What Is the Appropriate Timing for Bar Removal After the Nuss Repair for Pectus Excavatum?

INTRODUCTION: The Nuss procedure for pectus excavatum requires that the sternal elevation be maintained by indwelling metal bars that are traditionally removed approximately 3 y after the repair. METHODS: A retrospective cohort study was conducted of all patients who underwent primary Nuss repair from 2007 to 2018 in two institutions and had a follow-up of at least 24 mo. Pectus bars had been left in place beyond 3 y in patients concerned over possible recurrence after bar removal. Structured interviews were held to assess pain, chest tightness, or other discomfort, and any adverse events related to pectus bars. Results were compared between patients in whom pectus bars were removed after 3 y (standard group) and those in whom bars were left in place longer (extended bar duration group). RESULTS: Two hundred and thirty-one patients (91% males, mean age 23.9 ± 8.3, mean Haller index 4.9 ± 2.3) were included. Bar duration was 30.6 ± 6.6 mo in the standard group (51 patients) versus 69.1 ± 26.3 mo in the extended group (180 patients). Some discomfort was reported by 81.6% in the standard group versus 62.9% in the extended group (P = 0.033), and discomfort occurring at least monthly or more often was only reported by 30% in the standard versus 30.3% in the extended group (P = 1.000). Quality of life improved in 92.6% of the standard group versus 94.7% of the extended group (P = 1.000). No significant adverse events were reported in either group. CONCLUSIONS: Our data suggest that an extended bar duration after the Nuss repair may not cause any adverse event nor negatively affect quality of life.

Radiomics and gene expression profile to characterise the disease and predict outcome in patients with lung cancer.

OBJECTIVE: The objectives of our study were to assess the association of radiomic and genomic data with histology and patient outcome in non-small cell lung cancer (NSCLC). METHODS: In this retrospective single-centre observational study, we selected 151 surgically treated patients with adenocarcinoma or squamous cell carcinoma who performed baseline [18F] FDG PET/CT. A subgroup of patients with cancer tissue samples at the Institutional Biobank (n = 74/151) was included in the genomic analysis. Features were extracted from both PET and CT images using an in-house tool. The genomic analysis included detection of genetic variants, fusion transcripts, and gene expression. Generalised linear model (GLM) and machine learning (ML) algorithms were used to predict histology and tumour recurrence. RESULTS: Standardised uptake value (SUV) and kurtosis (among the PET and CT radiomic features, respectively), and the expression of TP63, EPHA10, FBN2, and IL1RAP were associated with the histotype. No correlation was found between radiomic features/genomic data and relapse using GLM. The ML approach identified several radiomic/genomic rules to predict the histotype successfully. The ML approach showed a modest ability of PET radiomic features to predict relapse, while it identified a robust gene expression signature able to predict patient relapse correctly. The best-performing ML radiogenomic rule predicting the outcome resulted in an area under the curve (AUC) of 0.87. CONCLUSIONS: Radiogenomic data may provide clinically relevant information in NSCLC patients regarding the histotype, aggressiveness, and progression. Gene expression analysis showed potential new biomarkers and targets valuable for patient management and treatment. The application of ML allows to increase the efficacy of radiogenomic analysis and provides novel insights into cancer biology.

Computed tomography (CT)-derived radiomic features differentiate prevascular mediastinum masses as thymic neoplasms versus lymphomas.

OBJECTIVES: We aimed to assess the ability of radiomics, applied to not-enhanced computed tomography (CT), to differentiate mediastinal masses as thymic neoplasms vs lymphomas. METHODS: The present study was an observational retrospective trial. Inclusion criteria were pathology-proven thymic neoplasia or lymphoma with mediastinal localization, availability of CT. Exclusion criteria were age < 16 years and mediastinal lymphoma lesion < 4 cm. We selected 108 patients (M:F = 47:61, median age 48 years, range 17-79) and divided them into a training and a validation group. Radiomic features were used as predictors in linear discriminant analysis. We built different radiomic models considering segmentation software and resampling setting. Clinical variables were used as predictors to build a clinical model. Scoring metrics included sensitivity, specificity, accuracy and area under the curve (AUC). Wilcoxon paired test was used to compare the AUCs. RESULTS: Fifty-five patients were affected by thymic neoplasia and 53 by lymphoma. In the validation analysis, the best radiomics model sensitivity, specificity, accuracy and AUC resulted 76.2 ± 7.0, 77.8 ± 5.5, 76.9 ± 6.0 and 0.84 ± 0.06, respectively. In the validation analysis of the clinical model, the same metrics resulted 95.2 ± 7.0, 88.9 ± 8.9, 92.3 ± 8.5 and 0.98 ± 0.07, respectively. The AUCs of the best radiomic and the clinical model not differed. CONCLUSIONS: We developed and validated a CT-based radiomic model able to differentiate mediastinal masses on non-contrast-enhanced images, as thymic neoplasms or lymphoma. The proposed method was not affected by image postprocessing. Therefore, the present image-derived method has the potential to noninvasively support diagnosis in patients with prevascular mediastinal masses with major impact on management of asymptomatic cases.

Prediction of disease-free survival by the PET/CT radiomic signature in non-small cell lung cancer patients undergoing surgery.

PURPOSE: Radiomic features derived from the texture analysis of different imaging modalities e show promise in lesion characterisation, response prediction, and prognostication in lung cancer patients. The present study aimed to identify an images-based radiomic signature capable of predicting disease-free survival (DFS) in non-small cell lung cancer (NSCLC) patients undergoing surgery. METHODS: A cohort of 295 patients was selected. Clinical parameters (age, sex, histological type, tumour grade, and stage) were recorded for all patients. The endpoint of this study was DFS. Both computed tomography (CT) and fluorodeoxyglucose positron emission tomography (PET) images generated from the PET/CT scanner were analysed. Textural features were calculated using the LifeX package. Statistical analysis was performed using the R platform. The datasets were separated into two cohorts by random selection to perform training and validation of the statistical models. Predictors were fed into a multivariate Cox proportional hazard regression model and the receiver operating characteristic (ROC) curve as well as the corresponding area under the curve (AUC) were computed for each model built. RESULTS: The Cox models that included radiomic features for the CT, the PET, and the PET+CT images resulted in an AUC of 0.75 (95%CI: 0.65-0.85), 0.68 (95%CI: 0.57-0.80), and 0.68 (95%CI: 0.58-0.74), respectively. The addition of clinical predictors to the Cox models resulted in an AUC of 0.61 (95%CI: 0.51-0.69), 0.64 (95%CI: 0.53-0.75), and 0.65 (95%CI: 0.50-0.72) for the CT, the PET, and the PET+CT images, respectively. CONCLUSIONS: A radiomic signature, for either CT, PET, or PET/CT images, has been identified and validated for the prediction of disease-free survival in patients with non-small cell lung cancer treated by surgery.

Ability of FDG PET and CT radiomics features to differentiate between primary and metastatic lung lesions.

PURPOSE: To evaluate the ability of CT and PET radiomics features to classify lung lesions as primary or metastatic, and secondly to differentiate histological subtypes of primary lung cancers. METHODS: A cohort of 534 patients with lung lesions were retrospectively studied. Radiomics texture features were extracted using the LIFEx package from semiautomatically segmented PET and CT images. Histology data were recorded in all patients. The patient cohort was divided into a training and a validation group and linear discriminant analysis (LDA) was performed to classify the lesions using both direct and backward stepwise methods. The robustness of the procedure was tested by repeating the entire process 100 times with different assignments to the training and validation groups. Scoring metrics included analysis of the receiver operating characteristic curves in terms of area under the curve (AUC), sensitivity, specificity and accuracy. RESULTS: Radiomics features extracted from CT and PET datasets were able to differentiate primary tumours from metastases in both the training and the validation group (AUCs 0.79 ± 0.03 and 0.70 ± 0.04, respectively, from the CT dataset; AUCs 0.92 ± 0.01 and 0.91 ± 0.03, respectively, from the PET dataset). The AUC cut-off thresholds identified by LDA using direct and backward elimination strategies were -0.79 ± 0.06 and -0.81 ± 0.08, respectively (CT dataset) and -0.69 ± 0.05 and -0.68 ± 0.04, respectively (PET dataset). For differentiation between primary subgroups based on CT features, the AUCs in the training and validation groups were 0.81 ± 0.02 and 0.69 ± 0.04 for adenocarcinoma (Adc) vs. squamous cell carcinoma (Sqc) or "Other", 0.85 ± 0.02 and 0.70 ± 0.05 for Sqc vs. Adc or Other, and 0.77 ± 0.03 and 0.57 ± 0.05 for Other vs. Adc or Sqc. The same analyses for the PET data revealed AUCs of 0.90 ± 0.10 and 0.80 ± 0.04, 0.80 ± 0.02 and 0.61 ± 0.06, and 0.97 ± 0.01 and 0.88 ± 0.04, respectively. CONCLUSION: PET radiomics features were able to differentiate between primary and metastatic lung lesions and showed the potential to identify primary lung cancer subtypes.

Prognostic and diagnostic potential of local and circulating levels of pentraxin 3 in lung cancer patients.

There is a well-established link between inflammation and cancer of various organs, but little data are available on inflammation-associated markers of diagnostic and prognostic clinical utility in pulmonary malignancy. Blood samples were prospectively collected from 75 resectable lung cancer patients before surgery and in a cohort of 1,358 high-risk subjects. Serum levels of long pentraxin 3 (PTX3) were determined by high-sensitivity ELISA. PTX3 immunostaining was evaluated by immunohistochemistry in cancer tissue. Serum PTX3 levels in the high-risk population were not predictive of developing subsequent lung cancer or any other malignancy; however, serum PTX3 values in patients with lung cancer were significantly higher compared with cancer-free heavy smokers. With a cutoff of 4.5 ng/ml, specificity was 0.80, sensitivity 0.69, positive predictive value 0.15 and negative predictive value 0.98. The receiver operating curve (ROC) for serum PTX3 had an area under the curve (AUC) of 83.52%. Preoperative serum PTX3 levels in lung cancer patients did not correlate with patient outcome, but high interstitial expression of PTX3 in resected tumor specimens was a significant independent prognostic factor associated with shorter survival (p < 0.001). These results support the potential of serum PTX3 as a lung cancer biomarker in high-risk subjects. Furthermore, PTX3 immunohistochemistry findings support the role of local inflammatory mechanisms in determining clinical outcome and suggest that local expression of PTX3 may be of prognostic utility in lung cancer patients.

Long-Term Follow-up Results of the DANTE Trial, a Randomized Study of Lung Cancer Screening with Spiral Computed Tomography.

RATIONALE: Screening for lung cancer with low-dose spiral computed tomography (LDCT) has been shown to reduce lung cancer mortality by 20% compared with screening with chest X-ray (CXR) in the National Lung Screening Trial, but uncertainty remains concerning the efficacy of LDCT screening in a community setting. OBJECTIVES: To explore the effect of LDCT screening on lung cancer mortality compared with no screening. Secondary endpoints included incidence, stage, and resectability rates. METHODS: Male smokers of 20+ pack-years, aged 60 to 74 years, underwent a baseline CXR and sputum cytology examination and received five screening rounds with LDCT or a yearly clinical review only in a randomized fashion. MEASUREMENTS AND MAIN RESULTS: A total of 1,264 subjects were enrolled in the LDCT arm and 1,186 in the control arm. Their median age was 64.0 years (interquartile range, 5), and median smoking exposure was 45.0 pack-years. The median follow-up was 8.35 years. One hundred four patients (8.23%) were diagnosed with lung cancer in the screening arm (66 by CT), 47 of whom (3.71%) had stage I disease; 72 control patients (6.07%) were diagnosed with lung cancer, with 16 (1.35%) being stage I cases. Lung cancer mortality was 543 per 100,000 person-years (95% confidence interval, 413-700) in the LDCT arm versus 544 per 100,000 person-years (95% CI, 410-709) in the control arm (hazard ratio, 0.993; 95% confidence interval, 0.688-1.433). CONCLUSIONS: Because of its limited statistical power, the results of the DANTE (Detection And screening of early lung cancer with Novel imaging TEchnology) trial do not allow us to make a definitive statement about the efficacy of LDCT screening. However, they underline the importance of obtaining additional data from randomized trials with intervention-free reference arms before the implementation of population screening.

Follicular dendritic cell sarcoma with atypical features surrounding undescended testis: description of a rare case.

Dendritic cell tumors are extremely rare neoplasms and occur both in nodal and extranodal sites. We report a case of an intra-abdominal follicular dendritic cell sarcoma (FDCS). The aim of this study is to describe histological, immunohistochemical, and ultrastructural features of FDCS in order to better define an abdominal mass with unusual immunophenotype and atypical clinical and radiological presentation.

Huge malignant phyllodes breast tumor: a real entity in a new era of early breast cancer.

Phyllodes tumor is an extremely rare tumor of the breast. It occurs in females in the third and fourth decades. The difficulty in distinguishing between phyllodes tumors and benign fibroadenoma may lead to misdiagnosis. Lymph node involvement is rarely described in phyllodes tumors; for this reason, sentinel node biopsy may be warranted. We present a case of a 33-year-old woman affected by huge tumor of the right breast with ulceration in the skin with a rapid tumor growth and with omolateral axillary metastasis.

Integrating AI-Powered Digital Pathology and Imaging Mass Cytometry Identifies Key Classifiers of Tumor Cells, Stroma, and Immune Cells in Non-Small Cell Lung Cancer.

Artificial intelligence (AI)-powered approaches are becoming increasingly used as histopathologic tools to extract subvisual features and improve diagnostic workflows. On the other hand, hi-plex approaches are widely adopted to analyze the immune ecosystem in tumor specimens. Here, we aimed at combining AI-aided histopathology and imaging mass cytometry (IMC) to analyze the ecosystem of non-small cell lung cancer (NSCLC). An AI-based approach was used on hematoxylin and eosin (H&E) sections from 158 NSCLC specimens to accurately identify tumor cells, both adenocarcinoma and squamous carcinoma cells, and to generate a classifier of tumor cell spatial clustering. Consecutive tissue sections were stained with metal-labeled antibodies and processed through the IMC workflow, allowing quantitative detection of 24 markers related to tumor cells, tissue architecture, CD45+ myeloid and lymphoid cells, and immune activation. IMC identified 11 macrophage clusters that mainly localized in the stroma, except for S100A8+ cells, which infiltrated tumor nests. T cells were preferentially localized in peritumor areas or in tumor nests, the latter being associated with better prognosis, and they were more abundant in highly clustered tumors. Integrated tumor and immune classifiers were validated as prognostic on whole slides. In conclusion, integration of AI-powered H&E and multiparametric IMC allows investigation of spatial patterns and reveals tissue relevant features with clinical relevance. SIGNIFICANCE: Leveraging artificial intelligence-powered H&E analysis integrated with hi-plex imaging mass cytometry provides insights into the tumor ecosystem and can translate tumor features into classifiers to predict prognosis, genotype, and therapy response.

Autoimmunity in thymic epithelial tumors: a not yet clarified pathologic paradigm associated with several unmet clinical needs.

Thymic epithelial tumors (TETs) are rare mediastinal cancers originating from the thymus, classified in two main histotypes: thymoma and thymic carcinoma (TC). TETs affect a primary lymphoid organ playing a critical role in keeping T-cell homeostasis and ensuring an adequate immunological tolerance against "self". In particular, thymomas and not TC are frequently associated with autoimmune diseases (ADs), with Myasthenia Gravis being the most common AD present in 30% of patients with thymoma. This comorbidity, in addition to negatively affecting the quality and duration of patients' life, reduces the spectrum of the available therapeutic options. Indeed, the presence of autoimmunity represents an exclusion criteria for the administration of the newest immunotherapeutic treatments with checkpoint inhibitors. The pathophysiological correlation between TETs and autoimmunity remains a mystery. Several studies have demonstrated the presence of a residual and active thymopoiesis in adult patients affected by thymomas, especially in mixed and lymphocytic-rich thymomas, currently known as type AB and B thymomas. The aim of this review is to provide the state of art in regard to the histological features of the different TET histotype, to the role of the different immune cells infiltrating tumor microenvironments and their impact in the break of central immunologic thymic tolerance in thymomas. We discuss here both cellular and molecular immunologic mechanisms inducing the onset of autoimmunity in TETs, limiting the portfolio of therapeutic strategies against TETs and greatly impacting the prognosis of associated autoimmune diseases.

Blood-Derived Systemic Inflammation Markers and Risk of Nodal Failure in Stage Ia Non-Small Cell Lung Cancer: A Multicentric Study.

BACKGROUND: Unexpected spread to regional lymph nodes can be found in up to 10% of patients with early stage non-small cell lung cancer (NSCLC), thereby affecting both prognosis and treatment. Given the known relation between systemic inflammation and tumor progression, we sought to evaluate whether blood-derived systemic inflammation markers might help to the predict nodal outcome in patients with stage Ia NSCLC. METHODS: Preoperative levels of neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic inflammation score (SII, platelets × NLR) were collected from 368 patients who underwent curative lung resection for NSCLC. After categorization, inflammatory markers were subjected to logistic regression and time-event analysis in order to find associations with occult nodal spread and postoperative nodal recurrence. RESULTS: No inflammation marker was associated with the risk of occult nodal spread. SII showed a marginal effect on early nodal recurrence at a quasi-significant level (p = 0.065). However, patients with T1c tumors and elevated PLR and/or SII had significantly shorter times to nodal recurrence compared to T1a/T1b patients (p = 0.001), while patients with T1c and normal PLR/SII did not (p = 0.128). CONCLUSIONS: blood-derived inflammation markers had no value in the preoperative prediction of nodal status. Nevertheless, our results might suggest a modulating effect of platelet-derived inflammation markers on nodal progression after the resection of tumors larger than 2 cm.

The Development of an Intelligent Agent to Detect and Non-Invasively Characterize Lung Lesions on CT Scans: Ready for the "Real World"?

(1) Background: Once lung lesions are identified on CT scans, they must be characterized by assessing the risk of malignancy. Despite the promising performance of computer-aided systems, some limitations related to the study design and technical issues undermine these tools' efficiency; an "intelligent agent" to detect and non-invasively characterize lung lesions on CT scans is proposed. (2) Methods: Two main modules tackled the detection of lung nodules on CT scans and the diagnosis of each nodule into benign and malignant categories. Computer-aided detection (CADe) and computer aided-diagnosis (CADx) modules relied on deep learning techniques such as Retina U-Net and the convolutional neural network; (3) Results: Tests were conducted on one publicly available dataset and two local datasets featuring CT scans acquired with different devices to reveal deep learning performances in "real-world" clinical scenarios. The CADe module reached an accuracy rate of 78%, while the CADx's accuracy, specificity, and sensitivity stand at 80%, 73%, and 85.7%, respectively; (4) Conclusions: Two different deep learning techniques have been adapted for CADe and CADx purposes in both publicly available and private CT scan datasets. Experiments have shown adequate performance in both detection and diagnosis tasks. Nevertheless, some drawbacks still characterize the supervised learning paradigm employed in networks such as CNN and Retina U-Net in real-world clinical scenarios, with CT scans from different devices with different sensors' fingerprints and spatial resolution. Continuous reassessment of CADe and CADx's performance is needed during their implementation in clinical practice.

Percutaneous Computed Tomography (CT)-Guided Localization with Indocyanine Green for the Thoracoscopic Resection of Small Pulmonary Nodules.

BACKGROUND: The identification of small lung nodules is challenging during mini-invasive thoracic surgery. Unable to palpate them directly, surgeons have developed several methods to preoperatively localize pulmonary nodules, including the computed tomography-guided positioning of coils or metallic landmarks (hook wire) or bronchoscopic marking. METHODS: We present a series of patients scheduled for the video-assisted thoracoscopic sublobar resection of small pulmonary nodules, in which we performed preoperative percutaneous computed tomography (CT)-guided nodule localization through the injection of a mixture of indocyanine green and human albumin. RESULTS: A total of 40 patients underwent a preoperative CT-guided injection of indocyanine green followed by VATS resection within 24 h. Patients tolerated the procedure well, no pain medication was administrated, and no complications were observed during the marking procedure. All pulmonary nodules were easily detected and successfully resected. CONCLUSION: the near-infrared dye marking solution of indocyanine green (ICG) with diluted human albumin was safe, effective, and easy to perform. The ICG solution has the potential to facilitate the accurate localization and resection of pulmonary nodules during VATS surgery, avoiding the risk of marker displacement/migration.

A Risk Model to Predict the Delivery of Adjuvant Chemotherapy Following Lung Resection in Patients With Pathologically Positive Lymph Nodes.

To investigate factors associated with the ability to receive adjuvant chemotherapy in patients with pathological N1 and N2 stage after anatomic lung resections for non-small cell lung cancer (NSCLC). Multicenter retrospective analysis on 707 consecutive patients found pathologic N1 (pN1) or N2 (pN2) disease following anatomic lung resections for NSCLC (2014-2019). Multiple imputation logistic regression was used to identify factors associated with adjuvant chemotherapy and to develop a model to predict the probability of starting this treatment. The model was externally validated in a population of 253 patients. In the derivation set, 442 patients were pN1 and 265 pN2. 58% received at least 1 cycle of adjuvant chemotherapy. The variables significantly associated with the probability of starting chemotherapy after multivariable regression analysis were: younger age (p < 0.0001), Body Mass Index (BMI) (p = 0.031), Forced Expiratory Volume in 1 second (FEV1) (p = 0.037), better performance status (PS) (p < 0.0001), absence of chronic kidney disease (CKD) (p = 0.016), resection lesser than pneumonectomy (p = 0.010). The logit of the prediction model was: 6.58 -0.112 x age +0.039 x BMI +0.009 x FEV1 -0.650 x PS -1.388 x CKD -0.550 x pneumonectomy. The predicted rate of adjuvant chemotherapy in the validation set was 59.2 and similar to the observed 1 (59%, p = 0.87) confirming the model performance in external setting. This study identified several factors associated with the probability of initiating adjuvant chemotherapy after lung resection in node-positive patients. This information can be used during preoperative multidisciplinary meetings and patients counseling to support decision-making process regarding the timing of systemic treatment.

Early Hospital Discharge on Day Two Post Robotic Lobectomy with Telehealth Home Monitoring: A Pilot Study.

Despite the adoption of enhanced recovery programs, the reported postoperative length of stay after robotic surgery is 4 days even in highly specialized centers. We report preliminary results of a pilot study for a new protocol of early discharge (on day 2) with telehealth home monitoring after robotic lobectomy for lung cancer. All patients with a caregiver were discharged on postoperative day 2 with a telemonitoring device if they satisfied specific discharge criteria. Teleconsultations were scheduled once in the afternoon of post-operative day 2, twice on postoperative day 3, and then once a day until the chest tube removal. Post-discharge vital signs were recorded by patients at least four times daily through the device and were available for consultation by two surgeons through phone application. In case of sudden variation of vital signs or occurrence of adverse events, a direct telephone line was available for patients as well as a protected re-hospitalization path. Primary outcome was the safety evaluated by the occurrence of post-discharge complications and readmissions. Secondary outcome was the evaluation of resources optimization (hospitalization days) maintaining the standard of care. During the study period, twelve patients satisfied all preoperative clinical criteria to be enrolled in our protocol. Two of twelve enrolled patients were successively excluded because they did not satisfy discharge criteria on postoperative day 2. During telehealth home monitoring a total of 27/427 vital-sign measurements violated the threshold in seven patients. Among the threshold violations, only 1 out of 27 was a critical violation and was managed at home. No postoperative complication occurred neither readmission was needed. A mean number of three hospitalization days was avoided and an estimated economic benefit of about EUR 500 for a single patient was obtained if compared with patients submitted to VATS lobectomy in the same period. These preliminary results confirm that adoption of telemonitoring allows, in selected patients, a safe discharge on postoperative day 2 after robotic surgery for early-stage NSCLC. A potential economic benefit could derive from this protocol if this data will be confirmed in larger sample.

Analysis of Risk Factors for Tracheal Stenosis Managed during COVID-19 Pandemic: A Retrospective, Case-Control Study from Two European Referral Centre.

INTRODUCTION: Benign subglottic/tracheal stenosis (SG/TS) is a life-threatening condition commonly caused by prolonged endotracheal intubation or tracheostomy. Invasive mechanical ventilation was frequently used to manage severe COVID-19, resulting in an increased number of patients with various degrees of residual stenosis following respiratory weaning. The aim of this study was to compare demographics, radiological characteristics, and surgical outcomes between COVID-19 and non-COVID patients treated for tracheal stenosis and investigate the potential differences between the groups. MATERIALS AND METHODS: We retrospectively retrieved electronical medical records of patients managed at two referral centers for airways diseases (IRCCS Humanitas Research Hospital and Avicenne Hospital) with tracheal stenosis between March 2020 and May 2022 and grouped according to SAR-CoV-2 infection status. All patients underwent a radiological and endoscopic evaluation followed by multidisciplinary team consultation. Follow-up was performed through quarterly outpatient consultation. Clinical findings and outcomes were analyzed by using SPPS software. A significance level of 5% (p < 0.05) was adopted for comparisons. RESULTS: A total of 59 patients with a mean age of 56.4 (±13.4) years were surgically managed. Tracheal stenosis was COVID related in 36 (61%) patients. Obesity was frequent in the COVID-19 group (29.7 ± 5.4 vs. 26.9 ± 3, p = 0.043) while no difference was found regarding age, sex, number, and types of comorbidities between the two groups. In the COVID-19 group, orotracheal intubation lasted longer (17.7 ± 14.5 vs. 9.7 ± 5.8 days, p = 0.001), tracheotomy (80%, p = 0.003) as well as re-tracheotomy (6% of cases, p = 0.025) were more frequent and tracheotomy maintenance was longer (21.5 ± 11.9 days, p = 0.006) when compared to the non-COVID group. COVID-19 stenosis was located more distal from vocal folds (3.0 ± 1.86 vs. 1.8 ± 2.03 cm) yet without evidence of a difference (p = 0.07). The number of tracheal rings involved was lower in the non-COVID group (1.7 ± 1 vs. 2.6 ± 0.8 p = 0.001) and stenosis were more frequently managed by rigid bronchoscopy (74% vs. 47%, p = 0.04) when compared to the COVID-19 group. Finally, no difference in recurrence rate was detected between the groups (35% vs. 15%, p = 0.18). CONCLUSIONS: Obesity, a longer time of intubation, tracheostomy, re-tracheostomy, and longer decannulation time occurred more frequently in COVID-related tracheal stenosis. These events may explain the higher number of tracheal rings involved, although we cannot exclude the direct role of SARS-CoV-2 infection in the genesis of tracheal stenosis. Further studies with in vitro/in vivo models will be helpful to better understand the role of inflammatory status caused by SARS-CoV-2 in upper airways.

Muscle and Muscle-like Autoantigen Expression in Myasthenia Gravis Thymus: Possible Molecular Hint for Autosensitization.

The thymus is widely recognized as an immunological niche where autoimmunity against the acetylcholine receptor (AChR) develops in myasthenia gravis (MG) patients, who mostly present thymic hyperplasia and thymoma. Thymoma-associated MG is frequently characterized by autoantibodies to the muscular ryanodine receptor 1 (RYR1) and titin (TTN), along with anti-AChR antibodies. By real-time PCR, we analyzed muscle-CHRNA1, RYR1, and TTN-and muscle-like-NEFM, RYR3 and HSP60-autoantigen gene expression in MG thymuses with hyperplasia and thymoma, normal thymuses and non-MG thymomas, to check for molecular changes potentially leading to an altered antigen presentation and autoreactivity. We found that CHRNA1 (AChR-α subunit) and AIRE (autoimmune regulator) genes were expressed at lower levels in hyperplastic and thymoma MG compared to the control thymuses, and that the RYR1 and TTN levels were decreased in MG versus the non-MG thymomas. Genes encoding autoantigens that share epitopes with AChR-α (NEFM and HSP60), RYR1 (neuronal RYR3), and TTN (NEFM) were up-regulated in thymomas versus hyperplastic and control thymuses, with distinct molecular patterns across the thymoma histotypes that could be relevant for autoimmunity development. Our findings support the idea that altered muscle autoantigen expression, related with hyperplastic and neoplastic changes, may favor autosensitization in the MG thymus, and that molecular mimicry involving tumor-related muscle-like proteins may be a mechanism that makes thymoma prone to developing MG.

Phenotypic diversity of T cells in human primary and metastatic brain tumors revealed by multiomic interrogation.

The immune-specialized environment of the healthy brain is tightly regulated to prevent excessive neuroinflammation. However, after cancer development, a tissue-specific conflict between brain-preserving immune suppression and tumor-directed immune activation may ensue. To interrogate potential roles of T cells in this process, we profiled these cells from individuals with primary or metastatic brain cancers via integrated analyses on the single-cell and bulk population levels. Our analysis revealed similarities and differences in T cell biology between individuals, with the most pronounced differences observed in a subgroup of individuals with brain metastasis, characterized by accumulation of CXCL13-expressing CD39+ potentially tumor-reactive T (pTRT) cells. In this subgroup, high pTRT cell abundance was comparable to that in primary lung cancer, whereas all other brain tumors had low levels, similar to primary breast cancer. These findings indicate that T cell-mediated tumor reactivity can occur in certain brain metastases and may inform stratification for treatment with immunotherapy.

Acquisition of suppressive function by conventional T cells limits antitumor immunity upon Treg depletion.

Regulatory T (Treg) cells contribute to immune homeostasis but suppress immune responses to cancer. Strategies to disrupt Treg cell-mediated cancer immunosuppression have been met with limited clinical success, but the underlying mechanisms for treatment failure are poorly understood. By modeling Treg cell-targeted immunotherapy in mice, we find that CD4+ Foxp3- conventional T (Tconv) cells acquire suppressive function upon depletion of Foxp3+ Treg cells, limiting therapeutic efficacy. Foxp3- Tconv cells within tumors adopt a Treg cell-like transcriptional profile upon ablation of Treg cells and acquire the ability to suppress T cell activation and proliferation ex vivo. Suppressive activity is enriched among CD4+ Tconv cells marked by expression of C-C motif receptor 8 (CCR8), which are found in mouse and human tumors. Upon Treg cell depletion, CCR8+ Tconv cells undergo systemic and intratumoral activation and expansion, and mediate IL-10-dependent suppression of antitumor immunity. Consequently, conditional deletion of Il10 within T cells augments antitumor immunity upon Treg cell depletion in mice, and antibody blockade of IL-10 signaling synergizes with Treg cell depletion to overcome treatment resistance. These findings reveal a secondary layer of immunosuppression by Tconv cells released upon therapeutic Treg cell depletion and suggest that broader consideration of suppressive function within the T cell lineage is required for development of effective Treg cell-targeted therapies.