Q-omics provides the consensus-scored STK3 profile across patient tissues and cancer cell-line models. STK3 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, STK3 is differentially expressed in 15, with the highest sampling consensus in HNSC. Additionally, STK3 protein abundance shows 26,777 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRP, HNSC, and GBM as cancer lineages where STK3 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 STK3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes STK3 survival associations across molecular data types. STK3 RNA expression shows survival associations in the most cancer types (23), followed by mass-spec protein abundance (10). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible STK3 RNA expression–survival associations across cancer types. High STK3 expression shows unfavorable associations in KIRP, UVM, LGG, PAAD, HNSC and LUSC. The KIRP 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 KIRP as the clearest survival context for STK3 RNA expression.
This table summarizes STK3 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 8. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for STK3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. STK3 shows higher tumor expression in HNSC, COAD, STAD, LIHC, LUSC and LUAD. The HNSC box plot shows higher STK3 RNA expression in tumor versus normal tissue (log2 FC = +1.475, t-test p < 0.001).
This table shows molecular features associated with STK3 in patient tissues and cancer cell lines. In patient samples, STK3 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, STK3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LARGE_INTESTINE, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and BLOOD_Lymphoma.
