Q-omics provides the consensus-scored RHOG2P profile across patient tissues and cancer cell-line models. RHOG2P expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, RHOG2P is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, RHOG2P RNA expression shows 14,132 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight ACC, HNSC, and TGCT as cancer lineages where RHOG2P 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 RHOG2P — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RHOG2P survival associations across molecular data types. RHOG2P RNA expression shows survival associations in the most cancer types (22). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RHOG2P RNA expression–survival associations across cancer types. High RHOG2P expression shows unfavorable associations in ACC, KIRC, BRCA, UVM and PRAD, but favorable associations in BLCA. The ACC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .002). Together, the overview and detailed table identify ACC as the clearest survival context for RHOG2P RNA expression.
This table summarizes RHOG2P tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for RHOG2P. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RHOG2P shows higher tumor expression in HNSC, KICH, LUAD, LUSC, COAD and LIHC. The HNSC box plot shows higher RHOG2P RNA expression in tumor versus normal tissue (log2 FC = +0.263, t-test p < 0.001).
This table shows molecular features associated with RHOG2P in patient tissues and cancer cell lines. In patient samples, RHOG2P shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set.
