Staging Of Malignancies Research Articles

GINS1 as a Novel Biomarker of Survival in Colon Adenocarcinoma Patients — A Secondary Publication

The study focused on elaborating the role of GINS1 expression and its regulatory mechanisms in colon adenocarcinoma (COAD). Using the UALCAN informational index, GINS1 expression assessment unveiled a critical up-regulation in malignant cells that stood out from normal controls, suggesting its contribution to COAD expansion. Further dismantling GINS1 expression across various boundaries revealed unsurprising up-regulation in different malignant development stages, racial groups, genders, and age classes in COAD patients, characteristics for its imperative role in cancer progression. Moreover, this study investigated the promoter methylation status of GINS1, uncovering a critical uniqueness between COAD samples and normal controls. Analyzing promoter methylation across various clinical boundaries uncovered powerful variations, with particular methylation patterns seen across cancer stages, race groups, genders, and age groups. Survival analysis using the Kaplan-Meier (KM) plotter tool showed a colossal connection between GINS1 expression levels and overall survival (OS) in COAD patients, with low GINS1 expression interfacing with higher OS. Additionally, mutational examination using the cBioPortal stage revealed that no critical change was found in COAD. Overall, these findings revealed the complex contribution of GINS1 in COAD pathogenesis, underlining its actual limit as a prognostic biomarker and supportive therapeutic agent in COAD management.

The real-world impact of next-generation sequencing in advanced stages of solid tumor malignancies.

e23066 Background: Next-generation sequencing (NGS) is a revolutionary technology that allows for DNA and RNA genomic analysis of malignant tumors via tissue or blood sample to aid in diagnosis and treatment while providing predictive and prognostic data about cancer patients. 75.6% of US oncologists use NGS in advanced cancer patients. As there are now site-agnostic approvals of certain targeted therapies, ASCO published a provisional clinical opinion stating that there is a rationale for genomic testing of all solid tumors. This retrospective study evaluates the impact of NGS testing in advanced solid tumor patients in a community based cancer center in Florida. Methods: Patients were diagnosed with stage 3 or 4 solid malignancy between January 1st, 2019 - December 31st, 2022. 496 patients were reviewed of which 269 patients were included in the study as they underwent NGS testing with either tissue (70.6%), blood (25.3%) or both (4.1%). Results: Median age of the study population was 71% with 87% of patients being insured with Medicare. 52.4% of patients were male. Overall, 67.7% of patients had biomarkers identified, 47.2% had FDA approved targeted therapies, and 77.3% had clinical trials identified. NGS testing impacted first line therapy in only 10% of patients where a matched therapy was initiated as first line treatment. Median time from initial diagnosis to NGS result was 53 days while the median time from diagnosis to initiation of first line of therapy was 47.5 days. In the entire study population, 14.1% never received therapy and 40.9% of patients passed. Of the 110 patients who passed, median overall survival in patients who had a biomarker identified through NGS testing was 6 months compared to 7 months in patients without a biomarker. Rates of biomarker identification and availability of FDA approved therapy were similar between deceased patients (67.3% and 45.5%) and those who were alive at time of analysis (63.1% and 48.4%). Conclusions: NGS testing has become part of routine oncologic care in patients with advanced solid malignancies, however in only 10% of cases did it impact first line therapy. Though currently NGS testing has a limited role in the initial management of advanced solid tumors, it is imperative that this technology continues to be used and developed as it leads to hypothesis generating and clinically relevant questions in discovery of oncogenic drivers, targets for novel therapeutics, and mechanisms of resistance to therapies. [Table: see text]

Graphene-based synthetic peptide electrochemical sensor for colorectal cancer diagnosis

This work reports the development of an electrochemical sensor using graphene-peptide conjugates for detecting colorectal cancer (CRC) biomarker leucine-rich alpha-2 glycoprotein-1 (LRG1). To enable LRG1 quantification, we rationally designed peptides with dual graphene anchoring motifs for optimal orientation and binding activity when immobilized on a reduced graphene oxide (rGO) electrochemical transducer surface. The graphene nanomaterial provides several advantages such as high conductivity, large surface area, and excellent stability that can enhance the sensor's analytical performance metrics. Furthermore, the synthetic peptides offer benefits like smaller size, specificity, ease of modification and cost-effective production compared to traditional antibody receptors. Under optimized conditions, the peptide sensor exhibited high sensitivity of 22.3 μA/(ng/mL.cm2), low limit of detection (75 pg/mL LRG1 in serum), accuracy of 101.1 % spiked recovery, and precision within 6 % RSD. Testing with colonoscopy-classified patient serum specimens discriminated normal, precancerous adenomatous polyps and malignant carcinoma stages based on LRG1 overexpression. A 24 % elevation for adenomas and 103 % higher levels in CRC were observed. Validation with spiked plasma samples indicated 97–104 % recovery and <7 % RSD, proving accurate detection capability. Comparison to antibody-based sensors showed superior linear range, sensitivity, reproducibility, and faster assay time. This demonstrates the promise of computational peptide designing combined with advanced nanomaterials for electrochemical detection of CRC progression through serum protein biomarkers.

Precancerous Change Detection Technique on Mammography Breast Cancer Images based on Mean Ratio and Log Ratio using Fuzzy c Mean Classification with Gabor Filter

The growing rate of breast cancer necessitates immediate global attention. Mammography images are used to determine the stage of malignancy. Breast cancer stages must be identified in order to save a person's life. This article's main goal is to identify different techniques to obtain the difference between two breast cancer mammography images taken of the same individual at different times. This is the first effort to identify breast cancer in mammography images using change detection techniques. The Mammogram Image Change Detection (ICD) technique is also a recent advancement to prevent breast cancer in the early stage and precancerous level in medical images. The main purpose of this work is to observe the changes between breast cancer images in different screening periods using different techniques. Mammogram Breast Cancer Image Change Detection (MBCICD) methods usually start with a Difference Image (DI) and classify the pixels in the DI into changed and unaffected classes using unsupervised fuzzy c means (FCM) clustering methods based on texture features taken from the log and mean ratio difference pictures. Two operators, mean ratio and log ratio, were used to check the changes in the images. The Gabor wavelet is utilized as a feature extraction technique among several standards. Using the Gabor wavelet ratio operators is a useful method for altering the detection of breast cancer in mammography images. Currently, it is challenging to obtain real malignant images of the same person for testing or training. In this study, two images are utilized. To clearly see the changes, one is an image from the MIAS breast cancer mammography images dataset, and the other is a self-generated change image. The research aims to examine the image results and other quantitative analysis results of proposed change detection methods on cancer images. The Mean Ratio Accuracy result is 0.9738, and the Log ratio PCC is 0.9737. The classification results are the Log Ratio + Gabor Filter + FCM is 0.9737, and Mean Ratio +Gabor Filter + FCM is 0.9719. The mean Ratio Accuracy result is 0.9738, Log ratio is 0.9737. Log Ratio + Gabor Filter + FCM is 0.9737, Mean Ratio +Gabor Filter + FCM is 0.9719. Comparing the PCC of proposed change detection methods with the FDA-RMG method on the same dataset, the accuracy is 0.9481 only. The study concludes that variations in mammography breast cancer images could be successfully identified using the ratio operators with Gabor wavelet features.

Application of Data Mining Techniques in Biopsy Interpretation and Staging of Carcinoma Cancer Disease: A Case Study of Northeastern Nigeria

This paper introduces an innovative framework tailored for carcinoma cancer staging in northeastern Nigeria, employing data mining techniques and machine learning algorithms, with analysis conducted using the WEKA toolkit. Given the challenges in healthcare systems, especially in cancer diagnosis and treatment, this study aims to enhance diagnostic precision thorough analysis of biopsy reports. By assessing Support Vector Machine (SVM) and decision tree algorithms using datasets from six tertiary health institutions, the framework demonstrates promising outcomes in accurately determining cancer malignancy stage. SVM exhibits high accuracies in staging breast and prostate cancer, while decision tree algorithms show notable accuracy rates in staging skin cancer. These results highlight the potential of machine learning in advancing cancer diagnosis and treatment planning, particularly in resource-constrained settings, and pave the way for the development of computer-aided diagnostic tools tailored for carcinoma cancer staging in northeastern Nigeria.

SNHG15-mediated feedback loop interplays with HNRNPA1/SLC7A11/GPX4 pathway to promote gastric cancer progression.

Dysregulation of long noncoding RNA (lncRNA) expression plays a pivotal role in the initiation and progression of gastric cancer (GC). However, the regulation of lncRNA SNHG15 in GC has not been well studied. Mechanisms for ferroptosis by SNHG15 have not been revealed. Here, we aimed to explore SNHG15-mediated biological functions and underlying molecular mechanisms in GC. The novel SNHG15 was identified by analyzing RNA-sequencing (RNA-seq) data of GC tissues from our cohort and TCGA dataset, and further validated by qRT-PCR in GC cells and tissues. Gain- and loss-of-function assays were performed to examine the role of SNHG15 on GC both invitro and invivo. SNHG15 was highly expressed in GC. The enhanced SNHG15 was positively correlated with malignant stage and poor prognosis in GC patients. Gain- and loss-of-function studies showed that SNHG15 was required to affect GC cell growth, migration and invasion both invitro and invivo. Mechanistically, the oncogenic transcription factors E2F1 and MYC could bind to the SNHG15 promoter and enhance its expression. Meanwhile, SNHG15 increased E2F1 and MYC mRNA expression by sponging miR-24-3p. Notably, SNHG15 could also enhance the stability of SLC7A11 in the cytoplasm by competitively binding HNRNPA1. In addition, SNHG15 inhibited ferroptosis through an HNRNPA1-dependent regulation of SLC7A11/GPX4 axis. Our results support a novel model in which E2F1- and MYC-activated SNHG15 regulates ferroptosis via an HNRNPA1-dependent modulation of the SLC7A11/GPX4 axis, which serves as the critical effectors in GC progression, and provides a new therapeutic direction in the treatment of GC.

HEALTH-RELATED QUALITY OF LIFE IN POSTMENOPAUSAL WOMEN WITH ADVANCED BREAST CANCER RECEIVING ADJUVANT HORMONE THERAPY (RIBOCICLIB AND LETROZOLE)

Breast cancer is a type of cancer that affects many women in Indonesia. Adjuvant hormone therapies, such as letrozole and ribociclib, have succeeded in improving the patient's quality of life. This study aimed to assess the quality of life of postmenopausal women with advanced breast cancer who received adjuvant hormone therapy with ribociclib and letrozole. A cross-sectional study was conducted using retrospective data from postmenopausal female breast cancer patients at Dharmais Cancer Hospital between 2020 and 2023 who met the inclusion criteria. To determine the impact of sociodemographics on patient quality of life, data were examined using the quality of life score (EQ5D5L) and Spearman test. There were 29 patients, with a mean age of 54.9 years (SD = 8.65); the highest education level was high school (34.5%); The majority of occupations are housewives (69%), and the majority are stage IV (34.5%). The mean utility and VAS values of Ribociclib were 0.885 and 81.66, respectively, whereas those for letrozole were 0.725 and 78.46, respectively. Analysis of the relationship between quality of life and patient characteristics showed that the quality of life of patients with breast cancer treated with adjuvant ribociclib and letrozole therapy was influenced by the stage of breast cancer (p = 0.008). These findings indicate that patients receiving ribociclib and letrozole therapy have a good quality of life, which quality of life quality of life is influenced by the stage of malignancy. Keywords: breast cancer, quality of life, letrozole, ribociclib, post menopause

18F-Fluorodeoxyglucose-Avid Benign Anthracotic Mediastinal Lymphadenitis Mimicking Metastatic Lymphadenopathy.

The staging of malignancy is critical for its effective management. 18F-fluorodeoxyglucose (FDG) positron emission tomography-computed tomography (PET/CT) imaging is a common modality for malignancy staging, which identifies areas of FDG avidity. However, multiple benign etiologies can cause false-positive 18F FDG-avid nodes. Among these, extrapulmonary involvement of anthracosis in the form of lymphadenopathy is a rare entity. In patients with concomitant malignancies, the presence of 18F FDG-avid anthracotic lymph nodal enlargement may mimic nodal metastasis. Endosonography-guided tissue acquisition may help differentiate between the two. Herein, we describe six cases of FDG-avid benign anthracotic lymphadenitis detected during staging workups for patients with malignancies who later underwent curative resection.

Liver Cancer Prediction Using Matlab

Abstract: The liver is necessary for survival and is also prone to many diseases. CT examinations can be used to plan and properly administer radiation treatments for cancers and to guide biopsies and other minimally invasive procedure. The statistical and textural information are obtained from the extracted cancer using the features like mean, standard deviation and entropy of the obtained sub bands are calculated and stored in a feature vector (in format of mat file). The extracted features are fed as input to Extreme Machine Learning classifier to identify the presence of Liver cancer disease and to classify it as Malignant or Benign stage.

Proton Therapy in Non-Rhabdomyosarcoma Soft Tissue Sarcomas of Children and Adolescents.

This paper provides insights into the use of Proton Beam Therapy (PBT) in pediatric patients with non-rhabdomyosarcoma soft tissue sarcomas (NRSTS). NRSTS are a heterogeneous group of rare and aggressive mesenchymal extraskeletal tumors, presenting complex and challenging clinical management scenarios. The overall survival rate for patients with NRSTS is around 70%, but the outcome is strictly related to the presence of various variables, such as the histological subtype, grade of malignancy and tumor stage at diagnosis. Multimodal therapy is typically considered the preferred treatment for high-grade NRSTS. Radiotherapy plays a key role in the treatment of children and adolescents with NRSTS. However, the potential for radiation-induced side effects partially limits its use. Therefore, PBT represents a very suitable therapeutic option for these patients. The unique depth-dose characteristics of protons can be leveraged to minimize doses to healthy tissue significantly, potentially allowing for increased tumor doses and enhanced preservation of surrounding tissues. These benefits suggest that PBT may improve local control while reducing toxicity and improving quality of life. While clear evidence of therapeutic superiority of PBT over other modern photon techniques in NRSTS is still lacking-partly due to the limited data available-PBT can be an excellent treatment option for young patients with these tumors. A dedicated international comprehensive collaborative approach is essential to better define its role within the multidisciplinary management of NRSTS. Shared guidelines for PBT indications-based on the patient's age, estimated outcome, and tumor location-and centralization in high-level referral centers are needed to optimize the use of resources, since access to PBT remains a challenge due to the limited number of available proton therapy facilities.

Breast cancer lesion segmentation based on co-learning feature fusion and Transformer

The PET/CT imaging technology combining positron emission tomography (PET) and computed tomography (CT) is the most advanced imaging examination method currently, and is mainly used for tumor screening, differential diagnosis of benign and malignant tumors, staging and grading. This paper proposes a method for breast cancer lesion segmentation based on PET/CT bimodal images, and designs a dual-path U-Net framework, which mainly includes three modules: encoder module, feature fusion module and decoder module. Among them, the encoder module uses traditional convolution for feature extraction of single mode image; The feature fusion module adopts collaborative learning feature fusion technology and uses Transformer to extract the global features of the fusion image; The decoder module mainly uses multi-layer perceptron to achieve lesion segmentation. This experiment uses actual clinical PET/CT data to evaluate the effectiveness of the algorithm. The experimental results show that the accuracy, recall and accuracy of breast cancer lesion segmentation are 95.67%, 97.58% and 96.16%, respectively, which are better than the baseline algorithm. Therefore, it proves the rationality of the single and bimodal feature extraction method combining convolution and Transformer in the experimental design of this article, and provides reference for feature extraction methods for tasks such as multimodal medical image segmentation or classification.

Prediction and Classifications of Breast Cancer using Enhanced Convolutional Neural Network Approaches

In worldwide women mortality increases extremely every year due to breast cancer and diagnosis of the issue through prediction is very much imperative for healthy lifespan. Here precision of cancer extrapolation is an essential thing for survivability of patient with appropriate treatment. Deep learning algorithms have materialised as influential tool for predicting breast cancer in medical image processing, which leverages capabilities of artificial neural networks (ANN) that are intended to mimic an architecture and functionalities of human brain. Superior features of convolutional neural network (CNN) in deep learning for handling image-based data like, exploiting spatial information, hierarchical feature learning, parameter sharing and data augmentation are important parameters in medical image processing. In this paper CNN algorithm is incorporated for predicting breast cancer in earlier and malignant stage, the results are compared with other deep learning algorithms and our proposed algorithm is expected to give better performance in parameters like accuracy testing, image classifiers, gene sequence classifiers and malignancy detection.

Diagnostic Accuracy of Cancer in Pleural Effusion: A Combination Serum Tumor Markers and Cytology

Abstract Background: Cytological examination of body effusion has an essential role in different tumor staging and research of malignancy. Objectives: It is to study the diagnostic effect of serum tumor markers in differentiation between benign and malignant pleural effusion. Materials and Methods: A retrospective research was done on 39 patients (28 male and 11 female with an age range of 50–77 years old). All samples undergo diagnostic thoracocentesis. The cutoff values of serum tumor markers (CEA &lt; 5 ng/mL; CA125 &lt;35 U/mL; CA19-9 &lt; 37 U/mL; and CA15-3 &lt; 31 U/mL). Results: Thirty-nine cases, resulting in 26 (67%) benign pleural effusions and 13 (33%) malignant pleural effusions, mean ± SD of age was higher malignant pleural effusion than benign type. The sensitivity of cytology was 33%. Malignant pleural effusion tended to have higher serum marker tumor concentrations. A comparison association between benign and malignant pleural effusion revealed statistically significant only in CEA. Most areas under the curve had moderate values that ranged between 0.6 for CA125, CA15.3, and other combined tumor markers, except for CEA, which had a good AUC (0.799). The best efficacy of a single tumor marker is CEA with a cutoff value of 2.05 ng/mL; at this cutoff value, the sensitivity, specificity, and accuracy were 69.2%, 88.5%, and 82.1%, respectively. Conclusion: Single serum tumor markers showed moderate sensitivity and low specificity; their combination does not result in to increase level of sensitivity and specificity to a good and dependent level for diagnosis of the malignant pleural effusion. Cytology and serum tumor markers have aided role in diagnosis. Thoracoscopy and pleural biopsy remain dependent diagnostic tools for malignant pleural effusion.

PET Imaging of Fibroblast Activation Protein in Various Cancers Using [18F]AlF‑NOTA‑FAPI‑04: Comparison with 18F-FDG in a Single-Center, Prospective Study

ObjectivesTargeting fibroblast-activation protein is a newer diagnostic approach for the visualization of tumor stroma, and a novel aluminum-[18F] fluoride (Al18F)-labeled fibroblast-activation protein inhibitor-4 (FAPI-04), hereafter [18F] AlF-NOTA-FAPI-04, presents a promising alternative to gallium 68 (68Ga)–labeled FAPI owing to its relatively longer half-life. This study sought to evaluate the clinical usefulness of [18F] AlF-NOTA-FAPI-04 PET/CT for the diagnosis of various types of cancer, compared with [18F] FDG PET/CT. Materials and MethodsIn this prospective study conducted from October 2021 to January 2024, a total of 148 patients with 16 different tumor entities underwent contemporaneous 18F-FDG and 18F-FAPI-04 PET/CT either for an initial assessment or for recurrence detection. Uptake of 18F-FDG and 18F-FAPI-04 was quantified by the maximum standard uptake value (SUV max). Diagnostic sensitivity, specificity and accuracy were compared by using the McNemar test between these two imaging agents. Results18F-FAPI-04 PET/CT could clearly depict 16 different types of cancer with excellent image contrast, thereby leading to a higher detection rate of primary tumors than did 18F-FDG PET/CT (98.06% vs. 81.55%, P＜0.001). In per-lymph node analysis, the sensitivity, specificity, and accuracy in the diagnosis of metastatic lymph nodes were 92.44%, 90.44%, and 91.56%, respectively, which was much higher than that 18F-FDG PET/CT (80.23%, 79.41% and 79.87%, respectively). Meanwhile, 18F-FAPI-04 PET/CT outperformed 18F-FDG PET/CT in identifying more suspected distant metastases (86.57% vs. 74.13%, P＜0.001). Furthermore, 18F-FAPI-04 PET/CT upgraded tumor staging in 36/101 patients (35.6%), and detected tumor recurrence or metastases in 43/47 patients (91.49%). ConclusionOur findings demonstrated that primary and metastatic lesions in patients with various types of malignant tumors are well-visualized on 18F-FAPI-04 PET/CT, which exhibited a superior diagnostic performance than 18F-FDG PET/CT. Moreover, 18F-FAPI-04 PET/CT is a promising tool for tumor staging and follow-up of various malignancies.

Abstract 6894: Modeling the spectrum of vascular changes occurring in healthy and early malignant cancers on a chip

Abstract The transition of a healthy tissue to a pre-malignant and subsequent malignant stage is typically characterized by a marked increase in extracellular fibrosis and collagen density. Such changes coincide with a significant increase in tissue stiffness as the tumor progresses. Despite the large body of work on endothelial cell changes in tumoral angiogenesis, little is known about the dynamic interactions of endothelial cells, perivascular cells, and the extracellular matrix in early-to-late cancers. Appreciating such interactions is crucial for understanding tumorigenesis and early tumor progression. To model the spectrum of vascular changes occurring on pre-tumoral and tumoral ecosystems, we developed an organ-on-a-chip model of biomimetic pericyte-supported capillaries with collagen having increasingly higher density, stiffness and discrete fibril microarchitectures. Briefly, 160-um channels were engineered using type I collagen that underwent fibrillogenesis at different temperatures (4, 16, 21, and 37oC). Thus, the microarchitecture and stiffness would vary from a soft reticular network (healthy/pre-cancerous vascular capillaries) to a stiff fibrillar mesh (fibrotic/tumoral vascular capillaries). We then seeded human umbilical vein endothelial cells (HUVECs) and mesenchymal stem cells (MSCs) in the collagen channels. After 48h, samples were fixed and stained for actin (cytoskeleton), NG2 (pericyte differentiation), and CD31 (endothelial cell junction), laminin, and cell anchorage system, imaged with a confocal microscope and analyzed with Imaris. In addition, we used a Nanostring panel with 770 genes related to the tumor microenvironment in healthy and fibrosis. Vascular capillaries engineered in contact with softer reticular collagen, consistent with a healthy ECM, showed more pericyte differentiation (p&amp;lt;0.05), inter-endothelial cell junctions (p&amp;lt;0.05), and effective barrier function. In contrast, stiffer fibrillar collagen, which is consistent with the characteristics of the fibrotic malignant extracellular microenvironment, was associated with cell migration outward the vessel, leakiness, and higher RNA expression of interleukin 8 (IL8), TP53, transforming growth factor beta, vimentin, and collagen III genes, thus suggesting a system that compatible with the spectrum of tumoral vasculature changes in cancer and pre-cancer lesions. When vessels were engineered without MSCs, those differences were drastically minimized, To further understand the mechanisms, HUVEC-perivascular cell adhesion was disrupted using silencing RNA for NOTCH3. Upon silencing NOTCH3, the morphology and function of vasculature were reestablished, pointing to a major role of perivascular cells in vascular changes in early tumors. Funding: NIDCR 1K01DE030484-01A1 to CMF R01DE026170, 3R01DE026170-03S1 and 3R01DE026170-03S2 to LEB Citation Format: Cristiane Franca, Avathamsa Athirasala, Emilios Dimitriadis, Jennifer Bays, Kenneth Yamada, Christopher Chen, Luiz E. Bertassoni. Modeling the spectrum of vascular changes occurring in healthy and early malignant cancers on a chip [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6894.

Approach to the Patient With Bilateral Adrenal Masses.

Bilateral adrenal masses, increasingly encountered in clinical practice, manifest across diverse contexts, including incidental discovery, malignancy staging, and targeted imaging after hormonal diagnosis of adrenal disorders. The spectrum encompasses various pathologies, such as cortical adenomas, macronodular adrenal disease, pheochromocytomas, myelolipomas, infiltrative disorders, and primary and secondary malignancies. Notably, not all masses in both adrenal glands necessarily share the same etiology, often exhibiting diverse causes. Recently, the European Society of Endocrinology and the European Network for the Study of Adrenal Tumors updated guidelines, introduced a 4-option schema based on imaging, aiding in targeted hormonal testing and management. This "Approach to the Patient" review delves into the latest advancements in imaging, biochemical, and genetic approaches for the diagnostic and management nuances of bilateral adrenal masses. It provides insights and a contemporary framework for navigating the complexities associated with this clinical entity.

Sentinel Node Mapping in Ovarian Tumors: A Study Using Lymphoscintigraphy and SPECT/CT.

Ovarian cancer in the early stage requires a complete surgical staging, including radical lymphadenectomy, implying subsequent risk of morbidity and complications. Sentinel lymph node (SLN) mapping is a procedure that attempts to reduce radical lymphadenectomy-related complications and morbidities. Our study evaluates the feasibility of SLN mapping in patients with ovarian tumors by the use of intraoperative Technetium-99m-Phytate (Tc-99m-Phytate) and postoperative lymphoscintigraphy using tomographic (single-photon emission computed tomography/computed tomography (SPECT/CT)) acquisition. Thirty-two patients with ovarian mass participated in this study. Intraoperative injection of the radiopharmaceutical was performed just after laparotomy and before the removal of tumor in utero-ovarian and suspensory ligaments of the ovary just beneath the peritoneum. Subsequently, pelvic and para-aortic lymphadenectomy was performed for malignant masses, and the presence of tumor in the lymph nodes was assessed through histopathological examination. Conversely, lymphadenectomy was not performed in patients with benign lesions or borderline ovarian tumors. Lymphoscintigraphy was performed within 24 hr using tomographic acquisition (SPECT/CT) of the abdomen and pelvis. Final pathological examination showed 19 patients with benign pathology, 5 with borderline tumors, and 6 with malignant ovarian tumors. SPECT/CT identified SLNs in para-aortic-only areas in 6 (20%), pelvic/para-aortic areas in 14 (47%), and pelvic-only areas in 7 (23%) cases. Notably, additional unusual SLN locations were revealed in perirenal, intergluteal, and posterior to psoas muscle regions in three patients. We were not able to calculate the false negative rate due to the absence of patients with involved lymph nodes. SLN mapping using intraoperative injection of radiotracers is safe and feasible. Larger studies with more malignant cases are needed to better evaluate the sensitivity of this method for lymphatic staging of ovarian malignancies.

Near-infrared spectroscopy as a novel method of exvivo bladder cancer tissue characterisation.

To evaluate near-infrared (NIR) spectroscopy in differentiating between benign and malignant bladder pathologies ex vivo immediately after resection, including the grade and stage of malignancy. A total of 355 spectra were measured on 71 bladder specimens from patients undergoing transurethral resection of bladder tumour (TURBT) between April and August 2022. Scan time was 5 s, undertaken using a portable NIR spectrometer within 10 min from excision. Specimens were then sent for routine histopathological correlation. Machine learning models were applied to the spectral dataset to construct diagnostic algorithms; these were then tested for their ability to predict the histological diagnosis of each sample using its NIR spectrum. A two-group algorithm comparing low- vs high-grade urothelial cancer demonstrated 97% sensitivity, 99% specificity, and the area under the receiver operating characteristic curve (AUC) was 0.997. A three-group algorithm predicting stages Ta vs T1 vs T2 achieved 97% sensitivity, 92% specificity, and the AUC was 0.996. This first study evaluating the diagnostic potential of NIR spectroscopy in urothelial cancer shows that it can be accurately used to assess tissue in an ex vivo setting immediately after TURBT. This offers point-of-care assessment of bladder pathology, with potential to influence the extent of resection, reducing both the need for re-resection where invasive disease may be suspected, and also the potential for complications where extent of diagnostic resection can be limited. Further studies utilising fibre-optic probes offer the potential for in vivo assessment.

Exosomal biomarkers in the differential diagnosis of ovarian tumors: the emerging roles of CA125, HE4, and C5a

ObjectiveInvestigating the utility of serum exosomal markers CA125, HE4, and C5a, both individually and in combination, for distinguishing between benign and malignant ovarian tumors.MethodsIn this study, we selected a total of 234 patients diagnosed with ovarian tumors, including 34 with malignant tumors, 10 with borderline ovarian tumors, and 190 with benign tumors. This study conducted comparisons of exosomal levels of CA125, HE4, and C5a among distinct groups, as well as making comparisons between serum and exosomal levels of CA125 and HE4. Furthermore, the diagnostic performance was assessed through Receiver Operating Characteristic (ROC) curve analysis. The Area Under the Curve (AUC) was computed, and a comparative evaluation of sensitivity and specificity was conducted to ascertain their effectiveness in determining the nature of ovarian tumors across different markers.ResultsSerum CA125 and HE4 levels, the ROMA index, exosomal CA125, HE4, C5a levels, and their combined applied value (OCS value) were notably elevated in the ovarian non-benign tumor group compared to the benign tumor group, with statistical significance (P < 0.05). Exosomal and serum levels of CA125 and HE4 exhibited a positive correlation, with concentrations of these markers in serum surpassing those in exosomes. The combined OCS (AUC = 0.871) for CA125, HE4, and C5a in exosomes demonstrated superior sensitivity (0.773) and specificity (0.932) compared to serum tumor markers (CA125, HE4) and the ROMA index. The tumor stage represents an autonomous risk factor influencing the prognosis of individuals with ovarian malignancies.ConclusionThe stage of ovarian malignancy is an independent risk factor for its prognosis. The combination of exosomal CA125, HE4 and C5a has a higher clinical value for the identification of the nature of ovarian tumours.

MAGE-A11 is a potential prognostic biomarker and immunotherapeutic target in gastric cancer.

Gastric cancer poses a serious threat to human health and affects the digestive system. The lack of early symptoms and a dearth of effective identification methods make diagnosis difficult, with many patients only receiving a definitive diagnosis at a malignant stage, causing them to miss out on optimal therapeutic interventions. Melanoma-associated antigen-A (MAGE-A) is part of the MAGE family and falls under the cancer/testis antigen (CTA) category. The MAGE-A subfamily plays a significant role in tumorigenesis, proliferation and migration. The expression, prognosis and function of MAGE-A family members in GC, however, remain unclear. Our research and screening have shown that MAGE-A11 was highly expressed in GC tissues and was associated with poor patient prognosis. Additionally, MAGE-A11 functioned as an independent prognostic factor in GC through Cox regression analysis, and its expression showed significant correlation with both tumour immune cell infiltration and responsiveness to immunotherapy. Our data further indicated that MAGE-A11 regulated GC cell proliferation and migration. Subsequently, our findings propose that MAGE-A11 may operate as a prognostic factor, having potential as an immunotherapy target for GC.