Diverse Tumor Types Research Articles

Trop2-Targeted Molecular Imaging in Solid Tumors: Current Advances and Future Outlook.

Trophoblast cell surface antigen 2 (Trop2), a transmembrane glycoprotein, plays a dual role in physiological and pathological processes. In healthy tissues, Trop2 facilitates development and orchestrates intracellular calcium signaling. However, its overexpression in numerous solid tumors shifts its function toward driving cell proliferation and metastasis, thus leading to a poor prognosis. The clinical relevance of Trop2 is underscored by its utility as both a biomarker for diagnostic imaging and a target for therapy. Notably, the U.S. Food and Drug Administration (FDA) has approved sacituzumab govitecan (SG), a novel Trop2-targeted agent, for treating triple-negative breast cancer (TNBC) and refractory urothelial cancer, highlighting the significance of Trop2 in clinical oncology. Molecular imaging, a powerful tool for visualizing and quantifying biological phenomena at the molecular and cellular levels, has emerged as a critical technique for studying Trop2. This approach encompasses various modalities, including optical imaging, positron emission tomography (PET), single photon emission computed tomography (SPECT), and targeted antibodies labeled with radioactive isotopes. Incorporating Trop2-targeted molecular imaging into clinical practice is vital for the early detection, prognostic assessment, and treatment planning of a broad spectrum of solid tumors. Our review captures the latest progress in Trop2-targeted molecular imaging, focusing on both diagnostic and therapeutic applications across diverse tumor types, including lung, breast, gastric, pancreatic, prostate, and cervical cancers, as well as salivary gland carcinomas. We critically evaluate the current state by examining the relevant applications, diagnostic accuracy, therapeutic efficacy, and inherent limitations. Finally, we analyze the challenges impeding widespread clinical application and offer insights into strategies for advancing the field, thereby guiding future research endeavors.

Multi‐omics graph convolutional networks for digestive system tumour classification and early‐late stage diagnosis

AbstractThe prevalence of digestive system tumours (DST) poses a significant challenge in the global crusade against cancer. These neoplasms constitute 20% of all documented cancer diagnoses and contribute to 22.5% of cancer‐related fatalities. The accurate diagnosis of DST is paramount for vigilant patient monitoring and the judicious selection of optimal treatments. Addressing this challenge, the authors introduce a novel methodology, denominated as the Multi‐omics Graph Transformer Convolutional Network (MGTCN). This innovative approach aims to discern various DST tumour types and proficiently discern between early‐late stage tumours, ensuring a high degree of accuracy. The MGTCN model incorporates the Graph Transformer Layer framework to meticulously transform the multi‐omics adjacency matrix, thereby illuminating potential associations among diverse samples. A rigorous experimental evaluation was undertaken on the DST dataset from The Cancer Genome Atlas to scrutinise the efficacy of the MGTCN model. The outcomes unequivocally underscore the efficiency and precision of MGTCN in diagnosing diverse DST tumour types and successfully discriminating between early‐late stage DST cases. The source code for this groundbreaking study is readily accessible for download at https://github.com/bigone1/MGTCN.

Functional Roles of Long Non-coding RNAs on Stem Cell-related Pathways in Glioblastoma

: Long non-coding RNAs (lncRNAs), characterized by their length exceeding 200 nucleotides and lack of protein-coding capacity, are intricately associated with a wide array of cellular processes, encompassing cell invasion, differentiation, proliferation, migration, apoptosis, and regeneration. Perturbations in lncRNA expression have been observed in numerous diseases and have emerged as pivotal players in the pathogenesis of diverse tumor types. Glioblastoma, a highly malignant primary tumor of the central nervous system (CNS), remains a formidable challenge even with the advent of novel therapeutic interventions, as primary glioblastomas invariably exhibit therapy resistance and aggressive behavior. Glioblastomas can arise from progenitor cells or neuroglial stem cells, revealing profound cellular heterogeneity, notably in the form of glioblastoma stem cells (GSCs) possessing stem-like properties. Glioblastomas comprise neural precursors that harbor essential characteristics of neural stem cells (NSCs). Several signaling pathways have been implicated in the regulation of self-renewal in both cancer cells and stem cells. In addition to their involvement in therapy resistance and survival of glioblastoma, lncRNAs are implicated in the modulation of GSC behaviors through diverse pathways and the intricate regulation of various genes and proteins. This review aims to comprehensively discuss the interplay between lncRNAs, their associated pathways, and GSCs, shedding light on their potential implications in glioblastoma.

Covalent Modification of p53 by (E)-1-(4-Methylpiperazin-1-yl)-3-(5-nitrofuran-2-yl)prop-2-en-1-one.

TP53 is commonly mutated in cancer, giving rise to loss of wild-type tumor suppressor function and increases in gain-of-function oncogenic roles. Thus, inhibition of mutant p53 and reactivation of wild-type function represents a potential means to target diverse tumor types. (E)-1-(4-Methylpiperazin-1-yl)-3-(5-nitrofuran-2-yl)prop-2-en-1-one (NSC59984), first identified from a high-throughput screen, induces wild-type p53 signaling and antiproliferative effects while inhibiting mutant p53 gain-of-function activities. Here, we investigate the specific mechanism of action of NSC59984 against p53. We found that NSC59984 reacts with thiols via an unusual Michael addition at the α-carbon. Covalent modification of p53 Cys124 and Cys229 was observed both following in vitro reaction and upon treatment of cells. Finally, we used a biotinylated form of NSC59984 and, separately, thermal proteome profiling to examine off-target effects, identifying several metabolic proteins involved in cellular metabolism as potential targets. These results demonstrate that covalent modification of p53 by NSC59984 leads to increased wild-type activity and suggest that potential reaction with metabolic enzymes may contribute to antiproliferative function.

Ang-1 promotes tumorigenesis and mediates the anti-cancer effects of Artesunate on Choroidal melanoma via the regulation of Akt/mTOR signaling pathway

The impact of Ang-1 on tumors remains a subject of contention, with its mechanism of action exhibiting complexity in the progression of diverse tumor types. Ang-1 has been shown to promote the progression of glioma, glioma, esophageal and human cervical cancer, whereas it exerts inhibitory effects on the growth of breast and colon cancer. However, the specific function of Ang-1 in CM has not been clarified. This research aims to explore the function of Ang-1 on CM and the underlying mechanism. WB and qPCR were utilized to measure the expression levels of different factors in CM cells. Clonogenic, CCK-8 and Transwell migration assay were used to probe CM cells’ proliferation and migration ability. Xenograft tumor model was used to testify the effect of Ang-1 and Artesunate (ART) on the growth of CM in vivo. We found Ang-1 promoted CM proliferation and migration, while it was inhibited by ART in vitro. Moreover, both ART treatment and Ang-1 knockdown had the effect of suppressing tumor growth in CM xenograft model. Mechanically, Ang-1 activated Akt/mTOR pathway and induced epithelial-mesenchymal transition (EMT) in CM cells. Furthermore, ART regulated Akt/mTOR pathway by decreasing the expression of Ang-1 in CM cells. Ang-1 promotes tumorigenesis of CM by regulating Akt/mTOR pathway, which can be inhibited by ART.

Real-Life Experience with Entrectinib in Neurotrophic Tyrosine Receptor Kinase Fusion-Positive Solid Tumors: A Multicenter Retrospective Trial.

Neurotrophic tyrosine receptor kinase (NTRK) gene fusions represent rare somatic mutations in many types of cancer and have enabled the use of promising targeted therapies. In clinical studies, increased response rates to tropomyosin receptor kinase inhibitors have been demonstrated in NTRK fusion-positive cancer types; however, real-world experiences on these targeted agents are scarce. We evaluated the clinical characteristics and treatment responses of NTRK fusion-positive patients who received entrectinib treatment within the scope of an early access program in Turkey. This multicenter, retrospective analysis involved 17 patients with solid tumors harboring NTRK fusions or rearrangements from 14 oncology centers between June 2019 and 31 March 2024. Demographic and clinical data were obtained via retrospective review of medical records with a cutoff date of 31 March 2024. The median age at diagnosis of the patients in our study was 42 [interquartile range (IQR) 33-60] years. Nine different types of solid tumors were diagnosed in these patients. The most common NTRK gene rearrangements involved NTRK1 (n=8), followed by NTRK3 (n=7). The median duration of entrectinib usage was 6.9 (IQR 3.1-16.1) months. Dose reductions due to side effects were performed in four patients: two due to leukopenia, one due to visual disturbance, and one due to troponin elevation. Leukopenia was the most commonly observed side effect. The objective response rate (ORR) was 35.3% (95% confidence interval (CI) 14.2-62.7), with complete response (CR) achieved in four patients. The duration of response (DOR) in patients who responded after initiating entrectinib was 9.8 (95% CI 0-30.7) months, the median overall survival (mOS) in all patients was 20.8 (95% CI 0-48.5) months, and the time-to-treatment failure (TTF) was 6.4 (95% CI 0-13.5) months. In this retrospective study, we aimed to obtain real-world data concerning the use of entrectinib in patients with solid tumors harboring NTRK fusion genes. Although our findings are partially similar to the results of clinical studies, prospective studies in larger patient groups with more diverse tumor types and different demographic characteristics are needed to confirm the findings.

WDR77 in Pan-Cancer: Revealing expression patterns, genetic insights, and functional roles across diverse tumor types, with a spotlight on colorectal cancer

ObjectiveDespite its involvement in regulating various cellular functions, the expression and role of WD repeat-containing protein 77 (WDR77) in cancer remain elusive. This study aims to explore the expression and potential roles of WDR77 across multiple cancers, with a particular focus on its relevance in colorectal cancer (CRC). MethodsWe obtained WDR77 RNA-seq data, mutations, CNVs, and DNA methylation data from the TCGA, GTEx, and GEO databases to investigate its expression patterns and prognostic value. Additionally, we examined the correlation between WDR77 expression and somatic mutations, copy number variations, DNA methylation, and mRNA modifications. We utilized GSVA, GSEA algorithms, and CRISPR KO data from the Dependency Map database to explore WDR77′s potential biological functions. The association between WDR77 and the tumor immune microenvironment was investigated using ESTIMATE and IOBR algorithms. Finally, we assessed WDR77 expression in CRC and its impact on cell proliferation through qRT-PCR, Western blotting, immunohistochemistry, CCK8, colony formation, and EdU assays. ResultsWDR77 was upregulated in various tumors and correlated with poor patient prognosis. Its high expression positively correlated with pathways related to cell proliferation and negatively correlated with immune-related pathways. In CRC, WDR77 expression was associated with specific clinical features, genomic alterations, and immune microenvironment characteristics. Experimental validation confirmed upregulated WDR77 expression in CRC tissues and cells, with WDR77 knockdown significantly inhibiting CRC cell proliferation. ConclusionWDR77 holds potential as an oncogene and biological marker in various cancers, particularly CRC.

MDH2 regulates the sensitivity of clear cell renal cell carcinoma to ferroptosis through its interaction with FSP1

Malate dehydrogenase 2 is a pivotal enzyme in the tricarboxylic acid cycle. Recent studies have highlighted the significant involvement of MDH2 in the pathogenesis and progression of diverse types of tumors, yet its precise mechanistic underpinnings remain elusive. This study revealed a significant decrease in MDH2 expression in renal cancer tissues. And knocking out MDH2 was observed to hinder the proliferation of normal renal tubular epithelial cells but notably enhance the proliferation of ccRCC. Furthermore, mechanistically, we found that MDH2 inhibits the proliferation of ccRCC by promoting ferroptosis, while enhancing the sensitivity of ccRCC to ferroptosis inducers, promoting lipid peroxidation. We also demonstrated that MDH2 regulates the ubiquitination of FSP1 through protein-protein interactions, leading to a decrease in FSP1 protein levels and maintaining high sensitivity of ccRCC to ferroptosis. In conclusion, our study demonstrates that the reduced MDH2 expression in ccRCC results in increased expression of FSP1, thereby reducing its sensitivity to ferroptosis. It unveils a non-metabolic role for the downregulation of MDH2 in ccRCC progression.

Genes Co-Expressed with ESR2 Influence Clinical Outcomes in Cancer Patients: TCGA Data Analysis.

ERβ has been assigned a tumor suppressor role in many cancer types. However, as conflicting findings emerge, ERβ's tissue-specific expression and functional role have remained elusive. There remains a notable gap in compact and comprehensive analyses of ESR2 mRNA expression levels across diverse tumor types coupled with an exploration of its potential gene network. In this study, we aim to address these gaps by presenting a comprehensive analysis of ESR2 transcriptomic data. We distinguished cancer types with significant changes in ESR2 expression levels compared to corresponding healthy tissue and concluded that ESR2 influences patient survival. Gene Set Enrichment Analysis (GSEA) distinguished molecular pathways affected by ESR2, including oxidative phosphorylation and epithelial-mesenchymal transition. Finally, we investigated genes displaying similar expression patterns as ESR2 in tumor tissues, identifying potential co-expressed genes that may exert a synergistic effect on clinical outcomes, with significant results, including the expression of ACIN1, SYNE2, TNFRSF13C, and MDM4. Collectively, our results highlight the significant influence of ESR2 mRNA expression on the transcriptomic landscape and the overall metabolism of cancerous cells across various tumor types.

Patient-derived mini-colons enable long-term modeling of tumor-microenvironment complexity.

Existing organoid models fall short of fully capturing the complexity of cancer because they lack sufficient multicellular diversity, tissue-level organization, biological durability and experimental flexibility. Thus, many multifactorial cancer processes, especially those involving the tumor microenvironment, are difficult to study ex vivo. To overcome these limitations, we herein implemented tissue-engineering and microfabrication technologies to develop topobiologically complex, patient-specific cancer avatars. Focusing on colorectal cancer, we generated miniature tissues consisting of long-lived gut-shaped human colon epithelia ('mini-colons') that stably integrate cancer cells and their native tumor microenvironment in a format optimized for real-time, high-resolution evaluation of cellular dynamics. We demonstrate the potential of this system through several applications: a comprehensive evaluation of drug effectivity, toxicity and resistance in anticancer therapies; the discovery of a mechanism triggered by cancer-associated fibroblasts that drives cancer invasion; and the identification of immunomodulatory interactions among different components of the tumor microenvironment. Similar approaches should be feasible for diverse tumor types.

TULIPs decorate the three-dimensional genome of PFA ependymoma

Posterior fossa group A (PFA) ependymoma is a lethal brain cancer diagnosed in infants and young children. The lack of driver events in the PFA linear genome led us to search its 3D genome for characteristic features. Here, we reconstructed 3D genomes from diverse childhood tumor types and uncovered a global topology in PFA that is highly reminiscent of stem and progenitor cells in a variety of human tissues. A remarkable feature exclusively present in PFA are type B ultra long-range interactions in PFAs (TULIPs), regions separated by great distances along the linear genome that interact with each other in the 3D nuclear space with surprising strength. TULIPs occur in all PFA samples and recur at predictable genomic coordinates, and their formation is induced by expression of EZHIP. The universality of TULIPs across PFA samples suggests a conservation of molecular principles that could be exploited therapeutically.

Peer-to-peer validation of Ki-67 scoring in a pathology quality circle as a tool to assess interobserver variability: are we better than we thought?

Ki-67, a nuclear protein expressed in all stages of cellular proliferation, is a valuable tool to assess tumor proliferation and has been linked to more aggressive tumor behavior. However, interlaboratory staining heterogeneity and inter-observer variability challenge its reproducibility. Round Robin tests are a suitable tool to standardize and harmonize immunohistochemical and molecular analyses in histopathology. The study investigates the interrater and interlaboratory reproducibility of Ki-67-scoring using both manual and automated approaches. Unstained TMA slides comprising diverse tumor types (breast cancer, neuroendocrine tumors, lymphomas, and head and neck squamous cell carcinoma) were distributed to six pathology laboratories, each employing their routine staining protocols. Manual and automated scoring methods were applied, and interrater and interlaboratory agreement assessed using intraclass correlation coefficients (ICC). The results highlight good-to-excellent reliability overall, with automated scoring demonstrating higher consistency (ICC 0.955) than manual scoring (ICC 0.871). Results were more variable when looking at the individual entities. Reliability remained good for lymphomas (ICC 0.878) and breast cancer (ICC 0.784) and was poor in well-differentiated neuroendocrine tumors (ICC 0.354). This study clearly advocates standardized practices and training to ensure consistency in Ki-67-assessment, and it demonstrates that this can be achieved in a peer-to-peer approach in local quality-circles.

Clinical Correlation of Transcription Factor SOX3 in Cancer: Unveiling Its Role in Tumorigenesis.

Members of the SOX (SRY-related HMG box) family of transcription factors are crucial for embryonic development and cell fate determination. This review investigates the role of SOX3 in cancer, as aberrations in SOX3 expression have been implicated in several cancers, including osteosarcoma, breast, esophageal, endometrial, ovarian, gastric, hepatocellular carcinomas, glioblastoma, and leukemia. These dysregulations modulate key cancer outcomes such as apoptosis, epithelial-mesenchymal transition (EMT), invasion, migration, cell cycle, and proliferation, contributing to cancer development. SOX3 exhibits varied expression patterns correlated with clinicopathological parameters in diverse tumor types. This review aims to elucidate the nuanced role of SOX3 in tumorigenesis, correlating its expression with clinical and pathological characteristics in cancer patients and cellular modelsBy providing a comprehensive exploration of SOX3 involvement in cancer, this review underscores the multifaceted role of SOX3 across distinct tumor types. The complexity uncovered in SOX3 function emphasizes the need for further research to unravel its full potential in cancer therapeutics.

NSUN2/YBX1 promotes the progression of breast cancer by enhancing HGH1 mRNA stability through m5C methylation

BackgroundRNA m5C methylation has been extensively implicated in the occurrence and development of tumors. As the main methyltransferase, NSUN2 plays a crucial regulatory role across diverse tumor types. However, the precise impact of NSUN2-mediated m5C modification on breast cancer (BC) remains unclear. Our study aims to elucidate the molecular mechanism underlying how NSUN2 regulates the target gene HGH1 (also known as FAM203) through m5C modification, thereby promoting BC progression. Additionally, this study targets at preliminarily clarifying the biological roles of NSUN2 and HGH1 in BC.MethodsTumor and adjacent tissues from 5 BC patients were collected, and the m5C modification target HGH1 in BC was screened through RNA sequencing (RNA-seq) and single-base resolution m5C methylation sequencing (RNA-BisSeq). Methylation RNA immunoprecipitation-qPCR (MeRIP-qPCR) and RNA-binding protein immunoprecipitation-qPCR (RIP-qPCR) confirmed that the methylation molecules NSUN2 and YBX1 specifically recognized and bound to HGH1 through m5C modification. In addition, proteomics, co-immunoprecipitation (co-IP), and Ribosome sequencing (Ribo-Seq) were used to explore the biological role of HGH1 in BC.ResultsAs the main m5C methylation molecule, NSUN2 is abnormally overexpressed in BC and increases the overall level of RNA m5C. Knocking down NSUN2 can inhibit BC progression in vitro or in vivo. Combined RNA-seq and RNA-BisSeq analysis identified HGH1 as a potential target of abnormal m5C modifications. We clarified the mechanism by which NSUN2 regulates HGH1 expression through m5C modification, a process that involves interactions with the YBX1 protein, which collectively impacts mRNA stability and protein synthesis. Furthermore, this study is the first to reveal the binding interaction between HGH1 and the translation elongation factor EEF2, providing a comprehensive understanding of its ability to regulate transcript translation efficiency and protein synthesis in BC cells.ConclusionsThis study preliminarily clarifies the regulatory role of the NSUN2-YBX1-m5C-HGH1 axis from post-transcriptional modification to protein translation, revealing the key role of abnormal RNA m5C modification in BC and suggesting that HGH1 may be a new epigenetic biomarker and potential therapeutic target for BC.

EVEREST-2: A seamless phase 1/2 study of A2B694, a mesothelin (MSLN) logic-gated Tmod CAR T-cell therapy, in patients with solid tumors that show MSLN expression and human leukocyte antigen (HLA)-A*02 loss of heterozygosity (LOH).

TPS2699 Background: Despite the success in hematologic cancers, chimeric antigen receptor (CAR) T-cell therapies are challenging to implement in solid tumors owing to a lack of tumor-specific targets that discriminate cancer from normal cells. MSLN expression normally is limited to the mesothelium of major body cavities but can be upregulated in diverse solid tumor types (TCGA 2022), making it a potential target for cancer therapy. MSLN-targeted cell approaches, including CAR T-cell and T-cell receptor fusion therapies, have shown promising clinical activity; however, on-target, off-tumor toxicity including fatal events have occurred (1-3). A2B694 is an autologous logic-gated, MSLN-targeted Tmod CAR T-cell therapy that addresses the challenges of on-target, off-tumor toxicity by combining 2 CARs: an activating and blocking receptor. The activator recognizes MSLN present on the surface of both tumor and normal cells; the blocker binds HLA-A*02 and prevents CAR T-cell activity. Thus, in patients with both germline HLA-A*02 and tumor-associated HLA-A*02 LOH, the blocker prevents on-target, off-tumor toxicity on normal cells owing to retained HLA-A*02 expression (4). Through this unique discriminatory mechanism, A2B694 may provide a therapeutic window to treat patients with MSLN-expressing solid tumors exhibiting HLA-A*02 LOH. Methods: EVEREST-2 (NCT06051695) is a first-in-human, phase 1/2, open-label, nonrandomized study to evaluate the safety and efficacy of A2B694 in adults with recurrent unresectable, locally advanced, or metastatic cancers with MSLN expression, including non-small cell lung cancer, colorectal cancer, pancreatic cancer, ovarian cancer, mesothelioma, or other solid tumors with MSLN expression. Eligible patients should have received ≥1 line of prior therapy such as checkpoint inhibitor, molecular targeted, or chemotherapy. Enrollment to EVEREST-2 occurs through the prescreening study BASECAMP-1 (NCT04981119), which identifies patients with tumor-associated HLA-A*02 LOH via next-generation sequencing (Tempus AI, Inc.). Eligible patients enroll in the BASECAMP-1 study and undergo leukapheresis. A2B694 is manufactured from cryopreserved T cells when clinically appropriate for patients. The primary objective of phase 1 is to evaluate the safety and tolerability of A2B694 and identify the recommended phase 2 dose (RP2D). The dose-expansion phase will confirm RP2D and collect biomarker data to further characterize A2B694. Phase 2 will assess overall response rate per RECIST v1.1. 1. Beatty, et al. Gastroenterology. 2018. 2. Haas, et al. Mol Ther. 2023. 3. Hong, et al. ESMO 2021. Abstract 9590. 4. Hamburger, et al. Mol Immunol. 2020. Clinical trial information: NCT06051695 .

Nationwide Real-World Data of Microsatellite Instability and/or Mismatch Repair Deficiency in Cancer: Prevalence and Testing Patterns.

Determination of microsatellite instability (MSI)/mismatch repair (MMR) status in cancer has several clinical implications. Our aim was to integrate MSI/MMR status from patients tested in Greece to assess the prevalence of MSI-high (MSI-H)/deficient MMR (dMMR) per tumor type, testing patterns over time and concordance between MSI and MMR status. We retrospectively recorded MSI/MMR testing data of patients with diverse tumor types performed in pathology and molecular diagnostics laboratories across Greece. Overall, 18 of 22 pathology and/or molecular diagnostics laboratories accepted our invitation to participate. In the 18 laboratories located across the country, 7916 tumor samples were evaluated for MSI/MMR status. MSI/MMR testing significantly increased in patients with colorectal cancer (CRC) and other tumor types overtime (p < 0.05). The highest prevalence was reported in endometrial cancer (47 of 225 patients, 20.9%). MSI-H/dMMR was observed in most tumor types, even in low proportions. Among 904 tumors assessed both for MSI and MMR status, 21 had discordant results (overall discordance rate, 2.3%). We reported MSI-H/dMMR prevalence rates in patients with diverse cancers, while demonstrating increasing referral patterns from medical oncologists in the country overtime. The anticipated high rate of concordance between MSI and MMR status in paired analysis was confirmed.

Integrated approach of federated learning with transfer learning for classification and diagnosis of brain tumor

Brain tumor classification using MRI images is a crucial yet challenging task in medical imaging. Accurate diagnosis is vital for effective treatment planning but is often hindered by the complex nature of tumor morphology and variations in imaging. Traditional methodologies primarily rely on manual interpretation of MRI images, supplemented by conventional machine learning techniques. These approaches often lack the robustness and scalability needed for precise and automated tumor classification. The major limitations include a high degree of manual intervention, potential for human error, limited ability to handle large datasets, and lack of generalizability to diverse tumor types and imaging conditions.To address these challenges, we propose a federated learning-based deep learning model that leverages the power of Convolutional Neural Networks (CNN) for automated and accurate brain tumor classification. This innovative approach not only emphasizes the use of a modified VGG16 architecture optimized for brain MRI images but also highlights the significance of federated learning and transfer learning in the medical imaging domain. Federated learning enables decentralized model training across multiple clients without compromising data privacy, addressing the critical need for confidentiality in medical data handling. This model architecture benefits from the transfer learning technique by utilizing a pre-trained CNN, which significantly enhances its ability to classify brain tumors accurately by leveraging knowledge gained from vast and diverse datasets.Our model is trained on a diverse dataset combining figshare, SARTAJ, and Br35H datasets, employing a federated learning approach for decentralized, privacy-preserving model training. The adoption of transfer learning further bolsters the model’s performance, making it adept at handling the intricate variations in MRI images associated with different types of brain tumors. The model demonstrates high precision (0.99 for glioma, 0.95 for meningioma, 1.00 for no tumor, and 0.98 for pituitary), recall, and F1-scores in classification, outperforming existing methods. The overall accuracy stands at 98%, showcasing the model’s efficacy in classifying various tumor types accurately, thus highlighting the transformative potential of federated learning and transfer learning in enhancing brain tumor classification using MRI images.

Brain Tumor and Lung Disease Detection using Deep Learning

Brain Tumor and Lung Disease Detection using Deep Learning stands at the forefront of medical innovation, revolutionizing diagnostics with cutting-edge technology. Leveraging intricate algorithms and convolutional neural networks (CNNs), it automates the analysis of MRI scans for brain tumors and chest CT-Scans for lung diseases. Through meticulous feature extraction, this system precisely identifies diverse tumor types like glioma, meningioma, and pituitary tumors, along with lung pathologies such as bacterial pneumonia, viral pneumonia, and tuberculosis. By harnessing the power of deep learning, this ambitious project aims to significantly enhance diagnostic efficiency and accuracy, ushering in a new era in medical practice. Beyond expediting diagnoses, it holds promise in tailoring treatment strategies for improved patient care and treatment outcomes across neurology and pulmonology. Keywords: Brain Tumor Detection, Lung Disease Identification, Advanced Medical Diagnostics, Convolutional neural networks, Neural Network-based Diagnosis, Medical Diagnostics.

Research progress on venous thrombosis development in patients with malignant tumors.

The coexistence of venous thromboembolism (VTE) within patients with cancer, known as cancer-associated thrombosis (CAT), stands as a prominent cause of mortality in this population. Over recent years, the incidence of VTE has demonstrated a steady increase across diverse tumor types, influenced by several factors such as patient management, tumor-specific risks, and treatment-related aspects. Furthermore, mutations in specific genes have been identified as potential contributors to increased CAT occurrence in particular cancer subtypes. We conducted an extensive review encompassing pivotal historical and ongoing studies on CAT. This review elucidates the risks, mechanisms, reliable markers, and risk assessment methodologies that can significantly guide effective interventions in clinical practice.

Molecular phenotyping of small cell lung cancer using targeted cfDNA profiling of transcriptional regulatory regions.

We report an approach for cancer phenotyping based on targeted sequencing of cell-free DNA (cfDNA) for small cell lung cancer (SCLC). In SCLC, differential activation of transcription factors (TFs), such as ASCL1, NEUROD1, POU2F3, and REST defines molecular subtypes. We designed a targeted capture panel that identifies chromatin organization signatures at 1535 TF binding sites and 13,240 gene transcription start sites and detects exonic mutations in 842 genes. Sequencing of cfDNA from SCLC patient-derived xenograft models captured TF activity and gene expression and revealed individual highly informative loci. Prediction models of ASCL1 and NEUROD1 activity using informative loci achieved areas under the receiver operating characteristic curve (AUCs) from 0.84 to 0.88 in patients with SCLC. As non-SCLC (NSCLC) often transforms to SCLC following targeted therapy, we applied our framework to distinguish NSCLC from SCLC and achieved an AUC of 0.99. Our approach shows promising utility for SCLC subtyping and transformation monitoring, with potential applicability to diverse tumor types.