Dynamic 18 F-FDG PET/CT can predict the major pathological response to neoadjuvant immunotherapy in non-small cell lung cancer

Potential predictors of the pathologic response after neoadjuvant chemoimmunotherapy in resectable non-small cell lung cancer: a narrative review

Background and Objective

Neoadjuvant chemoimmunotherapy (NACI) is the standard of care for patients with resectable non-small cell lung cancer (NSCLC). Although the pathological complete response (pCR) after NACI reportedly exceeds 20%, an optimal predictor of pCR is yet to be established. This review aims to examine the possible predictors of pCR after NACI.

Methods

We identified research article published between 2018 and 2022 in English by the PubMed database. Fifty research studies were considered as relevant article, and were examined to edit information for this narrative review.

Key Content and Findings

Recently, several studies have explored potential biomarkers for the pathological response after NACI. For example, 18F-fluorodeoxyglucose positron emission tomography (18F-FDG-PET) imaging, tumor microenvironment (TME), genetic alternation such as circulating tumor DNA (ctDNA), and clinical markers such as neutrophil-to-lymphocyte ratio (NLR) and smoking signature were assessed in patients with resectable NSCLC to predict the pathological response after NACI. Based on the PET response criteria, the complete metabolic response (CMR) achieved a positive predictive value (PPV) of 71.4% for predicting pCR, and the decreasing rate of post-therapy maximum standardized uptake value (SUVmax) after NACI substantially correlated with the major pathological response (MPR). TME, as a significant marker for MPR in tumor specimens, was identified as an increase in CD8+ T cells and decrease in CD3+ T cells or Foxp3 T cells. Considering blood samples, TME comprised an increase in CD4+PD-1+ cells or natural killer cells and a decrease in CD3+CD56+CTLA4+ cells, total T cells, Th cells, myeloid-derived suppressor cells (MDSCs), or regulatory T cells. Although low pretreatment levels of ctDNA and undetectable ctDNA levels after NACI were markedly associated with survival, the relationship between ctDNA levels and pCR remains elusive. Moreover, the patients with a high baseline NLR had a low incidence of pCR. Heavy smoking (>40 pack-years) was favorable for predicting pathological response.

Conclusions

A reduced rate of 18F-FDG uptake post-NACI and TME-related surface markers on lymphocytes could be optimal predictors for pCR. However, the role of these pCR predictors for NACI remains poorly validated, warranting further investigations. This review focuses on predictive biomarkers for pathological response after NACI in patients with resectable NSCLC.

Immunotherapy for early-stage non-small cell lung cancer: A system review

With the addition of immunotherapy, lung cancer, one of the most common cancers with high mortality rates, has broadened the treatment landscape. Immune checkpoint inhibitors have demonstrated significant efficacy in the treatment of non-small cell lung cancer (NSCLC) and are now used as the first-line therapy for metastatic disease, consolidation therapy after radiotherapy for unresectable locally advanced disease, and adjuvant therapy after surgical resection and chemotherapy for resectable disease. The use of adjuvant and neoadjuvant immunotherapy in patients with early-stage NSCLC, however, is still debatable. We will address several aspects, namely the initial efficacy of monotherapy, the efficacy of combination chemotherapy, immunotherapy-related biomarkers, adverse effects, ongoing randomized controlled trials, and current issues and future directions for immunotherapy in early-stage NSCLC will be discussed here.

Utility of 18F-FDG uptake in predicting major pathological response to neoadjuvant immunotherapy in patients with resectable non‑small cell lung cancer

PURPOSE

The aim of present study was to investigate the efficiency of ¹⁸F-FDG uptake in predicting major pathological response (MPR) in resectable non-small cell lung cancer (NSCLC) patients with neoadjuvant immunotherapy.

METHODS

A total of 104 patients with stage I-IIIB NSCLC were retrospectively derived from National Cancer Center of China, of which 36 cases received immune checkpoint inhibitors (ICIs) monotherapy (I-M) and 68 cases with ICI combination therapy (I-C). ¹⁸F-FDG PET-CT scans were performed at baseline and after neoadjuvant therapy (NAT). Receiver-operating characteristic (ROC) curve analyses were conducted and area under ROC curve (AUC) was calculated for biomarkers including maximum standardized uptake value (SUVmax), inflammatory biomarkers, tumor mutation burden (TMB), PD-L1 tumor proportion score (TPS) and iRECIST.

RESULTS

Fifty-four resected NSCLC tumors achieved MPR (51.9%, 54/104). In both neoadjuvant I-M and I-C cohorts, post-NAT SUVmax and the percentage changes of SUVmax (ΔSUVmax%) were significantly lower in the patients with MPR versus non-MPR (p < 0.01), and were also negatively correlated with the degree of pathological regression (p < 0.01). The AUC of ΔSUVmax% for predicting MPR was respectively 1.00 (95% CI: 1.00-1.00) in neoadjuvant I-M cohort and 0.94 (95% CI: 0.86-1.00) in I-C cohort. Baseline SUVmax had a statistical prediction value for MPR only in I-M cohort, with an AUC up to 0.76 at the threshold of 17.0. ΔSUVmax% showed an obvious advantage in MPR prediction over inflammatory biomarkers, TMB, PD-L1 TPS and iRECIST.

CONCLUSION

¹⁸F-FDG uptake can predict MPR in NSCLC patients with neoadjuvant immunotherapy.

Neoadjuvant immune-checkpoint inhibitors in lung cancer - a primer for radiologists

The introduction of neoadjuvant immune checkpoint inhibitors plus platinum-based chemotherapy has changed treatment regimens of patient's early-stage lung cancer. This treatment combination induces high rates of complete pathologic response and improves clinical endpoints. Imaging plays a fundamental role in assessment of treatment response, monitoring of (immune-related) adverse events and enables both the surgeon and pathologist optimal treatment and diagnostic workup of the resected tumor samples. Knowledge of the strengths and weaknesses of diagnostic imaging in this setting are essential for radiologists to provide valuable input in multidisciplinary team decisions.

Utility of 18F-FDG PET/CT uptake values in predicting response to neoadjuvant chemoimmunotherapy in resectable non-small cell lung cancer

INTRODUCTION

Reliable predictive markers are lacking for resectable non-small cell lung cancer (NSCLC) patients treated with neoadjuvant chemoimmunotherapy. The present study investigated the utility of SUV_max values acquired from PET/CT to predict the response to neoadjuvant chemoimmunotherapy for resectable NSCLC.

MATERAL AND METHODS

SUV_max, clinical and pathological outcomes, were collected from patients in 5 hospitals. Patients who received dynamic PET/CT surveillance were divided into cohorts A (chemoimmunotherapy) and B (chemotherapy), respectively, while cohort C (chemoimmunotherapy) comprised patients undergoing post-therapy PET/CT. Associations between SUV_max and major pathologic response (MPR) were evaluated through receiver operating characteristic (ROC) curves.

RESULTS

A total of 129 cases with an MPR rate of 46.5 % was identified. In neoadjuvant chemoimmunotherapy, ΔSUV_max% (AUC: 0.890, 95 % CI: 0.761-0.949) and post-therapy SUV_max (AUC: 0.933, 95 % CI: 0.802-0.959) could accurately predict MPR. On the contrary, the baseline SUV_max was not associated with MPR (p = 0.184). Furthermore, an independent cohort C proved that post-therapy SUV_max could serve as an independent predictor (AUC: 0.928, 95 % CI: 0.823-0.958). In addition, robust predictive performance could be observed when we use the optimal cut-off point of both ΔSUV_max% (54.4 %, AUC: 0.912, 95 % CI: 0.824-0.994) and post-therapy SUV_max (3.565, AUC: 0.912, 95 % CI: 0.824-0.994) in neoadjuvant chemoimmunotherapy. The RNA data revealed that the expression of PFKFB4, a key enzyme in glycolysis, was positively correlated with SUV_max value and tumor cell proliferation after neoadjuvant chemoimmunotherapy.

CONCLUSION

These findings highlighted that the ΔSUV_max% and remained SUV_max were accurate and non-invasive tests for the prediction of MPR after neoadjuvant chemoimmunotherapy.

Comprehensive 18F-FDG PET-based radiomics in elevating the pathological response to neoadjuvant immunochemotherapy for resectable stage III non-small-cell lung cancer: A pilot study

PURPOSE

To develop a comprehensive PET radiomics model to predict the pathological response after neoadjuvant toripalimab with chemotherapy in resectable stage III non-small-cell lung cancer (NSCLC) patients.

METHODS

Stage III NSCLC patients who received three cycles of neoadjuvant toripalimab with chemotherapy and underwent ¹⁸F-FDG PET/CT were enrolled. Baseline ¹⁸F-FDG PET/CT was performed before treatment, and preoperative ¹⁸F-FDG PET/CT was performed three weeks after the completion of neoadjuvant treatment. Surgical resection was performed 4-5 weeks after the completion of neoadjuvant treatment. Standardized uptake value (SUV) statistics features and radiomics features were derived from baseline and preoperative PET images. Delta features were derived. The radiologic response and metabolic response were assessed by iRECIST and iPERCIST, respectively. The correlations between PD-L1 expression, driver-gene status, peripheral blood biomarkers, and the pathological responses (complete pathological response [CPR]; major pathological response [MPR]) were assessed. Associations between PET features and pathological responses were evaluated by logistic regression.

RESULTS

Thirty patients underwent surgery and 29 of them performed preoperative PET/CT. Twenty patients achieved MPR and 16 of them achieved CPR. In univariate analysis, five SUV statistics features and two radiomics features were significantly associated with pathological responses. In multi-variate analysis, SUV_max, SUV_peak, SUL_peak, and End-PET-GLDM-LargeDependenceHighGrayLevelEmphasis (End-GLDM-LDHGLE) were independently associated with CPR. SUV_peak and SUL_peak performed better than SUV_max and SUL_max for MPR prediction. No significant correlation, neither between the radiologic response and the pathological response, nor among PD-L1, driver gene status, and baseline PET features was found. Inflammatory response biomarkers by peripheral blood showed no difference in different treatment responses.

CONCLUSION

The logistic regression model using comprehensive PET features contributed to predicting the pathological response after neoadjuvant toripalimab with chemotherapy in resectable stage III NSCLC patients.