Cell Line Derived Xenograft Mouse Models Are a Suitable in vivo Model for Studying Tumor Budding in Colorectal Cancer

Emerging In Vitro and In Vivo Models: Hope for the Better Understanding of Cancer Progression and Treatment

Various cancer models have been developed to aid the understanding of the underlying mechanisms of tumor development and evaluate the effectiveness of various anticancer drugs in preclinical studies. These models accurately reproduce the critical stages of tumor initiation and development to mimic the tumor microenvironment better. Using these models for target validation, tumor response evaluation, resistance modeling, and toxicity comprehension can significantly enhance the drug development process. Herein, various in vivo or animal models are presented, typically consisting of several mice and in vitro models ranging in complexity from transwell models to spheroids and CRISPR-Cas9 technologies. While in vitro models have been used for decades and dominate the early stages of drug development, they are still limited primary to simplistic tests based on testing on a single cell type cultivated in Petri dishes. Recent advancements in developing new cancer therapies necessitate the generation of complicated animal models that accurately mimic the tumor's complexity and microenvironment. Mice make effective tumor models as they are affordable, have a short reproductive cycle, exhibit rapid tumor growth, and are simple to manipulate genetically. Human cancer mouse models are crucial to understanding the neoplastic process and basic and clinical research improvements. The following review summarizes different in vitro and in vivo metastasis models, their advantages and disadvantages, and their ability to serve as a model for cancer research.

Orthotopic and metastatic tumour models in preclinical cancer research

Mouse models of disease play a pivotal role at all stages of cancer drug development. Cell-line derived subcutaneous tumour models are predominant in early drug discovery, but there is growing recognition of the importance of the more complex orthotopic and metastatic tumour models for understanding both target biology in the correct tissue context, and the impact of the tumour microenvironment and the immune system in responses to treatment. The aim of this review is to highlight the value that orthotopic and metastatic models bring to the study of tumour biology and drug development while pointing out those models that are most likely to be encountered in the literature. Important developments in orthotopic models, such as the increasing use of early passage patient material (PDXs, organoids) and humanised mouse models are discussed, as these approaches have the potential to increase the predictive value of preclinical studies, and ultimately improve the success rate of anticancer drugs in clinical trials.

A review of animal models utilized in preclinical studies of approved gene therapy products: trends and insights

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

Neighboring macrophage-induced alteration in the phenotype of colorectal cancer cells in the tumor budding area

BACKGROUND

A higher number of tumor buds in the invasive front of colorectal cancer (CRC) specimens has been shown to contribute to a poor prognosis in CRC patients. Because macrophages (Mφs) have been demonstrated to alter the phenotype of cancer cells, we hypothesized that the phenotype of CRC cells in the tumor budding (TB) area might be changed by the interaction between CRC cells and Mφs.

METHODS

We assessed the expression of topoisomerase 1 in CRC cells to estimate the acquisition of chemoresistance in CRC. To demonstrate the tumor-stromal interaction between CRC cells and Mφs, we assessed two histological findings, the number of Mφs per single CRC cell and the proximity between CRC cells and Mφs by histological spatial analysis using HALO software.

RESULTS

The expression levels of topoisomerase 1 in CRC cells were decreased in deeper areas, especially in the TB area, compared to the surface area. Our histological spatial analysis revealed that 2.6 Mφs located within 60 μm of a single CRC cell were required to alter the phenotype of the CRC cell. Double-immunofluorescence staining revealed that higher Mφs were positive for interleukin-6 (IL-6) in the TB area and that AE1/AE3-positive CRC cells were also positive for phospho-STAT3 (pSTAT3) in the TB area; thus, the IL-6 receptor (IL-6R)/STAT3 signaling pathway in CRC cells was upregulated by IL-6 derived from neighboring Mφs.

CONCLUSION

IL-6 secreted from the neighboring Mφs would alter the phenotype of CRC cells via IL-6R/STAT3 signaling pathway.

Mesenchymal Stem Cells Target Gastric Cancer and Deliver Epirubicin via Tunneling Nanotubes for Enhanced Chemotherapy

BACKGROUND

A reduced effective local concentration significantly contributes to the unsatisfactory therapeutic results of epirubicin in gastric cancer. Mesenchymal stem cells exhibit targeted chemotaxis towards solid tumors and form tunneling nanotubes with tumor cells, facilitating the delivery of various substances. This study demonstrates the novelty of mesenchymal stem cells in releasing epirubicin into gastric cancer cells through tunneling nanotubes.

OBJECTIVE

Epirubicin delivery to gastric cancer cells using mesenchymal stem cells.

METHODS

In vitro transwell migration assays, live cell tracking, and in vivo targeting assays were used to demonstrate the chemotaxis of mesenchymal stem cells towards gastric cancer. We verified the targeted chemotaxis of mesenchymal stem cells towards gastric cancer cells and the epirubicin loading ability using a high-content imaging system (Equipment type:Operetta CLS). Additionally, tunneling nanotube formation and the targeted release of epirubicin-loaded mesenchymal stem cells co-cultured with gastric cancer cells through mesenchymal stem cell-tunneling nanotubes into gastric cancer cells was observed using Operetta CLS.

RESULTS

Mesenchymal stem cells demonstrated targeted chemotaxis towards gastric cancer, with effective epirubicin loading and tolerance. Co-culturing induced tunneling nanotube formation between these cells. Epirubicin-loaded mesenchymal stem cells were released into gastric cancer cells through tunneling nanotubes, significantly increasing their non-viability compared to the negative control group (p < 0.05).

CONCLUSIONS

We identified a novel approach for precisely targeting epirubicin release in gastric cancer cells. Therefore, mesenchymal stem cell-tunneling nanotubes could serve as a potential tool for targeted delivery of drugs, enhancing their chemotherapeutic effects in cancer cells.

Patient-Derived Xenografts: Historical Evolution, Immunocompromised Host Models, and Translational Significance

Patient-derived xenografts (PDXs) represent a critical advancement in preclinical cancer research, wherein human tumor samples are implanted into animal models for evaluation of therapeutic responses. PDXs have emerged as indispensable tools in translational cancer research, facilitating investigation into tumor microenvironments and personalized medicine. This chapter elucidates the historical evolution of PDXs, from early attempts in the eighteenth century to contemporary immunocompromised host models that enhance engraftment success.

Genetic Alterations of NF-κB and Its Regulators: A Rich Platform to Advance Colorectal Cancer Diagnosis and Treatment

Colorectal cancer (CRC) is the third leading cause of cancer mortality in the United States, with an estimated 52,000 deaths in 2023. Though significant progress has been made in both diagnosis and treatment of CRC in recent years, genetic heterogeneity of CRC-the culprit for possible CRC relapse and drug resistance, is still an insurmountable challenge. Thus, developing more effective therapeutics to overcome this challenge in new CRC treatment strategies is imperative. Genetic and epigenetic changes are well recognized to be responsible for the stepwise development of CRC malignancy. In this review, we focus on detailed genetic alteration information about the nuclear factor (NF)-κB signaling, including both NF-κB family members, and their regulators, such as protein arginine methyltransferase 5 (PRMT5), and outer dynein arm docking complex subunit 2 (ODAD2, also named armadillo repeat-containing 4, ARMC4), etc., in CRC patients. Moreover, we provide deep insight into different CRC research models, with a particular focus on patient-derived xenografts (PDX) and organoid models, and their potential applications in CRC research. Genetic alterations on NF-κB signaling components are estimated to be more than 50% of the overall genetic changes identified in CRC patients collected by cBioportal for Cancer Genomics; thus, emphasizing its paramount importance in CRC progression. Consequently, various genetic alterations on NF-κB signaling may hold great promise for novel therapeutic development in CRC. Future endeavors may focus on utilizing CRC models (e.g., PDX or organoids, or isogenic human embryonic stem cell (hESC)-derived colonic cells, or human pluripotent stem cells (hPSC)-derived colonic organoids, etc.) to further uncover the underpinning mechanism of these genetic alterations in NF-κB signaling in CRC progression. Moreover, establishing platforms for drug discovery in dishes, and developing Biobanks, etc., may further pave the way for the development of innovative personalized medicine to treat CRC in the future.

Molecular, Cellular, and Technical Aspects of Breast Cancer Cell Lines as a Foundational Tool in Cancer Research

Breast cancer comprises about 30% of all new female cancers each year and is the most common malignant cancer in women in the United States. Breast cancer cell lines have been harnessed for many years as a foundation for in vitro analytic studies to understand the use of cancer prevention and therapy. There has yet to be a compilation of works to analyze the pitfalls, novel discoveries, and essential techniques for breast cancer cell line studies in a scientific context. In this article, we review the history of breast cancer cell lines and their origins, as well as analyze the molecular pathways that pharmaceutical drugs apply to breast cancer cell lines in vitro and in vivo. Controversies regarding the origins of certain breast cancer cell lines, the benefits of utilizing Patient-Derived Xenograft (PDX) versus Cell-Derived Xenograft (CDX), and 2D versus 3D cell culturing techniques will be analyzed. Novel outcomes from epigenetic discovery with dietary compound usage are also discussed. This review is intended to create a foundational tool that will aid investigators when choosing a breast cancer cell line to use in multiple expanding areas such as epigenetic discovery, xenograft experimentation, and cancer prevention, among other areas.

The Coming of Age of AI/ML in Drug Discovery, Development, Clinical Testing, and Manufacturing: The FDA Perspectives

Artificial intelligence (AI) and machine learning (ML) represent significant advancements in computing, building on technologies that humanity has developed over millions of years-from the abacus to quantum computers. These tools have reached a pivotal moment in their development. In 2021 alone, the U.S. Food and Drug Administration (FDA) received over 100 product registration submissions that heavily relied on AI/ML for applications such as monitoring and improving human performance in compiling dossiers. To ensure the safe and effective use of AI/ML in drug discovery and manufacturing, the FDA and numerous other U.S. federal agencies have issued continuously updated, stringent guidelines. Intriguingly, these guidelines are often generated or updated with the aid of AI/ML tools themselves. The overarching goal is to expedite drug discovery, enhance the safety profiles of existing drugs, introduce novel treatment modalities, and improve manufacturing compliance and robustness. Recent FDA publications offer an encouraging outlook on the potential of these tools, emphasizing the need for their careful deployment. This has expanded market opportunities for retraining personnel handling these technologies and enabled innovative applications in emerging therapies such as gene editing, CRISPR-Cas9, CAR-T cells, mRNA-based treatments, and personalized medicine. In summary, the maturation of AI/ML technologies is a testament to human ingenuity. Far from being autonomous entities, these are tools created by and for humans designed to solve complex problems now and in the future. This paper aims to present the status of these technologies, along with examples of their present and future applications.

Proteomics in Childhood Acute Lymphoblastic Leukemia: Challenges and Opportunities

Acute lymphoblastic leukemia (ALL) is the most common cancer in children and one of the success stories in cancer therapeutics. Risk-directed therapy based on clinical, biologic and genetic features has played a significant role in this accomplishment. Despite the observed improvement in survival rates, leukemia remains one of the leading causes of cancer-related deaths. Implementation of next-generation genomic and transcriptomic sequencing tools has illustrated the genomic landscape of ALL. However, the underlying dynamic changes at protein level still remain a challenge. Proteomics is a cutting-edge technology aimed at deciphering the mechanisms, pathways, and the degree to which the proteome impacts leukemia subtypes. Advances in mass spectrometry enable high-throughput collection of global proteomic profiles, representing an opportunity to unveil new biological markers and druggable targets. The purpose of this narrative review article is to provide a comprehensive overview of studies that have utilized applications of proteomics in an attempt to gain insight into the pathogenesis and identification of biomarkers in childhood ALL.

A 3D Analysis of Cleared Human Melanoma

Cutaneous melanoma is one of the most aggressive and deadliest cancers in human beings due to its invasiveness and other factors. Histopathological analysis is crucial for a proper diagnosis. Optical tissue clearing is a novel field that allows 3D image acquisition of large-scale biological tissues. Optical clearing and immunolabeling for 3D fluorescence imaging has yet to be extensively applied to melanoma. In the present manuscript, we establish, for the first time, an optical clearing and immunostaining procedure for human melanoma and human cell line-derived melanoma xenograft models using the CUBIC (clear, unobstructed brain imaging cocktails) technique. We have successfully cleared the samples and achieved 3D volumetric visualization of the tumor microenvironment, vasculature, and cell populations.

Patient-derived xenograft (PDX) models, applications and challenges in cancer research

The establishing of the first cancer models created a new perspective on the identification and evaluation of new anti-cancer therapies in preclinical studies. Patient-derived xenograft models are created by tumor tissue engraftment. These models accurately represent the biology and heterogeneity of different cancers and recapitulate tumor microenvironment. These features have made it a reliable model along with the development of humanized models. Therefore, they are used in many studies, such as the development of anti-cancer drugs, co-clinical trials, personalized medicine, immunotherapy, and PDX biobanks. This review summarizes patient-derived xenograft models development procedures, drug development applications in various cancers, challenges and limitations.

Large-Scale Gastric Cancer Susceptibility Gene Identification Based on Gradient Boosting Decision Tree

The early clinical symptoms of gastric cancer are not obvious, and metastasis may have occurred at the time of treatment. Poor prognosis is one of the important reasons for the high mortality of gastric cancer. Therefore, the identification of gastric cancer-related genes can be used as relevant markers for diagnosis and treatment to improve diagnosis precision and guide personalized treatment. In order to further reveal the pathogenesis of gastric cancer at the gene level, we proposed a method based on Gradient Boosting Decision Tree (GBDT) to identify the susceptible genes of gastric cancer through gene interaction network. Based on the known genes related to gastric cancer, we collected more genes which can interact with them and constructed a gene interaction network. Random Walk was used to extract network association of each gene and we used GBDT to identify the gastric cancer-related genes. To verify the AUC and AUPR of our algorithm, we implemented 10-fold cross-validation. GBDT achieved AUC as 0.89 and AUPR as 0.81. We selected four other methods to compare with GBDT and found GBDT performed best.

Bridging the Species Gap: Morphological and Molecular Comparison of Feline and Human Intestinal Carcinomas

Simple Summary

Colorectal cancer (CRC) is the second leading cause of cancer deaths in humans (2020) but modeling late-stage human CRC, including high tumor budding and metastatic activity, experimentally in mouse models is a major challenge. In the present study, histopathological, immunohistochemical and molecular features of spontaneous intestinal carcinomas in cats were evaluated with a special focus on their potential applicability as a valuable model for human CRC. Feline intestinal tumors display aggressive growth patterns and adequately model invasive late-stage human CRC. They exhibit the same histological subtypes and display strikingly high tumor budding activity, both of which are highly significant prognostic factors in human CRC. Moreover, human and feline colorectal tumors harbor the same mutations of the CTNNB1 gene, encoding β-catenin. Our data indicate that feline intestinal carcinomas constitute a valuable and promising in vivo model for human CRC. Further comparative oncological research, and especially investigation of the molecular landscape of feline intestinal neoplasms, is imperative.

Abstract

Limited availability of in vivo experimental models for invasive colorectal cancer (CRC) including metastasis and high tumor budding activity is a major problem in colorectal cancer research. In order to compare feline and human intestinal carcinomas, tumors of 49 cats were histologically subtyped, graded and further characterized according to the human WHO classification. Subsequently, feline tumors were compared to a cohort of 1004 human CRC cases. Feline intestinal tumors closely resembled the human phenotype on a histomorphological level. In both species, adenocarcinoma not otherwise specified (ANOS) was the most common WHO subtype. In cats, the second most common subtype of the colon (36.4%), serrated adenocarcinoma (SAC), was overrepresented compared to human CRC (8.7%). Mucinous adenocarcinoma (MAC) was the second most common subtype of the small intestine (12.5%). Intriguingly, feline carcinomas, particularly small intestinal, were generally of high tumor budding (Bd) status (Bd3), which is designated an independent prognostic key factor in human CRC. We also investigated the relevance of feline CTNNB1 exon 2 alterations by Sanger sequencing. In four cases of feline colonic malignancies (3 ANOS, 1 SAC), somatic missense mutations of feline CTNNB1 (p.D32G, p.D32N, p.G34R, and p.S37F) were detected, indicating that mutational alterations of the WNT/β-catenin signaling pathway potentially play an essential role in feline intestinal tumorigenesis comparable to humans and dogs. These results indicate that spontaneous intestinal tumors of cats constitute a useful but so far underutilized model for human CRC. Our study provides a solid foundation for advanced comparative oncology studies and emphasizes the need for further (molecular) characterization of feline intestinal carcinomas.

New Insight to Overcome Tumor Resistance: An Overview from Cellular to Clinical Therapies

Disease relapse caused by drug resistance still represents a major clinical hurdle in cancer treatments. Tumor cells may take advantage of different intracellular and genetic systems attenuating the drug effects. Resistant cells or minimal residual disease (MRD) cells have strong clinical relevance, as they might give rise to secondary tumors when the therapy is concluded. Thus, MRDs are crucial therapeutic targets in order to prevent tumor relapse. Therefore, several groups aim at understanding how MRDs are orginated, characterizing their molecular features, and eradicating them. In this review, we will describe MRD from a genetic, evolutionary, and molecular point of view. Moreover, we will focus on the new in vitro, in vivo, preclinical, and clinical studies that aim at eradicating tumor resistance.

Establishment of an In Vivo Xenograft Mouse Model of a Subcutaneous Submillimeter HT-29 Tumor Formed from a Single Spheroid Transplanted Using Radiation-Crosslinked Gelatin Hydrogel Microwell

Colorectal cancer is a frequent cause of death worldwide. The detection and treatment of small nodules are crucial for improving survival of colorectal cancer patients. Submillimeter tumors are useful tools for developing novel methods to approach this issue. However, there are no suitable in vivo models that allow easy monitoring of the growth of these tumors. This study established a xenograft mouse model of subcutaneous submillimeter tumors with human colorectal cancer HT-29 cells. We transplanted a single spheroid formed by HT-29 cells expressing red fluorescent protein (RFP) (HT-29-RFP). Additionally, we adopted our newly developed radiation-crosslinked gelatin hydrogel microwells (rGHMs), which can be used as a culture base to form spheroids and as a transplantation scaffold with biocompatibility and biodegradability. Spheroids approximately 700 μm in size were uniformly created in seven days in the respective rGHMs. Every single spheroid was extracted either with or without rGHM and transplanted into the subcutis of severe combined immunodeficiency (SCID) mice (n = 4). After 21 days, the spheroids inoculated together with rGHM successfully formed uniform subcutaneous submillimeter tumor xenografts that were observable in vivo in a stereoscopic fluorescence microscope in all transplanted mice. In contrast, spheroids transplanted without rGHM also developed small tumors in all mice but showed higher variability in size than those transplanted with rGHM. During transplantation, the rGHM ensured easy handling and stabilization of the position of a single spheroid. Inoculation of spheroids with rGHM in the nude mice was similarly examined (n = 4), showing that only one out of four mice formed tumors. In conclusion, rGHM effectively formed spheroids and created uniformed xenografted submillimeter tumors of HT-29-RFP in SCID mice. Our model could provide a useful platform to develop medicines and methods for detection and treatment of small nodules of colorectal cancer.

Classification of colorectal tissue images from high throughput tissue microarrays by ensemble deep learning methods

Tissue microarray (TMA) core images are a treasure trove for artificial intelligence applications. However, a common problem of TMAs is multiple sectioning, which can change the content of the intended tissue core and requires re-labelling. Here, we investigate different ensemble methods for colorectal tissue classification using high-throughput TMAs. Hematoxylin and Eosin (H&E) core images of 0.6 mm or 1.0 mm diameter from three international cohorts were extracted from 54 digital slides (n = 15,150 cores). After TMA core extraction and color enhancement, five different flows of independent and ensemble deep learning were applied. Training and testing data with 2144 and 13,006 cores included three classes: tumor, normal or "other" tissue. Ground-truth data were collected from 30 ngTMA slides (n = 8689 cores). A test augmentation is applied to reduce the uncertain prediction. Predictive accuracy of the best method, namely Soft Voting Ensemble of one VGG and one CapsNet models was 0.982, 0.947 and 0.939 for normal, "other" and tumor, which outperformed to independent or ensemble learning with one base-estimator. Our high-accuracy algorithm for colorectal tissue classification in high-throughput TMAs is amenable to images from different institutions, core sizes and stain intensity. It helps to reduce error in TMA core evaluations with previously given labels.

Continuous formation of small clusters with LGR5-positive cells contributes to tumor growth in a colorectal cancer xenograft model

New cancer characteristics can be discovered by focusing on the process of tumor formation. Cancer stem cells (CSCs) are a key subpopulation, as they are theorized to be at the apex of the tumor hierarchy. We can better understand their function in the tumor hierarchy by using sectioned samples to observe the growth of tumors from their origins as CSCs. In this study, we evaluated the growth of moderate differentiated colorectal cancer from LGR5-positive cells, which is a CSC marker of colorectal cancer, using xenograft and three-dimensional culture models spatiotemporally. These cells express LGR5 at high levels and show CSC phenotypes. To detect them, we used a previously generated antibody that specifically targets LGR5, and were therefore able to observe LGR5-positive cells aggregating into small clusters (sCLs) over the course of tumor growth. Because these LGR5-expressing sCLs formed continuously during growth mainly in the invasive front, we concluded that the structure must contribute significantly to the expansion of CSCs and to tumor growth overall. We confirmed the formation of sCLs from gland structures using a three-dimensional culture model. In addition, sCLs exhibited upregulated genes related to stress response and partial/hybrid epithelial-mesenchymal transition (EMT), as well as genes reported to be prognosis factors. Finally, sCLs with high LGR5 expression were identified in clinical samples. Based on these results, we elucidate how sCLs are an important contributors to tumor growth and the expansion of CSCs.

A Scaffold-Free 3-D Co-Culture Mimics the Major Features of the Reverse Warburg Effect In Vitro

Most tumors consume large amounts of glucose. Concepts to explain the mechanisms that mediate the achievement of this metabolic need have proposed a switch of the tumor mass to aerobic glycolysis. Depending on whether primarily tumor or stroma cells undergo such a commutation, the terms ‘Warburg effect’ or ‘reverse Warburg effect’ were coined to describe the underlying biological phenomena. However, current in vitro systems relying on 2-D culture, single cell-type spheroids, or basal-membrane extract (BME/Matrigel)-containing 3-D structures do not thoroughly reflect these processes. Here, we aimed to establish a BME/Matrigel-free 3-D microarray cancer model to recapitulate the metabolic interplay between cancer and stromal cells that allows mechanistic analyses and drug testing. Human HT-29 colon cancer and CCD-1137Sk fibroblast cells were used in mono- and co-cultures as 2-D monolayers, spheroids, and in a cell-chip format. Metabolic patterns were studied with immunofluorescence and confocal microscopy. In chip-based co-cultures, HT-29 cells showed facilitated 3-D growth and increased levels of hexokinase-2, TP53-induced glycolysis and apoptosis regulator (TIGAR), lactate dehydrogenase, and: translocase of outer mitochondrial membrane 20 (TOMM20), when compared with HT-29 mono-cultures. Fibroblasts co-cultured with HT-29 cells expressed higher levels of mono-carboxylate transporter 4, hexokinase-2, microtubule-associated proteins 1A/1B light chain 3, and ubiquitin-binding protein p62 than in fibroblast mono-cultures, in both 2-D cultures and chips. Tetramethylrhodamin-methylester (TMRM) live-cell imaging of chip co-cultures revealed a higher mitochondrial potential in cancer cells than in fibroblasts. The findings demonstrate a crosstalk between cancer cells and fibroblasts that affects cellular growth and metabolism. Chip-based 3-D co-cultures of cancer cells and fibroblasts mimicked features of the reverse Warburg effect.

Association of Tumor Budding With Immune Evasion Pathways in Primary Colorectal Cancer and Patient-Derived Xenografts

Tumor budding has been found to be of prognostic significance for several cancers, including colorectal cancer (CRC). Additionally, the molecular classification of CRC has led to the identification of different immune microenvironments linked to distinct prognosis and therapeutic response. However, the association between tumor budding and the different molecular subtypes of CRC and distinct immune profiles have not been fully elucidated. This study focused, firstly, on the validation of derived xenograft models (PDXs) for the evaluation of tumor budding and their human counterparts and, secondly, on the association between tumor budding and the immune tumor microenvironment by the analysis of gene expression signatures of immune checkpoints, Toll-like receptors (TLRs), and chemokine families. Clinical CRC samples with different grades of tumor budding and their corresponding PDXs were included in this study. Tumor budding grade was reliably reproduced in early passages of PDXs, and high-grade tumor budding was intimately related with a poor-prognosis CMS4 mesenchymal subtype. In addition, an upregulation of negative regulatory immune checkpoints (PDL1, TIM-3, NOX2, and IDO1), TLRs (TLR1, TLR3, TLR4, and TLR6), and chemokine receptors and ligands (CXCR2, CXCR4, CXCL1, CXCL2, CXCL6, and CXCL9) was detected in high-grade tumor budding in both human samples and their corresponding xenografts. Our data support a close link between high-grade tumor budding in CRC and a distinctive immune-suppressive microenvironment promoting tumor invasion, which may have a determinant role in the poor prognosis of the CMS4 mesenchymal subtype. In addition, our study demonstrates that PDX models may constitute a robust preclinical platform for the development of novel therapies directed against tumor budding in CRC.

Recent advances in mass spectrometry based clinical proteomics: applications to cancer research

Cancer biomarkers have transformed current practices in the oncology clinic. Continued discovery and validation are crucial for improving early diagnosis, risk stratification, and monitoring patient response to treatment. Profiling of the tumour genome and transcriptome are now established tools for the discovery of novel biomarkers, but alterations in proteome expression are more likely to reflect changes in tumour pathophysiology. In the past, clinical diagnostics have strongly relied on antibody-based detection strategies, but these methods carry certain limitations. Mass spectrometry (MS) is a powerful method that enables increasingly comprehensive insights into changes of the proteome to advance personalized medicine. In this review, recent improvements in MS-based clinical proteomics are highlighted with a focus on oncology. We will provide a detailed overview of clinically relevant samples types, as well as, consideration for sample preparation methods, protein quantitation strategies, MS configurations, and data analysis pipelines currently available to researchers. Critical consideration of each step is necessary to address the pressing clinical questions that advance cancer patient diagnosis and prognosis. While the majority of studies focus on the discovery of clinically-relevant biomarkers, there is a growing demand for rigorous biomarker validation. These studies focus on high-throughput targeted MS assays and multi-centre studies with standardized protocols. Additionally, improvements in MS sensitivity are opening the door to new classes of tumour-specific proteoforms including post-translational modifications and variants originating from genomic aberrations. Overlaying proteomic data to complement genomic and transcriptomic datasets forges the growing field of proteogenomics, which shows great potential to improve our understanding of cancer biology. Overall, these advancements not only solidify MS-based clinical proteomics' integral position in cancer research, but also accelerate the shift towards becoming a regular component of routine analysis and clinical practice.

Proteomic investigations into resistance in colorectal cancer

Introduction: Despite advances in screening and treatment options, colorectal cancer (CRC) remains one of the most prevalent and lethal cancer subtypes. Resistance to cytotoxic or targeted therapy has remained a constant challenge to the treatment and long-term management of patients, attracting intense worldwide investigation since the 1950s. Through extensive investigations into the proteomic mechanisms and functions that convey resistance to therapy/s, researchers have become able to implicate alterations in several signaling pathways that provide and sustain resistance to treatment.Areas covered: In this review, we summarize how protein alterations are associated with resistance to therapy, with particular emphasis on CRC. An overview of the mechanisms of therapeutic resistance is described, highlighting recent studies which endeavor to elucidate the proteomic changes that are associated with the acquisition and promulgation of therapeutic resistance.Expert opinion: While cancers such as CRC have been intensively studied for decades, unresponsiveness and the resistance to therapy remain critical obstacles in the treatment of patients. Due to the inherent biological and clinical heterogeneity of individual CRCs, proteomic methods stand to become powerful tools to provide biological insights that may guide therapeutic strategies with the ultimate goal of refining emergent immunotherapeutic treatments.