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A relatively healthy male patient in his 60s presented with chest pain and shortness of breath in addition to a history of significant weight loss over the preceding months. He was admitted to the hospital and investigated with a CT pulmonary angiogram, which did not demonstrate a pulmonary embolus, but he subsequently went on to have an ultrasound and CT scan because of abnormal findings. His CT demonstrated some thickening of the mid-transverse colon, and, in addition, large volume liver metastases described as innumerable and probably replacing most of the liver.Initially, his liver function tests were only mildly deranged at the presentation. Flexible sigmoidoscopy was performed, and a transverse colonic malignancy was identified and biopsied, which demonstrated an extrapulmonary small cell carcinoma (EPSCC). He was admitted for urgent chemotherapy for newly diagnosed metastatic small-cell colonic cancer; he developed tumour lysis syndrome following his first dose of chemotherapy. He continued to decline following this and died soon after his admission. Metastatic small-cell colonic cancer is a rare diagnosis which is challenging to manage due to the lack of trial evidence to drive treatment strategies. The management largely follows the pulmonary small cell cancer pathway. We, therefore, present a colonic EPSCC case outlining the diagnostic and treatment strategies for this disease.

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In recent years, there has been significant research interest in the field of immunotherapy for non-small cell lung cancer (NSCLC) within the academic community. Given the observed variations in individual responses, despite similarities in histopathologic type, immunohistochemical index, TNM stage, or mutation status, the identification of a reliable biomarker for early prediction of therapeutic responses is of utmost importance. Conventional medical imaging techniques primarily focus on macroscopic tumor monitoring, which may no longer adequately fulfill the requirements of clinical diagnosis and treatment. CT (computerized tomography) or PEF/CT-based radiomics has the potential to investigate the molecular-level biological attributes of tumors, such as PD-1/PD-L1 expression and tumor mutation burden, which offers a novel approach to assess the effectiveness of immunotherapy and forecast patient prognosis. The utilization of cutting-edge radiological imaging techniques, including radiomics, PET/CT, machine learning, and artificial intelligence, demonstrates significant potential in predicting diagnosis, treatment response, immunosuppressive characteristics, and immune-related adverse events. The current review highlights that CT scan-based radiomics is a reliable and feasible way to predict the benefits of immunotherapy in patients with advanced NSCLC.

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BACKGROUND: Incidental and screen-detected pulmonary nodules are common. The increasing capabilities of advanced diagnostic bronchoscopy will increase bronchoscopists' procedural volume necessitating optimization of procedural scheduling and workflow. OBJECTIVES: The objectives of this study were to determine total time in the procedure room, total bronchoscopy procedure time, and robotic-assisted bronchoscopy procedure time longitudinally and per specific procedure performed. DESIGN: A single-center observational study of all consecutive patients undergoing shape-sensing robotic-assisted bronchoscopy (RAB) biopsy procedures for the evaluation of pulmonary lesions with variable probability for malignancy. METHODS: Chart review to collect patient demographics, lesion characteristics, and procedural specifics. Descriptive and comparative statistics are reported. RESULTS: Actual bronchoscopy procedure time may decrease with increased institutional experience over time, however, there is limited ability to reduce non-bronchoscopy related time within the procedure room. The use of cone beam computed tomography (CBCT), rapid on-site evaluation (ROSE), and performance of staging endobronchial ultrasound transbronchial needle aspiration (EBUS-TBNA) in a single procedure are each associated with additional time requirements. CONCLUSION: Institutional procedural block times should adapt to the nature of advanced diagnostic bronchoscopy procedures to allow for the accommodation of new modalities such as RAB combined with other technologies including radial endobronchial ultrasound, CBCT, ROSE, and staging linear EBUS. Identifying institutional median procedural times may assist in scheduling and ideal block time utilization.

Times necessary to perform robotic assisted bronchoscopy biopsy procedures at a single hospitalBackground: Lung lesions and nodules are commonly seen on computed tomography (CT) scans. With advances in technology, more of these lesions are being biopsied with robotic assisted bronchoscopy (RAB) procedures, leading to increased demand. Health care providers who perform these procedures have finite available time in which they must accommodate all their procedures. Understanding procedure times is necessary to fully utilize schedules. Methods and aims overview: We describe our experience of 5 pulmonologists performing 700 robotic assisted bronchoscopies at a single hospital. Our aim is to describe the time needed for the robotic bronchoscopies over time and with specific procedures. Results and conclusion: We find that as more robotic assisted bronchoscopies are performed, the overall procedure time may decrease. Using cone beam computed tomography during the procedure, having on- site pathology review of biopsies, and obtaining biopsies of lymph nodes may lengthen the procedure time. The time spent preparing the patient for the procedure excluding the bronchoscopy remained stable. Understanding the time necessary based on what is performed during the procedure will allow it to be scheduled for the appropriate amount of time. As a result, procedure days can be fully optimized, minimizing scheduling impacts on patients and health care workers.

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In their letter-to-the-editor entitled "Letter to the Editor: Incidence rate of occult lymph node metastasis in clinical T1 - 2N0M0 small cell lung cancer patients and radiomic prediction based on contrast-enhanced CT imaging: a multicenter study", Prof. Chen et al. provided insightful comments and suggestions on our original study. We appreciate the authors' feedback and have conducted a preliminary exploration of the predictive value of serum tumor markers (TMs) for occult lymph node metastasis (OLM) in clinical T1 - 2N0M0 (cT1 - 2N0M0) small cell lung cancer (SCLC) patients. The results indicate that neuron-specific enolase (NSE), carbohydrate antigen 125 (CA125), and squamous cell carcinoma antigen (SCC) have potential predictive value for detecting OLM in cT1 - 2N0M0 SCLC patients. Additionally, further exploration and confirmation through prospective, large-scale studies with robust external validation are needed.

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BACKGROUD: Supernatants from various cytological samples, including body cavity effusion, sputum, bronchoalveolar lavage fluid (BALF), and needle aspiration, have been validated for detecting genetic alterations using cell-free DNA (cfDNA) in patients with non-small cell lung cancer (NSCLC). However, the sensitivity of fusion variations detection remains challenging. The protection of cell-free RNA (cfRNA) is critical for resolving the issue. METHODS: A protective solution (PS) was applied for preserving cfRNA in cytological supernatant (CS), and the quality of protected cfRNA was assessed by cycle threshold (CT) values from reverse transcription quantitative polymerase chain reaction (RT-qPCR). Furthermore, we collected an additional set of malignant cytological and matched tumor samples from 84 NSCLC patients, cfDNA & cfRNA extraction and double detection for driver gene mutations was validated using the multi-gene mutations detection by RT-qPCR. RESULTS: Under the optimal protection system, 91.0% (101/111) of cfRNA were protected effectively. Among the 84 NSCLC patient samples, seven cytological samples failed the tests. In comparison with tumor samples, the overall sensitivity and specificity of detecting driver genes of supernatant cfDNA and cfRNA were 93.8% (74/77) and 100% (77/77), respectively. Notably, when focusing exclusively on patients with fusion gene changes, both sensitivity and specificity reached 100% (11/11) for EML4-ALK, ROS1, RET fusions, and MET ex14 skipping. CONCLUSION: These findings suggest that cfDNA & cfRNA extraction and double detection strategy recommended in this study improve the accuracy of driver genes mutations test, especially for RNA-based assay.

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Cancer seems to have a vast number of deaths due to its heterogeneity, aggressiveness, and significant propensity for metastasis. The predominant categories of cancer that may affect males and females and occur worldwide are colon and lung cancer. A precise and on-time analysis of this cancer can increase the survival rate and improve the appropriate treatment characteristics. An efficient and effective method for the speedy and accurate recognition of tumours in the colon and lung areas is provided as an alternative to cancer recognition methods. Earlier diagnosis of the disease on the front drastically reduces the chance of death. Machine learning (ML) and deep learning (DL) approaches can accelerate this cancer diagnosis, facilitating researcher workers to study a vast majority of patients in a limited period and at a low cost. This research presents Histopathological Imaging for the Early Detection of Lung and Colon Cancer via Ensemble DL (HIELCC-EDL) model. The HIELCC-EDL technique utilizes histopathological images to identify lung and colon cancer (LCC). To achieve this, the HIELCC-EDL technique uses the Wiener filtering (WF) method for noise elimination. In addition, the HIELCC-EDL model uses the channel attention Residual Network (CA-ResNet50) model for learning complex feature patterns. Moreover, the hyperparameter selection of the CA-ResNet50 model is performed using the tuna swarm optimization (TSO) technique. Finally, the detection of LCC is achieved by using the ensemble of three classifiers such as extreme learning machine (ELM), competitive neural networks (CNNs), and long short-term memory (LSTM). To illustrate the promising performance of the HIELCC-EDL model, a complete set of experimentations was performed on a benchmark dataset. The experimental validation of the HIELCC-EDL model portrayed a superior accuracy value of 99.60% over recent approaches.

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Flexible technology in sensors have received much attention in monitoring of human health through various physiological indicators. Thus, it drawn a lot of interest in the development of flexible substrate for the diagnosis of various diseases via analysis of analytes. Present work focusses on the development of ecofriendly, portable, flexible, conducting thread (Th) and used as smart substrate for fabrication of biosensor towards ultrasensitive detection of the lung cancer biomarker (cytoskeleton-associated protein 4; CKAP4). The zirconium trisulfide-reduced graphene oxide nanocomposite and poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) modified cotton thread based biosensor was fabricated via dip coating method. Next, successive immobilization of monoclonal antibodies of CKAP4 (anti-CKAP4) and bovine serum albumin (BSA) was performed via drop cast approach using fabricated electrode [nZrS3@rGO/PEDOT:PSS/Th]. The response of fabricated electrode (BSA/anti-CKAP4/ZrS3@rGO/PEDOT:PSS/Th) was recorded electrochemically versus CKAP4 concentration via chronoamperometry (CA). The results showed wider linear detection range of 6.25-800 pg mL-1, excellent sensitivity of 85.2 µA[log(pg mL-1)]-1cm-2 with good stability up to 42 days. The response of fabricated biosensor was supported by investigating response of CKAP4 biomarker present in patients of lung cancer (concentration as determined through enzyme-linked immunosorbent assay) and obtained results exhibited excellent correlation with that of standard samples.

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After the publication of the original article, the authors noticed an error in the departmental affiliation of one of the contributors, Don MASCARENHAS. The corrected version of the department is provided below, and the original article has been updated accordingly. Archana BHAT < sup > 1 < /sup > , Manjunath J < sup > 1 < /sup > , Don MASCARENHAS < sup > 2 < /sup > < br / > Department of < sup > 1 < /sup > Pathology and < sup > 2 < /sup > Pulmonology, Father Muller Medical College, MANGALORE, INDIA.

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Previous studies have shown that rapid on-site evaluation (ROSE) improves the diagnostic yield of bronchoscopy using endobronchial ultrasound with a guide sheath (EBUS-GS) for peripheral pulmonary lesions (PPL). While ROSE of imprint cytology from forceps biopsy has been widely discussed, there are few reports on ROSE of brush cytology. This study investigated the utility of ROSE of brush cytology during bronchoscopy. We retrospectively analyzed data from 214 patients who underwent bronchoscopy with EBUS-GS for PPL. The patients in the ROSE group had significantly higher diagnostic sensitivity through the entire bronchoscopy process than in the non-ROSE group (96.8% vs. 83.3%, P = 0.002). The use of ROSE significantly increased the sensitivity of brush cytology with Papanicolaou staining (92.9% vs. 75.0%, P < 0.001). When ROSE was sequentially repeated on brushing specimens, initially negative ROSE results converted to positive in 79.5% of cases, and the proportion of specimens with high tumor cell counts increased from 42.1 to 69.0%. This study concludes that ROSE of brush cytology improves the diagnostic accuracy of bronchoscopy and enhances specimen quality through repeated brushing.

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BACKGROUND: In oncology, electronic health records contain textual key information for the diagnosis, staging, and treatment planning of patients with cancer. However, text data processing requires a lot of time and effort, which limits the utilization of these data. Recent advances in natural language processing (NLP) technology, including large language models, can be applied to cancer research. Particularly, extracting the information required for the pathological stage from surgical pathology reports can be utilized to update cancer staging according to the latest cancer staging guidelines. OBJECTIVES: This study has two main objectives. The first objective is to evaluate the performance of extracting information from text-based surgical pathology reports and determining pathological stages based on the extracted information using fine-tuned generative language models (GLMs) for patients with lung cancer. The second objective is to determine the feasibility of utilizing relatively small GLMs for information extraction in a resource-constrained computing environment. METHODS: Lung cancer surgical pathology reports were collected from the Common Data Model database of Seoul National University Bundang Hospital (SNUBH), a tertiary hospital in Korea. We selected 42 descriptors necessary for tumor-node (TN) classification based on these reports and created a gold standard with validation by two clinical experts. The pathology reports and gold standard were used to generate prompt-response pairs for training and evaluating GLMs which then were used to extract information required for staging from pathology reports. RESULTS: We evaluated the information extraction performance of six trained models as well as their performance in TN classification using the extracted information. The Deductive Mistral-7B model, which was pre-trained with the deductive dataset, showed the best performance overall, with an exact match ratio of 92.24% in the information extraction problem and an accuracy of 0.9876 (predicting T and N classification concurrently) in classification. CONCLUSION: This study demonstrated that training GLMs with deductive datasets can improve information extraction performance, and GLMs with a relatively small number of parameters at approximately seven billion can achieve high performance in this problem. The proposed GLM-based information extraction method is expected to be useful in clinical decision-making support, lung cancer staging and research.

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Malignant melanoma, a cancer type with a high mortality rate and increasing incidence worldwide, primarily affects the skin but can also occur in various other organs and tissues, including the respiratory tract. Although primary lung malignant melanomas are rare, they are often diagnosed at advanced stages due to their asymptomatic nature, and their atypical presentations may lead to misdiagnosis as other malignancies. In this case report, a mass lesion almost completely filling the right lung initially led to the consideration of small cell lung carcinoma, but a definitive pathological diagnosis could not be obtained in subsequent studies. The diagnosis was confirmed by soft tissue biopsy taken from the anterior thoracic wall. Considering clinical, pathological, and radiological evaluations, possible diagnoses included sarcoma, small-cell lung cancer, and melanoma. The patient, diagnosed through multiple tissue sampling and detailed dermatological examination, presents an interesting atypical case. This case highlights that rare variants of melanoma can be mistaken for other cancer types, such as lung cancer, sarcoma, or lymphoma. Patients may not always present with a noticeable skin lesion; therefore, a meticulous skin examination is crucial in such cases. Malignant melanoma is a noteworthy disease, considering its increasing incidence and early diagnosis holds vital importance for appropriate treatment and management.

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BACKGROUND: Crystalloid storage histiocytosis (CSH) is a rare clinical condition characterized by abnormally high numbers of histiocytes with a large accumulation of crystalline immunoglobulins. Due to its relative rarity, clinical diagnosis of it is frequently incomplete or incorrect. We report a case with pulmonary crystal-storing histiocytosis that was mistakenly identified as lung carcinoma. METHODS: Percutaneous lung biopsy, bronchoscopy. RESULTS: Percutaneous lung biopsy pathology shows granulomatous inflammation with massive eosinophilic infiltration, immunohistochemistry shows CD68, kappa positive, S-100, desmin, myogenin, lambda negative. The final diagnosis is pulmonary crystal-storing histiocytosis. CONCLUSIONS: To get pathology tissue for a definitive diagnosis, patients with pulmonary nodules who have changes in tumor markers or nodule size should have bronchoscopy or percutaneous lung biopsy done as soon as possible.

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Lung adenocarcinoma (LUAD) is the dominant histotype of non-small cell lung cancer. Panoptosis, a comprehensive form of programmed cell death, is central to carcinogenesis. In this study, the expression of PANoptosis-related genes (PRGs) and their impact on the development, prognosis, tumor microenvironment, and treatment response of patients with lung adenocarcinoma (LUAD) were systematically evaluated. PRGs were selected from The Cancer Genome Atlas database and Genecards dataset using differential expression analysis. The signature of included PRGs was identified using univariate Cox regression analysis and LASSO regression analysis. Additionally, a nomogram was developed that includes signature and clinical information. Kaplan-Meier survival analysis and receiver operating characteristic curves were used to assess the predictive validity of these risk models. Finally, functional analysis of the selected PRGs in signature and analysis of immune landscape were also performed. Preliminary identification of 10 genes related to PANoptosis has significant implications for prognosis. Subsequently, seven related genes were integrated to classify LUAD patients into different survival risk groups. The prognostic risk score generated from the signature and the TNM stage were as independent prognostic factors and were utilized in creating a nomogram plot. Both the features and the nomogram plot showed accurate performance in predicting the overall survival of LUAD patients. The PRGs were enriched in several biological functions and pathways, and stratified studies were conducted on the differences in immune landscape between high-risk and low-risk groups based on their characteristics. Ultimately, our evaluation focused on the differences in drug treatment efficacy between the high-risk and low-risk groups, providing a foundation for future research directions. Potential associations between PRGs and patient prognosis in LUAD have been identified in this study. Potential biomarkers for clinical application could be considered for the prognostic predictors identified in this study.

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BACKGROUND: The plasma concentrations of acyl coenzyme A binding protein (ACBP, also known as diazepam-binding inhibitor, DBI, or 'endozepine') increase with age and obesity, two parameters that are also amongst the most important risk factors for cancer. METHODS: We measured ACBP/DBI in the plasma from cancer-free individuals, high-risk patients like the carriers of TP53 or BRCA1/2 mutations, and non-syndromic healthy subjects who later developed cancer. In mice, the neutralization of ACBP/DBI was used in models of non-small cell lung cancer (NSCLC) and breast cancer development and as a combination treatment with chemoimmunotherapy (chemotherapy + PD-1 blockade) in the context of NSCLC and sarcomas. The anticancer T cell response upon ACBP/DBI neutralization was characterized by flow cytometry and single-cell RNA sequencing. RESULTS: Circulating levels of ACBP/DBI were higher in patients with genetic cancer predisposition (BRCA1/2 or TP53 germline mutations) than in matched controls. In non-syndromic cases, high ACBP/DBI levels were predictive of future cancer development, and especially elevated in patients who later developed lung cancer. In preclinical models, ACBP/DBI neutralization slowed down breast cancer and NSCLC development and enhanced the efficacy of chemoimmunotherapy in NSCLC and sarcoma models. When combined with chemoimmunotherapy, the neutralizing monoclonal antibody against ACBP/DBI reduced the frequency of regulatory T cells in the tumor bed, modulated the immune checkpoint profile, and increased activation markers. CONCLUSION: These findings suggest that ACBP/DBI acts as an endogenous immune suppressor. We conclude that elevation of ACBP/DBI constitutes a risk factor for the development of cancer and that ACBP/DBI is an actionable target for improving cancer immunosurveillance.

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BACKGROUND: Lung cancer, a major global health concern, disproportionately impacts low socioeconomic status (SES) patients, who face suboptimal care and reduced survival. This study aimed to evaluate the prognostic performance of traditional Cox proportional hazards (CoxPH) regression and machine learning models, specifically Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), and Extreme Gradient Boosting (XGBoost), in patients with advanced lung cancer with low SES. DESIGN: A retrospective study. METHOD: The 949 patients with advanced lung cancer with low SES who entered the hospice ward of a tertiary hospital in Wuhan, China, from January 2012 to December 2021 were randomized into training and testing groups in a 3:1 ratio. CoxPH regression methods and four machine learning algorithms (DT, RF, SVM, and XGBoost) were used to construct prognostic risk prediction models. RESULTS: The CoxPH regression-based nomogram demonstrated reliable predictive accuracy for survival at 60, 90, and 120 days. Among the machine learning models, XGBoost showed the best performance, whereas RF had the lowest accuracy at 60 days, DT at 90 days, and SVM at 120 days. Key predictors across all models included Karnofsky Performance Status (KPS) score, quality of life (QOL) score, and cough symptoms. CONCLUSIONS: CoxPH, DT, RF, SVM, and XGBoost models are effective in predicting mortality risk over 60-120 days in patients with advanced lung cancer with low SES. Monitoring KPS, QOL, and cough symptoms is crucial for identifying high-risk patients who may require intensified care. Clinicians should select models tailored to individual patient needs and preferences due to varying prediction accuracies. REPORTING METHOD: This study was reported in strict compliance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guideline. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution.

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