Q-omics provides the consensus-scored KLF16 profile across patient tissues and cancer cell-line models. KLF16 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, KLF16 is differentially expressed in 15, with the highest sampling consensus in KIRC. Additionally, KLF16 protein abundance shows 19,162 significant protein co-abundance associations, with the highest sampling consensus in HNSC. Together, these results highlight ACC, KIRC, and HNSC as cancer lineages where KLF16 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 KLF16 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes KLF16 survival associations across molecular data types. KLF16 RNA expression shows survival associations in the most cancer types (23), 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 KLF16 RNA expression–survival associations across cancer types. High KLF16 expression shows unfavorable associations in ACC, MESO, KIRC, LUAD, BRCA and LGG. 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 KLF16 RNA expression.
This table summarizes KLF16 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 6. The strongest signals are observed in KIRC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for KLF16. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. KLF16 shows higher tumor expression in KIRC, COAD, STAD, THCA, HNSC and LUSC. The KIRC box plot shows higher KLF16 RNA expression in tumor versus normal tissue (log2 FC = +0.749, t-test p < 0.001).
This table shows molecular features associated with KLF16 in patient tissues and cancer cell lines. In patient samples, KLF16 shows the broadest associations at the RNA and protein expression levels, with HNSC recurring as the lineage with the largest associated feature set. In cancer cell lines, KLF16 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 BLOOD_Myeloma and BLOOD_Lymphoma.
