Q-omics provides the consensus-scored RIPK1 profile across patient tissues and cancer cell-line models. RIPK1 expression is associated with patient survival in 18 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, RIPK1 is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, RIPK1 protein abundance shows 35,739 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, and GBM as cancer lineages where RIPK1 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 RIPK1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RIPK1 survival associations across molecular data types. RIPK1 RNA expression shows survival associations in the most cancer types (18), followed by mutation status (5) and mass-spec protein abundance (10). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RIPK1 RNA expression–survival associations across cancer types. High RIPK1 expression shows unfavorable associations in ACC, LGG and MESO, but favorable associations in KIRC, THYM and HNSC. The KIRC 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 KIRC as the clearest survival context for RIPK1 RNA expression.
This table summarizes RIPK1 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 12. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for RIPK1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RIPK1 shows lower tumor expression in THCA, KICH and COAD and higher tumor expression in KIRC, LIHC and HNSC. The KIRC box plot shows higher RIPK1 RNA expression in tumor versus normal tissue (log2 FC = +0.532, t-test p < 0.001).
This table shows molecular features associated with RIPK1 in patient tissues and cancer cell lines. In patient samples, RIPK1 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, RIPK1 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 CNS and BLOOD_Leukemia.
