Q-omics provides the consensus-scored RECK profile across patient tissues and cancer cell-line models. RECK expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in KICH. Among the 18 cancer types available for tumor–normal comparison, RECK is differentially expressed in 13, with the highest sampling consensus in LUAD. Additionally, RECK protein abundance shows 25,680 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight KICH, LUAD, and LSCC as cancer lineages where RECK 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 RECK — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RECK survival associations across molecular data types. RECK RNA expression shows survival associations in the most cancer types (28), followed by mutation status (8) 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 RECK RNA expression–survival associations across cancer types. High RECK expression shows unfavorable associations in KICH, MESO, STAD and LGG, but favorable associations in KIRC and UCS. The KICH Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify KICH as the clearest survival context for RECK RNA expression.
This table summarizes RECK 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 8. The strongest signals are observed in LUAD for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for RECK. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RECK shows lower tumor expression in LUAD, COAD, BLCA, LUSC, THCA and KICH. The LUAD box plot shows higher RECK RNA expression in normal versus tumor tissue (log2 FC = −1.491, t-test p < 0.001).
This table shows molecular features associated with RECK in patient tissues and cancer cell lines. In patient samples, RECK shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, RECK RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OESOPHAGUS, while CRISPR and shRNA rows add functional-dependency signals in BONE and BLOOD_Leukemia.
