Q-omics provides the consensus-scored GLO1 profile across patient tissues and cancer cell-line models. GLO1 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, GLO1 is differentially expressed in 14, with the highest sampling consensus in HNSC. Additionally, GLO1 protein abundance shows 23,133 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight LIHC, HNSC, and PDAC as cancer lineages where GLO1 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 GLO1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GLO1 survival associations across molecular data types. GLO1 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (2) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible GLO1 RNA expression–survival associations across cancer types. High GLO1 expression shows unfavorable associations in LIHC, ESCA, MESO, KIRP, ACC and SARC. The LIHC 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 LIHC as the clearest survival context for GLO1 RNA expression.
This table summarizes GLO1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 4. The strongest signals are observed in HNSC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for GLO1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GLO1 shows lower tumor expression in THCA and KICH and higher tumor expression in HNSC, COAD, BRCA and LIHC. The HNSC box plot shows higher GLO1 RNA expression in tumor versus normal tissue (log2 FC = +0.956, t-test p < 0.001).
This table shows molecular features associated with GLO1 in patient tissues and cancer cell lines. In patient samples, GLO1 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, GLO1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in STOMACH and UPPER_AERODIGESTIVE_TRACT.
