Evaluation of a blood miRNA/mRNA signature to follow-up Lu-PRRT therapy for G1/G2 intestinal neuroendocrine tumors.

Background: 177Lu-oxodotreotide peptide receptor therapy (LuPRRT) is an efficient treatment for midgut neuroendocrine tumors (NETs) of variable radiological response. Several clinical, biological, and imaging parameters may be used to establish a relative disease prognosis but none is able to predict early efficacy or toxicities. We investigated expression levels for mRNA and miRNA involved in radiosensitivity and tumor progression searching for correlations related to patient outcome during LuPRRT therapy. Methods: Thirty-five patients received LuPRRT for G1/G2 midgut NETs between May 2019 and September 2021. Peripheral blood samples were collected prior to irradiation, before and 48 h after the second and the fourth LuPRRT, and at 6-month follow-up. Multiple regression analyses and Pearson correlations were performed to identify the miRNA/mRNA signature that will best predict response to LuPRRT. Results: Focusing on four mRNAs and three miRNAs, we identified a miRNA/mRNA signature enabling the early identification of responders to LuPRRT with significant reduced miRNA/mRNA expression after the first LuPRRT administration for patients with progressive disease at 1 year (p < 0.001). The relevance of this signature was reinforced by studying its evolution up to 6 months post-LuPRRT. Moreover, nadir absolute lymphocyte count within the first 2 months after the first LuPRRT administration was significantly related to low miRNA/mRNA expression level (p < 0.05) for patients with progressive disease. Conclusion: We present a pilot study exploring a miRNA/mRNA signature that correlates with early hematologic toxicity and therapeutic response 12 months following LuPRRT. This signature will be tested prospectively in a larger series of patients.

Improving colorectal cancer screening programs.

In this editorial we comment on the article by Agatsuma et al published in the World Journal of Gastroenterology. They suggest policies for more effective colorectal screening. Screening is the main policy that has led to lower mortality rates in later years among the population that was eligible for screening. Colonoscopy is the gold standard tool for screening and has preventive effects by removing precancerous or early malignant polyps. However, colonoscopy is an invasive process, and fecal tests such as the current hemoglobin immunodetection were developed, followed by endoscopy, as the general tool for population screening, avoiding logistical and economic problems. Even so, participation and adherence rates are low. Different screening options are being developed with the idea that if people could choose between the ones that best suit them, participation in population-based screening programs would increase. Blood tests, such as a recent one that detects cell-free DNA shed by tumors called circulating tumor DNA, showed a similar accuracy rate to stool tests for cancer, but were less sensitive for advanced precancerous lesions. At the time when the crosstalk between the immune system and cancer was being established as a new hallmark of cancer, novel immune system-related biomarkers and information on patients' immune parameters, such as cell counts of different immune populations, were studied for the early detection of colorectal cancer, since they could be effective in asymptomatic people, appearing earlier in the adenoma-carcinoma development compared to the presence of fecal blood. sCD26, for example, detected 80.37% of advanced adenomas. To reach as many eligible people as possible, starting at an earlier age than current programs, the direction could be to apply tests based on blood, urine or salivary fluid to samples taken during routine visits to the primary health system.

New immune phenotypes for treatment response in high-grade serous ovarian carcinoma patients.

Despite advances in surgical and therapeutic approaches, high-grade serous ovarian carcinoma (HGSOC) prognosis remains poor. Surgery is an indispensable component of therapeutic protocols, as removal of all visible tumor lesions (cytoreduction) profoundly improves the overall survival. Enhanced predictive tools for assessing cytoreduction are essential to optimize therapeutic precision. Patients' immune status broadly reflects the tumor cell biological behavior and the patient responses to disease and treatment. Serum cytokine profiling is a sensitive measure of immune adaption and deviation, yet its integration into treatment paradigms is underexplored. This study is part of the IMPACT trial (NCT03378297) and aimed to characterize immune responses before and during primary treatment for HGSOC to identify biomarkers for treatment selection and prognosis. Longitudinal serum samples from 22 patients were collected from diagnosis until response evaluation. Patients underwent primary cytoreductive surgery or neoadjuvant chemotherapy (NACT) based on laparoscopy scoring. Twenty-seven serum cytokines analyzed by Bio-Plex 200, revealed two immune phenotypes at diagnosis: Immune High with marked higher serum cytokine levels than Immune Low. The immune phenotypes reflected the laparoscopy scoring and allocation to surgical treatment. The five Immune High patients undergoing primary cytoreductive surgery exhibited immune mobilization and extended progression-free survival, compared to the Immune Low patients undergoing the same treatment. Both laparoscopy and cytoreductive surgery induced substantial and transient changes in serum cytokines, with upregulation of the inflammatory cytokine IL-6 and downregulation of the multifunctional cytokines IP-10, Eotaxin, IL-4, and IL-7. Over the study period, cytokine levels uniformly decreased in all patients, leading to the elimination of the initial immune phenotypes regardless of treatment choice. This study reveals distinct pre-treatment immune phenotypes in HGSOC patients that might be informative for treatment stratification and prognosis. This potential novel biomarker holds promise as a foundation for improved assessment of treatment responses in patients with HGSOC. ClinicalTrials.gov Identifier: NCT03378297.

Metabolomic profiling of upper GI malignancies in blood and tissue: a systematic review and meta-analysis.

OBJECTIVE: To conduct a systematic review and meta-analysis of case-control and cohort human studies evaluating metabolite markers identified using high-throughput metabolomics techniques on esophageal cancer (EC), cancer of the gastroesophageal junction (GEJ), and gastric cancer (GC) in blood and tissue. BACKGROUND: Upper gastrointestinal cancers (UGC), predominantly EC, GEJ, and GC, are malignant tumour types with high morbidity and mortality rates. Numerous studies have focused on metabolomic profiling of UGC in recent years. In this systematic review and meta-analysis, we have provided a collective summary of previous findings on metabolites and metabolomic profiling associated with EC, GEJ and GC. METHODS: Following the PRISMA procedure, a systematic search of four databases (Embase, PubMed, MEDLINE, and Web of Science) for molecular epidemiologic studies on the metabolomic profiles of EC, GEJ and GC was conducted and registered at PROSPERO (CRD42023486631). The Newcastle-Ottawa Scale (NOS) was used to benchmark the risk of bias for case-controlled and cohort studies. QUADOMICS, an adaptation of the QUADAS-2 (Quality Assessment of Diagnostic Accuracy) tool, was used to rate diagnostic accuracy studies. Original articles comparing metabolite patterns between patients with and without UGC were included. Two investigators independently completed title and abstract screening, data extraction, and quality evaluation. Meta-analysis was conducted whenever possible. We used a random effects model to investigate the association between metabolite levels and UGC. RESULTS: A total of 66 original studies involving 7267 patients that met the required criteria were included for review. 169 metabolites were differentially distributed in patients with UGC compared to healthy patients among 44 GC, 9 GEJ, and 25 EC studies including metabolites involved in glycolysis, anaerobic respiration, tricarboxylic acid cycle, and lipid metabolism. Phosphatidylcholines, eicosanoids, and adenosine triphosphate were among the most frequently reported lipids and metabolites of cellular respiration, while BCAA, lysine, and asparagine were among the most commonly reported amino acids. Previously identified lipid metabolites included saturated and unsaturated free fatty acids and ketones. However, the key findings across studies have been inconsistent, possibly due to limited sample sizes and the majority being hospital-based case-control analyses lacking an independent replication group. CONCLUSION: Thus far, metabolomic studies have provided new opportunities for screening, etiological factors, and biomarkers for UGC, supporting the potential of applying metabolomic profiling in early cancer diagnosis. According to the results of our meta-analysis especially BCAA and TMAO as well as certain phosphatidylcholines should be implicated into the diagnostic procedure of patients with UGC. We envision that metabolomics will significantly enhance our understanding of the carcinogenesis and progression process of UGC and may eventually facilitate precise oncological and patient-tailored management of UGC.

Analysis of serum peptidome profiles of non-metastatic and metastatic feline mammary carcinoma using liquid chromatography-tandem mass spectrometry.

BACKGROUND: Feline mammary carcinoma (FMC) is a common aggressive and highly metastatic cancer affecting female cats. Early detection is essential for preventing local and distant metastasis, thereby improving overall survival rates. While acquiring molecular data before surgery offers significant potential benefits, the current protein biomarkers for monitoring disease progression in non-metastatic FMC (NmFMC) and metastatic FMC (mFMC) are limited. The objective of this study was to investigate the serum peptidome profiles of NmFMC and mFMC using liquid chromatography-tandem mass spectrometry. A cross-sectional study was conducted to compare serum peptidome profiles in 13 NmFMC, 23 mFMC and 18 healthy cats. The liquid chromatography-tandem mass spectrometry analysis was performed on non-trypsinized samples. RESULTS: Out of a total of 8284 expressed proteins observed, several proteins were found to be associated with human breast cancer. In NmFMC, distinctive protein expressions encompassed double-stranded RNA-binding protein Staufen homolog 2 (STAU2), associated with cell proliferation, along with bromodomain adjacent to zinc finger domain 2A (BAZ2A) and gamma-aminobutyric acid type A receptor subunit epsilon (GABRE), identified as potential treatment targets. Paradoxically, positive prognostic markers emerged, such as complement C1q like 3 (C1QL3) and erythrocyte membrane protein band 4.1 (EPB41 or 4.1R). Within the mFMC group, overexpressed proteins associated with poor prognosis were exhibited, including B-cell lymphoma 6 transcription repressor (BCL6), thioredoxin reductase 3 (TXNRD3) and ceruloplasmin (CP). Meanwhile, the presence of POU class 5 homeobox (POU5F1 or OCT4) and laminin subunit alpha 1 (LAMA1), reported as metastatic biomarkers, was noted. CONCLUSION: The presence of both pro- and anti-proliferative proteins was observed, potentially indicating a distinctive characteristic of NmFMC. Conversely, proteins associated with poor prognosis and metastasis were noted in the mFMC group.

Integrative analysis of blood transcriptome profiles in small-cell lung cancer patients for identification of novel chemotherapy resistance-related biomarkers.

Introduction: Chemoresistance constitutes a prevalent factor that significantly impacts thesurvival of patients undergoing treatment for smal-cell lung cancer (SCLC). Chemotherapy resistance in SCLC patients is generally classified as primary or acquired resistance, each governedby distinct mechanisms that remain inadequately researched. Methods: In this study, we performed transcriptome screening of peripheral blood plasma obtainedfrom 17 patients before and after receiving combined etoposide and platinum treatment. We firs testimated pseudo-single-cell analysis using xCell and ESTIMATE and identified differentially expressed genes (DEGs), then performed network analysis to discover key hub genes involved in chemotherapy resistance. Results: Our analysis showed a significant increase in class-switched memory B cell scores acrossboth chemotherapy resistance patterns, indicating their potential crucial role in mediatingresistance. Moreover, network analysis identifed PRICKLE3, TNFSFI0, ACSLl and EP300 as potential contributors to primary resistance, with SNWl, SENP2 and SMNDCl emerging assignificant factors in acquired resistance, providing valuable insights into chemotherapy resistancein SCLC. Discussion: These findings offer valuable insights for understanding chemotherapy resistance and related gene signatures in SCLC, which could help further biological validation studies.

[Epigenetic markers of choroidal melanoma]. / Epigeneticheskie markery melanomy khorioidei.

MicroRNAs (miRNAs) are short non-coding RNAs (18-25 nucleotides in length) that are important participants in the regulation of gene expression. In 2003, their active role in oncogenesis was demonstrated. In 2008, the first report on the isolation of miRNAs from uveal melanoma (UM) tissue was published. Four years later (2012), the presence of miRNAs in the plasma of patients with this category was shown. To date, changes in the expression level of 100 miRNAs in the plasma of cancer patients (with cancer of various localizations) out of the 2654 miRNAs described in mirbase.org have been proven. In the plasma of patients with UM, changes in the expression of only 13 miRNAs have been confirmed. As a rule, studies were conducted in patients at the stage of hematogenous metastasis of UM. PURPOSE: This study analyzed the expression pattern of miRNA-223 and miRNA-126 in patients with localized choroidal melanoma (CM) taking into account biometric parameters in the absence of metastases. MATERIAL AND METHODS: Blood plasma of 84 patients with M0N0 CM aged 35-86 years (mean age 63.4±1.2 years) was investigated. The basis for the diagnosis of CM was the results of ophthalmological examination, optical coherence tomography, and ultrasound scanning. In all cases, the absence of metastases was proven (using computed tomography or magnetic resonance imaging). Control - plasma of 28 volunteers (mean age 62.9±1.42 years, age range 45-78 years), who did not have tumoral, autoimmune, or chronic inflammatory processes. The expression levels of miRNAs circulating in blood plasma were determined by real-time polymerase chain reaction. RESULTS: An increase in the expression levels of miRNA-223 and miRNA-126 in the plasma of all 84 patients with CM was confirmed compared to the control group. Features of the miRNA expression pattern that emerged with changes in the tumor's quantitative parameters were identified. CONCLUSION: Evaluation of the levels of miRNA-223 and miRNA-126 in the blood plasma of patients with CM can be used in clinical practice to clarify the diagnosis of CM, as well as to predict the development of hematogenous metastases.

MUC16 as a serum-based prognostic indicator of prometastatic gastric cancer.

Metastatic gastric cancer (GC) presents significant clinical challenges due to its poor prognosis and limited treatment options. To address this, we conducted a targeted protein biomarker discovery study to identify markers predictive of metastasis in advanced GC (AGC). Serum samples from 176 AGC patients (T stage 3 or higher) were analyzed using the Olink Proteomics Target panels. Patients were retrospectively categorized into nonmetastatic, metastatic, and recurrence groups, and differential protein expression was assessed. Machine learning and gene set enrichment analysis (GSEA) methods were applied to discover biomarkers and predict prognosis. Four proteins (MUC16, CAIX, 5'-NT, and CD8A) were significantly elevated in metastatic GC patients compared to the control group. Additionally, GSEA indicated that the response to interleukin-4 and hypoxia-related pathways were enriched in metastatic patients. Random forest classification and decision-tree modeling showed that MUC16 could be a predictive marker for metastasis in GC patients. Additionally, ELISA validation confirmed elevated MUC16 levels in metastatic patients. Notably, high MUC16 levels were independently associated with metastatic progression in T3 or higher GC. These findings suggest the potential of MUC16 as a clinically relevant biomarker for identifying GC patients at high risk of metastasis.

Impending role of inflammatory markers and their specificity and sensitivity in breast cancer patients.

Cancer and related disorders are the most common cause of cancer-related mortality with the incidence of 1 in 9 among the pre-menopausal Pakistani females. among the most common ailments worldwide, indicating the importance of developing particular techniques that could help attenuate the effects of breast cancer and related outcomes. The primary aim of the current study was to review the role of inflammatory and stress markers in the development and progression of breast cancer. Four hundred ninety-eight (n = 498) patients with breast cancer and four hundred and ninety-eight (n = 498) age- and sex-matched controls were selected for this case‒control study. Serum samples were obtained, and the levels of stress and inflammatory markers, including Matrix metalloproteases (MMPs), Interleukins (ILs), Heat shock proteins (HSPs), Malondialdehyde (MDA), Nitric Oxide (NO), inducible Nitric Oxide Synthase (iNOS) and Tumour necrosis factor-alpha (TNF-α), were determined. Most (62%) patients had metastatic breast cancer (stage III or IV) with an adverse grade (65% with Grade III and 35% with Grade II). The present study showed that the levels of oxidants such as MDA, ILs, MMPs and HSPs were significantly greater, while the levels of antioxidants such as Superoxide Dismutase (SOD), Glutathione (GSH), Catalase (CAT), vitamin A, C and D were significantly lower in breast cancer patients than in controls, suggesting their diagnostic importance and role in the pathophysiology of breast cancer. Oxidants, including IL-1, HSP27 and MMP9, which are highly specific and sensitive, may be used to develop the pathophysiological pathways of metastatic breast cancer in these patients. These pathways include cell invasion, cell migration and epithelial-mesenchymal transition. Therefore, we concluded that an increase in growth factors, e.g., Vascular Endothelial Growth Factor (VEGF), Tumour Growth Factor-beta (TGF-ß) and B-cell lymphoma (Bcl2), under the influence of these variables plays a crucial role in the metastasis of breast cancer.

Serum miRNA-1 may serve as a promising noninvasive biomarker for predicting treatment response in breast cancer patients receiving neoadjuvant chemotherapy.

BACKGROUND: MicroRNA-1 (miR-1) is a tumour suppressor that can inhibit cell proliferation and invasion in several cancer types. In addition, miR-1 was found to be associated with drug sensitivity. Circulating miRNAs have been proven to be potential biomarkers with predictive and prognostic value. However, studies of miR-1 expression in the serum of breast cancer (BC) patients are relatively scarce, especially in patients receiving neoadjuvant chemotherapy (NAC). METHODS: Serum samples from 80 patients were collected before chemotherapy, and RT-PCR was performed to detect the serum expression of miR-1. The correlation between miR-1 expression in serum and clinicopathological factors, including pathological complete response (pCR), was analyzed by the chi-squared test and logistic regression. KEGG and GSEA analysis were also performed to determine the biological processes and signalling pathways involved. RESULTS: The miR-1 high group included more patients who achieved a pCR than did the miR-1 low group (p < 0.001). Higher serum miR-1 levels showed a strong correlation with decreased ER (R = 0.368, p < 0.001) and PR (R = 0.238, p = 0.033) levels. The univariate model of miR-1 for predicting pCR achieved an AUC of 0.705 according to the ROC curve. According to the interaction analysis, miR-1 interacted with Ki67 to predict the NAC response. According to the Kaplan-Meier plot, a high serum miR-1 level was related to better disease-free survival (DFS) in the NAC cohort. KEGG analysis and GSEA results indicated that miR-1 may be related to the PPAR signalling pathway and glycolysis. CONCLUSIONS: In summary, our data suggested that miR-1 could be a potential biomarker for pCR and survival outcomes in patients with BC treated with NAC.

Rapid detection of lung cancer based on serum Raman spectroscopy and a support vector machine: a case-control study.

BACKGROUND: Early screening and detection of lung cancer is essential for the diagnosis and prognosis of the disease. In this paper, we investigated the feasibility of serum Raman spectroscopy for rapid lung cancer screening. METHODS: Raman spectra were collected from 45 patients with lung cancer, 45 with benign lung lesions, and 45 healthy volunteers. And then the support vector machine (SVM) algorithm was applied to build a diagnostic model for lung cancer. Furthermore, 15 independent individuals were sampled for external validation, including 5 lung cancer patients, 5 benign lung lesion patients, and 5 healthy controls. RESULTS: The diagnostic sensitivity, specificity, and accuracy were 91.67%, 92.22%, 90.56% (lung cancer vs. healthy control), 92.22%,95.56%,93.33% (benign lung lesion vs. healthy) and 80.00%, 83.33%, 80.83% (lung cancer vs. benign lung lesion), repectively. In the independent validation cohort, our model showed that all the samples were classified correctly. CONCLUSION: Therefore, this study demonstrates that the serum Raman spectroscopy analysis technique combined with the SVM algorithm has great potential for the noninvasive detection of lung cancer.

An ultrasensitive electrochemical/colorimetric dual-mode self-powered biosensing platform for lung cancer marker detection by multiple-signal amplification strategy.

BACKGROUND: In recent years, miRNAs have emerged as potentially valuable tumor markers, and their sensitive and accurate detection is crucial for early screening and diagnosis of tumors. However, the analysis of miRNAs faces significant challenges due to their short sequence, susceptibility to degradation, high similarity, low expression level in cells, and stringent requirements for in vitro research environments. Therefore, the development of sensitive and efficient new methods for the detection of tumor markers is crucial for the early intervention of related tumors. RESULTS: An ultrasensitive electrochemical/colorimetric dual-mode self-powered biosensor platform is established to detect microRNA-21 (miR-21) via a multi-signal amplification strategy. Gold nanoparticles (AuNPs) and VS4 nanosheets self-assembled 3D nanorods (VS4-Ns-Nrs) are prepared for constructing a superior performance enzyme biofuel cell (EBFC). The double-signal amplification strategy of Y-shaped DNA nanostructure and catalytic hairpin assembly (CHA) is adopted to further improve enhance the strength and specificity of the output signal. In addition, a capacitor is matched with EBFC to generate an instantaneous current that is amplified several times, and the output detection signal is improved once more. At the same time, electrochemical and colorimetric methods are used for dual-mode strategy to achieve the accuracy of detection. The linear range of detection is from 0.001 pg/mL to 1000 pg/mL, with a relatively low limit of detection (LOD) of 0.16 fg/mL (S/N = 3). SIGNIFICANCE: The established method enables accurate and sensitive detection of markers in patients with lung cancer, providing technical support and data reference for precise identification. It is anticipated to offer a sensitive and practical new technology and approach for early diagnosis, clinical treatment, and drug screening of cancer and other related major diseases.

Exploring the causal association between uric acid and lung cancer in east Asian and European populations: a mendelian randomization study.

BACKGROUND: Lung cancer still ranks first in the mortality rate of cancer. Uric acid is a product of purine metabolism in humans. Its presence in the serum is controversial; some say that its high levels have a protective effect against tumors, others say the opposite, that is, high levels increase the risk of cancer. Therefore, the aim of this study was to investigate the potential causal association between serum uric acid levels and lung cancer. METHODS: Mendelian randomization was used to achieve our aim. Sensitivity analyses was performed to validate the reliability of the results, followed by reverse Mendelian analyses to determine a potential reverse causal association. RESULTS: A significant causal association was found between serum uric acid levels and lung cancer in East Asian and European populations. Further sublayer analysis revealed a significant causal association between uric acid and small cell lung cancer, while no potential association was observed between uric acid and non-small cell lung cancer, squamous lung cancer, and lung adenocarcinoma. The sensitivity analyses confirmed the reliability of the results. Reverse Mendelian analysis showed no reverse causal association between uric acid and lung cancer. CONCLUSIONS: The results of this study suggested that serum uric acid levels were negatively associated with lung cancer, with uric acid being a potential protective factor for lung cancer. In addition, uric acid level monitoring was simple and inexpensive. Therefore, it might be used as a biomarker for lung cancer, promoting its wide use clinical practice.

Promoter profiles in plasma CfDNA exhibits a potential utility of predicting the efficacy of neoadjuvant chemotherapy in breast cancer patients.

BACKGROUND: Gene expression profiles in breast tissue biopsies contain information related to chemotherapy efficacy. The promoter profiles in cell-free DNA (cfDNA) carrying gene expression information of the original tissues may be used to predict the response to neoadjuvant chemotherapy in breast cancer as a non-invasive biomarker. In this study, the feasibility of the promoter profiles in plasma cfDNA was evaluated as a novel clinical model for noninvasively predicting the efficacy of neoadjuvant chemotherapy in breast cancer. METHOD: First of all, global chromatin (5 Mb windows), sub-compartments and promoter profiles in plasma cfDNA samples from 94 patients with breast cancer before neoadjuvant chemotherapy (pCR = 31 vs. non-pCR = 63) were analyzed, and then classifiers were developed for predicting the efficacy of neoadjuvant chemotherapy in breast cancer. Further, the promoter profile changes in sequential cfDNA samples from 30 patients (pCR = 8 vs. non-pCR = 22) during neoadjuvant chemotherapy were analyzed to explore the potential benefits of cfDNA promoter profile changes as a novel potential biomarker for predicting the treatment efficacy. RESULTS: The results showed significantly distinct promoter profile in plasma cfDNA of pCR patients compared with non-pCR patients before neoadjuvant chemotherapy. The classifier based on promoter profiles in a Random Forest model produced the largest area under the curve of 0.980 (95% CI: 0.978-0.983). After neoadjuvant chemotherapy, 332 genes with significantly differential promoter profile changes in sequential cfDNA samples of pCR patients was observed, compared with non-pCR patients, and their functions were closely related to treatment response. CONCLUSION: These results suggest that promoter profiles in plasma cfDNA may be a powerful, non-invasive tool for predicting the efficacy of neoadjuvant chemotherapy breast cancer patients before treatment, and the on-treatment cfDNA promoter profiles have potential benefits for predicting the treatment efficacy.

Evaluating soluble Axl as a biomarker for glioblastoma: A pilot study.

With current imaging, discriminating tumor progression from treatment effect following immunotherapy or oncolytic virotherapy of glioblastoma (GBM) is challenging. A blood based diagnostic biomarker would therefore be helpful. Axl is a receptor tyrosine kinase that is highly expressed by many cancers including GBM. Axl expression is regulated through enzymatic cleavage of its extracellular domain. The resulting fragment can be detected in serum as soluble Axl (sAxl). sAxl levels can distinguish patients with melanoma, hepatocellular carcinoma, and pancreatic ductal adenocarcinoma from healthy controls. This is a pilot study to determine if sAxl is a candidate biomarker for GBM. The sAxl levels in the serum of 40 healthy volunteers and 20 GBM patients were determined using an enzyme-linked immunosorbent assay (ELISA). Pre- and post- operative sAxl levels were obtained. Volumetric MRI evaluation provided GBM tumor volume metrics. There was no significant difference in the sAxl levels of the volunteers (30.16±1.88 ng/ml) and GBM patients (30.74±1.96 ng/ml) p = 0.27. The postoperative sAxl levels were significantly higher than preoperative levels (32.32±2.26 ng/ml vs 30.74±1.96 ng/ml, p = 0.03). We found no correlation between tumor volume and sAxl levels. Axl expression was low or absent in 6 of 11 (55%) patient derived GBM cell lines. Given the wide range of Axl expression by GBM tumors, sAxl may not be a reliable indicator of GBM. However, given the small sample size in this study, a larger study may be considered.

Uterine tumors resembling ovarian sex cord tumors: A retrospective analysis of 7 cases from a single institution.

To investigate the clinicopathological features, diagnosis, surgical treatment and prognosis of uterine tumors similar to ovarian sex cord tumors (UTROSCT). The clinical data, surgical approach, histopathological, and immunohistochemical features of 7 cases of UTROSCTs were retrospectively reviewed and followed up. All 4 patients were premenopausal women. The most common clinical presentation was menorrhagia (n = 4) followed by postmenopausal lower abdominal mass (n = 2) and postmenopausal bleeding (n = 1). Gynecological ultrasonography suggested uterine fibroids in 4 cases, adenomyosis with uterine fibroids in 2 cases, and an intrauterine mass in 1 case. Pelvic MRI was performed preoperatively in only 2 cases, and both indicated uterine fibroid degeneration, including 1 patient with suspected malignancy. Preoperative serum tumor markers were measured in 6 patients, and only 1 patient had elevated CA125 levels, up to 158 U/mL. Total hysterectomy with bilateral adnexectomy or salpingectomy was the most common treatment pattern (n = 6). The tumors were located within the myometrium (n = 4), submucosa (n = 1), and isthmus to external cervical os (n = 1), with a range of 2 to 12 (mean = 8) cm. Edema and degeneration were observed in 2 cases, and necrosis in 1 case. Postoperative follow-up ranged from 31 to 82 (mean = 43) months. Unfortunately, 1 patient died at 54 months of follow-up without undergoing hysterectomy. The remaining 6 cases showed no tumor recurrence or metastasis after surgery. Histological examination revealed a tumor composed of epithelioid tumor-like cells arranged in cords, trabeculae, and nests. All 7 tumors showed expression of 2 sex cord differentiation markers. Furthermore, all tumors expressed the smooth muscle marker, while epithelial marker CK (4/7). endometrial stromal marker CD10(0/7). The Ki-67 proliferation index was found to be <5% (5/7). The option of total hysterectomy may be considered for women who do not have any fertility requirements. However, for young women who desire to maintain their reproductive capacity, surgery to preserve the uterus may be an alternative, although it necessitates careful postoperative monitoring. In terms of follow-up monitoring, MRI is more suitable than ultrasound. The diagnosis of UTROSCT heavily relies on histopathological examination and immunohistochemical analysis.

Role of Machine Learning in Liquid Biopsy of Brain Tumours.

Liquid biopsy has multiple benefits and is used extensively in other fields of oncology, but its role in neuro-oncology has been limited so far. Multiple tumour-derived materials like circulating tumour cells (CTCs), tumour-educated platelets (TEPs), cell-free DNA (cfDNA), circulating tumour DNA (ctDNA), and miRNA are studied in CSF, blood (plasma, serum) or urine. Large and complex amounts of data from liquid biopsy can be simplified by machine learning using various algorithms. By using this technique, we can diagnose brain tumours and differentiate low versus highgrade glioma and true progression from pseudo-progression. The potential of liquid biopsy in brain tumours has not been extensively studied, but it has a bright future in the coming years. Here, we present a literature review on the role of machine learning in liquid biopsy of brain tumours.

AI models predicting breast cancer distant metastasis using LightGBM with clinical blood markers and ultrasound maximum diameter.

Breast cancer metastasis significantly impacts women's health globally. This study aimed to construct predictive models using clinical blood markers and ultrasound data to predict distant metastasis in breast cancer patients, ensuring clinical applicability, cost-effectiveness, relative non-invasiveness, and accessibility of these models. Analysis was conducted on data from 416 patients across two centers, focusing on clinical blood markers (tumor markers, liver and kidney function indicators, blood lipid markers, cardiovascular biomarkers) and maximum lesion diameter from ultrasound. Feature reduction was performed using Spearman correlation and LASSO regression. Two models were built using LightGBM: a clinical model (using clinical blood markers) and a combined model (incorporating clinical blood markers and ultrasound features), validated in training, internal test, and external validation (test1) cohorts. Feature importance analysis was conducted for both models, followed by univariate and multivariate regression analyses of these features. The AUC values of the clinical model in the training, internal test, and external validation (test1) cohorts were 0.950, 0.795, and 0.883, respectively. The combined model showed AUC values of 0.955, 0.835, and 0.918 in the training, internal test, and external validation (test1) cohorts, respectively. Clinical utility curve analysis indicated the combined model's superior net benefit in identifying breast cancer with distant metastasis across all cohorts. This suggests the combined model's superior discriminatory ability and strong generalization performance. Creatine kinase isoenzyme (CK-MB), CEA, CA153, albumin, creatine kinase, and maximum lesion diameter from ultrasound played significant roles in model prediction. CA153, CK-MB, lipoprotein (a), and maximum lesion diameter from ultrasound positively correlated with breast cancer distant metastasis, while indirect bilirubin and magnesium ions showed negative correlations. This study successfully utilized clinical blood markers and ultrasound data to develop AI models for predicting distant metastasis in breast cancer. The combined model, incorporating clinical blood markers and ultrasound features, exhibited higher accuracy, suggesting its potential clinical utility in predicting and identifying breast cancer distant metastasis. These findings highlight the potential prospects of developing cost-effective and accessible predictive tools in clinical oncology.

Circulating tumor extracellular vesicles to monitor metastatic prostate cancer genomics and transcriptomic evolution.

Extracellular vesicles (EVs) secreted by tumors are abundant in plasma, but their potential for interrogating the molecular features of tumors through multi-omic profiling remains widely unexplored. Genomic and transcriptomic profiling of circulating EV-DNA and EV-RNA isolated from in vitro and in vivo models of metastatic prostate cancer (mPC) reveal a high contribution of tumor material to EV-loaded DNA/RNA, validating the findings in two cohorts of longitudinal plasma samples collected from patients during androgen receptor signaling inhibitor (ARSI) or taxane-based therapy. EV-DNA genomic features recapitulate matched-patient biopsies and circulating tumor DNA (ctDNA) and associate with clinical progression. We develop a novel approach to enable transcriptomic profiling of EV-RNA (RExCuE). We report how the transcriptome of circulating EVs is enriched for tumor-associated transcripts, captures certain patient and tumor features, and reflects on-therapy tumor adaptation changes. Altogether, we show that EV profiling enables longitudinal transcriptomic and genomic profiling of mPC in liquid biopsy.