Q-omics provides the consensus-scored EXOSC4 profile across patient tissues and cancer cell-line models. EXOSC4 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, EXOSC4 is differentially expressed in 16, with the highest sampling consensus in HNSC. Additionally, EXOSC4 protein abundance shows 19,261 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight UVM, HNSC, and GBM as cancer lineages where EXOSC4 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 EXOSC4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EXOSC4 survival associations across molecular data types. EXOSC4 RNA expression shows survival associations in the most cancer types (25), 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 EXOSC4 RNA expression–survival associations across cancer types. High EXOSC4 expression shows unfavorable associations in UVM, LIHC, ACC, HNSC, CESC and KIRP. The UVM 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 UVM as the clearest survival context for EXOSC4 RNA expression.
This table summarizes EXOSC4 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 6. The strongest signals are observed in HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for EXOSC4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EXOSC4 shows higher tumor expression in HNSC, COAD, BLCA, STAD, LIHC and LUSC. The HNSC box plot shows higher EXOSC4 RNA expression in tumor versus normal tissue (log2 FC = +1.176, t-test p < 0.001).
This table shows molecular features associated with EXOSC4 in patient tissues and cancer cell lines. In patient samples, EXOSC4 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, EXOSC4 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 BREAST and BLOOD_Lymphoma.
