Q-omics provides the consensus-scored SKP1 profile across patient tissues and cancer cell-line models. SKP1 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, SKP1 is differentially expressed in 11, with the highest sampling consensus in LIHC. Additionally, SKP1 protein abundance shows 26,608 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight HNSC, LIHC, and GBM as cancer lineages where SKP1 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 SKP1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SKP1 survival associations across molecular data types. SKP1 RNA expression shows survival associations in the most cancer types (24), 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 SKP1 RNA expression–survival associations across cancer types. High SKP1 expression shows unfavorable associations in HNSC, SCLC and STAD, but favorable associations in KIRC, MESO and COAD. The HNSC 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 HNSC as the clearest survival context for SKP1 RNA expression.
This table summarizes SKP1 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 LIHC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for SKP1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SKP1 shows lower tumor expression in KICH, THCA, UCEC, BLCA and LUSC and higher tumor expression in LIHC. The LIHC box plot shows higher SKP1 RNA expression in tumor versus normal tissue (log2 FC = +1.105, t-test p < 0.001).
This table shows molecular features associated with SKP1 in patient tissues and cancer cell lines. In patient samples, SKP1 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, SKP1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and BLOOD_Leukemia.
