Q-omics provides the consensus-scored SIK2 profile across patient tissues and cancer cell-line models. SIK2 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, SIK2 is differentially expressed in 10, with the highest sampling consensus in THCA. Additionally, SIK2 RNA expression shows 21,130 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight KIRC, THCA, and THYM as cancer lineages where SIK2 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 SIK2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SIK2 survival associations across molecular data types. SIK2 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (4) 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 SIK2 RNA expression–survival associations across cancer types. High SIK2 expression shows unfavorable associations in BLCA and ACC, but favorable associations in KIRC, UCS, UCEC and LIHC. 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 SIK2 RNA expression.
This table summarizes SIK2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 4. The strongest signals are observed in THCA for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for SIK2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SIK2 shows lower tumor expression in THCA, LUAD, LUSC, BLCA, BRCA and KIRP. The THCA box plot shows higher SIK2 RNA expression in normal versus tumor tissue (log2 FC = −0.878, t-test p < 0.001).
This table shows molecular features associated with SIK2 in patient tissues and cancer cell lines. In patient samples, SIK2 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, SIK2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Lymphoma, while CRISPR and shRNA rows add functional-dependency signals in KIDNEY and BLOOD_Leukemia.
