Q-omics provides the consensus-scored SKIV2L profile across patient tissues and cancer cell-line models. SKIV2L expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in COAD. Among the 18 cancer types available for tumor–normal comparison, SKIV2L is differentially expressed in 15, with the highest sampling consensus in HNSC. Additionally, SKIV2L RNA expression shows 18,706 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight COAD, HNSC, and ACC as cancer lineages where SKIV2L 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 SKIV2L — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SKIV2L survival associations across molecular data types. SKIV2L RNA expression shows survival associations in the most cancer types (26), followed by mutation status (6) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SKIV2L RNA expression–survival associations across cancer types. High SKIV2L expression shows unfavorable associations in COAD, KIRC, UVM, LIHC and LGG, but favorable associations in THYM. The COAD Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify COAD as the clearest survival context for SKIV2L RNA expression.
This table summarizes SKIV2L tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 5. The strongest signals are observed in HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for SKIV2L. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SKIV2L shows higher tumor expression in HNSC, COAD, LIHC, LUAD, KIRP and BLCA. The HNSC box plot shows higher SKIV2L RNA expression in tumor versus normal tissue (log2 FC = +0.853, t-test p < 0.001).
This table shows molecular features associated with SKIV2L in patient tissues and cancer cell lines. In patient samples, SKIV2L 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, SKIV2L RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and BLOOD_Leukemia.
