Q-omics provides the consensus-scored HIF1A profile across patient tissues and cancer cell-line models. HIF1A expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in STAD. Among the 18 cancer types available for tumor–normal comparison, HIF1A is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, HIF1A RNA expression shows 19,678 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight STAD, HNSC, and UVM as cancer lineages where HIF1A 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 HIF1A — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes HIF1A survival associations across molecular data types. HIF1A RNA expression shows survival associations in the most cancer types (25), followed by mutation status (7) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible HIF1A RNA expression–survival associations across cancer types. High HIF1A expression shows unfavorable associations in STAD, CESC, UVM and MESO, but favorable associations in SKCM and LUSC. The STAD Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .005). Together, the overview and detailed table identify STAD as the clearest survival context for HIF1A RNA expression.
This table summarizes HIF1A tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 8. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for HIF1A. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. HIF1A shows lower tumor expression in KIRC and KICH and higher tumor expression in HNSC, LUAD, BLCA and LUSC. The HNSC box plot shows higher HIF1A RNA expression in tumor versus normal tissue (log2 FC = +2.058, t-test p < 0.001).
This table shows molecular features associated with HIF1A in patient tissues and cancer cell lines. In patient samples, HIF1A shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, HIF1A RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in CNS and BONE.
