Q-omics provides the consensus-scored STEAP1B profile across patient tissues and cancer cell-line models. STEAP1B expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, STEAP1B is differentially expressed in 10, with the highest sampling consensus in HNSC. Additionally, STEAP1B RNA expression shows 16,560 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRP, HNSC, and ACC as cancer lineages where STEAP1B 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 STEAP1B — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes STEAP1B survival associations across molecular data types. STEAP1B RNA expression shows survival associations in the most cancer types (23), followed by mutation status (5) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible STEAP1B RNA expression–survival associations across cancer types. High STEAP1B expression shows unfavorable associations in KIRP, ACC, KICH, LIHC, STAD and BLCA. The KIRP 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 KIRP as the clearest survival context for STEAP1B RNA expression.
This table summarizes STEAP1B tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 2. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for STEAP1B. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. STEAP1B shows lower tumor expression in BRCA and higher tumor expression in HNSC, KIRC, LIHC, LUSC and LUAD. The HNSC box plot shows higher STEAP1B RNA expression in tumor versus normal tissue (log2 FC = +1.712, t-test p < 0.001).
This table shows molecular features associated with STEAP1B in patient tissues and cancer cell lines. In patient samples, STEAP1B shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, STEAP1B RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OESOPHAGUS, while CRISPR and shRNA rows add functional-dependency signals in BREAST and SKIN.
