Intersections between innate immune response and gastric cancer development.

Worldwide, gastric cancer (GC) is the fifth most commonly diagnosed malignancy. It has a reduced prevalence but has maintained its poor prognosis being the fourth leading cause of deaths related to cancer. The highest mortality rates occur in Asian and Latin American countries, where cases are usually diagnosed at advanced stages. Overall, GC is viewed as the consequence of a multifactorial process, involving the virulence of the Helicobacter pylori (H. pylori) strains, as well as some environmental factors, dietary habits, and host intrinsic factors. The tumor microenvironment in GC appears to be chronically inflamed which promotes tumor progression and reduces the therapeutic opportunities. It has been suggested that inflammation assessment needs to be measured qualitatively and quantitatively, considering cell-infiltration types, availability of receptors to detect damage and pathogens, and presence or absence of aggressive H. pylori strains. Gastrointestinal epithelial cells express several Toll-like receptors and determine the first defensive line against pathogens, and have been also described as mediators of tumorigenesis. However, other molecules, such as cytokines related to inflammation and innate immunity, including immune checkpoint molecules, interferon-gamma pathway and NETosis have been associated with an increased risk of GC. Therefore, this review will explore innate immune activation in the context of premalignant lesions of the gastric epithelium and established gastric tumors.

Simultaneous and Spatially-Resolved Analysis of T-Lymphocytes, Macrophages and PD-L1 Immune Checkpoint in Rare Cancers.

Penile, vulvar and anal neoplasms show an incidence lower than 0.5% of the population per year and therefore can be considered as rare cancers but with a dramatic impact on quality of life and survival. This work describes the experience of a Chilean cancer center using multiplexed immunofluorescence to study a case series of four penile cancers, two anal cancers and one vulvar cancer and simultaneous detection of CD8, CD68, PD-L1, Cytokeratin and Ki-67 in FFPE samples. Fluorescent image analyses were performed using open sources for automated tissue segmentation and cell phenotyping. Our results showed an objective and reliable counting of objects with a single or combined labeling or within a specific tissue compartment. The variability was below 10%, and the correlation between analytical events was 0.92-0.97. Critical cell phenotypes, such as TILs, PD-L1+ or proliferative tumor cells were detected in a supervised and unsupervised manner with a limit of detection of less than 1% of relative abundance. Finally, the observed diversity and abundance of the different cell phenotypes within the tumor microenvironment for the three studied tumor types confirmed that our methodology is useful and robust to be applicable for many other solid tumors.

Advances in mass cytometry and its applicability to digital pathology in clinical-translational cancer research.

The development and subsequent adaptation of mass cytometry for the histological analysis of tissue sections has allowed the simultaneous spatial characterization of multiple components. This is useful to find the correlation between the genotypic and phenotypic profile of tumor cells and their environment in clinical-translational studies. In this revision, we provide an overview of the most relevant hallmarks in the development, implementation and application of multiplexed imaging in the study of cancer and other conditions. A special focus is placed on studies based on imaging mass cytometry (IMC) and multiplexed ion beam imaging (MIBI). The purpose of this review is to help our readers become familiar with the verification techniques employed on this tool and outline the multiple applications reported in the literature. This review will also provide guidance on the use of IMC or MIBI in any field of biomedical research.

Improved ontology for eukaryotic single-exon coding sequences in biological databases.

Efficient extraction of knowledge from biological data requires the development of structured vocabularies to unambiguously define biological terms. This paper proposes descriptions and definitions to disambiguate the term 'single-exon gene'. Eukaryotic Single-Exon Genes (SEGs) have been defined as genes that do not have introns in their protein coding sequences. They have been studied not only to determine their origin and evolution but also because their expression has been linked to several types of human cancer and neurological/developmental disorders and many exhibit tissue-specific transcription. Unfortunately, the term 'SEGs' is rife with ambiguity, leading to biological misinterpretations. In the classic definition, no distinction is made between SEGs that harbor introns in their untranslated regions (UTRs) versus those without. This distinction is important to make because the presence of introns in UTRs affects transcriptional regulation and post-transcriptional processing of the mRNA. In addition, recent whole-transcriptome shotgun sequencing has led to the discovery of many examples of single-exon mRNAs that arise from alternative splicing of multi-exon genes, these single-exon isoforms are being confused with SEGs despite their clearly different origin. The increasing expansion of RNA-seq datasets makes it imperative to distinguish the different SEG types before annotation errors become indelibly propagated in biological databases. This paper develops a structured vocabulary for their disambiguation, allowing a major reassessment of their evolutionary trajectories, regulation, RNA processing and transport, and provides the opportunity to improve the detection of gene associations with disorders including cancers, neurological and developmental diseases.

The Reprimo Gene Family: A Novel Gene Lineage in Gastric Cancer with Tumor Suppressive Properties.

The reprimo (RPRM) gene family is a group of single exon genes present exclusively within the vertebrate lineage. Two out of three members of this family are present in humans: RPRM and RPRM-Like (RPRML). RPRM induces cell cycle arrest at G2/M in response to p53 expression. Loss-of-expression of RPRM is related to increased cell proliferation and growth in gastric cancer. This evidence suggests that RPRM has tumor suppressive properties. However, the molecular mechanisms and signaling partners by which RPRM exerts its functions remain unknown. Moreover, scarce studies have attempted to characterize RPRML, and its functionality is unclear. Herein, we highlight the role of the RPRM gene family in gastric carcinogenesis, as well as its potential applications in clinical settings. In addition, we summarize the current knowledge on the phylogeny and expression patterns of this family of genes in embryonic zebrafish and adult humans. Strikingly, in both species, RPRM is expressed primarily in the digestive tract, blood vessels and central nervous system, supporting the use of zebrafish for further functional characterization of RPRM. Finally, drawing on embryonic and adult expression patterns, we address the potential relevance of RPRM and RPRML in cancer. Active investigation or analytical research in the coming years should contribute to novel translational applications of this poorly understood gene family as potential biomarkers and development of novel cancer therapies.

SinEx DB: a database for single exon coding sequences in mammalian genomes.

Eukaryotic genes are typically interrupted by intragenic, noncoding sequences termed introns. However, some genes lack introns in their coding sequence (CDS) and are generally known as 'single exon genes' (SEGs). In this work, a SEG is defined as a nuclear, protein-coding gene that lacks introns in its CDS. Whereas, many public databases of Eukaryotic multi-exon genes are available, there are only two specialized databases for SEGs. The present work addresses the need for a more extensive and diverse database by creating SinEx DB, a publicly available, searchable database of predicted SEGs from 10 completely sequenced mammalian genomes including human. SinEx DB houses the DNA and protein sequence information of these SEGs and includes their functional predictions (KOG) and the relative distribution of these functions within species. The information is stored in a relational database built with My SQL Server 5.1.33 and the complete dataset of SEG sequences and their functional predictions are available for downloading. SinEx DB can be interrogated by: (i) a browsable phylogenetic schema, (ii) carrying out BLAST searches to the in-house SinEx DB of SEGs and (iii) via an advanced search mode in which the database can be searched by key words and any combination of searches by species and predicted functions. SinEx DB provides a rich source of information for advancing our understanding of the evolution and function of SEGs.Database URL: www.sinex.cl.