Laboratory Investigation

Non-destructive 3D pathology methods have emerged in recent years with the potential to enhance standard 2D histopathology by greatly increasing the amount of tissue sampled by imaging and by providing volumetric morphological context. Another key advantage is that tissues remain intact, allowing re-embedding after imaging for potential long-term storage and future histological or molecular analyses. However, the impact of 3D pathology protocols on biomolecules -- including DNA, RNA, and proteins -- and their compatibility with downstream assays, has not been systematically evaluated. Here, we applied a previously optimized 3D pathology protocol -- involving deparaffinization, fluorescent H&E-analog staining, optical clearing, and open-top light-sheet microscopy -- to formalin-fixed paraffin-embedded (FFPE) specimens of breast, prostate, and head and neck cancer. Following the protocol, tissues were re-embedded in paraffin and compared with paired FFPE controls that did not undergo 3D pathology processing. DNA and RNA were extracted and subjected to quality assessments. Amplifiability was tested by PCR and reverse transcription quantitative PCR (RT-qPCR) of housekeeping genes. Although the results showed a slight decrease in the average yield and increased fragmentation of both DNA and RNA, amplifiability was largely preserved. Sanger sequencing of the PCR products confirmed accurate sequence determinations, while total RNA sequencing indicated that the global transcriptomic profile was largely unchanged. IHC staining of common biomarkers produced comparable signals, suggesting those proteins are well preserved after the 3D pathology workflow. These results demonstrate the feasibility of combining 3D pathology with downstream molecular applications.

BackgroundSingle-cell RNA-seq has emerged as an innovative technology used to study complex tissues and characterize cell types, states, and lineages at a single-cell level. Classification of bulk tumors by their individual cellular constituents has also created new opportunities to generate single-cell atlases for many organs, cancers, and developmental models. Despite the tremendous promise of this technology, recent evidence studying epithelial tissues and diverse carcinomas suggests the methods used for tissue processing, cell disaggregation, and preservation can significantly bias gene expression and alter the observed cell types. To determine whether sarcomas - tumors of mesenchymal origin - are subject to the same technical artifacts, we profiled patient-derived tumor explants (PDXs) propagated from three aggressive subtypes: osteosarcoma, Ewing sarcoma (ES), desmoplastic small round cell tumor (DSRCT). Given the rarity of these sarcoma subtypes, we explored whether single-nuclei RNA-seq from more widely available archival frozen specimens could accurately be identified by gene expression signatures linked to tissue phenotype or pathognomonic fusion proteins. ResultsWe systematically assessed dissociation methods across different sarcoma subtypes. We compared gene expression from single-cell and single-nucleus RNA-sequencing of 125,831 whole-cells and nuclei from ES, DSRCT, and osteosarcoma PDXs. We detected warm dissociation artifacts in single-cell samples and gene length bias in single-nucleus samples. Classic sarcoma gene signatures were observed regardless of dissociation method. In addition, we showed that dissociation method biases can be computationally corrected. ConclusionsWe highlighted transcriptional biases, including warm dissociation and gene-length biases, introduced by the dissociation method for various sarcoma subtypes. This work is the first to characterize how the dissociation methods used for sc/snRNA-seq may affect the interpretation of the molecular features in sarcoma PDXs.

Atypical fibroxanthoma (AFX) and pleomorphic dermal sarcoma (PDS) are cutaneous neoplasms that fall along a spectrum. PDS is more aggressive than AFX with higher rates of local and distant metastases. Diagnostic biomarkers for AFX and PDS are lacking and therefore these tumors are diagnosed only after excluding other dermal spindle cell neoplasms, including cutaneous leiomyosarcoma (cLMS), spindle cell melanoma (SCM), and sarcomatoid squamous cell carcinoma (sSCC). To identify clinically valuable biomarkers, we contrast the tumors within the diagnostic differential using single-cell RNA sequencing and bulk proteomic data. Gene Ontology (GO) analysis of transcripts and proteins enriched in AFX/PDS identified multiple shared pathways associated with cell adherence and the extracellular matrix. We identify that LRP1, LTBP2, and NAV1 are all enriched in AFX/PDS over other tumors in the differential at both the level of mRNA and protein. IHC reveals that LRP1 is 90% sensitive and 73% specific for AFX/PDS in a cohort of AFX, PDS, cLMS, SCM, and sSCC. This outperforms published data for CD10, which is currently used clinically (sensitivity 83.5% and specificity 50%). When used in conjunction with LTBP2, specificity for AFX/PDS within the differential rises from 73% to 93%. These findings suggest that LRP1, particularly if evaluated in conjunction with existing stains, can improve diagnostic accuracy for AFX and PDS.

Tumor samples are conserved in clinical practice in formalin-fixed paraffin-embedded (FFPE) blocks. Formalin fixation chemically alters nucleic acids, rendering transcriptomic analysis challenging. RNA-sequencing is usually performed on tumor bulk, without distinction of cell subtypes or location. Here we describe the development of a robust method for RNA extraction and exome-capture RNA-sequencing of laser-capture microdissected tumor cells (TC) and stromal immune cells (TIL) based on their morphology. We applied this method on 7 tumor samples (surgical or core needle biopsy) of triple-negative breast cancer (TNBC) stored in FFPE blocks over 3-10 years. Unsupervised clustering and principal component analysis showed a clear separation between gene-expression profile of TIL and TC. TIL were enriched in markers of B cells (CD79B, PAX5 and BLNK) and T cells (CD2, CD3D and CD8B) whereas tumor cells expressed epithelial markers (EPCAM, MUC1 and KRT8). Microenvironment cell populations-counter (MCP)-counter deconvolution showed an enrichment in adaptive immune cell signatures in microdissected TIL. Transcripts of immune checkpoints were differentially expressed in TIL and TC. We further validated our results by qRT-PCR and multispectral immunohistochemistry. In conclusion, we showed that combining laser-capture microdissection and RNA-sequencing on archived FFPE blocks is feasible and allows spatial transcriptional characterization of tumor microenvironment.

T-cell lymphomas are often histologically indistinguishable from benign T-cell infiltrates. Clonality testing is frequently required for diagnosis. It lacks the spatial context and is slow and expensive, relying on complex, multiplexed PCR reactions, interpreted by experienced scientists or pathologists. We previously published details of a pair of highly specific monoclonal antibodies against the two alternatively used, but very similar, T-cell receptor {beta} constant regions, TCR{beta}1 and TCR{beta}2. We demonstrated the feasibility of immunohistochemical detection of TCR{beta}1 and TCR{beta}2 in formalin-fixed, paraffin-embedded (FFPE) tissue as a novel diagnostic strategy for T-cell lymphomas. Here we validate an improved pairing of TCR{beta}1/2 rabbit monoclonal antibodies, and demonstrate their utility for single and double immunostaining, including with a chimeric mouse anti-TCR{beta}2 antibody. Finally, we show that this staining is amenable to automated cell counting, permitting accurate calculation of the TCR{beta}2:TCR{beta}1 ratio.

BackgroundPatient-derived organoids (PDOs) generated from benign breast tissue and breast carcinomas have successfully recapitulated their respective in vivo counterparts. PDOs model tumorigenesis and allow for screening of novel therapeutics personalized to individual patients. However, acquiring cells to generate PDOs is cumbersome. We demonstrate the feasibility of fine needle aspiration biopsy (FNAB) for harvesting cells for PDOs modeling ductal carcinoma in situ (DCIS). MethodsSurgical specimens from patients with biopsy-proven DCIS were used for this study. Core needle biopsy (CNB) was performed on fresh specimens in the operating room, and tissue was mechanically dissociated before culture in basement membrane extract (BME) and organoid medium to generate PDOs. FNAB was performed in the gross room on fresh specimens, and the remaining aspirate was similarly submitted for PDO culture. ResultsPDOs were successfully generated in 15/18 specimens obtained by CNB and 7/11 specimens obtained by FNAB. The average time to initial organoid growth was 4 days for FNAB specimens compared to 19.3 days for CNB specimens. Tumor cells were seen on 7/11 FNAB smears and 16/18 CNB touch preps. Immunofluorescence staining confirmed the presence of both luminal and myoepithelial cells in derived PDOs. ConclusionsFNAB effectively obtains cells for PDOs modeling DCIS. CNB after mincing yielded PDOs with a high success rate, but they were slow to establish. Notably, the time to organoid growth was significantly shorter for FNAB specimens. Thus, FNAB offers an efficient alternative for breast PDO culture and can reduce the time and resources spent on generating PDO cultures.

Traditional clonogenic assays remain central to evaluating the self-renewal capacity of tumor cells. However, the assay relies on subjective endpoint measurements, is restricted to two-dimensional monolayer growth, and lacks the single cell resolution required to resolve heterogeneous expansion behaviors. We describe a high-density microwell array-based platform for quantitative assessment of single cell clonogenic growth outcomes, defined by cell count distributions spanning non-dividing, slow-dividing, and fast-dividing three-dimensional colony forming phenotypes. This approach links initial single-cell occupancy to defined growth outcomes across thousands of indexed microwells per well. The platform integrates high-density, low-adhesion microwell arrays within industry standard device plate formats and an automated image analysis pipeline incorporating machine learning, enabling parallel quantification of spatially indexed founder-derived microwells using widely accessible automated imaging systems. The assay was implemented in both 4-well and 96-well plate formats to evaluate reproducibility and scalability across different plate configurations. Using three glioblastoma cell lines as model systems, we demonstrate reproducible single founder occupancy and consistent clonal growth outcome distributions across replicate formats. This integrated microscale assay platform enables systematic quantitative characterization of clonogenic expansion capacity at single cell resolution and is compatible with applications in cancer biology, therapeutic testing, and functional single cell phenotyping. By resolving single-cell persistence, limited expansion and high expansion outcomes within a scalable high-density format, this approach expands the analytical resolution of single cell clonogenic profiling beyond traditional binary colony scoring.

Deep insights into the complex cellular and molecular changes occurring during different (patho-)physiological conditions are essential for understanding the interactions and regulation of different proteins. This understanding is crucial for both research and diagnostics. However, the effectiveness of conventional immunofluorescence, an effective tool for visualizing the spatial distribution of cells or proteins, is limited in complex tissues. This is mainly due to challenges such as the spectral overlap of fluorophore wavelengths, a limited range of antibody types, and the inherent variability of samples. Multiplex immunofluorescence imaging offers a solution to these limitations by enabling precise localization of proteins and identification of different cell types in a single tissue sample. In this study, we demonstrate the cyclic staining and de-staining of paraffin kidney sections, making it suitable for routine use and compatible with super-resolution microscopy for podocyte ultrastructural studies. We have further developed a computerized workflow for data processing which is accessible to all researchers through commercially available reagents and open-access image analysis codes. As a proof of principle, we identified CDH2 as a marker for cellular lesions of sclerotic glomeruli in the nephrotoxic serum nephritis mouse model and cross-validated this finding with a human Nephroseq dataset indicating its translatability. In summary, our work represents a significant advance in multiplex imaging, which is crucial for understanding the localization of numerous proteins in a single FFPE kidney section and the compatibility with super-resolution microscopy to study ultrastructural changes of podocytes.

The application of single-cell transcriptomic approaches has deepened our understanding of tumor heterogeneity, immune dynamics, and molecular programs underlying therapy response. The recent development of fixation-compatible single-cell platforms, such as 10x Genomics Flex, offers the opportunity to profile archived formalin-fixed, paraffin-embedded (FFPE) specimens, expanding access to clinically valuable samples. However, most benchmarking studies of recent single-cell RNA sequencing (scRNA-seq) technologies have relied on peripheral blood mononuclear cells, limiting their relevance to human tissues. Here, we compared three 10x single-cell RNA profiling methods, fresh tumor scRNA-seq, flash-frozen single-nucleus Multiome, and FFPE single-nucleus Flex (snFlex), using clear cell renal cell carcinoma (ccRCC) biopsies. Across methods, we observed broadly consistent cell type-specific transcriptional profiles among major ccRCC cell populations. Despite lower gene and UMI counts, snFlex reliably identified fine-grained states within CD8+ T cells, tumor-associated macrophages, and tumor compartments, comparable to those detected by scRNA-seq. Together, these findings highlight the distinct advantages of each technology depending on sample preservation type and study design, providing practical guidance for single-cell RNA profiling technology selection in translational studies using human tumor biopsies.

BackgroundRecent advances in molecular genetics have dramatically improved our understanding of the pathophysiology and classification of salivary gland tumors. The identification of recurrent oncogenic fusions has been especially helpful in distinguishing entities with overlapping histomorphology. MethodsChromogenic RNA in situ hybridization (RNA-ISH) using BaseScope technology was performed to detect gene fusions associated with microsecretory adenocarcinoma (MSA), MEF2C::SS18, and mucoepidermoid carcinoma (MEC), CRTC1::MAML2, using probes specific to the exon junctions of the MEF2C::SS18 (exon 7 of MEF2C to exon 4 of SS18) and CRTC1::MAML2 (exon 1 of CRTC1 to exon 2 of MAML2) fusion transcripts. Sixteen cases of MEF2C::SS18 fusion-positive MSA, six cases of CRTC1::MAML2 fusion-positive MEC, three cases of fusion-unknown MEC, and one case of fusion-negative MEC were included in the test cohort. Positive signal strength was assessed using a semi-quantitative scoring method as per manufacturer guidelines. ResultsFusion transcripts were detected by RNA-ISH results in 14/16 cases (88%) of fusion-positive MSAs and 3/6 cases (50%) of fusion-positive MEC. Interestingly, 2 cases (67%) of fusion-unknown MEC were also positive by RNA-ISH for CRTC1::MAML2 while the fusion-negative MEC was also negative by RNA-ISH. Positivity ranged between 1+ (one dot per cell in [≥]5% of tumor cells in one 40X field) and 2+ (two to three dots per cell in [≥]5% of tumor cells in one 40X field). ConclusionHere, we provide the first assessment of chromogenic RNA-ISH to detect gene fusions associated with microsecretory adenocarcinoma, MEF2C::SS18, and mucoepidermoid carcinoma, CRTC1::MAML2. Our results highlight the potential for ultrasensitive RNA-ISH to be used as an alternative method of fusion detection for salivary gland malignancies with highly conserved fusion transcript exon junctions. While additional studies are needed to validate the clinical utility of the assay and to determine optimal testing conditions, RNA-ISH may provide a means for restricted fusion analysis in cases with limited material and for pathologists without easy access to conventional molecular diagnostic testing.

Soft-tissue sarcoma (STS) are rare and heterogeneous mesenchymal tumours with over 100 recognized human subtypes. Despite advances in cytogenetic and molecular characterization, diagnostic precision and therapeutic options remain limited for most subtypes. Spontaneously occurring canine STS could represent valuable translational models, due to their higher incidence and clinical similarity to human counterparts. However, molecular cross-species comparisons of specific subtypes are largely missing. Here, we performed a tissue-resolved, cross-species analysis of tumour and matched adjacent normal tissue (NT) in human and canine fibrosarcoma (FSA) and myxofibrosarcoma (MFS) by laser-capture microdissection of FFPE specimens combined with RNAseq and LC-MS/MS. Multimodal profiling revealed FSA and MFS to represent a molecular continuum rather than distinct entities in both species, resulted in identification of clinically relevant subgroups based on immune activation, proliferative activity and copy number alterations, and identified a novel canine STS subtype associated with a gene fusion. Moreover, our analyses revealed cross-species conserved transcriptomic and proteomic alterations distinguishing tumour from NT, including pathways linked to extracellular matrix remodelling, immune modulation, and cell proliferation. These data establish the first comprehensive molecular comparison of canine and human FSA and MFS, highlight the translational relevance of canine models, and identify candidate biomarkers for diagnostic refinement and development of targeted therapeutic modalities.

BackgroundBreast cancer remains the most frequently diagnosed cancer among women worldwide, with invasive ductal carcinoma (IDC) representing the most common subtype. Despite its high prevalence, current diagnostic workflows rely on 5 {micro}m-thin haematoxylin and eosin-stained (H&E) sections, inherently limiting spatial insight into tumor architecture and extracellular matrix (ECM) organization. As the interest in studying intratumoral heterogeneity increases, three-dimensional (3D) imaging is becoming an increasingly valuable tool. MethodsThis study applied a tissue clearing and imaging pipeline to large formalin-fixed paraffin-embedded (FFPE) breast and lymph node tissue using IDC samples from Maastricht University Medical Centre+. Deparaffinized samples were processed using a modified MASH protocol. Tissues were labelled with Neutral Red, Eosin Y, Methyl Green, and DAPI. Tissue shrinkage was analysed across all processed samples. Two-photon (2P) microscopy was used to image malignant and non-malignant breast tissue, and matched axillary lymph nodes from a patient with grade I IDC to depths of up to 1000 {micro}m via DAPI and second harmonic generation (SHG) channels. Image analysis included assessments of dye penetration, nuclear and collagen content, and fiber orientation using FIJI software. ResultsClearing and staining preserved tissue structure and achieved high transparency across millimetre-scale volumes. 2D surface shrinkage averaged 6.7% (p < 0.001). DAPI signal penetration was consistent with SHG signal profiles up to approximately 600 {micro}m of tissue depth. Structures such as terminal ductal lobular units, adipocytes, vasculature, and lymphoid follicles were clearly visualized in 3D. Quantitative and qualitative analysis in grade I IDC tissue revealed regional differences in cell size and shape, collagen content, and fiber coherency, indicating localized early-stage ECM remodelling. ConclusionThis is the first study to apply 2P microscopy with MASH clearing to large FFPE IDC breast and lymph node samples. The protocol enables reproducible high-resolution volumetric imaging and lays the groundwork for future research applications, leading to potential diagnostic applications.

Epithelioid hemangioendothelioma (EHE) is a difficult to treat vascular sarcoma defined by TAZ- CAMTA1 or YAP-TFE3 fusion proteins. Human cell lines needed to further understand the pathogenesis of EHE have been lacking. Herein, we describe a method to generate EHE extended primary cell cultures. An integrated multi -omic and functional approach was used to characterize these cultures. The cell cultures, relatively homogenous by single cell RNA-Seq, demonstrated established characteristics of EHE including increased proliferation, anchorage independent growth, as well as the overall gene expression profile and secondary genetic alterations seen in EHE. Whole genome sequencing (WGS) identified links to epigenetic modifying complexes, metabolic processes, and pointed to the importance of the extracellular matrix (ECM) in these tumors. Bulk RNA-Seq demonstrated upregulation of pathways including PI3K-Akt signaling, ECM/ECM receptor interaction, and the Hippo signaling pathway. Development of these extended primary cell cultures allowed for single-cell profiling which demonstrated different cell compartments within the cultures. Furthermore, the cultures served as a therapeutic platform to test the efficacy of TEAD inhibitors in vitro. Overall, the development of EHE primary cell cultures will aid in the mechanistic understanding of this sarcoma and serve as a model system to test new therapeutic approaches.

The diagnosis of Mycosis Fungoides (MF) is difficult and often delayed, exacerbated by the constraint of conventional immunohistochemistry (IHC) to analyze only one antigen per tissue section, often necessitating repeat biopsies and extensive workups. We sought to validate a high-throughput Multiplex Immunofluorescence (MIF) method, coupled with computer-automated image analysis, to generate comprehensive immunophenotyping data from a single formalin-fixed, paraffin-embedded (FFPE) biopsy. We applied an 11-biomarker MIF panel across 18 archived skin specimens (9 MF/TCR clonality positive and 9 control/TCR clonality negative). Initial validation confirmed that MIF antigen expression and spatial localization were concordant with sequential IHC-stained sections. Whole slide image stacks were analyzed using both computer-assisted and fully computer-automated pipelines. Both methods successfully delineated immunophenotypic differences. MF specimens showed a significant expansion of hematopoietic cells and proliferative T-lymphocytes compared to controls. Crucially, MF tissues also exhibited a significant increase in the percentage of atypical T-lymphocytes. Our results validate the potential of MIF to obtain comprehensive, high-dimensional diagnostic information from a single tissue section. Integration with computer-automated analysis offers a scalable, high-throughput platform that can significantly aid in the timely and accurate diagnosis of cutaneous lymphomas.

The evaluation of erb-b2 receptor tyrosine kinase 2 (ERBB2 or HER2) gene amplification status through Dual in Situ Hybridization (DISH) currently relies on manual assessment by pathologists. There are several deep learning-based algorithms for H&E or ISH analysis. However, DISH analysis tools are still lacking. We developed a fully automated deep learning-based quantification system to assist pathologists in identifying the most relevant cells throughout the entire DISH image. In the comparison between pathologists and the auto-quantification system, the overall percentage agreement (OPA) by case was 88. 9% (80/90). These results demonstrate that each image, with a processing time of approximately 1 minute, achieves similar results compared to pathologists assessments, while the manual procedure will take 10-20 times longer to examine the same specimen. This approach offers a versatile system for bright-field HER2 DISH image analysis. The system provides faster, cheaper, standardized, and versatile diagnostic tools to aid pathologists in the HER2 DISH diagnostic process.

BackgroundClassification of central nervous system (CNS) tumors has become increasingly complex over the past decade, raising concerns about the availability, feasibility and sustainability of comprehensive molecular diagnostics. We have evaluated nanopore whole genome sequencing (nWGS) as a single workflow to replace multiple diagnostic assays. MethodsWe performed nWGS on DNA extracted from 90 adult CNS tumor samples (58 retrospective, 32 prospective) and compared the results to findings from standard of care (SoC) diagnostic work-up. Analysis was done through an automated workflow that consolidated diagnostically and therapeutically relevant genomic alterations, including copy-number variation, structural, and single-nucleotide variants, chromosomal aberrations, gene fusions and methylation-based classification. ResultsNanopore WGS enabled final diagnostic classification in all samples with >15% tumor cell content, requiring [~]3 hours of hands-on library preparation, parallel sample processing, and sequencing times within 72 hours. Methylation-based classification was available within 1 hour and was concordant with the integrated final diagnosis in 89% of cases (80/90). All diagnostically relevant copy-number variations, single-nucleotide variants, and gene fusions were concordant with standard-of-care testing, and MGMT promoter methylation status matched in 94% of cases. In addition, nWGS identified prognostic and potentially actionable variants that were not reported or covered by SoC. ConclusionsNanopore WGS delivers comprehensive genetic and epigenetic results with a fast turn-around compared to standard methods. This enables efficient, accurate, and scalable molecular diagnostics of CNS tumors using a single platform. Its broad applicability supports its implementation in routine clinical practice and may be extended to other cancer types requiring complex genomic profiling.

BackgroundMulti-analyte liquid biopsies represents an emerging opportunity for non-invasive cancer assessment. We developed ONCE (ONe Aliquot for Circulating Elements), a novel multi-analytes liquid biopsy approach for the isolation of extracellular vesicles (EVs) and cell-free DNA (cfDNA) from a single aliquot of blood. MethodsWe assessed ONCE performance to classify HER2-positive early-stage breast cancer (BrCa) patients by combining RNA and DNA signals on n=64 healthy donors (HD) and non-metastatic BrCa patients. Specifically, we investigated EVs-derived RNA (EV-RNA) and cfDNA by next-generation sequencing (NGS) and by digital droplet PCR (ddPCR). Additionally, we utilized imaging flow cytometry to evaluate EVs as potential carriers of the HER2 protein. ResultsWestern blot analysis and immunocapture assay revealed that EVs-enriched proteins were detected at similar levels among the HER2+ and HER2- subtypes. Sequencing of cfDNA and EV-RNA from HER2- and HER2+ patients demonstrated concordance with in situ molecular analyses of matched tissues. Combined analysis of the two circulating analytes by ddPCR showed increased sensitivity in ERBB2/HER2 detection compared to single nucleic acid components. Multi-analyte liquid biopsy prediction performance was comparable to tissue-based sequencing results from TCGA. Also, we observed HER2 protein on the surface of EVs isolated from the HER2+ BrCa plasma, thus corroborating the potential relevance of studying EVs as companion analyte to cfDNA. ConclusionsThis data confirms the relevance of combining cfDNA and EV-RNA analytes for cancer assessment and supports the ONCE approach as a valuable tool for multi-analytes liquid biopsies clinical implementation.

BackgroundsNext-generation sequencing (NGS) and droplet digital PCR (ddPCR) are both established methods for detecting EGFR mutations in non-small cell lung cancer (NSCLC). However, comprehensive validation of their concordance in mutation detection and variant allele frequency (VAF) quantification across heterogeneous sample types remains limited. Inconsistent results from different sample types (e.g., cfDNA, FFPE) pose a significant challenge to clinical decisions. This is particularly critical for advanced NSCLC patients, who often rely on liquid biopsy, yet the concordance between liquid and tissue-based testing lacks validation in large-scale studies. Another issue in clinical practice is that many tumor samples are limited in quantity, making it difficult to meet testing requirements. Therefore, it is worth exploring whether pre-capture NGS libraries can serve as substitutes for original DNA. MethodsIn this study, we first developed three assays to detect EGFR L858R, exon 19 deletions (Ex19del) and T790M, respectively using ddPCR platform. Their Limit of Detection (LOD) could reach 0.01% at 100 ng of input DNA. Subsequently, we conducted a large retrospective clinical study to systematically compare the detection performance of ddPCR and NGS across three mutation types using approximately 1,000 EGFR-positive samples, including cell-free DNA (cfDNA), pre-capture NGS libraries of cfDNA (cfDNA-prePCR), FFPE-derived DNA (ffpeDNA), pre-capture NGS libraries of FFPE-derived DNA (ffpeDNA-prePCR), fresh tumor tissue DNA (ttDNA), pre-capture NGS libraries of ttDNA (ttDNA-prePCR), pleural effusion supernatants DNA (peDNA), and pre-capture NGS libraries of peDNA (peDNA-prePCR). They were analyzed for detection concordance and VAF correlation. Especially, we made comparisons of the tumor DNA, including ctDNA and tumor tissue DNA, with their paired pre-capture NGS library. ResultsKey findings demonstrated excellent overall agreement between NGS and ddPCR. The mutation detection concordance rates were 98.72% (overall), with subtype-specific rates of 98.93% (L858R), 99.23% (Ex19del), and 97.14% (T790M). VAF measurements between ddPCR and NGS showed exceptional correlation (Pearsons r = 0.975, P<0.001). Notably, pre-capture NGS libraries showed remarkable VAF concordance with their source materials (0.993 for cfDNA libraries vs cfDNA; 0.998 for tumor tissue libraries vs tumor DNA with EGFR L858R; 0.991 for tumor tissue libraries vs tumor DNA with EGFR Ex19del). ConclusionsNGS and ddPCR demonstrate high concordance in EGFR mutation detection and VAF quantification, supporting their complementary roles in clinical testing. Using pre-capture libraries as an alternative to source samples can avoid repeat biopsies and enables subsequent testing for patients with inadequate FFPE sample quantity. These findings establish an evidence base for integrated diagnostic paradigms leveraging NGSs multiplexing power and ddPCRs sensitivity.

Circulating Tumor Cells (CTCs) are commonly analyzed through genomic profiling, which does not capture posttranslational and functional alterations of encoded proteins. To address this limitation, we developed ZeptoCTC, a single-cell protein analysis workflow that combines established technologies for single-cell isolation and sensitive Reverse Phase Protein Array (RPPA) analysis to assess multiple protein expression and activation in individual CTCs. The workflow involves single cell labeling, isolation, lysis, and printing of the true single cell lysates onto a ZeptoChip using a modified micromanipulator CellCelectorTM. Subsequently, the printed lysates undergo fluorescence immunoassay RPPA protein detection using a ZeptoReader followed by signal quantification with Image J software. ZeptoCTC was successfully optimized, beginning with the measurement of EpCAM protein expression--a standard marker for CTC detection. As expected, mean fluorescence signals for EpCAM levels were significantly higher in single MCF-7 cells compared to MDA-MB-231 cells. Next, Capivasertib-treated MCF-7 cells exhibited an approximately 2-fold increase in the pAkt/Akt ratio compared to non-treated control cells. This finding was consistent with a co-performed western blot analysis of pooled MCF-7 cells. Application of ZeptoCTC to the analysis of single CTCs derived from a metastasized breast cancer (MBC) patient indicated a significantly higher level of pAkt, accompanied by a corresponding increase in pErk level when compared to patient-matched WBC. Finally, the current workflow successfully indicated the detectable pAkt and Akt signal difference in CTCs from two MBC patients: one with an Akt1 wild-type genotype, and the other harboring approximately 80% Akt1(E17K) mutated CTCs. The mutated CTCs revealed clearly elevated pAkt levels (1.8-fold), along with an even more strongly elevated total Akt (3.4-fold) when compared to the respective signals measured in wild-type CTCs. In conclusion, ZeptoCTC is a highly sensitive method for measuring the expression and phosphorylation of treatment-relevant proteins in key cancer-driving signaling pathways from true single cell samples.

The immunohistochemistry (IHC) methods widely used in diagnostic medicine and biomedical research are kinetically complex reaction-diffusion processes that, ideally, produce stain intensities correlated with the local antigen concentration. Yet after 75 years of use, practical theoretical tools to rigorously plan and interpret IHC experiments are still lacking. Because modeling the reactions requires time-consuming computer simulation, impractical for regular use, most protocols are optimized empirically, without detailed knowledge of the reaction rates and antigen-antibody equilibria. The resulting stain intensities can be calibrated against standards with known antigen abundance, but they are typically not interpretable in terms of chemical antigen concentrations. To address these limitations, we developed a fast interpolation method to model reaction-diffusion behavior, and experimental methods to characterize IHC kinetic parameters in formalin-fixed paraffin-embedded (FFPE) samples. Used together, these allow experimental measurement of both the chemical concentration of antigen in the sample and the reaction-diffusion parameters consistent with the assay results. Results show 1) direct immunofluorescent detection has low nanomolar sensitivity with >1000-fold dynamic range, and 2) antibody diffusion rates in FFPE samples can be >1000-fold slower than in aqueous solutions, producing diffusion-limited conditions in which the IHC reaction time course may depend on the sample antigen concentration. Awareness of these details is necessary to avoid potential underestimation of both the absolute and relative antigen concentrations in different samples that may occur if staining is stopped before reaching equilibrium. Software tools are provided to allow users to rapidly model IHC reaction time courses and to fit experimental time course data with candidate reaction parameters. The principles described here apply equally to other tissue-based "spatial omics" analyses and should be considered when designing and interpreting experiments requiring any macromolecule to diffuse into and react in a tissue section. SIGNIFICANCEThe theoretical and experimental framework described here advances IHC staining from a qualitative or semi-quantitative method towards a more rigorously quantitative assay. The practical ability to predict IHC reaction kinetics and fit reaction parameters to experimental data has the potential to advance IHC applications in diagnostic medicine and biomedical research in three ways: 1) interpretation of experimental and diagnostic samples stained under different conditions can be more objective, facilitating comparison of results from different protocols and different laboratories; 2) IHC staining can be interpreted as molar chemical antigen-antibody concentrations calculated from the reaction parameters measured in the studied sample; 3) the correlation between antigen concentration and biological behavior can be examined more reliably. Practical software tools are provided.