Q-omics provides the consensus-scored PSMC3IP profile across patient tissues and cancer cell-line models. PSMC3IP expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, PSMC3IP is differentially expressed in 16, with the highest sampling consensus in HNSC. Additionally, PSMC3IP RNA expression shows 20,983 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight ACC, HNSC, and LSCC as cancer lineages where PSMC3IP 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 PSMC3IP — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PSMC3IP survival associations across molecular data types. PSMC3IP RNA expression shows survival associations in the most cancer types (26), followed by mutation status (1) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PSMC3IP RNA expression–survival associations across cancer types. High PSMC3IP expression shows unfavorable associations in ACC, MESO, KICH, LIHC, KIRC and LGG. 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 PSMC3IP RNA expression.
This table summarizes PSMC3IP 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 5. The strongest signals are observed in HNSC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for PSMC3IP. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PSMC3IP shows higher tumor expression in HNSC, KIRP, COAD, BLCA, LIHC and LUSC. The HNSC box plot shows higher PSMC3IP RNA expression in tumor versus normal tissue (log2 FC = +1.405, t-test p < 0.001).
This table shows molecular features associated with PSMC3IP in patient tissues and cancer cell lines. In patient samples, PSMC3IP 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, PSMC3IP RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and LARGE_INTESTINE.
