Prostate cancer progression is inherently heterogeneous, driven by complex interactions among tumor biology, patient-specific factors, and treatment response. Existing deterministic models inadequately capture this variability, limiting their ability to represent the stochastic nature of disease evolution and to support reliable prediction in clinical settings. This study introduces a probabilistic framework for modeling prostate cancer progression based on the Fokker–Planck equation, which governs the temporal evolution of the probability density of a latent disease state. The latent state, associated with tumor burden and prostate-specific antigen (PSA) dynamics, evolves under the combined influence of deterministic and stochastic processes. The drift term characterizes tumor growth and therapeutic effects, while the diffusion term captures intrinsic biological variability arising from genetic mutations, microenvironmental conditions, and inter-patient heterogeneity. Numerical simulations demonstrate the evolution of disease-state distributions under varying treatment scenarios, highlighting the ability of the proposed framework to capture a spectrum of plausible trajectories rather than a single deterministic outcome. This enables a more realistic representation of disease progression and treatment response at both individual and population levels. The proposed approach provides a principled foundation for integrating stochastic tumor dynamics with clinical biomarkers and therapeutic interventions. By moving beyond deterministic assumptions, it supports the development of predictive, patient-specific models and advances the application of probabilistic reasoning in oncology and health informatics.
Prostate cancer progression is a complex and heterogeneous process that cannot be fully captured by deterministic models or by reliance on a single biomarker such as prostate-specific antigen (PSA). While PSA is widely used in clinical practice, it provides an incomplete and sometimes misleading representation of the underlying tumor dynamics, particularly in cases of low PSA but significant disease burden or during treatment response. In this study, we utilize anonymous clinical data from prostate cancer patients and propose a stochastic modeling framework to characterize the temporal evolution of prostate cancer as a complex process, incorporating both deterministic biological mechanisms and stochastic variability across patients. The proposed model introduces a latent disease state representing tumor burden, which evolves according to drift and diffusion components reflecting tumor growth, treatment effects, and intrinsic biological uncertainty. In addition to PSA, key clinical variables such as Gleason grade group, disease stage, and treatment exposure are integrated into the model to enhance its clinical interpretability and predictive capability. Numerical simulations demonstrate that the stochastic framework captures clinically meaningful behaviors, including heterogeneous progression trajectories, treatment-induced declines in PSA, and divergence between observed PSA levels and true disease burden. Unlike traditional survival or regression-based approaches, the model provides a full probability distribution of disease states over time, allowing for uncertainty quantification and personalized risk assessment. The results suggest that incorporating latent-state stochastic dynamics can significantly improve the understanding and prediction of prostate cancer progression, offering a foundation for next-generation decision-support systems in precision oncology.
Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related death, and anti-silencing function 1B histone chaperone (ASF1B) has been implicated in several cancers. This study aimed to investigate the role and molecular mechanism of ASF1B in HCC. ASF1B expression was analyzed using the TIMER2, GEO, Oncomine, and GEPIA2 databases, as well as western blotting. Cell viability, cell cycle distribution, and apoptosis were assessed via CCK-8 assay and flow cytometry, respectively. Survival analysis and immune infiltration analysis were performed using the TIMER2 database, and enrichment analysis was conducted via Metascape. Results showed that ASF1B expression was significantly higher in HCC tissues than in normal tissues, and high ASF1B expression predicted poor prognosis and was associated with higher tumor stage. Knockdown of ASF1B by siRNA significantly reduced cell viability, promoted apoptosis, and induced G1 phase cell cycle arrest in SNU-423 cells. Moreover, ASF1B expression was positively correlated with the infiltration levels of immune cells and tumor microenvironment signature cells, particularly functional T cells. Enrichment analysis further indicated that ASF1B may contribute to HCC progression through mechanisms involving cell cycle, cell division and differentiation, and DNA replication and repair. Collectively, these findings suggest that ASF1B overexpression predicts poor prognosis and increased immune infiltration in HCC, highlighting ASF1B as a potential therapeutic target for this malignancy.
This study integrates Kaplan–Meier survival analysis with the Stochastic and Augmented Interpretable Health Analytics (SAIHA) framework to model long-term survival in pancreatic cancer, a malignancy characterized by late diagnosis, rapid progression, and poor prognosis. The Kaplan–Meier estimator was first employed to nonparametrically characterize empirical survival probabilities across the observed follow-up period, capturing censoring patterns and short-term mortality dynamics without imposing distributional assumptions. This step provided a transparent baseline representation of survival up to approximately four years post-diagnosis, where empirical data density remains sufficient for reliable estimation. To address the limitations of traditional Kaplan–Meier analysis in extrapolating beyond observed follow-up, the SAIHA framework was then applied using a Weibull survival model to propagate uncertainty, incorporate population heterogeneity, and generate probabilistic survival projections into the long-term horizon. The Weibull distribution was selected for its flexibility in modeling monotonic hazard functions commonly observed in aggressive cancers and for its interpretability within clinical contexts. Parameter uncertainty was explicitly modeled to reflect variability in disease progression and treatment response across patients. The combined model predicts a pronounced decline in survival beyond year four, with the most likely five-year survival probability estimated near 3% and a median six-year survival approaching 1.5%. These projections align with known epidemiological patterns of pancreatic cancer and underscore the persistent lethality of the disease despite advances in therapy. Importantly, the SAIHA framework provides full survival distributions rather than point estimates, enabling clinicians and researchers to assess uncertainty bounds and tail risks associated with long-term outcomes. Overall, the integrated Kaplan–Meier–SAIHA approach extends classical survival analysis by combining empirical rigor with stochastic, distribution-aware forecasting. This methodology offers a robust and interpretable framework for high-risk clinical prediction, supporting more informed decision-making in oncology research, population health modeling, and precision medicine applications.
Background: Cervical cancer remains a major public health concern in low- and middle-income countries. Screening uptake in Cameroon is far below the World Health Organization’s elimination targets. This study assessed socio-demographic, economic, and informational determinants of low cervical cancer screening uptake among sexually active women in an urban district of Yaoundé. Methods: A cross-sectional study was conducted from September to October 2023 in the Biyem-Assi Health District. A convenience sample of 250 sexually active women aged 25–59 years completed a pre-tested structured questionnaire. Logistic regression was used to identify factors associated with non-participation. Significance was set at p < 0.05. Results: Overall, 89.0% of participants had never been screened. Independent predictors of non-participation were being single (AOR 5.79; 95% CI 3.60–9.45), lack of awareness of screening centers (AOR 5.02; 95% CI 1.24–20.29), no health insurance (AOR 3.91; 95% CI 1.70–8.98), poor knowledge of cervical cancer (AOR 3.16; 95% CI 1.12–8.94), unemployment (AOR 2.16; 95% CI 1.18-4.00), and having ≤1 child (AOR 1.94; 95% CI 1.21-3.12). Conclusion: Cervical cancer screening uptake is critically low in this urban population. The main barriers relate to socioeconomic vulnerability and lack of specific information on where screening services are offered. Improving service visibility, reducing costs, and integrating screening into routine health services may help increase uptake, although further research is required to evaluate feasibility and impact.
Background: We assessed the differential sole and Doxorubicin-(Doxo)-combined chemotherapy of the phytomedicines Crocin and Flavocoxid-(flvcox), against the-mouse-Ehrlich-Ascites-Carcinoma-solid-tumor-model-(EAC). We further identified the underlying-molecular mechanisms of actions, interrelations of probed signals, as well as the relative-potency among all used drug modalities. Methods: Functional studies evaluated tumor-burden, animal-survival, serum/tumor redox-status, and levels of key-effectors coherent with tumorigenesis, inflammation, and host-immunity, namely (serum IL-10 and TNF-α) and with tumor-apoptosis (Caspase-3-expression). Furthermore, histopathological examinations were performed to envisage the associated structural changes. Results: EAC-bearing mice had significantly raised serum-TNF-α and tumor lipid-peroxide (MDA) levels, but lower serum IL-10-levels and total serum antioxidant-capacity-(TAC), thereby showing animal-fatalities after-3-weeks. Crocin administration significantly-shrank tumor-mass by (50%), -reduced tumor lipid-peroxide-(MDA) and serum-TNF-α levels; but raised serum-IL-10, TAC and tumor-caspase-3 levels; ultimately augmenting animal survival by (79%). Flvcox had weaker survival-effects (44%) than that of crocin. Correlation studies showed IL-10, contrary to TNF-α to boost animal-survival, and suppress tumor-size. Tumor caspase-3 levels augmented both animal-survival and the TAC-level, while opposed tumor-weight and tumor-MDA levels. Besides, tumor oxidative-stress boosted tumor growth, and reduced caspase-3 levels, thereby worsening animal survival. Histopathology analyses confirmed functional studies. Conclusions: 1)- The study reveals that Doxo confers superior cytotoxicity but inferior cytokine-balance, redox-status and animal-rescuing profiles; 2)- Crocin and Flvcox elicit prominent sole- and combined-cytotoxicity, and animal-rescuing potentials, by restoring the disrupted-balance of the cytokines (IL-10/TNF-α), optimizing serum/tumor redox-potentials and accelerating tumor-cell apoptosis; 3)- Cross-talk was evidently documented among (key-cytokines), (tumor-burden), (redox-status), and (tumor-apoptosis), in a manner that dictates the efficacy of sole (or) mutual-therapy, and their influence on animal-survival in response to cancer.
A gene mutation refers to a small alteration in DNA that can occur at any time. While many of these changes have minimal impact, some can lead to uncontrolled cell growth, potentially contributing to the development, progression, and spread of diseases such as cancer. These mutations may arise from various factors. For instance, in lung cancer, cigarette smoking is a well-known cause of genetic mutations that can elevate cancer risk. Similarly, exposure to air pollution or harmful toxins can produce the same effect. In some cases, however, mutations occur spontaneously, without any identifiable cause. While not all cancers are caused by gene mutations, certain mutations are strongly linked to specific types of cancer. For example, mutations genes are frequently within tumor cells and are not usually inherited or passed down through families. In this paper, we will investigate gene mutations and will examine the ways in which these mutations may cause various diseases including cancers. It is found that high accuracy classification of gene mutations can be reached by a combination of LSTM (Long Short-Term Memory (LSTM) is an enhanced version of the Recurrent Neural Network) and Markov probabilistic transitions.
Health informatics plays a crucial role in the early detection of lung cancer by enhancing the collection, analysis, and application of patient data in clinical settings. It enables the integration of data from electronic health records (EHRs), imaging, pathology reports, and even genomic information. Artificial Intelligence (AI) and Machine Learning (ML) technologies further support lung cancer detection by tracking disease progression over time, identifying changes that may suggest malignancy, and reducing false-positive and unnecessary procedures. A fundamental challenge, however, remains: many existing lung cancer prediction models report accuracy below 80%, emphasizing the need for more effective classification techniques. In this work, we introduce a novel approach that significantly improves predictive accuracy, achieving rates between 95% and 98% a notable advancement over current methods using the same dataset. This improvement is driven by a recently developed Generative AI technology, considered one of the most powerful tools for enhancing the performance of health informatics systems.
Breast cancer is a type of cancer that is distinguished by the uncontrolled and abnormal growth of breast cells. Globally, it remained the most frequently diagnosed neoplastic disease in women and the leading cause of cancer-related death. Despite the increasing incidence of breast cancer in Ethiopia, there has been a limited study that determines the risk factors for breast cancer. This study employed a hospital-based matched case-control design to analyze breast cancer risk factors for women seeking care at the Hawassa University Comprehensive Specialized Hospital in Hawassa, Ethiopia. A hospital-based, unmatched case-control study design was employed from March 1 to April 30, 2022, among 131 cases and 257 control women attending Hawassa University Comprehensive Specialized Hospital. Data were collected using a standardized, pre-tested questionnaire. SPSS version 20 was used for the statistical analysis of the data. Descriptive statistics were used to summarize the socio-demographic, reproductive, and other characteristics of respondents. The bivariable and multivariable logistic regression analyses were used to assess variables associated with breast cancer and were presented with a 95% confidence interval. The final result was displayed using text figures and tables. In this study, age [AOR=5.79, 95%CI (2.11, 12.75)], family history of cancer (AOR=6.05, 95% CI (1.92 19.03), not consuming fruits (AOR=3.34, 955; CI 1.32, 8.48), eating sea foods (fish) (AOR=.24, 95% CI 0.1, 0.60), using packed food or drink (AOR= 4.10 95% CI, 1.23, 13.67), hormonal contraceptive use (AOR= 3.86 95%, CI 1.62, 9.24), having history of breast injury (AOR= 3.29 95% CI 1.20 9.01), history of abortion (AOR=3.16, 95% CI 1.11 9.00), exposure of radiation (AOR= 2.64 95% CI, 1.14 6.15) were risk factors associated with breast cancer. Having a family history of cancer, not eating fruits, not eating sea foods (fish), using packed foods or drinks, using hormonal contraception, having a history of breast injury, a history of abortion, and previous radiation exposure were all risk factors for breast cancer. Health professionals should deliver health education on the importance of a fruit and fish diet and its association with lower breast cancer risk.
This project aimed to manipulate DNA (deoxyribonucleic acid) aptamer AS1411, a short single-stranded oligonucleotide currently being developed to improve chemotherapy’s target cell specificity. As this aptamer binds explicitly to nucleolin, an overexpressed protein on the surface of cancer cells, chemotherapy damage to surrounding tissue may be lessened. This study modified the AS1411 DNA aptamer, which was named AS1411-N12, by adding 12 nucleotides to the 3’ and 5’ ends, forming a “flap” structure. The edition of said flap is attributed to theory that the increased mass will allow for tighter binding. This modification was hypothesized to further improve the DNA aptamer’s binding efficiency to the nucleolin protein expressed on cancer cells. Binding reactions occurred between DNA aptamers (AS1411 and AS1411-N12) and nucleolin samples. The resulting solutions were processed using micro-centrifugal filters, which separated small unbound single-stranded DNA aptamers from bigger unbound proteins and the DNA-Nucleolin complexes. Measured absorbance of the unbound filtered DNA aptamers were analyzed to compare binding efficiencies of the modified aptamer vs. the control. The average absorbance through 3 trials of the control AS1411 DNA aptamer was 1.907 at 260 nm, while the average absorbance through 3 trials was 1.364 at 260 nm. Through Beer's Law, the unbound DNA control concentration was 146.6 µM while the modified DNA aptamers was 54.17 µM. This modification was highly effective as it yielded a 63% change in absorbance showing a drastic decrease in the amount of DNA aptamer left in solution. The modified DNA aptamer was significantly more effective in binding to its target protein. When attached to chemotherapy, AS1411-N12 will have a higher affinity to Nucleolin, improving cancer treatment.
Introduction: Healthcare professionals working in oncology are exposed to intense and constant stressors, given the severity of the diseases and frequent confrontation with patient death, which can lead to significant psychological distress and professional burnout. This study's objective was to identify the sociodemographic, social, and work-related determinants contributing to this distress among the nursing staff in the medical oncology department of the Yaoundé General Hospital. Materials and Methods: This was a qualitative study conducted from July to December 2017 in a reference medical oncology unit in Cameroon. The study population comprised the entire nursing and medical staff of the department. A non-probability, exhaustive sampling method was used, resulting in seventeen healthcare workers (13 women, 4 men; 10 nurses, 7 doctors) participating. Data were collected through audio-recorded individual semi-structured interviews and subsequently analyzed using manual content analysis. Results: The analysis revealed that psychological distress is a multifaceted issue driven by three main categories of determinants. Sociodemographic factors identified as sources of pressure included female gender, place of residence (linked to long commutes and traffic stress), family pressure, and personal/financial difficulties. Social factors highlighted varying coping strategies, from prayer and communication to emotional detachment (disconnection/splitting) in the face of patient suffering and death. Work-related environmental determinants were found to be the primary cause of distress, unanimously described by staff. These organizational factors included an unbearably heavy workload due to understaffing, stress from managing patient pain and death (often reduced to administrative tasks), difficult interprofessional communication between nurses and doctors, a severe lack of continuous professional training, and a complete absence of gratification or recognition from management. Conclusion: Psychological distress among oncology healthcare professionals is strongly associated with sociodemographic, social, and, critically, pervasive work-related environmental determinants. The heavy and poorly managed workload, coupled with a lack of institutional support, training, and recognition, are major sources of suffering that require urgent attention from hospital administrators to mitigate psychosocial risks.
Background and objectives: Breast cancer (BC) is the leading cancer in Indian women. This study examined relationships between demographic variables of women in rural Vitla and urban areas of Mangalore, Moodbidri and Puttur in Dakshina Kannada District and their awareness of BC screening policy, BC and health insurance. The objectives were to know if rural women have adequate knowledge of BC screening. Methods: 100 women cashew factory workers in Vitla were given an oral questionnaire in Kannada and 65 women from urban areas of Mangalore, Moodbidri and Puttur were given the questionnaire in English. Results: Answer sets were analysed, results indicated no significant correlation between respondents’ education and awareness about BC Screening, Self-Examination (BSE) and government screening policies in Vitla (Dakshina Kannada). No relationship was observed between age and awareness. Women in Vitla (Mangalore is 40 km away from Vitla), were aware of BC and had Ayushman Bharat cover; yet they had no idea about screening or its policy but agreed to screen if motivated. All urban women had received higher education, some had heard of BC screening and had health insurance yet were unwilling to screen. Others had not heard of screening but were willing to go. Interpretation and conclusions: India has a 2016 Government policy to screen BC which has not reached all rural women. It must be implemented effectively as early diagnoses and detection can reduce mortality in BC.
Background: For precancerous cervical lesion (PCL) treatment to be effective and minimizing its consequences, adherence to treatment follow-ups is essential. However, in Ethiopia, women frequently do not follow suggested schedules, and barriers and facilitators are understudied, particularly in Harar city. Purpose: This study aimed at exploring barriers and facilitators to adherence to precancerous cervical lesion treatment follow-up. This information can help inform prevention interventions. Methods: This qualitative study was conducted at a large regional oncology center in Harar, Ethiopia between March and April 2023. The study included a purposive sample of 14 women with precancerous cervical lesions for individual in-depth interviews, as well as 10 nurses working with patients at the oncology center for focus group discussions. Participants interviewed individually using semi-structured interviews guide with the assistance of a voice recorder and field notes. The data were transcribed verbatim and analyzed using a thematic approach. Results: The study identified three major themes for barriers and five major themes for facilitators of adherence to precancerous cervical lesion treatment follow-ups. Conclusion: Personal, clinical, and social barriers impact adherence to precancerous cervical lesion treatment follow-ups. Strategies such as reminders, template preparation, counseling, nearby access, and media awareness can help improve adherence. It is essential to develop programs that are patient, family, society, and clinical-oriented, culturally sensitive, and inclusive to effectively address these barriers.
Background: The anti-epileptic NKCC1 inhibitor Bumetanide (BUM) and the microtubule acting anthelminthic agent Mebendazole (MEB), have anti-cancer properties. Tumor & its environment generate neuronal hyperactivity that aggravates the clinical outcome suggesting that their combination might block hyperactivity (BUM) and augment cell death (MEB). Methods: We tested the effects of the combo on i) NKCC1 activity in human cell lines, ii) electrical activity recorded from mouse hippocampal neurons & tumors freshly resected from patients, iii) glioblastoma-brain co-cultures, iv) cell death in human tumoroids. Results: BUM efficiently inhibited NKCC1 & unexpectedly, MEB applications also via a likely indirect action. In rodent hippocampal neurons, BUM blocked GABAergic Giant Depolarizing Potentials and seizures and co-applications of MEB produced a fourfold increase of BUM's efficacy. In freshly removed brain tumors, E GABA reversal recorded with single GABA channels was highly depolarized (close to -25 mV) in keeping with NKCC1 over activity. BUM fully blocked ongoing epileptic activity. In GBM-Brain cultures, the combo produced stronger effects then independent applications of MEB or BUM. In tumoroids, the combo also efficiently produced strong cell death & morphological changes in some tumors. Conclusion: The combination of BUM & MEB acts complementarily on brain tumors, the former blocking seizures, and the latter producing cell death. Their combination increases their hyperactivity inhibitory actions and cell death. The combo might therefore be used to treat brain tumors combining 2 different mechanisms and targets.
The mechanisms of cancer are discussed by analyzing the characteristics of the functional state and biological behavior of the abnormal nuclear cells. The abnormal nuclear cells with abnormal nuclear structure and function are a kind of sick cell or functional defect cells having existed in human body for a long time. The abnormal nuclear cells are resulted from the nuclear damage caused by the radiation, viruses and various carcinogenic compounds. Some of genes in human body are expressed, some are not expressed for life. The expressional genes are functional genes, the genes never expressed for life in human body are dormant genes or sealed genes. The nuclear damages destroy cell state of differentiation, affect gene expressional regulation and change gene expressional profiling, resulting in loss of expression of the functional genes and reactivation of the sealed genes; which finally leads to cancer, aging and other chronic refractory diseases. The cancer is not resulted from the genetic mutations or chromosomal aberrations, but rather the reactivation of genes involved in proliferation due to the nuclear damage. The biological characteristics of the cancer cells, such as the shedding and metastasis, immune tolerance, uncontrolled, loss of contact inhibition function and so on, all originate from the nuclear aberrant cells. The nuclear damage can trigger the genes that drive mitosis, leading to cancer. Thus, re-sealing the several genes that trigger the proliferation may completely prevent or cure cancers.
Cancer is the leading cause of death and a major obstacle to increasing life expectancy worldwide in the 21st century. Oral cavity cancers are the most common type of head and neck cancers. This study aimed to determine the polymorphism and genetic diversity of the tumor protein P53 (TP53) in oral cavity cancers in Senegal. From a total of 40 patients with oral cavity cancer, we collected 40 cancerous tissue samples, 20 adjacent healthy tissue samples, and 15 blood samples. Blood samples were collected from participants in the control group. Tissue samples were obtained from each patient during a biopsy after obtaining informed consent. DNA extraction, polymerase chain reaction (PCR), and sequencing were performed. MEGA, BioEdit, and DnaSP software were used to analyze polymorphisms and genetic diversity. A total of 36.80%, 22.27%, and 7.74% polymorphic sites were found in cancerous tissues, healthy tissues, and blood samples, respectively. Nine amino acids showed significant differences in distribution between participants in the control group and patients. Significant differences were also observed within and between populations. This study revealed an increasing number of oral cancer cases in Senegal. Moreover, healthy tissues exhibited the same genetic alterations as cancerous tissues.
Microsatellite instability (MSI) is a hallmark of mismatch repair (MMR) deficiency and characterizes a distinct subset of colorectal cancers (CRC). In parallel, telomere length dynamics have emerged as important contributors to genomic stability and tumorigenesis. However, the relationship between MSI status, MMR protein expression, and telomere maintenance remains poorly defined. This study aimed to investigate the association between MSI status and telomere length in CRC cell lines and to evaluate the expression of key MMR proteins (MLH1, MSH2, MSH6, PMS2) to elucidate molecular differences between MSI and microsatellite stable (MSS) phenotypes. A panel of CRC cell lines with known MSI and MSS statuses was used. Telomere length was quantified using real-time quantitative PCR (qPCR) based on the T/S ratio method. MSI status was confirmed via PCR using mononucleotide repeat markers. Western blotting was performed to assess protein expressions of MLH1, MSH2, MSH6, and PMS2. β-actin served as a loading control. qPCR analysis revealed that MSI cell lines exhibited significantly longer telomeres compared to MSS lines (P < 0.05). Western blot results showed reduced or absent expression of MLH1 and PMS2 in MSI cell lines, confirming MMR deficiency. In contrast, MSS cell lines maintained normal expression of all tested MMR proteins. These findings suggest a link between defective MMR function and altered telomere dynamics in MSI-CRC. MSI CRC cell lines exhibit telomere elongation and loss of key MMR proteins, highlighting distinct molecular features compared to MSS counterparts. These insights may inform future strategies for personalized CRC diagnostics and therapeutics, particularly in the context of telomere-targeted or immunomodulatory treatments.
Recently, extensive studies have shown that ferroptosis boosted a perspective for its usage in cancer therapeutics. The current study aims to construct a robust ferroptosis-related lncRNAs signature prediction model to increase the predicted value of colorectal cancer (CRC) by bioinformatics analysis. By comparing CRC tissue with adjacent normal tissues, we screened 2541 differentially expressed lncRNAs from The Cancer Genome Atlas (TCGA) CRC using the R language and "limma" package, of which 439 are ferroptosis-related lncRNAs. Univariate Cox regression, lasso regression, multivariate Cox regression are used to construct a seven ferroptosis-related lncRNAs (AC005550.2, LINC02381, AL137782.1, C2orf27A, AC156455.1, AL354993.2, AC008760.1) prognostic signature in train set. This model's prognosis in the high-risk group is worse than that of the low-risk group in the train set, test set, and entire set. Based on the stratification of clinical variables (gender, age, clinical stage, postoperative tumor status, CEA levels, perineural invasion, vascular invasion, mismatch repair (MMR) and gene mutation status (KRAS, BRAF)), the high-risk group's prognosis is also worse than that of the low-risk group. The area under curve (AUC) of receiver operating characteristic (ROC) curve for predicting three years survival in the train set, test set, and entire set were 0.796, 0.715, and 0.758, respectively. Furthermore, Univariate Cox regression and multivariate Cox regression displayed that the signature could serve as an independent prognostic factor; meanwhile, we draw the nomogram based on multivariate Cox regression (P<0.05). Compared to clinical variables, this signature's ROC curves demonstrated the second largest AUC value (0.737). The expression of these lncRNAs and the lncRNA signature are related to clinical stage, T stage, Lymph-node status, distant metastasis, KRAS mutation, BRAF mutation, MMR status, and perineural invasion. Finally, GSEA analysis results show that the signature is involved in six KEGG signal pathways, such as KEGG_HEDGEHOG_SIGNALING_PATHWAY, KEGG_ALPHA_LINOLENIC_ACID_METABOLISM, KEGG_ARACHIDONIC_ACID_METABOLISM, KEGG_CITRATE_CYCLE_TCA_CYCLE, KEGG_PENTOSE_PHOSPHATE_PATHWAY, KEGG_FRUCTOSE_AND_MANNOSE_METABOLISM. In conclusion, the current study shows a seven ferroptosis-related lncRNA signature could efficiently function as a novel and independent prognosis biomarker and therapeutic target for CRC patients.
Giant Cell Tumor of Bone (GCTB) is a common intermediate tumor, and the specific molecular mechanisms of this disease have not been fully elucidated.It exhibits strong heterogeneity in terms of targets, regulatory mechanisms, cell types, states, and subset distributions in the immune microenvironment.Traditional collective-level analyses cannot accurately reveal these differences.Single-cell sequencing technology is a technique that sequences the genome, transcriptome, and epigenome of diseases at the single-cell level.Single-cell sequencing can utilize a higher pixel resolution to reveal characteristic states of different cell subpopulations, contributing to broadening new perspectives for the study of GCTB heterogeneity.It holds significant value for the precise diagnosis of GCTB, identification of potential immunotherapy targets, and prognosis assessment.This study primarily reviews research related to GCTB, single-cell high-throughput sequencing technology, GCTB immune microenvironment, GCTB heterogeneity, and the construction of GCTB cell maps.It aims to provide theoretical reference for research on single-cell sequencing technology in GCTB and offers a theoretical basis for in-depth exploration of the mechanisms and treatment of GCTB.
For patients with early-stage non-small cell lung cancer (NSCLC) who cannot undergo surgery, stereotactic body radiotherapy (SBRT), also known as stereotactic ablative radiotherapy (SABR), usually achieves good therapeutic effects. This new treatment method has the characteristics of low toxicity and high efficacy for peripheral lung cancer. However, in central type lung cancer, especially in lesions near structures such as bronchial trees or mediastinum, there is an increased risk of severity. This review summarizes the following areas: (1) the methods and indications of using SBRT to treat NSCLC patients in different areas; (2) the principle and advantages and disadvantages of targeted MRI linear accelerators; (3) the diagnostic and evaluation process of targeted MRI linear accelerator therapy for lung cancer; (4) the clinical process of targeted MRI linear accelerator treatment for lung cancer; (5) tracking and monitoring of targeted MRI linear accelerator therapy for lung cancer; (6) pulmonary MRI disorders may include the following situations; (7) how to evaluate stage I-IV non-small cell lung cancer with targeted MRI linear accelerator; (8) how to locate central and peripheral lung cancer using targeted MRI linear accelerators; (9) increase safety of SBRT in central locations.
