Q-omics provides the consensus-scored SNX11 profile across patient tissues and cancer cell-line models. SNX11 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, SNX11 is differentially expressed in 10, with the highest sampling consensus in HNSC. Additionally, SNX11 protein abundance shows 25,394 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight ACC, HNSC, and LSCC as cancer lineages where SNX11 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 SNX11 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SNX11 survival associations across molecular data types. SNX11 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (4) and mass-spec protein abundance (10). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SNX11 RNA expression–survival associations across cancer types. High SNX11 expression shows unfavorable associations in ACC, LIHC and LAML, but favorable associations in ESCA, KIRC and BRCA. The ACC 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 ACC as the clearest survival context for SNX11 RNA expression.
This table summarizes SNX11 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 9. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for SNX11. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SNX11 shows lower tumor expression in KICH and THCA and higher tumor expression in HNSC, LIHC, CHOL and BLCA. The HNSC box plot shows higher SNX11 RNA expression in tumor versus normal tissue (log2 FC = +0.547, t-test p < 0.001).
This table shows molecular features associated with SNX11 in patient tissues and cancer cell lines. In patient samples, SNX11 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, SNX11 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 LARGE_INTESTINE and BLOOD_Lymphoma.
