Cancer Research Articles

Lexicon for blood-based early detection and screening: BLOODPAC consensus document.

In the United States, 2.0 million new cancer cases and around 600,000 cancer deaths are estimated to occur in 2024. Early detection gives cancer patients the best chance for treatment success. Currently, cancer screening in the general population is recommended for a limited set of cancers; as a result, most cancer types are not regularly screened. Thus, in recent years, we have seen a wave of novel, non-invasive, single- and multi-cancer detection tests (SCD and MCD), promising detection of cancer signals prior to the onset of symptoms and/or clinical diagnosis. To accelerate the development, access, and adoption of these tests, the Blood Profiling Atlas in Cancer (BLOODPAC) Consortium, a collaborative infrastructure for developing standards and best practices, established the Early Detection & Screening (ED&S) Working Group. The early detection space is in need of consensus around definitions for SCD and MCD tests that harmonize terminology across diverse stakeholders, thereby reducing communication barriers and ultimately advancing the discipline. To this end, the ED&S Working Group compiled a lexicon of terms, chosen based on perceived importance, frequency of use, lack of clarity, and unique challenges in the context of SCD and MCD tests. This lexicon was submitted to the FDA for their feedback, which was incorporated. In this work, we present the first installment of the lexicon, consisting of 14 primary terms, that will be part of an online dictionary and provide a foundation for future projects of BLOODPAC's ED&S Working Group.

Mechanistic insights into behavioral clusters associated with cancer-related systemic inflammatory response.

This focused, narrative review mostly describes our team's investigations into the potential inflammatory mechanisms that contribute to the development of cancer-related gastrointestinal (GI) mucositis and its associated symptoms. This review summarizes details of our clinical and preclinical findings to test the role of inflammation in the development and occurrence of these cancer-related conditions. GI mucositis (GIM) is a common, distressing condition reported by cancer patients. GIM is often clustered with other behaviors including fatigue, pain, anorexia, depression, and diarrhea. It is hypothesized that there is a common biologic mechanism underpinning this symptom cluster. Our multi-platform investigations revealed that GIM and its associated cluster of behaviors may be triggered by local inflammation spreading systemically causing pro-inflammatory-mediated toxicities, leading to alterations in immune, metabolic, and nervous system functions and activities. For example, behavioral toxicities related to local irradiation for non-metastatic cancer may be triggered by mGluR5 activation influencing prolonged T cell as well as NF-κB transcription factor activities. Thus, interventions targeting inflammation and associated pathways may be a reasonable strategy to alleviate GIM and its symptom cluster. GIM may be a sign of a broader systemic inflammatory response triggered by cancer or its treatment. Addressing GIM and its associated symptoms primarily involves supportive care strategies focused on relieving symptoms, promoting healing, and preventing complications.

High-level tumour methylation of BRCA1 and RAD51C is required for homologous recombination deficiency in solid cancers.

In ovarian and breast cancer, promoter methylation of BRCA1 or RAD51C is a promising biomarker for PARP inhibitor response, as high levels lead to homologous recombination deficiency (HRD). Yet the extent and role of such methylation in other cancers is not clear. This study comprehensively investigated promoter methylation of eight homologous recombination repair genes across 23 solid cancer types. Here, we showed that BRCA1 methylated cancers were associated with reduced gene expression, loss of heterozygosity (LOH), TP53 mutations and genomic features of HRD. We identified BRCA1 methylation in 3% of the copy-number high subtype of endometrial cancer, and as a rare event in six other cancer types, including lung squamous cell, pancreatic, bladder and stomach cancer. RAD51C promoter methylation was widespread across multiple cancer types, but HRD features were only observed for cases which contained high-level tumour methylation and LOH of RAD51C. While RAD51C methylation was frequent in stomach adenocarcinoma (6%) and low-grade glioma (2.5%), it was mostly detected at a low tumour level, suggestive of heterozygous methylation, and was associated with CpG island methylator phenotype. Our findings indicate that high-level tumour methylation of BRCA1 and RAD51C should be explored as a PARP inhibitor biomarker across multiple cancers.

Natural STAT3 Inhibitors for Cancer Treatment: A Comprehensive Literature Review.

Cancer is one of the leading causes of mortality and morbidity worldwide, affecting millions of people physically and financially every year. Over time, many anticancer treatments have been proposed and studied, including synthetic compound consumption, surgical procedures, or grueling chemotherapy. Although these treatments have improved the daily life quality of patients and increased their survival rate and life expectancy, they have also shown significant drawbacks, including staggering costs, multiple side effects, and difficulty in compliance and adherence to treatment. Therefore, natural compounds have been considered a possible key to overcoming these problems in recent years, and thorough research has been done to assess their effectiveness. In these studies, scientists have discovered a meaningful interaction between several natural materials and signal transducer and activator of transcription 3 molecules. STAT3 is a transcriptional protein that is vital for cell growth and survival. Mechanistic studies have established that activated STAT3 can increase cancer cell proliferation and invasion while reducing anticancer immunity. Thus, inhibiting STAT3 signaling by natural compounds has become one of the favorite research topics and an attractive target for developing novel cancer treatments. In the present article, we intend to comprehensively review the latest knowledge about the effects of various organic compounds on inhibiting the STAT3 signaling pathway to cure different cancer diseases.

Blood Pressure and Cardiovascular Risk in Women With Breast Cancer: The Pathways Heart Study

BackgroundHypertension is an important contributor to cardiovascular disease (CVD) in breast cancer (BC) survivors; however, research on blood pressure (BP) and CVD outcomes in BC survivors is limited. ObjectivesThe purpose of this study was to better characterize the association between BP and CVD in a large, longitudinal cohort of BC patients. MethodsWomen with invasive BC diagnosed from 2005 to 2013 at Kaiser Permanente Northern California were matched 1:5 to women without BC. Patient data were obtained from electronic health records. Multivariable Cox regression and penalized spline models were used to explore the linear and nonlinear relationship of systolic blood pressure (SBP) and diastolic blood pressure (DBP) on CVD outcomes. ResultsBC cases (n = 12,713) and controls (n = 55,886) had median follow-up of 9.6 years (IQR: 5.0-11.9 years). Women with BC had a mean age of 60.6 years; 64.8% were non-Hispanic White. For ischemic heart disease (IHD), every 10 mmHg increase in SBP and DBP was associated with 1.23 (95% CI: 1.14-1.33) and 1.10 (95% CI: 0.98-1.24) risk, respectively, in women with BC. For stroke, every 10 mmHg increase in SBP and DBP was associated with a 1.45 (95% CI: 1.34-1.58) and 1.91 (95% CI: 1.68-2.18) risk, respectively. A U-shaped relationship was observed between heart failure/cardiomyopathy and BP. The associations between BP and risk of IHD, stroke, and any primary CVD were not statistically different comparing women with BC to controls, but risks varied by BC status for heart failure/cardiomyopathy (P for interaction = 0.01). ConclusionsWomen with and without BC showed similar risks for IHD, stroke, and any primary CVD suggesting similar BP targets should be pursued regardless of BC survivorship status.

Evaluating nutrition in advanced ovarian cancer: which biomarker works best?

BackgroundAdvanced epithelial ovarian cancer (OC) patients often present with malnutrition; however, the ideal nutritional evaluation tool is unclear. We aimed to evaluate the role of preoperative albumin, Prognostic Nutritional Index [PNI], neutrophil-to-lymphocyte ratio [NLR], and platelet-to-lymphocyte ratio [PLR] as independent predictors of severe postoperative complications and 90-day mortality in OC patients who underwent primary cytoreductive surgery to identify the ideal tool. MethodsOC patients who underwent surgery at Mayo Clinic (2003–2018) were included; biomarkers were retrospectively retrieved and established cut-offs were utilized. Outcomes included severe complications (Accordion grade ≥ 3) and 90-day mortality. Univariate and multivariable logistic regression models were performed. Biomarkers were evaluated in separate models adjusted for age and American Society of Anesthesiologists (ASA) score for 90-day mortality, and adjusted for age, ASA score, stage, and surgical complexity for severe complications. ResultsAlbumin <3.5 g/dL, PNI < 45, NLR > 6 and PLR ≥ 200 were univariately associated with 90-day mortality (all p < 0.05) in 627 patients that met inclusion criteria. Each marker remained significant in adjusted models with albumin having the highest OR: 6.04 [95% CI:2.80–13.03] and AUC (0.83). Univariately, PNI <45, NLR >6, and PLR ≥200 were significant predictors of severe complications(all p < 0.05), however failed to reach significance in adjusted models. Albumin was not associated with severe complications. ConclusionAll biomarkers were associated with 90-day mortality in adjusted models, with albumin being the easiest predictor to attain clinically; none with severe complications. Future research should focus less on methods of nutritional assessment and more on strategies to improve nutrition during OC tumor-directed therapy.

SANAS-Net: spatial attention neural architecture search for breast cancer detection

&lt;p&gt;The utilization of mammography images plays a vital role in the prompt detection and treatment of breast cancer. Breast imaging techniques aid medical professionals in assessing the dimensions, morphology, and spatial orientation of breast lesions, facilitating the differentiation between benign and malignant conditions. Breast tissue can vary widely in terms of density, composition, and structure, leading to complexities in distinguishing between benign and malignant conditions. The primary contribution of this paper is the proposal of a spatial attention-based neural architecture search network (SANAS-Net) technique that incorporates a spatial attention mechanism, enabling the model to learn and prioritize key regions within mammograms (MMs). Multi-head attention is employed within the transformer blocks to effectively capture a wide range of spatial relations and feature interactions. Global contextual information was integrated into the transformer blocks by means of introducing positional embeddings. Several practical studies have been undertaken to verify the effectiveness of our methodology in identifying fully attentive networks that exhibit good performance in distinguishing between malignant and benign breast cancer cases. The experimental study reached a test accuracy of 89.95%, which is way higher than previously proposed algorithms for mammography imagebased breast cancer detection.&lt;/p&gt;

Hsa_circ_0000129 targets miR-383-5p/tropomyosin 3 axis to facilitate ovarian cancer progression.

Ovarian cancer is one of the most prevalent malignancies among women. CircRNAs play key roles in the progression of ovarian cancer. This study aimed to investigate the mechanism of action of hsa_circ_0000129 and its effects on ovarian cancer. Expression of hsa_circ_0000129, tropomyosin 3 (TPM3), and miR-383-5p in ovarian cancer cell lines and tissue specimens was detected using qRT-PCR or western blotting. Cell counting kit-8 (CCK-8), colony formation, and transwell assays were performed to assess viability, proliferation, and migration of ovarian cancer cells. A xenograft model was used to study tumorigenicity of ovarian cancer cells in vivo. Luciferase and RNA immunoprecipitation assays were performed to determine binding between miR-383-5p and hsa_circ_0000129 or TPM3. Upregulation of hsa_circ_0000129 and TPM3 and downregulation of miR-383-5p were observed in ovarian cancer. Low hsa_circ_0000129 and TPM3 expression repressed viability, migration, and proliferation of ovarian cancer cells. Inhibition of miR-383-5p had a contrary effect. Furthermore, knockdown of hsa_circ_0000129 restricted the tumorigenicity of ovarian cancer cells. Mechanistically, hsa_circ_0000129 has a sponging effect on miR-383-5p, which targets TPM3. Hsa_circ_0000129 stimulated development of the malignant ovarian cancer phenotype by sponging miR-383-5p and releasing TPM3.

The role of SRC-3 in prostate cancer progression and implications for therapeutic targeting: A systematic review

Context: Prostate cancer remains a significant global health concern, and understanding the molecular drivers of this disease is crucial for developing effective diagnostic and therapeutic strategies. Steroid receptor coactivator-3 (SRC-3), a member of the SRC family, has emerged as a key player in prostate cancer pathogenesis. Aims: To examine the role of SRC-3 in prostate cancer, encompassing molecular mechanisms, clinical implications, and therapeutic opportunities. Methods: A systematic literature search following PRISMA guidelines was conducted in PubMed, PMC, and other relevant databases to identify studies that investigate SRC-3 in prostate cancer. Results: 785 articles were retrieved from databases using specific keywords and MeSH terms related to SRC-3 and Prostate Cancer. After removing 461 duplicates, 260 articles were excluded based on title and abstract review. Subsequently, a comprehensive screening by three researchers resulted in 47 relevant articles for this systematic review. Evidence suggests that SRC-3 expression correlates with prostate cancer aggressiveness, disease recurrence, and poor patient outcomes. Its potential as a diagnostic biomarker and therapeutic target if explored, offers insights into personalized medicine approaches. Conclusions: SRC-3 plays a pivotal role in prostate cancer, influencing disease progression and clinical outcomes. Understanding the molecular intricacies of SRC-3 in prostate cancer offers new opportunities for precision medicine and innovative therapeutic approaches. This review provides a comprehensive overview of SRC-3's involvement in prostate cancer, emphasizing its clinical relevance and potential as a therapeutic target, ultimately contributing to improved patient care in the era of personalized oncology.

The mechanisms of diseases and global approaches

New approaches for elucidating mechanisms of diseases including environmental diseases, cancer, metabolic diseases, infectious diseases are challenging. After the presentation on elucidating the mechanism of cancer and infectious diseases, lectures by Dr. Tae-Young Kim (Korea) on metabolic deuterium oxide labeling in environmental diseases, Dr. Rosalia Rodriguez-Rodriguez (Spain) on targeting the hypothalamus with nanomedicines to treat metabolic diseases, Dr. Chang-Beom Park (Korea) on methodological approach for evaluation of the environmental diseases were presented. The deeper understanding of the global research approaches on diseases will be expected based on the fruitful discussion at the international symposium.

Prevalence of exocrine pancreatic insufficiency at 12 months after acute pancreatitis: a prospective, multicentre, longitudinal cohort study

Exocrine Pancreatic insufficiency (EPI) occurs following acute pancreatitis (AP) at variably reported rates and with unclear recovery timeline. The aim of this study was to establish the prevalence and predictors of EPI at 12 months after AP in a prospective cohort. In this prospective, multicentre, longitudinal cohort study, adult participants (≥18 years) admitted to the hospital with an AP attack (defined by Revised Atlanta Classification) were enrolled in a United States multi-centre longitudinal cohort (Sites: The Ohio State University, University of Pittsburgh, and Johns Hopkins University). Patients were excluded if they had pancreatic cancer, chronic pancreatitis, or malabsorptive disease (including previously diagnosed EPI). Participant data was obtained by interview and by review of the electronic medical record. EPI was assessed by stool fecal elastase (FE-1) levels collected at baseline, 3 months, and 12 months (primary endpoint). EPI was defined by FE-1 <200μg/g; severe FE-1 level ≤100μg/g; mild FE-1 101-200μg/g. Multivariable logistic regression was used to identify predictors of EPI at 12 months. This study is registered with ClinicalTrials.gov, NCT03063398. EPI was observed in 29 (34.1%) of the 85 participants [44 (51.8%) male, mean age 54.7±14.1 years] who provided stool samples at 12 months. For the study overall, participants were recruited between June 22, 2017 and October 18, 2021. A total of 5794 individuals were screened, 311 of whom were eligible for the study. 112 participants provided stool samples at baseline, 79 completed stool samples at 3 months, and 85 completed samples at 12 months. 64 participants included samples at all 3 timepoints. In univariable analysis, factors significantly associated with EPI at 12 months included recurrent (versus index) AP, pre-existing diabetes, alcohol, and idiopathic etiologies, and increasing severity of AP. In multivariable analysis, the odds of having EPI at 12 months increased 4-fold with idiopathic AP etiology (Odds Ratio 4.095, 95% Confidence Interval [CI] 1.418, 11.826), and 3-fold with moderately severe or severe AP (Odds Ratio 3.166, 95% CI 1.156, 8.670), and baseline diabetes mellitus (Odds Ratio 3.217, 95% CI 1.113, 9.298). Even individuals with an index mild attack of AP (n=39) developed severe EPI at 12 months (prevalence 12.8%). EPI as diagnosed by FE-1 is present in over one third of prospectively assessed patients at 12 months post-AP. Since EPI develops in patients with mild AP, investigations are needed to understand the mechanisms of injury and identify methods for tailored screening. This study was supported by an Investigator Initiated Research Grant from AbbVie, Inc.

Asbestos exposure and asbestosis mortality in Italian cement-asbestos cohorts: Dose-response relationship and the role of competing death causes.

In Italy, asbestos was used intensively until its ban in 1992, which was extended for asbestos cement factories until 1994. The aim of this study was to evaluate the dose-response between asbestos exposure and asbestosis mortality across a pool of Italian occupational cohorts, taking into account the presence of competing risks. Cohorts were followed for vital status and the cause of death was ascertained by a linkage with mortality registers. Cause-specific (CS) Cox-regression models were used to evaluate the dose-exposure relationship between asbestosis mortality and the time-dependent cumulative exposure index (CEI) to asbestos. Fine and Gray regression models were computed to assess the effect of competing risks of death. The cohort included 12,963 asbestos cement workers. During the follow-up period (1960-2012), of a total of 6961 deaths, we observed 416 deaths attributed to asbestosis, 879 to lung cancer, 400 to primary pleural cancer, 135 to peritoneal cancer, and 1825 to diseases of the circulatory system. The CS model showed a strong association between CEI and asbestosis mortality. Dose-response models estimated an increasing trend in mortality even below a CEI of 25 ff/mL-years. Lung cancer and circulatory diseases were the main competing causes of death. Asbestos exposure among Italian asbestos-cement workers has led to a very high number of deaths from asbestosis and asbestos-related diseases. The increasing risk trend associated with excess deaths, even at low exposure levels, suggests that the proposed limit values would not have been adequate to prevent disability and mortality from asbestosis.

Advances in Oral Exfoliative Cytology: From Cancer Diagnosis to Systemic Disease Detection.

Oral exfoliative cytology has emerged as a valuable tool in the early detection of oral cancer and other systemic diseases. This review comprehensively examines the current applications and recent advancements in oral exfoliative cytology techniques. We analyzed published literature from the past decade, focusing on methodological improvements, diagnostic accuracy, and emerging applications. Key findings include: (1) Enhanced cell collection and preparation methods have significantly improved sample quality and diagnostic reliability. (2) Integration of molecular markers and DNA analysis with traditional cytomorphological assessment has increased diagnostic sensitivity and specificity for oral cancer detection. (3) Novel applications in systemic disease detection, including diabetes and iron overload disorders, demonstrate the expanding utility of this technique. (4) Computer-assisted analysis and deep learning algorithms show promise in improving diagnostic accuracy and efficiency. Despite these advancements, challenges remain in standardization and widespread clinical implementation. This review provides a critical evaluation of oral exfoliative cytology's current status and future potential in oral and systemic disease diagnosis.

Nuclear Imaging Modalities in the Diagnosis and Management of Thyroid Cancer.

In this review we have brought forward various nuclear imaging modalities used in the diagnosis, staging, and management of thyroid cancer. Thyroid cancer is the most common endocrine malignancy, accounting for approximately 3% of all new cancer diagnoses. Nuclear imaging plays an important role in the evaluation of thyroid cancer, and the use of radioiodine imaging, FDG imaging, and somatostatin receptor imaging are all valuable tools in the management of this disease. Radioiodine imaging involves the use of Iodine-123 [I-123] or Iodine-131 [I-131] to evaluate thyroid function and detect thyroid cancer. I-123 is a gamma-emitting isotope that is used in thyroid imaging to evaluate thyroid function and detect thyroid nodules. I-131 is a beta-emitting isotope that is used for the treatment of thyroid cancer. Radioiodine imaging is used to detect the presence of thyroid nodules and evaluate thyroid function. FDG imaging is a PET imaging modality that is used to evaluate the metabolic activity of thyroid cancer cells. FDG is a glucose analogue that is taken up by cells that are metabolically active, such as cancer cells. FDG PET/CT can detect primary thyroid cancer and metastatic disease, including lymph nodes and distant metastases. FDG PET/CT is also used to monitor treatment response and detect the recurrence of thyroid cancer. Somatostatin receptor imaging involves the use of radiolabeled somatostatin analogues to detect neuroendocrine tumors, including thyroid cancer. Radiolabeled somatostatin analogues, such as Indium-111 octreotide or Gallium-68 DOTATATE, are administered to the patient, and a gamma camera is used to detect areas of uptake. Somatostatin receptor imaging is highly sensitive and specific for the detection of metastatic thyroid cancer. Methods: A comprehensive search of relevant literature was done using online databases of PubMed, Embase, and Cochrane Library using the keywords "thyroid cancer," "nuclear imaging," "radioiodine imaging," "FDG PET/CT," and "somatostatin receptor imaging" to identify relevant studies to be included in this review. Conclusion: Nuclear imaging plays an important role in the diagnosis, staging, and management of thyroid cancer. The use of radioiodine imaging, thyroglobulin imaging, FDG imaging, and somatostatin receptor imaging are all valuable tools in the evaluation of thyroid cancer. With further research and development, nuclear imaging techniques have the potential to improve the diagnosis and management of thyroid cancer and other endocrine malignancies.

Coping with modesty during radiotherapy for breast cancer: a multicentric study.

Breast cancer is the most frequently diagnosed tumour, representing nearly 30% of all new cases in women. Radiotherapy (RT) plays a crucial role in the management of breast cancer. The objective of this study is to assess modesty in patients undergoing RT for breast cancer and take their suggestions and ideas into consideration to enhance the quality of treatment in this regard. The study enrolled 555 breast cancer patients undergoing adjuvant RT in three Italian centres. Patients completed a self-test questionnaire assessing their comfort level concerning modesty during therapy and their relationship with strangers and healthcare professionals. The impact of religious views and potential changes in sexuality were also examined. Results showed that modesty was a common concern across the overall cohort of patients, with discomfort in being undressed during RT correlating with discomfort experienced in other daily life situations. Most patients felt more at ease with same sex healthcare workers. Age was also a major factor with younger patients generally feeling more comfortable with healthcare workers of the same age group. Interestingly, the surgical technique used (mastectomy vs. quadrantectomy) did not significantly influence modesty perceptions. Patients provided valuable suggestions to improve privacy and modesty during RT. This study demonstrates that modesty is an important issue for women undergoing RT, which can be influenced by personal characteristics and hospital-related factors. A reflection about the need to address modesty concerns and to incorporate dedicated interventions for protecting patients' physical and emotional well-being is warranted. Initiatives to improve communication, involvement, and body image support should also be integrated into the care path of patients to better their overall therapeutic experience. This study paves the way for broader research and interventions in daily cancer care.

Advancements in Biotechnology and Stem Cell Therapies for Breast Cancer Patients.

This comprehensive review article examines the integration of biotechnology and stem cell therapy in breast cancer diagnosis and treatment. It discusses the use of biotechnological tools such as liquid biopsies, genomic profiling, and imaging technologies for accurate diagnosis and monitoring of treatment response. Stem cell-based approaches, their role in modeling breast cancer progression, and their potential for breast reconstruction post-mastectomy are explored. The review highlights the importance of personalized treatment strategies that combine biotechnological tools and stem cell therapies. Ethical considerations, challenges in clinical translation, and regulatory frameworks are also addressed. The article concludes by emphasizing the potential of integrating biotechnology and stem cell therapy to improve breast cancer outcomes, highlighting the need for continued research and collaboration in this field.

Transparent precision: Explainable AI empowered breast cancer recommendations for personalized treatment

&lt;p&gt;Breast cancer stands as a prevalent global concern, prompting extensive research into its origins and personalized treatment through Artificial Intelligence (AI)-driven precision medicine. However, AI's black box nature hinders result acceptance. This study delves into Explainable AI (XAI) integration for breast cancer precision medicine recommendations. Transparent AI models, fuelled by patient data, enable personalized treatment recommendations. Techniques like feature analysis and decision trees enhance transparency, fostering trust between medical practitioners and patients. This harmonizes AI's potential with the imperative for clear medical decisions, propelling breast cancer care within the precision medicine era. This research work is dedicated to leveraging clinical and genomic data from samples of metastatic breast cancer. The primary aim is to develop a machine learning (ML) model capable of predicting optimal treatment approaches, including but not limited to hormonal therapy, chemotherapy, and anti-HER2 therapy. The objective is to enhance treatment selection by harnessing advanced computational techniques and comprehensive data analysis. A decision tree model developed here for the prediction of suitable personalized treatment for breast cancer patients achieves 99.87% overall prediction accuracy. Thus, the use of XAI in healthcare will build trust in doctors as well as patients.&lt;/p&gt;

EDA2R-NIK signaling in cancer cachexia.

Cachexia is a debilitating condition causing weight loss and skeletal muscle wasting that negatively influences treatment and survival of cancer patients. The objective of this review is to describe recent discoveries on the role of a novel signaling pathway involving ectodysplasin A2 receptor (EDA2R) and nuclear factor κB (NFκB)-inducing kinase (NIK) in muscle atrophy. Studies identified tumor-induced upregulation of EDA2R expression in muscle tissues in pre-clinical cachexia models and patients with various cancers. Activation of EDA2R by its ligand promoted atrophy in cultured myotubes and muscle tissue, which depended on NIK activity. The non-canonical NFκB pathway via NIK also stimulated muscle atrophy. Mice lacking EDA2R or NIK were protected from muscle loss due to tumors. Tumor-induced cytokine oncostatin M (OSM) upregulated EDA2R expression in muscles whereas OSM receptor-deficient mice were resistant to muscle wasting. Recent discoveries revealed a mechanism involving EDA2R-NIK signaling and OSM that drives cancer-associated muscle loss, opening up new directions for designing anti-cachexia treatments. The therapeutic potential of targeting this mechanism to prevent muscle loss should be further investigated. Future research should also explore broader implications of the EDA2R-NIK pathway in other muscle wasting diseases and overall muscle health.

Characterizing Sentinel Lymph Node Status in Breast Cancer Patients Using a Deep-Learning Model Compared With Radiologists' Analysis of Grayscale Ultrasound and Lymphosonography.

The objective of the study was to use a deep learning model to differentiate between benign and malignant sentinel lymph nodes (SLNs) in patients with breast cancer compared to radiologists' assessments.Seventy-nine women with breast cancer were enrolled and underwent lymphosonography and contrast-enhanced ultrasound (CEUS) examination after subcutaneous injection of ultrasound contrast agent around their tumor to identify SLNs. Google AutoML was used to develop image classification model. Grayscale and CEUS images acquired during the ultrasound examination were uploaded with a data distribution of 80% for training/20% for testing. The performance metric used was area under precision/recall curve (AuPRC). In addition, 3 radiologists assessed SLNs as normal or abnormal based on a clinical established classification. Two-hundred seventeen SLNs were divided in 2 for model development; model 1 included all SLNs and model 2 had an equal number of benign and malignant SLNs. Validation results model 1 AuPRC 0.84 (grayscale)/0.91 (CEUS) and model 2 AuPRC 0.91 (grayscale)/0.87 (CEUS). The comparison between artificial intelligence (AI) and readers' showed statistical significant differences between all models and ultrasound modes; model 1 grayscale AI versus readers, P = 0.047, and model 1 CEUS AI versus readers, P < 0.001. Model 2 r grayscale AI versus readers, P = 0.032, and model 2 CEUS AI versus readers, P = 0.041.The interreader agreement overall result showed κ values of 0.20 for grayscale and 0.17 for CEUS.In conclusion, AutoML showed improved diagnostic performance in balance volume datasets. Radiologist performance was not influenced by the dataset's distribution.

Design, Molecular Docking and Molecular Dynamic Simulation of New Heterocyclic Derivatives as Potential Anticancer Agents

Background: Despite significant progress in the development of anticancer medications, obstacles such as drug resistance, poor efficacy, and excessive toxicity have significantly impacted the daily lives of cancer patients. Consequently, the search for highly selective, effective, and non-toxic molecules remains a major challenge for cancer researchers. Objective: To utilize a computer program for evaluating new benzothiophene derivatives to investigate how they influence the estrogen-related receptor-gamma (ERRγ) active sites as anticancer agents. Methods: The molecular docking method used the Cambridge Crystallographic Data Centre's (CCDC) Genetic Optimization for Ligand Docking (GOLD) tool. We used the Desmond modules of the Schrodinger 2023 to perform MDS on the derivative with the highest docking score. The Swiss ADME server then assessed our drugs' pharmacokinetic profile, which included how well they crossed the blood-brain barrier (BBB), bound to P-gp, and were bioavailable. Results: The compounds were docked with the ERRγ crystal structure (2GPV) to assess their binding affinity to active sites. One of them earned a high score (102.62), and six compounds had a higher binding energy than the gold standard medication, tamoxifen. The molecular dynamic simulation analysis found that compound 1 closely matched the ERRγ based on RMSD and RMSF data. After examining the ADME study of practically active substances, they follow Lipinski's laws and other pharmacokinetic features. Conclusions: These chemicals have the potential to act as precursors in the development of new anticancer medicines.