Q-omics provides the consensus-scored INTS4P2 profile across patient tissues and cancer cell-line models. INTS4P2 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in READ. Among the 18 cancer types available for tumor–normal comparison, INTS4P2 is differentially expressed in 7, with the highest sampling consensus in KIRC. Additionally, INTS4P2 RNA expression shows 19,717 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight READ, KIRC, and THYM as cancer lineages where INTS4P2 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 INTS4P2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes INTS4P2 survival associations across molecular data types. INTS4P2 RNA expression shows survival associations in the most cancer types (21), followed by mutation status (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible INTS4P2 RNA expression–survival associations across cancer types. High INTS4P2 expression shows unfavorable associations in LUAD and CESC, but favorable associations in READ, UCS, SKCM and PAAD. The READ Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify READ as the clearest survival context for INTS4P2 RNA expression.
This table summarizes INTS4P2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 7. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for INTS4P2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. INTS4P2 shows lower tumor expression in UCEC and BLCA and higher tumor expression in KIRC, LIHC, CHOL and KIRP. The KIRC box plot shows higher INTS4P2 RNA expression in tumor versus normal tissue (log2 FC = +0.157, t-test p < 0.001).
This table shows molecular features associated with INTS4P2 in patient tissues and cancer cell lines. In patient samples, INTS4P2 shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, INTS4P2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUAD.
