Q-omics provides the consensus-scored FHIT profile across patient tissues and cancer cell-line models. FHIT expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, FHIT is differentially expressed in 13, with the highest sampling consensus in KIRC. Additionally, FHIT protein abundance shows 26,607 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRP, KIRC, and GBM as cancer lineages where FHIT 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 FHIT — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes FHIT survival associations across molecular data types. FHIT RNA expression shows survival associations in the most cancer types (23), followed by mutation status (3) 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 FHIT RNA expression–survival associations across cancer types. High FHIT expression shows favorable associations in KIRP, ACC, BRCA, UVM, MESO and HNSC. The KIRP 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 KIRP as the clearest survival context for FHIT RNA expression.
This table summarizes FHIT tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, 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 FHIT. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. FHIT shows lower tumor expression in KIRC, HNSC, THCA, KICH and BRCA and higher tumor expression in LIHC. The KIRC box plot shows higher FHIT RNA expression in normal versus tumor tissue (log2 FC = −0.785, t-test p < 0.001).
This table shows molecular features associated with FHIT in patient tissues and cancer cell lines. In patient samples, FHIT 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, FHIT RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and BREAST.
