Q-omics provides the consensus-scored PRPF4B profile across patient tissues and cancer cell-line models. PRPF4B expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, PRPF4B is differentially expressed in 10, with the highest sampling consensus in LIHC. Additionally, PRPF4B protein abundance shows 38,431 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight ACC, LIHC, and GBM as cancer lineages where PRPF4B 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 PRPF4B — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PRPF4B survival associations across molecular data types. PRPF4B RNA expression shows survival associations in the most cancer types (24), followed by mutation status (3) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PRPF4B RNA expression–survival associations across cancer types. High PRPF4B expression shows unfavorable associations in ACC and LIHC, but favorable associations in BLCA, UCS, KIRC and READ. 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 PRPF4B RNA expression.
This table summarizes PRPF4B tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 13. The strongest signals are observed in THCA for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for PRPF4B. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PRPF4B shows lower tumor expression in THCA and KICH and higher tumor expression in LIHC, HNSC, STAD and CHOL. The LIHC box plot shows higher PRPF4B RNA expression in tumor versus normal tissue (log2 FC = +0.899, t-test p < 0.001).
This table shows molecular features associated with PRPF4B in patient tissues and cancer cell lines. In patient samples, PRPF4B 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, PRPF4B RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in LIVER and BLOOD_Leukemia.
