Q-omics provides the consensus-scored GDPD3 profile across patient tissues and cancer cell-line models. GDPD3 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, GDPD3 is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, GDPD3 RNA expression shows 16,531 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRC, HNSC, and UVM as cancer lineages where GDPD3 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 GDPD3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GDPD3 survival associations across molecular data types. GDPD3 RNA expression shows survival associations in the most cancer types (21), followed by mutation status (5) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible GDPD3 RNA expression–survival associations across cancer types. High GDPD3 expression shows unfavorable associations in KIRC, ACC, KIRP and UVM, but favorable associations in SKCM and COAD. 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 GDPD3 RNA expression.
This table summarizes GDPD3 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 8. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for GDPD3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GDPD3 shows lower tumor expression in HNSC, KIRP, COAD, KICH and READ and higher tumor expression in BLCA. The HNSC box plot shows higher GDPD3 RNA expression in normal versus tumor tissue (log2 FC = −2.733, t-test p < 0.001).
This table shows molecular features associated with GDPD3 in patient tissues and cancer cell lines. In patient samples, GDPD3 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, GDPD3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in BONE and BLOOD_Leukemia.
