Marshallnorup9680

Pancreatic cancer (PC) has a dismal prognosis due to its insidious early symptoms and poor early detection rate. Exosomes can be released by various cell types and tend to be a potential novel biomarker for PC detection. In this study, we explored the proteomic profiles of plasma exosomes collected from patients with PC at different stages and other pancreatic diseases.

Plasma samples were collected from six groups of patients, including PC at stage I/II, PC at stage III/IV, well-differentiated pancreatic neuroendocrine tumor (P-NET), pancreatic cystic lesions (PCLs), chronic pancreatitis (CP), and healthy controls (HCs). Plasma-derived exosomes were isolated by ultracentrifugation and identified routinely. Isobaric tags for relative and absolute quantification (iTRAQ) based proteomic analysis along with bioinformatic analysis were performed to elucidate the biological functions of proteins. The expression of exosomal ALIX was further confirmed by enzyme-linked immunosorbent assay in a larger cohort of pad on proteomic profiling, proteins isolated from the plasma-derived exosomes may function as ideal non-invasive biomarkers for the clinical diagnosis of PC. Importantly, exosomal ALIX combined with CA199 has great potentials in detection of PC, especially in distinguishing PC patients at early stages from advanced stages.

In summary, our study demonstrated that based on proteomic profiling, proteins isolated from the plasma-derived exosomes may function as ideal non-invasive biomarkers for the clinical diagnosis of PC. Importantly, exosomal ALIX combined with CA199 has great potentials in detection of PC, especially in distinguishing PC patients at early stages from advanced stages.

The naked-eye invisibility of indocyanine green fluorescence limits the application of near-infrared fluorescence imaging (NIR) systems for real-time navigation during sentinel lymph node biopsy (SLNB) in patients with breast cancer undergoing surgery. This study aims to evaluate the effectiveness and safety of a novel NIR system in visualizing indocyanine green fluorescence images in the surgical field and the application value of combined methylene blue (MB) and the novel NIR system in SLNB.

Sixty patients with clinical node-negative breast cancer received indocyanine green (ICG) and MB as tracers. click here Two NIR system instruments, namely, lymphatic fluorescence imaging system (LFIS) designed by the University of Science and Technology of China and vascular imager by Langfang Mingde Medical Biotechnology Co., Ltd. (Langfang vascular imager), were used as navigation assistance to locate sentinel lymph nodes (SLNs). Excising the lymph nodes developed by both MB and ICG by two NIR systems or palpably suspicious stration number ChiCTR2000039542.Background There is controversy about the characteristics and prognostic implications of signet ring cell gastric cancers and non-signet ring cell gastric cancers. Objective This study aims to evaluate clinicopathological characteristics and prognoses of signet ring cell carcinoma (SRCC) and non-signet ring cell carcinoma (NSRCC) of stomach. Methods Studies compared between SRCC and NSRCC of the stomach after gastrectomy and published before September 1st, 2020, in the PubMed, Cochrane, and Embase databases, were identified systematically. Results A total of 2,865 studies were screened, and 36 studies were included, with 19,174 patients in the SRCC group and 55,942 patients in the NSRCC group. SRCC patients were younger in age (P less then 0.001), less likely to be male patients (P less then 0.001), more afflicted with upper third lesions (P less then 0.001), and presenting with more Borrmann type IV tumors (P = 0.005) than NSRCC patients. Lymph nodes metastasis was similar between SRCC and NSRCC patients with advanced tumor stage (OR 0.86, 95% CI 0.671.10, P = 0.23), but lower in the SRCC than NSRCC patients with early tumor stage (OR 0.73; 95% CI 0.560.98, P = 0.02). SRCC patients had comparable survival outcomes with NSRCC patients for early gastric cancers (HR 1.05, 95% CI 0.651.68, P less then 0.001) but had significantly poor prognosis for patients with advanced tumor stage (HR 1.50, 95% CI 1.281.76, P less then 0.001). Conclusions Signet ring cell carcinomas of the stomach are an increasingly common histopathological subtype of gastric cancers. These kinds of patients tend to be younger in age and more often female. Although, signet ring cell gastric cancer is a negative prognostic factor for patients with advanced stage. The difference is that for early stage of signet ring cell gastric cancers, it has low lymph nodes metastasis rate and comparable prognosis with non-signet ring cell cancers.

Locally advanced rectal cancer (LARC) is a heterogeneous disease with little information about

status and image features. The purpose of this study was to analyze the association between T2 magnetic resonance imaging (MRI) radiomics features and

status in LARC patients.

Eighty-three patients with

status information and T2 MRI images between 2012.05 and 2019.09 were included. Least absolute shrinkage and selection operator (LASSO) regression was performed to assess the associations between features and gene status. The patients were divided 73 into training and validation sets. The C-index and the average area under the receiver operator characteristic curve (AUC) were used for performance evaluation.

The clinical characteristics of 83 patients in the

mutant and wild-type cohorts were balanced. Forty-two (50.6%) patients had

mutations, and 41 (49.4%) patients had wild-type

. A total of 253 radiomics features were extracted from the T2-MRI images of LARC patients. One radiomic feature named X.LL_scaled_std, a standard deviation value of scaled wavelet-transformed low-pass channel filter, was selected from 253 features (

=0.019). The radiomics-based C-index values were 0.801 (95% CI 0.772-0.830) and 0.703 (95% CI 0.620-0.786) in the training and validation sets,respectively.

Radiomics features could differentiate

status in LARC patients based on T2-MRI images. Further validation in a larger dataset is necessary in the future.

Radiomics features could differentiate KRAS status in LARC patients based on T2-MRI images. Further validation in a larger dataset is necessary in the future.