Q-omics provides the consensus-scored STX6 profile across patient tissues and cancer cell-line models. STX6 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, STX6 is differentially expressed in 16, with the highest sampling consensus in HNSC. Additionally, STX6 RNA expression shows 20,890 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRP, HNSC, and ACC as cancer lineages where STX6 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 STX6 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes STX6 survival associations across molecular data types. STX6 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (4) and 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 STX6 RNA expression–survival associations across cancer types. High STX6 expression shows unfavorable associations in KIRP, ACC, LIHC and PAAD, but favorable associations in OV and ESCA. 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 STX6 RNA expression.
This table summarizes STX6 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 6. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for STX6. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. STX6 shows higher tumor expression in HNSC, KIRC, BLCA, STAD, COAD and LIHC. The HNSC box plot shows higher STX6 RNA expression in tumor versus normal tissue (log2 FC = +1.316, t-test p < 0.001).
This table shows molecular features associated with STX6 in patient tissues and cancer cell lines. In patient samples, STX6 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, STX6 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in LUNG_SCLC and BLOOD_Leukemia.
