Q-omics provides the consensus-scored IGSF1 profile across patient tissues and cancer cell-line models. IGSF1 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in UCEC. Among the 18 cancer types available for tumor–normal comparison, IGSF1 is differentially expressed in 13, with the highest sampling consensus in THCA. Additionally, IGSF1 RNA expression shows 14,345 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight UCEC, THCA, and THYM as cancer lineages where IGSF1 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 IGSF1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes IGSF1 survival associations across molecular data types. IGSF1 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (11). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible IGSF1 RNA expression–survival associations across cancer types. High IGSF1 expression shows unfavorable associations in UCEC, STAD, LUAD and LIHC, but favorable associations in BRCA and SKCM. The UCEC 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 UCEC as the clearest survival context for IGSF1 RNA expression.
This table summarizes IGSF1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 1. The strongest signals are observed in THCA for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for IGSF1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. IGSF1 shows lower tumor expression in BRCA and UCEC and higher tumor expression in THCA, LUSC, LUAD and LIHC. The THCA box plot shows higher IGSF1 RNA expression in tumor versus normal tissue (log2 FC = +4.045, t-test p < 0.001).
This table shows molecular features associated with IGSF1 in patient tissues and cancer cell lines. In patient samples, IGSF1 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, IGSF1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Lymphoma, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUSC and LARGE_INTESTINE.
