Q-omics provides the consensus-scored PRPF19 profile across patient tissues and cancer cell-line models. PRPF19 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, PRPF19 is differentially expressed in 15, with the highest sampling consensus in COAD. Additionally, PRPF19 protein abundance shows 30,179 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight LIHC, COAD, and LSCC as cancer lineages where PRPF19 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 PRPF19 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PRPF19 survival associations across molecular data types. PRPF19 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (4) 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 PRPF19 RNA expression–survival associations across cancer types. High PRPF19 expression shows unfavorable associations in LIHC, BLCA, KICH, KIRP, HNSC and LUAD. The LIHC 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 LIHC as the clearest survival context for PRPF19 RNA expression.
This table summarizes PRPF19 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 7. The strongest signals are observed in COAD for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for PRPF19. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PRPF19 shows higher tumor expression in COAD, HNSC, KIRP, KIRC, STAD and LIHC. The COAD box plot shows higher PRPF19 RNA expression in tumor versus normal tissue (log2 FC = +1.043, t-test p < 0.001).
This table shows molecular features associated with PRPF19 in patient tissues and cancer cell lines. In patient samples, PRPF19 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, PRPF19 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in LUNG_SCLC and BLOOD_Leukemia.
