Objective: To explore the value of dual-energy computed tomography (DECT) radiomics of the regional largest short-axis lymph nodes for evaluating lymph node metastasis in patients with rectal cancer.Materials and Methods: One hundred forty-one patients with rectal cancer (58 in LNM+ group, 83 in LNM- group) who underwent preoperative total abdominal DECT were divided into a training group and testing group (7:3 ratio). After post-processing DECT venous phase images, 120kVp-like images and iodine (water) images were obtained. The highest-risk lymph nodes were identified, and their long-axis and short-axis diameter and DECT quantitative parameters were measured manually by two experienced radiologists who were blind to the postoperative pathological results. Four DECT parameters were analyzed: arterial phase (AP) normalized iodine concentration, AP normalized effective atomic number, the venous phase (VP) normalized iodine concentration, and the venous phase normalized effective atomic number. The carcinoembryonic antigen (CEA) levels were recorded one week before surgery. Radiomics features of the largest lymph nodes were extracted, standardized, and reduced before modeling. Radomics signatures of 120kVp-like images (Rad-signature_120kVp) and iodine map (Rad-signature_Imap) were built based on Logistic Regression via Least Absolute Shrinkage and Selection Operator (LASSO).Results: Eight hundred thirty-three features were extracted from 120kVp-like and iodine images, respectively. In testing group, the radiomics features based on 120kVp-like images showed the best diagnostic performance (AUC=0.922) compared to other predictors [CT morphological indicators (short-axis diameter (AUC=0.779, IDI=0.262) and long-axis diameter alone (AUC=0.714, IDI=0.329)), CEA alone (AUC=0.540, IDI=0.414), and normalized DECT parameters alone (AUC=0.504-0.718, IDI=0.290-0.476)](P<0.05 in Delong test). Contrary, DECT iodine map-based radiomic signatures showed similar performance in predicting lymph node metastasis (AUC=0.866). The decision curve showed that the 120kVp-like-based radiomics signature has the highest net income.Conclusion: Predictive model based on DECT and the largest short-axis diameter lymph nodes has the highest diagnostic value in predicting lymph node metastasis in patients with rectal cancer.

As the richest immune cells in most tumor microenvironments (TMEs), tumor-associated macrophages (TAMs) play an important role in tumor development and treatment sensitivity. The phenotypes and functions of TAMs vary according to their sources and tumor progression. Different TAM phenotypes display distinct behaviors in terms of tumor immunity and are regulated by intracellular and exogenous molecules. Additionally, dysfunctional and oxidatively stressed mitochondrial-derived mitochondrial DNA (mtDNA) plays an important role in remodeling the phenotypes and functions of TAMs. This article reviews the interactions between mtDNA and TAMs in the TME and further discusses the influence of their performance on tumor genesis and development.

To assess the value of a multiparametric magnetic resonance imaging (MRI)-based model integrating radiomics features with clinical and MRI semantic features for preoperative evaluation of tumor budding (TB) in rectal cancer. A total of 120 patients with pathologically confirmed rectal cancer were retrospectively analyzed. The patients were randomized into training and validation cohorts in a 6:4 ratio. Radiomics features were extracted and selected from preoperative T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and contrast-enhanced T1-weighted imaging (T1CE) sequences, after which the corresponding radiomics score (RS) was calculated, and the radiomics models (T2WI model, DWI model, and T1CE model) were constructed. Logistic regression analysis was selected to develop a combined model integrated RS_T2WI, RS_DWI, RS_T1CE, and clinical and MRI semantic features. The efficacy of each model in diagnosing TB grade was observed by the receiver operating characteristic (ROC) curve. Decision curve analysis (DCA) was used to assess the clinical benefits of the models. Seven features were extracted and selected from each T2WI, DWI, and T1CE sequence to calculate the corresponding RS and construct the corresponding radiomics model. MRI reported N stage was an independent risk factor for TB. The area under the ROC curve of the combined model was 0.961 and 0.891 in the training and validation cohorts, respectively. The combined model showed better performance than the other models. DCA showed that the net benefit of the combined model was better than that of the other models in the vast majority of threshold probabilities. A combined model integrating radiomics features and MRI semantic features allows for noninvasive preoperative evaluation of TB grading in patients with rectal cancer.

Pancreatic carcinoma is an aggressive subtype of cancer with poor prognosis, known for its refractory nature. To address this challenge, we have established a stable nanoplatform that combines chemotherapy with photodynamic therapy (PDT) to achieve better curative efficacy. First, we designed and synthesized a disulfide-bonded paclitaxel (PTX)-based prodrug, which was further mixed with gemcitabine (GEM) and photosensitizer THPP in an optimized ratio. Subsequently, the mixture was added dropwise into amphiphilic polymer DSPE-PEG water solution to form micelles composed of DSPE-PEG nanoparticles (TPG NPs). The TPG NPs were around 135 nm, and showed great ability of DTT stimulated release of PTX and GEM. Moreover, the TPG NPs can be efficiently uptaken by pancreatic cancer PANC-1 cells and effectively kill them, especially when combined with 650 nm laser irradiation. Finally, the TPG NPs have shown enhanced long-term circulation ability and also exhibited efficient anti-tumor activity in combination with 650 nm laser irradiation in a pancreatic cancer mouse model. In summary, the designed TPG NPs possesses great potential for co-delivery of paclitaxel prodrug, GEM and THPP, which enables combined chemo-photodynamic therapy for cancer treatment. In addition, the stimulated release of PTX prodrug and GEM also allows for better targeting of tumor cells and the increased therapeutic effect against cancer cells. Overall, the TPG NPs can serve as a good candidate for pancreatic cancer treatment.