Q-omics provides the consensus-scored PRPF6 profile across patient tissues and cancer cell-line models. PRPF6 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, PRPF6 is differentially expressed in 14, with the highest sampling consensus in STAD. Additionally, PRPF6 protein abundance shows 31,773 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight LIHC, STAD, and GBM as cancer lineages where PRPF6 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 PRPF6 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PRPF6 survival associations across molecular data types. PRPF6 RNA expression shows survival associations in the most cancer types (21), followed by mutation status (2) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PRPF6 RNA expression–survival associations across cancer types. High PRPF6 expression shows unfavorable associations in LIHC, BLCA, KICH, ACC and MESO, but favorable associations in KIRC. 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 PRPF6 RNA expression.
This table summarizes PRPF6 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 8. The strongest signals are observed in COAD for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for PRPF6. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PRPF6 shows lower tumor expression in UCEC and higher tumor expression in STAD, COAD, LIHC, HNSC and KIRC. The STAD box plot shows higher PRPF6 RNA expression in tumor versus normal tissue (log2 FC = +1.206, t-test p < 0.001).
This table shows molecular features associated with PRPF6 in patient tissues and cancer cell lines. In patient samples, PRPF6 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, PRPF6 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and LARGE_INTESTINE.
