The clinical management of ER-positive/HER2-negative (ERpHER2n) breast cancer is complicated by a heterogeneous patient population, with some patients exhibiting endocrine resistance and an increased risk of recurrence. Among these high-risk subgroups, ERpHER2n Basal-like (ERpHER2n-Basal) breast cancer, as defined by PAM50 gene expression subtyping, remains poorly characterized due to limited available material. However, understanding the somatic molecular features driving treatment resistance and progression is critical for optimizing therapy.

Immunotherapy has revolutionized the treatment of cancer and tremendously prolonged the overall survival of patients; however, only parts of patients could derive durable clinical benefit from it. Predicting clinical responses to immunotherapy and interpreting the response mechanism remain major challenges.

Noninvasive prenatal screening for aneuploidies and microdeletion/microduplication syndromes (MMS) has gained widespread clinical application. However, the development of noninvasive prenatal diagnosis for monogenic disorders (NIPT-M) has progressed slower. Existing NIPT-M approaches often require specialized designs, are limited to a narrow range of genes, or are expensive and impractical for clinical implementation.

Metabolites are closely linked to individual health and disease conditions. Identifying genetic factors influencing metabolite levels in specific diseases can enhance our understanding of disease etiology and informing precision medicine. This study aims to characterize the genetic architecture of metabolites in specific disease states and explore their potential biological functions.

CD4⁺ T cell responses are key to adaptive immunity, yet the mechanisms underlying peptide selection and immunodominance across MHC class II variants in humans remain poorly defined. Two non-mutually exclusive models - First Bind-then cut (FBtc) and First Cut-then bind (FCtb) - have been proposed to explain immunodominant peptide selection, but experimental evidence in humans is mostly limited to a single allotype (HLA-DRB1*01:01).

Cis-regulatory elements (CREs) control oncogene expression and malignant phenotypes. The high clinicopathological heterogeneity of cancer cannot be explained by gene expression alone, being attributed to CRE heterogeneity. However, characterizing cancer-associated CREs is challenging. To address this issue, we performed a single-cell epigenomic analysis of clinical specimens.

Cardiac fibrosis is a key feature of pathological cardiac remodelling that significantly impacts heart function through contributing to stiffness, diastolic dysfunction, and arrhythmias, ultimately leading to heart failure (HF). Despite extensive research into fibrosis-related matrix alterations, therapeutic advancements are limited, in part owing to the different nature (reparative vs interstitial) and tissue distribution of fibrosis involved. To identify unique features of fibrosis phenotypes, we investigated fibroblast (FB) heterogeneity and spatial distribution in left ventricular myocardium in HF patients with ischemic (ICM) and dilated cardiomyopathy (DCM). Infarct scar was also analysed.

T/myeloid mixed-phenotype acute leukemia (T/My MPAL) is a malignant disease characterized by co-expression of lymphoid and myeloid features. The lack of molecular classification of T/My MPAL results in highly heterogeneity in treatment responses and clinical outcomes. Identifying molecular subtypes and developing subtype-specific treatment strategies are crucial for improving prognosis and enabling personalized therapies.

Imprinted genes are expressed in a parental-origin-specific manner. The imprinted regions including imprinted genes have differentially methylated regions (DMRs) with different 5-methylcytosine (5mC) patterns for CpGs on each parental allele, and DMRs function as imprinting control centers. Aberrant expression of the imprinted genes caused by structural variants involving DMRs, single-nucleotide variants in imprinted genes, uniparental disomy, and epimutation lead to imprinting disorders (IDs). Nanopore-based targeted long-read sequencing (T-LRS) can obtain sequence reads 10-100 kb long together with information on DNA methylation in each CpG and is cost-effective compared to whole-genome LRS. T-LRS is a valuable tool for efficient genetic testing for IDs and has great potential to elucidate the regulatory mechanisms in the imprinted regions. However, there is no T-LRS system targeting all ID-related regions.

Tuberculosis (TB) remains a major public health concern. Improving TB control programs and treatment success requires a deeper understanding of the factors that determine disease presentation and treatment outcomes. While the importance of patient factors is well established, our understanding of the bacterial determinants of disease presentation and treatment outcomes in TB remains limited.

Genome instability, tumour-promoting inflammation, and immune escape are three distinct hallmarks of cancer. However, accumulating scientific and clinical evidence over the past decade have uncovered a multifaceted interplay of complex dynamic network of interactions between genome instability, the DNA damage response (DDR), and tumour immunogenicity. Fuelled by the clinical successes of immune checkpoint blockers (ICB), growing interest for immuno-oncology and recent cancer biology discoveries have allowed a better understanding of the underlying biology and clinical opportunities brought by this interplay-which is yet, still only in its infancy. The cooperative nature of tumour cell-intrinsic and -extrinsic mechanisms involved suggests that harnessing genomic instability in cancer does not only hamper cancer cells fitness but also stimulate the anti-tumour immune response, thereby paving the way to the development of DDR-based immunomodulatory therapeutic strategies applicable to a variety of molecular and histological cancer types. Here, we review the various aspects of this crosstalk between genome instability and tumour immunogenicity, including feedforward and feedback mechanisms affecting either side of this interplay, as well as the specific consequences of chromosomal instability. We further discuss emerging DDR-based predictive biomarkers of response to ICB therapies, and finally examine the latest clinical developments of therapeutic combinations that exploit the DDR-immunity interplay in immuno-oncology.

Type 1 autoimmune pancreatitis (AIP) is pancreatic manifestation of IgG4-related disease (IgG4-RD), characterized by pancreatic lymphoplasmacytic infiltration. Despite this well-known pathological feature, the immune microenvironment and the complex cellular interactions within the pancreas in AIP remain poorly understood. This study aimed to characterize the local immune features of the pancreas in AIP patients.

Cytotoxic T cells are key effectors in the immune response against pathogens and tumors. Thus, identifying those immunogenic epitopes driving T-cell activation conforms a fundamental goal for antigen-based immunotherapies. T-cell antigen discovery is challenged by immense epitope landscapes, unfeasible to screen ad hoc experimentally due to the high cost and low throughput of immunogenicity validations. Precedingly, immunoinformatic models, with orders of magnitude higher throughput such as HLA-I binding affinity tools, are used to predict the antigenic potential of T-cell epitopes. However, the resulting immunogenicity screening success rates (ISSR)-the capacity to rank truly immunogenic epitopes among top-scored candidates prioritized for experimental validation-have remained incremental and the immunological explainability underlying model predictions limited.

Determining the correct structure of large, interspersed duplications and related complex genomic rearrangements in genetic disease is critical when establishing causal roles and requires a technology able to span the entire duplicated segment(s) on single molecules. We assessed the use of Bionano optical genome mapping (OGM) for this purpose.

Pancreatic ductal adenocarcinoma (PDAC) presents a significant challenge, with a 5-year survival rate of approximately 10%. Tumor heterogeneity contributes to the limited effectiveness of treatments. Several tumor and stroma molecular classifiers have attempted to clarify this heterogeneity with moderate agreement. Recognizing the complexity introduced by this extensive array of taxonomies, this study aims to develop a consensus molecular classifier by including both tumor and stroma features.

Distinguishing whether genetic variants in protein kinases cause gain or loss of function is critical in clinical genetics. In particular, gain (and not loss)-of-function variants are often immediately amenable to treatment by inhibitors, making their identification a potential boon to personalised medicine. Most existing computational methods for variant pathogenicity prediction simply distinguish damaging from benign variants and provide no further functional insights. Here, we present a data-driven approach that differentiates activating, deactivating, and resistance variants.

Acute promyelocytic leukemia (APL) is a subtype of acute myeloid leukemia (AML), characterized by a fusion between the PML and RARA genes and by a block in the myeloid maturation at the promyelocytic stage.

Rare damaging genetic variation accounts for a substantial proportion of the risk of rare developmental disorders (DDs), but common genetic variants as well as environmental factors, including prematurity, also contribute. Little is known about the interplay between prematurity and genetic variation in influencing phenotypic outcomes in DDs, nor about how genetic factors may contribute to risk of preterm birth in DDs.

Neoadjuvant therapy plays an important role in the treatment of glioblastoma (GBM), but a considerable proportion of patients remain unresponsive to the combination of immune checkpoint blockade (ICB) and antiangiogenic therapy. Understanding the mechanisms underlying resistance to this treatment and developing novel therapeutic strategies are crucial.

A comprehensive and representative reference database is crucial for accurate taxonomic and functional profiling of the human gut microbiome in population-level studies. However, as approximately 70% of current microbial reference data originate from European and North American populations, other regions, including East Asia-and particularly China-remain significantly underrepresented.

Typhoid fever results from systemic infection with Salmonella enterica serovar Typhi (Typhi) and causes 10 million illnesses annually. Disease control relies on prevention (water, sanitation, and hygiene interventions or vaccination) and effective antimicrobial treatment. Antimicrobial-resistant (AMR) Typhi lineages have emerged and become established in many parts of the world. Knowledge of local pathogen populations informed by genomic surveillance, including of lineages (defined by the GenoTyphi scheme) and AMR determinants, is increasingly used to inform local treatment guidelines and to inform vaccination strategy. Current tools for genotyping Typhi require multiple read alignment or assembly steps and have not been validated for analysis of data generated with Oxford Nanopore Technologies (ONT) long-read sequencing devices. Here, we introduce Typhi Mykrobe, a command line software tool for rapid genotyping of Typhi lineages, AMR determinants, and plasmid replicons direct from sequencing reads.