Q-omics provides the consensus-scored INTS6 profile across patient tissues and cancer cell-line models. INTS6 expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, INTS6 is differentially expressed in 10, with the highest sampling consensus in HNSC. Additionally, INTS6 RNA expression shows 20,519 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight ACC, HNSC, and UVM as cancer lineages where INTS6 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 INTS6 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes INTS6 survival associations across molecular data types. INTS6 RNA expression shows survival associations in the most cancer types (28), followed by mutation status (6) 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 INTS6 RNA expression–survival associations across cancer types. High INTS6 expression shows unfavorable associations in ACC, HNSC, ESCA and CESC, but favorable associations in KIRC and UCEC. 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 INTS6 RNA expression.
This table summarizes INTS6 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 7. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for INTS6. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. INTS6 shows lower tumor expression in THCA and KICH and higher tumor expression in HNSC, STAD, COAD and BRCA. The HNSC box plot shows higher INTS6 RNA expression in tumor versus normal tissue (log2 FC = +0.492, t-test p < 0.001).
This table shows molecular features associated with INTS6 in patient tissues and cancer cell lines. In patient samples, INTS6 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, INTS6 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_NSCLC_LUAD and BLOOD_Leukemia.
