Q-omics provides the consensus-scored NFIC profile across patient tissues and cancer cell-line models. NFIC expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, NFIC is differentially expressed in 11, with the highest sampling consensus in BLCA. Additionally, NFIC protein abundance shows 24,325 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight UVM, BLCA, and GBM as cancer lineages where NFIC 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 NFIC — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes NFIC survival associations across molecular data types. NFIC RNA expression shows survival associations in the most cancer types (26), followed by mutation status (4) 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 NFIC RNA expression–survival associations across cancer types. High NFIC expression shows unfavorable associations in UVM, BLCA, MESO and LGG, but favorable associations in UCEC and HNSC. The UVM 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 UVM as the clearest survival context for NFIC RNA expression.
This table summarizes NFIC tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 5. The strongest signals are observed in BLCA for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for NFIC. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. NFIC shows lower tumor expression in BLCA, THCA, LUSC, LUAD and UCEC and higher tumor expression in LIHC. The BLCA box plot shows higher NFIC RNA expression in normal versus tumor tissue (log2 FC = −2.470, t-test p < 0.001).
This table shows molecular features associated with NFIC in patient tissues and cancer cell lines. In patient samples, NFIC 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, NFIC 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 PANCREAS and LARGE_INTESTINE.
