RANBP2 like and GRIP domain containing 6Genealiases: RGP6 · RGPD7 · RanBP2L1 · RanBP2L2
Q-omics provides the consensus-scored RGPD6 profile across patient tissues and cancer cell-line models. RGPD6 expression is associated with patient survival in 17 of 34 cancer types, with the highest sampling consensus in STAD. Among the 18 cancer types available for tumor–normal comparison, RGPD6 is differentially expressed in 3, with the highest sampling consensus in HNSC. Additionally, RGPD6 RNA expression shows 10,987 significant gene co-expression associations, with the highest sampling consensus in SKCM. Together, these results highlight STAD, HNSC, and SKCM as cancer lineages where RGPD6 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 RGPD6 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RGPD6 survival associations across molecular data types. RGPD6 RNA expression shows survival associations in the most cancer types (17). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RGPD6 RNA expression–survival associations across cancer types. High RGPD6 expression shows unfavorable associations in STAD, OV, KIRP, ACC, KIRC and PAAD. The STAD Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify STAD as the clearest survival context for RGPD6 RNA expression.
This table summarizes RGPD6 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 3. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for RGPD6. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RGPD6 shows lower tumor expression in LUAD and higher tumor expression in HNSC and KIRP. The HNSC box plot shows higher RGPD6 RNA expression in tumor versus normal tissue (log2 FC = +0.005, t-test p < 0.001).
This table shows molecular features associated with RGPD6 in patient tissues and cancer cell lines. In patient samples, RGPD6 shows the broadest associations at the RNA and protein expression levels, with SKCM recurring as the lineage with the largest associated feature set. In cancer cell lines, RGPD6 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LARGE_INTESTINE, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and OESOPHAGUS.
