Q-omics provides the consensus-scored SNX8 profile across patient tissues and cancer cell-line models. SNX8 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in KICH. Among the 18 cancer types available for tumor–normal comparison, SNX8 is differentially expressed in 14, with the highest sampling consensus in HNSC. Additionally, SNX8 RNA expression shows 18,639 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KICH, HNSC, and ACC as cancer lineages where SNX8 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 SNX8 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SNX8 survival associations across molecular data types. SNX8 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (4) 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 SNX8 RNA expression–survival associations across cancer types. High SNX8 expression shows unfavorable associations in KICH, ACC, LIHC, LGG and OV, but favorable associations in ESCA. The KICH 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 KICH as the clearest survival context for SNX8 RNA expression.
This table summarizes SNX8 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 6. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for SNX8. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SNX8 shows higher tumor expression in HNSC, COAD, KIRC, STAD, LIHC and BLCA. The HNSC box plot shows higher SNX8 RNA expression in tumor versus normal tissue (log2 FC = +0.965, t-test p < 0.001).
This table shows molecular features associated with SNX8 in patient tissues and cancer cell lines. In patient samples, SNX8 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, SNX8 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Myeloma, while CRISPR and shRNA rows add functional-dependency signals in OVARY and BLOOD_Lymphoma.
