Q-omics provides the consensus-scored TP53I13 profile across patient tissues and cancer cell-line models. TP53I13 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, TP53I13 is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, TP53I13 RNA expression shows 16,217 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, HNSC, and ACC as cancer lineages where TP53I13 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 TP53I13 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes TP53I13 survival associations across molecular data types. TP53I13 RNA expression shows survival associations in the most cancer types (21), followed by mutation status (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible TP53I13 RNA expression–survival associations across cancer types. High TP53I13 expression shows unfavorable associations in KIRC, UVM, LGG and HNSC, but favorable associations in UCEC and PAAD. The KIRC 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 KIRC as the clearest survival context for TP53I13 RNA expression.
This table summarizes TP53I13 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for TP53I13. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. TP53I13 shows lower tumor expression in KICH and higher tumor expression in HNSC, KIRC, KIRP, BLCA and COAD. The HNSC box plot shows higher TP53I13 RNA expression in tumor versus normal tissue (log2 FC = +1.498, t-test p < 0.001).
This table shows molecular features associated with TP53I13 in patient tissues and cancer cell lines. In patient samples, TP53I13 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, TP53I13 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in BREAST and BLOOD_Leukemia.
