Q-omics provides the consensus-scored STK19 profile across patient tissues and cancer cell-line models. STK19 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, STK19 is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, STK19 RNA expression shows 19,106 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and KIRC as cancer lineages where STK19 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 STK19 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes STK19 survival associations across molecular data types. STK19 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (2) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible STK19 RNA expression–survival associations across cancer types. High STK19 expression shows unfavorable associations in ACC, COAD and LGG, but favorable associations in READ, UVM and THYM. The ACC 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 ACC as the clearest survival context for STK19 RNA expression.
This table summarizes STK19 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 3. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for STK19. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. STK19 shows lower tumor expression in KICH and higher tumor expression in KIRC, LIHC, COAD, BLCA and BRCA. The KIRC box plot shows higher STK19 RNA expression in tumor versus normal tissue (log2 FC = +0.631, t-test p < 0.001).
This table shows molecular features associated with STK19 in patient tissues and cancer cell lines. In patient samples, STK19 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, STK19 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Myeloma and BLOOD_Leukemia.
