Q-omics provides the consensus-scored HOXC4 profile across patient tissues and cancer cell-line models. HOXC4 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, HOXC4 is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, HOXC4 RNA expression shows 17,984 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight UVM, HNSC, and ACC as cancer lineages where HOXC4 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 HOXC4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes HOXC4 survival associations across molecular data types. HOXC4 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (6) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible HOXC4 RNA expression–survival associations across cancer types. High HOXC4 expression shows unfavorable associations in UVM, HNSC, COAD, ACC and LGG, but favorable associations in BRCA. 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 HOXC4 RNA expression.
This table summarizes HOXC4 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 1. The strongest signals are observed in HNSC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for HOXC4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. HOXC4 shows lower tumor expression in KIRC and higher tumor expression in HNSC, BRCA, LUSC, BLCA and LUAD. The HNSC box plot shows higher HOXC4 RNA expression in tumor versus normal tissue (log2 FC = +1.526, t-test p < 0.001).
This table shows molecular features associated with HOXC4 in patient tissues and cancer cell lines. In patient samples, HOXC4 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, HOXC4 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in KIDNEY, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Myeloma and SKIN.
