Ibrutinib‐based combination therapy with high‐dose methotrexate (HD‐MTX) has recently shown clinical activity against relapse/refractory (R/R) primary central nervous system lymphoma (PCNSL). Herein, we report our real‐world experience of treating 11 newly diagnosed PCNSL patients with the ibrutinib/MTX combination. HD‐MTX was given at 3.5 g/m² every 2‐week for eight doses. Ibrutinib was held upon HD‐MTX infusion until clearance and was administered daily post‐induction until disease progression, intolerable toxicity, or death. Nine out of 11 patients completed the induction phase and received ibrutinib as maintenance therapy. An objective response rate (ORR) of 82% (9/11) was observed including complete response (64%) and partial response (18%). The median progression‐free survival (PFS) was 7.4 months while the median overall survival (OS) was not reached. The ibrutinib/MTX combination was well tolerated in these treatment‐naïve PCNSL patients with an acceptable safety profile. Moreover, the longitudinal analysis of cerebrospinal fluid (CSF) circulating tumor DNA (ctDNA) revealed that CSF ctDNA detection was closely associated with tumor response, and sustained tumor responses correlated with the clearance of ctDNA from the CSF. In sum, our data not only demonstrated the clinical benefit of the ibrutinib and HD‐MTX combination regimen in treating newly diagnosed PCNSL patients in a real‐world setting, but also highlighted the significance of liquid biopsy including CSF ctDNA in tracing tumor burden and assessing treatment response.

T cell lymphoma (TCL) is a highly heterogeneous group of diseases with a poor prognosis and low 5-year overall survival rate. The current therapeutic regimens have relatively low efficacy rates. Clinical studies of single-target chimeric antigen receptor T cell (CAR-T cell) therapy in T lymphocytes require large and multiple infusions, increasing the risks and cost of treatment; therefore, optimizing targeted therapy is a way to improve overall prognosis. Despite significant advances in bispecific CAR-T cell therapy to avoid antigen escape in treatment of B cell lymphoma, applying this strategy to TCL requires further investigation. Here, we constructed an alpaca nanobody (Nb) phage library and generated high-affinity and -specificity Nbs targeting CD30 and CD5, respectively. Based on multiple rounds of screening, bispecific NbCD30-CD5-CAR T cells were constructed, and their superior anti-tumor effect against TCL was validated in vitro and in vivo. Our findings demonstrated that Nb-derived bispecific CAR-T cells significantly improved anti-tumor efficacy in TCL treatment compared with single-target CAR-T cells and bispecific single chain variable fragment (scFv)-derived CAR-T cells. Because Nbs are smaller and less immunogenic, the synergistic effect of Nb-based bispecific CAR-T cells may improve their safety and efficacy in future clinical applications.

Background: Tumor mutation burden (TMB) as estimated by cancer gene panels (CGPs) has been confirmed to be associated with prognosis and is effective in predicting clinical benefit from immune checkpoint blockade (ICB) in solid tumors. However, whether the TMB calculated by CGPs is associated with overall survival (OS) for patients with diffuse large B-cell lymphoma (DLBCL) is worth exploring. Methods: The prognostic value of panel-TMB, calculated by a panel of 69 genes (GP69), for 87 DLBCL patients in our clinical center (GDPH dataset) was explored. The results were further validated using 37 DLBCL patients from the Cancer Genome Atlas (TCGA) database (TCGA dataset). Results: Spearman correlation analysis suggested that panel-TMB is positively correlated with the TMB calculated by whole-exome sequencing (wTMB) in the TCGA dataset (R = 0.76, P < 0.0001). Both GDPH and TCGA results demonstrated that higher panel-TMB is significantly associated with a poor OS for DLBCL patients (P < 0.05) where a panel of 13 genes was associated with poor OS, and another panel of 26 genes was correlated with a favorable OS for DLBCL patients. Further subgroup analysis indicated that higher panel-TMB had shorter OS in DLBCL patients with younger than 60 years, elevated LDH, greater than one extranodal involvement, stage III/IV, an IPI score of 3–5, or HBsAg, anti-HBc, or HBV-DNA negativity (P < 0.05). Interestingly, the nomogram model constructed by panel-TMB, stage, and IPI could individually and visually predict the 1-, 2- and 3-year OS rates of DLBCL patients. Conclusions: We established GP69 for the evaluation of OS for Chinese DLBCL patients. panel-TMB might be a potential predictor for prognostic stratification of DLBCL patients.

Circulating tumor DNA (ctDNA) carries tumor-specific genetic and epigenetic variations. To identify extranodal natural killer/T cell lymphoma (ENKTL)-specific methylation markers and establish a diagnostic and prognosis prediction model for ENKTL, we describe the ENKTL-specific ctDNA methylation patterns by analyzing the methylation profiles of ENKTL plasma samples. We construct a diagnostic prediction model based on ctDNA methylation markers with both high specificity and sensitivity and close relevance to tumor staging and therapeutic response. Subsequently, we built a prognostic prediction model showing excellent performance, and its predictive accuracy is significantly better than the Ann Arbor staging and prognostic index of natural killer lymphoma (PINK) risk system. Notably, we further establish a PINK-C risk grading system to select individualized treatment for patients with different prognostic risks. In conclusion, these results suggest that ctDNA methylation markers are of great value in diagnosis, monitoring, and prognosis, which might have implications for clinical decision-making of patients with ENKTL.

Background: With the rapid increase of chest computed tomography (CT) images, the workload faced by radiologists has increased dramatically. It is undeniable that the use of artificial intelligence (AI) image‐assisted diagnosis system in clinical treatment is a major trend in medical development. Therefore, in order to explore the value and diagnostic accuracy of the current AI system in clinical application, we aim to compare the detection and differentiation of benign and malignant pulmonary nodules between AI system and physicians, so as to provide a theoretical basis for clinical application.Methods: Our study encompassed a cohort of 23 336 patients who underwent chest low‐dose spiral CT screening for lung cancer at the Health Management Center of West China Hospital. We conducted a comparative analysis between AI‐assisted reading and manual interpretation, focusing on the detection and differentiation of benign and malignant pulmonary nodules.Results: The AI‐assisted reading exhibited a significantly higher screening positive rate and probability of diagnosing malignant pulmonary nodules compared with manual interpretation (p < 0.001). Moreover, AI scanning demonstrated a markedly superior detection rate of malignant pulmonary nodules compared with manual scanning (97.2% vs. 86.4%, p < 0.001). Additionally, the lung cancer detection rate was substantially higher in the AI reading group compared with the manual reading group (98.9% vs. 90.3%, p < 0.001).Conclusions: Our findings underscore the superior screening positive rate and lung cancer detection rate achieved through AI‐assisted reading compared with manual interpretation. Thus, AI exhibits considerable potential as an adjunctive tool in lung cancer screening within clinical practice settings.

Purpose: The purpose of this study is to perform a retrospective analysis of disease outcomes and mutational profiles in patients with adult T-cell lymphoblastic lymphoma (T-LBL). Patients and Methods: A total of 43 patients were treated over a 9-year period at a single institution. The study examined treatment outcomes, clinical characteristics, and the use of circulating tumor DNA (ctDNA) and mutational profiling for patient diagnosis. Results: The estimated overall survival (OS) and progression-free survival (PFS) time for all patients was 37.0 (95% CI: 17.7– 56.2) and 28.1 (95% CI: 0.9– 55.4) months, respectively. Chidamide maintenance was used in five patients exhibiting unfavorable genetic alterations, with no evidence of relapse. Next-generation sequencing of pretreatment tumor tissue was undertaken for 15 patients. NOTCH1 mutations were the most frequent genetic alterations, followed by mutations in PHF6, TP53, JAK1, JAK3, PTEN, and DNM2. The genetic profile of the blood was similar to that of the tumor. Kappa coefficient analysis (14 patients, 56 time points, kappa = 1.0, p = 0.00) indicated a 92.6% agreement between ctDNA response and tumor volume measurements at post treatment when compared with baseline. Detection of ctDNA predicted disease relapse in two patients. Conclusion: The prognosis of patients with adult T-LBL remains very poor. Detection of tumor-associated sequences in ctDNA may be an effective method for diagnosing T-LBL and measuring treatment efficacy. Incorporation of new drugs such as histone deacetylase inhibitors (HDACi)has the potential to improve outcomes in these patients.