Deciphering the role of FUS::DDIT3 expression and tumor microenvironment in myxoid liposarcoma development

BACKGROUND

Myxoid liposarcoma (MLS) displays a distinctive tumor microenvironment and is characterized by the FUS::DDIT3 fusion oncogene, however, the precise functional contributions of these two elements remain enigmatic in tumor development.

METHODS

To study the cell-free microenvironment in MLS, we developed an experimental model system based on decellularized patient-derived xenograft tumors. We characterized the cell-free scaffold using mass spectrometry. Subsequently, scaffolds were repopulated using sarcoma cells with or without FUS::DDIT3 expression that were analyzed with histology and RNA sequencing.

RESULTS

Characterization of cell-free MLS scaffolds revealed intact structure and a large variation of protein types remaining after decellularization. We demonstrated an optimal culture time of 3 weeks and showed that FUS::DDIT3 expression decreased cell proliferation and scaffold invasiveness. The cell-free MLS microenvironment and FUS::DDIT3 expression both induced biological processes related to cell-to-cell and cell-to-extracellular matrix interactions, as well as chromatin remodeling, immune response, and metabolism. Data indicated that FUS::DDIT3 expression more than the microenvironment determined the pre-adipocytic phenotype that is typical for MLS.

CONCLUSIONS

Our experimental approach opens new means to study the tumor microenvironment in detail and our findings suggest that FUS::DDIT3-expressing tumor cells can create their own extracellular niche.

A Small Molecule with Big Impact: MRTX1133 Targets the KRASG12D Mutation in Pancreatic Cancer

KRAS mutations drive oncogenic alterations in numerous cancers, particularly in human pancreatic ductal adenocarcinoma (PDAC). About 93% of PDACs have KRAS mutations, with G12D (∼42% of cases) and G12V (∼32% of cases) being the most common. The recent approval of sotorasib (AMG510), a small-molecule, covalent, and selective KRASG12C inhibitor, for treating patients with non-small cell lung cancer represents a breakthrough in KRAS targeted therapy. However, there is a need to develop other much-needed KRAS-mutant inhibitors for PDAC therapy. Notably, Mirati Therapeutics recently developed MRTX1133, a small-molecule, noncovalent, and selective KRASG12D inhibitor through extensive structure-based drug design. MRTX1133 has demonstrated potent in vitro and in vivo antitumor efficacy against KRASG12D-mutant cancer cells, especially in PDAC, leading to its recent initiation of a phase I/II clinical trial. Here, we provide a summary of the recent advancements related to the use of MRTX1133 for treating KRASG12D-mutant PDAC, focusing on its efficacy and underlying mechanistic actions. In addition, we discuss potential challenges and future directions for MRTX1133 therapy for PDAC, including overcoming intrinsic and acquired drug resistance, developing effective combination therapies, and improving MRTX1133's oral bioavailability and target spectrum. The promising results obtained from preclinical studies suggest that MRTX1133 could revolutionize the treatment of PDAC, bringing about a paradigm shift in its management.

A Humanized Patient-Derived Xenograft Model for Pancreatic Cancer

Pancreatic cancer is associated with a high mortality rate, and there are still very few effective treatment options. Patient-derived xenografts have proven to be invaluable preclinical disease models to study cancer biology and facilitate testing of novel therapeutics. However, the severely immune-deficient mice used to generate standard models lack any functional immune system, thereby limiting their utility as a tool to investigate the tumor-immune cell interface. This chapter will outline a method for establishment of "humanized" patient-derived xenografts, which are reconstituted with human immune cells to imitate the immune-rich microenvironment of pancreatic cancer.

Ex vivo to in vivo model of malignant peripheral nerve sheath tumors for precision oncology

BACKGROUND

Malignant peripheral nerve sheath tumors (MPNST) are aggressive soft tissue sarcomas that often develop in patients with neurofibromatosis type 1 (NF1). To address the critical need for novel therapeutics in MPNST, we aimed to establish an ex vivo 3D platform that accurately captured the genomic diversity of MPNST and could be utilized in a medium-throughput manner for drug screening studies to be validated in vivo using patient-derived xenografts (PDX).

METHODS

Genomic analysis was performed on all PDX-tumor pairs. Selected PDX were harvested for assembly into 3D microtissues. Based on prior work in our labs, we evaluated drugs (trabectedin, olaparib, and mirdametinib) ex vivo and in vivo. For 3D microtissue studies, cell viability was the endpoint as assessed by Zeiss Axio Observer. For PDX drug studies, tumor volume was measured twice weekly. Bulk RNA sequencing was performed to identify pathways enriched in cells.

RESULTS

We developed 13 NF1-associated MPNST-PDX and identified mutations or structural abnormalities in NF1 (100%), SUZ12 (85%), EED (15%), TP53 (15%), CDKN2A (85%), and chromosome 8 gain (77%). We successfully assembled PDX into 3D microtissues, categorized as robust (>90% viability at 48 h), good (>50%), or unusable (<50%). We evaluated drug response to "robust" or "good" microtissues, namely MN-2, JH-2-002, JH-2-079-c, and WU-225. Drug response ex vivo predicted drug response in vivo, and enhanced drug effects were observed in select models.

CONCLUSIONS

These data support the successful establishment of a novel 3D platform for drug discovery and MPNST biology exploration in a system representative of the human condition.

KRAS, NRAS, BRAF, and PIK3CA mutation rates, clinicopathological association, and their prognostic value in Iranian colorectal cancer patients

AIM

Mutations in KRAS, NRAS, BRAF, and PIK3CA genes are critical factors in clinical evaluation of colorectal cancer (CRC) development and progression. In Iran, however, the data regarding genetic profile of CRC patients is limited except for KRAS exon2 and BRAF V600F mutations. This study aimed to investigate the mutational spectrum and prognostic effects of these genes and explore the relationship between these mutations and clinicopathological features of CRC.

METHOD

To achieve these objectives, mutations in KRAS (exons 2, 3, and 4), NRAS (exons 2, 3, and 4), PIK3CA (exons 9 and 20), and BRAF (exon 15) was determined using PCR and pyrosequencing in a total of 151 patients with colorectal cancer.

RESULTS

KRAS, BRAF, NRAS, and PIK3CA mutations were identified in 41%, 5.96%, 3.97%, and 13.24% of the cases, respectively. There were some significant correlations between clinicopathological features and KRAS, PIK3CA, BRAF, and NRAS mutations. Mutations in KRAS and PIK3CA were shown to be independent risk factors for poor survival of the patients at stage I-IV (p < 0.0001 and p = 0.001, respectively). No significant impact on prognosis was observed in patients with BRAF mutations.

CONCLUSION

Our study revealed the prevalence of CRC biomarkers mutations in Iranian patients and emphasized the role of KRAS and PIK3CA on shorter overall survival rates in this population.

Endoscopic Ultrasound-Guided Fine-Needle Biopsies to Generate Preclinical Disease Models to Study Inflammation in Pancreatic Ductal Adenocarcinoma

Patient-derived xenografts (PDXs) are valuable models to study cancer biology, behavior, and response to therapies in vivo. Pancreatic cancer is an aggressive and treatment-resistant disease, and typical biopsies are often of low cellular yield and therefore present challenges for the creation of PDXs. This chapter will describe a method to establish PDX models from tissue biopsies obtained via endoscopic ultrasound-guided fine-needle aspiration, a relatively noninvasive technique which compared to surgery is available to pancreatic cancer patients at all stages of disease. Furthermore, we also describe methods to incorporate "humanization" of PDXs via reconstitution with human immune cells, thus mimicking the immune cell-rich microenvironment of pancreatic tumors.

Colorectal cancer-derived exosomes and modulation KRAS signaling

Colorectal cancer (CRC) is one of the most common cancers worldwide and one of the main causes of cancer-associated mortality. At the period of diagnosis, metastases to other tissues will be present in around 30% of CRC individuals. Individuals with CRC continue to have a poor prognosis despite advances in medication. There is a growing body of literature that CRC develops as a result of the aggregation of various mutations in tumor oncogenes or suppressor genes and that diagnosing cancer in its initial phases may assist in increasing the overall lifespan of individuals with the illness. On the other hand, tumor cells may discharge exosomes in response to oncogenic mutations. By Inhibiting signaling pathways, including the Kirsten rat sarcoma virus (KRAS) mechanism, which is important in a variety of cell activities, exosomes have been shown to cause colorectal cancer in animal studies. The purpose of this review was to summarize the latest discoveries on the modulation of KRAS signaling by exosomes extracted from colorectal cancer.

Exploration of the System-Level Mechanisms of the Herbal Drug FDY003 for Pancreatic Cancer Treatment: A Network Pharmacological Investigation

Pancreatic cancer (PC) is the most lethal cancer with the lowest survival rate globally. Although the prescription of herbal drugs against PC is gaining increasing attention, their polypharmacological therapeutic mechanisms are yet to be fully understood. Based on network pharmacology, we explored the anti-PC properties and system-level mechanisms of the herbal drug FDY003. FDY003 decreased the viability of human PC cells and strengthened their chemosensitivity. Network pharmacological analysis of FDY003 indicated the presence of 16 active phytochemical components and 123 PC-related pharmacological targets. Functional enrichment analysis revealed that the PC-related targets of FDY003 participate in the regulation of cell growth and proliferation, cell cycle process, cell survival, and cell death. In addition, FDY003 was shown to target diverse key pathways associated with PC pathophysiology, namely, the PIK3-Akt, MAPK, FoxO, focal adhesion, TNF, p53, HIF-1, and Ras pathways. Our network pharmacological findings advance the mechanistic understanding of the anti-PC properties of FDY003 from a system perspective.

A pancreas tumor derived organoid study: from drug screen to precision medicine

Pancreatic ductal adenocarcinoma (PDAC) one of the deadliest malignant tumor. Despite considerable progress in pancreatic cancer treatment in the past 10 years, PDAC mortality has shown no appreciable change, and systemic therapies for PDAC generally lack efficacy. Thus, developing biomarkers for treatment guidance is urgently required. This review focuses on pancreatic tumor organoids (PTOs), which can mimic the characteristics of the original tumor in vitro. As a powerful tool with several applications, PTOs represent a new strategy for targeted therapy in pancreatic cancer and contribute to the advancement of the field of personalized medicine.

Understanding cell-cell communication and signaling in the colorectal cancer microenvironment

Carcinomas are complex heterocellular systems containing epithelial cancer cells, stromal fibroblasts, and multiple immune cell-types. Cell-cell communication between these tumor microenvironments (TME) and cells drives cancer progression and influences response to existing therapies. In order to provide better treatments for patients, we must understand how various cell-types collaborate within the TME to drive cancer and consider the multiple signals present between and within different cancer types. To investigate how tissues function, we need a model to measure both how signals are transferred between cells and how that information is processed within cells. The interplay of collaboration between different cell-types requires cell-cell communication. This article aims to review the current in vitro and in vivo mono-cellular and multi-cellular cultures models of colorectal cancer (CRC), and to explore how they can be used for single-cell multi-omics approaches for isolating multiple types of molecules from a single-cell required for cell-cell communication to distinguish cancer cells from normal cells. Integrating the existing single-cell signaling measurements and models, and through understanding the cell identity and how different cell types communicate, will help predict drug sensitivities in tumor cells and between- and within-patients responses.

Patient-derived xenograft (PDX) models of colorectal carcinoma (CRC) as a platform for chemosensitivity and biomarker analysis in personalized medicine

Patient-derived xenograft (PDX) tumor models represent a valuable platform for identifying new biomarkers and novel targets, to evaluate therapy response and resistance mechanisms. This study aimed at establishment, characterization and therapy testing of colorectal carcinoma-derived PDX. We generated 49 PDX and validated identity between patient tumor and corresponding PDX. Sensitivity of PDX toward conventional and targeted drugs revealed that 92% of PDX responded toward irinotecan, 45% toward 5-FU, 65% toward bevacizumab, and 61% toward cetuximab. Expression of epidermal growth factor receptor (EGFR) ligands correlated to the sensitivity toward cetuximab. Proto-oncogene B-RAF, EGFR, Kirsten rat sarcoma virus oncogene homolog gene copy number correlated positively with cetuximab and erlotinib sensitivity. The mutational analyses revealed an individual mutational profile of PDX and mainly identical profiles of PDX from primary tumor vs corresponding metastasis. Mutation in PIK3CA was a determinant of accelerated tumor doubling time. PDX with wildtype Kirsten rat sarcoma virus oncogene homolog, proto-oncogene B-RAF, and phosphatidylinositol-4,5-bisphosphate 3-kinaseM catalytic subunit alfa showed higher sensitivity toward cetuximab and erlotinib. To study the molecular mechanism of cetuximab resistance, cetuximab resistant PDX models were generated, and changes in HER2, HER3, betacellulin, transforming growth factor alfa were observed. Global proteome and phosphoproteome profiling showed a reduction in canonical EGFR-mediated signaling via PTPN11 (SHP2) and AKT1S1 (PRAS40) and an increase in anti-apoptotic signaling as a consequence of acquired cetuximab resistance. This demonstrates that PDX models provide a multitude of possibilities to identify and validate biomarkers, signaling pathways and resistance mechanisms for clinically relevant improvement in cancer therapy.

Current and Future Horizons of Patient-Derived Xenograft Models in Colorectal Cancer Translational Research

Our poor understanding of the intricate biology of cancer and the limited availability of preclinical models that faithfully recapitulate the complexity of tumors are primary contributors to the high failure rate of novel therapeutics in oncology clinical studies. To address this need, patient-derived xenograft (PDX) platforms have been widely deployed and have reached a point of development where we can critically review their utility to model and interrogate relevant clinical scenarios, including tumor heterogeneity and clonal evolution, contributions of the tumor microenvironment, identification of novel drugs and biomarkers, and mechanisms of drug resistance. Colorectal cancer (CRC) constitutes a unique case to illustrate clinical perspectives revealed by PDX studies, as they overcome limitations intrinsic to conventional ex vivo models. Furthermore, the success of molecularly annotated "Avatar" models for co-clinical trials in other diseases suggests that this approach may provide an additional opportunity to improve clinical decisions, including opportunities for precision targeted therapeutics, for patients with CRC in real time. Although critical weaknesses have been identified with regard to the ability of PDX models to predict clinical outcomes, for now, they are certainly the model of choice for preclinical studies in CRC. Ongoing multi-institutional efforts to develop and share large-scale, well-annotated PDX resources aim to maximize their translational potential. This review comprehensively surveys the current status of PDX models in translational CRC research and discusses the opportunities and considerations for future PDX development.

Identification of Differentially Expressed Genes between Original Breast Cancer and Xenograft Using Machine Learning Algorithms

Breast cancer is one of the most common malignancies in women. Patient-derived tumor xenograft (PDX) model is a cutting-edge approach for drug research on breast cancer. However, PDX still exhibits differences from original human tumors, thereby challenging the molecular understanding of tumorigenesis. In particular, gene expression changes after tissues are transplanted from human to mouse model. In this study, we propose a novel computational method by incorporating several machine learning algorithms, including Monte Carlo feature selection (MCFS), random forest (RF), and rough set-based rule learning, to identify genes with significant expression differences between PDX and original human tumors. First, 831 breast tumors, including 657 PDX and 174 human tumors, were collected. Based on MCFS and RF, 32 genes were then identified to be informative for the prediction of PDX and human tumors and can be used to construct a prediction model. The prediction model exhibits a Matthews coefficient correlation value of 0.777. Seven interpretable interactions within the informative gene were detected based on the rough set-based rule learning. Furthermore, the seven interpretable interactions can be well supported by previous experimental studies. Our study not only presents a method for identifying informative genes with differential expression but also provides insights into the mechanism through which gene expression changes after being transplanted from human tumor into mouse model. This work would be helpful for research and drug development for breast cancer.

Genomic characterization of patient-derived xenograft models established from fine needle aspirate biopsies of a primary pancreatic ductal adenocarcinoma and from patient-matched metastatic sites

N-of-1 trials target actionable mutations, yet such approaches do not test genomically-informed therapies in patient tumor models prior to patient treatment. To address this, we developed patient-derived xenograft (PDX) models from fine needle aspiration (FNA) biopsies (FNA-PDX) obtained from primary pancreatic ductal adenocarcinoma (PDAC) at the time of diagnosis. Here, we characterize PDX models established from one primary and two metastatic sites of one patient. We identified an activating KRAS G12R mutation among other mutations in these models. In explant cells derived from these PDX tumor models with a KRAS G12R mutation, treatment with inhibitors of CDKs (including CDK9) reduced phosphorylation of a marker of CDK9 activity (phospho-RNAPII CTD Ser2/5) and reduced viability/growth of explant cells derived from PDAC PDX models. Similarly, a CDK inhibitor reduced phospho-RNAPII CTD Ser2/5, increased apoptosis, and inhibited tumor growth in FNA-PDX and patient-matched metastatic-PDX models. In summary, PDX models can be constructed from FNA biopsies of PDAC which in turn can enable genomic characterization and identification of potential therapies.

Molecular characterization of colorectal cancer patients and concomitant patient-derived tumor cell establishment

Background

We aimed to establish a prospectively enrolled colorectal cancer (CRC) cohort for targeted sequencing of primary tumors from CRC patients. In parallel, we established collateral PDC models from the matched primary tumor tissues, which may be later used as preclinical models for genome-directed targeted therapy experiments.

Results

In all, we identified 27 SNVs in the 6 genes such as PIK3CA (N = 16), BRAF (N = 6), NRAS (N = 2), and CTNNB1 (N = 1), PTEN (N = 1), and ERBB2 (N = 1). RET-NCOA4 translocation was observed in one out of 105 patients (0.9%). PDC models were successfully established from 62 (55.4%) of the 112 samples. To confirm the genomic features of various tumor cells, we compared variant allele frequency results of the primary tumor and progeny PDCs. The Pearson correlation coefficient between the variants from primary tumor cells and PDCs was 0.881.

Methods

Between April 2014 and June 2015, 112 patients with CRC who underwent resection of the primary tumor were enrolled in the SMC Oncology Biomarker study. The PDC culture protocol was performed for all eligible patients. All of the primary tumors from the 112 patients who provided written informed consent were genomically sequenced with targeted sequencing. In parallel, PDC establishment was attempted for all sequenced tumors.

Conclusions

We have prospectively sequenced a CRC cohort of 105 patients and successfully established 62 PDC in parallel. Each genomically characterized PDCs can be used as a preclinical model especially in rare genomic alteration event.

Current status and perspectives of patient-derived xenograft models in cancer research

Cancers remain a major public health problem worldwide, which still require profound research in both the basic and preclinical fields. Patient-derived xenograft (PDX) models are created when cancerous cells or tissues from patients' primary tumors are implanted into immunodeficient mice to simulate human tumor biology in vivo, which have been extensively used in cancer research. The routes of implantation appeared to affect the outcome of PDX research, and there has been increasing applications of patient-derived orthotopic xenograft (PDOX) models. In this review, we firstly summarize the methodology to establish PDX models and then go over recent application and function of PDX models in basic cancer research on the areas of cancer characterization, initiation, proliferation, metastasis, and tumor microenvironment and in preclinical explorations of anti-cancer targets, drugs, and therapeutic strategies and finally give our perspectives on the future prospects of PDX models.

Colorectal cancer models for novel drug discovery

INTRODUCTION

Despite increased screening rates and advances in targeted therapy, colorectal cancer (CRC) remains the third leading cause of cancer-related mortality. CRC models that recapitulate key features of human disease are essential to the development of novel and effective therapeutics. Classic methods of modeling CRC such as human cell lines and xenograft mice, while useful for many applications, carry significant limitations. Recently developed in vitro and in vivo models overcome some of these deficiencies and thus can be utilized to better model CRC for mechanistic and translational research.

AREAS COVERED

The authors review established models of in vitro cell culture and describe advances in organoid culture for studying normal and malignant intestine. They also discuss key features of classic xenograft models and describe other approaches for in vivo CRC research, including patient-derived xenograft, carcinogen-induced, orthotopic transplantation and transgenic mouse models. We also describe mouse models of metastatic CRC.

EXPERT OPINION

No single model is optimal for drug discovery in CRC. Genetically engineered models overcome many limitations of xenograft models. Three-dimensional organoids can be efficiently derived from both normal and malignant tissue for large-scale in vitro and in vivo (transplantation) studies and are thus a significant advance in CRC drug discovery.