A Single-Arm Multi-Center Phase II Clinical Trial of Cadonilimab (anti-PD-1/CTLA-4) in Combination with or without Conventional Second-Line Treatment for Patients with Extensive Stage Small Cell Lung Cancer.

BACKGROUND: Cadonilimab (AK104) is a bispecific IgG-single-chain Fv fragment (ScFv) antibody that binds to PD-1 and CTLA-4. Cadonilimab has shown encouraging anti-tumour activity and a favourable safety profile in several tumour types. In second-line treatment, there is no defined standard of care for patients with extensive-stage small-cell lung cancer (ES-SCLC). Cadonilimab is expected to show substantial clinical efficacy. OBJECTIVE: To assess the antitumor activity and safety of cadonilimab monotherapy or combination with conventional therapy in ES-SCLC patients who failed first-line treatment. METHODS: In this multicenter, open-label, phase II study, ES-SCLC patients who had failed first-line treatment, also aged 18 years to 70 years with histologically or cytologically confirmed ES-SCLC, and an Eastern Cooperative Oncology Group performance status (ECOG-PS) of 0-2 were eligible. Patients will receive cadonilimab 10 mg/kg every three weeks (Q3 W) among 24 months until progressive disease (PD) or adverse events (AE) discovery. The primary endpoint is progression-free survival (PFS). TRIAL REGISTRATION: NCT05901584.

Fibroblast Growth Factor 23 is a Potential Prognostic Biomarker in Uterine Sarcoma.

BACKGROUND: Uterine sarcoma (US) is a highly malignant cancer with poor prognosis and high mortality in women. In this study, we evaluated the expression of human fibroblast growth factor 23 (FGF23) in different US subtypes and the relationship between survival and clinicopathological characteristics. METHODS: We conducted a comparative analysis of FGF23 gene expression in different pathological types of US. Utilizing a cohort from The Cancer Genome Atlas of 57 patients, a 50-patient microarray dataset (GSE119043) from the Gene Expression Omnibus and a Suining cohort of 44 patients, we analyzed gene expression profiles and corresponding clinicopathological information. Immunohistochemistry was used to examine the expression level of FGF23 in four US subtypes. Survival analysis was used to assess the relationship between FGF23 expression and prognosis in US patients. RESULTS: Compared with uterine normal smooth muscle and uterine leiomyoma, FGF23 expression was significantly upregulated in US and was differentially expressed in four US subtypes. Uterine carcinosarcoma exhibited the highest expression of FGF23 among the subtypes. Survival analysis revealed no correlation between FGF23 expression and either overall survival or progression-free survival in US (P > 0.05). Similar results were obtained from the validation cohorts. Univariate and multivariate analyses showed no significant correlation between FGF23 expression and the US prognosis. Tumor stage, CA125, and tumor recurrence were independent prognostic factors for survival of US patients. CONCLUSION: FGF23 was highly expressed in US and was promising as a novel potential biomarker for the diagnosis and prognosis of US.

Machine Learning-assisted immunophenotyping of peripheral blood identifies innate immune cells as best predictor of response to induction chemo-immunotherapy in head and neck squamous cell carcinoma - knowledge obtained from the CheckRad-CD8 trial.

PURPOSE: Individual prediction of treatment response is crucial for personalized treatment in multimodal approaches against head-and-neck squamous cell carcinoma (HNSCC). So far, no reliable predictive parameters for treatment schemes containing immunotherapy have been identified. This study aims to predict treatment response to induction chemo-immunotherapy based on the peripheral blood immune status in patients with locally advanced HNSCC. METHODS: The peripheral blood immune phenotype was assessed in whole blood samples in patients treated in the phase II CheckRad-CD8 trial as part of the pre-planned translational research program. Blood samples were analyzed by multicolor flow cytometry before (T1) and after (T2) induction chemo-immunotherapy with cisplatin/docetaxel/durvalumab/tremelimumab. Machine Learning techniques were used to predict pathological complete response (pCR) after induction therapy. RESULTS: The tested classifier methods (LDA, SVM, LR, RF, DT, and XGBoost) allowed a distinct prediction of pCR. Highest accuracy was achieved with a low number of features represented as principal components. Immune parameters obtained from the absolute difference (lT2-T1l) allowed the best prediction of pCR. In general, less than 30 parameters and at most 10 principal components were needed for highly accurate predictions. Across several datasets, cells of the innate immune system such as polymorphonuclear cells, monocytes, and plasmacytoid dendritic cells are most prominent. CONCLUSIONS: Our analyses imply that alterations of the innate immune cell distribution in the peripheral blood following induction chemo-immuno-therapy is highly predictive for pCR in HNSCC.

TCCIA: a comprehensive resource for exploring CircRNA in cancer immunotherapy.

BACKGROUND: Immunotherapies targeting immune checkpoints have gained increasing attention in cancer treatment, emphasizing the need for predictive biomarkers. Circular RNAs (circRNAs) have emerged as critical regulators of tumor immunity, particularly in the PD-1/PD-L1 pathway, and have shown potential in predicting immunotherapy efficacy. Yet, the detailed roles of circRNAs in cancer immunotherapy are not fully understood. While existing databases focus on either circRNA profiles or immunotherapy cohorts, there is currently no platform that enables the exploration of the intricate interplay between circRNAs and anti-tumor immunotherapy. A comprehensive resource combining circRNA profiles, immunotherapy responses, and clinical outcomes is essential to advance our understanding of circRNA-mediated tumor-immune interactions and to develop effective biomarkers. METHODS: To address these gaps, we constructed The Cancer CircRNA Immunome Atlas (TCCIA), the first database that combines circRNA profiles, immunotherapy response data, and clinical outcomes across multicancer types. The construction of TCCIA involved applying standardized preprocessing to the raw sequencing FASTQ files, characterizing circRNA profiles using an ensemble approach based on four established circRNA detection tools, analyzing tumor immunophenotypes, and compiling immunotherapy response data from diverse cohorts treated with immune checkpoint blockades (ICBs). RESULTS: TCCIA encompasses over 4,000 clinical samples obtained from 25 cohorts treated with ICBs along with other treatment modalities. The database provides researchers and clinicians with a cloud-based platform that enables interactive exploration of circRNA data in the context of ICB. The platform offers a range of analytical tools, including browse of identified circRNAs, visualization of circRNA abundance and correlation, association analysis between circRNAs and clinical variables, assessment of the tumor immune microenvironment, exploration of tumor molecular signatures, evaluation of treatment response or prognosis, and identification of altered circRNAs in immunotherapy-sensitive and resistant tumors. To illustrate the utility of TCCIA, we showcase two examples, including circTMTC3 and circMGA, by employing analysis of large-scale melanoma and bladder cancer cohorts, which unveil distinct impacts and clinical implications of different circRNA expression in cancer immunotherapy. CONCLUSIONS: TCCIA represents a significant advancement over existing resources, providing a comprehensive platform to investigate the role of circRNAs in immuno-oncology.

[Congenital pulmonary alveolar proteinosis in a neonate]. / æ–°ç”Ÿå„¿å ˆå¤©æ€§è‚ºæ³¡è›‹ç™½æ²‰ç§¯ç—‡1例.

The male patient was referred to the hospital at 44 days old due to dyspnea after birth and inability to wean off oxygen. His brother died three days after birth due to respiratory failure. The main symptoms observed were respiratory failure, dyspnea, and hypoxemia. A chest CT scan revealed characteristic reduced opacity in both lungs with a "crazy-paving" appearance. The bronchoalveolar lavage fluid (BALF) showed periodic acid-Schiff positive proteinaceous deposits. Genetic testing indicated a compound heterozygous mutation in the ABCA3 gene. The diagnosis for the infant was congenital pulmonary alveolar proteinosis (PAP). Congenital PAP is a significant cause of challenging-to-treat respiratory failure in full-term infants. Therefore, congenital PAP should be considered in infants experiencing persistently difficult-to-treat dyspnea shortly after birth. Early utilization of chest CT scans, BALF pathological examination, and genetic testing may aid in early diagnosis.

[Heart failure caused by congenital hepatic hemangioma complicated with arteriovenous fistula in a neonate]. / æ–°ç”Ÿå„¿å ˆå¤©æ€§è‚è¡€ç®¡ç˜¤ä¼´åŠ¨é™è„‰ç˜˜å¯¼è‡´å¿ƒåŠŸèƒ½ä¸å ¨1例.

The three-day-old female infant was admitted to the hospital due to respiratory distress after birth. She was born premature at 36+2 weeks gestational age. Prenatal ultrasound suggested abnormal development of the fetal liver vessels, and she had dyspnea that required respiratory support after birth. Chest X-ray indicated an enlarged cardiac silhouette, and cardiac ultrasound revealed enlargement of the right atrium and right ventricle. Diagnosis of hepatic hemangioma with arteriovenous fistula was confirmed through liver ultrasound and abdominal enhanced CT. At 19 days old, she underwent ligation of the hepatic artery under general anesthesia, which led to an improvement in cardiac function and she was subsequently discharged. Genetic testing revealed a mutation in the ACVRL1 gene, which was inherited from the mother. The article primarily introduces a case of neonatal heart failure caused by hepatic hemangioma with arteriovenous fistula, and multi-disciplinary diagnosis and treatment of this disease.

Analysis of Adverse Drug Reaction Reports from a Public Hospital in Shanxi Province in 2022.

Objective: Through analyzing the characteristics and influencing factors of adverse drug reactions/adverse events (ADR/ADE) in a hospital to promote rational drug use in the clinic. Methods: A total of 1221 ADR/ADE reports collected from a hospital in 2022 were retrieved through the National Adverse Drug Reaction Monitoring Center. The effective reports were screened according to the Guiding Principles for Collection and Reporting of Individual Adverse Drug Reactions, and classified the standardized drugs. The systems/organs and main clinical symptoms affected by ADR/ADE were classified according to the WHO Glossary of Adverse Drug Reaction Terms. The severity, age and gender, occupational distribution, drug category, route of administration, drug dosage form, system/organ involved, and main clinical symptoms of ADR/ADE reports were analyzed. Results: Among 1221 ADR/ADE reports, 890 cases (75.27%) reported by doctors; 144 cases (11.79%) were serious; Precisely 49.22% of ADR/ADE occurred in patients aged 51 to 70 years old; The highest incidence of adverse reactions was 636 cases (52.09%) by intravenous infusion, 406 cases (33.25%) by oral administration. The top categories of reported cases were anti-infective drugs (29.40%) and anti-tumor drugs (27.52%); Systems/organs involved in ADR/ADE were mainly the skin and its accessories (24.96%) and blood system (21.35%). 166 cases were cured, 893 cases were symptomatic, 160 cases were unknown, and 2 cases had sequelae. Conclusion: The occurrence of ADR/ADE is related to many influencing factors such as age, drug categories, and route of administration. Therefore, it is recommended that hospitals strengthen the monitoring of ADR/ADE, especially the elderly, anti-infective drugs and intravenous administration.

Identification of immunological bioprocesses involved in peri-implantitis using weighted gene co-expression network analysis.

BACKGROUND: Peri-implantitis is an irreversible infectious disease that occurs with high incidence. Exploring the immune responses of peri-implantitis is key to developing targeted treatment strategies. However, there is limited research on the immune response of peri-implantitis. METHODS: This study performed a weighted gene co-expression network analysis to identify the peri-implantitis related gene network and conducted a functional enrichment analysis of the gene network. Thereafter, the candidate hub genes were selected by constructing a protein-protein interaction network and drawing an upset plot. The hub genes were identified through their significant associations with disease condition and validated using quantitative reverse transcription-polymerase chain reaction (qRT-PCR) analysis. Using the gene set variation analysis, the hub genes were further used to explore infiltrating immunocytes and immune factors in peri-implantitis. Finally, the immunocytes and immune factor related hub genes were intersected to obtain the therapeutic target, which was validated using histological staining. RESULTS: The peri-implantitis related gene network was enriched in innate and adaptive immune response. Subsequently, interleukin (IL)1B, IL10, ITGAM, ITGB1, STAT3, and TLR4 were identified as hub genes. Plasmacytoid dendritic cells, macrophages, myeloid-derived suppressor cells, natural killer T cells, and immature B cells were positively and significantly related to the hub genes IL1B, TLR4, ITGAM, and ITGB1 (correlation coefficient > 0.80). While immune factors CXCL10, IL6, and CXCL12 and hub genes IL10 and IL1B held the highest degree in the immune factors network. IL1B may be a promising therapeutic target. CONCLUSION: This study provides new insights into the hub genes, immunocytes, and immune factors underlying peri-implantitis immunological bioprocess.

Identification and characterization of circular RNAs as novel putative biomarkers to predict anti-PD-1 monotherapy response in metastatic melanoma patients - Knowledge from two independent international studies.

Melanoma is the most aggressive skin malignancy with high morbidity. Anti-programmed cell death protein 1 (PD-1) monotherapy has been applied in metastatic melanoma. However, still most of the patients do not respond to anti-PD-1 and the availability of the present approved biomarkers therefore is limited. Here we combined the transcriptomic and clinical data of 163 advanced melanoma patients receiving anti-PD-1 from NIH Melanoma Genome Sequencing Project (phs000452, 122 patients) as the training and internal validation cohort, and Melanoma Institute Australia cohort (PRJEB23709, 41 patients) as the external validation cohort, respectively. Circular RNAs (circRNAs) are an evolutionarily conserved novel class of noncoding endogenous RNAs (ncRNAs) found in the eukaryotic transcriptome and were used based on RNAseq data for our analyses. 74,243 circular RNAs (circRNAs) were identified with NCLscan and CIRCexplorer2. Thereof, 70 circRNAs significantly associated with progression-free survival and overall survival. Further, a prognostic circRNAs signature consisting of HSA_CIRCpedia_1497, HSA_CIRCpedia_12559, HSA_CIRCpedia_43640, HSA_CIRCpedia_43070, and HSA_CIRCpedia_21660 could be determined with LASSO regression. This signature was a prognostic factor of overall survival and progression-free survival among the analyzed advanced melanoma patients. The concordance indexes (C-index of OStraining: 0.61, C-index of PFStraining: 0.68) also confirmed its credibility and accuracy. First enrichment analysis indicated that immune response and pathways related to tumor immune microenvironment were enriched. In conclusion, we succeeded to construct and validate novel prognostic circRNAs signature for advanced melanoma patients treated with anti-PD-1 immunotherapy.

Risk factors and machine learning prediction models for bronchopulmonary dysplasia severity in the Chinese population.

BACKGROUND: Bronchopulmonary dysplasia (BPD) is a common chronic lung disease in extremely preterm neonates. The outcome and clinical burden vary dramatically according to severity. Although some prediction tools for BPD exist, they seldom pay attention to disease severity and are based on populations in developed countries. This study aimed to develop machine learning prediction models for BPD severity based on selected clinical factors in a Chinese population. METHODS: In this retrospective, single-center study, we included patients with a gestational age < 32 weeks who were diagnosed with BPD in our neonatal intensive care unit from 2016 to 2020. We collected their clinical information during the maternal, birth and early postnatal periods. Risk factors were selected through univariable and ordinal logistic regression analyses. Prediction models based on logistic regression (LR), gradient boosting decision tree, XGBoost (XGB) and random forest (RF) models were implemented and assessed by the area under the receiver operating characteristic curve (AUC). RESULTS: We ultimately included 471 patients (279 mild, 147 moderate, and 45 severe cases). On ordinal logistic regression, gestational diabetes mellitus, initial fraction of inspiration O2 value, invasive ventilation, acidosis, hypochloremia, C-reactive protein level, patent ductus arteriosus and Gram-negative respiratory culture were independent risk factors for BPD severity. All the XGB, LR and RF models (AUC = 0.85, 0.86 and 0.84, respectively) all had good performance. CONCLUSIONS: We found risk factors for BPD severity in our population and developed machine learning models based on them. The models have good performance and can be used to aid in predicting BPD severity in the Chinese population.

Positive response to trastuzumab deruxtecan in a patient with HER2-mutant NSCLC after multiple lines therapy, including T-DM1: a case report.

Human epidermal growth factor 2 (HER2) mutations are uncommon in non-small cell lung cancer (NSCLC), and the lack of established, effective, targeted drugs has resulted in a persistently poor prognosis. Herein, we report the case of a non-smoking, 58-year-old man diagnosed with lung adenocarcinoma (cT3N0M1c, stage IVB) harboring a HER2 mutation (Y772_A775dupYVMA) and PD-L1 (-). The patient's Eastern Cooperative Oncology Group performance status (PS) score was assessed as 1. He commenced first-line treatment with chemotherapy, followed by immuno-chemotherapy, and with disease progression, he received HER2-targeted therapy and chemotherapy with an anti-angiogenic agent. However, HER2-targeted therapy, including pan-HER tyrosine kinase inhibitors (afatinib, pyrotinib, and pozitinib) and antibody-drug conjugate (T-DM1), produced only stable disease (SD) as the best response. After the previously described treatment, primary tumor recurrence and multiple brain metastases were observed. Despite the patient's compromised overall physical condition with a PS score of 3-4, he was administered T-DXd in addition to whole-brain radiotherapy (WBRT). Remarkably, both intracranial metastases and primary lesions were significantly reduced, he achieved a partial response (PR), and his PS score increased from 3-4 to 1. He was then treated with T-DXd for almost 9 months until the disease again progressed, and he did not discontinue the drug despite the occurrence of myelosuppression during this period. This is a critical case as it exerted an effective response to T-DXd despite multiple lines therapy, including T-DM1. Simultaneously, despite the occurrence of myelosuppression in the patient during T-DXd, it was controlled after aggressive treatment.

Definition of a new blood cell count score for early survival prediction for non-small cell lung cancer patients treated with atezolizumab: Integrated analysis of four multicenter clinical trials.

Importance: Blood cell count test (BCT) is a robust method that provides direct quantification of various types of immune cells to reveal the immune landscape to predict atezolizumab treatment outcomes for clinicians to decide the next phase of treatment. Objective: This study aims to define a new BCTscore model to predict atezolizumab treatment benefits in non-small lung cell cancer (NSCLC) patients. Design Setting and Participants: This study analyzed four international, multicenter clinical trials (OAK, BIRCH, POPLAR, and FIR trials) to conduct post-hoc analyses of NSCLC patients undergoing atezolizumab (anti-PD-L1) single-agent treatment (n = 1,479) or docetaxel single-agent treatment (n = 707). BCT was conducted at three time points: pre-treatment (T1), the first day of treatment cycle 3 (T2), and first day of treatment cycle 5 (T3). Univariate and multivariate Cox regression analyses were conducted to identify early BCT biomarkers to predict atezolizumab treatment outcomes in NSCLC patients. Main Outcomes and Measures: Overall survival (OS) was used as the primary end point, whereas progression-free survival (PFS) according to Response Evaluation Criteria in Solid Tumors (RECIST), clinical benefit (CB), and objective response rate (ORR) were used as secondary end points. Results: The BCT biomarkers of neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) at time point T3 and neutrophil-to-monocyte ratio (NMR) at time point T2 with absolute cutoff values of NLR_T3 = 5, PLR_T3 = 180, and NMR_T2 = 6 were identified as strong predictive biomarkers for atezolizumab (Ate)-treated NSCLC patients in comparison with docetaxel (Dtx)-treated patients regarding OS (BCTscore low risk: HR Ate vs. Dtx = 1.54 (95% CI: 1.04-2.27), P = 0.031; high risk: HR Ate vs. Dtx = 0.84 (95% CI: 0.62-1.12), P = 0.235). The identified BCTscore model showed better OS AUC in the OAK (AUC12month = 0.696), BIRCH (AUC12month = 0.672) and POPLAR+FIR studies (AUC12month = 0.727) than that of each of the three single BCT biomarkers. Conclusion and Relevance: The BCTscore model is a valid predictive and prognostic biomarker for early survival prediction in atezolizumab-treated NSCLC patients.

Elucidation of the Application of Blood Test Biomarkers to Predict Immune-Related Adverse Events in Atezolizumab-Treated NSCLC Patients Using Machine Learning Methods.

Background: Development of severe immune-related adverse events (irAEs) is a major predicament to stop treatment with immune checkpoint inhibitors, even though tumor progression is suppressed. However, no effective early phase biomarker has been established to predict irAE until now. Method: This study retrospectively used the data of four international, multi-center clinical trials to investigate the application of blood test biomarkers to predict irAEs in atezolizumab-treated advanced non-small cell lung cancer (NSCLC) patients. Seven machine learning methods were exploited to dissect the importance score of 21 blood test biomarkers after 1,000 simulations by the training cohort consisting of 80%, 70%, and 60% of the combined cohort with 1,320 eligible patients. Results: XGBoost and LASSO exhibited the best performance in this study with relatively higher consistency between the training and test cohorts. The best area under the curve (AUC) was obtained by a 10-biomarker panel using the XGBoost method for the 8:2 training:test cohort ratio (training cohort AUC = 0.692, test cohort AUC = 0.681). This panel could be further narrowed down to a three-biomarker panel consisting of C-reactive protein (CRP), platelet-to-lymphocyte ratio (PLR), and thyroid-stimulating hormone (TSH) with a small median AUC difference using the XGBoost method [for the 8:2 training:test cohort ratio, training cohort AUC difference = -0.035 (p < 0.0001), and test cohort AUC difference = 0.001 (p=0.965)]. Conclusion: Blood test biomarkers currently do not have sufficient predictive power to predict irAE development in atezolizumab-treated advanced NSCLC patients. Nevertheless, biomarkers related to adaptive immunity and liver or thyroid dysfunction warrant further investigation.

Organ-specific metastatic landscape dissects PD-(L)1 blockade efficacy in advanced non-small cell lung cancer: applicability from clinical trials to real-world practice.

BACKGROUND: Organ-specific metastatic context has not been incorporated into the clinical practice of guiding programmed death-(ligand) 1 [PD-(L)1] blockade, due to a lack of understanding of its predictive versus prognostic value. We aim at delineating and then incorporating both the predictive and prognostic effects of the metastatic-organ landscape to dissect PD-(L)1 blockade efficacy in non-small cell lung cancer (NSCLC). METHODS: A total of 2062 NSCLC patients from a double-arm randomized trial (OAK), two immunotherapy trials (FIR, BIRCH), and a real-world cohort (NFyy) were included. The metastatic organs were stratified into two categories based on their treatment-dependent predictive significance versus treatment-independent prognosis. A metastasis-based scoring system (METscore) was developed and validated for guiding PD-(L)1 blockade in clinical trials and real-world practice. RESULTS: Patients harboring various organ-specific metastases presented significantly different responses to immunotherapy, and those with brain and adrenal gland metastases survived longer than others [overall survival (OS), p = 0.0105; progression-free survival (PFS), p = 0.0167]. In contrast, survival outcomes were similar in chemotherapy-treated patients regardless of metastatic sites (OS, p = 0.3742; PFS, p = 0.8242). Intriguingly, the immunotherapeutic predictive significance of the metastatic-organ landscape was specifically presented in PD-L1-positive populations (PD-L1 > 1%). Among them, a paradoxical coexistence of a favorable predictive effect coupled with an unfavorable prognostic effect was observed in metastases to adrenal glands, brain, and liver (category I organs), whereas metastases to bone, pleura, pleural effusion, and mediastinum yielded consistent unfavorable predictive and prognostic effects (category II organs). METscore was capable of integrating both predictive and prognostic effects of the entire landscape and dissected OS outcome of NSCLC patients received PD-(L)1 blockade (p < 0.0001) but not chemotherapy (p = 0.0805) in the OAK training cohort. Meanwhile, general performance of METscore was first validated in FIR (p = 0.0350) and BIRCH (p < 0.0001), and then in the real-world NFyy cohort (p = 0.0181). Notably, METscore was also applicable to patients received PD-(L)1 blockade as first-line treatment both in the clinical trials (OS, p = 0.0087; PFS, p = 0.0290) and in the real-world practice (OS, p = 0.0182; PFS, p = 0.0045). CONCLUSIONS: Organ-specific metastatic landscape served as a potential predictor of immunotherapy, and METscore might enable noninvasive forecast of PD-(L)1 blockade efficacy using baseline radiologic assessments in advanced NSCLC.

A modified lung ultrasound score to evaluate short-term clinical outcomes of bronchopulmonary dysplasia.

BACKGROUND: Lung ultrasound (LUS) is a useful tool for assessing the severity of lung disease, without radiation exposure. However, there is little data on the practicality of LUS in assessing the severity of bronchopulmonary dysplasia (BPD) and evaluating short-term clinical outcomes. We adapted a LUS score to evaluate BPD severity and assess the reliability of mLUS score correlated with short-term clinical outcomes. METHODS: Prospective diagnostic accuracy study was designed to enroll preterm infants with gestational age < 34 weeks. Lung ultrasonography was performed at 36 weeks postmenstrual age. The diagnostic and predictive values of new modified lung ultrasound (mLUS) scores based on eight standard sections were compared with classic lung ultrasound (cLUS) scores. RESULTS: A total of 128 infants were enrolled in this cohort, including 30 without BPD; 31 with mild BPD; 23 with moderate BPD and 44 with severe BPD. The mLUS score was significantly correlated with the short-term clinical outcomes, superior to cLUS score. The mLUS score well correlated with moderate and severe BPD (AUC = 0.813, 95% CI 0.739-0.888) and severe BPD (AUC = 0.801, 95% CI 0.728-0.875), which were superior to cLUS score. The ROC analysis of mLUS score to evaluate the other short-term outcomes also showed significant superiority to cLUS score. The optimal cutoff points for mLUS score were 14 for moderate and severe BPD and 16 for severe BPD. CONCLUSIONS: The mLUS score correlates significantly with short-term clinical outcomes and well evaluates these outcomes in preterm infants.

Induction chemoimmunotherapy followed by CD8+ immune cell-based patient selection for chemotherapy-free radioimmunotherapy in locally advanced head and neck cancer.

PURPOSE: The first aim of the trial is to study feasibility of combined programmed death protein ligand 1/cytotoxic T-lymphocyte-associated protein 4 inhibition concomitant to radiotherapy. In addition, efficacy of the entire treatment scheme consisting of induction chemoimmunotherapy followed by chemotherapy-free radioimmunotherapy (RIT) after intratumoral CD8 +immune cell-based patient selection will be analyzed. METHODS: Patients with stage III-IVB head and neck squamous cell carcinoma were eligible for this multicenter phase II trial. Treatment consisted of a single cycle of cisplatin 30 mg/m² days 1-3, docetaxel 75 mg/m² day 1, durvalumab 1500 mg fix dose day 5 and tremelimumab 75 mg fix dose day 5. Patients with increased intratumoral CD8 +immune cell density or pathological complete response (pCR) in the rebiopsy entered RIT up to a total dose of 70 Gy. Patients received further three cycles of durvalumab/tremelimumab followed by eight cycles of durvalumab mono (every 4 weeks). The intended treatment for patients not meeting these criteria was standard radiochemotherapy outside the trial. Primary endpoint was a feasibility rate of patients entering RIT to receive treatment until at least cycle 6 of immunotherapy of ≥80%. RESULTS: Between September 2018 and May 2020, 80 patients were enrolled (one excluded). Out of these, 23 patients had human papilloma virus (HPV)-positive oropharyngeal cancer. Median follow-up was 17.2 months. After induction chemoimmunotherapy 41 patients had pCR and 31 had increased intratumoral CD8 +immune cells. Of 60 patients entering RIT (primary endpoint cohort), 10 experienced imiting toxic (mainly hepatitis) and four discontinued for other reasons, resulting in a feasibility rate of 82%. The RIT cohort (n=60) had a progression-free survival (PFS) rate at one and 2 years of 78% and 72%, respectively, and an overall survival rate at one and 2 years of 90% and 84%, respectively. Patients with HPV-positive oropharyngeal cancers had greater benefit from RIT with a 2-year PFS rate of 94% compared with 64% for HPV-negative oropharyngeal cancers and other locations. In the entire study cohort (n=79) the 2-year PFS rate was 68% (91% for HPV-positive oropharynx vs 59% for others). Toxicity grade 3-4 mainly consisted of dysphagia (53%), leukopenia (52%) and infections (32%). CONCLUSIONS: The trial met the primary endpoint feasibility of RIT. Induction chemo-immunotherapy followed by chemotherapy-free RIT after intratumoral CD8 +immune cell-based patient selection has promising PFS. TRIAL REGISTRATION NUMBER: The trial was registered with ClinicalTrials.gov (identifier: NCT03426657). The trial was conducted as investigator-sponsored trial (IST).

Identification of an endogenous retroviral signature to predict anti-PD1 response in advanced clear cell renal cell carcinoma: an integrated analysis of three clinical trials.

Background: Endogenous retrovirus (ERV) elements are genomic footprints of ancestral retroviral infections within the human genome. Previous studies have demonstrated that dysregulated ERV transcription level is associated with immune cell infiltration in cancers, but the association between ERV expression and programmed cell death protein 1 (PD-1) blockade response is currently unraveled for solid cancers, such as advanced clear cell renal cell carcinoma (ccRCC). Methods: ERV mRNA profiles were obtained from three clinical trials of ccRCC where the patients were treated with anti-PD-1 (CM-009, CM-010, CM-025, and TCGA-KIRC data). Patients treated with nivolumab were divided into training and test cohort, while the TCGA-KIRC cohort was used as an external validation. Univariate Cox regression analysis and least absolute shrinkage and selection operator regression were used to establish the signature. Immune cell infiltration analysis and gene set enrichment analysis were performed to explore potential biological mechanisms. Results: An ERV signature was established based on nine ERV expression patterns. In the training cohort, the median overall survival in the low- and high-risk group was 45.2 and 19.6 months [hazard ratio (HR) = 0.49, 0.32-0.75, p < 0.001], respectively. The results were confirmed in the test (HR = 0.41, 0.20-0.83, p = 0.013), and in the TCGA-KIRC cohort (HR = 0.55, 0.34-0.90, p = 0.017). Moreover, in the CM-025 cohort, the low-risk group that received nivolumab had a more favorable survival compared with those that received the mTOR inhibitor everolimus, while no significant differences were observed in the high-risk group. CD8+ T cells were enriched in the low-risk group, while immune suppressive pathways were suppressed. Conclusion: The newly identified ERV signature is not only a prognostic, but also a predictive biomarker for advanced ccRCC patients who received anti-PD-1 therapy, which can guide personalized treatment in cancer patients in the future.