Laboratory Investigation

Whole-genome sequencing (WGS) enables comprehensive analysis of tumour genomes, but its use in formalin-fixed paraffin-embedded (FFPE) samples is limited by DNA fragmentation and low yields. Whole-genome amplification (WGA) methods such as multiple displacement amplification (MDA) can boost DNA availability but distort copy-number alteration (CNA) profiles. DNA ligation-mediated MDA (DLMDA) mitigates this bias by reconstituting fragmented templates, yet its performance in FFPE-derived DNA remains uncertain. We compared paired DLMDA pre-amplified (2h, 8h) and non-pre-amplified FFPE prostate tumour samples from 22 archival blocks (5, 15 and 20 years old). DLMDA increased DNA yield by 42- to 86-fold, with global CNA patterns largely preserved. However, DLMDA significantly reduced the number of detected CNA deletions and amplifications. These effects were independent of both block age and reaction time. CNA dropouts were randomly distributed across the genome, indicating that DLMDA does not introduce regional bias. Our results show that DLMDA enables robust DNA yield recovery and avoids false-positive CNA artefacts, but at the cost of reduced CNA sensitivity. While suitable for CNA screening pipelines through WGS, further improvements are required to minimise the false-negative risk and improve the techniques sensitivity for FFPE-based genomics.

BackgroundTumor vasculature is a key driver of glioma progression, yet routine quantification depends on subjective histopathologic assessment or resource-intensive ancillary immunohistochemistry. A scalable, objective method for vascular phenotyping from routine histology remains an unmet need. MethodsWe leveraged 10x Genomics Xenium spatial transcriptomics data from a glioblastoma specimen to generate molecularly resolved annotations of GBM-associated endothelial cells and pericytes across 809,041 cells. These annotations were transferred to matched H&E-stained sections to train a DINO-DETR-based object detection model using a binary classification scheme (vascular vs. other). The model was validated on four independent Xenium patient slides and applied to a retrospective cohort of 119 diffuse gliomas spanning WHO grades 2-4 (oligodendroglioma, astrocytoma, and glioblastoma) with linked survival data. ResultsBinary vascular cell detection achieved a precision of 0.78, a recall of 0.63, and an F1 score of 0.70, with an overall accuracy of 98.6%. Orthogonal spatial validation confirmed that predicted vascular cells were preferentially localized within annotated blood vessel regions. In subtype-stratified survival analysis, high AI-derived vascular cell proportion was significantly associated with worse overall survival in astrocytoma patients (log-rank p < 0.019). ConclusionCross-modal AI training using spatial transcriptomics enables scalable, molecularly informed vascular quantification directly from routine H&E slides. Within the astrocytoma subtype, where tumor grade is most heterogeneous and vascular phenotype most variable, objective vascular quantification provides independent prognostic information demonstrating the potential of spatially supervised deep learning to extract clinically meaningful microenvironmental signals from universally available histologic material.

Circulating tumor cells (CTCs), and especially CTC-clusters, are linked to poor prognosis and may reveal mechanisms of metastasis and treatment resistance. Therefore, developing unbiased methods for the functional characterization of CTCs in liquid biopsies is an urgent need. Here, we present an evaluation of multiplex imaging mass cytometry (IMC) to analyze CTCs in mice with human xenograft tumors. In a single-step process, IMC uses metal-labeled antibodies to simultaneously detect a large number of proteins/modifications within minimally manipulated small volumes of blood from the tail vein or heart. We used breast cancer cell lines and a patient-derived xenograft (PDX) to assess antibodies for cross-species interpretation. Along with manual verification, HALO-AI-based cell segmentation was used to identify CTCs and quantify markers. Despite some limitations regarding human-specificity, this technology can be used to investigate the effect of genetic and pharmacological interventions on the properties of single and cluster CTCs in tumor-bearing mice.

Collagen organisation within the tumour microenvironment plays a critical role in tumour progression and has emerged as an important structural biomarker in cancer. Second Harmonic Generation (SHG) microscopy enables label-free visualisation and quantitative assessment of fibrillar collagen architecture; however, its high cost, specialised instrumentation, and limited field-of-view restrict routine clinical application. In this study, we evaluated whether collagen features quantified from digitally scanned Masson-Goldners Trichrome-stained histopathological sections can approximate measurements obtained from SHG microscopy. Formalin-fixed paraffin-embedded breast tumour tissues, including benign and invasive ductal carcinoma (IDC) samples with varying collagen content, were analysed using SHG microscopy and whole-slide brightfield imaging. Matched regions of interest were analysed using two independent digital image analysis approaches: a conventional ImageJ-based workflow (TWOMBLI) and a machine learning-based computational pipeline. Collagen structural parameters including collagen deposition area, fibre number, and alignment metrics were quantified and compared across imaging modalities using correlation analysis. SHG signals were consistently detected from trichrome-stained sections, confirming compatibility of SHG imaging. Quantitative comparison demonstrated significant concordance between SHG-derived collagen metrics and those obtained from digital image analysis pipelines, particularly for collagen area and fibre alignment. These findings demonstrate that computational analysis of routine histopathological images can capture key spatial features of collagen organisation comparable to SHG microscopy. Digital pathology-based collagen quantification therefore, represents a scalable and clinically accessible approach for assessing extracellular matrix architecture in tumour tissues.

Fluorescent in situ hybridization (FISH) enables highly sensitive, high-resolution detection of gene transcripts. Moreover, by employing multiple probes, this technique allows for multiplexed, simultaneous detection of distinct gene expression patterns spatiotemporally, making it a valuable spatial transcriptomics approach. Owing to these advantages, FISH techniques are rapidly being adopted across diverse areas of basic biology. However, conventional protocols often rely on volatile, toxic reagents such as formalin or methanol, posing potential health risks to researchers. Here, we present a safer protocol that replaces these chemicals with low-toxicity alternatives, without compromising the high detection sensitivity of FISH. We validated this protocol using both in situ hybridization chain reaction (HCR) and signal amplification by exchange reaction (SABER)-FISH in frozen sections of various model organisms, including mouse (Mus musculus), amphibians (Xenopus laevis and Pleurodeles waltl), and medaka (Oryzias latipes). Our results demonstrate successful multiplexed detection of morphogenetic and cell-type marker genes in these model animals using this safer protocol. The protocol has the additional advantage of requiring no proteolytic enzyme treatment, thus preserving tissue integrity. Furthermore, we show that this protocol is fully compatible with EGFP immunostaining, allowing for the simultaneous detection of mRNAs and reporter proteins in transgenic animals. This protocol retains the benefits of highly sensitive, multiplexed, and multimodal detection afforded by integrating in situ HCR and SABER-FISH with immunohistochemistry, while providing a safer option for researchers, thereby offering a valuable tool for basic biology.

Gallbladder cancer (GBC) is a highly lethal malignancy with limited experimental models to study disease biology or evaluate therapeutic responses. Although canonical Wnt activation is commonly used for patient-derived organoid (PDO) development and expansion, gallbladder PDOs has also been generated under Wnt-inhibitory conditions. No comparative assessment has determined how Wnt pathway modulation influences gallbladder PDO development, phenotype or drug response. This study systematically compared the impact of canonical Wnt activation (WNTAct medium containing CHIR99021) versus inhibition (WNTInh medium containing DKK1) on the establishment, propagation, molecular features and therapeutic responses of PDOs generated from malignant or non-malignant gallbladder tissues derived from the same patient. Both media supported successful PDO generation with comparable efficiency, preserving biliary epithelial functions and marker expression. Transcriptomic profiling confirmed selective enrichment of canonical Wnt target genes in PDOs generated in WNTAct cultures. WNTAct conditions enabled markedly superior long-term propagation, whereas WNTInh cultures more consistently retained the dysplastic features in malignant samples. Gemcitabine response assays demonstrated significantly greater drug sensitivity in PDOs grown in WNTAct medium, a phenotype reversible upon media switching but requiring extended adaptation, indicating a dynamic and context-dependent influence of Wnt signaling on chemotherapeutic vulnerability. Collectively, the findings reveal a trade-off between long-term propagation and histological fidelity in gallbladder PDOs and show that Wnt signaling modulates gemcitabine sensitivity in a reversible manner. This comparative framework provides practical guidance for selecting culture conditions for gallbladder PDO based disease modelling and precision oncology applications.

Although several ancillary tests are available in limited laboratories, diagnosis of microphthalmia (MiT)/TFE family translocation renal cell carcinoma (tRCC) could be challenging due to diverse and overlapping tumor morphology and the lack of reliable biomarkers. GPNMB has been recently identified as a diagnostic marker for various renal neoplasms with FLCN/TSC/mTOR-TFE alterations. However, the sensitivity and specificity of GPNMB immunostain are suboptimal and the result interpretation in ambiguous cases could be difficult. To search additional biomarkers that could improve the screening sensitivity and predict genetic aberrations in FLCN/TSC/mTOR-TFE pathway in renal tumors, we performed bioinformatic analysis of publicly available cancer databases and found GPR143, a transmembrane protein regulated by MiT transcription factors, was highly expressed in a subset of renal cell carcinomas (RCCs). In two the Cancer Genome Atlas (TCGA) kidney cancer cohorts, RCCs with high levels of GPR143 expression were enriched for renal neoplasms with FLCN/TSC/mTOR-TFE alterations. Similar to GPNMB labeling, GPR143 immunostain was positive in the majority of tRCC cases and renal tumors with FLCN/TSC/mTOR alterations, suggesting that GPR143 could function as another surrogate marker for FLCN/TSC/mTOR-TFE alterations in certain renal tumors. Interestingly, despite the concordant GPR143 and GPNMB immunoreactivity in most renal neoplasms with FLCN/TSC/mTOR-TFE alterations, diffuse GPR143 immunostain was observed in some cases with negative or focal GPNMB labeling. Taken together, our results indicate GPR143 could serve as a useful adjunct marker to improve the sensitivity for screening renal tumors with FLCN/TSC/mTOR-TFE alterations.

Myeloproliferative neoplasms (MPNs) are characterized by progressive myelofibrosis that drives morbidity and mortality. Liquid biopsy approaches to noninvasively monitor fibrotic progression remain limited. We performed comparative transcriptomic profiling of CD45-depleted platelet-enriched and CD45+ leukocyte-enriched fractions from matched peripheral blood samples of 76 individuals (27 primary myelofibrosis, 17 polycythemia vera, 14 essential thrombocythemia, 18 healthy controls). Platelet RNA sequencing was performed in 2018-2020 on Illumina HiSeq 4000, while WBC RNA sequencing was conducted in 2023 on Illumina NovaSeq 6000 from cryopreserved CD45+ enriched fractions of specimens obtained at the identical time and from the same blood sample as the platelet RNA. Despite comparable library preparation protocols and higher sequencing depth in WBC samples, platelet transcriptomes exhibited 5.1-fold more differential expression in myelofibrosis (3,453 versus 681 genes, adjusted p<0.05, |log2FC|>1). Platelet signatures were enriched for proteostasis pathways including endoplasmic reticulum stress and unfolded protein response, reflecting megakaryocyte dysfunction in the fibrotic bone marrow niche. WBC signatures predominantly featured immune activation and proliferative pathways, indicating systemic inflammatory responses. Multinomial LASSO classification demonstrated superior performance of platelet-based models for myelofibrosis diagnosis (AUROC 0.85) compared to WBC-based (AUROC 0.77) or clinical models (AUROC 0.59). Combined platelet+WBC models did not improve performance (AUROC 0.80), indicating complementary but non-additive information. These findings establish platelet transcriptomic profiling as a superior noninvasive biomarker platform for monitoring myelofibrosis in MPNs, capturing megakaryocyte-driven fibrogenesis with greater sensitivity than peripheral leukocyte-based approaches. HighlightsUsing matched WBC and platelet RNA-seq from MPN patients, we identify myelofibrosis-associated transcriptomic signatures specifically enriched in platelets. Multinomial LASSO modeling highlights platelet-derived gene expression as a dominant and predictive biomarker of myelofibrosis, outperforming clinical parameters and WBC signatures. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=75 SRC="FIGDIR/small/714941v1_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@1d695aborg.highwire.dtl.DTLVardef@fc250forg.highwire.dtl.DTLVardef@1e52e8eorg.highwire.dtl.DTLVardef@15378e3_HPS_FORMAT_FIGEXP M_FIG C_FIG

BackgroundTherapeutic agents targeting the PD1-PDL1 interaction are of great clinical value, however accurately predicting which patients are most likely to benefit is challenging. Improved predictive biomarkers for anti-PD1 therapy are clearly needed. Quantifying PD1 saturation by PDL1 in tumor tissue has the potential to serve as such a biomarker. Here we report a novel bioassay called the PD1 Ligand Receptor Complex Aptamer (LIRECAP) assay and demonstrate it can be used to quantify the saturation of PD1 by PDL1 in formalin-fixed paraffin-embedded tumor biospecimens. ResultsThe PD1 LIRECAP assay was developed by identifying a pair of RNA aptamers. One aptamer preferentially binds to unoccupied PD1 (P aptamer) and the other to the PD1-PDL1 complex (C aptamer). P and C aptamers were added together to a formalin-fixed sample, and bound aptamer extracted. A 2-color qRT-PCR assay using a single set of primers was used to determine the ratio of the sample-bound C to P aptamers (C:P ratio) which reflected PD1 saturation by PDL1 in the sample. Quantification of PD1 saturation by PDL1 as determined by the PD1 LIRECAP assay correlated closely with PD1-mediated signaling and PD1-PDL1 proximity. Analysis of sarcoma FFPE biospecimens confirmed the assay is technically reproducible on clinical biospecimens. There were significant differences in PD1 saturation by PDL1 between patients as well as considerable intratumoral heterogeneity. ConclusionsThe PD1 LIRECAP assay is novel assay that can be used to quantify PD1 saturation by PDL1 in clinical biospecimens. The assay is technically feasible, reproducible, and has the potential to serve as a superior predictive biomarker for PD1/PDL1-based therapy. Similar assays based on this platform could be used in other systems and settings to quantify interaction between two molecules.

Keratin-positive giant cell-rich tumor (KPGCT) is a newly described bone and soft tissue tumor. The tumor is characterized by scattered keratin-positive cells and the presence of HMGA2::NCOR2 fusions. It is not known if the HMGA2::NCOR2 fusion is located in the keratin-positive cells, and little is known about how KPGCT develops. KPGCT shares some histologic features with tenosynovial giant cell tumor (TGCT), a soft tissue tumor with CSF1 rearrangements. Single-nuclei RNA sequencing (snRNA-seq) and Xenium spatial transcriptomics were used to elucidate the mechanisms driving KPGCT and compare KPGCT to TGCT. We show that the neoplastic cells in KPGCT constitute only a minority of cells in the tumor, and that they co-express keratin, HMGA2 and CSF1. The neoplastic cells in KPGCT express no synovial markers, confirming KPGCT as a distinct entity, separate from TGCT. The bulk of the tumor consists of CSF1R-expressing macrophages and osteoclast-like giant cells, suggesting an important role for CSF1-CSF1R signaling. In addition, we find that the cells with the HMGA2 translocation show activation of the hippo signaling pathway, which is known to regulate CSF1 expression. We show that the CSF1-CSF1R axis, possibly regulated through the hippo signaling pathway, plays an important role in KPGCT. This axis likely stimulates the migration and proliferation of macrophages, which form the majority of cells in the tumor, as well as their differentiation into osteoclasts-like giant cells. These results provide a rationale for the use of CSF1R inhibitors, which have already shown efficacy in TGCT, as a therapy for KPGCT. SignificanceKeratin-positive giant cell-rich tumor (KPGCT) is a rare, newly described soft tissue and bone tumor. By examining this tumour on a single-cell level, we confirm the identity of the neoplastic cells on a molecular level, showing these form a minority of cells in the tumor. We show that activation of the hippo pathway in the neoplastic cells is a likely driver of tumorigenesis. Additionally, we show the neoplastic cells produce large amounts of CSF1, attracting the macrophages that form the majority of cells in the tumor. This finding gives supporting evidence for anecdotal reports of response to CSF1 inhibitor therapy. Finally, we identify key differences between KPGCT and tenosynovial giant cell tumor, a tumor that shares histological features with KPGCT.

Engineering macrophages with chimeric antigen receptors is emerging as a promising cancer therapeutic. Chimeric antigen receptor-expressing macrophages (CAR-Ms) engineered to recognize tumor-specific antigens have been shown to inhibit tumor growth and activate adaptive immune responses, leading to robust tumor control in animal studies. Based on this work, clinical trials have been initiated. While the trials have shown promise, challenges remain. The dynamic interactions between CAR-Ms and cancer cells and the exact mechanisms driving anti-tumor effects remain poorly defined. Defining the dynamic interactions between CAR-Ms and cancer cells will provide critical insights for optimizing future CAR-M design and improving therapeutic efficacy. We sought to directly visualize CAR-M interactions with glioblastoma cells at high-resolution and in real-time using CAR-Ms engineered to recognize Neural-Glial Antigen 2 (NG2), an antigen expressed on glioblastoma cells. Using patient-derived glioblastoma cells, we formed glioblastoma spheroids and embedded them in a 3D matrix together with CAR-Ms. Using time-lapse microscopy, as expected, we found that NG2-targeting CAR-Ms engulfed glioblastoma cells. However, excitingly, we found that NG2-targeting CAR-Ms blocked >85% of glioblastoma cell invasion in 3D. This inhibition of glioblastoma invasion was not due to a significant change in CAR-M polarization states. Together, these data suggest that NG2-targeting CAR-Ms both engulf glioblastoma cells and block glioblastoma invasive behavior.

BackgroundCompetitive transplantation is essential for defining intrinsic repopulating capacity of murine hematopoietic stem and progenitor cells (HSPCs), yet comparable assays for human cells have been limited by the lack of a robust in vivo platform. MethodsHere, we describe a novel competitive transplantation method in humanized NOD.Cg-KitW-41J Tyr + Prkdcscid Il2rgtm1Wjl/ThomJ (NBSGW) mice that enables simultaneous engraftment and longitudinal tracking of distinct human grafts within a shared microenvironment. ResultsUsing human leukocyte antigen-mismatched donor CD34+ cells, this method facilitates standard flow cytometry panels to track multiple donor cell chimerism, lineage output, and HSPC composition. The experimental framework may be adapted to different mouse models, conditioning strategies, donor sources, and treatments. ConclusionsOverall, this humanized competitive repopulation assay fills a critical translational gap and offers a flexible foundation for advancing mechanistic discovery in human hematopoietic biology and improving clinical strategies for stem cell transplantation.

BO_SCPLOWACKGROUNDC_SCPLOWThere is increasing momentum behind the clinical implementation of AI-based software for image analysis in digital pathology. As regulations, standards, and national approaches to the clinical use of AI continue to develop, the marketplace of AI products is expanding and evolving - presenting pathologists with a multitude of devices that offer the potential to improve pathology services. MO_SCPLOWETHODSC_SCPLOWTo maintain pace with this changing AI device landscape, we conducted a comprehensive search for, and analysis of, commercial AI products for image analysis in digital pathology. This included CE-marked and Research Use Only (RUO) products using images with histological stains (e.g., H&E) or immunohistochemical (IHC) labelling. Product information and published clinical validation studies were assessed, to understand the quality of supporting evidence on available products, and product details were compiled into a public register: https://osf.io/gb84r/overview. RO_SCPLOWESULTSC_SCPLOWIn total, we identified and assessed 90 CE-marked and 227 RUO AI products. We found that AI products for cancer detection in prostate and breast pathology comprised a substantial portion of the marketplace for H&E image analysis, while IHC products were almost exclusively for use in breast cancer. Clinical validation studies on these products have steadily increased; however, we found that published studies were only available for just over half of H&E products and just over a quarter of IHC products. For CE-marked products, the dataset quality and diversity for AI model performance validation was highly variable, and particularly limited for IHC products. Furthermore, only a limited number of products included studies that assessed measures of clinical utility. CO_SCPLOWONCLUSIONC_SCPLOWAs clinical deployment of AI products for image analysis in histopathology grows, there is a need for transparency, rigorous validation, and clear evidence supporting clinical utility and cost-effectiveness. Independent scrutiny of the expanding offering of AI products provides insight into the opportunities and shortcomings in this domain.

Diffuse large B-cell lymphoma (DLBCL), the most common aggressive lymphoma, encompasses histologically similar but genetically distinct cancers. Recent genetic studies have defined at least six molecular subtypes, yet none account for Epstein-Barr virus (EBV), despite 5-15% of DLBCLs being EBV-associated. By reanalyzing published whole-exome and RNA-sequencing data from 481 tumors, we identified 19 EBV-positive cases. These were significantly enriched in the BN2 subtype (6/19), while most (11/19) remained unclassified. In BN2 tumors, several subtype-defining mutations were reduced in frequency among EBV-positive cases, supporting the hypothesis that EBV oncogenes substitute for specific cellular alterations and may confound DLBCL classification algorithms. Extending our analysis to cell lines, we found that the widely used Val cell line harbors the B95-8 laboratory EBV strain; other EBV-positive lines appeared authentic but modeled only non-BN2 subtypes and expressed an atypical viral latency III program, whereas some DLBCL tumors expressed the atypical latency III program and others latency I or II. Together, these findings demonstrate that EBV-positive DLBCL, like DLBCL itself, is not a single disease, and that current in vitro models only partially capture its biological heterogeneity. Key pointsO_LIEBV-positive DLBCL is not a single disease and EBV status can impact genetic-based classifications. C_LIO_LICurrent EBV-positive DLBCL cell lines do not adequately capture tumor complexity; we determined that Val is a problematic cell line. C_LI

Soft tissue leiomyosarcoma (STLMS) is an aggressive malignancy for which robust molecular subclassification and mechanism-based therapeutic strategies still remain limited. We performed integrative proteogenomic analyses of primary and metastatic STLMS to define subtype-associated molecular programs. Joint analysis of the proteome and phosphoproteome identified 3 biologically distinct subtypes. P1 was characterized by relative genomic stability, low proliferative activity, and enrichment of FGFR2- and PDK-associated signaling. In contrast, P2 and P3 showed greater chromosomal instability and more aggressive clinical behavior, but with distinct molecular features. Notably, P2 was associated with inflammatory and RTK-RAS pathway programs, activation of CDK-AURKA/B-mTOR-ERK kinase networks, IGF1R/PDGFRA alterations, and the poorest outcomes. On the other hand, P3 showed strong cell cycle and DNA repair programs, elevated NCOR1 expression, and increased expression of nonhomologous end joining components, including PARP1. Homologous recombination deficiency analyses distinguished HRD-low P1 from HRD-high P2/P3, and paired analyses suggested increased HRD-related features in metastatic lesions within P3. Immune profiling identified an immune-hot yet potentially suppressive state in P2, marked by higher LGALS9 expression and M2-like macrophage infiltration. To support clinical translation, we developed a tissue microarray-based immunohistochemical classifier that enabled surrogate assignment of proteome-defined subtypes in an independent cohort and showed recurrence-free survival differences across inferred subtypes. These findings together establish a proteogenomic framework for STLMS heterogeneity and nominate subtype-associated biological vulnerabilities for future translational and clinical investigation.

BackgroundHead and neck squamous cell carcinoma (HNSCC) comprises a heterogeneous group of epithelial malignancies associated with poor survival ({approx}50%), limited therapeutic options, and a lack of predictive biomarkers. Concurrent chemoradiotherapy (CRT) remains the standard treatment for advanced disease; however, many patients fail to respond, develop resistance, or eventually relapse. The development of three-dimensional organoid technology has enabled the generation of patient-derived organoids (PDOs), offering a promising platform for personalized therapeutic testing. MethodsWe established a biobank of HNSCC PDOs from fresh laryngeal and pharyngeal tumor samples, including human papillomavirus-positive (HPV+) cases. Organoid formation and expansion rates were analyzed in relation to clinical parameters. Selected representative PDOs were histologically and molecularly characterized. Additionally, several models were exposed to cisplatin and radiation to evaluate treatment response, and a subset was assessed for tumorigenicity in subcutaneous mouse models. ResultsFifty-seven PDO models were successfully established, long-term expanded, and cryopreserved. Prior chemotherapy and/or radiotherapy was identified as an independent negative predictor of organoid outgrowth and expansion capacity compared with treatment-naive samples. Histological features, including differentiation grade and immunohistochemical markers, were largely preserved and strongly correlated with the original tumors. PDOs displayed heterogeneous responses to cisplatin and radiotherapy, with HPV-positive models showing greater sensitivity, consistent with clinical observations. Global transcriptomic profiling revealed molecular subtypes concordant with established HNSCC classifications and suggested an additional subtype characterized by low MYC and mTORC1 transcriptional activity. ConclusionHNSCC PDOs faithfully recapitulate tumor histology and molecular diversity, providing a robust platform to investigate tumor biology and therapeutic response.

Osteosarcoma (OS) is an aggressive bone cancer that most commonly affects children and young adults. OS exhibits a high degree of genomic complexity, as well as cellular plasticity, and dynamic transcriptional regulation is suggested to contribute to treatment resistance and metastasis. Cell lines are well characterized as models to advance our knowledge on OS biology. HOS and U2OS cells have increased invasiveness and higher migratory ability compared with MG63. In this study, we employed a tandem array of consensus transcription factor response elements (catTFREs) proteomic approach to characterize transcription factor (TF) regulatory networks related to OS aggressiveness. We mapped 7,594 proteins and enriched 352 transcription factors and coregulators. When we integrated proteomics with cell line specific gene expression and chromatin accessibility we classified the proteins into different OS cell line dependent sub-clusters and identified TFs and coregulators common for all cell lines and specific for individual cell lines. We demonstrate that RUNX2, MYBL2 and HMGA2 are specifically enriched in HOS and U2OS and may be linked to the cell aggressiveness. ETV5, JUNB, NFIX and ZEB1 were among TFs specific to MG63. Our analysis provides a more comprehensive understanding of the transcriptional drivers that shape OS regulatory landscapes and may have future therapeutic implications.

Anti-hormonal therapies such as selective estrogen receptor modulators like tamoxifen or aromatase inhibitors like letrozole represent a cornerstone for breast cancer prevention and therapy of estrogen receptor-positive breast cancer. Therapeutic monitoring can include blood tests and imaging; however, genetically-based approaches are not yet in practice. Ideally, a test would be able to detect a positive molecular response across different estrogen pathway-suppressive approaches. Circular RNAs are a species of non-coding RNAs detectable in plasma that have been proposed as non-invasive therapeutic biomarkers. To determine whether a set of specific circular RNAs is altered across estrogen-suppressive pathway approaches, we analyzed mammary gland-specific total RNA sequencing data from two individual genetically engineered mouse models (GEMMs) of estrogen pathway-induced breast cancer, with or without exposure to tamoxifen or letrozole. The nf-core/circrna pipeline was used to identify circRNAs that were differentially expressed in response to either tamoxifen or letrozole. We then screened for circRNAs that were differentially regulated by both anti-hormonals. Four up-regulated and 31 down-regulated circRNAs with host genes known to be expressed in human breast epithelial cells were identified as showing reproducible differential regulation in response to anti-hormonal treatment.

BACKGROUNDSubcutaneous white adipose tissue (scWAT), a key metabolic and endocrine organ, is inevitably exposed during radiotherapy (RT). While RT is a cornerstone of cancer treatment, its efficacy is limited by toxicity to surrounding healthy tissues. Ultra-high dose rate (FLASH) RT has emerged as a promising modality capable of preserving tumor control while reducing normal tissue damage - the so-called FLASH effect. Clinical evidence indicates that childhood exposure to conventional (CONV) RT is associated with long-term dysmetabolism and WAT dysfunction. However, the impact of FLASH-RT on WAT has not been investigated. AIMTo compare the effects of FLASH- and CONV-RT on adipocyte function and scWAT homeostasis, and to identify molecular and structural changes associated with each modality. METHODSWe evaluated the effects of FLASH- and CONV-RT on adipocytes and scWAT using a dedicated linear accelerator capable of delivering both modalities. Experiments were performed in the human SGBS preadipocyte/adipocyte cell line and in a mouse model subjected to proximal hind limb irradiation, with analyses conducted 70 days post-exposure. RESULTSRT impaired adipogenic differentiation in a dose-dependent manner, with a relative sparing effect of FLASH at 4-8 Gy. Mature adipocytes exhibited radioresistance, with protection by FLASH at 8 Gy. In vivo, both regimens reduced fat mass without affecting body weight, with greater loss following CONV-RT. Transcriptomic profiling of scWAT revealed inflammatory and neurodegenerative signatures after CONV-RT, whereas FLASH-RT induced minimal transcriptional changes. Histological and ultrastructural analyses confirmed increased cellular damage, vacuolization, lipid spill-over, and reduced PLIN1 expression, predominantly in CONV-treated mice. CONCLUSIONSWAT homeostasis is sensitive to conventional RT, whereas FLASH-RT better preserves tissue structure and function, with implications for long-term metabolic health in cancer survivors.

While single-cell RNA sequencing (scRNA-seq) has been the first widely adopted single-cell transcriptomic approach, its reliance on fresh tissue samples has substantially limited its applicability to clinically relevant specimen. Single-nucleus RNA sequencing (snRNA-seq) overcomes this constrain by enabling transcriptomic profiling from frozen material. However, isolating high-quality nuclei from frozen cardiac tissue remains technically challenging due to the dense extracellular matrix, complex tissue architecture, and heterogeneous cellular composition of the heart. To address these challenges, numerous nuclei isolation protocols have been adapted and optimized, resulting in substantial methodological heterogeneity across studies. Despite the widespread use of snRNA-seq in cardiac research, a robust and standardized nuclei isolation protocol that consistently yields high-quality nuclei from frozen human heart tissue is still lacking. Here, we present a comprehensive, end-to-end protocol for nuclei isolation from frozen human left ventricle, along with a detailed downstream pipeline for snRNA-seq data analysis. Our hybrid nuclei isolation strategy integrates multiple sequential clean-up steps designed to preserve nuclear integrity and RNA quality prior to sequencing. Compared with commonly used nuclei isolation protocols, this approach yields substantially higher number of nuclei while maintaining comparable numbers of detected genes and counts, even at lower sequencing depth. Adoption of this protocol may reduce technical variability across studies and facilitate more reproducible snRNA-seq analyses of human cardiac tissue.