Hasil untuk "Neoplasms. Tumors. Oncology. Including cancer and carcinogens"

C. Friedman, T. Proverbs-Singh, M. Postow

O. Mete, S. Asa, A. Gill et al.

Rebecka M Ernst, Linnea Banker, Meridith Schoening et al.

The term collision tumor is used when two unique neoplasms occur in the same organ at the same time. Ovarian collision tumors are extremely rare with different combinations of the following tumors being cited in the literature: surface epithelial tumors, sex-cord stromal tumors, and germ cell tumors. While several cases of combined mucinous neoplasms and granulosa cell tumors have been identified, only one collision case of Sertoli Leydig Cell Tumor (SLCT) and high-grade serous carcinoma (HGSC) has been published (1-6). This case report, diagnosed in late 2022, includes the presentation, clinical management, and ultimately pathologic diagnosis of a rare collision tumor of the ovary composed on SLCT and HGSC. A 70 year old female, G4P4 presented to an outside emergency department for an episode of lightheadedness, dizziness, fatigue, and muscle weakness. Her blood pressure was elevated in the 200s and she was diagnosed with malignant hypertension. Her primary care provider worked her up for adrenal masses with a CT scan and she was referred to gynecologic oncology. On physical exam at her referral, her abdomen was soft and nondistended. A small umbilical hernia was noted. Her CA-125 was 578 units/mL and testosterone 99.40 ng/dL. CT, transvaginal ultrasound, and a PET scan all confirmed extensive peritoneal carcinomatosis including omental caking, mesenteric nodules, and posterior pelvic peritoneal mass and a complex 5.0 cm solid cystic right ovarian lesion, suspicious for malignancy. Additionally, a small volume of abdominopelvic free fluid was identified. These findings were consistent with a peritoneal carcinomatosis. The patient was taken for diagnostic laparoscopy, right salpingo-oophorectomy, and biopsies of the omentum and pelvic peritoneum. In the OR, 1-4mm nodules scattered throughout the pelvic and abdominal peritoneum, small bowel mesentery, and diaphragm were noted. Pathologic review confirmed a poorly differentiated SLCT of the right ovary (Stage IIIIC- pT3C Nx M0) with metastasis to the omentum and right pelvic side wall. Additionally, the right ovary was positive for HGSC metastatic from the fallopian tube. After H&E examination immunostains for p53, napsin, PAX8, synaptophysin, CD56, and inhibin were ordered with adequate controls. Tumor cells corresponding to poorly differentiated SLCT were positive for p53, CD56, and inhibin, while negative for PAX8, napsin, and synaptophysin. The metastatic HGSC was only positive for PAX8 and p53. Serous carcinoma of the fallopian tube is the most common form of ovarian cancer. SLCT are rare and typically found with Stage I disease. Stage III or IV are especially rare and there is little known on these neoplasms presenting at an advanced stage. The mechanism of collision tumor development has many hypotheses, though the most straight forward theory is that each tumor develops independently of the other and by chance collides into the other (7). SLCT are rare neoplasms seen even more rarely with a concurrent tumor in the ovary. Additionally, an advanced stage SLCT makes this case even more unexpected. More research needs to be done to further understand collision tumors of the ovary and their associated findings, prognosis, and development.

Zeynep Erdoğan İyigün, Tolga Ozmen, Serkan İlgün et al.

Objective: The aim of this study was to evaluate the relationship between subclinical lymphedema identified prior to surgical intervention and clinical lymphedema observed in the late period, the incidence of lymphedema in our cohort, and the associated risk factors. Materials and Methods: This prospective study was conducted with early-stage breast cancer patients who had been enrolled in a previous study. For diagnosing lymphedema, physical examination, L-Dex® score, and circumferential measurement was used. The L-Dex® score was used as a screening test for preoperative, subclinical lymphedema since there were no clinical findings. Patients with subclinical lymphedema were provided with education and followed up more frequently with regular monitoring. Results: The mean age of the 217 participants was 56.7±12.7 years (range 29–90), and the mean body mass index was 27.7±3.3 kg/m2 (range 19.3–36.9). Among the 217 patients, lymphedema was detected in 31 (14.7%) at a median follow-up period of 89 months (range 73–108 months). Multivariable analysis of factors associated with late-stage lymphedema revealed positive lymph node count and capsular invasion as significant factors (p = 0.001 for both). Forty (18.4%) had preoperative subclinical lymphedema. At the end of the follow-up period, lymphedema persisted in 11 patients (27.5%) and resolved in 29 patients (72.5%). In multivariable analysis, the positive lymph node count was identified as an independent variable in these patients. Conclusion: Identifying high-risk patients, regular monitoring, and early intervention can significantly reduce the risk of clinical lymphedema through timely treatment.

Elham Karimi, Shalaleh Abbasnezhad, Maedeh Arabpour et al.

ABSTRACT Background Retinoblastoma (RB) is a malignant eye tumor that predominantly affects children. Although survival rates have improved significantly due to advancements in treatment, subsequent malignant neoplasms (SMNs) continue to be major causes of death in both heritable and non‐heritable RB cases. These SMNs are often associated with mutations in the RB1 gene, as well as the effects of radiotherapy or chemotherapy. There are no previous reports of a nonhereditary RB survivor developing three sequential hematologic malignancies (AML, lymphoma, and ALL) over 20 years. Most secondary primary cancers (SPCs) in RB survivors are solid tumors, such as osteosarcoma, soft tissue sarcoma, and melanoma, with hematologic malignancies being far less common, especially as third or subsequent primary tumors. Case We report a case of a 21‐year‐old Iranian male who developed multiple distinct hematologic malignancies following retinoblastoma treatment. Using NGS, Sanger sequencing, and bioinformatic analysis, the possibility of germline mutations was surveyed. Conclusion Germline changes associated with malignancies were examined using next‐generation sequencing (NGS). There were no germline alterations discovered, suggesting no predisposition to develop cancer. Three pathogenic/likely pathogenic heterozygous variants were found in the patient by carrier screening. Absence of germline RB1 mutations or other hereditary cancer syndromes implicates treatment‐related factors (chemotherapy/radiotherapy) as the primary driver of sequential malignancies. Nonhereditary retinoblastoma (RB) survivors have a lower risk of secondary malignancies (SMNs) compared to their hereditary counterparts. Chemotherapy, especially alkylating agents, increases the risk of secondary acute myelogenous leukemia (AML) and other leukemias and lymphomas due to its mutagenic effects and genetic factors. Although RB survivors rarely develop secondary cancers, the limited patient numbers and short follow‐up periods may influence SPC risk assessments. Continuous monitoring and personalized follow‐up care are crucial for managing long‐term risks in these survivors. This research emphasizes the essential importance of ongoing monitoring and follow‐up for survivors of retinoblastoma (RB) to identify and address secondary malignancies (SMNs), improve the management of long‐term complications, and enhance both life expectancy and quality of life.

Wensi Zhao, Nan Zhao, Dedong Cao

ABSTRACT Background Immune checkpoint inhibitor (ICI) has reshaped the treatment landscape of esophageal squamous cell carcinoma (ESCC). But most patients end up with disease progression and/or therapeutic intolerance. The subsequent ICI rechallenge raises some discussions. Methods A retrospective study was conducted to assess the efficacy and safety of reintroduction of ICI in patients with advanced or metastatic ESCC after first‐line ICI failure. Outcomes included median overall survival (OS), progression‐free survival (PFS), objective response rate (ORR), disease control rate (DCR) and safety. Subgroup analysis and prognostic analysis were also performed. Results A total of 1320 patients were screened and 138 were enrolled: 109 received second‐line ICI‐based therapies, and 29 received non‐ICI therapies. As of data cutoff on November 30, 2024, patients with ICI rechallenge, compared with non‐ICI rechallenge, achieved an improved second‐line OS (10.4 vs. 5.8 months; HR = 0.53, 95% CI: 0.33–0.84; p = 0.006) and showed a favorable PFS trend (5.0 vs. 3.0 months; HR = 0.75, 95% CI: 0.48–1.17; p = 0.202). The 6‐month PFS rate was 42.9% versus 22.3%, and the 12‐month OS rate was 41.5% versus 23.2%, respectively. The ORR was 30.3% versus13.8% and the DCR was 79.8% versus 58.6%, respectively. ICI combined with chemoradiotherapy was the most popular option for subsequent ICI rechallenge, with an OS of 11.2 months. Treatment‐related adverse events of grade ≥ 3 occurred in 47 (43.1%) and 11 (37.9%) patients in the two groups. Conclusion Second‐line ICI rechallenge provided OS benefits in advanced or metastatic ESCC, with manageable safety. Further prospective study is warranted.

Yiming Mao, Ting Li, Wenqiang Lu et al.

Abstract Glioblastoma (GBM) is an extremely aggressive and diverse type of brain tumor that is associated with a poor prognosis. Immunogenic cell death (ICD) is a particular form of cellular demise that is closely linked to antineoplastic immune responses. However, it is important to note that the function of ICD in GBM is not yet fully understood. Utilizing single-cell analysis, AddModuleScore, and weighted gene co-expression network analyses (WGCNA), ICD-related genes were identified at both the bulk transcriptome and single-cell levels. Based on these newly identified ICD-related genes, a novel signature for GBM was developed employing three machine learning methods: LASSO, XGBoost, and RandomForest. This prognostic model comprises four characteristic genes: G0S2, NEUROD1, SERPINE2, and LZTS1. The overall survival was significantly lower for the high-risk group compared to the low-risk group in the TCGA-GBM cohort (P < 0.001), CGGA693 cohort (P < 0.001), CGGA325 cohort (P < 0.001), and CGGA301 cohort (P < 0.001). This dichotomy indicates that the riskscore encapsulates a spectrum of tumor microenvironment phenotypes, ranging from immune-permissive (high-risk group) to immune-excluded (low-risk group), with direct implications for therapeutic response. Tumor microenvironment profiling has revealed that the high-risk patients display elevated stromal and immune scores, alongside reduced tumor purity, indicative of a densely infiltrated, macrophage-rich microenvironment. By elucidating the interaction between ICD and macrophage biology, this study establishes a robust prognostic model that surpasses traditional clinical parameters, offering insights into tumor microenvironment immunity and therapeutic vulnerabilities in GBM.

Veronica Salvatore, Antonella Viola, Alessandra Spezzano et al.

ABSTRACT Objectives Sepsis is defined as a life‐threatening, dysfunctional body‐response to infection. Procalcitonin (PCT) is considered a marker of sepsis due to bacterial infections and it has been extensively used as a guide to antimicrobial management in the general population. The clinical role of PCT in cancer patients admitted to the Emergency Department (ED) for infection is still little researched. Methods A prospective observational study enrolling all adult patients hospitalized for infection referred to the ED of IRCCS Azienda Ospedaliero‐Universitaria di Bologna between February 1st, 2023 and July 31st, 2023 was conducted. The primary endpoint was to evaluate the accuracy of PCT in the diagnosis of sepsis (defined according to the latest guidelines) in patients with cancer in comparison to non‐cancer patients. Results 1041 out of 1125 eligible patients were enrolled (559 males and 482 females), out of whom 289 (27.8%) had active cancer. PCT levels differed between cancer and non‐cancer patients (1 ng/mL with IQR 5.85 vs. 0.6 ng/mL with IQR 2.7; p < 0.001). The AUROC of PCT for the diagnosis of sepsis in the entire enrolled population was 0.717 (95% CI 0.683–0.745), whereas it was 0.655 (95% CI 0.592–0.718) in cancer patients and 0.743 (95% CI 0.708–0.778) in non‐cancer patients (p = 0.016). A PCT cut‐off of 0.5 ng/mL (PCT ≥ 0.5 ng/mL) confirmed its accuracy for predicting sepsis in non‐cancer patients (sensitivity 71.5%, specificity 64.1%) but the specificity fell to 44.7% in cancer patients, although sensitivity remained good (sensitivity 78.9%). Conversely, a higher PCT cut‐off of 1 ng/mL, as the most accurate threshold identified in the present study in the cancer population, showed a sensitivity of 66.9% and specificity of 61.2% in predicting sepsis in cancer patients. Conclusion Our study confirms the clinical role of PCT as a part of the diagnostic algorithm for sepsis but its diagnostic role is sub optimal in cancer patients.

Andrew Zhou

Accurate segmentation of brain tumors is vital for diagnosis, surgical planning, and treatment monitoring. Deep learning has advanced on benchmarks, but two issues limit clinical use: no uncertainty estimates for errors and no segmentation of healthy brain structures around tumors for surgery. Current methods fail to unify tumor localization with anatomical context and lack confidence scores. This study presents an uncertainty-aware framework augmenting nnUNet with a channel for voxel-wise uncertainty. Trained on BraTS2023, it yields a correlation of 0.750 and RMSD of 0.047 for uncertainty without hurting tumor accuracy. It predicts uncertainty in one pass, with no extra networks or inferences, aiding clinical decisions. For whole-brain context, a unified model combines normal and cancer datasets, achieving a DSC of 0.81 for brain structures and 0.86 for tumor, with robust key-region performance. Combining both innovations gives the first model outputting tumor in natural surroundings plus an overlaid uncertainty map. Visual checks of outputs show uncertainty offers key insights to evaluate predictions and fix errors, helping informed surgical decisions from AI.

Soumen Ghosh, Christine Jestin Hannan, Rajat Vashistha et al.

Robust generalization is essential for deploying deep learning based tumor segmentation in clinical PET-CT workflows, where anatomical sites, scanners, and patient populations vary widely. This study presents the first cross cancer evaluation of nnU-Net on PET-CT, introducing two novel, expert-annotated whole-body datasets. 279 patients with oesophageal cancer (Australian cohort) and 54 with lung cancer (Indian cohort). These cohorts complement the public AutoPET dataset and enable systematic stress-testing of cross domain performance. We trained and tested 3D nnUNet models under three paradigms. Target only (oesophageal), public only (AutoPET), and combined training. For the tested sets, the oesophageal only model achieved the best in-domain accuracy (mean DSC, 57.8) but failed on external Indian lung cohort (mean DSC less than 3.4), indicating severe overfitting. The public only model generalized more broadly (mean DSC, 63.5 on AutoPET, 51.6 on Indian lung cohort) but underperformed in oesophageal Australian cohort (mean DSC, 26.7). The combined approach provided the most balanced results (mean DSC, lung (52.9), oesophageal (40.7), AutoPET (60.9)), reducing boundary errors and improving robustness across all cohorts. These findings demonstrate that dataset diversity, particularly multi demographic, multi center and multi cancer integration, outweighs architectural novelty as the key driver of robust generalization. This work presents the demography based cross cancer deep learning segmentation evaluation and highlights dataset diversity, rather than model complexity, as the foundation for clinically robust segmentation.

Kiril Vasilev, Alexandre Misrahi, Eeshaan Jain et al.

Multimodal Large Language Models (LLMs) hold promise for biomedical reasoning, but current benchmarks fail to capture the complexity of real-world clinical workflows. Existing evaluations primarily assess unimodal, decontextualized question-answering, overlooking multi-agent decision-making environments such as Molecular Tumor Boards (MTBs). MTBs bring together diverse experts in oncology, where diagnostic and prognostic tasks require integrating heterogeneous data and evolving insights over time. Current benchmarks lack this longitudinal and multimodal complexity. We introduce MTBBench, an agentic benchmark simulating MTB-style decision-making through clinically challenging, multimodal, and longitudinal oncology questions. Ground truth annotations are validated by clinicians via a co-developed app, ensuring clinical relevance. We benchmark multiple open and closed-source LLMs and show that, even at scale, they lack reliability -- frequently hallucinating, struggling with reasoning from time-resolved data, and failing to reconcile conflicting evidence or different modalities. To address these limitations, MTBBench goes beyond benchmarking by providing an agentic framework with foundation model-based tools that enhance multi-modal and longitudinal reasoning, leading to task-level performance gains of up to 9.0% and 11.2%, respectively. Overall, MTBBench offers a challenging and realistic testbed for advancing multimodal LLM reasoning, reliability, and tool-use with a focus on MTB environments in precision oncology.

Ahmad Maqboul, Bakheet Elsadek

ICAM-1 (intercellular adhesion molecule 1) and MPZ (myelin protein zero) are thought to be a factor in the integrity of nerve tissues. In this report, we attempted to trace the expression of ICAM-1, responsible for cell-to-cell adhesion, and of MPZ, the main constituent of myelin sheath, in malignant tissues of the sciatic nerve (SN) in inbred male Copenhagen rats. AT-1 Cells (anaplastic tumor 1) were injected in the perineurial sheath, and tissues of the SNs were collected after 7, 14 and 21 days and compared to a sham-operated group of rats (n = 6 each). Tissues were sectioned and histologically examined, under light microscope, and stained for measuring the immunoreactivity of ICAM-1 and MPZ under laser scanning microscope. The cancer model was established, and the tumor growth was confirmed. ICAM-1 showed severe decreases, proportional to the growing anaplastic cells, as compared to the sham group. MPZ revealed, however, a distinct defensive pattern before substantially decreasing in a comparison with sham. These results support the notion that malignancies damage peripheral nerves and cause severe axonal injury and loss of neuronal integrity, and clearly define the role of ICAM-1 and MPZ in safeguarding the nerve tissues.

Mohammad Subhi Al-Batah, Muhyeeddin Alqaraleh, Mowafaq Salem Alzboon

Oral cancer presents a formidable challenge in oncology, necessitating early diagnosis and accurate prognosis to enhance patient survival rates. Recent advancements in machine learning and data mining have revolutionized traditional diagnostic methodologies, providing sophisticated and automated tools for differentiating between benign and malignant oral lesions. This study presents a comprehensive review of cutting-edge data mining methodologies, including Neural Networks, K-Nearest Neighbors (KNN), Support Vector Machines (SVM), and ensemble learning techniques, specifically applied to the diagnosis and prognosis of oral cancer. Through a rigorous comparative analysis, our findings reveal that Neural Networks surpass other models, achieving an impressive classification accuracy of 93,6 % in predicting oral cancer. Furthermore, we underscore the potential benefits of integrating feature selection and dimensionality reduction techniques to enhance model performance. These insights underscore the significant promise of advanced data mining techniques in bolstering early detection, optimizing treatment strategies, and ultimately improving patient outcomes in the realm of oral oncology.

V. Chigvintsev, P.V. Trusov

Within this study, a phenomenological mathematical model has been developed and parameterized; it is based on the system of evolution equations and designed for quantification of effects produced by age on population cancer risk. The model describes risk dynamics as the function of likelihood of cancer and its severity relying on retrospective population data. The 10th percentile of incidence per administrative territories was used to identify the background age-related component cleared from influence of local carcinogenic factors. The equation parameters were estimated by the least square method. The model parameterization revealed considerable inter-nosology variability in key parameters, which reflected specific features of pathogenesis of different tumor types. Analysis of age-related dynamics in the risk structure revealed that contributions made by specific nosologies were re-distributed systemically. We established progressive predominance of malignant neoplasms of the digestive system in the cancer risk structure since they became the leading age-related pathology in older age groups. A parallel considerable decline was found as regards contributions made by other nosologies, breast cancer included. The resulting picture of age-related evolution of cancer risk shows a discrepancy from the conventional priorities in oncological care, which are often oriented at nosologies with high median incidence. The modeling results highlight the necessity to shift the attention focus on pathologies with the most intensive age-related risk and fatality accumulation. This primarily includes tumors of the digestive system since they make the major contribution to age-related cancer mortality, which is not fully considered within the existing approaches. This emphasizes the necessity to adapt preventive and screening strategies considering the biologically determined structure of population risk. The focus should be shifted on targeted gerontological oncology. The developed model adequately describes age-related carcinogenesis and provides solid basis for assessing additional risks caused by specific endo- and exogenous effects as well as for developing targeted gerontological oncological strategies.

O. R. Khabarov, D. Zima, O. F. Bezrukov et al.

Purpose of the study. To evaluate the impact of the COVID-19 pandemic on the structure of surgical thyroid pathology among the population of the Republic of Crimea and Sevastopol City in 2019–2024 through a retrospective data analysis.Patients and methods. A retrospective analysis of the data (patient medical records, electronic databases) was carried out. Patients were divided into four groups: pre-pandemic, pandemic, and post-pandemic (early and late periods). A total of 1038 cases were analyzed (684 from Crimea, 354 from Sevastopol). Only histological data from surgical specimens were included. Statistical analysis was performed using StatTech v. 4.7.1, applying Pearson’s chi-square (with Holm correction) and Cramer’s V tests. Differences were considered statistically significant at p < 0.05.Results. Analysis of 2019–2024 data revealed significant changes in the structure of surgical thyroid pathology in Crimea and Sevastopol. The post-pandemic period had an increased proportion of malignant neoplasms: thyroid cancer frequency in Crimea rose by 9.8–11.5 % (p < 0.05) and in Sevastopol by 9.8–33. 5 % (p < 0.001). Papillary carcinoma became dominant, increasing from 24.7 % to 31.0 % in Crimea and reaching 57.6 % in Sevastopol. Crimea recorded higher lymph node metastasis (up to 38.6 %,  p = 0.003) and capsular invasion (26.3 %, p < 0.001), while Sevastopol showed multicentric tumor growth during the pandemic (31.9 %, p = 0.003). A surge in toxic goiter at the pandemic peak (Crimea: 10.8 % to 26.6 %; Sevastopol: 1.6 % to 11.7 %) normalized by 2024. Gender analysis confirmed women’s predominance among patients (85–92 %), particularly in the menopausal period.Conclusion. The COVID-19 pandemic caused delayed diagnosis and increased aggressive thyroid cancer forms, linked to restricted routine care and the virus’s direct impact on thyroid tissue. The rise in aggressive thyroid cancer subtypes, including metastatic and invasive forms, reflects postponed surgeries and screening during restrictions, underscoring the need for enhanced screening programs. These findings highlight the importance of adapting healthcare systems to global crises, including reserving resources for oncology care and developing early diagnostic algorithms.

S. Kubekova, N. Zagorulya, N. Malayev et al.

According to Global Cancer Statistics (GLOBOCAN 2022), Africa, Europe, and Asia account for up to 90% of all cases of primary liver cancer, with 70.1% of cases occurring on the Asian continent. In the Republic of Kazakhstan in 2023, the incidence of liver cancer was 5.6 per 100,000 population, and the mortality rate was 2.7. Between 2014 and 2023, liver cancer had the lowest five-year survival rate among all malignant neoplasms in Kazakhstan1. Hepatocellular carcinoma (HCC) is the most common malignant tumor of the liver, accounting for up to 85% of all forms of primary cancer2. HCC therapy varies depending on the stage of the disease and includes a variety of clinical strategies: from targeted and immunotherapy to liver transplantation3. Sorafenib remains the main drug for the treatment of HCC4,5, while doxorubicin is used in transarterial chemoembolization of the hepatic artery (TACE)6. However, the use of modern methods of HCC treatment is accompanied by the risk of developing cardiotoxicity 7, leading to cancer therapy-related cardiac dysfunction (CTRCD) 8. However, the use of modern methods of treating GCC is accompanied by the risk of developing cardiotoxicity 7, leading to cancer therapy-related cardiac dysfunction (CTRCD) 8. CTRCD is accompanied by the development of reversible or irreversible, functional or structural changes in the myocardium and manifests itself with symptoms of cardiovascular disease 8,9. Complications that develop during chemotherapy negatively affect both the quality of life and overall survival of patients, regardless of the prognosis associated with the underlying disease 10. Confirmation of cardiotoxicity requires a comprehensive diagnostic approach, including clinical evaluation, electrocardiography (ECG), echocardiography (TTE), and cardiac biomarkers (high-sensitivity troponin (hs-cTn), brain natriuretic peptide (NTproBNP)) 11,12. Among these, TTE (namely global longitudinal strain (GLS) and NTproBNP levels) are the most sensitive tools for diagnosing early preclinical LV dysfunction and monitoring the dynamics of cardiotoxicity13. And considering clinical practicality, sensitivity, and specificity, GLS, hs-cTn, and NT-proBNP are the most preferred diagnostic methods14. Unfortunately, not all laboratories in Kazakhstan are capable of measuring hs-cTn and NT-proBNP levels, and not all cancer centers are equipped with the necessary equipment to detect early markers of myocardial dysfunction, such as GLS. Nevertheless, in recent years there has been a steady trend towards wider implementation of these methods in oncology practice due to their high diagnostic value and improved technical accessibility. Currently, there is extensive data on increased levels of cardiac biomarkers in patients receiving sorafenib and doxorubicin 15-17. In our study, we analyzed changes in laboratory parameters of hs-cTn I and NT-proBNP in patients with HCC receiving targeted therapy and targeted therapy in combination with TACE. The analysis was performed before treatment and 6 months after the start of therapy, both within groups and between groups. MATERIALS AND METHODS The result of the article is a subanalysis in a prospective study performed under grant from the Ministry of Science and High Education of the Republic of Kazakhstan (Individual Registration Number AP19176025). The study was carried out from October 2024 to September 2025. The research was conducted in accordance with the Declaration of Helsinki and was approved by the Ethics Committee of the of nJSC «Astana Medical University» (No. 21 from 09/2023). All participants provided written informed consent prior to enrollment in the study. A total of 69 patients with HCC were included in the study. The patients were divided into two groups based on the treatment protocol. The first group consisted of 29 patients who received daily targeted therapy with sorafenib at a dose of 800 mg per day. The second group included 40 patients who, in addition to receiving sorafenib at the same dose, underwent TACE with doxorubicin at a dose of 50 mg. Exclusion criteria included patients under 18 years of age, those with metastatic liver cancer, other types of malignancies, cardiovascular diseases, any intraventricular conduction abnormalities, heart rhythm disturbances, ejection fraction less than 50% and a glomerular filtration rate (GFR) less than 30 mL/min. All patients underwent laboratory testing (validated equipment from Roche Diagnostics, Mannheim, Germany) of cardiac biomarkers (hs-cTn I и NTproBNP) before the initiation of therapy (4 ± 1 days) and 6 months after the start of treatment. To assess the probability of developing chronic heart failure, a logistic regression model was constructed, where the predictors were indicators of left ventricular systolic function, and the dependent variable was the occurrence of CHF 6 months after the start of target therapy. Equation (a) was constructed to reflect the dependence of the probability of CHF on GLS indicators. The equation was as follows: Р = (а) where P is the theoretical probability of developing CHF 6 months after the start of therapy, z = (FAC in % x 0.938) + (GLS in % x 0.478) + 410.467. The cut-off value in the model was set at 0.2. If, after calculations, P was less than 0.2, the risk of developing CHF was considered to be higher. Statistical analysis was performed using SPSS version 26 (IBM, USA). For variables with a non-normal distribution, non-parametric methods were applied: the Mann–Whitney U test (for intergroup comparisons) and the Wilcoxon test (for intragroup comparisons). For variables with a normal distribution, Student’s t-test was used. Statistical significance was set at p < 0.05. Data are presented as means with standard deviations, and binary variables are presented as frequencies in absolute values and percentages. Ethical approval The study was approved by the Astana Medical University ethics committee RESULTS Table 1 presents the general characteristics of patients receiving both targeted therapy and targeted therapy combined with transarterial chemoembolization (TACE). The total number of patients with hepatocellular carcinoma included in the study was 69. Women prevailed in the targeted therapy group, accounting for 19 people (66%), and in the targeted therapy combined with TACE group, accounting for 23 women (57%). The average age of patients was 57±8.1 and 59±7.7, respectively. Body mass index, hemoglobin, leukocyte, and platelet levels were within normal limits, with no differences between the two groups. Both groups were at stage C2 of GFR (glomerular filtration rate). BJMS, Vol. 24 No. 04 October’25 Page : 1215-1221

Ana Fernández Baranda, Vincent Bansaye, Evelyne Lauret et al.

Mathematical modeling allows us to better understand myeloproliferative neoplasms (MPN), a group of blood cancers, emergence and development. We test different mathematical models on an initial cohort to determine the emergence and evolution times before diagnosis of JAK2V617F+ classical MPN (Polycythemia Vera (PV) and Essential Thrombocythemia (ET)). We consider the time before diagnosis as the sum of two independent periods: the time (from embryonic development) for the JAK2V617F mutation to occur, not disappear and enter proliferation, and a second time corresponding to the expansion of the clonal population until diagnosis. We prove that the rate of active mutation occurrence increases exponentially with age following the Gompertz model rather than being constant. We find that the first tumorous cell takes an average time of $63.1 \pm 13$ years to appear and start proliferation. On the other hand, the expansion time is constant: $8.8$ years once the mutation has emerged. These results are validated in an external cohort. Using this model, we analyze JAK2V617F ET versus PV, and obtain that the time of active mutation occurrence for PV takes approximately $1.5$ years more than for ET to develop, while the expansion time was similar. In conclusion, our age-dependent approach for the emergence and development of MPN demonstrates that the emergence of a JAKV617F mutation should be linked to an aging mechanism, and indicates a $8-9$ years period of time to develop a full MPN.

Himanshu Pandey, Akhil Amod, Shivang et al.

Artificial Intelligence (AI) and Large Language Models (LLMs) hold significant promise in revolutionizing healthcare, especially in clinical applications. Simultaneously, Digital Twin technology, which models and simulates complex systems, has gained traction in enhancing patient care. However, despite the advances in experimental clinical settings, the potential of AI and digital twins to streamline clinical operations remains largely untapped. This paper introduces a novel digital twin framework specifically designed to enhance oncology clinical operations. We propose the integration of multiple specialized digital twins, such as the Medical Necessity Twin, Care Navigator Twin, and Clinical History Twin, to enhance workflow efficiency and personalize care for each patient based on their unique data. Furthermore, by synthesizing multiple data sources and aligning them with the National Comprehensive Cancer Network (NCCN) guidelines, we create a dynamic Cancer Care Path, a continuously evolving knowledge base that enables these digital twins to provide precise, tailored clinical recommendations.

Minmin Wang, Xu Xie, Yuxi Guo et al.

Tumor Treating Fields (TTFields) is a non-invasive anticancer modality that utilizes alternating electric fields to disrupt cancer cell division and growth. While generally well-tolerated with minimal side effects, traditional TTFields therapy for lung tumors faces challenges due to the influence of respiratory motion. We design a novel closed-loop TTFields strategy for lung tumors by incorporating electrical impedance tomography (EIT) for real-time respiratory phase monitoring and dynamic parameter adjustments. Furthermore, we conduct theoretical analysis to evaluate the performance of the proposed method using the lung motion model. Compared to conventional TTFields settings, we observed that variations in the electrical conductivity of lung during different respiratory phases led to a decrease in the average electric field intensity within lung tumors, transitioning from end-expiratory (1.08 V/cm) to end-inspiratory (0.87 V/cm) phases. Utilizing our proposed closed-Loop TTFields approach at the same dose setting (2400 mA, consistent with the traditional TTFields setting), we can achieve a higher and consistent average electric field strength at the tumor site (1.30 V/cm) across different respiratory stages. Our proposed closed-loop TTFields method has the potential to improved lung tumor therapy by mitigating the impact of respiratory motion.

Вахтанг Михайлович Мерабишвили, Е.В. Бахидзе, Адель Федоровна Урманчеева et al.

Введение. Рак влагалища (С52) – один из редчайших типов гинекологического рака. Созданный в 2019 году в России популяционный раковый регистр (ПРР) на уровне Северо-Западного федерального округа (СЗФО РФ) позволил осуществлять углубленный анализ распространенности и эффективности лечения пациентов с редко встречающимися новообразованиями (рак сердца, глаза, вилочковой железы, мужской молочной железы и др.), в том числе и злокачественными новообразованиями (ЗНО) влагалища. Цель. Изучить распространенность рака влагалища (С52) на основе вновь созданной базы данных (БД) ПРР СЗФО РФ, гистологическую структуру опухолей, расчет однолетней и пятилетней выживаемости пациентов. Материалы и методы. Материалом исследования являются данные Международного агентства по исследованию рака (МАИР), справочники МНИОИ им. П.А. Герцена и НМИЦ онкологии им. Н.Н. Петрова, БД популяционных раковых регистров Санкт-Петербурга и Северо-Западного федерального округа России. Обработка данных осуществлялась с помощью лицензионных программ MS Excel 2013–2016 и Statistica 6.1. Для расчета выживаемости использована модифицированная программа Eurocare, а также математические, библиографические и статистические методы. Результаты. Проведенное исследование подтвердило относительную редкость выявления первичных случаев рака влагалища среди женского населения России и СЗФО РФ: 0,3–0,40/0000, без существенной динамики с 2011 по 2022 г. Показана специфика повозрастного распределения заболеваемости: ЗНО влагалища практически не регистрируются до 30-летнего возраста, от 30 до 34 лет – единичные случаи (0,10/0000), максимальный повозрастной показатель – в 75–79 лет (2,110/0000), а максимальное число заболевших – в 50–59 лет. Однолетняя выживаемость учтенных пациентов в 2000–2009 гг. – 61,5%, пятилетняя – 31,2%. Низкие показатели выживаемости связаны с поздней диагностикой: в I ст. – 13,51% пациентов; II – 28,62%; III – 27,22%; IV – 16,13%, без указания стадии – 14,42%. Однолетняя выживаемость учтенных пациентов в 2010–2019 гг. достигла 70,9%, что объясняется увеличением в 2 раза выявления в I ст. – 26,6%. Пятилетняя выживаемость городских пациентов несколько выше, чем сельских: 32,8% и 28,5 соответственно. Выводы. Анализ данных популяционного исследования указывает на необходимость поиска путей улучшения диагностики и лечения рака влагалища. Introduction. Vaginal cancer (C52) is one of the rarest types of gynecological cancer. The population cancer registry (PRR) created in Russia in 2019 at the level of the Northwestern Federal District (NWFD RF) allowed for an in-depth analysis of the prevalence and effectiveness of treatment for patients with rare tumors (cancer of the heart, eye, thymus, male breast, etc.), including malignant neoplasms (malignant neoplasms) of the vagina. Purpose. To study the prevalence of vaginal cancer (C52) based on the newly created database (DB) of the PRR of the Northwestern Federal District of the Russian Federation, the histological structure of tumors, calculation of one-year and five-year survival of patients. Materials and methods. The research material is data from the International Agency for Research on Cancer (IARC), reference books of the Moscow Research Institute named after P.A. Herzen and National Medical Research Center of Oncology named after N.N. Petrov, databases (DB) of population cancer registries (PRR) of St. Petersburg and the North- Western Federal District of Russia (NWFD RF). Data processing was carried out using licensed programs MS Excel 2013–2016 and STATISTICA 6.1. To calculate survival, a modified Eurocare program was used, as well as mathematical, bibliographic and statistical methods. To conduct the study, 977 primary cases of vaginal cancer were selected from the PRR database of the Northwestern Federal District of the Russian Federation, recorded for the period from 2000 to 2019. Results. The study confirmed the relative rarity of identifying primary cases of vaginal cancer among the female population of Russia and the Northwestern Federal District of the Russian Federation: 0.3–0.40/0000, without significant dynamics from 2011 to 2022. The specificity of the age distribution of morbidity is shown: vaginal cancer is practically not registered until the age of 30, from 30 to 34 years – isolated cases (0.10/0000), the maximum age-specific indicator is at 75–79 years (2.110/0000), and the maximum number of cases is 50–59 years old. The one-year survival rate of registered patients in 2000–2009 was 61.5%, five-year survival rate was 31.2%. Low survival rates are associated with late diagnosis: in stage I. – 13.51% of patients; II – 28.62%; III – 27.22%; IV – 16.13%, without specifying the stage – 14.42%. The one-year survival rate of registered patients in 2010–2019 reached 70.9%, which is explained by a 2-fold increase in detection in stage I. – 26.6%. The five-year survival rate of urban patients is slightly higher than that of rural patients: 32.8% and 28.5, respectively. Summary. Analysis of population-based data points to the need to find ways to improve the diagnosis and treatment of vaginal cancer.