Technology in Cancer Research & Treatment最新文献

Objectives: Gastric cancer (GC) is one of the most prevalent malignancies worldwide, and early detection is crucial for improving patient survival rates. We aimed to identify immune infiltrating cell-related biomarkers in early gastric cancer (EGC) progression.

Methods: The GSE55696 and GSE130823 datasets with low-grade intraepithelial neoplasia (LGIN), high-grade intraepithelial neoplasia (HGIN), and EGC samples were downloaded from the Gene Expression Omnibus database to perform an observational study. Immune infiltration analysis was performed by single sample gene set enrichment analysis and Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data. Weighted gene co-expression network analysis was used to explore the co-expression modules and genes, and further enrichment analysis was performed on these genes. A protein-protein interaction (PPI) network of these genes was constructed to identify biomarkers associated with EGC progression. Screened hub genes were validated by the rank sum test and reverse transcription quantitative polymerase chain reaction.

Results: Immune scores were significantly elevated in EGC samples compared to LGIN and HGIN samples. The green-yellow module exhibited the strongest correlation with both immune score and disease progression. The 87 genes within this module were associated with the chemokine signaling pathways, the PI3K-Akt signaling pathways, leukocyte transendothelial migration, and Ras signaling pathways. Through PPI network analysis, the hub genes identified were protein tyrosine phosphatase receptor-type C (PTPRC), pleckstrin, CD53, CD48, lymphocyte cytosolic protein 1 (LCP1), hematopoietic cell-specific Lyn substrate 1, IKAROS Family Zinc Finger 1, Bruton tyrosine kinase, and Vav guanine nucleotide exchange factor 1. Notably, CD48, LCP1, and PTPRC showed high expression levels in EGC samples, with the remaining hub genes demonstrating a similar expression trend.

Conclusion: This study identified 9 immune cell-related biomarkers that may be actively involved in the progression of EGC and serve as potential targets for GC diagnosis and treatment.

Male breast cancer (MBC), one of the rare types of cancer among men where the global incidence rate is 1.8% of all breast cancers cases with a yearly increase in a pace of 1.1%. Since the last 10 years, the incidence has been increased from 7.2% to 10.3% and the mortality rate was decreased from 11% to 3.8%. Nevertheless, the rate of diagnoses has been expected to be around 2.6% in the near future, still there is a great lack in studies to characterize the MBC including the developed countries. Based on our search, it is evidenced from the literature that the number of risk factors for the cause of MBC are significant, which includes the increase in age, family genetic history, mutations in specific genes due to various environmental impacts, hormonal imbalance and unregulated expression receptors for specific hormones of high levels of estrogen or androgen receptors compared to females. MBCs are broadly classified into ductal and lobular carcinomas with further sub-types, with some of the symptoms including a lump or swelling in the breast, redness of flaky skin in the breast, irritation and nipple discharge that is similar to the female breast cancer (FBC). The most common diagnostic tools currently in use are the ultrasound guided sonography, mammography, and biopsies. Treatment modalities for MBC include surgery, radiotherapy, chemotherapy, hormonal therapy, and targeted therapies. However, the guidelines followed for the diagnosis and treatment modalities of MBC are mostly based on FBC that is due to the lack of prospective studies related to MBC. However, there are distinct clinical and molecular features of MBC, it is a need to develop different clinical methods with more multinational approaches to help oncologist to improve care for MBC patients.

Background: Strategies to minimize the impact of the COVID-19 pandemic led to a reduction in diagnostic testing. It is important to assess the magnitude and duration of this impact to plan ongoing care and avoid long-lasting impacts of the pandemic. Objective: We examined the association between the COVID-19 pandemic and the rate of diagnostic tests for breast, cervical, and colorectal cancer in Manitoba, Canada. Design and Participants: A population-based, cross-sectional study design with an interrupted time series analysis was used that included diagnostic tests from January 1, 2015 until August 31, 2022. Setting: Manitoba, Canada. Main Outcomes: Outcomes included mammogram, breast ultrasound, colposcopy, and colonoscopy rates per 100,000. Cumulative and percent cumulative differences between the fitted and counterfactual number of tests were estimated. Mean, median, and 90th percentile number of days from referral to colonoscopy date by referral type (elective, semiurgent, urgent) were determined. Results: In April 2020, following the declaration of the COVID-19 public health emergency, bilateral mammograms decreased by 77%, unilateral mammograms by 70%, breast ultrasounds by 53%, colposcopies by 63%, and colonoscopies by 75%. In Winnipeg (the largest urban center in the province), elective and semiurgent colonoscopies decreased by 76% and 39%, respectively. There was no decrease in urgent colonoscopies. As of August 2022, there were an estimated 7270 (10.7%) fewer bilateral mammograms, 2722 (14.8%) fewer breast ultrasounds, 836 (3.3%) fewer colposcopies, and 11 600 (13.8%) fewer colonoscopies than expected in the absence of COVID-19. As of December 2022, in Winnipeg, there were an estimated 6030 (23.9%) fewer elective colonoscopies, 313 (2.6%) fewer semiurgent colonoscopies, and 438 (27.3%) more urgent colonoscopies. Conclusions: In Manitoba, the COVID-19 pandemic was associated with sizable decreases in diagnostic tests for breast, colorectal, and cervical cancer. Two and a half years later, there remained large cumulative deficits in bilateral mammograms, breast ultrasounds, and colonoscopies.

Purpose: A daily quality assurance (QA) check in proton therapy is ensuring that the range of each proton beam energy in water is accurate to 1 mm. This is important for ensuring that the tumor is adequately irradiated while minimizing damage to surrounding healthy tissue. It is also important to verify the total charge collected against the beam model. This work proposes a time-efficient method for verifying the range and total charge of proton beams at different energies using a multilayer Faraday collector (MLFC).

Methods: We used an MLFC-128-250 MeV comprising 128 layers of thin copper foils separated by thin insulating Kapton^TM layers. Protons passing through the collector induce a charge on the metallic foils, which is integrated and measured by a multichannel electrometer. The charge deposition on the foils provides information about the beam range.

Results: Our results show that the proton beam range obtained using MLFC correlates closely with the range obtained from commissioning water tank measurements for all proton energies. Upon applying a range calibration factor, the maximum deviation is 0.4 g/cm². The MLFC range showed no dependence on the number of monitor units and the source-to-surface distance. Range measurements collected over multiple weeks exhibited stability. The total charge collected agrees closely with the theoretical charge from the treatment planning system beam model for low- and mid-range energies.

Conclusions: We have calibrated and commissioned the use of the MLFC to easily verify range and total charge of proton beams. This tool will improve the workflow efficiency of the proton QA.

Objectives: The purpose of this research is to summarize the structure of radiomics-based knowledge and to explore potential trends and priorities by using bibliometric analysis. Methods: Select radiomics-related publications from 2012 to October 2022 from the Science Core Collection Web site. Use VOSviewer (version 1.6.18), CiteSpace (version 6.1.3), Tableau (version 2022), Microsoft Excel and Rstudio's free online platforms (http://bibliometric.com) for co-writing, co-citing, and co-occurrence analysis of countries, institutions, authors, references, and keywords in the field. The visual analysis is also carried out on it. Results: The study included 6428 articles. Since 2012, there has been an increase in research papers based on radiomics. Judging by publications, China has made the largest contribution in this area. We identify the most productive institutions and authors as Fudan University and Tianjie. The top three magazines with the most publications are《FRONTIERS IN ONCOLOGY》, 《EUROPEAN RADIOLOGY》, and 《CANCERS》. According to the results of reference and keyword analysis, "deep learning, nomogram, ultrasound, f-18-fdg, machine learning, covid-19, radiogenomics" has been determined as the main research direction in the future. Conclusion: Radiomics is in a phase of vigorous development with broad prospects. Cross-border cooperation between countries and institutions should be strengthened in the future. It can be predicted that the development of deep learning-based models and multimodal fusion models will be the focus of future research. Advances in knowledge: This study explores the current state of research and hot spots in the field of radiomics from multiple perspectives, comprehensively, and objectively reflecting the evolving trends in imaging-related research and providing a reference for future research.

Background: One of the most significant characteristics of cancer is epithelial-mesenchymal transition and research on the relationship between phenolic compounds and anticancer medications and epithelial-mesenchymal transition is widespread. Methods: In order to investigate the potential effects of Taxifolin on enhancing the effectiveness of Epirubicin in treating breast cancer, specifically in 4T1 cells and an allograft BALB/c model, the effects of Taxifolin and Epirubicin, both individually and in combination, were examined. Cell viability assays and cytotoxicity assays in 4T1 cells were performed. In addition, 4T1 cells were implanted into female BALB/c mice to conduct in vivo studies and evaluate the therapeutic efficacy of Taxifolin and Epirubicin alone or in combination. Tumor volumes and histological analysis were also assessed in mice. To further understand the mechanisms involved, we examined the messenger RNA and protein levels of epithelial-mesenchymal transition-related genes, as well as active Caspase-3/7 levels, using quantitative real-time polymerase chain reaction, western blot, and enzyme-linked immunosorbent assays, respectively. Results: In vitro results demonstrated that the coadministration of Taxifolin and Epirubicin reduced cell viability and cytotoxicity in 4T1 cell lines. In vivo, coadministration of Taxifolin and Epirubicin suppressed tumor growth in BALB/c mice with 4T1 breast cancer cells. Additionally, this combination treatment significantly increased the levels of active caspase-3/7 and downregulated the messenger RNA and protein levels of N-cadherin, β-catenin, vimentin, snail, and slug, but upregulated the E-cadherin gene. It significantly decreased the messenger RNA levels of the Zeb1 and Zeb2 genes. Conclusion: The in vitro and in vivo results of our study indicate that the concurrent use of Epirubicin with Taxifolin has supportive effects on breast cancer treatment.

Introduction: We aimed to modify the LR-5 strategy to improve the diagnostic sensitivity for hepatocellular carcinoma (HCC) in high-risk patients while maintaining specificity. Methods: This study retrospectively analyzed 412 patients with 445 liver observations who underwent preoperative gadolinium ethoxybenzyl DTPA (GD-EOB-DTPA)-enhanced MRI followed by surgical procedures or biopsies. All observations were classified according to LI-RADS v2018, and the classifications were adjusted by modifying major features (MF)(substituting threshold growth with a more HCC-specific ancillary features (AF): presence of blood products within the mass, arterial phase hyperenhancement (APHE) was interpreted with hypointensity on precontrast imaging- isointensity in arterial phase (AP) and extending washout to transitional phase (TP)(2 min)). The specificity, sensitivity, and positive predictive value (PPV) were assessed to compare LR-5 (definitely HCC) diagnostic efficacy between LI-RADS version 2018 and modified LI-RADS. Results: Apart from nonenhancing "capsule", the interreader agreement of MFs and HCC-specific AFs between the two readers reached substantial or excellent ranges (κ values ranging from 0.631 to 0.911). According to LI-5 v2018, the specificity, sensitivity and PPV of HCC were 90.74%, 82.35%, and 98.17%, respectively. Based on a more HCC-specific AF, signal intensity in AP and TP (2 min), the sensitivity of the three modified strategies were 86.19%, 93.09%, 96.67% (P < .05)), while maintaining high specificity and PPV rates at 88.89% and 98.25% (P > .05) Conclusion: Further investigation into the efficacy of threshold growth as a MF is warranted. By utilizing GD-EOB-DTPA-enhanced MRI, enhancing the sensitivity of the modified LR-5 category may be achieved without compromising specificity and PPV in diagnosing HCC among high-risk patients.

Objective: To develop and validate predictive models based on clinical parameters, and radiomic features to distinguish pulmonary pure invasive mucinous adenocarcinoma (pIMA) from mixed mucinous adenocarcinoma (mIMA) before surgery. Method: From January 2017 to December 2022, 193 pIMA and 111 mIMA were retrospectively analyzed at our hospital in this retrospective study. From contrast-enhanced computed tomography, 1037 radiomic features were extracted. The patients were randomly divided into a training group and a test group (n = 213 and 91, respectively) in a 7:3 ratio. The least absolute shrinkage and selection operator algorithm was used to select radiomic features. In this study, 9 machine learning radiomics prediction models were applied. The radiomics score was then calculated based on the best-performing machine learning model adopted. The clinical model was developed using the same machine learning model of radiomics. In the end, a combined model based on clinical factors and radiomics features was developed. The area under the receiver operating characteristic curve (AUC) value and decision curve analysis (DCA) were used to evaluate the clinical usefulness of the prediction model. Results: The combined model established by the Gaussian Naive Bayes machine learning method exhibited the best performance. The AUC of the combined model, clinical model, and radiomics model were 0.81, 0.80, and 0.68 in the training group and 0.91, 0.80, and 0.81 in the test group, respectively. The Brier scores of the combined model were 0.171 and 0.112. The DCA curve also showed that the combined model was beneficial to clinical settings. Conclusion: The combined model integration of radiomics features and clinical parameters may have potential value for the preoperative differentiation of pIMA from mIMA.

Introduction: In recent years, the development of drug-eluting embolization beads that can be imaged has become a hot research topic in regard to meeting clinical needs. In our previous study, we successfully developed nano-assembled microspheres (NAMs) for multimodal imaging purposes. NAMs can not only be visualized under CT/MR/Raman imaging but can also load clinically required doses of doxorubicin. It is important to systematically compare the pharmacokinetics of NAMs with those of commercially available DC Beads and CalliSpheres to evaluate the clinical application potential of NAMs. Methods: In our study, we compared NAMs with two types of drug-eluting beads (DEBs) in terms of irinotecan, drug-loading capacity, release profiles, microsphere diameter variation, and morphological characteristics. Results: Our results indicate that NAMs had an irinotecan loading capacity similar to those of DC Beads and CalliSpheres but exhibited better sustained release in vitro. Conclusion: NAMs have great potential for application in transcatheter arterial chemoembolization for the treatment of colorectal cancer liver metastases.