Therapeutic co-assemblies for synergistic NSCLC treatment through dual topoisomerase I and tubulin inhibitors.

Camptothecin (CPT) and podophyllotoxin (PPT) function as topoisomerase (TOP) I and tubulin inhibitors, respectively, with potent anticancer effects in a variety of cancers. Despite its promise, the clinical applicability of the combination of CPT and PPT faces challenges, including potential side effect and limited therapeutic efficacy. In this study, we designed co-assembly nanomedicines with the different weight (w/w) ratios of amphiphilic Evans blue conjugated CPT prodrug (EB-ss-CPT) and PPT molecules, denoted as ECT Nano.

Comparative analysis of tertiary lymphoid structures for predicting survival of colorectal cancer: a whole-slide images-based study.

Background: Tertiary lymphoid structures (TLS) are major components in the immune microenvironment, correlating with a favorable prognosis in colorectal cancer. However, the methods used to define and characterize TLS were not united, hindering its clinical application. This study aims to seek a more stable method to characterize TLS and clarify their prognostic value in larger multicenter cohorts.

A novel GAN-based three-axis mutually supervised super-resolution reconstruction method for rectal cancer MR image.

Background And Objective: This study aims to enhance the resolution in the axial direction of rectal cancer magnetic resonance (MR) imaging scans to improve the accuracy of visual interpretation and quantitative analysis. MR imaging is a critical technique for the diagnosis and treatment planning of rectal cancer. However, obtaining high-resolution MR images is both time-consuming and costly.

Preoperative MRI Features Associated With Axillary Nodal Burden and Disease-Free Survival in Patients With Early-Stage Breast Cancer.

Objective: To investigate the potential association among preoperative breast MRI features, axillary nodal burden (ANB), and disease-free survival (DFS) in patients with early-stage breast cancer.

Materials And Methods: We retrospectively reviewed 297 patients with early-stage breast cancer (cT1-2N0M0) who underwent preoperative MRI between December 2016 and December 2018. Based on the number of positive axillary lymph nodes (LNs) determined by postoperative pathology, the patients were divided into high nodal burden (HNB; ≥3 positive LNs) and non-HNB (<3 positive LNs) groups.

Macrophage membrane-based biomimetic nanocarrier system for enhanced immune activation and combination therapy in liver cancer.

Previous studies have demonstrated that the combination of photodynamic therapy, photothermal therapy and chemotherapy is highly effective in treating hepatocellular carcinoma (HCC). However, the clinical application of this approach has been hindered by the lack of efficient and low-toxicity drug delivery platforms. To address this issue, we developed a novel biomimetic nanocarrier platform named ZID@RM, which utilizes ZIF8 functional nanoparticles encapsulated with macrophage membrane and loaded with indocyanine green and doxorubicin.

Multiparametric MRI-based Radiomics Analysis for Prediction of Lymph Node Metastasis and Survival Outcome in Gastric Cancer: A Dual-center Study.

Rationale And Objectives: Gastric cancer (GC) is highly heterogeneous, and accurate preoperative assessment of lymph node status remains challenging. We aimed to develop a multiparametric MRI-based model for predicting lymph node metastasis (LNM) in GC and to explore its prognostic implications.

Materials And Methods: In this dual-center retrospective study, 479 GC patients undergoing preoperative multiparametric MRI before radical gastrectomy were enrolled.

Incidence rate of occult lymph node metastasis in clinical TNM small cell lung cancer patients and radiomic prediction based on contrast-enhanced CT imaging: a multicenter study : Original research.

Background: This study aimed to explore the incidence of occult lymph node metastasis (OLM) in clinical TNM (cTNM) small cell lung cancer (SCLC) patients and develop machine learning prediction models using preoperative intratumoral and peritumoral contrast-enhanced CT-based radiomic data.

Methods: By conducting a retrospective analysis involving 242 eligible patients from 4 centeres, we determined the incidence of OLM in cTNM SCLC patients. For each lesion, two ROIs were defined using the gross tumour volume (GTV) and peritumoral volume 15 mm around the tumour (PTV).

Imaging segmentation mechanism for rectal tumors using improved U-Net.

Objective: In radiation therapy, cancerous region segmentation in magnetic resonance images (MRI) is a critical step. For rectal cancer, the automatic segmentation of rectal tumors from an MRI is a great challenge. There are two main shortcomings in existing deep learning-based methods that lead to incorrect segmentation: 1) there are many organs surrounding the rectum, and the shape of some organs is similar to that of rectal tumors; 2) high-level features extracted by conventional neural networks often do not contain enough high-resolution information.

FedDUS: Lung tumor segmentation on CT images through federated semi-supervised with dynamic update strategy.

Background And Objective: Lung tumor annotation is a key upstream task for further diagnosis and prognosis. Although deep learning techniques have promoted automation of lung tumor segmentation, there remain challenges impeding its application in clinical practice, such as a lack of prior annotation for model training and data-sharing among centers.

Methods: In this paper, we use data from six centers to design a novel federated semi-supervised learning (FSSL) framework with dynamic model aggregation and improve segmentation performance for lung tumors.

A medical image segmentation method for rectal tumors based on multi-scale feature retention and multiple attention mechanisms.

Background: With the continuous development of deep learning algorithms in the field of medical images, models for medical image processing based on convolutional neural networks have made great progress. Since medical images of rectal tumors are characterized by specific morphological features and complex edges that differ from natural images, achieving good segmentation results often requires a higher level of enrichment through the utilization of semantic features.

Purpose: The efficiency of feature extraction and utilization has been improved to some extent through enhanced hardware arithmetic and deeper networks in most models.

Multicenter Evaluation of a Weakly Supervised Deep Learning Model for Lymph Node Diagnosis in Rectal Cancer at MRI.

Purpose To develop a Weakly supervISed model DevelOpment fraMework (WISDOM) model to construct a lymph node (LN) diagnosis model for patients with rectal cancer (RC) that uses preoperative MRI data coupled with postoperative patient-level pathologic information. Materials and Methods In this retrospective study, the WISDOM model was built using MRI (T2-weighted and diffusion-weighted imaging) and patient-level pathologic information (the number of postoperatively confirmed metastatic LNs and resected LNs) based on the data of patients with RC between January 2016 and November 2017. The incremental value of the model in assisting radiologists was investigated.

A computed tomography-based multitask deep learning model for predicting tumour stroma ratio and treatment outcomes in patients with colorectal cancer: a multicentre cohort study.

Background: Tumour-stroma interactions, as indicated by tumour-stroma ratio (TSR), offer valuable prognostic stratification information. Current histological assessment of TSR is limited by tissue accessibility and spatial heterogeneity. The authors aimed to develop a multitask deep learning (MDL) model to noninvasively predict TSR and prognosis in colorectal cancer (CRC).

Radiomics analysis of multiparametric MRI for preoperative prediction of microsatellite instability status in endometrial cancer: a dual-center study.

Objective: To develop and validate a multiparametric MRI-based radiomics model for prediction of microsatellite instability (MSI) status in patients with endometrial cancer (EC).

Methods: A total of 225 patients from Center I including 158 in the training cohort and 67 in the internal testing cohort, and 132 patients from Center II were included as an external validation cohort. All the patients were pathologically confirmed EC who underwent pelvic MRI before treatment.

SwinHR: Hemodynamic-powered hierarchical vision transformer for breast tumor segmentation.

Accurate and automated segmentation of breast tumors in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) plays a critical role in computer-aided diagnosis and treatment of breast cancer. However, this task is challenging, due to random variation in tumor sizes, shapes, appearances, and blurred boundaries of tumors caused by inherent heterogeneity of breast cancer. Moreover, the presence of ill-posed artifacts in DCE-MRI further complicate the process of tumor region annotation.

RACK1 facilitates breast cancer progression by competitively inhibiting the binding of β-catenin to PSMD2 and enhancing the stability of β-catenin.

The receptor for activated C kinase 1 (RACK1) is a key scaffolding protein with multifunctional and multifaceted properties. By mediating protein-protein interactions, RACK1 integrates multiple intracellular signals involved in the regulation of various physiological and pathological processes. Dysregulation of RACK1 has been implicated in the initiation and progression of many tumors.

RTAU-Net: A novel 3D rectal tumor segmentation model based on dual path fusion and attentional guidance.

Background And Objective: According to the Global Cancer Statistics 2020, colorectal cancer has the third-highest diagnosis rate (10.0 %) and the second-highest mortality rate (9.4 %) among the 36 types.

Fructose-Induced mTORC1 Activation Promotes Pancreatic Cancer Progression through Inhibition of Autophagy.

Unlabelled: Excessive fructose intake is associated with the occurrence, progression, and poor prognosis of various tumors. A better understanding of the mechanisms underlying the functions of fructose in cancer could facilitate the development of better treatment and prevention strategies. In this study, we investigated the functional association between fructose utilization and pancreatic ductal adenocarcinoma (PDAC) progression.

Computerized tertiary lymphoid structures density on H&E-images is a prognostic biomarker in resectable lung adenocarcinoma.

The increased amount of tertiary lymphoid structures (TLSs) is associated with a favorable prognosis in patients with lung adenocarcinoma (LUAD). However, evaluating TLSs manually is an experience-dependent and time-consuming process, which limits its clinical application. In this multi-center study, we developed an automated computational workflow for quantifying the TLS density in the tumor region of routine hematoxylin and eosin (H&E)-stained whole-slide images (WSIs).

Comprehensively analysis of splicing factors to construct prognosis prediction classifier in prostate cancer.

Splicing factors (SFs) are proteins that control the alternative splicing (AS) of RNAs, which have been recognized as new cancer hallmarks. Their dysregulation has been found to be involved in many biological processes of cancer, such as carcinogenesis, proliferation, metastasis and senescence. Dysregulation of SFs has been demonstrated to contribute to the progression of prostate cancer (PCa).

An MRI-based scoring system for pretreatment risk stratification in locally advanced rectal cancer.

Background: Accurately assessing the risk of recurrence in patients with locally advanced rectal cancer (LARC) before treatment is important for the development of treatment strategies. The purpose of this study is to develop an MRI-based scoring system to predict the risk of recurrence in patients with LARC.

Methods: This was a multicenter observational study that enrolled participants who underwent neoadjuvant chemoradiotherapy.

Fructose promotes angiogenesis by improving vascular endothelial cell function and upregulating VEGF expression in cancer cells.

Background: Fructose is a very common sugar found in natural foods, while current studies demonstrate that high fructose intake is significantly associated with increased risk of multiple cancers and more aggressive tumor behavior, but the relevant mechanisms are not fully understood.

Methods: Tumor-grafting experiments and in vitro angiogenesis assays were conducted to detect the effect of fructose and the conditioned medium of fructose-cultured tumor cells on biological function of vascular endothelial cells (VECs) and angiogenesis. 448 colorectal cancer specimens were utilized to analyze the relationship between Glut5 expression levels in VECs and tumor cells and microvascular density (MVD).