Q-omics provides the consensus-scored BIRC8 profile across patient tissues and cancer cell-line models. BIRC8 expression is associated with patient survival in 10 of 34 cancer types, with the highest sampling consensus in ACC. Additionally, BIRC8 RNA expression shows 6,222 significant pathway-activity associations, with the highest sampling consensus in STAD. Together, these results highlight ACC, and STAD as cancer lineages where BIRC8 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 BIRC8 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes BIRC8 survival associations across molecular data types. BIRC8 RNA expression shows survival associations in the most cancer types (10), followed by mutation status (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible BIRC8 RNA expression–survival associations across cancer types. High BIRC8 expression shows unfavorable associations in ACC, LIHC, KIRC, COAD and PAAD, but favorable associations in BLCA. The ACC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify ACC as the clearest survival context for BIRC8 RNA expression.
This table shows molecular features associated with BIRC8 in patient tissues and cancer cell lines. In patient samples, BIRC8 shows the broadest associations at the RNA and protein expression levels, with STAD recurring as the lineage with the largest associated feature set. In cancer cell lines, BIRC8 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in BREAST and LUNG_SCLC.
