As the most frequently occurring cancer worldwide, breast cancer (BC) is the leading cause of cancer-related death in women. The overexpression of HER2 (human epidermal growth factor receptor 2) is found in about 15% of BC patients, and it is often associated with a poor prognosis due to the effect on cell proliferation, migration, invasion, and survival. As a result of the heterogeneity of BC, molecular imaging with HER2 probes can non-invasively, in real time, and quantitatively reflect the expression status of HER2 in tumors. This will provide a new approach for patients to choose treatment options and monitor treatment response. Furthermore, radionuclide molecular imaging has the potential of repetitive measurements, and it can help solve the problem of heterogeneous expression and conversion of HER2 status during disease progression or treatment. Different imaging probes of targeting proteins, such as monoclonal antibodies, antibody fragments, nanobodies, and affibodies, are currently in preclinical and clinical development. Moreover, in recent years, HER2-specific peptides have been widely developed for molecular imaging techniques for HER2-positive cancers. This article summarized different types of molecular probes targeting HER2 used in current clinical applications and the developmental trend of some HER2-specific peptides.

The aarF domain containing kinase 2 (ADCK2) is a mitochondria-locating protein, important for fatty acid metabolism and coenzyme Q biosynthesis. The bioinformatics results show that elevated ADCK2 transcripts in NSCLC correlate with poor overall survival and poor anti-PD-1/PD-L1 therapy response. ADCK2 is overexpressed in local human NSCLC tissues and various primary and established NSCLC cells. In NSCLC cells, ADCK2 shRNA or CRISPR/Cas9 knockout remarkably suppressed cell viability, proliferation, cell cycle progression, cell mobility, and provoked cell apoptosis. Moreover, ADCK2 depletion disrupted mitochondrial functions in NSCLC cells, causing cytochrome C release, mitochondrial depolarization, DNA damage and ATP reduction. Contrarily, ectopic ADCK2 overexpression promoted NSCLC cell growth. Further studies revealed that ADCK2 depletion inactivated Akt-mTOR signaling in primary NSCLC cells. NSCLC xenograft growth in nude mice was significantly hindered after ADCK2 silencing or knockout. ADCK2 depletion, apoptosis induction and oxidative injury as well as ATP reduction and Akt-mTOR inactivation were detected in ADCK2-silenced or ADCK2-knockout NSCLC xenograft tissues. Together overexpressed ADCK2 is important for the growth of NSCLC cells, representing an important therapeutic molecular oncotarget.

This study aimed to develop a predictive model utilizing radiomics and body composition features derived from 18F-FDG PET/CT scans to forecast progression-free survival (PFS) and overall survival (OS) outcomes in patients with esophageal squamous cell carcinoma (ESCC). We analyzed data from 91 patients who underwent baseline 18F-FDG PET/CT imaging. Radiomic features extracted from PET and CT images and subsequent radiomics scores (Rad-scores) were calculated. Body composition metrics were also quantified, including muscle and fat distribution at the L3 level from CT scans. Multiparametric survival models were constructed using Cox regression analysis, and their performance was assessed using the area under the time-dependent receiver operating characteristic (ROC) curve (AUC) and concordance index (C-index). Multivariate analysis identified Rad-scorePFS (P = 0.003), sarcopenia (P < 0.001), and visceral adipose tissue index (VATI) (P < 0.001) as independent predictors of PFS. For OS, Rad-scoreOS (P = 0.001), sarcopenia (P = 0.002), VATI (P = 0.037), stage (P = 0.042), and body mass index (BMI) (P = 0.008) were confirmed as independent prognostic factors. Integration of the Rad-score with clinical variables and body composition parameters enhanced predictive accuracy, yielding C-indices of 0.810 (95% CI: 0.737–0.884) for PFS and 0.806 (95% CI: 0.720–0.891) for OS. This study underscored the potential of combining Rad-score with clinical and body composition data to refine prognostic assessment in ESCC patients.

Hyperfunctional mitochondria provide a growth advantage by supporting the energy-intensive processes essential for non-small cell lung cancer (NSCLC). NADH:ubiquinone oxidoreductase core subunit S8 (NDUFS8) is a key subunit of mitochondrial complex I involved in oxidative phosphorylation (OXPHOS) and cellular energy production. Bioinformatics and local tissue examinations show that NDUFS8 expression is elevated in NSCLC compared to normal lung tissue. Both immortalized and primary human NSCLC cells exhibit higher NDUFS8 levels. Single-cell RNA sequencing confirmed NDUFS8 upregulation in cancerous cells of NSCLC tumor. Silencing NDUFS8 via shRNA or Cas9/sgRNA-mediated knockout (KO) disrupted mitochondrial functions, leading to decreased complex I activity, ATP depletion, mitochondrial depolarization, increased reactive oxygen species (ROS) production, and heightened lipid peroxidation. Furthermore, NDUFS8 silencing/KO triggered apoptosis and significantly reduced Akt-mTOR activation, cell viability, proliferation, and motility in various NSCLC cells. In contrast, ectopic overexpression of NDUFS8 boosted mitochondrial complex I activity and ATP levels, promoting Akt-mTOR activation, and enhancing NSCLC cell proliferation and motility. NDUFS8 also contributes to radioresistance in NSCLC; silencing or KO enhanced ionizing radiation (IR)-induced cytotoxicity, while overexpression mitigated it. Intratumoral injection of NDUFS8 shRNA-expressing adeno-associated virus significantly inhibited growth of primary NSCLC xenografts in nude mice, with observed NDUFS8 silencing, ATP reduction, oxidative damage, proliferation inhibition, Akt-mTOR inactivation and apoptosis in treated tissues. These findings highlight the pivotal pro-tumorigenic role of NDUFS8 in NSCLC.

Background: Patients with lung cancer face a heightened risk of developing sarcopenia. Despite this known risk, the impact of sarcopenia on the long-term prognosis of lung cancer patients, specifically concerning progression-free survival (PFS) and overall survival (OS), remains unclear. The primary objective of our study was to examine the correlation between metabolic parameters derived from ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) and sarcopenia, as well as the prognostic value of sarcopenia in patients with surgically resected early-stage non-small cell lung cancer (NSCLC). Methods: In this retrospective cross-sectional study, we analyzed 187 NSCLC patients who underwent ¹⁸F-FDG PET/CT at the First Affiliated Hospital of Soochow University between March 2019 and October 2023. Patients were divided into two groups based on the presence (n=46) or absence (n=141) of sarcopenia. The correlation between sarcopenia, metabolic parameters, and patient characteristics was evaluated using chi-square and Mann-Whitney U tests. Survival analyses, including PFS and OS, were conducted using Kaplan-Meier analysis and Cox proportional hazards regression. Based on sarcopenia, metabolic parameters and patient characteristics, patients were classified into high-risk (n=28), intermediate-risk (n=121), and low-risk (n=38) groups. Results: Our analysis identified gender, body mass index (BMI), psoas Hounsfield unit (HU), and maximum standardized uptake value of the psoas major muscle (SUV_max-Muscle) as independent predictors of sarcopenia (P<0.05 for all). A nomogram model, utilizing these parameters, was constructed to predict sarcopenia. Survival analysis further demonstrated that total lesion glycolysis [hazard ratio (HR) =2.499; 95% confidence interval (CI): 2.014–3.267; P=0.016], sarcopenia (HR =3.323; 95% CI: 1.748–6.316; P<0.001), and programmed death ligand-1 (PD-L1) expression (HR =0.093; 95% CI: 0.012–0.698; P=0.021) emerged as independent predictors of OS in early-stage NSCLC. Notably, patients categorized as high-risk, characterized by elevated total lesion glycolysis, presence of sarcopenia, and PD-L1 positivity, exhibited a significantly poorer prognosis compared to the intermediate-risk (P<0.05) and low-risk groups (P<0.05). Conclusions: Our findings indicated an inverse relationship between SUV_max-Muscle or psoas HU with the incidence of sarcopenia in NSCLC patients. Additionally, total lesion glycolysis, sarcopenia, and PD-L1 expression were identified as independent prognostic factors for OS in early-stage NSCLC. The risk stratification model, incorporating total lesion glycolysis, sarcopenia, and PD-L1 expression, assumed a pivotal role in guiding personalized therapy decisions and post-treatment monitoring.

Objective: It is crucially essential to differentially diagnose single-nodule pulmonary metastases (SNPMs) and second primary lung cancer (SPLC) in patients with colorectal cancer (CRC), which has important clinical implications for treatment strategies. In this study, we aimed to establish a feasible differential diagnosis model by combining¹⁸F-fluorodeoxyglucose positron-emission tomography (¹⁸F-FDG PET) radiomics, computed tomography (CT) radiomics, and clinical features.Materials and Methods: CRC patients with SNPM or SPLC who underwent¹⁸F-FDG PET/CT from January 2013 to July 2022 were enrolled in this retrospective study. The radiomic features were extracted by manually outlining the lesions on PET/CT images, and the radiomic modeling was realized by various screening methods and classifiers. In addition, clinical features were analyzed by univariate analysis and logistic regression (LR) analysis to be included in the combined model. Finally, the diagnostic performances of these models were illustrated by the receiver operating characteristic (ROC) curves and the area under the curve (AUC).Results: We studied data from 61 patients, including 36 SNPMs and 25 SPLCs, with an average age of 65.56 ± 10.355 years. Spicule sign and ground-glass opacity (GGO) were significant independent predictors of clinical features (P= 0.012 andP< 0.001, respectively) to build the clinical model. We achieved a PET radiomic model (AUC = 0.789), a CT radiomic model (AUC = 0.818), and a PET/CT radiomic model (AUC = 0.900). The PET/CT radiomic models were combined with the clinical model, and a well-performing model was established by LR analysis (AUC = 0.940).Conclusions: For CRC patients, the radiomic models we developed had good performance for the differential diagnosis of SNPM and SPLC. The combination of radiomic and clinical features had better diagnostic value than a single model.