Q-omics provides the consensus-scored SFXN3 profile across patient tissues and cancer cell-line models. SFXN3 expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, SFXN3 is differentially expressed in 16, with the highest sampling consensus in HNSC. Additionally, SFXN3 protein abundance shows 27,006 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight UVM, HNSC, and LSCC as cancer lineages where SFXN3 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 SFXN3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SFXN3 survival associations across molecular data types. SFXN3 RNA expression shows survival associations in the most cancer types (28), followed by mutation status (2) 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 SFXN3 RNA expression–survival associations across cancer types. High SFXN3 expression shows unfavorable associations in UVM, HNSC, MESO, ACC, LAML and KICH. 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 SFXN3 RNA expression.
This table summarizes SFXN3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 6. The strongest signals are observed in KIRC for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for SFXN3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SFXN3 shows lower tumor expression in LUSC and higher tumor expression in HNSC, KIRC, COAD, KIRP and THCA. The HNSC box plot shows higher SFXN3 RNA expression in tumor versus normal tissue (log2 FC = +2.002, t-test p < 0.001).
This table shows molecular features associated with SFXN3 in patient tissues and cancer cell lines. In patient samples, SFXN3 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, SFXN3 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 SKIN and BLOOD_Lymphoma.
