Q-omics provides the consensus-scored FLOT2 profile across patient tissues and cancer cell-line models. FLOT2 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, FLOT2 is differentially expressed in 10, with the highest sampling consensus in KICH. Additionally, FLOT2 RNA expression shows 18,966 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and KICH as cancer lineages where FLOT2 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 FLOT2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes FLOT2 survival associations across molecular data types. FLOT2 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (3) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible FLOT2 RNA expression–survival associations across cancer types. High FLOT2 expression shows unfavorable associations in ACC, UVM, LIHC and LGG, but favorable associations in KIRC and THCA. 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 FLOT2 RNA expression.
This table summarizes FLOT2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 7. The strongest signals are observed in KICH for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for FLOT2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. FLOT2 shows lower tumor expression in KICH and higher tumor expression in KIRP, KIRC, HNSC, LIHC and THCA. The KICH box plot shows higher FLOT2 RNA expression in normal versus tumor tissue (log2 FC = −1.598, t-test p < 0.001).
This table shows molecular features associated with FLOT2 in patient tissues and cancer cell lines. In patient samples, FLOT2 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, FLOT2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in OESOPHAGUS and SOFT_TISSUE.
