Q-omics provides the consensus-scored SPATC1L profile across patient tissues and cancer cell-line models. SPATC1L expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, SPATC1L is differentially expressed in 11, with the highest sampling consensus in LIHC. Additionally, SPATC1L RNA expression shows 13,344 significant gene co-expression associations, with the highest sampling consensus in LIHC. Together, these results highlight KIRC, and LIHC as cancer lineages where SPATC1L 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 SPATC1L — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SPATC1L survival associations across molecular data types. SPATC1L RNA expression shows survival associations in the most cancer types (23), 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 SPATC1L RNA expression–survival associations across cancer types. High SPATC1L expression shows unfavorable associations in KIRC, READ, LIHC and LGG, but favorable associations in UCS and PAAD. The KIRC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .002). Together, the overview and detailed table identify KIRC as the clearest survival context for SPATC1L RNA expression.
This table summarizes SPATC1L tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11. The strongest signals are observed in LIHC for RNA.
This table ranks reproducible tumor–normal expression differences for SPATC1L. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SPATC1L shows higher tumor expression in LIHC, LUAD, LUSC, HNSC, BRCA and CHOL. The LIHC box plot shows higher SPATC1L RNA expression in tumor versus normal tissue (log2 FC = +2.176, t-test p < 0.001).
This table shows molecular features associated with SPATC1L in patient tissues and cancer cell lines. In patient samples, SPATC1L shows the broadest associations at the RNA and protein expression levels, with LIHC recurring as the lineage with the largest associated feature set. In cancer cell lines, SPATC1L RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in OESOPHAGUS and BLOOD_Leukemia.
