Q-omics provides the consensus-scored PLCL2 profile across patient tissues and cancer cell-line models. PLCL2 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, PLCL2 is differentially expressed in 12, with the highest sampling consensus in COAD. Additionally, PLCL2 protein abundance shows 30,734 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight KIRC, COAD, and LSCC as cancer lineages where PLCL2 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 PLCL2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PLCL2 survival associations across molecular data types. PLCL2 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (4) 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 PLCL2 RNA expression–survival associations across cancer types. High PLCL2 expression shows unfavorable associations in UVM and ACC, but favorable associations in KIRC, HNSC, SKCM and LUAD. 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 PLCL2 RNA expression.
This table summarizes PLCL2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 5. The strongest signals are observed in COAD for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for PLCL2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PLCL2 shows lower tumor expression in COAD, KIRP, THCA, KIRC, LUSC and UCEC. The COAD box plot shows higher PLCL2 RNA expression in normal versus tumor tissue (log2 FC = −2.417, t-test p < 0.001).
This table shows molecular features associated with PLCL2 in patient tissues and cancer cell lines. In patient samples, PLCL2 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, PLCL2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OESOPHAGUS, while CRISPR and shRNA rows add functional-dependency signals in BONE and BLOOD_Leukemia.
