Chang Chen’s research while affiliated with The Hong Kong Polytechnic University and other places

The progression of lung adenocarcinoma is primarily driven by cancer stem cells (CSCs), which have self-renewal capabilities and confer resistance to therapies, including neoadjuvant treatments combining chemotherapy and immune checkpoint inhibitors. In this study, we identified that OV6 ⁺ tumor cells exhibit stem-like characteristics and are notably enriched in patients with non–major pathological response, closely associated with resistance to combination therapies. Hypoxia and HIF1α were found to drive the formation of OV6 ⁺ CSCs. METTL3, a methyltransferase, was revealed as a critical regulator of OV6 ⁺ CSCs by stabilizing NFE2L3 messenger RNA via an N ⁶ -methyladenosine–dependent manner, thereby up-regulating NFE2L3 and activating the intrinsic WNT signaling pathway essential for maintaining stemness. OV6 ⁺ tumor cells promoted M2 macrophage infiltration and the formation of an immunosuppressive tumor microenvironment (TME). Targeting METTL3 effectively eliminated OV6 ⁺ CSCs and suppressed tumor progression. Moreover, the combination of STM2457 with cisplatin overcame chemoresistance, remodeled the TME, and provided promising insights for enhancing the efficacy of neoadjuvant combination therapies.

Micro/nanorobots are being increasingly utilized as new diagnostic and therapeutic platforms in the biomedical field, enabling remote navigation to hard‐to‐reach tissues and the execution of various medical procedures. Although significant progress has been made in the development of biomedical micro/nanorobots, how to achieve closed‐loop control of them from sensing, memory, and precise trajectory planning to feedback to carry out biomedical tasks remains a challenge. Bacteria with self‐propulsion and autonomous intelligence properties are well suited to be engineered as microrobots to achieve closed‐loop control for biomedical applications. By virtue of synthetic biology, bacterial microrobots possess an expanded genetic toolbox, allowing them to load input sensors to respond or remember external signals. To achieve accurate control in the complex physiological environment, the development of bacterial microrobots should be matched with the corresponding control system design. In this review, a detailed summary of the sensing and control mechanisms of bacterial microrobots is presented. The engineering and applications of bacterial microrobots in the biomedical field are highlighted. Their future directions of bacterial autonomous intelligent microrobots for precision medicine are forecasted.

Autonomous driving progress relies on large-scale annotated datasets. In this work, we explore the potential of generative models to produce vast quantities of freely-labeled data for autonomous driving applications and present SubjectDrive, the first model proven to scale generative data production in a way that could continuously improve autonomous driving applications. We investigate the impact of scaling up the quantity of generative data on the performance of downstream perception models and find that enhancing data diversity plays a crucial role in effectively scaling generative data production. Therefore, we have developed a novel model equipped with a subject control mechanism, which allows the generative model to leverage diverse external data sources for producing varied and useful data. Extensive evaluations confirm SubjectDrive's efficacy in generating scalable autonomous driving training data, marking a significant step toward revolutionizing data production methods in this field.

Diagnosing lung cancer at a curable stage offers the opportunity for a favorable prognosis. The emerging epigenomics analysis on plasma cell-free DNA (cfDNA), including 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC) modifications, has acted as a promising approach facilitating the identification of lung cancer. And, integrating 5mC biomarker with chest computed tomography (CT) image features could optimize the diagnosis of lung cancer, exceeding the performance of models built on single feature. However, the clinical applicability of integrated markers might be limited by the potential risk of overfitting due to small sample size. Hence, we prospectively collected peripheral blood sample and the paired chest CT images of 2032 patients with indeterminate pulmonary nodules across 5 centers, and constructed a large-scale, multi-institutional, multiomics database that encompass CT imaging data and plasma cfDNA fragmentomic in 5mC-, 5hmC-enriched regions. To our best knowledge, this dataset is the first radio-epigenomic dataset with the largest sample size, and provides multi-dimensional insights for early diagnosis of lung cancer, facilitating the individuated management for lung cancer.

Calreticulin (CALR) preserves reticular homeostasis by maintaining correct protein folding within the endoplasmic reticulum. Immunogenic cell death (ICD) is a regulated form of cell death and could activate adaptive immune response. As one of the damage-associated molecular patterns during ICD process, surface-exposed CALR resulted in the activation of adaptive immune response. Here, we evaluated the expression patterns of CALR in a cohort of 231 untreated triple-negative breast cancer (TNBC) and determined correlations between CALR expression and clinicopathologic parameters, programmed cell death ligand 1 (PD-L1) expression in immune cells (ICs), and survival. In addition, we analyzed a TNBC data set from The Cancer Genome Atlas to explore the relationship between mRNA expression of CALR and clinicopathologic features, IC infiltration, and survival. Tissue microarray results showed that high CLAR was strongly correlated with advanced stage ( P = 0.022), shorter disease-free survival ( P = 0.008) and overall survival ( P = 0.002), and independently predicted prognosis in TNBC. Spearman analyses demonstrated that CALR negatively correlated with PD-L1 in ICs ( r = -0.198, P = 0.003). Patients with low CALR and high PD-L1 in ICs had the best disease-free survival ( P = 0.013) and overall survival ( P = 0.004) compared with other patients, especially the patients with high CALR and low PD-L1 in ICs. In the “The Cancer Genome Atlas” cohort, CALR mRNA expression in tumors was significantly higher than that in normal tissues ( P < 0.001). CALR expression was strongly and positively related to other ICD-related genes. These findings demonstrated that the expression of CALR could independently predict the prognosis in patients with TNBC, and it may play a potential synergistic role in treatments involving immunotherapy.