Q-omics provides the consensus-scored TAS2R7 profile across patient tissues and cancer cell-line models. TAS2R7 expression is associated with patient survival in 13 of 34 cancer types, with the highest sampling consensus in KIRP. Additionally, TAS2R7 RNA expression shows 7,792 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRP, and GBM as cancer lineages where TAS2R7 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 TAS2R7 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes TAS2R7 survival associations across molecular data types. TAS2R7 RNA expression shows survival associations in the most cancer types (13), followed by mutation status (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible TAS2R7 RNA expression–survival associations across cancer types. High TAS2R7 expression shows unfavorable associations in KIRP, LUSC, UCS, LUAD, DLBC and ACC. The KIRP 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 KIRP as the clearest survival context for TAS2R7 RNA expression.
This table shows molecular features associated with TAS2R7 in patient tissues and cancer cell lines. In patient samples, TAS2R7 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, TAS2R7 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and LUNG_NSCLC_LUSC.
