Q-omics provides the consensus-scored CTSE profile across patient tissues and cancer cell-line models. CTSE expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, CTSE is differentially expressed in 8, with the highest sampling consensus in KICH. Additionally, CTSE RNA expression shows 13,706 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight KIRC, KICH, and TGCT as cancer lineages where CTSE 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 CTSE — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CTSE survival associations across molecular data types. CTSE RNA expression shows survival associations in the most cancer types (27), 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 CTSE RNA expression–survival associations across cancer types. High CTSE expression shows unfavorable associations in KIRP, LUSC and UVM, but favorable associations in KIRC, BLCA and UCEC. 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 CTSE RNA expression.
This table summarizes CTSE tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8, while mass-spec protein shows differences in 5. The strongest signals are observed in KICH for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for CTSE. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CTSE shows lower tumor expression in KICH, LUSC and PRAD and higher tumor expression in KIRC, HNSC and CHOL. The KICH box plot shows higher CTSE RNA expression in normal versus tumor tissue (log2 FC = −0.466, t-test p < 0.001).
This table shows molecular features associated with CTSE in patient tissues and cancer cell lines. In patient samples, CTSE 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, CTSE RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in BREAST and SKIN.
