Ab initio identification of putative human transcription factor binding sites by comparative genomics

Background

Understanding transcriptional regulation of gene expression is one of the greatest challenges of modern molecular biology. A central role in this mechanism is played by transcription factors, which typically bind to specific, short DNA sequence motifs usually located in the upstream region of the regulated genes. We discuss here a simple and powerful approach for the ab initio identification of these cis-regulatory motifs. The method we present integrates several elements: human-mouse comparison, statistical analysis of genomic sequences and the concept of coregulation. We apply it to a complete scan of the human genome.

Results

By using the catalogue of conserved upstream sequences collected in the CORG database we construct sets of genes sharing the same overrepresented motif (short DNA sequence) in their upstream regions both in human and in mouse. We perform this construction for all possible motifs from 5 to 8 nucleotides in length and then filter the resulting sets looking for two types of evidence of coregulation: first, we analyze the Gene Ontology annotation of the genes in the set, searching for statistically significant common annotations; second, we analyze the expression profiles of the genes in the set as measured by microarray experiments, searching for evidence of coexpression. The sets which pass one or both filters are conjectured to contain a significant fraction of coregulated genes, and the upstream motifs characterizing the sets are thus good candidates to be the binding sites of the TF's involved in such regulation.

In this way we find various known motifs and also some new candidate binding sites.

Conclusion

We have discussed a new integrated algorithm for the "ab initio" identification of transcription factor binding sites in the human genome. The method is based on three ingredients: comparative genomics, overrepresentation, different types of coregulation. The method is applied to a full-scan of the human genome, giving satisfactory results.

Consensus clustering methodology to improve molecular stratification of non-small cell lung cancer

Recent advances in machine learning research, combined with the reduced sequencing costs enabled by modern next-generation sequencing, paved the way to the implementation of precision medicine through routine multi-omics molecular profiling of tumours. Thus, there is an emerging need of reliable models exploiting such data to retrieve clinically useful information. Here, we introduce an original consensus clustering approach, overcoming the intrinsic instability of common clustering methods based on molecular data. This approach is applied to the case of non-small cell lung cancer (NSCLC), integrating data of an ongoing clinical study (PROMOLE) with those made available by The Cancer Genome Atlas, to define a molecular-based stratification of the patients beyond, but still preserving, histological subtyping. The resulting subgroups are biologically characterized by well-defined mutational and gene-expression profiles and are significantly related to disease-free survival (DFS). Interestingly, it was observed that (1) cluster B, characterized by a short DFS, is enriched in KEAP1 and SKP2 mutations, that makes it an ideal candidate for further studies with inhibitors, and (2) over- and under-representation of inflammation and immune systems pathways in squamous-cell carcinomas subgroups could be potentially exploited to stratify patients treated with immunotherapy.

OS06.3A LSD1-directed therapy curtails glioblastoma tumorigenicity by limiting the adaptation of tumor initiating cells to stressful environments

BACKGROUND

Glioblastoma (GBM) is a fatal tumor whose aggressiveness, heterogeneity, therapy resistance and poor blood-brain-barrier penetration hinder the amelioration of the standard-of-care. Included in the GBM mass are the tumor initiating cells (TICs), representing the driver of GBM growth and relapse in virtue of their stem-like traits and therapy-resistance. Being constantly exposed to environmental stress, including nutrients deficiency, hypoxia and therapeutic insults, all GBM cells -and TICs in particular- have to be highly adaptive in order to survive. Thus, their ability to cope with stress could be targeted to curtail TICs maintenance and the whole GBM aggressiveness. The key of TICs adaptation relies, among the others, on their epigenetic plasticity, hence encouraging epigenetic drugs testing.

MATERIAL AND METHODS

By exploiting patient-derived GBM TICs and orthotopic xenograft models, we tested the antitumorigenic features of a novel, selective, orally bioavailable and brain-penetrant Lysine-specific histone demethylase 1 inhibitor (LSD1i). We confirmed the specificity of its effects by LSD1 genetic targeting. A combination of RNA-seq, Chromatin Immunoprecipitation(ChIP)-seq, Mass Spectrometry and reverse genetic experiments unraveled LSD1 molecular players in GBM TICs.

RESULTS

We identified LSD1 as a druggable target in human GBM: LSD1i treatment, mirrored by LSD1 genetic targeting, impairs growth, viability, stem-like traits and in vivo tumorigenicity of GBM TICs. Mechanistically, LSD1 is crucial for the expression of the activating transcription factor 4 (ATF4), which coordinates the integrated stress response (ISR) to manage stressful stimuli as nutrient deprivation and endoplasmic reticulum stress. By mimicking these stress cues in vitro, we found that LSD1i triggers a delayed but unabated ATF4 translation which provokes an over-lasting ISR, eventually culminating in GBM TICs apoptosis. Lastly, LSD1 demethylase activity is dispensable for ATF4 induction. Rather, LSD1i exerts its anti-tumorigenic potential by interfering with LSD1 scaffolding function in GBM TICs.

CONCLUSION

LSD1-directed therapy is likely a promising strategy to hinder GBM. By sensitizing GBM TICs to stress, LSD1i endangers the GBM TICs pool. The effectiveness of LSD1i administration in different patient-derived GBM TICs and xenografts, regardless of their molecular profile, places a strong rationale toward the clinical translation of this approach for GBM management.

FUNDING

Italian association for Cancer Research (AIRC) and Italian Ministry of Health

TFEB inhibition induces melanoma shut-down by blocking the cell cycle and rewiring metabolism

Melanomas are characterised by accelerated cell proliferation and metabolic reprogramming resulting from the contemporary dysregulation of the MAPK pathway, glycolysis and the tricarboxylic acid (TCA) cycle. Here, we suggest that the oncogenic transcription factor EB (TFEB), a key regulator of lysosomal biogenesis and function, controls melanoma tumour growth through a transcriptional programme targeting ERK1/2 activity and glucose, glutamine and cholesterol metabolism. Mechanistically, TFEB binds and negatively regulates the promoter of DUSP-1, which dephosphorylates ERK1/2. In melanoma cells, TFEB silencing correlates with ERK1/2 dephosphorylation at the activation-related p-Thr185 and p-Tyr187 residues. The decreased ERK1/2 activity synergises with TFEB control of CDK4 expression, resulting in cell proliferation blockade. Simultaneously, TFEB rewires metabolism, influencing glycolysis, glucose and glutamine uptake, and cholesterol synthesis. In TFEB-silenced melanoma cells, cholesterol synthesis is impaired, and the uptake of glucose and glutamine is inhibited, leading to a reduction in glycolysis, glutaminolysis and oxidative phosphorylation. Moreover, the reduction in TFEB level induces reverses TCA cycle, leading to fatty acid production. A syngeneic BRAFV600E melanoma model recapitulated the in vitro study results, showing that TFEB silencing sustains the reduction in tumour growth, increase in DUSP-1 level and inhibition of ERK1/2 action, suggesting a pivotal role for TFEB in maintaining proliferative melanoma cell behaviour and the operational metabolic pathways necessary for meeting the high energy demands of melanoma cells.