Q-omics provides the consensus-scored HEMGN profile across patient tissues and cancer cell-line models. HEMGN expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, HEMGN is differentially expressed in 9, with the highest sampling consensus in THCA. Additionally, HEMGN RNA expression shows 10,255 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight SKCM, THCA, and THYM as cancer lineages where HEMGN 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 HEMGN — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes HEMGN survival associations across molecular data types. HEMGN RNA expression shows survival associations in the most cancer types (24), 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 HEMGN RNA expression–survival associations across cancer types. High HEMGN expression shows unfavorable associations in ACC, but favorable associations in SKCM, PAAD, LUAD, CESC and LIHC. The SKCM 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 SKCM as the clearest survival context for HEMGN RNA expression.
This table summarizes HEMGN tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9, while mass-spec protein shows differences in 3. The strongest signals are observed in THCA for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for HEMGN. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. HEMGN shows lower tumor expression in THCA, LUAD, COAD, LUSC, BLCA and BRCA. The THCA box plot shows higher HEMGN RNA expression in normal versus tumor tissue (log2 FC = −0.530, t-test p < 0.001).
This table shows molecular features associated with HEMGN in patient tissues and cancer cell lines. In patient samples, HEMGN shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, HEMGN RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in OVARY and BLOOD_Leukemia.
