Analysis of Associated Factors, Construction, and Application of a Predictive Model for Lymph Node Metastasis in Colorectal Cancer.

Background: In colorectal cancer (CRC) , understanding lymph node metastasis (LNM) is critical for effective treatment. Better approaches are required for identifying and assessing the risk contributions of factors influencing lymph node metastasis in colorectal cancer. Objective: This study aims to analyze factors associated with LNM in CRC and develop a risk prediction model. Methods: A retrospective cohort study was conducted and a total of 181 CRC patients admitted between March 2020 and April 2023 were selected as research participants. Among them, 47 patients developed LNM, while the remaining 134 did not. Clinical data, including age, sex, pathological stages, were collected. Logistic regression was employed to identify factors influencing LNM in CRC, forming the basis for constructing a risk model. The diagnostic efficiency of this model was assessed through receiver operating characteristic (ROC) curves. Results: Tumor nodules and histological types showed no correlation with LNM in CRC (P > .05). However, pathological staging, vascular and neural invasion, use of VEGF inhibitors, and preoperative CEA were identified as independent risk factors for LNM in CRC (P < .05). The established model demonstrated a good fit with the observations. ROC curve analysis indicated an area under the curve (AUC) of 0.884 for predicting LNM in CRC, signifying excellent predictive performance. Conclusions: The risk model, formulated on factors associated with LNM in CRC, serves as a efficient tool in assessing the probability of LNM. It provides invaluable insights that can significantly enhance clinical approaches to the diagnosis and treatment of CRC in the future.

Clinicopathologic analysis of nodal T-follicular helper cell lymphomas, a multicenter retrospective study from China.

Background: Nodal T-follicular helper cell lymphomas (nTFHLs) represent a new family of peripheral T-cell lymphomas (PTCLs), and comparative studies of their constituents are rare. Methods: This study retrospectively enrolled 10 patients with nTFHL-F and 30 patients with nTFHL-NOS diagnosed between December 2017 and October 2023 at six large comprehensive tertiary hospitals; 188 patients with nTFHL-AI were diagnosed during the same period at the First Affiliated Hospital of Zhengzhou University for comparison. Results: Compared with nTFHL-AI, nTFHL-NOS patients exhibited better clinical manifestations, lower TFH expression levels, and a lower Ki-67 index. However, no differences in clinicopathological features were observed between nTFHL-F and nTFHL-AI patients as well as nTFHL-NOS patients. According to the survival analysis, the median OS for patients with nTFHL-NOS, nTFHL-AI, and nTFHL-F were 14.2 months, 10 months, and 5 months, respectively, whereas the median TTP were 14 months, 5 months, and 3 months, respectively. Statistical analysis revealed differences in TTP among the three subtypes(P=0.0173). Among the population of patients receiving CHOP-like induction therapy, there were significant differences in the OS and TTP among the nTFHL-NOS, nTFHL-AI, and nTFHL-F patients (P=0.0134, P=0.0205). Both the GDPT and C-PET regimens significantly improved the ORR, OS, and PFS in nTFHL patients. Conclusion: There are significant differences in the clinical manifestations, pathology, and survival outcomes among the three subtypes of nTFHLs. However, further research with a larger sample size, and involving clinical pathology and molecular genetics is needed to determine the distinctive biological characteristics of these tumors.

Prediction of tumor origin in cancers of unknown primary origin with cytology-based deep learning.

Cancer of unknown primary (CUP) site poses diagnostic challenges due to its elusive nature. Many cases of CUP manifest as pleural and peritoneal serous effusions. Leveraging cytological images from 57,220 cases at four tertiary hospitals, we developed a deep-learning method for tumor origin differentiation using cytological histology (TORCH) that can identify malignancy and predict tumor origin in both hydrothorax and ascites. We examined its performance on three internal (n = 12,799) and two external (n = 14,538) testing sets. In both internal and external testing sets, TORCH achieved area under the receiver operating curve values ranging from 0.953 to 0.991 for cancer diagnosis and 0.953 to 0.979 for tumor origin localization. TORCH accurately predicted primary tumor origins, with a top-1 accuracy of 82.6% and top-3 accuracy of 98.9%. Compared with results derived from pathologists, TORCH showed better prediction efficacy (1.677 versus 1.265, P < 0.001), enhancing junior pathologists' diagnostic scores significantly (1.326 versus 1.101, P < 0.001). Patients with CUP whose initial treatment protocol was concordant with TORCH-predicted origins had better overall survival than those who were administrated discordant treatment (27 versus 17 months, P = 0.006). Our study underscores the potential of TORCH as a valuable ancillary tool in clinical practice, although further validation in randomized trials is warranted.

Peripheral T cell lymphoma initially presenting in lung biopsies: A diagnostic challenge.

BACKGROUND: Primary or secondary pulmonary involvement by peripheral T cell lymphoma (PTCL) is rare and difficult to diagnose particularly via lung biopsies. METHODS: 22 cases of PTCL diagnosed initially in lung biopsies between January 2006 and November 2020 were retrospectively reviewed followed at Nanjing Drum Tower Hospital and the First Affiliated Hospital of Zhengzhou University, respectively, including clinical manifestations, baseline biochemical indexes, images, histological findings and other available ancillary studies such as immunostaining, Epstein-Barr virus encoded RNA (EBER) in situ hybridization and T-cell receptor rearrangement analysis upon diagnosis. RESULTS: The median age of these patients was 59 years old (range: 29-82 years) at diagnosis. The majority of them complained of fever, cough and fatigue. Computed tomography scans mainly revealed multiple ill-defined nodules/masses of various sizes and densities with or without air bronchogram. Microscopically, most lesions showed lymphoid cells with clear cytoplasm and irregular nuclear contours diffusely infiltrating alveolar septa or alveolar spaces in an inflammatory background. Several cases had a predominance of small neoplastic cells (n = 4) with atypical, irregular nuclei. One case showed a diffuse monotonous pattern of growth. Angioinvasion and necrosis were not uncommon findings. The neoplastic cells in all cases were positive for one or more T-cell markers, and negative for B-cell-lineage antigens and EBER. 19 out of 22 patients had complete follow-up information, and 17 patients were dead at the last follow-up. CONCLUSIONS: Pulmonary involvement by PTCL is rare with dismal outcome. Aggressive clinical course and several clinicopathologic clues, albeit unspecific, may alert the pathologists of the possibilities of pulmonary PTCLs.

Construction of a nomogram model for deep vein thrombosis in patients with tibial plateau fracture based on the Systemic Inflammatory Response Index.

BACKGROUND: In recent years, the incidence of tibial plateau fracture has been on the rise, predominantly affecting the elderly population. Deep vein thrombosis may lead to poor prognosis in patients. the Systemic Inflammatory Response Index are novel biomarkers of inflammation, and this study aims to verify their predictive effect and construct the nomogram model. METHOD: This study used binary logistic regression analysis to predict the predictive effect of SIRI on the occurrence of DVT in tibial plateau fracture patients. And use R studio to construct nomogram model. RESULT: The results showed that NC (7.036 [3.516, 14.080], p < 0.001), LYM (0.507 [0.265, 0.969], p = 0.04), and SIRI (2.090 [1.044, 4.182], p = 0.037) were independent predictive factors for DVT. The nomogram demonstrated good predictive performance with small errors in both the training and validation groups, and most clinical patients could benefit from them. CONCLUSION: The nomogram constructed based on SIRI can assist clinicians in early assessment of the probability of DVT occurrence.

Computational Pathology for Prediction of Isocitrate Dehydrogenase Gene Mutation from Whole Slide Images in Adult Patients with Diffuse Glioma.

Isocitrate dehydrogenase gene (IDH) mutation is one of the most important molecular markers of glioma. Accurate detection of IDH status is a crucial step for integrated diagnosis of adult-type diffuse gliomas. Herein, a clustering-based hybrid of a convolutional neural network and a vision transformer deep learning model was developed to detect IDH mutation status from annotation-free hematoxylin and eosin-stained whole slide pathologic images of 2275 adult patients with diffuse gliomas. For comparison, a pure convolutional neural network, a pure vision transformer, and a classic multiple-instance learning model were also assessed. The hybrid model achieved an area under the receiver operating characteristic curve of 0.973 in the validation set and 0.953 in the external test set, outperforming the other models. The hybrid model's ability in IDH detection between difficult subgroups with different IDH status but shared histologic features, achieving areas under the receiver operating characteristic curve ranging from 0.850 to 0.985 in validation and test sets. These data suggest that the proposed hybrid model has a potential to be used as a computational pathology tool for preliminary rapid detection of IDH mutation from whole slide images in adult patients with diffuse gliomas.

Immune cell early activation, apoptotic kinetic, and T-cell functional impairment in domestic pigs after ASFV CADC_HN09 strain infection.

African swine fever (ASF) caused by the African swine fever virus (ASFV) is a fatal and highly contagious disease of domestic pigs characterized by rapid disease progression and death within 2 weeks. How the immune cells respond to acute ASFV infection and contribute to the immunopathogenesis of ASFV has not been completely understood. In this study, we examined the activation, apoptosis, and functional changes of distinct immune cells in domestic pigs following acute infection with the ASFV CADC_HN09 strain using multicolor flow cytometry. We found that ASFV infection induced broad apoptosis of DCs, monocytes, neutrophils, and lymphocytes in the peripheral blood of pigs over time. The expression of MHC class II molecule (SLA-DR/DQ) on monocytes and conventional DCs as well as CD21 expression on B cells were downregulated after ASFV infection, implying a potential impairment of antigen presentation and humoral response. Further examination of CD69 and ex vivo expression of IFN-γ on immune cells showed that T cells were transiently activated and expressed IFN-γ as early as 5 days post-infection. However, the capability of T cells to produce cytokines was significantly impaired in the infected pigs when stimulated with mitogen. These results suggest that the adaptive cellular immunity to ASFV might be initiated but later overridden by ASFV-induced immunosuppression. Our study clarified the cell types that were affected by ASFV infection and contributed to lymphopenia, improving our understanding of the immunopathogenesis of ASFV.

Ultrafast Response Organic Photoswitch Materials and Their Application in Volumetric 3D Display.

Volumetric three-dimensional (3D) display technology based on static screens is a crucial branch of 3D displays. The essential component in volumetric 3D displays is selectively excitable display media that can generate voxels at any position. Here, we synthesized a series of organic photoswitch materials to meet the specific requirements of 3D display mediums. In these photoswitch solutions, voxels are activated ultrafast within tens of picoseconds at the intersection of two control lasers and faded rapidly within tens of milliseconds when switching light is turned off. An experimental volumetric 3D display system utilizing an organic photoswitch solution as a screen is demonstrated. The system not only achieves a dynamic 3D display but also enables 360° viewing. The volumetric 3D display system can display true 3D images without auxiliary glasses and is expected to be applicable in fields as diverse as virtual reality, medical imaging, architectural design, and military visualization.

Nomogram based on high-density lipoprotein cholesterol for the occurrence of preoperative deep vein thrombosis in patients with intertrochanteric femur fracture: a retrospective study.

BACKGROUND: This study aims to develop a nomogram and forecast the incidence of DVT in individuals suffering from an intertrochanteric femur fracture. METHOD: This work created a nomogram using the R programming language and employed logistic regression to determine independent predicting features. An external validation dataset was used to validate the nomogram. RESULT: The findings demonstrated the independence of LYM (0.02[0.01-0.09], p < 0.001), ALB (0.83[0.74, 0.94], p = 0.002), and HDL-C (0.18[0.04, 0.71], p = 0.014). Good prediction performance with modest errors was shown by the nomogram in both the training and validation groups. CONCLUSION: In conclusion, the nomogram that was created using HDL-C, ALB, and LYM can assist medical professionals in determining the likelihood that DVT will occur.

The expression and clinical significance of PLK1/p-PLK1 protein in NK/T cell Lymphoma.

AIMS: To investigate the expression of polo-like kinase 1 protein (PLK1) and its phosphorylation level (p-PLK1) in extranodal NK/T cell lymphoma (NKTCL) and their correlation with clinical characteristics and prognosis. METHODS: We collected 40 cases of NKTCL (referred to as the experimental group), which received diagnoses at the First Affiliated Hospital of Zhengzhou University between January 2018 and October 2022. Concurrently, we assembled a control group, including 20 cases afflicted with nasopharyngeal mucosal lymphoid hyperplasia diseases during the same timeframe. We utilized immunohistochemical techniques to evaluate the levels of PLK1 and p-PLK1 expression in both the experimental and control groups. Subsequently, we conducted an analysis to identify disparities in their expression and explore their relationships with clinical characteristics and patient prognosis. RESULTS: Among the 40 NKTCL patients, there were 27 males and 11 females, with a median age of 51 years (range 12-80 years). Compared to the control group, the tissue samples of NKTCL patients exhibited significantly elevated expression levels and active phosphorylation levels of PLK1 (P < 0.05). Correlation analysis of the immunohistochemical H score and Ki-67 positive rate of PLK1 and p-PLK1, revealed a significant positive correlation for both (P < 0.0001, each). No statistically significant differences were observed in the distribution of PLK1 and p-PLK1 expression in NKTCL patients with respect to gender, age, Ann Arbor stage, PINK-E score, B-symptoms, lactate dehydrogenase, ß2-microglobulin, blood EBV-DNA, bone marrow invasion, and lymph node metastasis (p > 0.05). Grouping based on PLK1 and p-PLK1 immunohistochemical H-scores revealed that the high expression of PLK1 and p-PLK1 was associated with poor prognosis. CONCLUSIONS: The expression levels and active phosphorylation levels of PLK1 were significantly increased in NK/T cell lymphoma, and patients with overexpression of PLK1 and p-PLK1 had a poorer prognosis.

Predictive value of suprasellar extension for intracranial infection after endoscopic transsphenoidal pituitary adenoma resection.

OBJECTIVE: To investigate the relationship between suprasellar extension (SSE) and intracranial infection after endoscopic endonasal transsphenoidal approach (EETA) for pituitary adenoma resection. METHODS: We retrospectively analyzed 94 patients with suprasellar extended pituitary adenoma admitted to the Department of Neurosurgery of the Affiliated Hospital of Guilin Medical College from January 2018 to December 2021. We measured the preoperative magnetic resonance sagittal SSE and collected clinical data and divided the patients into groups according to the presence of postoperative intracranial infection. The critical value for the SSE was calculated by using a working characteristic curve for the subjects. The risk factors for intracranial infection after EETA resection of pituitary adenomas were analyzed by multivariate regression analysis. RESULTS: Among the 94 patients, 12 cases (12.8%) were placed in the infection group and 82 cases (87.2%) in the non-infection group. The cut-off value for the SSE in the sagittal position was 15.6 mm, the sensitivity was 75%, the specificity was 87.8%, and the area under the curve (AUC) was 0.801. The coronary cut-off value for the SSE was 15.8 mm, the sensitivity was 66.7%, the specificity was 79.3%, and the AUC was 0.787. The SSE values in the sagittal and coronal positions were correlated with postoperative intracranial infection (P < 0.05). After univariate analysis, those with significant differences were included in the multivariate regression analysis. It was concluded that the extension distance of the tumor above the sella in the sagittal position was ≥ 15.6 mm, the tumor texture was hard, and the postoperative cerebrospinal fluid leakage were the independent risk factors for intracranial infection after EETA resection of suprasellar extended pituitary tumors (P < 0.05). CONCLUSIONS: The value of SSE on sagittal MRI can predict intracranial infection in patients with suprasellar extended pituitary adenoma after endoscopic endonasal transsphenoidal resection. This finding recommends neurosurgeons pay more attention to the imaging characteristics of pituitary adenomas and select appropriate treatment plans in combination with the intraoperative conditions to reduce the incidence of intracranial infection.

Neuropathologist-level integrated classification of adult-type diffuse gliomas using deep learning from whole-slide pathological images.

Current diagnosis of glioma types requires combining both histological features and molecular characteristics, which is an expensive and time-consuming procedure. Determining the tumor types directly from whole-slide images (WSIs) is of great value for glioma diagnosis. This study presents an integrated diagnosis model for automatic classification of diffuse gliomas from annotation-free standard WSIs. Our model is developed on a training cohort (n = 1362) and a validation cohort (n = 340), and tested on an internal testing cohort (n = 289) and two external cohorts (n = 305 and 328, respectively). The model can learn imaging features containing both pathological morphology and underlying biological clues to achieve the integrated diagnosis. Our model achieves high performance with area under receiver operator curve all above 0.90 in classifying major tumor types, in identifying tumor grades within type, and especially in distinguishing tumor genotypes with shared histological features. This integrated diagnosis model has the potential to be used in clinical scenarios for automated and unbiased classification of adult-type diffuse gliomas.

Identifying novel disease categories through divergence optimization: An approach to prevent misdiagnosis in medical imaging.

Given the significant changes in human lifestyle, the incidence of colon cancer has rapidly increased. The diagnostic process can often be complicated due to symptom similarities between colon cancer and other colon-related diseases. In an effort to minimize misdiagnosis, deep learning-based approaches for colon cancer diagnosis have notably progressed within the field of clinical medicine, offering more precise detection and improved patient outcomes. Despite these advancements, practical application of these techniques continues to encounter two major challenges: 1) due to the need for expert annotation, only a limited number of labels are utilized for diagnosis; and 2) the existence of diverse disease types can lead to misdiagnosis when the model encounters unfamiliar disease categories. To overcome these hurdles, we present a method incorporating Universal Domain Adaptation (UniDA). By optimizing the divergence of samples in the source domain, our method detects noise. Furthermore, to identify categories that are not present in the source domain, we optimize the divergence of unlabeled samples in the target domain. Experimental validation on two gastrointestinal datasets demonstrates that our method surpasses current state-of-the-art domain adaptation techniques in identifying unknown disease classes. It is worth noting that our proposed method is the first work of medical image diagnosis aimed at the identification of unknown categories of diseases.

Prognostic significance of fibrinogen and neutrophil/lymphocyte ratio score and D-dimer/Albumin ratio for prognosis in patients with aneurysmal subarachnoid hemorrhage.

BACKGROUND: Recent research indicates that systemic inflammation significantly affects the overall prognosis of individuals with aneurysmal subarachnoid hemorrhage. To delve deeper into this issue, a retrospective study was undertaken. The study aimed to investigate the relationship between fibrinogen and neutrophil/lymphocyte ratio scores, D-dimer/Albumin ratios, and the Glasgow Outcome Scale at 6 months post-discharge for patients with aSAH. METHODS: A retrospective analysis was conducted on 321 patients who experienced aneurysmal subarachnoid hemorrhage. These patients were monitored using the Glasgow Outcome Scale six months after being discharged from Huizhou Central People's Hospital. Patients with GOS scores between 1 and 3 were classified as having a poor prognosis, while those with scores ranging from 4 to 5 were considered to have a good prognosis. To create distinct sets, patients were randomly divided into both training and validation groups. The best cut-off value for the D-dimer/Albumin ratio was established through ROC curves, and the scores for fibrinogen and the neutrophil/lymphocyte ratio were calculated. Utilizing multivariate logistic regression analysis, independent risk factors linked to an unfavorable prognosis in aSAH patients were identified. A nomogram model was developed and validated based on these findings, providing an improved approach for evaluating the prognostic influence of risk factors. To gauge the model's predictive performance, several analytical tools such as ROC curves, calibration curves, and decision curve analysis were employed. This comprehensive approach ensured a thorough assessment of the prognostic prediction capabilities of the model. RESULTS: Multivariate regression analysis revealed that Age (OR=3.87, 95%CI=1.54-9.73, p=0.004), Pneumonia (OR=3.54, 95%CI=1.41-8.86, p=0.007), WFNS (OR=3.24, 95%CI=1.23-8.54, p=0.017), DAR (OR=2.88, 95%CI=1.13-7.34, p=0.027), and F-NLR (OR=3.12, 95%CI=1.22-7.97, p=0.017) were identified as independent risk factors influencing the prognosis of patients with aSAH. Additionally, the area under the ROC curve was 0.866 (95%CI=0.805-0.927) for the training set and 0.924 (95%CI=0.849-0.999) for the validation set. The calibration curve analysis demonstrated a minor error of 0.02 for the training set and 0.051 for the validation set. Furthermore, both the training set and validation set displayed significant clinical benefits according to the DCA curves, underscoring the meaningful utility of the developed nomogram. CONCLUSIONS: Fibrinogen and neutrophil/lymphocyte ratio scores, and the D-dimer/Albumin ratio emerged as significant independent risk factors for prognosticating the outcomes of patients with aSAH. Leveraging these factors, a robust nomogram model was meticulously developed, showcasing its impressive precision in prognostic predictions. These results underscore the promising clinical applicability of these biomarkers as effective prognostic indicators for individuals afflicted by aSAH.

A nomogram model based on the combination of the systemic immune-inflammation index, body mass index, and neutrophil/lymphocyte ratio to predict the risk of preoperative deep venous thrombosis in elderly patients with intertrochanteric femoral fracture: a retrospective cohort study.

OBJECTIVES: Deep vein thrombosis (DVT) has been considered as a frequent and serious consequence of intertrochanteric femoral fractures in the elderly. Several negative repercussions of DVT can be considerably mitigated by its timely recognition and treatment. The current work was aimed at exploring the factors independently predicting DVT among cases suffering from intertrochanteric femoral fractures and validate their predictive usefulness in diagnosing DVT. METHODS: Between April 2017 and July 2022, clinical information from 209 cases showing preoperative DVT for femoral intertrochanteric fractures were retrospectively evaluated. In patients with femoral intertrochanteric fractures, logistic regression analysis with a backward stepwise method was adopted for detecting independent predictors for the diagnosis of preoperative DVT. Using multivariate logistic regression, a nomogram prediction model was developed and verified with the testing group. RESULTS: According to multivariate logistic regression model, body mass index (BMI) (OR 0.79, 95% CI 0.63-0.99, P = 0.042), neutrophil/lymphocyte ratio (NLR) (OR 7.29, 95% CI 1.53, 34.64, P = 0.0012), and systemic immune-inflammation index (SII) (OR 6.61, 95% CI 2.35, 18.59, P = 0.001) were independent predictors for DVT before surgery among cases developing intertrochanteric femoral fracture. AUC values were 0.862 and 0.767 for training and testing groups, separately, while their mean errors in the calibration curve were 0.027 and 0.038 separately. Decision curve analysis (DCA) curve revealed a high value of clinical application for both groups. CONCLUSION: Upon admission, BMI, NLR, and SII are independent predictors of DVT before surgery among cases developing intertrochanteric femoral fractures. Additionally, the nomogram based on the BMI, NLR, and SII can assist clinicians in determining if preventive and symptomatic therapies are required to improve DVT prognosis and reduce its associated mortality.

Clinical evaluation of a multitarget fecal immunochemical test-sDNA test for colorectal cancer screening in a high-risk population: a prospective, multicenter clinical study.

Colorectal cancer (CRC) is a major malignancy threatening the health of people in China and screening could be effective for preventing the occurrence and reducing the mortality of CRC. We conducted a multicenter, prospective clinical study which recruited 4,245 high-risk CRC individuals defined as having positive risk-adapted scores or fecal immunochemical test (FIT) results, to evaluate the clinical performance of the multitarget fecal immunochemical and stool DNA (FIT-sDNA) test for CRC screening. Each participant was asked to provide a stool sample prior to bowel preparation, and FIT-sDNA test and FIT were performed independently of colonoscopy. We found that 186 (4.4%) were confirmed to have CRC, and 375 (8.8%) had advanced precancerous neoplasia among the high CRC risk individuals. The sensitivity of detecting CRC for FIT-sDNA test was 91.9% (95% CI, 86.8-95.3), compared with 62.4% (95% CI, 54.9-69.3) for FIT (P < 0.001). The sensitivity for detecting advanced precancerous neoplasia was 63.5% (95% CI, 58.3-68.3) for FIT-sDNA test, compared with 30.9% (95% CI, 26.3-35.6) for FIT (P < 0.001). Multitarget FIT-sDNA test detected more colorectal advanced neoplasia than FIT. Overall, these findings indicated that in areas with limited colonoscopy resources, FIT-sDNA test could be a promising further risk triaging modality to select patients for colonoscopy in CRC screening.

PARP inhibitor exerts an anti-tumor effect via LMO2 and synergizes with cisplatin in natural killer/T cell lymphoma.

BACKGROUND: PARP inhibitor (PARPi), as a kind of DNA damage repair inhibitor, has been shown to be effective in various solid tumors and hematologic malignancies. Natural killer/T cell lymphoma (NKTCL) is a highly aggressive malignancy, the treatment of which has long been a major challenge in the clinic. Here, we investigated the efficacy and mechanism of PARPi, and the therapeutic value of PARPi combined with cisplatin in NKTCL. METHODS: The cell proliferation, cell apoptosis, and cell cycle of NKTCL cells were detected respectively by CCK-8 and flow cytometry. The changes of mRNA expression and protein level were measured respectively by mRNA-sequencing, quantitative real-time PCR, western blotting, and immunofluorescence. LMO2 expression was detected by immunohistochemistry and western blotting. Targeted knockdown of LMO2 was conducted by short hairpin RNA. The tumor xenograft models were established to evaluate the efficacy of drugs in vivo. RESULTS: PARPi inhibited cell proliferation, promoted cell apoptosis, and induced S-phase cell cycle arrest in NKTCL cells. PARPi led to the accumulation of DNA damage by blocking DNA repair and DNA replication. Additionally, LMO2 deficiency reduced the sensitivity of NKTCL cells to PARPi. Finally, the combination of PARPi and cisplatin exhibited significant synergistic effects both in vitro and in vivo. CONCLUSIONS: In summary, we found that PARPi exerted an anti-tumor effect via LMO2 and synergized with cisplatin in NKTCL, which provides the theoretical basis for the clinical application of PARPi.