BACKGROUND. Multiple islet autoantibodies (AAbs) predict the development of type 1 diabetes (T1D) and hyperglycemia within 10 years. By contrast, T1D develops in only approximately 15% of individuals who are positive for single AAbs (generally against glutamic acid decarboxylase [GADA]); hence, the single GADA⁺ state may represent an early stage of T1D. METHODS. Here, we functionally, histologically, and molecularly phenotyped human islets from nondiabetic GADA⁺ and T1D donors. RESULTS. Similar to the few remaining β cells in the T1D islets, GADA⁺ donor islets demonstrated a preserved insulin secretory response. By contrast, α cell glucagon secretion was dysregulated in both GADA⁺ and T1D islets, with impaired glucose suppression of glucagon secretion. Single-cell RNA-Seq of GADA⁺ α cells revealed distinct abnormalities in glycolysis and oxidative phosphorylation pathways and a marked downregulation of cAMP-dependent protein kinase inhibitor β (PKIB), providing a molecular basis for the loss of glucose suppression and the increased effect of 3-isobutyl-1-methylxanthine (IBMX) observed in GADA⁺ donor islets. CONCLUSION. We found that α cell dysfunction was present during the early stages of islet autoimmunity at a time when β cell mass was still normal, raising important questions about the role of early α cell dysfunction in the progression of T1D. FUNDING. This work was supported by grants from the NIH (3UC4DK112217-01S1, U01DK123594-02, UC4DK112217, UC4DK112232, U01DK123716, and P30 DK019525) and the Vanderbilt Diabetes Research and Training Center (DK20593).

Microbiome, including bacteria, fungi, and viruses, plays a crucial role in shaping distal and proximal anti-tumor immunity. Mounting evidence showed that commensal microbiome critically modulates immunophenotyping of hepatocellular carcinoma (HCC), a leading cause of cancer-related death. However, their role in anti-tumor surveillance of HCC is still poorly understood. Herein, we spotlighted growing interests in how the microbiome influences the progression and immunotherapeutic responses of HCC via changing local tumor microenvironment (TME) upon translocating to the sites of HCC through different “cell-type niches”. Moreover, we summarized not only the associations but also the deep insight into the mechanisms of how the extrinsic microbiomes interplay with hosts to shape immune surveillance and regulate TME and immunotherapeutic responses. Collectively, we provided a rationale for a mechanism-guided fine-tuned microbiome to be neoadjuvant immunotherapy in the near future.

Helicobacter pylori (H. pylori), a globally prevalent pathogen Group I carcinogen, presents a formidable challenge in gastric cancer prevention due to its increasing antimicrobial resistance and strain diversity. This comprehensive review critically analyzes the limitations of conventional antibiotic-based therapies and explores cutting-edge approaches to combat H. pylori infections and associated gastric carcinogenesis. We emphasize the pressing need for innovative therapeutic strategies, with a particular focus on precision medicine and tailored vaccine development. Despite promising advancements in enhancing host immunity, current Helicobacter pylori vaccine clinical trials have yet to achieve long-term efficacy or gain approval regulatory approval. We propose a paradigm-shifting approach leveraging artificial intelligence (AI) to design precision-targeted, multiepitope vaccines tailored to multiple H. pylori subtypes. This AI-driven strategy has the potential to revolutionize antigen selection and optimize vaccine efficacy, addressing the critical need for personalized interventions in H. pylori eradication efforts. By leveraging AI in vaccine design, we propose a revolutionary approach to precision therapy that could significantly reduce H. pylori -associated gastric cancer burden.

Vaccine development for pathogens has faced significant challenges, contributing to a public health burden. B‐cell epitope (BCE) prediction is a crucial process in vaccine development, but is hindered by limited efficiency and accuracy. To address this, B‐Epic, the first pipeline applying Transformer to predict BCEs is independently developed. B‐Epic's robustness is validated through multiple testing datasets, including distinguishing clinically‐approved vaccine targets, identifying BCEs (the Immune Epitope Database testing dataset; n = 23,888) and immunoreactive peptides ( Trypanosoma cruzi peptidome; n = 239,575) with high AUCs of 0.882 and 0.945, respectively, outperforming widely used tools. Based on its superior performance, B‐Epic is applied to the prevention of carcinogenic pathogens. In the application to Helicobacter pylori , peptides screened by B‐Epic can activate B cells in experiments, suggesting their potential as vaccine targets. In another application to Epstein‐Barr virus, B‐Epic identifies pan‐immunoreactive peptides in a clinical cohort ( n = 899). These peptides exhibit higher reactogenicity in nasopharyngeal carcinoma patients than in healthy controls ( n = 140), indicating their viability as immunodiagnostic targets. Overall, B‐Epic utilizes self‐attention, high‐dimensional feature projection, and convolutional neural networks to autonomously extract complicated BCE features, enabling accurate BCE prediction and thereby facilitating efforts to prevent infectious diseases and cancers.

Immunotherapy has revolutionized the treatment paradigm for hepatocellular carcinoma (HCC). However, its efficacy varies significantly with each patient’s genetic composition and the complex interactions with their microbiome, both of which are pivotal in shaping anti-tumor immunity. The emergence of microbial neoantigens, a novel class of tumor vaccines, heralds a transformative shift in HCC therapy. This review explores the untapped potential of microbial neoantigens as innovative tumor vaccines, poised to redefine current HCC treatment modalities. For instance, neoantigens derived from the microbiome have demonstrated the capacity to enhance anti-tumor immunity in colorectal cancer, suggesting similar applications in HCC. By harnessing these unique neoantigens, we propose a framework for a personalized immunotherapeutic response, aiming to deliver a more precise and potent treatment strategy for HCC. Leveraging these neoantigens could significantly advance personalized medicine, potentially revolutionizing patient outcomes in HCC therapy.