Q-omics provides the consensus-scored RIPK4 profile across patient tissues and cancer cell-line models. RIPK4 expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, RIPK4 is differentially expressed in 10, with the highest sampling consensus in KICH. Additionally, RIPK4 RNA expression shows 17,674 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight ACC, KICH, and THYM as cancer lineages where RIPK4 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 RIPK4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RIPK4 survival associations across molecular data types. RIPK4 RNA expression shows survival associations in the most cancer types (19), followed by mutation status (4) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RIPK4 RNA expression–survival associations across cancer types. High RIPK4 expression shows unfavorable associations in ACC, COAD and OV, but favorable associations in KIRC, UVM and SCLC. The ACC 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 ACC as the clearest survival context for RIPK4 RNA expression.
This table summarizes RIPK4 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 3. The strongest signals are observed in KICH for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for RIPK4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RIPK4 shows lower tumor expression in KICH and THCA and higher tumor expression in COAD, UCEC, LUSC and BLCA. The KICH box plot shows higher RIPK4 RNA expression in normal versus tumor tissue (log2 FC = −2.390, t-test p < 0.001).
This table shows molecular features associated with RIPK4 in patient tissues and cancer cell lines. In patient samples, RIPK4 shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, RIPK4 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and BREAST.
