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PubMed2004

Genotypic and phenotypic biomarker profiles for individual risk assessment and cancer detection (lessons from bladder cancer risk assessment in symptomatic patients and workers exposed to benzidine).

There is a need for improved methods for detecting individuals at risk for cancer to target subsets of patients for more intensive individual screening and targeted cancer therapy and chemoprevention. One approach for accomplishing this objective is to detect premalignant molecular fingerprints in an organ at risk for cancer or to define biomarkers reflective of treatment selection and response. Bladder cancer is an excellent model for testing this approach; however, comprehending the strategy for biomarker selection and analysis is more complicated than is generally appreciated. The objective of this article is to provide a succinct overview of our experience with the selection of biomarkers for bladder cancer detection, first in symptomatic patients and then in high-risk cohorts of workers at risk for bladder cancer. Biomarker selection depends on multiple parameters, each of which must be optimized to enhance the utility of a biomarker for clinical application. Many markers that initially show promise fail in the clinical arena for a variety of reasons. Important parameters include when a biomarker is expressed in carcinogenesis (i.e., early vs. late), the sample type, and the method of analysis. These all contribute to the sensitivity, specificity, and ultimate clinical utility of a biomarker. New technologies/ support the notion that all diseases start in the cell, and Seymore West indicated the cell, under appropriate conditions, can function as a microcuvette for biophysical cytochemical analysis. Spectroscopy provides an accurate and sensitive method for quantitative single-cell proteomics. Improved and more stable fluorescence probes will enhance the utility of cellular chemistry, as will a rationale approach for biomarker selection based on the concepts of field cancerization, complemented by improved quantitative analysis of protein markers at the single-cell level. Our laboratory has developed a platform for single-cell proteomic analysis that can be applied to multiple basic science and clinical problems. Single-cell proteomics also facilitates the study of genetic instability and epigenetic signaling (stromal-epithelial interactions) in relation to cancer therapy and diagnosis. Because most cancers arise through multiple signaling pathways and are heterogeneous, the identification of appropriate biomarker profiles provides a number of strategic advantages over a single biomarker. Complex networks of signaling pathways lead to increased cell proliferation, decreased cell adhesion, cellular differentiation, genetic instability, and other functions associated with the malignant phenotype. The purpose of this presentation is to illustrate the fundamental concepts for selection and profile analysis of high-level phenotypic biomarkers developed for bladder cancer risk assessment, screening, and early bladder cancer detection.

Benzidines↗

PubMed2006

Miniaturized platforms for the detection of single-nucleotide polymorphisms.

Conventional methods for detecting single-nucleotide polymorphisms (SNPs), the most common form of genetic variation in human beings, are mostly limited by their analysis time and throughputs. In contrast, advances in microfabrication technology have led to the development of miniaturized platforms that can potentially provide rapid high-throughput analysis at small sample volumes. This review highlights some of the recent developments in the miniaturization of SNP detection platforms, including microarray-based, bead-based microfluidic and microelectrophoresis-based platforms. Particular attention is paid to their ease of fabrication, analysis time, and level of throughput.

Electrophoresis↗

PubMed2026

transFusion: a novel comprehensive platform for integration analysis of single-cell and spatial transcriptomics.

MOTIVATION: Understanding spatial organization, intercellular interactions, and regulatory networks within the spatial context of tissues is crucial for uncovering complex biological processes and disease mechanisms. Spatial transcriptomics technologies have revolutionized this field by enabling the spatially resolved profiling of gene expression. 10× Visium has emerged as the predominant spatial technology, but its low resolution and the complexity of integrating multimodal datasets present significant analytical challenges, particularly for researchers with limited computational and statistical expertise. Current spatial transcriptomics analysis platforms generally fall short of effectively integrating multimodal data and maximizing the utility of spatial information-such as uncovering complex cellular spatial dependencies, multimodal gradient patterns, and spatial coexpression of ligand-receptor pairs and regulatory networks related to disease or biological states-thereby limiting their ability to provide comprehensive end-to-end analytical workflows when analyzing 10× Visium data. RESULTS: To address these limitations, we developed transFusion, a novel, advanced web-based platform specializing in the most comprehensive and effective integration analysis of scRNA-seq and 10× Visium spatial transcriptomics data. transFusion offers 12 key functions, from basic visualization to advanced analyses, including intercellular dependency analysis, ligand-receptor coexpression identification and visualization, and spatial multimodal gradient variation patterns. Two case studies were used to demonstrate transFusion's capabilities in exploring tissue architecture, intercellular communication, dependency networks, and multimodal gradient variation patterns with minimal computational skills and statistical expertise. transFusion provides a flexible and powerful framework for multimodal data integration analysis. AVAILABILITY AND IMPLEMENTATION: transFusion is freely available at https://github.com/WQLin8/transFusion.

Spatial Transcriptomics↗

PubMed2006

Strategies for comparing gene expression profiles from different microarray platforms: application to a case-control experiment.

Meta-analysis of microarray data is increasingly important, considering both the availability of multiple platforms using disparate technologies and the accumulation in public repositories of data sets from different laboratories. We addressed the issue of comparing gene expression profiles from two microarray platforms by devising a standardized investigative strategy. We tested this procedure by studying MDA-MB-231 cells, which undergo apoptosis on treatment with resveratrol. Gene expression profiles were obtained using high-density, short-oligonucleotide, single-color microarray platforms: GeneChip (Affymetrix) and CodeLink (Amersham). Interplatform analyses were carried out on 8414 common transcripts represented on both platforms, as identified by LocusLink ID, representing 70.8% and 88.6% of annotated GeneChip and CodeLink features, respectively. We identified 105 differentially expressed genes (DEGs) on CodeLink and 42 DEGs on GeneChip. Among them, only 9 DEGs were commonly identified by both platforms. Multiple analyses (BLAST alignment of probes with target sequences, gene ontology, literature mining, and quantitative real-time PCR) permitted us to investigate the factors contributing to the generation of platform-dependent results in single-color microarray experiments. An effective approach to cross-platform comparison involves microarrays of similar technologies, samples prepared by identical methods, and a standardized battery of bioinformatic and statistical analyses.

Breast Neoplasms↗

PubMed2026

Clinical evidence on non-viral CAR-T cell therapies for solid tumors: a scoping review.

BACKGROUND: Chimeric antigen receptor (CAR) T-cell therapy in solid tumors is hindered by the immunosuppressive tumor microenvironment and by toxicities associated with viral-vector manufacturing. Non-viral gene delivery platforms have emerged as a potential alternative, though clinical evidence remains fragmented. METHODS: Following an a priori protocol registered on the Open Science Framework (OSF; https://doi.org/10.17605/OSF.IO/2TPQS) and adhering to JBI/PRISMA-ScR guidelines, a systematic search was conducted across four databases from inception through May 15, 2026. Patient-level data were extracted to describe cellular persistence and clinical outcomes across strictly non-viral delivery platforms. RESULTS: Four early-phase studies met the inclusion criteria, encompassing 28 heavily pretreated patients with metastatic solid tumors. Two non-viral platforms were identified: mRNA electroporation (n=19; intravenous in 13, intratumoral in 6) and the piggyBac transposon system (n=9). Across both mRNA routes, transient CAR-T persistence (<7 days) was observed, with no objective responses (ORR 0%), though disease stabilization yielded a disease control rate (DCR) of 53%; cross-route comparison is limited by differing distribution profiles. The piggyBac system showed longer persistence (~28 days) and a DCR of 78%, including the only documented objective response (ORR 11%). No Grade ≥3 cytokine release syndrome or neurotoxicity was reported in any of the 28 patients, and no tocilizumab or systemic corticosteroids were required. CONCLUSIONS: Within this limited early-phase evidence base, no severe toxicities attributable to non-viral platforms were reported, and the evidence identifies knowledge gaps warranting prospective investigation. mRNA platforms showed transient persistence and disease stabilization in 53% of patients. One partial response was documented with the piggyBac platform in a single patient; however, this outcome cannot be attributed to the delivery platform given simultaneous differences in target antigen, tumor histology, route of administration, and geographic setting. No firm conclusions regarding comparative platform performance can be drawn from this evidence base. SYSTEMATIC REVIEW REGISTRATION: https://doi.org/10.17605/OSF.IO/2TPQS, identifier OSF.IO/2TPQS.

Humans↗

PubMed2026

Longitudinal In Vivo Imaging at Single-Lesion Resolution Identifies Allele-Associated Response and Resistance Dynamics in EGFR-Mutant Lung Cancer.

Acquired resistance to targeted therapies is inevitable in EGFR-mutant non-small cell lung cancer (NSCLC), yet the principles governing its emergence in vivo remain incompletely understood. In particular, how lesion-level response patterns vary across distinct EGFR allele contexts during therapy has not been systematically examined at single-lesion resolution. Here, we establish a longitudinal in vivo imaging platform enabling single-lesion resolution tracking of tumor behavior during therapy in genetically engineered mouse models representing clinically relevant EGFR alleles. Using high-resolution micro-computed tomography (micro-CT) and three-dimensional reconstruction, we monitor tumor growth, therapeutic response, and resistance during osimertinib treatment. EGFR genotype is associated with distinct patterns of tumor growth, response kinetics, and resistance timing. Therapeutic response is spatially heterogeneous, with coexisting lesions undergoing complete regression, persistence, or progression within the same lung. During treatment, spatially distinct lesion-level behaviors included persistent growth during therapy and initial regression followed by regrowth. These findings demonstrate the utility of longitudinal micro-CT imaging to investigate allele-associated differences in treatment response and resistance timing at single-lesion resolution in vivo.

Animals↗

PubMed2000

Flow cytometry-based minisequencing: a new platform for high-throughput single-nucleotide polymorphism scoring.

Single-nucleotide polymorphisms (SNPs) are the most abundant type of human genetic variation. These variable sites are present at high density in the genome, making them powerful tools for mapping and diagnosing disease-related alleles. We have developed a sensitive and rapid flow cytometry-based assay for the multiplexed analysis of SNPs based on polymerase-mediated primer extension, or minisequencing, using microspheres as solid supports. The new method involves subnanomolar concentrations of sample in small volumes ( approximately 10 microl) which can be analyzed at rates of one sample per minute or faster, without a wash step. Further, genomic analysis using multiplexing microsphere arrays (GAMMArrays), enables the simultaneous analysis of dozens, and potentially hundreds of SNPs per sample. We have tested the new method by genotyping the Glu69 variant from the HLA DPB1 locus, a SNP associated with chronic beryllium disease, as well as HLA DPA1 alleles using the multiplexed method. The results demonstrate the sensitivity and accuracy of flow cytometry-based minisequencing, a powerful new tool for genome- and global-scale SNP analysis.

Base Sequence↗

PubMed2006

A yeast platform for the production of single-chain antibody-green fluorescent protein fusions.

Fusion proteins comprised of a binding domain and green fluorescent protein (GFP) have the potential to act as one-step binding reagents. In this study, eight single-chain antibodies (scFv) and one single-chain T-cell receptor (scTCR) were secreted as fusions to GFP using a Saccharomyces cerevisiae expression system. Fusion protein secretion levels ranged over 3 orders of magnitude, from 4 microg/liter to 4 mg/liter, and correlated well with the secretion levels of the unfused scFv/scTCR. Three fusion types with various linker lengths and fusion orientations were tested for each scFv/scTCR. Although the fusion protein secretion levels were not significantly affected by the nature of the fusion construct, the properties of the fusion protein were clearly influenced. The fluorescence yield per fusion molecule was increased by separating the scFv/scTCR and GFP with an extended (GGGGS)3 linker, and fusions with scFv/scTCR at the carboxy-terminus were more resistant to degradation. By evaluating leader sequence processing and using GFP fluorescence to track intracellular processing, it was determined that the majority of fusion protein synthesized by the yeast was not secreted and in most cases was accumulating in an immature, although active, endoplasmic-reticulum (ER)-processed form. This contrasted with unfused scFv, which accumulated in both immature ER-processed and mature post-Golgi forms. The results indicated that yeast can be used as an effective host for the secretion of scFv/scTCR-GFP fusion proteins and that as a result of intracellular secretory bottlenecks, there is considerable yeast secretory capacity remaining to be exploited.

Flow Cytometry↗

PubMed2004

KARMA: a web server application for comparing and annotating heterogeneous microarray platforms.

We have developed a universal web server application (KARMA) that allows comparison and annotation of user-defined pairs of microarray platforms based on diverse types of genome annotation data (across different species) collected from multiple sources. The application is an effective tool for diverse microarray platforms, including arrays that are provided by (i) the Keck Microarray Resource at Yale, (ii) commercially available Affymetrix GeneChips and spotted arrays and (iii) custom arrays made by individual academics. The tool provides a web interface that allows users to input pairs of test files that represent diverse array platforms for either single or multiple species. The program dynamically identifies analogous DNA fragments spotted or synthesized on multiple microarray platforms based on the following types of information: (i) NCBI-Unigene identifiers, if the platforms being compared are within the same species or (ii) NCBI-Homologene data, if they are cross-species. The single-species comparison is implemented based on set operations: intersection, union and difference. Other forms of retrievable annotation data, including LocusLink, SwissProt and Gene Ontology (GO), are collected from multiple remote sites and stored in an integrated fashion using an Oracle database. The KARMA database, which is updated periodically, is available on line at the following URL: http://ymd.med.yale.edu/karma/cgi-bin/karma.pl.

Gene Expression Profiling↗

PubMed2025

Differentiation latency and dormancy signatures define fetal liver hematopoietic stem cells at single-cell resolution.

Decoding the mechanisms governing the self-renewal of hematopoietic stem cells (HSCs) during their expansion in the fetal liver (FL) could unlock novel therapeutic strategies to expand transplantable HSCs, a long-standing challenge. To explore intrinsic and extrinsic regulation of FL-HSC self-renewal at single-cell resolution, we engineered a culture platform replicating the FL endothelial niche that supports the amplification of serially engraftable HSCs. Leveraging this platform together with single-cell index flow cytometry, live imaging, transplantation assays, and single-cell RNA sequencing, we demonstrate that differentiation latency, cell-division symmetry, and transcriptional signatures of biosynthetic dormancy are distinguishing properties of rare FL-HSCs capable of serial multilineage hematopoietic reconstitution. Our findings support a paradigm in which intrinsic programs and niche-derived signals together facilitate the symmetric self-renewal of FL-HSCs while delaying their active participation in hematopoiesis. Our study also provides a resource for future investigations into intrinsic and extrinsic signaling pathways governing FL-HSC self-renewal.

Hematopoietic Stem Cells↗

PubMed2006

Cross-platform expression profiling demonstrates that SV40 small tumor antigen activates Notch, Hedgehog, and Wnt signaling in human cells.

BACKGROUND: We previously analyzed human embryonic kidney (HEK) cell lines for the effects that simian virus 40 (SV40) small tumor antigen (ST) has on gene expression using Affymetrix U133 GeneChips. To cross-validate and extend our initial findings, we sought to compare the expression profiles of these cell lines using an alternative microarray platform. METHODS: We have analyzed matched cell lines with and without expression of SV40 ST using an Applied Biosystems (AB) microarray platform that uses single 60-mer oligonucleotides and single-color quantitative chemiluminescence for detection. RESULTS: While we were able to previously identify only 456 genes affected by ST with the Affymetrix platform, we identified 1927 individual genes with the AB platform. Additional technical replicates increased the number of identified genes to 3478 genes and confirmed the changes in 278 (61%) of our original set of 456 genes. Among the 3200 genes newly identified as affected by SV40 ST, we confirmed 20 by QRTPCR including several components of the Wnt, Notch, and Hedgehog signaling pathways, consistent with SV40 ST activation of these developmental pathways. While inhibitors of Notch activation had no effect on cell survival, cyclopamine had a potent killing effect on cells expressing SV40 ST. CONCLUSIONS: These data show that SV40 ST expression alters cell survival pathways to sensitize cells to the killing effect of Hedgehog pathway inhibitors.

Antigens, Polyomavirus Transforming↗

PubMed2006

Rapid quantitative analysis using a single molecule counting approach.

Single molecule detection of target molecules specifically bound by paired fluorescently labeled probes has shown great potential for sensitive quantitation of biomolecules. To date, no reports have rigorously evaluated the analytical capabilities of a single molecule detection platform employing this dual-probe approach or the performance of its data analysis methodology. In this paper, we describe a rapid, automated, and sensitive multicolor single molecule detection apparatus and a novel extension of coincident event counting based on detection of fluorescent probes. The approach estimates the number of dual-labeled molecules of interest from the total number of coincident fluorescent events observed by correcting for unbound probes that randomly pass through the interrogation zone simultaneously. Event counting was evaluated on three combinations of distinct fluorescence channels and was demonstrated to outperform conventional spatial cross-correlation in generating a wider linear dynamic response to target molecules. Furthermore, this approach succeeded in detecting subpicomolar concentrations of a model RNA target to which fluorescently labeled oligonucleotide probes were hybridized in a complex background of RNA. These results illustrate that the fluorescent event counting approach described represents a general tool for rapid sensitive quantitative analysis of any sample analyte, including nucleic acids and proteins, for which pairs of specific probes can be developed.

Base Sequence↗

PubMed2000

A model of hippocampally dependent navigation, using the temporal difference learning rule.

This paper presents a model of how hippocampal place cells might be used for spatial navigation in two watermaze tasks: the standard reference memory task and a delayed matching-to-place task. In the reference memory task, the escape platform occupies a single location and rats gradually learn relatively direct paths to the goal over the course of days, in each of which they perform a fixed number of trials. In the delayed matching-to-place task, the escape platform occupies a novel location on each day, and rats gradually acquire one-trial learning, i.e., direct paths on the second trial of each day. The model uses a local, incremental, and statistically efficient connectionist algorithm called temporal difference learning in two distinct components. The first is a reinforcement-based "actor-critic" network that is a general model of classical and instrumental conditioning. In this case, it is applied to navigation, using place cells to provide information about state. By itself, the actor-critic can learn the reference memory task, but this learning is inflexible to changes to the platform location. We argue that one-trial learning in the delayed matching-to-place task demands a goal-independent representation of space. This is provided by the second component of the model: a network that uses temporal difference learning and self-motion information to acquire consistent spatial coordinates in the environment. Each component of the model is necessary at a different stage of the task; the actor-critic provides a way of transferring control to the component that performs best. The model successfully captures gradual acquisition in both tasks, and, in particular, the ultimate development of one-trial learning in the delayed matching-to-place task. Place cells report a form of stable, allocentric information that is well-suited to the various kinds of learning in the model.

Animals↗

PubMed2025

Stereo-cell: Spatial enhanced-resolution single-cell sequencing with high-density DNA nanoball-patterned arrays.

Single-cell sequencing technologies have advanced our understanding of cellular heterogeneity and biological complexity. However, existing methods face limitations in throughput, capture uniformity, cell size flexibility, and technical extensibility. We present Stereo-cell, a spatial enhanced-resolution single-cell sequencing platform based on high-density DNA nanoball (DNB)-patterned arrays, which enables scalable and unbiased cell capture at a wide input range and supports high-fidelity transcriptome profiling. Stereo-cell further allows integration with imaging-based modalities and multiomics strategies, including immunofluorescence and epitope profiling. This platform is also compatible with profiling extracellular vesicles, microstructures, and large cells, whereas its spatial resolution facilitates in situ analysis of cell-cell interactions, cellular microenvironments, and subcellular transcript localization. Together, Stereo-cell provides a flexible framework for expanding single-cell research applications.

Animals↗

PubMed2005

Beyond single pathway inhibition: MEK inhibitors as a platform for the development of pharmacological combinations with synergistic anti-leukemic effects.

The MEK/MAPK signaling module is a key integration point along signal transduction cascades that regulate cell growth, survival, and differentiation, and is aberrantly activated in many human tumors. In tumor cells, constitutive MAPK activation affords increased proliferation and resistance to apoptotic stimuli, including classical cytotoxic drugs. In most instances, however, MAPK inhibition has cytostatic rather than cytotoxic effects, which may explain the lack of objective responses observed in early clinical trials of MEK inhibitors. Nevertheless, amenability of the MAPK pathway to pharmacodynamic evaluation and negligible clinical toxicity make MEK inhibitors an ideal platform to build pharmacological combinations with synergistic antitumor activity. In AML, the MEK/MAPK pathway is constitutively activated in the majority of cases (75%), conferring a uniformly poor prognosis; in preclinical models of AML, MEK blockade profoundly inhibits cell growth and proliferation and downregulates the expression of several anti-apoptotic players, thereby lowering the apoptotic threshold. Apoptosis induction, however, requires concentrations of MEK inhibitors much higher than those required to inhibit proliferation. Nevertheless, MEK blockade efficiently and selectively sensitizes leukemic cells to sub-optimal doses of other apoptotic stimuli, including classical cytotoxics (nucleoside analogs, microtubule-targeted drugs, gamma-irradiation), biologicals (retinoids, interferons, arsenic trioxide), and, most interestingly, other signal transduction/apoptosis modulators (UCN-01, STI571, Bcl-2 antagonists). In most instances, these MEK inhibition-based combinations result in a striking pro-apoptotic synergism in preclinical models. Here we briefly discuss evidence suggesting that MAPK pathway inhibition could play a prominent role in the development of integrated therapeutic strategies aimed at synergistic anti-leukemic effects.

Animals↗

PubMed1999

Evaluation of ankle instability using the Biodex Stability System.

Ten patients with chronic unilateral functional lateral instability of the ankle were evaluated using the Biodex Stability System. This system uses a multiaxial testing platform which can be set at variable degrees of instability. Patients are then tested for their ability to "balance" the platform during single-limb stance, and a stability index is electronically generated. This stability index is believed to be an objective measurement that correlates with proprioceptive status of the ankle. Instability of the ankle was confirmed in all 10 patients, using stress radiographs. Two levels of platform stability were tested. With the platform in its most stable configuration, there was minimal difference between the previously injured and the uninjured ankle. With the platform set to permit up to 20 degrees of tilt in any plane, 6 of 10 patients had more difficulty balancing the platform with their injured ankle (higher stability index). This preliminary study suggests that the Biodex Stability System may be a useful tool in trying to objectively measure proprioceptive function.

Adult↗

PubMed2026

Spatially guided in vivo single-cell functional genomics of postnatal heart.

Understanding how spatial organization and cell-cell interactions shape gene regulatory programs is central to decoding tissue development and function. The transition at birth, marked by increased circulatory demands and rapid tissue growth, requires precise spatiotemporal coordination of cardiac maturation. In this study, we generated a high-resolution spatial and temporal atlas of the postnatal mouse heart by integrating single-nucleus RNA sequencing with image-based spatial transcriptomics. This framework revealed dynamic cellular interactions, niche-specific signaling and transcriptional programs guiding cardiomyocyte maturation. To functionally test prioritized regulators in vivo and at scale, we developed PIP-seq (probe-based indel-detectable Perturb-seq), a high-throughput platform that detects single guide RNA identity, infers gene editing and profiles transcription from fixed nuclei. Applying PIP-seq to the developing postnatal heart, we identified 21 previously uncharacterized regulators of cardiomyocyte maturation, including genes essential for sarcomere assembly, metabolic reprogramming and electrophysiological transitions. Together, our findings define how microenvironmental signals and intrinsic gene programs cooperate to guide heart maturation and establish a broadly applicable framework for functional genomics in complex tissues.

Animals↗

PubMed2004

A new biomechanical model for the functional assessment of knee osteoarthritis.

The severity of symptoms in osteoarthritis (OA) of the knee can be difficult to assess. A new method for assessing medial compartment OA of the knee is proposed. The purpose of this study was to determine if a relationship exists between the severity of OA and single limb stance knee adduction moment (SSKAM). Fourteen patients with medial compartment OA of the knee were tested and compared with 14 age-matched volunteers. WOMAC OA index scores were documented. Biomechanical data were collected from a single Kistler force platform and a six-camera ProReflex motion analysis system, and the knee adduction moments were calculated. A significant difference in the maximum, minimum and mean adduction moments was found between the two groups, and a correlation of r=0.66 for WOMAC physical function subscale, r=0.63 for the WOMAC pain subscale and r=0.63 for the sum of the subscales and mean SSKAM was found. Single limb stance adduction moments provide additional, objective information in the assessment of medial compartment OA of the knee. It may be useful in the selection of patients for surgery and for evaluating various treatment modalities for medial compartment OA of the knee.

Adult↗