Discover. Oncology最新文献

Radiomics is a method that extracts many features from medical images using various algorithms. Medical nomograms are graphical representations of statistical predictive models that produce a likelihood of a clinical event for a specific individual based on biological and clinical data. The radiomic nomogram was first introduced in 2016 to study the integration of specific radiomic characteristics with clinically significant risk factors for patients with colorectal cancer lymph node metastases. Thereby it gained momentum and made its way into different domains of breast, liver, and head and neck cancer. Deep learning-based radiomics which automatically generates and extracts significant features from the input data using various neural network architectures, along with the generation and usage of nomograms are the latest developments in the application of radiomics for the diagnosis of gall bladder carcinoma. Although radiomics has demonstrated encouraging outcomes in the diagnosis of gall bladder carcinoma, but most of the studies conducted suffer from a lack of external validation cohorts, smaller sample sizes, and paucity of prospective utility in routine clinical settings.

Antibody-drug conjugates (ADCs) represent a novel class of targeted anti-tumor medications that utilize the covalent linkage between monoclonal antibodies and cytotoxic agents. This unique mechanism combines the cytotoxic potency of drugs with the targeting specificity conferred by antigen recognition. However, it is essential to recognize that many ADCs still face challenges related to off-target toxicity akin to cytotoxic payloads, as well as targeted toxicity and other potential life-threatening adverse effects, such as treatment-induced interstitial lung injury. Currently, of the four approved ADC drugs for breast cancer, several reports have documented post-treatment lung injury-related fatalities. As a result, treatment-induced interstitial lung injury due to ADC drugs has become a clinical concern. In this review article, we delve into the factors associated with ADC-induced interstitial lung injury in patients with advanced-stage breast cancer and highlight strategies expected to decrease the incidence of ADC-related interstitial lung injury in the years ahead. These efforts are directed at enhancing treatment outcomes in both advanced and early-stage cancer patients while also providing insights into the development and innovation of ADC drugs and bolstering clinicians' understanding of the diagnosis and management of ADC-associated interstitial lung injury.

The aim of our research was to explore the character of autophagy related 12 (ATG12) in the development of hepatocellular carcinoma (HCC). A total of  145 HCC tissues as well as paired adjacent normal tissues were collected, then immunohistochemistry was conducted to access the expression of ATG12. HCC cells were transfected with pcDNA ATG12 or si-ATG12 to overexpress ATG12 or downregulate ATG12. The vitality of HCC cells was accessed using CCK-8 assay, and the ability of invasion of them was tested through Transwell assay. The apoptotic rate of HCC cells was calculated by flow cytometry. The expression of ATG12 was lower in HCC tissues than that in normal tissues, and HCC patients with high ATG12 level survived longer. Overexpressed of ATG12 restrained vitality and invasion of HCC cells, while elevated apoptotic rate of HCC cells. Silence of ATG12 expression yielded opposite results to overexpression of ATG12 in HCC cells. In conclusion, ATG12 is low expressed in HCC, which attenuated the growth and invasion of HCC, while induced the apoptosis of HCC cells. Current research suggested that ATG12 might be a potential target for the diagnosis and treatment of HCC.

Background: Primary liver cancer, particularly hepatocellular carcinoma, is one of the most common gastrointestinal cancers. An increasing number of studies indicate that nanomaterials play a significant role in the diagnosis and treatment of liver cancer. However, despite the extensive and diverse research on nanomaterials and liver cancer, bibliometric studies in this field have not yet been reported. This study aims to comprehensively evaluate the application prospects and development trends of nanomaterials in primary liver cancer over the past 20 years. By elucidating the current state of research on liver cancer, we intend to provide valuable reference information for researchers in this field.

Methods: We conducted a comprehensive search of the Web of Science Core Collection for publications related to liver cancer and nanomaterials from January 1, 2004, to December 31, 2023. Relevant literature was selected based on specific inclusion and exclusion criteria. These selected publications were subsequently analyzed using CiteSpace, VOSviewer, and the R package "bibliometrix" to identify trends, influential countries, institutions, authors, journals, and research hotspots in this field.

Results: This study included a total of 1641 publications, with an annual growth rate of 25.45%. China and the United States are leading in this field, accounting for 67.46% and 11.27% of the total publications, respectively. The Chinese Academy of Sciences and Shao D are the most cited institution and author, respectively. The International Journal of Nanomedicine is the most influential journal in this field, while Biomaterials is the most highly cited and co-cited journal. Research hotspots mainly focus on improving drug delivery efficiency, inducing cancer cell apoptosis, photodynamic therapy, photothermal therapy, and combination treatments. Emerging research directions include the tumor microenvironment, polyethylene glycol, and immunogenic cell death.

Conclusion: The results of this study indicate that the application of nanomaterials in the field of liver cancer is gradually becoming a significant research area, with a focus on improving drug delivery efficiency, enhancing therapeutic efficacy, and reducing side effects.

The immune response plays a pivotal role in tumor progression and therapy. However, the influence of protein PAR polymerases (PARPs) modifications on cell infiltration within the tumor microenvironment (TME) remains insufficiently understood. In this study, the Clinical and RNA sequencing data we performed a comprehensive analysis of PARPs modification patterns, exploring their associations with TME cell infiltration were acquired from the Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) database. To quantify PARPs modification in individual tumors, we developed a novel metric, the PARPscore, derived using principal component analysis. Our findings revealed three distinct PARPs modification patterns, each correlated with unique TME infiltration characteristics and tumor immunophenotypes. These patterns demonstrated predictive value for various clinical parameters, including inflammation stage, tumor subtypes, TME matrix activity, genetic variations, and patient prognosis. Notably, the high PARPscore subtype exhibited features of stromal activation and reduced immune infiltration, indicative of a non-inflamed, immune-excluded TME phenotype, and was associated with poorer survival outcomes. Conversely, lower PARPscore subtypes corresponded to substantial therapeutic benefits and improved outcomes in two independent immunotherapy cohorts. This study underscores the critical role of PARPs modification in shaping the diverse and dynamic TME. By delineating tumor-specific PARPs modification patterns, we provide valuable insights into TME complexity and its implications for immunotherapy.

Lung squamous cell carcinoma (LUSC) is a subtype of non-small cell lung cancer. It has a grim prognosis for patients, primarily because the disease often remains asymptomatic in its early stages. As a result, it is frequently diagnosed at an advanced stage, limiting treatment options. This underscores the importance of studying potential biomarkers and developing personalized treatment strategies. In this study, we used an advanced bioinformatics approach, integrating two authoritative databases, NCBI's GEO and TCGA, to perform a large-scale cross-platform gene expression analysis. To deeply mine the gene expression data of a large number of lung squamous carcinoma samples, we used a screening strategy based on median absolute deviation to select genes that differed significantly in multiple datasets. The expression variations of these genes between normal and cancerous tissues provided us with valuable clues revealing key molecules that may be involved in the disease process. Through rigorous statistical tests, we identified 36 genes that were significantly associated with patient survival, and further constructed a model using Cox proportional risk model containing 11 key genes (MRPL40, GABPB1AS1, PTPN3, SNCA, PYGB, RAP1, VDR, PHPT1, KIAA0100, TBC1D30, CYP7B1) in a risk prediction model. The prediction model not only reflects the strong correlation between gene expression and LUSC prognosis, but also provides clinicians with an effective tool to predict patients' survival prospects. In the future, this model is expected to guide the development of individualized treatment plans, thereby improving the quality of life and overall prognosis of patients.

Objective: Endometrial cancer (EC) is the ninth most common malignancy among women. While mutations in JAK2 are frequently observed in EC, the specific biological functions of JAK2 in endometrial cancer are poorly understood.

Methods: The genetic alterations of JAK2 in different cancer types were explored using sequencing dataset deposited at TCGA database. JAK2 mutations were detected in EC formalin-fixed paraffin-embedded (FFPE) samples using Sanger sequencing. The expression levels of JAK2 was accessed using the TCGA database and immunohistochemistry. Furthermore, the relationships between JAK2 expression and staging and prognosis of EC patients were investigated using the TCGA database. Down-regulation of JAK2 were achieved by transient transfection with short hairpin RNAs (shRNAs). Effects of JAK2 on cancer cells proliferation and migration were evaluated by CCK8, colony formation, and transwell assay. The potential biological functions of JAK2 in EC were identified based on bioinformatics analysis. Effects of JAK2 on expression levels of target genes were detected by RT-qPCR and western blotting. Co-immunoprecipitation (co-IP) assays was used to detect the physical association between JAK2 and HIF-1α.

Results: Frequent mutations and down-regulation of JAK2 were found in EC. Loss-of-function (LOF) assays suggested that JAK2 silencing in endometrial cancer cells promoted cell proliferation and migration, which were partially dependent on HIF-1α signaling pathway. Furthermore, our findings demonstrated that JAK2 interacted with HIF-1α and reduced HIF1α protein expression under hypoxia.

Conclusion: These findings revealed novel molecular mechanisms underlying JAK2 LOF mutations-driven endometrial tumorigenesis and revealed that the HIF-1α pathway may be a potential therapeutic target in JAK2-mutated endometrial cancer.

Gastric cancer (GC) remains a prevalent and aggressive malignancy with a poor prognosis. This study aimed to identify diagnostic and prognostic biomarkers while exploring their potential functions in GC. A total of 598 upregulated and 506 downregulated genes were identified in GC patients. Among these, survival-related differentially expressed genes (DEGs), including ADAMTS12, F5, and VCAN, were highlighted. Pan-cancer analyses revealed their dysregulation across multiple tumor types. A novel prognostic signature, incorporating ADAMTS12 and F5, effectively stratified GC patients into low- and high-risk groups, demonstrating significant differences in overall survival and robust predictive performance. ADAMTS12, strongly associated with advanced clinical stages and poor prognosis, was validated in an independent cohort and exhibited promising diagnostic potential. RT-PCR and western blot analyses confirmed its high expression in GC tissues and cell lines. Functional assays further demonstrated that ADAMTS12 promotes GC cell proliferation and invasion. In summary, this study provides critical insights into the molecular landscape of GC, offering a potential prognostic tool and therapeutic target.

Background: Chemotherapy is crucial in the management of tumors, but challenges such as chemoresistance and adverse reactions frequently lead to therapeutic delays or even premature cessation. A growing body of research underscores a profound connection between the gut microbiota (GM) and cancer chemotherapy (CC). This paper aims to pinpoint highly influential publications and monitor the current landscape and evolving trends within the realm of GM/CC research.

Methods: On October 1st, 2024, a comprehensive search for GM/CC publications spanning the past 20 years from 2004 to 2023 was conducted utilizing the Web of Science Core Collection (WoSCC). The scope encompassed both articles and reviews, and the data was subsequently extracted. To gain insights into the evolution and dynamics of this research field, we employed bibliometric analysis tools such as the Bibliometrix R package, VOSviewer, and Microsoft Excel to visualize and analyze various dimensions, including prominent journals, leading authors, esteemed institutions, contributing countries/regions, highly cited papers, and frequently occurring keywords.

Results: A total of 888 papers were obtained. The number of publications about GM/CC studies has increased gradually. China and the United States published the largest number of papers. The INSERM was in the leading position in publishers. The most productive authors were Zitvogel L from France. Cancers had the largest number of papers. Citation analysis explained the historical evolution and breakthroughs in GM/CC research. Highly cited papers and common keywords illustrated the status and trends of GM/CC research. Four clusters were identified, and the hot topics included the role of the GM in the efficacy and toxicity of CC, the targeting of the GM to improve the outcome of CC, the mechanism by which the GM affects CC, and the correlation of the GM with carcinogenesis and cancer therapy. Metabolism, GM-derived metabolites, tumor microenvironment, immunity, intestinal barrier, tumor microbiota and Fusobacterium nucleatum may become the new hotspots and trends of GM/CC research.

Conclusion: This study analyzed global publications and bibliometric characteristics of the links between GM and CC, identified highly cited papers in GM/CC, provided insight into the status, hotspots, and trends of global GM/CC research, and showed that the GM can be used to predict the efficacy and toxicity of CC and modifying the GM can improve the outcomes of chemotherapeutics, which may inform clinical researchers of future directions.

Patients with chronic myeloid leukemia (CML) frequently develop resistance to tyrosine kinase inhibitors such as imatinib. In this study, we explored the role of the insulin-like growth factor 1 (IGF-1) signaling pathway in CML and imatinib resistance. An analysis of IGF-1 gene expression using public databases revealed elevated levels of insulin-like growth factor-binding proteins in patients with chronic-phase CML. Further research revealed that IGF-1-related genes were upregulated in patients who were unresponsive to imatinib, suggesting that IGF-1 signaling plays a role in the resistance mechanism. Furthermore, we evaluated the efficacy of linsitinib, a selective insulin-like growth factor-1 receptor (IGF-1R) inhibitor, in inhibiting the growth of CML cell lines, including imatinib-resistant cell lines, and observed a notable decrease in cell viability and an increase in cytotoxicity. The combination of imatinib and linsitinib reduced cell viability and increased caspase-3/7 activity in imatinib-resistant cells. Moreover, silencing of IGF-1R by small interfering ribonucleic acid increased the sensitivity of CML cell lines to imatinib, indicating that IGF-1R could be a strategic target for overcoming resistance. These findings highlight the therapeutic potential of linsitinib and that IGF-1R inhibition may improve the treatment outcomes of patients with imatinib-resistant CML.