The International Association for the Study of Lung Cancer (IASLC) Molecular Database Project: Objectives, Challenges and Opportunities

With an estimated 2.2 million worldwide cases and 1.9 million deaths in 2017, lung cancer is the leading cause of cancer mortality in most countries.¹ Aggregate 5-year survival of lung cancer patients, as low as 4% in Low/Middle Income Countries, was estimated at 21% in the US in 2020.^1,2 There is great opportunity, with the emergence of molecular biomarkers of disease behavior, to improve treatment and survival. Biomarker testing, the portal to personalized treatment of lung cancer, has splintered a once seemingly monolithic disease into fragments of genomic and proteomic disease subsets with widely different, but generally improving, treatment and survival expectations.^3-5 Rapid evolution in knowledge of lung molecular carcinogenesis and biomarkers promises to enhance our strictly anatomy-based structural classification of the likely severity of disease (stage).

Scope and limitations of current prognostication nomenclature.

Staging serves three main purposes-communication, prognostication and direction of treatment.⁶ The Tumor (T), Node (N), and Metastasis (M) system is a strictly anatomy-based communication of the extent of cancer and, by inference, its likely impact on quality of life and death (prognosis), which then informs the choice of treatment modalities. Since its introduction between 1966 and 1968, the TNM staging system has facilitated communication about lung cancer across time and space, bridging geographic, linguistic, healthcare infrastructural, socio-economic and cultural differences. The system has gone through seven revisions, each designed to improve its utility in identifying anatomic clusters of patients with similar prognoses, and, indirectly, improve its practical utility in guiding treatment.

Role of the International Association for the Study of Lung Cancer (IASLC).

The IASLC provided the evidence that informed the 7^th and 8^th editions of the lung cancer staging system. Under the guidance of the Staging and Prognostic Factors Committee, a team of analysts at Cancer Research And Biostatistics (CRAB) rigorously analyzed granular patient-level data provided by multiple worldwide partners.⁷ For the 9^th edition of the TNM staging system, CRAB is collecting data on lung cancers diagnosed from January 1, 2011 to December 31, 2019, with follow up through December 31, 2021. Current plans are to publish the new proposed staging criteria in 2024, for international adoption in 2025.⁸

Because prognosis varies with molecular features as widely as with anatomic features, and staging details and therapies may differ for different molecular subsets of tumors, the SPFC has made a parallel call for molecular data with which to supplement the analysis of TNM-associated survival differences. Although the present manuscript describes the efforts directed towards lung cancer, similar efforts will be carried out for other thoracic malignancies- esophageal cancer, mesothelioma, and thymoma. Biologic heterogeneity and highly effective targeted therapies are blurring the lines of demarcation between NSCLC patients of different TNM stage. For example, whereas the aggregate 5 year survival of patients with stage IV lung cancer in the US was estimated at approximately 5% in 2020,³ patients with activating mutations of the Epidermal Growth Factor Receptor (EGFR) treated with the first generation of tyrosine kinase inhibitors (TKIs) at a single US institution between 2002 and 2009 had aggregate 5-year survival of 15%, similar to the aggregate 5-year survival of the monolithic NSCLC patients with clinical stage IIIA.⁹ Very long survival time has also been reported with first generation EGFR TKIs in some patients with stage IV NSCLC with a median survival extending beyond 11 years;¹⁰ patients with stage IV Anaplastic Lymphoma Kinase (ALK)-mutated NSCLC treated with Alectinib had a 5-year overall survival rate of 62.5%, similar to the expected survival rate of recipients of curative-intent surgery for stage I NSCLC.¹¹

In the ADAURA trial, adjuvant Osimertinib therapy for Union for International Cancer Control/American Joint Committee on Cancer 8^th edition pathologic stage IIA-IIIB NSCLC with L858R or deletion of exon 19 mutations of EGFR was associated with a hazard ratio for disease recurrence or death at 24 months of 0.2 (95% confidence interval ranging from 0.14 to 0.3).¹² Biomarker-delineated subsets of lung cancer may not only be predictive of sensitivity to specific types of treatment, they may possess intrinsic biologic differences that impact on prognosis even in early stage patients who undergo curative-intent surgical resection without adjuvant therapies.^13,14 The prognostic and predictive value of targetable gene mutations and co-mutations across the spectrum of NSCLC stage needs to be clarified in large, global datasets with sufficient statistical power.

Alternate existing databases.

Existing lung cancer molecular databases include: the Lung Cancer Mutation Consortium, a group of 14 National Cancer Institute-Designated Comprehensive Cancer Centers which tested 1007 patients with stage IV adenocarcinoma for one to 10 oncogenic driver mutations;¹⁵ The Cancer Genome Atlas, which includes multi-omics data on slightly more than 1,000, mostly resected early-stage NSCLC with limited treatment and follow up data;¹⁶ Catalogue Of Somatic Mutations In Cancer, which includes published cancer cases with mutation and gene copy number alterations;¹⁷ and the American Association for Cancer Research’s Genomics Evidence Neoplasia Information Exchange project, which has more than 200,000 profiled samples (from 18 major cancer centers including 13 from the US and approximately 14,000, mostly advanced lung adenocarcinoma patients), focuses on cataloguing mutations, and has limited clinical and pathological information.¹⁸ Indeed, these datasets all have limited clinical and pathological information.

Unique position of the IASLC Staging and Prognostic Factors Committee to tackle this project.

Given the diversity in prevalence of genomic aberrations such as EGFR mutations, and the relative rarity of others, there is great opportunity to leverage IASLC’s global reach to construct a robust, detailed, and rigorously curated database with which to study the molecular diversity of lung cancer across geographic, cultural, racial and ethnic boundaries; and to better understand how the molecular profile of lung cancer intersects with patterns of care delivery and outcomes.^19,20 The opportunity is especially great with rarer molecular subtypes, which cannot be sufficiently addressed through local or even national databases, and early stage, potentially curable lung cancer, about which there is insufficient information.^13,14 The CRAB data management and analysis infrastructure creates economies of scale that make this ambitious project feasible.

Where we are:

Lung cancer is a disease of genomic aberration. As of December 2020, nine genomic/protein markers could be used to select US Food and Drug Administration-approved treatment for stage IV lung cancer (EGFR, ALK, BRAF^V600E, ROS1, NTRK, MET exon 14 skipping, and RET mutations; PDL1 tumor proportion score >50%; and micro-satellite instability high or mis-match repair deficient tumors).⁵ Two other biomarkers- mutations of ERBB2 and KRAS received ‘breakthrough therapy designation’ for fast-tracked clinical development. This trend will only increase with time along with the list of prognostic and predictive markers.

Where we want to go:

The molecular profile project provides timely opportunity to improve on the status quo in lung cancer. Although the initial effort has focused on lung cancer, in the future we will expand the project to include mesothelioma and thymic tumors. Examples exist from other cancers, such as breast cancer and hematopoietic malignancies, in which the use of genomic and proteomic markers has long since been embedded in routine prognostication and pathways of treatment in ways that significantly augment the clinical utility of traditional classification systems, sometimes blurring the lines between hither-to anatomically distinct stage subsets.

Objectives of the molecular database project include:

1. Provide a global platform for a deeper, broader understanding of the value of molecular testing and targeted therapy for prognostication, prediction and treatment selection across the full spectrum of TNM stage.

2. Evaluate novel single or multiple prognostic markers that could add biological information regarding the outcome of patients in the different TNM stages. These novel prognostic factors would add to the current clinical gold-standard criteria and would be formally considered using criteria developed by the Prognostic Factors Sub-committee, and the Minimal Standards Working Group.

3. Create evidence in a set of highly characterized lung cancers with complete clinical, pathologic and staging information to support the role of biomarkers in lung cancer diagnosis, prognosis and treatment selection, across the stage spectrum.

4. Create evidence to support advocacy for routine genomic testing where appropriate.¹²

5. Define important research questions that might be the focus of observational studies, pragmatic trials and clinical trials of existing and emerging biomarkers and therapeutics.

6. Invite applications for projects to analyze the molecular database.

Challenges:

The primary challenge is to secure a sufficiently large, diverse and globally representative dataset, across the full spectrum of TNM stage (not solely advanced stage disease), to enable robust analysis and meaningful discovery. Differences in biomarker assays, testing platforms, test performance characteristics, variation in clinical use of biomarker testing, selection biases in who gets tested and why, the complexity and rapid evolution of the tests and interpretation of results, all represent significant challenges. These challenges are multiplied by national and regional differences in clinical practice and resources.^19,20 However, these challenges are also a strength – the data will reflect real world practices and varying implementation across the globe, and will not derive solely from elite academic institutions. As anatomic staging has had to evolve with improved surgical and staging technologies, so must this effort.

Unrelated secular changes further confound outcomes analyses- not only are molecular tests changing over time, with new genetic/molecular metrics being developed, but general survivability is improving also. Most of this can be investigated with subgroup analyses or validation in an external dataset. Both approaches require large, robust datasets. Genetic traits with smaller effect sizes will require a larger sample size for power to detect associated changes. Because a null finding could either be due to true lack of signal, or lack of statistical power, analyses will have to prioritize genetic traits with adequate sample size for analysis. Finally, many genetic traits are relatively rare, so a large sample size is needed to capture enough mutation-positive patients for meaningful analysis.

Opportunities.

This project will accelerate our understanding of lung cancer biology, clinical care and care delivery on a global scale. It will improve our understanding of the prognosis and optimal treatment of lung cancer across time and space, a function currently served solely by the TNM staging system.

Logistic matters:

the Molecular Sub-Committee is actively soliciting high-quality data from the global community of researchers and clinicians. We seek patient demographic and clinical information, clinical and pathologic TNM details, and biomarker details from any validated assay or platform. Patients with newly diagnosed lung cancer, of any histologic type, staged by the 8^th edition TNM, irrespective of stage or treatment, are eligible. Ideally, data should be submitted via CRAB’s Electronic Data Capture portal. Curators of large datasets can directly discuss alternative data submission approaches with CRAB. Contributors will be appropriately acknowledged in all publications arising from this dataset. The IASLC will financially support large volume data contributors on a case-by-case basis depending on geographic priority, the size and quality of data contribution.

Individuals and groups interested in contributing data to the IASLC Staging Project should visit the IASLC website, fill in their application and send it online. Application forms are available at www.iaslc.org > Research & Education > Research Committees & Projects > Staging and Prognostic Factors Committee > Submit Data for the 9^th Edition. The ‘Protocol Document’, a Tool Kit, and an ‘Application for Funding’ to defray the cost of data submission, template Data Use Agreements and Frequently Asked Questions about the logistics of participation can also be found there.

Appendix

Members of the Molecular Sub-committee (in alphabetical order) and their institutions:

Luiz H. Araujo, MD, PhD, Brazilian National Cancer Institute, Rio de Janeiro – Brazil; Frank Detterbeck, MD, FACS, FCCP, Department of Surgery, Yale University, New Haven, CT, USA; Oliver Gautschi, MD, University of Berne and Cantonal Hospital of Lucerne, Switzerland; Keith Kerr, MD, FRCPath, Department of Pathology, Aberdeen University School of Medicine, UK.; Peter J. Kneuertz, MD, Division of Thoracic Surgery, Department of Surgery, The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA; Philip Mack, PhD, Center for Thoracic Oncology, Tisch Cancer Institute, Icahn School of Medicine, Mount Sinai Health System, New York, NY, USA; Jose Maria Matilla, MD, PhD, Department of Thoracic Surgery, Hospital Clinico Universitario Valladolid, University of Valladolid, Valladolid (Spain); Andrew G Nicholson, DM, Department of Histopathology, Royal Brompton and Harefield Hospitals, London and National Heart and Lung Institute, Imperial College, London, UK; Harvey Pass, MD, Department of Surgery, New York University, New York, NY, USA; Carolyn J. Presley, MD, Division of Medical Oncology, Department of Internal Medicine, The Ohio State University Comprehensive Cancer Center. Columbus, OH, USA; Kenichi Suda, MD, PhD, Division of Thoracic Surgery, Department of Surgery, Kindai University Faculty of Medicine, Osaka, Japan; Ignacio Wistuba, MD, Department of Translational Molecular Pathology, MD Anderson Cancer Center, Houston, TX, USA; Dawei Yang, MD, Department of pulmonary medicine, Zhongshan Hospital, Fudan University, Shanghai, China; Yasushi Yatabe, MD, PhD, Department of Diagnostic Pathology, National Cancer Center, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045 Japan