP13 activates AKT/mTORC1/c-Myc signaling in these cells.

CONCLUSION

Our results have identified the role and potential mechanism by which TRIP13 affects LUAD cells, which may provide a useful marker for helping to diagnose this disease and create new therapies against it.

The Role of Biomarkers in Adrenocortical Carcinoma: A Review of Current Evidence and Future Perspectives

Adrenocortical carcinoma (ACC) is a rare endocrine malignancy arising from the adrenal cortex often with unexpected biological behavior. It can occur at any age, with two peaks of incidence: in the first and between fifth and seventh decades of life. Although ACC are mostly hormonally active, precursors and metabolites, rather than end products of steroidogenesis are produced by dedifferentiated and immature malignant cells. Distinguishing the etiology of adrenal mass, between benign adenomas, which are quite frequent in general population, and malignant carcinomas with dismal prognosis is often unfeasible. Even after pathohistological analysis, diagnosis of adrenocortical carcinomas is not always straightforward and represents a great challenge for experienced and multidisciplinary expert teams. No single imaging method, hormonal work-up or immunohistochemical labelling can definitively prove the diagnosis of ACC. Over several decades' great efforts have been made in finding novel reliable and available diagnostic and prognostic factors including steroid metabolome profiling or target gene identification. Despite these achievements, the 5-year mortality rate still accounts for approximately 75% to 90%, ACC is frequently diagnosed in advanced stages and therapeutic options are unfortunately limited. Therefore, imperative is to identify new biological markers that can predict patient prognosis and provide new therapeutic options.

A computational drug repositioning method applied to rare diseases: Adrenocortical carcinoma

Rare or orphan diseases affect only small populations, thereby limiting the economic incentive for the drug development process, often resulting in a lack of progress towards treatment. Drug repositioning is a promising approach in these cases, due to its low cost. In this approach, one attempts to identify new purposes for existing drugs that have already been developed and approved for use. By applying the process of drug repositioning to identify novel treatments for rare diseases, we can overcome the lack of economic incentives and make concrete progress towards new therapies. Adrenocortical Carcinoma (ACC) is a rare disease with no practical and definitive therapeutic approach. We apply Heter-LP, a new method of drug repositioning, to suggest novel therapeutic avenues for ACC. Our analysis identifies innovative putative drug-disease, drug-target, and disease-target relationships for ACC, which include Cosyntropin (drug) and DHCR7, IGF1R, MC1R, MAP3K3, TOP2A (protein targets). When results are analyzed using all available information, a number of novel predicted associations related to ACC appear to be valid according to current knowledge. We expect the predicted relations will be useful for drug repositioning in ACC since the resulting ranked lists of drugs and protein targets can be used to expedite the necessary clinical processes.

Prognostic Value of c-Myc Immunohistochemical Expression in Muscle Invasive Urothelial Carcinoma of the Urinary Bladder: A Retrospective Study

Objective:

This study aimed to investigate the immunohistochemical expression of c-Myc in muscle invasive urothelial carcinoma (MIUC) of the urinary bladder and to evaluate the correlation of c-Myc expression with different clinicopathological parameters and outcome, including a relatively new histopathological tumor characteristic that is the growth pattern of tumor invasion.

Methods:

A total of 66 formalin-fixed and paraffin-embedded sections of MIUC obtained from radical cystectomy specimens were enrolled. The sections were stained with c-Myc antibody using immunohistochemistry technique.

Results:

Tumor cells showed variability in nuclear c-Myc expression according to the growth pattern of invasion. The median H-score of nuclear expression of infiltrative pattern was significantly higher than that of non-infiltrative pattern (p<0.001). Nuclear expression of c-Myc in tumor tissue had a significant association with poor prognostic factors (sarcomatoid variant (p<0.001), perineural invasion (p=0.037), lymphovascular invasion (p<0.001), lymph node metastasis (p<0.001), distant metastasis (p=0.042) and advanced stage grouping (p=0.001). Kaplan Meier survival analysis demonstrated that c-Myc expression could not be significantly correlated with overall survival or disease free survival rates.

Conclusion:

Nuclear c-Myc seems to have a prominent role in epithelial to mesenchymal transition with consequential in tumor progression and metastasis, while it is not as much useful to predict the clinical behavior of patients with MIUC.