The burgeoning spatial multi-omics in human gastrointestinal cancers.

The development and progression of diseases in multicellular organisms unfold within the intricate three-dimensional body environment. Thus, to comprehensively understand the molecular mechanisms governing individual development and disease progression, precise acquisition of biological data, including genome, transcriptome, proteome, metabolome, and epigenome, with single-cell resolution and spatial information within the body's three-dimensional context, is essential. This foundational information serves as the basis for deciphering cellular and molecular mechanisms. Although single-cell multi-omics technology can provide biological information such as genome, transcriptome, proteome, metabolome, and epigenome with single-cell resolution, the sample preparation process leads to the loss of spatial information. Spatial multi-omics technology, however, facilitates the characterization of biological data, such as genome, transcriptome, proteome, metabolome, and epigenome in tissue samples, while retaining their spatial context. Consequently, these techniques significantly enhance our understanding of individual development and disease pathology. Currently, spatial multi-omics technology has played a vital role in elucidating various processes in tumor biology, including tumor occurrence, development, and metastasis, particularly in the realms of tumor immunity and the heterogeneity of the tumor microenvironment. Therefore, this article provides a comprehensive overview of spatial transcriptomics, spatial proteomics, and spatial metabolomics-related technologies and their application in research concerning esophageal cancer, gastric cancer, and colorectal cancer. The objective is to foster the research and implementation of spatial multi-omics technology in digestive tumor diseases. This review will provide new technical insights for molecular biology researchers.

Investigating gene signatures associated with immunity in colon adenocarcinoma to predict the immunotherapy effectiveness using NFM and WGCNA algorithms.

Colon adenocarcinoma (COAD), a frequently encountered and highly lethal malignancy of the digestive system, has been the focus of intensive research regarding its prognosis. The intricate immune microenvironment plays a pivotal role in the pathological progression of COAD; nevertheless, the underlying molecular mechanisms remain incompletely understood. This study aims to explore the immune gene expression patterns in COAD, construct a robust prognostic model, and delve into the molecular mechanisms and potential therapeutic targets for COAD liver metastasis, thereby providing critical support for individualized treatment strategies and prognostic evaluation. Initially, we curated a comprehensive dataset by screening 2600 immune-related genes (IRGs) from the ImmPort and InnateDB databases, successfully obtaining a rich data resource. Subsequently, the COAD patient cohort was classified using the non-negative matrix factorization (NMF) algorithm, enabling accurate categorization. Continuing on, utilizing the weighted gene co-expression network analysis (WGCNA) method, we analyzed the top 5000 genes with the smallest p-values among the differentially expressed genes (DEGs) between immune subtypes. Through this rigorous screening process, we identified the gene modules with the strongest correlation to the COAD subpopulation, and the intersection of genes in these modules with DEGs (COAD vs COAD vs Normal colon tissue) is referred to as Differentially Expressed Immune Genes Associated with COAD (DEIGRC). Employing diverse bioinformatics methodologies, we successfully developed a prognostic model (DPM) consisting of six genes derived from the DEIGRC, which was further validated across multiple independent datasets. Not only does this predictive model accurately forecast the prognosis of COAD patients, but it also provides valuable insights for formulating personalized treatment regimens. Within the constructed DPM, we observed a downregulation of CALB2 expression levels in COAD tissues, whereas NOXA1, KDF1, LARS2, GSR, and TIMP1 exhibited upregulated expression levels. These genes likely play indispensable roles in the initiation and progression of COAD and thus represent potential therapeutic targets for patient management. Furthermore, our investigation into the molecular mechanisms and therapeutic targets for COAD liver metastasis revealed associations with relevant processes such as fat digestion and absorption, cancer gene protein polysaccharides, and nitrogen metabolism. Consequently, genes including CAV1, ANXA1, CPS1, EDNRA, and GC emerge as promising candidates as therapeutic targets for COAD liver metastasis, thereby providing crucial insights for future clinical practices and drug development. In summary, this study uncovers the immune gene expression patterns in COAD, establishes a robust prognostic model, and elucidates the molecular mechanisms and potential therapeutic targets for COAD liver metastasis, thereby possessing significant theoretical and clinical implications. These findings are anticipated to offer substantial support for both the treatment and prognosis management of COAD patients.

Autophagy in Disease Onset and Progression.

Autophagy is a biological phenomenon whereby components of cells can self-degrade using autophagosomes. During this process, cells can clear dysfunctional organelles or unwanted elements. Autophagy can recycle unnecessary biomolecules into new components or sometimes, even destroy the cells themselves. This cellular process was first observed in 1962 by Keith R. Porter et al. Since then, autophagy has been studied for over 60 years, and much has been learned on the topic. Nevertheless, the process is still not fully understood. It has been proven, for example, that autophagy can be a positive force for maintaining good health by removing older or damaged cells. By contrast, autophagy is also involved in the onset and progression of various conditions caused by pathogenic infections. These diseases generally involve several important organs in the human body, including the liver, kidney, heart, and central nervous system. The regulation of the defects of autophagy defects may potentially be used to treat some diseases. This review comprehensively discusses recent research frontiers and topics of interest regarding autophagy-related diseases.

[A study on expression of p53, p27 and bcl-2 protein in non-small cell lung cancer].

BACKGROUND: To study the relationship between the expression of p53, p27, bcl-2 protein and the clinical pathological characteristics of non-small cell lung cancer (NSCLC). METHODS: Expression of p53, p27 and bcl-2 protein was detected in 76 NSCLC samples by immunohistochemistry. RESULTS: The positive rate of p53, p27 and bcl-2 protein was 36.84% (28/76), 44.74% (34/76) and 48.68% (37/76) respectively, and 7 cases were positive for p53, p27 and bcl-2 protein. Positive rate of p53, p27 and bcl-2 protein was not related to the pathological type, lymph node metastasis, and TNM stage. The positive rate of p53 in higher differentiation group was significantly lower than that in lower differentiation group (P < 0.05). The positive rate of p27 and bcl-2 in higher differentiation group was significantly higher than that in lower differentiation group (P < 0.05). CONCLUSIONS: Overexpression of p53, p27 and bcl-2 genes may play an important role in the oncogenesis and development of NSCLC.