Q-omics provides the consensus-scored CPSF1 profile across patient tissues and cancer cell-line models. CPSF1 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, CPSF1 is differentially expressed in 15, with the highest sampling consensus in COAD. Additionally, CPSF1 protein abundance shows 30,389 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, COAD, and GBM as cancer lineages where CPSF1 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 CPSF1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CPSF1 survival associations across molecular data types. CPSF1 RNA expression shows survival associations in the most cancer types (27), 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 CPSF1 RNA expression–survival associations across cancer types. High CPSF1 expression shows unfavorable associations in KIRC, ACC, MESO, KICH and LIHC, but favorable associations in SCLC. The KIRC 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 KIRC as the clearest survival context for CPSF1 RNA expression.
This table summarizes CPSF1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 8. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for CPSF1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CPSF1 shows higher tumor expression in COAD, HNSC, KIRC, LIHC, LUAD and BLCA. The COAD box plot shows higher CPSF1 RNA expression in tumor versus normal tissue (log2 FC = +1.769, t-test p < 0.001).
This table shows molecular features associated with CPSF1 in patient tissues and cancer cell lines. In patient samples, CPSF1 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, CPSF1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Myeloma, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and BONE.
