Q-omics provides the consensus-scored BHMT2 profile across patient tissues and cancer cell-line models. BHMT2 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, BHMT2 is differentially expressed in 15, with the highest sampling consensus in KICH. Additionally, BHMT2 RNA expression shows 18,109 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight KIRC, KICH, and PDAC as cancer lineages where BHMT2 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 BHMT2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes BHMT2 survival associations across molecular data types. BHMT2 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (4) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible BHMT2 RNA expression–survival associations across cancer types. High BHMT2 expression shows unfavorable associations in BLCA, but favorable associations in KIRC, ACC, HNSC, THCA and SARC. 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 BHMT2 RNA expression.
This table summarizes BHMT2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 2. The strongest signals are observed in BLCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for BHMT2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. BHMT2 shows lower tumor expression in KICH, BLCA, COAD, THCA, KIRP and HNSC. The KICH box plot shows higher BHMT2 RNA expression in normal versus tumor tissue (log2 FC = −6.500, t-test p < 0.001).
This table shows molecular features associated with BHMT2 in patient tissues and cancer cell lines. In patient samples, BHMT2 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, BHMT2 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 LUNG_NSCLC_LUAD and BLOOD_Leukemia.
