Q-omics provides the consensus-scored RASGEF1C profile across patient tissues and cancer cell-line models. RASGEF1C expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in LUAD. Among the 18 cancer types available for tumor–normal comparison, RASGEF1C is differentially expressed in 11, with the highest sampling consensus in KIRP. Additionally, RASGEF1C RNA expression shows 13,876 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight LUAD, KIRP, and GBM as cancer lineages where RASGEF1C 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 RASGEF1C — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RASGEF1C survival associations across molecular data types. RASGEF1C RNA expression shows survival associations in the most cancer types (22), followed by mutation status (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RASGEF1C RNA expression–survival associations across cancer types. High RASGEF1C expression shows unfavorable associations in LUAD, KICH, LIHC and KIRC, but favorable associations in LGG and ACC. The LUAD 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 LUAD as the clearest survival context for RASGEF1C RNA expression.
This table summarizes RASGEF1C tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11. The strongest signals are observed in KIRP for RNA.
This table ranks reproducible tumor–normal expression differences for RASGEF1C. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RASGEF1C shows lower tumor expression in BLCA, COAD, KICH and BRCA and higher tumor expression in KIRP and KIRC. The KIRP box plot shows higher RASGEF1C RNA expression in tumor versus normal tissue (log2 FC = +1.539, t-test p < 0.001).
This table shows molecular features associated with RASGEF1C in patient tissues and cancer cell lines. In patient samples, RASGEF1C 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, RASGEF1C 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 OVARY and SKIN.
