Biology subjects

Bieniasz-Krzywiec, P.

Publications and source records attributed to Bieniasz-Krzywiec, P..

2 recordsLinked to original sources

bioRxiv2020

DNA Methylation Repels Binding of HIF Transcription Factors to Maintain Tumour Immunotolerance

AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSBackgroundC_ST_ABSHypoxia is pervasive in cancer and other diseases. Cells sense and adapt to hypoxia by activating hypoxia-inducible transcription factors (HIFs), but it is still an outstanding question why cell types differ in their transcriptional response to hypoxia. ResultsHere, we report that HIFs fail to bind CpG dinucleotides that are methylated in their consensus binding sequence, both in in vitro biochemical binding assays and in vivo studies of differentially methylated isogenic cell lines. Based on in silico structural modelling, we show that 5-methylcytosine indeed causes steric hindrance in the HIF binding pocket. A model wherein cell-type-specific methylation landscapes, as laid-down by the differential expression and binding of other transcription factors under normoxia control cell-type-specific hypoxia responses is observed. We also discover ectopic HIF binding sites in repeat regions which are normally methylated. Genetic and pharmacological DNA demethylation, but also cancer-associated DNA hypomethylation, expose these binding sites, inducing HIF-dependent expression of cryptic transcripts. In line with such cryptic transcripts being more prone to cause double-stranded RNA and viral mimicry, we observe low DNA methylation and high cryptic transcript expression in tumours with high immune checkpoint expression, but not in tumours with low immune checkpoint expression, where they would compromise tumour immunotolerance. In a low-immunogenic tumour model, DNA demethylation upregulates cryptic transcript expression in a HIF-dependent manner, causing immune activation and reducing tumour growth. ConclusionsOur data elucidate the mechanism underlying cell-type specific responses to hypoxia, and suggest DNA methylation and hypoxia to underlie tumour immunotolerance.

genomics↗

bioRxiv2018

Truncation and Motif Based Pan-Cancer Analysis Highlights Novel Tumor Suppressing Kinases.

A major challenge in cancer genomics is identifying driver mutations from the large number of neutral passenger mutations within a given tumor. Here, we utilize motifs critical for kinase activity to functionally filter genomic data to identify driver mutations that would otherwise be lost within mutational noise. In the first step of our screen, we define a putative tumor suppressing kinome by identifying kinases with truncation mutations occurring within or before the kinase domain. We aligned these kinase sequences and, utilizing data from the Cancer Cell Line Encyclopedia and The Cancer Genome Atlas databases, identified amino acids that represent predicted hotspots for loss-of-function mutations. The functional consequences of new LOF mutations were validated and the top 15 hotspot LOF residues were used in a pan-cancer analysis to define the tumor-suppressing kinome. A ranked list revealed MAP2K7 as a candidate tumor suppressor in gastric cancer, despite the mutational frequency of MAP2K7 falling within the mutational noise for this cancer type. The majority of mutations in MAP2K7 abolished catalytic activity compared to the wild type kinase, consistent with a tumor suppressive role for MAP2K7 in gastric cancer. Furthermore, reactivation of the JNK pathway in gastric cancer cells harboring LOF mutations in MAP2K7 or JNK1 suppresses clonogenicity and growth in soft agar, demonstrating the functional importance of inactivating the JNK pathway in gastric cancer. In summary, our data highlights a broadly applicable strategy to identify functional cancer driver mutations leading us to define the JNK pathway as tumor suppressive in gastric cancer.\n\nSummaryA unique computational pan-cancer analysis pinpoints novel tumor suppressing kinases, and highlights the power of functional genomics by defining the JNK pathway as tumor suppressive in gastric cancer.

cancer biology↗