Q-omics provides the consensus-scored PRPF4 profile across patient tissues and cancer cell-line models. PRPF4 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, PRPF4 is differentially expressed in 16, with the highest sampling consensus in HNSC. Additionally, PRPF4 protein abundance shows 32,729 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight ACC, HNSC, and LSCC as cancer lineages where PRPF4 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 PRPF4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PRPF4 survival associations across molecular data types. PRPF4 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (5) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PRPF4 RNA expression–survival associations across cancer types. High PRPF4 expression shows unfavorable associations in ACC, LIHC, KIRP and BLCA, but favorable associations in KIRC and SCLC. The ACC 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 ACC as the clearest survival context for PRPF4 RNA expression.
This table summarizes PRPF4 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 8. The strongest signals are observed in HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for PRPF4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PRPF4 shows lower tumor expression in THCA and higher tumor expression in HNSC, COAD, STAD, LIHC and LUSC. The HNSC box plot shows higher PRPF4 RNA expression in tumor versus normal tissue (log2 FC = +1.582, t-test p < 0.001).
This table shows molecular features associated with PRPF4 in patient tissues and cancer cell lines. In patient samples, PRPF4 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, PRPF4 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 LARGE_INTESTINE and BLOOD_Leukemia.
