Q-omics provides the consensus-scored CFHR2 profile across patient tissues and cancer cell-line models. CFHR2 expression is associated with patient survival in 4 of 34 cancer types, with the highest sampling consensus in CHOL. Among the 18 cancer types available for tumor–normal comparison, CFHR2 is differentially expressed in 2, with the highest sampling consensus in CHOL. Additionally, CFHR2 protein abundance shows 31,480 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight CHOL, and LSCC as cancer lineages where CFHR2 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 CFHR2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CFHR2 survival associations across molecular data types. CFHR2 RNA expression shows survival associations in the most cancer types (4), followed by mutation status (4) and mass-spec protein abundance (10). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CFHR2 RNA expression–survival associations across cancer types. High CFHR2 expression shows unfavorable associations in CHOL and PAAD, but favorable associations in LIHC and SCLC. The CHOL Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify CHOL as the clearest survival context for CFHR2 RNA expression.
This table summarizes CFHR2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 2, while mass-spec protein shows differences in 10. The strongest signals are observed in CHOL for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for CFHR2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CFHR2 shows lower tumor expression in CHOL and LIHC and higher tumor expression in LIHC. The CHOL box plot shows higher CFHR2 RNA expression in normal versus tumor tissue (log2 FC = −4.069, t-test p < 0.001).
This table shows molecular features associated with CFHR2 in patient tissues and cancer cell lines. In patient samples, CFHR2 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, CFHR2 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 BREAST and CNS.
