Artificial intelligence-derived gut microbiome as a predictive biomarker for therapeutic response to immunotherapy in lung cancer: protocol for a multicentre, prospective, observational study

Exploiting bacteria for cancer immunotherapy

Immunotherapy has revolutionized the treatment of cancer but continues to be constrained by limited response rates, acquired resistance, toxicities and high costs, which necessitates the development of new, innovative strategies. The discovery of a connection between the human microbiota and cancer dates back 4,000 years, when local infection was observed to result in tumour eradication in some individuals. However, the true oncological relevance of the intratumoural microbiota was not recognized until the turn of the twentieth century. The intratumoural microbiota can have pivotal roles in both the pathogenesis and treatment of cancer. In particular, intratumoural bacteria can either promote or inhibit cancer growth via remodelling of the tumour microenvironment. Over the past two decades, remarkable progress has been made preclinically in engineering bacteria as agents for cancer immunotherapy; some of these bacterial products have successfully reached the clinical stages of development. In this Review, we discuss the characteristics of intratumoural bacteria and their intricate interactions with the tumour microenvironment. We also describe the many strategies used to engineer bacteria for use in the treatment of cancer, summarizing contemporary data from completed and ongoing clinical trials. The work described herein highlights the potential of bacteria to transform the landscape of cancer therapy, bridging ancient wisdom with modern scientific innovation.

Modulating gut microbiome in cancer immunotherapy: Harnessing microbes to enhance treatment efficacy

Immunotherapy has emerged as a robust approach against cancer, yet its efficacy has varied among individuals, accompanied by the occurrence of immune-related adverse events. As a result, the efficacy of immunotherapy is far from satisfactory, and enormous efforts have been invested to develop strategies to improve patient outcomes. The gut microbiome is now well acknowledged for its critical role in immunotherapy, with better understanding on host-microbes interaction in the context of cancer treatment. Also, an increasing number of trials have been conducted to evaluate the potential and feasibility of microbiome-targeting approaches to enhance efficacy of cancer treatment in patients. Here, the role of the gut microbiome and metabolites (e.g., short-chain fatty acids, tryptophan metabolites) in immunotherapy and the underlying mechanisms are explored. The application of microbiome-targeting approaches that aim to improve immunotherapy efficacy (e.g., fecal microbiota transplantation, probiotics, dietary intervention) is also elaborated, with further discussion on current challenges and suggestions for future research.

Multi-omics and artificial intelligence predict clinical outcomes of immunotherapy in non-small cell lung cancer patients

In recent years, various types of immunotherapy, particularly the use of immune checkpoint inhibitors targeting programmed cell death 1 or programmed death ligand 1 (PD-L1), have revolutionized the management and prognosis of non-small cell lung cancer. PD-L1 is frequently used as a biomarker for predicting the likely benefit of immunotherapy for patients. However, some patients receiving immunotherapy have high response rates despite having low levels of PD-L1. Therefore, the identification of this group of patients is extremely important to improve prognosis. The tumor microenvironment contains tumor, stromal, and infiltrating immune cells with its composition differing significantly within tumors, between tumors, and between individuals. The omics approach aims to provide a comprehensive assessment of each patient through high-throughput extracted features, promising a more comprehensive characterization of this complex ecosystem. However, features identified by high-throughput methods are complex and present analytical challenges to clinicians and data scientists. It is thus feasible that artificial intelligence could assist in the identification of features that are beyond human discernment as well as in the performance of repetitive tasks. In this paper, we review the prediction of immunotherapy efficacy by different biomarkers (genomic, transcriptomic, proteomic, microbiomic, and radiomic), together with the use of artificial intelligence and the challenges and future directions of these fields.

Role of gut microbiome in cancer immunotherapy: from predictive biomarker to therapeutic target

Immunotherapy has emerged as an effective treatment for various types of cancers. Recent studies have highlighted a significant correlation between the gut microbiome and patients' response to immunotherapy. Several characteristics of the gut microbiome, such as community structures, taxonomic compositions, and molecular functions, have been identified as crucial biomarkers for predicting immunotherapy response and immune-related adverse events (irAEs). Unlike other -omics, the gut microbiome can serve as not only biomarkers but also potential targets for enhancing the efficacy of immunotherapy. Approaches for modulating the gut microbiome include probiotics/prebiotics supplementation, dietary interventions, fecal microbiota transplantation (FMT), and antibiotic administration. This review primarily focuses on elucidating the potential role of the gut microbiome in predicting the response to cancer immunotherapy and improving its efficacy. Notably, we explore reasons behind inconsistent findings observed in different studies, and highlight the underlying benefits of antibiotics in liver cancer immunotherapy.

The Role of Gut Microbiota in the Clinical Outcome of Septic Patients: State of the Art and Future Perspectives

Sepsis is a life-threatening multiple-organ dysfunction caused by a dysregulated host response to infection, with high mortality worldwide; 11 million deaths per year are attributable to sepsis in high-income countries. Several research groups have reported that septic patients display a dysbiotic gut microbiota, often related to high mortality. Based on current knowledge, in this narrative review, we revised original articles, clinical trials, and pilot studies to evaluate the beneficial effect of gut microbiota manipulation in clinical practice, starting from an early diagnosis of sepsis and an in-depth analysis of gut microbiota.

The current landscape of predictive and prognostic biomarkers for immune checkpoint blockade in ovarian cancer

Immune checkpoint blockade (ICB) therapy has evoked a prominent shift in anticancer therapy. Durable clinical antitumor activity to ICB has been observed in patients with ovarian cancer (OC). However, only a subset of patients derive clinical benefit, and immune-related adverse events (irAEs) caused by ICB therapy can lead to permanent tissue damage and even fatal consequences. It is thus urgent to develop predictive biomarkers to optimize patient outcomes and minimize toxicity risk. Herein, we review current predictive and prognostic biomarkers for checkpoint immunotherapy in OC and highlight emerging biomarkers to guide treatment with ICB. The prevalent biomarkers, such as PD-L1 expression status, tumor-infiltrating lymphocytes, mutational burden, and immune gene signatures, are further discussed. We provide a state-of-the-art survey on prognostic and predictive biomarkers for checkpoint immunotherapy and offer valuable information for guiding precision immunotherapy