Gender Difference in sidE eFfects of ImmuNotherapy: a possible clue to optimize cancEr tReatment (G-DEFINER): study protocol of an observational prospective multicenter study

BACKGROUND

Immune checkpoint inhibitors (ICIs) have significantly improved outcomes in various cancers. ICI treatment is associated with the incidence of immune-related adverse events (irAEs) which can affect any organ. Data on irAEs occurrence in relation to sex- differentiation and their association with gender-specific factors are limited.

AIMS

The primary objective of the G-DEFINER study is to compare the irAEs incidence in female and male patients who undergo ICI treatment. Secondary objectives are: to compare the irAEs incidence in pre- and postmenopausal female patients; to compare the irAEs incidence in female and male patients according to different clinical and gender-related factors (lifestyle, psychosocial, and behavioral factors). Exploratory objectives of the study are to compare and contrast hormonal, gene-expression, SNPs, cytokines, and gut microbiota profiles in relation to irAEs incidence in female and male patients.

METHODS AND RESULTS

The patients are recruited from Fondazione IRCCS Istituto Nazionale dei Tumori, Italy, St Vincent's University Hospital, Ireland, Oslo University Hospital, Norway, and Karolinska Insitutet/Karolinska University Hospital, Sweden. The inclusion of patients was delayed due to the Covid pandemic, leading to a total of 250 patients recruited versus a planned number of 400 patients. Clinical and translational data will be analyzed.

INTERPRETATION

The expected outcomes are to improve the management of cancer patients treated with ICIs, leading to more personalized clinical approaches that consider potential toxicity profiles. The real world nature of the trial makes it highly applicable for timely irAEs diagnosis.

Response to lorlatinib rechallenge in a case of ALK-rearranged metastatic NSCLC with a resistance mutation to second generation TKIs

INTRODUCTION

Several anaplastic lymphoma kinase (ALK) tyrosine kinase inhibitors (TKIs) have been developed for the treatment of echinoderm microtubule-associated protein-like 4 (EML4)-ALK-rearranged non-small cell lung cancer (NSCLC), with the newer generation agents brigatinib, alectinib and lorlatinib showing prolonged responses. With the increasing number of target therapies available, the optimal sequence is yet to be defined, as resistance profiles may evolve over time and in response to sequential ALK inhibitors. Therefore, ALK-targeted strategies may be personalized based upon the presence of specific ALK resistance mutations.

METHODS

Here, we report on the case of a patient who has been treated with a sequence of three ALK TKIs after receiving diagnosis of ALK-rearranged metastatic NSCLC in 2015 and gained further benefit upon lorlatinib rechallenge after the acquisition of the G1202R resistance mutation to second generation TKIs.

RESULTS AND CONCLUSION

In this case, the first ALK resistance mutation detected after progression on first line TKI, the I1171N, is a common resistance mutation after alectinib and confers sensitivity to brigatinib, that the patient received afterwards with a long-term disease stability. The second ALK resistance mutation detected after a chemotherapy interval, the G1202R, is the most common resistance mutation after second generation ALK TKIs and has been associated with sensitivity to third generation TKIs, such as lorlatinib. This case of a patient with EML4-ALK-rearranged NSCLC shows that sequential treatment with next-generation ALK TKIs, including rechallenge, can induce profound remissions, even in heavily pretreated patients, and that ALK-targeted strategies may be personalized by considering the presence of distinct ALK resistance mutations.

Demographic Analysis of Cancer Research Priorities and Treatment Correlations

Understanding the diversity in cancer research priorities and the correlations among different treatment modalities is essential to address the evolving landscape of oncology. This study, conducted in collaboration with the European Cancer Patient Coalition (ECPC) and Childhood Cancer International-Europe (CCI-E) as part of the "UNCAN.eu" initiative, analyzed data from a comprehensive survey to explore the complex interplay of demographics, time since cancer diagnosis, and types of treatments received. Demographic analysis revealed intriguing trends, highlighting the importance of tailoring cancer research efforts to specific age groups and genders. Individuals aged 45-69 exhibited highly aligned research priorities, emphasizing the need to address the unique concerns of middle-aged and older populations. In contrast, patients over 70 years demonstrated a divergence in research priorities, underscoring the importance of recognising the distinct needs of older individuals in cancer research. The analysis of correlations among different types of cancer treatments underscored the multidisciplinary approach to cancer care, with surgery, radiotherapy, chemotherapy, precision therapy, and biological therapies playing integral roles. These findings support the need for personalized and combined treatment strategies to achieve optimal outcomes. In conclusion, this study provides valuable insights into the complexity of cancer research priorities and treatment correlations in a European context. It emphasizes the importance of a multifaceted, patient-centred approach to cancer research and treatment, highlighting the need for ongoing support, adaptation, and collaboration to address the ever-changing landscape of oncology.

APOLLO 11 Project, Consortium in Advanced Lung Cancer Patients Treated With Innovative Therapies: Integration of Real-World Data and Translational Research

INTRODUCTION

Despite several therapeutic efforts, lung cancer remains a highly lethal disease. Novel therapeutic approaches encompass immune-checkpoint inhibitors, targeted therapeutics and antibody-drug conjugates, with different results. Several studies have been aimed at identifying biomarkers able to predict benefit from these therapies and create a prediction model of response, despite this there is a lack of information to help clinicians in the choice of therapy for lung cancer patients with advanced disease. This is primarily due to the complexity of lung cancer biology, where a single or few biomarkers are not sufficient to provide enough predictive capability to explain biologic differences; other reasons include the paucity of data collected by single studies performed in heterogeneous unmatched cohorts and the methodology of analysis. In fact, classical statistical methods are unable to analyze and integrate the magnitude of information from multiple biological and clinical sources (eg, genomics, transcriptomics, and radiomics).

METHODS AND OBJECTIVES

APOLLO11 is an Italian multicentre, observational study involving patients with a diagnosis of advanced lung cancer (NSCLC and SCLC) treated with innovative therapies. Retrospective and prospective collection of multiomic data, such as tissue- (eg, for genomic, transcriptomic analysis) and blood-based biologic material (eg, ctDNA, PBMC), in addition to clinical and radiological data (eg, for radiomic analysis) will be collected. The overall aim of the project is to build a consortium integrating different datasets and a virtual biobank from participating Italian lung cancer centers. To face with the large amount of data provided, AI and ML techniques will be applied will be applied to manage this large dataset in an effort to build an R-Model, integrating retrospective and prospective population-based data. The ultimate goal is to create a tool able to help physicians and patients to make treatment decisions.

CONCLUSION

APOLLO11 aims to propose a breakthrough approach in lung cancer research, replacing the old, monocentric viewpoint towards a multicomprehensive, multiomic, multicenter model. Multicenter cancer datasets incorporating common virtual biobank and new methodologic approaches including artificial intelligence, machine learning up to deep learning is the road to the future in oncology launched by this project.

Aligning Cancer Research Priorities in Europe with Recommendations for Conquering Cancer: A Comprehensive Analysis

Improvements in cancer care require a new degree of collaboration beyond the purely medical sphere, extending deeply into the world of other stakeholders-preeminently patients but also the other stakeholders in the hardware and software of care. Cancer remains a global health challenge, necessitating collaborative efforts to understand, prevent, and treat this complex disease. To achieve this goal, a comprehensive analysis was conducted, aligning the prioritization of cancer research measures in 13 European countries with 13 key recommendations for conquering cancer in the region. The study utilized a survey involving both patients and citizens, alongside data from IQVIA, a global healthcare data provider, to assess the availability and access to single-biomarker tests in multiple European countries. The results revealed a focused approach toward understanding, preventing, and treating cancer, with each country emphasizing specific research measures tailored to its strengths and healthcare objectives. This analysis highlights the intricate relationship between research priorities, access to biomarker tests, and financial support. Timely access to tests and increased availability positively influence research areas such as cancer prevention, early detection, ageing, and data utilization. The alignment of these country-specific measures with 13 recommendations for conquering cancer in Europe underscores the importance of tailored strategies for understanding, preventing, and treating cancer.

Tackling the implementation gap for the uptake of NGS and advanced molecular diagnostics into healthcare systems

Next-generation sequencing (NGS) and liquid biopsy (LB) showed positive results in the fight against different cancer types. This paper aims to assess the uptake of advanced molecular diagnostics/NGS for quick and efficient genetic profiles of tumour cells. For that purpose, the European Alliance for Personalised Medicine conducted a series of expert interviews to ascertain the current status across member states. One stakeholder meeting was additionally conducted to prioritize relevant factors by stakeholders. Seven common pillars were identified, and twenty-five measures were defined based on these pillars. Results showed that a multi-faceted approach is necessary for successful NGS implementation and that regional differences may be influenced by healthcare policies, resources, and infrastructure. It is important to consider different correlations when interpreting the results and to use them as a starting point for further discussion.

Artificial intelligence for predictive biomarker discovery in immuno-oncology: a systematic review

BACKGROUND

The widespread use of immune checkpoint inhibitors (ICIs) has revolutionised treatment of multiple cancer types. However, selecting patients who may benefit from ICI remains challenging. Artificial intelligence (AI) approaches allow exploitation of high-dimension oncological data in research and development of precision immuno-oncology.

MATERIALS AND METHODS

We conducted a systematic literature review of peer-reviewed original articles studying the ICI efficacy prediction in cancer patients across five data modalities: genomics (including genomics, transcriptomics, and epigenomics), radiomics, digital pathology (pathomics), and real-world and multimodality data.

RESULTS

A total of 90 studies were included in this systematic review, with 80% published in 2021-2022. Among them, 37 studies included genomic, 20 radiomic, 8 pathomic, 20 real-world, and 5 multimodal data. Standard machine learning (ML) methods were used in 72% of studies, deep learning (DL) methods in 22%, and both in 6%. The most frequently studied cancer type was non-small-cell lung cancer (36%), followed by melanoma (16%), while 25% included pan-cancer studies. No prospective study design incorporated AI-based methodologies from the outset; rather, all implemented AI as a post hoc analysis. Novel biomarkers for ICI in radiomics and pathomics were identified using AI approaches, and molecular biomarkers have expanded past genomics into transcriptomics and epigenomics. Finally, complex algorithms and new types of AI-based markers, such as meta-biomarkers, are emerging by integrating multimodal/multi-omics data.

CONCLUSION

AI-based methods have expanded the horizon for biomarker discovery, demonstrating the power of integrating multimodal data from existing datasets to discover new meta-biomarkers. While most of the included studies showed promise for AI-based prediction of benefit from immunotherapy, none provided high-level evidence for immediate practice change. A priori planned prospective trial designs are needed to cover all lifecycle steps of these software biomarkers, from development and validation to integration into clinical practice.

High bone tumor burden to identify advanced non-small cell lung cancer patients with survival benefit upon bone targeted agents and immune checkpoint inhibitors

BACKGROUND

Bone-targeted agents (BTA), such as denosumab (DN) and zoledronic acid (ZA), have historically reduced the risk of skeletal related events in cancer patients with bone metastases (BM), with no improvement in survival outcomes. In the immunotherapy era, BM have been associated with poor prognosis upon immune-checkpoint inhibitors (ICI). Currently, the impact of bone tumor burden on survival upon BTAs in advanced non-small cell lung cancer (aNSCLC) patients treated with ICI remains unknown.

METHODS

Data from ICI-treated aNSCLC patients with BM (4/2013-5/2022) in one institution were retrospectively collected. BTA-ICI concurrent treatment was defined as BTA administration at any time before or within 90 days from ICI start. High bone tumor burden (HBTB) was defined as ≥ 3 sites of BM. Median OS (mOS) was estimated with Kaplan-Meier. Aikaike's information criterion (AIC) was used to select the best model for data analysis adjusted for clinical variables.

RESULTS

Of 134 patients included, 51 (38 %) received BTA. At a mFU of 39.6 months (m), BTA-ICIs concurrent treatment did not significantly impact on mOS [8.3 m (95% CI 3.9-12.8) versus (vs) 6.8 m (95% CI 4.0-9.6) p = 0.36]; these results were confirmed after adjustment for clinical variables selected by AIC. A multivariate model showed a significant interaction between BTA use and HBTB or radiation therapy to BM. In subgroup analyses, only HBTB confirmed to be associated with significantly longer mOS [8.3 m (95% CI 2.4-14.2) vs 3.5 m (95% CI 2.9-4.1), p = 0.003] and mPFS [3.0 m (95% CI 1.6-4.4) vs 1.8 m (95% CI 1.6-2.0) p = 0.001] upon BTA-ICI concurrent treatment, with the most pronounced OS benefit observed for DN-ICI concurrent regimen [15.2 m (95% CI 0.1-30.7) vs 3.5 m (95% CI 2.9-4.1) p = 0.002].

CONCLUSIONS

In the immunotherapy era, HBTB can identify patients experiencing survival benefit with BTA, especially with DN-ICI combination. HBTB should be included as a stratification factor in the upcoming trials assessing BTA and ICI combinations in patients with aNSCLC and BM.

Association Between Lung Immune Prognostic Index and Durvalumab Consolidation Outcomes in Patients With Locally Advanced Non-Small-Cell Lung Cancer

INTRODUCTION

The LIPI, based on pretreatment derived neutrophils/[leukocytes-neutrophils] ratio (dNLR) and LDH, is associated with immune checkpoint inhibitors (ICI) outcomes in advanced non-small-cell lung cancer (NSCLC). We aimed to assess baseline LIPI correlation with durvalumab consolidation outcomes in the locally advanced setting.

MATERIAL AND METHODS

Multicentre retrospective study (330 patients) with stage III unresectable NSCLC treated with durvalumab after chemo-radiotherapy between April 2015 and December 2020; 65 patients treated with chemo-radiotherapy only. Baseline LIPI characterized 3 groups: good (dNLR≤3+LDH≤ULN), intermediate (dNLR>3/LDH>ULN) and poor (dNLR>3+LDH>ULN). Primary endpoint was overall survival (OS).

RESULTS

In the durvalumab cohort, median age was 67 years, 95% smokers, 98% with a performance status of 0-1; 60% had nonsquamous histology and 16% a PD-L1 expression <1%. Radiotherapy was delivered concurrently in 81%. LIPI was evaluable in 216 patients: 66% good, 31% intermediate, 3% poor. LIPI significantly correlated with median OS (median follow-up: 19 months): 18.1 months vs. 47.0 months vs. not reached in poor, intermediate and good LIPI groups, respectively (P = .03). A trend between objective response rate and LIPI groups was observed: 0% vs. 41% vs. 45%, respectively (P = .05). The pooled intermediate/poor LIPI group was associated with shorter OS (HR 1.97; P = .03) and higher risk of progressive disease (OR 2.68; P = .047). Survivals and response were not influenced in the control cohort.

CONCLUSION

Baseline LIPI correlated with outcomes in patients with locally advanced NSCLC treated with durvalumab consolidation, but not in those who only received chemo-radiotherapy, providing further evidence of its prognostic and potential predictive role of ICI benefit in NSCLC.

Exploring the Role of Immunotherapy-Based Treatments for Advanced Non-Small-Cell Lung Cancer With Novel Driver Alterations

BACKGROUND

Immunotherapy (IO) single agent or combined with chemotherapy (CT-IO) is the standard treatment for advanced non-small-cell lung cancer (aNSCLC) without driver alterations. IO efficacy in patients with novel driver alterations is not well reported.

MATERIALS AND METHODS

Data of aNSCLC patients treated with IO or CT-IO in any line from January 2016 to September 2022 were retrospectively collected. Patients harboring novel driver alterations (m-cohort), including MET exon 14 skipping, BRAF (V600E or atypical), RET rearrangements, HER2 point mutations/exon 20 insertions or uncommon EGFR mutations/EGFR exon 20 insertions, and wild type patients (wt-cohort) were eligible. Clinico-pathological data were extracted from Institutional databases and compared through chi square or Fisher's exact test. Survivals were estimated through Kaplan-Meier method and compared by log-rank test.

RESULTS

m-cohort and wt-cohort included 84 and 444 patients, respectively. Progression free survival (PFS) was 5.53 vs. 4.57 months (P= .846) and overall survival (OS) was 25.1 vs. 9.37 months, (P < .0001) for m-cohort compared to wt-cohort. Within the m-cohort, BRAF atypical mutations had the better outcomes (Overall Response Rate [ORR], PFS), targeted agents timing did not affect response to IO and CT-IO had better ORR and disease control rate (DCR) compared to IO single agent (P = .0160 and P = .0152). In the PD-L1≥50% group, first line IO single agent resulted in inferior ORR (P = .027) and PFS (P = .022) in m-cohort compared to wt-cohort.

CONCLUSION

IO based treatments seem not detrimental for patients harboring novel driver alteration. Adding CT could improve modest responses to IO alone. Confirmation on larger datasets is required.

PEOPLE (NTC03447678), a phase II trial to test pembrolizumab as first-line treatment in patients with advanced NSCLC with PD-L1 <50%: a multiomics analysis

BACKGROUND

Chemoimmunotherapy represents the standard of care for patients with advanced non-small cell lung cancer (NSCLC) and programmed death-ligand 1 (PD-L1) <50%. Although single-agent pembrolizumab has also demonstrated some activity in this setting, no reliable biomarkers yet exist for selecting patients likely to respond to single-agent immunotherapy. The main purpose of the study was to identify potential new biomarkers associated with progression-free-survival (PFS) within a multiomics analysis.

METHODS

PEOPLE (NTC03447678) was a prospective phase II trial evaluating first-line pembrolizumab in patients with advanced EGFR and ALK wild type treatment-naïve NSCLC with PD-L1 <50%. Circulating immune profiling was performed by determination of absolute cell counts with multiparametric flow cytometry on freshly isolated whole blood samples at baseline and at first radiological evaluation. Gene expression profiling was performed using nCounter PanCancer IO 360 Panel (NanoString) on baseline tissue. Gut bacterial taxonomic abundance was obtained by shotgun metagenomic sequencing of stool samples at baseline. Omics data were analyzed with sequential univariate Cox proportional hazards regression predicting PFS, with Benjamini-Hochberg multiple comparisons correction. Biological features significant with univariate analysis were analyzed with multivariate least absolute shrinkage and selection operator (LASSO).

RESULTS

From May 2018 to October 2020, 65 patients were enrolled. Median follow-up and PFS were 26.4 and 2.9 months, respectively. LASSO integration analysis, with an optimal lambda of 0.28, showed that peripheral blood natural killer cells/CD56dimCD16+ (HR 0.56, 0.41-0.76, p=0.006) abundance at baseline and non-classical CD14dimCD16+monocytes (HR 0.52, 0.36-0.75, p=0.004), eosinophils (CD15+CD16-) (HR 0.62, 0.44-0.89, p=0.03) and lymphocytes (HR 0.32, 0.19-0.56, p=0.001) after first radiologic evaluation correlated with favorable PFS as well as high baseline expression levels of CD244 (HR 0.74, 0.62-0.87, p=0.05) protein tyrosine phosphatase receptor type C (HR 0.55, 0.38-0.81, p=0.098) and killer cell lectin like receptor B1 (HR 0.76, 0.66-0.89, p=0.05). Interferon-responsive factor 9 and cartilage oligomeric matrix protein genes correlated with unfavorable PFS (HR 3.03, 1.52-6.02, p 0.08 and HR 1.22, 1.08-1.37, p=0.06, corrected). No microbiome features were selected.

CONCLUSIONS

This multiomics approach was able to identify immune cell subsets and expression levels of genes associated to PFS in patients with PD-L1 <50% NSCLC treated with first-line pembrolizumab. These preliminary data will be confirmed in the larger multicentric international I3LUNG trial (NCT05537922).

TRIAL REGISTRATION NUMBER

2017-002841-31.

Artificial Intelligence in Clinical Oncology: From Data to Digital Pathology and Treatment

Recently, a wide spectrum of artificial intelligence (AI)-based applications in the broader categories of digital pathology, biomarker development, and treatment have been explored. In the domain of digital pathology, these have included novel analytical strategies for realizing new information derived from standard histology to guide treatment selection and biomarker development to predict treatment selection and response. In therapeutics, these have included AI-driven drug target discovery, drug design and repurposing, combination regimen optimization, modulated dosing, and beyond. Given the continued advances that are emerging, it is important to develop workflows that seamlessly combine the various segments of AI innovation to comprehensively augment the diagnostic and interventional arsenal of the clinical oncology community. To overcome challenges that remain with regard to the ideation, validation, and deployment of AI in clinical oncology, recommendations toward bringing this workflow to fruition are also provided from clinical, engineering, implementation, and health care economics considerations. Ultimately, this work proposes frameworks that can potentially integrate these domains toward the sustainable adoption of practice-changing AI by the clinical oncology community to drive improved patient outcomes.

STYLE (NCT03449173) a phase II Trial of Sunitinib in patients with type B3 Thymoma or Thymic Carcinoma in second and further lines

BACKGROUND

Thymic malignancies are rare tumors with few therapeutic options. The STYLE trial was aimed to evaluate activity and safety of sunitinib in advanced/recurrent type B3 thymoma (T) and thymic carcinoma (TC).

METHODS

In this multicenter Simon 2 stages phase II trial, patients with pretreated T/TC were enrolled in two cohorts and assessed separately. Sunitinib was administered 50mg daily for 4-weeks, followed by a 2-week rest period (schedule 4/2), until disease progression or unacceptable toxicity. The primary endpoint was objectives response rate (ORR). Progression free survival (PFS), overall survival (OS), disease control rate (DCR) and safety were secondary endpoints.

RESULTS

From 03/2017 to 01/2022, 12 T and 32 TC patients were enrolled. At stage 1 ORR was 0% (90%CI 0.0-22.1) in T and 16.7% (90%CI 3.1-43.8) in TC, so T cohort was closed. At stage 2, the primary endpoint was met for TC with ORR of 21.7% (90%CI 9.0%-40.4%). In the ITT analysis DCR was 91.7% (95%CI 61.5%-99.8%) in Ts and 89.3% (95%CI 71.8%-97.7%) in TCs. mPFS was 7.7 months (95%CI 2.4-45.5) in Ts, 8.8 (95%CI 5.3-11.1) in TCs; mOS was 47.9 months (95%CI 4.5-not reached) in Ts, and 27.8 (95%CI 13.2-53.2) in TCs. Adverse events (AEs) occurred in 91.7% T and 93.5% TCs. Grade ≥3 treatment-related AEs were reported in 25.0% T and 51.6% TC.

CONCLUSIONS

This trial confirms the activity of sunitinib in TC patients, supporting its use as second line treatment.

Abstract 5506: Circulating immature neutrophils early detect hyperprogressive disease upon first-line PD-1/PD-L1 inhibitors in non-small cell lung cancer patients selecting best candidates for platinum-based chemotherapy and PD-1/PD-L1 inhibitors combinations

Background: Hyperprogressive disease (HPD) has been described in ≃14-25% of pretreated non-small cell lung cancer (NSCLC) patients upon single-agent (SA) PD-1/PD-L1 inhibitors (ICI) and has not been reported upon platinum-based chemotherapy (PCT) and ICI combinations. So far, no predictive biomarkers are available for HPD early detection.

Methods: NSCLC patients treated with 1st line SA-ICI or PCT-ICI were assessed for HPD and circulating neutrophils. HPD was defined as delta tumor growth rate (TGR) &gt;50% and/or TGR ratio ≥2. Circulating low density neutrophils (LDNs) were assessed by flow cytometry on peripheral blood mononuclear cells (PMBCs). LDNs were defined as CD66b+CD15+ cells among CD11b+ PBMCs and immature subtypes as CD10− LDNs. The LDNs predictive role was assessed by penalized model-based tests.

Results: 144 NSCLC patients were included: 75 treated with SA-ICI, 69 with PCT-ICI. In the SA-ICI cohort, HPD occurred in 8 (11%) patients, while progressive disease (PD) and response or stable disease (PR/SD) occurred in 33 (44%) and 34 (45%) of patients respectively. Immature circulating CD10− LDNs were significantly higher in baseline blood samples of HPD patients [median (ME): 39.3, interquartile range (IQR): 28.7] compared to PD [ME: 7.4, IQR: 14.9, p&lt;0.01] or PR/SD patients [ME: 3.7, IQR: 12.6, p&lt;0.01]. Circulating CD10− LDNs were associated with HPD [odds ratio (OR): 1.17, 95% CI: 1.06; 1.29], with a good prediction capability [cross-validated AUC 0.97 (95%CI: 0.94;1.00)]. A 30.5% cut-off value for CD10− LDNs circulating neutrophils was identified by Younden index to discriminate HPD from others. In the PCT-ICI cohort, 14 patients had circulating CD10− LDNs ≥30.5%, being at high risk of HPD. However, no HPD was observed in PCT-ICI cohort and dynamic LDNs evaluation in high HPD risk patients showed 52.3% (IQR: 28.4) median reduction in CD10− LDNs upon PCT-ICI, versus only 8.9% (IQR: 34.6) reduction in HPD patients upon SA-ICI, suggesting that PCT prevents HPD by reducing selectively immature LDNs.

Conclusions: Baseline circulating immature neutrophils characterize HPD upon 1st line SA-ICI and a 30.5% cut-off of immature neutrophils could select NSCLC patients to be addressed to PCT-ICI combinations.

Citation Format: Roberto Ferrara, Giuseppe Lo Russo, Chiara Maura Ciniselli, Annamaria Piva, Barbara Bassani, Elena Jachetti, Giuseppina Calareso, Valeria Duroni, Settimio Di Gregorio, Claudia Proto, Arsela Prelaj, Alessandro De Toma, Mario Occhipinti, Marta Brambilla, Sara Manglaviti, Laura Mazzeo, Arturo Rinaldi, Teresa Beninato, Monica Ganzinelli, Filippo De Braud, Marina Chiara Garassino, Paolo Verderio, Mario Paolo Colombo, Sabina Sangaletti. Circulating immature neutrophils early detect hyperprogressive disease upon first-line PD-1/PD-L1 inhibitors in non-small cell lung cancer patients selecting best candidates for platinum-based chemotherapy and PD-1/PD-L1 inhibitors combinations. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5506.

Poziotinib in Treatment-Naïve Non-Small-Cell Lung Cancer Harboring HER2 Exon 20 Mutations: ZENITH20-4, A Multicenter, Multicohort, Open-label Phase 2 Trial (Cohort 4)

INTRODUCTION

Erb-b2 receptor tyrosine kinase 2 gene (ERBB2 or HER2) alterations are found in approximately 2-5% of non-small cell lung cancers (NSCLCs); the majority are exon 20 insertion mutations. The efficacy and safety of poziotinib, an oral tyrosine kinase inhibitor, were assessed in treatment-naïve NSCLC patients whose tumors harbor HER2 exon 20 insertions.

METHODS

ZENITH20 is an open-label, multicohort, multicenter global phase 2 trial. ZENITH20-C4 enrolled treatment-naïve NSCLC patients with tumors harboring HER2 exon 20 insertions. Poziotinib was administered 16 mg once daily (QD) or 8 mg twice daily (BID). The primary endpoint was objective response rate (ORR) by independent central review (ICR). Secondary and exploratory endpoints included disease control rate (DCR), duration of response (DoR), progression-free survival (PFS), and safety.

RESULTS

Eighty patients (16 mg QD, n=47; 8 mg BID, n=33) were treated in ZENITH20-C4. ORR was 39% (95% CI, 28%-50%; 31/80), with a DCR of 73% (95% CI, 61%-82%; 58/80); 80% of patients experienced tumor reduction. Median DoR was 5.7 months (95% CI, 4.6-11.9 months), and median PFS was 5.6 months (95% CI, 5.4-7.3 months). The most common grade 3 treatment-related adverse events (TRAEs) were rash (QD, 45%; BID, 39%), stomatitis (QD, 21%; BID, 15%), and diarrhea (QD, 15%; BID, 21%). Among all subtypes of HER2 exon 20 insertions, 7 patients (9%) harboring tumors with G778_P780dupGSP had the best clinical outcomes (ORR, 71%).

CONCLUSIONS

Poziotinib demonstrated clinically meaningful efficacy with a manageable toxicity profile for treatment-naïve NSCLC patients harboring HER2 exon 20 mutations.

The EU-funded I3LUNG Project: Integrative Science, Intelligent Data Platform for Individualized LUNG Cancer Care With Immunotherapy

Although immunotherapy (IO) has changed the paradigm for the treatment of patients with advanced non-small cell lung cancers (aNSCLC), only around 30% to 50% of treated patients experience a long-term benefit from IO. Furthermore, the identification of the 30 to 50% of patients who respond remains a major challenge, as programmed Death-Ligand 1 (PD-L1) is currently the only biomarker used to predict the outcome of IO in NSCLC patients despite its limited efficacy. Considering the dynamic complexity of the immune system-tumor microenvironment (TME) and its interaction with the host's and patient's behavior, it is unlikely that a single biomarker will accurately predict a patient's outcomes. In this scenario, Artificial Intelligence (AI) and Machine Learning (ML) are becoming essential to the development of powerful decision-making tools that are able to deal with this high-complexity and provide individualized predictions to better match treatments to individual patients and thus improve patient outcomes and reduce the economic burden of aNSCLC on healthcare systems. I³LUNG is an international, multicenter, retrospective and prospective, observational study of patients with aNSCLC treated with IO, entirely funded by European Union (EU) under the Horizon 2020 (H2020) program. Using AI-based tools, the aim of this study is to promote individualized treatment in aNSCLC, with the goals of improving survival and quality of life, minimizing or preventing undue toxicity and promoting efficient resource allocation. The final objective of the project is the construction of a novel, integrated, AI-assisted data storage and elaboration platform to guide IO administration in aNSCLC, ensuring easy access and cost-effective use by healthcare providers and patients.

Challenges and knowledge gaps with immune checkpoint inhibitors monotherapy in the management of patients with non-small-cell lung cancer: a survey of oncologist perceptions

BACKGROUND

Immune checkpoint-inhibitors (ICIs) are changing outcomes in different cancer settings, notably for patients with non-small-cell lung cancer (NSCLC). There are, however, still important gaps of evidence for clinical practice when using these novel treatments. In this study, we assessed physicians' opinion and experience on challenges for clinical practice with ICIs monotherapy in NSCLC.

METHODS

A survey was conducted on experienced physicians treating patients with NSCLC with ICIs. Two rounds of pilot tests were carried out for validation among a group of experts. Topics under analysis were in relation to treatment of elderly populations, performance status, brain metastases, use of steroids or antibiotics, the effects of gut microbiome, autoimmune diseases, human immunodeficiency virus infection, solid organ transplants, use of anti-programmed cell death protein 1 versus anti-programmed death-ligand 1 drugs, atypical tumour responses, predictors of response, duration of treatment and a final open question on additional relevant challenges.

RESULTS

Two hundred and twenty-one answers were collected, including 106 (48%) valid answers from experts for final analysis (physicians who have treated at least 20 patients with NSCLC with ICIs). The vast majority agreed that the selected topics in this study are important challenges ahead and more evidence is needed. Moreover, predictors of response, treating brain metastasis, shorter duration of treatment, the effects of gut microbiome and concomitant use of steroids were voted the most important topics to be further addressed in prospective clinical research.

CONCLUSIONS

This survey contributed to understanding which are the main challenges for clinical practice with ICIs monotherapy in NSCLC. It can also contribute to guide further clinical research, considering the opinions and experience of those who regularly treat NSCLC patients with ICIs.

Real-world data to build explainable trustworthy artificial intelligence models for prediction of immunotherapy efficacy in NSCLC patients

Introduction

Artificial Intelligence (AI) methods are being increasingly investigated as a means to generate predictive models applicable in the clinical practice. In this study, we developed a model to predict the efficacy of immunotherapy (IO) in patients with advanced non-small cell lung cancer (NSCLC) using eXplainable AI (XAI) Machine Learning (ML) methods.

Methods

We prospectively collected real-world data from patients with an advanced NSCLC condition receiving immune-checkpoint inhibitors (ICIs) either as a single agent or in combination with chemotherapy. With regards to six different outcomes - Disease Control Rate (DCR), Objective Response Rate (ORR), 6 and 24-month Overall Survival (OS6 and OS24), 3-months Progression-Free Survival (PFS3) and Time to Treatment Failure (TTF3) - we evaluated five different classification ML models: CatBoost (CB), Logistic Regression (LR), Neural Network (NN), Random Forest (RF) and Support Vector Machine (SVM). We used the Shapley Additive Explanation (SHAP) values to explain model predictions.

Results

Of 480 patients included in the study 407 received immunotherapy and 73 chemo- and immunotherapy. From all the ML models, CB performed the best for OS6 and TTF3, (accuracy 0.83 and 0.81, respectively). CB and LR reached accuracy of 0.75 and 0.73 for the outcome DCR. SHAP for CB demonstrated that the feature that strongly influences models' prediction for all three outcomes was Neutrophil to Lymphocyte Ratio (NLR). Performance Status (ECOG-PS) was an important feature for the outcomes OS6 and TTF3, while PD-L1, Line of IO and chemo-immunotherapy appeared to be more important in predicting DCR.

Conclusions

In this study we developed a ML algorithm based on real-world data, explained by SHAP techniques, and able to accurately predict the efficacy of immunotherapy in sets of NSCLC patients.

Biological Rationale for Peripheral Blood Cell-Derived Inflammatory Indices and Related Prognostic Scores in Patients with Advanced Non-Small-Cell Lung Cancer

PURPOSE OF REVIEW

To describe the biological rationale of peripheral blood cells (PBC)-derived inflammatory indexes and assess the related prognostic scores for patients with advanced non-small cell lung cancer (aNSCLC) treated with immune-checkpoint inhibitors (ICI).

RECENT FINDINGS

Inflammatory indexes based on PBC may indicate a pro-inflammatory condition affecting the immune response to cancer. The lung immune prognostic index (LIPI), consisting of derived neutrophils-to-lymphocyte ratio (NLR) and lactate dehydrogenase, is a validated prognostic tool, especially for pretreated aNSCLC patients, where the combination of NLR and PD-L1 tumour expression might also be predictive of immunotherapy benefit. In untreated high-PD-L1 aNSCLC patients, the Lung-Immune-Prognostic score (LIPS), including NLR, ECOG PS and concomitant steroids, is prognostic, and its modified version might indicate patients with favourable outcomes despite an ECOG PS of 2. NLR times platelets (i.e., SII), included in the NHS-Lung score, might improve the prognostication for combined chemoimmunotherapy. PBC-derived inflammatory indexes and related scores represent accurate, reproducible and non-expensive prognostic tools with clinical and research utility.

Comparative assessment of early mortality risk upon immune checkpoint inhibitors alone or in combination with other agents across solid malignancies: a systematic review and meta-analysis

BACKGROUND

The early crossing of survival curves in randomised clinical trials (RCTs) with immune checkpoint blockers suggests an excess of mortality in the first months of treatment. However, the exact estimation of the early death (ED) rate, the comparison between ED upon immune checkpoint inhibitors (ICI) alone or in combination with other agents and the impact of tumour type, and PD-L1 expression on ED are unknown.

METHODS

RCTs comparing ICI alone (ICI-only group) or in combination with other non-ICI therapies (ICI-OT group) (experimental arms) versus non-ICI treatments (control arm) were included. ED was defined as death within the first 3 months of treatment. The primary outcome was the comparison of ED between experimental and control arms, and the secondary outcome was the comparison of ED risk between ICI-only and ICI-OT. ED rates estimated by risk ratio (RR) were pooled by random effect model.

RESULTS

A total of 56 RCTs (40,215 participants, 14 cancer types) were included. ED occurred in 14.2% and 6.7% of patients in ICI-only and ICI-OT groups, respectively. ED risk significantly increased with ICI-only (RR: 1.29, 95% CI 1.05-1.57) versus non-ICI therapies, while it was lower with ICI-OT versus non-ICI treatments (RR: 0.81, 95% CI 0.73-0.90). ED risk was significantly higher upon ICI-only compared to ICI-OT (RR: 1.57, 95% CI 1.26-1.95). Gastric and urothelial carcinoma were at higher risk of ED. PD-L1 expression and ICI drug classes were not associated with ED.

CONCLUSIONS

ED upon first-line ICI is a clinically relevant phenomenon across solid malignancies, not predictable by PD-L1 expression but preventable through the addition of other treatments to ICI.

PEOPLE (NCT03447678), a first-line phase II pembrolizumab trial, in negative and low PD-L1 advanced NSCLC: clinical outcomes and association with circulating immune biomarkers

BACKGROUND

The PEOPLE trial aimed to identify new immune biomarkers in negative and low programmed death-ligand 1 (PD-L1) (0%-49%) advanced non-small-cell lung cancer (aNSCLC) patients treated with first-line pembrolizumab. Here we report the main outcomes and the circulating immune biomarkers analysis.

PATIENTS AND METHODS

The primary endpoint of this phase II trial was the identification of immune biomarkers associated with progression-free survival (PFS). Overall survival (OS), objective response rate (ORR), disease control rate (DCR), duration of response (DoR) and safety were secondary endpoints. Absolute cell counts for 36 subsets belonging to innate and adaptive immunity were determined by multiparametric flow cytometry in peripheral blood at baseline and at first radiologic evaluation. An orthoblique principal components-based clustering approach and multivariable Cox regression model adjusted for clinical variables were used to analyze immune variables and their correlation with clinical endpoints.

RESULTS

From May 2018 to October 2020, 65 patients were enrolled. After a median follow-up of 26.4 months, the median PFS was 2.9 months [95% confidence interval (CI) 1.8-5.6 months] and median OS was 12.1 months (95% CI 8.7-17.1 months). The ORR was 21.5%, DCR was 47.7% and median DoR was 14.5 months (95% CI 6.4-24.9 months). Drug-related grade 3-4 adverse events were 9.2%. Higher T cell and natural killer (NK) cell count at baseline and at the first radiologic evaluation were associated with improved PFS, DCR and OS. On the contrary, higher myeloid cell count at baseline or at the first radiologic evaluation was significantly associated with worse OS and DCR.

CONCLUSIONS

Circulating immune biomarkers can contribute to predict outcomes in negative and low PD-L1 aNSCLC patients treated with first-line single-agent pembrolizumab.

Molecular Epidemiology and Treatment Patterns of Patients With EGFR Exon 20-Mutant NSCLC in the Precision Oncology Era: The European EXOTIC Registry

Introduction

Real-world evidence regarding molecular epidemiology and management patterns of patients with EGFR exon-20 mutated, advanced NSCLC outside the context of clinical trials is lacking.

Methods

We created a European registry for patients with advanced EGFR exon 20-mutant NSCLC diagnosed from January 2019 to December 2021. Patients enrolled in clinical trials were excluded. Clinicopathologic and molecular epidemiology data were collected, and treatment patterns were recorded. Clinical end points according to treatment assignment were assessed using Kaplan-Meier curves and Cox regression models.

Results

Data on 175 patients from 33 centers across nine countries were included in the final analysis. Median age was 64.0 (range: 29.7-87.8) years. Main features included female sex (56.3%), never or past smokers (76.0%), adenocarcinoma (95.4%), and tropism for bone (47.4%) and brain (32.0%) metastases. Mean programmed death-ligand 1 tumor proportional score was 15.8% (range: 0%-95%) and mean tumor mutational burden was 7.06 (range: 0-18.8) mutations per megabase. Exon 20 was detected in the tissue (90.7%), plasma (8.7%), or both (0.6%), using mostly targeted next-generation sequencing (64.0%) or polymerase chain reaction (26.0%). Mutations were mainly insertions (59.3%), followed by duplications (28.1%), deletions-insertions (7.7%), and the T790M (4.5%). Insertions and duplications were located mainly in the near loop (codons 767-771, 83.1%) and the far loop (codons 771-775, 13%) and only in 3.9% within the C helix (codons 761-766). Main co-alterations included mutations in TP53 (61.8%) and MET amplifications (9.4%). Treatment on mutation identification included chemotherapy (CT) (33.8%), CT-immunotherapy (IO) (18.2%), osimertinib (22.1%), poziotinib (9.1%), mobocertinib (6.5%), mono-IO (3.9%), and amivantamab (1.3%). Disease control rates were 66.2% with CT plus or minus IO, 55.8% with osimertinib, 64.8% with poziotinib, and 76.9% with mobocertinib. Corresponding median overall survival was 19.7, 15.9, 9.2, and 22.4 months, respectively. In multivariate analysis, type of treatment (new targeted agents versus CT ± IO) affected progression-free survival (p = 0.051) and overall survival (p = 0.03).

Conclusions

EXOTIC represents the largest academic real-world evidence data set on EGFR exon 20-mutant NSCLC in Europe. Indirectly compared, treatment with new exon 20-targeting agents is likely to confer survival benefit than CT plus or minus IO.

Circulating Fatty Acid Profile as a Biomarker for Immunotherapy in Advanced Non-Small Cell Lung Cancer

INTRODUCTION

Lipid metabolism impacts immune cell differentiation, activation, and functions, modulating inflammatory mediators, energy homeostasis, and cell membrane composition. Despite preclinical evidence, data in humans lack concerning tumors and immunotherapy (IO). We aimed at investigating the correlations between circulating lipids and the outcome of non-small cell lung cancer (NSCLC) patients treated with IO.

MATERIALS AND METHODS

We identified all patients with advanced NSCLC treated with IO at our Institution with available baseline plasma samples. Fatty acids (FAs) were analyzed through gas chromatography. Survival curves were estimated by the Kaplan-Meier method. Cox multivariate models were constructed through a stepwise procedure, with entry and exit P value set at .2.

RESULTS

We identified 112 patients, mostly with performance status 1 (65.2%) and PD-L1≥1% (75.3%). Median progression-free survival (PFS) and overall survival (OS) were 2.8 and 11.0 months, respectively. Multivariable model for survival identified a positive association of circulating free (FFA) C16:0 (P .005) and esterified (EFA) C16:1 (P .030) with PFS, and a positive association of EFA C16:1 (P .001) and EFA C18:0 (P .020) with OS. EFA C16:0 was negatively associated with PFS (P .008).

CONCLUSION

FFA C16:0 and FAs derived from its unsaturation (EFA C16:1) and elongation (EFA C18:0) are associated with a better outcome in NSCLC patients treated with IO. It is conceivable that the ratio among those FAs may modify membrane fluidity and receptor activity, influencing IO efficacy. These data pave the way for the investigation of lipid-modulating strategies in association with IO in NSCLC.

Circulating CD81-expressing extracellular vesicles as biomarkers of response for immune-checkpoint inhibitors in advanced NSCLC

PD-L1 in tumor cells is the only used biomarker for anti PD1/PD-L1 immune-checkpoints inhibitors (ICI) in Non Small Cell Lung Cancer (NSCLC) patients. However, this parameter is inaccurate to predict response, especially in patients with low tumor PD-L1. Here, we evaluated circulating EVs as possible biomarkers for ICI in advanced NSCLC patients with low tumoral PD-L1. EVs were isolated from plasma of 64 PD-L1 low, ICI-treated NSCLC patients, classified either as responders (R; complete or partial response by RECIST 1.1) or non-responders (NR). EVs were characterized following MISEV guidelines and by flow cytometry. T cells from healthy donors were triggered in vitro using patients’ EVs. Unsupervised statistical approach was applied to correlate EVs’ and patients’ features to clinical response. R-EVs showed higher levels of tetraspanins (CD9, CD81, CD63) than NR-EVs, significantly associated to better overall response rate (ORR). In multivariable analysis CD81-EVs correlated with ORR. Unsupervised analysis revealed a cluster of variables on EVs, including tetraspanins, significantly associated with ORR and improved survival. R-EVs expressed more costimulatory molecules than NR-EVs although both increased T cell proliferation and partially, activation. Tetraspanins levels on EVs could represent promising biomarkers for ICI response in NSCLC.

Prognostic scores including peripheral blood-derived inflammatory indices in patients with advanced non-small-cell lung cancer treated with immune checkpoint inhibitors

Peripheral blood inflammatory indices, like the neutrophil-to-lymphocyte ratio (NLR), may reflect the host's pro-inflammatory status and systemic immune response to cancer-related inflammation. We reviewed 22 combined prognostic scores based on peripheral blood-derived inflammatory indices for aNSCLC patients treated with single-agent or combination immune-checkpoint inhibitors (ICI) as first-line or subsequent therapy lines and attempted evidence strength assessment and scoring. The Lung Immune Prognostic Index (LIPI), consisting of derived NLR and LDH, was the most studied score with validated prognostic value in over five thousand aNSCLC ICI-naïve or pretreated patients. The combination of NLR and tumour programmed-cell-death-ligand1 (PD-L1) expression showed a predictive value. The Lung-Immune-Prognostic score (LIPS) might help identify patients with poor performance status but a favourable outcome following first-line ICI. These non-expensive scores can help clinicians discuss the prognosis with aNSCLC patients approaching ICI, identify those less likely to benefit from single-agent ICI and orient future clinical research.

Case Report: Exceptional Response to Poziotinib in Patient with Metastatic Non-Small Cell Lung Cancer With EGFR Exon 20 Insertion Mutation

Among the several next-generation tyrosine kinase inhibitors (TKIs) tested against uncommon EFGR alterations, poziotinib has been demonstrated to be a powerful agent for metastatic non-small-cell lung cancer (mNSCLC) with aberrations in HER2 exon 20, and FDA approval is being sought in the previously-treated population. Poziotinib has also shown activity in mNSCLC with aberrations in EGFR exon 20. Herein, we report the first published case of a patient affected by mNSCLC harbouring an EGFR exon 20 insertion (EGFRex20ins) mutation who achieved a complete response (CR) under treatment with poziotinib as part of the ZENITH20 trial. In January 2021, a former smoker 62-year-old female patient was diagnosed with relapse, after two surgeries and post-operative chemotherapy of mNSCLC, at liver and retroperitoneal nodes. Given the identification by Next Generation Sequencing (NGS) of EGFRex20ins mutation, she was enrolled in ZENITH20-cohort 5 trial, a phase 2 multicentre study aimed to assess the efficacy and safety of poziotinib in patients with EGFR or HER2 exon 20 insertion mutations. Poziotinib as first-line systemic therapy for metastatic disease was initiated at the end of January 2021 and administrated at the initial dosage of 8 mg orally twice daily (BID). The most common side effects from the beginning of the treatment included alopecia, macular skin rash, diarrhoea, xerostomia, and conjunctivitis. Due to these adverse events, poziotinib was discontinued during the first 3 months and then reduced to 6 mg orally BID in April 2021. After the dose de-escalation, the adverse events ameliorated, and the patient better tolerated the treatment without further interruption. Since the first reevaluation (after 4 weeks of therapy), the treatment with poziotinib resulted to be remarkably effective, with a partial response (PR) subsequently confirmed in May and July 2021. Then, in October 2021, a CT scan confirmed a CR, maintained with good tolerance at the last reevaluation in February 2022. Treatment is still ongoing at the same dosage. In this case, poziotinib has represented a successful and well-tolerated first-line treatment alternative to chemotherapy in this patient with EGFR exon 20 insertion mutated mNSCLC.

Prognostic role of neutrophil-to-lymphocyte ratio and EPSILoN score in advanced non-small-cell lung cancer patients treated with first-line chemo-immunotherapy

Background: Clinical and laboratory biomarkers in patients with advanced non-small-cell lung cancer (aNSCLC) receiving chemo-immunotherapy (CIT) are still poorly explored. Materials & methods: All consecutive aNSCLC patients who received at least one cycle of first-line CIT were enrolled. The impact of several clinical and laboratory biomarkers on outcomes was evaluated through Cox proportional hazard models. Results: Higher neutrophil-to-lymphocyte ratio was shown to be an independent prognostic biomarker of both worse progression-free survival and worse overall survival. The EPSILoN score was able to divide patients into three different prognostic groups, with a median overall survival of 73.2, 45.6 and 8.6 months for the favorable, intermediate and poor groups, respectively. Conclusion: The neutrophil-to-lymphocyte ratio and EPSILoN score were shown to have a prognostic value in aNSCLC patients treated with CIT.

Immunotherapy and chemo-immunotherapy for non–small cell lung cancer with novel actionable oncogenic driver alterations

9057

Background: Immune checkpoint inhibitors (IO) single agent or in combination with platinum chemotherapy (CT-IO) are standard of care for Stage IV non-small cell lung cancer (NSCLC) according to PD-L1 expression. While the efficacy of IO among patients (pts) with common EGFR and ALK alterations appears to be limited, its activity in pts with novel oncogenic drivers alterations is not well characterized. Compared to non-oncogene-addicted NSCLC, the overall response rate (ORR) seems to be similar in BRAF and c-MET altered NSCLC, lower in RET altered NSCLC, while data are less consistent in HER2 and EGFR exon 20 (EGFRex20) altered NSCLCs. Methods: From January 2016 to January 2022, we retrospectively enrolled pts with Stage IV NSCLC that received IO or combination CT– IO in any line, ECOG PS 0 - 2 and detection of MET exon 14 skipping mutations (METex14), BRAF mutations (V600E or non-V600E), RET rearrangement, HER2 point mutations (HER2mut)/exon 20 insertions (HER2ex20) or uncommon EGFR mutations (uEGFRmut)/EGFRex20. A review of clinicopathologic and molecular features and an analysis of response to combination or single-agent IO were conducted. Results: Among sixty-four pts enrolled, 20 (31%) had METex14, 19 (30%) had EGFR alterations [12 (19%) EGFRex20, 7 (11%) uEGFRmut], 8 (12%) had BRAF mutation (3 V600E and 5 non-V600E), 13(20%) had HER2 alterations [7 (11%) HER2ex20, 6 (10%) HER2mut] and 4 (6%) were RET rearranged. 43 received IO single agent and 21 received CT-IO. With a median follow up of 22 months (m), median progression free survival (mPFS) was 5.40 m (0.95 CI 4.73-6.9) overall, 6.77m in CT-IO arm (0.95 CI 5.37-NA) and 5.10m in IO arm (0.95 CI 2.60-6.7), with a trend to better mPFS for CT-IO (p 0.054). Regarding specific mutations irrespectively from treatment arm, NSCLC harboring METex14 showed a mPFS of 5.33 m (0.95 CI, 2.30-13.9), BRAF 9.9 m (0.95 CI, 6.70-NA), EGFR 4.93 m (0.95 CI, 1.80-6.9), HER2 11.4 (0.95 CI, 4.2-NA), RET 5.28 (0.95 CI, 1.42-NA). Disease control rate (DCR) was better in the CT-IO arm vs IO one in the overall population (84.2% vs 50%, p 0.013). Conclusions: Novel driver alterations seem to show a benefit from IO treatments. CT-IO seems to have a better outcome in terms of DCR. Therefore, IO-based treatment should be evaluated also in tumors harboring novel driver alterations. [Table: see text]

PEOPLE (NTC03447678), a phase II trial to test pembrolizumab as first-line treatment in patients with advanced NSCLC with PD-L1 < 50%: A multiomics approach

9051

Background: Chemo-immunotherapy is the standard of care for patients with advanced NSCLC and PD-L1 < 50%. Efficacy has been reported in this setting with single agent pembrolizumab, but no reliable biomarkers yet exist for selecting patients likely to respond to single agent immunotherapy. The aim of this trial was to identify potential new immune biomarkers associated with PFS in NSCLC patients with PD-L1 < 50% treated with first line pembrolizumab. Methods: Advanced EGFR and ALK wild type treatment-naïve NSCLC patients with PD-L1 < 50% were enrolled. Gene expression profile was performed using nCounter PanCancer IO 360 Panel (Nanostring) on baseline tissue. Circulating immune profiling was performed by determination of absolute cell counts with multiparametric flow cytometry on freshly isolated whole blood samples at baseline and at first radiological evaluation. Gut bacterial taxonomic abundance was obtained by shotgun metagenomic sequencing of stool sample at baseline. Pembrolizumab was administered at 200 mg flat dose every 3 weeks until 35 cycles, disease progression or unacceptable toxicity. Omics data was analyzed with sequential univariate Cox Proportional Hazards regression predicting PFS, with Benjamini-Hochberg multiple comparisons correction. Biological features significant with univariate analysis were analyzed with multivariate Least Absolute Shrinkage and Selection Operator (LASSO). Results: From May 2018 to October 2020 65 patients were enrolled. Main characteristics were: male 67.6%, smokers 87.7%, PD-L1 positive 70.8%. Median follow up and PFS were 26.4 and 2.9 months, respectively. Gene expression profile was performed in 48 patients, microbiome in 54 patients and circulating immune profiling in 56 patients at baseline and in 46 patients at first radiologic evaluation. LASSO multivariate analysis with optimal lambda of 0.28 showed high expression levels of IRF9 and COMP genes was associated with an unfavorable PFS (HR 3.03, 1.52 – 6.02, p = 0.08 and HR 1.22, 1.08 – 1.37, corrected p = 0.06, respectively). High expression levels of CD244 (HR 0.74, 0.62- 0.67, p = 0.05), PTPRC (HR 0.55, 0.38 – 0.81, p = 0.098), KLRB1 (HR 0.76, 0.66 – 0.89, p = 0.05) in tissue samples and NK cells/CD56dimCD16+ (HR 0.56, 0.41 – 0.76, p = 0.006) in peripheral blood at baseline and non classical CD14dim CD16+ monocytes (HR 0.52, 0.36 – 0.75, p = 0.004), eosinophils (CD 15+CD16-) (HR 0.62, 0.44 – 0.89, p = 0.003) lymphocytes (HR 0.28, 0.15 – 0.5, p < 0.001) in peripheral blood after first radiologic evaluation were associated to a favorable PFS. No microbiome features were selected by LASSO. Conclusions: To the best of our knowledge, this is the first prospective trial in NSCLC with PD-L1 < 50% performed with a multi-omic approach able to identify immune cell subsets and expression levels of genes associated to PFS under first line treatment with pembrolizumab. Clinical trial information: NTC03447678.

A systematic review and meta-analysis of early death (ED) upon immune checkpoint inhibitors (ICI) alone or combined with other non-ICIs treatments as first-line treatment of advanced solid tumors

2669

Background: An early crossing of the Kaplan-Meier overall survival curves in randomized clinical trials (RCTs) comparing ICI alone to standard treatments has been observed across different cancer types, suggesting the existence of an excess of mortality upon ICI. Whether ED reflects the natural history of the disease or it is a treatment specific phenomenon remains unclear. Therefore, we conducted a metanalysis of RCTs to analyze the association of ICI treatment with ED. Methods: PubMed, Embase and Cochrane were searched (until 12/2021) for RCTs comparing 1st-line PD-1/PD-L1 inhibitors +/- CTLA-4 inhibitors (ICI-only group) or the same drugs in combination with other non-ICI therapies (ICI+OT group) (experimental arms) vs non-ICI treatments (control arm) in patients (pts) with advanced solid cancers. ED was defined as death within the first 3 months of treatment. RCTs providing the number of pts in the intention-to-treat (ITT) population who were alive within 0-3 months from randomization were considered eligible. Primary outcome was ED rate both in the ICI-only and in the ICI+OT groups vs control arm. Secondary outcome was to compare ED risk between ICI-only group and ICI+OT group. Further analysis according to PD-L1 level were performed. The ED rates were estimated by risk-ratio (RR) with 95% confidence intervals (CI) and pooled by random effect model. Heterogeneity was assessed by I2 statistics. Results: 56 RCTs (n = 38697 pts) were eligible, 48.2% included pts with thoracic malignancies. In the ICI-only group (18 RCTs, n = 6638 pts) 50.5% of pts received anti-PD-1/PD-L1 monotherapy and 43.4% anti-PD-1/PD-L1 + anti-CTLA-4 agents. In the ICI+OT group (43 RCTs, n = 15421 pts) 80.1% of pts received ICI + chemotherapy. Compared to control arm, risk of ED was significantly higher for pts who received ICI-only therapies (RR 1.27, 95% CI 1.04-155, p = 0.02, I2: 73%), but significantly lower in ICI+OT group (RR 0.80, 95% CI 0.71-0.89, p < 0.00001, I2: 36%). Risk of ED was also significantly higher with ICI-only compared to ICI-OT (RR 1.59, 95% CI 1.26-2.00). ED risk was higher upon ICI-only also in pts with high PD-L1 expression (TPS ≥50%, TC or IC 3, CPS ≥10) and, after excluding Keynote-024, this result became statistically significant (7 RCTs, RR 1.54, 95% CI 1.13-2.10, p = 0.007) with I2 reducing from 63 to 46%. Conclusions: Across cancer types ED is a treatment specific phenomenon, increasing with first-line anti-PD-1/PD-L1 +/- CTLA-4 inhibitors and occurring also in pts with high PD-L1 expression, whereas it can be prevented by combining ICI with other non-ICI treatments.

PEOPLE (NTC03447678), a phase II trial of first-line, single-agent pembrolizumab in advanced NSCLC with low PD-L1: Clinical outcomes and association with circulating immune biomarkers

9033

Background: In advanced NSCLC (aNSCLC) with PD-L1 < 50% chemo-immunotherapy is the standard of care. Although the activity of single agent pembrolizumab was reported, no biomarkers have been identified able to select patients who mostly benefit. The trial aimed to identify immune biomarkers associated with PFS in aNSCLC patients with PD-L1 levels < 50% treated with first-line pembrolizumab. Here we reported for the first time the clinical outcomes of the trial and circulating immune profiling (CIP) biomarkers correlated to PFS. Methods: This phase II trial was conducted at Fondazione IRCCS Istituto Nazionale dei Tumori of Milan. Eligible patients were previously untreated stage IIIB-IV NSCLC, EGFR and ALK wild type with PD-L1 < 50%, PS 0-2. PD-L1 was assessed with 22-C3 antibody (Dako). Patients received pembrolizumab 200 mg every 3 weeks until 35 cycles, disease progression or unacceptable toxicity. The primary endpoint was the association of immune biomarkers with PFS. OS, ORR, DCR, DoR and safety were secondary endpoints. CIP was performed by determination of absolute cell counts for 36 innate and adaptive immunity subsets through multiparametric flow cytometry on freshly isolated whole blood samples at baseline. An orthoblique principal components-based clustering approach and multivariable Cox regression model adjusted for clinical variables were used to analyse CIP variables and their correlation with clinical endpoints. Results: From May 2018 to October 2020, of 87 screened, 65 patients were enrolled. The median age was 70.9 years, most patients were male (67.7%), smoker (87.7%), non-squamous (83.1%), PDL1 + (70.8%). 12 patients (18.5%) had PS 2. During a median follow-up of 26.4 months (mo), 51 radiological progressions, 46 deaths and 60 PFS events were observed. The median PFS was 2.9 mo (95%CI 1.8 - 5.6) and the median OS was 12.1 mo (95%CI 8.7 - 17.1). The ORR was 24.1% (2 complete and 12 partial responses), DCR was 53.4% and median DoR was 14.5 mo (95%CI 6.4 - 24.9). Drug related G3-G4 adverse events were: 2 hyponatremia, 2 lipase increased, 1 pneumonitis. Out of 7 CIP clusters identified, 2 were statistically significant at multivariable analysis on 57 patients. Higher baseline counts of 8 subsets within these two clusters were associated with better PFS (HR values range: 0.88-0.98; p values range: 0.001- 0.016). The significant subsets included lymphocytes (cells expressing CD3, or CD19 or CD56, but lacking granulocyte and monocyte markers) and main NK subsets (including CD56dim CD16+, CD56dim CD16- and HLA-DR+ NK cells). Conclusions: This trial confirmed that pembrolizumab as first-line single agent is safe and active also in a subgroup of aNSCLC patients with PD-L1 < 50%. CIP biomarkers can be useful to identify patients with a favourable outcome, thus avoiding the adding toxicity of chemotherapy. Clinical trial information: NTC03447678.

Machine Learning Using Real-World and Translational Data to Improve Treatment Selection for NSCLC Patients Treated with Immunotherapy

Simple Summary

In this paper, the authors show that artificial intelligence (AI) and machine learning (ML) are useful approaches to integrate multifactorial data and helpful for personalized prediction. In detail, compared to PD-L1 for advanced non-small cell lung cancer (NSCLC), ML tools predicted better responder (R) and non-responder (NR) patients to immunotherapy (IO). It was also able to indirectly foresee OS and PFS of R and NR patients. Given the high incidence of NSCLC, and the absence of reliable biomarkers to predict the response to IO other than PD-L1, the authors believe this research may be of great interest to anyone involved in thoracic oncology. Furthermore, given the growing interest from the scientific community in AI and ML, the authors believe that this manuscript could represent a fascinating topic to anyone who needs to exploit the enormous potential of these tools in the treatment of cancer.

Abstract

(1) Background: In advanced non-small cell lung cancer (aNSCLC), programmed death ligand 1 (PD-L1) remains the only biomarker for candidate patients to immunotherapy (IO). This study aimed at using artificial intelligence (AI) and machine learning (ML) tools to improve response and efficacy predictions in aNSCLC patients treated with IO. (2) Methods: Real world data and the blood microRNA signature classifier (MSC) were used. Patients were divided into responders (R) and non-responders (NR) to determine if the overall survival of the patients was likely to be shorter or longer than 24 months from baseline IO. (3) Results: One-hundred sixty-four out of 200 patients (i.e., only those ones with PD-L1 data available) were considered in the model, 73 (44.5%) were R and 91 (55.5%) NR. Overall, the best model was the linear regression (RL) and included 5 features. The model predicting R/NR of patients achieved accuracy ACC = 0.756, F1 score F1 = 0.722, and area under the ROC curve AUC = 0.82. LR was also the best-performing model in predicting patients with long survival (24 months OS), achieving ACC = 0.839, F1 = 0.908, and AUC = 0.87. (4) Conclusions: The results suggest that the integration of multifactorial data provided by ML techniques is a useful tool to select NSCLC patients as candidates for IO.

Systemic lupus erythematosus reactivation after chemoimmunotherapy in preexisting autoimmune disease

The use of immune checkpoint inhibitors (ICIs) offers new possibilities in modern treatment of many types of cancers. Few data regarding safety and efficacy of ICIs are available, and are mainly from retrospective studies and case reports rather than from clinical trials, in the context of preexisting autoimmune disease, mainly due to the risk of severe toxicity. We present an unexpected life-threatening reactivation of systemic lupus erythematosus after one dose of chemo-immunotherapy with pembrolizumab for oligometastatic non-small-cell lung cancer. We analyze data coming from the published literature in this setting and discuss the risk-benefit balance of immunotherapy in patients with preexisting severe autoimmune disease.

Carcinomatosis under control by osimertinib in EGFR and TP53 mutated lung adenocarcinoma

INTRODUCTION

Approximately 25%-30% of patients with non-small cell lung cancer (NSCLC) develop central nervous system (CNS) metastases during the course of the disease; this percentage is higher in patients with epidermal growth factor receptor (EGFR) mutations. Leptomeningeal metastases, infrequent in the advanced setting, have a particularly dismal prognosis. Osimertinib, a third-generation EGFR inhibitor, can provide effective and durable response in this setting.

CASE DESCRIPTION

We present a 62-year-old man with progressive vomiting, headache, short-term memory impairment, and left lower limb hyposthenia. Computed tomography (CT) showed bilateral lung nodules, multiple lymphadenopathies, liver and bone metastases, and CNS and leptomeningeal dissemination, including multiple parenchymal nodules located at supra- and infratentorial brain. Bone needle biopsy documented TTF1+ lung adenocarcinoma. Whole brain radiotherapy (WBRT) and symptomatic treatments were started. Next-generation sequencing reported deletion of exon 19 of EGFR and mutation 8 of TP53. Osimertinib 80 mg was promptly started and WBRT interrupted. Some days after the patient experienced repetitive seizures and neurologic worsening, antiepileptic drugs and dexamethasone were implemented, with gradual improvement. Radiologic evaluation, including brain MRI and thorax-abdominal CT, showed partial response on CNS as well as extracranial sites, which was sustained.

CONCLUSIONS

First-line treatment with osimertinib can be safe and effective in EGFR-mutated NSCLC even in presence of multiple negative predictive factors (poor Performance Status, diffuse leptomeningeal involvement, TP53 comutation), suggesting that deferring local treatments can be feasible in this setting, allowing the patient to maintain a good quality of life.

15 First-line platinum-based chemotherapy combined with PD-1/PD-L1 inhibitors (ICI) prevents hyperprogression in non-small cell lung cancer (NSCLC) patients by reducing circulating immature neutrophils

Background

Hyperprogression (HPD) has been described in ≃14–26% of NSCLC patients upon single-agent ICI1 and has not been reported upon ICI and platinum-based chemotherapy (PCT) combinations. Both high circulating neutrophils2 and senescent T-cells3 correlated with HPD, however the exact neutrophils-T-cells interplay and the role of specific neutrophils subsets in driving HPD is unknown.

Methods

NSCLC patients treated with 1st line ICI as single-agent or in combination with PCT were assessed for HPD and circulating neutrophils’ phenotype. HPD required 3 assessment (2 before ICI, 1 upon ICI) and was defined as delta tumor growth rate (TGR) (TGR upon ICI – TGR before ICI) >50% and/or TGR ratio (TGR upon ICI/TGR before ICI) ≥2. Circulating low density neutrophils (LDNs) subtypes were assessed by flow cytometry on peripheral blood mononuclear cells (PMBCs). LDNs were defined as CD66b+CD15+ cells among CD11b+ PBMCs. Immature subtypes were defined as CD10- LDNs. T-cells were isolated from healthy donors and cocultured with patients‘ LDNs to characterize the neutrophils-T-cells interplay. LDNs subtypes were isolated from patients and treated in-vitro with cisplatin to assess cell death.

Results

46 NSCLC patients were treated with single-agent ICI and 17 with PCT+ICI (table 1). In the ICI single-agent cohort, PD and HPD occurred in 21 (41%) and 4 (9%) patients. Before ICI start, HPD patients had significantly higher median% of circulating immature CD10- LDNs neutrophils [43.5 (min 29.5; max 82.6) vs 10.3 (min 0.1; max 79.4), p=0.01] compared to PD patients (figure 1). In the ICI-PCT cohort no HPD was reported. 5 patients had baseline CD10- LDNs ≥ 43.5% (median% of CD10- LDNs in HPD patients upon single-agent ICI), 2 of them had stable disease and 3 PD upon ICI-PCT. In these 5 patients, CD10- LDNs significantly decreased during ICI-PCT compared to what observed in HPD patients upon single-agent ICI [median variation -43.4 (min -67.6, max -31.6) vs +6.9 (min -33, max +44), p= 0.03] (figure 2). After 7 days of coculture with T-cells, immature CD10- LDNs significantly reduced T-cells survival and promoted a T-cell senescent phenotype (CD28 loss, CD57 gain) impairing T-cells proliferation and increasing IFN-gamma production (figure 3). Cisplatin treatment significantly increased necrotic cell death among CD10- LDNs compared to CD10+ LDNs (figure 4).

Abstract 15 Table 1

Patients characteristics in the single-agent ICI and PCT+ICI cohorts

Abstract 15 Figure 1

Patterns of response, progression and hyperprogression to single-agent ICI and correlation with mature (CD10+) or immature (CD10-) LDNs’ subtypes

Abstract 15 Figure 2

Neutrophils dynamic variation upon treatment (5 patients with high baseline CD10- LDNs and PD/SD to chemo-ICI vs 4 patients with HPD upon single-agent ICI)

Abstract 15 Figure 3

Mature (CD10+) and immature (CD10-) LDNs in coculture with T-cells from an healthy donor differently influence CD8 and CD4 T-cells survival, proliferation, IFN-gamma production and expression of a senescent (CD28- CD57+) phenotype.

Abstract 15 Figure 4

Cisplatin in-vitro treatment at different concentration (1 uM and 5 uM) increases necrotic (7AAD expression) cell death preferentially of immature (CD10-) rather than mature (CD10+) LDNs

Conclusions

Higher baseline immature CD10- LDNs impair T-cell survival and promote T-cell senescence being a circulating biomarker of HPD upon single-agent ICI. The addition of PCT prevents HPD by inducing immature neutrophils cell death.

References

Ferrara R, Mezquita L, Texier M, Lahmar J, Audigier-Valette C, Tessonnier L, et al. Hyperprogressive disease in patients with advanced non-small cell lung cancer treated with pd-1/pd-l1 inhibitors or with single-agent chemotherapy. JAMA Oncol 2018;4:1543–52. https://doi.org/10.1001/jamaoncol.2018.3676

Kim Y, Kim CH, Lee HY, Lee S-H, Kim HS, Lee S, et al. Comprehensive clinical and genetic characterization of hyperprogression based on volumetry in advanced non-small cell lung cancer treated with immune checkpoint inhibitor. J Thorac Oncol 2019;14:1608–18. https://doi.org/10.1016/j.jtho.2019.05.033

Ferrara R, Naigeon M, Auclin E, Duchemann B, Cassard L, Jouniaux JM, et al. Circulating T-cell immunosenescence in advanced non-small cell lung cancer patients treated with single agent PD-1/PD-L1 inhibitors or platinum-based chemotherapy. Clin Cancer Res 2020. https://doi.org/10.1158/1078-0432.CCR-20-1420.

Ethics Approval

Patients blood was obtained after signature of informed consent and within an observational prospective study (INT 22_15) approved by local Institutional Ethical Committee.

Immune-Checkpoint Inhibitors in Advanced Non-Small Cell Lung Cancer With Uncommon Histology

BACKGROUND

Immune-checkpoint inhibitors (ICIs) have significantly improved outcome of advanced non-small cell lung cancer (aNSCLC) patients. However, their efficacy remains uncertain in uncommon histologies (UH).

MATERIALS AND METHODS

Data from ICI treated aNSCLC patients (April,2013-January,2021) in one Institution were retrospectively collected. Univariate and multivariate survival analyses were estimated by Kaplan-Meier and Cox proportional hazards regression model, respectively. Objective response rate (ORR) and disease control rate (DCR) were assessed.

RESULTS

Of 375 patients, 79 (21.1%) had UH: 19 (24.1%) sarcomatoid carcinoma, 15 (19.0%) mucinous adenocarcinoma, 10 (12.6%) enteric adenocarcinoma, 8 (10.1%) adenocarcinoma not otherwise specified, 7 (8.9%) large-cell neuroendocrine carcinoma, 6 (7.6%) mixed histology non-adenosquamous, 5 (6.3%) adenosquamous carcinoma, 9 (11.4%) other UH. In UH group, programmed death-ligand 1 (PD-L1) <1%, 1-49%, ≥50% and unknown expression were reported in 27.8%, 22.8%, 31.7% and 17.7% patients respectively and ICI was the second/further-line in the majority of patients. After a median follow-up of 35.64 months (m), median progression-free survival (mPFS) was 2.5 m in UH [95% CI 2.2-2.9 m] versus (vs.) 2.7 m in CH [95% CI 2.3-3.2 m, P-value = .584]; median overall survival (mOS) was 8.8 m [95% CI 4.9-12.6 m] vs. 9.7 m [95% CI 8.0-11.3 m, P-value = .653]. At multivariate analyses only ECOG PS was a confirmed prognostic factor in UH. ORR and DCR were 25.3% and 40.5% in UH vs. 21.6% and 49.5% in CH [P-value = .493 and .155 respectively].

CONCLUSIONS

No significant differences were detected between UH and CH groups. Prospective trials are needed to understand ICIs role in UH population.

Abstract 1669: Immunometabolism of circulating neutrophils in hyperprogressive disease (HPD) upon first-line PD-1/PD-L1 inhibitors (ICI) alone or in combination with platinum-based chemotherapy (PCT) in non-small cell lung cancer (NSCLC) patients (pts)

Background: HPD has been described in 14-26% of NSCLC pts upon single agent ICI and correlates with poor survival. Currently, HPD occurrence has not been explored upon ICI-PCT and biomarkers of HPD are lacking. Although high circulating neutrophils (Ns) correlated with HPD in NSCLC pts, the role of specific Ns subsets is unknown.

Methods: NSCLC pts treated with 1st line ICI as single agent or in combination with PCT were assessed for HPD and circulating Ns' phenotype. Tumor response was evaluated by RECIST 1.1. HPD required 3 assessment (2 before ICI, 1 upon ICI) and was defined as delta tumor growth rate (TGR) (TGR upon ICI - TGR before ICI) &gt;50% and/or TGR ratio (TGR upon ICI/TGR before ICI) ≥2. Circulating low density Ns (LDNs) subtypes were assessed by flow cytometry (FC) on peripheral blood mononuclear cells (PBMCs). LDNs were defined as CD66b+CD15+ cells among CD11b+ PBMCs. Immature subtypes were defined as CD10- LDNs. Fatty acids (FA) (bodipy-palmitate) uptake was assessed by FC. T-cells of healthy donors were isolated and activated in vitro with CD3/CD28 beads in presence or not of pts' Ns to characterize their interplay.

Results: Of 63 NSCLC pts, 22% had PD-L1 on tumor cells ≥50%. In the ICI single agent cohort (N=46), PD and HPD occurred in 21 (41%) and 4 (9%) pts, respectively. Before ICI start, HPD pts had significantly higher median percentage (%) of circulating immature CD10- LDNs [43.5 (min 29.5; max 82.6) vs 10.3 (min 0.1; max 79.4), p=0.01] compared to PD pts. In the ICI-PCT cohort (N=17), PD occurred in 4 (23%) pts, no HPD was reported. 5 pts had baseline CD10- LDNs ≥ 43.5% (median % of CD10- LDNs in HPD pts upon single agent ICI), 2 of them had SD and 3 PD upon ICI-PCT. In these 5 pts, CD10- LDNs significantly decreased during ICI-PCT compared to what observed in HPD pts during single agent ICI [median variation -43.4 (min -67.6, max -31.6) vs +6.9 (min -33, max +44), p= 0.03]. CD10- LDNs did not impair T-cells proliferation and IFNγ production, measured after 7 days of coculture but significantly reduced T-cell survival compared to CD10+LDNs. Baseline metabolic profile assessment showed that immature CD10- LDNs had a predominant lipid metabolism with a higher FA uptake [bodipy-palmitate mean florescence intensity (MFI) ± standard deviation (SD): 46754±11562] compared to lymphocytes [bodipy-palmitate MFI ±SD: 11542±405].

Conclusion: Higher baseline immature CD10- LDNs is a circulating biomarker of HPD upon single agent ICI. The addition of PCT prevents HPD reducing the immature Ns subset. The FA metabolism of immature LDNs does not affect T-cells proliferation/activation but reduces T-cells survival, suggesting that these two processes are differently regulated and that immature Ns reduce T-cells life span by metabolic competition.

Citation Format: Roberto Ferrara, Elena Jachetti, Giuseppina Calareso, Marta Brambilla, Giuseppe Lo Russo, Claudia Proto, Arsela Prelaj, Diego Signorelli, Giulia Galli, Alessandro De Toma, Mario Occhipinti, Sara Manglaviti, Alice Labianca, Monica Ganzinelli, Sestina Maria Spanò, Giuliano Molino, Antonia Martinetti, Francesca Gabriella Greco, Marta Bini, Teresa Beninato, Filippo de Braud, Mario Paolo Colombo, Marina Chiara Garassino, Sabrina Sangaletti. Immunometabolism of circulating neutrophils in hyperprogressive disease (HPD) upon first-line PD-1/PD-L1 inhibitors (ICI) alone or in combination with platinum-based chemotherapy (PCT) in non-small cell lung cancer (NSCLC) patients (pts) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1669.

Exploring the role of respiratory microbiome in lung cancer: A systematic review

Giving the potential contribute in cancer initiation and progression, lung microbiota represents a promising topic in cancer research, although still unexplored. We performed a systematic literature search to identify clinical studies evaluating lung microbiota composition, its correlation with lung cancer patients' clinico-pathological features and prognosis. Of the identified 370 studies, 21 were eligible and included. Although studies were heterogeneous, lung cancer resulted to be enriched in peculiar microbial communities, with differences in composition and diversity according to clinico-pathological parameters. Few studies explored how lung microbiota influences cancer outcome. In light of these findings and borrowing the suggestions coming from gut microbiota, we speculate that respiratory microbiome may influence pathogenesis, progression and outcome of lung cancer. Taking advantage of the experience of chronical lung diseases, prospective studies should be designed to evaluate lung microbiota changes throughout any phase of lung cancer course, particularly with the advent of immunotherapy as pivotal treatment.