Host microbiome depletion attenuates biofluid metabolite responses following radiation exposure.

Development of novel biodosimetry assays and medical countermeasures is needed to obtain a level of radiation preparedness in the event of malicious or accidental mass exposures to ionizing radiation (IR). For biodosimetry, metabolic profiling with mass spectrometry (MS) platforms has identified several small molecules in easily accessible biofluids that are promising for dose reconstruction. As our microbiome has profound effects on biofluid metabolite composition, it is of interest how variation in the host microbiome may affect metabolomics based biodosimetry. Here, we 'knocked out' the microbiome of male and female C57BL/6 mice (Abx mice) using antibiotics and then irradiated (0, 3, or 8 Gy) them to determine the role of the host microbiome on biofluid radiation signatures (1 and 3 d urine, 3 d serum). Biofluid metabolite levels were compared to a sham and irradiated group of mice with a normal microbiome (Abx-con mice). To compare post-irradiation effects in urine, we calculated the Spearman's correlation coefficients of metabolite levels with radiation dose. For selected metabolites of interest, we performed more detailed analyses using linear mixed effect models to determine the effects of radiation dose, time, and microbiome depletion. Serum metabolite levels were compared using an ANOVA. Several metabolites were affected after antibiotic administration in the tryptophan and amino acid pathways, sterol hormone, xenobiotic and bile acid pathways (urine) and lipid metabolism (serum), with a post-irradiation attenuative effect observed for Abx mice. In urine, dose×time interactions were supported for a defined radiation metabolite panel (carnitine, hexosamine-valine-isoleucine [Hex-V-I], creatine, citric acid, and Nε,Nε,Nε-trimethyllysine [TML]) and dose for N1-acetylspermidine, which also provided excellent (AUROC ≥ 0.90) to good (AUROC ≥ 0.80) sensitivity and specificity according to the area under the receiver operator characteristic curve (AUROC) analysis. In serum, a panel consisting of carnitine, citric acid, lysophosphatidylcholine (LysoPC) (14:0), LysoPC (20:3), and LysoPC (22:5) also gave excellent to good sensitivity and specificity for identifying post-irradiated individuals at 3 d. Although the microbiome affected the basal levels and/or post-irradiation levels of these metabolites, their utility in dose reconstruction irrespective of microbiome status is encouraging for the use of metabolomics as a novel biodosimetry assay.

Real-Time Gated Proton Therapy: Commissioning and Clinical Workflow for the Hitachi System.

Purpose: To describe the commissioning of real-time gated proton therapy (RGPT) and the establishment of an appropriate clinical workflow for the treatment of patients. Materials and Methods: Hitachi PROBEAT provides pencil beam scanning proton therapy with an advanced onboard imaging system including real-time fluoroscopy. RGPT utilizes a matching score to provide instantaneous system performance feedback and quality control for patient safety. The CIRS Dynamic System combined with a Thorax Phantom or plastic water was utilized to mimic target motion. The OCTAVIUS was utilized to measure end-to-end dosimetric accuracy for a moving target across a range of simulated situations. Using this dosimetric data, the gating threshold was carefully evaluated and selected based on the intended treatment sites and planning techniques. An image-guidance workflow was developed and applied to patient treatment. Results: Dosimetric data demonstrated that proton plan delivery uncertainty could be within 2 mm for a moving target. The dose delivery to a moving target could pass 3%/3 mm gamma analysis following the commissioning process and application of the clinical workflow detailed in this manuscript. A clinical workflow was established and successfully applied to patient treatment utilizing RGPT. Prostate cancer patients with implanted platinum fiducial markers were treated with RGPT. Their target motion and gating signal data were available for intrafraction motion analysis. Conclusion: Real-time gated proton therapy with the Hitachi System has been fully investigated and commissioned for clinical application. RGPT can provide advanced and reliable real-time image guidance to enhance patient safety and inform important treatment planning parameters, such as planning target volume margins and uncertainty parameters for robust plan optimization. RGPT improved the treatment of patients with prostate cancer in situations where intrafraction motion is more than defined tolerance.

The prognostic impact of tumor location in non-muscle-invasive bladder cancer patients undergoing transurethral resection: insights from a cohort study utilizing chinese multicenter and SEER registries.

OBJECTIVE: Most bladder cancers are non-muscle invasive bladder cancer (NMIBC), and transurethral resection of bladder tumors (TURBT) is the standard treatment. However, postoperative recurrence remains a significant challenge, and the influence of bladder tumor location on prognosis is still unclear. This study aims to investigate how tumor location affects the prognosis of NMIBC patients undergoing TURBT and to identify the optimal surgical approach. METHODS: A multicenter study was conducted, which included Chinese NMIBC data from 15 hospitals (1996-2019) and data from 17 registries of the Surveillance, Epidemiology, and End Results database (SEER) (2000-2020). Patients initially diagnosed with NMIBC and undergoing TURBT or partial cystectomy were analyzed, with cases lost to follow-up or with missing data excluded. The study investigated the overall survival (OS), disease-specific survival (DSS), and recurrence-free survival (RFS) among patients with different tumor locations. Kaplan-Meier, Cox regression, and propensity score matching methods were employed to explore the association between tumor location and prognosis. Stratified populations were analyzed to minimize bias. RESULTS: This study included 118,477 NMIBC patients and highlighted tumor location as a crucial factor impacting post-TURBT prognosis. Both anterior wall and dome tumors independently predicted adverse outcomes in two cohorts. For anterior wall tumors, the Chinese cohort showed hazard ratios (HR) for OS of 4.35 (P < 0.0001); RFS of 2.21 (P < 0.0001); SEER cohort OS HR of 1.10 (P = 0.0001); DSS HR of 1.13 (P = 0.0183). Dome tumors displayed similar trends (Chinese NMIBC cohort OS HR of 7.91 (P < 0.0001); RFS HR of 2.12 (P < 0.0001); SEER OS HR of 1.05 (P = 0.0087); DSS HR of 1.14 (P = 0.0006)). Partial cystectomy significantly improved the survival of dome tumor patients compared to standard TURBT treatment (P < 0.01). CONCLUSION: This study reveals the significant impact of tumor location in NMIBC patients on the outcomes of TURBT treatment, with tumors in the anterior wall and bladder dome showing poor post-TURBT prognosis. Compared to TURBT treatment, partial cystectomy improves the prognosis for bladder dome tumors. This study provides guidance for personalized treatment and prognosis management for NMIBC patients.

MRI radiomics nomogram integrating postoperative adjuvant treatments in recurrence risk prediction for patients with early-stage cervical cancer.

BACKGROUND AND PURPOSE: Adjuvant treatments are valuable to decrease the recurrence rate and improve survival for early-stage cervical cancer patients (ESCC), Therefore, recurrence risk evaluation is critical for the choice of postoperative treatment. A magnetic resonance imaging (MRI) based radiomics nomogram integrating postoperative adjuvant treatments was constructed and validated externally to improve the recurrence risk prediction for ESCC. MATERIAL AND METHODS: 212 ESCC patients underwent surgery and adjuvant treatments from three centers were enrolled and divided into the training, internal validation, and external validation cohorts. Their clinical data, pretreatment T2-weighted images (T2WI) were retrieved and analyzed. Radiomics models were constructed using machine learning methods with features extracted and screen from sagittal and axial T2WI. A nomogram for recurrence prediction was build and evaluated using multivariable logistic regression analysis integrating radiomic signature and adjuvant treatments. RESULTS: A total of 8 radiomic features were screened out of 1020 extracted features. The extreme gradient boosting (XGboost) model based on MRI radiomic features performed best in recurrence prediction with an area under curve (AUC) of 0.833, 0.822 in the internal and external validation cohorts, respectively. The nomogram integrating radiomic signature and clinical factors achieved an AUC of 0.806, 0.718 in the internal and external validation cohorts, respectively, for recurrence risk prediction for ESCC. CONCLUSION: In this study, the nomogram integrating T2WI radiomic signature and clinical factors is valuable to predict the recurrence risk, thereby allowing timely planning for effective treatments for ESCC with high risk of recurrence.

A finite element model of human hindfoot and its application in supramalleolar osteotomy.

BACKGROUND: The majority of the ankle osteoarthritis cases are posttraumatic and affect younger patients with a longer projected life span. Hence, joint-preserving surgery, such as supramalleolar osteotomy becomes popular among young patients, especially those with asymmetric arthritis due to alignment deformities. However, there is a lack of biomechanical studies on postoperative evaluation of stress at ankle joints. We aimed to construct a verifiable finite element model of the human hindfoot, and to explore the effect of different osteotomy parameters on the treatment of varus ankle arthritis. METHODS: The bones of the hindfoot are reconstructed using normal CT tomography data from healthy volunteers, while the cartilages and ligaments are determined from the literature. The finite element calculation results are compared with the weight-bearing CT (WBCT) data to validate the model. By setting different model parameters, such as the osteotomy height (L) and the osteotomy distraction distance (h), the effects of different surgical parameters on the contact stress of the ankle joint surface are compared. FINDINGS: The alignment and the deformation of hindfoot bones as determined by the finite element analysis aligns closely with the data obtained from WBCT. The maximum contact stress of the ankle joint surface calculated by this model increases with the increase of the varus angle. The maximum contact stresses as a function of the L and h of the ankle joint surface are determined. INTERPRETATION: The relationship between surgical parameters and stress at the ankle joint in our study could further help guiding the planning of the supramalleolar osteotomy according to the varus/valgus alignment of the patients.

Clinical, pathological, and molecular features of central nervous system tumors with BCOR internal tandem duplication.

Central nervous system tumor with BCOR internal tandem duplication (CNS tumor with BCOR-ITD) constitutes a molecularly distinct entity, characterized by internal tandem duplication within exon 15 of the BCOR transcriptional co-repressor gene (BCOR-ITD). The current study aimed to elucidate the clinical, pathological, and molecular attributes of CNS tumors with BCOR-ITD and explore their putative cellular origin. This study cohort comprised four pediatric cases, aged 23 months to 13 years at initial presentation. Magnetic resonance imaging revealed large, well-circumscribed intra-CNS masses localized heterogeneously throughout the CNS. Microscopically, tumors were composed of spindle to ovoid cells, exhibiting perivascular pseudorosettes and palisading necrosis, but lacking microvascular proliferation. Immunohistochemical staining showed diffuse tumor cell expression of BCOR, CD56, CD99, vimentin, and the stem cell markers PAX6, SOX2, CD133 and Nestin, alongside focal positivity for Olig-2, S100, SOX10, Syn and NeuN. Molecularly, all cases harbored BCOR-ITDs ranging from 87 to 119 base pairs in length, including one case with two distinct ITDs. Notably, the ITDs were interrupted by unique 1-3 bp insertions in all cases. In summary, CNS tumors with BCOR-ITD exhibit characteristic clinical, pathological, and molecular features detectable through BCOR immunohistochemistry and confirmatory molecular analyses. Their expression of stem cell markers raises the possibility of an origin from neuroepithelial stem cells rather than representing true embryonal neoplasms.

Scalable telomere-to-telomere assembly for diploid and polyploid genomes with double graph.

Despite advances in long-read sequencing technologies, constructing a near telomere-to-telomere assembly is still computationally demanding. Here we present hifiasm (UL), an efficient de novo assembly algorithm combining multiple sequencing technologies to scale up population-wide near telomere-to-telomere assemblies. Applied to 22 human and two plant genomes, our algorithm produces better diploid assemblies at a cost of an order of magnitude lower than existing methods, and it also works with polyploid genomes.

Enhancing multiple myeloma staging: a novel cell death risk model approach.

The prognostication of survival trajectories in multiple myeloma (MM) patients presents a substantial clinical challenge. Leveraging transcriptomic and clinical profiles from an expansive cohort of 2,088 MM patients, sourced from the Gene Expression Omnibus and The Cancer Genome Atlas repositories, we applied a sophisticated nested lasso regression technique to construct a prognostic model predicated on 28 gene pairings intrinsic to cell death pathways, thereby deriving a quantifiable risk stratification metric. Employing a threshold of 0.15, we dichotomized the MM samples into discrete high-risk and low-risk categories. Notably, the delineated high-risk cohort exhibited a statistically significant diminution in survival duration, a finding which consistently replicated across both training and external validation datasets. The prognostic acumen of our cell death signature was further corroborated by TIME ROC analyses, with the model demonstrating robust performance, evidenced by AUC metrics consistently surpassing the 0.6 benchmark across the evaluated arrays. Further analytical rigor was applied through multivariate COX regression analyses, which ratified the cell death risk model as an independent prognostic determinant. In an innovative stratagem, we amalgamated this risk stratification with the established International Staging System (ISS), culminating in the genesis of a novel, refined ISS categorization. This tripartite classification system was subjected to comparative analysis against extant prognostic models, whereupon it manifested superior predictive precision, as reflected by an elevated C-index. In summation, our endeavors have yielded a clinically viable gene pairing model predicated on cellular mortality, which, when synthesized with the ISS, engenders an augmented prognostic tool that exhibits pronounced predictive prowess in the context of multiple myeloma.

Human telomere length is chromosome end-specific and conserved across individuals.

Short telomeres cause age-related disease, and long telomeres contribute to cancer; however, the mechanisms regulating telomere length are unclear. We developed a nanopore-based method, which we call Telomere Profiling, to determine telomere length at nearly single-nucleotide resolution. Mapping telomere reads to chromosome ends showed chromosome end-specific length distributions that could differ by more than six kilobases. Examination of telomere lengths in 147 individuals revealed that certain chromosome ends were consistently longer or shorter. The same rank order was found in newborn cord blood, suggesting that telomere length is determined at birth and that chromosome end-specific telomere length differences are maintained as telomeres shorten with age. Telomere Profiling makes precision investigation of telomere length widely accessible for laboratory, clinical, and drug discovery efforts and will allow deeper insights into telomere biology.

[Tibiotalocalcaneal arthrodesis for end-stage ankle and hindfoot arthropathy: Short- and mid-term clinical outcomes].

OBJECTIVE: To analyze the clinical data of patients with end-stage ankle and hindfoot arthropathy who underwent tibiotalocalcaneal (TTC) arthrodesis by the same surgeon, explore the short- and mid-term clinical results, complications and functional improvement, and discuss the clinical prognosis and precautions of TTC arthrodesis. METHODS: Retrospective analysis was made on the clinical data of 40 patients who underwent TTC arthrodesis by the same surgeon from March 2011 to December 2020. In this study, 23 males and 17 females were included, with an average age of (49.1±16.0) years. All the patients underwent unilateral surgery. The clinical characteristics, imaging manifestations, main diagnosis and specific surgical techniques of the patients were recorded. The clinical outcomes were evaluated by comparison of the American Orthopaedic Foot and Ankle Society (AOFAS) ankle-hindfoot score and visual analogue scale (VAS) between pre-operation and at the last follow-up. The fusion healing time, symptom improvement (significant improvement, certain improvement, no improvement or deterioration) and postoperative complications were also recorded. RESULTS: The median follow-up time was 38.0 (26.3, 58.8) months. The preoperative VAS score was 6.0 (4.0, 7.0), and the AOFAS score was 33.0 (25.3, 47.3). At the last follow-up, the median VAS score was 0 (0, 3.0), and the AOFAS score was 80.0 (59.0, 84.0). All the significantly improved compared with their preoperative corresponding values (P < 0.05). There was no wound necrosis or infection in the patients. One patient suffered from subtalar joint nonunion, which was syphilitic Charcot arthropathy. The median bony healing time of other patients was 15.0 (12.0, 20.0) weeks. Among the included patients, there were 25 cases with significant improvement in symptom compared with that preoperative, 8 cases with certain improvement, 4 cases with no improvement, and 3 cases with worse symptoms than that before operation. CONCLUSION: TTC arthrodesis is a reliable method for the treatment of the end-stage ankle and hindfoot arthropathy. The function of most patients was improved postoperatively, with little impact on daily life. The causes of poor prognosis included toe stiffness, stress concentration in adjacent knee joints, nonunion and pain of unknown causes.

A novel tumor mutation-related long non-coding RNA signature for predicting overall survival and immunotherapy response in lung adenocarcinoma.

Background: Immunotherapy has changed the treatment landscape for lung cancer. This study aims to construct a tumor mutation-related model that combines long non-coding RNA (lncRNA) expression levels and tumor mutation levels in tumor genomes to detect the possibilities of the lncRNA signature as an indicator for predicting the prognosis and response to immunotherapy in lung adenocarcinoma (LUAD). Methods: We downloaded the tumor mutation profiles and RNA-seq expression database of LUAD from The Cancer Genome Atlas (TCGA). Differentially expressed lncRNAs were extracted based on the cumulative number of mutations. Cox regression analyses were used to identify the prognostic lncRNA signature, and the prognostic value of the five selected lncRNAs was validated by using survival analysis and the receiver operating characteristic (ROC) curve. We used qPCR to validate the expression of five selected lncRNAs between human lung epithelial and human lung adenocarcinoma cell lines. The ImmuCellAI, immunophenoscore (IPS) scores and Tumor Immune Dysfunction and Exclusion (TIDE) analyses were used to predict the response to immunotherapy for this mutation related lncRNA signature. Results: A total of 162 lncRNAs were detected among the differentially expressed lncRNAs between the Tumor mutational burden (TMB)-high group and the TMB-low group. Then, five lncRNAs (PLAC4, LINC01116, LINC02163, MIR223HG, FAM83A-AS1) were identified as tumor mutation-related candidates for constructing the prognostic prediction model. Kaplan‒Meier curves showed that the overall survival of the low-risk group was significantly better than that of the high-risk group, and the results of the GSE50081 set were consistent. The expression levels of PD1, PD-L1 and CTLA4 in the low-risk group were higher than those in the high-risk group. The IPS scores and TIDE scores of patients in the low-risk group were significantly higher than those in the high-risk group. Conclusion: Our findings demonstrated that the five lncRNAs (PLAC4, LINC01116, LINC02163, MIR223HG, FAM83A-AS1) were identified as candidates for constructing the tumor mutation-related model which may serve as an indicator of tumor mutation levels and have important implications for predicting the response to immunotherapy in LUAD.

Blockade of the deubiquitinating enzyme USP48 degrades oncogenic HMGA2 and inhibits colorectal cancer invasion and metastasis.

HMGA2, a pivotal transcription factor, functions as a versatile regulator implicated in the progression of diverse aggressive malignancies. In this study, mass spectrometry was employed to identify ubiquitin-specific proteases that potentially interact with HMGA2, and USP48 was identified as a deubiquitinating enzyme of HMGA2. The enforced expression of USP48 significantly increased HMGA2 protein levels by inhibiting its degradation, while the deprivation of USP48 promoted HMGA2 degradation, thereby suppressing tumor invasion and metastasis. We discovered that USP48 undergoes SUMOylation at lysine 258, which enhances its binding affinity to HMGA2. Through subsequent phenotypic screening of small molecules, we identified DUB-IN-2 as a remarkably potent pharmacological inhibitor of USP48. Interestingly, the small-molecule inhibitor targeting USP48 induces destabilization of HMGA2. Clinically, upregulation of USP48 or HMGA2 in cancerous tissues is indicative of poor prognosis for patients with colorectal cancer (CRC). Collectively, our study not only elucidates the regulatory mechanism of DUBs involved in HMGA2 stability and validates USP48 as a potential therapeutic target for CRC, but also identifies DUB-IN-2 as a potent inhibitor of USP48 and a promising candidate for CRC treatment.

In vivo EPID-based daily treatment error identification for volumetric-modulated arc therapy in head and neck cancers with a hierarchical convolutional neural network: a feasibility study.

We proposed a deep learning approach to classify various error types in daily VMAT treatment of head and neck cancer patients based on EPID dosimetry, which could provide additional information to support clinical decisions for adaptive planning. 146 arcs from 42 head and neck patients were analyzed. Anatomical changes and setup errors were simulated in 17,820 EPID images of 99 arcs obtained from 30 patients using in-house software for model training, validation, and testing. Subsequently, 141 clinical EPID images from 47 arcs belonging to the remaining 12 patients were utilized for clinical testing. The hierarchical convolutional neural network (HCNN) model was trained to classify error types and magnitudes using EPID dose difference maps. Gamma analysis with 3%/2 mm (dose difference/distance to agreement) criteria was also performed. The F1 score, a combination of precision and recall, was utilized to evaluate the performance of the HCNN model and gamma analysis. The adaptive fractioned doses were calculated to verify the HCNN classification results. For error type identification, the overall F1 score of the HCNN model was 0.99 and 0.91 for primary type and subtype identification, respectively. For error magnitude identification, the overall F1 score in the simulation dataset was 0.96 and 0.70 for the HCNN model and gamma analysis, respectively; while the overall F1 score in the clinical dataset was 0.79 and 0.20 for the HCNN model and gamma analysis, respectively. The HCNN model-based EPID dosimetry can identify changes in patient transmission doses and distinguish the treatment error category, which could potentially provide information for head and neck cancer treatment adaption.

Association Between Preoperative Sleep Disturbance and Postoperative Delirium in Elderly: A Retrospective Cohort Study.

Purpose: Postoperative sleep disturbance, characterized by diminished postoperative sleep quality, is a risk factor for postoperative delirium (POD); however, the association between pre-existing sleep disturbance and POD remains unclear. This study aimed to evaluate the association between preoperative sleep disturbance and POD in elderly patients after non-cardiac surgery. Patients and methods: This retrospective cohort study was conducted at a single center and enrolled 489 elderly patients who underwent surgery between May 1, 2020, and March 31, 2021. Patients were divided into the sleep disorder (SD) and non-sleep disorder (NSD) groups according to the occurrence of one or more symptoms of insomnia within one month or sleep- Numerical Rating Scale (NRS)≥6 before surgery. The primary outcome was the incidence of POD. Propensity score matching analysis was performed between the two groups. Multiple logistic regression analysis was performed to identify the risk factors for POD. Results: In both the unmatched cohort (16.0% vs 6.7%, P=0.003) and the matched cohort (17.0% vs 6.2%, P=0.023), the incidence of POD was higher in the SD group than in the NSD group. In addition, the postoperative sleep quality and the VAS score at postoperative 24 h were significantly lower in the SD group than in the NSD group. Multivariate logistic regression analysis indicated that age (Odds Ratio, 1.13 [95% CI: 1.04-1.23], P=0.003) and preoperative sleep disturbance (Odds Ratio, 3.03 [95% CI: 1.09-9.52], P=0.034) were independent risk factors for the development of POD. Conclusion: The incidence of POD was higher in patients with pre-existing sleep disturbance than those without it. Whether improving sleep quality for preoperative sleep disturbance may help prevent POD remains to be determined.

Clinical VMAT machine parameter optimization for localized prostate cancer using deep reinforcement learning.

BACKGROUND: Volumetric modulated arc therapy (VMAT) machine parameter optimization (MPO) remains computationally expensive and sensitive to input dose objectives creating challenges for manual and automatic planning. Reinforcement learning (RL) involves machine learning through extensive trial-and-error, demonstrating performance exceeding humans, and existing algorithms in several domains. PURPOSE: To develop and evaluate an RL approach for VMAT MPO for localized prostate cancer to rapidly and automatically generate deliverable VMAT plans for a clinical linear accelerator (linac) and compare resultant dosimetry to clinical plans. METHODS: We extended our previous RL approach to enable VMAT MPO of a 3D beam model for a clinical linac through a policy network. It accepts an input state describing the current control point and predicts continuous machine parameters for the next control point, which are used to update the input state, repeating until plan termination. RL training was conducted to minimize a dose-based cost function for prescription of 60 Gy in 20 fractions using CT scans and contours from 136 retrospective localized prostate cancer patients, 20 of which had existing plans used to initialize training. Data augmentation was employed to mitigate over-fitting, and parameter exploration was achieved using Gaussian perturbations. Following training, RL VMAT was applied to an independent cohort of 15 patients, and the resultant dosimetry was compared to clinical plans. We also combined the RL approach with our clinical treatment planning system (TPS) to automate final plan refinement, and creating the potential for manual review and edits as required for clinical use. RESULTS: RL training was conducted for 5000 iterations, producing 40 000 plans during exploration. Mean ± SD execution time to produce deliverable VMAT plans in the test cohort was 3.3 ± 0.5 s which were automatically refined in the TPS taking an additional 77.4 ± 5.8 s. When normalized to provide equivalent target coverage, the RL+TPS plans provided a similar mean ± SD overall maximum dose of 63.2 ± 0.6 Gy and a lower mean rectum dose of 17.4 ± 7.4 compared to 63.9 ± 1.5 Gy (p = 0.061) and 21.0 ± 6.0 (p = 0.024) for the clinical plans. CONCLUSIONS: An approach for VMAT MPO using RL for a clinical linac model was developed and applied to automatically generate deliverable plans for localized prostate cancer patients, and when combined with the clinical TPS shows potential to rapidly generate high-quality plans. The RL VMAT approach shows promise to discover advanced linac control policies through trial-and-error, and algorithm limitations and future directions are identified and discussed.

Prognostic and Immunotherapeutic Predictive Value of CAD Gene in Hepatocellular Carcinoma: Integrated Bioinformatics and Experimental Analysis.

Hepatocellular carcinoma (HCC) is a common type of cancer that ranks first in cancer-associated death worldwide. Carbamoyl-phosphate synthetase 2, aspartate transcarbamylase, and dihydroorotase (CAD) are the key components of the pyrimidine pathway, which promotes cancer development. However, the function of CAD in HCC needs to be clarified. In this study, the clinical and transcriptome data of 424 TCGA-derived HCC cases were analyzed. The results demonstrated that high CAD expression was associated with poor prognosis in HCC patients. The effect of CAD on HCC was then investigated comprehensively using GO annotation analysis, KEGG enrichment analysis, Gene Set Enrichment Analysis (GSEA), and CIBERSORT algorithm. The results showed that CAD expression was correlated with immune checkpoint inhibitors and immune cell infiltration. In addition, low CAD levels in HCC patients predicted increased sensitivity to anti-CTLA4 and PD1, while HCC patients with high CAD expression exhibited high sensitivity to chemotherapeutic and molecular-targeted agents, including gemcitabine, paclitaxel, and sorafenib. Finally, the results from clinical sample suggested that CAD expression increased remarkably in HCC compared with non-cancerous tissues. Loss of function experiments demonstrated that CAD knockdown could significantly inhibit HCC cell growth and migration both in vitro and in vivo. Collectively, the results indicated that CAD is a potential oncogene during HCC metastasis and progression. Therefore, CAD is recommended as a candidate marker and target for HCC prediction and treatment.

Serplulimab monotherapy in extensive-stage small-cell lung cancer with brain metastasis: a case report.

Small-cell lung cancer (SCLC) is an aggressive form of lung cancer with limited treatment options, especially for extensive-stage (ES) patients. We present a case of a 70-year-old male with ES-SCLC and asymptomatic brain metastasis who opted for immune monotherapy with serplulimab (an anti-PD-1 antibody). After four cycles, the patient achieved a confirmed partial response and a progression-free survival of over 1 year. Moreover, we observed a consistent decline in tumor biomarkers, and brain MRI indicated reduced metastatic activity. Remarkably, the patient tolerated the treatment well, with only mild diarrhea. This case highlights serplulimab's potential as a first-line treatment in select ES-SCLC patients, emphasizing the importance of further research on immunotherapy predictive biomarkers.

Small-cell lung cancer (SCLC) is a severe type of lung cancer that often does not have many treatment options, especially in its advanced stages. This article discusses the experience of a 70-year-old man with advanced SCLC who also had cancer spread to his brain but did not show symptoms. He chose to try a new kind of cancer treatment called serplulimab, which works by helping the immune system fight the cancer. After receiving this treatment four-times, his cancer showed significant improvement, and he did not experience further cancer growth for more than 1 year. Tests also revealed that his cancer markers decreased, and the cancer in his brain became less active. Notably, he tolerated this agent with only mild diarrhea occurring. This case is important because it suggests that serplulimab could be an effective first treatment for some patients with advanced SCLC, and it highlights the need for more research to find ways to predict who will benefit from this type of therapy.

Suppression of A-to-I RNA-editing enzyme ADAR1 sensitizes hepatocellular carcinoma cells to oxidative stress through regulating Keap1/Nrf2 pathway.

BACKGROUND: A-to-I RNA editing is an abundant post-transcriptional modification event in hepatocellular carcinoma (HCC). Evidence suggests that adenosine deaminases acting on RNA 1 (ADAR1) correlates to oxidative stress that is a crucial factor of HCC pathogenesis. The present study investigated the effect of ADAR1 on survival and oxidative stress of HCC, and underlying mechanisms. METHODS: ADAR1 expression was measured in fifty HCC and normal tissues via real-time quantitative PCR, and immunohistochemistry. For stable knockdown or overexpression of ADAR1, adeno-associated virus vectors carrying sh-ADAR1 or ADAR1 overexpression were transfected into HepG2 and SMMC-7721 cells. Transfected cells were exposed to oxidative stress agonist tBHP or sorafenib Bay 43-9006. Cell proliferation, apoptosis, and oxidative stress were measured, and tumor xenograft experiment was implemented. RESULTS: ADAR1 was up-regulated in HCC and correlated to unfavorable clinical outcomes. ADAR1 deficiency attenuated proliferation of HCC cells and tumor growth and enhanced apoptosis. Moreover, its loss facilitated intracellular ROS accumulation, and elevated Keap1 and lowered Nrf2 expression. Intracellular GSH content and SOD activity were decreased and MDA content was increased in the absence of ADAR1. The opposite results were observed when ADAR1 was overexpressed. The effects of tBHP and Bay 43-9006 on survival, apoptosis, intracellular ROS accumulation, and Keap1/Nrf2 pathway were further exacerbated by simultaneous inhibition of ADAR1. CONCLUSIONS: The current study unveils that ADAR1 is required for survival and oxidative stress of HCC cells, and targeting ADAR1 may sensitize HCC cells to oxidative stress via modulating Keap1/Nrf2 pathway.

Advancing the application of the analytical renal pathology system in allograft IgA nephropathy patients.

BACKGROUND: The analytical renal pathology system (ARPS) based on convolutional neural networks has been used successfully in native IgA nephropathy (IgAN) patients. Considering the similarity of pathologic features, we aim to evaluate the performance of the ARPS in allograft IgAN patients and broaden its implementation. METHODS: Biopsy-proven allograft IgAN patients from two different centers were enrolled for internal and external validation. We implemented the ARPS to identify glomerular lesions and intrinsic glomerular cells, and then evaluated its performance. Consistency between the ARPS and pathologists was assessed using intraclass correlation coefficients. The association of digital pathological features with clinical and pathological data was measured. Kaplan-Meier survival curve and cox proportional hazards model were applied to investigate prognosis prediction. RESULTS: A total of 56 biopsy-proven allograft IgAN patients from the internal center and 17 biopsy-proven allograft IgAN patients from the external center were enrolled in this study. The ARPS was successfully applied to identify the glomerular lesions (F1-score, 0.696-0.959) and quantify intrinsic glomerular cells (F1-score, 0.888-0.968) in allograft IgAN patients rapidly and precisely. Furthermore, the mesangial hypercellularity score was positively correlated with all mesangial metrics provided by ARPS [Spearman's correlation coefficient (r), 0.439-0.472, and all p values < 0.001]. Besides, a higher allograft survival was noticed among patients in the high-level groups of the maximum and ratio of endothelial cells, as well as the maximum and density of podocytes. CONCLUSION: We propose that the ARPS could be implemented in future clinical practice with outstanding capability.

DLX1 acts as a novel prognostic biomarker involved in immune cell infiltration and tumor progression in lung adenocarcinoma.

Background: The biological function of distal-less homeobox 1 (DLX1) in lung adenocarcinoma (LUAD) remains unclear, despite a growing body of evidence that DLX1 is involved in the initiation and progression of various tumors. Methods: This study explored and confirmed the prognostic and immunologic roles of DLX1 in LUAD via bioinformatic analysis and cellular functional validation. MethSurv was used to analyze the DNA methylation levels of DLX1 and the prognostic value of CpG islands. DLX1 mutation rates and prognoses between patients with and without the mutated DLX1 gene were analyzed by cBioPortal. Finally, cellular functional assays were used to investigate the effect of DLX1 on LUAD cells. Results: Our results showed that DLX1 mRNA expression was significantly upregulated in LUAD. High DLX1 expression or promoter methylation was associated with worse prognosis, which confirmed DLX1 as an independent prognostic factor in LUAD. The level of multiple immune cell infiltration was significantly associated with DLX1 expression. Genes in the high DLX1 expression group were mainly enriched in cell cycle checkpoint, DNA replication, DNA repair, Fceri-mediated MAPK activation, TP53 activity regulation, and MET activation of PTK2-regulated signaling pathways. Cellular functional assays showed that the knockdown of DLX1 inhibited the proliferation, migration, and invasion of LUAD cells. Conclusion: Our study identified DLX1 as a potential diagnostic and prognostic biomarker, and a promising therapeutic target in LUAD.