Q-omics provides the consensus-scored NOC4L profile across patient tissues and cancer cell-line models. NOC4L expression is associated with patient survival in 30 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, NOC4L is differentially expressed in 17, with the highest sampling consensus in COAD. Additionally, NOC4L protein abundance shows 27,750 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, COAD, and GBM as cancer lineages where NOC4L 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 NOC4L — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes NOC4L survival associations across molecular data types. NOC4L RNA expression shows survival associations in the most cancer types (30), followed by mutation status (6) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible NOC4L RNA expression–survival associations across cancer types. High NOC4L expression shows unfavorable associations in KIRC, ACC, MESO, LUAD and LIHC, but favorable associations in SCLC. 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 NOC4L RNA expression.
This table summarizes NOC4L tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 17, while mass-spec protein shows differences in 6. The strongest signals are observed in COAD for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for NOC4L. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. NOC4L shows higher tumor expression in COAD, KIRP, LIHC, HNSC, STAD and LUSC. The COAD box plot shows higher NOC4L RNA expression in tumor versus normal tissue (log2 FC = +1.390, t-test p < 0.001).
This table shows molecular features associated with NOC4L in patient tissues and cancer cell lines. In patient samples, NOC4L 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, NOC4L RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and BLOOD_Lymphoma.
