Q-omics provides the consensus-scored ROGDI profile across patient tissues and cancer cell-line models. ROGDI expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, ROGDI is differentially expressed in 9, with the highest sampling consensus in KICH. Additionally, ROGDI protein abundance shows 26,237 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight UVM, KICH, and GBM as cancer lineages where ROGDI 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 ROGDI — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ROGDI survival associations across molecular data types. ROGDI RNA expression shows survival associations in the most cancer types (22), followed by mutation status (3) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ROGDI RNA expression–survival associations across cancer types. High ROGDI expression shows unfavorable associations in UVM, THCA and HNSC, but favorable associations in MESO, PAAD and KIRP. The UVM 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 UVM as the clearest survival context for ROGDI RNA expression.
This table summarizes ROGDI tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9, while mass-spec protein shows differences in 6. The strongest signals are observed in KICH for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for ROGDI. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ROGDI shows lower tumor expression in KICH, STAD, KIRC and COAD and higher tumor expression in BRCA and LIHC. The KICH box plot shows higher ROGDI RNA expression in normal versus tumor tissue (log2 FC = −1.330, t-test p = .004).
This table shows molecular features associated with ROGDI in patient tissues and cancer cell lines. In patient samples, ROGDI shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, ROGDI RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in OVARY and SOFT_TISSUE.
