Q-omics provides the consensus-scored CLC profile across patient tissues and cancer cell-line models. CLC expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in CESC. Among the 18 cancer types available for tumor–normal comparison, CLC is differentially expressed in 7, with the highest sampling consensus in LUSC. Additionally, CLC protein abundance shows 17,962 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight CESC, LUSC, and GBM as cancer lineages where CLC 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 CLC — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CLC survival associations across molecular data types. CLC RNA expression shows survival associations in the most cancer types (19), followed by mutation status (3) 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 CLC RNA expression–survival associations across cancer types. High CLC expression shows unfavorable associations in MESO, THYM and OV, but favorable associations in CESC, SKCM and KIRC. The CESC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .001). Together, the overview and detailed table identify CESC as the clearest survival context for CLC RNA expression.
This table summarizes CLC tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 7, while mass-spec protein shows differences in 5. The strongest signals are observed in LUSC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for CLC. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CLC shows lower tumor expression in LUSC, BRCA, LUAD, LIHC and PRAD and higher tumor expression in HNSC. The LUSC box plot shows higher CLC RNA expression in normal versus tumor tissue (log2 FC = −0.954, t-test p < 0.001).
This table shows molecular features associated with CLC in patient tissues and cancer cell lines. In patient samples, CLC 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, CLC RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Myeloma and BLOOD_Leukemia.
