Q-omics provides the consensus-scored PSME2 profile across patient tissues and cancer cell-line models. PSME2 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, PSME2 is differentially expressed in 16, with the highest sampling consensus in KIRC. Additionally, PSME2 protein abundance shows 25,617 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight SKCM, KIRC, and PDAC as cancer lineages where PSME2 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 PSME2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PSME2 survival associations across molecular data types. PSME2 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (3) 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 PSME2 RNA expression–survival associations across cancer types. High PSME2 expression shows unfavorable associations in KIRC, KICH, ACC, UVM and UCS, but favorable associations in SKCM. The SKCM 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 SKCM as the clearest survival context for PSME2 RNA expression.
This table summarizes PSME2 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 7. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for PSME2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PSME2 shows higher tumor expression in KIRC, LIHC, KIRP, HNSC, STAD and BLCA. The KIRC box plot shows higher PSME2 RNA expression in tumor versus normal tissue (log2 FC = +0.698, t-test p < 0.001).
This table shows molecular features associated with PSME2 in patient tissues and cancer cell lines. In patient samples, PSME2 shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, PSME2 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 CNS and BLOOD_Leukemia.
