Q-omics provides the consensus-scored SGK1 profile across patient tissues and cancer cell-line models. SGK1 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, SGK1 is differentially expressed in 11, with the highest sampling consensus in KICH. Additionally, SGK1 RNA expression shows 17,234 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight KIRC, KICH, and THYM as cancer lineages where SGK1 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 SGK1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SGK1 survival associations across molecular data types. SGK1 RNA expression shows survival associations in the most cancer types (21), followed by mutation status (11) 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 SGK1 RNA expression–survival associations across cancer types. High SGK1 expression shows unfavorable associations in UVM and OV, but favorable associations in KIRC, CESC, LUSC and SCLC. 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 SGK1 RNA expression.
This table summarizes SGK1 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 3. The strongest signals are observed in KICH for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for SGK1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SGK1 shows lower tumor expression in KICH, COAD, THCA, BLCA, LUAD and UCEC. The KICH box plot shows higher SGK1 RNA expression in normal versus tumor tissue (log2 FC = −3.420, t-test p < 0.001).
This table shows molecular features associated with SGK1 in patient tissues and cancer cell lines. In patient samples, SGK1 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, SGK1 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 LARGE_INTESTINE and BREAST.
