Q-omics provides the consensus-scored RETNLB profile across patient tissues and cancer cell-line models. RETNLB expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, RETNLB is differentially expressed in 9, with the highest sampling consensus in HNSC. Additionally, RETNLB RNA expression shows 7,191 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight KIRC, HNSC, and THYM as cancer lineages where RETNLB 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 RETNLB — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RETNLB survival associations across molecular data types. RETNLB RNA expression shows survival associations in the most cancer types (22), followed by mutation status (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RETNLB RNA expression–survival associations across cancer types. High RETNLB expression shows unfavorable associations in KIRC, UCEC, KICH, UVM, ACC and STAD. The KIRC 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 KIRC as the clearest survival context for RETNLB RNA expression.
This table summarizes RETNLB tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for RETNLB. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RETNLB shows lower tumor expression in COAD and READ and higher tumor expression in HNSC, LUSC, LUAD and BLCA. The HNSC box plot shows higher RETNLB RNA expression in tumor versus normal tissue (log2 FC = +0.322, t-test p < 0.001).
This table shows molecular features associated with RETNLB in patient tissues and cancer cell lines. In patient samples, RETNLB 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, RETNLB RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and BONE.
