Biology subjects

Pusztai, L.

Publications and source records attributed to Pusztai, L..

8 recordsLinked to original sources

bioRxiv2026

Distillation enables scalable high-fidelity virtual screening across ultra-large chemical libraries

Accurate virtual screening of ultra-large chemical libraries remains challenging. Existing approaches rely on lower-fidelity scoring functions or sampling-based strategies that can limit predictive accuracy and bias the exploration of chemical space. Here, we present FastBindRank, a distillation-based framework that transfers the predictive power of the structure-based model Boltz-2 into an efficient sequence-based surrogate. Trained on [~]1% of the 122-million-compound PubChem library, FastBindRank enables high-fidelity screening at scale. Applied to histone deacetylase 11 (HDAC11), FastBindRank substantially enriched high-confidence binders relative to the background chemical space. The lightweight model captured structural patterns associated with predicted binding, revealing structural determinants of binding. Under a comparable computational budget, FastBindRank achieved a 74-fold increase in hit rate and over a 30-fold increase in discovery yield over direct subset-based screening. Experimental validation confirmed the activity of two novel compounds. These results establish distillation as a practical strategy for scalable, high-fidelity virtual screening of ultra-large chemical libraries.

bioinformatics↗

bioRxiv2023

Dynamic clustering of genomics cohorts beyond race, ethnicity--and ancestry

BackgroundRecent decades have witnessed a steady decrease in the use of race categories in genomic studies. While studies that still include race categories vary in goal and type, these categories already build on a history during which racial color lines have been enforced and adjusted in the service of social and political systems of power and disenfranchisement. For early modern biological classification systems, data collection was also considerably arbitrary and limited. Fixed, discrete classifications have limited the study of human biodiversity and disrupted widely spread genetic and phenotypic continuums across geographic scales. Relatedly, the use of broad and predefined classification schemes--e.g. continent-based--across traits can risk missing important trait-specific genomic signals. ResultsTo address these issues, we introduce a dynamic approach to clustering human genomics cohorts on a trait-specific level and without using a set of predefined categories. We tested the approach on whole-exome sequencing datasets in ten cancer types and partitioned them based on germline variants in cancer-relevant genes that could confer cancer type-specific disease predisposition. Results demonstrate clustering patterns that transcend discrete continent-based categories across cancer types. Functional analysis based on cancer type-specific clusterings also captures the fundamental biological processes underlying cancer, differentiates between dynamic clusters on a functional level, and identifies novel potential drivers overlooked by a continent-based clustering model. ConclusionsThrough a trait-based lens, the dynamic clustering approach reveals genomic patterns that transcend predefined classification categories. We propose that coupled with diverse data collection, new clustering approaches have the potential to draw a more complete portrait of genomic variation and to address, in parallel, technical and social aspects of studying human biodiversity.

genomics↗

bioRxiv2022

Revisiting the bad luck hypothesis: Cancer risk and aging are linked to replication-driven changes to the epigenome

Aging is the leading risk factor for cancer. While its been proposed that the age-related accumulation of somatic mutations drives this relationship, it is likely not the full story. Here, we show that both aging and cancer share a common epigenetic replication signature, which we modeled from DNA methylation data in extensively passaged immortalized human cells in vitro and tested on clinical tissues. This epigenetic signature of replication - termed CellDRIFT - increased with age across multiple tissues, distinguished tumor from normal tissue, and was escalated in normal breast tissue from cancer patients. Additionally, within-person tissue differences were correlated with both predicted lifetime tissue-specific stem cell divisions and tissue-specific cancer risk. Overall, our findings suggest that age-related replication drives epigenetic changes in cells, pushing them towards a more tumorigenic state. One sentence summaryCellular replication leaves an epigenetic fingerprint that may partially underly the age-associated increase in cancer risk.

cancer biology↗

bioRxiv2021

A Network Propagation Approach to Prioritize Long Tail Genes in Cancer

IntroductionThe diversity of genomic alterations in cancer pose challenges to fully understanding the etiologies of the disease. Recent interest in infrequent mutations, in genes that reside in the "long tail" of the mutational distribution, uncovered new genes with significant implication in cancer development. The study of these genes often requires integrative approaches with multiple types of biological data. Network propagation methods have demonstrated high efficacy in uncovering genomic patterns underlying cancer using biological interaction networks. Yet, the majority of these analyses have focused their assessment on detecting known cancer genes or identifying altered subnetworks. In this paper, we introduce a network propagation approach that entirely focuses on long tail genes with potential functional impact on cancer development. ResultsWe identify sets of often overlooked, rarely to moderately mutated genes whose biological interactions significantly propel their mutation-frequency-based rank upwards during propagation in 17 cancer types. We call these sets "upward mobility genes" (UMGs, 28-83 genes per cancer type) and hypothesize that their significant rank improvement indicates functional importance. We report new cancer-pathway associations based on UMGs that were not previously identified using driver genes alone, validate UMGs role in cancer cell survival in vitro--alone and compared to other network methods--using extensive genome-wide RNAi and CRISPR data repositories, and further conduct in vitro functional screenings resulting the validation of 8 previously unreported genes. ConclusionOur analysis extends the spectrum of cancer relevant genes and identifies novel potential therapeutic targets.

bioinformatics↗

bioRxiv2021

Cancer relevance of human genes

BackgroundIt is unclear how many of genes contribute to the biology of cancer. We hypothesize that genes that interact with core cancer gene (CCG) in a protein-protein interaction network (PPI) may have functional importance. MethodsWe categorized genes into 1- (n=6791), 2- (n=7724), 3- (n=1587), and >3-steps (n=362) removed from the nearest CCG in the STRING PPI and demonstrate that the cancer-biology related functional contribution of the genes in these different neighborhood categories decreases as their distance from the CCGs increases. ResultsGenes closer to cancer genes manifest greater connectedness in the network, show greater importance in maintaining cell viability in a broad range of cancer cells in vitro, are also under greater negative germline selection pressure in the healthy populations, and have higher somatic mutation frequency and cancer effect. ConclusionsApproximately 70% of human genes are 1 or 2 steps removed from cancer genes in protein network and show functional importance in cancer-biology. These results suggest that the universe of cancer-relevant genes extends to thousands of genes that can contribute functional effects when dysregulated.

genomics↗

bioRxiv2020

CECR2 Drives Breast Cancer Metastasis by Suppressing Macrophage Inflammatory Responses

Epigenetic and transcriptional changes are critical for metastasis, the major cause of cancer-related deaths. Metastatic tumor cells escape immune surveillance more efficiently than tumor cells in the primary sites, but the mechanisms controlling their immune evasion are poorly understood. We found that distal metastases are more immune inert with increased M2 macrophages compared to their matched primary tumors. Acetyl-lysine reader CECR2 is an epigenetic regulator upregulated in metastases and positively associated with M2 macrophages. CECR2 specifically promotes breast cancer metastasis in multiple mouse models, with more profound effect in the immunocompetent setting. Mechanistically, NF-{kappa}B family member RELA recruits CECR2 to activate CSF1 and CXCL1, which are critical for macrophage-mediated immunosuppression at the metastatic sites. Furthermore, pharmacological inhibition of CECR2 bromodomain impedes NF-{kappa}B-mediated immune suppression by macrophages and inhibits breast cancer metastasis. These results reveal novel therapeutic strategies to treat metastatic breast cancer. Statement of SignificanceComparison of matched primary breast tumors and distal metastases show that metastases are more immune inert with increased tumor promoting macrophages. Depletion or pharmacological inhibition of CECR2 inhibits breast cancer metastasis by suppressing macrophage inflammatory responses, nominating CECR2 as a promising therapeutic target for cancer metastasis.

cancer biology↗

bioRxiv2020

Cancer-specific associations of driver genes with immunotherapy outcome

Genomic features such as microsatellite instability (MSI) and tumor mutation burden (TMB) are predictive of immune checkpoint inhibitor (ICI) response. However, they do not account for the functional effects of specific driver gene mutations, which may alter the immune microenvironment and influence immunotherapy outcomes. By analyzing a multi-cancer cohort of 1,525 ICI-treated patients, we identified 12 driver genes in 6 cancer types associated with treatment outcomes, including genes involved in oncogenic signaling pathways (NOTCH, WNT, FGFR) and chromatin remodeling. Mutations of PIK3CA, PBRM1, SMARCA4, and KMT2D were associated with worse outcomes across multiple cancer types. In comparison, genes showing cancer-specific associations--such as KEAP1, BRAF, and RNF43--harbored distinct variant types and variants, some of which were individually associated with outcomes. In colorectal cancer, a common RNF43 indel was a putative neoantigen associated with higher immune infiltration and favorable ICI outcomes. Finally, we showed that selected mutations were associated with PD-L1 status and could further stratify patient outcomes beyond MSI or TMB, highlighting their potential as biomarkers for immunotherapy.

genomics↗

bioRxiv2018

Reliability of Whole-Exome Sequencing for Assessing Intratumor Genetic Heterogeneity

Multi-region sequencing is used to detect intratumor genetic heterogeneity (ITGH) in tumors. To assess whether genuine ITGH can be distinguished from sequencing artifacts, we whole-exome sequenced (WES) three anatomically distinct regions of the same tumor with technical replicates to estimate technical noise. Somatic variants were detected with three different WES pipelines and subsequently validated by high-depth amplicon sequencing. The cancer-only pipeline was unreliable, with about 69% of the identified somatic variants being false positive. Even with matched normal DNA where 82% of the somatic variants were detected reliably, only 36%-78% were found consistently in technical replicate pairs. Overall 34%-80% of the discordant somatic variants, which could be interpreted as ITGH, were found to constitute technical noise. Excluding mutations affecting low mappability regions or occurring in certain mutational contexts was found to reduce artifacts, yet detection of subclonal mutations by WES in the absence of orthogonal validation remains unreliable.

genomics↗