Interrogating open issues in cancer precision medicine with patient-derived xenografts

Sympathetic axonogenesis promotes adenoid cystic carcinoma progression

Nerves are integral to the adenoid cystic carcinoma (ACC) microenvironment. The strong association of ACC with perineural invasion (PNI) is considered a hallmark of this disease. In human salivary ACC, we identify intratumoral, small-caliber, disorganized sympathetic nerves not observed in other salivary neoplasms. Norepinephrine or sympathetic ganglia explants enhance ACC proliferation in vitro. Two novel orthotopic ACC patient-derived xenograft (PDX) models recapitulate ACC morphology and demonstrate sympathetic innervation. Pharmacologic or surgical blockade of sympathetic nerves decreases ACC PDX growth. Bulk RNA sequencing of salivary ACC reveals correlations between noradrenergic nerve development signatures and worse patient survival. Metastatic ACC foci exhibit lower nerve signature gene expression levels than primary ACC. Sympathetic innervation in ACC is distinct from PNI and reflects tumor axonogenesis driven by noradrenergic neural development programs. These programs support ACC progression, are associated with poor prognosis, and may be inhibited as a therapeutic strategy.

Results of the Phase I/II Study and Preliminary B-cell Gene Signature of Combined Inhibition of Glutamine Metabolism and EGFR in Colorectal Cancer

PURPOSE

EGFR-targeting mAbs are essential for managing rat sarcoma virus wild-type metastatic colorectal cancer (mCRC), but their limited efficacy necessitates exploring immunologic and metabolic factors influencing response. This study evaluated glutamine metabolism targeting with EGFR inhibition to identify response biomarkers in patients with prior anti-EGFR treatment progression.

PATIENTS AND METHODS

We conducted a phase I/II trial in patients with KRAS wild-type mCRC, combining panitumumab (6 mg/kg) and CB-839 (600 mg/kg or 800 mg/kg), hypothesizing that the dual inhibition of glutamine metabolism and MAPK signaling would enhance outcomes. As study correlatives, we investigated the B-cell activation signature "B-score" and glutamine PET as potential treatment response biomarkers.

RESULTS

The combination of panitumumab and CB-839 was tolerable with manageable side effects, including grade 4 hypomagnesemia in four patients, a known panitumumab-related event. Two patients achieved partial response, and five had stable disease, with a 41% disease control rate. Median progression-free survival and overall survival were 1.84 and 8.87 months, respectively. A positive correlation between "B-score" and lesion size reduction suggested its association with clinical benefit (partial response and stable disease). Lower "B-score" correlated with greater tumor avidity for glutamine by PET, indicating B-cell activation sensitivity to glutamine depletion.

CONCLUSIONS

The combination of CB-839 and panitumumab showed safety and promising preliminary responses, but the study closed early due to CB-839 development termination. The B-cell activation signature "B-score" emerged as a potential biomarker for EGFR and glutaminase inhibition in mCRC, warranting further studies. These findings suggest opportunities to improve immune response and therapies in glutaminolysis-dependent tumors.

EGF-Upregulated lncRNA ESSENCE Promotes Colorectal Cancer Growth through Stabilizing CAD and Ferroptosis Defense

Epidermal growth factor receptor/mitogen-activated protein kinase (EGFR/MAPK) signaling is highly activated in various types of cancer. The long noncoding RNAs induced by this pathway and their roles in colorectal cancer (CRC) have not been fully elucidated. In this study, based on the profiling of long noncoding RNAs triggered by EGFR/MAPK signaling, we identified that ESSENCE (EGF [epidermal growth factor] Signal Sensing CAD's Effect; ENST00000415336), which is mediated by the transcription factor early growth response factor 1, functions as a potent oncogenic molecule that predicts poor prognosis in CRC. Mechanistically, ESSENCE directly interacts with carbamoyl-phosphate synthetase 2, aspartate transcarbamylase, and dihydroorotase (CAD) and competitively attenuates CAD degradation mediated by its newly discovered E3 ligase KEAP1, thereby suppressing ferroptosis and promoting CRC progression. Importantly, combinational treatment of the mitogen-activated extracellular signal-regulated kinase inhibitor selumetinib and ferroptosis inducer sulfasalazine synergistically suppresses ESSENCE-high CRC in a patient-derived xenograft mouse model. Taken together, these findings demonstrate the crucial role of ESSENCE in mediating CRC progression by regulating CAD stabilization and suggest a therapeutic strategy of targeting the ESSENCE-CAD axis in CRC.

Prospects and challenges of ovarian cancer organoids in chemotherapy research (Review)

Ovarian cancer (OC), a prevalent and severe malignancy of the female reproductive system, often presents with mild early symptoms and is therefore diagnosed at advanced stages, leading to a poor prognosis. Current chemotherapeutic treatment relies on platinum-based combinational therapy and there have been no recent breakthroughs in the development of new drugs. Advances in organoid technology offer a novel approach to study OC by simulating tumors and their microenvironment, enhancing drug screening effectiveness and accuracy, and providing a foundation for personalized therapy. In recent years, researchers have made notable advancements, successfully developing a diverse array of OC organoid models, with biobanks serving a pivotal role in enhancing their success rates and overall efficiency. The present review summarizes the advantages of organoids over other models, such as two-dimensional cell models, three-dimensional spheres and patient-derived xenograft models, as well as the application of organoids. In particular, the current review emphasizes the application of organoids in chemotherapeutic drug screening, testing and personalized treatment. The limitations and prospects of organoid technology are also discussed. The present study aimed to reveal the unique advantages of OC organoids in chemotherapeutic applications, so as to provide insights into screening and testing new drugs for OC.

RNA methylation of CD47 mediates tumor immunosuppression in EGFR-TKI resistant NSCLC

BACKGROUND

Although immune checkpoint inhibitors (ICIs) have been successfully utilized in patients with non-small cell lung cancer (NSCLC), EGFR-mutated patients didn't benefit from ICIs. The underlying mechanisms for the poor efficacy of this subgroup remain unclear.

METHODS

CD8+T cells cytotoxicity, DCs phagocytosis and immunofluorescence assay were applied to examine the immunosuppressive microenvironment of NSCLC. m6A RNA immunoprecipitation, luciferase assay and immunohistochemistry were used to explore the relationship between CD47 and ALKBH5 in EGFR-TKI resistant NSCLC. Autochthonous EGFR-driven lung tumor mouse model and PDXs were performed to explore the therapeutic potential of CD47 antibody and EGFR-TKI combination.

RESULTS

We found that EGFR-TKI resistance promoted a more immunosuppressive tumor microenvironment and inhibited anti-tumor functions of CD8+ T cells. Mechanistically, the m6A eraser ALKBH5 was inhibited in EGFR-TKI resistant NSCLC, which subsequently upregulates CD47 by catalyzing m6A demethylation and causes immunosuppression. Combined treatment with EGFR-TKI and inhibitors of CD47 enhances antitumor immunity and EGFR-TKI efficacy in vivo.

CONCLUSIONS

Collectively, our findings reveal the possible underlying mechanism for poor immune response of ICIs in EGFR-TKI resistant NSCLC and provide preclinical evidence that targeted therapy combined with innate immune checkpoint blockade may provide synergistic effects in NSCLC treatment.

Comprehensive assessment of computational methods for cancer immunoediting

Cancer immunoediting reflects the role of the immune system in eliminating tumor cells and shaping tumor immunogenicity, which leaves marks in the genome. In this study, we systematically evaluate four methods for quantifying immunoediting. In colorectal cancer samples from The Cancer Genome Atlas, we found that these methods identified 78.41%, 46.17%, 36.61%, and 4.92% of immunoedited samples, respectively, covering 92.90% of all colorectal cancer samples. Comparison of 10 patient-derived xenografts (PDXs) with their original tumors showed that different methods identified reduced immune selection in PDXs ranging from 44.44% to 60.0%. The proportion of such PDX-tumor pairs increases to 77.78% when considering the union of results from multiple methods, indicating the complementarity of these methods. We find that observed-to-expected ratios highly rely on neoantigen selection criteria and reference datasets. In contrast, HLA-binding mutation ratio, immune dN/dS, and enrichment score of cancer cell fraction were less affected by these factors. Our findings suggest integration of multiple methods may benefit future immunoediting analyses.

Preclinical models of soft tissue sarcomas - generation and applications to enhance translational research

Soft tissue sarcomas (STS) represent a large group of rare and ultra-rare tumors distinguished by unique morphological, molecular and clinical features. Patients with such rare cancers are generally underrepresented in clinical trials which has limited the introduction of new treatment options and subsequent improvement of patient outcomes. Preclinical models of STS that recapitulate the human disease can aid progress in identifying new effective treatments. However, due to the rarity of these tumors there are limited STS models available. Here we review the existing preclinical models of STS, including patient-derived cell lines and organoids, patient-derived xenografts and genetically engineered mouse models. We discuss the advantages and disadvantages of the different models and describe to what extent they have aided clinical translation. Finally, we consider what can be done in the future to enhance their predictivity in the preclinical setting.

Boosting human immunology: harnessing the potential of immune organoids

Studying the human immune system in vivo is challenging and often not possible. Therefore, most human immunology studies have been predominantly confined to peripheral blood analyses, which by themselves have inherent limitations, as many immune reactions take place within tissues. For example, potent antibody responses that contribute to fighting infections and provide protection following vaccination require cellular interactions between B cells and T cells in specialized micro-anatomical structures called germinal centers, which are found in secondary lymphoid organs such as spleen, lymph nodes, and tonsils. Thus, there is a clear demand for novel enhanced experimental systems that faithfully recapitulate the intricate dynamics of the human immune system as much as possible. In this review, we discuss recent advances in versatile human tonsil/adenoid tissue-based ex vivo immune organoid cultures as well as related cancer and autoimmunity-focused experimental setups. These systems have been implemented as translational immunology platforms for in-depth analyses of human B and T cell-mediated immune responses, thereby facilitating mechanistic studies as well as drug and vaccine testing in a human-first approach.

Human GM-CSF/IL-3 enhance tumor immune infiltration in humanized HCC patient-derived xenografts

Background & Aims

Response to immunotherapy in hepatocellular carcinoma (HCC) is suboptimal with no biomarkers to guide patient selection. "Humanized" mice represent promising models to address this deficiency but are limited by variable chimerism and underdeveloped myeloid compartments. We hypothesized that expression of human GM-CSF and IL-3 increases tumor immune cell infiltration, especially myeloid-derived cells, in humanized HCC patient-derived xenografts.

Material and Methods

NOG (NOD/Shi-scid/IL-2Rγnull) and NOG-EXL (huGM-CSF/huIL-3 NOG) mice conditioned with busulfan underwent i.v. injection of human CD34+ cells. HCC patient-derived xenograft tumors were then implanted subcutaneously or orthotopically. Following serial blood sampling, mice were euthanized at defined tumor sizes. Tumor, blood, liver, and spleen were analyzed by flow cytometry and immunohistochemistry.

Results

Humanized NOG-EXL mice demonstrated earlier and higher levels of human chimerism compared to humanized NOG mice (82.1% vs. 43.8%, p <0.0001) with a greater proportion of human monocytes (3.2% vs. 1.1%, p = 0.001) and neutrophils (0.8% vs. 0.3%, p = 0.02) in circulation. HCC tumors in humanized NOG-EXL mice exhibited greater human immune cell infiltration (57.6% vs. 30.2%, p = 0.04) with higher proportions of regulatory T cells (14.6% vs. 6.8%, p = 0.04), CD4+ PD-1 expression (84.7% vs. 32.0%, p <0.01), macrophages (1.2% vs. 0.6%, p = 0.02), and neutrophils (0.5% vs. 0.1%, p <0.0001). No differences were observed in tumor engraftment or growth latency in subcutaneous tumors, but orthotopic tumors required implantation at 2 rather than 4 weeks post-humanization for successful engraftment. Finally, utilizing adult bone marrow instead of fetal livers enabled partial HLA-matching to HCC tumors but required more CD34+ cells.

Conclusions

Human GM-CSF and IL-3 expression in humanized mice resulted in features more closely approximating the immune microenvironment of human disease, providing a promising model for investigating critical questions in immunotherapy for HCC.

Impact and implications

This study introduces a unique mouse model at a critical point in the evolution of treatment paradigms for patients with hepatocellular carcinoma (HCC). Immunotherapies have become the first-line treatment for advanced HCC; however, response rates remain low with no clear predictors of response to guide patient selection. In this context, animal models that recapitulate human disease are greatly needed. Leveraging xenograft tumors derived from patients with unresectable HCCs and a commercially available immunodeficient mouse strain that expresses human GM-CSF and IL-3, we demonstrate a novel but accessible approach for modeling the HCC tumor microenvironment.

PDX models for functional precision oncology and discovery science

Precision oncology relies on detailed molecular analysis of how diverse tumours respond to various therapies, with the aim to optimize treatment outcomes for individual patients. Patient-derived xenograft (PDX) models have been key to preclinical validation of precision oncology approaches, enabling the analysis of each tumour's unique genomic landscape and testing therapies that are predicted to be effective based on specific mutations, gene expression patterns or signalling abnormalities. To extend these standard precision oncology approaches, the field has strived to complement the otherwise static and often descriptive measurements with functional assays, termed functional precision oncology (FPO). By utilizing diverse PDX and PDX-derived models, FPO has gained traction as an effective preclinical and clinical tool to more precisely recapitulate patient biology using in vivo and ex vivo functional assays. Here, we explore advances and limitations of PDX and PDX-derived models for precision oncology and FPO. We also examine the future of PDX models for precision oncology in the age of artificial intelligence. Integrating these two disciplines could be the key to fast, accurate and cost-effective treatment prediction, revolutionizing oncology and providing patients with cancer with the most effective, personalized treatments.

Drug screening approaches for small-molecule compounds in cancer-targeted therapy

Small-molecule compounds exhibit distinct pharmacological properties and clinical effectiveness. Over the past decade, advances in covalent drug discovery have led to successful small-molecule drugs, such as EGFR, BTK, and KRAS (G12C) inhibitors, for cancer therapy. Researchers are paying more attention to refining drug screening methods aiming for high throughput, fast speed, high specificity, and accuracy. Therefore, the discovery and development of small-molecule drugs has been facilitated by significantly reducing screening time and financial resources, and increasing promising lead compounds compared with traditional methods. This review aims to introduce classical and emerging methods for screening small-molecule compounds in targeted cancer therapy. It includes classification, principles, advantages, disadvantages, and successful applications, serving as valuable references for subsequent researchers.

Prediction of Patient Drug Response via 3D Bioprinted Gastric Cancer Model Utilized Patient-Derived Tissue Laden Tissue-Specific Bioink

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.

Harnessing ferroptosis for precision oncology: challenges and prospects

The discovery of diverse molecular mechanisms of regulated cell death has opened new avenues for cancer therapy. Ferroptosis, a unique form of cell death driven by iron-catalyzed peroxidation of membrane phospholipids, holds particular promise for targeting resistant cancer types. This review critically examines current literature on ferroptosis, focusing on its defining features and therapeutic potential. We discuss how molecular profiling of tumors and liquid biopsies can generate extensive multi-omics datasets, which can be leveraged through machine learning-based analytical approaches for patient stratification. Addressing these challenges is essential for advancing the clinical integration of ferroptosis-driven treatments in cancer care.

Personalized prediction of anticancer potential of non-oncology drugs through learning from genome derived molecular pathways

Advances in cancer genomics have significantly expanded our understanding of cancer biology. However, the high cost of drug development limits our ability to translate this knowledge into precise treatments. Approved non-oncology drugs, comprising a large repository of chemical entities, offer a promising avenue for repurposing in cancer therapy. Herein we present CHANCE, a supervised machine learning model designed to predict the anticancer activities of non-oncology drugs for specific patients by simultaneously considering personalized coding and non-coding mutations. Utilizing protein-protein interaction networks, CHANCE harmonizes multilevel mutation annotations and integrates pharmacological information across different drugs into a single model. We systematically benchmarked the performance of CHANCE and show its predictions are better than previous model and highly interpretable. Applying CHANCE to approximately 5000 cancer samples indicated that >30% might respond to at least one non-oncology drug, with 11% non-oncology drugs predicted to have anticancer activities. Moreover, CHANCE predictions suggested an association between SMAD7 mutations and aspirin treatment response. Experimental validation using tumor cells derived from seven patients with pancreatic or esophageal cancer confirmed the potential anticancer activity of at least one non-oncology drug for five of these patients. To summarize, CHANCE offers a personalized and interpretable approach, serving as a valuable tool for mining non-oncology drugs in the precision oncology era.

Patient-derived xenograft models of gastrointestinal stromal tumors provide a ready-to-use platform for translational research

Gastrointestinal stromal tumors (GISTs) are the most common mesenchymal malignancy of the gastrointestinal tract. Most GISTs harbor mutations in oncogenes, such as KIT, and are treated with tyrosine kinase inhibitors (TKIs), such as imatinib. Most tumors develop secondary mutations, inducing drug resistance against the available TKIs, requiring novel therapies. We established a GIST patient-derived xenograft (PDX) platform of GIST that can be used for preclinical drug testing. Tumor tissue from consenting GIST patients was transplanted subcutaneously to NMRI nu/nu mice. Once tumor growth was observed, the tumor was re-transplanted to a next generation of mice. Tumors were characterized histopathologically and molecularly at every re-transplantation and compared with the original patient tumor. We transplanted 112 tumor samples from 99 GIST patients, resulting in 12 established and well-characterized GIST models with different mutations and TKI sensitivity. Three models harbor secondary KIT mutations. One model is characterized by a primary, imatinib-resistant PDGFRA exon 18 p.D842V mutation. Our established platform of well-characterized GIST PDX models, covering the most relevant driver mutations, serves as an excellent tool for preclinical drug testing and tumor biology studies.

Technological advances in clinical individualized medication for cancer therapy: from genes to whole organism

Efforts have been made to leverage technology to accurately identify tumor characteristics and predict how each cancer patient may respond to medications. This involves collecting data from various sources such as genomic data, histological information, functional drug profiling, and drug metabolism using techniques like polymerase chain reaction, sanger sequencing, next-generation sequencing, fluorescence in situ hybridization, immunohistochemistry staining, patient-derived tumor xenograft models, patient-derived organoid models, and therapeutic drug monitoring. The utilization of diverse detection technologies in clinical practice has made "individualized treatment" possible, but the desired level of accuracy has not been fully attained yet. Here, we briefly summarize the conventional and state-of-the-art technologies contributing to individualized medication in clinical settings, aiming to explore therapy options enhancing clinical outcomes.

Steroid hormone receptors, exome sequencing and treatment responsiveness of breast cancer patient-derived xenografts originated in a South American country

Breast cancer (BC) patient-derived xenografts (PDX) are relevant models for precision medicine. However, there are no collections derived from South American BC patients. Since ethnicity significantly impacts clinical outcomes, it is necessary to develop PDX models from different lineages. Our goals were to a) develop BC PDX from our population; b) characterize the expression of estrogen (ER), progesterone (PR), androgen (AR) and glucocorticoid (GR) receptors, basal and luminal cytokeratins, EGFR and HER2; c) identify PDX mutations; d) evaluate the response to treatments selected based on their biological and genetic features, and e) perform BC tissue cultures (BCTC) from PDX tissues and compare in vivo and ex vivo results. Surgical fragments were maintained in a culture medium and inoculated subcutaneously into untreated NSG female mice, or treated with estradiol pellets. Other fragments were fixed in formalin for diagnosis and immunohistochemistry, and a third piece was frozen at -80°C for molecular studies or whole exome-sequencing. Tumors were serially transplanted into NSG mice. Once the PDX was established, in vivo and ex vivo drug responses were evaluated. Eight PDX were established: two ER + [BC-AR685 (PR +) and BC-AR707 (PR-)], one from a triple-negative (TN) recurrence whose primary tumor was ER + (BC-AR485), one HER2 + (BC-AR474) and four TN primary tumors (BC-AR553, BC-AR546, BC-AR631 and BC-AR687). BC-AR685 had higher levels of PR isoform A than isoform B and was sensitive to mifepristone, tamoxifen, and palbociclib. BC-AR707 was inhibited by tamoxifen and testosterone. BC-AR474 was inhibited by trastuzumab and trastuzumab emtansine. BC-AR485 was sensitive to doxorubicin and resistant to paclitaxel in vivo and ex vivo. BC-AR687 carried a PIK3CA (C420R) mutation and was sensitive to alpelisib and mTOR inhibitors. All PDX expressed AR with varying intensities. GR and AR were co-expressed in the ER + tumors and in 3 TN PDX. We report the first PDX originated from South American countries that were genetically and biologically characterized and may be used in precision medicine studies. PDX expressing AR and/or GR are powerful tools to evaluate different endocrine treatment combinations even in TN tumors.

Patient-Derived Xenografts of Breast Cancer

Patient-derived xenografts (PDX) of breast cancer, obtained from the engraftment of tumour samples into immunodeficient mice, are the most effective preclinical models for studying the biology of human breast cancer and for the evaluation of new anti-cancer treatments. Notably, breast cancer PDX preserve the phenotypic and molecular characteristics of the donor tumours and reproduce the diversity of breast cancer. This preservation of breast cancer biology involves a number of different aspects, including tumour architecture and morphology, patterns of genomic alterations and gene expression, mutational status, and intra-tumour heterogeneity. For these reasons, these models have a strong predictive value in the translation of cancer therapeutics into clinical settings and can be considered as powerful and clinically relevant research tools for the identification of new treatments, mechanisms of drug resistance, and predictive biomarkers. PDX models have also been successfully used to analyse breast cancer metastasis and persister cancer cells surviving chemotherapy. Limitations of breast cancer PDX include the lack of a human immune system and the low take rate, especially for estrogen receptor (ER) and HER2-positive subtypes.

RANK/RANKL Signaling Pathway in Breast Development and Cancer

RANK pathway has attracted increasing interest as a promising target in breast cancer, given the availability of denosumab, an anti-RANKL drug. RANK signaling mediates progesterone-driven regulation of mammary gland development and favors breast cancer initiation by controlling mammary cell proliferation and stem cell fate. RANK activation promotes luminal mammary epithelial cell senescence, acting as an initial barrier to tumorigenesis but ultimately facilitating tumor progression and metastasis. Comprehensive analyses have demonstrated that RANK protein expression is an independent biomarker of poor prognosis in postmenopausal and estrogen receptor-negative breast cancer patients. RANK pathway also has multiple roles in immunity and inflammation, regulating innate and adaptive responses. In the tumor microenvironment, RANK and RANKL are expressed by different immune cell populations and contribute to the regulation of tumor immune surveillance, mainly driving immunosuppressive effects.Herein, we discuss the preventive and therapeutic potential of targeting RANK signaling in breast cancer given its tumor cell intrinsic and extrinsic effects. RANKL inhibition has been shown to induce mammary tumor cell differentiation and an antitumor immune response. Moreover, loss of RANK signaling increases sensitivity of breast cancer cells to chemotherapy, targeted therapies such as HER2 and CDK4/6 inhibitors, and immunotherapy. Finally, we describe clinical trials of denosumab for breast cancer prevention, such as those ongoing in women with high risk of developing breast cancer, large phase III clinical trials where the impact of adjuvant denosumab on disease-free survival has been assessed, and window trials to evaluate the immunomodulatory effects of denosumab in breast cancer and other solid tumors.

A Guide to Breast Cancer Research: An Introduction

"A Guide to Breast Cancer Research: From Cells and Molecular Mechanisms to Therapy" is designed as a comprehensive reference for early career investigators and postgraduate students. This book aims to provide a broad overview of contemporary breast cancer research. It covers key areas including development and cancer, metastasis and immunology, subtypes, signalling, therapy, and resistance. This book is organised into seven sections addressing mammary gland development, model systems, cellular origins and heterogeneity, cellular and molecular bases, signalling pathways, metastasis and immunity, and treatment and resistance mechanisms. A few topics such as specific signalling pathways, some emerging therapies, imaging technologies, and AI applications are only briefly mentioned or omitted, reflecting the ever-evolving nature of breast cancer research. This book emphasises the importance of collaboration in advancing cancer research. Initiatives like the Cancer Moonshot and Cancer Grand Challenges advocate for "radical collaboration" of researchers with shared visions and resources. We also note the significance of global efforts in breast cancer research, the need for addressing disparities in care across different regions and for equity in healthcare. Overall, this book showcases milestones and advances in breast cancer research over the past three decades, reflecting significant progress in understanding and treating the disease, which has led to improved patient outcomes.

Development of bioengineered 3D patient derived breast cancer organoid model focusing dynamic fibroblast-stem cell reciprocity

Three-dimensional (3D) models, such as tumor spheroids and organoids, are increasingly developed by integrating tissue engineering, regenerative medicine, and personalized therapy strategies. These advanced 3Din-vitromodels are not merely endpoint-driven but also offer the flexibility to be customized or modulated according to specific disease parameters. Unlike traditional 2D monolayer cultures, which inadequately capture the complexities of solid tumors, 3D co-culture systems provide a more accurate representation of the tumor microenvironment. This includes critical interactions with mesenchymal stem/stromal cells (MSCs) and induced pluripotent stem cells (iPSCs), which significantly modulate cancer cell behavior and therapeutic responses. Most of the findings from the co-culture of Michigan Cancer Foundation-7 breast cancer cells and MSC showed the formation of monolayers. Although changes in the plasticity of MSCs and iPSCs caused by other cells and extracellular matrix (ECM) have been extensively researched, the effect of MSCs on cancer stem cell (CSC) aggressiveness is still controversial and contradictory among different research communities. Some researchers have argued that CSCs proliferate more, while others have proposed that cancer spread occurs through dormancy. This highlights the need for further investigation into how these interactions shape cancer aggressiveness. The objective of this review is to explore changes in cancer cell behavior within a 3D microenvironment enriched with MSCs, iPSCs, and ECM components. By describing various MSC and iPSC-derived 3D breast cancer models that replicate tumor biology, we aim to elucidate potential therapeutic targets for breast cancer. A particular focus of this review is the Transwell system, which facilitates understanding how MSCs and iPSCs affect critical processes such as migration, invasion, and angiogenesis. The gradient formed between the two chambers is based on diffusion, as seen in the human body. Once optimized, this Transwell model can serve as a high-throughput screening platform for evaluating various anticancer agents. In the future, primary cell-based and patient-derived 3D organoid models hold promise for advancing personalized medicine and accelerating drug development processes.

Myeloid Cell Mobilization and Recruitment by Human Mesothelioma in NSG-SGM3 Mice

Malignant pleural mesothelioma is a neoplasm that is often detected late due to nonspecific symptoms. This study utilized NSG-SGM3 mice to examine interactions between a human-derived mesothelioma reporter cell line (MZT-Luc2-mCherry) and the host's myeloid compartment. Tumor growth was assessed using optical tomography, while cytokine/chemokine production was analyzed via multiplex assay. Histological and immunohistochemical analyses validated the epithelioid mesothelioma phenotype. In vitro mesothelioma cells secreted factors associated with myeloid cell chemoattraction and functions supporting the previously reported myeloid-biased secretory phenotype. In line with this, post-engraftment analysis revealed increased neutrophil-like Ly6G+ populations and decreased Ly6C+ inflammatory monocytes in the blood of tumor-bearing mice. Significant Ly6G+ cell infiltration was observed in the tumor, while CD11b+ myeloid cells were localized primarily in the tumor periphery. Tumor lysates showed increased levels of neutrophil chemoattractants and G-CSF, suggesting a previously not reported role of neutrophils in mesothelioma progression. This novel model provides a platform for studying mesothelioma-host interactions, focusing on the myeloid compartment. It may also serve as a tool to facilitate the development of new therapeutic strategies targeting myeloid cell-mediated mechanisms in mesothelioma.

Modeling craniopharyngioma for drug screening reveals a neuronal mechanism for tumor growth

Tumors occurring along the hypothalamus-pituitary axis receive axonal projection from neuroendocrine neurons, but it remains unclear whether neuroendocrine neuronal activity drives tumor expansion. Craniopharyngioma is a common suprasellar tumor with a propensity for invading the hypothalamus, leading to devastating endocrine and metabolic disorders. Here, we developed two autochthonous animal models that faithfully recapitulate the molecular pathology, clinical manifestations, and transcriptomic profiles of papillary craniopharyngioma. Using high-throughput drug screening, we identified 74 compounds with potent antitumor efficacy. The administration of (S)-amlodipine besylate achieved tumor regression in vivo, potentially by abrogating calcium transients and neuron-to-tumor chemical transmission. Chemogenetic manipulation of neuroendocrine neuronal activity bidirectionally regulated tumor cell growth in our mouse model, suggesting that craniopharyngioma hijacks hypothalamic neurons to promote tumor progression. These findings deepen our understanding of suprasellar tumor biology and offer promising avenues for clinical exploration of effective chemotherapies.

Castrate-resistant prostate cancer response to taxane is determined by an HNF1-dependent apoptosis resistance circuit

Metastatic castrate-resistant prostate cancer (mCRPC) is a genetically and phenotypically heterogeneous cancer where advancements are needed in biomarker discovery and targeted therapy. A critical and often effective component of treatment includes taxanes. We perform a high-throughput screen across a cohort of 30 diverse patient-derived castrate-resistant prostate cancer (CRPC) organoids to a library of 78 drugs. Combining quantitative response measures with transcriptomic analyses demonstrates that HNF1 homeobox A (HNF1A) drives a transcriptional program of taxane resistance, commonly dependent upon cellular inhibitor of apoptosis protein 2 (cIAP2). Monotherapy with cIAP2 inhibitor LCL161 is sufficient to treat HNF1A+ models of mCRPC previously resistant to docetaxel. These data may be useful in future clinical trial designs.

Tissue-engineered patient-derived osteosarcoma models dissecting tumour-bone interactions

Osteosarcoma is the most common malignant bone tumor, primarily affecting children and young adults. For these young patients, the current treatment options for osteosarcoma impose considerable constraints on daily life with significant morbidity and a low survival rate. Despite ongoing research efforts, the 5-year survival rate of first-diagnosed patients without metastases has not changed in the past four decades. The demand for novel treatments is currently still unmet, in particular for effective second-line therapy. Therefore, there is an urgent need for advanced preclinical models and drug-testing platforms that take into account the complex disease characteristics, the high heterogeneity of the tumour and the interactions with the bone microenvironment. In this review, we provide a comprehensive overview about state-of-the-art tissue-engineered and patient-specific models for osteosarcoma. These sophisticated platforms for advanced therapy trials aim to improve treatment outcomes for future patients by modelling the patient's disease state in a more accurate and complex way, thus improving the quality of preclinical research studies.

Integrative ensemble modelling of cetuximab sensitivity in colorectal cancer patient-derived xenografts

Patient-derived xenografts (PDXs) are tumour fragments engrafted into mice for preclinical studies. PDXs offer clear advantages over simpler in vitro cancer models - such as cancer cell lines (CCLs) and organoids - in terms of structural complexity, heterogeneity, and stromal interactions. Here, we characterise 231 colorectal cancer PDXs at the genomic, transcriptomic, and epigenetic levels, along with their response to cetuximab, an EGFR inhibitor used clinically for metastatic colorectal cancer. After evaluating the PDXs' quality, stability, and molecular concordance with publicly available patient cohorts, we present results from training, interpreting, and validating the integrative ensemble classifier CeSta. This model takes in input the PDXs' multi-omic characterisation and predicts their sensitivity to cetuximab treatment, achieving an area under the receiver operating characteristics curve > 0.88. Our study demonstrates that large PDX collections can be leveraged to train accurate, interpretable drug sensitivity models that: (1) better capture patient-derived therapeutic biomarkers compared to models trained on CCL data, (2) can be robustly validated across independent PDX cohorts, and (3) could contribute to the development of future therapeutic biomarkers.

Human GM-CSF/IL-3 enhance tumor immune infiltration in humanized HCC patient-derived xenografts

Background & Aims

Responses to immunotherapies in hepatocellular carcinoma (HCC) are suboptimal with no biomarkers to guide patient selection. "Humanized" mice represent promising models to address this deficiency but are limited by variable chimerism and underdeveloped myeloid compartments. We hypothesized that expression of human GM-CSF and IL-3 increases tumor immune cell infiltration, especially myeloid-derived cells, in humanized HCC patient-derived xenografts (PDXs).

Material and Methods

NOG (NOD/Shi- scid /IL-2R null ) and NOG-EXL (huGM-CSF/huIL-3 NOG) mice conditioned with Busulfan underwent i.v. injection of human CD34+ cells. HCC PDX tumors were then implanted subcutaneously (SQ) or orthotopically (OT). Following serial blood sampling, mice were euthanized at defined tumor sizes. Tumor, blood, liver, and spleen were analyzed by flow cytometry and immunohistochemistry.

Results

Humanized NOG-EXL mice demonstrated earlier and increased human chimerism compared to humanized NOG mice (82.1% vs 43.8%, p<0.0001) with increased proportion of human monocytes (3.2% vs 1.1%, p=0.001) and neutrophils (0.8% vs 0.3%, p=0.02) in circulation. HCC tumors in humanized NOG-EXL mice had increased human immune cell infiltration (57.6% vs 30.2%, p=0.04), noting increased regulatory T cells (14.6% vs 6.8%, p=0.04), CD4+ PD-1 expression (84.7% vs 32.0%, p<0.01), macrophages (1.2% vs 0.6%, p=0.02), and neutrophils (0.5% vs 0.1%, p<0.0001). No differences were observed in tumor engraftment or growth latency in SQ tumors, but OT tumors required implantation at two rather than four weeks post-humanization for successful engraftment. Finally, utilizing adult bone marrow instead of fetal livers enabled partial HLA-matching to HCC tumors but required more CD34+ cells.

Conclusions

Human GM-CSF and IL-3 expression in humanized mice resulted in features more closely approximating the immune microenvironment of human disease, providing a promising model for investigating critical questions in immunotherapy for HCC.

Impact and Implications

This study introduces a unique mouse model at a critical point in the evolution of treatment paradigms for patients with hepatocellular carcinoma (HCC). Immunotherapies have become first line treatment for advanced HCC; however, response rates remain low with no clear predictors of response to guide patient selection. In this context, animal models that recapitulate human disease are greatly needed. Leveraging xenograft tumors derived from patients with advanced HCCs and a commercially available immunodeficient mouse strain that expresses human GM-CSF and IL-3, we demonstrate a novel but accessible approach for modeling the HCC tumor microenvironment.

Ex Vivo Intestinal Organoid Models: Current State-of-the-Art and Challenges in Disease Modelling and Therapeutic Testing for Colorectal Cancer

Despite improvements in participation in population-based screening programme, colorectal cancer remains a major cause of cancer-related mortality worldwide. Targeted interventions are desirable to reduce the health and economic burden of this disease. Two-dimensional monolayers of colorectal cancer cell lines represent the traditional in vitro models for disease and are often used for diverse purposes, including the delineation of molecular pathways associated with disease aetiology or the gauging of drug efficacy. The lack of complexity in such models, chiefly the limited epithelial cell diversity and differentiation, attenuated mucus production, lack of microbial interactions and mechanical stresses, has driven interest in the development of more holistic and physiologically relevant in vitro model systems. In particular, established ex vivo patient-derived explant and patient-derived tumour xenograft models have been supplemented by progress in organoid and microfluidic organ-on-a-chip cultures. Here, we discuss the applicability of advanced culturing technologies, such as organoid systems, as models for colorectal cancer and for testing chemotherapeutic drug sensitivity and efficacy. We highlight current challenges associated with organoid technologies and discuss their future for more accurate disease modelling and personalized medicine.

Novel strategies to assess cytokine release mediated by chimeric antigen receptor T cells based on the adverse outcome pathway concept

The success of cellular immunotherapies such as chimeric antigen receptor (CAR) T cell therapy has led to their implementation as a revolutionary treatment option for cancer patients. However, the safe translation of such novel immunotherapies, from non-clinical assessment to first-in-human studies is still hampered by the lack of suitable in vitro and in vivo models recapitulating the complexity of the human immune system. Additionally, using cells derived from human healthy volunteers in such test systems may not adequately reflect the altered state of the patient's immune system thus potentially underestimating the risk of life-threatening conditions, such as cytokine release syndrome (CRS) following CAR T cell therapy. The IMI2/EU project imSAVAR (immune safety avatar: non-clinical mimicking of the immune system effects of immunomodulatory therapies) aims at creating a platform for novel tools and models for enhanced non-clinical prediction of possible adverse events associated with immunomodulatory therapies. This platform shall in the future guide early non-clinical safety assessment of novel immune therapeutics thereby also reducing the costs of their development. Therefore, we review current opportunities and challenges associated with non-clinical in vitro and in vivo models for the safety assessment of CAR T cell therapy ranging from organ-on-chip models up to advanced biomarker screening.

The use of organoids in creating immune microenvironments and treating gynecological tumors

Owing to patient-derived tumor tissues and cells, significant advances have been made in personalized cancer treatment and precision medicine, with cancer stem cell-derived three-dimensional tumor organoids serving as crucial in vitro models that accurately replicate the structural, phenotypic, and genetic characteristics of tumors. However, despite their extensive use in drug testing, genome editing, and transplantation for facilitating personalized treatment approaches in clinical practice, the inadequate capacity of these organoids to effectively model immune cells and stromal components within the tumor microenvironment limits their potential. Additionally, effective clinical immunotherapy has led the tumor immune microenvironment to garner considerable attention, increasing the demand for simulating patient-specific tumor-immune interactions. Consequently, co-culture techniques integrating tumor organoids with immune cells and tumor microenvironment constituents have been developed to expand the possibilities for personalized drug response investigations, with recent advancements enhancing the understanding of the strengths, limitations, and applicability of the co-culture approach. Herein, the recent advancements in the field of tumor organoids have been comprehensively reviewed, specifically highlighting the tumor organoid co-culture-related developments with various immune cell models and their implications for clinical research. Furthermore, this review delineates the current state of research and application of organoid models regarding the therapeutic approaches and related challenges for gynecological tumors. This study may provide a theoretical basis for further research on the use of patient-derived organoids in tumor immunity, drug development, and precision medicine.

CTC-derived pancreatic cancer models serve as research tools and are suitable for precision medicine approaches

Pancreatic ductal adenocarcinoma (PDAC) poses significant clinical challenges, often presenting as unresectable with limited biopsy options. Here, we show that circulating tumor cells (CTCs) offer a promising alternative, serving as a "liquid biopsy" that enables the generation of in vitro 3D models and highly aggressive in vivo models for functional and molecular studies in advanced PDAC. Within the retrieved CTC pool (median 65 CTCs/5 mL), we identify a subset (median content 8.9%) of CXCR4+ CTCs displaying heightened stemness and metabolic traits, reminiscent of circulating cancer stem cells. Through comprehensive analysis, we elucidate the importance of CTC-derived models for identifying potential targets and guiding treatment strategies. Screening of stemness-targeting compounds identified stearoyl-coenzyme A desaturase (SCD1) as a promising target for advanced PDAC. These results underscore the pivotal role of CTC-derived models in uncovering therapeutic avenues and ultimately advancing personalized care in PDAC.

Extracellular matrix regulation of cell spheroid invasion in a 3D bioprinted solid tumor-on-a-chip

Tumor organoids and tumors-on-chips can be built by placing patient-derived cells within an engineered extracellular matrix (ECM) for personalized medicine. The engineered ECM influences the tumor response, and understanding the ECM-tumor relationship accelerates translating tumors-on-chips into drug discovery and development. In this work, we tuned the physical and structural characteristics of ECM in a 3D bioprinted soft-tissue sarcoma microtissue. We formed cell spheroids at a controlled size and encapsulated them into our gelatin methacryloyl (GelMA)-based bioink to make perfusable hydrogel-based microfluidic chips. We then demonstrated the scalability and customization flexibility of our hydrogel-based chip via engineering tools. A multiscale physical and structural data analysis suggested a relationship between cell invasion response and bioink characteristics. Tumor cell invasive behavior and focal adhesion properties were observed in response to varying polymer network densities of the GelMA-based bioink. Immunostaining assays and reverse transcription-quantitative polymerase chain reaction (RT-qPCR) helped assess the bioactivity of the microtissue and measure the cell invasion. The RT-qPCR data showed higher expressions of HIF-1α, CD44, and MMP2 genes in a lower polymer density, highlighting the correlation between bioink structural porosity, ECM stiffness, and tumor spheroid response. This work is the first step in modeling STS tumor invasiveness in hydrogel-based microfluidic chips. STATEMENT OF SIGNIFICANCE: We optimized an engineering protocol for making tumor spheroids at a controlled size, embedding spheroids into a gelatin-based matrix, and constructing a perfusable microfluidic device. A higher tumor invasion was observed in a low-stiffness matrix than a high-stiffness matrix. The physical characterizations revealed how the stiffness is controlled by the density of polymer chain networks and porosity. The biological assays revealed how the structural properties of the gelatin matrix and hypoxia in tumor progression impact cell invasion. This work can contribute to personalized medicine by making more effective, tailored cancer models.

Precision Oncology and Systemic Targeted Therapy in Pseudomyxoma Peritonei

PURPOSE

Pseudomyxoma peritonei (PMP) is a rare and poorly understood malignant condition characterized by the accumulation of intra-abdominal mucin produced from peritoneal metastases. Currently, cytoreductive surgery remains the mainstay of treatment but disease recurrence and death after relapse frequently occur in patients with PMP. New therapeutic strategies are therefore urgently needed for these patients.

EXPERIMENTAL DESIGN

A total of 120 PMP samples from 50 patients were processed to generate a collection of 50 patient-derived organoid (PDO) and xenograft (PDX) models. Whole exome sequencing, immunohistochemistry analyses, and in vitro and in vivo drug efficacy studies were performed.

RESULTS

In this study, we have generated a collection of PMP preclinical models and identified druggable targets, including BRAFV600E, KRASG12C, and KRASG12D, that could also be detected in intra-abdominal mucin biopsies of patients with PMP using droplet digital PCR. Preclinical models preserved the histopathological markers from the original patient sample. The BRAFV600E inhibitor encorafenib reduced cell viability of BRAFV600E PMP-PDO models. Proof-of-concept in vivo experiments showed that a systemic treatment with encorafenib significantly reduced tumor growth and prolonged survival in subcutaneous and orthotopic BRAFV600E-PMP-PDX mouse models.

CONCLUSIONS

Our study demonstrates for the first time that systemic targeted therapies can effectively control PMP tumors. BRAF signaling pathway inhibition represents a new therapeutic opportunity for patients with BRAFV600E PMP who have a poor prognosis. Importantly, our present data and collection of preclinical models pave the way for evaluating the efficacy of other systemic targeted therapies toward extending the promise of precision oncology to patients with PMP.

Leveraging preclinical models of metastatic breast cancer

Women that present to the clinic with established breast cancer metastases have limited treatment options. Yet, the majority of preclinical studies are actually not directed at developing treatment regimens for established metastatic disease. In this review we will discuss the current state of preclinical macro-metastatic breast cancer models, including, but not limited to syngeneic GEMM, PDX and xenografts. Challenges within these models which are often overlooked include fluorophore-immunogenic neoantigens, differences in experimental vs spontaneous metastasis and tumor heterogeneity. Furthermore, due to cell plasticity in the tumor immune microenvironment (TIME) of the metastatic landscape, the treatment efficacy of newly approved immune checkpoint blockade (ICB) may differ in metastatic sites as compared to primary localized tumors.

Gastric Cancer Assembloids Derived from Patient-Derived Xenografts: A Preclinical Model for Therapeutic Drug Screening

The construction of reliable preclinical models is crucial for understanding the molecular mechanisms involved in gastric cancer and for advancing precision medicine. Currently, existing in vitro tumor models often do not accurately replicate the human gastric cancer environment and are unsuitable for high-throughput therapeutic drug screening. In this study, droplet microfluidic technology is employed to create novel gastric cancer assembloids by encapsulating patient-derived xenograft gastric cancer cells and patient stromal cells in Gelatin methacryloyl (GelMA)-Gelatin-Matrigel microgels. The usage of GelMA-Gelatin-Matrigel composite hydrogel effectively alleviated cell aggregation and sedimentation during the assembly process, allowing for the handling of large volumes of cell-laden hydrogel and the uniform generation of assembloids in a high-throughput manner. Notably, the patient-derived xenograft assembloids exhibited high consistency with primary tumors at both transcriptomic and histological levels, and can be efficiently scaled up for preclinical drug screening efforts. Furthermore, the drug screening results clearly demonstrated that the in vitro assembloid model closely mirrored in vivo drug responses. Thus, these findings suggest that gastric cancer assembloids, which effectively replicate the in vivo tumor microenvironment, show promise for enabling more precise high-throughput drug screening and predicting the clinical outcomes of various drugs.

OBSERVE: guidelines for the refinement of rodent cancer models

Existing guidelines on the preparation (Planning Research and Experimental Procedures on Animals: Recommendations for Excellence (PREPARE)) and reporting (Animal Research: Reporting of In Vivo Experiments (ARRIVE)) of animal experiments do not provide a clear and standardized approach for refinement during in vivo cancer studies, resulting in the publication of generic methodological sections that poorly reflect the attempts made at accurately monitoring different pathologies. Compliance with the 3Rs guidelines has mainly focused on reduction and replacement; however, refinement has been harder to implement. The Oncology Best-practices: Signs, Endpoints and Refinements for in Vivo Experiments (OBSERVE) guidelines are the result of a European initiative supported by EurOPDX and INFRAFRONTIER, and aim to facilitate the refinement of studies using in vivo cancer models by offering robust and practical recommendations on approaches to research scientists and animal care staff. We listed cancer-specific clinical signs as a reference point and from there developed sets of guidelines for a wide variety of rodent models, including genetically engineered models and patient derived xenografts. In this Consensus Statement, we systematically and comprehensively address refinement and monitoring approaches during the design and execution of murine cancer studies. We elaborate on the appropriate preparation of tumor-initiating biologicals and the refinement of tumor-implantation methods. We describe the clinical signs to monitor associated with tumor growth, the appropriate follow-up of animals tailored to varying clinical signs and humane endpoints, and an overview of severity assessment in relation to clinical signs, implantation method and tumor characteristics. The guidelines provide oncology researchers clear and robust guidance for the refinement of in vivo cancer models.

Repurposed AT9283 triggers anti-tumoral effects by targeting MKK3 oncogenic functions in Colorectal Cancer

BACKGROUND

Colorectal cancer (CRC) is the third most common type of cancer and the second leading cause of cancer-related deaths worldwide, with a survival rate near to 10% when diagnosed at an advanced stage. Hence, the identification of new molecular targets to design more selective and efficient therapies is urgently required. The Mitogen activated protein kinase kinase 3 (MKK3) is a dual-specificity threonine/tyrosine protein kinase that, activated in response to cellular stress and inflammatory stimuli, regulates a plethora of biological processes. Previous studies revealed novel MKK3 roles in supporting tumor malignancy, as its depletion induces autophagy and cell death in cancer lines of different tumor types, including CRC. Therefore, MKK3 may represent an interesting new therapeutic target in advanced CRC, however selective MKK3 inhibitors are currently not available.

METHODS

The study involved transcriptomic based drug repurposing approach and confirmatory assays with CRC lines, primary colonocytes and a subset of CRC patient-derived organoids (PDO). Investigations in vitro and in vivo were addressed.

RESULTS

The repurposing approach identified the multitargeted kinase inhibitor AT9283 as a putative compound with MKK3 depletion-mimicking activities. Indeed, AT9283 drops phospho- and total-MKK3 protein levels in tested CRC models. Likely the MKK3 silencing, AT9283 treatment: i) inhibited cell proliferation promoting autophagy and cell death in tested CRC lines and PDOs; ii) resulted well-tolerated by CCD-18Co colonocytes; iii) reduced cancer cell motility inhibiting CRC cell migration and invasion; iv) inhibited COLO205 xenograft tumor growth. Mechanistically, AT9283 abrogated MKK3 protein levels mainly through the inhibition of aurora kinase A (AURKA), impacting on MKK3/AURKA protein-protein interaction and protein stability therefore uncovering the relevance of MKK3/AURKA crosstalk in sustaining CRC malignancy in vitro and in vivo.

CONCLUSION

Overall, we demonstrated that the anti-tumoral effects triggered by AT9283 treatment recapitulated the MKK3 depletion effects in all tested CRC models in vitro and in vivo, suggesting that AT9283 is a repurposed drug. According to its good tolerance when tested with primary colonocytes (CCD-18CO), AT9283 is a promising drug for the development of novel therapeutic strategies to target MKK3 oncogenic functions in late-stage and metastatic CRC patients.

Evaluation of Combined Chemotherapy and Genomic-Driven Targeted Therapy in Patient-Derived Xenografts Identifies New Therapeutic Approaches in Squamous Non-Small-Cell Lung Cancer Patients

The combination of chemotherapy and targeted therapy has been validated in non-small-cell lung cancer (NSCLC) patients with EGFR mutations. We therefore investigated whether this type of combined approach could be more widely used by targeting other genetic alterations present in NSCLC. PDXs were generated from patients with NSCLC adenocarcinomas (ADCs) and squamous-cell carcinomas (SCCs). Targeted NGS analyses identified various molecular abnormalities in the MAPK and PI3K pathways and in the cell cycle process in our PDX panel. The antitumor efficacy of targeted therapies alone or in combination with chemotherapy was then tested in vivo. We observed that trametinib, BKM120, AZD2014 and palbociclib increased the efficacy of each chemotherapy in SCC PDXs, in contrast to a non-insignificant or slight improvement in ADCs. Furthermore, we observed high efficacy of trametinib in KRAS-, HRAS- and NRAS-mutated tumors (ADCs and SCCs), suggesting that the MEK inhibitor may be useful in a wider population of NSCLC patients, not just those with KRAS-mutated ADCs. Our results suggest that the detection of pathogenic variants by NGS should be performed in all NSCLCs, and particularly in SCCs, to offer patients a more effective combination of chemotherapy and targeted therapy.

Gastrointestinal Cancer Patient Derived Organoids at the Frontier of Personalized Medicine and Drug Screening

Cancer is a leading cause of death worldwide. Around one-third of the total global cancer incidence and mortality are related to gastrointestinal (GI) cancers. Over the past few years, rapid developments have been made in patient-derived organoid (PDO) models for gastrointestinal cancers. By closely mimicking the molecular properties of their parent tumors in vitro, PDOs have emerged as powerful tools in personalized medicine and drug discovery. Here, we review the current literature on the application of PDOs of common gastrointestinal cancers in the optimization of drug treatment strategies in the clinic and their rising importance in pre-clinical drug development. We discuss the advantages and limitations of gastrointestinal cancer PDOs and outline the microfluidics-based strategies that improve the throughput of PDO models in order to extract the maximal benefits in the personalized medicine and drug discovery process.

Cancer organoids 2.0: modelling the complexity of the tumour immune microenvironment

The development of neoplasia involves a complex and continuous interplay between malignantly transformed cells and the tumour microenvironment (TME). Cancer immunotherapies targeting the immune TME have been increasingly validated in clinical trials but response rates vary substantially between tumour histologies and are often transient, idiosyncratic and confounded by resistance. Faithful experimental models of the patient-specific tumour immune microenvironment, capable of recapitulating tumour biology and immunotherapy effects, would greatly improve patient selection, target identification and definition of resistance mechanisms for immuno-oncology therapeutics. In this Review, we discuss currently available and rapidly evolving 3D tumour organoid models that capture important immune features of the TME. We highlight diverse opportunities for organoid-based investigations of tumour immunity, drug development and precision medicine.

Tumor Cell Stemness and Stromal Cell Features Contribute to Oral Cancer Outcome Disparity in Black Americans

Black Americans (BAs) with head and neck cancer (HNC) have worse survival outcomes compared to the White patients. While HNC disparities in patient outcomes for BAs have been well recognized, the specific drivers of the inferior outcomes remain poorly understood. Here, we investigated the biologic features of patient tumor specimens obtained during the surgical treatment of oral cancers and performed a follow-up study of the patients' post-surgery recurrences and metastases with the aim to explore whether tumor biologic features could be associated with the poorer outcomes among BA patients compared with White American (WA) patients. We examined the tumor stemness traits and stromal properties as well as the post-surgery recurrence and metastasis of oral cancers among BA and WA patients. It was found that high levels of tumor self-renewal, invasion, tumorigenesis, metastasis, and tumor-promoting stromal characteristics were linked to post-surgery recurrence and metastasis. There were more BA than WA patients demonstrating high stemness traits and strong tumor-promoting stromal features in association with post-surgery tumor recurrences and metastases, although the investigated cases displayed clinically comparable TNM stages and histological grades. These findings demonstrated that the differences in tumor stemness and stromal property among cancers with comparable clinical diagnoses contribute to the outcome disparity in HNCs. More research is needed to understand the genetic and molecular basis of the biologic characteristics underlying the inferior outcomes among BA patients, so that targeting strategies can be developed to reduce HNC disparity.

Genomic profiling of a multi-lineage and multi-passage patient-derived xenograft biobank reflects heterogeneity of ovarian cancer

Ovarian cancer (OC) manifests as a complex disease characterized by inter- and intra-patient heterogeneity. Despite enhanced biological and genetic insights, OC remains a recalcitrant malignancy with minimal survival improvement. Based on multi-site sampling and a multi-lineage patient-derived xenograft (PDX) establishment strategy, we present herein the establishment of a comprehensive PDX biobank from histologically and molecularly heterogeneous OC patients. Comprehensive profiling of matched PDX and patient samples demonstrates that PDXs closely recapitulate parental tumors. By leveraging multi-lineage models, we reveal that the previously reported genomic disparities of PDX could be mainly attributed to intra-patient spatial heterogeneity instead of substantial model-independent genomic evolution. Moreover, DNA damage response pathway inhibitor (DDRi) screening uncovers heterogeneous responses across models. Prolonged iterative drug exposure recapitulates acquired drug resistance in initially sensitive models. Meanwhile, interrogation of induced drug-resistant (IDR) models reveals that suppressed interferon (IFN) response and activated Wnt/β-catenin signaling contribute to acquired DDRi drug resistance.

A Self-Assembled 3D Model Demonstrates How Stiffness Educates Tumor Cell Phenotypes and Therapy Resistance in Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) is characterized by a dense and stiff extracellular matrix (ECM) associated with tumor progression and therapy resistance. To further the understanding of how stiffening of the tumor microenvironment (TME) contributes to aggressiveness, a three-dimensional (3D) self-assembling hydrogel disease model is developed based on peptide amphiphiles (PAs, PA-E3Y) designed to tailor stiffness. The model displays nanofibrous architectures reminiscent of native TME and enables the study of the invasive behavior of PDAC cells. Enhanced tuneability of stiffness is demonstrated by interacting thermally annealed aqueous solutions of PA-E3Y (PA-E3Yh) with divalent cations to create hydrogels with mechanical properties and ultrastructure similar to native tumor ECM. It is shown that stiffening of PA-E3Yh hydrogels to levels found in PDAC induces ECM deposition, promotes epithelial-to-mesenchymal transition (EMT), enriches CD133+/CXCR4+ cancer stem cells (CSCs), and subsequently enhances drug resistance. The findings reveal how a stiff 3D environment renders PDAC cells more aggressive and therefore more faithfully recapitulates in vivo tumors.

Liensinine sensitizes colorectal cancer cells to oxaliplatin by targeting HIF-1α to inhibit autophagy

BACKGROUND

Oxaliplatin is the most common chemotherapeutic agent for patients with colorectal cancer. However, its anti-cancer efficacy is restricted by drug resistance occurring through several mechanisms, including autophagy. Liensinine exerts a considerable anti-tumor effect and can regulate autophagy. Inhibition of autophagy is a strategy to reverse resistance to oxaliplatin. The aim of this study was to check if liensinine can enhance the therapeutic efficacy of oxaliplatin in colorectal cancer and if so, elucidate its mechanism.

METHODS

Two colorectal cancer cell lines, HCT116 and LoVo, and one normal intestinal epithelial cell, NCM-460 were used for in vitro experiments. Cell Counting Kit-8 (CCK-8), colony formation, and flow cytometry assays were used to evaluate the cytotoxicity of liensinine and oxaliplatin. Network pharmacology analysis and Human XL Oncology Array were used to screen targets of liensinine. Transfections and autophagy regulators were used to confirm these targets. The relationship between the target and clinical effect of oxaliplatin was analyzed. Patient-derived xenograft (PDX) models were used to validate the effects of liensinine and oxaliplatin.

RESULTS

CCK-8 and colony formation assays both showed that the combination treatment of liensinine and oxaliplatin exerted synergistic effects. Results of the network pharmacology analysis and Human XL Oncology Array suggested that liensinine can inhibit autophagy by targeting HIF-1α/eNOS. HIF-1α was identified as the key factor modulated by liensinine in autophagy and induces resistance to oxaliplatin. HIF-1α levels in tumor cells and prognosis for FOLFOX were negatively correlated in clinical data. The results from three PDX models with different HIF-1α levels showed their association with intrinsic and acquired resistance to oxaliplatin in these models, which could be reversed by liensinine.

CONCLUSIONS

Research on the relationship between HIF-1α levels and the clinical effect of oxaliplatin is lacking, and whether liensinine regulates HIF-1α is unknown. Our findings suggest that liensinine overcomes the resistance of colorectal cancer cells to oxaliplatin by suppressing HIF-1α levels to inhibit autophagy. Our findings can contribute to improving prognosis following colorectal cancer therapy.

The potential of organoids in renal cell carcinoma research

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.

Mouse Models for Head and Neck Squamous Cell Carcinoma

The prognosis and survival rate of head and neck squamous cell carcinoma (HNSCC) have remained unchanged for years, and the pathogenesis of HNSCC is still not fully understood, necessitating further research. An ideal animal model that accurately replicates the complex microenvironment of HNSCC is urgently needed. Among all the animal models for preclinical cancer research, tumor-bearing mouse models are the best known and widely used due to their high similarity to humans. Currently, mouse models for HNSCC can be broadly categorized into chemical-induced models, genetically engineered mouse models (GEMMs), and transplanted mouse models, each with its distinct advantages and limitations. In chemical-induced models, the carcinogen spontaneously initiates tumor formation through a multistep process. The resemblance of this model to human carcinogenesis renders it an ideal preclinical platform for studying HNSCC initiation and progression from precancerous lesions. The major drawback is that these models are time-consuming and, like human cancer, unpredictable in terms of timing, location, and number of lesions. GEMMs involve transgenic and knockout mice with gene modifications, leading to malignant transformation within a tumor microenvironment that recapitulates tumorigenesis in vivo, including their interaction with the immune system. However, most HNSCC GEMMs exhibit low tumor incidence and limited prognostic significance when translated to clinical studies. Transplanted mouse models are the most widely used in cancer research due to their consistency, availability, and efficiency. Based on the donor and recipient species matching, transplanted mouse models can be divided into xenografts and syngeneic models. In the latter, transplanted cells and host are from the same strain, making syngeneic models relevant to study functional immune system. In this review, we provide a comprehensive summary of the characteristics, establishment methods, and potential applications of these different HNSCC mouse models, aiming to assist researchers in choosing suitable animal models for their research.

Omics-based molecular classifications empowering in precision oncology

BACKGROUND

In the past decades, cancer enigmatical heterogeneity at distinct expression levels could interpret disparities in therapeutic response and prognosis. It built hindrances to precision medicine, a tactic to tailor customized treatment informed by the tumors' molecular profile. Single-omics analysis dissected the biological features associated with carcinogenesis to some extent but still failed to revolutionize cancer treatment as expected. Integrated omics analysis incorporated tumor biological networks from diverse layers and deciphered a holistic overview of cancer behaviors, yielding precise molecular classification to facilitate the evolution and refinement of precision medicine.

CONCLUSION

This review outlined the biomarkers at multiple expression layers to tutor molecular classification and pinpoint tumor diagnosis, and explored the paradigm shift in precision therapy: from single- to multi-omics-based subtyping to optimize therapeutic regimens. Ultimately, we firmly believe that by parsing molecular characteristics, omics-based typing will be a powerful assistant for precision oncology.

Representation of genomic intratumor heterogeneity in multi-region non-small cell lung cancer patient-derived xenograft models

Patient-derived xenograft (PDX) models are widely used in cancer research. To investigate the genomic fidelity of non-small cell lung cancer PDX models, we established 48 PDX models from 22 patients enrolled in the TRACERx study. Multi-region tumor sampling increased successful PDX engraftment and most models were histologically similar to their parent tumor. Whole-exome sequencing enabled comparison of tumors and PDX models and we provide an adapted mouse reference genome for improved removal of NOD scid gamma (NSG) mouse-derived reads from sequencing data. PDX model establishment caused a genomic bottleneck, with models often representing a single tumor subclone. While distinct tumor subclones were represented in independent models from the same tumor, individual PDX models did not fully recapitulate intratumor heterogeneity. On-going genomic evolution in mice contributed modestly to the genomic distance between tumors and PDX models. Our study highlights the importance of considering primary tumor heterogeneity when using PDX models and emphasizes the benefit of comprehensive tumor sampling.

Recent advances in breast cancer cell line research

Breast cancer, a formidable global health challenge, needs continuous translational research to understand the complexity of mechanisms and improve therapeutic and diagnostic strategies. Breast cancer cell lines are of paramount importance as they significantly contribute to the initial stage of research to understand cancer biology. This review provides insights into targeted therapies and immunotherapies that have emerged using in vitro models and microbiome analysis. It focuses on therapeutic development using cell lines and the limitations of tumor heterogeneity and microenvironment. We explore the evolving landscape of breast cancer cell lines from two-dimensional (2-D) cultures to patient-derived xenograft (PDX) models advancing both fundamental and translational research. Patient-derived xenografts, cell line-derived xenografts (CDX), three-dimensional (3-D) cultures, organoids, and circulating tumor cells (CTC) models provide promising alternatives that capture the intricacies of the tumor microenvironment. This review bridges the gap between traditional cell lines and newer developments exploring the therapeutic and diagnostic advancements and needs for cell lines to expedite the progress in breast cancer research and treatment.