Q-omics provides the consensus-scored PLCG2 profile across patient tissues and cancer cell-line models. PLCG2 expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, PLCG2 is differentially expressed in 14, with the highest sampling consensus in KIRC. Additionally, PLCG2 protein abundance shows 24,626 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight HNSC, KIRC, and GBM as cancer lineages where PLCG2 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 PLCG2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PLCG2 survival associations across molecular data types. PLCG2 RNA expression shows survival associations in the most cancer types (19), followed by mutation status (8) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PLCG2 RNA expression–survival associations across cancer types. High PLCG2 expression shows unfavorable associations in ACC, but favorable associations in HNSC, KIRC, SKCM, LUAD and CHOL. The HNSC 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 HNSC as the clearest survival context for PLCG2 RNA expression.
This table summarizes PLCG2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 4. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for PLCG2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PLCG2 shows lower tumor expression in KIRC, KIRP, COAD, LUSC and LUAD and higher tumor expression in HNSC. The KIRC box plot shows higher PLCG2 RNA expression in normal versus tumor tissue (log2 FC = −1.506, t-test p < 0.001).
This table shows molecular features associated with PLCG2 in patient tissues and cancer cell lines. In patient samples, PLCG2 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, PLCG2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and LARGE_INTESTINE.
