Analysis of postoperative urinary incontinence and influencing factors of transurethral holmium laser enucleation of the prostate.

INTRODUCTION: To investigate the related factors of urinary incontinence after transurethral holmium laser enucleation of the prostate (HoLEP), and to provide guidance for clinical urinary control of HoLEP. METHODS: The clinical data of 548 patients who underwent HoLEP were retrospectively analyzed. The patients were followed up for the occurrence of urinary incontinence in the short term (2 weeks), medium term (3 months) and long term (6 months) after HoLEP. RESULTS: Among the 548 benign prostatic hyperplasia (BPH) patients, 79 cases (14.42%) had urinary incontinence at 2 weeks, 19 cases (3.47%) at 3 months and 2 cases (0.36%) at 6 months after surgery. Logistic regression analysis showed that age, prostate volume, diabetes mellitus, operation time, prostate tissue weight and histological prostatitis were risk factors for recent urinary incontinence (P<0.05). Age, diabetes and operation time were risk factors for mid-term urinary incontinence (P<0.05). The incidence of long-term urinary incontinence was low and no risk factor analysis was performed. CONCLUSIONS: For good urinary control after HoLEP, in addition to surgery-related factors such as surgical skills, proficiency and precise anatomy, patients' risk factors should also be paid attention to in order to improve postoperative urinary control more effectively and reduce the incidence of urinary incontinence.

Bridging the STRONG Gap: Call to Optimize Heart Failure Treatment after Hospitalization in Women and Men in Taiwan.

The benefits of rapidly up-titrating evidence-based treatments following heart failure (HF) hospitalizations were demonstrated in the STRONG-HF trial and emphasized in contemporary HF guideline. We aimed to assess up-titration patterns of guideline-directed medical treatments in Taiwanese HF population. Combining data from the TSOC-HFrEF registry and the TAROT-AHF study cohort, we formed the "Taiwan real-world cohort". We compared these data with subgroups of patients with left ventricular ejection fraction ≤ 40% in the STRONG-HF trial. Patients in the Taiwan exhibited similar blood pressure, heart rate and N-terminal pro B-type natriuretic peptide levels at discharge compared to those in the STRONG-HF trial. A higher proportion of patients in the STRONG-HF high-intensity care group received up-titrations compared to those in the usual care group and the Taiwan cohort. Composite all-cause mortality or HF hospitalization at 180 days for patients in the high-intensity care group, usual care group, and Taiwan cohort were 17.4%, 23.7%, and 31.9%, respectively, with differences largely contributed by HF hospitalization (10.1%, 17.9%, and 27.6%, respectively), while all-cause mortality rates were similar (11.0%, 9.6%, and 9.3%, respectively). Gender did not affect this trend. In conclusion, our data highlights a treatment gap between the STRONG-HF trial and real-world practices in Taiwan, urging prompt optimization of HF therapy.

Colorectal cancer-specific IFNß delivery overcomes dysfunctional dsRNA-mediated type I interferon signaling to increase the abscopal effect of radiotherapy.

BACKGROUND: Cancer-intrinsic type I interferon (IFN-I) production triggered by radiotherapy (RT) is mainly dependent on cytosolic double-stranded DNA (dsDNA)-mediated cGAS/STING signaling and increases cancer immunogenicity and enhances the antitumor immune response to increase therapeutic efficacy. However, cGAS/STING deficiency in colorectal cancer (CRC) may suppress the RT-induced antitumor immunity. Therefore, we aimed to evaluate the importance of the dsRNA-mediated antitumor immune response induced by RT in patients with CRC. METHODS: Cytosolic dsRNA level and its sensors were evaluated via cell-based assays (co-culture assay, confocal microscopy, pharmacological inhibition and immunofluorescent staining) and in vivo experiments. Biopsies and surgical tissues from patients with CRC who received preoperative chemoradiotherapy (neoCRT) were collected for multiplex cytokine assays, immunohistochemical analysis and SNP genotyping. We also generated a cancer-specific adenovirus-associated virus (AAV)-IFNß1 construct to evaluate its therapeutic efficacy in combination with RT, and the immune profiles were analyzed by flow cytometry and RNA-seq. RESULTS: Our studies revealed that RT stimulates the autonomous release of dsRNA from cancer cells to activate TLR3-mediated IFN-I signatures to facilitate antitumor immune responses. Patients harboring a dysfunctional TLR3 variant had reduced serum levels of IFN-I-related cytokines and intratumoral CD8+ immune cells and shorter disease-free survival following neoCRT treatment. The engineered cancer-targeted construct AAV-IFNß1 significantly improved the response to RT, leading to systematic eradication of distant tumors and prolonged survival in defective TLR3 preclinical models. CONCLUSION: Our results support that increasing cancer-intrinsic IFNß1 expression is an immunotherapeutic strategy that enhances the RT-induced antitumor immune response in locally patients with advanced CRC with dysfunctional TLR3.

Extractor-attention-predictor network for quantitative photoacoustic tomography.

Quantitative photoacoustic tomography (qPAT) holds great potential in estimating chromophore concentrations, whereas the involved optical inverse problem, aiming to recover absorption coefficient distributions from photoacoustic images, remains challenging. To address this problem, we propose an extractor-attention-predictor network architecture (EAPNet), which employs a contracting-expanding structure to capture contextual information alongside a multilayer perceptron to enhance nonlinear modeling capability. A spatial attention module is introduced to facilitate the utilization of important information. We also use a balanced loss function to prevent network parameter updates from being biased towards specific regions. Our method obtains satisfactory quantitative metrics in simulated and real-world validations. Moreover, it demonstrates superior robustness to target properties and yields reliable results for targets with small size, deep location, or relatively low absorption intensity, indicating its broader applicability. The EAPNet, compared to the conventional UNet, exhibits improved efficiency, which significantly enhances performance while maintaining similar network size and computational complexity.

Advances in molecular mechanisms and therapeutic strategies for central nervous system diseases based on gut microbiota imbalance.

BACKGROUD: Central nervous system (CNS) diseases pose a serious threat to human health, but the regulatory mechanisms and therapeutic strategies of CNS diseases need to be further explored. It has been demonstrated that the gut microbiota (GM) is closely related to CNS disease. GM structure disorders, abnormal microbial metabolites, intestinal barrier destruction and elevated inflammation exist in patients with CNS diseases and promote the development of CNS diseases. More importantly, GM remodeling alleviates CNS pathology to some extent. AIM OF REVIEW: Here, we have summarized the regulatory mechanism of the GM in CNS diseases and the potential treatment strategies for CNS repair based on GM regulation, aiming to provide safer and more effective strategies for CNS repair from the perspective of GM regulation. KEY SCIENTIFIC CONCEPTS OF REVIEW: The abundance and composition of GM is closely associated with the CNS diseases. On the basis of in-depth analysis of GM changes in mice with CNS disease, as well as the changes in its metabolites, therapeutic strategies, such as probiotics, prebiotics, and FMT, may be used to regulate GM balance and affect its microbial metabolites, thereby promoting the recovery of CNS diseases.

Collective effects of rising average temperatures and heat events on oviparous embryos.

Survival of the immobile embryo in response to rising temperature is important to determine a species' vulnerability to climate change. However, the collective effects of 2 key thermal characteristics associated with climate change (i.e., rising average temperature and acute heat events) on embryonic survival remain largely unexplored. We used empirical measurements and niche modeling to investigate how chronic and acute heat stress independently and collectively influence the embryonic survival of lizards across latitudes. We collected and bred lizards from 5 latitudes and incubated their eggs across a range of temperatures to quantify population-specific responses to chronic and acute heat stress. Using an embryonic development model parameterized with measured embryonic heat tolerances, we further identified a collective impact of embryonic chronic and acute heat tolerances on embryonic survival. We also incorporated embryonic chronic and acute heat tolerance in hybrid species distribution models to determine species' range shifts under climate change. Embryos' tolerance of chronic heat (T-chronic) remained consistent across latitudes, whereas their tolerance of acute heat (T-acute) was higher at high latitudes than at low latitudes. Tolerance of acute heat exerted a more pronounced influence than tolerance of chronic heat. In species distribution models, climate change led to the most significant habitat loss for each population and species in its low-latitude distribution. Consequently, habitat for populations across all latitudes will shift toward high latitudes. Our study also highlights the importance of considering embryonic survival under chronic and acute heat stresses to predict species' vulnerability to climate change.

Efectos colectivos del aumento de las temperaturas promedio y los eventos de calor en embriones ovíparos Resumen La supervivencia de los embriones inmóviles en respuesta al incremento de temperatura es importante para determinar la vulnerabilidad de las especies al cambio climático. Sin embargo, los efectos colectivos de dos características térmicas claves asociadas con el cambio climático (i. e., aumento de temperatura promedio y eventos de calor agudo) sobre la supervivencia embrionaria permanecen en gran parte inexplorados. Utilizamos mediciones empíricas y modelos de nicho para investigar cómo el estrés térmico crónico y agudo influye de forma independiente y colectiva en la supervivencia embrionaria de los lagartos en todas las latitudes. Recolectamos y criamos lagartos de cinco latitudes e incubamos sus huevos en un rango de temperaturas para cuantificar las respuestas específicas de la población al estrés por calor crónico y agudo. Posteriormente, mediante un modelo de desarrollo embrionario parametrizado con mediciones de tolerancia embrionaria al calor, identificamos un impacto colectivo de las tolerancias embrionarias al calor agudo y crónico en la supervivencia embrionaria. También incorporamos la tolerancia embrionaria crónica y aguda al calor en modelos de distribución de especies híbridas para determinar los cambios de distribución de las especies bajo el cambio climático. La tolerancia embrionaria al calor crónico (T­crónico) permaneció constante, mientras que la tolerancia al calor agudo (T­agudo) fue mayor en latitudes altas que en latitudes bajas. La tolerancia al calor agudo ejerció una influencia más pronunciada que la tolerancia al calor crónico. En los modelos de distribución de especies, el cambio climático provocó la pérdida de hábitat más significativa para cada población y especie en su distribución de latitudes bajas. En consecuencia, el hábitat para poblaciones en todas las latitudes se desplazará a latitudes altas. Nuestro estudio también resalta la importancia de considerar la supervivencia embrionaria bajo estrés térmico crónico y agudo para predecir la vulnerabilidad de las especies al cambio climático.

Activation of STING by the novel liposomal TLC388 enhances the therapeutic response to anti-PD-1 antibodies in combination with radiotherapy.

Current immune checkpoint inhibiters (ICIs) have contrasting clinical results in poorly immunogenic cancers such as microsatellite-stable colorectal cancer (MSS-CRC). Therefore, understanding and developing the combinational therapeutics for ICI-unresponsive cancers is critical. Here, we demonstrated that the novel topoisomerase I inhibitor TLC388 can reshape the tumor immune landscape, corroborating their antitumor effects combined with radiotherapy as well as immunotherapy. We found that TLC388 significantly triggered cytosolic single-stranded DNA (ssDNA) accumulation for STING activation, leading to type I interferons (IFN-Is) production for increased cancer immunogenicity to enhance antitumor immunity. TLC388-treated tumors were infiltrated by a vast number of dendritic cells, immune cells, and costimulatory molecules, contributing to the favorable antitumor immune response within the tumor microenvironment. The infiltration of cytotoxic T and NK cells were more profoundly existed within tumors in combination with radiotherapy and ICIs, leading to superior therapeutic efficacy in poorly immunogenic MSS-CRC. Taken together, these results showed that the novel topoisomerase I inhibitor TLC388 increased cancer immunogenicity by ssDNA/STING-mediated IFN-I production, enhancing antitumor immunity for better therapeutic efficacy in combination with radiotherapy and ICIs for poorly immunogenic cancer.

Integrated analysis of transcriptional changes in major depressive disorder: Insights from blood and anterior cingulate cortex.

Background: Major depressive disorder (MDD) was involved in widely transcriptional changes in central and peripheral tissues. While, previous studies focused on single tissues, making it difficult to represent systemic molecular changes throughout the body. Thus, there is an urgent need to explore the central and peripheral biomarkers with intrinsic correlation. Methods: We systematically retrieved gene expression profiles of blood and anterior cingulate cortex (ACC). 3 blood datatsets (84 MDD and 88 controls) and 6 ACC datasets (100 MDD and 100 controls) were obtained. Differential expression analysis, RobustRankAggreg (RRA) analysis, functional enrichment analysis, immune associated analysis and protein-protein interaction networks (PPI) were integrated. Furthermore, the key genes were validated in an independent ACC dataset (12 MDD and 15 controls) and a cohort with 120 MDD and 117 controls. Results: Differential expression analysis identified 2211 and 2021 differential expressed genes (DEGs) in blood and ACC, respectively. RRA identified 45 and 25 robust DEGs in blood and ACC based on DEGs, and all of them were closely associated with immune cells. Functional enrichment results showed both the robust DEGs in blood and ACC were enriched in humoral immune response. Furthermore, PPI identified 8 hub DEGs (CD79A, CD79B, CD19, MS4A1, PLP1, CLDN11, MOG, MAG) in blood and ACC. Independent ACC dataset showed the area under the curve (AUC) based on these hub DEGs was 0.77. Meanwhile, these hub DEGs were validated in the serum of MDD patients, and also showed a promising diagnostic power. Conclusions: The biomarker panel based on hub DEGs yield a promising diagnostic efficacy, and all of these hub DEGs were strongly correlated with immunity. Humoral immune response may be the key link between the brain and blood in MDD, and our results may provide further understanding for MDD.

Evaluation of large language models in breast cancer clinical scenarios: a comparative analysis based on ChatGPT-3.5, ChatGPT-4.0, and Claude2.

BACKGROUND: Large language models (LLMs) have garnered significant attention in the AI domain owing to their exemplary context recognition and response capabilities. However, the potential of LLMs in specific clinical scenarios, particularly in breast cancer diagnosis, treatment, and care, has not been fully explored. This study aimed to compare the performances of three major LLMs in the clinical context of breast cancer. METHODS: In this study, clinical scenarios designed specifically for breast cancer were segmented into five pivotal domains (nine cases): assessment and diagnosis, treatment decision-making, postoperative care, psychosocial support, and prognosis and rehabilitation. The LLMs were used to generate feedback for various queries related to these domains. For each scenario, a panel of five breast cancer specialists, each with over a decade of experience, evaluated the feedback from LLMs. They assessed feedback concerning LLMs in terms of their quality, relevance, and applicability. RESULTS: There was a moderate level of agreement among the raters (Fleiss' kappa=0.345, P<0.05). Comparing the performance of different models regarding response length, GPT-4.0 and GPT-3.5 provided relatively longer feedback than Claude2. Furthermore, across the nine case analyses, GPT-4.0 significantly outperformed the other two models in average quality, relevance, and applicability. Within the five clinical areas, GPT-4.0 markedly surpassed GPT-3.5 in the quality of the other four areas and scored higher than Claude2 in tasks related to psychosocial support and treatment decision-making. CONCLUSION: This study revealed that in the realm of clinical applications for breast cancer, GPT-4.0 showcases not only superiority in terms of quality and relevance but also demonstrates exceptional capability in applicability, especially when compared to GPT-3.5. Relative to Claude2, GPT-4.0 holds advantages in specific domains. With the expanding use of LLMs in the clinical field, ongoing optimization and rigorous accuracy assessments are paramount.

Unleashing the potential: integrating nano-delivery systems with traditional Chinese medicine.

This review explores the potential of integrating nano-delivery systems with traditional Chinese herbal medicine, acupuncture, and Chinese medical theory. It highlights the intersections and potential of nano-delivery systems in enhancing the effectiveness of traditional herbal medicine and acupuncture treatments. In addition, it discusses how the integration of nano-delivery systems with Chinese medical theory can modernize herbal medicine and make it more readily accessible on a global scale. Finally, it analyzes the challenges and future directions in this field.

Alterations of the gut microbiota in patients with schizophrenia.

Introduction: Schizophrenia is a complex psychiatric disorder, of which molecular pathogenesis remains largely unknown. Accumulating evidence suggest that gut microbiota may affect brain function via the complex gut-brain axis, which may be a potential contributor to schizophrenia. However, the alteration of gut microbiota showed high heterogeneity across different studies. Therefore, this study aims to identify the consistently altered gut microbial taxa associated with schizophrenia. Methods: We conducted a systematic search and synthesis of the up-to-date human gut microbiome studies on schizophrenia, and performed vote counting analyses to identify consistently changed microbiota. Further, we investigated the effects of potential confounders on the alteration of gut microbiota. Results: We obtained 30 available clinical studies, and found that there was no strong evidence to support significant differences in α-diversity and ß-diversity between schizophrenic patients and healthy controls. Among 428 differential gut microbial taxa collected from original studies, we found that 8 gut microbial taxa were consistently up-regulated in schizophrenic patients, including Proteobacteria, Gammaproteobacteria, Lactobacillaceae, Enterobacteriaceae, Lactobacillus, Succinivibrio, Prevotella and Acidaminococcus. While 5 taxa were consistently down-regulated in schizophrenia, including Fusicatenibacter, Faecalibacterium, Roseburia, Coprococcus and Anaerostipes. Discussion: These findings suggested that gut microbial changes in patients with schizophrenia were characterized by the depletion of anti-inflammatory butyrate-producing genera, and the enrichment of certain opportunistic bacteria genera and probiotics. This study contributes to further understanding the role of gut microbiota in schizophrenia, and developing microbiota-based diagnosis and therapy for schizophrenia.

Biomimetic and multifunctional nanocomposites for precision fungi theranostics.

Fungi infection is a serious threat to public health, but an effective antifungal strategy remains a challenge. Herein, a biomimetic nanocomposite with multifunctionalities, including fungi diagnosis, antifungal adhesion, precise fungi elimination, and cytokine sequestration, is constructed for battling Candida albicans (C. albicans) infection. By screening a range of cells, we find that the polarized macrophage cells have the strongest binding tendency toward C. albicans. Thus, their membranes were exfoliated to camouflage UCNPs and then decorated with photosensitizers (methylene blue, MB) and DNA sensing elements. The resulting nanocomposite can tightly bind to fungal surfaces, promote DNA recognition, and squeeze pro-inflammatory cytokines to relieve inflammation. Consequently, this nanocomposite can detect C. albicans with enhanced sensitivity and precisely eliminate fungal cells through photodynamic therapy with minimal phototoxicity because of its switchable fluorescence behavior. The developed nanocomposite with good biocompatibility achieves a satisfactory diagnostic and therapeutic effect in a C. albicans-infected mouse model, which offers a unique approach to fight fungi infection.

Temperature-Dependent Evaporative Anthropogenic VOC Emissions Significantly Exacerbate Regional Ozone Pollution.

The evaporative emissions of anthropogenic volatile organic compounds (AVOCs) are sensitive to ambient temperature. This sensitivity forms an air pollution-meteorology connection that has not been assessed on a regional scale. We parametrized the temperature dependence of evaporative AVOC fluxes in a regional air quality model and evaluated the impacts on surface ozone in the Beijing-Tianjin-Hebei (BTH) area of China during the summer of 2017. The temperature dependency of AVOC emissions drove an enhanced simulated ozone-temperature sensitivity of 1.0 to 1.8 µg m-3 K-1, comparable to the simulated ozone-temperature sensitivity driven by the temperature dependency of biogenic VOC emissions (1.7 to 2.4 µg m-3 K-1). Ozone enhancements driven by temperature-induced AVOC increases were localized to their point of emission and were relatively more important in urban areas than in rural regions. The inclusion of the temperature-dependent AVOC emissions in our model improved the simulated ozone-temperature sensitivities on days of ozone exceedance. Our results demonstrated the importance of temperature-dependent AVOC emissions on surface ozone pollution and its heretofore unrepresented role in air pollution-meteorology interactions.

Macrophage-modulating nanomedicine for cancer immunotherapy.

Tumor-associated macrophages (TAMs) play crucial roles in the immunosuppressive solid tumor microenvironment (TME). Despite their tumor-promoting functions, TAMs can also be therapeutically modulated to exhibit tumor-killing properties, making them attractive targets for tumor immunotherapy. This review highlights the recent advances in nanomedicine-based strategies centered around macrophages for enhanced cancer immunotherapy. Emerging nanomedicine-based strategies to modulate TAMs in cancer treatment include repolarization of the TAM phenotype, inhibition of monocyte recruitment, depletion of TAMs, and blockage of immune checkpoints. These strategies have shown great promise in significantly improving the efficacy of cancer immunotherapy. Moreover, macrophage-inspired drug delivery systems have demonstrated significant promise in inducing immunotherapeutic effects and enhancing therapeutic efficacy by facilitating evasion from the reticuloendothelial system and promoting accumulation at the tumor site. Finally, we also discuss the challenges and propose future opportunities associated with macrophage-modulating nanomedicine to enhance cancer immunotherapy.

Artificial intelligence-powered pharmacovigilance: A review of machine and deep learning in clinical text-based adverse drug event detection for benchmark datasets.

OBJECTIVE: The primary objective of this review is to investigate the effectiveness of machine learning and deep learning methodologies in the context of extracting adverse drug events (ADEs) from clinical benchmark datasets. We conduct an in-depth analysis, aiming to compare the merits and drawbacks of both machine learning and deep learning techniques, particularly within the framework of named-entity recognition (NER) and relation classification (RC) tasks related to ADE extraction. Additionally, our focus extends to the examination of specific features and their impact on the overall performance of these methodologies. In a broader perspective, our research extends to ADE extraction from various sources, including biomedical literature, social media data, and drug labels, removing the limitation to exclusively machine learning or deep learning methods. METHODS: We conducted an extensive literature review on PubMed using the query "(((machine learning [Medical Subject Headings (MeSH) Terms]) OR (deep learning [MeSH Terms])) AND (adverse drug event [MeSH Terms])) AND (extraction)", and supplemented this with a snowballing approach to review 275 references sourced from retrieved articles. RESULTS: In our analysis, we included twelve articles for review. For the NER task, deep learning models outperformed machine learning models. In the RC task, gradient Boosting, multilayer perceptron and random forest models excelled. The Bidirectional Encoder Representations from Transformers (BERT) model consistently achieved the best performance in the end-to-end task. Future efforts in the end-to-end task should prioritize improving NER accuracy, especially for 'ADE' and 'Reason'. CONCLUSION: These findings hold significant implications for advancing the field of ADE extraction and pharmacovigilance, ultimately contributing to improved drug safety monitoring and healthcare outcomes.

Effect of autologous dendritic cell cytokine-induced killer on refractory metastatic colorectal cancer: a matched case-control comparative study.

Background: Patients with metastatic colorectal cancer (mCRC) who are refractory to two or more lines of systemic chemotherapy have limited therapeutic options. The aim of this study was to evaluate the effect of autologous dendritic cell cytokine-induced killer (DC-CIK) transfer on the survival of patients with mCRC who are refractory or intolerant to at least two lines of systemic chemotherapies. Methods: A matched case-control comparative study was conducted with patients who received DC-CIK immunotherapy in addition to standard chemotherapy (cases) and those with standard chemotherapy alone (controls). The primary objective was to compare the duration of oncologic survival, including overall survival (OS) and progression-free survival (PFS), between the two groups. Results: A total of 27 cases and 27 controls were included. The median OS in the DC-CIK case group was 18.73 ± 5.48 months, which was significantly longer than that in the control group (14.23 ± 1.90 months, p = 0.045). However, there was no significant difference in PFS between the two groups (p = 0.086). Subgroup analysis showed that in patients with liver or extra-regional lymph node metastasis, DC-CIK cases had longer OS than controls (17.0 vs. 11.87 months, p = 0.019; not match vs. 6.93 months, p = 0.002, respectively). In patients with Eastern Cooperative Oncology Group (ECOG) scale 0 or wild RAS/BRAF, DC-CIK cases showed a significant increase in OS duration compared to controls (28.03 vs. 14.53 months, p = 0.038; 18.73 vs. 11.87 months, p = 0.013, respectively). Conclusions: The addition of autologous DC-CIK to standard chemotherapy had a positive effect on OS of patients with refractory mCRC, especially those with liver or extra-regional lymph node metastasis, ECOG = 0, and wild RAS/BRAF status.

Expert Consensus on Ion Channel Drugs for Chronic Pain Treatment in China.

Ion channel drugs have been increasing used for chronic pain management with progress in the development of selective calcium channel modulators. Although ion channel drugs have been proven safe and effective in clinical practice, uncertainty remains regarding its use to treat chronic pain. To standardize the clinical practice of ion channel drug for the treatment of chronic pain, the National Health Commission Capacity Building and Continuing Education Center for Pain Diagnosis and Treatment Special Ability Training Project established an expert group to form an expert consensus on the use of ion channel drugs for the treatment of chronic pain after repeated discussions on existing medical evidence combined with the well clinical experience of experts. The consensus provided information on the mechanism of action of ion channel drugs and their recommendations, caution use, contraindications, and precautions for their use in special populations to support doctors in their clinical decision-making.

The RNA sequencing results revealed the expression of different genes and signaling pathways during chemotherapy resistance in peripheral T-cell lymphoma.

BACKGROUND: Peripheral T-cell lymphoma (PTCL) is a subtype of non-Hodgkin's lymphoma that occurs primarily at extranodal sites and is commonly treated using chemotherapy and radiotherapy. PTCL is more malignant than other lymphoid tumors, resulting in a poor prognosis.The 5-year recurrence rate remains high, and there is a lack of standard treatment for patients with relapse-resistant disease. However, the molecular mechanisms underlying the resistance of peripheral T-cell lymphoma cells to chemotherapeutic drugs, as well as identifying strategies to overcome drug resistance remains unclear. In this study, we aimed to identify pivotal genes and signaling pathways associated with chemotherapy resistance in PTCL. METHODS: In this study, a total of 5 healthy controls and 7 clinical patients were enrolled; 4 patients were classified as chemotherapy sensitive, and 3 patients were classified as chemotherapy resistant. Peripheral blood samples were collected from each participant, and total RNA was extracted from the white blood cells. RNA sequencing was conducted on the Illumina HiSeq platform to obtain comprehensive gene expression profiles. Subsequently, the expression patterns of the DEGs associated with the most enriched signaling pathways, with a special focus on cancer-related genes, were validated using quantitative real-time polymerase chain reaction (qRT-PCR) in peripheral TCL patients. RESULTS: RNA sequencing (RNA-seq) analysis revealed 4063 differentially expressed genes (DEGs) in peripheral T-cell lymphoma specimens from patients with chemotherapy resistance, of which 1128 were upregulated and 2935 were downregulated. Subsequent quantitative gene expression analysis confirmed a differential expression pattern in all the libraries, with 9 downregulated genes and 10 upregulated genes validated through quantitative real-time PCR in 6 clinical specimens from patients with chemotherapy resistance. KEGG pathway analysis revealed significant alterations in several pathways, with 6 downregulated pathways and 9 upregulated pathways enriched in the DEGs. Notably, the TNF signaling pathway, which is extensively regulated, was among the pathways that exhibited significant changes. These findings suggest that DEGs and the TNF signaling pathway may play crucial roles in chemotherapy resistance in peripheral T-cell lymphoma. CONCLUSION: Our study revealed that the expression of specific genes, including TNFRSF1B, TRADD2, and MAP3K7, may play an important role in chemotherapy resistance in peripheral T-cell lymphoma. Moreover, we identified the downregulation of the TNF signaling pathway, a crucial pathway involved in cell survival, death, and differentiation, as a potential contributor to the development of chemotherapy resistance in peripheral T-cell lymphoma. These findings provide valuable insights into the molecular mechanisms underlying chemotherapy resistance and highlight potential targets for overcoming treatment resistance in this challenging disease.