Q-omics provides the consensus-scored SKI profile across patient tissues and cancer cell-line models. SKI expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, SKI is differentially expressed in 14, with the highest sampling consensus in KIRC. Additionally, SKI RNA expression shows 19,788 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight KIRC, and THYM as cancer lineages where SKI 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 SKI — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SKI survival associations across molecular data types. SKI RNA expression shows survival associations in the most cancer types (25), followed by mutation status (5) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SKI RNA expression–survival associations across cancer types. High SKI expression shows unfavorable associations in ACC, BLCA, LGG and CESC, but favorable associations in KIRC and UCS. 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 SKI RNA expression.
This table summarizes SKI tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 3. The strongest signals are observed in KIRC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for SKI. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SKI shows lower tumor expression in KICH, THCA, UCEC and LUAD and higher tumor expression in KIRC and STAD. The KIRC box plot shows higher SKI RNA expression in tumor versus normal tissue (log2 FC = +0.840, t-test p < 0.001).
This table shows molecular features associated with SKI in patient tissues and cancer cell lines. In patient samples, SKI shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, SKI RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in BREAST and LARGE_INTESTINE.
