Q-omics provides the consensus-scored KLHL29 profile across patient tissues and cancer cell-line models. KLHL29 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in COAD. Among the 18 cancer types available for tumor–normal comparison, KLHL29 is differentially expressed in 13, with the highest sampling consensus in COAD. Additionally, KLHL29 RNA expression shows 18,993 significant gene co-expression associations, with the highest sampling consensus in KIRP. Together, these results highlight COAD, and KIRP as cancer lineages where KLHL29 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 KLHL29 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes KLHL29 survival associations across molecular data types. KLHL29 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (6) 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 KLHL29 RNA expression–survival associations across cancer types. High KLHL29 expression shows unfavorable associations in LGG, KIRP, MESO and LIHC, but favorable associations in COAD and UCS. The COAD Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify COAD as the clearest survival context for KLHL29 RNA expression.
This table summarizes KLHL29 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 2. The strongest signals are observed in COAD for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for KLHL29. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. KLHL29 shows lower tumor expression in KICH and LUAD and higher tumor expression in COAD, KIRP, KIRC and LIHC. The COAD box plot shows higher KLHL29 RNA expression in tumor versus normal tissue (log2 FC = +1.161, t-test p < 0.001).
This table shows molecular features associated with KLHL29 in patient tissues and cancer cell lines. In patient samples, KLHL29 shows the broadest associations at the RNA and protein expression levels, with KIRP recurring as the lineage with the largest associated feature set. In cancer cell lines, KLHL29 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in OVARY and SOFT_TISSUE.
