Q-omics provides the consensus-scored PSME2P3 profile across patient tissues and cancer cell-line models. PSME2P3 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in READ. Among the 18 cancer types available for tumor–normal comparison, PSME2P3 is differentially expressed in 9, with the highest sampling consensus in LIHC. Additionally, PSME2P3 RNA expression shows 8,525 significant protein co-abundance associations, with the highest sampling consensus in BRCA. Together, these results highlight READ, LIHC, and BRCA as cancer lineages where PSME2P3 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 PSME2P3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PSME2P3 survival associations across molecular data types. PSME2P3 RNA expression shows survival associations in the most cancer types (22). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PSME2P3 RNA expression–survival associations across cancer types. High PSME2P3 expression shows unfavorable associations in ACC, UVM, UCS, THCA and LGG, but favorable associations in READ. The READ Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .001). Together, the overview and detailed table identify READ as the clearest survival context for PSME2P3 RNA expression.
This table summarizes PSME2P3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9. The strongest signals are observed in LIHC for RNA.
This table ranks reproducible tumor–normal expression differences for PSME2P3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PSME2P3 shows higher tumor expression in LIHC, COAD, BRCA, STAD, HNSC and ESCA. The LIHC box plot shows higher PSME2P3 RNA expression in tumor versus normal tissue (log2 FC = +0.437, t-test p < 0.001).
This table shows molecular features associated with PSME2P3 in patient tissues and cancer cell lines. In patient samples, PSME2P3 shows the broadest associations at the RNA and protein expression levels, with BRCA recurring as the lineage with the largest associated feature set.
