Technology in Cancer Research & Treatment最新文献

Background & Objective: Assessment of muscularis propria invasion is a crucial step in the management of urothelial carcinoma since it necessitates aggressive treatment. The diagnosis of muscle invasion is a challenging process for pathologists. Artificial intelligence is developing rapidly and being implemented in various fields of pathology. The purpose of this study was to develop an algorithm for the detection of muscularis propria invasion in urothelial carcinoma. Methods: The Training cohort consisted of 925 images from 50 specimens of urothelial carcinoma. Ninety-seven images from 10 new specimens were used as a validation cohort. Clinical validation used 127 whole specimens with a total of 617 slides. The algorithm determined areas where tumor and muscularis propria events were in nearest proximity, and presented these areas to the pathologist. Results: Analytical evaluation showed a sensitivity of 72% for muscularis propria and 65% for tumor, and a specificity of 46% and 77% for muscularis propria and tumor detection, respectively. The incorporation of the spatial proximity factor between muscularis propria and tumor in the clinical validation significantly improved the detection of muscularis propria invasion, as the algorithm managed to identify all except for one case with muscle invasive bladder cancer in the clinical validation cohort. The case missed by the algorithm was nested urothelial carcinoma, a rare subtype with unusual morphologic features. The pathologist managed to identify muscle invasion based on the images provided by the algorithm in a short time, with an average of approximately 5 s. Conclusion: The algorithm we developed may greatly aid in accurate identification of muscularis propria invasion by imitating the thought process of the pathologist.

Spinal cord astrocytoma (SCA) is a rare subtype of astrocytoma, posing challenges in diagnosis and treatment. Low-grade SCA can achieve long-term survival solely through surgery, while high-grade has a disappointing prognosis even with comprehensive treatment. Diagnostic criteria and standard treatment of intracranial astrocytoma have shown obvious limitations in SCA. Research on the molecular mechanism in SCA is lagging far behind that on intracranial astrocytoma. In recent years, huge breakthroughs have been made in molecular pathology of astrocytoma, and novel techniques have emerged, including DNA methylation analysis and radiomics. These advances are now making it possible to provide a precise diagnosis and develop corresponding treatment strategies in SCA. Our aim is to review the current status of diagnosis and treatment of SCA, and summarize the latest research advancement, including tumor subtype, molecular characteristics, diagnostic technology, and potential therapy strategies, thus deepening our understanding of this uncommon tumor type and providing guidance for accurate diagnosis and treatment.

Recently, large language models such as ChatGPT have made huge strides in understanding and generating human-like text and have demonstrated considerable success in natural language processing. These foundation models also perform well in computer vision. However, there is a growing need to use these technologies for specific medical tasks, especially for identifying cancer in images. This paper looks at how these foundation models, such as the segment anything model, could be used for cancer segmentation, discussing the potential benefits and challenges of applying large foundation models to help with cancer diagnoses.

Objective: This study presents a comparative analysis of RF and SVM for predicting calcein release from ultrasound-triggered, targeted liposomes under varied low-frequency ultrasound (LFUS) power densities (6.2, 9, and 10 mW/cm²).

Methods: Liposomes loaded with calcein and targeted with seven different moieties (cRGD, estrone, folate, Herceptin, hyaluronic acid, lactobionic acid, and transferrin) were synthesized using the thin-film hydration method. The liposomes were characterized using Dynamic Light Scattering and Bicinchoninic Acid assays. Extensive data collection and preprocessing were performed. RF and SVM models were trained and evaluated using mean absolute error (MAE), mean squared error (MSE), coefficient of determination (R²), and the a20 index as performance metrics.

Results: RF consistently outperformed SVM, achieving R² scores above 0.96 across all power densities, particularly excelling at higher power densities and indicating a strong correlation with the actual data.

Conclusion: RF outperforms SVM in drug release prediction, though both show strengths and apply based on specific prediction needs.

Background: Colorectal cancer (CRC) remains a global health concern with persistently high incidence and mortality rates. However, the specific pathogenesis of CRC remains poorly understood. This study aims to investigate the role and pathogenesis of serine and arginine rich splicing factor 10 (SRSF10) in colorectal cancer.

Methods: Bioinformatics analysis was employed to predict SRSF10 gene expression in CRC patients. Functional experiments involving SRSF10 knockdown and overexpression were conducted using CCK8, transwell, scratch assay, and flow cytometry. Additionally, the PRIdictor website was utilized to predict the SRSF10 interaction site with RFC5. The identification of different transcripts of SRSF10-acting RFC5 pre-mRNA was achieved through agarose gel electrophoresis.

Result: The knockdown of SRSF10 inhibited the proliferation and migration ability of CRC cells, while promoting apoptosis and altering the DNA replication of CRC cells. Conversely, when SRSF10 was highly expressed, it enhanced the proliferation and migration ability of CRC cells and caused changes in the cell cycle of colorectal cancer cells. This study revealed a change in the replicating factor C subunit 5 (RFC5) gene in colorectal cancer cells following SRSF10 knockdown. Furthermore, it was confirmed that SRSF10 increased RFC5 exon2-AS1(S) transcription variants, thereby promoting the development of colorectal cancer through AS1 exclusion to exon 2 of RFC5.

Conclusion: In summary, this study demonstrates that SRSF10 promotes the progression of colorectal cancer by generating an aberrantly spliced exclusion isoform of AS1 within RFC5 exon 2. These findings suggest that SRSF10 could serve as a crucial target for the clinical diagnosis and treatment of CRC.

Head and neck malignancies are a significant global health concern, with head and neck squamous cell carcinoma (HNSCC) being the sixth most common cancer worldwide accounting for > 90% of cases. In recent years, there has been growing recognition of the potential role of alternative splicing (AS) in the etiology of cancer. Increasing evidence suggests that AS is associated with various aspects of cancer progression, including tumor occurrence, invasion, metastasis, and drug resistance. Additionally, AS is involved in shaping the tumor microenvironment, which plays a crucial role in tumor development and response to therapy. AS can influence the expression of factors involved in angiogenesis, immune response, and extracellular matrix remodeling, all of which contribute to the formation of a supportive microenvironment for tumor growth. Exploring the mechanism of AS events in HNSCC could provide insights into the development and progression of this cancer, as well as its interaction with the tumor microenvironment. Understanding how AS contributes to the molecular changes in HNSCC cells and influences the tumor microenvironment could lead to the identification of new therapeutic targets. Targeted chemotherapy and immunotherapy strategies tailored to the specific AS patterns in HNSCC could potentially improve treatment outcomes and reduce side effects. This review explores the concept, types, processes, and technological advancements of AS, focusing on its role in the initiation, progression, treatment, and prognosis of HNSCC.

Purpose: Research on bone metastasis in esophageal cancer (EC) is relatively limited. Once bone metastasis occurs in patients, their prognosis is poor, and it severely affects their quality of life. Currently, there is a lack of convenient tumor markers for early identification of bone metastasis in EC. Our research aims to explore whether neutrophil-lymphocyte ratio (NLR) can predict bone metastasis in patients with EC.

Methods: Retrospective analysis of clinical indicators was performed on 604 patients with EC. They were divided into groups based on whether or not there was bone metastasis, and the patients' coagulation-related tests, blood routine, tumor markers and other indicators were collected. The receiver operating characteristic curve (ROC) were used to determine the predictive ability of parameters such as NLR for bone metastasis in EC, and univariate and multivariate logistic regression analyses were conducted to determine the impact of each indicator on bone metastasis. Using binary logistic regression to obtain the predictive probability of NLR combined with tumor markers.

Results: ROC curves analysis suggested that the area under the curve (AUC) of the NLR was 0.681, with a sensitivity of 79.2% and a specificity of 52.6%, which can be used as a predictive factor for bone metastasis in EC. Multivariate logistic regression analysis showed that high NLR (odds ratio [OR]: 2.608, 95% confidence interval [CI]: 1.395-4.874, P = 0.003) can function as an independent risk factor for bone metastasis in patients with EC. Additionally, high PT, high APTT, high FDP, high CEA, high CA724, low hemoglobin, and low platelet levels can also predict bone metastasis in EC. When NLR was combined with tumor markers, the area under the curve was 0.760 (95% CI: 0.713-0.807, P < 0.001), significantly enhancing the predictability of bone metastasis in EC.

Conclusion: NLR, as a convenient, non-invasive, and cost-effective inflammatory indicator, could predict bone metastasis in EC. Combining NLR with tumor markers can significantly improve the diagnostic accuracy of bone metastasis in EC.

Pyroptosis is a programmed cell death, which garners increasing attention by relating to immune and therapy response. However, the role of pyroptosis in colorectal cancer (CRC) remains unclear. Our study mainly to explore the role of pyroptosis in CRC. The mRNA expression data and corresponding clinical information of CRC patients were achieved from The Cancer Genome Atlas (TCGA). Pyroptosis-related genes (PRGs) were identified using DESeq2 R package and biological function was analyzed using cluster Profiler R package. A PRGs-based prognosis model was constructed by a univariate Cox and LASSO regression analyses. Then, the affecting of risk signature to clinicopathological characteristics, immune status and infiltrated immune cells, immune checkpoint and chemotherapy sensitivity was analyzed. qRT-PCR and IHC were performed for the expression level of PRGs. Moreover, a nomogram predict model was constructed. Total 57 PRGs were identified between 500 CRC samples and 44 normal samples. Those PRGs mainly enriched in immune-related and pyroptosis-related pathways. GABRD, NADK, TMEM240, RER1, AGRN, UBE2J2, CALML6, PLCH2, TMEM88B have been identified as gene signature and a prognostic model was constructed and validated. CRC patients with high-risk score showed poor survival, high TMB score, high proportion of CD4 + memory T cells, common lymphoid progenitors, cancer associated fibroblasts, mast cells, and neutrophils. The immune checkpoint related genes, CD160, CD200R1, CD244, CD28, CD40LG, CD44, CD48, CD80, CD86, HHLA2, ICOS, IDO1, TIGIT, TNFRSF25, TNFRSF4, TNFRSF9, TNFSF15, TNFSF18 also increased in high-risk score group. CRC patients with high-risk score more sensitive to docetaxel and rapamycin but resistance to gemcitabine and mitomycin. Moreover, a predictive nomogram for 1-, 3-, 5-year for CRC patients was established and validated. In the study, a PRGs-based prognostic model and a predictive model were constructed. These models are effective and robust in prediction the 1-, 3-, and 5-year survival of CRC patients.

Detect the expression of Farnesoid X Receptor(FXR), Multiple Drug Resistance Associated Protein-1(MRP-1) and Solute Carrier Family 7, Member 5 (SLC7A5) in hepatocellular carcinoma(HCC) of rat model, so as to provide new therapeutic targets for gene therapy of HCC. Sixty male Wistar rats were randomly divided into three groups. The rats in experimental group were given 0.2% diethylnitrosamine (DEN) by gavage with a dose of 10 mg/kg, 3 times a week, and it stopped at 12 weeks. The control group rats were given physiological saline by gavage, while the sham operation group did not receive anything by gavage. At 10 weeks, one rat in the experimental group was euthanized, and the changes of livers were recorded. The procedure was repeated at 12 weeks. After 12 weeks, HCC only occurred in the experimental group. After confirming the formation of the tumor through pathological examination, liver tissues and tumor tissues were taken from the three groups. FXR, MRP-1 and SLC7A5 expression in liver tissues and tumor tissues was detected. After 7 weeks the rats in experimental group ate less, and their weight was significantly reduced. Three months later, HCC was detected in 15 rats in the experimental group. The ratio of FXR/GAPDH mRNA, MRP-1/GAPDH mRNA, SLC7A5/GAPDH mRNA were significantly different among the three groups. Under the light microscope the FXR protein, MRP-1 protein, and SLC7A5 protein react with their respective antibodies, and they showed granular expression. Every pathological section included different numbers of positive cells in each group. FXR expression in HCC of rats was significantly lower than that in normal liver tissues, but MRP-1 and SLC7A5 expression in HCC were significantly higher than that in normal liver tissues, suggesting that drugs targeting FXR, MRP-1 and SLC7A5 may be new strategies for the treatment of HCC.

Purpose: This study aims to develop a data-collecting package ExpressMLC and investigate the applicability of MapCHECK2 for multileaf collimator (MLC) modeling and commissioning for complex radiation treatment plans. Materials and methods: The MLC model incorporates realistic parameters to account for sophisticated MLC features. A set of 8 single-beam plans, denoted by ExpressMLC, is created for the determination of parameters. For the commissioning of the MLC model, 4 intensity modulated radiation therapy (IMRT) plans specified by the AAPM TG 119 report were transferred to a computed tomography study of MapCHECK2, recalculated, and compared to measurements on a Varian accelerator. Both per-beam and composite-beam dose verification were conducted. Results: Through sufficient characterization of the MLC model, under 3%/2 mm and 2%/2 mm criteria, MapCHECK2 can be used to accurately verify per beam dose with gamma passing rate better than 90.9% and 89.3%, respectively, while the Gafchromic EBT3 films can achieve gamma passing rate better than 89.3% and 85.7%, respectively. Under the same criteria, MapCHECK2 can achieve composite beam dose verification with a gamma passing rate better than 95.9% and 90.3%, while the Gafchromic EBT3 films can achieve a gamma passing rate better than 96.1% and 91.8%; the p-value from the Mann Whitney test between gamma passing rates of the per beam dose verification using full MapCHECK2 package calibrated MLC model and film calibrated MLC model is .44 and .47, respectively; the p-value between those of the true composite beam dose verification is .62 and .36, respectively. Conclusion: It is confirmed that the 2-dimensional (2D) diode array MapCHECK2 can be used for data collection for MLC modeling with the combination of the ExpressMLC package of plans, whose doses are sufficient for the determination of MLC parameters. It could be a fitting alternative to films to boost the efficiency of MLC modeling and commissioning without sacrificing accuracy.