Q-omics provides the consensus-scored TATDN2 profile across patient tissues and cancer cell-line models. TATDN2 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, TATDN2 is differentially expressed in 13, with the highest sampling consensus in LIHC. Additionally, TATDN2 RNA expression shows 19,135 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight UVM, LIHC, and ACC as cancer lineages where TATDN2 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 TATDN2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes TATDN2 survival associations across molecular data types. TATDN2 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (3) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible TATDN2 RNA expression–survival associations across cancer types. High TATDN2 expression shows unfavorable associations in ACC, KICH, LIHC, LGG and SARC, but favorable associations in UVM. The UVM Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify UVM as the clearest survival context for TATDN2 RNA expression.
This table summarizes TATDN2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13. The strongest signals are observed in LIHC for RNA.
This table ranks reproducible tumor–normal expression differences for TATDN2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. TATDN2 shows lower tumor expression in THCA and KICH and higher tumor expression in LIHC, STAD, UCEC and COAD. The LIHC box plot shows higher TATDN2 RNA expression in tumor versus normal tissue (log2 FC = +1.387, t-test p < 0.001).
This table shows molecular features associated with TATDN2 in patient tissues and cancer cell lines. In patient samples, TATDN2 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, TATDN2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and BLOOD_Leukemia.
