nuclear transport factor 2Genealiases: NTF-2 · NTF2 · PP15
Q-omics provides the consensus-scored NUTF2 profile across patient tissues and cancer cell-line models. NUTF2 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, NUTF2 is differentially expressed in 16, with the highest sampling consensus in HNSC. Additionally, NUTF2 protein abundance shows 25,817 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight KIRC, HNSC, and PDAC as cancer lineages where NUTF2 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 NUTF2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes NUTF2 survival associations across molecular data types. NUTF2 RNA expression shows survival associations in the most cancer types (23), 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 NUTF2 RNA expression–survival associations across cancer types. High NUTF2 expression shows unfavorable associations in KIRC, ACC, MESO, HNSC, BRCA and LIHC. 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 NUTF2 RNA expression.
This table summarizes NUTF2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 6. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for NUTF2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. NUTF2 shows higher tumor expression in HNSC, KIRC, KIRP, COAD, LIHC and BLCA. The HNSC box plot shows higher NUTF2 RNA expression in tumor versus normal tissue (log2 FC = +1.302, t-test p < 0.001).
This table shows molecular features associated with NUTF2 in patient tissues and cancer cell lines. In patient samples, NUTF2 shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, NUTF2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in LUNG_SCLC and BLOOD_Lymphoma.
