Oral Cavity Squamous Cell Carcinoma Xenografts Retain Complex Genotypes and Intertumor Molecular Heterogeneity

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.

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.

Integrated variant allele frequency analysis pipeline and R package: easyVAF

Somatic sequence variants are associated with cancer diagnosis, prognostic stratification, and treatment response. Variant allele frequency (VAF), the percentage of sequence reads with a specific DNA variant over the read depth at that locus, has been used as a metric to quantify mutation rates in these applications. VAF has the potential for feature detection by reflecting changes in tumor clonal composition across treatments or time points. Although there are several packages, including Genome Analysis Toolkit and VarScan, designed for variant calling and rare mutation identification, there is no readily available package for comparing VAFs among and between groups to identify loci of interest. To this end, we have developed the R package easyVAF, which includes parametric and nonparametric tests to compare VAFs among multiple groups. It is accompanied by an interactive R Shiny app. With easyVAF, the investigator has the option between three statistical tests to maximize power while maintaining an acceptable type I error rate. This paper presents our proposed pipeline for VAF analysis, from quality checking to group comparison. We evaluate our method in a wide range of simulated scenarios and show that choosing the appropriate test to limit the type I error rate is critical. For situations where data is sparse, we recommend comparing VAFs with the beta-binomial likelihood ratio test over Fisher's exact test and Pearson's χ2 test.

Urokinase-Type Plasminogen Activator Receptor (uPAR) Expression and [64Cu]Cu-DOTA-AE105 uPAR-PET/CT in Patient-Derived Xenograft Models of Oral Squamous Cell Carcinoma

PURPOSE

[64Cu]Cu-DOTA-AE105 urokinase-type plasminogen activator receptor (uPAR)-PET/CT is a novel and promising imaging modality for cancer visualization, although it has not been tested in head and neck cancer patients nor in preclinical models that closely resemble these heterogenous tumors, i.e., patient-derived xenograft (PDX) models. The aim of the present study was to establish and validate oral squamous cell carcinoma (OSCC) PDX models and to evaluate [64Cu]Cu-uPAR-PET/CT for tumor imaging in these models.

PROCEDURES

PDX flank tumor models were established by engrafting tumor tissue from three patients with locally advanced OSCC into immunodeficient mice. [64Cu]Cu-DOTA-AE105 was injected in passage 2 (P2) mice, and [64Cu]Cu-uPAR-PET/CT was performed 1 h and 24 h after injection. After the last PET scan, all animals were euthanized, and tumors dissected for autoradiography and immunohistochemical (IHC) staining.

RESULTS

Three PDX models were established, and all of them showed histological stability and unchanged heterogenicity, uPAR expression, and Ki67 expression through passages. A significant correlation between uPAR expression and tumor growth was found. All tumors of all models (n=29) showed tumor uptake of [64Cu]Cu-DOTA-AE105. There was a clear visual concordance between the distribution of uPAR expression (IHC) and [64Cu]Cu-DOTA-AE105 uptake pattern in tumor tissue (autoradiography). No significant correlation was found between IHC (H-score) and PET-signal (SUVmax) (r=0.34; p=0.07).

CONCLUSIONS

OSCC PDX models in early passages histologically mimic donor tumors and could serve as a valuable platform for the development of uPAR-targeted imaging and therapeutic modalities. Furthermore, [64Cu]Cu-uPAR-PET/CT showed target- and tumor-specific uptake in OSCC PDX models demonstrating the diagnostic potential of this modality for OSCC patients.

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.

Integrated analysis of genomic and transcriptomic data for the discovery of splice-associated variants in cancer

Somatic mutations within non-coding regions and even exons may have unidentified regulatory consequences that are often overlooked in analysis workflows. Here we present RegTools ( www.regtools.org ), a computationally efficient, free, and open-source software package designed to integrate somatic variants from genomic data with splice junctions from bulk or single cell transcriptomic data to identify variants that may cause aberrant splicing. We apply RegTools to over 9000 tumor samples with both tumor DNA and RNA sequence data. RegTools discovers 235,778 events where a splice-associated variant significantly increases the splicing of a particular junction, across 158,200 unique variants and 131,212 unique junctions. To characterize these somatic variants and their associated splice isoforms, we annotate them with the Variant Effect Predictor, SpliceAI, and Genotype-Tissue Expression junction counts and compare our results to other tools that integrate genomic and transcriptomic data. While many events are corroborated by the aforementioned tools, the flexibility of RegTools also allows us to identify splice-associated variants in known cancer drivers, such as TP53, CDKN2A, and B2M, and other genes.

Therapeutic implications of transcriptomics in head and neck cancer patient-derived xenografts

There are currently no clinical strategies utilizing tumor gene expression to inform therapeutic selection for patients with head and neck squamous cell carcinoma (HNSCC). One of the challenges in developing predictive biomarkers is the limited characterization of preclinical HNSCC models. Patient-derived xenografts (PDXs) are increasingly recognized as translationally relevant preclinical avatars for human tumors; however, the overall transcriptomic concordance of HNSCC PDXs with primary human HNSCC is understudied, especially in human papillomavirus-associated (HPV+) disease. Here, we characterized 64 HNSCC PDXs (16 HPV+ and 48 HPV-) at the transcriptomic level using RNA-sequencing. The range of human-specific reads per PDX varied from 64.6%-96.5%, with a comparison of the most differentially expressed genes before and after removal of mouse transcripts revealing no significant benefit to filtering out mouse mRNA reads in this cohort. We demonstrate that four previously established HNSCC molecular subtypes found in The Cancer Genome Atlas (TCGA) are also clearly recapitulated in HNSCC PDXs. Unsupervised hierarchical clustering yielded a striking natural division of HNSCC PDXs by HPV status, with C19orf57 (BRME1), a gene previously correlated with positive response to cisplatin in cervical cancer, among the most significantly differentially expressed genes between HPV+ and HPV- PDXs. In vivo experiments demonstrated a possible relationship between increased C19orf57 expression and superior anti-tumor responses of PDXs to cisplatin, which should be investigated further. These findings highlight the value of PDXs as models for HPV+ and HPV- HNSCC, providing a resource for future discovery of predictive biomarkers to guide treatment selection in HNSCC.

A Novel Immune-Related Gene Signature to Identify the Tumor Microenvironment and Prognose Disease Among Patients With Oral Squamous Cell Carcinoma Patients Using ssGSEA: A Bioinformatics and Biological Validation Study

Oral squamous cell carcinoma (OSCC) is the most invasive oral malignancy in adults and is associated with a poor prognosis. Accurate prognostic models are urgently needed, however, knowledge of the probable mechanisms behind OSCC tumorigenesis and prognosis remain limited. The clinical importance of the interplay between the immune system and tumor microenvironment has become increasingly evident. This study explored immune-related alterations at the multi-omics level to extract accurate prognostic markers linked to the immune response and presents a more accurate landscape of the immune genomic map during OSCC. The Cancer Genome Atlas (TCGA) OSCC cohort (n = 329) was used to detect the immune infiltration pattern of OSCC and categorize patients into two immunity groups using single-sample gene set enrichment analysis (ssGSEA) and hierarchical clustering analysis. Multiple strategies, including lasso regression (LASSO), Cox proportional hazards regression, and principal component analysis (PCA) were used to screen clinically significant signatures and identify an incorporated prognosis model with robust discriminative power on the survival status of both the training and testing set. We identified two OSCC subtypes based on immunological characteristics: Immunity-high and immunity low, and verified that the categorization was accurate and repeatable. Immunity_ high cluster with a higher immunological and stromal score. 1047 differential genes (DEGs) integrate with immune genes to obtain 319 immue-related DEGs. A robust model with five signatures for OSCC patient prognosis was established. The GEO cohort (n = 97) were used to validate the risk model’s predictive value. The low-risk group had a better overall survival (OS) than the high-risk group. Significant prognostic potential for OSCC patients was found using ROC analysis and immune checkpoint gene expression was lower in the low-risk group. We also investigated at the therapeutic sensitivity of a number of frequently used chemotherapeutic drugs in patients with various risk factors. The underlying biological behavior of the OSCC cell line was preliminarily validated. This study characterizes a reliable marker of OSCC disease progression and provides a new potential target for immunotherapy against this disease.

FAT1 Upregulates in Oral Squamous Cell Carcinoma and Promotes Cell Proliferation via Cell Cycle and DNA Repair

Objective

Previous studies have revealed that FAT atypical cadherin 1 (FAT1) plays a tumor-suppressive or oncogenic role in a context-dependent manner in various cancers. However, the functions of FAT1 are ambiguous in tumorigenesis owing to inconsistent research in oral squamous cell carcinoma (OSCC). The present study aimed at gaining an insight into the role of FAT1 in the tumor genesis and development.

Methods

The expression, mutant, and survival data analyses were done using data from The Cancer Genome Atlas (TCGA), the Gene Expression Omnibus (GEO), and the Clinical Proteomic Tumor Analysis Consortium (CPTAC) database, verified with clinical samples via real-time polymerase chain reaction (qRT-PCR), Western blot (WB), and immunohistochemical (IHC) staining. OSCC cells transfected with siRNA were employed for in vitro assessment in cell proliferation, apoptosis, and migration ability in appropriate ways. The underlying mechanism was explored by RNA sequencing after FAT1 silencing.

Results

Overall, FAT1 significantly increased in OSCC with a poor prognosis outcome. The in vitro experiment showed the promoting effect of FAT1 in the proliferation and migration of OSCC cells. FAT1 can also inhibit both the early and late apoptosis of OSCC cells. RNA-sequencing analysis of FAT1 silencing revealed that the cell cycle, DNA replication, and some core genes (MCM2, MCM5, CCNE1 SPC24, MYBL2, KIF2C) may be the potential mechanism in OSCC.

Conclusions

FAT1 may act as an oncogene in OSCC with potential mechanism influencing the cell cycle and DNA repair.

Precision Medicine in Head and Neck Cancers: Genomic and Preclinical Approaches

Head and neck cancers (HNCs) represent the sixth most widespread malignancy worldwide. Surgery, radiotherapy, chemotherapeutic and immunotherapeutic drugs represent the main clinical approaches for HNC patients. Moreover, HNCs are characterised by an elevated mutational load; however, specific genetic mutations or biomarkers have not yet been found. In this scenario, personalised medicine is showing its efficacy. To study the reliability and the effects of personalised treatments, preclinical research can take advantage of next-generation sequencing and innovative technologies that have been developed to obtain genomic and multi-omic profiles to drive personalised treatments. The crosstalk between malignant and healthy components, as well as interactions with extracellular matrices, are important features which are responsible for treatment failure. Preclinical research has constantly implemented in vitro and in vivo models to mimic the natural tumour microenvironment. Among them, 3D systems have been developed to reproduce the tumour mass architecture, such as biomimetic scaffolds and organoids. In addition, in vivo models have been changed over the last decades to overcome problems such as animal management complexity and time-consuming experiments. In this review, we will explore the new approaches aimed to improve preclinical tools to study and apply precision medicine as a therapeutic option for patients affected by HNCs.

A novel immune checkpoint siglec-15 antibody inhibits LUAD by modulating mφ polarization in TME

BACKGROUND

Siglec-15 (S15) is a type-I transmembrane protein and is considered a new candidate of immune checkpoint inhibitor for cancer immunotherapy.

METHODS

In the present study, we first constructed and characterized a chimeric S15-specific monoclonal antibody (S15-4E6A). Then, the antitumor effectiveness and modulatory role of S15-4E6A in macrophages (mφs) were explored in vitro and in vivo. Finally, the underlying mechanism by which S15mAb inhibits LUAD was preliminarily explored.

RESULTS

The results demonstrated the successful construction of S15-4E6A, and S15-4E6A exerted an efficacious tumor-inhibitory effect on LUAD cells and xenografts. S15-4E6A could promote M1-mφ polarization while inhibiting M2-mφ polarization, both in vitro and in vivo.

CONCLUSIONS

S15-based immunotherapy that functions by modulating mφ polarization may be a promising strategy for the treatment of S15-positive LUAD.

Integrating CD4+ T cell help for therapeutic cancer vaccination in a preclinical head and neck cancer model

Head and neck squamous cell carcinomas (HNSCC) are well suited for cancer vaccination strategies. In addition to tumor-associated antigens (TAAs) and endogenous retrovirus (ERV) encoded proteins, HNSCCs have a relatively high tumor mutational burden encoding potential neoepitopes. Peptide vaccine candidates are prioritized by predicted high-affinity to major histocompatibility complex (MHC) class I with MHC-II affinity largely not being considered. Herein, we extend previous studies to evaluate therapeutic vaccination in the mouse oral cancer (MOC) 22 model. Two distinct MOC22 derived SLPs were tested – a TSA-oriented mutant intercellular adhesion molecule 1 (mICAM1) and p15E, an ERV encoded antigen. In silico prediction revealed mICAM1 SLP bore strong MHC-I and MHC-II epitopes sharing a mutant residue with vaccination significantly increasing both antigen-specific IFN-γ producing CD4⁺ and CD8⁺ T cells. By contrast, p15E SLP had a predicted high-affinity MHC-I epitope but lacked an MHC-II epitope and vaccination induced antigen-specific CD8⁺ but not CD4⁺ T cell responses. Therapeutic mICAM1 vaccination attenuated tumor growth effectively with mICAM1-specific T cells displaying durable IFN-γ production compared with p15E SLP. Furthermore, mICAM1 SLPs carrying weakened MHC-II binding epitopes were unable to control tumor growth. These data underscore the potential value of therapeutic targeting of HNSCC epitopes and highlight the importance of studying distinct antigen classes in this setting. Moreover, they raise the possibility that, at least in part, CD4⁺ T cell help is critical for cancer vaccination in this preclinical HNSCC model and suggest in silico prediction approaches prioritize overlapping MHC-I and MHC-II epitopes to generate potent cancer vaccines.

Preclinical models and technologies to advance nanovaccine development

The remarkable success of targeted immunotherapies is revolutionizing cancer treatment. However, tumor heterogeneity and low immunogenicity, in addition to several tumor-associated immunosuppression mechanisms are among the major factors that have precluded the success of cancer vaccines as targeted cancer immunotherapies. The exciting outcomes obtained in patients upon the injection of tumor-specific antigens and adjuvants intratumorally, reinvigorated interest in the use of nanotechnology to foster the delivery of vaccines to address cancer unmet needs. Thus, bridging nano-based vaccine platform development and predicted clinical outcomes the selection of the proper preclinical model will be fundamental. Preclinical models have revealed promising outcomes for cancer vaccines. However, only few cases were associated with clinical responses. This review addresses the major challenges related to the translation of cancer nano-based vaccines to the clinic, discussing the requirements for ex vivo and in vivo models of cancer to ensure the translation of preclinical success to patients.

Neuroblastoma Invasion Strategies Are Regulated by the Extracellular Matrix

Neuroblastoma is a paediatric malignancy of the developing sympathetic nervous system. About half of the patients have metastatic disease at the time of diagnosis and a survival rate of less than 50%. Our understanding of the cellular processes promoting neuroblastoma metastases will be facilitated by the development of appropriate experimental models. In this study, we aimed to explore the invasion of neuroblastoma cells and organoids from patient-derived xenografts (PDXs) grown embedded in 3D extracellular matrix (ECM) hydrogels by time-lapse microscopy and quantitative image analysis. We found that the ECM composition influenced the growth, viability and local invasion of organoids. The ECM compositions induced distinct cell behaviours, with Matrigel being the preferred substratum for local organoid invasion. Organoid invasion was cell line- and PDX-dependent. We identified six distinct phenotypes in PDX-derived organoids. In contrast, NB cell lines were more phenotypically restricted in their invasion strategies, as organoids isolated from cell line-derived xenografts displayed a broader range of phenotypes compared to clonal cell line clusters. The addition of FBS and bFGF induced more aggressive cell behaviour and a broader range of phenotypes. In contrast, the repression of the prognostic neuroblastoma marker, MYCN, resulted in less aggressive cell behaviour. The combination of PDX organoids, real-time imaging and the novel 3D culture assays developed herein will enable rapid progress in elucidating the molecular mechanisms that control neuroblastoma invasion.

Yap1 Mediates Trametinib Resistance in Head and Neck Squamous Cell Carcinomas

PURPOSE

In a head and neck squamous cell carcinoma (HNSCC) "window of opportunity" clinical trial, we reported that trametinib reduced MEK-Erk1/2 activation and resulted in tumor responses in a subset of patients. Here, we investigated resistance to trametinib and molecular correlates in HNSCC cell lines and patient samples.

EXPERIMENTAL DESIGN

HNSCC cell lines were treated with trametinib to generate resistant lines. Candidate bypass pathways were assessed using immunoblotting, CRISPR knockout, and survival assays. Effectiveness of combined trametinib and verteporfin targeting was evaluated. Patient-derived xenografts (PDXs) from responder patients were treated with trametinib and resistant tumors were analyzed. Window trial clinical samples were subjected to whole-exome and RNA sequencing.

RESULTS

HNSCC cell lines developed resistance (CAL27-TR and HSC3-TR) after prolonged trametinib exposure. Downstream effectors of the Hippo pathway were activated in CAL27-TR and HSC3-TR, and combined trametinib and verteporfin treatment resulted in synergistic treatment response. We defined the Hippo pathway effector Yap1 as an induced survival pathway promoting resistance to trametinib in HSC3-TR. Yap1 was necessary for HSC3-TR trametinib resistance, and constitutively active Yap1 was sufficient to confer resistance in parental HSC3. Analysis of trametinib neoadjuvant trial patient tumors indicated canonical MEK-Erk1/2 pathway activating mutations were infrequent, and Yap1 activity increased following trametinib treatment. Trametinib treatment of a PDX from a responder patient resulted in evolution of resistance with increased Yap1 expression and activity.

CONCLUSIONS

These studies identify a Yap1-dependent resistance to trametinib therapy in HNSCCs. Combined Yap1 and MEK targeting may represent a strategy to enhance HNSCC response.

Patient-Derived Xenograft and Organoid Models for Precision Medicine Targeting of the Tumour Microenvironment in Head and Neck Cancer

Patient survival from head and neck squamous cell carcinoma (HNSCC), the seventh most common cause of cancer, has not markedly improved in recent years despite the approval of targeted therapies and immunotherapy agents. Precision medicine approaches that seek to individualise therapy through the use of predictive biomarkers and stratification strategies offer opportunities to improve therapeutic success in HNSCC. To enable precision medicine of HNSCC, an understanding of the microenvironment that influences tumour growth and response to therapy is required alongside research tools that recapitulate the features of human tumours. In this review, we highlight the importance of the tumour microenvironment in HNSCC, with a focus on tumour hypoxia, and discuss the fidelity of patient-derived xenograft and organoids for modelling human HNSCC and response to therapy. We describe the benefits of patient-derived models over alternative preclinical models and their limitations in clinical relevance and how these impact their utility in precision medicine in HNSCC for the discovery of new therapeutic agents, as well as predictive biomarkers to identify patients' most likely to respond to therapy.

Head and neck cancer patient-derived xenograft models - A systematic review

BACKGROUND

Patient-derived xenograft (PDX) involve the direct surgical transfer of fresh human tumor samples to immunodeficient mice. This systematic review aimed to identify publications of head and neck cancer PDX (HNC-PDX) models, describing the main methodological characteristics and outcomes.

METHODS

An electronic search was undertaken in four databases, including publications having used HNC-PDX. Data were analyzed descriptively.

RESULTS

63 articles were yielded. The nude mouse was one most commonly animal model used (38.8 %), and squamous cell carcinoma accounted for the majority of HNC-PDX (80.6 %). Tumors were mostly implanted in the flank (86.3 %), and the latency period ranged from 30 to 401 days. The successful rate ranged from 17 % to 100 %. Different drugs and pathways were identified.

CONCLUSION

HNC-PDX appears to significantly recapitulate the morphology of the original HNC and represents a valuable method in translational research for the assessment of the in vivo effect of novel therapies for HNC.

Neoadjuvant and Adjuvant Pembrolizumab in Resectable Locally Advanced, Human Papillomavirus-Unrelated Head and Neck Cancer: A Multicenter, Phase II Trial

PURPOSE

Pembrolizumab improved survival in patients with recurrent or metastatic head and neck squamous-cell carcinoma (HNSCC). The aims of this study were to determine if pembrolizumab would be safe, result in pathologic tumor response (pTR), and lower the relapse rate in patients with resectable human papillomavirus (HPV)-unrelated HNSCC.

PATIENTS AND METHODS

Neoadjuvant pembrolizumab (200 mg) was administered and followed 2 to 3 weeks later by surgical tumor ablation. Postoperative (chemo)radiation was planned. Patients with high-risk pathology (positive margins and/or extranodal extension) received adjuvant pembrolizumab. pTR was quantified as the proportion of the resection bed with tumor necrosis, keratinous debris, and giant cells/histiocytes: pTR-0 (<10%), pTR-1 (10%-49%), and pTR-2 (≥50%). Coprimary endpoints were pTR-2 among all patients and 1-year relapse rate in patients with high-risk pathology (historical: 35%). Correlations of baseline PD-L1 and T-cell infiltration with pTR were assessed. Tumor clonal dynamics were evaluated (ClinicalTrials.gov NCT02296684).

RESULTS

Thirty-six patients enrolled. After neoadjuvant pembrolizumab, serious (grades 3-4) adverse events and unexpected surgical delays/complications did not occur. pTR-2 occurred in eight patients (22%), and pTR-1 in eight other patients (22%). One-year relapse rate among 18 patients with high-risk pathology was 16.7% (95% confidence interval, 3.6%-41.4%). pTR ≥10% correlated with baseline tumor PD-L1, immune infiltrate, and IFNγ activity. Matched samples showed upregulation of inhibitory checkpoints in patients with pTR-0 and confirmed clonal loss in some patients.

CONCLUSIONS

Among patients with locally advanced, HPV-unrelated HNSCC, pembrolizumab was safe, and any pathologic response was observed in 44% of patients with 0% pathologic complete responses. The 1-year relapse rate in patients with high-risk pathology was lower than historical.

Establishment and characterization of patient-derived xenografts as paraclinical models for head and neck cancer

Background

We investigated whether head and neck squamous cell carcinoma (HNSCC) patient-derived xenografts (PDXs) reaffirm patient responses to anti-cancer therapeutics.

Methods

Tumors from HNSCC patients were transplanted into immunodeficient mice and propagated via subsequent implantation. We evaluated established PDXs by histology, genomic profiling, and in vivo anti-cancer efficacy testing to confirm them as the authentic in vivo platform.

Results

From 62 HNSCCs, 15 (24%) PDXs were established. The primary cancer types were tongue (8), oropharynx (3), hypopharynx (1), ethmoid sinus cancer (1), supraglottic cancer (1), and parotid gland (1); six PDXs (40%) were established from biopsy specimens from advanced HNSCC. PDXs mostly retained donor characteristics and remained stable across passages. PIK3CA (H1047R), HRAS (G12D), and TP53 mutations (H193R, I195T, R248W, R273H, E298X) and EGFR, CCND1, MYC, and PIK3CA amplifications were identified. Using the acquisition method, biopsy showed a significantly higher engraftment rate when compared with that of surgical resection (100% [6/6] vs. 16.1% [9/56], P < 0.001). Specimens obtained from metastatic sites showed a significantly higher engraftment rate than did those from primary sites (100% [9/9] vs. 11.3% [6/53], P < 0.001). Three PDX models from HPV-positive tumors were established, as compared to 12 from HPV-negative (15.8% [3/19] and 27.9% [12/43] respectively, P = 0.311), suggesting that HPV positivity tends to show a low engraftment rate. Drug responses in PDX recapitulated the clinical responses of the matching patients with pan-HER inhibitors and pan-PI3K inhibitor.

Conclusions

Genetically and clinically annotated HNSCC PDXs could be useful preclinical tools for evaluating biomarkers, therapeutic targets, and new drug discovery.

Validity of patient-derived xenograft mouse models for lung cancer based on exome sequencing data

Patient-derived xenograft (PDX) mouse models are frequently used to test the drug efficacy in diverse types of cancer. They are known to recapitulate the patient characteristics faithfully, but a systematic survey with a large number of cases is yet missing in lung cancer. Here we report the comparison of genomic characters between mouse and patient tumor tissues in lung cancer based on exome sequencing data. We established PDX mouse models for 132 lung cancer patients and performed whole exome sequencing for trio samples of tumor-normal-xenograft tissues. Then we computed the somatic mutations and copy number variations, which were used to compare the PDX and patient tumor tissues. Genomic and histological conclusions for validity of PDX models agreed in most cases, but we observed eight (~7%) discordant cases. We further examined the changes in mutations and copy number alterations in PDX model production and passage processes, which highlighted the clonal evolution in PDX mouse models. Our study shows that the genomic characterization plays complementary roles to the histological examination in cancer studies utilizing PDX mouse models.

Bioinformatics and computational approaches for analyzing patient-derived disease models in cancer research

Patient-derived organoids (PDO) and patient-derived xenografts (PDX) continue to emerge as important preclinical platforms for investigations into the molecular landscape of cancer. While the advantages and disadvantage of these models have been described in detail, this review focuses in particular on the bioinformatics and state-of-the art techniques that accompany preclinical model development. We discuss the strength and limitations of currently used technologies, particularly 'omics profiling and bioinformatics analyses, in addressing the 'efficacy' of preclinical models, both for tumour characterization as well as their use in identifying potential therapeutics. We select pancreatic ductal adenocarcinoma (PDAC) as a case study to highlight the state of the art of the field, and address new avenues for improved bioinformatics characterization of preclinical models.

Mouse Tumor-Bearing Models as Preclinical Study Platforms for Oral Squamous Cell Carcinoma

Preclinical animal models of oral squamous cell carcinoma (OSCC) have been extensively studied in recent years. Investigating the pathogenesis and potential therapeutic strategies of OSCC is required to further progress in this field, and a suitable research animal model that reflects the intricacies of cancer biology is crucial. Of the animal models established for the study of cancers, mouse tumor-bearing models are among the most popular and widely deployed for their high fertility, low cost, and molecular and physiological similarity to humans, as well as the ease of rearing experimental mice. Currently, the different methods of establishing OSCC mouse models can be divided into three categories: chemical carcinogen-induced, transplanted and genetically engineered mouse models. Each of these methods has unique advantages and limitations, and the appropriate application of these techniques in OSCC research deserves our attention. Therefore, this review comprehensively investigates and summarizes the tumorigenesis mechanisms, characteristics, establishment methods, and current applications of OSCC mouse models in published papers. The objective of this review is to provide foundations and considerations for choosing suitable model establishment methods to study the relevant pathogenesis, early diagnosis, and clinical treatment of OSCC.

Systematic Review of Patient-Derived Xenograft Models for Preclinical Studies of Anti-Cancer Drugs in Solid Tumors

Patient-derived xenograft (PDX) models are used as powerful tools for understanding cancer biology in PDX clinical trials and co-clinical trials. In this systematic review, we focus on PDX clinical trials or co-clinical trials for drug development in solid tumors and summarize the utility of PDX models in the development of anti-cancer drugs, as well as the challenges involved in this approach, following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. Recently, the assessment of drug efficacy by PDX clinical and co-clinical trials has become an important method. PDX clinical trials can be used for the development of anti-cancer drugs before clinical trials, with their efficacy assessed by the modified response evaluation criteria in solid tumors (mRECIST). A few dozen cases of PDX models have completed enrollment, and the efficacy of the drugs is assessed by 1 × 1 × 1 or 3 × 1 × 1 approaches in the PDX clinical trials. Furthermore, co-clinical trials can be used for personalized care or precision medicine with the evaluation of a new drug or a novel combination. Several PDX models from patients in clinical trials have been used to assess the efficacy of individual drugs or drug combinations in co-clinical trials.

A controlled trial of HNSCC patient-derived xenografts reveals broad efficacy of PI3Kα inhibition in controlling tumor growth

Head and neck squamous cell carcinomas (HNSCCs) frequently harbor alterations in the PI3K/AKT/mTOR signaling axis, particularly in the PIK3CA gene. PI3K-targeted agents have therefore gained considerable preclinical and clinical interest as emerging therapies for HNSCC. Identification of predictive biomarkers of response would advance the clinical application of PI3K-targeted drugs for patients, in order to achieve maximal benefit. To date, studies of drug biomarkers have largely focused on screening cell lines, with much more limited in vivo testing, usually only as validation. This approach has rarely enabled accurate predictions of clinical efficacy. Recently, clinical trials of PDX models (PDX clinical trials) have been introduced as a preclinical approach to interrogate interpatient response heterogeneity. Already, PDX clinical trial responses have been demonstrated to correlate closely with patient outcomes. Here, using both an HNSCC specific, 28-cell line panel and a PDX clinical trial of 80 xenografts derived from 20 unique HNSCC tumors, we systematically examine patterns of response to PI3K inhibition in HNSCC. We find EGFR, AKT1 and CSMD1 copy number aberrations, but not PIK3CA mutations, to be associated with responsiveness to PI3K-targeted drugs. Further, we reveal PI3Kα inhibition to be almost globally tumoristatic in HNSCC xenografts regardless of PIK3CA mutational status, emphasizing its potential as a stabilizing neoadjuvant therapy for HNSCC patients.