Capturing colorectal cancer inter-tumor heterogeneity in patient-derived xenograft (PDX) models

Prediction of Clinical Precision Chemotherapy by Patient-Derived 3D Bioprinting Models of Colorectal Cancer and Its Liver Metastases

Methods accurately predicting the responses of colorectal cancer (CRC) and colorectal cancer liver metastasis (CRLM) to personalized chemotherapy remain limited due to tumor heterogeneity. This study introduces an innovative patient-derived CRC and CRLM tumor model for preclinical investigation, utilizing 3d-bioprinting (3DP) technology. Efficient construction of homogeneous in vitro 3D models of CRC/CRLM is achieved through the application of patient-derived primary tumor cells and 3D bioprinting with bioink. Genomic and histological analyses affirm that the CRC/CRLM 3DP tumor models effectively retain parental tumor biomarkers and mutation profiles. In vitro tests evaluating chemotherapeutic drug sensitivities reveal substantial tumor heterogeneity in chemotherapy responses within the 3DP CRC/CRLM models. Furthermore, a robust correlation is evident between the drug response in the CRLM 3DP model and the clinical outcomes of neoadjuvant chemotherapy. These findings imply a significant potential for the application of patient-derived 3DP cancer models in precision chemotherapy prediction and preclinical research for CRC/CRLM.

Microsatellite instability states serve as predictive biomarkers for tumors chemotherapy sensitivity

There is an urgent need for markers to predict the efficacy of different chemotherapy drugs. Herein, we examined whether microsatellite instability (MSI) status can predict tumor multidrug sensitivity and explored the underlying mechanisms. We downloaded data from several public databases. Drug sensitivity was compared between the high microsatellite instability (MSI-H) and microsatellite-stable/low microsatellite instability (MSS/MSI-L) groups. In addition, we performed pathway enrichment analysis and cellular chemosensitivity assays to explore the mechanisms by which MSI status may affect drug sensitivity and assessed the differences between drug-treated and control cell lines. We found that multiple MSI-H tumors were more sensitive to a variety of chemotherapy drugs than MSS/MSI-L tumors, and especially for CRC, chemosensitivity is enhanced through the downregulation of DDR pathways such as NHEJ. Additional DNA damage caused by chemotherapeutic drugs results in further downregulation of DDR pathways and enhances drug sensitivity, forming a cycle of increasing drug sensitivity.

Generation, evolution, interfering factors, applications, and challenges of patient-derived xenograft models in immunodeficient mice

Establishing appropriate preclinical models is essential for cancer research. Evidence suggests that cancer is a highly heterogeneous disease. This follows the growing use of cancer models in cancer research to avoid these differences between xenograft tumor models and patient tumors. In recent years, a patient-derived xenograft (PDX) tumor model has been actively generated and applied, which preserves both cell-cell interactions and the microenvironment of tumors by directly transplanting cancer tissue from tumors into immunodeficient mice. In addition to this, the advent of alternative hosts, such as zebrafish hosts, or in vitro models (organoids and microfluidics), has also facilitated the advancement of cancer research. However, they still have a long way to go before they become reliable models. The development of immunodeficient mice has enabled PDX to become more mature and radiate new vitality. As one of the most reliable and standard preclinical models, the PDX model in immunodeficient mice (PDX-IM) exerts important effects in drug screening, biomarker development, personalized medicine, co-clinical trials, and immunotherapy. Here, we focus on the development procedures and application of PDX-IM in detail, summarize the implications that the evolution of immunodeficient mice has brought to PDX-IM, and cover the key issues in developing PDX-IM in preclinical studies.

Patient-derived xenograft models in cancer therapy: technologies and applications

Patient-derived xenograft (PDX) models, in which tumor tissues from patients are implanted into immunocompromised or humanized mice, have shown superiority in recapitulating the characteristics of cancer, such as the spatial structure of cancer and the intratumor heterogeneity of cancer. Moreover, PDX models retain the genomic features of patients across different stages, subtypes, and diversified treatment backgrounds. Optimized PDX engraftment procedures and modern technologies such as multi-omics and deep learning have enabled a more comprehensive depiction of the PDX molecular landscape and boosted the utilization of PDX models. These irreplaceable advantages make PDX models an ideal choice in cancer treatment studies, such as preclinical trials of novel drugs, validating novel drug combinations, screening drug-sensitive patients, and exploring drug resistance mechanisms. In this review, we gave an overview of the history of PDX models and the process of PDX model establishment. Subsequently, the review presents the strengths and weaknesses of PDX models and highlights the integration of novel technologies in PDX model research. Finally, we delineated the broad application of PDX models in chemotherapy, targeted therapy, immunotherapy, and other novel therapies.

Pan-cancer molecular subtypes of metastasis reveal distinct and evolving transcriptional programs

Molecular mechanisms underlying cancer metastasis span diverse tissues of origin. Here, we synthesize and collate the transcriptomes of patient-derived xenografts and patient tumor metastases, and these data collectively represent 38 studies and over 3,000 patients and 4,000 tumors. We identify four expression-based subtypes of metastasis transcending tumor lineage. The first subtype has extensive copy alterations, higher expression of MYC transcriptional targets and DNA repair genes, and bromodomain inhibitor response association. The second subtype has higher expression of genes involving metabolism and prostaglandin synthesis and regulation. The third subtype has evidence of neuronal differentiation, higher expression of DNA and histone methylation genes and EZH2 transcriptional targets, and BCL2 inhibitor response association. The fourth subtype has higher expression of immune checkpoint and Notch pathway genes. The metastasis subtypes reflect expression differences from paired primaries, with subtype switching being common. These subtypes facilitate understanding of the molecular underpinnings of metastases beyond tissue-oriented domains, with therapeutic implications.

Patient-derived xenograft model in colorectal cancer basic and translational research

Colorectal cancer (CRC) is one of the most popular malignancies globally, with 930 000 deaths in 2020. The evaluation of CRC-related pathogenesis and the discovery of potential therapeutic targets will be meaningful and helpful for improving CRC treatment. With huge efforts made in past decades, the systematic treatment regimens have been applied to improve the prognosis of CRC patients. However, the sensitivity of CRC to chemotherapy and targeted therapy is different from person to person, which is an important cause of treatment failure. The emergence of patient-derived xenograft (PDX) models shows great potential to alleviate the straits. PDX models possess similar genetic and pathological characteristics as the features of primary tumors. Moreover, PDX has the ability to mimic the tumor microenvironment of the original tumor. Thus, the PDX model is an important tool to screen precise drugs for individualized treatment, seek predictive biomarkers for prognosis supervision, and evaluate the unknown mechanism in basic research. This paper reviews the recent advances in constructed methods and applications of the CRC PDX model, aiming to provide new knowledge for CRC basic research and therapeutics.

Recent advances in the development of transplanted colorectal cancer mouse models

Despite progress in prevention and treatment, colorectal cancer (CRC) remains the third most common malignancy worldwide and the second most common cause of cancer death in 2020. To evaluate various characteristics of human CRC, a variety of mouse models have been established. Transplant mouse models have distinct advantages in studying the clinical behavior and therapeutic progress of CRC. Host, xenograft, and transplantation routes are the basis of transplant mouse models. As the effects of the tumor microenvironment and the systemic environment on cancer cells are gradually revealed, 3 key elements of transplanted CRC mouse models have been revolutionized. This has led to the development of humanized mice, patient-derived xenografts, and orthotopic transplants that reflect the human systemic environment, patient's tumor of origin, and tumor growth microenvironments in immunodeficient mice, respectively. These milestone events have allowed for great progress in tumor biology and the treatment of CRC. This article reviews the evolution of these events and points out their strengths and weaknesses as innovative and useful preclinical tools to study CRC progression and metastasis and to exploit novel treatment schedules by establishing a testing platform. This review article depicts the optimal transplanted CRC mouse models and emphasizes the significance of surgical models in the study of CRC behavior and treatment response.

Targeting RAS Mutant Colorectal Cancer with Dual Inhibition of MEK and CDK4/6

KRAS and NRAS mutations occur in 45% of colorectal cancers, with combined MAPK pathway and CDK4/6 inhibition identified as a potential therapeutic strategy. In the current study, this combinatorial treatment approach was evaluated in a co-clinical trial in patient-derived xenografts (PDX), and safety was established in a clinical trial of binimetinib and palbociclib in patients with metastatic colorectal cancer with RAS mutations. Across 18 PDX models undergoing dual inhibition of MEK and CDK4/6, 60% of tumors regressed, meeting the co-clinical trial primary endpoint. Prolonged duration of response occurred predominantly in TP53 wild-type models. Clinical evaluation of binimetinib and palbociclib in a safety lead-in confirmed safety and provided preliminary evidence of activity. Prolonged treatment in PDX models resulted in feedback activation of receptor tyrosine kinases and acquired resistance, which was reversed with a SHP2 inhibitor. These results highlight the clinical potential of this combination in colorectal cancer, along with the utility of PDX-based co-clinical trial platforms for drug development.

SIGNIFICANCE

This co-clinical trial of combined MEK-CDK4/6 inhibition in RAS mutant colorectal cancer demonstrates therapeutic efficacy in patient-derived xenografts and safety in patients, identifies biomarkers of response, and uncovers targetable mechanisms of resistance.

Engineered colorectal cancer tissue recapitulates key attributes of a patient-derived xenograft tumor line

The development of physiologically relevantin vitrocolorectal cancer (CRC) models is vital for advancing understanding of tumor biology. Although CRC patient-derived xenografts (PDXs) recapitulate key patient tumor characteristics and demonstrate high concordance with clinical outcomes, the use of thisin vivomodel is costly and low-throughput. Here we report the establishment and in-depth characterization of anin vitrotissue-engineered CRC model using PDX cells. To form the 3D engineered CRC-PDX (3D-eCRC-PDX) tissues, CRC PDX tumors were expandedin vivo, dissociated, and the isolated cells encapsulated within PEG-fibrinogen hydrogels. Following PEG-fibrinogen encapsulation, cells remain viable and proliferate within 3D-eCRC-PDX tissues. Tumor cell subpopulations, including human cancer and mouse stromal cells, are maintained in long-term culture (29 days); cellular subpopulations increase ratiometrically over time. The 3D-eCRC-PDX tissues mimic the mechanical stiffness of originating tumors. Extracellular matrix protein production by cells in the 3D-eCRC-PDX tissues resulted in approximately 57% of proteins observed in the CRC-PDX tumors also being present in the 3D-eCRC-PDX tissues on day 22. Furthermore, we show congruence in enriched gene ontology molecular functions and Hallmark gene sets in 3D-eCRC-PDX tissues and CRC-PDX tumors compared to normal colon tissue, while prognostic Kaplan-Meier plots for overall and relapse free survival did not reveal significant differences between CRC-PDX tumors and 3D-eCRC-PDX tissues. Our results demonstrate high batch-to-batch consistency and strong correlation between ourin vitrotissue-engineered PDX-CRC model and the originatingin vivoPDX tumors, providing a foundation for future studies of disease progression and tumorigenic mechanisms.

Longitudinal evaluation of five nasopharyngeal carcinoma animal models on the microPET/MR platform

PURPOSE

We longitudinally evaluated the tumour growth and metabolic activity of three nasopharyngeal carcinoma (NPC) cell line models (C666-1, C17 and NPC43) and two xenograft models (Xeno76 and Xeno23) using a micropositron emission tomography and magnetic resonance (microPET/MR). With a better understanding of the interplay between tumour growth and metabolic characteristics of these NPC models, we aim to provide insights for the selection of appropriate NPC cell line/xenograft models to assist novel drug discovery and evaluation.

METHODS

Mice were imaged by ¹⁸F-deoxyglucose ([¹⁸F]FDG) microPET/MR twice a week for consecutive 3-7 weeks. [¹⁸F]FDG uptake was quantified by standardized uptake value (SUV) and presented as SUVmean tumour-to-liver ratio (SUVRmean). Longitudinal tumour growth patterns and metabolic patterns were recorded. SUVRmean and histological characteristics were compared across the five NPC models. Cisplatin was administrated to one selected optimal tumour model, C17, to evaluate our imaging platform.

RESULTS

We found variable tumour growth and metabolic patterns across different NPC tumour types. C17 has an optimal growth rate and higher tumour metabolic activity compared with C666-1. C666-1 has a fast growth rate but is low in SUVRmean at endpoint due to necrosis as confirmed by H&E. NPC43 and Xeno76 have relatively slow growth rates and are low in SUVRmean, due to severe necrosis. Xeno23 has the slowest growth rate, and a relative high SUVRmean. Cisplatin showed the expected therapeutic effect in the C17 model in marked reduction of tumour size and metabolism.

CONCLUSION

Our study establishes an imaging platform that characterizes the growth and metabolic patterns of different NPC models, and the platform is well able to demonstrate drug treatment outcome supporting its use in novel drug discovery and evaluation for NPC.

Molecular subclassification of gastrointestinal cancers based on cancer stem cell traits

Human gastrointestinal malignancies are highly heterogeneous cancers. Clinically, heterogeneity largely contributes to tumor progression and resistance to therapy. Heterogeneity within gastrointestinal cancers is defined by molecular subtypes in genomic and transcriptomic analyses. Cancer stem cells (CSCs) have been demonstrated to be a major source of tumor heterogeneity; therefore, assessing tumor heterogeneity by CSC trait-guided classification of gastrointestinal cancers is essential for the development of effective therapies. CSCs share critical features with embryonic stem cells (ESCs). Molecular investigations have revealed that embryonic genes and developmental signaling pathways regulating the properties of ESCs or cell lineage differentiation are abnormally active and might be oncofetal drivers in certain tumor subtypes. Currently, multiple strategies allow comprehensive identification of tumor subtype-specific oncofetal signatures and evaluation of subtype-specific therapies. In this review, we summarize current knowledge concerning the molecular classification of gastrointestinal malignancies based on CSC features and elucidate their clinical relevance. We also outline strategies for molecular subtype identification and subtype-based therapies. Finally, we explore how clinical implementation of tumor classification by CSC subtype might facilitate the development of more effective personalized therapies for gastrointestinal cancers.

Preclinical models as patients' avatars for precision medicine in colorectal cancer: past and future challenges

Colorectal cancer (CRC) is a complex and heterogeneous disease, characterized by dismal prognosis and low survival rate in the advanced (metastatic) stage. During the last decade, the establishment of novel preclinical models, leading to the generation of translational discovery and validation platforms, has opened up a new scenario for the clinical practice of CRC patients. To bridge the results developed at the bench with the medical decision process, the ideal model should be easily scalable, reliable to predict treatment responses, and flexibly adapted for various applications in the research. As such, the improved benefit of novel therapies being tested initially on valuable and reproducible preclinical models would lie in personalized treatment recommendations based on the biology and genomics of the patient's tumor with the overall aim to avoid overtreatment and unnecessary toxicity. In this review, we summarize different in vitro and in vivo models, which proved efficacy in detection of novel CRC culprits and shed light into the biology and therapy of this complex disease. Even though cell lines and patient-derived xenografts remain the mainstay of colorectal cancer research, the field has been confidently shifting to the use of organoids as the most relevant preclinical model. Prioritization of organoids is supported by increasing body of evidence that these represent excellent tools worth further therapeutic explorations. In addition, novel preclinical models such as zebrafish avatars are emerging as useful tools for pharmacological interrogation. Finally, all available models represent complementary tools that can be utilized for precision medicine applications.

Patient-derived tumor models: a more suitable tool for pre-clinical studies in colorectal cancer

Colorectal cancer (CRC), despite the advances in screening and surveillance, remains the second most common cause of cancer death worldwide. The biological inadequacy of pre-clinical models to fully recapitulate the multifactorial etiology and the complexity of tumor microenvironment and human CRC's genetic heterogeneity has limited cancer treatment development. This has led to the development of Patient-derived models able to phenocopy as much as possible the original inter- and intra-tumor heterogeneity of CRC, reflecting the tumor microenvironment's cellular interactions. Implantation of patient tissue into immunodeficient mice hosts and the culture of tumor organoids have allowed advances in cancer biology and metastasis. This review highlights the advantages and limits of Patient-derived models as innovative and valuable pre-clinical tools to study progression and metastasis of CRC, develop novel therapeutic strategies by creating a drug screening platform, and predict the efficacy of clinical response to therapy.

Pre-Operative Decitabine in Colon Cancer Patients: Analyses on WNT Target Methylation and Expression

DNA hypermethylation is common in colon cancer. Previously, we have shown that methylation of WNT target genes predicts poor prognosis in stage II colon cancer. The primary objective of this study was to assess whether pre-operative treatment with decitabine can decrease methylation and increase the expression of WNT target genes APCDD1, AXIN2 and DKK1 in colon cancer patients. A clinical study was conducted, investigating these potential effects of decitabine in colon cancer patients (DECO). Patients were treated two times with 25 mg/m² decitabine before surgery. Methylation and expression of LINE1 and WNT target genes (primary outcome) and expression of endogenous retroviral genes (secondary outcome) were analysed in pre- and post-treatment tumour samples using pyrosequencing and rt-PCR. Ten patients were treated with decitabine and eighteen patients were used as controls. Decitabine treatment only marginally decreased LINE1 methylation. More importantly, no differences in methylation or expression of WNT target or endogenous retroviral genes were observed. Due to the lack of an effect on primary and secondary outcomes, the study was prematurely closed. In conclusion, pre-operative treatment with decitabine is safe, but with the current dosing, the primary objective, increased WNT target gene expression, cannot be achieved.

Patient-derived xenograft: a developing tool for screening biomarkers and potential therapeutic targets for human esophageal cancers

Esophageal cancer (EC) represents a human malignancy, diagnosed often at the advanced stage of cancer and resulting in high morbidity and mortality. The development of precision medicine allows for the identification of more personalized therapeutic strategies to improve cancer treatment. By implanting primary cancer tissues into immunodeficient mice for expansion, patient-derived xenograft (PDX) models largely maintain similar histological and genetic representations naturally found in patients' tumor cells. PDX models of EC (EC-PDX) provide fine platforms to investigate the tumor microenvironment, tumor genomic heterogeneity, and tumor response to chemoradiotherapy, which are necessary for new drug discovery to combat EC in addition to optimization of current therapeutic strategies for EC. In this review, we summarize the methods used for establishing EC-PDX models and investigate the utilities of EC-PDX in screening predictive biomarkers and potential therapeutic targets. The challenge of this promising research tool is also discussed.

Landscapes of cellular phenotypic diversity in breast cancer xenografts and their impact on drug response

The heterogeneity of breast cancer plays a major role in drug response and resistance and has been extensively characterized at the genomic level. Here, a single-cell breast cancer mass cytometry (BCMC) panel is optimized to identify cell phenotypes and their oncogenic signalling states in a biobank of patient-derived tumour xenograft (PDTX) models representing the diversity of human breast cancer. The BCMC panel identifies 13 cellular phenotypes (11 human and 2 murine), associated with both breast cancer subtypes and specific genomic features. Pre-treatment cellular phenotypic composition is a determinant of response to anticancer therapies. Single-cell profiling also reveals drug-induced cellular phenotypic dynamics, unravelling previously unnoticed intra-tumour response diversity. The comprehensive view of the landscapes of cellular phenotypic heterogeneity in PDTXs uncovered by the BCMC panel, which is mirrored in primary human tumours, has profound implications for understanding and predicting therapy response and resistance.

Current methods in translational cancer research

Recent developments in pre-clinical screening tools, that more reliably predict the clinical effects and adverse events of candidate therapeutic agents, has ushered in a new era of drug development and screening. However, given the rapid pace with which these models have emerged, the individual merits of these translational research tools warrant careful evaluation in order to furnish clinical researchers with appropriate information to conduct pre-clinical screening in an accelerated and rational manner. This review assesses the predictive utility of both well-established and emerging pre-clinical methods in terms of their suitability as a screening platform for treatment response, ability to represent pharmacodynamic and pharmacokinetic drug properties, and lastly debates the translational limitations and benefits of these models. To this end, we will describe the current literature on cell culture, organoids, in vivo mouse models, and in silico computational approaches. Particular focus will be devoted to discussing gaps and unmet needs in the literature as well as current advancements and innovations achieved in the field, such as co-clinical trials and future avenues for refinement.

AKT3 Expression in Mesenchymal Colorectal Cancer Cells Drives Growth and Is Associated with Epithelial-Mesenchymal Transition

Simple Summary

Colorectal cancer can be subdivided into four distinct subtypes that are characterised by different clinical features and responses to therapies currently used in the clinic to treat this disease. One of those subtypes, called CMS4, is associated with a worse prognosis and poor response to therapies compared to other subtypes. We therefore set out to explore what proteins are differentially expressed and used in CMS4 to find potential new targets for therapy. We found that protein AKT3 is highly expressed in CMS4, and that active AKT3 inhibits a protein that stalls growth of cancer cells (p27^KIP1). We can target AKT3 with inhibitors which leads to strongly reduced growth of cancer cell lines that are categorised as CMS4. Furthermore, our data suggests that high AKT3 expression in tumour cells may be used to identify poor prognosis colorectal cancer patients. Future research should point out if high AKT3 expression can be used to select colorectal cancer patients that have a poor prognosis but that could benefit from AKT3-targeted treatment.

Abstract

Colorectal cancer (CRC) is a heterogeneous disease that can currently be subdivided into four distinct consensus molecular subtypes (CMS) based on gene expression profiling. The CMS4 subtype is marked by high expression of mesenchymal genes and is associated with a worse overall prognosis compared to other CMSs. Importantly, this subtype responds poorly to the standard therapies currently used to treat CRC. We set out to explore what regulatory signalling networks underlie the CMS4 phenotype of cancer cells, specifically, by analysing which kinases were more highly expressed in this subtype compared to others. We found AKT3 to be expressed in the cancer cell epithelium of CRC specimens, patient derived xenograft (PDX) models and in (primary) cell cultures representing CMS4. Importantly, chemical inhibition or knockout of this gene hampers outgrowth of this subtype, as AKT3 controls expression of the cell cycle regulator p27^KIP1. Furthermore, high AKT3 expression was associated with high expression of epithelial-mesenchymal transition (EMT) genes, and this observation could be expanded to cell lines representing other carcinoma types. More importantly, this association allowed for the identification of CRC patients with a high propensity to metastasise and an associated poor prognosis. High AKT3 expression in the tumour epithelial compartment may thus be used as a surrogate marker for EMT and may allow for a selection of CRC patients that could benefit from AKT3-targeted therapy.

Investigation of colorectal cancer in accordance with consensus molecular subtype classification

The classification of colorectal cancer (CRC) plays a pivotal role in predicting a patient's prognosis and determining treatment strategies. The consensus molecular subtype (CMS) classification system was constructed by analyzing genetic information from 18 CRC data sets, containing 4151 CRC samples. CRC was classified into four subtypes with distinct molecular and biological characteristics: CMS1 (microsatellite instability immune), CMS2 (canonical), CMS3 (metabolic), and CMS4 (mesenchymal). Since their designation in 2015, these classifications have been applied to basic and translational research of CRC, with the hope that understanding these subsets will influence a clinician's approach to therapeutic treatment and improve clinical outcomes. We reviewed CRC investigations in accordance with CMSs published in the last 5 years to further explore the clinical significance of these subtypes and identify underlying trends that may direct relevant future research. We determined that CMSs linked common features of CRC cell lines and PDX models in various studies. Furthermore, associations between prognosis and clinicopathological findings, including pathological grade and the stage of carcinogenesis, tumor budding, and tumor location, were correlated with CMS classification. Novel prognostic factors were identified, and the relationship between chemotherapeutic drug resistance and CMS has been fortified by our compilation of research; thus, indicating that this review provides advanced insight into clinical questions and treatment strategies for CRC.

Exploring and modelling colon cancer inter-tumour heterogeneity: opportunities and challenges

Colon cancer inter-tumour heterogeneity is installed on multiple levels, ranging from (epi)genetic driver events to signalling pathway rewiring reflected by differential gene expression patterns. Although the existence of heterogeneity in colon cancer has been recognised for a longer period of time, it is sparingly incorporated as a determining factor in current clinical practice. Here we describe how unsupervised gene expression-based classification efforts, amongst which the consensus molecular subtypes (CMS), can stratify patients in biological subgroups associated with distinct disease outcome and responses to therapy. We will discuss what is needed to extend these subtyping efforts to the clinic and we will argue that preclinical models recapitulate CMS subtypes and can be of vital use to increase our understanding of treatment response and resistance and to discover novel targets for therapy.

m6A methyltransferase METTL3 maintains colon cancer tumorigenicity by suppressing SOCS2 to promote cell proliferation

N⁶-methyladenosine (m⁶A) RNA modification maintained by N6-methyltransferases and demethylases is involved in multiple biological functions. Methyltransferase like 3 (METTL3) is a major N⁶-methyltransferase. However, the role of METTL3 and its installed m⁶A modification in colorectal tumorigenesis remains to be fully elucidated. METTL3 is highly expressed as indicated in colorectal cancer samples in the TCGA and Oncomine databases, implying its potential role in colon tumorigenesis. SW480 cell line with stable METTL3 knockout (METTL3-KO) was generated using CRISPR/Cas9 and were confirmed by the loss of METTL3 expression and suppression of m⁶A modification. The proliferation of METTL3-KO cells was significantly inhibited compared with that of control cells. METTL3-KO decreased the decay rate of suppressor of cytokine signaling 2 (SOCS2) RNA, resulting in elevated SOCS2 protein expression. m⁶A-RNA immunoprecipitation-qPCR (MeRIP-qPCR) revealed that SOCS2 mRNA was targeted by METTL3 for m⁶A modification. Similar to METTL3-KO SW480 cells, SW480 cells treated with 3-deazaadenosine, an RNA methylation inhibitor, exhibited elevated SOCS2 protein expression. Increased levels of SOCS2 in METTL3-KO SW480 cells were associated with decreased expression of leucine-rich repeat-containing G protein-coupled receptor 5 (LGR5), contributing to the inhibition of cell proliferation. The underlying associations among METTL3, SOCS2, and LGR5 were further confirmed in SW480 cells transfected with si-METTL3 and in tumor samples from patients with colorectal cancer. Taken together, our data demonstrate that an increased level of METTL3 may maintain the tumorigenicity of colon cancer cells by suppressing SOCS2.

BRAF Mutated Colorectal Cancer: New Treatment Approaches

Colon cancer is one of the most frequently diagnosed malignancies in adults, considering both its incidence and prevalence. Anatomically, the right colon is considered as being from the cecum to the splenic flexure, and the left colon is from the splenic flexure to the rectum. Sidedness is a surrogate of a wide spectrum of colorectal cancer (CRC) biology features (embryology, microbiome, methylation, microsatellite instability (MSI), BRAF, aging, KRAS, consensus molecular subtypes (CMS), etc.), which result in prognostic factors. Different molecular subtypes have been identified, according to genomic and transcriptomic criteria. A subgroup harboring a BRAF mutation has been described, and represents approximately 10% of the patients diagnosed with colon cancer. This subgroup has morphological, clinical, and therapeutic characteristics that differ substantially from patients who do not carry this genetic alteration. Unfortunately, there is no established standard of care for this particular cohort of patients. This manuscript aims to study the biology of this subgroup of colon cancer, to understand the current approach in clinical research.

Patient-Derived In Vitro Models for Drug Discovery in Colorectal Carcinoma

Lack of relevant preclinical models that reliably recapitulate the complexity and heterogeneity of human cancer has slowed down the development and approval of new anti-cancer therapies. Even though two-dimensional in vitro culture models remain widely used, they allow only partial cell-to-cell and cell-to-matrix interactions and therefore do not represent the complex nature of the tumor microenvironment. Therefore, better models reflecting intra-tumor heterogeneity need to be incorporated in the drug screening process to more reliably predict the efficacy of drug candidates. Classic methods of modelling colorectal carcinoma (CRC), while useful for many applications, carry numerous limitations. In this review, we address the recent advances in in vitro CRC model systems, ranging from conventional CRC patient-derived models, such as conditional reprogramming-based cell cultures, to more experimental and state-of-the-art models, such as cancer-on-chip platforms or liquid biopsy.

Mouse models of colorectal cancer: Past, present and future perspectives

Colorectal cancer (CRC) is the third most common diagnosed malignancy among both sexes in the United States as well as in the European Union. While the incidence and mortality rates in western, high developed countries are declining, reflecting the success of screening programs and improved treatment regimen, a rise of the overall global CRC burden can be observed due to lifestyle changes paralleling an increasing human development index. Despite a growing insight into the biology of CRC and many therapeutic improvements in the recent decades, preclinical in vivo models are still indispensable for the development of new treatment approaches. Since the development of carcinogen-induced rodent models for CRC more than 80 years ago, a plethora of animal models has been established to study colon cancer biology. Despite tenuous invasiveness and metastatic behavior, these models are useful for chemoprevention studies and to evaluate colitis-related carcinogenesis. Genetically engineered mouse models (GEMM) mirror the pathogenesis of sporadic as well as inherited CRC depending on the specific molecular pathways activated or inhibited. Although the vast majority of CRC GEMM lack invasiveness, metastasis and tumor heterogeneity, they still have proven useful for examination of the tumor microenvironment as well as systemic immune responses; thus, supporting development of new therapeutic avenues. Induction of metastatic disease by orthotopic injection of CRC cell lines is possible, but the so generated models lack genetic diversity and the number of suited cell lines is very limited. Patient-derived xenografts, in contrast, maintain the pathological and molecular characteristics of the individual patient’s CRC after subcutaneous implantation into immunodeficient mice and are therefore most reliable for preclinical drug development – even in comparison to GEMM or cell line-based analyses. However, subcutaneous patient-derived xenograft models are less suitable for studying most aspects of the tumor microenvironment and anti-tumoral immune responses. The authors review the distinct mouse models of CRC with an emphasis on their clinical relevance and shed light on the latest developments in the field of preclinical CRC models.

Patient-derived xenograft models for personalized medicine in colorectal cancer

Establishing superior preclinical models is critical for translational cancer research owing to the high failure rates of novel therapeutics in clinical studies. Even though cell line-derived xenograft models are easy to create, they have numerous limitations since these models do not represent the distinctive features of each cancer patient adequately. To circumvent the discrepancies between xenograft models and tumors, patient-derived xenograft (PDX) models have been developed. These models are established through the engraftment of tissue from a patient's tumor into an immune-deficient mouse, which preserves cell-cell interactions and tumor microenvironment. Since PDXs precisely replicate intratumoral heterogeneity, a range of chemotherapeutic agents can be tested on individual tumors. Colorectal cancer represents a unique case to demonstrate clinical perspectives revealed by PDX models since they surmount limitations of conventional ex vivo models. Even though PDX models have been associated with drawbacks with respect to prediction of clinical outcomes, they are currently the model of choice for preclinical investigations in colorectal cancer. In the current review, we provide an overview of the methodology and applications of PDX for colorectal cancer and discuss critical issues for the advancement of these models for preclinical research.

Comprehensive comparison of patient-derived xenograft models in Hepatocellular Carcinoma and metastatic Liver Cancer

Patient-derived xenograft (PDX) models are effective preclinical cancer models that reproduce the tumor microenvironment of the human body. The methods have been widely used for drug screening, biomarker development, co-clinical trials, and personalized medicine. However, the low success rate and the long tumorigenesis period have largely limited their usage. In the present studies, we compared the PDX establishment between hepatocellular cancer (HCC) and metastatic liver cancer (MLC), and identified the key factors affecting the transplantation rate of PDXs. Surgically resected tumor specimens obtained from patients were subcutaneously inoculated into immunodeficient mice to construct PDX models. The overall transplantation rate was 38.5% (20/52), with the HCC group (28.1%, 9/32) being lower than MLC group (56.2%, 9/16). In addition, HCC group took significantly longer latency period than MLC group to construct PDX models. Hematoxylin and eosin staining results showed that the histopathology of all generations in PDX models was similar to the original tumor in all three types of cancer. The transplantation rate of PDX models in HCC patients was significantly associated with blood type (P=0.001), TNM stage (P=0.023), lymph node metastasis (P=0.042) and peripheral blood CA19-9 level (P=0.049), while the transplantation rate of PDX models in MLC patients was significantly associated with tumor size (P=0.034). This study demonstrates that PDX models can effectively reproduce the histological patterns of human tumors. The transplantation rate depends on the type of original tumor. Furthermore, it shows that the invasiveness of the original liver cancer affects the possibility of its growth in immunodeficient mice.

The fidelity of cancer cells in PDX models: Characteristics, mechanism and clinical significance

Patient-derived xenograft (PDX) models are widely used as preclinical cancer models and are considered better than cell culture models in recapitulating the histological features, molecular characteristics and intratumoral heterogeneity (ITH) of human tumors. While the PDX model is commonly accepted for use in drug discovery and other translational studies, a growing body of evidence has suggested its limitations. Recently, the fidelity of cancer cells within a PDX has been questioned, which may impede the future application of these models. In this review, we will focus the variable phenotypes of xenograft tumors and the genomic instability and molecular inconsistency of PDX tumors after serial transplantation. Next, we will discuss the underlying mechanism of ITH and its clinical relevance. Stochastic selection bias in the sampling process and/or deterministic clonal dynamics due to murine selective pressure may have detrimental effects on the results of personalized medicine and drug screening studies. In addition, we aim to identify a possible solution for the issue of fidelity in current PDX models and to discuss emerging next-generation preclinical models.

Tumor characteristics associated with engraftment of patient-derived non-small cell lung cancer xenografts in immunocompromised mice

BACKGROUND

Patient-derived xenograft (PDX) models increasingly are used in translational research. However, the engraftment rates of patient tumor samples in immunodeficient mice to PDX models vary greatly.

METHODS

Tumor tissue samples from 308 patients with non-small cell lung cancer were implanted in immunodeficient mice. The patients were followed for 1.5 to approximately 6 years. The authors performed histological analysis of PDXs and some residual tumor tissues in mice with failed PDX growth at 1 year after implantation. Quantitative polymerase chain reaction and enzyme-linked immunoadsorbent assay were performed to measure the levels of Epstein-Barr virus genes and human immunoglobulin G in PDX samples. Patient characteristics were compared for PDX growth and overall survival as outcomes using Cox regression analyses. Disease staging was based on the 7th TNM staging system.

RESULTS

The overall engraftment rate for PDXs from patients with non-small cell lung cancer was 34%. Squamous cell carcinomas had a higher engraftment rate (53%) compared with adenocarcinomas. Tumor samples from patients with stage II and stage III disease and from larger tumors were found to have relatively high engraftment rates. Patients whose tumors successfully engrafted had worse overall survival, particularly those individuals with adenocarcinoma, stage III or stage IV disease, and moderately differentiated tumors. Lymphoma formation was one of the factors associated with engraftment failure. Human CD8-positive and CD20-positive cells were detected in residual samples of tumor tissue that failed to generate a PDX at 1 year after implantation. Human immunoglobulin G was detected in the plasma of mice that did not have PDX growth at 14 months after implantation.

CONCLUSIONS

The results of the current study indicate that the characteristics of cancer cells and the tumor immune microenvironment in primary tumors both can affect engraftment of a primary tumor sample.

Back to the Colorectal Cancer Consensus Molecular Subtype Future

PURPOSE OF REVIEW

This review seeks to provide an informed prospective on the advances in molecular profiling and analysis of colorectal cancer (CRC). The goal is to provide a historical context and current summary on how advances in gene and protein sequencing technology along with computer capabilities led to our current bioinformatic advances in the field.

RECENT FINDINGS

An explosion of knowledge has occurred regarding genetic, epigenetic, and biochemical alterations associated with the evolution of colorectal cancer. This has led to the realization that CRC is a heterogeneous disease with molecular alterations often dictating natural history, response to treatment, and outcome. The consensus molecular subtypes (CMS) classification classifies CRC into four molecular subtypes with distinct biological characteristics, which may form the basis for clinical stratification and subtype-based targeted intervention. This review summarizes new developments of a field moving "Back to the Future." CRC molecular subtyping will better identify key subtype specific therapeutic targets and responses to therapy.