Q-omics provides the consensus-scored INTS2 profile across patient tissues and cancer cell-line models. INTS2 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, INTS2 is differentially expressed in 15, with the highest sampling consensus in KIRP. Additionally, INTS2 protein abundance shows 28,117 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight KIRC, KIRP, and LSCC as cancer lineages where INTS2 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 INTS2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes INTS2 survival associations across molecular data types. INTS2 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (10) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible INTS2 RNA expression–survival associations across cancer types. High INTS2 expression shows unfavorable associations in CESC, LIHC, THCA and KIRP, but favorable associations in KIRC and UCS. The KIRC 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 KIRC as the clearest survival context for INTS2 RNA expression.
This table summarizes INTS2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 8. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for INTS2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. INTS2 shows lower tumor expression in THCA and higher tumor expression in KIRP, HNSC, BLCA, KIRC and LIHC. The KIRP box plot shows higher INTS2 RNA expression in tumor versus normal tissue (log2 FC = +1.015, t-test p < 0.001).
This table shows molecular features associated with INTS2 in patient tissues and cancer cell lines. In patient samples, INTS2 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, INTS2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in SKIN and BLOOD_Leukemia.
