Q-omics provides the consensus-scored PSME3 profile across patient tissues and cancer cell-line models. PSME3 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, PSME3 is differentially expressed in 17, with the highest sampling consensus in HNSC. Additionally, PSME3 protein abundance shows 34,003 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight UVM, HNSC, and LSCC as cancer lineages where PSME3 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 PSME3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PSME3 survival associations across molecular data types. PSME3 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (4) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PSME3 RNA expression–survival associations across cancer types. High PSME3 expression shows unfavorable associations in UVM, LIHC, LUAD, ACC, MESO and KICH. 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 PSME3 RNA expression.
This table summarizes PSME3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 17, while mass-spec protein shows differences in 10. The strongest signals are observed in HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for PSME3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PSME3 shows higher tumor expression in HNSC, COAD, LUAD, LIHC, STAD and BLCA. The HNSC box plot shows higher PSME3 RNA expression in tumor versus normal tissue (log2 FC = +0.912, t-test p < 0.001).
This table shows molecular features associated with PSME3 in patient tissues and cancer cell lines. In patient samples, PSME3 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, PSME3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in BREAST and UPPER_AERODIGESTIVE_TRACT.
