Liver cancer is one of the most common malignant tumors worldwide. Currently, the available treatment methods cannot fully control its recurrence and mortality rate. Establishing appropriate animal models for liver cancer is crucial for developing new treatment technologies and strategies. The patient-derived xenograft (PDX) model preserves the tumor's microenvironment and heterogeneity, which makes it advantageous for biological research, drug evaluation, personalized medicine, and other purposes. This article reviews the development, preparation techniques, application fields, and challenges of PDX models in liver cancer, providing insights for the research and exploration of PDX models in diagnostic and therapeutic strategies of liver cancer.

Multi-drug nanomedicine is gaining momentum for co-delivering more than one drug to the same site at the same time. Our analysis of 273 pre-clinical tumour growth inhibition studies shows that multi-drug nanotherapy outperforms single-drug therapy, multi-drug combination therapy, and single-drug nanotherapy by 43, 29 and 30%, respectively. Combination nanotherapy also results in the best overall survival rates, with 56% of studies demonstrating complete or partial survival, versus 20-37% for control regimens. Within the multi-drug nanomedicine groups, we analysed the effect of (co-)administration schedule and strategy, passive versus active targeting, nanocarrier material and the type of therapeutic agent. Most importantly, it was found that co-encapsulating two different drugs in the same nanoformulation reduces tumour growth by a further 19% compared with the combination of two individually encapsulated nanomedicines. We finally show that the benefit of multi-drug nanotherapy is consistently observed across different cancer types, in sensitive and resistant tumours, and in xenograft and allograft models. Altogether, this meta-analysis substantiates the value of multi-drug nanomedicine as a potent strategy to improve cancer therapy.

Despite significant research progress, tumor heterogeneity remains elusive, and its complexity poses a barrier to anticancer drug discovery and cancer treatment. Response to the same drug varies across patients, and the timing of treatment is an important factor in determining prognosis. Therefore, development of patient-specific preclinical models that can predict a patient's drug response within a short period is imperative. In this study, a printed gastric cancer (pGC) model is developed for preclinical chemotherapy using extrusion-based 3D bioprinting technology and tissue-specific bioinks containing patient-derived tumor chunks. The pGC model retained the original tumor characteristics and enabled rapid drug evaluation within 2 weeks of its isolation from the patient. In fact, it is confirmed that the drug response-related gene profile of pGC tissues co-cultured with human gastric fibroblasts (hGaFibro) is similar to that of patient tissues. This suggested that the application of the pGC model can potentially overcome the challenges associated with accurate drug evaluation in preclinical models (e.g., patient-derived xenografts) owing to the deficiency of stromal cells derived from the patient. Consequently, the pGC model manifested a remarkable similarity with patients in terms of response to chemotherapy and prognostic predictability. Hence, it is considered a promising preclinical tool for personalized and precise treatments.

Oral tumors are relatively common in dogs, and canine oral squamous cell carcinoma (COSCC) is the most prevalent oral malignancy of epithelial origin. COSCC is locally aggressive with up to 20% of patients showing regional or distant metastasis at the time of diagnosis. The treatment of choice most typically involves wide surgical excision. Although long-term remission is possible, treatments are associated with considerable morbidity and can negatively impact functionality and quality of life. OSCCs have substantial upregulation of the RAS-RAF-MEK-MAPK signaling axis, and we had previously hypothesized that small-molecule inhibitors that target RAS signaling might effectively inhibit tumor growth and progression. Here, we demonstrate that the MEK inhibitor trametinib, an FDA-approved drug for human cancers, substantially inhibits the growth of six COSCC cell lines established from current patient tumor samples. We further show preliminary clinical evidence that the drug is able to cause ~ 40% and ~ 80% tumor regression in two out of four patients with spontaneously occurring COSCC, a partial response according to commonly used RECIST criteria. Given the limited treatment options available and the number of dogs for which standard of care is not acceptable, these preliminary findings provide new hope that more suitable treatment options may soon enter the veterinary clinic.

We are on the brink of a paradigm shift in both theoretical and clinical oncology. Genomic and transcriptomic profiling, alongside personalized approaches that account for individual patient variability, are increasingly shaping discourse. Discussions on the future of personalized cancer medicine are mainly dominated by the potential of non-coding RNAs (ncRNAs), which play a prominent role in cancer progression and metastasis formation by regulating the expression of oncogenic or tumor suppressor proteins at transcriptional and post-transcriptional levels; furthermore, their cell-free counterparts might be involved in intercellular communication. Non-coding RNAs are considered to be promising biomarker candidates for early diagnosis of cancer as well as potential therapeutic agents. This review aims to provide clarity amidst the vast body of literature by focusing on diverse species of ncRNAs, exploring the structure, origin, function, and potential clinical applications of miRNAs, siRNAs, lncRNAs, circRNAs, snRNAs, snoRNAs, eRNAs, paRNAs, YRNAs, vtRNAs, and piRNAs. We discuss molecular methods used for their detection or functional studies both in vitro and in vivo. We also address the challenges that must be overcome to enter a new era of cancer diagnosis and therapy that will reshape the future of oncology.

The chicken chorioallantoic membrane (CAM) model is a potential alternative to the mouse model based on the 3R principles. However, its value for determination of the in vivo behaviors of radiolabeled peptides through positron emission tomography (PET) imaging needed investigation. Herein, the chicken CAM tumor models were established, and their feasibility was evaluated for evaluating the imaging properties of radiolabeled peptides using a 68Ga-labeled HER2 affibody.

Two human breast cancer cell lines were inoculated into chicken CAM and mice, respectively. The tumor-targeting potential and pharmacokinetic profile of a 68Ga-labeled affibody, 68Ga-MZHER, in both tumor models were also determined.

The tumor-formation time in chicken CAM model was shorter than that of mouse model. The uptake values of human epithelial growth factor receptor-2 (HER2)-positive Bcap37 tumors in chicken CAM and mouse models were 5.36 ± 0.26% ID/g and 5.26 ± 0.43% ID/g at 30 min postinjection of 68Ga-MZHER, respectively. At the same time points, the uptake values of HER2-negative MDA-MB-231 tumors in the chicken CAM models and mouse models were 1.57 ± 0.15% ID/g and 1.67 ± 0.25% ID/g, respectively. Ex vivo biodistribution confirmed that more radioactivity accumulated in Bcap37 tumors than in MDA-MD-231 tumors in both CAM and mouse models.

In this study, the CAM tumor model was successfully prepared. The chicken CAM model is a novel tool for quickly determining the in vivo properties of radiolabeled peptides targeting biomarkers. It may be beneficial for early monitoring of the therapeutic effect of a new drug through PET imaging with specific peptides.

Breast Cancer (BrCa) exhibits a high phenotypic heterogeneity, leading to the emergence of aggressive clones and the development of drug resistance. Considering the BrCa heterogeneity and that metabolic reprogramming is a cancer hallmark, we selected seven BrCa cell lines with diverse subtypes to provide their comprehensive metabolome characterization: five lines commonly used (SK-Br-3, T-47D, MCF-7, MDA-MB-436, and MDA-MB-231), and two patient-derived xenografts (Hbcx39 and Hbcx9). We characterized their endometabolomes using 1H-NMR spectroscopy. We found distinct metabolite profiles, with certain metabolites being common but differentially accumulated across the selected BrCa cell lines. High levels of glycine, lactate, glutamate, and formate, metabolites known to promote invasion and metastasis, were detected in all BrCa cells. In our experiment setting were identified unique metabolites to specific cell lines: xanthine and 2-oxoglutarate in SK-Br-3, 2-oxobutyrate in T-47D, cystathionine and glucose-1-phosphate in MCF-7, NAD+ in MDA-MB-436, isocitrate in MDA-MB-231, and NADP+ in Hbcx9. The unique and enriched metabolites enabled us to identify the metabolic pathways modulated in a cell-line-specific manner, which may represent potential candidate targets for therapeutic intervention. We believe this study may contribute to the functional characterization of BrCa cells and assist in selecting appropriate cell lines for drug-response studies.

The high mortality rate of breast cancer motivates researchers to search for effective treatments. Due to their ability to simulate human conditions, xenograft models such as CDX (Cell line-Derived Xenografts) and PDX (Patient-Derived Xenografts) have gained popularity in pre-clinical research. The choice of xenograft technique is influenced by the type of tumor employed, particularly in more aggressive tumor models like TNBC with metastases. Subcutaneous or orthotopic implantation may influence tumor engraftment rates and the applicability of the models for drug testing. To optimize xenograft models and support the development of breast cancer drugs, selecting a suitable transplantation technique is essential to attaining the best results.

This scoping review used PRISMA-Scr methodology to summarize findings from eleven articles published between 2012 and 2024 on pre-clinical trials related to xenograft models for breast cancer considering PDX began traction after 2010. Using specific criteria, the review included studies from electronic platforms. The inclusion criteria ensured relevant English sources were available in full text, while the exclusion criteria eliminated certain types of articles and inadequately comprehensive studies.

Subcutaneous and orthotopic implantation are critical methods for xenograft models in cancer research. Subcutaneous implantation is less invasive and more manageable but does not fully mimic the tumor's natural environment. Orthotopic implantation accurately mimic the migration, invasion, and molecular characteristics of the original tumor, although the procedure is more complex and requires specialized techniques. The specific research objectives determine their choice, the need for accurate tumor replication, and the testing convenience.

Orthotopic implantation is the preferable method for developing PDX and CDX models of breast cancer because it closely mimics the tumor microenvironment and metastatic behavior, yielding clinically relevant results for drug testing. Subcutaneous implantation may result in higher engraftment rates, but it cannot accurately represent the complexity of tumors.

Within ovarian cancer research, patient-derived xenograft (PDX) models recapitulate histologic features and genomic aberrations found in original tumors. However, conflicting data from published studies have demonstrated significant transcriptional differences between PDXs and original tumors, challenging the fidelity of these models. We employed a quantitative mass spectrometry-based proteomic approach coupled with generation of patient-specific databases using RNA-seq data to investigate the proteogenomic landscape of serially-passaged PDX models established from two patients with distinct subtypes of ovarian cancer. We demonstrate that the utilization of patient-specific databases guided by transcriptional profiles increases the depth of human protein identification in PDX models. Our data show that human proteomes of serially passaged PDXs differ significantly from their patient-derived tumor of origin. Analysis of differentially abundant proteins revealed enrichment of distinct biological pathways with major downregulated processes including extracellular matrix organization and the immune system. Finally, we investigated the relative abundances of ovarian cancer-related proteins identified from the Cancer Gene Census across serially passaged PDXs, and found their protein levels to be unstable across PDX models. Our findings highlight features of distinct and dynamic proteomes of serially-passaged PDX models of ovarian cancer.

Sigmoid colon cancer with spinal metastases is rare in distant metastasis. In addition, the prognosis of colon cancer patients with spinal metastases is extremely poor. In order to find effective therapeutic agents, we need to know the biological characteristics of such patients from related models.

We collected sigmoid colon cancer tissue from a young female subject who was diagnosed with sigmoid colon cancer with multiple spinal metastases. We successfully established a sigmoid colon cancer organoid using this tissue and investigated drug screening in the patient. HE staining, immunohistochemistry, and DNA sequencing were utilized to compare the biological characteristics between the original tumor and the organoid. Furthermore, we investigated the drug screening of the sigmoid colon cancer organoid in vitro.

A colon cancer organoid from sigmoid colon cancer with spinal metastases was successfully established. The organoid culture maintained the morphological features, histological features, and genomic landscape of the corresponding sigmoid colon cancer cells. Moreover, we performed drug screening tests to evaluate the effects of chemotherapeutic drugs and targeted drugs.

The sigmoid colon cancer organoid with spinal metastases was a favorable preclinical model to explore the clinicopathologic characteristics of colon cancer patients with spinal metastases.

Patient-derived xenograft (PDX) models of lymphoma typically involve the injection of human tumor cells into an immunocompromised murine host. PDXs have the advantage that the tumor cells grow in a 3D environment within the mouse, meaning the selection pressure of in vitro establishment is avoided and the tumor cells better maintain their genetic heterogeneity. Here, we outline a method for producing and maintaining a PDX model of lymphoma. We describe three different methods to isolate a single cell suspension of the primary patient tumor, followed by either subcutaneous or intraperitoneal injection into an immunocompromised mouse. We then detail how to monitor tumor growth and how to harvest, passage, and store the tumors once they have grown. We highlight and discuss important protocol considerations including technical hints as well as the advantages and disadvantages of the methods described.

Survival is one of the foremost endpoints in cancer therapy, and parametric survival analysis could comprehensively demonstrate the overall result of various different baseline and longitudinal factors. In this study, the survival of triple negative breast cancer 4T1 tumor-bearing mice treated by gemcitabine (GEM) and dexamethasone (DEX) was investigated with model-based analysis. The tumor size, lymphocyte (LY) and neutrophil (NE) of 4T1 tumor-bearing BALB/c mice were collected, and the PK/PD models of these longitudinal data were established in a sequential manner, respectively. The parametric time-to-event (TTE) model of survival was developed and the PK/PD models were tested and integrated as time-varying prognostic factors. The final model was evaluated and externally validated. LY and NE influence the survival directly, while tumor size showed its indirect impact on survival by affecting LY. The exposure of GEM significantly improved the survival results but DEX did not bring extra benefit. The models established in this study quantitatively characterized the abnormal increasing of LY and NE due to tumor progression in T1 tumor-bearing mice and also demonstrate their relationship with survival outcomes, and further provide a modeling framework to demonstrate potential prognostic factors of survival and evaluate the efficacy of different therapies.

The efficacy of radiation treatment (RT) of head and neck squamous cell carcinoma (HNSCC) is limited by radioresistance and the toxicity of FDA approved radiosensitizers. In extension to our previous research where we demonstrated that telaglenastat (CB839) increased efficacy of RT in in vitro and in vivo HNSCC models, here, we examine the radiosensitizing effects of telaglenastat in comparison to cisplatin's, as cisplatin is currently the standard of care for concurrent therapy. Combination of telaglenastat with RT reduced tumor volume in a HNSCC patient derived xenograft mouse model. The efficacy of telaglenastat with RT in reducing cell survival and increasing apoptosis was similar if not greater than that of cisplatin with RT in Cal27 and HN5 HNSCC cells. The addition of telaglenastat increased reactive oxygen species and reduced the antioxidant glutathione in both Cal27 and HN5 cells. Reverse Phase Protein Array analyses revealed alterations in cell death and DNA damage response proteins. This study provides the scientific underpinnings for the use of telaglenastat as a radiosensitizer in the treatment of HNSCC either as an alternative to cisplatin or in cisplatin-ineligible patients.

The tumor microenvironment (TME) is increasingly appreciated to play a decisive role in cancer development and response to therapy in all solid tumors. Hypoxia, acidosis, high interstitial pressure, nutrient-poor conditions, and high cellular heterogeneity of the TME arise from interactions between cancer cells and their environment. These properties, in turn, play key roles in the aggressiveness and therapy resistance of the disease, through complex reciprocal interactions between the cancer cell genotype and phenotype, and the physicochemical and cellular environment. Understanding this complexity requires the combination of sophisticated cancer models and high-resolution analysis tools. Models must allow both control and analysis of cellular and acellular TME properties, and analyses must be able to capture the complexity at high depth and spatial resolution. Here, we review the advantages and limitations of key models and methods in order to guide further TME research and outline future challenges.

Lung cancer is the most critical type of malignant tumor that threatens human health. Traditional preclinical models have certain defects; for example, they cannot accurately reflect the characteristics of lung cancer and their development is costly and time-consuming. Through self-organization, cancer stem cells (CSCs) generate cancer organoids that have a structure similar to that of lung cancer tissues, overcoming to some extent the aforementioned challenges, thus enabling them to have broader application prospects. Lung cancer organoid (LCO) development methods can be divided into three broad categories based on the source of cells, which include cell lines, patient-derived xenografts and patient tumor tissue/pleural effusion. There are 17 different methods that have been described for the development of LCOs. These methods can be further merged into six categories based on the source of cells, the pre-treatment method used, the composition of the medium and the culture scaffold. These categories are: i) CSCs induced by defined transcription factors; ii) suspension culture; iii) relative optimal culture medium; iv) suboptimal culture medium; v) mechanical digestion and suboptimal culture medium; and vi) hydrogel scaffold. In the current review, the advantages and disadvantages of each of the aforementioned methods are summarized, and references for supporting studies are cited.

Patient-derived xenografts (PDX) involve transplanting patient cells or tissues into immunodeficient mice, offering superior disease models compared with cell line xenografts and genetically engineered mice. In contrast to traditional cell-line xenografts and genetically engineered mice, PDX models harbor the molecular and biologic features from the original patient tumor and are generationally stable. This high fidelity makes PDX models particularly suitable for preclinical and coclinical drug testing, therefore better predicting therapeutic efficacy. Although PDX models are becoming more useful, the several factors influencing their reliability and predictive power are not well understood. Several existing studies have looked into the possibility that PDX models could be important in enhancing our knowledge with regard to tumor genetics, biomarker discovery, and personalized medicine; however, a number of problems still need to be addressed, such as the high cost and time-consuming processes involved, together with the variability in tumor take rates. This review addresses these gaps by detailing the methodologies to generate PDX models, their application in cancer research, and their advantages over other models. Further, it elaborates on how artificial intelligence and machine learning were incorporated into PDX studies to fast-track therapeutic evaluation. This review is an overview of the progress that has been done so far in using PDX models for cancer research and shows their potential to be further improved in improving our understanding of oncogenesis.

In T-cell acute lymphoblastic leukemia (T-ALL), more than 50% of cases display autoactivation of Notch1 signaling, leading to oncogenic transformation. We have previously identified a specific chemovar of Cannabis that induces apoptosis by preventing Notch1 maturation in leukemia cells. Here, we isolated three cannabinoids from this chemovar that synergistically mimic the effects of the whole extract. Two were previously known, cannabidiol (CBD) and cannabidivarin (CBDV), whereas the third cannabinoid, which we termed 331-18A, was identified and fully characterized in this study. We demonstrated that these cannabinoids act through cannabinoid receptor type 2 and TRPV1 to activate the integrated stress response pathway by depleting intracellular Ca2+. This is followed by increased mRNA and protein expression of ATF4, CHOP, and CHAC1, which is hindered by inhibiting the upstream initiation factor eIF2α. The increased abundance of CHAC1 prevents Notch1 maturation, thereby reducing the levels of the active Notch1 intracellular domain, and consequently decreasing cell viability and increasing apoptosis. Treatment with the three isolated molecules resulted in reduced tumor size and weight in vivo and slowed leukemia progression in mice models. Altogether, this study elucidated the mechanism of action of three distinct cannabinoids in modulating the Notch1 pathway, and constitutes an important step in the establishment of a new therapy for treating NOTCH1-mutated diseases and cancers such as T-ALL.

Breast cancer (BC) is one of the leading causes of high mortality rates in women worldwide. Although advancements have been made in the design of therapeutic strategies and drug discovery, drug resistance remains one of the key challenges. One of the ways to overcome drug resistance is finding potential drug combinations since the efficacy of combined drugs is higher than their individual efficacies if the combination is a synergistic pair. Therefore, the current study uses a BC patient-derived xenograft (PDX) dataset to evaluate the effects of various cancer drugs on breast cancer in vivo models. The drug effects are further validated by four machine learning models, namely Elastic Net, Least Absolute Shrinkage and Selection (LASSO), Support Vector Machine (SVM), Random Forests (RF), as well as exploring the shortlisted drugs in combination with paclitaxel, a baseline drug for enhanced efficacy on tumor volume reduction. Additionally, the study also shortlists the top 50 in vivo biomarkers correlated with the effects of the drugs. The outcomes could be significantly important for the design of an effective anti-breast cancer therapy.

This study investigates the molecular characteristics and therapeutic implications of the BRCA1 L1780P mutation, a rare variant prevalent among Korean hereditary breast cancer patients. Using patient-derived xenograft (PDX) models and cell lines (PDX-derived cell line) from carriers, sequencing analyses revealed loss of heterozygosity (LOH) at the BRCA1 locus, with one patient losing the wild-type allele and the other mutated allele. This reversion mutation may cf. resistance to homologous recombination deficiency (HRD)-targeting drugs such as PARP inhibitors (PARPi) and ATM inhibitors (ATMi). Although HRDetect and CHORD analyses confirmed a strong association between the L1780P mutation and HRD, effective initially, drug resistance developed in cases with reversion mutations. These findings underscore the complexity of using HRD prediction in personalized treatment strategies for breast cancer patients with BRCA1/2 mutations, as resistance may arise in reversion cases despite high HRD scores.

This MIB guide briefly summarizes the generation of patient-derived xenografts (PDXs) and highlights the importance of validating PDX models for the presence of B cell lymphoma of human origin before their use in radiotheranostic applications. The use of this protocol will allow researchers to learn different methods for screening PDX models for Epstein-Barr virus (EBV)-infected B cell lymphoma.

Hepatocellular carcinoma (HCC), the predominant primary liver tumor, remains one of the most lethal cancers worldwide, despite the advances in therapy in recent years. In addition to the traditional chemically and dietary-induced HCC models, a broad spectrum of novel preclinical tools have been generated following the advent of transgenic, transposon, organoid, and in silico technologies to overcome this gloomy scenario. These models have become rapidly robust preclinical instruments to unravel the molecular pathogenesis of liver cancer and establish new therapeutic approaches against this deadly disease. The present review article aims to summarize and discuss the commonly used preclinical models for HCC, evaluating their strengths and weaknesses.

Celastrol (CEL), an active compound isolated from the root of Tripterygium wilfordii, exhibits broad anticancer activities. However, its poor stability, narrow therapeutic window and numerous adverse effects limit its applications in vivo. In this study, an adenosine triphosphate (ATP) activatable CEL-Fe(III) chelate was designed, synthesized, and then encapsulated with a reactive oxygen species (ROS)-responsive polymer to obtain CEL-Fe nanoparticles (CEL-Fe NPs). In normal tissues, CEL-Fe NPs maintain structural stability and exhibit reduced systemic toxicity, while at the tumor site, an ATP-ROS-rich tumor microenvironment, drug release is triggered by ROS, and antitumor potency is restored by competitive binding of ATP. This intelligent CEL delivery system improves the biosafety and bioavailability of CEL for cancer therapy. Such a CEL-metal chelate strategy not only mitigates the challenges associated with CEL but also opens avenues for the generation of CEL derivatives, thereby expanding the therapeutic potential of CEL in clinical settings.

A high mortality rate makes hepatocellular carcinoma (HCC) a difficult cancer to treat. When surgery is not possible, liver cancer patients are treated with chemotherapy. However, HCC management and treatment are difficult. Sorafenib, which is a first-line treatment for hepatocellular carcinoma, initially slows disease progression. However, sorafenib resistance limits patient survival. Recent studies have linked HCC to programmed cell death, which has increased researcher interest in therapies targeting cell death. Pyroptosis, which is an inflammatory mode of programmed cell death, may be targeted to treat HCC. Pyroptosis pathways, executors, and effects are examined in this paper. This review summarizes how pyroptosis affects the tumor microenvironment (TME) in HCC, including the role of cytokines such as IL-1β and IL-18 in regulating immune responses. The use of chemotherapies and their ability to induce cancer cell pyroptosis as alternative treatments and combining them with other drugs to reduce side effects is also discussed. In conclusion, we highlight the potential of inducing pyroptosis to treat HCC and suggest ways to improve patient outcomes. Studies on cancer cell pyroptosis may lead to new HCC treatments.

Renal cell carcinoma, a leading cause of death in urological malignancies, arises from the nephron. Its characteristics include diversity in disease biology, varied clinical behaviors, different prognoses, and diverse responses to systemic therapies. The term 'organoids' is used to describe structures resembling tissues created through the three-dimensional cultivation of stem cells in vitro. These organoids, when derived from tumor tissues, can retain the diversity of the primary tumor, mirror its spatial tissue structure, and replicate similar organ-like functions. In contrast to conventional two-dimensional cell cultures and the transplantation of tumor tissues into other organisms, organoids derived from tumors maintain the complexity and microenvironment of the original tumor tissue. This fidelity makes them a more reliable model for the development of cancer drugs, potentially accelerating the translation of these drugs to clinical use and facilitating personalized treatment options for patients. This review aims to summarize the recent advancements in the use of organoids for studying renal cell carcinoma, focusing on their cultivation, potential applications, and inherent limitations.

Gastric organoids are models created in the laboratory using stem cells and sophisticated three-dimensional cell culture techniques. These models have shown great promise in providing valuable insights into gastric physiology and advanced disease research. This review comprehensively summarizes and analyzes the research advances in culture methods and techniques for adult stem cells and induced pluripotent stem cell-derived organoids, and patient-derived organoids. The potential value of gastric organoids in studying the pathogenesis of stomach-related diseases and facilitating drug screening is initially discussed. The construction of gastric organoids involves several key steps, including cell extraction and culture, three-dimensional structure formation, and functional expression. Simulating the structure and function of the human stomach by disease modeling with gastric organoids provides a platform to study the mechanism of gastric cancer induction by Helicobacter pylori. In addition, in drug screening and development, gastric organoids can be used as a key tool to evaluate drug efficacy and toxicity in preclinical trials. They can also be used for precision medicine according to the specific conditions of patients with gastric cancer, to assess drug resistance, and to predict the possibility of adverse reactions. However, despite the impressive progress in the field of gastric organoids, there are still many unknowns that need to be addressed, especially in the field of regenerative medicine. Meanwhile, the reproducibility and consistency of organoid cultures are major challenges that must be overcome. These challenges have had a significant impact on the development of gastric organoids. Nonetheless, as technology continues to advance, we can foresee more comprehensive research in the construction of gastric organoids. Such research will provide better solutions for the treatment of stomach-related diseases and personalized medicine.

Oral tumors are relatively common in dogs, and canine oral squamous cell carcinoma (COSCC) is the most prevalent oral malignancy of epithelial origin. COSCC is locally aggressive with up to 20% of patients showing regional or distant metastasis at the time of diagnosis. The treatment of choice most typically involves wide surgical excision. Although long-term remission is possible, treatments are associated with significant morbidity and can negatively impact functionality and quality of life. OSCCs have significant upregulation of the RAS-RAF-MEK-MAPK signaling axis, and we had previously hypothesized that small-molecule inhibitors that target RAS signaling might effectively inhibit tumor growth and progression. Here, we demonstrate that the MEK inhibitor trametinib, an FDA-approved drug for human cancers, significantly blocks the growth of several COSCC cell lines established from current patient tumor samples. We further show clinical evidence that the drug is able to cause significant tumor regression in some patients with spontaneously occurring COSCC. Given the limited treatment options available and the high rate of owner rejection of these offered options, these findings provide new hope that more acceptable treatment options may soon enter the veterinary clinic.

Scientific progress heavily relies on rigorous research, adherence to scientific standards, and transparent reporting. Animal models play a crucial role in advancing biomedical research, especially in the field of gene therapy. Animal models are vital tools in preclinical research, allowing scientists to predict outcomes and understand complex biological processes. The selection of appropriate animal models is critical, considering factors such as physiological and pathophysiological similarities, availability, and ethical considerations. Animal models continue to be indispensable tools in preclinical gene therapy research. Advancements in genetic engineering and model selection have improved the fidelity and relevance of these models. As gene therapy research progresses, careful consideration of animal models and transparent reporting will contribute to the development of effective therapies for various genetic disorders and diseases. This comprehensive review explores the use of animal models in preclinical gene therapy studies for approved products up to September 2023. The study encompasses 47 approved gene therapy products, with a focus on preclinical trials. This comprehensive analysis serves as a valuable reference for researchers in the gene therapy field, aiding in the selection of suitable animal models for their preclinical investigations.

Small cell lung cancer (SCLC) is a highly aggressive type of cancer frequently diagnosed with metastatic spread, rendering it surgically unresectable for the majority of patients. Although initial responses to platinum-based therapies are often observed, SCLC invariably relapses within months, frequently developing drug-resistance ultimately contributing to short overall survival rates. Recently, SCLC research aimed to elucidate the dynamic changes in the genetic and epigenetic landscape. These have revealed distinct subtypes of SCLC, each characterized by unique molecular signatures. The recent understanding of the molecular heterogeneity of SCLC has opened up potential avenues for precision medicine, enabling the development of targeted therapeutic strategies. In this review, we delve into the applied models and computational approaches that have been instrumental in the identification of promising drug candidates. We also explore the emerging molecular diagnostic tools that hold the potential to transform clinical practice and patient care.

Rare sarcomas present significant treatment challenges compared to more prevalent soft tissue sarcomas due to limited treatment options and a poor understanding of their biology. This study investigates a unique case of penile sarcoma, providing a comprehensive morphological and molecular analysis. Through the creation of experimental patient-derived models-including patient-derived xenograft (PDX), 3D, and monolayer primary cultures-we successfully replicated crucial molecular traits observed in the patient's tumor, such as smooth muscle actin and CD99 expression, along with specific mutations in genes like TSC2 and FGFR4. These models are helpful in assessing the potential for an in-depth exploration of this tumor's biology. This comprehensive approach holds promise in identifying potential therapeutic avenues for managing this exceedingly rare soft tissue sarcoma.

Metastatic penile squamous cell carcinoma (PSCC) has only a 50% response rate to first-line combination chemotherapies and there are currently no targeted-therapy approaches. Therefore, we have an urgent need in advanced-PSCC treatment to find novel therapies. Approximately half of all PSCC cases are positive for high-risk human papillomavirus (HR-HPV). Our objective was to generate HPV-positive (HPV+) and HPV-negative (HPV-) patient-derived xenograft (PDX) models and to determine the biological differences between HPV+ and HPV- disease. We generated four HPV+ and three HPV- PSCC PDX animal models by directly implanting resected patient tumor tissue into immunocompromised mice. PDX tumor tissue was found to be similar to patient tumor tissue (donor tissue) by histology and short tandem repeat fingerprinting. DNA mutations were mostly preserved in PDX tissues and similar APOBEC (apolipoprotein B mRNA editing catalytic polypeptide) mutational fractions in donor tissue and PDX tissues were noted. A higher APOBEC mutational fraction was found in HPV+ versus HPV- PDX tissues (p = 0.044), and significant transcriptomic and proteomic expression differences based on HPV status included p16 (CDKN2A), RRM2, and CDC25C. These models will allow for the direct testing of targeted therapies in PSCC and determine their response in correlation to HPV status.

Patient-derived cancer organoids (PDOs) hold considerable promise for personalizing therapy selection and improving patient outcomes. However, it is challenging to generate PDOs in sufficient numbers to test therapies in standard culture platforms. This challenge is particularly acute for pancreatic ductal adenocarcinoma (PDAC) where most patients are diagnosed at an advanced stage with non-resectable tumors and where patient tissue is in the form of needle biopsies. Here the development and characterization of microfluidic devices for testing therapies using a limited amount of tissue or PDOs available from PDAC biopsies is described. It is demonstrated that microfluidic PDOs are phenotypically and genotypically similar to the gold-standard Matrigel organoids with the advantages of 1) spheroid uniformity, 2) minimal cell number requirement, and 3) not relying on Matrigel. The utility of microfluidic PDOs is proven by testing PDO responses to several chemotherapies, including an inhibitor of glycogen synthase kinase (GSKI). In addition, microfluidic organoid cultures are used to test effectiveness of immunotherapy comprised of NK cells in combination with a novel biologic. In summary, our microfluidic device offers considerable benefits for personalizing oncology based on cancer biopsies and may, in the future, be developed into a companion diagnostic for chemotherapy or immunotherapy treatments.

Biomaterials embody a groundbreaking paradigm shift in the field of drug delivery and human applications. Their versatility and adaptability have not only enriched therapeutic outcomes but also significantly reduced the burden of adverse effects. This work serves as a comprehensive overview of biomaterials, with a particular emphasis on their pivotal role in drug delivery, classifying them in terms of their biobased, biodegradable, and biocompatible nature, and highlighting their characteristics and advantages. The examination also delves into the extensive array of applications for biomaterials in drug delivery, encompassing diverse medical fields such as cancer therapy, cardiovascular diseases, neurological disorders, and vaccination. This work also explores the actual challenges within this domain, including potential toxicity and the complexity of manufacturing processes. These challenges emphasize the necessity for thorough research and the continuous development of regulatory frameworks. The second aim of this review is to navigate through the compelling terrain of recent advances and prospects in biomaterials, envisioning a healthcare landscape where they empower precise, targeted, and personalized drug delivery. The potential for biomaterials to transform healthcare is staggering, as they promise treatments tailored to individual patient needs, offering hope for improved therapeutic efficacy, fewer side effects, and a brighter future for medical practice.

Translational oncology research strives to explore a new aspect: identifying subgroups that exhibit treatment response even during pre-clinical phases. In this study, we focus on PDX models and their implementation in mouse clinical trials (MCT). Our primary objective was to identify subgroups with different treatment responses using Latent Class Mixed Model (LCMM).We used a public dataset and focused on one treatment, encorafenib, and two indications, melanoma and colorectal cancer, for which efficacy depends on a specific mutation BRAF V600E. One LCMM per indication was implemented to classify treatment responses at the PDX level, analyzing the growth kinetics of treated tumors and matched controls within the PDX models. A simulation study was carried out to explore the performance of LCMM in this context. For both applications, LCMM identified classes for which the higher the proportion of mutated BRAF V600E PDX models the greater the treatment effect, which is aligned with encorafenib use recommendations. The simulation study showed that LCMM could identify classes with large differences in treatment effects. LCMM is a suitable tool for MCT to explore treatment response subgroups of PDX. Once these subgroups are defined, characterization of their phenotypes/genotypes could be performed to explore treatment response predictors.

Digestive system tumors are the leading cause of cancer-related deaths worldwide. Despite ongoing research, our understanding of their mechanisms and treatment remain inadequate. One promising tool for clinical applications is the use of gastrointestinal tract tumor organoids, which serve as an important in vitro model. Tumor organoids exhibit a genotype similar to the patient's tumor and effectively mimic various biological processes, including tissue renewal, stem cell, and ecological niche functions, and tissue response to drugs, mutations, or injury. As such, they are valuable for drug screening, developing novel drugs, assessing patient outcomes, and supporting immunotherapy. In addition, innovative materials and techniques can be used to optimize tumor organoid culture systems. Several applications of digestive system tumor organoids have been described and have shown promising results in related aspects. In this review, we discuss the current progress, limitations, and prospects of this model for digestive system tumors.

The use of patient-derived xenografts (PDXs) in cancer research is increasing due to their ability to closely mimic the features of patient tumors. The ability to quickly and robustly measure protein expression levels in these tissues is a key methodology required in a broad range of experimental designs. Western blotting (WB) is a cost effective and simple tool that is highly specific and sensitive for detecting and quantifying individual proteins, posttranslational modifications and aberrant signaling pathways. Here, we described a method to assess protein expression in PDX tissues using WB to detect proteins involved in cell growth signaling pathways.