Gastric Cancer and Viruses: A Fine Line between Friend or Foe

Investigation of Epstein-Barr virus, Cytomegalovirus, Human herpesvirus 6, and Polyoma viruses (JC virus, BK virus) among Gastric cancer patients: A cross sectional study

Background and Aims

Gastric cancer is a significant global issue with a high death rate. This malignancy could be associated with several viral agents such as EBV, CMV, HHV-6, JCV, and BKV.

Objective

Evaluation of EBV, CMV, HHV-6 ,and JCV, BKV frequency among gastric cancer patients.

Methods

In this cross-sectional study, a total number of 60 gastric cancer specimens (32 male, 28 female) were retrieved from the pathology lab. Formalin-fixed paraffin-embedded tissue was used for molecular testing. DNA was extracted from samples, according to protocol, and used for PCR reaction. Polymerase chain reactions were used to assess CMV, EBV, HHV-6, JCV, and BKV frequency.

Results and Conclusion

The mean age of the participants was 61 years and 53.3% (32) of the participants were Male. A total number of 5 samples (8.34%) were infected with viral agents. Four male gastric samples were infected with EBV (6.67%) and only one female sample contained the BKV genome (1.67%). Totally 8.34% of the samples were infected with EBV and BKV. The CMV, HHV-6, and JCV genome was not detected in the samples. In conclusion, the presence of two viral agents including EBV and BKV among male and female samples respectively, and the genome of other viruses were not detected.

Exploring the Microbiome in Gastric Cancer: Assessing Potential Implications and Contextualizing Microorganisms beyond H. pylori and Epstein-Barr Virus

While previous research has primarily focused on the impact of H. pylori and Epstein-Barr virus (EBV), emerging evidence suggests that other microbial influences, including viral and fungal infections, may also contribute to gastric cancer (GC) development. The intricate interactions between these microbes and the host's immune response provide a more comprehensive understanding of gastric cancer pathogenesis, diagnosis, and treatment. The review highlights the roles of established players such as H. pylori and EBV and the potential impacts of gut bacteria, mainly Lactobacillus, Streptococcus, hepatitis B virus, hepatitis C virus, and fungi such as Candida albicans. Advanced sequencing technologies offer unprecedented insights into the complexities of the gastric microbiome, from microbial diversity to potential diagnostic applications. Furthermore, the review highlights the potential for advanced GC diagnosis and therapies through a better understanding of the gut microbiome.

Mass Spectrometry-Based Proteomics of Minor Species in the Bulk: Questions to Raise with Respect to the Untargeted Analysis of Viral Proteins in Human Tissue

(1) Background: Untargeted mass spectrometry (MS)-based proteomic analysis is highly amenable to automation. Software algorithms translate raw spectral data into protein information obtained by a comparison to sequence databases. However, the technology has limitations, especially for analytes measured at the limit of detection. In a protein expression study of human gastric biopsies, the question arose whether or not it is possible, as well as sensible, to search for viral proteins in addition to those from the human host. (2) Methods: Experimental data-independent MS data were analyzed using protein sequences for oncoviruses, and BLAST analyses were performed to elucidate the level of sequence homology to host proteins. (3) Results: About one hundred viral proteins were assigned, but there was also up to 43% sequence homology to human proteins. (4) Conclusions: There are at least two reasons why the matches to viral proteins should be used with care. First, it is not plausible that large amounts of viral proteins should be present in human gastric biopsies, so the spectral quality of the peptides derived from viral proteins is likely low. As a consequence, the number of false assignments is high. Second, homologous peptides found both in human and virus proteomes contribute to matching errors. Thus, though shotgun proteomics raw data can technically be analyzed using any database, meaningful results cannot be always expected and a sanity check must be performed. Both instrumentation and bioinformatic processing in MS-based proteomics are continuously improving at lowering the limit of detection even further. Nevertheless, data output should always be controlled in order to avoid the over-interpretation of results.