Q-omics provides the consensus-scored CHPF profile across patient tissues and cancer cell-line models. CHPF expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in BRCA. Among the 18 cancer types available for tumor–normal comparison, CHPF is differentially expressed in 17, with the highest sampling consensus in HNSC. Additionally, CHPF RNA expression shows 18,078 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight BRCA, HNSC, and ACC as cancer lineages where CHPF 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 CHPF — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CHPF survival associations across molecular data types. CHPF RNA expression shows survival associations in the most cancer types (26), followed by mutation status (7) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CHPF RNA expression–survival associations across cancer types. High CHPF expression shows unfavorable associations in BRCA, HNSC, LGG, BLCA and LUAD, but favorable associations in UVM. The BRCA Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify BRCA as the clearest survival context for CHPF RNA expression.
This table summarizes CHPF tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 17, while mass-spec protein shows differences in 4. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for CHPF. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CHPF shows higher tumor expression in HNSC, COAD, KIRP, KIRC, LUAD and LUSC. The HNSC box plot shows higher CHPF RNA expression in tumor versus normal tissue (log2 FC = +2.045, t-test p < 0.001).
This table shows molecular features associated with CHPF in patient tissues and cancer cell lines. In patient samples, CHPF shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, CHPF RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and BONE.
