Q-omics provides the consensus-scored PLCB2 profile across patient tissues and cancer cell-line models. PLCB2 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, PLCB2 is differentially expressed in 11, with the highest sampling consensus in KIRC. Additionally, PLCB2 protein abundance shows 26,588 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight HNSC, KIRC, and LSCC as cancer lineages where PLCB2 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 PLCB2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PLCB2 survival associations across molecular data types. PLCB2 RNA expression shows survival associations in the most cancer types (21), followed by mutation status (7) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PLCB2 RNA expression–survival associations across cancer types. High PLCB2 expression shows unfavorable associations in KIRC, LGG and LAML, but favorable associations in HNSC, CESC and SKCM. 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 PLCB2 RNA expression.
This table summarizes PLCB2 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 KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for PLCB2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PLCB2 shows lower tumor expression in LUSC and LUAD and higher tumor expression in KIRC, KIRP, STAD and THCA. The KIRC box plot shows higher PLCB2 RNA expression in tumor versus normal tissue (log2 FC = +1.887, t-test p < 0.001).
This table shows molecular features associated with PLCB2 in patient tissues and cancer cell lines. In patient samples, PLCB2 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, PLCB2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUAD and BLOOD_Leukemia.
