Q-omics provides the consensus-scored SFXN2 profile across patient tissues and cancer cell-line models. SFXN2 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, SFXN2 is differentially expressed in 11, with the highest sampling consensus in KIRP. Additionally, SFXN2 RNA expression shows 19,099 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRC, KIRP, and UVM as cancer lineages where SFXN2 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 SFXN2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SFXN2 survival associations across molecular data types. SFXN2 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (4) 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 SFXN2 RNA expression–survival associations across cancer types. High SFXN2 expression shows unfavorable associations in UVM, but favorable associations in KIRC, BRCA, READ, LGG and KIRP. The KIRC 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 KIRC as the clearest survival context for SFXN2 RNA expression.
This table summarizes SFXN2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 4. The strongest signals are observed in KIRP for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for SFXN2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SFXN2 shows lower tumor expression in KIRP, THCA, KICH and KIRC and higher tumor expression in BRCA and COAD. The KIRP box plot shows higher SFXN2 RNA expression in normal versus tumor tissue (log2 FC = −2.325, t-test p < 0.001).
This table shows molecular features associated with SFXN2 in patient tissues and cancer cell lines. In patient samples, SFXN2 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, SFXN2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and BLOOD_Lymphoma.
