Q-omics provides the consensus-scored PMF1-BGLAP profile across patient tissues and cancer cell-line models. PMF1-BGLAP expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, PMF1-BGLAP is differentially expressed in 8, with the highest sampling consensus in KICH. Additionally, PMF1-BGLAP RNA expression shows 17,321 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, KICH, and ACC as cancer lineages where PMF1-BGLAP 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 PMF1-BGLAP — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PMF1-BGLAP survival associations across molecular data types. PMF1-BGLAP RNA expression shows survival associations in the most cancer types (22). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PMF1-BGLAP RNA expression–survival associations across cancer types. High PMF1-BGLAP expression shows unfavorable associations in KIRC, LIHC, COAD, BLCA, ACC and KICH. The KIRC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify KIRC as the clearest survival context for PMF1-BGLAP RNA expression.
This table summarizes PMF1-BGLAP tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8. The strongest signals are observed in KICH for RNA.
This table ranks reproducible tumor–normal expression differences for PMF1-BGLAP. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PMF1-BGLAP shows lower tumor expression in KICH and READ and higher tumor expression in LIHC, BRCA, HNSC and CHOL. The KICH box plot shows higher PMF1-BGLAP RNA expression in normal versus tumor tissue (log2 FC = −0.970, t-test p < 0.001).
This table shows molecular features associated with PMF1-BGLAP in patient tissues and cancer cell lines. In patient samples, PMF1-BGLAP shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, PMF1-BGLAP RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OESOPHAGUS, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma.
