Q-omics provides the consensus-scored CRHR2 profile across patient tissues and cancer cell-line models. CRHR2 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in LUAD. Among the 18 cancer types available for tumor–normal comparison, CRHR2 is differentially expressed in 9, with the highest sampling consensus in LIHC. Additionally, CRHR2 protein abundance shows 20,840 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight LUAD, LIHC, and PDAC as cancer lineages where CRHR2 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 CRHR2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CRHR2 survival associations across molecular data types. CRHR2 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (6) 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 CRHR2 RNA expression–survival associations across cancer types. High CRHR2 expression shows unfavorable associations in STAD and CESC, but favorable associations in LUAD, HNSC, PAAD and SARC. The LUAD 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 LUAD as the clearest survival context for CRHR2 RNA expression.
This table summarizes CRHR2 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 5. The strongest signals are observed in LIHC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for CRHR2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CRHR2 shows lower tumor expression in UCEC, BRCA and KICH and higher tumor expression in LIHC, THCA and CHOL. The LIHC box plot shows higher CRHR2 RNA expression in tumor versus normal tissue (log2 FC = +0.258, t-test p < 0.001).
This table shows molecular features associated with CRHR2 in patient tissues and cancer cell lines. In patient samples, CRHR2 shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, CRHR2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in URINARY_TRACT and BLOOD_Lymphoma.
