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

Deciphering Tumor Response: The Role of Fluoro-18-d-Glucose Uptake in Evaluating Targeted Therapies with Tyrosine Kinase Inhibitors

Background/Objectives: The inhibitory effects of tyrosine kinase inhibitors (TKIs) on glucose uptake through their binding to human glucose transporter-1 (GLUT-1) have been well documented. Thus, our research aimed to explore the potential impact of various TKIs of GLUT-1 on the standard [18F]FDG-PET monitoring of tumor response in patients. Methods: To achieve this, we conducted an analysis on three patients who were undergoing treatment with different TKIs and harbored actionable alterations. Alongside the assessment of FDG data (including SUVmax, total lesion glycolysis (TLG), and metabolic tumor volume (MTV)), we also examined the changes in tumor sizes through follow-up [18F]FDG-PET/CT imaging. Notably, our patients harbored alterations in BRAFV600, RET, and c-KIT and exhibited positive responses to the targeted treatment. Results: Our analysis revealed that FDG data derived from SUVmax, TLG, and MTV offered quantifiable outcomes that were consistent with the measurements of tumor size. Conclusions: These findings lend support to the notion that the inhibition of GLUT-1, as a consequence of treatment efficacy, could be indirectly gauged through [18F] FDG-PET/CT imaging in cancer patients undergoing TKI therapy.

First-line immunotherapy in non-small cell lung cancer: how to select and where to go

INTRODUCTION

Immunotherapy (IO) has established a new milestone in lung cancer treatment. Several registrational studies have approved immune checkpoint inhibitors (ICIs) in different settings, including the metastatic nonsmall cell lung cancer (NSCLC). As well known, responders are just a certain proportion of patients; therefore, their selection by using predictive factors has stood out as a crucial issue to address in tailoring a patient-centered care.

AREAS COVERED

In our review we propose a detailed yet handy cross section on ICIs as first-line treatment in metastatic NSCLC, regarding indications, histological, clinical, and blood-based biomarkers, other than their mechanisms of resistance and new immunological actionable targets. We performed a literature search through PubMed entering keywords complying with crucial features of immunotherapy.

EXPERT OPINION

IO represents the backbone of lung cancer treatment. Trials are currently testing novel immune blockade agents assessing combinatorial approaches with standard ICIs, or antibody drug conjugates (ADC), harboring immunological targets. Perfecting patients' selection is an ongoing challenge and a more and more urgent need in order to best predict responders who will consistently benefit from it.

Association between cigarette smoking history, metabolic phenotypes, and EGFR mutation status in patients with non-small cell lung cancer

Background

Cigarette smoking exerts a significant impact on metabolic phenotypes and epidermal growth factor receptor (EGFR) mutation status; however, their correlation remains insufficiently established. Therefore, the aim of this study was to investigate the association between cigarette smoking history, metabolic phenotypes, and EGFR mutation status in patients with non-small cell lung cancer (NSCLC).

Methods

We retrospectively analyzed 198 consecutive patients with NSCLC who underwent 18F-fluoro-2-deoxy-D-glucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) before treatment and were tested for EGFR mutation status between September 2019 and March 2022. Metabolic phenotypes, including the maximum standardized uptake value (SUVmax) of the primary tumors (pSUVmax), metastatic lymph nodes (nSUVmax), and distant metastases (mSUVmax) were assessed. Patients were classified into never-smokers and smokers based on detailed smoking history. The correlations between smoking status, metabolic parameters, and EGFR mutation status were evaluated in patients with NSCLC.

Results

We observed EGFR mutations in 73 (60.3%) of 121 never-smokers and 18 (23.4%) of 77 smokers (P<0.001). EGFR-mutant NSCLC had a lower pSUVmax than that of EGFR wild-type (WT; 8.9±4.5 vs. 12.7±6.9, P<0.001). Smokers had a higher pSUVmax than never-smokers (12.5±6.4 vs. 9.9±5.9, P=0.004). With the increase of cumulative smoking dose, the pSUVmax increased significantly (r=0.198, P=0.005). There was no significant difference between nSUVmax and mSUVmax in patients with or without EGFR mutation and smoking history. Cumulative smoking dose, pSUVmax, and their combination predicted EGFR mutation status with areas under the receiver operating characteristic (ROC) curves (AUCs) 0.688, 0.673, and 0.753, respectively.

Conclusions

Our findings indicate that cigarette smoking may be one of the triggers for increased pSUVmax and decreased EGFR mutations, further suggesting that EGFR mutations are associated with low pSUVmax, which may guide clinicians in risk stratification and treatment strategy selection for patients with NSCLC.

Assessing the role of colonic and other anatomical sites uptake by [18 F]FDG-PET/CT and immune-inflammatory peripheral blood indexes in patients with advanced non-small cell lung cancer treated with first-line immune checkpoint inhibitors

BACKGROUND

Inflammation in non-small cell lung cancer (NSCLC) may impair the response to immune checkpoint inhibitors (ICIs) and can be indicated by peripheral blood inflammatory indexes. 2-deoxy-2-[18 F]fluoro-D-glucose positron emission tomography/computed tomography ([18 F] FDG-PET/CT) may be used as a marker of inflammation by measuring glucose metabolism in different colonic sites.

METHODS

This retrospective analysis aimed to investigate the correlation between [18 F] FDGPET/CT SUVratio in six gastrointestinal districts, the spleen, the pharynx and the larynx alongside the most avid tumor lesion with peripheral blood inflammatory indexes, including the neutrophil-to-lymphocyte ratio (NLR), systemic immune-inflammatory index (SII, i.e., NLR times platelets) and lactate dehydrogenase (LDH), in patients with [18 F] FDG-PET/CT staged IV NSCLC who received first-line immune checkpoint inhibitors (ICIs). The role of SUVratios and peripheral blood inflammatory indexes in predicting overall survival (OS) and progression-free survival (PFS) was then explored.

RESULTS

A total of 43 patients were treated with first-line ICI alone (58%) or in combination with chemotherapy (42%). A significant correlation was only found between the rectosigmoid SUVratio and NLR (p = 0.0465). NLR >5.5 and LDH > 333.5 were associated with a worse OS (p = 0.033 and p = 0.009, respectively). The SII was associated with a worse PFS in patients treated with ICI alone (p = 0.033). None of the SUVratios were significantly associated with OS or PFS, although a high left colon SUVratio showed a trend toward a worse PFS.

CONCLUSION

There was no significant correlation between [18 F]FDG PET/CT uptake in different anatomical sites, and in the tumor, and systemic immune-inflammatory indexes. The prognostic role of high left colon SUVratio deserves further investigation.

Independent association of metabolic tumor response on FDG-PET with pulmonary toxicity following risk-adaptive chemoradiation for unresectable non-small cell lung cancer: Inherent radiosensitivity or immune response?

BACKGROUND

In the context of a phase II trial of risk-adaptive chemoradiation, we evaluated whether tumor metabolic response could serve as a correlate of treatment sensitivity and toxicity.

METHODS

Forty-five patients with AJCCv7 stage IIB-IIIB NSCLC enrolled on the FLARE-RT phase II trial (NCT02773238). [18F]fluorodeoxyglucose (FDG) PET-CT images were acquired prior to treatment and after 24 Gy during week 3. Patients with unfavorable on-treatment tumor response received concomitant boosts to 74 Gy total over 30 fractions rather than standard 60 Gy. Metabolic tumor volume and mean standardized uptake value (SUVmean) were calculated semi-automatically. Risk factors of pulmonary toxicity included concurrent chemotherapy regimen, adjuvant anti-PDL1 immunotherapy, and lung dosimetry. Incidence of CTCAE v4 grade 2+ pneumonitis was analyzed using the Fine-Gray method with competing risks of metastasis or death. Peripheral germline DNA microarray sequencing measured predefined candidate genes from distinct pathways: 96 DNA repair, 53 immunology, 38 oncology, 27 lung biology.

RESULTS

Twenty-four patients received proton therapy, 23 received ICI, 26 received carboplatin-paclitaxel, and 17 pneumonitis events were observed. Pneumonitis risk was significantly higher for patients with COPD (HR 3.78 [1.48, 9.60], p = 0.005), those treated with immunotherapy (HR 2.82 [1.03, 7.71], p = 0.043) but not with carboplatin-paclitaxel (HR 1.98 [0.71, 5.54], p = 0.19). Pneumonitis rates were similar among selected patients receiving 74 Gy radiation vs 60 Gy (p = 0.33), proton therapy vs photon (p = 0.60), or with higher lung dosimetric V20 (p = 0.30). Patients in the upper quartile decrease in SUVmean (>39.7%) were at greater risk for pneumonitis (HR 4.00 [1.54, 10.44], p = 0.005) and remained significant in multivariable analysis (HR 3.34 [1.23, 9.10], p = 0.018). Germline DNA gene alterations in immunology pathways were most frequently associated with pneumonitis.

CONCLUSION

Tumor metabolic response as measured by mean SUV is associated with increased pneumonitis risk in a clinical trial cohort of NSCLC patients independent of treatment factors. This may be partially attributed to patient-specific differences in immunogenicity.

Predictive Value of Total Metabolic Tumor Burden Prior to Treatment in NSCLC Patients Treated with Immune Checkpoint Inhibition

OBJECTIVES

We aimed to assess the predictive value of the total metabolic tumor burden prior to treatment in patients with advanced non-small-cell lung cancer (NSCLC) receiving immune checkpoint inhibitors (ICIs).

METHODS

Pre-treatment 2-deoxy-2-[¹⁸F]fluoro-D-glucose positron emission tomography/computed tomography (PET/CT) scans performed in two consecutive years for staging in adult patients with confirmed NSCLC were considered. Volume, maximum/mean standardized uptake value (SUVmax/SUVmean), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were assessed per delineated malignant lesion (including primary tumor, regional lymph nodes and distant metastases) in addition to the morphology of the primary tumor and clinical data. Total metabolic tumor burden was captured by _totalMTV and _totalTLG. Overall survival (OS), progression-free survival (PFS) and clinical benefit (CB) were used as endpoints for response to treatment.

RESULTS

A total of 125 NSCLC patients were included. Osseous metastases were the most frequent distant metastases (n = 17), followed by thoracal distant metastases (pulmonal = 14 and pleural = 13). Total metabolic tumor burden prior to treatment was significantly higher in patients treated with ICIs (mean _totalMTV ± standard deviation (SD) 72.2 ± 78.7; mean _totalTLG ± SD 462.2 ± 538.9) compared to those without ICI treatment (mean _totalMTV ± SD 58.1 ± 233.8; mean _totalTLG ± SD 290.0 ± 784.2). Among the patients who received ICIs, a solid morphology of the primary tumor on imaging prior to treatment was the strongest outcome predictor for OS (Hazard ratio HR 28.04, p < 0.01), PFS (HR 30.89, p < 0.01) and CB (parameter estimation PE 3.46, p < 0.01), followed by the metabolic features of the primary tumor. Interestingly, total metabolic tumor burden prior to immunotherapy showed a negligible impact on OS (p = 0.04) and PFS (p = 0.01) after treatment given the hazard ratios of 1.00, but also on CB (p = 0.01) given the PE < 0.01. Overall, biomarkers on pre-treatment PET/CT scans showed greater predictive power in patients receiving ICIs, compared to patients without ICI treatment.

CONCLUSIONS

Morphological and metabolic properties of the primary tumors prior to treatment in advanced NSCLC patients treated with ICI showed great outcome prediction performances, as opposed to the pre-treatment total metabolic tumor burdens, captured by _totalMTV and _totalTLG, both with negligible impact on OS, PFS and CB. However, the outcome prediction performance of the total metabolic tumor burden might be influenced by the value itself (e.g., poorer prediction performance at very high or very low values of total metabolic tumor burden). Further studies including subgroup analysis with regards to different values of total metabolic tumor burden and their respective outcome prediction performances might be needed.