The prognosis of patients with peripheral T‐cell lymphoma (PTCL) depends on bone marrow involvement (BMI). The bone marrow (BM) tumor microenvironment in PTCL remains unclear. We performed single‐cell RNA sequencing (scRNA‐seq) on 11 fresh BM samples from patients with BMI to reveal the associations of immune landscape and genetic variations with the prognosis of PTCL patients. Compared with PTCL not otherwise specified (NOS), angioimmunoblastic T‐cell lymphoma (AITL) had a higher number of T cells, lower number of lymphocytes, and greater inflammation. Immune heterogeneity in AITL is associated with prognosis. In particular, specific T‐cell receptor (TCR) T cells are enriched in patients with good response to anti‐CD30 therapy. We observed RhoA mutation‐associated neoantigens. Chidamide‐treated patients had a higher number of CD4+ regulatory cells and a better treatment response compared with other patients. In the nonresponder group, T‐cell enrichment progressed to secondary B‐cell enrichment and subsequently diffuse large B‐cell lymphoma. Moreover, AITL patients with lymphoma‐associated hemophagocytic syndrome had more T follicular helper (Tfh) cells with copy number variations in CHR5. To our knowledge, this study is the first to reveal the single‐cell landscape of BM microenvironment heterogeneity in PTCL patients with BMI. scRNA‐seq can be used to investigate the immune heterogeneity and genetic variations in AITL associated with prognosis.

It is controversial whether monotherapy with immunotherapeutics is effective in early-stage hepatocellular carcinoma (HCC). We evaluated immunotherapy monotherapy as an initial neoadjuvant strategy. This prospective, single-arm, phase II trial of an adaptive neoadjuvant strategy enrolled patients with resectable, early-stage HCC. All patients received tislelizumab monotherapy; non-responders received subsequent lenvatinib combination therapy preoperatively. For the overall efficacy of all 36 patients, the objective response rates were 13.9% and 30.6% as per the Response Evaluation Criteria in Solid Tumours v1.1 and modified Response Evaluation Criteria in Solid Tumours, respectively. Among the 33 patients who underwent resection, the major pathological response rate was 33.3% and the pathological complete response rate was 15.2%. Overall, grade ≥ 3 treatment-emergent adverse events occurred in 11.1%, with no surgical delays. Monotherapy responses were predicted by pretreatment tumour microenvironment features. Immune-regulatory cancer-associated fibroblasts colocalized with T cells identified responders, whereas angiogenic-metabolic signatures predicted resistance. A multimodal model integrating blood-based and imaging biomarkers accurately identified monotherapy-sensitive patients (average precision, 0.9167). The specificity for identifying responders was 100%. These preliminary findings suggest that neoadjuvant immunotherapy monotherapy exhibits promising antitumour activity and demonstrates a manageable safety profile in early-stage HCC. The tailored stratification approach appears clinically feasible and may help minimize unnecessary exposure to combination therapy-related toxicity while retaining tentative therapeutic efficacy.

Accurate inference of absolute copy numbers beyond simple gains and losses from single-cell chromatin accessibility (scATAC-seq) data remains challenging, thereby obscuring the distinction between genetic and epigenetically driven oncogenic dependencies. Here, we present TeaCNV, a computational framework that reconstructs clonal absolute copy number profiles and tumor clonal architectures from scATAC-seq data without matched DNA baselines. Through validation both in silico and against bulk whole-genome sequencing in renal cell carcinomas, TeaCNV resolved subclonal absolute copy number profiles with less than 10% error and detected copy number variations (CNVs) with 98.6% accuracy, outperforming existing methods. Applied to six cancer types including renal, breast, pancreatic, head and neck, colorectal, and ovarian cancers, TeaCNV delineated polyclonal architectures and revealed distinct chromatin accessibility patterns driven by CNVs in key driver genes, including AKT2, ZNF217, and SOX2. By enabling absolute copy number profiling and clonal deconvolution from epigenomic assays, TeaCNV bridges critical gaps in studying oncogenic dependencies and genotype–phenotype relationships at single-cell resolution.