Q-omics provides the consensus-scored HPGDS profile across patient tissues and cancer cell-line models. HPGDS expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, HPGDS is differentially expressed in 14, with the highest sampling consensus in COAD. Additionally, HPGDS protein abundance shows 25,485 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight HNSC, COAD, and LUAD as cancer lineages where HPGDS 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 HPGDS — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes HPGDS survival associations across molecular data types. HPGDS RNA expression shows survival associations in the most cancer types (25), followed by mutation status (5) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible HPGDS RNA expression–survival associations across cancer types. High HPGDS expression shows unfavorable associations in OV, but favorable associations in HNSC, LUAD, UCEC, ACC and CESC. The HNSC 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 HNSC as the clearest survival context for HPGDS RNA expression.
This table summarizes HPGDS 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 7. The strongest signals are observed in BLCA for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for HPGDS. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. HPGDS shows lower tumor expression in COAD, BLCA, LUSC and LUAD and higher tumor expression in THCA and KIRC. The COAD box plot shows higher HPGDS RNA expression in normal versus tumor tissue (log2 FC = −2.521, t-test p < 0.001).
This table shows molecular features associated with HPGDS in patient tissues and cancer cell lines. In patient samples, HPGDS shows the broadest associations at the RNA and protein expression levels, with LUAD recurring as the lineage with the largest associated feature set. In cancer cell lines, HPGDS RNA and mutation anchors are most strongly linked to RNA-expression features, especially in URINARY_TRACT, while CRISPR and shRNA rows add functional-dependency signals in OVARY and BLOOD_Leukemia.
