Q-omics provides the consensus-scored GDPD2 profile across patient tissues and cancer cell-line models. GDPD2 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in UCEC. Among the 18 cancer types available for tumor–normal comparison, GDPD2 is differentially expressed in 13, with the highest sampling consensus in COAD. Additionally, GDPD2 RNA expression shows 16,900 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight UCEC, COAD, and ACC as cancer lineages where GDPD2 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 GDPD2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GDPD2 survival associations across molecular data types. GDPD2 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (3) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible GDPD2 RNA expression–survival associations across cancer types. High GDPD2 expression shows unfavorable associations in UCEC, MESO, LGG and STAD, but favorable associations in KIRC and CESC. The UCEC 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 UCEC as the clearest survival context for GDPD2 RNA expression.
This table summarizes GDPD2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 1. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for GDPD2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GDPD2 shows lower tumor expression in COAD, KIRC, KIRP and READ and higher tumor expression in HNSC and LUSC. The COAD box plot shows higher GDPD2 RNA expression in normal versus tumor tissue (log2 FC = −3.098, t-test p < 0.001).
This table shows molecular features associated with GDPD2 in patient tissues and cancer cell lines. In patient samples, GDPD2 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, GDPD2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and BLOOD_Leukemia.
