Q-omics provides the consensus-scored PCIF1 profile across patient tissues and cancer cell-line models. PCIF1 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in SCLC. Among the 18 cancer types available for tumor–normal comparison, PCIF1 is differentially expressed in 15, with the highest sampling consensus in HNSC. Additionally, PCIF1 protein abundance shows 22,553 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight SCLC, HNSC, and GBM as cancer lineages where PCIF1 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 PCIF1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PCIF1 survival associations across molecular data types. PCIF1 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (5) 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 PCIF1 RNA expression–survival associations across cancer types. High PCIF1 expression shows unfavorable associations in LUSC and KICH, but favorable associations in SCLC, KIRC, UCS and UCEC. The SCLC 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 SCLC as the clearest survival context for PCIF1 RNA expression.
This table summarizes PCIF1 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 4. The strongest signals are observed in HNSC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for PCIF1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PCIF1 shows lower tumor expression in THCA and LUAD and higher tumor expression in HNSC, COAD, LIHC and STAD. The HNSC box plot shows higher PCIF1 RNA expression in tumor versus normal tissue (log2 FC = +0.699, t-test p < 0.001).
This table shows molecular features associated with PCIF1 in patient tissues and cancer cell lines. In patient samples, PCIF1 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, PCIF1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Lymphoma, while CRISPR and shRNA rows add functional-dependency signals in OESOPHAGUS and UPPER_AERODIGESTIVE_TRACT.
