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Alemanno F, Cavo M, Delle Cave D, Fachechi A, Rizzo R, D’Amone E, Gigli G, Lonardo E, Barra A, del Mercato LL. Quantifying heterogeneity to drug response in cancer-stroma kinetics. Proc Natl Acad Sci U S A 2023; 120:e2122352120. [PMID: 36897966 PMCID: PMC10089157 DOI: 10.1073/pnas.2122352120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Accepted: 02/04/2023] [Indexed: 03/12/2023] Open
Abstract
A crucial challenge in medicine is choosing which drug (or combination) will be the most advantageous for a particular patient. Usually, drug response rates differ substantially, and the reasons for this response unpredictability remain ambiguous. Consequently, it is central to classify features that contribute to the observed drug response variability. Pancreatic cancer is one of the deadliest cancers with limited therapeutic achievements due to the massive presence of stroma that generates an environment that enables tumor growth, metastasis, and drug resistance. To understand the cancer-stroma cross talk within the tumor microenvironment and to develop personalized adjuvant therapies, there is a necessity for effective approaches that offer measurable data to monitor the effect of drugs at the single-cell level. Here, we develop a computational approach, based on cell imaging, that quantifies the cellular cross talk between pancreatic tumor cells (L3.6pl or AsPC1) and pancreatic stellate cells (PSCs), coordinating their kinetics in presence of the chemotherapeutic agent gemcitabine. We report significant heterogeneity in the organization of cellular interactions in response to the drug. For L3.6pl cells, gemcitabine sensibly decreases stroma-stroma interactions but increases stroma-cancer interactions, overall enhancing motility and crowding. In the AsPC1 case, gemcitabine promotes the interactions among tumor cells, but it does not affect stroma-cancer interplay, possibly suggesting a milder effect of the drug on cell dynamics.
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Affiliation(s)
- Francesco Alemanno
- Institute of Nanotechnology, National Research Council, Lecce73100, Italy
- Dipartimento di Matematica e Fisica Ennio De Giorgi, Università del Salento, Lecce73100, Italy
| | - Marta Cavo
- Institute of Nanotechnology, National Research Council, Lecce73100, Italy
| | - Donatella Delle Cave
- Institute of Genetics and Biophysics Adriano Buzzati-Traverso, CNR, Naples80131, Italy
| | - Alberto Fachechi
- Dipartimento di Matematica Guido Castelnuovo, Sapienza Università di Roma, Rome00185, Italy
| | - Riccardo Rizzo
- Institute of Nanotechnology, National Research Council, Lecce73100, Italy
| | - Eliana D’Amone
- Institute of Nanotechnology, National Research Council, Lecce73100, Italy
| | - Giuseppe Gigli
- Institute of Nanotechnology, National Research Council, Lecce73100, Italy
- Dipartimento di Matematica e Fisica Ennio De Giorgi, Università del Salento, Lecce73100, Italy
| | - Enza Lonardo
- Institute of Genetics and Biophysics Adriano Buzzati-Traverso, CNR, Naples80131, Italy
| | - Adriano Barra
- Dipartimento di Matematica e Fisica Ennio De Giorgi, Università del Salento, Lecce73100, Italy
- Istituto Nazionale di Fisica Nucleare, Sezione di Lecce, Lecce73100, Italy
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Garibo-I-Orts Ò, Firbas N, Sebastiá L, Conejero JA. Gramian angular fields for leveraging pretrained computer vision models with anomalous diffusion trajectories. Phys Rev E 2023; 107:034138. [PMID: 37072993 DOI: 10.1103/physreve.107.034138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Accepted: 02/28/2023] [Indexed: 04/20/2023]
Abstract
Anomalous diffusion is present at all scales, from atomic to large ones. Some exemplary systems are ultracold atoms, telomeres in the nucleus of cells, moisture transport in cement-based materials, arthropods' free movement, and birds' migration patterns. The characterization of the diffusion gives critical information about the dynamics of these systems and provides an interdisciplinary framework with which to study diffusive transport. Thus, the problem of identifying underlying diffusive regimes and inferring the anomalous diffusion exponent α with high confidence is critical to physics, chemistry, biology, and ecology. Classification and analysis of raw trajectories combining machine learning techniques with statistics extracted from them have widely been studied in the Anomalous Diffusion Challenge [Muñoz-Gil et al., Nat. Commun. 12, 6253 (2021)2041-172310.1038/s41467-021-26320-w]. Here we present a new data-driven method for working with diffusive trajectories. This method utilizes Gramian angular fields (GAF) to encode one-dimensional trajectories as images (Gramian matrices), while preserving their spatiotemporal structure for input to computer-vision models. This allows us to leverage two well-established pretrained computer-vision models, ResNet and MobileNet, to characterize the underlying diffusive regime and infer the anomalous diffusion exponent α. Short raw trajectories of lengths between 10 and 50 are commonly encountered in single-particle tracking experiments and are the most difficult ones to characterize. We show that GAF images can outperform the current state-of-the-art while increasing accessibility to machine learning methods in an applied setting.
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Affiliation(s)
- Òscar Garibo-I-Orts
- GRID-Grupo de Investigacion en Ciencia de Datos Valencian International University-VIU, Carrer Pintor Sorolla 21, 46002 València, Spain
| | - Nicolas Firbas
- DBS-Department of Biological Sciences, National University of Singapore 16 Science Drive 4, Singapore 117558, Singapore
| | - Laura Sebastiá
- VRAIN-Valencian Research Institute for Artificial Intelligence Universitat Politècnica de València, Cami de Vera s/n, 46022 València, Spain
| | - J Alberto Conejero
- Instituto Universitario de Matemática Pura y Aplicada Universitat Politècnica de València, Cami de Vera s/n, 46022 València, Spain
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Chandra A, Prasad S, Alemanno F, De Luca M, Rizzo R, Romano R, Gigli G, Bucci C, Barra A, del Mercato LL. Fully Automated Computational Approach for Precisely Measuring Organelle Acidification with Optical pH Sensors. ACS APPLIED MATERIALS & INTERFACES 2022; 14:18133-18149. [PMID: 35404562 PMCID: PMC9052195 DOI: 10.1021/acsami.2c00389] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
pH balance and regulation within organelles are fundamental to cell homeostasis and proliferation. The ability to track pH in cells becomes significantly important to understand these processes in detail. Fluorescent sensors based on micro- and nanoparticles have been applied to measure intracellular pH; however, an accurate methodology to precisely monitor acidification kinetics of organelles in living cells has not been established, limiting the scope of this class of sensors. Here, silica-based fluorescent microparticles were utilized to probe the pH of intracellular organelles in MDA-MB-231 and MCF-7 breast cancer cells. In addition to the robust, ratiometric, trackable, and bioinert pH sensors, we developed a novel dimensionality reduction algorithm to automatically track and screen massive internalization events of pH sensors. We found that the mean acidification time is comparable among the two cell lines (ΔTMCF-7 = 16.3 min; ΔTMDA-MB-231 = 19.5 min); however, MCF-7 cells showed a much broader heterogeneity in comparison to MDA-MB-231 cells. The use of pH sensors and ratiometric imaging of living cells in combination with a novel computational approach allow analysis of thousands of events in a computationally inexpensive and faster way than the standard routes. The reported methodology can potentially be used to monitor pH as well as several other parameters associated with endocytosis.
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Affiliation(s)
- Anil Chandra
- Institute
of Nanotechnology, National Research Council (CNR-NANOTEC), Campus Ecotekne, Via Monteroni, Lecce 73100, Italy
| | - Saumya Prasad
- Institute
of Nanotechnology, National Research Council (CNR-NANOTEC), Campus Ecotekne, Via Monteroni, Lecce 73100, Italy
| | - Francesco Alemanno
- Institute
of Nanotechnology, National Research Council (CNR-NANOTEC), Campus Ecotekne, Via Monteroni, Lecce 73100, Italy
- Dipartimento
di Matematica e Fisica, Università
del Salento, Via Monteroni, Lecce 73100, Italy
| | - Maria De Luca
- Dipartimento
di Scienze e Tecnologie Biologiche ed Ambientali (DiSTeBa), Università del Salento, Via Monteroni, Lecce 73100, Italy
| | - Riccardo Rizzo
- Institute
of Nanotechnology, National Research Council (CNR-NANOTEC), Campus Ecotekne, Via Monteroni, Lecce 73100, Italy
| | - Roberta Romano
- Dipartimento
di Scienze e Tecnologie Biologiche ed Ambientali (DiSTeBa), Università del Salento, Via Monteroni, Lecce 73100, Italy
| | - Giuseppe Gigli
- Institute
of Nanotechnology, National Research Council (CNR-NANOTEC), Campus Ecotekne, Via Monteroni, Lecce 73100, Italy
- Dipartimento
di Matematica e Fisica, Università
del Salento, Via Monteroni, Lecce 73100, Italy
| | - Cecilia Bucci
- Dipartimento
di Scienze e Tecnologie Biologiche ed Ambientali (DiSTeBa), Università del Salento, Via Monteroni, Lecce 73100, Italy
| | - Adriano Barra
- Dipartimento
di Matematica e Fisica, Università
del Salento, Via Monteroni, Lecce 73100, Italy
- Istituto
Nazionale di Fisica Nucleare, Sezione di Lecce, Via Monteroni, Lecce 73100, Italy
| | - Loretta L. del Mercato
- Institute
of Nanotechnology, National Research Council (CNR-NANOTEC), Campus Ecotekne, Via Monteroni, Lecce 73100, Italy
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Harcha PA, López-López T, Palacios AG, Sáez PJ. Pannexin Channel Regulation of Cell Migration: Focus on Immune Cells. Front Immunol 2022; 12:750480. [PMID: 34975840 PMCID: PMC8716617 DOI: 10.3389/fimmu.2021.750480] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Accepted: 11/15/2021] [Indexed: 12/12/2022] Open
Abstract
The role of Pannexin (PANX) channels during collective and single cell migration is increasingly recognized. Amongst many functions that are relevant to cell migration, here we focus on the role of PANX-mediated adenine nucleotide release and associated autocrine and paracrine signaling. We also summarize the contribution of PANXs with the cytoskeleton, which is also key regulator of cell migration. PANXs, as mechanosensitive ATP releasing channels, provide a unique link between cell migration and purinergic communication. The functional association with several purinergic receptors, together with a plethora of signals that modulate their opening, allows PANX channels to integrate physical and chemical cues during inflammation. Ubiquitously expressed in almost all immune cells, PANX1 opening has been reported in different immunological contexts. Immune activation is the epitome coordination between cell communication and migration, as leukocytes (i.e., T cells, dendritic cells) exchange information while migrating towards the injury site. In the current review, we summarized the contribution of PANX channels during immune cell migration and recruitment; although we also compile the available evidence for non-immune cells (including fibroblasts, keratinocytes, astrocytes, and cancer cells). Finally, we discuss the current evidence of PANX1 and PANX3 channels as a both positive and/or negative regulator in different inflammatory conditions, proposing a general mechanism of these channels contribution during cell migration.
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Affiliation(s)
- Paloma A Harcha
- Centro Interdisciplinario de Neurociencia de Valparaíso, Instituto de Neurociencia, Facultad de Ciencias, Universidad de Valparaíso, Valparaíso, Chile
| | - Tamara López-López
- Cell Communication and Migration Laboratory, Institute of Biochemistry and Molecular Cell Biology, Center for Experimental Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Adrián G Palacios
- Centro Interdisciplinario de Neurociencia de Valparaíso, Instituto de Neurociencia, Facultad de Ciencias, Universidad de Valparaíso, Valparaíso, Chile
| | - Pablo J Sáez
- Cell Communication and Migration Laboratory, Institute of Biochemistry and Molecular Cell Biology, Center for Experimental Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
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