Current US Cancer Statistics: Alarming Trends in Young Adults?

Clinically Applicable Pathological Diagnosis System for Cell Clumps in Endometrial Cancer Screening via Deep Convolutional Neural Networks

OBJECTIVES

The soaring demand for endometrial cancer screening has exposed a huge shortage of cytopathologists worldwide. To address this problem, our study set out to establish an artificial intelligence system that automatically recognizes and diagnoses pathological images of endometrial cell clumps (ECCs).

METHODS

We used Li Brush to acquire endometrial cells from patients. Liquid-based cytology technology was used to provide slides. The slides were scanned and divided into malignant and benign groups. We proposed two (a U-net segmentation and a DenseNet classification) networks to identify images. Another four classification networks were used for comparison tests.

RESULTS

A total of 113 (42 malignant and 71 benign) endometrial samples were collected, and a dataset containing 15,913 images was constructed. A total of 39,000 ECCs patches were obtained by the segmentation network. Then, 26,880 and 11,520 patches were used for training and testing, respectively. On the premise that the training set reached 100%, the testing set gained 93.5% accuracy, 92.2% specificity, and 92.0% sensitivity. The remaining 600 malignant patches were used for verification.

CONCLUSIONS

An artificial intelligence system was successfully built to classify malignant and benign ECCs.

Diagnostic and prognostic value of MATN3 expression in gastric carcinoma: TCGA database mining

Backgrounds

Globally, the high morbidity and mortality of gastric carcinoma (GC) have been one of the great challenges facing humanity. However, the early diagnosis of GC is still unknown. Matrilin-3 (MATN3) is a member of the extracellular matrix (ECM) protein family. Previous studies have reported a correlation between the expression of MATN3 and bone disease. However, the role of MATN3 in GC has not been reported in depth, which can have a possible far-reaching implication for GC.

Methods

We explored the diagnostic and prognostic value and pathway enrichment of MATN3 expression in GC. Limma package conducted by R was used to analysis the difference expression data of MATN3 from The Cancer Genome Atlas (TCGA). The receiver operating characteristic (ROC) curve analysis was used to estimate the diagnostic value of MATN3 expression. univariate and multivariate analysis were used to assess the prognostic value of MATN3, and gene set enrichment analysis (GSEA) to identify the enriched signaling pathways.

Results

MATN3 was found to be significantly higher in GC tissue samples. GC patients with high MATN3 expression had poor prognosis. Then, GSEA showed that the gene sets were correlated with signaling pathways including ECM receptor interaction, hypertrophic cardiomyopathy (HCM), and glycosaminoglycan biosynthesis chondroitin sulfate, among others.

Conclusions

The study suggests that MATN3 can serve as a potential diagnostic and prognostic biomarker for GC.

Unsaturated fatty acid-tuned assembly of photosensitizers for enhanced photodynamic therapy via lipid peroxidation

Photodynamic therapy (PDT) destroys tumor cells mainly through singlet oxygen (¹O₂) generated by light-irradiated photosensitizers (PSs). However, the fleeting half-life of ¹O₂ greatly impairs PDT efficacy. Herein, we propose an unreported unsaturated fatty acid (UFA)-assisted PS co-assembly strategy to address this problem. Three UFAs, namely, oleic acid (OA), linoleic acid (LA) and linolenic acid (LNA), are capable of co-assembling with 5,10,15,20-tetrakis(4-aminophenyl)porphyrin (TAPP) into uniform nanoparticles. Under irradiation, TAPP produces ¹O₂, which directly attacks tumor cells and simultaneously oxidizes UFAs to generate lipid hydroperoxides with sustained damage. Interestingly, the unsaturation degree of UFAs is not only related to their peroxidation rate but also has a remarkable impact on the intracellular TAPP release characteristic of the nanoparticles (NPs). The TAPP-LA NPs could release the cargo rapidly and produce the highest lipid peroxidation and reactive oxygen species levels upon irradiation. Such a unique finding sheds new light on UFA-based combination applications for enhanced photodynamic efficacy by boosting lipid peroxidation.

Genomic and molecular alterations associated with early-onset and adolescent and young adult colorectal cancer

While the incidence of colorectal cancer (CRC) in the US has declined at a pace of 3% annually between 2003 and 2012, there has been an increase in the incidence of early-onset colorectal cancer (EOCRC). The reasons for this increase are unclear. Diet, the environment, the microbiome and alcohol consumption have all been proposed as contributing factors. There is the possibility that EOCRC has a unique biology. Overlapping with the EOCRC age range is CRC in adolescent and young adults (AYA) that share many molecular characteristics with EOCRC. The purpose of this review is to cover current progress in our understanding of the biology of CRC in the context of adolescent and young adult CRC and EOCRC and discuss future directions.

Sulforaphane: Expected to Become a Novel Antitumor Compound

Natural products are becoming increasingly popular in a variety of traditional, complementary, and alternative systems due to their potency and slight side effects. Natural compounds have been shown to be effective against many human diseases, especially cancers. Sulforaphane (SFE) is a traditional Chinese herbal medicine. In recent years, an increasing number of studies have been conducted to evaluate the antitumor effect of SFE. The roles of SFE in cancers are mainly through the regulation of potential biomarkers to activate or inhibit related signaling pathways. SFE has exhibited promising inhibitory effects on breast cancer, lung cancer, liver cancer, and other malignant tumors. In this review, we summarized the reports on the activity and functional mechanisms of SFE in cancer treatment and explored the efficacy and toxicity of SFE.