Survival Rate Of Cancer Patients Research Articles

Constructing lncRNA-miRNA-mRNA networks specific to individual cancer patients and finding prognostic biomarkers

BackgroundThe competitive endogenous RNA (ceRNA) hypothesis suggests that microRNAs (miRNAs) mediate a regulatory relation between long noncoding RNAs (lncRNAs) and messenger RNAs (mRNAs) which share similar miRNA response elements (MREs) to bind to the same miRNA. Since the ceRNA hypothesis was proposed, several studies have been conducted to construct a network of lncRNAs, miRNAs and mRNAs in cancer. However, most cancer-related ceRNA networks are intended for representing a general relation of RNAs in cancer rather than for a patient-specific relation. Due to the heterogeneous nature of cancer, lncRNA-miRNA-mRNA interactions can vary in different patients.ResultsWe have developed a new method for constructing a ceRNA network of lncRNAs, miRNAs and mRNAs, which is specific to an individual cancer patient and for finding prognostic biomarkers consisting of lncRNA-miRNA-mRNA triplets. We tested our method on extensive data sets of three types of cancer (breast cancer, liver cancer, and lung cancer) and obtained potential prognostic lncRNA-miRNA-mRNA triplets for each type of cancer.ConclusionsAnalysis of expression patterns of the RNAs involved in the triplets and survival rates of cancer patients revealed several interesting findings. First, even for the same cancer type, prognostic lncRNA-miRNA-mRNA triplets can be different depending on whether lncRNA and mRNA show opposite or similar expression patterns. Second, prognostic lncRNA-miRNA-mRNA triplets are often more predictive of survival rates than RNA pairs or individual RNAs. Our approach will be useful for constructing patient-specific lncRNA-miRNA-mRNA networks and for finding prognostic biomarkers from the networks.

Constructing lncRNA-miRNA-mRNA networks specific to individual cancer patients and finding prognostic biomarkers

BackgroundThe competitive endogenous RNA (ceRNA) hypothesis suggests that microRNAs (miRNAs) mediate a regulatory relation between long noncoding RNAs (lncRNAs) and messenger RNAs (mRNAs) which share similar miRNA response elements (MREs) to bind to the same miRNA. Since the ceRNA hypothesis was proposed, several studies have been conducted to construct a network of lncRNAs, miRNAs and mRNAs in cancer. However, most cancer-related ceRNA networks are intended for representing a general relation of RNAs in cancer rather than for a patient-specific relation. Due to the heterogeneous nature of cancer, lncRNA-miRNA-mRNA interactions can vary in different patients.ResultsWe have developed a new method for constructing a ceRNA network of lncRNAs, miRNAs and mRNAs, which is specific to an individual cancer patient and for finding prognostic biomarkers consisting of lncRNA-miRNA-mRNA triplets. We tested our method on extensive data sets of three types of cancer (breast cancer, liver cancer, and lung cancer) and obtained potential prognostic lncRNA-miRNA-mRNA triplets for each type of cancer.ConclusionsAnalysis of expression patterns of the RNAs involved in the triplets and survival rates of cancer patients revealed several interesting findings. First, even for the same cancer type, prognostic lncRNA-miRNA-mRNA triplets can be different depending on whether lncRNA and mRNA show opposite or similar expression patterns. Second, prognostic lncRNA-miRNA-mRNA triplets are often more predictive of survival rates than RNA pairs or individual RNAs. Our approach will be useful for constructing patient-specific lncRNA-miRNA-mRNA networks and for finding prognostic biomarkers from the networks.

Advances in ovarian tumor stem cells and therapy.

Ovarian cancer is considered the most lethal among all gynecological malignancies due to its early metastatic dissemination, extensive spread, and malignant ascites. The current standard of care for advanced ovarian cancer involves a combination of cytoreductive surgery and chemotherapy utilizing platinum-based and taxane-based agents. Although initial treatment yields clinical remission in 70-80% of patients, the majority eventually develop treatment resistance and tumor recurrence. A growing body of evidence indicates the existence of cancer stem cells within diverse solid tumors, including ovarian cancer, which function as a subpopulation to propel tumor growth and disease advancement by means of drug resistance, recurrence, and metastasis. The presence of ovarian cancer stem cells is widely considered to be a significant contributor to the unfavorable clinical outcomes observed in patients with ovarian cancer, as they play a crucial role in mediating chemotherapy resistance, recurrence, and metastasis. Ovarian cancer stem cells possess the capacity to reassemble within the entirety of the tumor following conventional treatment, thereby instigating the recurrence of ovarian cancer and inducing resistance to treatment. Consequently, the creation of therapeutic approaches aimed at eliminating ovarian cancer stem cells holds great potential for the management of ovarian cancer. These cells are regarded as one of the most auspicious targets and mechanisms for the treatment of ovarian cancer. There is a pressing need for a comprehensive comprehension of the fundamental mechanisms of ovarian cancer's recurrence, metastasis, and drug resistance, alongside the development of effective strategies to overcome chemoresistance, metastasis, and recurrence. The implementation of cancer stem cell therapies may potentially augment the tumor cells' sensitivity to existing chemotherapy protocols, thereby mitigating the risks of tumor metastasis and recurrence, and ultimately improving the survival rates of ovarian cancer patients.

The Role of AKR1B10 in Lung Cancer Malignancy Induced by Sublethal Doses of Chemotherapeutic Drugs.

Chemotherapy remains a cornerstone in lung cancer treatment, yet emerging evidence suggests that sublethal low doses may inadvertently enhance the malignancy. This study investigates the paradoxical effects of sublethal low-dose chemotherapy on non-small-cell lung cancer (NSCLC) cells, emphasizing the role of Aldo-keto reductase family 1 member B10 (AKR1B10). We found that sublethal doses of chemotherapy unexpectedly increased cancer cell migration approximately 2-fold and invasion approximately threefold, potentially promoting metastasis. Our analysis revealed a significant upregulation of AKR1B10 in response to taxol and doxorubicin treatment, correlating with poor survival rates in lung cancer patients. Furthermore, silencing AKR1B10 resulted in a 1-2-fold reduction in cell proliferation and a 2-3-fold reduction in colony formation and migration while increasing chemotherapy sensitivity. In contrast, the overexpression of AKR1B10 stimulated growth rate by approximately 2-fold via ERK pathway activation, underscoring its potential as a target for therapeutic intervention. The reversal of these effects upon the application of an ERK-specific inhibitor further validates the significance of the ERK pathway in AKR1B10-mediated chemoresistance. In conclusion, our findings significantly contribute to the understanding of chemotherapy-induced adaptations in lung cancer cells. The elevated AKR1B10 expression following sublethal chemotherapy presents a novel molecular mechanism contributing to the development of chemoresistance. It highlights the need for strategic approaches in chemotherapy administration to circumvent the inadvertent enhancement of cancer aggressiveness. This study positions AKR1B10 as a potential therapeutic target, offering a new avenue to improve lung cancer treatment outcomes by mitigating the adverse effects of sublethal chemotherapy.

The Impact of Specific High-Pathogenic Tp53 Mutations on Survival in Head and Neck Cancers

Head and neck cancers (HNC) constitute about 30-40 % of all cancers in India. tp53 tumor suppressor gene is the most common gene mutated in HNC but has not been demonstrated to have any diagnostic or prognostic significance. therefore, we hypothesize that the survival rate and prognosis of head and neck cancer patients are linked with certain specific high-pathogenic tp53 hot spot mutations. To evaluate the hypothesis, we conducted a retrospective study on a cohort of 100 HNC patients between April 2013 and April 2018. targeted deep sequencing was performed to identify specific somatic mutations. Kaplan–Meier analysis and log-rank tests were performed. Tp53 mutations were identified in 47 of the 100 cases, with dual mutations in 4 patients. Functional characteristics displayed loss of function in 54.9% and gain of function in 27.5 % of cases. the majority of cases displayed missense aberration (74.5%), followed by nonsense mutations (11.76%). Of these pathogenic mutations, 33.3% fell into 6 hot spot residues while mini hot spot residues constituted 20.5% of the mutations. There was no statistically significant difference in the median survival rate between patients with and without the out tp53 mutation. however, the median survival rate was linked with poor prognosis in patients with specific pathogenic hot spot mutations in 247, 248, 245, and 175 residues (p value= 0.028). The majority of hot spot mutations (66%) showed a gain of function which may have been contributory to the pathogenicity of the disease. Results provide evidence that the existence of high-pathogenicity hot spot residues appears to be the only mutation that warrants further research to identify the therapeutic and prognostic significance of the tp53 gene in the treatment of HNC. further systemic studies are recommended to validate this hypothesis.

Analysis of lymph node metastasis and survival prognosis in early gastric cancer patients: A retrospective study.

Early gastric cancer (EGC) is a common malignant tumor of the digestive system, and its lymph node metastasis and survival prognosis have been concerning. By retrospectively analyzing the clinical data of EGC patients, we can better understand the status of lymph node metastasis and its impact on survival and prognosis. To evaluate the prognosis of EGC patients and the factors that affect lymph node metastasis. The clinicopathological data of 1011 patients with EGC admitted to our hospital between January 2015 and December 2023 were collected in a retrospective cohort study. There were 561 males and 450 females. The mean age was 58 ± 11 years. The patient underwent radical gastrectomy. The status of lymph node metastasis in each group was determined according to the pathological examination results of surgical specimens. The outcomes were as follows: (1) Lymph node metastasis in EGC patients; (2) Analysis of influencing factors of lymph node metastasis in EGC; and (3) Analysis of prognostic factors in patients with EGC. Normally distributed measurement data are expressed as mean ± SD, and a t test was used for comparisons between groups. The data are expressed as absolute numbers or percentages, and the chi-square test was used for comparisons between groups. Rank data were compared using a nonparametric rank sum test. A log-rank test and a logistic regression model were used for univariate analysis. A logistic stepwise regression model and a Cox stepwise regression model were used for multivariate analysis. The Kaplan-Meier method was used to calculate the survival rate and construct survival curves. A log-rank test was used for survival analysis. Analysis of influencing factors of lymph node metastasis in EGC. The results of the multifactor analysis showed that tumor length and diameter, tumor site, tumor invasion depth, vascular thrombus, and tumor differentiation degree were independent influencing factors for lymph node metastasis in patients with EGC (odds ratios = 1.80, 1.49, 2.65, 5.76, and 0.60; 95%CI: 1.29-2.50, 1.11-2.00, 1.81-3.88, 3.87-8.59, and 0.48-0.76, respectively; P < 0.05). Analysis of prognostic factors in patients with EGC. All 1011 patients with EGC were followed up for 43 (0-13) months. The 3-year overall survival rate was 97.32%. Multivariate analysis revealed that age > 60 years and lymph node metastasis were independent risk factors for prognosis in patients with EGC (hazard ratio = 9.50, 2.20; 95%CI: 3.31-27.29, 1.00-4.87; P < 0.05). Further analysis revealed that the 3-year overall survival rates of gastric cancer patients aged > 60 years and ≤ 60 years were 99.37% and 94.66%, respectively, and the difference was statistically significant (P < 0.05). The 3-year overall survival rates of patients with and without lymph node metastasis were 95.42% and 97.92%, respectively, and the difference was statistically significant (P < 0.05). The lymph node metastasis rate of EGC patients was 23.64%. Tumor length, tumor site, tumor infiltration depth, vascular cancer thrombin, and tumor differentiation degree were found to be independent factors affecting lymph node metastasis in EGC patients. Age > 60 years and lymph node metastasis are independent risk factors for EGC prognosis.

Analysis of lymph node metastasis and survival prognosis in early gastric cancer patients: A retrospective study.

Early gastric cancer (EGC) is a common malignant tumor of the digestive system, and its lymph node metastasis and survival prognosis have been concerning. By retrospectively analyzing the clinical data of EGC patients, we can better understand the status of lymph node metastasis and its impact on survival and prognosis. To evaluate the prognosis of EGC patients and the factors that affect lymph node metastasis. The clinicopathological data of 1011 patients with EGC admitted to our hospital between January 2015 and December 2023 were collected in a retrospective cohort study. There were 561 males and 450 females. The mean age was 58 ± 11 years. The patient underwent radical gastrectomy. The status of lymph node metastasis in each group was determined according to the pathological examination results of surgical specimens. The outcomes were as follows: (1) Lymph node metastasis in EGC patients; (2) Analysis of influencing factors of lymph node metastasis in EGC; and (3) Analysis of prognostic factors in patients with EGC. Normally distributed measurement data are expressed as mean ± SD, and a t test was used for comparisons between groups. The data are expressed as absolute numbers or percentages, and the chi-square test was used for comparisons between groups. Rank data were compared using a nonparametric rank sum test. A log-rank test and a logistic regression model were used for univariate analysis. A logistic stepwise regression model and a Cox stepwise regression model were used for multivariate analysis. The Kaplan-Meier method was used to calculate the survival rate and construct survival curves. A log-rank test was used for survival analysis. Analysis of influencing factors of lymph node metastasis in EGC. The results of the multifactor analysis showed that tumor length and diameter, tumor site, tumor invasion depth, vascular thrombus, and tumor differentiation degree were independent influencing factors for lymph node metastasis in patients with EGC (odds ratios = 1.80, 1.49, 2.65, 5.76, and 0.60; 95%CI: 1.29-2.50, 1.11-2.00, 1.81-3.88, 3.87-8.59, and 0.48-0.76, respectively; P < 0.05). Analysis of prognostic factors in patients with EGC. All 1011 patients with EGC were followed up for 43 (0-13) months. The 3-year overall survival rate was 97.32%. Multivariate analysis revealed that age > 60 years and lymph node metastasis were independent risk factors for prognosis in patients with EGC (hazard ratio = 9.50, 2.20; 95%CI: 3.31-27.29, 1.00-4.87; P < 0.05). Further analysis revealed that the 3-year overall survival rates of gastric cancer patients aged > 60 years and ≤ 60 years were 99.37% and 94.66%, respectively, and the difference was statistically significant (P < 0.05). The 3-year overall survival rates of patients with and without lymph node metastasis were 95.42% and 97.92%, respectively, and the difference was statistically significant (P < 0.05). The lymph node metastasis rate of EGC patients was 23.64%. Tumor length, tumor site, tumor infiltration depth, vascular cancer thrombin, and tumor differentiation degree were found to be independent factors affecting lymph node metastasis in EGC patients. Age > 60 years and lymph node metastasis are independent risk factors for EGC prognosis.

Dual-reporter fluorescent probe for precise identification of liver cancer by sequentially responding to carboxylesterase and polarity

Early treatment significantly improves the survival rate of liver cancer patients, so the development of early diagnostic methods for liver cancer is urgent. Liver cancer can develop from viral hepatitis, alcoholic liver, and fatty liver, thus making the above diseases share common features such as elevated viscosity, reactive oxygen species, and reactive nitrogen species. Therefore, accurate differentiation between other liver diseases and liver cancer is both a paramount practical need and challenging. Numerous fluorescent probes have been reported for the diagnosis of liver cancer by detecting a single biomarker, but these probes lack specificity for liver cancer in complex biological systems. Obviously, using multiple liver cancer biomarkers as the basis for judgment can dramatically improve diagnostic accuracy. Herein, we report the first fluorescent probe, LD-TCE, that sequentially detects carboxylesterase (CE) and lipid droplet polarity in liver cancer cells with high sensitivity and selectivity, with linear detection of CE in the range of 0–6 U/mL and a 65-fold fluorescence enhancement in response to polarity. The probe first reacts with CE and releases weak fluorescence, which is then dramatically enhanced due to the decrease in lipid droplet polarity in liver cancer cells. This approach allows the probe to enable specific imaging of liver cancer with higher contrast and accuracy. The probe successfully achieved the screening of liver cancer cells and the precise identification of liver cancer in mice. More importantly, it is not disturbed by liver fibrosis, which is a common pathological feature of many liver diseases. We believe that the LD-TCE is expected to be a powerful tool for early diagnosis of liver cancer.

Molecular Mechanism of WWOX Inhibiting the Development of Esophageal Cancer by Inhibiting Hippo Signaling Pathway.

With the emergence of combined surgical treatments, complemented by radiotherapy and chemotherapy, survival rates for esophageal cancer patients have improved, but the overall 5-year survival rate remains low. Therefore, there is an urgent need for further research into the pathogenesis of esophageal cancer and the development of effective prevention, diagnosis, and treatment methods. We initially utilized the GeneCards and DisGeNET databases to identify the esophageal cancer-associated gene WWOX (WW domain containing oxidoreductase). Subsequently, we employed RT-qPCR (Reverse transcription-quantitative PCR) and WB (western blot) to investigate the differential expression of WWOX in HEEC (human esophageal endotheliocytes) and various ESCC (esophageal squamous cell carcinoma) cell lines. We further evaluated alterations in cell proliferation, migration and apoptosis via CCK8 (cell counting kit-8) and clonal formation, Transwell assays and flow cytometry. Additionally, we investigated changes in protein expressions related to the Hippo signaling pathway (YAP/TEAD) through RT-qPCR and WB. Lastly, to further elucidate the regulatory mechanism of WWOX in ESCC, we performed exogenous YAP rescue experiments in ESCC cells with WWOX overexpression to investigate the alterations in apoptosis and proliferation. Results indicated that the expression of WWOX in ESCC was significantly downregulated. Subsequently, upon overexpression of WWOX, ESCC cell proliferation and migration decreased, while apoptosis increased. Additionally, the expression of YAP and TEAD were reduced. However, the sustained overexpression of YAP attenuated the inhibitory effects of WWOX on ESCC cell malignancy. In conclusion, WWOX exerts inhibitory effects on the proliferation and migration of ESCC and promotes apoptosis by suppressing the Hippo signaling pathway. These findings highlight the potential of WWOX as a novel target for the diagnosis and treatment of esophageal cancer.

A new extended Pham distribution for modelling cancer data

In this study, a novel extended Pham model is offered and examined. This model can fit positive, negative, and approximately symmetric data. In addition, it features four alternative hazard rate shapes, namely increasing, decreasing, bathtub, and upside-down bathtub shapes. The new model's main properties, such as quantiles, moments, and mean deviations, are derived. To evaluate the estimation of distribution parameters, two approaches are studied. From a classical standpoint, the maximum likelihood technique is used to determine the point and approximate confidence intervals of all unknown parameters. The Bayesian estimation method, on the other hand, is considered via the Markov chain Monte Carlo technique for obtaining Bayes point estimates alongside Bayes credible intervals. We present various Monte Carlo simulation studies to investigate the efficacy of maximum likelihood and Bayes estimation findings for the model's parameters. Numerical investigations showed that the offered Bayes estimates outperformed those derived using the conventional method. We also analyzed two sets of real data taken from the medical sector; the first represents survival rates for cancer patients who received a combination of radiotherapy and chemotherapy, and the second consists of remission times for bladder cancer patients. These clinical scenarios reveal that the new model outperforms other important competing models based on specific statistical criteria. Ultimately, for both clinical data applications, the proposed extended Pham distribution is the best choice compared to the traditional Pham and the other well-known eight lifetime models.

An Annual Symposium on Disparities in Milwaukee, WI, with a 2023 Focus on Older Adults with Cancer.

Cancer-related inequities are prevalent in Wisconsin, with lower survival rates for breast, colorectal, and lung cancer patients from marginalized communities. This manuscript describes the ongoing efforts at the Medical College of Wisconsin and potential pathways of community engagement to promote education and awareness in reducing inequities in cancer care. While some cancer inequities are related to aggressive disease biology, health-related social risks may be addressed through community-academic partnerships via an open dialogue between the community members and academic faculty. To develop potential pathways of community-academic partnerships, an annual Cancer Disparities Symposium concept evolved as a pragmatic and sustainable model in an interactive learning environment. In this manuscript, we describe the programmatic development and execution of the annual Cancer Disparities Symposium, followed by highlights from this year's meeting focused on geriatric oncology as discussed by the speakers.

Evaluation of High-Dimensional Data Classification for Skin Malignancy Detection Using DL-Based Techniques

Skin cancer can be detected through visual screening and skin analysis based on the biopsy and pathological state of the human body. The survival rate of cancer patients is low, and millions of people are diagnosed annually. By determining the different comparative analyses, the skin malignancy classification is evaluated. Using the Isomap with the vision transformer, we analyze the high-dimensional images with dimensionality reduction. Skin cancer can present with severe cases and life-threatening symptoms. Overall performance evaluation and classification tend to improve the accuracy of the high-dimensional skin lesion dataset when completed. In deep learning methodologies, the distinct phases of skin malignancy classification are determined by its accuracy, specificity, F1 recall, and sensitivity while implementing the classification methodology. A nonlinear dimensionality reduction technique called Isomap preserves the data’s underlying nonlinear relationships intact. This is essential for the categorization of skin malignancies, as the features that separate malignant from benign skin lesions may not be linearly separable. Isomap decreases the data’s complexity while maintaining its essential characteristics, making it simpler to analyze and explain the findings. High-dimensional datasets for skin lesions have been evaluated and classified more effectively when evaluated and classified using Isomap with the vision transformer.

USE OF SGLT2–INHIBITORS IN THE TREATMENT OF ANTHRACICLINE CARDIOTOXICITY

Abstract The survival rate of cancer patients has significantly increased in the last 25 years thanks to the extraordinary advances in anti-tumor therapies. However, many chemotherapeutic agents are potentially cardiotoxic. In particular, anthracycline-induced cardiotoxicity is a clinical condition caused by chemotherapy drugs that lead to morpho-functional alterations and cell death of cardiomyocytes; the most typical clinical manifestation of this cardiotoxicity is the development of left ventricular dysfunction, which over time can evolve towards full-blown heart failure. It is therefore characterized by a reversible asymptomatic stage that progresses to an irreversible stage, often difficult to treat. For an early individualization of this toxicity, a dedicated clinic has been established in our center for the monitoring of patients undergoing treatment with cardiotoxic chemotherapy. We describe the case of a 53-year-old patient with preserved biventricular systolic function undergoing neoadjuvant treatment for breast cancer, who at the end of the second infusion of anthracyclines presented with mild exertional dyspnoea associated with radiological signs of pulmonary congestion and an increase in the indices of myocardionecrosis and BNP. The echocardiogram revealed a sudden worsening of the left ventricular systolic function which was 48%. It was therefore decided to hospitalize the patient and initiate infusional diuretic therapy with a rapid clinical and instrumental response. An SGLT2 inhibitor with indication for the treatment of heart failure with moderately reduced ejection fraction was also added to the therapy. At the one-month check-up, there was an almost complete recovery of left ventricular function and a clear symptomatic benefit with associated normalization of laboratory markers of myocardial damage and heart failure, with the possibility for the patient to undergo surgery to remove the left ventricle. tumor mass. This clinical case could represent a starting point to start considering therapy with SGLT2 inhibitors for the prevention and early treatment of cardiac toxicities from some chemotherapeutics, in order to avoid the process of irreversibility of myocardial damage with subsequent poor response to anti-inflammatory therapies. – conventional compensation.

Characteristics of Orthodontic Treatment in Cancer Survivors: A Systematic Review.

Background: Survival rates of cancer patients have increased globally and across age groups. Challenges arising from craniofacial growth-development disturbances and dental abnormalities might warrant modifications to standard orthodontic pathways of care. Objective: The aim of this study was to systematically summarize and critically assess the available literature regarding the characteristics of orthodontic treatment in cancer survivors. Materials and Methods: A systematic search was conducted in seven databases for studies on malignant tumor survivors having undergone orthodontic intervention with fixed appliances following cancer treatment up to August 2023. The outcomes of interest included quantitative data regarding various characteristics of orthodontic treatment and the post-treatment period. The risk of bias was assessed individually with the Newcastle-Ottawa scale. Results: Out of 347 records, 4 cohort studies were eventually included in the qualitative synthesis. Leukemia was the most common malignancy type, with treatment involving mainly chemotherapy and/or radiotherapy. The duration of orthodontic treatment in cancer survivors varied. Occlusal results, quality of life, and satisfaction were comparable to healthy peers. However, in some survivors' groups, treatment was shorter and the final results were compromised. Root resorption and oral mucositis were reported among the treated cancer survivors. Reduced occlusal outcome stability during the retention period was also reported. Conclusions: Overall, the duration of orthodontic treatment varied among cancer survivors. The occlusal results achieved were similar to those of their healthy peers, though potentially less stable. Patient-reported outcomes did not differ significantly between cancer survivors and healthy individuals treated orthodontically.

Injectable bio-multifunctional hyaluronic acid-based hydrogels loaded with poly ADP-ribose polymerase inhibitors for ovarian cancer therapy

The recent use of PARP inhibitors (PARPi) in the maintenance treatment of ovarian tumor has significantly improved the survival rates of cancer patients. However, the current oral administration of PARP inhibitors fails to realize optimal therapeutic effects due to the low bioavailability in cancerous tissues, and often leads to a range of systemic adverse effects including hematologic toxicities, digestive system reactions, and neurotoxicities. Therefore, the demand for an advanced drug delivery system that can ensure effective drug administration while minimizing these unfavorable reactions is pressing. Injectable hydrogel emerges as a promising solution for local administration with the capability of sustainable drug release. In this study, we developed an injectable hydrogel made from aminated hyaluronic acid and aldehyde-functionalized pluronic127 via Schiff base reaction. This hydrogel exhibits excellent injectability with short gelation time and remarkable self-healing ability, and is applied to load niraparib. The drug-loaded hydrogel (HP@Nir hydrogel) releases drugs sustainably as tested in vitro as well as displays significant anti-proliferation and anti-migratory properties on human epithelial ovarian cancer cell line. Notably, HP@Nir hydrogel effectively suppresses the growth of ovarian cancer, without significant adverse reactions as demonstrated in animal studies. Additionally, the developed hydrogel is gradually degraded in vivo for around 20 d, while maintaining good biocompatibility. Overall, the injectable hydrogel loaded with niraparib provides a secure and efficient strategy for the treatment and management of ovarian cancer.

Comparison of deep learning models to traditional Cox regression in predicting survival of colon cancer: Based on the SEER database.

In this study, a deep learning algorithm was used to predict the survival rate of colon cancer (CC) patients, and compared its performance with traditional Cox regression. In this population-based cohort study, we used the characteristics of patients diagnosed with CC between 2010 and 2015 from the Surveillance, Epidemiology and End Results (SEER) database. The population was randomized into a training set (n=10596, 70%) and a test set (n=4536, 30%). Brier scores, area under the (AUC) receiver operating characteristic curve and calibration curves were used to compare the performance of the three most popular deep learning models, namely, artificial neural networks (ANN), deep neural networks (DNN), and long-short term memory (LSTM) neural networks with Cox proportional hazard (CPH) model. In the independent test set, the Brier values of ANN, DNN, LSTM and CPH were 0.155, 0.149, 0.148, and 0.170, respectively. The AUC values were 0.906 (95% confidence interval [CI] 0.897-0.916), 0.908 (95% CI 0.899-0.918), 0.910 (95% CI 0.901-0.919), and 0.793 (95% CI 0.769-0.816), respectively. Deep learning showed superior promising results than CPH in predicting CC specific survival. Deep learning showed potential advantages over traditional CPH models in terms of prognostic assessment and treatment recommendations. LSTM exhibited optimal predictive accuracy and has the ability to provide reliable information on individual survival and treatment recommendations for CC patients.

The state of cancer care in Russia: liver cancer - (From 22). Age-related features of the observed and relative one-year and five-year survival of patients. (clinical and population-based study). Part 2.

Survival rate calculations for liver cancer patients at the federal level in the Russian Federation are only conducted in the North-Western Federal District and a few other individual administrative territories. In the first part of our study, we presented a detailed analysis of the prevalence of liver cancer, noting that the levels of standardized incidence and mortality rates in Russia and the North-Western Federal District are virtually identical, allowing us to consider the results of our study as nationally representative. The conducted research confirmed the seriousness of the issue of liver cancer among the population. However, certain advancements in patient treatment were recorded, with a significant increase in survival rates, primarily for one-year survival. For example, in the North-Western Federal District, one-year survival increased from 13.6% in 2000 to 23.1% in 2022, representing a 69.8% increase. At the same time, five-year survival rates remained largely unchanged. Increases in survival rates were observed in most age groups. A significant deficiency in the initial patient record-keeping was identified - insufficiently accurate determination of the stage of liver cancer. One-year survival rates for male and female liver cancer patients (22.7% and 22.1%) were nearly equal, as were the survival rates for liver cancer patients residing in urban and rural areas. Therefore, further improvement in the outcomes of treatment for this complex patient group can only be achieved through the implementation of regional and federal screening and epidemiological surveillance programs among populations at high and extremely high risk of developing hepatocellular carcinoma.

Construction and validation of an innovative prognostic nomogram for overall survival in cervical cancer patients with lung metastasis: an analysis utilizing the SEER database.

To facilitate patient consultation and assist in clinical decision-making, we developed a predictive model to analyze the overall survival (OS) rate of cervical cancer patients with concurrent lung metastasis for 6 months, 1 year, or 2 years. We extracted data on patients diagnosed with cervical cancer and concurrent lung metastasis between 2010 and 2020 from the Surveillance, Epidemiology, and End Results (SEER) database. Through a random assignment process, these patients were allocated to either a training cohort or a validation cohort, maintaining a 7:3 ratio. Utilizing both univariate and multivariate Cox regression analyses, we determined the independent prognostic factors influencing OS. To enhance predictive accuracy, we developed a nomogram model incorporating these identified independent prognostic variables. Model effectiveness was subsequently assessed using various metrics, including receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA). We gathered data on 1330 patients diagnosed with cervical cancer with lung metastases. An OS nomogram was developed, accounting for factors such as histological type, presence of metastases in other organs (brain, liver), surgical interventions, radiation therapy, and chemotherapy. The ROC curves, calibration plots, and DCA curves demonstrated the commendable predictive performance of the nomogram in assessing the prognosis of cervical cancer patients with lung metastases in both the training and validation cohorts. By utilizing clinical data from the SEER database, we have effectively devised a nomogram capable of predicting the 6-month, 1-year, and 2-year survival rates of cervical cancer patients with lung metastases. The nomogram boasts high accuracy, offering precise prognostic predictions. Its implementation can guide the formulation of individualized follow-up and treatment plans for enhanced patient care.

Leptomeningeal carcinomatosis, an emerging disease in internal medicine departments with a generally poor prognosis: two case reports

As a result of improved diagnostic methods and higher cancer patient survival rates, leptomeningeal carcinomatosis is being found in internal medicine departments more frequently. Melanoma, lung cancer, and breast adenocarcinoma are the three cancers that are most commonly associated. When the main tumor diffuses through the bloodstream, cerebrospinal fluid, or direct diffusion and causes multiple focal neurological symptoms, it is known as leptomeningeal involvement; the prognosis is usually not good. Despite multimodal treatment, leptomeningeal carcinomatosis is an advanced form of cancer that frequently results in rapid death. Treatment is typically palliative and consists primarily of intrathecal or systemic radiation and/or chemotherapy. New experimental therapies and immunotherapy are promising means of lowering morbidity and mortality. Clinical cases of leptomeningeal carcinomatosis are reported; both cases were identified at the Ospedale dei Castelli’s Department of Internal Medicine and resulted from primary breast pathology.

Do immune checkpoint inhibitor-related endocrinopathies affect survival rates in cancer patients? Presentation of two case reports

Do immune checkpoint inhibitor-related endocrinopathies affect survival rates in cancer patients? Presentation of two case reports