Q-omics provides the consensus-scored NINJ1 profile across patient tissues and cancer cell-line models. NINJ1 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in CESC. Among the 18 cancer types available for tumor–normal comparison, NINJ1 is differentially expressed in 15, with the highest sampling consensus in KICH. Additionally, NINJ1 protein abundance shows 18,587 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight CESC, KICH, and GBM as cancer lineages where NINJ1 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 NINJ1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes NINJ1 survival associations across molecular data types. NINJ1 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (2) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible NINJ1 RNA expression–survival associations across cancer types. High NINJ1 expression shows unfavorable associations in UCS and KICH, but favorable associations in CESC, BRCA, THCA and KIRP. The CESC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .001). Together, the overview and detailed table identify CESC as the clearest survival context for NINJ1 RNA expression.
This table summarizes NINJ1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 5. The strongest signals are observed in KICH for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for NINJ1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. NINJ1 shows lower tumor expression in KICH and higher tumor expression in LIHC, THCA, HNSC, BRCA and ESCA. The KICH box plot shows higher NINJ1 RNA expression in normal versus tumor tissue (log2 FC = −1.013, t-test p < 0.001).
This table shows molecular features associated with NINJ1 in patient tissues and cancer cell lines. In patient samples, NINJ1 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, NINJ1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in CNS and SOFT_TISSUE.
