Q-omics provides the consensus-scored BPGM profile across patient tissues and cancer cell-line models. BPGM expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, BPGM is differentially expressed in 11, with the highest sampling consensus in HNSC. Additionally, BPGM protein abundance shows 20,899 significant protein co-abundance associations, with the highest sampling consensus in CCRCC. Together, these results highlight KIRC, HNSC, and CCRCC as cancer lineages where BPGM 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 BPGM — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes BPGM survival associations across molecular data types. BPGM RNA expression shows survival associations in the most cancer types (20), followed by mutation status (3) 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 BPGM RNA expression–survival associations across cancer types. High BPGM expression shows unfavorable associations in UVM, LIHC, KIRP and LGG, but favorable associations in KIRC and CESC. 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 BPGM RNA expression.
This table summarizes BPGM tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 7. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for BPGM. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. BPGM shows lower tumor expression in KIRC and higher tumor expression in HNSC, LIHC, BLCA, BRCA and CHOL. The HNSC box plot shows higher BPGM RNA expression in tumor versus normal tissue (log2 FC = +1.711, t-test p < 0.001).
This table shows molecular features associated with BPGM in patient tissues and cancer cell lines. In patient samples, BPGM shows the broadest associations at the RNA and protein expression levels, with CCRCC recurring as the lineage with the largest associated feature set. In cancer cell lines, BPGM RNA and mutation anchors are most strongly linked to RNA-expression features, especially in KIDNEY, while CRISPR and shRNA rows add functional-dependency signals in SKIN and BLOOD_Leukemia.
