Q-omics provides the consensus-scored AIFM1 profile across patient tissues and cancer cell-line models. AIFM1 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, AIFM1 is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, AIFM1 protein abundance shows 18,290 significant protein co-abundance associations, with the highest sampling consensus in HNSC. Together, these results highlight UVM, and HNSC as cancer lineages where AIFM1 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 AIFM1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes AIFM1 survival associations across molecular data types. AIFM1 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (5) 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 AIFM1 RNA expression–survival associations across cancer types. High AIFM1 expression shows unfavorable associations in UVM and UCS, but favorable associations in KIRP, KIRC, READ and ACC. The UVM 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 UVM as the clearest survival context for AIFM1 RNA expression.
This table summarizes AIFM1 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 6. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for AIFM1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. AIFM1 shows lower tumor expression in THCA and higher tumor expression in HNSC, BLCA, LUAD, STAD and LUSC. The HNSC box plot shows higher AIFM1 RNA expression in tumor versus normal tissue (log2 FC = +0.637, t-test p < 0.001).
This table shows molecular features associated with AIFM1 in patient tissues and cancer cell lines. In patient samples, AIFM1 shows the broadest associations at the RNA and protein expression levels, with HNSC recurring as the lineage with the largest associated feature set. In cancer cell lines, AIFM1 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 URINARY_TRACT and UPPER_AERODIGESTIVE_TRACT.
