Lynch syndrome (LS), also known as hereditary nonpolyposis colorectal cancer, is a genetic condition that increases the risk of developing colorectal cancer (CRC) and other cancers due to defective DNA mismatch repair (dMMR). This article reports a case of a patient who developed lung adenocarcinoma followed by CRC. The detection of dMMR by immunohistochemistry in both the metastatic lesion and CRC led to retrospective testing, which revealed a concomitant loss of MLH1 and PMS2 in the primary lung cancer. Germline testing subsequently confirmed a diagnosis of LS associated with an MLH1 mutation, with significant familial clustering observed. The patient responded effectively to anti-PD-1 immunotherapy. This case highlights that lung adenocarcinoma can be a manifestation of LS and underscores the critical importance of retrospective MMR testing in establishing the diagnosis. Furthermore, it demonstrates the efficacy of immune checkpoint inhibitions in advanced dMMR tumors.

As high-throughput sequencing tools have advanced in recent years, scientists have discovered that lung cancer tissues are not sterile. The intratumoral microbiota exists in the tumor parenchyma and stroma in a low-biomass form. This finding has overturned the traditional concept of "sterile tumors" and brought the intratumoral microbiota to the forefront of tumor research. In this review, we focus on elucidating the mechanisms by which intratumoral microbiota influence lung cancer cells and the tumor microenvironment (TME), with the aim of clarifying their role in lung cancer progression. The intratumoral microbiota does not exist as a passive resident. Instead, it may actively induce and maintain a chronic inflammatory state through the secretion of metabolites, activation of signaling pathways, immune suppressor cell recruitment, and upregulation of immune checkpoint molecule expression, thereby promoting tumor cell proliferation, invasion, and immune evasion. From a clinical translation perspective, we explore the potential of using intratumoral microbiota characteristics to predict immunotherapy efficacy. Additionally, we assess the application prospects of engineered bacteria and targeted nanobiotics, which are based on synthetic biology, in reshaping the immune microenvironment. However, the field still faces significant challenges, particularly as the low biomass nature of lung tissues makes sequencing data highly susceptible to reagent contamination and batch effects. Additionally, the synergistic role of non-bacterial components such as fungi and viruses in the tumor ecosystem is often overlooked. Future research needs to establish rigorous quality control standards and integrate multi-omics technologies to comprehensively analyze the dynamic interaction network between the microbiota and host immunity, which will drive the clinical implementation of microbiome-based precision diagnostic and therapeutic strategies for lung cancer.

Hepatocellular carcinoma (HCC) remains a leading cause of cancer-related mortality, with limited efficacy of current therapies in advanced cases. As a key risk factor for HCC, liver fibrosis may influence tumor progression and immune responses. However, fibrosis-related therapeutic targets remain poorly defined. This study aimed to identify fibrosis-related genes in HCC tumor microenvironment (TME).

Our research integrated single-cell RNA sequencing (GSE149614), spatial transcriptomics (GSE245908), and bulk RNA-seq data to identify fibrosis-related prognostic genes in HCC. The genes were selected via the Random Survival Forest algorithm. Additionally, bioinformatics analyses were conducted to explore gene expression patterns, immune infiltration, and spatial localization. Key genes were further validated through in EDU incorporation assay, Transwell migration assay, and CCK-8 proliferation assay.

Firstly, single-cell analysis identified endothelial cells as key fibrosis-associated cluster in HCC. Three fibrosis-related prognostic genes, LUC7L3, CREB1, and YIPF4, were further identified and validated to patient survival, immune infiltration, and metabolic activity. In addition, enrichment and drug sensitivity analyses linked key genes to tumor-related pathways and chemotherapy response. Spatial transcriptomics then confirmed the spatial distribution and interactions of these genes. Lastly, cellular assays showed that YIPF4 promoted proliferation and migration of HCC cells.

In this study, we identified fibrosis-related prognostic genes in HCC, including LUC7L3, CREB1, and YIPF4. The roles of these genes in TME were further explored through relevant analyses, potentially providing clinical evidence to support decision-making in HCC management.

Glioma is a highly heterogeneous and aggressive malignancy of the central nervous system, and reliable molecular biomarkers are urgently needed to improve prognostic stratification and guide therapeutic decision-making. The MEX3 family of RNA-binding proteins has been implicated in tumorigenesis and post-transcriptional regulation; however, their comprehensive roles in glioma remain poorly understood.

Integrated bioinformatic analyses were performed using transcriptomic and clinical data from TCGA, CGGA, and GEO cohorts to evaluate the expression profiles, diagnostic and prognostic value, genetic alterations, molecular interactions, immune infiltration characteristics, and functional pathways associated with MEX3A, MEX3B, MEX3C, and MEX3D. Protein-protein interaction networks, gene set enrichment, and co-expression analyses were conducted to explore potential biological mechanisms. A MEX3-related prognostic risk model was constructed and validated in independent datasets. Drug sensitivity correlations were analyzed using public pharmacogenomic resources. In addition, in vitro experiments, including qRT-PCR, western blotting, proliferation, migration, and invasion assays, were performed in U251 and LN229 glioma cell lines to functionally validate the bioinformatic findings.

All four MEX3 family members were significantly upregulated in glioma tissues compared with normal controls and demonstrated strong diagnostic performance. Distinct prognostic patterns were observed, with MEX3D consistently identified as an independent predictor of poor overall, disease-specific, and progression-free survival. MEX3 genes were associated with diverse genetic alterations and were enriched in pathways related to RNA processing, cell cycle regulation, and cancer-associated signaling. Immune analyses revealed significant correlations between MEX3 expression and multiple immune cell populations as well as immune checkpoint molecules, suggesting potential roles in shaping the glioma immune microenvironment. A MEX3-related co-expression-based prognostic model showed robust survival-predictive ability and remained effective in external validation cohorts. Functional assays confirmed that silencing individual MEX3 genes significantly inhibited glioma cell proliferation, migration, and invasion in vitro.

This study provides a comprehensive characterization of the MEX3 family in glioma, demonstrating their dysregulation, prognostic relevance, immune associations, and functional contributions to malignant phenotypes. Among them, MEX3D emerges as a particularly promising prognostic biomarker. These findings establish a foundation for future mechanistic and translational studies exploring MEX3 family members as potential biomarkers or therapeutic targets in glioma.

Combination therapy targeting the PD-1/PD-L1 and TIGIT pathways has been explored to enhance the efficacy of current immunotherapies. In this study, we investigated strategies to further potentiate the co-blockade of PD-L1 and TIGIT for cancer immunotherapy. Firstly, we demonstrated that the bispecific antibody (HB0036) for PD-L1 and TIGIT co-blockade induced a greater T-cell proliferative response in vitro compared to the combined administration of the parental antibodies. This response was associated with CD226 upregulation and PD-1 downregulation. HB0036 significantly enriched the TIGIT antibody at PD-L1⁺ tumors and achieved improved tumor control with favorable immunological characteristics in both syngeneic and xenograft tumor models. Secondly, we showed that tumor control by co-targeting PD-L1 and TIGIT can be further enhanced by additionally blocking VEGF, a key player in tumorigenesis and tumor angiogenesis, in preclinical studies. Lastly, considering the heterogeneity of tumors, we analyzed how the expression patterns of PD-L1 and CD155 influence T cell responses. We also examined the spatial distribution of PD-L1 and CD155, along with related immunological parameters from patient samples, to assess the potential of PD-L1 and TIGIT co-blockade in diverse tumor contexts.

Immune-related adverse events, notably arthritis (irAE-arthritis), frequently occur in patients receiving immune checkpoint inhibitors. Arthritis severity varies from mild to severe, adversely impacting quality of life. Despite reports in clinical trials and real-world studies, the pathophysiology and optimal management of irAE-associated arthritis (irAE-arthritis) are still unclear.

From the inception to September 25, 2025, a search was conducted on PubMed, EMBASE, and MEDLINE for case reports/series on irAE-arthritis.

The most common rheumatic irAEs were arthritis. Various rheumatic syndromes have been reported, such as arthralgia, mono-/oligo-/polyarthritis, reactive and psoriatic arthritis, RS3PE, tenosynovitis. The onset of irAE-arthritis is attributed to T cell dysregulation, B cell activation with autoantibody production, cytokine - mediated inflammation, and impaired immune tolerance due to Treg dysfunction. NSAIDs, intra-articular/systemic corticosteroids, csDMARDs, and biologics play key roles in irAE-arthritis management, and JAK inhibitors may emerge as a significant therapeutic strategy in the future.

Given the increasing use of immunotherapy in oncology and other fields, developing a comprehensive understanding of irAE-arthritis is crucial. This review aims to provide an in-depth overview of current knowledge on irAE-arthritis, including its epidemiology, clinical presentation, underlying mechanisms, and management approaches.

Immune checkpoint molecules play a central role in regulating T cell function, maintaining immune homeostasis, and facilitating tumor immune evasion, making them critical targets in cancer immunotherapy. This review provides a comprehensive overview of the structural characteristics and signaling mechanisms of key co-inhibitory and co-stimulatory molecules, and their immunoregulatory roles in both solid tumors and hematological malignancies. Recent advances in the clinical application of immune checkpoint inhibitors, combination therapy strategies, and mechanisms of resistance are discussed. Furthermore, the importance of multi-target combinatorial approaches and personalized immune modulation is emphasized, offering valuable insights and directions for optimizing cancer immunotherapy strategies.

Artificial intelligence (AI) tools based on large language models (LLMs) are being increasingly used by researchers and may play a role in health-related research priority-setting exercises (RPSEs). However, little is known about how these tools may differ in the types of research priorities they generate.

We examined research priorities aimed at improving treatments for four diseases: cancer, COVID-19, HIV, and Alzheimer. We compared the outputs from five AI tools (DeepSeek, ChatGPT, Claude, Perplexity, and Gemini) using SBERT-BioBERT embeddings and cosine similarity scores, and assessed the stability of differences between them by re-running identical prompts and slightly modified versions.

We found that the outputs produced by Gemini were highly similar to those produced by the other tools. The two most different outputs were those produced by DeepSeek and Perplexity, whereby the former tended to emphasise technical medical issues, while the latter emphasised public health concerns. This substantive distinction between DeepSeek and Perplexity remained stable across repeated and tweaked prompts.

Our exploratory analysis suggests that Gemini performs well for researchers who prefer to generate health-related research priorities using a single AI model. For those planning to draw on multiple models, Perplexity and DeepSeek offer complementary perspectives.

Lymph node (LN) metastasis is a well-established independent prognostic factor in head and neck squamous cell carcinoma (HNSCC). Formation of suppressive tumour immune microenvironment (TIME) is a major contributor to tumour immune evasion and metastasis. However, the TIME landscape underlying LN-metastatic HNSCC remains poorly elucidated.

A total of 688 866 single-cell transcriptomes across 212 HNSCC samples were integrated. Comprehensive bioinformatic analyses on single-cell RNA sequencing and microarray datasets revealed a TREM2⁺ tumour-associated macrophage (TAM) cluster associated with LN metastasis. The functional role of TREM2⁺ TAMs was investigated through multiplex immunohistochemistry (mIHC) staining in clinical HNSCC cohort and in vitro co-culture experiments. Furthermore, machine learning algorithms were employed to construct a prognostic model for HNSCC.

Integrative single-cell analysis revealed the immunosuppressive TIME of LN-metastatic HNSCC, characterised by high infiltration of exhausted CD8⁺ T cells (CD8⁺ Tex). We identified a specific TREM2⁺ TAM cluster that was strongly associated with CD8⁺ Tex infiltration and LN metastasis. In vitro experiment confirmed that TREM2⁺ TAMs promoted CD8⁺ T cell exhaustion. Mechanistically, TREM2⁺ TAMs exhibited a terminally differentiated phenotype driven by ETV5, and secreted SPP1 to interact with CD44 on CD8⁺ T cells, thus upregulating BHLHE40 to promote CD8⁺ Tex formation. Clinically, a prognostic model based on TREM2⁺ TAM signature genes was trained to independently predict HNSCC outcomes.

This study delineates the mechanism that TREM2⁺ TAMs promote LN metastasis in HNSCC by facilitating CD8⁺ T cells exhaustion via SPP1-CD44-BHLHE40 axis, proposing TREM2⁺ TAMs as potential therapeutic target for HNSCC.

This phase I/II study aimed to evaluate the tolerability and the organ-sparing effects of continuous positive airway pressure (CPAP) in breast cancer radiotherapy (RT).

We conducted a prospective, single-institutional trial approved by the Ministry of Food and Drug Safety of South Korea. Patients with breast cancer who received postoperative RT underwent 4D-CT simulation and treatment planning under both free breathing (FB) and CPAP-assisted breathing (WC), with a target pressure of 20 cm H2O. Adverse events (AEs) were evaluated, and dosimetric parameters of organs at risk and heart position change were compared between the FB and WC arms.

Among 20 enrolled patients, four withdrew due to discomfort during simulation. During the trial, no CPAP-related AEs greater than grade 2 were observed. Compared to FB, CPAP reduced the mean heart dose by 33.8% (p < 0.001), as well as V5-V30 for both the left ventricle and left anterior descending artery (all p < 0.05). It also led to significant reductions in V5-V40 and the mean ipsilateral lung dose, including a 4.4% reduction in V20 (all p < 0.001). The heart centroid shifted rightward (4.8 mm), ventrally (8.1 mm), and caudally (16.3 mm) with CPAP, displacing the heart away from the RT field.

CPAP demonstrated both safety and efficacy for breast cancer RT, achieving significant reductions in cardiac and pulmonary radiation exposure. These findings support further investigation of CPAP as a novel respiratory motion management strategy. Future studies are warranted to identify optimal CPAP pressure levels to facilitate broader clinical implementation.