Q-omics provides the consensus-scored TNFRSF1A profile across patient tissues and cancer cell-line models. TNFRSF1A expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, TNFRSF1A is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, TNFRSF1A RNA expression shows 19,312 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight UVM, KIRC, and ACC as cancer lineages where TNFRSF1A 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 TNFRSF1A — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes TNFRSF1A survival associations across molecular data types. TNFRSF1A RNA expression shows survival associations in the most cancer types (26), followed by mutation status (3) 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 TNFRSF1A RNA expression–survival associations across cancer types. High TNFRSF1A expression shows unfavorable associations in UVM, LGG, LUAD and HNSC, but favorable associations in UCEC and SKCM. The UVM 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 UVM as the clearest survival context for TNFRSF1A RNA expression.
This table summarizes TNFRSF1A tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 3. The strongest signals are observed in KIRC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for TNFRSF1A. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. TNFRSF1A shows lower tumor expression in COAD and KICH and higher tumor expression in KIRC, HNSC, THCA and KIRP. The KIRC box plot shows higher TNFRSF1A RNA expression in tumor versus normal tissue (log2 FC = +1.238, t-test p < 0.001).
This table shows molecular features associated with TNFRSF1A in patient tissues and cancer cell lines. In patient samples, TNFRSF1A shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, TNFRSF1A RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LARGE_INTESTINE, while CRISPR and shRNA rows add functional-dependency signals in OVARY and BONE.
