Q-omics provides the consensus-scored GHRH profile across patient tissues and cancer cell-line models. GHRH expression is associated with patient survival in 18 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, GHRH is differentially expressed in 3, with the highest sampling consensus in HNSC. Additionally, GHRH protein abundance shows 27,775 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight KIRC, HNSC, and LUAD as cancer lineages where GHRH 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 GHRH — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GHRH survival associations across molecular data types. GHRH RNA expression shows survival associations in the most cancer types (18), followed by mutation status (3) 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 GHRH RNA expression–survival associations across cancer types. High GHRH expression shows unfavorable associations in KIRC, LIHC, THCA, DLBC and LUAD, but favorable associations in LUSC. The KIRC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .005). Together, the overview and detailed table identify KIRC as the clearest survival context for GHRH RNA expression.
This table summarizes GHRH tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 3, while mass-spec protein shows differences in 6. The strongest signals are observed in LUSC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for GHRH. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GHRH shows lower tumor expression in COAD and higher tumor expression in HNSC and LUSC. The HNSC box plot shows higher GHRH RNA expression in tumor versus normal tissue (log2 FC = +0.464, t-test p = .001).
This table shows molecular features associated with GHRH in patient tissues and cancer cell lines. In patient samples, GHRH 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, GHRH RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OESOPHAGUS, while CRISPR and shRNA rows add functional-dependency signals in LUNG_SCLC and BLOOD_Myeloma.
