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Biology subjects

Chin, K.

Publications and source records attributed to Chin, K..

At least 19 recordsLinked to original sources

A window trial in metastatic pancreatic ductal adenocarcinoma reveals resistance mechanisms to targeting the KRAS-MEK pathway

Copy number alterations of KRAS, mutated in over 90% of pancreatic ductal adenocarcinomas (PDAC), and MYC occur in 30-40% of PDAC. Here we demonstrate that KRAS and MYC are frequently co-gained and accompanied with worse prognosis in PDAC. In a Window-of-Opportunity clinical trial for metastatic PDAC, serial biopsies and deep multi-omics analyses were utilized to explore resistance mechanisms to MEK inhibition, as a surrogate for KRAS inhibition. Tumors from four of 14 patients showed Ki-67/CA19-9-based biomarker response (BR). Non-BR tumors were enriched for KRAS/MYC co-gain and KRASG12D variant. A transcriptomic signature of BR tumors was inversely correlated with KRASG12D/MYC co-gain in a large PDAC dataset and predictive for KRAS inhibitor response in multiple models. Finally, co-targeting KRAS and MYC was synergistic in KRASG12D/MYC co-gain PDAC. Together, this study provides insight into KRAS inhibitor resistance and supports MYC as an important target to improve patient outcomes in this deadly disease.

cancer biology↗

Interferon Restores Antigen Presentation and Sensitizes Medulloblastoma to T Cell Killing

Medulloblastomas are commonly considered immunologically cold and refractory to immunotherapy. One contributing factor to their low immunogenicity is impaired antigen presentation, which allows tumor cells to escape from cytotoxic T cells. Here we use a syngeneic mouse model of medulloblastoma to study the role of CD8+ T cells in medulloblastoma growth. We demonstrate that despite low expression of MHC Class I on tumor cells, depletion of CD8+ T cells accelerates tumor growth, whereas adoptive transfer of tumor-reactive CD8+ T cells prolongs survival. These anti-tumor effects rely on T cells secreting interferon gamma (IFN{gamma}), which induces MHC class I on tumor cells and facilitates tumor cell killing by T cells. Notably, this response is essential for CD8+ T cell-mediated tumor attack, as blocking IFN{gamma} signaling in vivo abrogates MHC class I induction and eliminates the beneficial effect of T cells. Importantly, delivering IFN{gamma} directly into tumors via convection-enhanced delivery (CED) enhances CD8+ T cell-mediated killing of tumor cells and significantly prolongs survival in tumor-bearing mice. These studies highlight the importance of T cells in controlling brain tumor growth and the value of IFN{gamma} as an adjuvant for T cell-based immunotherapy.

cancer biology↗

Modular Assembly of Biohybrid Machines Using Force-Enhanced Skeletal Muscle Actuators

Muscle-based biohybrid systems integrate living muscle with engineered structures to create soft robots, biological models, and regenerative platforms. However, current actuators often lack strength and are difficult to assemble into complex devices. This study presents a suspended compliant skeleton that enhances muscle maturation by providing passive resistance, enabling high-stroke self-exercise without external stimulation. Using immortalized C2C12 cells, the resulting actuators achieved millimeter-scale strokes and millinewton-scale forces, surpassing previous benchmarks. Magnetic interfaces embedded in the skeleton allowed modular assembly into multi-degree-of-freedom devices such as grippers, arms, and positioning stages. These interfaces also support actuator replacement and repair, improving resilience and scalability. This approach significantly boosts engineered muscle performance and offers a robust, modular platform for building high-functioning, repairable biohybrid machines.

bioengineering↗

PIVOT: an open-source tool for multi-omic spatial data registration

Advances in spatial profiling have resulted in the generation of multi-omic atlases that span biological scales. In general, multiple workflows are required for image registration, coordinate registration, and spot deconvolution to integrate modalities. To improve the throughput of registration of multi-omic cohorts, we introduce PIVOT, a user-friendly and open-source interface for streamlined nonlinear registration. We demonstrate PIVOTs strengths through registration of three multi-omic datasets, and show comparison of its performance to existing workflows.

bioinformatics↗

PIN1 Drives Cellular Plasticity and Immune Modulation in Chronic Pancreatitis

Background and AimsChronic pancreatitis (CP) is characterized by inflammation, fibrosis, and acinar-to-ductal metaplasia (ADM). PIN1, known to drive oncogenic signaling and cellular plasticity in cancer, has an unexplored role in CP. This study investigates PIN1s expression and function in CP pathogenesis using human tissues and mouse models. MethodsPIN1 expression was assessed in human CP tissue microarrays (TMAs) via immunohistochemistry (IHC) and cyclic immunofluorescence (CyCIF). Acute and chronic pancreatitis were induced in wild-type (WT) and PIN1 knockout (PIN1KO) mice using caerulein. Disease progression was monitored histologically, and immune profiling was conducted using flow cytometry. Pharmacological inhibition was performed using a small molecule PIN1 inhibitor-Sulfopin, and effects were evaluated by histology, qPCR, and cytokine analysis. Single-cell RNA sequencing (scRNA-seq) was performed on pancreatic tissues to perform pathway analysis and intercellular communication. ResultsPIN1 expression was elevated in human CP tissues, correlating with disease severity and ADM. In mice, both acute and chronic pancreatitis increased PIN1 expression, but only in our chronic PIN1KO mice displayed reduced pancreatic injury, fibrosis, ADM, and modulated immune infiltration. Pharmacological PIN1 inhibition mimicked the protective effects of genetic knockout, dampening inflammatory pathways. scRNA-seq revealed that PIN1 inhibition altered the intercellular communication networks between epithelial, immune, and stromal cells. ConclusionPIN1 drives cellular plasticity, immune modulation, and disease progression in CP. Targeting PIN1 may offer a therapeutic strategy to mitigate CP. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=184 HEIGHT=200 SRC="FIGDIR/small/653850v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@67f9fcorg.highwire.dtl.DTLVardef@4d4c1forg.highwire.dtl.DTLVardef@c099d7org.highwire.dtl.DTLVardef@b41aa5_HPS_FORMAT_FIGEXP M_FIG C_FIG Created in BioRender. Shah, V. (2025) https://BioRender.com/undefined

cell biology↗

MYC Serine 62 phosphorylation promotes its binding to DNA double strand breaks to facilitate repair and cell survival under genotoxic stress.

Genomic instability is a hallmark of cancer, driving oncogenic mutations that enhance tumor aggressiveness and drug resistance. MYC, a master transcription factor that is deregulated in nearly all human tumors, paradoxically induces replication stress and associated DNA damage while also increasing expression of DNA repair factors and mediating resistance to DNA-damaging therapies. Emerging evidence supports a non-transcriptional role for MYC in preserving genomic integrity at sites of active transcription and protecting stalled replication forks under stress. Understanding how MYCs genotoxic and genoprotective functions diverge may reveal new therapeutic strategies for MYC-driven cancers. Here, we identify a non-canonical role of MYC in DNA damage response (DDR) through its direct association with DNA breaks. We show that phosphorylation at serine 62 (pS62-MYC) is crucial for the efficient recruitment of MYC to damage sites, its interaction with repair factors BRCA1 and RAD51, and effective DNA repair to support cell survival under stress. Mass spectrometry analysis with MYC-BioID2 during replication stress reveals a shift in MYCs interactome, maintaining DDR associations while losing transcriptional regulators. These findings establish pS62-MYC as a key regulator of genomic stability and a potential therapeutic target in cancers.

cancer biology↗

HMG box-containing protein 1 (HBP1) prevents pancreatic injury in experimental pancreatitis but accelerates pancreatic neoplasia progression

Background & AimsPancreatitis is an inflammatory disease of the exocrine pancreas and a known risk factor for pancreatic ductal adenocarcinoma (PDAC). Previously, we identified HMG- box transcription factor 1 (HBP1) as a potential master transcription factor (TF) in the early progression of PDAC, with its expression associated with poor patient survival, underscoring its significance in pancreatic disease. However, the functional role of HBP1 in the onset and progression of acute pancreatitis (AP) remains unknown. MethodsWe examined HBP1 expression in human pancreatitis samples and a cerulein-induced AP mouse model. Pancreatic-specific conditional HBP1 knockout mice, with or without an oncogenic Kras mutation, were generated and compared to their littermate controls. Spatial transcriptomics and multiplexed protein assays, histological analysis, and immunostaining were utilized to characterize pathological changes. Findings from mouse models were validated using inducible HBP1-overexpressing human pancreatic ductal epithelial cells. ResultsHBP1 was upregulated in pancreatic exocrine cells in human chronic pancreatitis and mouse acute pancreatitis, with its expression in human chronic pancreatitis correlating with cancer presence. Pancreatic HBP1 ablation disrupted acinar homeostasis by impairing autophagic flux and exacerbating inflammation following injury. In the presence of oncogenic KRAS, HBP1 ablation delayed the formation of pancreatic intraepithelial neoplasia (PanIN), the precursor to PDAC, and slowed its progression to higher-grade lesions. ConclusionsHBP1 upregulation in pancreatitis mitigates pancreatic inflammatory injury; however, in the presence of oncogenic KRAS, it facilitates PanIN progression. Thus, HBP1 serves as a critical regulator in both pancreatitis and early pancreatic neoplasia, representing a potential therapeutic target for intervening pancreatitis and PanIN progression.

cell biology↗

Longitudinal and multimodal auditing of tumor adaptation to CDK4/6 inhibitors in HR+ metastatic breast cancers

CDK4/6 inhibitors (CDK4/6i) have transformed the treatment of hormone receptor-positive (HR+), HER2-negative (HR+) breast cancers as they are effective across all clinicopathological, age, and ethnicity subgroups for metastatic HR+ breast cancer. In metastatic ER+ breast cancer, CDK4/6i lead to strong and consistent improvement in survival across different lines of therapy. To improve understanding of how metastatic HR+ breast cancers become refractory to CDK4/6i, we have created a multimodal and longitudinal tumor atlas to investigate therapeutic adaptations in malignant cells and in the tumor immune microenvironment. This atlas is part of the NCI Cancer Moonshot Human Tumor Atlas Network and includes seven pairs of pre- and on-progression biopsies from five metastatic HR+ breast cancer patients treated with CDK4/6i. Biopsies were profiled with bulk genomics, transcriptomics, and proteomics as well as single-cell ATAC-seq and multiplex tissue imaging for spatial, single-cell resolution. These molecular datasets were then linked with detailed clinical metadata to create an atlas for understanding tumor adaptations during therapy. Analysis of our atlas datasets suggests a diverse set of tumor adaptations to CDK4/6i therapy. Malignant cells may adapt to therapy via mTORC1 activation, cell cycle bypass, and increased replication stress. The tumor immune microenvironment displayed evidence of both immune activation and immune suppression during therapy. Together, our metastatic ER+ breast cancer atlas represents a rich multimodal resource to better understand HR+ breast cancer tumor therapeutic adaptations to CDK4/6i therapy.

cancer biology↗

Robust biomarker discovery through multiplatform multiplex image analysis of breast cancer clinical cohorts

AO_SCPLOWBSTRACTC_SCPLOWSpatial profiling of tissues promises to elucidate tumor-microenvironment interactions and enable development of spatial biomarkers to predict patient response to immunotherapy and other therapeutics. However, spatial biomarker discovery is often carried out on a single patient cohort or imaging technology, limiting statistical power and increasing the likelihood of technical artifacts. In order to analyze multiple patient cohorts profiled on different platforms, we developed methods for comparative data analysis from three disparate multiplex imaging technologies: 1) cyclic immunofluorescence data we generated from 102 breast cancer patients with clinical follow-up, in addition to publicly available 2) imaging mass cytometry and 3) multiplex ion-beam imaging data. We demonstrate similar single-cell phenotyping results across breast cancer patient cohorts imaged with these three technologies and identify cellular abundance and proximity-based biomarkers with prognostic value across platforms. In multiple platforms, we identified lymphocyte infiltration as independently associated with longer survival in triple negative and high-proliferation breast tumors. Then, a comparison of nine spatial analysis methods revealed robust spatial biomarkers. In estrogen receptor-positive disease, quiescent stromal cells close to tumor were more abundant in good prognosis tumors while tumor neighborhoods of mixed fibroblast phenotypes were enriched in poor prognosis tumors. In triple-negative breast cancer (TNBC), macrophage proximity to tumor and B cell proximity to T cells were greater in good prognosis tumors, while tumor neighborhoods of vimentin-positive fibroblasts were enriched in poor prognosis tumors. We also tested previously published spatial biomarkers in our ensemble cohort, reproducing the positive prognostic value of isolated lymphocytes and lymphocyte occupancy and failing to reproduce the prognostic value of tumor-immune mixing score in TNBC. In conclusion, we demonstrate assembly of larger clinical cohorts from diverse platforms to aid in prognostic spatial biomarker identification and validation. SO_SCPLOWTATEMENTC_SCPLOWO_SCPCAP C_SCPCAPO_SCPLOWOFC_SCPLOWO_SCPCAP C_SCPCAPO_SCPLOWSIGNIFICANCEC_SCPLOWOur single-cell spatial analysis of multiple clinical cohorts uncovered novel biomarkers of patient outcome in breast cancer. Additionally, our data, software, and methods will help advance spatial characterization of the tumor microenvironment.

cancer biology↗

A Novel Mouse Model that Recapitulates the Heterogeneity of Human Triple Negative Breast Cancer

Triple-negative breast cancer (TNBC) patients have a poor prognosis and few treatment options. Mouse models of TNBC are important for development of new targeted therapies, but few TNBC mouse models exist. Here, we developed a novel TNBC murine model by mimicking two common TNBC mutations with high co-occurrence: amplification of the oncogene MYC and deletion of the tumor suppressor PTEN. This Myc;Ptenfl murine model develops TN mammary tumors that display histological and molecular features commonly found in human TNBC. We performed deep omic analyses on Myc;Ptenfl tumors including machine learning for morphologic features, bulk and single-cell RNA-sequencing, multiplex immunohistochemistry and single-cell phenotyping. Through comparison with human TNBC, we demonstrated that this new genetic mouse model develops mammary tumors with differential survival that closely resemble the inter- and intra-tumoral and microenvironmental heterogeneity of human TNBC; providing a unique pre-clinical tool for assessing the spectrum of patient TNBC biology and drug response. Statement of significanceThe development of cancer models that mimic triple-negative breast cancer (TNBC) microenvironment complexities is critical to develop effective drugs and enhance disease understanding. This study addresses a critical need in the field by identifying a murine model that faithfully mimics human TNBC heterogeneity and establishing a foundation for translating preclinical findings into effective human clinical trials.

cancer biology↗

A Web-based Software Resource for Interactive Analysis of Multiplex Tissue Imaging Datasets

Highly multiplexed tissue imaging (MTI) are powerful spatial proteomics technologies that enable in situ single-cell characterization of tissues. However, analysis and visualization of MTI datasets remains challenging, and we developed the Galaxy-ME software hub to address this challenge. Galaxy-ME is a web-based, interactive software hub that enables end-to-end analysis and visualization of MTI datasets and is accessible to everyone. To demonstrate its utility, Galaxy-ME was used to analyze datasets obtained from multiple MTI assays in both normal and cancerous tissues. Galaxy-ME is a publicly available web resource.

bioinformatics↗

A framework for multiplex imaging optimization and reproducible analysis

Multiplex imaging technologies are increasingly used for single-cell phenotyping and spatial characterization of tissues; however, transparent methods are needed for comparing the performance of platforms, protocols and analytical pipelines. We developed a python software, mplexable, for reproducible image processing and utilize Jupyter notebooks to share our optimization of signal removal, antibody specificity, background correction and batch normalization of the multiplex imaging with a focus on cyclic immunofluorescence (CyCIF). Our work both improves the CyCIF methodology and provides a framework for multiplexed image analytics that can be easily shared and reproduced.

cancer biology↗

PTBP1/HNRNP I controls intestinal epithelial cell regeneration by maintaining stem cell survival and stemness

Properly controlled intestinal epithelial cell regeneration is not only vital for protection against insults from environmental hazards but also crucial for preventing intestinal cancer. Intestinal stem cells located in the crypt region provide the driving force for epithelial regeneration, and thus their survival and death must be precisely regulated. We show here that polypyrimidine tract binding protein 1 (PTBP1, also called heterogeneous nuclear ribonucleoprotein I, or HNRNP I), an RNA-binding protein that post-transcriptionally regulates gene expression, is critical for intestinal stem cell survival and stemness. Mechanistically, we show that PTBP1 inhibits the expression of PHLDA3, an AKT repressor, and thereby maintains AKT activity in the intestinal stem cell compartment to promote stem cell survival and proliferation. Furthermore, we show that PTBP1 inhibits the expression of PTBP2, a paralog of PTBP1 that is known to induce neuron differentiation, through repressing inclusion of alternative exon 10 to Ptbp2 transcript. Loss of PTBP1 results in a significant upregulation of PTBP2, which is accompanied by splicing changes in genes that are important for neuronal cell development. This finding suggests that PTBP1 prevents aberrant differentiation of intestinal stem cells into neuronal cells through inhibiting PTBP2. Our results thus reveal a novel mechanism whereby PTBP1 maintains intestinal stem cell survival and stemness through the control of gene function post-transcriptionally.

molecular biology↗

Relevance of Circulating Hybrid Cells as a Non-Invasive Biomarker for Myriad Solid Tumors

AbstractMetastatic progression defines the final stages of tumor evolution and underlies the majority of cancer-related deaths. The heterogeneity in disseminated tumor cell populations capable of seeding and growing in distant organ sites contributes to the development of treatment resistant disease. We recently reported the identification of a novel tumor-derived cell population, circulating hybrid cells (CHCs), harboring attributes from both macrophages and neoplastic cells, including functional characteristics important to metastatic spread. These disseminated hybrids outnumber conventionally defined circulating tumor cells (CTCs) in cancer patients. It is unknown if CHCs represent a generalized cancer mechanism for cell dissemination, or if this population is relevant to the metastatic cascade. Herein, we detect CHCs in the peripheral blood of patients with cancer in myriad disease sites encompassing epithelial and non-epithelial malignancies. Further, we demonstrate that in vivo-derived hybrid cells harbor tumor-initiating capacity in murine cancer models and that CHCs from human breast cancer patients express stem cell antigens, features consistent with the ability to seed and grow at metastatic sites. Finally, we reveal heterogeneity of CHC phenotypes reflect key tumor features, including oncogenic mutations and functional protein expression. Importantly, this novel population of disseminated neoplastic cells opens a new area in cancer biology and renewed opportunity for battling metastatic disease. Simple SummaryThere is an incomplete understanding of circulating neoplastic cell populations and the fundamental mechanisms that drive dissemination, immune evasion, and growth --all critical information to more effectively prevent and treat cancer progression. A novel disseminated tumor cell population, circulating hybrid cells, are detected across many cancer types and carry functional tumor-initiating properties. Additionally, circulating hybrid cells are found at significantly higher levels than conventionally defined circulating tumor cells. Our study demonstrates that neoplastic hybrid cells harbor phenotypic and genetic characteristics of tumor and immune cells, display stem features, and are a generalizable phenomenon in solid tumors. Circulating hybrid cells therefore have relevance as a novel biomarker and open a new field of study in malignancy.

cancer biology↗

Toward reproducible, scalable, and robust data analysis across multiplex tissue imaging platforms

The emergence of megascale single-cell multiplex tissue imaging (MTI) datasets necessitates reproducible, scalable, and robust tools for cell phenotyping and spatial analysis. We developed open-source, graphics processing unit (GPU)-accelerated tools for intensity normalization, phenotyping, and microenvironment characterization. We deploy the toolkit on a human breast cancer (BC) tissue microarray stained by cyclic immunofluorescence and benchmark our cell phenotypes against a published MTI dataset. Finally, we demonstrate an integrative analysis revealing BC subtype-specific features.

systems biology↗

An Integrated Clinical, Omic, and Image Atlas of an Evolving Metastatic Breast Cancer

Mechanisms of therapeutic resistance manifest in metastatic cancers as tumor cell intrinsic alterations and extrinsic microenvironmental influences that can change during treatment. To support the development of methods for the identification of these mechanisms in individual patients, we present here an Omic and Multidimensional Spatial (OMS) Atlas generated from four serial biopsies of a metastatic breast cancer patient during 3.5 years of therapy. This resource links detailed, longitudinal clinical metadata including treatment times and doses, anatomic imaging, and blood-based response measurements to exploratory analytics including comprehensive DNA, RNA, and protein profiles, images of multiplexed immunostaining, and 2- and 3-dimensional scanning electron micrographs. These data reveal aspects of therapy-associated heterogeneity and evolution of the cancers genome, signaling pathways, immune microenvironment, cellular composition and organization, and ultrastructure. We present illustrative examples showing how integrative analyses of these data provide insights into potential mechanisms of response and resistance, and suggest novel therapeutic vulnerabilities.

cancer biology↗

Predictive modeling of virus inactivation by UV

Disinfection strategies are commonly applied to inactivate pathogenic viruses in water, food, air, and on surfaces to prevent the spread of infectious diseases. Determining how quickly viruses are inactivated to mitigate health risks is not always feasible due to biosafety restrictions or difficulties with virus culturability. Therefore, methods that would rapidly predict kinetics of virus inactivation by UV254 would be valuable, particularly for emerging and difficult-to-culture viruses. We conducted a rapid systematic literature review to collect high-quality inactivation rate constants for a wide range of viruses. Using these data and basic virus information (e.g., genome sequence attributes), we developed and evaluated four different model classes, including linear and non-linear approaches, to find the top performing prediction model. For both the (+) ssRNA and dsDNA virus types, multiple linear regressions were the top performing model classes. In both cases, the cross-validated root mean squared relative prediction errors were similar to those associated with experimental rate constants. We tested the models by predicting and measuring inactivation rate constants for two viruses that were not identified in our systematic review, including a (+) ssRNA mouse coronavirus and a dsDNA marine bacteriophage; the predicted rate constants were within 7% and 71% of the experimental rate constants, respectively. Finally, we applied our models to predict the UV254 rate constants of several viruses for which high-quality UV254 inactivation data are not available. Our models will be valuable for predicting inactivation kinetics of emerging or difficult-to-culture viruses.

microbiology↗

Comparison of ultrafiltration and iron chloride flocculation in the preparation of aquatic viromes from contrasting sample types

Viral metagenomes (viromes) are a valuable untargeted tool for studying viral diversity and the central roles viruses play in host disease, ecology, and evolution. Establishing effective methods to concentrate and purify viral genomes prior to sequencing is essential for high quality viromes. Using virus spike-and-recovery experiments, we stepwise compared two common approaches for virus concentration, ultrafiltration and iron chloride flocculation, across diverse matrices: wastewater influent, wastewater secondary effluent, river water, and seawater. Viral DNA was purified by removing cellular DNA via chloroform cell lysis, filtration, and enzymatic degradation of extra-viral DNA. We found that viral genomes were concentrated 1-2 orders of magnitude more with ultrafiltration than iron chloride flocculation for all matrices and resulted in higher quality DNA suitable for amplification-free and long-read sequencing. Given its widespread use and utility as an inexpensive field method for virome sampling, we nonetheless sought to optimize iron flocculation. We found viruses were best concentrated in seawater with 5-fold higher iron concentrations than the standard used, inhibition of DNase activity reduced purification effectiveness, and five-fold more iron was needed to flocculate viruses from freshwater than seawater--critical knowledge for those seeking to apply this broadly used method to freshwater virome samples. Overall, our results demonstrated that ultrafiltration and purification performed better than iron chloride flocculation and purification in the tested matrices. Given that the method performance depended on the solids content and salinity of the samples, we suggest spike-and-recovery experiments be applied when concentrating and purifying sample types that diverge from those tested here. ImportanceViruses in diverse habitats numerically dominate microbial community members and are consequential for host fate and responsible for disease outbreaks. Metagenomics has provided novel insights into their presence, diversity, and ecosystem impacts. Yet the approach is hindered by the challenge that, despite their numbers, viral genomes comprise a minor portion of total community DNA in a sample. To comprehensively describe a viral community with metagenomics, viral genomes must be effectively concentrated and purified to capture low abundance and rare viruses amidst the overwhelming presence of cellular genomic DNA. We evaluated two commonly applied methods for concentrating and purifying viral DNA, ultrafiltration and iron chloride flocculation, across four aquatic sample types that differ in their solids content and salinity. Our findings demonstrated the importance of sample characteristics for method effectivity and provided performance measures for a variety of matrices. These findings contribute a more comprehensive understanding of the impacts of virome sample preparation across diverse matrices and are thus important for guiding future virome studies, given the wide range of habitats in which viruses are studied.

microbiology↗