SUMO specific peptidase 6Genealiases: SSP1 · SUSP1
Q-omics provides the consensus-scored SENP6 profile across patient tissues and cancer cell-line models. SENP6 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, SENP6 is differentially expressed in 11, with the highest sampling consensus in HNSC. Additionally, SENP6 RNA expression shows 21,461 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight SKCM, HNSC, and ACC as cancer lineages where SENP6 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 SENP6 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SENP6 survival associations across molecular data types. SENP6 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (6) 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 SENP6 RNA expression–survival associations across cancer types. High SENP6 expression shows unfavorable associations in LIHC and ACC, but favorable associations in SKCM, UCS, CHOL and THYM. The SKCM Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .002). Together, the overview and detailed table identify SKCM as the clearest survival context for SENP6 RNA expression.
This table summarizes SENP6 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 4. The strongest signals are observed in HNSC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for SENP6. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SENP6 shows lower tumor expression in THCA, KICH and UCEC and higher tumor expression in HNSC, LIHC and CHOL. The HNSC box plot shows higher SENP6 RNA expression in tumor versus normal tissue (log2 FC = +0.622, t-test p < 0.001).
This table shows molecular features associated with SENP6 in patient tissues and cancer cell lines. In patient samples, SENP6 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, SENP6 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUSC and LARGE_INTESTINE.
