Q-omics provides the consensus-scored SNX16 profile across patient tissues and cancer cell-line models. SNX16 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, SNX16 is differentially expressed in 8, with the highest sampling consensus in LIHC. Additionally, SNX16 RNA expression shows 20,302 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRP, LIHC, and UVM as cancer lineages where SNX16 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 SNX16 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SNX16 survival associations across molecular data types. SNX16 RNA expression shows survival associations in the most cancer types (25), followed by 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 SNX16 RNA expression–survival associations across cancer types. High SNX16 expression shows unfavorable associations in KIRP, LIHC, UVM and SCLC, but favorable associations in KIRC and BRCA. The KIRP 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 KIRP as the clearest survival context for SNX16 RNA expression.
This table summarizes SNX16 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 7. The strongest signals are observed in LIHC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for SNX16. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SNX16 shows lower tumor expression in KICH and higher tumor expression in LIHC, KIRP, CHOL, HNSC and LUSC. The LIHC box plot shows higher SNX16 RNA expression in tumor versus normal tissue (log2 FC = +0.775, t-test p < 0.001).
This table shows molecular features associated with SNX16 in patient tissues and cancer cell lines. In patient samples, SNX16 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, SNX16 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LARGE_INTESTINE, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUAD and BLOOD_Leukemia.
