Q-omics provides the consensus-scored NRXN2 profile across patient tissues and cancer cell-line models. NRXN2 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, NRXN2 is differentially expressed in 13, with the highest sampling consensus in KIRC. Additionally, NRXN2 RNA expression shows 19,509 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight ACC, KIRC, and GBM as cancer lineages where NRXN2 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 NRXN2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes NRXN2 survival associations across molecular data types. NRXN2 RNA expression shows survival associations in the most cancer types (21), followed by mutation status (7) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible NRXN2 RNA expression–survival associations across cancer types. High NRXN2 expression shows unfavorable associations in ACC, BLCA and THCA, but favorable associations in KIRC, SCLC and CESC. The ACC 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 ACC as the clearest survival context for NRXN2 RNA expression.
This table summarizes NRXN2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 2. The strongest signals are observed in KIRC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for NRXN2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. NRXN2 shows lower tumor expression in KICH, THCA, UCEC and READ and higher tumor expression in KIRC and HNSC. The KIRC box plot shows higher NRXN2 RNA expression in tumor versus normal tissue (log2 FC = +1.506, t-test p < 0.001).
This table shows molecular features associated with NRXN2 in patient tissues and cancer cell lines. In patient samples, NRXN2 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, NRXN2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in LUNG_SCLC and LARGE_INTESTINE.
