Enabling population protein dynamics through Bayesian modeling.

Motivation: The knowledge of protein dynamics, or turnover, in patients provides invaluable information related to certain diseases, drug efficacy, or biological processes. A great corpus of experimental and computational methods has been developed, including by us, in the case of human patients followed in vivo. Moving one step further, we propose a novel modeling approach to capture population protein dynamics using Bayesian methods.

Farnesyltransferase inhibition overcomes oncogene-addicted non-small cell lung cancer adaptive resistance to targeted therapies.

Drug-tolerance has emerged as one of the major non-genetic adaptive processes driving resistance to targeted therapy (TT) in non-small cell lung cancer (NSCLC). However, the kinetics and sequence of molecular events governing this adaptive response remain poorly understood. Here, we combine real-time monitoring of the cell-cycle dynamics and single-cell RNA sequencing in a broad panel of oncogenic addiction such as EGFR-, ALK-, BRAF- and KRAS-mutant NSCLC, treated with their corresponding TT.

Modeling the Simultaneous Dynamics of Proteins in Blood Plasma and the Cerebrospinal Fluid in Human .

The analysis of protein dynamics or turnover in patients has the potential to reveal altered protein recycling, such as in Alzheimer's disease, and to provide informative data regarding drug efficacy or certain biological processes. The observed protein dynamics in a solid tissue or a fluid is the net result of not only protein synthesis and degradation but also transport across biological compartments. We report an accurate 3-biological compartment model able to simultaneously account for the protein dynamics observed in blood plasma and the cerebrospinal fluid (CSF) including a hidden central nervous system (CNS) compartment.

Prediction of response to promising first-line chemotherapy in ovarian cancer patients with residual peritoneal tumors: practical biomarkers and robust multiplex models.

Background: Platinum/taxane (TC) chemotherapy with debulking surgery stays the mainstay of the treatment in ovarian cancer patients with peritoneal metastasis, and recently its novel modality, intraperitoneal carboplatin with dose-dense paclitaxel (ddTCip), was shown to have greater therapeutic impact. Nevertheless, the response varies among patients and consequent recurrence, or relapse often occurs. Discovery of therapeutic response predictor to ddTCip and/or TC therapy is eagerly awaited to improve the treatment outcome.

Cancer-associated fibroblast spatial heterogeneity and expression in the tumor microenvironment modulate TGF-β activity and CD8 T-cell infiltration in breast cancer.

The tumor microenvironment (TME) and its multifaceted interactions with cancer cells are major targets for cancer treatment. Single-cell technologies have brought major insights into the TME, but the resulting complexity often precludes conclusions on function. We combined single-cell RNA sequencing and spatial transcriptomic data to explore the relationship between different cancer-associated fibroblast (CAF) populations and immune cell exclusion in breast tumors.

Circulating DNA reveals a specific and higher fragmentation of the Y chromosome.

Chromosome stability is a key point in genome evolution, particularly that of the Y chromosome. The Y chromosome loss in blood and tumor cells is well established. Through processes that are common to other chromosomes too, the Y chromosome undergoes degradation and fragmentation in the blood stream before elimination.

Design and selection of optimal ErbB-targeting bispecific antibodies in pancreatic cancer.

The ErbB family of receptor tyrosine kinases is a primary target for small molecules and antibodies for pancreatic cancer treatment. Nonetheless, the current treatments for this tumor are not optimal due to lack of efficacy, resistance, or toxicity. Here, using the novel BiXAb™ tetravalent format platform, we generated bispecific antibodies against EGFR, HER2, or HER3 by considering rational epitope combinations.

Inferring ligand-receptor cellular networks from bulk and spatial transcriptomic datasets with BulkSignalR.

The study of cellular networks mediated by ligand-receptor interactions has attracted much attention recently owing to single-cell omics. However, rich collections of bulk data accompanied with clinical information exists and continue to be generated with no equivalent in single-cell so far. In parallel, spatial transcriptomic (ST) analyses represent a revolutionary tool in biology.

Modular response analysis reformulated as a multilinear regression problem.

Motivation: Modular response analysis (MRA) is a well-established method to infer biological networks from perturbation data. Classically, MRA requires the solution of a linear system, and results are sensitive to noise in the data and perturbation intensities. Due to noise propagation, applications to networks of 10 nodes or more are difficult.

FT-GPI, a highly sensitive and accurate predictor of GPI-anchored proteins, reveals the composition and evolution of the GPI proteome in Plasmodium species.

Background: Protozoan parasites are known to attach specific and diverse group of proteins to their plasma membrane via a GPI anchor. In malaria parasites, GPI-anchored proteins (GPI-APs) have been shown to play an important role in host-pathogen interactions and a key function in host cell invasion and immune evasion. Because of their immunogenic properties, some of these proteins have been considered as malaria vaccine candidates.

The landscape of cancer-associated fibroblasts in colorectal cancer liver metastases.

Patients with colorectal cancer die mainly due to liver metastases (CRC-LM). Although the tumor microenvironment (TME) plays an important role in tumor development and therapeutic response, our understanding of the individual TME components, especially cancer-associated fibroblasts (CAFs), remains limited. We analyzed CRC-LM CAFs and cancer cells by single-cell transcriptomics and used bioinformatics for data analysis and integration with related available single-cell and bulk transcriptomic datasets.

Mechanical signatures of human colon cancers.

Besides the standard parameters used for colorectal cancer (CRC) management, new features are needed in clinical practice to improve progression-free and overall survival. In some cancers, the microenvironment mechanical properties can contribute to cancer progression and metastasis formation, or constitute a physical barrier for drug penetration or immune cell infiltration. These mechanical properties remain poorly known for colon tissues.

Application of modular response analysis to medium- to large-size biological systems.

The development of high-throughput genomic technologies associated with recent genetic perturbation techniques such as short hairpin RNA (shRNA), gene trapping, or gene editing (CRISPR/Cas9) has made it possible to obtain large perturbation data sets. These data sets are invaluable sources of information regarding the function of genes, and they offer unique opportunities to reverse engineer gene regulatory networks in specific cell types. Modular response analysis (MRA) is a well-accepted mathematical modeling method that is precisely aimed at such network inference tasks, but its use has been limited to rather small biological systems so far.

Mechanisms underlying the cooperation between loss of epithelial polarity and Notch signaling during neoplastic growth in Drosophila.

Aggressive neoplastic growth can be initiated by a limited number of genetic alterations, such as the well-established cooperation between loss of cell architecture and hyperactive signaling pathways. However, our understanding of how these different alterations interact and influence each other remains very incomplete. Using Drosophila paradigms of imaginal wing disc epithelial growth, we have monitored the changes in Notch pathway activity according to the polarity status of cells (scrib mutant).

Detection of soluble biomarkers of pancreatic cancer in endoscopic ultrasound-guided fine-needle aspiration samples.

Background: Biomarkers are urgently needed for pancreatic ductal adenocarcinoma (PDAC). Endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) is the cornerstone for diagnosing PDAC. We developed a method for discovery of PDAC biomarkers using the discarded EUS-FNA liquid.

An R package for generic modular response analysis and its application to estrogen and retinoic acid receptor crosstalk.

Modular response analysis (MRA) is a widely used inference technique developed to uncover directions and strengths of connections in molecular networks under a steady-state condition by means of perturbation experiments. We devised several extensions of this methodology to search genomic data for new associations with a biological network inferred by MRA, to improve the predictive accuracy of MRA-inferred networks, and to estimate confidence intervals of MRA parameters from datasets with low numbers of replicates. The classical MRA computations and their extensions were implemented in a freely available R package called aiMeRA ( https://github.

Transcriptomic and genomic heterogeneity in blastic plasmacytoid dendritic cell neoplasms: from ontogeny to oncogenesis.

Oncogenesis and ontogeny of blastic plasmacytoid dendritic cell neoplasm (BPDCN) remain uncertain, between canonical plasmacytoid dendritic cells (pDCs) and AXL+ SIGLEC6+ DCs (AS-DCs). We compared 12 BPDCN to 164 acute leukemia by Affymetrix HG-U133 Plus 2.0 arrays: BPDCN were closer to B-cell acute lymphoblastic leukemia (ALL), with enrichment in pDC, B-cell signatures, vesicular transport, deubiquitination pathways, and AS-DC signatures, but only in some cases.

The immune contexture of primary central nervous system diffuse large B cell lymphoma associates with patient survival and specific cell signaling.

Primary central nervous system diffuse large B-cell lymphoma (PCNSL) is a rare and aggressive entity that resides in an immune-privileged site. The tumor microenvironment (TME) and the disruption of the immune surveillance influence lymphoma pathogenesis and immunotherapy resistance. Despite growing knowledge on heterogeneous therapeutic responses, no comprehensive description of the PCNSL TME is available.

Machine Learning-Assisted Evaluation of Circulating DNA Quantitative Analysis for Cancer Screening.

While the utility of circulating cell-free DNA (cfDNA) in cancer screening and early detection have recently been investigated by testing genetic and epigenetic alterations, here, an original approach by examining cfDNA quantitative and structural features is developed. First, the potential of cfDNA quantitative and structural parameters is independently demonstrated in cell culture, murine, and human plasma models. Subsequently, these variables are evaluated in a large retrospective cohort of 289 healthy individuals and 983 patients with various cancer types; after age resampling, this evaluation is done independently and the variables are combined using a machine learning approach.

The molecular landscape and microenvironment of salivary duct carcinoma reveal new therapeutic opportunities.

: Salivary duct carcinoma (SDC) is a rare and aggressive salivary gland cancer subtype with poor prognosis. The mutational landscape of SDC has already been the object of several studies, however little is known regarding the functional genomics and the tumor microenvironment despite their importance in oncology. Our investigation aimed at describing both the functional genomics of SDC and the SDC microenvironment, along with their clinical relevance.

SingleCellSignalR: inference of intercellular networks from single-cell transcriptomics.

Single-cell transcriptomics offers unprecedented opportunities to infer the ligand-receptor (LR) interactions underlying cellular networks. We introduce a new, curated LR database and a novel regularized score to perform such inferences. For the first time, we try to assess the confidence in predicted LR interactions and show that our regularized score outperforms other scoring schemes while controlling false positives.

In Vivo Large-Scale Mapping of Protein Turnover in Human Cerebrospinal Fluid.

The extraction of accurate physiological parameters from clinical samples provides a unique perspective to understand disease etiology and evolution, including under therapy. We introduce a new methodologic framework to map patient proteome dynamics in vivo, either proteome-wide or in large targeted panels. We applied it to ventricular cerebrospinal fluid (CSF) and could determine the turnover parameters of almost 200 proteins, whereas a handful were known previously.

Notch inhibition overcomes resistance to tyrosine kinase inhibitors in EGFR-driven lung adenocarcinoma.

EGFR-mutated lung adenocarcinoma patients treated with gefitinib and osimertinib show a therapeutic benefit limited by the appearance of secondary mutations, such as EGFRT790M and EGFRC797S. It is generally assumed that these secondary mutations render EGFR completely unresponsive to the inhibitors, but contrary to this, we uncovered here that gefitinib and osimertinib increased STAT3 phosphorylation (p-STAT3) in EGFRT790M and EGFRC797S tumoral cells. Interestingly, we also found that concomitant Notch inhibition with gefitinib or osimertinib treatment induced a p-STAT3-dependent strong reduction in the levels of the transcriptional repressor HES1.