Q-omics provides the consensus-scored OPHN1 profile across patient tissues and cancer cell-line models. OPHN1 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, OPHN1 is differentially expressed in 11, with the highest sampling consensus in KIRC. Additionally, OPHN1 protein abundance shows 24,903 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight KIRC, and LUAD as cancer lineages where OPHN1 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 OPHN1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes OPHN1 survival associations across molecular data types. OPHN1 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (7) 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 OPHN1 RNA expression–survival associations across cancer types. High OPHN1 expression shows unfavorable associations in BLCA, THCA and LIHC, but favorable associations in KIRC, LGG and ACC. The KIRC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify KIRC as the clearest survival context for OPHN1 RNA expression.
This table summarizes OPHN1 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 7. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for OPHN1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. OPHN1 shows lower tumor expression in KIRC, THCA, KICH and BRCA and higher tumor expression in LIHC and HNSC. The KIRC box plot shows higher OPHN1 RNA expression in normal versus tumor tissue (log2 FC = −1.344, t-test p < 0.001).
This table shows molecular features associated with OPHN1 in patient tissues and cancer cell lines. In patient samples, OPHN1 shows the broadest associations at the RNA and protein expression levels, with LUAD recurring as the lineage with the largest associated feature set. In cancer cell lines, OPHN1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Myeloma and LARGE_INTESTINE.
