Q-omics provides the consensus-scored RNGTT profile across patient tissues and cancer cell-line models. RNGTT expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, RNGTT is differentially expressed in 14, with the highest sampling consensus in HNSC. Additionally, RNGTT protein abundance shows 22,825 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight MESO, HNSC, and GBM as cancer lineages where RNGTT 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 RNGTT — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RNGTT survival associations across molecular data types. RNGTT RNA expression shows survival associations in the most cancer types (25), followed by mutation status (7) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RNGTT RNA expression–survival associations across cancer types. High RNGTT expression shows unfavorable associations in MESO, LIHC, KICH, BLCA and LUSC, but favorable associations in THYM. The MESO 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 MESO as the clearest survival context for RNGTT RNA expression.
This table summarizes RNGTT tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 7. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for RNGTT. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RNGTT shows lower tumor expression in KICH and THCA and higher tumor expression in HNSC, LUAD, BLCA and KIRP. The HNSC box plot shows higher RNGTT RNA expression in tumor versus normal tissue (log2 FC = +0.688, t-test p < 0.001).
This table shows molecular features associated with RNGTT in patient tissues and cancer cell lines. In patient samples, RNGTT 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, RNGTT 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 BLOOD_Leukemia and UPPER_AERODIGESTIVE_TRACT.
