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

Cancers ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3743
Author(s):  
Tet Woo Lee ◽  
Amy Lai ◽  
Julia K. Harms ◽  
Dean C. Singleton ◽  
Benjamin D. Dickson ◽  
...  
Keyword(s):  
Head And Neck ◽  
Precision Medicine ◽  
Patient Survival ◽  
Predictive Biomarkers ◽  
Tumour Microenvironment ◽  
Response To Therapy ◽  
Preclinical Models ◽  
Therapeutic Success ◽  
Patient Derived Xenograft ◽  
Individualise Therapy

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.

scholarly journals Explainable Transformer-Based Neural Network forthe Prediction of Survival Outcomes in Non-SmallCell Lung Cancer (NSCLC)

2021 ◽  
Author(s):  
Gustavo Arango ◽  
Elly Kipkogei ◽  
Etai Jacob ◽  
Ioannis Kagiampakis ◽  
Arijit Patra
Keyword(s):  
Immune System ◽  
Precision Medicine ◽  
Cancer Patients ◽  
Patient Survival ◽  
Response To Therapy ◽  
Survival Models ◽  
Attractive Alternative ◽  
Survival Prediction ◽  
Molecular Features ◽  
Clinical Measurements

In this paper, we introduce the Clinical Transformer - a recasting of the widely used transformer architecture as a method for precision medicine to model relations between molecular and clinical measurements, and the survival of cancer patients. Although the emergence of immunotherapy offers a new hope for cancer patients with dramatic and durable responses having been reported, only a subset of patients demonstrate benefit. Such treatments do not directly target the tumor but recruit the patient immune system to fight the disease. Therefore, the response to therapy is more complicated to understand as it is affected by the patients physical condition, immune system fitness and the tumor. As in text, where the semantics of a word is dependent on the context of the sentence it belongs to, in immuno-therapy a biomarker may have limited meaning if measured independent of other clinical or molecular features. Hence, we hypothesize that the transformer-inspired model may potentially enable effective modelling of the semantics of different biomarkers with respect to patient survival time. Herein, we demonstrate that this approach can offer an attractive alternative to the survival models utilized incurrent practices as follows: (1) We formulate an embedding strategy applied to molecular and clinical data obtained from the patients. (2) We propose a customized objective function to predict patient survival. (3) We show the applicability of our proposed method to bioinformatics and precision medicine. Applying the clinical transformer to several immuno-oncology clinical studies, we demonstrate how the clinical transformer outperforms other linear and non-linear methods used in current practice for survival prediction. We also show that when initializing the weights of a domain-specific transformer by the weights of a cross-domain transformer, we further improve the predictions. Lastly, we show how the attention mechanism successfully captures some of the known biology behind these therapies

scholarly journals Leveraging Genomics for Head and Neck Cancer Treatment

2018 ◽  
Vol 97 (6) ◽  
pp. 603-613 ◽  
Author(s):  
J.D. Kemmer ◽  
D.E. Johnson ◽  
J.R. Grandis
Keyword(s):  
Head And Neck ◽  
Precision Medicine ◽  
Predictive Biomarkers ◽  
Molecular Targeting ◽  
Data Sets ◽  
Genetic Characteristics ◽  
Multiple Data ◽  
Genomic Landscape ◽  
Multiple Data Sets ◽  
Molecular Targeting Agents

The genomic landscape of head and neck squamous cell carcinoma (HNSCC) has been recently elucidated. Key epigenetic and genetic characteristics of this cancer have been reported and substantiated in multiple data sets, including those distinctive to the growing subset of human papilloma virus (HPV)–associated tumors. This increased understanding of the molecular underpinnings of HNSCC has not resulted in new approaches to treatment. Three Food and Drug Administration–approved molecular targeting agents are currently available to treat recurrent/metastatic disease, but these have exhibited efficacy only in subsets of HNSCC patients, and thus surgery, chemotherapy, and/or radiation remain as standard approaches. The lack of predictive biomarkers to any therapy represents an obstacle to achieving the promise of precision medicine. This review aims to familiarize the reader with current insights into the HNSCC genomic landscape, discuss the currently approved and promising molecular targeting agents under exploration in laboratories and clinics, and consider precision medicine approaches to HNSCC.

scholarly journals Survival-Associated Metabolic Genes in Human Papillomavirus-Positive Head and Neck Cancers

Cancers ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 253 ◽  
Author(s):  
Martin A. Prusinkiewicz ◽  
Steven F. Gameiro ◽  
Farhad Ghasemi ◽  
Mackenzie J. Dodge ◽  
Peter Y. F. Zeng ◽  
...  
Keyword(s):  
Human Papillomavirus ◽  
Head And Neck ◽  
Patient Survival ◽  
Tricarboxylic Acid Cycle ◽  
Predictive Biomarkers ◽  
Head And Neck Cancers ◽  
The Cancer Genome Atlas ◽  
Metabolic Genes ◽  
Hpv Status ◽  
The Impact

Human papillomavirus (HPV) causes an increasing number of head and neck squamous cell carcinomas (HNSCCs). Altered metabolism contributes to patient prognosis, but the impact of HPV status on HNSCC metabolism remains relatively uncharacterized. We hypothesize that metabolism-related gene expression differences unique to HPV-positive HNSCC influences patient survival. The Cancer Genome Atlas RNA-seq data from primary HNSCC patient samples were categorized as 73 HPV-positive, 442 HPV-negative, and 43 normal-adjacent control tissues. We analyzed 229 metabolic genes and identified numerous differentially expressed genes between HPV-positive and negative HNSCC patients. HPV-positive carcinomas exhibited lower expression levels of genes involved in glycolysis and higher levels of genes involved in the tricarboxylic acid cycle, oxidative phosphorylation, and β-oxidation than the HPV-negative carcinomas. Importantly, reduced expression of the metabolism-related genes SDHC, COX7A1, COX16, COX17, ELOVL6, GOT2, and SLC16A2 were correlated with improved patient survival only in the HPV-positive group. This work suggests that specific transcriptional alterations in metabolic genes may serve as predictive biomarkers of patient outcome and identifies potential targets for novel therapeutic intervention in HPV-positive head and neck cancers.

scholarly journals Single-Cell Spatial Proteomics Analyses of Head and Neck Squamous Cell Carcinoma Reveal Tumor Heterogeneity and Immune Architectures Associated with Clinical Outcome

2021 ◽  
Author(s):  
Katie E. Blise ◽  
Shamilene Sivagnanam ◽  
Grace L. Banik ◽  
Lisa M. Coussens ◽  
Jeremy Goecks
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Single Cell ◽  
Squamous Cell ◽  
Immune Cells ◽  
Spatial Organization ◽  
Patient Survival ◽  
Response To Therapy ◽  
Neck Squamous Cell Carcinoma

ABSTRACTRecent research has provided compelling evidence that the spatial organization of cells within the tumor-immune microenvironment (TiME) of solid tumors correlates with survival and response to therapy in numerous cancer types. Here, we report results of a quantitative single-cell spatial analysis of the TiME of primary and recurrent human head and neck squamous cell carcinoma (HNSCC) tumors, that builds upon our initial longitudinal study of these same HNSCCs that annotated immune complexity at near single cell resolution. Herein, we extended multiple spatial algorithms to quantify spatial landscapes of immune cells within TiMEs. Most notably, we report that spatial compartmentalization, rather than mixing, between neoplastic tumor cells and immune cells is associated with longer patient survival, as well as revealing mesenchymal spatial cellular neighborhoods and their association with improved patient outcomes. Results reported herein are concordant with studies in other tumor types, thus indicating that cellular heterogeneity within tumors trends with spatial TiME features, and are likely prognostic for patient survival.

scholarly journals Does the Microenvironment Hold the Hidden Key for Functional Precision Medicine in Pancreatic Cancer?

Cancers ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 2427
Author(s):  
John Kokkinos ◽  
Anya Jensen ◽  
George Sharbeen ◽  
Joshua A. McCarroll ◽  
David Goldstein ◽  
...  
Keyword(s):  
Precision Medicine ◽  
Ex Vivo ◽  
Performance Status ◽  
Treatment Options ◽  
Critical Role ◽  
Tumour Microenvironment ◽  
Tumour Cells ◽  
Ductal Adenocarcinoma ◽  
Preclinical Models ◽  
Culture Models

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers and no significant improvement in patient survival has been seen in the past three decades. Treatment options are limited and selection of chemotherapy in the clinic is usually based on the performance status of a patient rather than the biology of their disease. In recent years, research has attempted to unlock a personalised treatment strategy by identifying actionable molecular targets in tumour cells or using preclinical models to predict the effectiveness of chemotherapy. However, these approaches rely on the biology of PDAC tumour cells only and ignore the importance of the microenvironment and fibrotic stroma. In this review, we highlight the importance of the microenvironment in driving the chemoresistant nature of PDAC and the need for preclinical models to mimic the complex multi-cellular microenvironment of PDAC in the precision medicine pipeline. We discuss the potential for ex vivo whole-tissue culture models to inform precision medicine and their role in developing novel therapeutic strategies that hit both tumour and stromal compartments in PDAC. Thus, we highlight the critical role of the tumour microenvironment that needs to be addressed before a precision medicine program for PDAC can be implemented.

scholarly journals Use of nonsteroidal anti-inflammatory drugs predicts improved patient survival for PIK3CA-altered head and neck cancer

2019 ◽  
Vol 216 (2) ◽  
pp. 419-427 ◽  
Author(s):  
Matthew L. Hedberg ◽  
Noah D. Peyser ◽  
Julie E. Bauman ◽  
William E. Gooding ◽  
Hua Li ◽  
...  
Keyword(s):  
Head And Neck ◽  
Patient Survival ◽  
Pik3ca Mutation ◽  
Nsaid Therapy ◽  
Hazard Ratio ◽  
Preclinical Models ◽  
Pik3ca Mutations ◽  
Inflammatory Drugs ◽  
Anti Inflammatory ◽  
The Impact

PIK3CA is the most commonly altered oncogene in head and neck squamous cell carcinoma (HNSCC). We evaluated the impact of nonsteroidal anti-inflammatory drugs (NSAIDs) on survival in a PIK3CA-characterized cohort of 266 HNSCC patients and explored the mechanism in relevant preclinical models including patient-derived xenografts. Among subjects with PIK3CA mutations or amplification, regular NSAID use (≥6 mo) conferred markedly prolonged disease-specific survival (DSS; hazard ratio 0.23, P = 0.0032, 95% CI 0.09–0.62) and overall survival (OS; hazard ratio 0.31, P = 0.0043, 95% CI 0.14–0.69) compared with nonregular NSAID users. For PIK3CA-altered HNSCC, predicted 5-yr DSS was 72% for NSAID users and 25% for nonusers; predicted 5-yr OS was 78% for regular NSAID users and 45% for nonregular users. PIK3CA mutation predicted sensitivity to NSAIDs in preclinical models in association with increased systemic PGE2 production. These findings uncover a biologically plausible rationale to implement NSAID therapy in PIK3CA-altered HNSCC.

749 Spatial profiling of the tumour microenvironment in head and neck cancer to identify biomarkers of response to therapy

2020 ◽  
Vol 8 (Suppl 3) ◽  
pp. A798-A798
Author(s):  
Arutha Kulasinghe
Keyword(s):  
Head And Neck ◽  
Immune Cell ◽  
Checkpoint Inhibitors ◽  
Cell Types ◽  
Tumour Microenvironment ◽  
Response To Therapy ◽  
Spatial Profiling ◽  
University Of Technology ◽  
Immune Contexture

BackgroundImmune checkpoint inhibitors (ICI) have shown durable and long-term benefits in a subset of head and neck squamous cell carcinoma (HNSCC) patients. To identify patient-responders from non-responders, biomarkers are needed which are predictive of outcome to ICI therapy. Cues in the tumour microenvironment (TME) have been informative in understanding the tumour-immune contexture.MethodsIn this study, the NanoString GemoMx™ Digital Spatial Profiling (DSP) technology was used to determine the immune marker and compartment specific measurements in a cohort of HNSCC tumours from patients receiving ICI therapy.ResultsOur data revealed that markers involved with immune cell infiltration (CD8 T-cells) were not predictive of outcome to ICI therapy. Rather, a number of immune cell types (CD4, CD68, CD45, CD44, CD66b) were found to correlate with progressive disease.ConclusionsThis study, to our knowledge, represents the first spatial analysis of HNSCC tumours.Ethics ApprovalThe study was approved by the Queensland University of Technology Ethics Board.

scholarly journals Precision Therapy of Head and Neck Squamous Cell Carcinoma

2018 ◽  
Vol 97 (6) ◽  
pp. 614-621 ◽  
Author(s):  
P.J. Polverini ◽  
N.J. D’Silva ◽  
Y.L. Lei
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Precision Medicine ◽  
Squamous Cell ◽  
Response To Therapy ◽  
Neck Squamous Cell Carcinoma ◽  
Great Promise ◽  
Prevention And Treatment ◽  
Precision Therapy

Precision medicine is an approach to disease prevention and treatment that takes into account genetic variability and environmental and lifestyle influences that are unique to each patient. It facilitates stratification of patient populations that vary in their susceptibility to disease and response to therapy. Shared databases and the implementation of new technology systems designed to advance the integration of this information will enable health care providers to more accurately predict and customize prevention and treatment strategies for patients. Although precision medicine has had a limited impact in most areas of medicine, it has been shown to be an increasingly successful approach to cancer therapy. Despite early promising results targeting aberrant signaling pathways or inhibitors designed to block tumor-driven processes such as angiogenesis, limited success emphasizes the need to discover new biomarkers and treatment targets that are more reliable in predicting response to therapy and result in better health outcomes. Recent successes in the use of immunity-inducing antibodies have stimulated increased interest in the use of precision immunotherapy of head and neck squamous cell carcinoma. Using next-generation sequencing, the precise profiling of tumor-infiltrating lymphocytes has great promise to identify hypoimmunogenic cancer that would benefit from a rationally designed combinatorial approach. Continued interrogation of tumors will reveal new actionable targets with increasing therapeutic efficacy and fulfill the promise of precision therapy of head and neck cancer.

scholarly journals Towards Circulating-Tumor DNA-Based Precision Medicine

2019 ◽  
Vol 8 (9) ◽  
pp. 1365 ◽  
Author(s):  
Ai Hironaka-Mitsuhashi ◽  
Anna Sanchez Calle ◽  
Takahiro Ochiya ◽  
Shin Takayama ◽  
Akihiko Suto
Keyword(s):  
Decision Making ◽  
Precision Medicine ◽  
Clonal Evolution ◽  
Predictive Biomarkers ◽  
Circulating Tumor Dna ◽  
Response To Therapy ◽  
Molecular Characteristics ◽  
Cancer Management ◽  
Cancer Breast ◽  
Metastatic Setting

In the era of precision medicine, targeted therapies have been implemented for various diseases. Genomic information guides decision-making in cancer treatment. The improvements in next-generation sequencing and polymerase chain reaction have made it possible to access the genetic information using circulating-tumor DNAs (ctDNAs). Molecular characteristics of individual tumors can be obtained by analysis of ctDNAs, thus making them excellent tools to guide decision-making during treatment. In oncology, the use of ctDNAs in clinical practice is now gaining importance. Molecular analysis of ctDNAs has potential for multiple clinical applications, including early diagnosis, prognosis of disease, prognostic and/or predictive biomarkers, and monitoring response to therapy and clonal evolution. In this paper, we highlight the applications of ctDNAs in cancer management, especially in metastatic setting, and summarize recent studies about the use of ctDNAs as predictive biomarkers for the therapeutic adaptation/response in lung cancer, breast cancer, and colorectal cancer. These studies offer the evidence to use ctDNAs as a promising approach to solve unmet clinical needs.

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