Q-omics provides the consensus-scored PGA3 profile across patient tissues and cancer cell-line models. PGA3 expression is associated with patient survival in 16 of 34 cancer types, with the highest sampling consensus in LUSC. Among the 18 cancer types available for tumor–normal comparison, PGA3 is differentially expressed in 9, with the highest sampling consensus in THCA. Additionally, PGA3 RNA expression shows 5,970 significant pathway-activity associations, with the highest sampling consensus in KIRC. Together, these results highlight LUSC, THCA, and KIRC as cancer lineages where PGA3 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 PGA3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PGA3 survival associations across molecular data types. PGA3 RNA expression shows survival associations in the most cancer types (16), followed by mutation status (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PGA3 RNA expression–survival associations across cancer types. High PGA3 expression shows unfavorable associations in LUSC, LIHC, READ, ESCA, PAAD and THCA. The LUSC 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 LUSC as the clearest survival context for PGA3 RNA expression.
This table summarizes PGA3 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 THCA for RNA.
This table ranks reproducible tumor–normal expression differences for PGA3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PGA3 shows lower tumor expression in THCA, BRCA, STAD, LIHC and ESCA and higher tumor expression in KIRC. The THCA box plot shows higher PGA3 RNA expression in normal versus tumor tissue (log2 FC = −0.068, t-test p < 0.001).
This table shows molecular features associated with PGA3 in patient tissues and cancer cell lines. In patient samples, PGA3 shows the broadest associations at the RNA and protein expression levels, with KIRC recurring as the lineage with the largest associated feature set. In cancer cell lines, PGA3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in CNS and SOFT_TISSUE.
