Q-omics provides the consensus-scored SFXN4 profile across patient tissues and cancer cell-line models. SFXN4 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, SFXN4 is differentially expressed in 14, with the highest sampling consensus in KIRC. Additionally, SFXN4 RNA expression shows 18,022 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight UVM, KIRC, and LSCC as cancer lineages where SFXN4 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 SFXN4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SFXN4 survival associations across molecular data types. SFXN4 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (7) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SFXN4 RNA expression–survival associations across cancer types. High SFXN4 expression shows unfavorable associations in UVM, LIHC, CESC and KICH, but favorable associations in MESO and KIRP. 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 SFXN4 RNA expression.
This table summarizes SFXN4 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 4. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for SFXN4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SFXN4 shows lower tumor expression in THCA and higher tumor expression in KIRC, LUAD, LUSC, LIHC and STAD. The KIRC box plot shows higher SFXN4 RNA expression in tumor versus normal tissue (log2 FC = +0.621, t-test p < 0.001).
This table shows molecular features associated with SFXN4 in patient tissues and cancer cell lines. In patient samples, SFXN4 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, SFXN4 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in KIDNEY, while CRISPR and shRNA rows add functional-dependency signals in BONE and CNS.
