myosin VIIA and Rab interacting proteinGenealiases: SLAC2-C · SLAC2C
Q-omics provides the consensus-scored MYRIP profile across patient tissues and cancer cell-line models. MYRIP expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, MYRIP is differentially expressed in 15, with the highest sampling consensus in BLCA. Additionally, MYRIP RNA expression shows 18,801 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight KIRC, BLCA, and THYM as cancer lineages where MYRIP 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 MYRIP — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MYRIP survival associations across molecular data types. MYRIP RNA expression shows survival associations in the most cancer types (24), 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 MYRIP RNA expression–survival associations across cancer types. High MYRIP expression shows favorable associations in KIRC, BRCA, ACC, LIHC, SKCM and LUAD. 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 MYRIP RNA expression.
This table summarizes MYRIP tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 4. The strongest signals are observed in HNSC for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for MYRIP. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MYRIP shows lower tumor expression in BLCA, HNSC, STAD, LUSC, THCA and LUAD. The BLCA box plot shows higher MYRIP RNA expression in normal versus tumor tissue (log2 FC = −1.324, t-test p < 0.001).
This table shows molecular features associated with MYRIP in patient tissues and cancer cell lines. In patient samples, MYRIP shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, MYRIP 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 LUNG_NSCLC_LUSC and BREAST.
