Q-omics provides the consensus-scored SNX5 profile across patient tissues and cancer cell-line models. SNX5 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, SNX5 is differentially expressed in 11, with the highest sampling consensus in HNSC. Additionally, SNX5 protein abundance shows 30,406 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight LIHC, HNSC, and LUAD as cancer lineages where SNX5 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 SNX5 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SNX5 survival associations across molecular data types. SNX5 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (5) 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 SNX5 RNA expression–survival associations across cancer types. High SNX5 expression shows unfavorable associations in LIHC, MESO, KICH and LGG, but favorable associations in KIRC and READ. The LIHC 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 LIHC as the clearest survival context for SNX5 RNA expression.
This table summarizes SNX5 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 7. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for SNX5. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SNX5 shows lower tumor expression in KICH and LUAD and higher tumor expression in HNSC, BLCA, STAD and LIHC. The HNSC box plot shows higher SNX5 RNA expression in tumor versus normal tissue (log2 FC = +1.011, t-test p < 0.001).
This table shows molecular features associated with SNX5 in patient tissues and cancer cell lines. In patient samples, SNX5 shows the broadest associations at the RNA and protein expression levels, with LUAD recurring as the lineage with the largest associated feature set. In cancer cell lines, SNX5 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and BLOOD_Lymphoma.
