Q-omics provides the consensus-scored NR2C1 profile across patient tissues and cancer cell-line models. NR2C1 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, NR2C1 is differentially expressed in 15, with the highest sampling consensus in HNSC. Additionally, NR2C1 RNA expression shows 21,060 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight LIHC, HNSC, and UVM as cancer lineages where NR2C1 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 NR2C1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes NR2C1 survival associations across molecular data types. NR2C1 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (4) 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 NR2C1 RNA expression–survival associations across cancer types. High NR2C1 expression shows unfavorable associations in LIHC, ACC and KIRC, but favorable associations in BLCA, UCS and UCEC. The LIHC 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 LIHC as the clearest survival context for NR2C1 RNA expression.
This table summarizes NR2C1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 1. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for NR2C1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. NR2C1 shows lower tumor expression in THCA and LUAD and higher tumor expression in HNSC, LIHC, STAD and COAD. The HNSC box plot shows higher NR2C1 RNA expression in tumor versus normal tissue (log2 FC = +0.578, t-test p < 0.001).
This table shows molecular features associated with NR2C1 in patient tissues and cancer cell lines. In patient samples, NR2C1 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, NR2C1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUAD and BLOOD_Leukemia.
