Q-omics provides the consensus-scored SLX4 profile across patient tissues and cancer cell-line models. SLX4 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, SLX4 is differentially expressed in 15, with the highest sampling consensus in HNSC. Additionally, SLX4 RNA expression shows 19,619 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight MESO, HNSC, and UVM as cancer lineages where SLX4 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 SLX4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SLX4 survival associations across molecular data types. SLX4 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (11) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SLX4 RNA expression–survival associations across cancer types. High SLX4 expression shows unfavorable associations in MESO, KIRC, LGG, LIHC and LUSC, but favorable associations in HNSC. The MESO 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 MESO as the clearest survival context for SLX4 RNA expression.
This table summarizes SLX4 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 3. The strongest signals are observed in KIRC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for SLX4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SLX4 shows higher tumor expression in HNSC, KIRP, KIRC, COAD, LIHC and STAD. The HNSC box plot shows higher SLX4 RNA expression in tumor versus normal tissue (log2 FC = +0.889, t-test p < 0.001).
This table shows molecular features associated with SLX4 in patient tissues and cancer cell lines. In patient samples, SLX4 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, SLX4 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 UPPER_AERODIGESTIVE_TRACT and BLOOD_Lymphoma.
