Q-omics provides the consensus-scored RGP1 profile across patient tissues and cancer cell-line models. RGP1 expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, RGP1 is differentially expressed in 13, with the highest sampling consensus in LIHC. Additionally, RGP1 RNA expression shows 20,812 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, LIHC, and ACC as cancer lineages where RGP1 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 RGP1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RGP1 survival associations across molecular data types. RGP1 RNA expression shows survival associations in the most cancer types (28), followed by mutation status (6) 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 RGP1 RNA expression–survival associations across cancer types. High RGP1 expression shows unfavorable associations in ACC, LIHC, MESO and CESC, but favorable associations in KIRC and GBM. The KIRC 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 KIRC as the clearest survival context for RGP1 RNA expression.
This table summarizes RGP1 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 5. The strongest signals are observed in THCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for RGP1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RGP1 shows lower tumor expression in COAD, THCA, KIRC and BRCA and higher tumor expression in LIHC and HNSC. The LIHC box plot shows higher RGP1 RNA expression in tumor versus normal tissue (log2 FC = +1.500, t-test p < 0.001).
This table shows molecular features associated with RGP1 in patient tissues and cancer cell lines. In patient samples, RGP1 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, RGP1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUAD and BLOOD_Leukemia.
