Q-omics provides the consensus-scored PSMG4 profile across patient tissues and cancer cell-line models. PSMG4 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, PSMG4 is differentially expressed in 14, with the highest sampling consensus in COAD. Additionally, PSMG4 RNA expression shows 18,097 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and COAD as cancer lineages where PSMG4 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 PSMG4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PSMG4 survival associations across molecular data types. PSMG4 RNA expression shows survival associations in the most cancer types (21), followed by mutation status (1) 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 PSMG4 RNA expression–survival associations across cancer types. High PSMG4 expression shows unfavorable associations in ACC, KIRC, LIHC and KIRP, but favorable associations in READ and LUSC. The ACC 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 ACC as the clearest survival context for PSMG4 RNA expression.
This table summarizes PSMG4 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 5. The strongest signals are observed in COAD for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for PSMG4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PSMG4 shows lower tumor expression in THCA and higher tumor expression in COAD, LIHC, KIRC, STAD and HNSC. The COAD box plot shows higher PSMG4 RNA expression in tumor versus normal tissue (log2 FC = +1.292, t-test p < 0.001).
This table shows molecular features associated with PSMG4 in patient tissues and cancer cell lines. In patient samples, PSMG4 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, PSMG4 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in LIVER and SOFT_TISSUE.
