Q-omics provides the consensus-scored AIFM3 profile across patient tissues and cancer cell-line models. AIFM3 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in BLCA. Among the 18 cancer types available for tumor–normal comparison, AIFM3 is differentially expressed in 16, with the highest sampling consensus in KIRC. Additionally, AIFM3 RNA expression shows 16,630 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight BLCA, KIRC, and GBM as cancer lineages where AIFM3 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 AIFM3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes AIFM3 survival associations across molecular data types. AIFM3 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (10) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible AIFM3 RNA expression–survival associations across cancer types. High AIFM3 expression shows unfavorable associations in KIRC, KICH, UVM and UCS, but favorable associations in BLCA and READ. The BLCA Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify BLCA as the clearest survival context for AIFM3 RNA expression.
This table summarizes AIFM3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for AIFM3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. AIFM3 shows lower tumor expression in COAD and higher tumor expression in KIRC, STAD, LIHC, KICH and HNSC. The KIRC box plot shows higher AIFM3 RNA expression in tumor versus normal tissue (log2 FC = +0.209, t-test p < 0.001).
This table shows molecular features associated with AIFM3 in patient tissues and cancer cell lines. In patient samples, AIFM3 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, AIFM3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and LARGE_INTESTINE.
