Q-omics provides the consensus-scored KLHL17 profile across patient tissues and cancer cell-line models. KLHL17 expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, KLHL17 is differentially expressed in 16, with the highest sampling consensus in COAD. Additionally, KLHL17 RNA expression shows 18,768 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight ACC, COAD, and UVM as cancer lineages where KLHL17 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 KLHL17 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes KLHL17 survival associations across molecular data types. KLHL17 RNA expression shows survival associations in the most cancer types (19), followed by mutation status (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible KLHL17 RNA expression–survival associations across cancer types. High KLHL17 expression shows unfavorable associations in ACC, KIRC, LIHC, CESC and MESO, but favorable associations in HNSC. 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 KLHL17 RNA expression.
This table summarizes KLHL17 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for KLHL17. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. KLHL17 shows higher tumor expression in COAD, BLCA, HNSC, STAD, LIHC and THCA. The COAD box plot shows higher KLHL17 RNA expression in tumor versus normal tissue (log2 FC = +2.090, t-test p < 0.001).
This table shows molecular features associated with KLHL17 in patient tissues and cancer cell lines. In patient samples, KLHL17 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, KLHL17 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in URINARY_TRACT, while CRISPR and shRNA rows add functional-dependency signals in CNS and LARGE_INTESTINE.
