Association Between PD-L1 Expression and Metabolic Activity on 18F-FDG PET/CT in Patients with Small-sized Lung Cancer

Application of Aptamer-SERS Nanotags for Unveiling the PD-L1 Immunomarker Progression Correlated to the Cell Metabolic Bioprocess

In recent years, the expression and progression of programmed cell death ligand 1 (PD-L1) as an immunomarker in the context of a cell metabolic environment has gained significant attention in cancer research. However, intercellular bioprocesses that control the dynamics of PD-L1 have been largely unexplored. This study aimed to explore the cell metabolic states and conditions that govern dynamic variations of PD-L1 within the cell metabolic environment using an aptamer-based surface-enhanced Raman scattering (SERS) approach. The aptamer-SERS technique offers a sensitive, rapid, and powerful analytical tool for targeted and nondestructive detection of an immunomarker with high sensitivity and specificity. By combining aptamer-SERS with cell state profiling, we investigated the modulation in PD-L1 expression under different metabolic states, including glucose deprivation, metabolic coenzyme activity, and altered time/concentration-based cytokine availability. The most intriguing features in our findings include the cell-specific responses, cell differentiation by revealing distinct patterns, and dynamics of PD-L1 in different cell lines. Additionally, the time-dependent variations in PD-L1 expression, coupled with the dose-dependent relationship between glucose concentration and PD-L1 levels, underscore the complex interplay between immune checkpoint regulation and cellular metabolism. Therefore, this work demonstrates the advantages of using highly-sensitive and specific aptamer-SERS nanotags for investigating the immune checkpoint dynamics and related metabolic bioprocess.

Similarities and divergences in the metabolism of immune cells in cancer and helminthic infections

Energetic and nutritional requirements play a crucial role in shaping the immune cells that infiltrate tumor and parasite infection sites. The dynamic interaction between immune cells and the microenvironment, whether in the context of tumor or helminth infection, is essential for understanding the mechanisms of immunological polarization and developing strategies to manipulate them in order to promote a functional and efficient immune response that could aid in the treatment of these conditions. In this review, we present an overview of the immune response triggered during tumorigenesis and establishment of helminth infections, highlighting the transition to chronicity in both cases. We discuss the energetic demands of immune cells under normal conditions and in the presence of tumors and helminths. Additionally, we compare the metabolic changes that occur in the tumor microenvironment and the infection site, emphasizing the alterations that are induced to redirect the immune response, thereby promoting the survival of cancer cells or helminths. This emerging discipline provides valuable insights into disease pathogenesis. We also provide examples of novel strategies to enhance immune activity by targeting metabolic pathways that shape immune phenotypes, with the aim of achieving positive outcomes in cancer and helminth infections.

A novel association between Bmi-1 protein expression and the SUVmax obtained by 18F-FDG PET/CT in patients with gastric adenocarcinoma

This study aimed to examine B-cell-specific Moloney murine leukemia virus integration site 1 (Bmi-1) in gastric adenocarcinoma (GAC) and its association with the maximal standard uptake value (SUVmax) of preoperative fluorine-18-fludeoosyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT). Clinicopathological data were retrospectively collected from 60 primary GAC patients. The Bmi-1 protein expression in GAC and adjacent noncancerous tissues was examined by immunohistochemistry and western blot analysis. Pearson's correlation analysis was conducted to assess the correlation between Bmi-1 expression and the SUVmax. The Bmi-1 protein levels were significantly greater in GAC versus noncancerous tissues, and higher Bmi-1 was significantly correlated with a lower degree of tumor differentiation, higher tumor stages, more lymph node metastasis, and depth of invasion. The SUVmax value was significantly correlated with the T stage, N stage, and clinical stage, but not with age, gender, tumor size, histological differentiation degree, or Lauren classification. Moreover, a significant positive correlation between Bmi-1 and SUVmax was observed in GAC tissues. In conclusion, our findings demonstrate a novel correlation between Bmi-1 and preoperative SUVmax in GAC patients who did not receive radiotherapy, chemotherapy, or targeted treatment before surgery, and both are positively correlated with unfavorable prognostic factors and a higher grade of malignancy.

Prognostic value of 18F-FDG PET/CT in patients with advanced or metastatic non-small-cell lung cancer treated with immune checkpoint inhibitors: A systematic review and meta-analysis

PURPOSE

This study aimed to investigate the value of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) in predicting early immunotherapy response of immune checkpoint inhibitors (ICIs) in patients with advanced or metastatic non-small-cell lung cancer (NSCLC).

METHODS

A comprehensive search of PubMed, Web of science, Embase and the Cochrane library was performed to examine the prognostic value of 18F-FDG PET/CT in predicting early immunotherapy response of ICIs in patients with NSCLC. The main outcomes for evaluation were overall survival (OS) and progression-free survival (PFS). Detailed data from each study were extracted and analyzed using STATA 14.0 software.

RESULTS

13 eligible articles were included in this systematic review. Compared to baseline 18F-FDG PET/CT imaging, the pooled hazard ratios (HR) of maximum and mean standardized uptake values SUVmax, SUVmean, MTV and TLG for OS were 0.88 (95% CI: 0.69-1.12), 0.79 (95% CI: 0.50-1.27), 2.10 (95% CI: 1.57-2.82) and 1.58 (95% CI: 1.03-2.44), respectively. The pooled HR of SUVmax, SUVmean, MTV and TLG for PFS were 1.06 (95% CI: 0.68-1.65), 0.66 (95% CI: 0.48-0.90), 1.50 (95% CI: 1.26-1.79), 1.27 (95% CI: 0.92-1.77), respectively. Subgroup analysis showed that high MTV group had shorter OS than low MTV group in both first line group (HR: 1.97, 95% CI: 1.39-2.79) and undefined line group (HR: 2.11, 95% CI: 1.61-2.77). High MTV group also showed a shorter PFS in first line group (HR: 1.85, 95% CI: 1.28-2.68), and low TLG group had a longer OS in undefined group (HR: 1.37, 95% CI: 1.00-1.86). No significant differences were in other subgroup analysis.

CONCLUSION

Baseline MTV and TLG may have predictive value and should be prospectively studied in clinical trials. Baseline SUVmax and SUVmean may not be appropriate prognostic markers in advanced or metastatic NSCLC patients treated with ICIs.

SYSTEMATIC REVIEW REGISTRATION

https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=323906, identifier CRD42022323906.

Tumor response assessment on imaging following immunotherapy

In recent years, various systemic immunotherapies have been developed for cancer treatment, such as monoclonal antibodies (mABs) directed against immune checkpoints (immune checkpoint inhibitors, ICIs), oncolytic viruses, cytokines, cancer vaccines, and adoptive cell transfer. While being estimated to be eligible in 38.5% of patients with metastatic solid or hematological tumors, ICIs, in particular, demonstrate durable disease control across many oncologic diseases (e.g., in melanoma, lung, bladder, renal, head, and neck cancers) and overall survival benefits. Due to their unique mechanisms of action based on T-cell activation, response to immunotherapies is characterized by different patterns, such as progression prior to treatment response (pseudoprogression), hyperprogression, and dissociated responses following treatment. Because these features are not encountered in the Response Evaluation Criteria in Solid Tumors version 1.1 (RECIST 1.1), which is the standard for response assessment in oncology, new criteria were defined for immunotherapies. The most important changes in these new morphologic criteria are, firstly, the requirement for confirmatory imaging examinations in case of progression, and secondly, the appearance of new lesions is not necessarily considered a progressive disease. Until today, five morphologic (immune-related response criteria (irRC), immune-related RECIST (irRECIST), immune RECIST (iRECIST), immune-modified RECIST (imRECIST), and intra-tumoral RECIST (itRECIST)) criteria have been developed to accurately assess changes in target lesion sizes, taking into account the specific response patterns after immunotherapy. In addition to morphologic response criteria, 2-deoxy-2-[18F]fluoro-D-glucose positron emission tomography/computed tomography (18F-FDG-PET/CT) is a promising option for metabolic response assessment and four metabolic criteria are used (PET/CT Criteria for Early Prediction of Response to Immune Checkpoint Inhibitor Therapy (PECRIT), PET Response Evaluation Criteria for Immunotherapy (PERCIMT), immunotherapy-modified PET Response Criteria in Solid Tumors (imPERCIST5), and immune PERCIST (iPERCIST)). Besides, there is evidence that parameters on 18F-FDG-PET/CT, such as the standardized uptake value (SUV)max and several radiotracers, e.g., directed against PD-L1, may be potential imaging biomarkers of response. Moreover, the emerge of human intratumoral immunotherapy (HIT-IT), characterized by the direct injection of immunostimulatory agents into a tumor lesion, has given new importance to imaging assessment. This article reviews the specific imaging patterns of tumor response and progression and available imaging response criteria following immunotherapy.

Potentials of Non-Invasive 18F-FDG PET/CT in Immunotherapy Prediction for Non–Small Cell Lung Cancer

The immune checkpoint inhibitors (ICIs), by targeting cytotoxic-T-lymphocyte-associated protein 4, programmed cell death 1 (PD-1), or PD-ligand 1, have dramatically changed the natural history of several cancers, including non–small cell lung cancer (NSCLC). There are unusual response manifestations (such as pseudo-progression, hyper-progression, and immune-related adverse events) observed in patients with ICIs because of the unique mechanisms of these agents. These specific situations challenge response and prognostic assessment to ICIs challenging. This review demonstrates how ¹⁸F-FDG PET/CT can help identify these unusual response patterns in a non-invasive and effective way. Then, a series of semi-quantitative parameters derived from ¹⁸F-FDG PET/CT are introduced. These indexes have been recognized as the non-invasive biomarkers to predicting the efficacy of ICIs and survival of NSCLC patients according to the latest clinical studies. Moreover, the current situation regarding the functional criteria based on ¹⁸F-FDG PET/CT for immunotherapeutic response assessment is presented and analyzed. Although the criteria based on ¹⁸F-FDG PET/CT proposed some resolutions to overcome limitations of morphologic criteria in the assessment of tumor response to ICIs, further researches should be performed to validate and improve these assessing systems. Then, the last part in this review displays the present status and a perspective of novel specific PET probes targeting key molecules relevant to immunotherapy in prediction and response assessment.

Immunotherapy Monitoring with Immune Checkpoint Inhibitors Based on [18F]FDG PET/CT in Metastatic Melanomas and Lung Cancer

Immunotherapy with checkpoint inhibitors has prompted a major change not only in cancer treatment but also in medical imaging. In parallel with the implementation of new drugs modulating the immune system, new response criteria have been developed, aiming to overcome clinical drawbacks related to the new, unusual, patterns of response characterizing both solid tumors and lymphoma during the course of immunotherapy. The acknowledgement of pseudo-progression, hyper-progression, immune-dissociated response and so forth, has become mandatory for all imagers dealing with this clinical scenario. A long list of acronyms, i.e., irRC, iRECIST, irRECIST, imRECIST, PECRIT, PERCIMT, imPERCIST, iPERCIST, depicts the enormous effort made by radiology and nuclear medicine physicians in the last decade to optimize imaging parameters for better prediction of clinical benefit in immunotherapy regimens. Quite frequently, a combination of clinical-laboratory data with imaging findings has been tested, proving the ability to stratify patients into various risk groups. The next steps necessarily require a large scale validation of the most robust criteria, as well as the clinical implementation of immune-targeting tracers for immuno-PET or the exploitation of radiomics and artificial intelligence as complementary tools during the course of immunotherapy administration. For the present review article, a summary of PET/CT role for immunotherapy monitoring will be provided. By scrolling into various cancer types and applied response criteria, the reader will obtain necessary information for better understanding the potentials and limitations of the modality in the clinical setting.

Progress and future prospective of FDG-PET/CT imaging combined with optimized procedures in lung cancer: toward precision medicine

With a 5-year overall survival of approximately 20%, lung cancer has always been the number one cancer-specific killer all over the world. As a fusion of positron emission computed tomography (PET) and computed tomography (CT), PET/CT has revolutionized cancer imaging over the past 20 years. In this review, we focused on the optimization of the function of ¹⁸F-flurodeoxyglucose (FDG)-PET/CT in diagnosis, prognostic prediction and therapy management of lung cancers by computer programs. FDG-PET/CT has demonstrated a surprising role in development of therapeutic biomarkers, prediction of therapeutic responses and long-term survival, which could be conducive to solving existing dilemmas. Meanwhile, novel tracers and optimized procedures are also developed to control the quality and improve the effect of PET/CT. With the continuous development of some new imaging agents and their clinical applications, application value of PET/CT has broad prospects in this area.

Radiomic biomarkers of tumor immune biology and immunotherapy response

Immunotherapies are leading to improved outcomes for many cancers, including those with devastating prognoses. As therapies like immune checkpoint inhibitors (ICI) become a mainstay in treatment regimens, many concurrent challenges have arisen - for instance, delineating clinical responders from non-responders. Predicting response has proven to be difficult given a lack of consistent and accurate biomarkers, heterogeneity of the tumor microenvironment (TME), and a poor understanding of resistance mechanisms. For the most part, imaging data have remained an untapped, yet abundant, resource to address these challenges. In recent years, quantitative image analyses have highlighted the utility of medical imaging in predicting tumor phenotypes, prognosis, and therapeutic response. These studies have been fueled by an explosion of resources in high-throughput mining of image features (i.e. radiomics) and artificial intelligence. In this review, we highlight current progress in radiomics to understand tumor immune biology and predict clinical responses to immunotherapies. We also discuss limitations in these studies and future directions for the field, particularly if high-dimensional imaging data are to play a larger role in precision medicine.

Metabolic Parameters as Biomarkers of Response to Immunotherapy and Prognosis in Non-Small Cell Lung Cancer (NSCLC): A Real World Experience

Immune-checkpoint inhibitors (ICIs) have been proven to have great efficacy in non-small cell lung cancer (NSCLC) as single agents or in combination therapy, being capable to induce deep and durable remission. However, severe adverse events may occur and about 40% of patients do not benefit from the treatment. Predictive factors of response to ICIs are needed in order to customize treatment. The aim of this study is to evaluate the correlation between quantitative positron emission tomography (PET) parameters defined before starting ICI therapy and responses to treatment and patient outcome. We retrospectively analyzed 92 NSCLC patients treated with nivolumab, pembrolizumab or atezolizumab. Basal PET/computed tomography (CT) scan parameters (whole-body metabolic tumor volume-wMTV, total lesion glycolysis-wTLG, higher standardized uptake volume maximum and mean-SUVmax and SUVmean) were calculated for each patient and correlated with outcomes. Patients who achieved disease control (complete response + partial response + stable disease) had significantly lower MTV median values than patients who had not (progressive disease) (77 vs. 160.2, p = 0.039). Furthermore, patients with MTV and TLG values lower than the median values had improved OS compared to patients with higher MTV and TLG (p = 0.03 and 0.05, respectively). No relation was found between the other parameters and outcome. In conclusion, baseline metabolic tumor burden, measured with MTV, might be an independent predictor of treatment response to ICI and a prognostic biomarker in NSCLC patients.

Correlation Between Dual-Time-Point FDG PET and Tumor Microenvironment Immune Types in Non-Small Cell Lung Cancer

Purpose

Dual-time-point ¹⁸F-fluorodeoxyglucose positron emission tomography (DTP ¹⁸F-FDG PET), which reflects the dynamics of tumor glucose metabolism, may also provide a novel approach to the characterization of both cancer cells and immune cells within the tumor immune microenvironment (TIME). We investigated the correlations between the metabolic parameters (MPs) of DTP ¹⁸F-FDG PET images and the tumor microenvironment immune types (TMITs) in patients with non-small cell lung cancer (NSCLC).

Methods

A retrospective analysis was performed in 91 patients with NSCLC who underwent preoperative DTP ¹⁸F-FDG PET/CT scans. MPs in the early scan (eSUVmax, eSUVmean, eMTV, eTLG) and delayed scan (dSUVmax, dSUVmean, dMTV, dTLG) were calculated, respectively. The change in MPs (ΔSUVmax, ΔSUVmean, ΔMTV, ΔTLG) between the two time points were calculated. Tumor specimens were analyzed by immunohistochemistry for PD-1/PD-L1 expression and CD8⁺ tumor-infiltrating lymphocytes (TILs). TIME was classified into four immune types (TMIT I ~ IV) according to the expression of PD-L1 and CD8⁺ TILs. Correlations between MPs with TMITs and the immune-related biomarkers were analyzed. A composite metabolic signature (Meta-Sig) and a combined model of Meta-Sig and clinical factors were constructed to predict patients with TMIT I tumors.

Results

eSUVmax, eSUVmean, dSUVmax, dSUVmean, ΔSUVmax, ΔSUVmean, and ΔTLG were significantly higher in PD-L1 positive patients (p = 0.0007, 0.0006, < 0.0001, < 0.0001, 0.0002, 0.0002, 0.0247, respectively), and in TMIT-I tumors (p = 0.0001, < 0.0001, < 0.0001, < 0.0001, 0.0009, 0.0009, 0.0144, respectively). Compared to stand-alone MP, the Meta-Sig and combined model displayed better performance for assessing TMIT-I tumors (Meta-sig: AUC = 0.818, sensitivity = 86.36%, specificity = 73.91%; Model: AUC = 0.869, sensitivity = 77.27%, specificity = 82.61%).

Conclusion

High glucose metabolism on DTP ¹⁸F-FDG PET correlated with the TMIT-I tumors, and the Meta-Sig and combined model based on clinical and metabolic information could improve the performance of identifying the patients who may respond to immunotherapy.

Association between PD-L1 expression and 18F-FDG uptake in ovarian cancer

OBJECTIVE

Immunotherapy for programmed cell death 1 (PD-1) and its ligand, PD-L1, has been considered an effective treatment for ovarian cancer. ¹⁸F-labeled fluoro-2-deoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) is a widely used noninvasive imaging tool for diagnosing several cancers. In this study, we investigated the association between PD-L1 expression and the maximum standardized uptake value (SUVmax) using ¹⁸F-FDG PET/CT.

METHODS

We retrospectively analyzed clinical data of patients with ovarian cancer who underwent ¹⁸F-FDG PET/CT. Patients were categorized into two groups according to PD-L1 expression results. The relationship between clinicopathological characteristics of patients with ovarian cancer and PD-L1 expression was examined.

RESULTS

SUVmax was significantly higher in PD-L1-positive tumors than in PD-L1-negative tumors (16.1 ± 5.2 and 12.7 ± 7.0, respectively; p = 0.026). There were no significant differences in age, histologic type, and tumor grade between the PD-L1-negative and PD-L1-positive groups. The receiver operating characteristic curve analysis demonstrated that the highest accuracy (61.8%) for predicting PD-L1 expression was obtained with an SUVmax cutoff value of 10.5.

CONCLUSION

There was a significant correlation between ¹⁸F-FDG uptake and PD-L1 expression, suggesting a role of ¹⁸F-FDG PET/CT in selecting ovarian cancer candidates for anti-PD-L1 antibody therapy.

Association between 18F-FDG metabolic activity and programmed death ligand-1 (PD-L1) expression using 22C3 immunohistochemistry assays in non-small cell lung cancer (NSCLC) resection specimens

OBJECTIVE

This study sought to investigate the association between ¹⁸F-fludeoxyglucose (¹⁸F-FDG) uptake in positron emission tomography/CT (PET/CT) scans and different programmed death ligand-1 (PD-L1) expression conditions in non-small cell lung cancer (NSCLC).

METHODS

From October 2017 to December 2019, NSCLC was retrospectively identified in 419 consecutive patients who underwent ¹⁸F-FDG PET/CT scans and PD-L1 expression tests using the PD-L1 22C3 assay. The association between clinicopathological characteristics and PD-L1 expression was assessed.

RESULTS

The frequency of PD-L1-positive tumours was 38.2% (160/419) in NSCLC. In NSCLC, the multivariate analysis showed a high maximum standardised uptake value (SUVmax) (p < 0.0001) and an EGFR wild type genotype (p = 0.027) was significantly associated with PD-L1-positivity. In adenocarcinoma (ADC), the multivariate analysis showed that a high SUVmax (p < 0.0001) was significantly associated with PD-L1-positivity. In NSCLC and ADC, a Mann-Whitney U test showed significant differences between groups with PD-L1 high expression and PD-L1 low expression levels in terms of SUVmax (p = 0.011 and p = 0.013, respectively). The results of the receiver operating characteristic curve analysis showed that the area under the curve of the SUVmax was 0.767 (95% CI, 0.720-0.814; p < 0.0001) and 0.712 (95% CI, 0.651-0.774; p < 0.0001) in NSCLC and ADC, respectively.

CONCLUSION

The study demonstrates that the SUVmax was significantly associated with PD-L1 expression in NSCLC and ADC. The SUVmax was significantly different between the PD-L1 high and low expression conditions, as quantified using a PD-L1 22C3 assay.

ADVANCES IN KNOWLEDGE

This study provides direct evidence that SUVmax as a metabolic biomarker may help select patients with NSCLC likely to benefit from pembrolizumab.

Interpretation and visualization techniques for deep learning models in medical imaging

Deep learning (DL) approaches to medical image analysis tasks have recently become popular; however, they suffer from a lack of human interpretability critical for both increasing understanding of the methods' operation and enabling clinical translation. This review summarizes currently available methods for performing image model interpretation and critically evaluates published uses of these methods for medical imaging applications. We divide model interpretation in two categories: (1) understanding model structure and function and (2) understanding model output. Understanding model structure and function summarizes ways to inspect the learned features of the model and how those features act on an image. We discuss techniques for reducing the dimensionality of high-dimensional data and cover autoencoders, both of which can also be leveraged for model interpretation. Understanding model output covers attribution-based methods, such as saliency maps and class activation maps, which produce heatmaps describing the importance of different parts of an image to the model prediction. We describe the mathematics behind these methods, give examples of their use in medical imaging, and compare them against one another. We summarize several published toolkits for model interpretation specific to medical imaging applications, cover limitations of current model interpretation methods, provide recommendations for DL practitioners looking to incorporate model interpretation into their task, and offer general discussion on the importance of model interpretation in medical imaging contexts.

Impact of PET/CT for Assessing Response to Immunotherapy-A Clinical Perspective

Cancer immunotherapy using immune-checkpoint inhibitors (ICI) has revolutionized the therapeutic landscape of various malignancies like non-small-cell lung cancer or melanoma. Pre-therapy response prediction and assessment during ICI treatment is challenging due to the lack of reliable biomarkers and the possibility of atypical radiological response patterns. Positron emission tomography/computed tomography (PET/CT) enables the visualization and quantification of metabolic lesion activity additional to conventional CT imaging. Various biomarkers derived from PET/CT have been reported as predictors for response to ICI and may aid to overcome the challenges clinicians currently face in the management of ICI-treated patients. In this narrative review, experts in nuclear medicine, thoracic oncology, dermatooncology, hemato- and internal oncology, urological and head/neck tumors performed literature reviews in their respective field and a joint discussion on the use of PET/CT in the context of ICI treatment. The aims were to give a clinical overview on present standards and evidence, to identify current challenges and fields of research and to enable an outlook to future developments and their possible implications. Multiple promising studies concerning ICI response assessment or prediction using biomarkers derived from PET/CT alone or as composite biomarkers have been identified for various malignancies and disease stages. Of interest, additional major incentives in the field may evolve from novel tracers specifically targeting immune-checkpoint molecules which could allow not only response assessment and prognosis, but also visualization of histological tumor cell properties like programmed death-ligand (PD-L1) expression in vivo. Despite the broad range of existing literature on PET/CT-derived biomarkers in ICI therapy, implications for daily clinical practice remain elusive. High-quality prospective data are urgently warranted to determine whether patients benefit from the application of PET/CT in terms of prognosis. At the moment, the lack of such evidence as well as the absence of standardized imaging methods and biomarkers still precludes PET/CT imaging to be included in the relevant clinical practice guidelines.

Clinical application and research advancement of positron emission tomography/computed tomography in colorectal cancer

Colorectal cancer is one of the most common malignant tumors of the digestive system. Early diagnosis and accurate staging and restaging of tumors are the preconditions for standardized treatment of colorectal cancer, which is conducive to the selection of treatment options and the evaluation of prognosis, as well as the improvement of patients' quality of life. With the popularization of fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography (PET/CT), its value in the diagnosis, staging and restaging, treatment decision-making, and efficacy and prognosis assessment of colorectal cancer is becoming increasingly important. This review briefly introduces the application and advancement of PET/CT in the diagnosis and treatment of colorectal cancer, in the hope that clinicians can have a more comprehensive understanding of the significance of PET/CT in the diagnosis and treatment of colorectal cancer.

Predictive value of 18F-fluorodeoxyglucose positron emission tomography/computed tomography for PD-L1 expression in non-small cell lung cancer: A systematic review and meta-analysis

Background

The purpose of the current study was to investigate the predictive value of 18F‐fluorodeoxyglucose positron emission tomography/computed tomography (18F‐FDG PET/CT) for programmed death ligand 1 (PD‐L1) in non‐small cell lung cancer (NSCLC) patients through a systematic review and meta‐analysis.

Methods

The PubMed, Cochrane, and EMBASE database, from the earliest available date of indexing through 30 April 2020, were searched for studies evaluating the diagnostic performance of 18F‐FDG PET/CT for prediction of PD‐L1 expression in NSCLC patients.

Results

Across six studies (1739 patients), the pooled sensitivity for 18F‐FDG PET/CT was 0.72 (95% CI: 0.58–0.82) with heterogeneity (I² = 90.9, P < 0.001) and a pooled specificity of 0.69 (95% CI: 0.64–0.74) with heterogeneity (I² = 77.9, P < 0.001). Likelihood ratio (LR) syntheses gave an overall positive likelihood ratio (LR +) of 2.3 (95% CI: 1.8–2.9) and negative likelihood ratio (LR‐) of 0.41 (95% CI: 0.26–0.63). The pooled diagnostic odds ratio (DOR) was six (95% CI: 3–11). Hierarchical summary receiver operating characteristic (ROC) curve indicated that the area under the curve was 0.74 (95% CI: 0.70–0.78).

Conclusions

The current meta‐analysis showed a moderate sensitivity and specificity of 18F‐FDG PET/CT for the prediction of PD‐L1 expression in NSCLC patients. The DOR was low and the likelihood ratio scatter‐gram indicated that 18F‐FDG PET/CT might not be useful for the prediction of PD‐L1 expression in NSCLC patients and not for its exclusion.

Key points

Significant findings of the study

The current meta‐analysis showed a moderate sensitivity and specificity of 18F‐FDG PET/CT for the prediction of PD‐L1 expression in NSCLC patients. The DOR was low and the likelihood ratio scattergram indicated that 18F‐FDG PET/CT might not be useful for the prediction of PD‐L1 expression in NSCLC patients and not for its exclusion.

What this study adds

This study concluded that the role of 18F‐FDG PET/CT in predicting tumor expression of PD‐L1 should be further elucidated.

Relationship between SP142 PD-L1 Expression and 18F-FDG Uptake in Non-Small-Cell Lung Cancer

Objectives

Immune checkpoint blockers constitute the first-line treatment for advanced non-small-cell lung cancer (NSCLC) with ≥50% PD-L1 expression. In NSCLC, PD-L1 positivity is correlated with high ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) uptake. However, these studies only included patients undergoing surgical resection, almost all in their early stages. Moreover, differences in ¹⁸F-FDG uptake between NSCLC with high (≥50%) and low (49%) PD-L1 expression remain unknown. We aimed to investigate the association between metabolic parameter ¹⁸F-FDG uptake and PD-L1 expression status in NSCLC patients.

Methods

From February 2017 to June 2018, 428 consecutive NSCLC patients who underwent ¹⁸F-FDG positron emission tomography/computed tomography (PET/CT) and SP142 PD-L1 expression analysis were retrospectively assessed. The association between clinicopathological characteristics and PD-L1 expression was examined.

Results

The frequency of PD-L1-positive tumors was 38.1% (163/428), 28.5% (91/319), and 64.2% (61/95) for NSCLC, adenocarcinoma (ADC), and squamous cell carcinoma (SCC), respectively. Maximal standard uptake (SUVmax) was significantly higher in PD-L1-positive than in PD-L1-negative NSCLC (p < 0.0001), ADC (p < 0.0001), and SCC (p=0.006). SUVmax was significantly higher in NSCLC (p=0.001) and ADC (p=0.003) with high rather than low PD-L1 expression. The receiver operating characteristic curve yielded area under the curve values of 0.726 (95% CI, 0.679–0.774, p < 0.0001), 0.694 (95% CI, 0.634–0.755, p < 0.0001), and 0.625 (95% CI, 0.513–0.738, p=0.044) for NSCLC, ADC, and SCC, respectively.

Conclusion

¹⁸F-FDG tumor uptake is strongly, positively correlated with PD-L1 expression in NSCLC and significantly differs between high and low PD-L1-expressing individuals.

PD-L1 expression correlation with metabolic parameters of FDG PET/CT and clinicopathological characteristics in non-small cell lung cancer

BACKGROUND

Immunotherapy targeting programmed cell death 1 (PD-1) or its ligand 1 (PD-L1) has shown promising results in non-small cell lung cancer (NSCLC) patients. Exploring PD-L1 expression could help to select NSCLC candidates for immunotherapy. Fluorine-18 fluorodeoxyglucose (FDG) PET/CT could provide phenotypic information on malignant tumors. Thus, this study investigated PD-L1 expression correlation with metabolic parameters of FDG PET/CT and clinicopathological characteristics in NSCLC.

METHODS

FDG PET/CT metabolic parameters including maximum standard uptake (SUVmax), metabolic tumor volume and total lesion glycolysis of primary lesion (MTV-P, TLG-P), and combination of primary lesion and metastases (MTV-C, TLG-C) were compared with PD-L1-positive expression in patients with NSCLC. Moreover, clinicopathological characteristics, including age, gender, smoking history, serum tumor markers, tumor location, size, TNM stage, and genetic mutation were also reviewed.

RESULTS

All 374 patients (215 men; 159 women; age 63 ± 9 years) included 283 adenocarcinomas (ACs) and 91 squamous cell carcinomas (SCCs). PD-L1 expression was positive in 27.8% (104/374) cases. SUVmax, TLG-P, and TLG-C of PD-L1 positivity were significantly higher than PD-L1 negativity. Moreover, PD-L1 expression was obviously correlated with man, smoking, and central NSCLC. If ACs and SCCs were separately analyzed, PD-L1 positivity in ACs and SCCs was 21.6% (61/283) and 47.5% (43/91), respectively, and only SUVmax was obviously associated with PD-L1 expression. Furthermore, multivariate analysis revealed that only SUVmax was an independent predictor of PD-L1 positive expression in overall NSCLC, AC, and SCC. Using a SUVmax cut-off value of 12.5, PD-L1 status of NSCLC was predicted by FDG PET/CT with sensitivity, specificity, and accuracy of 65.4%, 86.7%, and 80.7%, respectively.

CONCLUSIONS

PD-L1 expression of NSCLC was related to SUVmax, TLG, man, smoking, and central location. However, only SUVmax was an independent predictor of PD-L1 positivity, which could help to explore the existence of immune checkpoints.

Relationship between PD-L1 expression and 18F-FDG uptake in gastric cancer

PURPOSE

Immunotherapy has been successfully utilized for treatment of gastric cancer, so the identification of clinicopathologic features that are predictive of response to this therapy is crucial. ¹⁸F-FDG PET/CT can provide information on the molecular phenotype of many malignant tumors. The correlation between ¹⁸F-FDG accumulation and PD-L1/PD-L1-TILs status in gastric cancer patients has not been investigated. The aim of the current study is to assess whether ¹⁸F-FDG accumulation is associated with PD-L1/PD-L1-TILs status, and whether ¹⁸F-FDG PET/CT may be useful for predicting PD-L1/PD-L1-TILs expression of gastric cancer.

RESULTS

Tumors with positive PD-L1 expression had higher SUVmax than in tumors with negative PD-L1 expression (15.0 ± 8.0 vs. 7.2 ± 4.2, respectively; P = 0.004). Tumors with positive PD-L1-TILs expression also had higher SUVmax than in tumors with negative PD-L1-TILs expression (10.3 ± 6.5 vs. 6.6 ± 3.7, respectively; P = 0.034). Multivariate analysis suggested that SUVmax remained significantly correlated with the status of PD-L1 (P = 0.043) and PD-L1-TILs (P = 0.016). PD-L1 expression was predicted with an accuracy of 67.2% when a SUVmax value of 8.55 was used as a cutoff point for analysis. Similarly, PD-L1-TILs expression was predicted with an accuracy of 64.2%, when a SUVmax value of 7.9 was used as the threshold for analysis.

CONCLUSION

Higher ¹⁸F-FDG accumulation in gastric cancers is correlated with positive PD-L1/PD-L1-TILs expression. ¹⁸F-FDG PET/CT may be used to predict the status of PD-L1/PD-L1-TILs and thus aid in optimal treatment decision.

METHODS

A retrospective analysis was conducted on 64 patients with gastric cancer who underwent ¹⁸F-FDG PET/CT. SUVmax was calculated from the ¹⁸F-FDG accumulation of the primary tumor. The relationship between SUVmax and PD-L1/PD-L1-TILs status was analyzed.

Liquid biopsy-based single-cell metabolic phenotyping of lung cancer patients for informative diagnostics

Accurate prediction of chemo- or targeted therapy responses for patients with similar driver oncogenes through a simple and least-invasive assay represents an unmet need in the clinical diagnosis of non-small cell lung cancer. Using a single-cell on-chip metabolic cytometry and fluorescent metabolic probes, we show metabolic phenotyping on the rare disseminated tumor cells in pleural effusions across a panel of 32 lung adenocarcinoma patients. Our results reveal extensive metabolic heterogeneity of tumor cells that differentially engage in glycolysis and mitochondrial oxidation. The cell number ratio of the two metabolic phenotypes is found to be predictive for patient therapy response, physiological performance, and survival. Transcriptome analysis reveals that the glycolytic phenotype is associated with mesenchymal-like cell state with elevated expression of the resistant-leading receptor tyrosine kinase AXL and immune checkpoint ligands. Drug targeting AXL induces a significant cell killing in the glycolytic cells without affecting the cells with active mitochondrial oxidation.

Non-invasive methods to predict treatment response are urgently needed. Here in lung cancer, the authors develop a single-cell on-chip cytometry method to metabolically phenotype disseminated tumor cells, revealing metabolic heterogeneity and predictors of therapy response and survival.

Radiological Features of Programmed Cell Death-Ligand 2-positive Lung Adenocarcinoma: A Single-institution Retrospective Study

AIM

Programmed cell death-ligand 1 and 2 (PD-L1 and PD-L2) are ligands of the programmed cell death-1 (PD1) receptor. PD1/PD-L1 inhibitors have shown clinical efficacy in non-small cell lung cancer (NSCLC). However, relatively little is known about the expression of PD-L2, or its association with the clinicopathological features of NSCLC. Here, the radiological features of PD-L2-positive lung adenocarcinoma were evaluated.

MATERIALS AND METHODS

PD-L1 and PD-L2 expression were evaluated by immunohistochemical staining of surgically-resected specimens from 393 patients with primary lung adenocarcinoma who underwent preoperative thin-section computed tomography (CT), 222 of whom also underwent ¹⁸F-fluorodeoxyglucose positron-emission tomography/CT (¹⁸F-FDG-PET/CT).

RESULTS

Among the 393 specimens, 132 (33.6%) and 266 (67.7%) were positive for PD-L1 and PD-L2 expression, respectively. Multivariate analysis showed that the absence of surrounding ground glass opacity and the presence of air bronchogram were significantly associated with PD-L2 expression; however, there was no significant association between PD-L2 expression and the consolidation/tumor ratio. In 222 ¹⁸F-FDG-PET/CT, the maximum standardized uptake value was significantly higher in patients with PD-L2-positive compared to those with PD-L2-negative tumors.

CONCLUSION

PD-L2-positive lung adenocarcinomas are less radiologically malignant and invasive than their PD-L1-positive counterparts.