Pulmonary Oncology

Principal Investigators

Overall goals

Lung cancer is the leading cause of cancer-related deaths worldwide. At UCL Respiratory, we aim to understand how precancerous changes in the lungs develop into cancer, use large data sets to find cancer earlier, and apply artificial intelligence to uncover new patterns in imaging and cancer biology. By leveraging lung cancer screening programs and advanced technologies like robotic bronchoscopy, alongside clinical trials, we strive to transform how lung cancer is diagnosed and treated.

Early detection of lung cancer

Professor Sam Janes led the SUMMIT study, the largest lung cancer screening initiative of its kind in the UK which aimed to detect lung cancer through CT scans and a new blood test.  

The SUMMIT study provided critical evidence that contributed to the development of the UKs lung cancer screening program the ‘Targeted Lung Health Check’ program.

His research also investigates potential biomarkers detected through blood or other biological samples (e.g. infrared spectroscopy of cheek swabs, and breath volatile organic compounds) that reveal early molecular changes of cancer development. By integrating biomarker testing into screening programmes, he aims to enhance early detection of lung cancer and improve patient outcomes.

Lung Cancer Biology and Translational Research

Professor Sam Janes' group has an extensive programme investigating lung cancer biology and novel therapeutic approaches. Approximately one-third of lung cancer cases originate from precancerous lesions in the airway lining.

Professor Janes leads groundbreaking research in airway stem cell biology and lung cancer to uncover the biological mechanisms that maintain airway health and identify the earliest cellular and molecular changes that lead to lung cancer.

He aims to pinpoint key genes that promote invasive behaviour in precancerous cells and to explore how these cells evade immune surveillance. He leads TACTICAL, a first-in-man clinical trial investigating the use of genetically modified stem cells to deliver anti-cancer therapies for advanced lung cancer.

Understand Lung Cancer Through 'Big Data'

Professor Neal Navani and the Lung Cancer Epidemiology and Data Science Laboratory at UCL Respiratory focuses on building risk prediction models for lung cancer and understanding and reducing inequalities in lung cancer outcomes. They derive and validate new algorithms to predict the risk of cancer in nodules using linkage of primary care and national registry datasets. In the long term, the group aims to iteratively analyse real world and clinical trial data with artificial intelligence to predict individual treatment effects and outcomes.

Molecular Imaging and Theranostics

Professor Ashley Groves has a long history of using nuclear medicine techniques to investigate lung cancer and contributes to multiple areas within the UCL Respiratory portfolio of research. He specialises in the development of imaging / histological correlate, identifying molecular targets to direct molecular radiotherapy, and often working in partnership with industry.

Harnessing Artificial Intelligence in Lung Cancer

Artificial intelligence is transforming lung cancer research by enhancing early detection, diagnosis, and treatment planning. Dr Joe Jacobs and other UCL researchers are developing AI-driven computer-aided diagnosis (CAD) systems that integrate imaging data with clinical information to predict malignancy in lung nodules and use artificial intelligence to accurately predict prognosis in patients with lung cancer.

Interventional Pulmonology

Professor Neal Navani and Dr Ricky Thakrar use interventional pulmonology techniques to improve outcomes for patients with lung cancer. Central to this is robotic bronchoscopy, a transformative technology that allows sampling of potential cancer tissue from hard-to-reach areas, which when combined with molecular analysis can better inform treatment.

In collaboration with UCL's engineering teams, we are developing innovative diagnostic tools, such as optical ultrasound, to further enhance the precision of robotic bronchoscopy. In addition, they investigate endoscopic treatments of lung cancer such as microwave ablation, cryoablation, and drug injection.

The interventional bronchoscopy team are committed to improving quality standards and conduct research into the barriers to effective learning. To support this, they have developed life-like synthetic lung phantoms to provide clinicians with realistic, hands-on practice to refine their bronchoscopic skills.

Airway Stem Cells and Tissue Regeneration

Maintaining the integrity of the epithelium lining the airways is essential for its multiple functions. Professor Sam Janes team has developed methods to expand human airway epithelial stem cells, and to differentiate these cells towards the mature airway cell types in three-dimensional (3D) organoids. Using these tools and molecular biology approaches he investigates the mechanisms that regulate cell fate decisions in the airway epithelium, and how airway stem cells maintain and repair lung epithelium. His group also investigates the effect of the microenvironment, including fibroblasts, immune cells and extracellular matrix, on airway epithelial stem cells.

Publications

1. Aslani S, Alluri P, Gudmundsson E ... Janes SM ... Jacob J (2024). Enhancing cancer prediction in challenging screen-detected incident lung nodules using time-series deep learning. Comput Med Imaging Graph. 2024 May 20;116: 102399. Epub ahead of print.
2. Cheng DO, Khaw CR, McCabe J ... Janes SM, Jacob J (2024). Predicting histopathological features of aggressiveness in lung cancer using CT radiomics: a systematic review. Clin Radiol. 2024 May 17: S0009-9260(24)00248-4.
3. Giddings R, Joseph A, Callender T, Janes SM ... Navani N (2024). Factors influencing clinician and patient interaction with machine learning-based risk prediction models: a systematic review. Lancet Digit Health. 2024 Feb;6(2): e131-e144.
4. Black GB, Janes SM, et al (2024). The Role of Smoking Status in Making Risk-Informed Diagnostic Decisions in the Lung Cancer Pathway: A Qualitative Study of Health Care Professionals and Patients. Med Decis Making. 2024 Feb;44(2): 152-162.
5. Callender T, Imrie F ... Navani N, van der Schaar M, Janes SM (2024). Assessing eligibility for lung cancer screening using parsimonious ensemble machine learning models: development and validation study. PLoS Med. 2023 Oct 3;20(10): e1004287.
6. Creamer AW, Horst C, Dickson JL ... Janes SM; SUMMIT Consortium (2024). Stage at Diagnosis Following Delay to Interval Scans for Indeterminate Nodules in Lung Cancer Screening: An Observational Study Examining the Outcomes of CHEST Expert Panel Recommendations. Chest. 2024 Apr;165(4): 1020-1024.
7. Hynds RE, Huebner A, Pearce DR, Hill MS ... Janes SM, et al (2024). Representation of genomic intratumor heterogeneity in multi-region non-small cell lung cancer patient-derived xenograft models. Nat Commun. 2024 May 31;15(1): 4653.
8. Succony L, Gómez-López S, Pennycuick A, Alhendi ASN ... Janes SM (2022). Lrig1 expression identifies airway basal cells with high proliferative capacity and restricts lung squamous cell carcinoma growth. Eur Respir J. 2022 Mar 31;59(3): 2000816.
9. Pennycuick A, Teixeira VH, AbdulJabbar K, Raza SEA ... Thakrar RM ... Janes SM (2020). Immune Surveillance in Clinical Regression of Preinvasive Squamous Cell Lung Cancer. Cancer Discov. 2020 Oct;10(10): 1489-1499.
10. Yoshida K, Gowers KHC, Lee-Six H ... Thakrar RM ... Janes SM, et al (2020). Tobacco smoking and somatic mutations in human bronchial epithelium. Nature. 2020 Feb; 578(7794): 266-272.

Funding and Grants

Samuel Janes CI
ASPIRE - Lung Health Check Bioresource
Funder: North Central Cancer Alliance
Award: £150,000

Neal Navani CI
OLIVE - Improving Early Detection of Lung Cancer in Never Smokers (2024)
Funder: NIHR
Award: £462,672

Samuel Janes CI
Mapping Longitudinal Squamous Cell (2023)
Funder: MRC
Award: £1,904,210

Samuel Janes CI
PREVALUNG EU (2023-2027)
Funder: EU
Award: £284,518

Samuel Janes Co-I
ACED Programme (2023)
Funder: Cancer Research UK
Award: £2,534,281

Samuel Janes Co-I
CRUK Lung Cancer Centre of Excellence (2024-2029)
Funder: Cancer Research UK
Award: £5,000,000

Neal Navani CI
NextGen MDT - Use of AI in Multidisciplinary Teams (2023)
Funder: Merck Sharp & Dohme
Award: £105,000

Neal Navani Co-I
Lung Cancer Data Quality Platform (Australia) (2023)
Funder: Cancer Australia
Award: £311,359

Neal Navani CI
Lung-ORACLE - Predicting Lung Cancer Outcomes Using AI (2022)
Funder: NIHR
Award: £454,292

Neal Navani Co-I
Lung-OPTIMA - Harmonising EU Cancer Data (2022)
Funder: EU-Horizon
Award: £117,591

Neal Navani Co-I
Lung-IMPACT - Detecting Lung Cancer in CXRs with AI (2022)
Funder: SBRI Healthcare / NHS Cancer Programme
Award: £3,200,000

Sam Janes and Ricky Thakrar CO-I
DOLCE – Detecting lung cancer using AI
Funder: NHSE

Sam Janes CI
ELIMINATE (2021)
Funder: Cancer Research UK
Award: £1,900,000

Neal Navani CI
REACT- Real-Time Cancer Analytics (2021)
Funder: Cancer Research UK
Award: £199,622

Neal Navani CI
National Lung Cancer Audit (2021)
Funder: Health Quality Improvement Partnership (NHSE)
Award: £975,000

Neal Navani Co-I
NIMBLE - Nodule Biomarker Discovery for Lung Cancer Diagnosis (2021)
Funder: Cancer Research UK
Award: £229,000

Neal Navani and Ricky Thakrar Co-I
Endobronchial Imaging with Optical Ultrasound (OPUS) (2023)
Funder: EPSRC (UKRI)
Award: £908,828

Neal Navani CI
PRECISE - Risk Prediction of Lung Nodules (2020)
Funder: MRC Clinical Academic Research Partnership
Award: £298,940

Neal Navani Co-I
ICON - Inequalities in Cancer (2019)
Funder: Cancer Research UK Population Research Committee
Award: £1,500,000

Sam Janes CI
EARL Trial - Electrocautery for treatment of preinvasive lung cancer (2018)
Funder: Cancer Research UK
Award: £1,200,000

Neal Navani Co-I
Streamline Trial - MRI for Lung Cancer Staging (2016)
Funder: NIHR HTA
Award: £1,300,000

Neal Navani CI
LungBOOST - EBUS for Lung Cancer Diagnosis and Staging (2008)
Funder: MRC Clinical Research Training Fellowship
Award: £224,000

Facilities and Techniques

• Lung cancer screening, including the SUMMIT (13,000 participants) with imaging, clinical, and molecular data, and the application of artificial intelligence (AI). 
• ALPINE is a comprehensive biomarker study in patients undergoing lung cancer screening. 
• Lung tissue pipeline with primary cell cultures, human tissue slice models and lung organoids
• Bioinformatics and computational expertise
• Artificial Intelligence and convolutional neural networks in imaging to improve early lung cancer detection. 
• Advanced bronchoscopic techniques including robotic bronchoscopy for precision diagnostics and tissue acquisition, allowing minimally invasive sampling of hard-to-reach lung areas, supporting multiplatform studies in early lung cancer and respiratory disease. 
• Cancer cell genomics
• In vitro and in vivo lung cancer models, techniques for cell genetic manipulation, cancer immunology, molecular mechanisms of tissue repair.