Q-omics provides the consensus-scored HSF1 profile across patient tissues and cancer cell-line models. HSF1 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, HSF1 is differentially expressed in 15, with the highest sampling consensus in COAD. Additionally, HSF1 protein abundance shows 24,289 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight LIHC, COAD, and GBM as cancer lineages where HSF1 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 HSF1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes HSF1 survival associations across molecular data types. HSF1 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (3) 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 HSF1 RNA expression–survival associations across cancer types. High HSF1 expression shows unfavorable associations in LIHC, KIRC, CESC, KICH, ACC and KIRP. The LIHC 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 LIHC as the clearest survival context for HSF1 RNA expression.
This table summarizes HSF1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 6. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for HSF1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. HSF1 shows higher tumor expression in COAD, HNSC, KIRP, KIRC, LIHC and LUAD. The COAD box plot shows higher HSF1 RNA expression in tumor versus normal tissue (log2 FC = +1.327, t-test p < 0.001).
This table shows molecular features associated with HSF1 in patient tissues and cancer cell lines. In patient samples, HSF1 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, HSF1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and BLOOD_Lymphoma.
