Publications by authors named "Etai Jacob"

Cancer treatment has made significant advancements in recent decades, however many patients still experience treatment failure or resistance. Attempts to identify determinants of response have been hampered by a lack of tools that simultaneously accommodate smaller datasets, sparse or missing measurements, multimodal clinicogenomic data, and that can be interpreted to extract biological or clinical insights. We introduce the Clinical Transformer, an explainable transformer-based deep-learning framework that addresses these challenges.

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System-level patient health signals, as captured by treatment-emergent adverse events (TEAEs), might contain correlates of immune checkpoint inhibitor (ICI) therapy response. Using all TEAEs and a novel machine learning modeling approach, we derived a composite signature predictive of, and potentially specific to, the response to the anti-PD-L1 ICI durvalumab in patients with non-small-cell lung cancer (NSCLC). We trained on data from the durvalumab arm and chemotherapy arm in the MYSTIC clinical trial and tested on data from four independent durvalumab-containing NSCLC trials using only the first 60 days' TEAEs.

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Accurate survival prediction for Non-Small Cell Lung Cancer (NSCLC) patients remains a significant challenge for the scientific and clinical community despite decades of advanced analytics. Addressing this challenge not only helps inform the critical aspects of clinical study design and biomarker discovery but also ensures that the 'right patient' receives the 'right treatment'. However, survival prediction is a highly complex task, given the large number of 'omics; and clinical features, as well as the high degree of freedom that drive patient survival.

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Importance: The association between body composition (BC) and cancer outcomes is complex and incompletely understood. Previous research in non-small-cell lung cancer (NSCLC) has been limited to small, single-institution studies and yielded promising, albeit heterogeneous, results.

Objectives: To evaluate the association of BC with oncologic outcomes in patients receiving immunotherapy for advanced or metastatic NSCLC.

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The ability to accurately predict non-small cell lung cancer (NSCLC) patient survival is crucial for informing physician decision-making, and the increasing availability of multi-omics data offers the promise of enhancing prognosis predictions. We present a multimodal integration approach that leverages microRNA, mRNA, DNA methylation, long non-coding RNA (lncRNA) and clinical data to predict NSCLC survival and identify patient subtypes, utilizing denoising autoencoders for data compression and integration. Survival performance for patients with lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC) was compared across modality combinations and data integration methods.

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Article Synopsis
  • Transcriptional differences in cancer cells are influenced by changes in the epigenetic state of chromatin, impacting tumor evolution and drug resistance.
  • Micronuclei and chromosome bridges, common in cancer, can lead to lasting reductions in gene expression and change how genes are regulated even after returning to normal cells.
  • These changes may occur due to long-lasting DNA damage, linking epigenetic shifts in gene expression to chromosomal instability and issues in nuclear structure.
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The nuclear envelope (NE) undergoes dynamic remodeling to maintain NE integrity, a process involving the inner nuclear membrane protein LEM2 recruiting CHMP7/Cmp7 and then ESCRT-III. However, prior work has hinted at CHMP7/ESCRT-independent mechanisms. To identify such mechanisms, we studied NE assembly in Schizosaccharomyces japonicus, a fission yeast that undergoes partial mitotic NE breakdown and reassembly.

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Transforming growth factor-β (TGF-β) superfamily members are critical signals in tissue homeostasis and pathogenesis. Melanoma grows in the epidermis and invades the dermis before metastasizing. This disease progression is accompanied by increased sensitivity to microenvironmental TGF-β.

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Aberrant activation of innate immune receptors can cause a spectrum of immune disorders, such as Aicardi-Goutières syndrome (AGS). One such receptor is MDA5, a viral dsRNA sensor that induces antiviral immune response. Using a newly developed RNase-protection/RNA-seq approach, we demonstrate here that constitutive activation of MDA5 in AGS results from the loss of tolerance to cellular dsRNAs formed by Alu retroelements.

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Laminin, an ∼800-kDa heterotrimeric protein, is a major functional component of the extracellular matrix, contributing to tissue development and maintenance. The unique architecture of laminin is not currently amenable to determination at high resolution, as its flexible and narrow segments complicate both crystallization and single-particle reconstruction by electron microscopy. Therefore, we used cross-linking and MS, evaluated using computational methods, to address key questions regarding laminin quaternary structure.

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Methods for analysing correlated mutations in proteins are becoming an increasingly powerful tool for predicting contacts within and between proteins. Nevertheless, limitations remain due to the requirement for large multiple sequence alignments (MSA) and the fact that, in general, only the relatively small number of top-ranking predictions are reliable. To date, methods for analysing correlated mutations have relied exclusively on amino acid MSAs as inputs.

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Computational analysis of proteomes in all kingdoms of life reveals a strong tendency for N-terminal domains in two-domain proteins to have shorter sequences than their neighboring C-terminal domains. Given that folding rates are affected by chain length, we asked whether the tendency for N-terminal domains to be shorter than their neighboring C-terminal domains reflects selection for faster-folding N-terminal domains. Calculations of absolute contact order, another predictor of folding rate, provide additional evidence that N-terminal domains tend to fold faster than their neighboring C-terminal domains.

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Motivation: The folding of many proteins in vivo and in vitro is assisted by molecular chaperones. A well-characterized molecular chaperone system is the chaperonin GroEL/GroES from Escherichia coli which has a homolog found in the eukaryotic cytosol called CCT. All chaperonins have a ring structure with a cavity in which the substrate protein folds.

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Motivation: It is widely known that terminal residues of proteins (i.e. the N- and C-termini) are predominantly located on the surface of proteins and exposed to the solvent.

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