Q-omics provides the consensus-scored RCOR3 profile across patient tissues and cancer cell-line models. RCOR3 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, RCOR3 is differentially expressed in 10, with the highest sampling consensus in LIHC. Additionally, RCOR3 protein abundance shows 22,053 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight ACC, LIHC, and GBM as cancer lineages where RCOR3 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 RCOR3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RCOR3 survival associations across molecular data types. RCOR3 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (5) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RCOR3 RNA expression–survival associations across cancer types. High RCOR3 expression shows unfavorable associations in ACC, LIHC and UVM, but favorable associations in SCLC, GBM and BRCA. The ACC 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 ACC as the clearest survival context for RCOR3 RNA expression.
This table summarizes RCOR3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 4. The strongest signals are observed in LIHC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for RCOR3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RCOR3 shows lower tumor expression in KICH, UCEC and THCA and higher tumor expression in LIHC, BRCA and CHOL. The LIHC box plot shows higher RCOR3 RNA expression in tumor versus normal tissue (log2 FC = +1.268, t-test p < 0.001).
This table shows molecular features associated with RCOR3 in patient tissues and cancer cell lines. In patient samples, RCOR3 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, RCOR3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Lymphoma, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and BLOOD_Leukemia.
