Q-omics provides the consensus-scored HIP1 profile across patient tissues and cancer cell-line models. HIP1 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, HIP1 is differentially expressed in 15, with the highest sampling consensus in HNSC. Additionally, HIP1 protein abundance shows 22,427 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight UVM, HNSC, and LUAD as cancer lineages where HIP1 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 HIP1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes HIP1 survival associations across molecular data types. HIP1 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (5) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible HIP1 RNA expression–survival associations across cancer types. High HIP1 expression shows unfavorable associations in UVM, COAD, LAML and ACC, but favorable associations in KIRC and ESCA. The UVM 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 UVM as the clearest survival context for HIP1 RNA expression.
This table summarizes HIP1 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 PDAC for protein.
This table ranks reproducible tumor–normal expression differences for HIP1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. HIP1 shows lower tumor expression in KICH and higher tumor expression in HNSC, LIHC, THCA, STAD and COAD. The HNSC box plot shows higher HIP1 RNA expression in tumor versus normal tissue (log2 FC = +1.584, t-test p < 0.001).
This table shows molecular features associated with HIP1 in patient tissues and cancer cell lines. In patient samples, HIP1 shows the broadest associations at the RNA and protein expression levels, with LUAD recurring as the lineage with the largest associated feature set. In cancer cell lines, HIP1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in STOMACH, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and LARGE_INTESTINE.
