Targeting protein tyrosine phosphatases for CDK6-induced immunotherapy resistance.

Elucidating the mechanisms of resistance to immunotherapy and developing strategies to improve its efficacy are challenging goals. Bioinformatics analysis demonstrates that high CDK6 expression in melanoma is associated with poor progression-free survival of patients receiving single-agent immunotherapy. Depletion of CDK6 or cyclin D3 (but not of CDK4, cyclin D1, or D2) in cells of the tumor microenvironment inhibits tumor growth. CDK6 depletion reshapes the tumor immune microenvironment, and the host anti-tumor effect depends on cyclin D3/CDK6-expressing CD8+ and CD4+ T cells. This occurs by CDK6 phosphorylating and increasing the activities of PTP1B and T cell protein tyrosine phosphatase (TCPTP), which, in turn, decreases tyrosine phosphorylation of CD3ζ, reducing the signal transduction for T cell activation. Administration of a PTP1B and TCPTP inhibitor prove more efficacious than using a CDK6 degrader in enhancing T cell-mediated immunotherapy. Targeting protein tyrosine phosphatases (PTPs) might be an effective strategy for cancer patients who resist immunotherapy treatment.

Team principles for successful interdisciplinary research teams.

Interdisciplinary research teams can be extremely beneficial when addressing difficult clinical problems. The incorporation of conceptual and methodological strategies from a variety of research disciplines and health professions yields transformative results. In this setting, the long-term goal of team science is to improve patient care, with emphasis on population health outcomes. However, team principles necessary for effective research teams are rarely taught in health professional schools. To form successful interdisciplinary research teams in cardio-oncology and beyond, guiding principles and organizational recommendations are necessary. Cardiovascular disease results in annual direct costs of $220 billion (about $680 per person in the US) and is the leading cause of death for cancer survivors, including adult survivors of childhood cancers. Optimizing cardio-oncology research in interdisciplinary research teams has the potential to aid in the investigation of strategies for saving hundreds of thousands of lives each year in the United States and mitigating the annual cost of cardiovascular disease. Despite published reports on experiences developing research teams across organizations, specialties and settings, there is no single journal article that compiles principles for cardiology or cardio-oncology research teams. In this review, recurring threads linked to working as a team, as well as optimal methods, advantages, and problems that arise when managing teams are described in the context of career development and research. The worth and hurdles of a team approach, based on practical lessons learned from establishing our multidisciplinary research team and information gleaned from relevant specialties in the development of a successful team are presented.

Establishing an interdisciplinary research team for cardio-oncology artificial intelligence informatics precision and health equity.

Study objective: A multi-institutional interdisciplinary team was created to develop a research group focused on leveraging artificial intelligence and informatics for cardio-oncology patients. Cardio-oncology is an emerging medical field dedicated to prevention, screening, and management of adverse cardiovascular effects of cancer/ cancer therapies. Cardiovascular disease is a leading cause of death in cancer survivors. Cardiovascular risk in these patients is higher than in the general population. However, prediction and prevention of adverse cardiovascular events in individuals with a history of cancer/cancer treatment is challenging. Thus, establishing an interdisciplinary team to create cardiovascular risk stratification clinical decision aids for integration into electronic health records for oncology patients was considered crucial. Design/setting/participants: Core team members from the Medical College of Wisconsin (MCW), University of Wisconsin-Milwaukee (UWM), and Milwaukee School of Engineering (MSOE), and additional members from Cleveland Clinic, Mayo Clinic, and other institutions have joined forces to apply high-performance computing in cardio-oncology. Results: The team is comprised of clinicians and researchers from relevant complementary and synergistic fields relevant to this work. The team has built an epidemiological cohort of ~5000 cancer survivors that will serve as a database for interdisciplinary multi-institutional artificial intelligence projects. Conclusion: Lessons learned from establishing this team, as well as initial findings from the epidemiology cohort, are presented. Barriers have been broken down to form a multi-institutional interdisciplinary team for health informatics research in cardio-oncology. A database of cancer survivors has been created collaboratively by the team and provides initial insight into cardiovascular outcomes and comorbidities in this population.

Deep learning tools and modeling to estimate the temporal expression of cell cycle proteins from 2D still images.

Automatic characterization of fluorescent labeling in intact mammalian tissues remains a challenge due to the lack of quantifying techniques capable of segregating densely packed nuclei and intricate tissue patterns. Here, we describe a powerful deep learning-based approach that couples remarkably precise nuclear segmentation with quantitation of fluorescent labeling intensity within segmented nuclei, and then apply it to the analysis of cell cycle dependent protein concentration in mouse tissues using 2D fluorescent still images. First, several existing deep learning-based methods were evaluated to accurately segment nuclei using different imaging modalities with a small training dataset. Next, we developed a deep learning-based approach to identify and measure fluorescent labels within segmented nuclei, and created an ImageJ plugin to allow for efficient manual correction of nuclear segmentation and label identification. Lastly, using fluorescence intensity as a readout for protein concentration, a three-step global estimation method was applied to the characterization of the cell cycle dependent expression of E2F proteins in the developing mouse intestine.

Nuclear PFKP promotes CXCR4-dependent infiltration by T cell acute lymphoblastic leukemia.

PFKP (phosphofructokinase, platelet), the major isoform of PFK1 expressed in T cell acute lymphoblastic leukemia (T-ALL), is predominantly expressed in the cytoplasm to carry out its glycolytic function. Our study showed that PFKP is a nucleocytoplasmic shuttling protein with functional nuclear export and nuclear localization sequences (NLSs). Cyclin D3/CDK6 facilitated PFKP nuclear translocation by dimerization and by exposing the NLS of PFKP to induce the interaction between PFKP and importin 9. Nuclear PFKP stimulated the expression of C-X-C chemokine receptor type 4 (CXCR4), a chemokine receptor regulating leukemia homing/infiltration, to promote T-ALL cell invasion, which depended on the activity of c-Myc. In vivo experiments showed that nuclear PFKP promoted leukemia homing/infiltration into the bone marrow, spleen, and liver, which could be blocked with CXCR4 antagonists. Immunohistochemical staining of tissues from a clinically well-annotated cohort of T cell lymphoma/leukemia patients showed nuclear PFKP localization in invasive cancers, but not in nonmalignant T lymph node or reactive hyperplasia. The presence of nuclear PFKP in these specimens correlated with poor survival in patients with T cell malignancy, suggesting the potential utility of nuclear PFKP as a diagnostic marker.

Fragile X-related protein family: a double-edged sword in neurodevelopmental disorders and cancer.

The fragile X-related (FXR) family proteins FMRP, FXR1, and FXR2 are RNA binding proteins that play a critical role in RNA metabolism, neuronal plasticity, and muscle development. These proteins share significant homology in their protein domains, which are functionally and structurally similar to each other. FXR family members are known to play an essential role in causing fragile X mental retardation syndrome (FXS), the most common genetic form of autism spectrum disorder. Recent advances in our understanding of this family of proteins have occurred in tandem with discoveries of great importance to neurological disorders and cancer biology via the identification of their novel RNA and protein targets. Herein, we review the FXR family of proteins as they pertain to FXS, other mental illnesses, and cancer. We emphasize recent findings and analyses that suggest contrasting functions of this protein family in FXS and tumorigenesis based on their expression patterns in human tissues. Finally, we discuss current gaps in our knowledge regarding the FXR protein family and their role in FXS and cancer and suggest future studies to facilitate bench to bedside translation of the findings.

Mitochondrial protein import is regulated by p17/PERMIT to mediate lipid metabolism and cellular stress.

How lipid metabolism is regulated at the outer mitochondrial membrane (OMM) for transducing stress signaling remains largely unknown. We show here that this process is controlled by trafficking of ceramide synthase 1 (CerS1) from the endoplasmic reticulum (ER) to the OMM by a previously uncharacterized p17, which is now renamed protein that mediates ER-mitochondria trafficking (PERMIT). Data revealed that p17/PERMIT associates with newly translated CerS1 on the ER surface to mediate its trafficking to the OMM. Cellular stress induces Drp1 nitrosylation/activation, releasing p17/PERMIT to retrieve CerS1 for its OMM trafficking, resulting in mitochondrial ceramide generation, mitophagy and cell death. In vivo, CRISPR-Cas9-dependent genetic ablation of p17/PERMIT prevents acute stress-mediated CerS1 trafficking to OMM, attenuating mitophagy in p17/PERMIT-/- mice, compared to controls, in various metabolically active tissues, including brain, muscle, and pancreas. Thus, these data have implications in diseases associated with accumulation of damaged mitochondria such as cancer and/or neurodegeneration.

Optical computed tomography for spatially isotropic four-dimensional imaging of live single cells.

Quantitative three-dimensional (3D) computed tomography (CT) imaging of living single cells enables orientation-independent morphometric analysis of the intricacies of cellular physiology. Since its invention, x-ray CT has become indispensable in the clinic for diagnostic and prognostic purposes due to its quantitative absorption-based imaging in true 3D that allows objects of interest to be viewed and measured from any orientation. However, x-ray CT has not been useful at the level of single cells because there is insufficient contrast to form an image. Recently, optical CT has been developed successfully for fixed cells, but this technology called Cell-CT is incompatible with live-cell imaging due to the use of stains, such as hematoxylin, that are not compatible with cell viability. We present a novel development of optical CT for quantitative, multispectral functional 4D (three spatial + one spectral dimension) imaging of living single cells. The method applied to immune system cells offers truly isotropic 3D spatial resolution and enables time-resolved imaging studies of cells suspended in aqueous medium. Using live-cell optical CT, we found a heterogeneous response to mitochondrial fission inhibition in mouse macrophages and differential basal remodeling of small (0.1 to 1 fl) and large (1 to 20 fl) nuclear and mitochondrial structures on a 20- to 30-s time scale in human myelogenous leukemia cells. Because of its robust 3D measurement capabilities, live-cell optical CT represents a powerful new tool in the biomedical research field.

A platform for high-throughput bioenergy production phenotype characterization in single cells.

Driven by an increasing number of studies demonstrating its relevance to a broad variety of disease states, the bioenergy production phenotype has been widely characterized at the bulk sample level. Its cell-to-cell variability, a key player associated with cancer cell survival and recurrence, however, remains poorly understood due to ensemble averaging of the current approaches. We present a technology platform for performing oxygen consumption and extracellular acidification measurements of several hundreds to 1,000 individual cells per assay, while offering simultaneous analysis of cellular communication effects on the energy production phenotype. The platform comprises two major components: a tandem optical sensor for combined oxygen and pH detection, and a microwell device for isolation and analysis of single and few cells in hermetically sealed sub-nanoliter chambers. Our approach revealed subpopulations of cells with aberrant energy production profiles and enables determination of cellular response variability to electron transfer chain inhibitors and ion uncouplers.

Vorinostat differentially alters 3D nuclear structure of cancer and non-cancerous esophageal cells.

The histone deacetylase (HDAC) inhibitor vorinostat has received significant attention in recent years as an 'epigenetic' drug used to treat solid tumors. However, its mechanisms of action are not entirely understood, particularly with regard to its interaction with the aberrations in 3D nuclear structure that accompany neoplastic progression. We investigated the impact of vorinostat on human esophageal epithelial cell lines derived from normal, metaplastic (pre-cancerous), and malignant tissue. Using a combination of novel optical computed tomography (CT)-based quantitative 3D absorption microscopy and conventional confocal fluorescence microscopy, we show that subjecting malignant cells to vorinostat preferentially alters their 3D nuclear architecture relative to non-cancerous cells. Optical CT (cell CT) imaging of fixed single cells showed that drug-treated cancer cells exhibit significant alterations in nuclear morphometry. Confocal microscopy revealed that vorinostat caused changes in the distribution of H3K9ac-marked euchromatin and H3K9me3-marked constitutive heterochromatin. Additionally, 3D immuno-FISH showed that drug-induced expression of the DNA repair gene MGMT was accompanied by spatial relocation toward the center of the nucleus in the nuclei of metaplastic but not in non-neoplastic cells. Our data suggest that vorinostat's differential modulation of 3D nuclear architecture in normal and abnormal cells could play a functional role in its anti-cancer action.

Sensitizing cancer cells to TRAIL-induced death by micellar delivery of mitoxantrone.

TNFα-related apoptosis-inducing ligand (TRAIL) induces death selectively in cancer cells. However, subpopulations of cancer cells are either resistant to or can develop resistance to TRAIL-induced death. As a result, strategies that overcome this resistance are currently under investigation. We have recently identified several US FDA-approved drugs with TRAIL-sensitization activity against prostate, breast and pancreatic cancer cells. Mitoxantrone, a previously unknown TRAIL sensitizer identified in the screen, was successfully encapsulated in methoxy-, amine- and carboxyl-terminated PEG-DSPE micelles in order to facilitate delivery of the drug to cancer cells. All three micelle types were extensively characterized for their physicochemical properties and evaluated for their ability to sensitize cancer cells to TRAIL-induced death. Our results indicate that micelle-encapsulated mitoxantrone can be advantageously employed in synergistic treatments with TRAIL, leading to a biocompatible delivery system and amplified cell killing activity for combination chemotherapeutic cancer treatments.

Integrated metagenomic and metatranscriptomic analyses of microbial communities in the meso- and bathypelagic realm of north pacific ocean.

Although emerging evidence indicates that deep-sea water contains an untapped reservoir of high metabolic and genetic diversity, this realm has not been studied well compared with surface sea water. The study provided the first integrated meta-genomic and -transcriptomic analysis of the microbial communities in deep-sea water of North Pacific Ocean. DNA/RNA amplifications and simultaneous metagenomic and metatranscriptomic analyses were employed to discover information concerning deep-sea microbial communities from four different deep-sea sites ranging from the mesopelagic to pelagic ocean. Within the prokaryotic community, bacteria is absolutely dominant (~90%) over archaea in both metagenomic and metatranscriptomic data pools. The emergence of archaeal phyla Crenarchaeota, Euryarchaeota, Thaumarchaeota, bacterial phyla Actinobacteria, Firmicutes, sub-phyla Betaproteobacteria, Deltaproteobacteria, and Gammaproteobacteria, and the decrease of bacterial phyla Bacteroidetes and Alphaproteobacteria are the main composition changes of prokaryotic communities in the deep-sea water, when compared with the reference Global Ocean Sampling Expedition (GOS) surface water. Photosynthetic Cyanobacteria exist in all four metagenomic libraries and two metatranscriptomic libraries. In Eukaryota community, decreased abundance of fungi and algae in deep sea was observed. RNA/DNA ratio was employed as an index to show metabolic activity strength of microbes in deep sea. Functional analysis indicated that deep-sea microbes are leading a defensive lifestyle.

Single-cell analysis reveals early manifestation of cancerous phenotype in pre-malignant esophageal cells.

Cellular heterogeneity plays a pivotal role in a variety of functional processes in vivo including carcinogenesis. However, our knowledge about cell-to-cell diversity and how differences in individual cells manifest in alterations at the population level remains very limited mainly due to the lack of appropriate tools enabling studies at the single-cell level. We present a study on changes in cellular heterogeneity in the context of pre-malignant progression in response to hypoxic stress. Utilizing pre-malignant progression of Barrett's esophagus (BE) as a disease model system we studied molecular mechanisms underlying the progression from metaplastic to dysplastic (pre-cancerous) stage. We used newly developed methods enabling measurements of cell-to-cell differences in copy numbers of mitochondrial DNA, expression levels of a set of mitochondrial and nuclear genes involved in hypoxia response pathways, and mitochondrial membrane potential. In contrast to bulk cell studies reported earlier, our study shows significant differences between metaplastic and dysplastic BE cells in both average values and single-cell parameter distributions of mtDNA copy numbers, mitochondrial function, and mRNA expression levels of studied genes. Based on single-cell data analysis, we propose that mitochondria may be one of the key factors in pre-malignant progression in BE.

A physical sciences network characterization of non-tumorigenic and metastatic cells.

To investigate the transition from non-cancerous to metastatic from a physical sciences perspective, the Physical Sciences-Oncology Centers (PS-OC) Network performed molecular and biophysical comparative studies of the non-tumorigenic MCF-10A and metastatic MDA-MB-231 breast epithelial cell lines, commonly used as models of cancer metastasis. Experiments were performed in 20 laboratories from 12 PS-OCs. Each laboratory was supplied with identical aliquots and common reagents and culture protocols. Analyses of these measurements revealed dramatic differences in their mechanics, migration, adhesion, oxygen response, and proteomic profiles. Model-based multi-omics approaches identified key differences between these cells' regulatory networks involved in morphology and survival. These results provide a multifaceted description of cellular parameters of two widely used cell lines and demonstrate the value of the PS-OC Network approach for integration of diverse experimental observations to elucidate the phenotypes associated with cancer metastasis.

Method for physiologic phenotype characterization at the single-cell level in non-interacting and interacting cells.

Intercellular heterogeneity is a key factor in a variety of core cellular processes including proliferation, stimulus response, carcinogenesis, and drug resistance. However, cell-to-cell variability studies at the single-cell level have been hampered by the lack of enabling experimental techniques. We present a measurement platform that features the capability to quantify oxygen consumption rates of individual, non-interacting and interacting cells under normoxic and hypoxic conditions. It is based on real-time concentration measurements of metabolites of interest by means of extracellular optical sensors in cell-isolating microwells of subnanoliter volume. We present the results of a series of measurements of oxygen consumption rates (OCRs) of individual non-interacting and interacting human epithelial cells. We measured the effects of cell-to-cell interactions by using the system's capability to isolate two and three cells in a single well. The major advantages of the approach are: 1. ratiometric, intensity-based characterization of the metabolic phenotype at the single-cell level, 2. minimal invasiveness due to the distant positioning of sensors, and 3. ability to study the effects of cell-cell interactions on cellular respiration rates.

Nanostructured oxygen sensor--using micelles to incorporate a hydrophobic platinum porphyrin.

Hydrophobic platinum(II)-5,10,15,20-tetrakis-(2,3,4,5,6-pentafluorophenyl)-porphyrin (PtTFPP) was physically incorporated into micelles formed from poly(ε-caprolactone)-block-poly(ethylene glycol) to enable the application of PtTFPP in aqueous solution. Micelles were characterized using dynamic light scattering (DLS) and atomic force microscopy (AFM) to show an average diameter of about 140 nm. PtTFPP showed higher quantum efficiency in micellar solution than in tetrahydrofuran (THF) and dichloromethane (CH2Cl2). PtTFPP in micelles also exhibited higher photostability than that of PtTFPP suspended in water. PtTFPP in micelles exhibited good oxygen sensitivity and response time. This study provided an efficient approach to enable the application of hydrophobic oxygen sensors in a biological environment.

A statistical framework for multiparameter analysis at the single-cell level.

Phenotypic characterization of individual cells provides crucial insights into intercellular heterogeneity and enables access to information that is unavailable from ensemble averaged, bulk cell analyses. Single-cell studies have attracted significant interest in recent years and spurred the development of a variety of commercially available and research-grade technologies. To quantify cell-to-cell variability of cell populations, we have developed an experimental platform for real-time measurements of oxygen consumption (OC) kinetics at the single-cell level. Unique challenges inherent to these single-cell measurements arise, and no existing data analysis methodology is available to address them. Here we present a data processing and analysis method that addresses challenges encountered with this unique type of data in order to extract biologically relevant information. We applied the method to analyze OC profiles obtained with single cells of two different cell lines derived from metaplastic and dysplastic human Barrett's esophageal epithelium. In terms of method development, three main challenges were considered for this heterogeneous dynamic system: (i) high levels of noise, (ii) the lack of a priori knowledge of single-cell dynamics, and (iii) the role of intercellular variability within and across cell types. Several strategies and solutions to address each of these three challenges are presented. The features such as slopes, intercepts, breakpoint or change-point were extracted for every OC profile and compared across individual cells and cell types. The results demonstrated that the extracted features facilitated exposition of subtle differences between individual cells and their responses to cell-cell interactions. With minor modifications, this method can be used to process and analyze data from other acquisition and experimental modalities at the single-cell level, providing a valuable statistical framework for single-cell analysis.

A series of poly[N-(2-hydroxypropyl)methacrylamide] copolymers with anthracene-derived fluorophores showing aggregation-induced emission properties for bioimaging.

A series of new poly[N-(2-hydroxypropyl)methacrylamide]-based amphiphilic copolymers were synthesized through a radical copolymerization of a monomeric/hydrophobic fluorophore possessing aggregation-induced emission (AIE) property with N-(2-hydroxypropyl)methacrylamide. Photophysical properties were investigated using UV-Vis absorbance and fluorescence spectrophotometry. Influences of the polymer structures with different molar ratios of the AIE fluorophores on their photophysical properties were studied. Results show that the AIE fluorophores aggregate in the cores of the micelles formed from the amphiphilic random copolymers and polymers with more hydrophobic AIE fluorophores facilitate stronger aggregations of the AIE segments to obtain higher quantum efficiencies. The polymers reported herein have good water solubility, enabling the application of hydrophobic AIE materials in biological conditions. The polymers were endocytosed by two experimental cell lines, human brain glioblastoma U87MG cells and human esophagus premalignant CP-A, with a distribution into the cytoplasm. The polymers are non-cytotoxic to the two cell lines at a polymer concentration of 1 mg/mL.

Isotropic 3D nuclear morphometry of normal, fibrocystic and malignant breast epithelial cells reveals new structural alterations.

BACKGROUND: Grading schemes for breast cancer diagnosis are predominantly based on pathologists' qualitative assessment of altered nuclear structure from 2D brightfield microscopy images. However, cells are three-dimensional (3D) objects with features that are inherently 3D and thus poorly characterized in 2D. Our goal is to quantitatively characterize nuclear structure in 3D, assess its variation with malignancy, and investigate whether such variation correlates with standard nuclear grading criteria. METHODOLOGY: We applied micro-optical computed tomographic imaging and automated 3D nuclear morphometry to quantify and compare morphological variations between human cell lines derived from normal, benign fibrocystic or malignant breast epithelium. To reproduce the appearance and contrast in clinical cytopathology images, we stained cells with hematoxylin and eosin and obtained 3D images of 150 individual stained cells of each cell type at sub-micron, isotropic resolution. Applying volumetric image analyses, we computed 42 3D morphological and textural descriptors of cellular and nuclear structure. PRINCIPAL FINDINGS: We observed four distinct nuclear shape categories, the predominant being a mushroom cap shape. Cell and nuclear volumes increased from normal to fibrocystic to metastatic type, but there was little difference in the volume ratio of nucleus to cytoplasm (N/C ratio) between the lines. Abnormal cell nuclei had more nucleoli, markedly higher density and clumpier chromatin organization compared to normal. Nuclei of non-tumorigenic, fibrocystic cells exhibited larger textural variations than metastatic cell nuclei. At p<0.0025 by ANOVA and Kruskal-Wallis tests, 90% of our computed descriptors statistically differentiated control from abnormal cell populations, but only 69% of these features statistically differentiated the fibrocystic from the metastatic cell populations. CONCLUSIONS: Our results provide a new perspective on nuclear structure variations associated with malignancy and point to the value of automated quantitative 3D nuclear morphometry as an objective tool to enable development of sensitive and specific nuclear grade classification in breast cancer diagnosis.

Using fluorine-containing amphiphilic random copolymers to manipulate the quantum yields of aggregation-induced emission fluorophores in aqueous solutions and the use of these polymers for fluorescent bioimaging.

Two new series of aggregation-induced emission (AIE) fluorophore-containing amphiphilic copolymers possessing the segments of a monomeric AIE fluorophore, N-(2-hydroxypropyl)methacrylamide (HPMA), [2-(methacryloyloxy)ethyl]trimethylammonium chloride (MATMA), and/or 2,2,2-trifluoroethyl methacrylate (TFEMA) were synthesized. Photophysical properties were investigated using UV-Vis absorbance and fluorescence spectrofluorometry. The increases of molar fractions of the hydrophobic AIE fluorophores and/or the trifluoroethyl moieties result in the higher quantum yields of the AIE fluorophores in the polymers. Using 1-mol% of AIE fluorophores with the tuning of molar fractions of TFEMA, 40% quantum yield was achieved, whereas only less than 10% quantum yield was obtained for the polymers without the TFEMA segments. The quantum yield difference indicates the importance of the fluorine segments for getting high quantum yields of the AIE fluorophores. These polymers were explored for fluorescent bioimaging using human brain glioblastoma U87MG and human esophagus premalignant CP-A cell lines. All the polymers are cell permeable and located in the cellular cytoplasma area. Cellular uptake was demonstrated to be through endocytosis, which is time and energy dependent. The polymers are non-cytotoxic to the two cell lines. Because the polymers contain (19)F segments, we studied the spin-lattice relaxation time (T1) and spin-spin relaxation time (T2) of these polymers. T1 and T2 are the two important parameters for the evaluations of the capacity of these polymers for further applications in (19)F magnetic resonance imaging ((19)F MRI). Structure influence on T1 and T2, especially for T2, was observed. These new multifunctional materials are the first series of fluorinated polymers with AIE fluorophores for bioapplications.