Q-omics provides the consensus-scored PRPF8 profile across patient tissues and cancer cell-line models. PRPF8 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, PRPF8 is differentially expressed in 11, with the highest sampling consensus in HNSC. Additionally, PRPF8 protein abundance shows 32,454 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, HNSC, and GBM as cancer lineages where PRPF8 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 PRPF8 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PRPF8 survival associations across molecular data types. PRPF8 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (7) 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 PRPF8 RNA expression–survival associations across cancer types. High PRPF8 expression shows unfavorable associations in KICH and MESO, but favorable associations in KIRC, SCLC, UCEC and READ. The KIRC 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 KIRC as the clearest survival context for PRPF8 RNA expression.
This table summarizes PRPF8 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 7. The strongest signals are observed in HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for PRPF8. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PRPF8 shows lower tumor expression in THCA and BRCA and higher tumor expression in HNSC, LIHC, CHOL and KIRP. The HNSC box plot shows higher PRPF8 RNA expression in tumor versus normal tissue (log2 FC = +0.597, t-test p < 0.001).
This table shows molecular features associated with PRPF8 in patient tissues and cancer cell lines. In patient samples, PRPF8 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, PRPF8 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LARGE_INTESTINE, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and SKIN.
