Correlation analysis between CISD1 and immune checkpoint blockade proteins. (IMAGE)
Caption
(A–C) The radar plots generated from SangerBox illustrate the correlation between CISD1 expression and tumor mutation burden (TMB) (A), microsatellite instability (MSI) (B), and neoantigen burden (NEO) (C) across various cancers. The correlation coefficients are shown, with cancer types labeled around the plot perimeter. Significant correlations (P < 0.05) are highlighted in red, and the blue lines indicate the correlation values. Negative correlation coefficients are presented inside the plots. (D) The heatmap generated from SangerBox shows the correlation between CISD1 expression and various immune checkpoint blockade-related genes, including PD1, PD-L1, and CTLA4, across multiple cancer types. The color gradient represents correlation coefficients, with red indicating positive correlations and blue indicating negative correlations. Significant correlations are marked by stars (*), and dark green means no significant. (E) The scatter plot generated from TISIDB shows the log2 fold change between responders and non-responders to immune checkpoint blockade therapy (e.g., PD-1, PD-L1) in various cancer types. The position on the X-axis represents the fold change, while the Y-axis shows the moderated t-test P-values. (F) CISD1 is a diagnostic, prognostic, and immunotherapeutic biomarker in multiple cancers. This picture simply summarizes the evidence that CISD1 is a reliable and promising biomarker. CISD1 plays a critical role in cellular energetics; it participates in many biological processes related to energy and metabolism. Its expression levels are elevated in multiple cancers, and it undergoes genetic alterations in various cancers, which enable it to aid in cancer early diagnosis. Patients with increased expression levels of CISD1 have relatively lower survival rates; moreover, its positive correlation with tumor stemness indices and RNA modifications indicates that it can be used to predict prognosis. It is positively correlated with tumor infiltration and immune checkpoint genes, and it exhibits higher expression levels in patients who respond to tumor immunotherapy
Credit
Caiyue Li, Zhipin Liang, Gabrielle Vontz, Connor Kent, Wenbo Ma, Lei Liu, Riya Dahal, Jovanny Zabaleta, Guoshuai Cai, Jia Zhou, Huangen Ding, Qiang Shen
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