immunoglobulin superfamily member 9Genealiases: FP18798 · IGSF9A · Nrt1
Q-omics provides the consensus-scored IGSF9 profile across patient tissues and cancer cell-line models. IGSF9 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, IGSF9 is differentially expressed in 13, with the highest sampling consensus in KIRC. Additionally, IGSF9 RNA expression shows 16,163 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight ACC, KIRC, and TGCT as cancer lineages where IGSF9 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 IGSF9 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes IGSF9 survival associations across molecular data types. IGSF9 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (7) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible IGSF9 RNA expression–survival associations across cancer types. High IGSF9 expression shows unfavorable associations in ACC, SKCM, LGG and LUAD, but favorable associations in HNSC and LUSC. 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 IGSF9 RNA expression.
This table summarizes IGSF9 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 4. The strongest signals are observed in KIRC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for IGSF9. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. IGSF9 shows lower tumor expression in KIRC and COAD and higher tumor expression in BLCA, HNSC, LUSC and LUAD. The KIRC box plot shows higher IGSF9 RNA expression in normal versus tumor tissue (log2 FC = −0.693, t-test p < 0.001).
This table shows molecular features associated with IGSF9 in patient tissues and cancer cell lines. In patient samples, IGSF9 shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, IGSF9 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in OVARY and BONE.
