# Bimodal Genomic Approach Predicting Semaphorin 7A (SEMA7A) as Prognostic Biomarker in Adrenocortical Carcinoma

## TL;DR

This study identifies SEMA7A as a poor prognostic biomarker in adrenocortical carcinoma and suggests it as a potential target for immunotherapy.

## Contribution

The study introduces a bimodal genomic approach to identify SEMA7A as a novel prognostic biomarker and therapeutic target in ACC.

## Key findings

- High SEMA7A expression is associated with poor prognosis in ACC patients (hazard ratio = 4.27; p-value < 0.001).
- SEMA7A is co-expressed with integrin-β1, FAK, and MAPK/ERK signaling pathways in ACC tumors.
- IHC analysis confirms a significant correlation between SEMA7A RNA and protein expression in ACC tissues.

## Abstract

Adrenocortical cancer (ACC) remains a challenging disease primarily due to the scarcity of reliable biomarkers for predicting patient outcomes and informing innovative therapeutic strategies, as well as its rarity, which restricts the scope of clinical trials. In our study, we developed a bimodal approach using RNA-seq data for stratifying cancer patients and predicting prognostic biomarkers. Our findings indicate that a substantial proportion of ACC tumors exhibit expression of SEMA7A, a glycoprotein involved in Semaphorin cell surface signaling. Notably, elevated levels of SEMA7A were identified as a poor prognostic biomarker and were associated with activation of the integrin–ERK-MAPK signaling pathways. These findings were further confirmed by an IHC analysis of ACC samples obtained from tissue microarray slides and National Cancer Institute (NCI) cancer patients. These results suggest that ACC tumors with high SEMA7A expression should be considered at elevated risk, and SEMA7A may serve as a potential target for immunotherapeutic strategies, including antibody–drug conjugates, T-cell engagers, and/or small-molecule inhibitors targeting the MAPK pathway.

Background: Adrenocortical carcinoma (ACC) is a rare and aggressive endocrine malignancy with a high mortality and poor prognosis. To elucidate the genetic underpinnings of ACCs, we have analyzed the transcriptome profiles of ACC tumor samples from patients enrolled in the TCGA and NCI cohorts. Methods: We developed a bimodal approach using Gaussian Mixture Models to identify genes with bimodal distribution in ACC samples. Among the 72 bimodally expressed genes that are used to stratify patients into prognostic groups, we focused on SEMA7A, as it encodes a glycosylphosphatidylinositol-anchored membrane glycoprotein (Semaphorin 7a) regulating integrin-mediated signaling, cell migration and immune responses. Results: Our findings reveal that high expression levels of SEMA7A gene are associated with poor prognosis (hazard ratio = 4.27; p-value < 0.001). In hormone-producing ACCs, SEMA7A expression is elevated and positively correlated with genes driving steroidogenesis, aldosterone and cortisol synthesis, including CYP17A1, CYP11A1, INHA, DLK1, NR5A1 and MC2R. Correlation analyses show that SEMA7A is co-expressed with the integrin-β1, FAK (focal adhesion kinase) and MAPK/ERK (mitogen-activated protein kinase/extracellular signal regulated kinases) signaling pathways. Immunohistochemistry (IHC) staining demonstrates the feasibility of evaluating SEMA7A in ACC tissues and shows a significant correlation between gene expression (RNA-Seq) and protein expression (IHC). Conclusions: These findings suggest SEMA7A as a candidate for further research in ACC biology and a candidate for cancer therapy, as well as a potential prognosis biomarker for ACC patients.