Q-omics provides the consensus-scored PSMG3 profile across patient tissues and cancer cell-line models. PSMG3 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, PSMG3 is differentially expressed in 17, with the highest sampling consensus in BLCA. Additionally, PSMG3 protein abundance shows 22,412 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight UVM, BLCA, and PDAC as cancer lineages where PSMG3 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 PSMG3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PSMG3 survival associations across molecular data types. PSMG3 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (4) 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 PSMG3 RNA expression–survival associations across cancer types. High PSMG3 expression shows unfavorable associations in UVM, KIRC, ACC, LIHC, KICH and COAD. 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 PSMG3 RNA expression.
This table summarizes PSMG3 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 7. The strongest signals are observed in BLCA for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for PSMG3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PSMG3 shows higher tumor expression in BLCA, COAD, HNSC, LUAD, LIHC and STAD. The BLCA box plot shows higher PSMG3 RNA expression in tumor versus normal tissue (log2 FC = +1.803, t-test p < 0.001).
This table shows molecular features associated with PSMG3 in patient tissues and cancer cell lines. In patient samples, PSMG3 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, PSMG3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OESOPHAGUS, while CRISPR and shRNA rows add functional-dependency signals in STOMACH and CNS.
