Q-omics provides the consensus-scored KLHL5 profile across patient tissues and cancer cell-line models. KLHL5 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, KLHL5 is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, KLHL5 RNA expression shows 20,765 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and HNSC as cancer lineages where KLHL5 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 KLHL5 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes KLHL5 survival associations across molecular data types. KLHL5 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (5) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible KLHL5 RNA expression–survival associations across cancer types. High KLHL5 expression shows unfavorable associations in ACC, MESO, KIRP and SCLC, but favorable associations in KIRC and SKCM. 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 KLHL5 RNA expression.
This table summarizes KLHL5 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 4. The strongest signals are observed in HNSC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for KLHL5. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. KLHL5 shows lower tumor expression in KICH and KIRP and higher tumor expression in HNSC, LIHC, LUAD and LUSC. The HNSC box plot shows higher KLHL5 RNA expression in tumor versus normal tissue (log2 FC = +1.873, t-test p < 0.001).
This table shows molecular features associated with KLHL5 in patient tissues and cancer cell lines. In patient samples, KLHL5 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, KLHL5 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in OESOPHAGUS and BLOOD_Lymphoma.
