Histone deacetylase inhibitors (HDACi) induce growth arrest and apoptosis in colon cancer cells and are being considered for colon cancer therapy. The underlying mechanism of action of these effects is poorly defined with both transcription-dependent and -independent mechanisms implicated. We screened a panel of 30 colon cancer cell lines for sensitivity to HDACi-induced apoptosis and correlated the differences with gene expression patterns induced by HDACi in the five most sensitive and resistant lines. A robust and reproducible transcriptional response involving coordinate induction of multiple immediate-early (fos, jun, egr1, egr3, atf3, arc, nr4a1) and stress response genes (Ndrg4, Mt1B, Mt1E, Mt1F, Mt1H) was selectively induced in HDACi sensitive cells. Notably, a significant percentage of these genes were basally repressed in colon tumors. Bioinformatics analysis revealed that the promoter regions of the HDACi-induced genes were enriched for KLF4/Sp1/Sp3 transcription factor binding sites. Altering KLF4 levels failed to modulate apoptosis or transcriptional responses to HDACi treatment. In contrast, HDACi preferentially stimulated the activity of Spl/Sp3 and blocking their action attenuated both the transcriptional and apoptotic responses to HDACi treatment. Our findings link HDACi-induced apoptosis to activation of a Spl/Sp3-mediated response that involves derepression of a transcriptional network basally repressed in colon cancer.

INTRODUCTION Tumor mutational burden (TMB) is a quantitative assessment of the number of somatic mutations within a tumor genome. Immunotherapy benefit has been associated with TMB assessed by whole exome sequencing (wesTMB) and by gene panel sequencing (psTMB). The initiatives of Quality in Pathology (QuIP) and Friends of Cancer Research (FoCR) have jointly addressed the need for harmonization between TMB testing options in tissues. This QuIP study identifies critical sources of variation in psTMB assessment. METHODS Twenty samples from three tumor types (LUAD, HNSC, COAD) with available WES data were analyzed for psTMB, using six panels across 15 testing centers. Inter-laboratory and inter-platform variation including agreement on variant calling and TMB classification were investigated. Bridging factors to transform psTMB to wesTMB values were empirically derived. The impact of germline filtering was evaluated. RESULTS Sixteen samples demonstrated low interlaboratory and interpanel psTMB variation with 87.7% of pairwise comparisons showing a Spearman's >0.6. A wesTMB cutpoint of 199 missense mutations projected to psTMB cutpoints between 7.8 and 12.6 muts/Mbp; the corresponding psTMB and wesTMB classifications agreed in 74.9% of cases. For three-tier classification with cutpoints of 100 and 300 mutations, agreement was observed in 76.7%, weak misclassification in 21.8%, and strong misclassification in 1.5% of cases. Confounders of psTMB estimation included fixation artifacts, DNA input, sequencing depth, genome coverage, and variant allele frequency cutpoints. CONCLUSIONS This study provides real-world evidence that all evaluated panels can be used to estimate TMB in a routine diagnostic setting and identifies important parameters for reliable tissue TMB assessment that require careful control. As complex/composite biomarkers beyond TMB are likely playing an increasing role in therapy prediction, the efforts by QuIP and FoCR also delineate a general framework and blueprint for the evaluation of such assays.