Cancer Investigation最新文献

Lung cancer (LC) remains a leading cause of mortality worldwide, affecting individuals across all genders and age groups. Early and accurate diagnosis is critical for effective treatment and improved survival rates. Computed Tomography (CT) imaging is widely used for LC detection and classification. However, manual identification can be time-consuming and error-prone due to the visual similarities among various LC types. Deep learning (DL) has shown significant promise in medical image analysis. Although numerous studies have investigated LC detection using deep learning techniques, the effective extraction of highly correlated features remains a significant challenge, thereby limiting diagnostic accuracy. Furthermore, most existing models encounter substantial computational complexity and find it difficult to efficiently handle the high-dimensional nature of CT images. This study introduces an optimized CBAM-EfficientNet model to enhance feature extraction and improve LC classification. EfficientNet is utilized to reduce computational complexity, while the Convolutional Block Attention Module (CBAM) emphasizes essential spatial and channel features. Additionally, optimization algorithms including Gray Wolf Optimization (GWO), Whale Optimization (WO), and the Bat Algorithm (BA) are applied to fine-tune hyperparameters and boost predictive accuracy. The proposed model, integrated with different optimization strategies, is evaluated on two benchmark datasets. The GWO-based CBAM-EfficientNet achieves outstanding classification accuracies of 99.81% and 99.25% on the Lung-PET-CT-Dx and LIDC-IDRI datasets, respectively. Following GWO, the BA-based CBAM-EfficientNet achieves 99.44% and 98.75% accuracy on the same datasets. Comparative analysis highlights the superiority of the proposed model over existing approaches, demonstrating strong potential for reliable and automated LC diagnosis. Its lightweight architecture also supports real-time implementation, offering valuable assistance to radiologists in high-demand clinical environments.

The therapeutic application of T cells engineered to express chimeric antigen receptors (CARs) is hindered by the risk of antigen escape in single-target CAR constructs, particularly in the treatment of solid tumors. Pancreatic cancer cells frequently overexpress tumor-associated antigens, such as human epidermal growth factor receptor 2 (HER2) and Mesothelin (Meso). In this study, we therefore investigated the therapeutic effect of tandem dual CAR-T cells co-targeting Her2 and Meso versus single-targeted CAR-T cells in pancreatic cancer models. We constructed a dual CAR by fusing a HER2-binding single-chain variable fragment (ScFv) with a Meso-binding ScFv. The expression levels of CARs and the anti-tumor efficacy of CAR-T cells were systematically compared via in vitro and in vivo experiments. In HER2/Meso co-expressing pancreatic cancer cell lines (AsPC-1 and SW-1990), dual CAR-T cells exhibited superior antitumor activity, accompanied by increased secretion of anti-tumor cytokines (IL-2 and IFN-γ), compare to HER2-specific or Meso-specific single-target CAR-T cells. In a xenograft mouse model, dual CAR-T cells significantly reduced tumor volume and prolonged mouse survival relative to single-target CAR-T cells. Collectively, our findings demonstrated that dual CAR-T cells enhance antitumor cytotoxicity, supporting their potential as a promising therapeutic strategy for Pancreatic Cancer and other solid tumors.

Background: Irisin influences key cancer-related processes such as cell proliferation, apoptosis, angiogenesis, and metastasis. This review aimed to evaluate serum irisin's potential in cancer diagnosis, prognosis, and treatment monitoring.

Methods: Databases including Scopus, PubMed, Cochrane, and others were searched. Studies comparing serum irisin in cancer patients and healthy individuals were assessed using Joanna Briggs Institute criteria.

Results: Nine studies showed significantly lower irisin levels in cancer patients (SMD: -1.16, p < 0.0001), especially in hepatocellular and bladder cancers.

Conclusion: Reduced serum irisin may serve as a diagnostic cancer biomarker, though its utility varies by cancer type and requires further research.

Prospero registration no: CRD420250650210.

Ovarian cancer remains one of the most lethal gynecological malignancies, with a high mortality rate primarily due to late-stage diagnosis. Genetic predispositions play a significant role in its development, alongside environmental and lifestyle factors. The main objective of the study was to check the association of XRCC1, XRCC3, and RAD51 gene polymorphism with ovarian cancer. In the present 300 ovarian cancer patients and 300 healthy controls blood samples collected. The results showed that the heterozygous (GA) genotype of rs25487 SNP shows significant correlation with ovarian cancer with decreased risk of disease (OR = 0.39; 95% CI = 0.17-0.88; p < 0.02), whereas the homozygous variant (AA) genotype of the same SNP exhibits a non-significant relation with ovarian cancer. The combined genotype model of this SNP indicated a highly significant association with increased risk of ovarian cancer by twofold (OR = 2.10;95% CI = 1.22-3.64; p < 0.007). In case of rs861539 heterozygous (CT) showed significant association by increasing the risk of disease almost threefold (OR = 2.73; 95% CI 1.68-4.41; p < 0.0001). while the mutant (TT) of the same SNP showed again significant association but with decreased risk of ovarian cancer (OR = 0.27; 95% CI 0.16-0.47; p < 0.0001). The genotype distribution of the RAD51 gene's SNP (rs1801320) shows that heterozygous (GC) individuals exhibit a significant correlation and increased risk of ovarian cancer by twofold (OR = 2.81;95% CI = 1.72-4.60; p ≤ 0.0001). Conversely, the mutant (CC) of rs1801320 exhibits a significant correlation with a decrease in the risk of ovarian cancer (OR = 0.32; 95% CI = 0.19-0.55; p < 0.0001). In conclusion, the study's findings suggest that a higher chance of ovarian cancer is related to the gene XRCC1, XRCC3, and RAD51 polymorphisms. In this study, SNPs were analyzed for their potential role as biomarkers for the diagnosis of ovarian cancer.

The purpose of this study was to evaluate the efficacy and safety of Azacitidine, alone or in combination with Venetoclax, in the treatment of newly diagnosed acute myeloid leukemia in patients with significant comorbidities who are ineligible for intensive chemotherapy. Most patients in the cohort had high-risk acute myeloid leukemia based on clinical and cytogenetic characteristics and required low-intensity therapeutic regimens, such as Azacitidine with or without Venetoclax, due to their age and comorbidities. It was shown that 77% of patients treated with hypomethylating agents with the addition of Venetoclax achieved complete remission. In addition, the clinical case of a 61-year-old patient with severe comorbidity status is described in the end of the article. The diagnosis included a transient ischemic attack in the context of an unruptured cerebral aneurysm, for which the patient was not a candidate for thrombolytic therapy, alongside other conditions requiring comprehensive treatment. A limitation of this study was a small sample of patients with acute myeloid leukemia.

Usage of complementary and alternative medicine (CAM) is widespread in the population. Accordingly, knowledge on CAM is important for physicians. To learn more on the knowledge during studying medicine, we conducted a web-based survey using a standardized questionnaire among medical students regarding evidence-based medicine (EbM) and CAM. Yet, while 43% marked that they felt able to define EbM, less than a quarter were familiar with CAM. There is a strong contrast between students' agreement to EbM, and the low self-rating of their competences in EbM. Efforts must be increased to educate medical students in the skills of EbM.

Objective: The aim of this study is to elucidate the function of Kras, which is involved in the development and progression of pancreatic cancer.

Methods: We have previously isolated pancreas-derived cells from mice and induced genes expressed in pancreatic ducts and exocrine and endocrine cells by expressing transcription factor genes and a plasmid expressing polyoma ori to create cells with stable foreign gene expression. Comprehensive gene analysis was used to analyze the function of Kras by introducing wild-type Kras and mutant Kras into these cells.

Results: No changes in cell morphology were observed with wild-type Kras expression, but expression of mutant Kras led to cystic changes. Mutant Kras gene transfer induced the expression of Mus5ac and Cck genes. Gene expression in these cells was detected by microarray analysis, and comparison of gene profiles showed that the genes promoted amoeboid cell assembly and immunosuppression.

Conclusion: The use of these cells will facilitate screening of drugs that block Kras function and elucidate how Kras induces pancreatic cancer.

Exosomes are 30-150 nm extracellular vesicles released by nearly all cells, including tumor cells. Cancer cell-derived exosomes carry various molecular contents - proteins, mRNAs, microRNAs- that are transferred to recipient cells, contributing to cancer development, angiogenesis, metastasis, and immune evasion. Breast cancer-derived exosomes (BEXs) express multiple immunomodulatory molecules, particularly the ectoenzymes CD39 and CD73, which catalyze the conversion of adenosine triphosphate (ATP) into adenosine. Adenosine then binds its receptors (ADORs) to transmit immunosuppressive signals. BEXs also express immune checkpoint molecules such as programmed death ligand 1 (PD-L1), CD200, and CD47 that suppress immune surveillance through interaction with programmed cell death protein 1 (PD-1), CD200R, and signal-regulatory protein alpha (SIRPα), respectively. Notably, PD-L1 appears to be more enriched on exosomes than on tumor cell surfaces, underscoring the pivotal role of BEXs in immune regulation. Given their influence on several hallmarks of cancer, BEXs are promising candidates for future diagnostic and therapeutic strategies, particularly in immunotherapy.

Inflammation contributes to tumorigenesis and can be determined systemically from routine bloods collected through diagnostic workup by quantifying ratios of neutrophils, lymphocytes, platelets and monocytes. Retrospective data from 104 male breast cancer (BC) patients was collected. We measured pre-treatment neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and monocyte-to-lymphocyte ratio (MLR) and quantitatively evaluated other male BC studies. Prognostic values of NLR and PLR were assessed by overall survival (OS). Elevated NLR (≥3.23) and PLR (≥129.53) were associated with significantly decreased OS. None of the previously reported cutoffs for NLR or PLR were significant when applied to our data. NLR remained associated with worse OS in a quantitative evaluation. Relationship between BMI and pre-operative NLR, PLR, and MLR ratios showed that severely obese patients tended to have higher PLR and MLR values. In conclusion, elevated NLR and PLR were linked to poorer outcomes in male BC. While more precise cut-off values are required to fully understand the potential of these biomarkers in managing BC in men, this study suggests that NLR and PLR may affect prognosis.

Background: FARSB is a β-regulatory subunit of phenylalanine tRNA synthetase. It is reported that FARSB was involved in cancer progression. However, the molecular function of FARSB in breast cancer was unclear. This study aimed to investigate the prognostic significance of FARSB expression and its relationship with immunity in breast cancer.

Methods: Several databases, including TCGA, HPA, and UALCAN database, were applied to study FARSB mRNA and protein expression and its association with aggressiveness in breast cancer. We used immunohistochemical staining (IHC) to study FARSB expression in breast cancer and normal tissues. Chi square test was explored to study the correlation between FARSB expression and clinical features in breast cancer. Kaplan-Meier analysis and Cox regression were utilized to discuss the prognosis of breast cancer. Spearman analysis was applied to analyze the association between FARSB expression and immunity. We studied the correlation of FARSB with common breast cancer chemotherapeutic drugs. We conducted GO, KEGG, and GSEA enrichment analysis to study the molecular function of FARSB in breast cancer.

Results: The TCGA database suggested that FARSB was increased in several cancers, including breast cancer. HPA and UALCAN databases suggested that FARSB protein expression was higher in breast cancer than normal tissues. IHC analysis also confirmed the higher expression of FARSB in breast cancer. FARSB expression had correlation with ER status and PR status. In TCGA database, FARSB expression was related to ER status, PR status, and PAM50. Overexpression FARSB had adverse prognosis, and Cox regression considered FARSB as a prognostic marker. Immunological analysis demonstrated that FARSB was linked with immune cell infiltration and immune checkpoints. High FARSB expression had low TIDE score. In addition, FARSB was linked to drugs, such as 5-fluorouracil, doxorubicin, gemcitabine, and paclitaxel. GSEA analysis suggested that FARSB was involved in the pathways, including cell cycle, aminoacyl TRNA biosynthesis, DNA replication, spliceosome, and mismatch repair.

Conclusion: FARSB was highly expression at mRNA and protein level in breast cancer. Overexpression of FARSB had a poor prognosis in breast cancer. FARSB expression was associated with immunity and acted as a new target for cancer immunological therapy.