The Integrative Analysis of Lung Cancer Etiology and Risk (INTEGRAL) program is an NCI-funded initiative with an objective to develop tools to optimize low-dose CT (LDCT) lung cancer screening. Here, we de-scribe the rationale and design for the Risk Biomarker and Nodule Malignancy projects within INTEGRAL. The overarching goal of these projects is to systematically investigate circulating protein markers to include on a panel for use (i) pre-LDCT, to identify people likely to benefit from screening, and (ii) post-LDCT, to differentiate benign versus malignant nodules. To identify informative proteins, the Risk Biomarker project measured 1161 proteins in a nested-case control study within 2 prospective cohorts (n = 252 lung cancer cases and 252 controls) and replicated associations for a subset of proteins in 4 cohorts (n = 479 cases and 479 controls). Eligible participants had a current or former history of smok-ing and cases were diagnosed up to 3 years following blood draw. The Nodule Malignancy project mea-sured 1078 proteins among participants with a heavy smoking history within four LDCT screening stud-ies (n = 425 cases diagnosed up to 5 years following blood draw, 430 benign-nodule controls, and 398 nodule-free controls).The INTEGRAL panel will enable absolute quantification of 21 proteins. We will evaluate its perfor-mance in the Risk Biomarker project using a case-cohort study including 14 cohorts (n = 1696 cases and 2926 subcohort representatives), and in the Nodule Malignancy project within five LDCT screening studies (n = 675 cases, 680 benign-nodule controls, and 648 nodule-free controls). Future progress to advance lung cancer early detection biomarkers will require carefully designed validation, translational, and comparative studies.

Mutations in the VAV1 guanine nucleotide exchange factor 1 have been recently found in peripheral T cell lymphoma and nonsmall-cell lung cancer (NSCLC). To understand their pathogenic potential, we generated a gene-edited mouse model that expresses a VAV1 mutant protein that recapitulates the signalling alterations present in the VAV1 mutant subclass most frequently found in tumours. We could not detect any overt tumourigenic process in those mice. However, the concurrent elimination of the Trp53 tumour suppressor gene in them drives T cell lymphomagenesis. This process represents an exacerbation of the normal functions that wild-type VAV1 plays in follicular helper T cells. We also found that, in combination with the Kras oncogene, the VAV1 mutant version favours progression of NSCLC. These data indicate that VAV1 mutations play critical, although highly cell-type-specific, roles in tumourigenesis. They also indicate that such functions are contingent on the mutational landscape of the tumours involved.

Myeloid-derived suppressor cells (MDSCs) play a major role in cancer progression. In this study, we investigated the mechanisms by which complement C5a increases the capacity of polymorphonuclear MDSCs (PMN-MDSCs) to promote tumor growth and metastatic spread. Stimulation of PMN-MDSCs with C5a favored the invasion of cancer cells via a process dependent on the formation of neutrophil extracellular traps (NETs). NETosis was dependent on the production of high mobility group box 1 (HMGB1) by cancer cells. Moreover, C5a induced the surface expression of the HMGB1 receptors TLR4 and RAGE in PMN-MDSCs. In a mouse lung metastasis model, inhibition of C5a, C5a receptor-1 (C5aR1) or NETosis reduced the number of circulating-tumor cells (CTCs) and the metastatic burden. In support of the translational relevance of these findings, C5a was able to stimulate migration and NETosis in PMN-MDSCs obtained from lung cancer patients. Furthermore, myeloperoxidase (MPO)-DNA complexes, as markers of NETosis, were elevated in lung cancer patients and significantly correlated with C5a levels. In conclusion, C5a induces the formation of NETs from PMN-MDSCs in the presence of cancer cells, which may facilitate cancer cell dissemination and metastasis.

Lung cancer remains the leading cause of cancer-related death worldwide. We identify DSTYK, a dual serine/threonine and tyrosine non-receptor protein kinase, as a novel actionable target altered in non-small cell lung cancer (NSCLC). We also show DSTYK's association with a lower overall survival (OS) and poorer progression-free survival (PFS) in multiple patient cohorts. Abrogation of DSTYK in lung cancer experimental systems prevents mTOR-dependent cytoprotective autophagy, impairs lysosomal biogenesis and maturation, and induces accumulation of autophagosomes. Moreover, DSTYK inhibition severely affects mitochondrial fitness. We demonstrate in vivo that inhibition of DSTYK sensitizes lung cancer cells to TNF-alpha-mediated CD8+-killing and immune-resistant lung tumors to anti-PD-1 treatment. Finally, in a series of lung cancer patients, DSTYK copy number gain predicts lack of response to the immunotherapy. In summary, we have uncovered DSTYK as new therapeutic target in lung cancer. Prioritization of this novel target for drug development and clinical testing may expand the percentage of NSCLC patients benefiting from immune-based treatments.

Background Most patients with advanced non-small-cell lung cancer (NSCLC) fail to derive significant benefit from programmed cell death protein-1 (PD-1) axis blockade, and new biomarkers of response are needed. In this study, we aimed to discover and validate spatially resolved protein markers associated with sensitivity to PD-1 axis inhibition in NSCLC. Methods We initially assessed a discovery cohort of 56 patients with NSCLC treated with PD-1 axis inhibitors at Yale Cancer Center. Using the GeoMx Digital Spatial Profiling (DSP) system, 71 proteins were measured in spatial context on each spot in a tissue microarray. We used the AQUA method of quantitative immunofluorescence (QIF) to orthogonally validate candidate biomarkers. For external independent validation, we assessed whole tissue sections derived from 128 patients with NSCLC treated with single-agent PD-1 axis inhibitors at the 12 de Octubre Hospital (Madrid) using DSP. We further analyzed two immunotherapy untreated cohorts to address prognostic significance (n=252 from Yale Cancer Center; n=124 from University Clinic of Navarra) using QIF and DSP, respectively. Results Using continuous log-scaled data, we identified CD44 expression in the tumor compartment (pan-cytokeratin (CK)+) as a novel predictor of prolonged progression-free survival (PFS) (multivariate HR=0.68, p=0.043) in the discovery set. We validated by QIF that tumor CD44 levels assessed as continuous QIF scores were associated with longer PFS (multivariate HR=0.31, p=0.022) and overall survival (multivariate HR=0.29, p=0.038). Using DSP in an independent immunotherapy treated cohort, we validated that CD44 levels in the tumor compartment, but not in the immune compartment (panCK-/CD45+), were associated with clinical benefit (OR=1.22, p=0.018) and extended PFS under PD-1 axis inhibition using the highest tertile cutpoint (multivariate HR=0.62, p=0.03). The effect of tumor cell CD44 in predicting PFS remained significant after correcting for programmed death-ligand 1 (PD-L1) Tumor Proportion Score (TPS) in both cohorts. High tumor cell CD44 was not prognostic in the absence of immunotherapy. Using DSP data, intratumoral regions with elevated tumor cell CD44 expression showed prominent (fold change>1.5, adjusted p<0.05) upregulation of PD-L1, TIM-3, ICOS, and CD40 in two independent cohorts. Conclusions This work highlights CD44 as a novel indicative biomarker of sensitivity to PD-1 axis blockade that might help to improve immunotherapy strategies for NSCLC.

There is a paucity of adequate mouse models and cell lines available to study lung squamous cell carcinoma (LUSC). We have generated and characterized two models of phenotypically different transplantable LUSC cell lines, i.e. UN-SCC679 and UN-SCC680, derived from A/J mice that had been chemically induced with N-nitroso-tris-chloroethylurea (NTCU). Furthermore, we genetically characterized and compared both LUSC cell lines by performing whole-exome and RNA sequencing. These experiments revealed similar genetic and transcriptomic patterns that may correspond to the classic LUSC human subtype. In addition, we compared the immune landscape generated by both tumor cells lines in vivo and assessed their response to immune checkpoint inhibition. The differences between the two cell lines are a good model for the remarkable heterogeneity of human squamous cell carcinoma. Study of the metastatic potential of these models revealed that both cell lines represent the organotropism of LUSC in humans, i.e. affinity to the brain, bones, liver and adrenal glands. In summary, we have generated valuable cell line tools for LUSC research, which recapitulates the complexity of the human disease.

Introduction: SCLC is an extremely aggressive subtype of lung cancer without approved targeted therapies. Here we identified YES1 as a novel targetable oncogene driving SCLC maintenance and metastasis.Methods: Association between YES1 levels and prognosis was evaluated in SCLC clinical samples. In vitro functional experiments for proliferation, apoptosis, cell cycle, and cytotoxicity were performed. Genetic and pharmacologic inhibition of YES1 was evaluated in vivo in cell-and patient -derived xenografts and metastasis. YES1 levels were eval-uated in mouse and patient plasma-derived exosomes.Results: Overexpression or gain/amplification of YES1 was identified in 31% and 26% of cases, respectively, across molecular subgroups, and was found as an independent predictor of poor prognosis. Genetic depletion of YES1 dramatically reduced cell proliferation, three-dimensional organoid formation, tumor growth, and distant metastasis, leading to extensive apoptosis and tumor regressions. Mechanistically, YES1-inhibited cells revealed alterations in the replisome and DNA repair processes, that conferred sensitivity to irradiation. Pharmacologic blockade with the novel YES1 inhibitor CH6953755 or dasatinib induced marked antitumor activity in organoid models and cell-and patient-derived xenografts. YES1 protein was detected in plasma exosomes from patients and mouse models, with levels matching those of tumors, suggesting that circulating YES1 could represent a biomarker for patient selection/ monitoring.Conclusions: Our results provide evidence that YES1 is a new druggable oncogenic target and biomarker to advance the clinical management of a subpopulation of patients with SCLC.

Locally advanced non-small cell lung cancer (NSCLC) is frequent at diagnosis and requires multimodal treatment approaches. Neoadjuvant chemotherapy (NACT) followed by surgery is the treatment of choice for operable locally advanced NSCLC (Stage IIIA). However, the majority of patients are NACT-resistant and show persistent lymph nodal metastases (LNmets) and an adverse outcome. Therefore, the identification of mechanisms and biomarkers of NACT resistance is paramount for ameliorating the prognosis of patients with Stage IIIA NSCLC. Here, we investigated the miRNome and transcriptome of chemo-naive LNmets collected from patients with Stage IIIA NSCLC (N = 64). We found that a microRNA signature accurately predicts NACT response. Mechanistically, we discovered a miR-455-5p/PD-L1 regulatory axis which drives chemotherapy resistance, hallmarks metastases with active IFN-gamma response pathway (an inducer of PD-L1 expression), and impacts T cells viability and relative abundances in tumor microenvironment (TME). Our data provide new biomarkers to predict NACT response and add molecular insights relevant for improving the management of patients with locally advanced NSCLC.

Lung cancer screening detects early-stage cancers, but also a large number of benign nodules. Molecular markers can help in the lung cancer screening process by refining inclusion criteria or guiding the management of indeterminate pulmonary nodules. In this study, we developed a diagnostic model based on the quantification in plasma of complement-derived fragment C4c, cytokeratin fragment 21-1 (CYFRA 21-1) and C-reactive protein (CRP). The model was first validated in two independent cohorts, and showed a good diagnostic performance across a range of lung tumor types, emphasizing its high specificity and positive predictive value. We next tested its utility in two clinically relevant contexts: assessment of lung cancer risk and nodule malignancy. The scores derived from the model were associated with a significantly higher risk of having lung cancer in asymptomatic individuals enrolled in a computed tomography (CT)-screening program (OR = 1.89; 95% CI = 1.20-2.97). Our model also served to discriminate between benign and malignant pulmonary nodules (AUC: 0.86; 95% CI = 0.80-0.92) with very good specificity (92%). Moreover, the model performed better in combination with clinical factors, and may be used to reclassify patients with intermediate-risk indeterminate pulmonary nodules into patients who require a more aggressive work-up. In conclusion, we propose a new diagnostic biomarker panel that may dictate which incidental or screening-detected pulmonary nodules require a more active work-up. (Translational Research 2021; 233:77-91)

Simple Summary The increasing number of data supporting use of a personalized approach in cancer treatment, is changing the path of patient's management. In the same time, the availability of technologies should allow patients to receive the best test for the specific individual condition. This is theoretically true, when a specific test is designed for the specific disease condition, while it is difficult to implement in the setting of agnostic therapies. Financial sources availability related to the non homogeneous health systems working in the different countries do not allow for an immediate implementation of the technologies and test commercially available. Future perspectives for targeted oncology include tumor-agnostic drugs, which target a given mutation and could be used in treating cancers from multiple organ types. Therefore, the present paper is aimed to both underline a how much important is this new view and also to sensitize the international bodies that supervise health policies at the decision-making level, with the aim of harmonizing cancer treatment pathways in at least all European countries. Rapid and continuing advances in biomarker testing are not being matched by uptake in health systems, and this is hampering both patient care and innovation. It also risks costing health systems the opportunity to make their services more efficient and, over time, more economical. The potential that genomics has brought to biomarker testing in diagnosis, prediction and research is being realised, pre-eminently in many cancers, but also in an ever-wider range of conditions-notably BRCA1/2 testing in ovarian, breast, pancreatic and prostate cancers. Nevertheless, the implementation of genetic testing in clinical routine setting is still challenging. Development is impeded by country-related heterogeneity, data deficiencies, and lack of policy alignment on standards, approval-and the role of real-world evidence in the process-and reimbursement. The acute nature of the problem is compellingly illustrated by the particular challenges facing the development and use of tumour agnostic therapies, where the gaps in preparedness for taking advantage of this innovative approach to cancer therapy are sharply exposed. Europe should already have in place a guarantee of universal access to a minimum suite of biomarker tests and should be planning for an optimum testing scenario with a wider range of biomarker tests integrated into a more sophisticated health system articulated around personalised medicine. Improving healthcare and winning advantages for Europe's industrial competitiveness and innovation require an appropriate policy framework-starting with an update to outdated recommendations. We show herein the main issues and proposals that emerged during the previous advisory boards organised by the European Alliance for Personalized Medicine which mainly focus on possible scenarios of harmonisation of both oncogenetic testing and management of cancer patients.