Q-omics provides the consensus-scored HECA profile across patient tissues and cancer cell-line models. HECA expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, HECA is differentially expressed in 10, with the highest sampling consensus in KIRC. Additionally, HECA protein abundance shows 21,375 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight KIRP, KIRC, and LUAD as cancer lineages where HECA 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 HECA — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes HECA survival associations across molecular data types. HECA RNA expression shows survival associations in the most cancer types (25), followed by mutation status (4) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible HECA RNA expression–survival associations across cancer types. High HECA expression shows unfavorable associations in KIRP, ACC and OV, but favorable associations in KIRC, HNSC and SKCM. The KIRP 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 KIRP as the clearest survival context for HECA RNA expression.
This table summarizes HECA tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 7. The strongest signals are observed in KIRC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for HECA. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. HECA shows lower tumor expression in LUAD, THCA, UCEC and BRCA and higher tumor expression in KIRC and HNSC. The KIRC box plot shows higher HECA RNA expression in tumor versus normal tissue (log2 FC = +0.651, t-test p < 0.001).
This table shows molecular features associated with HECA in patient tissues and cancer cell lines. In patient samples, HECA 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, HECA RNA and mutation anchors are most strongly linked to RNA-expression features, especially in URINARY_TRACT, while CRISPR and shRNA rows add functional-dependency signals in BREAST and BLOOD_Leukemia.
