3-hydroxy-3-methylglutaryl-CoA lyase like 1Genealiases: ERCHL · bA418P12.1 · er-cHL
Q-omics provides the consensus-scored HMGCLL1 profile across patient tissues and cancer cell-line models. HMGCLL1 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, HMGCLL1 is differentially expressed in 16, with the highest sampling consensus in KIRC. Additionally, HMGCLL1 RNA expression shows 21,002 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight ACC, KIRC, and GBM as cancer lineages where HMGCLL1 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 HMGCLL1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes HMGCLL1 survival associations across molecular data types. HMGCLL1 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible HMGCLL1 RNA expression–survival associations across cancer types. High HMGCLL1 expression shows favorable associations in ACC, KIRC, LUAD, COAD, LGG and BRCA. The ACC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .001). Together, the overview and detailed table identify ACC as the clearest survival context for HMGCLL1 RNA expression.
This table summarizes HMGCLL1 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 KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for HMGCLL1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. HMGCLL1 shows lower tumor expression in KIRC, LUAD, COAD, BLCA, KICH and LUSC. The KIRC box plot shows higher HMGCLL1 RNA expression in normal versus tumor tissue (log2 FC = −0.374, t-test p < 0.001).
This table shows molecular features associated with HMGCLL1 in patient tissues and cancer cell lines. In patient samples, HMGCLL1 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, HMGCLL1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in BONE and LARGE_INTESTINE.
