Q-omics provides the consensus-scored RTCB profile across patient tissues and cancer cell-line models. RTCB expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, RTCB is differentially expressed in 10, with the highest sampling consensus in HNSC. Additionally, RTCB protein abundance shows 23,335 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight ACC, HNSC, and GBM as cancer lineages where RTCB 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 RTCB — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RTCB survival associations across molecular data types. RTCB RNA expression shows survival associations in the most cancer types (23), followed by mutation status (4) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RTCB RNA expression–survival associations across cancer types. High RTCB expression shows unfavorable associations in ACC, HNSC and LIHC, but favorable associations in UCEC, LUSC and READ. 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 RTCB RNA expression.
This table summarizes RTCB 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 9. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for RTCB. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RTCB shows lower tumor expression in KICH and higher tumor expression in HNSC, LIHC, LUSC, CHOL and BLCA. The HNSC box plot shows higher RTCB RNA expression in tumor versus normal tissue (log2 FC = +0.417, t-test p < 0.001).
This table shows molecular features associated with RTCB in patient tissues and cancer cell lines. In patient samples, RTCB 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, RTCB RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in LUNG_SCLC and BLOOD_Lymphoma.
