Q-omics provides the consensus-scored HMGCL profile across patient tissues and cancer cell-line models. HMGCL expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, HMGCL is differentially expressed in 13, with the highest sampling consensus in COAD. Additionally, HMGCL protein abundance shows 20,660 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight KIRP, COAD, and PDAC as cancer lineages where HMGCL 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 HMGCL — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes HMGCL survival associations across molecular data types. HMGCL RNA expression shows survival associations in the most cancer types (22), followed by mutation status (4) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible HMGCL RNA expression–survival associations across cancer types. High HMGCL expression shows unfavorable associations in UCS and LGG, but favorable associations in KIRP, COAD, BRCA and KIRC. The KIRP 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 KIRP as the clearest survival context for HMGCL RNA expression.
This table summarizes HMGCL 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 7. The strongest signals are observed in COAD for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for HMGCL. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. HMGCL shows lower tumor expression in COAD, KICH, KIRP, KIRC, LIHC and LUSC. The COAD box plot shows higher HMGCL RNA expression in normal versus tumor tissue (log2 FC = −0.938, t-test p < 0.001).
This table shows molecular features associated with HMGCL in patient tissues and cancer cell lines. In patient samples, HMGCL shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, HMGCL RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and PANCREAS.
