Kaihong Huang

Correction for ‘Nanoparticles modified by triple single chain antibodies for MRI examination and targeted therapy in pancreatic cancer’ by Jinmao Zou et al. , Nanoscale , 2020, 12 , 4473–4490, https://doi.org/10.1039/C9NR04976B.

Background Pancreatic cancer (PC) is characterized by abnormally fibrotic mesenchyme, which notably influences on the effectiveness of immunotherapy. Low-dose arsenic trioxide (ATO, 1.0 μM) can inhibit the activation of pancreatic stellate cells (PSCs) and affect fibrosis, which is a potential strategy for enhancing the sensitivity to immunotherapy. Methods Extracellular matrix (ECM) models were employed to assess the regulatory effects of ATO on ECM and peripheral blood mononuclear cells. Orthotopic C57BL/6J models were utilized to evaluate the influence of ATO on CD8⁺T cell infiltration and immunotherapy in PC. Additionally, nanomaterials loaded with ATO designed to specifically target PSCs (scAbFAP-α-HMSNs-PAA-ATO) were produced to enhance targeting effects of ATO. Results Low-dose ATO (1.0 μM) suppressed PSCs activation, exhibiting potential for synergistic immunotherapy. Under low-dose ATO intervention, ECM underwent remodeling, leading to increases in CD8⁺T cell infiltration, thereby enhancing anti-PD-L1 therapy effect. We further demonstrated that low-dose ATO remodeled ECM by regulating the expression of LOXL3 in PSCs. scAbFAP-α-HMSNs-PAA-ATO exhibited improved targeting capabilities, and enhanced capacity to inhibit fibrosis and sensitize immunotherapy. Conclusions Our research reveals that low-dose ATO, by regulating LOXL3, remodels the ECM and enhances CD8⁺T cell infiltration, thus sensitizing the efficacy of immunotherapy, which provides a novel strategy for comprehensive treatment to PC.

Colon cancer, a frequently encountered malignancy, exhibits a comparatively poor survival prognosis. Perineural invasion (PNI), highly correlated with tumor progression and metastasis, is a substantial effective predictor of stage II-III colon cancer. Nonetheless, the lack of effective and facile predictive methodologies for detecting PNI prior operation in colon cancer remains a persistent challenge. Pre-operative computer tomography (CT) images and clinical data of patients diagnosed with stage II-III colon cancer between January 2015 and December 2023 were obtained from two sub-districts of Sun Yat-sen Memorial Hospital (SYSUMH). The LASSO/RF/PCA filters were used to screen radiomics features and LR/SVM models were utilized to construct radiomics model. A comprehensive model, shown as nomogram finally, combining with radiomics score and significant clinical features were developed and validated by area under the curve (AUC) and decision curve analysis (DCA). The total cohort, comprising 426 individuals, was randomly divided into a development cohort and a validation cohort as a 7:3 ratio. Radiomics scores were extracted from LASSO-SVM models with AUC of 0.898/0.726 in the development and validation cohorts, respectively. Significant clinical features (CA199, CA125, T-stage, and N-stage) were used to establish combining model with radiomics scores. The combined model exhibited superior reliability compared to single radiomics model in AUC value (0.792 vs. 0.726, p = 0.003) in validation cohorts. The radiomics-clinical model demonstrated an AUC of 0.918/0.792, a sensitivity of 0.907/0.813 and a specificity of 0.804/0.716 in the development and validation cohorts, respectively. The study developed and validated a predictive nomogram model combining radiomics scores and clinical features, and showed good performance in predicting PNI pre-operation in stage II-III colon cancer patients.

Pancreatic ductal adenocarcinoma (PDAC) is characterised by immune evasion that contribute to poor prognosis. Cancer‐associated fibroblasts (CAFs) play a pivotal role in orchestrating the PDAC tumour microenvironment. We investigated the role of CAF‐derived extracellular vesicle (EV)‐packaged long non‐coding RNAs (lncRNAs) in immune evasion and explored gene therapy using engineered EVs loading small interfering RNAs (siRNAs) as a potential therapeutic strategy. Our findings highlight the significance of EV‐packaged lncRNA RP11‐161H23.5 from CAF in promoting PDAC immune evasion by downregulating HLA‐A expression, a key component of antigen presentation. Mechanistically, RP11‐161H23.5 forms a complex with CNOT4, a subunit of the mRNA deadenylase CCR4‐NOT complex, enhancing the degradation of HLA‐A mRNA by shortening its poly(A) tail. This immune evasion mechanism compromises the anti‐tumour immune response. To combat this, we propose an innovative approach utilising engineered EVs as natural and biocompatible nanocarriers for siRNA‐based gene therapy and this strategy holds promise for enhancing the effectiveness of immunotherapy in PDAC. Overall, our study sheds light on the critical role of CAF‐derived EV‐packaged lncRNA RP11‐161H23.5/CNOT4/HLA‐A axis in PDAC immune evasion and presents a novel avenue for therapeutic intervention.

Background: This study aims to (1) identify preoperative testing-based characteristics associated with enhanced prognosis and survival for cholangiocarcinoma patients, and (2)create a distinctive nomogram to anticipate each patient’s cancer-specific survival (CSS). Methods: Retrospective analysis was performed on 197 CCA patients who underwent radical surgery at Sun Yat-sen Memorial Hospital; they were divided into a 131-person “training cohort” and a 66-person “internal validation cohort.“ The prognostic nomogram was created following a preliminary Cox proportional hazard regression search for independent factors influencing the patients’ CSS. Its applicable domain was examined via an external validation cohort, which included 235 patients from the Sun Yat-sen University Cancer Center. Results: The median follow-up period for the 131 patients in the training group was 49.3 months (range, 9.3 to 133.9 months). One-, three-, and five-year CSS rates were 68.7%, 24.5%, and 9.2%, respectively, with the median CSS length being 27.4 months (range: 1.4 to 125.2 months). PLT, CEA, AFP, tumor location, differentiation, lymph node metastasis, chemotherapy, and TNM stage were determined to be independent risk factors for CCA patients by univariate and multivariate Cox proportional hazard regression analysis. We were able to accurately predict postoperative CSS after incorporating all of these characteristics into a nomogram. The AJCC’s 8th edition staging method’s C-indices were statistically substantially (P < 0.001) lower than the nomogram’s C-indices (0.84, 0.77, and 0.74 in the training, internal and external validation cohorts respectively). Conclusions: A realistic and useful model for clinical decision-making and the optimization of therapy is presented as a nomogram that includes serum markers and clinicopathologic features for predicting postoperative survival in cholangiocarcinoma.

Background: Nearly one fourth of patients with pancreatic ductal adenocarcinoma (PDAC) occur to liver metastasis after surgery, and liver metastasis is a risk factor for prognosis for those patients with surgery therapy. However, there is no effective way to predict liver metastasis post-operation. Method: Clinical data and preoperative magnetic resonance imaging (MRI) of PDAC patients diagnosed between July 2010 and July 2020 were retrospectively collected from three hospital centers in China. The significant MRI radiomics features or clinicopathological characteristics were used to establish a model to predict liver metastasis in the development and validation cohort. Results: A total of 204 PDAC patients from three hospital centers were divided randomly (7:3) into development and validation cohort. Due to poor predictive value of clinical features, MRI radiomics model had similar receiver operating characteristics curve (ROC) value to clinical-radiomics combing model in development cohort (0.878 vs. 0.880, p = 0.897) but better ROC in validation dataset (0.815 vs. 0.732, p = 0.022). Radiomics model got a sensitivity of 0.872/0.750 and a specificity of 0.760/0.822 to predict liver metastasis in development and validation cohort, respectively. Among 54 patients randomly selected with post-operation specimens, fibrosis markers (α-smooth muscle actin) staining was shown to promote radiomics model with ROC value from 0.772 to 0.923 (p = 0.049) to predict liver metastasis. Conclusion: This study developed and validated an MRI-based radiomics model and showed a good performance in predicting liver metastasis in resectable PDAC patients.

Pancreatic ductal adenocarcinoma (PDAC) is one of the highest mortalities malignant tumors, which is characterized by difficult diagnosis, rapid progression and high recurrence rate. Nevertheless, PDAC responds poorly to conventional therapies, which highlights the urgency to identify novel prognostic and therapeutic targets. LEMT2 was a newly discovered protein-encoding gene with little cancer research and an unclear mechanism. Thus, this study aimed to illustrate LETM2 as the crucial oncogene for tumor progression in PDAC. In this study, we analyzed the expression level and prognostic value of LETM2 in multiple cancers using pan-cancer analysis. The analyses based on the TCGA-GTEx dataset indicated that the LETM2 expression was obviously elevated in several cancers, and it was the most significantly related to the dismal prognosis of PDAC. Subsequently, we demonstrated the functional role and mechanism of LETM2 by clinical sample evaluation, and in in vitro and in vivo experiments. Immunohistochemical analyses showed that high expression of LETM2 was correlated with poor outcomes of PDAC. Moreover, we demonstrated that LETM2 knockdown significantly inhibited tumor proliferation and metastasis, and promoted cell apoptosis, while LETM2 overexpression exerted the opposite effects. Finally, the impairment caused by LETM2-knockdown could be recovered via excitation of the PI3k-Akt pathway in vitro and in vivo animal models, which suggested that LETM2 could activate the downstream PI3K-Akt pathway to participate in PDAC progression. In conclusion, the study enhanced our understanding of LETM2 as an oncogene hallmark of PDAC. LETM2 may facilitate tumor progression by activating the PI3K-Akt signaling pathway, which provides potential targets for the diagnosis, treatment, and prognosis of pancreatic cancer.