Q-omics provides the consensus-scored IQCA1L profile across patient tissues and cancer cell-line models. IQCA1L expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, IQCA1L is differentially expressed in 5, with the highest sampling consensus in BRCA. Additionally, IQCA1L RNA expression shows 9,570 significant gene co-expression associations, with the highest sampling consensus in SARC. Together, these results highlight ACC, BRCA, and SARC as cancer lineages where IQCA1L 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 IQCA1L — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes IQCA1L survival associations across molecular data types. IQCA1L RNA expression shows survival associations in the most cancer types (19). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible IQCA1L RNA expression–survival associations across cancer types. High IQCA1L expression shows unfavorable associations in ACC, LIHC, KIRC and ESCA, but favorable associations in SKCM and UVM. 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 IQCA1L RNA expression.
This table summarizes IQCA1L tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 5. The strongest signals are observed in BRCA for RNA.
This table ranks reproducible tumor–normal expression differences for IQCA1L. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. IQCA1L shows lower tumor expression in BRCA, THCA and COAD and higher tumor expression in UCEC and KIRC. The BRCA box plot shows higher IQCA1L RNA expression in normal versus tumor tissue (log2 FC = −0.022, t-test p = .001).
This table shows molecular features associated with IQCA1L in patient tissues and cancer cell lines. In patient samples, IQCA1L shows the broadest associations at the RNA and protein expression levels, with SARC recurring as the lineage with the largest associated feature set. In cancer cell lines, IQCA1L RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia.
