Somatic rearrangements causing oncogenic ectodomain deletions of FGFR1 in squamous cell lung cancer.

The discovery of frequent 8p11-p12 amplifications in squamous cell lung cancer (SQLC) has fueled hopes that FGFR1, located inside this amplicon, might be a therapeutic target. In a clinical trial, only 11% of patients with 8p11 amplification (detected by FISH) responded to FGFR kinase inhibitor treatment. To understand the mechanism of FGFR1 dependency, we performed deep genomic characterization of 52 SQLCs with 8p11-p12 amplification, including 10 tumors obtained from patients who had been treated with FGFR inhibitors. We discovered somatically altered variants of FGFR1 with deletion of exons 1-8 that resulted from intragenic tail-to-tail rearrangements. These ectodomain-deficient FGFR1 variants (ΔEC-FGFR1) were expressed in the affected tumors and were tumorigenic in both in vitro and in vivo models of lung cancer. Mechanistically, breakage-fusion-bridges were the source of 8p11-p12 amplification, resulting from frequent head-to-head and tail-to-tail rearrangements. Generally, tail-to-tail rearrangements within or in close proximity upstream of FGFR1 were associated with FGFR1 dependency. Thus, the genomic events shaping the architecture of the 8p11-p12 amplicon provide a mechanistic explanation for the emergence of FGFR1-driven SQLC. Specifically, we believe that FGFR1 ectodomain-deficient and FGFR1-centered amplifications caused by tail-to-tail rearrangements are a novel somatic genomic event that might be predictive of therapeutically relevant FGFR1 dependency.

A New Plasmacytoid Dendritic Cell-Based Vaccine in Combination with Anti-PD-1 Expands the Tumor-Specific CD8+ T Cells of Lung Cancer Patients.

The purpose of immune checkpoint inhibitor (ICI)-based therapies is to help the patient's immune system to combat tumors by restoring the immune response mediated by CD8+ cytotoxic T cells. Despite impressive clinical responses, most patients do not respond to ICIs. Therapeutic vaccines with autologous professional antigen-presenting cells, including dendritic cells, do not show yet significant clinical benefit. To improve these approaches, we have developed a new therapeutic vaccine based on an allogeneic plasmacytoid dendritic cell line (PDC*line), which efficiently activates the CD8+ T-cell response in the context of melanoma. The goal of the study is to demonstrate the potential of this platform to activate circulating tumor-specific CD8+ T cells in patients with lung cancer, specifically non-small-cell lung cancer (NSCLC). PDC*line cells loaded with peptides derived from tumor antigens are used to stimulate the peripheral blood mononuclear cells of NSCLC patients. Very interestingly, we demonstrate an efficient activation of specific T cells for at least two tumor antigens in 69% of patients irrespective of tumor antigen mRNA overexpression and NSCLC subtype. We also show, for the first time, that the antitumor CD8+ T-cell expansion is considerably improved by clinical-grade anti-PD-1 antibodies. Using PDC*line cells as an antigen presentation platform, we show that circulating antitumor CD8+ T cells from lung cancer patients can be activated, and we demonstrate the synergistic effect of anti-PD-1 on this expansion. These results are encouraging for the development of a PDC*line-based vaccine in NSCLC patients, especially in combination with ICIs.

Defining Morphologic Features of Invasion in Pulmonary Nonmucinous Adenocarcinoma With Lepidic Growth: A Proposal by the International Association for the Study of Lung Cancer Pathology Committee.

INTRODUCTION: Since the eight edition of the Union for International Cancer Control and American Joint Committee on Cancer TNM classification system, the primary tumor pT stage is determined on the basis of presence and size of the invasive components. The aim of this study was to identify histologic features in tumors with lepidic growth pattern which may be used to establish criteria for distinguishing invasive from noninvasive areas. METHODS: A Delphi approach was used with two rounds of blinded anonymized analysis of resected nonmucinous lung adenocarcinoma cases with presumed invasive and noninvasive components, followed by one round of reviewer de-anonymized and unblinded review of cases with known outcomes. A digital pathology platform was used for measuring total tumor size and invasive tumor size. RESULTS: The mean coefficient of variation for measuring total tumor size and tumor invasive size was 6.9% (range: 1.7%-22.3%) and 54% (range: 14.7%-155%), respectively, with substantial variations in interpretation of the size and location of invasion among pathologists. Following the presentation of the results and further discussion among members at large of the International Association for the Study of Lung Cancer Pathology Committee, extensive epithelial proliferation (EEP) in areas of collapsed lepidic growth pattern is recognized as a feature likely to be associated with invasive growth. The EEP is characterized by multilayered luminal epithelial cell growth, usually with high-grade cytologic features in several alveolar spaces. CONCLUSIONS: Collapsed alveoli and transition zones with EEP were identified by the Delphi process as morphologic features that were a source of interobserver variability. Definition criteria for collapse and EEP are proposed to improve reproducibility of invasion measurement.

The 2021 WHO Classification of Lung Tumors: Impact of Advances Since 2015.

The 2021 WHO Classification of Thoracic Tumours was published earlier this year, with classification of lung tumors being one of the chapters. The principles remain those of using morphology first, supported by immunohistochemistry, and then molecular techniques. In 2015, there was particular emphasis on using immunohistochemistry to make classification more accurate. In 2021, there is greater emphasis throughout the book on advances in molecular pathology across all tumor types. Major features within this edition are (1) broader emphasis on genetic testing than in the 2015 WHO Classification; (2) a section entirely dedicated to the classification of small diagnostic samples; (3) continued recommendation to document percentages of histologic patterns in invasive nonmucinous adenocarcinomas, with utilization of these features to apply a formal grading system, and using only invasive size for T-factor size determination in part lepidic nonmucinous lung adenocarcinomas as recommended by the eighth edition TNM classification; (4) recognition of spread through airspaces as a histologic feature with prognostic significance; (5) moving lymphoepithelial carcinoma to squamous cell carcinomas; (6) update on evolving concepts in lung neuroendocrine neoplasm classification; (7) recognition of bronchiolar adenoma/ciliated muconodular papillary tumor as a new entity within the adenoma subgroup; (8) recognition of thoracic SMARCA4-deficient undifferentiated tumor; and (9) inclusion of essential and desirable diagnostic criteria for each tumor.

The International Association for the Study of Lung Cancer Global Survey on Programmed Death-Ligand 1 Testing for NSCLC.

INTRODUCTION: Programmed death-ligand 1 (PD-L1) immunohistochemistry (IHC) is required to determine the eligibility for pembrolizumab monotherapy in advanced NSCLC worldwide and for several other indications depending on the country. Four assays have been approved/ Communauté Européene-In vitro Diagnostic (CV-IVD)-marked, but PD-L1 IHC seems diversely implemented across regions and laboratories with the application of laboratory-developed tests (LDTs). METHOD: To assess the practice of PD-L1 IHC and identify issues and disparities, the International Association for the Study of Lung Cancer Pathology Committee conducted a global survey for pathologists from January to May 2019, comprising multiple questions on preanalytical, analytical, and postanalytical conditions. RESULT: A total of 344 pathologists from 64 countries participated with 41% from Europe, 24% from North America, and 18% from Asia. Besides biopsies and resections, cellblocks were used by 75% of the participants and smears by 11%. The clone 22C3 was most often used (69%) followed by SP263 (51%). They were applied as an LDT by 40% and 30% of the users, respectively, and 76% of the participants developed at least one LDT. Half of the participants reported a turnaround time of less than or equal to 2 days, whereas 13% reported that of greater than or equal to 5 days. In addition, quality assurance (QA), formal training for scoring, and standardized reporting were not implemented by 18%, 16%, and 14% of the participants, respectively. CONCLUSIONS: Heterogeneity in PD-L1 testing is marked across regions and laboratories in terms of antibody clones, IHC assays, samples, turnaround times, and QA measures. The lack of QA, formal training, and standardized reporting stated by a considerable minority identifies a need for additional QA measures and training opportunities.

Prognostic and predictive effect of KRAS gene copy number and mutation status in early stage non-small cell lung cancer patients.

BACKGROUND: In the current analysis, we characterize the prognostic significance of KRAS mutations with concomitant copy number aberrations (CNA) in early stage non-small cell lung cancer (NSCLC), and evaluate the ability to predict survival benefit from adjuvant chemotherapy. METHODS: Clinical and genomic data from the LACE (Lung Adjuvant Cisplatin Evaluation)-Bio consortium was utilized. CNAs were categorized as Gain (CN ≥2) or Neutral (Neut)/Loss; KRAS status was defined as wild type (WT) or mutant (MUT). The following groups were compared in all patients and the adenocarcinoma subgroup, and were correlated to survival endpoints using a Cox proportional hazards model: WT + Neut/Loss (reference), WT + Gain, MUT + Gain and MUT + Neut/Loss. A treatment-by-variable interaction was added to evaluate predictive effect. RESULTS: Of the 946 (399 adenocarcinoma) NSCLC patients, 41 [30] had MUT + Gain, 145 [99] MUT + Neut/Loss, 125 [16] WT + Gain, and 635 [254] WT + Neut/Loss. A non-significant trend towards worse lung cancer-specific survival (LCSS; HR =1.34; 95% CI, 0.83-2.17, P=0.232), DFS (HR =1.34; 95% CI, 0.86-2.09, P=0.202) and OS (HR =1.59; 95% CI, 0.99-2.54, P=0.055) was seen in KRAS MUT + Gain patients relative to KRAS WT + Neut/Loss patients. A negative prognostic effect of KRAS MUT + Neut/Loss was observed for LCSS (HR =1.32; 95% CI, 1.01-1.71, P=0.038) relative to KRAS WT + Neut/Loss on univariable analysis, but to a lesser extent after adjusting for covariates (HR =1.28; 95% CI, 0.97-1.68, P=0.078). KRAS MUT + Gain was associated with a greater beneficial effect of chemotherapy on DFS compared to KRAS WT + Neut/Loss patients (rHR =0.33; 95% CI, 0.11-0.99, P=0.048), with a non-significant trend also seen for LCSS (rHR =0.41; 95% CI, 0.13-1.33, P=0.138) and OS (rHR =0.40; 95% CI, 0.13-1.26, P=0.116) in the adenocarcinoma subgroup. CONCLUSIONS: A small prognostic effect of KRAS mutation was identified for LCSS, and a trend towards worse LCSS, DFS and OS was noted for KRAS MUT + Gain. A potential predictive effect of concomitant KRAS mutation and copy number gain was observed for DFS in adenocarcinoma patients. These results could be driven by the small number of patients and require validation.

Small-cell lung cancer.

Small-cell lung cancer (SCLC) represents about 15% of all lung cancers and is marked by an exceptionally high proliferative rate, strong predilection for early metastasis and poor prognosis. SCLC is strongly associated with exposure to tobacco carcinogens. Most patients have metastatic disease at diagnosis, with only one-third having earlier-stage disease that is amenable to potentially curative multimodality therapy. Genomic profiling of SCLC reveals extensive chromosomal rearrangements and a high mutation burden, almost always including functional inactivation of the tumour suppressor genes TP53 and RB1. Analyses of both human SCLC and murine models have defined subtypes of disease based on the relative expression of dominant transcriptional regulators and have also revealed substantial intratumoural heterogeneity. Aspects of this heterogeneity have been implicated in tumour evolution, metastasis and acquired therapeutic resistance. Although clinical progress in SCLC treatment has been notoriously slow, a better understanding of the biology of disease has uncovered novel vulnerabilities that might be amenable to targeted therapeutic approaches. The recent introduction of immune checkpoint blockade into the treatment of patients with SCLC is offering new hope, with a small subset of patients deriving prolonged benefit. Strategies to direct targeted therapies to those patients who are most likely to respond and to extend the durable benefit of effective antitumour immunity to a greater fraction of patients are urgently needed and are now being actively explored.

The Promises and Challenges of Tumor Mutation Burden as an Immunotherapy Biomarker: A Perspective from the International Association for the Study of Lung Cancer Pathology Committee.

Immune checkpoint inhibitor (ICI) therapies have revolutionized the management of patients with NSCLC and have led to unprecedented improvements in response rates and survival in a subset of patients with this fatal disease. However, the available therapies work only for a minority of patients, are associated with substantial societal cost, and may lead to considerable immune-related adverse events. Therefore, patient selection must be optimized through the use of relevant biomarkers. Programmed death-ligand 1 protein expression by immunohistochemistry is widely used today for the selection of programmed cell death protein 1 inhibitor therapy in patients with NSCLC; however, this approach lacks robust sensitivity and specificity for predicting response. Tumor mutation burden (TMB), or the number of somatic mutations derived from next-generation sequencing techniques, has been widely explored as an alternative or complementary biomarker for response to ICIs. In theory, a higher TMB increases the probability of tumor neoantigen production and therefore, the likelihood of immune recognition and tumor cell killing. Although TMB alone is a simplistic surrogate of this complex interplay, it is a quantitative variable that can be relatively readily measured using currently available sequencing techniques. A large number of clinical trials and retrospective analyses, employing both tumor and blood-based sequencing tools, have evaluated the performance of TMB as a predictive biomarker, and in many cases reveal a correlation between high TMB and ICI response rates and progression-free survival. Many challenges remain before the implementation of TMB as a biomarker in clinical practice. These include the following: (1) identification of therapies whose response is best informed by TMB status; (2) robust definition of a predictive TMB cut point; (3) acceptable sequencing panel size and design; and (4) the need for robust technical and informatic rigor to generate precise and accurate TMB measurements across different laboratories. Finally, effective prediction of response to ICI therapy will likely require integration of TMB with a host of other potential biomarkers, including tumor genomic driver alterations, tumor-immune milieu, and other features of the host immune system. This perspective piece will review the current clinical evidence for TMB as a biomarker and address the technical sequencing considerations and ongoing challenges in the use of TMB in routine practice.

A Grading System for Invasive Pulmonary Adenocarcinoma: A Proposal From the International Association for the Study of Lung Cancer Pathology Committee.

INTRODUCTION: A grading system for pulmonary adenocarcinoma has not been established. The International Association for the Study of Lung Cancer pathology panel evaluated a set of histologic criteria associated with prognosis aimed at establishing a grading system for invasive pulmonary adenocarcinoma. METHODS: A multi-institutional study involving multiple cohorts of invasive pulmonary adenocarcinomas was conducted. A cohort of 284 stage I pulmonary adenocarcinomas was used as a training set to identify histologic features associated with patient outcomes (recurrence-free survival [RFS] and overall survival [OS]). Receiver operating characteristic curve analysis was used to select the best model, which was validated (n = 212) and tested (n = 300, including stage I-III) in independent cohorts. Reproducibility of the model was assessed using kappa statistics. RESULTS: The best model (area under the receiver operating characteristic curve [AUC] = 0.749 for RFS and 0.787 for OS) was composed of a combination of predominant plus high-grade histologic pattern with a cutoff of 20% for the latter. The model consists of the following: grade 1, lepidic predominant tumor; grade 2, acinar or papillary predominant tumor, both with no or less than 20% of high-grade patterns; and grade 3, any tumor with 20% or more of high-grade patterns (solid, micropapillary, or complex gland). Similar results were seen in the validation (AUC = 0.732 for RFS and 0.787 for OS) and test cohorts (AUC = 0.690 for RFS and 0.743 for OS), confirming the predictive value of the model. Interobserver reproducibility revealed good agreement (k = 0.617). CONCLUSIONS: A grading system based on the predominant and high-grade patterns is practical and prognostic for invasive pulmonary adenocarcinoma.

Needlestack: an ultra-sensitive variant caller for multi-sample next generation sequencing data.

The emergence of next-generation sequencing (NGS) has revolutionized the way of reaching a genome sequence, with the promise of potentially providing a comprehensive characterization of DNA variations. Nevertheless, detecting somatic mutations is still a difficult problem, in particular when trying to identify low abundance mutations, such as subclonal mutations, tumour-derived alterations in body fluids or somatic mutations from histological normal tissue. The main challenge is to precisely distinguish between sequencing artefacts and true mutations, particularly when the latter are so rare they reach similar abundance levels as artefacts. Here, we present needlestack, a highly sensitive variant caller, which directly learns from the data the level of systematic sequencing errors to accurately call mutations. Needlestack is based on the idea that the sequencing error rate can be dynamically estimated from analysing multiple samples together. We show that the sequencing error rate varies across alterations, illustrating the need to precisely estimate it. We evaluate the performance of needlestack for various types of variations, and we show that needlestack is robust among positions and outperforms existing state-of-the-art method for low abundance mutations. Needlestack, along with its source code is freely available on the GitHub platform: https://github.com/IARCbioinfo/needlestack.

PenDA, a rank-based method for personalized differential analysis: Application to lung cancer.

The hopes of precision medicine rely on our capacity to measure various high-throughput genomic information of a patient and to integrate them for personalized diagnosis and adapted treatment. Reaching these ambitious objectives will require the development of efficient tools for the detection of molecular defects at the individual level. Here, we propose a novel method, PenDA, to perform Personalized Differential Analysis at the scale of a single sample. PenDA is based on the local ordering of gene expressions within individual cases and infers the deregulation status of genes in a sample of interest compared to a reference dataset. Based on realistic simulations of RNA-seq data of tumors, we showed that PenDA outcompetes existing approaches with very high specificity and sensitivity and is robust to normalization effects. Applying the method to lung cancer cohorts, we observed that deregulated genes in tumors exhibit a cancer-type-specific commitment towards up- or down-regulation. Based on the individual information of deregulation given by PenDA, we were able to define two new molecular histologies for lung adenocarcinoma cancers strongly correlated to survival. In particular, we identified 37 biomarkers whose up-regulation lead to bad prognosis and that we validated on two independent cohorts. PenDA provides a robust, generic tool to extract personalized deregulation patterns that can then be used for the discovery of therapeutic targets and for personalized diagnosis. An open-access, user-friendly R package is available at https://github.com/bcm-uga/penda.

New Approaches to SCLC Therapy: From the Laboratory to the Clinic.

The outcomes of patients with SCLC have not yet been substantially impacted by the revolution in precision oncology, primarily owing to a paucity of genetic alterations in actionable driver oncogenes. Nevertheless, systemic therapies that include immunotherapy are beginning to show promise in the clinic. Although, these results are encouraging, many patients do not respond to, or rapidly recur after, current regimens, necessitating alternative or complementary therapeutic strategies. In this review, we discuss ongoing investigations into the pathobiology of this recalcitrant cancer and the therapeutic vulnerabilities that are exposed by the disease state. Included within this discussion, is a snapshot of the current biomarker and clinical trial landscapes for SCLC. Finally, we identify key knowledge gaps that should be addressed to advance the field in pursuit of reduced SCLC mortality. This review largely summarizes work presented at the Third Biennial International Association for the Study of Lung Cancer SCLC Meeting.

PD-L1 Testing for Lung Cancer in 2019: Perspective From the IASLC Pathology Committee.

The recent development of immune checkpoint inhibitors (ICIs) has led to promising advances in the treatment of patients with NSCLC and SCLC with advanced or metastatic disease. Most ICIs target programmed cell death protein 1 (PD-1) or programmed death ligand 1 (PD-L1) axis with the aim of restoring antitumor immunity. Multiple clinical trials for ICIs have evaluated a predictive value of PD-L1 protein expression in tumor cells and tumor-infiltrating immune cells (ICs) by immunohistochemistry (IHC), for which different assays with specific IHC platforms were applied. Of those, some PD-L1 IHC assays have been validated for the prescription of the corresponding agent for first- or second-line treatment. However, not all laboratories are equipped with the dedicated platforms, and many laboratories have set up in-house or laboratory-developed tests that are more affordable than the generally expensive clinical trial-validated assays. Although PD-L1 IHC test is now deployed in most pathology laboratories, its appropriate implementation and interpretation are critical as a predictive biomarker and can be challenging owing to the multiple antibody clones and platforms or assays available and given the typically small size of samples provided. Because many articles have been published since the issue of the IASLC Atlas of PD-L1 Immunohistochemistry Testing in Lung Cancer, this review by the IASLC Pathology Committee provides updates on the indications of ICIs for lung cancer in 2019 and discusses important considerations on preanalytical, analytical, and postanalytical aspects of PD-L1 IHC testing, including specimen type, validation of assays, external quality assurance, and training.

The IASLC Lung Cancer Staging Project: Analysis of Resection Margin Status and Proposals for Residual Tumor Descriptors for Non-Small Cell Lung Cancer.

OBJECTIVE: Our aim was to validate the prognostic relevance in NSCLC of potential residual tumor (R) descriptors, including the proposed International Association for the Study of Lung Cancer definition for uncertain resection, referred to as R(un). METHODS: A total of 14,712 patients undergoing resection with full R status and survival were analyzed. The following were also evaluated: whether fewer than three N2 stations were explored, lobe-specific nodal dissection, extracapsular extension, highest lymph node station status, carcinoma in situ at the bronchial resection margin, and pleural lavage cytologic examination result. Revised categories of R0, R(un), R1, and R2 were tested for survival impact. RESULTS: In all, 14,293 cases were R0, 263 were R1, and 156 were R2 (median survivals not reached, 33 months, and 29 months, respectively). R status correlated with T and N categories. A total of 9290 cases (63%) had three or more N2 stations explored and 6641 cases (45%) had lobe-specific nodal dissection, correlated with increasing pN2. Extracapsular extension was present in 62 of 364 cases with available data (17%). The highest station was positive in 942 cases (6.4%). The pleural lavage cytologic examination result was positive in 59 of 1705 cases (3.5%): 13 had carcinoma in situ at the bronchial resection margin. After reassignment because of inadequate nodal staging in 56% of cases, 6070 cases were R0, 8185 were R(un), 301 were R1, and 156 were R2. In node-positive cases, the median survival times were 70, 50, and 30 months for R0, R(un) (p < 0.0001), and R1 (p < 0.001), respectively, with no significant difference between R0 and R(un) in pN0 cases. CONCLUSIONS: R descriptors have prognostic relevance, with R(un) survival stratifying between R0 and R1. Therefore, a detailed evaluation of R factor is of particular importance in the design and analyses of clinical trials of adjuvant therapies.