Q-omics provides the consensus-scored EBAG9P1 profile across patient tissues and cancer cell-line models. EBAG9P1 expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, EBAG9P1 is differentially expressed in 9, with the highest sampling consensus in HNSC. Additionally, EBAG9P1 RNA expression shows 18,930 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight HNSC, and THYM as cancer lineages where EBAG9P1 shows reproducible signals across survival, tumor–normal expression, and patient cross-omics analyses.
Every result is evaluated using two consensus scores. Sampling consensus measures how consistently a finding is reproduced within a cancer lineage across different conditions. Lineage consensus measures how broadly the result is shared across cancer types, distinguishing pan-cancer signals from lineage-specific patterns.
Premium analyses for EBAG9P1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EBAG9P1 survival associations across molecular data types. EBAG9P1 RNA expression shows survival associations in the most cancer types (20). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible EBAG9P1 RNA expression–survival associations across cancer types. High EBAG9P1 expression shows unfavorable associations in COAD, but favorable associations in HNSC, SKCM, LGG, UCS and BRCA. The HNSC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify HNSC as the clearest survival context for EBAG9P1 RNA expression.
This table summarizes EBAG9P1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for EBAG9P1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EBAG9P1 shows lower tumor expression in THCA and higher tumor expression in HNSC, STAD, LIHC, BLCA and CHOL. The HNSC box plot shows higher EBAG9P1 RNA expression in tumor versus normal tissue (log2 FC = +0.305, t-test p < 0.001).
This table shows molecular features associated with EBAG9P1 in patient tissues and cancer cell lines. In patient samples, EBAG9P1 shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set.
