Q-omics provides the consensus-scored STK16 profile across patient tissues and cancer cell-line models. STK16 expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, STK16 is differentially expressed in 10, with the highest sampling consensus in KICH. Additionally, STK16 RNA expression shows 19,132 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight UVM, KICH, and ACC as cancer lineages where STK16 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 STK16 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes STK16 survival associations across molecular data types. STK16 RNA expression shows survival associations in the most cancer types (20), 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 STK16 RNA expression–survival associations across cancer types. High STK16 expression shows unfavorable associations in UVM, ACC and LAML, but favorable associations in MESO, UCEC and KIRC. The UVM 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 UVM as the clearest survival context for STK16 RNA expression.
This table summarizes STK16 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 LIHC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for STK16. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. STK16 shows lower tumor expression in KICH and THCA and higher tumor expression in KIRC, LIHC, BRCA and CHOL. The KICH box plot shows higher STK16 RNA expression in normal versus tumor tissue (log2 FC = −1.185, t-test p < 0.001).
This table shows molecular features associated with STK16 in patient tissues and cancer cell lines. In patient samples, STK16 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, STK16 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in LUNG_SCLC and UPPER_AERODIGESTIVE_TRACT.
