癌症生物学

Immunohistochemistry (IHC) is a highly specific and widely used laboratory technique for assessing protein localization and expression in tissue samples. Interpretation of 3,3’ diamino benzidine (DAB)-based IHC is often based on observer-dependent manual scoring or traditional imaging software, which may show variability in DAB staining quantification. Furthermore, conventional image analysis tools often face limitations in precisely defining cell boundaries and quantifying membrane-specific signals. In this study, we present a standardized image analysis workflow using CellProfiler, an open-source software for image analysis for the quantification of membrane staining intensity in IHC images captured from slides prepared using formalin-fixed paraffin-embedded (FFPE) human cervical cancer tissue sections. The image analysis workflow was demonstrated using ASCT2 (SLC1A5), a membrane-localized amino acid transporter, as a representative biomarker for membrane-associated protein expression. This protocol involves image preprocessing, object identification, segmentation, and intensity measurement modules to distinguish cell membranes from cytoplasmic regions, enabling automated quantification of membrane intensity signals. The CellProfiler pipeline demonstrated improved accuracy in cell boundary identification and quantification of membrane-specific staining intensity. This is a rapid quantification process, since processing of each image only takes a few seconds; therefore, the analysis for 100 images can be performed within 10–15 min. This segmentation and quantification strategy is applicable to other membrane-based biomarkers after appropriate optimization of segmentation parameters. Following further minor modifications to the object identification modules, this pipeline can be used to detect and quantify cytoplasm- or nuclei-localized DAB-IHC markers across different tissue types. Overall, this protocol provides a standardized, user-friendly, and reproducible workflow for quantitative IHC image analysis that can be broadly applied to the study of protein biomarkers of different localizations, such as nuclei, cytoplasm, and cell membranes from different tissue types.

Gastric cancer remains a major global health challenge, and reliable prognostic biomarkers are urgently needed to guide treatment decisions. Here, we present a simple and efficient protocol for a novel liquid biopsy approach based on quantifying gastric fluid DNA (gfDNA) collected during routine esophagogastroduodenoscopy (EGD). We have previously shown that gfDNA carries gastric cancer–derived mutations; moreover, its concentration increases with tumor progression and varies according to cancer prognosis. This empirically observed increase in gfDNA may mechanistically stem from enhanced cellular turnover, tissue disorganization, dysbiosis of the local microbiota, and/or fluctuations in immune cell infiltrates. Surprisingly, however, in patients diagnosed with gastric cancer, elevated gfDNA levels were also associated with improved survival. This paradoxical finding may be reconciled by an increased anti-tumor immune cell response in treatment-responsive gastric cancers, as well as by the contribution of non-tumoral DNA from inflammatory processes within the microenvironment of the stomach. Here, we detail a standardized protocol for gastric fluid collection and processing, designed to support downstream gfDNA quantification among other potential molecular applications.

Breast cancer is the most frequently diagnosed cancer in women, representing approximately 25% of all cancers in women worldwide. Both breast cancer research and histopathological diagnostics mainly show a two-dimensional planar view of the three-dimensional breast cancerous architecture. Recently, the application of optical tissue clearing, together with 3D microscopy, has been applied to visualize the complexity of whole tumor samples. Preliminary studies on whole-organ mouse mammary glands and tissues from human breast cancer patients subjected to optical tissue clearing and volumetric imaging have enabled the detection of previously unrecognized spatial cellular interactions and structural features within intact breast tissue. There is currently no standardized clearing workflow for breast and lymph node tissues. In this protocol, we optimized and validated the MASH (multiscale architectonic staining of human cortex) immunolabeling-enabled three-dimensional imaging of solvent-cleared organs (iDISCO)-like clearing and labeling pipeline for the investigation of formalin-fixed and paraffin-embedded (FFPE) breast tissue and lymph nodes obtained from breast cancer patients. This illustrates the application of the protocol in a new biological and clinical context, as human breast and lymph node tissues differ substantially from brain tissues in their composition, architecture, and optical properties. Whole FFPE tissue blocks are deparaffinized in liquid paraffin and xylene, bleached through methanol dehydration and a subsequent hydrogen peroxide incubation, and stained with a diverse set of small molecule dyes. As a next step, the tissues are delipidated and subjected to refractive index matching with ethyl cinnamate to reach optimal tissue transparency. Importantly, the applied dehydration and delipidation nicely preserve the morphology of the tissue, and the shrinkage is minimal. This allows reliable 3D imaging of large tissue samples within a timeframe of 10 days, providing clinicians and biomedical researchers with a more holistic view of the FFPE tissue sample and its spatial organization.

Organoids as a drug discovery platform represent an emerging field that continues to refine its tools. NanoBRET (bioluminescence resonance energy transfer) has emerged as a proximity-based and highly sensitive assay to measure protein–protein and protein–ligand interactions. NanoBRET assays were developed and are currently used for 2D cell line experiments. Here, we present the development of the first organoid-compatible Nanoluciferase (Nluc) for 3D model systems. We utilise the Nluc for NanoBRET assays to test drug–target engagement. We describe steps for seeding, transfecting, and replating of mouse colorectal cancer organoids. In addition, we provide detailed procedures for the NanoBRET assay. Various lines of evidence have shown significant difference in drug response between 2D human cell lines and 3D model systems, including patient-derived organoids. Our protocol provides a template for measuring this difference in the context of drug–target engagement.

Patient-derived glioblastoma (GBM) cells are valuable models for GBM research due to their rarity and the highly lethal nature of this cancer. Preserving these cells through long-term cryopreservation is therefore essential for advancing future investigations. However, recent studies have reported that standard cell recovery protocols are inefficient, resulting in poor cell survival and limited regrowth. Here, we established an optimized culture protocol that enhances the recovery and expansion of patient-derived GBM cells by combining Matrigel with an increased concentration of fetal bovine serum (FBS). This approach significantly improves cell attachment and recovery after thawing cells that have been cryopreserved for more than a decade. Importantly, the recovered cells retain key phenotypic characteristics and remain suitable for downstream applications, including drug testing and spheroid formation. Together, this optimized protocol provides a novel strategy to increase the availability of patient-derived GBM cells by improving their efficient recovery from long-term cryopreservation, thereby maximizing their utility in GBM research.

Extracellular vesicles (EVs) are nanoscale particles secreted by all cells and present in all biological fluids, where they carry molecular cargo reflective of health and disease states. Their diagnostic potential is often obscured by the high abundance of non-EV proteins and lipoproteins (e.g., albumin, apolipoproteins) that complicate proteomic analysis of primary biofluids, such as ascites fluid. Conventional isolation strategies face a persistent trade-off between EV purity and yield. To overcome this, a magnetic bead-based protocol (Mag-Net) to enrich EVs according to electrochemical surface charge using strong anion-exchange chemistry (SAX) was adapted for proteomics. Our workflow is specifically adapted to ascites fluid from human or murine sources. This approach effectively separates EVs from high-abundance proteins and lipoproteins, enabling proteomic profiling from as little as 2 μL of ascites fluid. Demonstrated in both murine and human ovarian cancer models, Mag-Net offers a reproducible, scalable, and automation-ready solution for EV isolation from various biofluids.

Breast cancer (BC) is the most frequently diagnosed malignancy in women and a leading cause of cancer-related mortality worldwide. Current clinical management relies on molecular classification—based on estrogen receptor (ER), progesterone receptor (PR), HER2, and Ki67 expression—to guide prognosis and therapy. Triple-negative breast cancer (TNBC), which lacks ER, PR, and HER2 expression, represents 15%–20% of cases and is characterized by aggressive behavior, early recurrence, and a paucity of targeted treatment options. These challenges underscore the urgent need for improved preclinical models that better recapitulate tumor biology to accelerate therapeutic discovery. While conventional monolayer (2D) cultures have contributed significantly to cancer research, they fail to mimic critical features of the three-dimensional (3D) tumor microenvironment (TME), thereby limiting clinical translation. To address this gap, 3D spheroid models have emerged as a powerful intermediary, more accurately replicating in vivo conditions such as cell–cell and cell–matrix interactions, nutrient and oxygen gradients, and the development of hypoxic cores. These features make spheroids a physiologically relevant platform for studying complex processes like metastasis, drug resistance, and treatment response. Here, we present a robust, simple, and cost-effective protocol for generating uniform 3D spheroids. Our method enables consistent monitoring of spheroid formation and growth over time, with quantitative, image-based size analysis to ensure reproducibility and scalability. Designed for flexibility, the protocol is broadly applicable across diverse cell types, effectively bridging the gap between traditional 2D cultures and complex in vivo studies. By providing an accessible and reliable model of the 3D TME, this protocol opens new avenues for high-throughput drug screening, mechanistic studies of tumor progression, and the advancement of personalized medicine strategies in breast cancer and beyond.

Prostate carcinoma (PCa) progression is strongly influenced by the surrounding tumor microenvironment, where cancer-associated fibroblasts (CAFs) represent the most abundant and functionally relevant stromal population. Despite their importance, the lack of stable cell lines representing CAF phenotypes limits the study of stromal–tumor interactions. To address this limitation, we provide an optimized protocol for isolating CAFs from fresh human PCa biopsies based on a mechanical procedure exploiting the specific CAF ability to migrate out from the tumor explants. This approach preserves tissue architecture and maintains CAF viability and phenotype. The resulting ex vivo CAF cultures provide a suitable model to investigate CAF biology within the tumor microenvironment.

Breast cancer remains one of the most prevalent and deadly malignancies affecting women worldwide. Its progression and metastatic behavior are driven by complex mechanisms. To develop more effective therapeutic strategies, it is crucial to understand tumor growth, angiogenesis, and microenvironmental interactions. Although traditional in vivo models such as murine xenografts have long been used to study tumor biology, these approaches are often time-consuming, costly, and ethically constrained. In contrast, the chick embryo chorioallantoic membrane (CAM) assay offers a rapid, cost-effective, and ethically flexible alternative for evaluating tumor development and angiogenesis. This protocol describes an in ovo CAM-based xenograft model in which human breast cancer cells are implanted onto the vascularized CAM of chick embryos. This method enables real-time evaluation of tumor growth. Furthermore, the model allows for manipulation of experimental conditions, including pharmacological treatments or genetic modifications, to study specific molecular mechanisms involved in breast cancer progression. The major advantages of this protocol lie in its simplicity, reduced cost, and capacity for high-throughput screening, making it a valuable tool for translational cancer research.

The extracellular matrix (ECM) critically shapes melanoma progression and therapeutic response, yet commonly used matrices such as Matrigel fail to capture tissue- and disease-specific ECM properties. This protocol provides a streamlined and scalable method for generating murine, tissue-specific ECM hydrogels from skin, lung, and melanoma tumors, therefore overcoming the restricted materials of mouse-derived ECM. The workflow integrates tissue-tailored decellularization, lyophilization, mechanical fragmentation, pepsin digestion, and physiological polymerization to produce hydrogels that reliably preserve fibrillar collagen architecture and organ-specific ECM cues. Decellularization efficiency and ECM integrity are validated by DNA quantification, H&E staining, and Picrosirius Red staining analysis. These hydrogels provide a species- and tissue-matched platform for studying melanoma–ECM–immune interactions, pre-metastatic niche features, and therapy-induced ECM remodeling. Overall, this protocol offers a reproducible and physiologically relevant ECM model that expands experimental capabilities for melanoma biology and treatment-resistance research and that can be easily extended to other tumors and tissues.