Tumor Heterogeneity Research Articles

Profiling Breast Tumor Heterogeneity and Identifying Breast Cancer Subtypes Through Tumor-Associated Immune Cell Signatures and Immuno Nano Sensors.

Breast cancer is a complex and heterogeneous disease with varying cellular, genetic, epigenetic, and molecular expressions.The detection of intratumor heterogeneity in breast cancer poses significant challenges due to its complex multifaceted characteristics, yet its identification is crucial for guiding effective treatment decisions and understanding the diseaseprogression. Currently, there exists no method capable of capturing the full extent of breast tumor heterogeneity. In this study, the aim is to identify and characterize metabolic heterogeneity in breast tumors using immune cells and an ultrafast laser-fabricated Immuno Nano Sensor.Combining spectral markers from both Natural Killer (NK)and T cells, a machine-learning approach is implemented to distinguish cancer from healthy samples, identify primary versus metastatic tumors, and determine estrogen receptor (ER)/progesterone receptor (PR) status at the single-cell level. The platform successfully distinguished heterogeneous breast cancer samples fromhealthy individuals, achieving97.8%sensitivity and92.2%specificity, andaccurately identifiedprimary tumors from metastatic tumors. Characteristic spectral signatures allow for discrimination between ER/PR-positive andnegative tumors with 97.5% sensitivity.This study demonstrates the potential of immune cell-based metabolic profiling in providing a comprehensive assessment of breast tumor heterogeneity and paving the way for minimally invasive liquid biopsy approaches in breast cancer diagnosis and management.

A comprehensive luminal breast cancer patient-derived xenografts (PDX) library to capture tumor heterogeneity and explore the mechanisms of resistance to CDK4/6 inhibitors.

Breast cancer (BC) is marked by significant genetic, morphological and clinical heterogeneity. To capture this heterogeneity and unravel the molecular mechanisms driving tumor progression and drug resistance, we established a comprehensive patient-derived xenograft (PDX) biobank, focusing particularly on luminal (estrogen receptor, ER+) and young premenopausal patients, for whom PDX models are currently scarce. Across all BC subtypes, our efforts resulted in an overall success rate of 17% (26 established PDX lines out of 151 total attempts), specifically 15% in luminal, 12% in human epidermal growth factor receptor 2 positive (HER2+) and 35% in triple negative BC. These PDX mirrored morphologic and genetic features of BC from which they originated, serving as a reliable tool to investigate drug resistance and test therapeutic strategies. We focused on understanding resistance to CDK4/6 inhibitors (CDK4/6i), which are crucial in the treatment of patients with advanced luminal BC. Treating a sensitive luminal BC PDX with the CDK4/6i palbociclib revealed that, despite initial tumor shrinkage, some tumors might eventually regrow under drug treatment. RNA sequencing, followed by gene set enrichment analyses, unveiled that these PDXs have become refractory to CDK4/6i, both at biological and molecular levels, displaying significant enrichment in proliferation pathways, such as MTORC1, E2F and MYC. Using organoids derived from these PDX (PDxO), we observed that acquisition of CDK4/6i resistance conferred cross-resistance to endocrine therapy and that targeting MTORC1 was a successful strategy to overcome CDK4/6i resistance. Considered together, these results indicate that our PDX models may serve as robust tools to elucidate the molecular basis of BC disease progression and, by providing the possibility to simultaneously test different therapies on the same tumor, to surmount treatment resistance. While this approach is of course not feasible in the clinic, its exploitation in PDX may expedite the identification and development of more successful therapies for patients with advanced luminal BC. © 2024 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Methodological aspects of correlative, multimodal, multiparametric breast cancer imaging: from data acquisition to image processing for AI-based radioproteomics in a preclinical setting

Preclinical high-field magnetic resonance imaging (MRI) systems offer a diverse array of MRI techniques, providing rich multiparametric MRI (mpMRI) platforms for studying numerous biological parameters. mpMRI platforms prove particularly indispensable when investigating tumors that exhibit profound intratumoral heterogeneity, such as breast cancer. A thoughtful comprehension of the origins of intratumoral heterogeneity is imperative for the judicious assessment of new targeted therapies and treatment interventions. Furthermore, when data from mpMRI are complemented with data from other in vivo imaging modalities, such as positron emission tomography (PET), and correlated with data from ex vivo modalities, such as matrix-assisted laser desorption imaging mass spectrometry (MALDI IMS), the in vivo parameters can be further elucidated at a molecular level and microscopic scale. Nevertheless, extracting meaningful scientific insights from such complex datasets necessitates the utilization of machine learning (ML) approaches to discern region-specific radiomic features. The development of correlative, multimodal imaging (CMI) workflows, such as one incorporating MRI, PET and MALDI IMS, is inherently challenging, given the many technological and methodological challenges related to multimodal data acquisition as well as the physiological limitations of the laboratory mice of the investigation. Standardization efforts in image acquisition and processing are required to increase the reproducibility and translatability of CMI data. To address the challenges of developing standardized CMI workflows and stimulate dialog regarding this area of need, we present a practical workflow to investigate tumor heterogeneity in breast cancer xenografts across various spatial scales. Our workflow entails simultaneous functional MRI and PET acquisitions in living mice, followed by correlation with post-imaging MALDI IMS and histologic data. Additionally, we propose data preprocessing steps for potential ML applications. We illustrate the feasibility of this workflow through two examples, showcasing its effectiveness in comparing in vivo and ex vivo images to evaluate tumor metabolism and hypoxia in mice with breast cancer xenografts.

Identification of molecular subtypes based on bile acid metabolism in cholangiocarcinoma

BackgroundCholangiocarcinoma is a highly heterogeneous tumor with bile acid metabolism involving in its development. The aim of this study was to characterize bile acid metabolism and identify specific subtypes to better stratify cholangiocarcinoma patients for individualized treatment and prognostic assessment.MethodsA total of 30 bile acids were quantified using the ultra-performance liquid chromatography tandem mass spectrometry. Using Consensus clustering, the molecular subtypes related to bile acid metabolism were identified. The prognosis, clinicopathologic characteristics, immune landscape, and therapeutic response were compared between these subtypes. The single-cell RNA sequencing (scRNA-seq) analysis and preliminary cell experiment were also conducted to verify our findings.ResultsThe altered bile acid profile and genetic variation of bile acid metabolism-related genes in cholangiocarcinoma were demonstrated. The cholangiocarcinoma was categorized into bile acid metabolism-active and -inactive subtypes with different prognoses, clinicopathologic characteristics, tumor microenvironments (TME) and therapeutic responses. This categorization was reproducible and predictable. Specifically, the bile acid metabolism-active subtype showed a poor prognosis with an immunosuppressive microenvironment and an inactive response to immunotherapy, while the bile acid metabolism-inactive subtype showed the opposite characteristics. Moreover, the scRNA-seq revealed that immunotherapy altered bile acid metabolism in TME of cholangiocarcinoma. Finally, a prognostic signature related to bile acid metabolism was developed, which exhibited strong power for prognostic assessment of cholangiocarcinoma. Consistently, these results were verified by immunohistochemistry, cell proliferation, migration, and apoptosis assays.ConclusionIn conclusion, a novel cholangiocarcinoma classification based on bile acid metabolism was established. This classification was significant for the estimation of TME and prognosis.

Identification and validation of M2 macrophage-related gene signature as a novel prognostic model for head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC) is a highly heterogeneous tumor. Commonly used tumor staging don’t sufficiently and accurately assess the prognosis of HNSCC patients, resulting in a lack of guidance for clinical treatment decisions. M2 macrophage infiltration has been shown to be strongly associated with the tumor prognosis. In this study, we used the Cancer Genome Atlas (TCGA) data to screen for genes co-expressed with M2 macrophages in HNSCC. We used univariate Cox regression to screen out the genes associated with HNSCC prognosis, and constructed a HNSCC prognosis model by Lasso regression analysis. The results confirmed that the model had good predictive value and accuracy for the prognosis of HNSCC patients by survival analysis, ROC curve and nomogram. We divided the HNSCC samples into high-risk and low-risk groups according to the risk score, and the results showed that patients in the high-risk group were more prone to genetic mutations and had a higher tumor mutational burden. In addition, there were significant differences between risk groups in terms of immune cell infiltration and drug sensitivity. The HNSCC prognostic model established in this study may provide guidance for clinical therapeutic decision-making and provide a theoretical foundation for the development of new immunotherapy methods.

Bone mineral density affects tumor growth by shaping microenvironmental heterogeneity

Breast cancer bone metastasis is a major cause of mortality in patients with advanced breast cancer. Although decreased mineral density is a known risk factor for bone metastasis, the underlying mechanisms remain poorly understood because studying the isolated effect of bone mineral density on tumor heterogeneity is challenging with conventional approaches. Moreover, mineralized biomaterials are commonly utilized for clinical bone defect repair, but how mineralized biomaterials affect the foreign body response and wound healing is unclear. Here, we investigate how bone mineral affects tumor growth and microenvironmental complexity in vivo by combining single-cell RNA-sequencing with mineral-containing or mineral-free decellularized bone matrices. We discover that the absence of bone mineral significantly influences fibroblast and immune cell heterogeneity, promoting phenotypes that increase tumor growth and alter the response to injury or disease. Importantly, we observe that the stromal response to bone mineral content depends on the murine tumor model used. While lack of bone mineral induces tumor-promoting microenvironments in both immunocompromised and immunocompetent animals, these changes are mediated by altered fibroblast phenotype in immunocompromised mice and macrophage polarization in immunocompetent mice. Collectively, our findings suggest that bone mineral density affects tumor growth by impacting microenvironmental complexity in an organism-dependent manner.

Deciphering the landscape of triple negative breast cancer from microenvironment dynamics and molecular insights to biomarker analysis and therapeutic modalities.

Triple negative breast cancer (TNBC) displays a notable challenge in clinical oncology due to its invasive nature which is attributed to the absence of progesterone receptor (PR), estrogen receptor (ER), and human epidermal growth factor receptor (HER-2). The heterogenous tumor microenvironment (TME) of TNBC is composed of diverse constituents that intricately interact to evade immune response and facilitate cancer progression and metastasis. Based on molecular gene expression, TNBC is classified into four molecular subtypes: basal-like (BL1 and BL2), luminal androgen receptor (LAR), immunomodulatory (IM), and mesenchymal. TNBC is an aggressive histological variant with adverse prognosis and poor therapeutic response. The lack of response in most of the TNBC patients could be attributed to the heterogeneity of the disease, highlighting the need for more effective treatments and reliable prognostic biomarkers. Targeting certain signaling pathways and their components has emerged as a promising therapeutic strategy for improving patient outcomes. In this review, we have summarized the interactions among various components of the dynamic TME in TNBC and discussed the classification of its molecular subtypes. Moreover, the purpose of this review is to compile and provide an overview of the most recent data about recently discovered novel TNBC biomarkers and targeted therapeutics that have proven successful in treating metastatic TNBC. The emergence of novel therapeutic strategies such as chemoimmunotherapy, chimeric antigen receptor (CAR)-T cells-based immunotherapy, phytometabolites-mediated natural therapy, photodynamic and photothermal approaches have made a significant positive impact and have paved the way for more effective interventions.

Single-cell omics and machine learning integration to develop a polyamine metabolism-based risk score model in breast cancer patients

BackgroundBreast cancer remains the leading malignant neoplasm among women globally, posing significant challenges in terms of treatment and prognostic evaluation. The metabolic pathway of polyamines is crucial in breast cancer progression, with a strong association to the increased capabilities of tumor cells for proliferation, invasion, and metastasis.MethodsWe used a multi-omics approach combining bulk RNA sequencing and single-cell RNA sequencing (scRNA-seq) to study polyamine metabolism. Data from The Cancer Genome Atlas, Gene Expression Omnibus, and Genotype-Tissue Expression identified 286 differentially expressed genes linked to polyamine pathways in breast cancer. These genes were analyzed using univariate COX and machine learning algorithms to develop a prognostic scoring algorithm. Single-cell RNA sequencing validated the model by examining gene expression heterogeneity at the cellular level.ResultsOur single-cell analyses revealed distinct subpopulations with different expressions of genes related to polyamine metabolism, highlighting the heterogeneity of the tumor microenvironment. The SuperPC model (a constructed risk score) demonstrated high accuracy when predicting patient outcomes. The immune profiling and functional enrichment analyses revealed that the genes identified play a crucial role in cell cycle control and immune modulation. Single-cell validation confirmed that polyamine metabolism genes were present in specific cell clusters. This highlights their potential as therapeutic targets.ConclusionsThis study integrates single cell omics with machine-learning to develop a robust scoring model for breast cancer based on polyamine metabolic pathways. Our findings offer new insights into tumor heterogeneity, and a novel framework to personalize prognosis. Single-cell technologies are being used in this context to enhance our understanding of the complex molecular terrain of breast cancer and support more effective clinical management.

Current Drug Resistance Mechanisms and Treatment Options in Gastrointestinal Stromal Tumors: Summary and Update.

Gastrointestinal stromal tumor (GIST) is characterized by well-defined oncogenes. Despite the significant improvement in treatment outcomes with adjuvant imatinib therapy for patients, drug resistance remains a major challenge for GIST therapy. This review focuses on the mechanisms contributing to drug resistance phenotype in GIST, such as primary imatinib-resistant mutants, secondary mutations, non-covalent binding of TKI to its target, tumor heterogeneity, re-activation of pro-survival/proliferation pathways through non-KIT/PDGFRA kinases, and loss of therapeutic targets in wild-type GIST. Corresponding suggestions are proposed to overcome drug-resistance phenotype of GIST. This review also summarizes the suitability of currently approved TKIs on different KIT/PDGFRA mutations and updates related clinical trials. Recent potent drugs and emerging strategies against advanced GISTs in clinical trials are presented. Additionally, metabolic intervention offers a new avenue for clinical management in GIST. A landscape of metabolism in GIST and metabolic changes under imatinib treatment are summarized based on currently published data. The OXPHOS pathway is a promising therapeutic target in combination with TKI against sensitive KIT/PDGFRA mutants. Comprehensive understanding of the above resistance mechanisms, experimental drugs/strategies and metabolic changes is critical to implement the proper therapy strategy and improve the clinical therapy outcomes for GIST.

Prognosis prediction of head and neck squamous cell carcinoma through the basement membrane-related lncRNA risk model

BackgroundHead and neck squamous cell carcinoma (HNSCC) ranks among the most widespread and significantly heterogeneous malignant tumors globally. Increasing evidence suggests that the basement membrane (BM) and associated long non-coding RNAs (lncRNA) are correlated with the onset of HNSCC and its prognosis. Our study aims to construct a basement membrane-associated lncRNAs (BMlncRNAs) marker to accurately predict the prognosis of HNSCC patients and find novel immunotherapy targets.MethodsThe Cancer Genome Atlas (TCGA) database was accessed to acquire the transcriptome expression matrices, somatic mutation data, and clinical follow-up data of HNSCC patients. Utilizing co-expression analysis, the BMlncRNAs were identified and the differentially expressed lncRNAs (DEBMlncRNA) were then filtered, The filtering thresholds are FDR<0.05 and |log2FC|≥1. Furthermore, univariate analysis, least absolute shrinkage and selection operator (LASSO), and multivariable Cox regression were utilized to develop the risk model. The model then underwent thorough evaluation across diverse perspectives, encompassing tumor immune infiltration, tumor mutation burden (TMB), functional enrichment, and chemotherapy sensitivity.ResultsThe risk assessment model consists of 14 BMlncRNA pairs. The acquired data is indicative of the reliability of the risk score in its capacity as a prognostic factor. Individuals at high risk exhibited a poorer prognosis, and a statistically significant variance was noted in TMB and tumor immune infiltration compared to the low-risk group. Additionally, heightened sensitivity to paclitaxel and docetaxel was evident in the patients at high risk.ConclusionWe have established a BMLncRNA-based prognostic model that can provide clinical guidance for future laboratory and clinical studies of HNSCC.

Chinese multidisciplinary expert consensus on the rational use of surufatinib in clinical practice（2024 edition）

Neuroendocrine neoplasms are a group of heterogeneous tumors originating from the neuroendocrine system, which can occur in any part of the body. Pulmonary and gastroenteropancreatic neuroendocrine tumors are the most common. In recent years, the global incidence of neuroendocrine tumors has increased more significantly than other types of tumors, especially in the past 40 years. The drug treatment of neuroendocrine tumors includes somatostatin analogues, anti-angiogenesis targeting drugs, nuclide therapy and chemotherapy. Surufatinib is an oral tyrosine kinase receptor inhibitors that targets for vascular endothelial growth factor receptor (VEGFR1-3), fibroblast growth factor receptor 1 (FGFR1), and colony-stimulating factor-1 receptor (CSF-1R), has received approval in 2020 and 2021 for the treatment of locally advanced or metastatic, progressive nonfunctional, well-differentiated (G1, G2) neuroendocrine tumors (NETs) of both pancreatic and extrapancreatic origin that are unresectable. Ongoing exploratory studies are investigating its potential application in other tumor types. Common adverse reactions observed during surufatinib treatment include hypertension, proteinuria, bleeding events, and hepatic lab test abnormal and diarrhea. Chinese multidisciplinary expert consensus on the rational use of surufatinib in clinical practice (2024 edition) aims to provide standardized guidance for its rational use and enhance patient compliance to maximize therapeutic benefits.

Mechanobiology studies of bladder tumor cells using laterally squeezing microfluidic flow cytometry

The deformability and uptake capability of cells are critical indicators of their biomechanical properties and functional behaviors, particularly in tumor heterogeneity and cancer research. Here, we introduce a microfluidic flow cytometry platform integrated with a laterally adjustable squeezing structure for the characterization of bladder tumor cells (including 5637 and EJ cell lines) and uroepithelial cells (SV-HUC-1 cell line). The deformability of these cell types under varying channel width conditions was clearly assessed using this platform. The results demonstrated that tumor cells exhibited higher deformability compared to uroepithelial cells, with the EJ cell line exhibiting the greatest difference. Furthermore, the relationship between the malignancy, deformability, and uptake capability of bladder cells was explored through co-cultivation experiments with 2 μm particles. As the malignancy increased, the cells became more deformable and exhibited stronger phagocytic capability with particles. Subsequently, the heterogeneity of tumor cells was investigated by analyzing the deformability of phagocytic and non-phagocytic subpopulations within EJ cells. The developed microfluidic platform offers a promising high-throughput method to assess the biomechanical and phagocytic characteristics of cells, providing valuable insights into tumor cell biology, and potentially improving clinical status of urinary cytology examinations for bladder cancer.

Metabolism: an important player in glioma survival and development.

Gliomas are malignant tumors originating from both neuroglial cells and neural stem cells. The involvement of neural stem cells contributes to the tumor's heterogeneity, affecting its metabolic features, development, and response to therapy. This review provides a brief introduction to the importance of metabolism in gliomas before systematically categorizing them into specific groups based on their histological and molecular genetic markers. Metabolism plays a critical role in glioma biology, as tumor cells rely heavily on altered metabolic pathways to support their rapid growth, survival, and progression. Dysregulated metabolic processes, involving carbohydrates, lipids, and amino acids not only fuel tumor development but also contribute to therapy resistance and metastatic potential. By understanding these metabolic changes, key intervention points, such as mutations in genes like RTK, EGFR, RAS, and IDH can be identified, paving the way for novel therapeutic strategies. This review emphasizes the connection between metabolic pathways and clinical challenges, offering actionable insights for future research and therapeutic development in gliomas.

Guiding treatment decisions in renal cell carcinoma: the role of biomarkers and clinical factors.

Immune checkpoint inhibitors (ICIs) have transformed the treatment landscape for metastatic renal cell carcinoma (mRCC), significantly improving overall survival and achieving durable responses. This review is timely due to the increasing number of ICI-based regimens now considered standard care for RCC. There is an urgent need to identify reliable biomarkers that can predict therapeutic responses and resistance, a key challenge in current research. While tumor-specific factors such as pathological characteristics, genomic mutations, and transcriptional profiles have been extensively studied, no definitive predictive biomarker has yet emerged. Additionally, advanced technologies are being explored to address tumor heterogeneity. Recent research has focused on novel areas such as the microbiome, radiomics, and spatial transcriptomics, which show promise as potential biomarkers. The translation of these emerging biomarker findings into clinical practice is essential to improving personalized treatment strategies for RCC. Until reliable biomarkers are clinically available, clinical factors may play a pivotal role in guiding individualized treatment decisions to optimize patient outcomes.

Functionalized Nanomaterials In Pancreatic Cancer Theranostics And Molecular Imaging.

Pancreatic cancer (PC) is one of the most fatal malignancies in the world. This lethality persists due to lack of effective and efficient treatment strategies. Pancreatic ductal adenocarcinoma (PDAC) is an aggressive epithelial malignancy which has a high incidence rate and contributes to overall cancer fatalities. As of 2022, pancreatic cancer contributes to about 3 % of all cancers globally. Over the years, research has characterised germline predisposition, the origin cell, precursor lesions, genetic alterations, structural alterations, transcriptional changes, tumour heterogeneity, metastatic progression, and the tumour microenvironment, which has improved the understanding of PDAC carcinogenesis. By using molecular-based target therapies, these fundamental advancements support primary prevention, screening, early detection, and treatment. The focus of this review is the use of targeted nanoparticles as an alternative to conventional pancreatic cancer treatment due to the various side effects of the latter. The principles of nanoparticle based cancer therapy is efficient targeting of tumour cells via enhanced permeability and retention (EPR) effects and decrease the chemotherapy side effects due to their non-specificity. To increase the efficiency of existing therapies and modify target nanoparticles, several molecular markers of pancreatic cancer cells have been identified. Thus pancreatic cancer cells can be detected using appropriately functionalized nanoparticles with specific signalling molecules. Once cancer has been identified, these nanoparticles can kill the tumour by inducing hyperthermia, medication delivery, immunotherapy or gene therapy. As potent co-delivery methods for adjuvants and tumor-associated antigens; nanoparticles (NPs) have demonstrated significant promise as delivery vehicles in cancer therapy. This ensures the precise internalization of the functionalized nanoparticle and thus also activates the immune system effectively against tumor cells. This review also discusses the immunological factors behind the uptake of functionalized nanoparticles in cancer therapies. Theranostics, which combine imaging and therapeutic chemicals in a single nanocarrier, are the next generation of medicines. Pancreatic cancer treatment may be revolutionised by the development of a tailored nanocarrier with diagnostic, therapeutic, and imaging capabilities. It is extremely difficult to incorporate various therapeutic modalities into a single nanocarrier without compromising the individual functionalities. Surface modification of nanocarriers with antibodies or proteins will enable to attain multifunctionality which increases the efficiency of pancreatic cancer therapy.

Mechanical properties of pediatric low-grade gliomas in children with and without neurofibromatosis type 1.

Prognoses for pediatric brain tumors are suboptimal, as even in low-grade tumors, management techniques can lead to damage in the developing brain. Therefore, advanced neuroimaging methods are critical for developing optimal management plans and improving patient care. Magnetic resonance elastography (MRE) has allowed for the characterization of adult gliomas by their mechanical properties, which are uniquely sensitive to the complex interplay of cellularity, vasculature, and interstitium. However, pediatric tumors differ in behavior and cytoarchitecture, and their mechanical properties have never been assessed. Here, we conduct the first study of pediatric brain tumor mechanical properties by using MRE to measure tissue stiffness and damping ratio in low grade gliomas (LGGs). We additionally measure the mechanical properties of non-neoplastic focal abnormal signal intensities (FASIs) in children with neurofibromatosis type 1 (NF1). 23 patients age 4-17 years who had MR imaging results consistent with a primary LGG or with NF1 were included in this study. We found that pediatric gliomas are on an average 10.9% softer (p = 0.010) with a 17.3% lower (p = 0.009) viscosity than reference tissue. Softness of tumors appeared consistent across tumor subtypes and unrelated to tumor size or contrast-enhancement. In NF1 we found that, unlike gliomas, FASIs are stiffer, though not significantly, than reference tissue by an average of 10.4% and have a 16.7% lower damping ratio. Measuring tumor mechanical properties patterning and heterogeneity has potential to aid in prediction of biological behavior and inform management strategies for pediatric patients.

Lipid levels and insulin resistance markers in gastric cancer patients: diagnostic and prognostic significance.

Gastric cancer (GC) is a highly heterogeneous and aggressive malignant tumor that seriously affects the life safety of people all over the world. Its early manifestations are subtle. The present study aimed to investigate the clinical significance of serum lipid profiles, insulin resistance markers including the triglyceride-glucose (TyG) index and the atherosclerotic index (AI), in GC patients. A retrospective analysis encompassed 215 GC patients and 827 healthy individuals. The study results show that the total cholesterol, triglycerides, low-density lipoprotein, high-density lipoprotein levels, and the TyG index of GC patients were significantly lower than those of the control group before and after propensity score matching analysis. In the GC group, the levels of CEA, CA199, CA125, and CA724 tumor markers were higher than those in the healthy control group. Patients in advanced stages exhibited lower serum levels of serum lipids and TyG index compared to those in early stages. ROC analysis revealed that the TyG index, CA125, and CA199 combination yielded the highest positive prediction rate for GC at 98.6%. TyG index is significantly associated with the risk of adverse reactions after chemotherapy (OR = 1.104, 95% CI 1.028-1.186, P < 0.01). Multiple tumor markers and the TyG index combined detection showed correlations with five adverse reactions caused by chemotherapy (r < 0.6, P < 0.05). Preoperative lipid profiles in the serum show a strong correlation with patients diagnosed with GC. Evaluating a combination of various serum lipids and cancer markers significantly improves diagnostic precision for GC and the ability to predict chemotherapy side effects.

Acquired Bortezomib Resistance in Multiple Myeloma:From Mechanisms to Strategy.

Multiple myeloma (MM) is a heterogeneous plasma cell tumor with a survival period of several months to over ten years. Despite the development of various new drugs, MM is still incurable and recurs repeatedly. Bortezomib, a landmark event in the history of MM treatment, has dramatically improved the prognosis of patients with MM. Although proteasome inhibitors (PIs) represented by bortezomib, have greatly prolonged MM survival, unfortunately, almost all MM will develop bortezomib resistance, leading to relapse with a shorter survival. It has been reported that both the tumor microenvironment and myeloma cells drive bortezomib resistance. Multiple treatment methods have been attempted to overcome bortezomib resistance, but unfortunately, there has been no breakthrough. It is believed that the key resistance mechanism has not yet been discovered. A deeper understanding of the mechanism of bortezomib resistance and strategies to overcome it can help identify key resistance mechanisms and further improve the prognosis of MM.

Acute Acquired Comitant Esotropia

Acute acquired comitant esotropia (AACE) is an infrequent presentation of esotropia, characterized by sudden onset eye misalignment and diplopia. The purpose of this article is to review four cases of children diagnosed with AACE. We present 4 cases (children 610 years) of AACE. All of them suddenly developed diplopia and esotropia, with largeangle. After complete ophthalmological and neurological examinations in three cases out of four, strabismus surgery was conducted. In one case heterogenous neoplasm was detected and sent to an oncologist and neurosurgeon for evaluation and morphological verification. Bilateral medial rectus recession in two cases and unilateral recession of the medial rectus and resection of the lateral rectus in one case were performed. After strabismus surgery fully recovered binocular vision and was no longer noticeable diplopia. Neurological examinations and neuroimaging should be performed to exclude any potential intracranial disease. Surgery should be taken into consideration 6 months after the onset of the esotropia, if the deviation is stable. Strabismus surgery of AACE has good motor and sensory results and can successfully restore good binocular function The excessive use of smartphones may be associated with developing and increasing AACE.

The Utilization of PRAME in the Diagnosis, Prognosis, and Treatment of Melanoma.

Melanoma, a deadly form of skin cancer, has seen improved survival rates due to advances in diagnosis and treatment, yet the need for further improvement remains critical. Tumor-associated antigens, such as PRAME (Preferentially Expressed Antigen in Melanoma), offer promising avenues for enhanced diagnostic precision, prognostic assessment, and targeted immunotherapy. PRAME, a cancer testis antigen, is selectively expressed in various cancers, including melanoma, and plays a key role in promoting tumorigenesis through inhibition of retinoic acid signaling, epithelial-to-mesenchymal transition, and immune evasion. This review explores the diagnostic utility of PRAME in distinguishing melanoma from benign nevi, its prognostic value in aggressive melanoma subtypes, and its potential as a therapeutic target in cancer vaccines and adoptive T-cell therapies. While PRAME-targeted therapies face challenges such as tumor heterogeneity and immune suppression, ongoing research aims to overcome these barriers, offering hope for more effective melanoma treatments.