Q-omics provides the consensus-scored HMGCS2 profile across patient tissues and cancer cell-line models. HMGCS2 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, HMGCS2 is differentially expressed in 13, with the highest sampling consensus in COAD. Additionally, HMGCS2 RNA expression shows 12,937 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight KIRC, COAD, and TGCT as cancer lineages where HMGCS2 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 HMGCS2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes HMGCS2 survival associations across molecular data types. HMGCS2 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (6) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible HMGCS2 RNA expression–survival associations across cancer types. High HMGCS2 expression shows favorable associations in KIRC, OV, LIHC, BLCA, LGG and KICH. The KIRC 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 KIRC as the clearest survival context for HMGCS2 RNA expression.
This table summarizes HMGCS2 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 6. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for HMGCS2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. HMGCS2 shows lower tumor expression in COAD, HNSC, KIRP, KIRC, KICH and LUAD. The COAD box plot shows higher HMGCS2 RNA expression in normal versus tumor tissue (log2 FC = −3.740, t-test p < 0.001).
This table shows molecular features associated with HMGCS2 in patient tissues and cancer cell lines. In patient samples, HMGCS2 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, HMGCS2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in SKIN and LARGE_INTESTINE.
