Q-omics provides the consensus-scored FLII profile across patient tissues and cancer cell-line models. FLII expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, FLII is differentially expressed in 11, with the highest sampling consensus in KIRP. Additionally, FLII protein abundance shows 27,071 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight ACC, KIRP, and GBM as cancer lineages where FLII 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 FLII — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes FLII survival associations across molecular data types. FLII RNA expression shows survival associations in the most cancer types (26), followed by mutation status (7) 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 FLII RNA expression–survival associations across cancer types. High FLII expression shows unfavorable associations in ACC, LGG and MESO, but favorable associations in SCLC, BRCA and KIRC. The ACC 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 ACC as the clearest survival context for FLII RNA expression.
This table summarizes FLII 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 6. The strongest signals are observed in THCA for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for FLII. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. FLII shows higher tumor expression in KIRP, THCA, KIRC, LIHC, HNSC and CHOL. The KIRP box plot shows higher FLII RNA expression in tumor versus normal tissue (log2 FC = +1.559, t-test p < 0.001).
This table shows molecular features associated with FLII in patient tissues and cancer cell lines. In patient samples, FLII 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, FLII 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_Leukemia.
