Fluorodeoxyglucose uptake is associated with low tumor-infiltrating lymphocyte levels in patients with small cell lung cancer

RadioFlow Cytometry Reveals That [18F]FDG Uptake in K-RAS Lung Cancer Is Driven by Immune Cells: An Analysis on a Single-Cell Level

Tumor metabolism is a hallmark of cancer, yet cellular heterogeneity within the tumor microenvironment presents a significant challenge, as bulk analysis masks the diverse metabolic profiles of individual cell populations. This complexity complicates our understanding of [18F]FDG uptake by distinct cell types in the tumor microenvironment. This study aims to investigate [18F]FDG uptake at the single-cell level in the lung of Kirsten rat sarcoma virus-driven cancer mouse models using the novel technique radio-flow cytometry (radioFlow). Methods: Two Kirsten rat sarcoma virus-driven lung cancer mouse models were injected with [18F]FDG for small-animal PET/CT and subsequent fluorescence-activated cell sorting of the lung. For radioFlow, the sorted cell fractions were then measured in a γ-counter and their radioactivity was normalized to the number of cells. Results: RadioFlow analysis of the lung tissue of both models showed a robust cell type-specific uptake pattern across experiments. Our key findings indicate that the [18F]FDG PET signal predominantly derives from immune cells (CD45+, F4/80-, 78.3% ± 6.6%; macrophage, 13.9% ± 4.3%), whereas tumor cells contributed only with 2.8% ± 1.0%, similar to the uptake of structural cells (CD45-; tumor cells, 5.0% ± 2.3%). Normalization showed that macrophages exhibited the highest glucose metabolism in both tumor models (57% ± 8%), followed by the remaining immune cells (27% ± 3%). Conclusion: These findings highlight the critical influence of immune cell metabolism on [18F]FDG imaging, emphasizing the need to account for immune contributions when interpreting [18F]FDG imaging in cancer.

Activating Invasion and Metastasis in Small Cell Lung Cancer: Role of the Tumour Immune Microenvironment and Mechanisms of Vasculogenesis, Epithelial-Mesenchymal Transition, Cell Migration, and Organ Tropism

BACKGROUND

Small cell lung cancer (SCLC) harbours the most aggressive phenotype of all lung cancers to correlate with its bleak prognosis. The aggression of SCLC is partially attributable to its strong metastatic tendencies. The biological processes facilitating the metastasis in SCLC are still poorly understood and garnering a deeper understanding of these processes may enable the exploration of additional targets against this cancer hallmark in the treatment of SCLC.

RECENT FINDINGS

This narrative review will discuss the proposed molecular mechanisms by which the cancer hallmark of activating invasion and metastasis is featured in SCLC through important steps of the metastatic pathway, and address the various molecular targets that may be considered for therapeutic intervention. The tumour immune microenvironment plays an important role in facilitating immunotherapy resistance, whilst the poor infiltration of natural killer cells in particular fosters a pro-metastatic environment in SCLC. SCLC vasculogenesis is achieved through VEGF expression and vascular mimicry, and epithelial-mesenchymal transition is facilitated by the expression of the transcriptional repressors of E-cadherin, the suppression of the Notch signalling pathway and tumour heterogeneity. Nuclear factor I/B, selectin and B1 integrin hold important roles in SCLC migration, whilst various molecular markers are expressed by SCLC to assist organ-specific homing during metastasis. The review will also discuss a recent article observing miR-1 mRNA upregulation as a potential therapeutic option in targeting the metastatic activity of SCLC.

CONCLUSION

Treatment of SCLC remains a clinical challenge due to its recalcitrant and aggressive nature. Amongst the many hallmarks used by SCLC to enable its aggressive behaviour, that of its ability to invade surrounding tissue and metastasise is particularly notable and understanding the molecular mechanisms in SCLC metastasis can identify therapeutic targets to attenuate SCLC aggression and improve mortality.

Prognostic significance of 18F-Fluorodeoxyglucose positron-emission tomography parameters in patients with biliary tract cancers: a meta-analysis

BACKGROUND AND OBJECTIVE

Numerous previous studies have assessed the prognostic role of 18F-fluorodeoxyglucose positron-emission tomography (18F FDG PET) in patients with biliary tract cancer (BTC), but those results were inconsistent. The present study aims to determine the predictive value of 18F FDG PET in BTC patients via a meta-analysis.

METHODS

The underlying studies related to 18F FDG PET and BTC patients` outcomes were searched and identified in the online databases. The interested parameters include total lesion glycolysis (TLG), metabolic tumor volume (MTV), primary tumor and metastatic lymph node (LN) maximum standardized uptake value (SUVmax), as well as change of SUVmax (ΔSUVmax) during treatment. Overall survival (OS), disease-free survival (DFS), and progression-free survival (PFS) were considered as the primary endpoints. Hazard ratio (HR) and corresponding 95% confidence intervals (CIs) were defined as the effective measure and calculated by a pooled analysis. Publication bias was assessed by funnel plot, Bagg's and Egger's tests.

RESULTS

Totally, 23 studies involving 1478 patients were included in the present meta-analysis. After a pooled analysis, it revealed that a high SUVmax was significantly associated with a poor OS (HR:2.07, 95%CI: 1.74-2.46, P = 0.000) and DFS (HR: 2.28, 95%CI: 1.53-3.41, P = 0.000). In addition, an increased TLG level contributed to a shorter OS (HR:1.91, 95%CI: 1.26-2.90, P = 0.002) and DFS (HR: 4.34, 95%CI: 1.42-13.27, P = 0.01). Moreover, we confirmed that an elevated MTV was significantly associated with increased mortality (HR:2.04, 95%CI:1.26-3.31, P = 0.004) and disease relapse (HR: 3.88, 95%CI:1.25-12.09, P = 0.019) risks. Besides, the present study uncovered that increased ΔSUVmax could predict poor OS (HR:1.26, 95%CI:1.06-1.50, P = 0.008) instead of PFS (HR: 1.96, 95%CI: 0.82-4.72, P = 0.280). Lastly, we found that LN SUVmax did not link to OS (HR: 1.49, 95%CI: 0.83-2.68, P = 0.178). No obvious publication bias was detected in the present study.

CONCLUSION

18F FDG PET parameters, including SUVmax, TLG, MTV, and ΔSUVmax, could be applied as convenient and reliable factors for predicting BTC patients` outcomes.

Metabolic tumor volume and sites of organ involvement predict outcome in NSCLC immune-checkpoint inhibitor therapy

PURPOSE

The purpose of this study was to assess the ability of pretreatment PET parameters and peripheral blood biomarkers to predict progression-free survival (PFS) and overall survival (OS) in NSCLC patients treated with ICIT.

METHODS

We prospectively included 87 patients in this study who underwent pre-treatment [18F]-FDG PET/CT. Organ-specific and total metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were measured using a semiautomatic software. Sites of organ involvement (SOI) were assessed by PET/CT. The log-rank test and Cox-regression analysis were used to assess associations between clinical, laboratory, and imaging parameters with PFS and OS. Time dependent ROC were calculated and model performance was evaluated in terms of its clinical utility.

RESULTS

MTV increased with the number of SOI and was correlated with neutrophil and lymphocyte cell count (Spearman's rho = 0.27 or 0.32; p =.02 or 0.003; respectively). Even after adjustment for known risk factors, such as PD-1 expression and neutrophil cell count, the MTV and the number of SOI were independent risk factors for progression (per 100 cm3; adjusted hazard ratio [aHR]: 1.13; 95% confidence interval [95%CI]: 1.01-1.28; p =.04; single SOI vs. ≥ 4 SOI: aHR: 2.26, 95%CI: 1.04-4.94; p =.04). MTV and the number of SOI were independent risk factors for overall survival (per 100 cm3 aHR: 1.11, 95%CI: 1.01-1.23; p =.03; single SOI vs. ≥ 4 SOI: aHR: 4.54, 95%CI: 1.64-12.58; p =.04). The combination of MTV and the number of SOI improved the risk stratification for PFS and OS (log-rank test p <.001; C-index: 0.64 and 0.67).

CONCLUSION

The MTV and the number of SOI are simple imaging markers that provide complementary information to facilitate risk stratification in NSCLC patients scheduled for ICIT.

Primary tumor SUVmax and ratio of SUVmax to primary tumor size on pretreatment 18F-FDG-PET/CT scan in small cell lung cancer : Which is superior for the prognosis?

BACKGROUND

The prognostic impact of tumor SUVmax (t-SUVmax) in small cell lung cancer (SCLC) has been questioned with controversial results, and the significance of the ratio of tumor SUVmax to primary tumor size (SUVmax/t-size) in SCLC has yet to be clarified as well. In this study, a retrospective analysis was carried out to figure out the prognostic and predictive powers of pretreatment primary t‑SUVmax and t‑SUVmax/t-size ratio in patients with SCLC.

METHODS

A total of 349 SCLC patients who underwent pretreatment staging with PET/CT scan were enrolled in the study and analyzed retrospectively.

RESULTS

In limited disease SCLC (LD-SCLC), tumor size was significantly associated with both t‑SUVmax (p = 0.02) and t‑SUVmax/t-size (p = 0.0001). Furthermore, performance status, tumor size (p = 0.001), and liver metastasis were significantly associated with t‑SUVmax in extended disease SCLC (ED-SCLC). Moreover, tumor size (p = 0.0001), performance status, cigarette smoking history, and pulmonary/pleural metastasis were found to be correlated with t‑SUVmax/t-size. No associations were found between clinical stages and either t‑SUVmax or t‑SUVmax/t-size (p = 0.9 for both), and t‑SUVmax and t‑SUVmax/t-size values were found to have similar survival rates in both LD-SCLC and ED-SCLC patients. In univariate and multivariate analyses, both t‑SUVmax and t‑SUVmax/t-size were found not to be associated with overall survival (p > 0.05) CONCLUSION: This study does not advocate the use of either t‑SUVmax or t‑SUVmax/t-size on pretreatment 18F‑FDG-PET/CT scan as prognostic and predictive tools for both LD-SCLC and ED-SCLC patients. Likewise, we did not find that t‑SUVmax/t-size was superior to t‑SUVmax in that respect.

Tumor infiltrating lymphocytes and radiological picture of the tumor

Tumor microenvironment (TME) is a complex entity that includes besides the tumor cells also a whole range of immune cells. Among various populations of immune cells infiltrating the tumor, tumor infiltrating lymphocytes (TILs) are a population of lymphocytes characterized by high reactivity against the tumor component. As, TILs play a key role in mediating responses to several types of therapy and significantly improve patient outcomes in some cancer types including for instance breast cancer and lung cancer, their assessment has become a good predictive tool in the evaluation of potential treatment efficacy. Currently, the evaluation of the density of TILs infiltration is performed by histopathological. However, recent studies have shed light on potential utility of several imaging methods, including ultrasonography, magnetic resonance imaging (MRI), positron emission tomography-computed tomography (PET-CT), and radiomics, in the assessment of TILs levels. The greatest attention concerning the utility of radiology methods is directed to breast and lung cancers, nevertheless imaging methods of TILs are constantly being developed also for other malignancies. Here, we focus on reviewing the radiological methods used to assess the level of TILs in different cancer types and on the extraction of the most favorable radiological features assessed by each method.

Four-dimensional quantitative analysis using FDG-PET in clinical oncology

Positron emission tomography (PET) with F-18 fluorodeoxyglucose (FDG) has been commonly used in many oncological areas. High-resolution PET permits a three-dimensional analysis of FDG distributions on various lesions in vivo, which can be applied for tissue characterization, risk analysis, and treatment monitoring after chemoradiotherapy and immunotherapy. Metabolic changes can be assessed using the tumor absolute FDG uptake as standardized uptake value (SUV) and metabolic tumor volume (MTV). In addition, tumor heterogeneity assessment can potentially estimate tumor aggressiveness and resistance to chemoradiotherapy. Attempts have been made to quantify intratumoral heterogeneity using radiomics. Recent reports have indicated the clinical feasibility of a dynamic FDG PET-computed tomography (CT) in pilot cohort studies of oncological cases. Dynamic imaging permits the assessment of temporal changes in FDG uptake after administration, which is particularly useful for differentiating pathological from physiological uptakes with high diagnostic accuracy. In addition, several new parameters have been introduced for the in vivo quantitative analysis of FDG metabolic processes. Thus, a four-dimensional FDG PET-CT is available for precise tissue characterization of various lesions. This review introduces various new techniques for the quantitative analysis of FDG distribution and glucose metabolism using a four-dimensional FDG analysis with PET-CT. This elegant study reveals the important role of tissue characterization and treatment strategies in oncology.

Correlation of 18F-FDG PET/CT metabolic parameters with the expression of immune biomarkers in the tumour microenvironment in lung adenocarcinoma

AIM

To explore the association between metabolic parameters evaluated by integrated 2-[¹⁸F]-fluoro-2-deoxy-d-glucose (FDG) positron-emission tomography (PET)/computed tomography (CT) and the expression of immune biomarkers in the tumour microenvironment in lung adenocarcinoma.

MATERIALS AND METHODS

This study included 134 patients. Metabolic parameters were obtained by PET/CT. Immunohistochemistry analysis was used for FOXP3-TILs (transcription factor forkhead box protein 3 tumour-infiltrating lymphocytes), CD8-TILs, CD4-TILs, CD68-TAMs (tumour-associated macrophages) and galectin-1 (Gal-1) tumour expression.

RESULTS

There were significant positive associations between FDG PET metabolic parameters and the median percentage of immune reactive areas (IRA%) covered by FOXP3-TILs and CD68-TAMs. Negative associations with the median IRA% covered by CD4-TILs and CD8-TILs were observed: maximal standardised uptake value (SUV_max), metabolic tumour volume (MTV), total lesion glycolysis (TLG), and IRA% for FOXP3-TILs (rho = 0.437, 0.400, 0.414; p<0.0001 for all parameters); SUV_max, MTV, TLG, and IRA% for CD68-TAMs (rho = 0.356, 0.355, 0.354; p<0.0001 for all parameters); SUV_max, MTV, TLG, and IRA% for CD4-TILs (rho = -0.164, -0.190, -0.191; p=0.059, 0.028, 0.027, respectively); SUV_max, MTV, TLG, and IRA% for CD8-TILs (rho = -0.305, -0.316, -0.322; p<0.0001 for all parameters). There were significant positive associations between tumour Gal-1 expression and the median IRA% covered by FOXP3-TILs and CD68-TAMs (rho = 0.379; p<0.0001; rho = 0.370; p<0.0001, respectively), and a significant negative association with the median IRA% covered by CD8-TILs (rho = -0.347; p<0.0001) was observed. Tumour stage (p=0.008), Gal-1 expression (p=0.008), and median IRA% covered by CD8-TILs (p=0.054) were independent risk factors for overall survival.

CONCLUSION

FDG PET may facilitate a comprehensive evaluation of the tumour microenvironment and predict response to immunotherapy.

Molecular Characterization and Therapeutic Approaches to Small Cell Lung Cancer: Imaging Implications

Small cell lung cancer (SCLC) is a highly aggressive malignancy with exceptionally poor prognosis, comprising approximately 15% of lung cancers. Emerging knowledge of the molecular and genomic landscape of SCLC and recent successful clinical applications of new systemic agents have allowed for precision oncology treatment approaches. Imaging is essential for the diagnosis, staging, and treatment monitoring of patients with SCLC. The role of imaging is increasing with the approval of new treatment agents, including immune checkpoint inhibitors, which lead to novel imaging manifestations of response and toxicities. The purpose of this state-of-the-art review is to provide the reader with the latest information about SCLC, focusing on the subtyping of this malignancy (molecular characterization) and the emerging systemic therapeutic approaches and their implications for imaging. The review will also discuss the future directions of SCLC imaging, radiomics and machine learning.

Unraveling tumor microenvironment of small-cell lung cancer: implications for immunotherapy

Small-cell lung cancer (SCLC) is an aggressive lung cancer subtype and its first-line treatment has remained unchanged for decades. In recent years, immunotherapy has emerged as a therapeutic strategy for tumor treatment, whereas, patients with SCLC exhibit poor overall responses to immunotherapy alone, which highlights the necessity for combinatorial approaches. The tumor microenvironment (TME), an integral component in cancer, is widely implicated in tumorigenesis and tumor metastasis. The interactions of various cells within TME shape the adverse conditions of the tumor microenvironment (characterized by hypoxia, nutrient restriction, and acidity) and are considered responsible for the modest therapeutic responses to immunotherapy. Several studies have suggested that adverse TME can regulate immune cell activation and function. However, the specific regulatory mechanisms and their implications on immunotherapy remain unclear. Thus, it is worth unraveling the characteristics of TME and its impact on antitumor immunity, in the hope of devising novel strategies to reinforce immunotherapeutic effects on SCLC. In this review, we firstly elaborate on the immune landscape of SCLC and the formation of three remarkable characteristics in TME, as well as the interaction among them. Next, we summarize the latest findings regarding the impacts of adverse TME on immune cells and its targeted therapy in SCLC. Finally, we discuss the ongoing trials in combination therapy and potential directions of SCLC therapy. Collectively, the findings combined here are expected to aid the design of trials for combining immunotherapy with therapy targeting the TME of SCLC.

Monitoring of Current Cancer Therapy by Positron Emission Tomography and Possible Role of Radiomics Assessment

Evaluation of cancer therapy with imaging is crucial as a surrogate marker of effectiveness and survival. The unique response patterns to therapy with immune-checkpoint inhibitors have facilitated the revision of response evaluation criteria using FDG-PET, because the immune response recalls reactive cells such as activated T-cells and macrophages, which show increased glucose metabolism and apparent progression on morphological imaging. Cellular metabolism and function are critical determinants of the viability of active cells in the tumor microenvironment, which would be novel targets of therapies, such as tumor immunity, metabolism, and genetic mutation. Considering tumor heterogeneity and variation in therapy response specific to the mechanisms of therapy, appropriate response evaluation is required. Radiomics approaches, which combine objective image features with a machine learning algorithm as well as pathologic and genetic data, have remarkably progressed over the past decade, and PET radiomics has increased quality and reliability based on the prosperous publications and standardization initiatives. PET and multimodal imaging will play a definitive role in personalized therapeutic strategies by the precise monitoring in future cancer therapy.

Application of molecular imaging in immune checkpoints therapy: From response assessment to prognosis prediction

Recently, immune checkpoint therapy (ICT) represented by programmed cell death1 (PD-1) and its major ligands, programmed death ligand 1 (PD-L1), has achieved significant success. Detection of PD-L1 by immunohistochemistry (IHC) is a classic method to guide the treatment of ICT patients. However, PD-L1 expression in the tumor microenvironment is highly complex. Thus, PD-L1 IHC is inadequate to fully understand the relevance of PD-L1 levels in the whole body and their dynamics to improve therapeutic outcomes. Intriguingly, numerous studies have revealed that molecular imaging technologies could potentially meet this need. Therefore, the purpose of this narrative review is to summarize the preclinical and clinical application of ICT guided by molecular imaging technology, and to explore the future opportunities and practical difficulties of these innovations.

The value of the Standardized Uptake Value (SUV) and Metabolic Tumor Volume (MTV) in lung cancer

The diagnosis, staging and therapeutic monitoring of lung cancer were amongst the first applications for which the utility of FDG PET was documented and FDG PET/CT is now a routine diagnostic tool for clinical decision-making. As well as having high sensitivity for detection of disease sites, which provides critical information about stage, the intensity of uptake provides deeper biological characterization, while the burden of disease also has potential clinical significance. These disease characteristics can easily be quantified on delayed whole-body imaging as the maximum standardized uptake value (SUV_max) and metabolic tumor volume (MTV), respectively. There have been significant efforts to harmonize the measurement of these features, particularly within the context of clinical trials. Nevertheless, however calculated, in general, a high SUV_max and large MTV have been shown to have an adverse prognostic significance. Nevertheless, the use of these parameters in the interpretation and reporting of clinical scans remains inconsistent and somewhat controversial. This review details the current status of semi-quantitative FDG PET/CT in the evaluation of lung cancer.

Clinical characteristics and patient outcomes of molecular subtypes of small cell lung cancer (SCLC)

Background

Recent studies have shown that according to the expression levels of achaete-scute homolog 1 (ASCL1), neurogenic differentiation factor 1 (NEUROD1), and POU class 2 homeobox 3 (POU2F3), small cell lung cancer (SCLC) can be divided into four subtypes: SCLC-A (ASCL1-dominant), SCLC-N (NEUROD1-dominant), SCLC-P (POU2F3-dominant), and SCLC-I (triple negative or SCLC-inflamed). However, there are limited data on the clinical characteristics and prognosis of molecular subtypes of SCLC.

Methods

Immunohistochemistry (IHC) was used to detect the expression levels of ASCL1, NEUROD1, and POU2F3 in 53 patient samples of resectable SCLC. The subtype was defined by the differential expression of the transcription factors for ASCL1, NEUROD1, and POU2F3 or the low expression of all three factors with an inflamed gene signature (SCLC-A, SCLC-N, SCLC-P, and SCLC-I, respectively). The clinicopathological characteristics, immunological features (programmed death ligand 1 [PD-L1] expression and CD8+ tumor infiltrating lymphocyte [TIL] density), and patient outcomes of the four subtypes of SCLC were analyzed.

Results

Positive ASCL1, NEUROD1, and POU2F3 staining was detected in 43 (79.2%), 27 (51.0%), and 17 (32.1%) SCLC specimens by IHC. According to the results of IHC analysis, SCLC was divided into four subtypes: SCLC-A (39.6%), SCLC-N (28.3%), SCLC-P (17.0%), and SCLC-I (15.1%). The 5-year overall survival (OS) rates of these four subtypes were 61.9%, 69.3%, 41.7%, and 85.7%, respectively (P=0.251). There were significant differences in smoking status among different subtypes of SCLC (P= 0.031). However, we did not confirm the correlation between subtypes of SCLC and other clinicopathological factors or immune profiles. Cox multivariate analysis showed that N stage (P=0.025), CD8+ TILs (P=0.024), Ki-67 level (P=0.040), and SCLC-P (P=0.023) were independent prognostic factors for resectable SCLC.

Conclusions

Our IHC-based study validated the proposed classification of SCLC using the expression patterns of key transcriptional regulatory factors. We found that SCLC-P was associated with smokers and was one of the poor prognostic factors of limited-stage SCLC. In addition, no correlation was found between PD-L1 expression or CD8+ TIL density and SCLC subtypes.

Infiltrating T lymphocytes in the tumor microenvironment of small cell lung cancer: a state of knowledge review

Immune checkpoint inhibitors (ICIs) have brought new hope for the treatment of patients with small cell lung cancer (SCLC) over the past decades. However, the overall response rate is limited, and is lower than that in non-small cell lung cancer (NSCLC). This is in part because of the lack of pre-existing tumor-infiltrating T lymphocytes (TITLs), especially cytotoxic T cells (CTLs), in the SCLC tumor microenvironment (TME), resulting in insufficient anti-tumor immune response. To unleash the full potential of ICIs, the trafficking and infiltration of TITLs to the tumor is necessary and tightly regulated, the highly immunosuppressive tumor microenvironment blunts the infiltration and function of TITLs that reach the tumor in SCLC. Here, we review the characteristics of TITLs, the effects of various factors on T cell infiltration, and possible strategies to restore or promote T cell infiltration in the TME of SCLC.

Human leukocyte antigen class II-based immune risk model for recurrence evaluation in stage I-III small cell lung cancer

Background

Immunotherapy has revolutionized therapeutic patterns of small cell lung cancer (SCLC). Human leukocyte antigen class II (HLA class II) is related to antitumor immunity. However, the implications of HLA class II in SCLC remain incompletely understood.

Materials and methods

We investigated the expression patterns of HLA class II on tumor cells and tumor-infiltrating lymphocytes (TILs) by immunohistochemistry staining and its association with clinical parameters, immune markers, and recurrence-free survival (RFS) in 102 patients with stage I–III SCLC with radical surgery. Additionally, an HLA class II-based immune risk model was established by least absolute shrinkage and selection operator regression. With bioinformatics methods, we investigated HLA class II-related enrichment pathways and immune infiltration landscape in SCLC.

Results

HLA class II on tumor cells and TILs was positively expressed in 9 (8.8%) and 45 (44.1%) patients with SCLC, respectively. HLA class II on TILs was negatively associated with lymph node metastasis and positively correlated with programmed death-ligand 1 (PD-L1) on TILs (p<0.001) and multiple immune markers (CD3, CD4, CD8, FOXP3; p<0.001). Lymph node metastasis (OR 0.314, 95% CI 0.118 to 0.838, p=0.021) and PD-L1 on TILs (OR 3.233, 95% CI 1.051 to 9.95, p=0.041) were independent predictive factors of HLA class II on TILs. HLA class II positivity on TILs prompted a longer RFS (40.2 months, 95% CI 31.7 to 48.7 vs 28.8 months, 95% CI 21.4 to 36.3, p=0.014). HLA class II on TILs, PD-L1 on TILs, CD4, and FOXP3 were enrolled in the immune risk model, which categorized patients into high-risk and low-risk groups and had better power for predicting the recurrence than tumor stage. Pathway enrichment analyses showed that patients with high HLA class II expression demonstrated signatures of transmembrane transportation, channel activity, and neuroactive ligand–receptor interaction. High-risk SCLC patients had a higher proportion of T follicular helper cells (p=0.034) and a lower proportion of activated memory CD4-positive T cells (p=0.040) and resting dendritic cells (p=0.045) versus low-risk patients.

Conclusions

HLA class II plays a crucial role in tumor immune microenvironment and recurrence prediction. This work demonstrates the prognostic and clinical values of HLA class II in patients with SCLC.

Correlation Between 18F-FDG Uptake and Immune Cell Infiltration in Metastatic Brain Lesions

Background

The purpose of this study was to investigate the correlation between ¹⁸F-fluorodeoxyglucose (FDG) uptake and infiltrating immune cells in metastatic brain lesions.

Methods

This retrospective study included 34 patients with metastatic brain lesions who underwent brain ¹⁸F-FDG positron emission tomography (PET)/computed tomography (CT) followed by surgery. ¹⁸F-FDG uptake ratio was calculated by dividing the standardized uptake value (SUV) of the metastatic brain lesion by the contralateral normal white matter uptake value. We investigated the clinicopathological characteristics of the patients and analyzed the correlation between ¹⁸F-FDG uptake and infiltration of various immune cells. In addition, we evaluated immune-expression levels of glucose transporter 1 (GLUT1), hexokinase 2 (HK2), and Ki-67 in metastatic brain lesions.

Results

The degree of ¹⁸F-FDG uptake of metastatic brain lesions was not significantly correlated with clinical parameters. There was no significant relationship between the ¹⁸F-FDG uptake and degree of immune cell infiltration in brain metastasis. Furthermore, other markers, such as GLUT1, HK2, and Ki-67, were not correlated with degree of ¹⁸F-FDG uptake. In metastatic brain lesions that originated from breast cancer, a higher degree of ¹⁸F-FDG uptake was observed in those with high expression of CD68.

Conclusions

In metastatic brain lesions, the degree of ¹⁸F-FDG uptake was not significantly associated with infiltration of immune cells. The ¹⁸F-FDG uptake of metastatic brain lesions from breast cancer, however, might be associated with macrophage activity.

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.

Prognostic Value of 18F-FDG-PET Parameters in Patients with Small Cell Lung Cancer: A Meta-Analysis and Review of Current Literature

Many studies have suggested a prognostic value of one or several positron emission tomography (PET) parameters in patients with small cell lung cancer (SCLC). However, studies are often small, and there is a considerable interstudy disagreement about which PET parameters have a prognostic value. The objective of this study was to perform a review and meta-analysis to identify the most promising PET parameter for prognostication. PubMed^®, Cochrane, and Embase^® were searched for papers addressing the prognostic value of any PET parameter at any treatment phase with any endpoint in patients with SCLC. Pooled hazard ratios (HRs) were calculated by a random effects model for the prognostic value of the baseline maximum standardized uptake value (SUV_max) and metabolic tumor volume (MTV). The qualitative analysis included 38 studies, of these, 19 studies were included in the meta-analyses. The pooled results showed that high baseline MTV was prognostic for overall survival (OS) (HR: 2.83 (95% confidence interval [CI]: 2.00–4.01) and progression-free survival (PFS) (HR: 3.11 (95% CI: 1.99–4.90)). The prognostic value of SUV_max was less pronounced (OS: HR: 1.50 (95% CI: 1.17–1.91); PFS: HR: 1.24 (95% CI: 0.94–1.63)). Baseline MTV is a strong prognosticator for OS and PFS in patients with SCLC. MTV has a prognostic value superior to those of other PET parameters, but whether MTV is superior to other prognosticators of tumor burden needs further investigation.

Value of 18F-FDG-PET to predict PD-L1 expression and outcomes of PD-1 inhibition therapy in human cancers

Anti-programmed cell death-1 (PD-1)/programmed death ligand-1 (PD-L1) antibodies are administered in varied human cancer types. The expression of PD-L1 within tumor cells has been identified as a predictive marker, although assessing its expression has benefitted only patients with non-small cell lung cancer (NSCLC) or head and neck cancer. Whereas, more than 75% of the patients with NSCLC showing partial response to PD-1 blockade therapy experienced long-term survival for more than 5-years Thus, identifying the responders to PD-1 blockade at early phase after its initiation is of clinical importance. The 2-deoxy-2-[fluorine-18] fluoro-D-glucose (¹⁸F-FDG) on positron emission tomography (PET) can evaluate any tumor shrinkage by assessing the metabolic tumor volume at an earlier phase than conventional modalities such as computed tomography (CT). While several reports describe the correlation of PD-L1 expression with ¹⁸F-FDG uptake rate in the tumor cells, it remains to be delineated whether this rate determined by the glucose metabolism and hypoxia is associated with the status of immune microenvironment, including the expression of PD-L1. Moreover, details of the relationship between expression of PD-L1 and ¹⁸F-FDG uptake is still unclear. Therefore, we reviewed the clinical significance of ¹⁸F-FDG uptake on PET as a predictor of the efficacy of PD-1 blockade therapy, by correlating with the expression of PD-L1, in patients with several neoplasms.

Tumor metabolic volume by 18F-FDG-PET as a prognostic predictor of first-line pembrolizumab for NSCLC patients with PD-L1 ≥ 50

There is a lack of markers for predicting favorable outcomes after pembrolizumab therapy in patients with non-small cell lung cancer (NSCLC) with programmed death ligand-1 (PD-L1) expression ≥ 50%. This retrospective study examined the prognostic significance of 2-deoxy-2-[18F] fluoro-d-glucose (¹⁸F-FDG) uptake as a predictive marker of first-line pembrolizumab. Forty-eight patients with previously untreated NSCLC and PD-L1 expression levels ≥ 50% who underwent ¹⁸F-FDG-positron emission tomography (PET) just before administration of pembrolizumab monotherapy were eligible and underwent assessment of metabolic tumor volume (MTV), total lesion glycolysis (TLG), and maximum of standardized uptake value (SUV_max) on ¹⁸F-FDG uptake. The objective response rate, median progression-free survival, and median overall survival were 51.1%, 7.1 months, and 18.6 months, respectively. In univariate survival analyses, high MTV was barely a significant prognostic predictor and was confirmed as an independent factor linked to worse outcomes in multivariate analysis, predominantly in patients with a histological diagnosis of adenocarcinoma. A high MTV was significantly associated with distant metastases (especially bone metastasis), C-reactive protein (CRP) level, and PD-L1 expression ≥ 75%. Metabolic tumor activity assessed as MTV from ¹⁸F-FDG uptake predicted the prognosis after first-line pembrolizumab treatment in patients with NSCLC and PD-L1 expression ≥ 50%, especially for adenocarcinoma.

Potential of FDG-PET as Prognostic Significance after anti-PD-1 Antibody against Patients with Previously Treated Non-Small Cell Lung Cancer

It remains unclear whether the accumulation of 2-deoxy-2-[¹⁸F]fluoro-d-glucose (¹⁸F-FDG) before the initiation of anti-programmed death-1 (PD-1) antibody can predict the outcome after its treatment. The aim of this study is to retrospectively examine the prognostic significance of ¹⁸F-FDG uptake as a predictive marker of anti-PD-1 antibody. Eighty-five patients with previously treated non-small cell lung cancer (NSCLC) who underwent ¹⁸F-FDG-positron emission tomography (PET) just before administration of nivolumab or pembrolizumab monotherapy were eligible in our study, and metabolic tumor volume (MTV), total lesion glycolysis (TLG) and the maximum of standardized under value (SUV_max) on ¹⁸F-FDG uptake were assessed. Objective response rate, median progression-free survival and median overall survival were 36.6%, 161 days and 716 days, respectively. The frequency of any immune-related adverse events was significantly higher in patients with low ¹⁸F-FDG uptake on PET than in those with high uptake. By multivariate analysis, the tumor metabolic activity by TLG and MTV was identified as an independent prognostic factor for predicting outcome after anti-PD-1 antibody therapy, but not SUV_max, predominantly in patients with adenocarcinoma. Metabolic tumor indices as TLG and MTV on ¹⁸F-FDG uptake could predict the prognosis after anti-PD-1 antibodies in patients with previously treated NSCLC.