proline rich and Gla domain 4Genealiases: PRGP4 · TMG4
Q-omics provides the consensus-scored PRRG4 profile across patient tissues and cancer cell-line models. PRRG4 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, PRRG4 is differentially expressed in 11, with the highest sampling consensus in KICH. Additionally, PRRG4 RNA expression shows 19,204 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight KIRC, KICH, and THYM as cancer lineages where PRRG4 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 PRRG4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PRRG4 survival associations across molecular data types. PRRG4 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (2) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PRRG4 RNA expression–survival associations across cancer types. High PRRG4 expression shows unfavorable associations in PAAD, but favorable associations in KIRC, SKCM, COAD, BRCA and LUSC. The KIRC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify KIRC as the clearest survival context for PRRG4 RNA expression.
This table summarizes PRRG4 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 5. The strongest signals are observed in KICH for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for PRRG4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PRRG4 shows lower tumor expression in KICH and READ and higher tumor expression in BRCA, HNSC, LUSC and STAD. The KICH box plot shows higher PRRG4 RNA expression in normal versus tumor tissue (log2 FC = −1.378, t-test p < 0.001).
This table shows molecular features associated with PRRG4 in patient tissues and cancer cell lines. In patient samples, PRRG4 shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, PRRG4 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and BLOOD_Lymphoma.
