Q-omics provides the consensus-scored PGS1 profile across patient tissues and cancer cell-line models. PGS1 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, PGS1 is differentially expressed in 15, with the highest sampling consensus in HNSC. Additionally, PGS1 RNA expression shows 20,176 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, HNSC, and ACC as cancer lineages where PGS1 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 PGS1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PGS1 survival associations across molecular data types. PGS1 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (4) 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 PGS1 RNA expression–survival associations across cancer types. High PGS1 expression shows unfavorable associations in KIRC, ACC, LIHC and LGG, but favorable associations in LUAD and HNSC. The KIRC 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 KIRC as the clearest survival context for PGS1 RNA expression.
This table summarizes PGS1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 3. The strongest signals are observed in HNSC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for PGS1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PGS1 shows higher tumor expression in HNSC, BLCA, KIRP, KIRC, COAD and LIHC. The HNSC box plot shows higher PGS1 RNA expression in tumor versus normal tissue (log2 FC = +1.021, t-test p < 0.001).
This table shows molecular features associated with PGS1 in patient tissues and cancer cell lines. In patient samples, PGS1 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, PGS1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and BLOOD_Leukemia.
