Adult T-cell leukemia-lymphoma (ATL) is a rare, aggressive malignancy prevalent in Japan, the Caribbean, and Central/South America. This multicenter retrospective study evaluated the effectiveness and safety of brentuximab vedotin with cyclophosphamide, doxorubicin, and prednisolone (BV-CHP) in patients aged ≥ 18 years with previously untreated CD30-positive ATL, verified through immunohistochemistry/flow cytometry, from six hospitals in Japan. Outcomes included overall response rate (ORR; primary outcome), overall survival (OS), progression-free survival (PFS), complete response rate (CRR), disease control rate (DCR), and safety. Subgroup analyses evaluated lesion site, ATL subtype, age, and CD30 expression. Of 46 screened patients, 36 (median age 71 years; 66.7% female) were analyzed and started BV-CHP between April 2020 and January 2024. CD30 positivity was confirmed in all patients. ORR was 86.1% (95% confidence interval [CI] 70.5-95.3), CRR 61.1% (95% CI 43.5-76.9), and DCR 91.7% (95% CI 77.5-98.3). ORR by lesion site (lymph nodes, peripheral blood, skin) was 93.8%, 90.9%, and 83.3%, respectively, by ATL subtype (acute, lymphoma) was 78.9% and 94.1%, respectively, and by age (≤ 70 years, > 70 years) was 84.6% and 87.0%, respectively. One patient with CD30 expression < 10% achieved a complete response; ORR was 73.7% in 19 patients with CD30 expression ≥ 10%. Median OS and PFS was 535 days (95% CI 343-not estimable) and 205 days (95% CI 166-279), respectively. Treatment-emergent adverse events of any grade and grade ≥ 3 both occurred in 88.9% of patients, with neutropenia, febrile neutropenia, and thrombocytopenia being most common. Among 11 patients who underwent allogeneic stem cell transplantation, two developed acute graft-versus-host disease; median PFS was 234 days (95% CI 168-343), compared with 180 days (95% CI 96-279) without transplantation. BV-CHP demonstrated high ORR and CRR across age groups and ATL subtypes with a manageable safety profile, supporting its potential use as a standard treatment option.

B cell maturation antigen (BCMA) has emerged as a prominent immunotherapeutic target in multiple myeloma (MM) due to its restricted expression on MM cells, plasma cells and mature B cells, with minimal presence in other normal tissues. In this study, we demonstrate through RNA sequencing and flow cytometry analyses of acute myeloid leukemia (AML) cell lines and primary patient samples that BCMA is also a relevant AML-associated antigen. Its robust surface expression on AML cells positions it as a promising candidate for targeted immunotherapy. Functionally, our findings indicate that BCMA in AML operates similarly to its role in MM - engaging the NF-kB pathway upon ligand binding, thereby activating gene expression programs that support leukemia cell survival and proliferation. We assessed several BCMA-targeted immunotherapeutic strategies, including bispecific T-cell engagers (TCE) and chimeric antigen receptor (CAR) transduced T-cells, NK-cells, and macrophages. We found that TCE treatment and BCMA CAR engineering markedly improved effector cell mediated cytotoxicity against AML cells, underscoring BCMA's potential as a viable therapeutic target in AML. Furthermore, BCMA- directed TCE therapy significantly augmented the anti-leukemic activity of adoptively transferred CD8⁺ T-cells in a human AML xenograft model. Taken together, these findings support BCMA as a novel immunotherapeutic target in AML. Leveraging existing BCMA-directed treatments developed for MM could enable rapid clinical translation and broaden immunotherapy options for patients with AML.

Mammographic density (MD) is an established biomarker of breast cancer (BC) risk. However, its relationship to BC pathological subtypes remains unclear. This study aimed to investigate this association and assess whether it differs by body mass index (BMI) and menopausal status.

MD percentage was assessed in the diagnostic mammograms of the contralateral breast of 714 BC patients recruited from eight Spanish hospitals. Participants completed an epidemiological questionnaire, and hospital researchers collected clinical and pathological data. Standardized prevalences (SPs) and standardized prevalence ratios (SPRs) for each BC pathological subtype across MD categories were estimated based on multinomial logistic regression models, both overall and stratified by BMI and menopausal status.

Mean MD was 26.1% (SD = 17.3). Although no statistically significant differences were detected, women with MD ≥ 50% had a 13% lower SP of hormone receptor positive tumors (SPR = 0.87; 95% CI 0.67-1.13), a 36% higher SP of human epidermal growth factor receptor 2 positive (HER2+) tumors (SPR = 1.36; 95% CI 0.72-2.58), and a 23% higher SP of triple negative (TN) tumors (SPR = 1.23; 95% CI 0.47-3.22), compared to those with MD < 10%. These patterns were mainly observed in pre/perimenopausal women and in those with BMI ≥ 25 kg/m².

High MD might be mainly associated with the development of more aggressive and non-hormone-dependent cancers, such as HER2+ and TN BC, especially among pre/perimenopausal an overweight women.

Chimeric Antigen Receptor T (CAR-T) cell therapy has revolutionized cancer immunotherapy, particularly in hematological malignancies. However, the clinical application of autologous CAR-T cells faces significant high cost and manufacturing challenges. Universal allogeneic CAR-T cells, derived from healthy donors, represent a promising solution to these obstacles. These "off-the-shelf" therapies aim to reduce the complexity and cost of CAR-T production. Despite exciting advancements in genome-editing technologies and promising clinical trial data, significant challenges remain, including graft-versus-host disease (GVHD), Host-versus-graft reaction (HVGR), off-target effects, genotoxicity, and manufacturing scalability. To address these concerns, genome-editing technologies such as ZFNs, TALENs, Meganucleases, CRISPR systems, base editing, and prime editing are being employed. This review summarizes the progress of universal allogeneic CAR-T cell therapies, addresses the critical challenges, and discusses the future directions for their clinical implementation.

Follicular lymphoma (FL) represents the most common subtype of indolent non-Hodgkin's lymphoma. Extranodal involvement (ENI) indicates a poor clinical outcome in patients who received rituximab-based immunochemotherapy. Recent studies indicate that genetic alterations and tumor microenvironment dysregulation drive extranodal dissemination and lymphoma progression. However, the molecular mechanisms underlying ENI in FL remain to be fully elucidated.

Aiming to investigate the influence of oncogenic mutations and tumor microenvironment alterations on ENI in FL, the clinical features of 501 patients with newly diagnosed FL receiving rituximab-based therapy were analyzed, with DNA and RNA sequencing performed on 403 and 175 patients, respectively.

Multiple ENI was observed in 120 (24%) patients and was significantly related to advanced Ann Arbor stage, decreased hemoglobin, elevated lactate dehydrogenase, elevated beta-2 microglobulin, lymph nodes ≥ 5 sites, lymph nodes > 6 cm, and high risk of progression of disease within 2 years (POD24). Increased KMT2D, CREBBP, CARD11, and STAT6 mutations, as well as downregulation of immune-associated pathways and alterations in lipid metabolism, were associated with multiple ENI. In the rituximab plus chemotherapy (R-chemo) cohort (n = 344), involvement of bone marrow, lung, liver, bones, and kidney/adrenal glands were unfavorable predictors of progression-free survival (PFS), with involvement of liver and kidney/adrenal glands as unfavorable predictors of overall survival (OS). However, in the rituximab plus lenalidomide immunotherapy (R2) cohort (n = 157), no ENI site showed a significant difference in PFS and OS.

Negative prognostic impact of multiple ENI upon R-chemo therapy could be overcome by R2 therapy in FL. Better understanding of the biological behavior of multiple ENI could provide a potential clinical rationale for future mechanism-based therapy of FL.

This study aimed to evaluate RBM15 gene expression and the potential effects as a biomarker in LUAD progression.

The RNA sequencing (RNA-seq) data and clinical data of patients with LUAD were acquired from The Cancer Genome Atlas (TCGA) databases. Kaplan-Meier (K-M) curves were generated to investigate the relationship between RBM15 and the prognosis of patients with LUAD. Gene Ontology (GO) and Reactome enrichment analyses were performed using the "cluster Profiler" R package. Finally, the Tumor Immune Estimation Resource (TIMER)database and CIBERSORT algorithm were used to assess the correlations between RBM15 expression and immune infiltration in LUAD.

RBM15 was upregulated in tumor tissue, and it was regarded as an independent prognostic factor in LUAD. The genes co-expressed with RBM15 were closely related to cell cycle checkpoints and M phase signaling pathways. Furthermore, there was a significant correlation between RBM15 gene expression and immune infiltration in LUAD.

Our data suggested that RBM15 is critical in LUAD progression, is associated with tumor immune infiltration and served as a valuable potential diagnostic biomarker in patients.

Non-small cell lung cancer (NSCLC) with chest wall invasion is typically diagnosed at initial presentation, and nodal involvement (especially N2 station) correlates with poor prognosis. To our knowledge, this is the first report of a solitary squamous cell carcinoma of the right chest wall arising 21 months after video-assisted thoracoscopic surgery (VATS) lobectomy for left NSCLC (pT1bN0M0). Primary solitary chest wall squamous cell carcinoma in adults is poorly documented, with limited data on its clinical manifestations, pathology, and management. This case aims to enhance understanding of this rare entity, aiding in avoiding misdiagnosis and inappropriate treatment (Yin et al. in Med (Baltim) 2018;97(44):e13112).

This study aimed to apply CUBIC tissue clearing combined with three-dimensional (3D) imaging to visualize the pathological architecture of systemic light chain (AL) amyloidosis in the human tongue, assess spatial and microstructural changes associated with amyloid deposition, and explore its potential to enhance early diagnostic accuracy.

Seven tongue specimens from confirmed AL amyloidosis cases underwent CUBIC processing, multiplex immunofluorescence staining, and 3D imaging. Vascular density, surface area, vessel and muscle fiber diameters were compared between amyloid deposition and non-deposition regions. Ten additional specimens initially negative for AL amyloidosis were re-evaluated using the same procedure, suspected cases were verified by repeat histology and clinical follow-up.

In amyloid deposition regions, vascular density and surface area were (0.14 ± 0.04) μm³ and (0.46 ± 0.11) μm², showing 50.0% and 33.3% reductions compared to non-deposition regions [(0.28 ± 0.06) μm³ and (0.69 ± 0.12) μm²]. Median vessel diameter in vessels with luminal amyloid deposition was 5.99 μm (IQR: 5.07-7.39), 30.5% smaller than that in vessels without deposition [8.62 μm (IQR: 7.26-11.03)]. Muscle fibers surrounded by amyloid deposits had a diameter of (3.62 ± 0.28)μm, slightly smaller than that of fibers without deposition [(3.70 ± 0.23)] μm. All differences were significant (P < 0.05). Among the ten initially negative cases, five were reclassified as highly suspected and one was confirmed during follow-up.

CUBIC-based 3D imaging enables detailed visualization and quantification of amyloid-associated microstructural changes in tongue tissue, providing deeper insight into disease mechanisms and serving as a valuable complement to conventional histopathology for enhancing early diagnostic accuracy in AL amyloidosis.

The Rho GTPase-activating protein (RhoGAP) family represents a large and diverse group of proteins that act as key regulators of Rho GTPases, small GTP-binding proteins involved in cellular signaling. Tight regulation of Rho GTPase activity is essential for fundamental biological processes, including cell motility, contractility, growth, differentiation, and development. Despite their biological importance, the roles of RhoGAPs in cancer remain largely undefined.

Bioinformatics analysis was performed using data from The Cancer Genome Atlas (TCGA), covering over 10,000 samples across 33 cancer types. The role of ARHGAP11A in the DNA damage response was evaluated through single-cell sequencing, western blotting, and colony formation assays.

Pan-cancer analysis of RhoGAP family genes identified ARHGAP11A as the most significantly overexpressed member in tumors compared to adjacent normal tissues. ARHGAP11A expression was found to be elevated in most cancer types and was associated with DNA repair activity. Furthermore, its expression positively correlated with tumor mutational burden (TMB), a recognized predictive biomarker for immunotherapy. Intriguingly, it also correlated with increased infiltration of regulatory T (Treg) cells, which are known to suppress anti-tumor immunity. Consistent with these observations, high ARHGAP11A expression was concurrently linked to poor patient survival outcomes across multiple cancers. We also observed a positive correlation between ARHGAP11A and CHK1, suggesting a functional collaboration. In vitro experiments further demonstrated that ARHGAP11A confers resistance to DNA damage induced by CHK1 inhibitors.

ARHGAP11A is a promising prognostic marker in cancer, with potential therapeutic implications through targeting DNA repair pathways and modulating the tumor immune microenvironment.

To address limitations of conventional Quantitative Structure-Activity Relationship (QSAR) descriptors in capturing molecular electronic and spatial complexity, we developed a high-dimensional framework using three-dimensional electron density features. Electron densities were computed via density functional theory (DFT), converted to 3D point clouds, and encoded into multi-scale descriptors including radial distribution functions, spherical harmonic expansions, point feature histograms, and persistent homology. This design enabled molecular characterization across statistical, geometric, and topological dimensions. The proposed descriptors consistently improved performance across multiple machine learning models; for instance, Area Under the Curve (AUC) increased from 0.88 to 0.96 with Light Gradient Boosting Machine (LightGBM). Benchmarking demonstrated superior performance versus industry-standard ECFP4 fingerprints. Control experiments using purely geometric (CPK) point clouds yielded substantially lower performance, confirming that predictive gains stem from electronic structure information rather than high-dimensional geometry alone. Feature attribution analysis revealed that local geometric descriptors and intensity-based electronic features were primary contributors, while integration with conventional 1D/2D descriptors further enhanced accuracy, indicating strong complementarity. Model robustness was validated through DeLong and permutation tests, calibration assessments, and applicability domain analysis. This study provides proof-of-concept evidence that DFT-derived electron density features can be systematically integrated into QSAR modeling. Despite computational cost limitations and reduced chemical interpretability, results demonstrate that electronic-structure-based descriptors offer valuable complementarity to established approaches, opening new avenues for molecular representation in drug discovery.