Q-omics provides the consensus-scored PACRGL profile across patient tissues and cancer cell-line models. PACRGL expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in UCS. Among the 18 cancer types available for tumor–normal comparison, PACRGL is differentially expressed in 10, with the highest sampling consensus in THCA. Additionally, PACRGL RNA expression shows 20,467 significant gene co-expression associations, with the highest sampling consensus in KIRP. Together, these results highlight UCS, THCA, and KIRP as cancer lineages where PACRGL 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 PACRGL — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PACRGL survival associations across molecular data types. PACRGL RNA expression shows survival associations in the most cancer types (25), followed by mutation status (2) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PACRGL RNA expression–survival associations across cancer types. High PACRGL expression shows unfavorable associations in THCA and KICH, but favorable associations in UCS, STAD, BLCA and BRCA. The UCS Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .001). Together, the overview and detailed table identify UCS as the clearest survival context for PACRGL RNA expression.
This table summarizes PACRGL tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10. The strongest signals are observed in THCA for RNA.
This table ranks reproducible tumor–normal expression differences for PACRGL. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PACRGL shows lower tumor expression in THCA and KICH and higher tumor expression in LIHC, CHOL, COAD and LUAD. The THCA box plot shows higher PACRGL RNA expression in normal versus tumor tissue (log2 FC = −0.522, t-test p < 0.001).
This table shows molecular features associated with PACRGL in patient tissues and cancer cell lines. In patient samples, PACRGL shows the broadest associations at the RNA and protein expression levels, with KIRP recurring as the lineage with the largest associated feature set. In cancer cell lines, PACRGL RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and LARGE_INTESTINE.
