Gene-Microbiome Co-expression Networks in Colon Cancer

Exploring prognostic microbiota markers in patients with endometrial carcinoma: Intratumoral insights

Endometrial cancer, a leading gynecological malignancy, is profoundly influenced by the uterine microbiota, a key factor in disease prognosis and treatment. Our study underscores the distinct microbial compositions in endometrial cancer compared to adjacent non-cancerous tissues, revealing a dominant presence of p_Actinobacteria in cancerous tissues as opposed to p_Firmicutes in surrounding areas. Through comprehensive analysis, we identified 485 unique microorganisms in cancer tissues, 26 of which correlate with patient prognosis. Employing univariate Cox regression and LASSO regression analyses, we devised a microbial risk scoring model, effectively stratifying patients into high and low-risk categories, thereby providing predictive insights into their overall survival. We further developed a nomogram that incorporates the microbial risk score along with age, grade, and clinical stage, significantly enhancing the accuracy of our clinical prediction model for endometrial cancer. Moreover, our study delves into the differential immune landscapes of high-risk and low-risk patients. The low-risk group displayed a higher prevalence of activated B cells and increased T cell co-stimulation, indicative of a robust immune response. Conversely, high-risk patients showed elevated tumor immune dysfunction and exclusion scores, suggesting less favorable outcomes in immunotherapy. Notably, the efficacy of IPS-CTLA4 and PD1/PD-L1/PD-L2 blockers was substantially higher in the low-risk group, pointing to a more responsive immunotherapeutic approach. In summary, our research elucidates the unique microbial patterns in endometrial cancer and adjacent tissues, and establishes both a microbial risk score model and a clinical prediction nomogram. These findings highlight the potential of uterine microbiota as a biomarker for customizing treatment strategies, enabling precise interventions for high-risk patients while preventing overtreatment in low-risk cases. This study emphasizes the microbiota's role in tailoring immunotherapy, offering a novel perspective in the treatment and prognosis of endometrial cancer. Significantly, our study's expansive sample analysis from the TCGA-UCEC cohort, employing linear discriminant analysis effect size methodology, not only validates but also enhances our understanding of the microbiota's role in endometrial cancer, paving the way for novel diagnostic and therapeutic approaches in its management.

Review on computer-assisted biosynthetic capacities elucidation to assess metabolic interactions and communication within microbial communities

Microbial communities thrive through interactions and communication, which are challenging to study as most microorganisms are not cultivable. To address this challenge, researchers focus on the extracellular space where communication events occur. Exometabolomics and interactome analysis provide insights into the molecules involved in communication and the dynamics of their interactions. Advances in sequencing technologies and computational methods enable the reconstruction of taxonomic and functional profiles of microbial communities using high-throughput multi-omics data. Network-based approaches, including community flux balance analysis, aim to model molecular interactions within and between communities. Despite these advances, challenges remain in computer-assisted biosynthetic capacities elucidation, requiring continued innovation and collaboration among diverse scientists. This review provides insights into the current state and future directions of computer-assisted biosynthetic capacities elucidation in studying microbial communities.

A Multi-Omics Overview of Colorectal Cancer to Address Mechanisms of Disease, Metastasis, Patient Disparities and Outcomes

Human colorectal cancer (CRC) is one of the most common malignancies in men and women across the globe, albeit CRC incidence and mortality shows a substantial racial and ethnic disparity, with the highest burden in African American patients. Even with effective screening tools such as colonoscopy and diagnostic detection assays, CRC remains a substantial health burden. In addition, primary tumors located in the proximal (right) or distal (left) sides of the colorectum have been shown to be unique tumor types that require unique treatment schema. Distal metastases in the liver and other organ systems are the major causes of mortality in CRC patients. Characterizing genomic, epigenomic, transcriptomic and proteomic (multi-omics) alterations has led to a better understanding of primary tumor biology, resulting in targeted therapeutic advancements. In this regard, molecular-based CRC subgroups have been developed that show correlations with patient outcomes. Molecular characterization of CRC metastases has highlighted similarities and differences between metastases and primary tumors; however, our understanding as to how to improve patient outcomes based on metastasis biology is lagging and remains a major obstacle to improving CRC patient outcomes. In this review, we will summarize the multi-omics features of primary CRC tumors and their metastases across racial and ethnic groups, the differences in proximal and distal tumor biology, molecular-based CRC subgroups, treatment strategies and challenges for improving patient outcomes.

Host Genetics and Microbiota Interactions in Colorectal Cancer: Shared or Independent Risk?

The role of microbiota in colorectal cancer has been studied since alterations in its composition were observed. In addition, there are more and more pieces of evidence that microbiota could be implicated in colorectal cancer progression. Thus, the components of the microbiota could be biomarkers for the diagnosis and prognosis of colorectal cancer. In addition, it is important to address how the microbiota interacts with the host and how the host shapes the microbiota, in order to understand the biological pathways and mechanisms involved in their relationship and the consequences of their interactions in colorectal cancer. Thereby, it could be possible to find feasible measures and treatments to prevent or better diagnose colorectal cancer. In this review, we will try to summarize the role of the microbiota in colorectal cancer and its interactions with the host and the host genetics, coming to some conclusions that could be useful to find the gaps in our knowledge and propose future steps in this field.

Introduction to Genomic Network Reconstruction for Cancer Research

High-throughput genomic technologies have revolutionized the study of cancer. Current research in oncology is now limited more for the capacity of analyzing and interpreting data, rather than the availability of data itself. Integrative approaches to obtain functional information from data are at the core of the disciplines gathered under the systems biology banner. In this context, network models have been used to study cancer, from the identification of key molecules involved in the disease to the discovery of functional alterations associated with specific manifestations of the disease.In this chapter, we describe the state of the art of network reconstruction from genomic data, with an emphasis in gene expression experiments. We explore the strengths and limitations of correlation, Bayesian, and information theoretic approaches to network reconstruction. We present tools that leverage the flexibility of network science to gain a deeper understanding of cancer biology.

The Intratumor Microbiota Signatures Associate With Subtype, Tumor Stage, and Survival Status of Esophageal Carcinoma

Altered human microbiome characteristic has been linked with esophageal carcinoma (ESCA), analysis of microbial profiling directly derived from ESCA tumor tissue is beneficial for studying the microbial functions in tumorigenesis and development of ESCA. In this study, we identified the intratumor microbiome signature and investigated the correlation between microbes and clinical characteristics of patients with ESCA, on the basis of data and information obtained from The Cancer Microbiome Atlas (TCMA) and The Cancer Genome Atlas (TCGA) databases. A total of 82 samples were analyzed for microbial composition at various taxonomic levels, including 40 tumor samples of esophageal squamous cell carcinoma (ESCC), 20 tumor samples of esophageal adenocarcinoma (EAD), and 22 adjacent normal samples. The results showed that the relative abundance of several microbes changed in tumors compared to their paired normal tissues, such as Firmicutes increased significantly while Proteobacteria decreased in tumor samples. We also identified a microbial signature composed of ten microbes that may help in the classification of ESCC and EAD, the two subtypes of ESCA. Correlation analysis demonstrated that compositions of microbes Fusobacteria/Fusobacteriia/Fusobacteriales, Lactobacillales/Lactobacillaceae/Lactobacillus, Clostridia/Clostridiales, Proteobacteria, and Negativicutes were correlated with the clinical characteristics of ESCA patients. In summary, this study supports the feasibility of detecting intratumor microbial composition derived from tumor sequencing data, and it provides novel insights into the roles of microbiota in tumors. Ultimately, as the second genome of human body, microbiome signature analysis may help to add more information to the blueprint of human biology.

Probiotics and gut health

BACKGROUND

Gut microbiota is a complex ecosystem of bacteria, viruses, archea, protozoa and yeasts in our intestine. It has several functions maintaining human body equilibrium. Microbial " dysbiosis " can be responsible for several gastrointestinal diseases.

METHODS

to build a narrative review we performed a Pubmed, Medline, EMBASE search for English language papers, reviews, meta-analyses, case series, and randomized controlled trials (RCTs) by keywords and their associations: gut microbiota, dysbiosis, gastrointestinal diseases, probiotics.

RESULTS

gut microbiota is altered in several gastrointestinal diseases with very different pathophysiology. They range from multi-factorial diseases such as irritable bowel syndrome (IBS), non-alcoholic fatty liver disease (NAFLD) and gastric and colorectal cancers, immunemediated such as celiac disease, inflammatory bowel diseases (IBD), antibioticrelated such as Clostridium Difficile infection (CDI). Microbial dysbiosis re-modulation by probiotics is feasible and safe in some of them.

CONCLUSIONS

gut microbial dysbiosis is statistically associated with several gastro-intestinal diseases, affecting their pathophysiology. Its reverse by probiotics has some promising evidences of efficacy.