Radiotherapy Planning and Molecular Imaging in Lung Cancer

Advances in Non-Small Cell Lung Cancer: Current Insights and Future Directions

The leading cause of cancer deaths worldwide is attributed to non-small cell lung cancer (NSCLC), necessitating a continual focus on improving the diagnosis and treatment of this disease. In this review, the latest breakthroughs and emerging trends in managing NSCLC are highlighted. Major advancements in diagnostic methods, including better imaging technologies and the utilization of molecular biomarkers, are discussed. These advancements have greatly enhanced early detection and personalized treatment plans. Significant improvements in patient outcomes have been achieved by new targeted therapies and immunotherapies, providing new hope for individuals with advanced NSCLC. This review discusses the persistent challenges in accessing advanced treatments and their associated costs despite recent progress. Promising research into new therapies, such as CAR-T cell therapy and oncolytic viruses, which could further revolutionize NSCLC treatment, is also highlighted. This review aims to inform and inspire continued efforts to improve outcomes for NSCLC patients globally, by offering a comprehensive overview of the current state of NSCLC treatment and future possibilities.

[Research progress on the identification of central lung cancer and atelectasis using multimodal imaging]

Central lung cancer is a common disease in clinic which usually occurs above the segmental bronchus. It is commonly accompanied by bronchial stenosis or obstruction, which can easily lead to atelectasis. Accurately distinguishing lung cancer from atelectasis is important for tumor staging, delineating the radiotherapy target area, and evaluating treatment efficacy. This article reviews domestic and foreign literatures on how to define the boundary between central lung cancer and atelectasis based on multimodal images, aiming to summarize the experiences and propose the prospects.

[Construction of A Nomogram Prediction Model for PD-L1 Expression in Non-small Cell Lung Cancer Based on 18F-FDG PET/CT Metabolic Parameters]

BACKGROUND

In recent years, immunotherapy represented by programmed cell death 1 (PD-1)/programmed cell death ligand 1 (PD-L1) immunosuppressants has greatly changed the status of non-small cell lung cancer (NSCLC) treatment. PD-L1 has become an important biomarker for screening NSCLC immunotherapy beneficiaries, but how to easily and accurately detect whether PD-L1 is expressed in NSCLC patients is a difficult problem for clinicians. The aim of this study was to construct a Nomogram prediction model of PD-L1 expression in NSCLC patients based on 18F-fluorodeoxy glucose (18F-FDG) positron emission tomography/conputed tomography (PET/CT) metabolic parameters and to evaluate its predictive value.

METHODS

Retrospective collection of 18F-FDG PET/CT metabolic parameters, clinicopathological information and PD-L1 test results of 155 NSCLC patients from Inner Mongolia People's Hospital between September 2016 and July 2021. The patients were divided into the training group (n=117) and the internal validation group (n=38), and another 51 cases of NSCLC patients in our hospital between August 2021 and July 2022 were collected as the external validation group according to the same criteria. Then all of them were categorized according to the results of PD-L1 assay into PD-L1+ group and PD-L1- group. The metabolic parameters and clinicopathological information of patients in the training group were analyzed by univariate and binary Logistic regression, and a Nomogram prediction model was constructed based on the screened independent influencing factors. The effect of the model was evaluated by receiver operating characteristic (ROC) curve, calibration curve and decision curve analysis (DCA) in both the training group and the internal and external validation groups.

RESULTS

Binary Logistic regression analysis showed that metabolic tumor volume (MTV), gender and tumor diameter were independent influences on PD-L1 expression. Then a Nomogram prediction model was constructed based on the above independent influences. The ROC curve for the model in the training group shows an area under the curve (AUC) of 0.769 (95%CI: 0.683-0.856) with an optimal cutoff value of 0.538. The AUC was 0.775 (95%CI: 0.614-0.936) in the internal validation group and 0.752 (95%CI: 0.612-0.893) in the external validation group. The calibration curves were tested by the Hosmer-Lemeshow test and showed that the training group (χ2=0.040, P=0.979), the internal validation group (χ2=2.605, P=0.271), and the external validation group (χ2=0.396, P=0.820) were well calibrated. The DCA curves show that the model provides clinical benefit to patients over a wide range of thresholds (training group: 0.00-0.72, internal validation group: 0.00-0.87, external validation group: 0.00-0.66).

CONCLUSIONS

The Nomogram prediction model constructed on the basis of 18F-FDG PET/CT metabolic parameters has greater application value in predicting PD-L1 expression in NSCLC patients.

Cancer-associated fibroblasts in radiotherapy: Bystanders or protagonists?

BACKGROUND

The primary goal of radiotherapy (RT) is to induce cellular damage on malignant cells; however, it is becoming increasingly recognized the important role played by the tumor microenvironment (TME) in therapy outcomes. Therapeutic irradiation of tumor lesions provokes profound cellular and biological reconfigurations within the TME that ultimately may influence the fate of the therapy.

MAIN CONTENT

Cancer-associated fibroblasts (CAFs) are known to participate in all stages of cancer progression and are increasingly acknowledged to contribute to therapy resistance. Accumulated evidence suggests that, upon radiation, fibroblasts/CAFs avoid cell death but instead enter a permanent senescent state, which in turn may influence the behavior of tumor cells and other components of the TME. Despite the proposed participation of senescent fibroblasts on tumor radioprotection, it is still incompletely understood the impact that RT has on CAFs and the ultimate role that irradiated CAFs have on therapy outcomes. Some of the current controversies may emerge from generalizing observations obtained using normal fibroblasts and CAFs, which are different cell entities that may respond differently to radiation exposure.

CONCLUSION

In this review we present current knowledge on the field of CAFs role in radiotherapy; we discuss the potential tumorigenic functions of radiation-induced senescent fibroblasts and CAFs and we make an effort to integrate the knowledge emerging from preclinical experimentation with observations from the clinics. Video Abstract.