Tumor immunotherapy is the fourth therapy after surgery, chemotherapy, and radiotherapy. It has made great breakthroughs in the treatment of some epithelial tumors and hematological tumors. However, its adverse reactions are common or even more serious, and the response rate in some solid tumors is not satisfactory. With the maturity of genomics and metabolomics technologies, the effect of intestinal microbiota in tumor development and treatment has gradually been recognized. The microbiota may affect tumor immunity by regulating the host immune system and tumor microenvironment. Some bacteria help fight tumors by activating immunity, while some bacteria mediate immunosuppression to help cancer cells escape from the immune system. More and more studies have revealed that the effects and complications of tumor immunotherapy are related to the composition of the gut microbiota. The composition of the intestinal microbiota that is sensitive to treatment or prone to adverse reactions has certain characteristics. These characteristics may be used as biomarkers to predict the prognosis of immunotherapy and may also be developed as "immune potentiators" to assist immunotherapy. Some clinical and preclinical studies have proved that microbial intervention, including microbial transplantation, can improve the sensitivity of immunotherapy or reduce adverse reactions to a certain extent. With the development of gene editing technology and nanotechnology, the design and development of engineered bacteria that contribute to immunotherapy has become a new research hotspot. Based on the relationship between the intestinal microbiota and immunotherapy, the correct mining of microbial information and the development of reasonable and feasible microbial intervention methods are expected to optimize tumor immunotherapy to a large extent and bring new breakthroughs in tumor treatment.

/pdf/the-role-of-gut-microbiota-in-tumor-immunotherapy-4mrjk4ramw.pdf

The Role of Gut Microbiota in Tumor Immunotherapy

Many individuals diagnosed with autism spectrum disorder (ASD) experience gastrointestinal (GI) dysfunction and show microbial dysbiosis. Variation in gut microbial populations is associated with increased risk for GI symptoms such as chronic constipation and diarrhoea, which decrease quality of life. Several preclinical models of autism also demonstrate microbial dysbiosis. Given that much pre-clinical research is conducted in mouse models, it is important to understand the similarities and differences between the gut microbiome in humans and these models in the context of autism. We conducted a systematic review of the literature using PubMed, ProQuest and Scopus databases to compare microbiome profiles of patients with autism and transgenic (NL3R451C, Shank3 KO, 15q dup), phenotype-first (BTBR) and environmental (Poly I:C, Maternal Inflammation Activation (MIA), valproate) mouse models of autism. Overall, we report changes in fecal microbial communities relevant to ASD based on both clinical and preclinical studies. Here, we identify an overlapping cluster of genera that are modified in both fecal samples from individuals with ASD and mouse models of autism. Specifically, we describe an increased abundance of Bilophila, Clostridium, Dorea and Lactobacillus and a decrease in Blautia genera in both humans and rodents relevant to this disorder. Studies in both humans and mice highlighted multidirectional changes in abundance (i.e. in some cases increased abundance whereas other reports showed decreases) for several genera including Akkermansia, Bacteroides, Bifidobacterium, Parabacteroides and Prevotella, suggesting that these genera may be susceptible to modification in autism. Identification of these microbial profiles may assist in characterising underlying biological mechanisms involving host-microbe interactions and provide future therapeutic targets for improving gut health in autism.

/pdf/comparing-the-gut-microbiome-in-autism-and-preclinical-3q23fp2q.pdf

Comparing the Gut Microbiome in Autism and Preclinical Models: A Systematic Review

Autism spectrum disorder (ASD) is defined as a complex heterogeneous disorder and characterized by stereotyped behavior and deficits in communication and social interactions. The emerging microbial knowledge has pointed to a potential link between gut microbiota dysbiosis and ASD. Evidence from animal and human studies showed that shifts in composition and activity of the gut microbiota may causally contribute to the etiopathogenesis of core symptoms in the ASD individuals with gastrointestinal tract disturbances and act on microbiota-gut-brain. In this review, we summarized the characterized gut bacterial composition of ASD and the involvement of gut microbiota and their metabolites in the onset and progression of ASD; the possible underlying mechanisms are also highlighted. Given this correlation, we also provide an overview of the microbial-based therapeutic interventions such as probiotics, antibiotics, fecal microbiota transplantation therapy, and dietary interventions and address their potential benefits on behavioral symptoms of ASD. The precise contribution of altering gut microbiome to treating core symptoms in the ASD needs to be further clarified. It seemed to open up promising avenues to develop microbial-based therapies in ASD.

Alteration of Gut Microbiota: New Strategy for Treating Autism Spectrum Disorder

We read with interest the study by Kartal et al showing that the gutmicrobiotaderived biomarkers for disease stratification are often shared by subjects across disease cohorts. Here, we confirmed their observations with findings from a newly diagnosed natural killer/Tcell lymphoma (NKTCL) cohort, in which the gut biomarkers were significantly overlapped with those of multiple disease cohorts and consistently enriched/depleted in subjects with those diseases. Importantly, many of the shared biomarkers were remarkably associated with patient outcomes in our cohort, implying that they may have broad prognostic values in multiple diseases. ‘Microbiotagutlymphoma axis’ represents a fascinating avenue of microbiotamediated lymphomagenesis and intervention opportunity, but the implications of gut microbiota in NKTCL remain enigmatic. To identify gut microbiotaderived diagnostic biomarkers for NKTCL, we recruited a discovery cohort consisting of 30 treatmentnaïve patients and 20 healthy controls (HCs), and a validation cohort, including 12 patients and 13 HCs, respectively (online supplemental materials and methods). We applied shotgun metagenomic sequencing to their faecal samples, profiled their gut metagenomes using mOTUs2 V.2.5, and trained a patientstratification classifier with all specieslevel taxonomic features using the LASSO algorithm implemented in SIAMCAT. Our classifier achieved an accuracy of 0.868 area under the receiver operating characteristic curve (AUROC) on the discovery cohort, and 0.910 AUROC on the validation cohort (figure 1A). To increase the sample size for model training, we retrained a LASSO classifier for the NKTCL using all the samples from both cohorts, and achieved an accuracy of 0.813 AUROC in crossvalidation, which strongly support the role of gut microbiota as diagnostic biomarkers for NKTCL. To examine the specificity of the NKTCL gutmicrobiotaderived signature, we applied the allsample NKTCL classifier to 29 public gut microbiota cohorts (online supplemental table S1). We observed an overall false positive rate (FPR) of 3.1% in the HCs, but higher FPRs in patients of several cohorts (figure 1B), especially those of the pancreatic cancer (Kartal_ DE_2022_PC, Kartal_ES_2022_PC, Nagata_JP_2022_PC), Crohn’s Disease (He_2017_CD, Franzosa_2018_CD, Forslund_2015_CD) and liver disease (Qin_2014_LD). These results imply significant overlaps in the biomarkers between these diseases and NKTCL, which was confirmed using LEfSe analysis (figure 1C). Importantly, these biomarkers were consistently enriched/ depleted in most cohorts, including the enrichment of oralderived taxa of Veillonella and Streptococcus in the patients, and known beneficial species in HCs such as Faecalibacterium prausnitzii, Eubacterium rectale and Bifidobacterium adolescentis 6 7 (figure 1C). These findings indicate that our classifier can accurately distinguish NKTCL patients from HCs; nevertheless, due to the shared biomarkers with other diseases, combination of selected clinical indicators with microbial biomarkers would be salutary for a distinctive diagnostic model. Survival data were available for the NKTCL patients in the discovery cohort. Notably, many identified microbiome biomarkers, especially those shared by multiple diseases, could significantly predict the overall survival (OS) and progressionfree survival (PFS) of the patients, including Streptococcus parasanguinis, Romboutsia timonensis and Veillonella atypica (online supplemental figure 1A–D). Finally, we created a Streptococcus parasanguinis– Romboutsia timonensis index (SRI) as the relative abundance ratio of the two species, and obtained the best prognostic prediction power than other individual species and combinations. Namely, NKTCL patients with higher SRI scores showed significantly worse OS and PFS than those with lower SRI scores (figure 1D–E). Furthermore, we observed remarkable correlations between high SRI score and multiple adverse prognostic factors of NKTCL, including PINKE, stage, lymph node involvement and responses to firstline treatment (all p<0.05; figure 1F). Overall, our results lend support for gut microbiota as a potent assistive diagnostic tool for NKTCL. Moreover, the SRI score, based on the shared biomarkers, may have extensive prognostic utility in multiple diseases and deserves further scrutiny (online supplemental discussion). Zhuangzhuang Shi, Guoru Hu, Min W Li, Lei Zhang, Xin Li, Ling Li, Xinhua Wang, Xiaorui Fu, Zhenchang Sun, Xudong Zhang, Li Tian, Zhaoming Li, WeiHua Chen , Mingzhi Zhang Department of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China Department of Bioinformatics and Systems Biology, Huazhong University of Science and Technology College of Life Sciences and Technology, Wuhan, Hubei, China Lymphoma Diagnosis and Treatment Centre of Henan Province, Zhengzhou, Henan, China State Key Laboratory of Esophageal Cancer Prevention & Treatment and Henan Key Laboratory for Esophageal Cancer Research, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China Academy of Medical Sciences of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan, China Institution of Medical Artificial Intelligence, Binzhou Medical University, Yantai, Shandong, China College of Life Science, Henan Normal University, Xinxiang, Henan, China

https://gut.bmj.com/content/gutjnl/early/2022/11/08/gutjnl-2022-328256.full.pdf

Gut microbiota as non-invasive diagnostic and prognostic biomarkers for natural killer/T-cell lymphoma

Phenylketonuria is a recessive genetic disorder of amino-acid metabolism, where impaired phenylalanine hydroxylase function leads to the accumulation of neurotoxic phenylalanine levels in the brain. Severe cognitive and neuronal impairment are observed in untreated/late-diagnosed patients, and even early treated ones are not safe from life-long sequelae. Despite the wealth of knowledge acquired from available disease models, the chronic effect of Phenylketonuria in the brain is still poorly understood and the consequences to the aging brain remain an open question. Thus, there is the need for better predictive models, able to recapitulate specific mechanisms of this disease. Human induced pluripotent stem cells (hiPSCs), with their ability to differentiate and self-organize in multiple tissues, might provide a new exciting in vitro platform to model specific PKU-derived neuronal impairment. In this review, we gather what is known about the impact of phenylalanine in the brain of patients and highlight where hiPSC-derived organoids could contribute to the understanding of this disease.

/pdf/engineering-organoids-for-in-vitro-modeling-of-2m9obncr.pdf

Engineering Organoids for in vitro Modeling of Phenylketonuria

Lymphoid neoplasms encompass a heterogeneous group of malignancies with a predilection for immunocompromised individuals, and the disease burden of lymphoid neoplasms has been rising globally over ...

https://journals.sagepub.com/doi/pdf/10.1177/11795549211024197

Emerging Roles for the Gut Microbiome in Lymphoid Neoplasms.

/pdf/an-updated-rbd-fc-fusion-vaccine-booster-increases-28m5rrjb.pdf

An updated RBD-Fc fusion vaccine booster increases neutralization of SARS-CoV-2 Omicron variants

Taurolidine improved protection against highly pathogenetic avian influenza H5N1 virus lethal-infection in mouse model by regulating the NF-κB signaling pathway

Multiple myeloma (MM) is an aggressive plasma cell malignancy, causing a number of deaths worldwide every year. Chimeric antigen receptor (CAR) transduced T‐cell therapy has been a promising immunotherapy against hematological malignancies.

https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/cam4.5818

Zhuangzhuang Shi

Papers

Emerging Roles for the Gut Microbiome in Lymphoid Neoplasms.

Gut microbiota as non-invasive diagnostic and prognostic biomarkers for natural killer/T-cell lymphoma

An updated RBD-Fc fusion vaccine booster increases neutralization of SARS-CoV-2 Omicron variants

Taurolidine improved protection against highly pathogenetic avian influenza H5N1 virus lethal-infection in mouse model by regulating the NF-κB signaling pathway

A second‐generation CD38‐CAR‐T cell for the treatment of multiple myeloma