Immunotherapy In Lung Cancer Patients Research Articles

Symptom clusters and symptom network analysis during immunotherapy in lung cancer patients.

This study analyzes symptoms in lung cancer patients undergoing immunotherapy to identify core symptom clusters through network analysis and lay a foundation for effective symptom management programs. The sample comprised 240 lung cancer patients receiving immunotherapy. Participants were assessed using the Memorial Symptom Assessment Scale. Exploratory factor analysis was used to extract symptom clusters, and network analysis using JASP 0.17.3 was performed to explore the centrality indices and density of the symptom network. Five symptom clusters were identified, i.e., emotion-related, lung cancer-related, physical, skin, and neural symptom clusters, with a cumulative variance contribution rate of 55.819%. Network analysis revealed that sadness was the most intense symptom (rs = 2.189), dizziness was the most central symptom (rc = 1.388), and fatigue was the most significant bridging symptom (rb = 2.575). This study identified five symptom clusters and a symptom network among lung cancer patients during immunotherapy. The network analysis's centrality indices and network density results can assist healthcare professionals in devising more precise symptom management strategies.

Abstract LB445: USP24 suppresses T cell anti-tumor activity by enhancing the stability of the PD-1 protein

Abstract Persistent programmed cell death-1 (PD-1)/PD-L1 inhibitory signaling disrupts T cell cytotoxic function, leading to T cell exhaustion—a phenomenon strongly associated with advanced cancer progression and immunotherapy failure. Deciphering the mechanisms behind dysregulated PD-1 expression and reactivating tumor-infiltrating lymphocytes (TILs) in the tumor microenvironment (TME) is crucial. Our previous research established that tumor-associated macrophage-derived IL-6 promotes STAT3-dependent PD-1 transcriptional activity and immunotherapy resistance. The current study further explores whether IL-6 abundance in the TME contributes to PD-1 protein stability. Results indicate that IL-6 extended PD-1 protein half-life in T cells, suggesting its role in modulating PD-1 protein stability. Furthermore, analysis of the GEO database showed a positive correlation between the expression of ubiquitin-specific-processing protease (USP) family enzymes and PD-1 in non-responding patients receiving anti-PD-1 therapy. Knockdown experiments revealed that USP24 strongly downregulated PD-1 protein expression and stability. USP24 depletion reversed IL-6-induced PD-1 expression and stability, with USP24 colocalizing with PD-1 at the plasma membrane upon IL-6 stimulation. Immunoprecipitation-Western blot assays confirmed that USP24 directly interacted with PD-1 and countered E3 ligase c-Cbl-mediated ubiquitination. Depleting USP24 suppressed PD-1-mediated immunosuppression both in vitro and in vivo. In lung-specific EGFRL858R/USP24C1698A functional knockout mice, tumor progression was slower, and exhausted tumor-infiltrating PD-1+ TIM-3+ CD8+ T cells reduced compared to EGFRL858R mice. Inhibiting PD-1 stability with an IL-6 neutralizing antibody or the novel inhibitor USP24-i-101 decreased tumor volume and increased activated cytotoxic T cell infiltration in vivo. Moreover, USP24-i-101 enhanced therapeutic effects in combination with anti-CTLA4 immunotherapy. Clinically, our in-house cohort revealed elevated USP24 expression in tumor-infiltrating lymphocytes or peripheral T cells, correlating with worse clinical outcomes and unfavorable responses to immunotherapy in lung cancer patients. This study uncovers USP24 as a novel PD-1 regulator, deubiquitinating PD-1 to enhance protein stability and suppress T cell function. In conclusion, USP24 emerges as a potential target for enhancing anti-tumor immunity and as a biomarker predicting clinical responses to immunotherapy in lung cancer. Citation Format: Hung-Chia Hsieh, Jan-Jong Hung, Yi-Ching Wang. USP24 suppresses T cell anti-tumor activity by enhancing the stability of the PD-1 protein [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB445.

Global bibliometric mapping of the research trends in artificial intelligence-based digital pathology for lung cancer over the past two decades.

The rapid development of computer technology has led to a revolutionary transformation in artificial intelligence (AI)-assisted healthcare. The integration of whole-slide imaging technology with AI algorithms has facilitated the development of digital pathology for lung cancer (LC). However, there is a lack of comprehensive scientometric analysis in this field. A bibliometric analysis was conducted on 197 publications related to digital pathology in LC from 502 institutions across 39 countries, published in 97 academic journals in the Web of Science Core Collection between 2004 and 2023. Our analysis has identified the United States and China as the primary research nations in the field of digital pathology in LC. However, it is important to note that the current research primarily consists of independent studies among countries, emphasizing the necessity of strengthening academic collaboration and data sharing between nations. The current focus and challenge of research related to digital pathology in LC lie in enhancing the accuracy of classification and prediction through improved deep learning algorithms. The integration of multi-omics studies presents a promising future research direction. Additionally, researchers are increasingly exploring the application of digital pathology in immunotherapy for LC patients. In conclusion, this study provides a comprehensive knowledge framework for digital pathology in LC, highlighting research trends, hotspots, and gaps in this field. It also provides a theoretical basis for the application of AI in clinical decision-making for LC patients.

Effect of baseline cancer pain on the efficacy of immunotherapy in lung cancer patients.

Cancer pain is a common symptom in cancer patients. However, few reports have evaluated the effect of baseline cancer pain on the efficacy of immunotherapy in lung cancer patients. The aim of this retrospective study is to reveal the effect of baseline cancer pain on the prognosis of lung cancer patients receiving immunotherapy. We retrospectively reviewed the medical records of lung cancer patients who received immunotherapy at Zhejiang Cancer Hospital and were included 280 patients with or without baseline cancer pain. Propensity score matching (PSM) was used to minimize potential selection bias. Progression-free survival (PFS) and overall survival (OS) were assessed using Kaplan-Meier estimation and log-rank tests. Cox proportional hazard regression analysis was performed to identify factors associated with survival independence. The median PFS and OS of the patients with baseline cancer pain were significantly shorter than that of patients without baseline cancer pain (PFS: 3.1 vs. 6.5 months, P=0.001; OS: 16.5 vs. 31.2 months, P<0.001). PSM also included 27 patients with or without breakthrough pain. Patients with breakthrough pain had significantly shorter median PFS and OS than those without breakthrough pain (PFS: 1.9 vs. 4.2 months, P=0.001; OS: 9.9 vs. 18.7 months, P=0.012). Cox analysis results implicated breakthrough pain as an independent prognostic factor for immunotherapy. Baseline cancer pain is a negative prognostic factor for lung cancer patients receiving immunotherapy. Patients with baseline cancer pain may have a worse survival prognosis if they develop breakthrough pain.

Cancer Cell-Intrinsic Alterations Associated with an Immunosuppressive Tumor Microenvironment and Resistance to Immunotherapy in Lung Cancer.

Despite the great clinical success of immunotherapy in lung cancer patients, only a small percentage of them (<40%) will benefit from this therapy alone or combined with other strategies. Cancer cell-intrinsic and cell-extrinsic mechanisms have been associated with a lack of response to immunotherapy. The present study is focused on cancer cell-intrinsic genetic, epigenetic, transcriptomic and metabolic alterations that reshape the tumor microenvironment (TME) and determine response or refractoriness to immune checkpoint inhibitors (ICIs). Mutations in KRAS, SKT11(LKB1), KEAP1 and TP53 and co-mutations of these genes are the main determinants of ICI response in non-small-cell lung cancer (NSCLC) patients. Recent insights into metabolic changes in cancer cells that impose restrictions on cytotoxic T cells and the efficacy of ICIs indicate that targeting such metabolic restrictions may favor therapeutic responses. Other emerging pathways for therapeutic interventions include epigenetic modulators and DNA damage repair (DDR) pathways, especially in small-cell lung cancer (SCLC). Therefore, the many potential pathways for enhancing the effect of ICIs suggest that, in a few years, we will have much more personalized medicine for lung cancer patients treated with immunotherapy. Such strategies could include vaccines and chimeric antigen receptor (CAR) cells.

Inhibition of distinct glycolytic enzymes produces differential effects on CD4 T cell function

Abstract Introduction: When T cells are activated, they upregulate glycolysis and take on a requisite Warburg phenotype. In this study, we evaluated the effect of inhibiting two distinct glycolytic enzymes, GAPDH and PGAM, on CD4 T cell differentiation. Methods/Results: Using the GAPDH inhibitor heptelidic acid, we found that GAPDH inhibition produces a potent anti-inflammatory phenotype in Th1 cells, significantly reducing IFNγ expression. We further showed that GAPDH inhibition produces the anti-inflammatory metabolite methylglyoxal, which is necessary for its anti-inflammatory effect. GAPDH inhibition also produced anti-inflammatory effects in vivo, as heptelidic acid significantly reduced disease severity and altered immune subsets in a therapeutic treatment paradigm in the MOG 35–55EAE model of multiple sclerosis. Furthermore, we showed that GAPDH inhibition enhances Treg polarization, while inhibiting PGAM, a downstream glycolytic enzyme, potently blocked Treg polarization. Additionally, we found that inhibition of PGAM increases serine biosynthesis and subsequently alters 1-carbon metabolism. We also found that PGAM gene expression is associated with Treg differentiation and response to immunotherapy in lung cancer patients. Conclusion: Overall, our in vitroand in vivoresults indicate that targeting the glycolytic enzyme GAPDH produces an anti-inflammatory phenotype via the methylglyoxal pathway, while targeting the downstream enzyme PGAM produces an opposite effect via regulation of serine synthesis. Our findings suggest that the functional consequences of glycolysis inhibition depend on the specific enzymes targeted, which represent promising novel therapeutic targets for immunological disease. This work was supported by NIH/NINDS grant K08NS104266 and Conrad N. Hilton Foundation Marilyn Hilton Bridging Award for Physician Scientists grant 17316 to MDK. WHG was supported by NIH MSTP Grant T32 GM136577 and the American Association of Immunologists’ Careers in Immunology Fellowship Program.

Promising immunotherapeutic targets in lung cancer based on single-cell RNA sequencing.

Immunotherapy has made great strides in the treatment of lung cancer, but a significant proportion of patients still do not respond to treatment. Therefore, the identification of novel targets is crucial to improving the response to immunotherapy. The tumor microenvironment (TME) is a complex niche composed of diverse pro-tumor molecules and cell populations, making the function and mechanism of a unique cell subset difficult to understand. However, the advent of single-cell RNA sequencing (scRNA-seq) technology has made it possible to identify cellular markers and understand their potential functions and mechanisms in the TME. In this review, we highlight recent advances emerging from scRNA-seq studies in lung cancer, with a particular focus on stromal cells. We elucidate the cellular developmental trajectory, phenotypic remodeling, and cell interactions during tumor progression. Our review proposes predictive biomarkers and novel targets for lung cancer immunotherapy based on cellular markers identified through scRNA-seq. The identification of novel targets could help improve the response to immunotherapy. The use of scRNA-seq technology could provide new strategies to understand the TME and develop personalized immunotherapy for lung cancer patients.

Ginsenosides, potential TMPRSS2 inhibitors, a trade-off between the therapeutic combination for anti-PD-1 immunotherapy and the treatment of COVID-19 infection of LUAD patients.

Background: Acting as a viral entry for coronavirus to invade human cells, TMPRSS2 has become a target for the prevention and treatment of COVID-19 infection. Before this, TMPRSS2 has presented biological functions in cancer, but the roles remain controversial and the mechanism remains unelucidated. Some chemicals have been reported to be inhibitors of TMPRSS2 and also demonstrated other pharmacological properties. At this stage, it is important to discover more new compounds targeting TMPRSS2, especially from natural products, for the prevention and treatment of COVID-19 infection. Methods: We analyzed the correlation between TMPRSS2 expression, methylation level, overall survival rate, clinical parameters, biological process, and determined the correlation between TMPRSS2 and tumor-infiltrating lymphocytes in the tumor and adjacent normal tissue of adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC) respectively by using various types of bioinformatics approaches. Moreover, we determined the correlation between TMPRSS2 protein level and the prognosis of LUAD and LUSC cohorts by immunohistochemistry assay. Furthermore, the cancer immunome atlas (TCIA) database was used to predict the relationship between the expression of TMPRSS2 and response to programmed cell death protein 1 (PD-1) blocker immunotherapy in lung cancer patients. Finally, the putative binding site of ginsenosides bound to TMPRSS2 protein was built from homology modeling to screen high-potency TMPRSS2 inhibitors. Results: We found that TMPRSS2 recruits various types of immunocytes, including CD8+, CD4+ T cells, B cells and DCs both in LUAD and LUSC patients, and the correlation between TMPRSS2 expression and CD8+ and CD4+ T cells are stronger in LUAD rather than in LUSC, but excludes macrophages and neutrophils in LUAD patient cohorts. These might be the reason that higher mRNA and protein levels of TMPRSS2 are associated with better prognosis in LUAD cohorts rather than in LUSC cohorts. Furthermore, we found that TMPRSS2 was positively correlated with the prognosis in patient nonresponse to anti-PD-1 therapy. Therefore, we made an inference that increasing the expression level of TMPRSS2 may improve the anti-PD-1 immunotherapy efficacy. Finally, five ginsenosides candidates with high inhibition potency were screened from the natural chemical library to be used as TMPRSS2 inhibitors. Conclusion: All these may imply that TMPRSS2 might be a novel prognostic biomarker and serve as a potential immunomodulator target of immunotherapy combination therapies in LUAD patients nonresponse to anti-PD-1 therapy. Also, these findings may suggest we should pay more attention to LUAD patients, especially those infected with COVID-19, who should avoid medicating TMPRSS2 inhibitors, such as ginsenosides to gain prophylactic and therapeutic benefits against COVID-19.

Advances in the Study of Tissue-resident Memory T Cells in Lung Cancer

Immune checkpoint inhibitors (ICIs) have been widely used in the treatment of lung cancer, but the benefit population is limited and there is a lack of effective predictive markers of efficacy. Tissue-resident memory T cells (TRM) reside in tissues and exert anti-tumor effects by expressing the integrins CD103, CD49a or C-type lectin CD69 and immune checkpoint receptors. TRM expressing programmed cell death 1 (PD-1) is enriched with transcriptional products associated with cytotoxicity and enhances T cell (antigen) receptor (TCR)-mediated cytotoxicity. TRM is a promising biomarker for predicting the efficacy and prognosis of immunotherapy in lung cancer patients. This review will describe the progress of TRM research in lung cancer. .

Onco-biome in pharmacotherapy for lung cancer: a narrative review

The gut microbiota (GM) was recently recognized to play an important role in modulating systemic immune responses and is known to influence the effects or adverse events of immune checkpoint blockade (ICB) or carcinogenesis by crosstalk with regulators of cancer-related immunity, and this relationship is complex and multifactorial. Diversity in the gut microbiome and the abundance of specific bacterial species have been identified to be associated with better response and prognosis. Therefore, the purpose of the current interest in the gut microbiome is to enable modulation of the immune system in donor cancer patients by the administration of specific bacterial species and enabling their dominance. To understand this "terra incognita" is to uncover the role of the mechanisms underlying unknown organ functions, and this knowledge will lead to enhanced immunotherapy for lung cancer patients. In this article, we summarized the literature on the relationship between the microbiome and lung cancer and the potential of the microbiome as a therapeutic target. This article is organized into the following sections: introduction, methods, microbiota and cancer development, microbiota and lung cancer treatment, future directions, and conclusion. The gut microbiome is currently becoming the hallmark of cancer research and has an established and critical role in regulating antitumor immunity and the response to ICB in patients with lung cancers.

Applicability analysis of immunotherapy for lung cancer patients based on deep learning

According to global and Chinese cancer statistics, lung cancer is the second most common cancer globally with the highest mortality rate and a severe threat to human life and health. In recent years, immunotherapy has made significant breakthroughs in the treatment of cancer patients. However, only 30% of patients are applicable and may have immune-related adverse events. The traditional immunological inspection methods have limitations and often can not obtain the expected benefits. Deep learning is a typical representation learning method that can spontaneously mine the hidden feature of effective classification from seas of data. In order to alleviate medical resources and reduce costs, this paper proposes a deep learning-based method to predict patients best suited for immune checkpoint blocking therapy from patients CT images. The deep immunotherapy analysis method proposed in this paper is divided into three steps:(1) Using LUNA16 public dataset to develop a deep learning model for nodule detection. (2) Nodule detection was performed on the Anti-PD-1_Lung dataset, and the effectiveness of immunotherapy was determined by comparing the detection results of nodules before and after immunotherapy. (3) After the data set was processed, the deep learning method trained and analyzed the Lung images. According to the experimental results and comparative analysis, the proposed deep immunotherapy analysis method has a good performance in the detection of nodules. It works for the predictions for the applicability of immunotherapy for lung cancer.1.

EP07.01-011 Integrating PD-L1 Expression to the CALGB Prognostic Scoring System in Malignant Pleural Mesothelioma

Programmed death ligand-1 (PD-L1) expression is a predictive biomarker guiding treatment decisions with immunotherapy in lung cancer patients, but its role in malignant pleural mesothelioma (MPM) is unclear. However, evidence suggests that higher PDL-1 expression correlates with worse survival outcomes. The Cancer and Leukemia Group B (CALGB) prognostic scoring system is widely used to define prognosis in MPM. This study aims to assess the prognostic value of PDL-1 expression integrating it into the CALGB scoring system.

Smoking signature is superior to programmed death-ligand 1 expression in predicting pathological response to neoadjuvant immunotherapy in lung cancer patients.

BackgroundThere is a paucity of biomarkers that can predict the degree of pathological response [e.g., pathological complete response (pCR) or major response (pMR)] to immunotherapy. Neoadjuvant immunotherapy provides an ideal setting for exploring responsive biomarkers because the pathological responses can be directly and accurately evaluated.MethodsWe retrospectively collected the clinicopathological characteristics and treatment outcomes of non-small cell lung cancer (NSCLC) patients who received neoadjuvant immunotherapy or chemo-immunotherapy followed by surgery between 2018 and 2020 at a large academic thoracic cancer center. Clinicopathological factors associated with pathological response were analyzed.ResultsA total of 39 patients (35 males and 4 females) were included. The most common histological subtype was lung squamous cell carcinoma (LUSC) (n=28, 71.8%), followed by lung adenocarcinoma (LUAD) (n=11, 28.2%). After neoadjuvant treatment, computed tomography (CT) scan-based evaluation showed poor agreement with the postoperatively pathological examination (weighted kappa =0.0225; P=0.795), suggesting the poor performance of CT scans in evaluating the response to immunotherapy. Importantly, we found that the smoking signature displayed a better performance than programmed death-ligand 1 (PD-L1) expression in predicting the pathological response (area under the curve: 0.690 vs. 0.456; P=0.0259), which might have resulted from increased tumor mutational burden (TMB) and/or microsatellite instability (MSI) relating to smoking exposure.ConclusionsThese findings suggest that CT scan-based evaluation is not able to accurately reflect the pathological response to immunotherapy and that smoking signature is a superior marker to PD-L1 expression in predicting the benefit of immunotherapy in NSCLC patients.

TNFα and Immune Checkpoint Inhibition: Friend or Foe for Lung Cancer?

Tumor necrosis factor-alpha (TNFα) can bind two distinct receptors (TNFR1/2). The transmembrane form (tmTNFα) preferentially binds to TNFR2. Upon tmTNFα cleavage by the TNF-alpha-converting enzyme (TACE), its soluble (sTNFα) form is released with higher affinity for TNFR1. This assortment empowers TNFα with a plethora of opposing roles in the processes of tumor cell survival (and apoptosis) and anti-tumor immune stimulation (and suppression), in addition to angiogenesis and metastases. Its functions and biomarker potential to predict cancer progression and response to immunotherapy are reviewed here, with a focus on lung cancer. By mining existing sequencing data, we further demonstrate that the expression levels of TNF and TACE are significantly decreased in lung adenocarcinoma patients, while the TNFR1/TNFR2 balance are increased. We conclude that the biomarker potential of TNFα alone will most likely not provide conclusive findings, but that TACE could have a key role along with the delicate balance of sTNFα/tmTNFα as well as TNFR1/TNFR2, hence stressing the importance of more research into the potential of rationalized treatments that combine TNFα pathway modulators with immunotherapy for lung cancer patients.

P66.04 Real World Data: Immunotherapy in Lung Cancer Patients over 65 Years Old in Spain

In the last decade, immunotherapy (IT) has become a key therapeutic tool in lung cancer treatment. The number of elderly patients with this pathology in Spain has been progressively increased in recent years, becoming a representative subgroup nowadays. Studies carried out with IT in these patients are a minority and controversial, generating a need in clinical practice. The aim of the study is to establish clinical and toxicity differences between patients older and younger than 65 years, treated with IT. Retrospective study that includes all epidemiological, clinical and pathological data of patients > 65 and <65 years diagnosed with lung cancer at Puerta de Hierro Hospital from January 2014 to March 2020, and who received treatment with IT, either in the first line or successive. A total of 155 patients were analyzed. Table 1 summarizes the main characteristics between both populations. The mean number of treatments received in both groups was similar (3.0 in <65 years vs 2.7 in> 65). When both groups were compared, no statistically significant differences in the percentage of patients who needed to interrupt IT due to toxicity were observed, being 15.9% of those <65 years and 17.9% of those> 65 years (p = 0.576) who required this interruption. There were also no differences in toxicity between grade 3 or 4 (10.2% vs 10.4%, p = 0.99) or in the number of admissions due to immune-related toxicity (IR) (9.0% vs 4.5%, p = 0.19). Neither group required immunosuppressive treatment for severe toxicity, but they did require steroids at high doses. There were no deaths secondary to IT toxicity, being the majority due to disease progression.Table 1Characteristics<65 years (88)>65 years (67)Gender Male Woman54.5% 45.6%74.6% 25.4%Median age5872ECOG 0-1 ≥293.2% 4.5%97.0% 3.0%Charlson index810StageI – 3.4% II – 6.8% III - 33.0% IV – 56.8%I – 3.0% II – 11.9% III – 23.9% IV – 61.2%Histology Adenocarcinoma Squamous cell carcinoma Small cell Others59.1% 27.3% 2.3% 11.4%56.7% 25.4% 4.5% 13.4%PDL-1 Positive Negative Unknown29.5% 9.1% 13.6%32.8% 16.4% 7.5%Disease situation at the toxicity moment Complete response Partial response Stable disease Progression8.2% 13.7% 20.5% 47.9%1.6% 27.9% 23.0% 32.8%Toxicity types Asthenia Anemia Pneumonitis Thyroid disorders Cutaneous Colitis Nephritis Hepatitis Others11.4% 1.1% 14.8% 10.2% 9.1% 6.8% 0% 3.4% 13.6%13.4% 0% 11.9% 11.9% 9.0% 4.5% 4.5% 1.5% 9.0%Toxicity grade 1 2 3 417.0% 6.8% 5.7% 3.4%14.9% 13.4% 8.9% 1.5% Open table in a new tab Patients > 65 years with lung cancer who received IT treatment in our center do not experience more serious adverse events, do not require more treatment interruptions or more admissions, compared to those <65 years. Consequently, IT should be a valid treatment option in this population and its management should be optimized, with the aim of offering the best possible quality of care to this subgroup of patients.

Safety and efficacy of immune checkpoint inhibitors in non-small-cell lung cancer: focus on challenging populations.

In recent years, immune-checkpoint inhibitors (ICIs) have represented one of the major breakthroughs in advanced non-small cell lung cancer treatment scenario. However, enrollment in registering clinical trials is usually restricted, since frail patients (i.e., elderly, individuals with poor performance status and/or active brain metastases), as well as patients with chronic infections or who take concurrent medications, such as steroids, are routinely excluded. Thus, safety and efficacy of ICIs for these subgroups have not been adequately assessed in clinical trials, although these populations often occur in clinical practice. We reviewed the available data regarding the use of ICIs in these 'special' populations, including a focus on the issues raised by the administration of immunotherapy in lung cancer patients infected with Sars-Cov-2.

Acquired Resistance to PD-1/PD-L1 Blockade in Lung Cancer: Mechanisms and Patterns of Failure.

Simple SummaryAcquired resistance to immunotherapy is an emerging issue, especially as the indications for immunotherapy expand to many different solid tumor malignancies. This review attempts to summarize the mechanisms and clinical outcomes of acquired resistance in non-small-cell lung cancers and explores future directions for research to understand and address this important question.Immunotherapy is now the preferred treatment for most lung cancer patients. It is used to treat unresectable stage III non-small-cell lung cancer and is the first-line therapy for non-oncogene-driven advanced/metastatic non-small-cell lung cancer patients (either alone or in combination with chemotherapy). Unfortunately, most patients that respond initially to immunotherapy develop resistance over time, thus limiting the durability of immunotherapy. A better understanding of the mechanisms of acquired resistance is urgently needed to expand the benefit of immunotherapy in lung cancer patients. This review aims to summarize the mechanisms and clinical outcomes of acquired resistance of anti-PD-1/PD-L1 therapies in non-small-cell lung cancer patients.

PET/CT and the Response to Immunotherapy in Lung Cancer.

ObjectiveIn recent years, the introduction of immune checkpoint inhibitors has significantly changed the outcome of patients affected by lung cancer and cutaneous melanoma. Although the clinical advantages, the selection of patients and the evaluation of response to immunotherapy remain unclear, the immune-related Response Evaluation Criteria in Solid Tumor (irRECIST) was proposed as an update of the RECIST criteria for the assessment of response to immunotherapy. However, morphological images cannot predict early response to therapy that represents a challenge in clinical practice. 18F-FDG PET/CT before and after immunotherapy has an indeterminate role, demonstrating ambiguous results due to inflammatory effects secondary to activation of the immune system. The aim of the present review was to analyze the role of PET/CT as a guide for immunotherapy, by analyzing the current status and future perspectives.MethodsA literature search was conducted in order to select all papers that discussed the role of PET/CT with FDG or other tracers in the evaluation or prediction of response to immunotherapy in lung cancer patients.ResultsMany papers are now available. Many clinical trials have demonstrated the efficacy of immunotherapy in lung cancer patients. FDG PET/CT can be used for the prediction of response to immunotherapy, while its utility for the evaluation of response is not still clearly reported. Moreover, the standardization of FDG PET/CT interpretation is missing and different criteria, such as information, have been investigated until now.ConclusionThe utility of FDG PET/CT for patients with lung cancer undergoing immunotherapies is still preliminary and not well addressed. New agents for PET are promising, but large clinical trials are mandatory.

117 - An audit to investigate initial experience with immunotherapy for lung cancer patients at West Suffolk Hospital

117 - An audit to investigate initial experience with immunotherapy for lung cancer patients at West Suffolk Hospital

P1.04-16 Early Antibiotic Use Affects the Efficacy of First Line Immunotherapy in Lung Cancer Patients but Route of Administration Seems to be Decisive

P1.04-16 Early Antibiotic Use Affects the Efficacy of First Line Immunotherapy in Lung Cancer Patients but Route of Administration Seems to be Decisive