Q-omics provides the consensus-scored KLHL30 profile across patient tissues and cancer cell-line models. KLHL30 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, KLHL30 is differentially expressed in 13, with the highest sampling consensus in BLCA. Additionally, KLHL30 RNA expression shows 15,653 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight UVM, BLCA, and TGCT as cancer lineages where KLHL30 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 KLHL30 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes KLHL30 survival associations across molecular data types. KLHL30 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible KLHL30 RNA expression–survival associations across cancer types. High KLHL30 expression shows unfavorable associations in UVM, STAD, LUSC, READ and PAAD, but favorable associations in DLBC. The UVM 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 UVM as the clearest survival context for KLHL30 RNA expression.
This table summarizes KLHL30 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for KLHL30. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. KLHL30 shows lower tumor expression in BLCA, KIRC, BRCA, KICH and LUSC and higher tumor expression in THCA. The BLCA box plot shows higher KLHL30 RNA expression in normal versus tumor tissue (log2 FC = −2.084, t-test p < 0.001).
This table shows molecular features associated with KLHL30 in patient tissues and cancer cell lines. In patient samples, KLHL30 shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, KLHL30 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in SKIN and SOFT_TISSUE.
