Q-omics provides the consensus-scored CRP profile across patient tissues and cancer cell-line models. CRP expression is associated with patient survival in 18 of 34 cancer types, with the highest sampling consensus in ESCA. Among the 18 cancer types available for tumor–normal comparison, CRP is differentially expressed in 7, with the highest sampling consensus in KIRC. Additionally, CRP RNA expression shows 5,654 significant pathway-activity associations, with the highest sampling consensus in BRCA. Together, these results highlight ESCA, KIRC, and BRCA as cancer lineages where CRP 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 CRP — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CRP survival associations across molecular data types. CRP RNA expression shows survival associations in the most cancer types (18), followed by mutation status (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CRP RNA expression–survival associations across cancer types. High CRP expression shows unfavorable associations in LUAD, KICH, BRCA, KIRC and KIRP, but favorable associations in ESCA. The ESCA Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .001). Together, the overview and detailed table identify ESCA as the clearest survival context for CRP RNA expression.
This table summarizes CRP tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 7, while mass-spec protein shows differences in 3. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for CRP. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CRP shows lower tumor expression in LIHC, LUAD, CHOL and BRCA and higher tumor expression in KIRC and THCA. The KIRC box plot shows higher CRP RNA expression in tumor versus normal tissue (log2 FC = +0.692, t-test p < 0.001).
This table shows molecular features associated with CRP in patient tissues and cancer cell lines. In patient samples, CRP shows the broadest associations at the RNA and protein expression levels, with BRCA recurring as the lineage with the largest associated feature set. In cancer cell lines, CRP RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in LUNG_SCLC and BLOOD_Lymphoma.
