Q-omics provides the consensus-scored HEXA profile across patient tissues and cancer cell-line models. HEXA expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in UCEC. Among the 18 cancer types available for tumor–normal comparison, HEXA is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, HEXA protein abundance shows 22,364 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight UCEC, HNSC, and GBM as cancer lineages where HEXA 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 HEXA — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes HEXA survival associations across molecular data types. HEXA RNA expression shows survival associations in the most cancer types (26), followed by mutation status (5) 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 HEXA RNA expression–survival associations across cancer types. High HEXA expression shows unfavorable associations in HNSC, LGG, UVM, GBM and KIRP, but favorable associations in UCEC. The UCEC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify UCEC as the clearest survival context for HEXA RNA expression.
This table summarizes HEXA 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 7. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for HEXA. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. HEXA shows lower tumor expression in LUSC and higher tumor expression in HNSC, KIRC, LIHC, STAD and THCA. The HNSC box plot shows higher HEXA RNA expression in tumor versus normal tissue (log2 FC = +1.438, t-test p < 0.001).
This table shows molecular features associated with HEXA in patient tissues and cancer cell lines. In patient samples, HEXA 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, HEXA RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LARGE_INTESTINE, while CRISPR and shRNA rows add functional-dependency signals in SKIN and BONE.
