Tumor-infiltrating lymphocytes predict efficacy of immunotherapy in advanced non-small cell lung cancer: a single-center retrospective cohort study.

BACKGROUND/PURPOSE: The current study aimed to investigate the correlation between tumor-infiltrating lymphocytes (TILs) and immunotherapy efficacy in patients with advanced non-small cell lung cancer (NSCLC). MATERIALS AND METHODS: Eighty-nine patients with advanced NSCLC who received immune checkpoint inhibitors (ICIs) monotherapy were retrospectively enrolled in this study. The density of TILs in paraffin-embedded pathological tissues taken before receiving ICIs was quantitatively analyzed by immunohistochemical staining. The density of TILs was treated as a dichotomous variable using the median as the cutoff value. The Kaplan-Meier analysis was used to assess survival differences between groups. Univariate and multivariate Cox analyses were applied to screen out independent prognostic factors and further construct a nomogram prediction model to predict survival. RESULTS: Survival analysis showed that CD8+ TILs, CD4+ TILs, and IFN-γ+ Th1 were significant positive indicators for predicting progression-free survival (PFS) and overall survival (OS) (p < 0.05), whereas Foxp3+ Treg were a significant negative predictor (p < 0.05). The predictive role of IL-4+ Th2 was not apparent in this study and requires further investigation and exploration (p > 0.05). The nomogram prediction model exhibited good discriminative ability, with C-index values of 0.723 (95% CI 0.682-0.764) and 0.793 (95% CI, 0.738-0.848) in the training cohort and validation cohort, respectively. The AUC values indicated that the nomogram prediction model had high predictive value and the calibration curve presented good prediction accuracy. CONCLUSIONS: TILs could predict the efficacy of immunotherapy and may become a promising predictor.

Plasma Markers for Early Prediction of Radiation-Induced Myocardial Damage.

There is no sensitive and effective method to predict radiation-induced myocardial damage (RIMD). The aim of this study was to explore effective plasma biomarkers for early prediction of RIMD after radiotherapy (RT) in lung cancer patients and in a rat model. Biomarker levels were measured in plasma samples collected before and after thoracic RT from 17 lung cancer patients. For the animal model, a single radiation dose of 40 Gy was delivered to the cardiac apex of female Wistar rats. Control rats received sham irradiation (0 Gy). Dynamic plasma biomarker detection and histopathological analysis to confirm RIMD were performed in rats up to 6 months after RT. In lung cancer patients, the plasma caspase-3 concentration was significantly increased after thoracic RT (P = 0.0479), with increasing but nonsignificant trends observed for caspase-1, CCL2, vascular endothelial growth factor (VEGF), interleukin-1ß, and IL-6 (P > 0.05). Changes in caspase-3, VEGF, and IL-6 correlated significantly with mean heart dose (P < 0.05). In the RIMD rat model, caspase-1, caspase-3, CCl-2, VEGF, CCl-5, and TGF-ß1 levels were significantly elevated in the first week post-RT (P < 0.05), which was earlier than pathological changes. Myocardial tissue of the RIMD rats also showed significant macrophage infiltration at 1 month (P < 0.01) and fibrosis at 6 months postradiation (P < 0.0001). Macrophage infiltration correlated significantly with plasma caspase-3, CCL2, CCL5, VEGF, and TGF-ß1 levels from 3 weeks to 2 months post-RT. Increased plasma caspase-1, caspase-3, CCl-2, and VEGF levels were detected before RIMD-related pathological changes, indicating their clinical potential as biomarkers for early prediction of RIMD.

Response Prediction Using 18F-FAPI-04 PET/CT in Patients with Esophageal Squamous Cell Carcinoma Treated with Concurrent Chemoradiotherapy.

This prospective study examined whether imaging results obtained using the tracer 18F-AlF-NOTA-fibroblast activation protein inhibitor (FAPI)-04 (denoted as 18F-FAPI-04) in PET/CT can predict the short-term outcome in patients with locally advanced esophageal squamous cell carcinoma (LA-ESCC) treated with concurrent chemoradiotherapy (CCRT). Methods: The 18 enrolled LA-ESCC patients underwent 18F-FAPI-04 PET/CT scanning before CCRT. The SUVmax, SUVmean, SUVpeak, metabolic tumor volume, and total lesion fibroblast activation protein expression of the primary tumor were recorded. Additionally, the SUVmax of the primary tumor and SUVmean of normal tissue (muscle and blood) were measured, and their ratios were denoted as target-to-background ratios (TBRmuscle and TBRblood). Patients were classified as responders or nonresponders according to RECIST (version 1.1), and variables were compared between the 2 groups. Results: The TBRblood, TBRmuscle, and SUVmean were significantly higher in nonresponders than in responders (all P < 0.05). Receiver-operating-characteristic curve analysis identified TBRblood (area under the curve [AUC], 0.883; P = 0.008), TBRmuscle (AUC, 0.896; P = 0.006) and SUVmean (AUC, 0.870; P = 0.010) as significant predictors of the response to CCRT, with cutoffs of 10.68, 10.95, and 6.88, respectively. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were also determined for TBRblood (100.0%, 72.7%, 66.7%, 88.9%, and 77.8%, respectively), TBRmuscle (100.0%, 72.7%, 66.7%, 88.9%, and 77.8%, respectively), and SUVmean (85.7%, 81.8%, 75.0%, 90.0%, and 83.3%, respectively). On univariate logistic regression analysis, TBRblood (P = 0.026), TBRmuscle (P = 0.036), SUVmean (P = 0.045), and tumor site (P = 0.032) were significantly correlated with the short-term outcome. On multivariable logistic regression analysis, TBRblood (P = 0.046) was an independent prognostic factor for short-term outcome. Conclusion: A higher baseline TBRblood on 18F-FAPI-04 PET/CT scans was associated with a poor response to CCRT in LA-ESCC patients, and thus, TBRblood may be useful for screening LA-ESCC patients before CCRT treatment.

Diagnostic Value of 18F-NOTA-FAPI PET/CT in a Rat Model of Radiation-Induced Lung Damage.

In this study, we explore the diagnostic value of a novel PET/CT imaging tracer that specifically targets fibroblast activation protein (FAP), 18F-NOTA-FAPI, in a radiation induced lung damage (RILD) rat model. High focal radiation (40, 60, or 90 Gy) was administered to a 5-mm diameter area of the right lung in Wistar rats for evaluation of RILD induction. Lung tissues exposed to 90 Gy radiation were scanned with 18F-NOTA-FAPI PET/CT and with 18F-FDG. Dynamic 18F-NOTA-FAPI PET/CT scanning was performed on day 42 post-irradiation. After in vivo scanning, lung cryosections were prepared for autoradiography, hematoxylin and eosin (HE) and immunohistochemical (IHC) staining. An animal model of RILD was established and validated by histopathological analysis. On 18F-NOTA-FAPI PET/CT, RILD was first observed on days 42, 35 and 7 in the 40, 60 and 90 Gy groups, respectively. After treatment with 90 Gy, 18F-NOTA-FAPI uptake in an area of RILD emerged on day 7 (0.65 ± 0.05%ID/ml) and reappeared on day 28 (0.81 ± 0.09%ID/ml), remaining stable for 4-6 weeks. Autoradiography and HE staining IHC staining revealed that 18F-NOTA-FAPI accumulated mainly in the center of the irradiated area. IHC staining confirmed the presence of FAP+ macrophages in the RILD area, while FAP+ fibroblasts were observed in the peripheral area of irradiated lung tissue. 18F-NOTA-FAPI represents a promising radiotracer for in vivo imaging of RILD in a dose- and time-dependent manner. Noninvasive imaging of FAP may potentially aiding in the clinical management of radiotherapy patients.

[18F]AlF-NOTA-FAPI-04 PET/CT uptake in metastatic lesions on PET/CT imaging might distinguish different pathological types of lung cancer.

PURPOSE: Heterogeneity is found in the tumor microenvironment among different pathological types of tumors. Radionuclide-labeled fibroblast-activation-protein inhibitor (FAPI), as an important tracer for non-invasive imaging of the tumor microenvironment, can be used to evaluate the expression of FAP in cancer-associated fibroblasts, macrophages, and tumor cells. Our aim was to explore the ability of [18F]AlF-NOTA-FAPI-04 positron emission tomography (PET)/computed tomography (CT) to distinguish different types of lung cancer by evaluating the uptake of this tracer in primary and metastatic lesions. METHODS: We prospectively enrolled 61 patients with histopathologically proven primary lung cancer with metastases. PET/CT scanning was performed before any antitumor therapy and 1 h after injection of 235.10 ± 3.89 MBq of [18F]AlF-NOTA-FAPI-04. Maximum standard uptake values (SUVmax) were calculated for comparison among primary and metastatic lesions. Immunohistochemical staining for FAP was performed on tumor specimens. RESULTS: Sixty-one patients with adenocarcinoma (ADC, n = 30), squamous cell carcinoma (SCC, n = 17), and small cell lung cancer (SCLC, n = 14) were enrolled in this study, and 61 primary tumors and 199 metastases were evaluated. No difference in [18F]AlF-NOTA-FAPI-04 uptake was observed among primary ADC, SCC, and SCLC tumors (P = 0.198). Additionally, no difference in uptake was found between primary and metastatic lesions of lung cancer with the same pathological type (P > 0.05). However, uptake did differ among metastases of differing pathological types (P < 0.001). The SUVmax of metastatic lymph nodes was highest for SCC, followed by ADC and then SCLC (P < 0.001). The SUVmax of bone metastases also was highest for SCC, followed by ADC and SCLC (P < 0.05), but no difference was observed between ADC and SCLC. The SUVmax of metastases in other organs was higher in SCC cases than in ADC cases but did not differ between SCC and SCLC or ADC and SCLC. Bone metastases exhibited higher uptake than those of lymph nodes and other organs in SCC and ADC (P < 0.05) but not in SCLC. Positive correlations were found between FAPI uptake and FAP expression in surgical plus biopsy specimens (r = 0.439, P = 0.012) and surgical specimens (r = 0.938, P = 0.005). CONCLUSION: [18F]AlF-NOTA-FAPI-04 PET/CT imaging revealed differences in FAP expression in metastases of lung cancer, with the highest expression specifically in bone metastases, and thus, may be valuable for distinguishing different pathological types of lung cancer.

Commensal microbiota contributes to predicting the response to immune checkpoint inhibitors in non-small-cell lung cancer patients.

Immunotherapy against cancer, through immune checkpoint inhibitors targeting the programmed cell death-1/programmed cell death-ligand 1 axis, is particularly successful in tumors by relieving the immune escape. However, interindividual responses to immunotherapy are often heterogeneous. Therefore, it is essential to screen out predictive tumor biomarkers. In this study, we analyzed the commensal microbiota in stool samples and paired sputum samples from 75 metastatic non-small-cell lung cancer (NSCLC) patients at baseline and during treatment with immune checkpoint inhibitors. Results showed distinct microbes' signatures between the gut microbiota and paired respiratory microbiota. The alpha diversity between the gut and respiratory microbiota was uncorrelated, and only the gut microbiota alpha diversity was associated with anti-programmed cell death-1 response. Higher gut microbiota alpha diversity indicated better response and more prolonged progression-free survival. Comparison of bacterial communities between responders and nonresponders showed some favorable/unfavorable microbes enriched in responders/nonresponders, indicating that commensal microbiota had potential predictive value for the response to immune checkpoint inhibitors. Generally, some rare low abundance gut microbes and high abundance respiratory microbes lead to discrepancies in microbial composition between responders and nonresponders. A significant positive correlation was observed between the abundance of Streptococcus and CD8+ T cells. These results highlighted the intimate relationship between commensal microbiota and the response to immunotherapy in NSCLC patients. Gut microbiota and respiratory microbiota are promising biomarkers to screen suitable candidates who are likely to benefit from immune checkpoint inhibitor-based immunotherapy.