MAGE-A genes as predictors of the outcome of laryngeal squamous cell carcinoma

The MAGE A1-A10 Expression associated with Histopathological Findings of Malignant or Non-Malignant Cells in Peripheral Lung Tumors

OBJECTIVE

The objective was to evaluate the expression of melanoma antigen (MAGE) A from A1 to 10 (A1-10) and the individual MAGE A family in the peripheral lung tumors and to analyze its association with histopathological findings.

METHODS

A cross-sectional study was conducted on 67 samples of peripheral lung tumor obtained by core biopsies from patients with clinical diagnoses such as lung and mediastinal tumors. The specimens were divided into two, one to perform histopathological diagnosis and the last for mRNA MAGE A examination. A Nested polymerase chain reaction (PCR) was performed using universal primer, MF10/MR10 and MF10/MR12. The collected data were analyzed by appropriate statistical techniques.

RESULT

The histopathological finding showed 41 (61.2 %) of specimens as malignant cells and 26 (38.8 %) of specimens as non-malignant cells. MAGE A1-10 was expressed at 47 (70.1 %) and MAGE A1-6 was expressed at 25 (37.3 %) of specimens. In a malignant cell, MAGE A1-10 and MAGE A1-6 were expressed at 33 (80.5 %) and 19 (46.3 %), respectively. In non-malignant cells, MAGE A1-10 and MAGE A1-6 were expressed at 14 (53.9 %) and 6 (23.1 %,) respectively. The MAGE A1-10 and MAGE A8 expressions were significantly associated with histopathological findings of malignant or non-malignant cells. The sensitivity, specificity, and diagnostic accuracy of MAGE A1-10 were 80.5 %, 46.2 %, and 67.2 %, respectively; while for MAGE A8 were 41.5 %, 88.5 %, and 59.7 %, respectively.

CONCLUSION

The MAGE A1-10 expression was the most commonly detected and associated with the histopathological finding. Moreover, it was more sensitive and specific and had higher diagnostic accuracy than others. Therefore, the MAGE A1-10 assay may improve the accuracy of the diagnosis of malignancy in peripheral lung tumors.

Alterations in Gene Pair Correlations as Potential Diagnostic Markers for Colon Cancer

Colorectal cancer (CRC) is a leading cause of death from cancer in Canada. Early detection of CRC remains crucial in managing disease prognosis and improving patient survival. It can also facilitate prevention, screening, and treatment before the disease progresses to a chronic stage. In this study, we developed a strategy for identifying colon cancer biomarkers from both gene expression and gene pair correlation. Using the RNA-Seq dataset TCGA-COAD, a panel of 71 genes, including the 20 most upregulated genes, 20 most downregulated genes and 31 genes involved in the most significantly altered gene pairs, were selected as potential biomarkers for colon cancer. This signature set of genes could be used for early diagnosis. Furthermore, this strategy could be applied to other types of cancer.