Q-omics provides the consensus-scored NGF profile across patient tissues and cancer cell-line models. NGF expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, NGF is differentially expressed in 10, with the highest sampling consensus in KIRC. Additionally, NGF RNA expression shows 14,621 significant protein co-abundance associations, with the highest sampling consensus in UCEC. Together, these results highlight KIRP, KIRC, and UCEC as cancer lineages where NGF 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 NGF — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes NGF survival associations across molecular data types. NGF RNA expression shows survival associations in the most cancer types (25), followed by mutation status (4) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible NGF RNA expression–survival associations across cancer types. High NGF expression shows unfavorable associations in KIRP, BLCA, STAD, UVM, COAD and HNSC. The KIRP 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 KIRP as the clearest survival context for NGF RNA expression.
This table summarizes NGF tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 3. The strongest signals are observed in KIRC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for NGF. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. NGF shows lower tumor expression in KICH, UCEC, BLCA and KIRP and higher tumor expression in KIRC and HNSC. The KIRC box plot shows higher NGF RNA expression in tumor versus normal tissue (log2 FC = +1.863, t-test p < 0.001).
This table shows molecular features associated with NGF in patient tissues and cancer cell lines. In patient samples, NGF shows the broadest associations at the RNA and protein expression levels, with UCEC recurring as the lineage with the largest associated feature set. In cancer cell lines, NGF RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in BONE and LARGE_INTESTINE.
