reticulon 4 interacting protein 1Genealiases: NIMP · OPA10 · Yim1
Q-omics provides the consensus-scored RTN4IP1 profile across patient tissues and cancer cell-line models. RTN4IP1 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in BRCA. Among the 18 cancer types available for tumor–normal comparison, RTN4IP1 is differentially expressed in 14, with the highest sampling consensus in KIRC. Additionally, RTN4IP1 protein abundance shows 20,320 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight BRCA, KIRC, and GBM as cancer lineages where RTN4IP1 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 RTN4IP1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RTN4IP1 survival associations across molecular data types. RTN4IP1 RNA expression shows survival associations in the most cancer types (22), 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 RTN4IP1 RNA expression–survival associations across cancer types. High RTN4IP1 expression shows unfavorable associations in BRCA, LIHC, LGG and HNSC, but favorable associations in KIRP and READ. The BRCA 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 BRCA as the clearest survival context for RTN4IP1 RNA expression.
This table summarizes RTN4IP1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 7. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for RTN4IP1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RTN4IP1 shows lower tumor expression in KIRC, THCA and KICH and higher tumor expression in STAD, LIHC and BLCA. The KIRC box plot shows higher RTN4IP1 RNA expression in normal versus tumor tissue (log2 FC = −0.711, t-test p < 0.001).
This table shows molecular features associated with RTN4IP1 in patient tissues and cancer cell lines. In patient samples, RTN4IP1 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, RTN4IP1 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 LARGE_INTESTINE and BLOOD_Lymphoma.
