Thyroid Dysfunction (TD) is a common immune-related adverse events (irAEs) in the treatment of advanced lung cancer with programmed cell death protein 1 (PD-1) and programmed death 1 ligand (PD-L1) inhibitors, with incidence accounting for 6–8% of all irAEs. The incidence of TD is receiving increasing attention from clinicians, given its potential impact on clinical efficacy. However, the molecular mechanisms, biomarkers, and clinical impact of TD resulting from PD-1/PD-L1 inhibitor treatment in advanced lung cancer are unclear. To present a comprehensive review of current advancements in research about the molecular mechanisms, influential factors, and clinical manifestations in the treatment of advanced lung cancer with PD-1 and PD-L1 inhibitors, as well as the correlation between TD and the efficacy of PD-1 and PD-L1 inhibitors. A systematic search was conducted using PubMed, Web of Science, Cochrane Library, Embase and Google Scholar databases, with the keywords including thyroid dysfunction, efficacy, mechanisms, immune checkpoint inhibitors, PD-1/PD-L1 inhibitors, and advanced lung cancer. PD-1/PD-L1 inhibitors can induce T cell-mediated destructive thyroiditis, thyroid autoantibody-mediated autoimmunity, and a decrease in the number of immunosuppressive monocytes (circulating cluster of differentiation (CD)14⁺ human leukocyte antigen (HLA)-DRlow/negatives monocytes, CD14⁺ HLA-DR ^+ lo/neg), leading to TD. Several factors, including peripheral blood inflammatory markers, body mass index (BMI), baseline thyroid-stimulating hormone (TSH) level, gender, smoking history, hypertension, and previous opioid use, may also contribute to the development of TD. However, there is currently a lack of reliable predictive biomarkers for TD, although anti-thyroid antibodies, TSH levels, and peripheral blood inflammatory markers are expected to be predictive. Interestingly, some studies suggested a positive correlation between TD and clinical efficacy, i.e., patients experiencing TD showed better outcomes in objective response rate (ORR), disease control rate (DCR), progression-free survival (PFS), and overall survival (OS), compared with those without TD. However, most of these studies were single-center and had small sample sizes, so more multi-center studies are needed to provide further data support. TD resulting from PD-1/PD-L1 inhibitor treatment in advanced lung cancer may be associated with good clinical outcomes. The clarification of the molecular mechanisms underlying TD and the identification of reliable predictive biomarkers will guide clinicians in managing TD in this patient population.

Tumor treating fields (TTFields) are a type of sinusoidal alternating current electric field that has proven effective in inhibiting the reproduction of dividing tumor cells. Despite their recognized impact, the precise biophysical mechanisms underlying the unique effects of TTFields remain unknown. Many of the previous studies predominantly attribute the inhibitory effects of TTFields to mitotic disruption, with intracellular microtubules identified as crucial targets. However, this conceptual framework lacks substantiation at the mesoscopic level. This study addresses the existing gap by constructing force models for tubulin and other key subcellular structures involved in microtubule electrophysiological activities under TTFields exposure. The primary objective is to explore whether the electric force or torque exerted by TTFields significantly influences the normal structure and activities of microtubules. Initially, we examine the potential effect on the dynamic stability of microtubule structures by calculating the electric field torque on the tubulin dimer orientation. Furthermore, given the importance of electrostatics in microtubule-associated activities, such as chromosome segregation and substance transport of kinesin during mitosis, we investigate the interaction between TTFields and these electrostatic processes. Our data show that the electrodynamic effects of TTFields are most likely too weak to disrupt normal microtubule electrophysiological activities significantly. Consequently, we posit that the observed cytoskeleton destruction in mitosis is more likely attributable to non-mechanical mechanisms.

To investigate the correlation between thyroid dysfunction (TD) and the efficacy of programmed cell death protein 1 (PD-1) and programmed death ligand 1 (PD-L1) inhibitors in the treatment of advanced lung cancer, and the possible influencing factors for TD occurrence, providing insights that could guide individualized therapeutic approaches. The data of 120 advanced lung cancer patients from January 2019 to August 2024 were retrospectively collected. Then, the patients were divided into TD and non-TD subgroups according to whether TD occurred or not, to analyse the possible factors influencing the occurrence of TD and the correlation between TD and PD-1/PD-L1 inhibitor efficacy. For all cases, the baseline TSH level was significantly higher in the TD subgroup than in the non-TD subgroup (median: 2.33 mIU/L vs. 1.58 mIU/L, p = 0.001). The progression-free survival (PFS) was significantly longer in the TD subgroup than in the non-TD subgroup (mPFS: 7.90 months vs. 4.87 months, p = 0.003), and the patients in the TD subgroup had a lower HR for progression (0.499, 95% CI (0.317–0.766)). For the PD-1/PD-L1 inhibitor group, the baseline TSH level was also significantly higher in the TD subgroup than in the non-TD subgroup (median: 2.16 mIU/L vs. 1.52 mIU/L, p = 0.009). The PFS was also significantly longer in the TD subgroup than in the non-TD subgroup (mPFS: 8.83 months vs. 6.50 months, p = 0.041). The baseline TSH level was the predictive factor for the occurrence of TD. The occurrence of TD was positively associated with a favorable prognosis for patients with advanced lung cancer.

TTFields is a novel FDA-approved technology utilized for treating glioblastoma multiforme (GBM) within the brain. Presently, the effectiveness of therapy is evaluated through MRI imaging at random two-month intervals. Electrical impedance is an important and effective parameter for reflecting changes in tissue properties. In TTFields treatment for brain tumors, electrodes attached to the scalp deliver electric field energy to the tumor region. We hypothesize that these electrodes can also serve as sensors to detect impedance changes caused by tumor alterations in real time, thus continuously assessing the effectiveness of the treatment. In this work, we propose and scrutinize this hypothesis by conducting an in silico study to confirm the potential feasibility of the proposed concept. Our results indicate that the impedance amplitude change measured between opposing TTFields electrode arrays utilizing voltage and frequency of 50 V and 200 kHz (typical TTFields treatment parameters), has enough resolution (> 1mm) and Signal-to-Noise Ratio (> 40 dB) to evaluate tumor size change in the head. The impedance detection technique may be a significant augmentation to TTFields cancer treatment, enabling the continuous evaluation of safety and efficacy throughout the procedure.

Claudin18.2 is a highly specific therapeutic target selectively expressed in gastric cancer cells. Emerging evidence suggests that Claudin18.2 positivity m