Q-omics provides the consensus-scored PRSS56 profile across patient tissues and cancer cell-line models. PRSS56 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in UCEC. Among the 18 cancer types available for tumor–normal comparison, PRSS56 is differentially expressed in 9, with the highest sampling consensus in KICH. Additionally, PRSS56 RNA expression shows 8,084 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight UCEC, KICH, and TGCT as cancer lineages where PRSS56 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 PRSS56 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PRSS56 survival associations across molecular data types. PRSS56 RNA expression shows survival associations in the most cancer types (21). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PRSS56 RNA expression–survival associations across cancer types. High PRSS56 expression shows unfavorable associations in SKCM, BLCA, DLBC, LIHC and MESO, but favorable associations in UCEC. The UCEC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .006). Together, the overview and detailed table identify UCEC as the clearest survival context for PRSS56 RNA expression.
This table summarizes PRSS56 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9, while mass-spec protein shows differences in 1. The strongest signals are observed in KICH for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for PRSS56. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PRSS56 shows lower tumor expression in KICH and higher tumor expression in UCEC, COAD, LIHC, LUSC and PAAD. The KICH box plot shows higher PRSS56 RNA expression in normal versus tumor tissue (log2 FC = −0.050, t-test p < 0.001).
This table shows molecular features associated with PRSS56 in patient tissues and cancer cell lines. In patient samples, PRSS56 shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, PRSS56 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LARGE_INTESTINE, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and URINARY_TRACT.
