Q-omics provides the consensus-scored SEC16B profile across patient tissues and cancer cell-line models. SEC16B expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, SEC16B is differentially expressed in 8, with the highest sampling consensus in KIRC. Additionally, SEC16B RNA expression shows 17,786 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight UVM, and KIRC as cancer lineages where SEC16B 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 SEC16B — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SEC16B survival associations across molecular data types. SEC16B RNA expression shows survival associations in the most cancer types (19), followed by mutation status (8) 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 SEC16B RNA expression–survival associations across cancer types. High SEC16B expression shows unfavorable associations in UVM, CHOL, COAD and LGG, but favorable associations in SKCM and ACC. The UVM 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 UVM as the clearest survival context for SEC16B RNA expression.
This table summarizes SEC16B tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8, while mass-spec protein shows differences in 1. The strongest signals are observed in KIRC for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for SEC16B. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SEC16B shows lower tumor expression in KICH and BRCA and higher tumor expression in KIRC, HNSC, COAD and LIHC. The KIRC box plot shows higher SEC16B RNA expression in tumor versus normal tissue (log2 FC = +0.227, t-test p < 0.001).
This table shows molecular features associated with SEC16B in patient tissues and cancer cell lines. In patient samples, SEC16B shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, SEC16B 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 PANCREAS and CNS.
