Q-omics provides the consensus-scored PRKG2 profile across patient tissues and cancer cell-line models. PRKG2 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in LGG. Among the 18 cancer types available for tumor–normal comparison, PRKG2 is differentially expressed in 13, with the highest sampling consensus in COAD. Additionally, PRKG2 RNA expression shows 16,729 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight LGG, COAD, and TGCT as cancer lineages where PRKG2 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 PRKG2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PRKG2 survival associations across molecular data types. PRKG2 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (9) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PRKG2 RNA expression–survival associations across cancer types. High PRKG2 expression shows unfavorable associations in CESC, HNSC, BRCA and UCEC, but favorable associations in LGG and KIRC. The LGG 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 LGG as the clearest survival context for PRKG2 RNA expression.
This table summarizes PRKG2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, 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 PRKG2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PRKG2 shows lower tumor expression in COAD, LUAD, KICH, LUSC and THCA and higher tumor expression in HNSC. The COAD box plot shows higher PRKG2 RNA expression in normal versus tumor tissue (log2 FC = −2.892, t-test p < 0.001).
This table shows molecular features associated with PRKG2 in patient tissues and cancer cell lines. In patient samples, PRKG2 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, PRKG2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and BLOOD_Leukemia.
