Survival Rate Of Cancer Patients Research Articles

Neutralizing antibody against GDF15 for treatment of cancer-associated cachexia.

GDF15 (growth differentiation factor 15), also known as macrophage inhibitory cytokine 1 (MIC-1), is a circulating protein involved in the regulation of energy balance and weight control. Elevated levels of GDF15 have been associated with cachexia and reduced survival rates in cancer patients. Through the activation of the GFRAL (GDNF-family receptor α-like)-RET (Rearranged during Transfection) signaling pathway, GDF15 can induce weight loss, making it a potential target for treating cachexia. Currently, there are no approved antibody drugs specifically targeting GDF15 for cancer cachexia treatment. However, efforts have been made to develop antibody-based therapeutics against this emerging target. In this study, we generated a monoclonal antibody KY-NAb-GDF15 against GDF15 that effectively blocks downstream signaling mediated by GFRAL upon stimulation by GDF15. This antibody demonstrates robust neutralizing activity and exhibits high binding specificity. Importantly, our findings indicate that this antibody holds promise in alleviating cancer-induced cachexia and mitigating chemotherapy-induced weight loss, thereby offering significant therapeutic potential for managing cancer cachexia.

Machine learning-assisted pattern recognition and imaging of multiplexed cancer cells via a porphyrin-embedded dendrimer array.

Early cancer detection plays a vital role in improving the survival rate of cancer patients, underscoring the importance of developing cancer detection methods. However, it is a great challenge to achieve simple, rapid, and accurate methods for simultaneously discerning various cancers. Herein we developed a 5-element porphyrin-embedded dendrimer-based sensor array, targeting the parallel discrimination of multiple cancers. The porphyrin-embedded dendrimers were modified with various functional groups to generate differentiated interactions with diverse cancer cells, which has been validated by fluorescence responses and laser confocal microscopy imaging. The dual-channel, five-element array, featuring ten signal outputs, achieved 100% accuracy in distinguishing between one human normal cell and six human cancerous cells, as well as in differentiating among mixed cells. Moreover, the screen 6-channel array can accurately distinguish 9 cells from mice and humans in minutes through optimization by multiple machine learning algorithms, including two normal cells and 7 cancerous cells with only 1000 cells, highlighting the significant potential of a porphyrin-embedded dendrimer-based parallel discriminating platform in early cancer diagnosis.

Targeting RNA N6-methyladenosine modification-- a novel therapeutic target for HER2- positive gastric cancer.

Gastric cancer is one of the most common cancers and is considered the 5th most frequent occurring cancer worldwide. It has gained great attention from the clinicians and researchers because of high mortality rate. It is generally treated with chemotherapy, radiotherapy, and surgery. Recently, additional treatment options including immunotherapy and targeted therapy and immunotherapy have been developed. However, poor prognosis, limited survival rate of patients, and drug resistance to treatment remain critical problems. To improve treatment options or to overcome the bottleneck of treatment, identification of diagnostic and prognostic markers, determining the most effective therapeutic options, and uncovering the molecular regulations associated with treatment strategies are required. In this regard n6-methyladenosine (m6A) regulation is considered important. This reversible modification plays a crucial role in progression, development and treatment of HER2-positive gastric cancer. Here, we discuss the role of m6A modification in HER2-positive gastric cancer progression through collecting related studies at present. We further discuss the association of m6A modification with therapeutic efficacy in HER2-positive gastric cancer and list some examples. We conclude that modification of m6A can be a new strategy for improving the prognosis and survival rate of HER2-positive gastric cancer patients.

Efficacy of tyrosine kinase inhibitors examined by a combination of Raman micro-spectroscopy and a deep wavelet scattering-based multivariate analysis framework.

HER2 is a crucial therapeutic target in breast cancer, and the survival rate of breast cancer patients has increased because of this receptor's inhibition. However, tumors have shown resistance to this therapeutic strategy due to oncogenic mutations that decrease the binding of several HER2-targeted drugs, including lapatinib, and confer resistance to this drug. Neratinib can overcome this drug resistance and effectively inhibit HER2 signaling and tumor growth. In the present study, we examined the efficacy of lapatinib and neratinib using breast cancer cells by Raman microscopy combined with a deep wavelet scattering-based multivariate analysis framework. This approach discriminated between control cells and drug-treated cells with high accuracy, compared to classical principal component analysis. Both lapatinib and neratinib induced changes in the cellular biochemical composition. Furthermore, the Raman results were compared with the results of several in vitro assays. For instance, drug-treated cells exhibited (i) inhibition of ERK and AKT phosphorylation, (ii) inhibition of cellular proliferation, (iii) cell-cycle arrest, and (iv) apoptosis as indicated by western blotting, real-time cell analysis (RTCA), cell-cycle analysis, and apoptosis assays. Thus, the observed Raman spectral changes are attributed to cell-cycle arrest and apoptosis. The results also indicated that neratinib is more potent than lapatinib. Moreover, the uptake and distribution of lapatinib in cells were visualized through its label-free marker bands in the fingerprint region using Raman spectral imaging. These results show the prospects of Raman microscopy in drug evaluation and presumably in drug discovery.

Introducing effective genes in lymph node metastasis of breast cancer patients using SHAP values based on the mRNA expression data.

Breast cancer, a global concern predominantly impacting women, poses a significant threat when not identified early. While survival rates for breast cancer patients are typically favorable, the emergence of regional metastases markedly diminishes survival prospects. Detecting metastases and comprehending their molecular underpinnings are crucial for tailoring effective treatments and improving patient survival outcomes. Various artificial intelligence methods and techniques were employed in this study to achieve accurate outcomes. Initially, the data was organized and underwent hold-out cross-validation, data cleaning, and normalization. Subsequently, feature selection was conducted using ANOVA and binary Particle Swarm Optimization (PSO). During the analysis phase, the discriminative power of the selected features was evaluated using machine learning classification algorithms. Finally, the selected features were considered, and the SHAP algorithm was utilized to identify the most significant features for enhancing the decoding of dominant molecular mechanisms in lymph node metastases. In this study, five main steps were followed for the analysis of mRNA expression data: reading, preprocessing, feature selection, classification, and SHAP algorithm. The RF classifier utilized the candidate mRNAs to differentiate between negative and positive categories with an accuracy of 61% and an AUC of 0.6. During the SHAP process, intriguing relationships between the selected mRNAs and positive/negative lymph node status were discovered. The results indicate that GDF5, BAHCC1, LCN2, FGF14-AS2, and IDH2 are among the top five most impactful mRNAs based on their SHAP values. The prominent identified mRNAs including GDF5, BAHCC1, LCN2, FGF14-AS2, and IDH2, are implicated in lymph node metastasis. This study holds promise in elucidating a thorough insight into key candidate genes that could significantly impact the early detection and tailored therapeutic strategies for lymph node metastasis in patients with breast cancer.

Quality of Life in Female Breast Cancer Patients and Survivors in a South African Municipality.

Breast cancer diagnosis and treatment processes affect patients physically and mentally, and have an impact on their quality of life, even years after receiving treatment. The objective of this study was to determine the quality of life in female breast cancer patients and survivors in a South African context. The municipality within which participants were recruited for this study was Ekurhuleni, based in the Gauteng province, South Africa. This study followed a cross-sectional research design. Quantitative data was collected. The Quality-of-Life Patient/Cancer Survivor Version (2012) was used to determine participants' quality of life in 4 subscales, namely, physical, psychological, social, and spiritual. The questionnaire was accessible to participants via the online Google Forms platform as well as in hard-copy format at local medical facilities. The Statistical Package for Social Sciences (SPSS) was used to compute statistics, and the level of significance was set at 95% (P < .05). One hundred female breast cancer patients and survivors from the region of Ekurhuleni, South Africa, took part in this study. The findings demonstrate that the quality-of-life subscale with the highest score was spiritual well-being (6.66 ± 2.07) and the lowest was psychological well-being (4.91 ± 1.93). No significant difference was found between quality of life and type of facility attended. Significant differences were found in quality-of-life ratings between breast cancer patient and breast cancer survivor populations. Breast cancer can result in a compromised quality of life, and with the increased prevalence and survival rate of breast cancer patients, both the short- and long-term effects of the condition and its treatments are heightened.

Clinicopathological Characteristics of Oral Squamous Cell Carcinoma at the Central Referral and Teaching Hospital in West Java, Indonesia.

This study aimed to investigate the clinicopathological characteristics of oral squamous cell carcinoma (OSCC) patients and analyze the relationship between the degree of differentiation and factors including age, sex, stage, and tumor location in West Java, Indonesia. A retrospective cross-sectional study was conducted at the Central Referral and Teaching Hospital in West Java, Indonesia. The data were collected by reviewing medical records with International Classification of Diseases (ICD) codes C00-C06 from 2016 to 2023. Descriptive statistics were employed to summarize the clinicopathological characteristics of OSCC patients. Chi-square, rank Spearman tests, and contingency correlation coefficients were used to analyze the relationship between the degree of differentiation and various factors, such as age, sex, stage, and tumor location of OSCC. Out of the 627 oral cancer patients, 70.49% were diagnosed with OSCC with a gender distribution of 45.7% males and 54.3% females, predominantly within the age range of 30-49 (37.2%). Most OSCC cases were stage IV (37.7%), with the tongue identified as the most common site (68.8%). A consistent trend of higher well-differentiated and moderately differentiated OSCC by age and gender was observed. Statistical analysis revealed no significant correlation between age, gender, tumor location, and the degree of OSCC differentiation (p>0.05). However, a statistically significant correlation was identified between the degree of OSCC differentiation and stage (p<0.001, r=0.460). There is a correlation between the degree of differentiation of OSCC and stage, suggesting significant prognostic implications that can aid in treatment planning and outcome prediction. However, further studies are needed due to the lack of comprehensive data on risk factors and survival rates of oral cancer patients, which is essential for enhancing prevention and treatment strategies for OSCC.

Identification of cachexia in lung cancer patients with an ensemble learning approach.

Nutritional intervention prior to the occurrence of cachexia will significantly improve the survival rate of lung cancer patients. This study aimed to establish an ensemble learning model based on anthropometry and blood indicators without information on body weight loss to identify the risk factors of cachexia for early administration of nutritional support and for preventing the occurrence of cachexia in lung cancer patients. This multicenter study included 4,712 lung cancer patients. The least absolute shrinkage and selection operator (LASSO) method was used to obtain the key indexes. The characteristics excluded weight loss information, and the study data were randomly divided into a training set (70%) and a test set (30%). The training set was used to select the optimal model among 18 models and verify the model performance. A total of 18 machine learning models were evaluated to predict the occurrence of cachexia, and their performance was determined using area under the curve (AUC), accuracy, precision, recall, F1 score, and Matthews correlation coefficient (MCC). Among 4,712 patients, 1,392 (29.5%) patients were diagnosed with cachexia based on the framework of Fearon et al. A 17-variable gradient boosting classifier (GBC) model including body mass index (BMI), feeding situation, tumor stage, neutrophil-to-lymphocyte ratio (NLR), and some gastrointestinal symptoms was selected among the 18 machine learning models. The GBC model showed good performance in predicting cachexia in the training set (AUC = 0.854, accuracy = 0.819, precision = 0.771, recall = 0.574, F1 score = 0.658, MCC = 0.549, and kappa = 0.538). The abovementioned indicator values were also confirmed in the test set (AUC = 0.859, accuracy = 0.818, precision = 0.801, recall = 0.550, F1 score = 0.652, and MCC = 0.552, and kappa = 0.535). The learning curve, decision boundary, precision recall (PR) curve, the receiver operating curve (ROC), the classification report, and the confusion matrix in the test sets demonstrated good performance. The feature importance diagram showed the contribution of each feature to the model. The GBC model established in this study could facilitate the identification of cancer cachexia in lung cancer patients without weight loss information, which would guide early implementation of nutritional interventions to decrease the occurrence of cachexia and improve the overall survival (OS).

ATIP/ATIP1 regulates prostate cancer metastasis through mitochondrial dynamic-dependent signaling.

Mitochondria play a fundamental role in cell survival and motility. Abnormalities in mitochondria are associated with carcinogenesis, especially with tumor metastasis. In this study, we explore the biological function of ATIP1, which is a mitochondrial-located isoform of angiotensin II AT2 receptor interacting proteins (ATIPs) in prostate cancer cells. The results showed that ATIP is downregulated in prostate cancer tissues and is negatively correlated with the disease-free survival rate of prostate cancer patients. Silencing of ATIP promotes mitochondrial fission and enhances tumor cell migration and invasion. Reconstitution of ATIP1 in ATIP-deficient cells significantly attenuates mitochondrial trafficking and tumor cell movement. Therefore, ATIP1 is a negative regulator of mitochondrial dynamics and tumor cell motility and is also a potential biomarker for predicting prostate cancer malignancy.

Patient Profile and Survival Rate of Breast Cancer Patients with FEC Chemotherapy Regimen at H. Adam Malik Hospital

Breast cancer is a prevalent disease that impacts public health worldwide, including Indonesia. There are various chemotherapy regimens that are currently available. One widely utilized chemotherapy regimen for breast cancer is the FEC regimen, which combines 5-fluorouracil, epirubicin, and cyclophosphamide. This study provides a study of patient profiles and survival rates among breast cancer patients undergoing FEC chemotherapy at H. Adam Malik Hospital. The study utilized a descriptive-retrospective approach with data collected from the medical records of patients who underwent FEC therapy at RSUP H. Adam Malik during January-December 2019. A total of 157 patients were administered anthracycline-based treatment, with 54 patients receiving FEC (34.39%). The majority of individuals under the FEC regimen were primarily luminal B (51.75%) and IBC (33.33%). The survival rate for individuals using the FEC chemotherapy regimen was found to be 37.98 months. Additionally, patients with risk factors associated with invasive breast cancer (IBC) exhibited a 1.20-fold increased risk of mortality compared to individuals with other forms of breast cancer. The first-line FEC chemotherapy regimen continues to be a feasible therapeutic option for subtypes of breast cancer, and there is no discernible variation in survival rate observed across these characteristics.

The Role of microRNA in Spermatogenesis: Is There a Place for Fertility Preservation Innovation?

Oncological treatments have dramatically improved over the last decade, and as a result, survival rates for cancer patients have also improved. Quality of life, including concerns about fertility, has become a major focus for both oncologists and patients. While oncologic treatments are often highly effective at suppressing neoplastic growth, they are frequently associated with severe gonadotoxicity, leading to infertility. For male patients, the therapeutic option to preserve fertility is semen cryopreservation. In prepubertal patients, immature testicular tissue can be sampled and stored to allow post-cure transplantation of the tissue, immature germ cells, or in vitro spermatogenesis. However, experimental techniques have not yet been proven effective for restoring sperm production for these patients. MicroRNAs (miRNAs) have emerged as promising molecular markers and therapeutic tools in various diseases. These small regulatory RNAs possess the unique characteristic of having multiple gene targets. MiRNA-based therapeutics can, therefore, be used to modulate the expression of different genes involved in signaling pathways dysregulated by changes in the physiological environment (disease, temperature, ex vivo culture, pharmacological agents). This review discusses the possible role of miRNA as an innovative treatment option in male fertility preservation-restoration strategies and describes the diverse applications where these new therapeutic tools could serve as fertility protection agents.

Bronchoalveolar lavage fluid assessment facilitates precision medicine for lung cancer.

Lung cancer is the most common and fatal malignant disease worldwide and has the highest mortality rate among tumor-related causes of death. Early diagnosis and precision medicine can significantly improve the survival rate and prognosis of lung cancer patients. At present, the clinical diagnosis of lung cancer is challenging due to a lack of effective non-invasive detection methods and biomarkers, and treatment is primarily hindered by drug resistance and high tumor heterogeneity. Liquid biopsy is a method for detecting circulating biomarkers in the blood and other body fluids containing genetic information from primary tumor tissues. Bronchoalveolar lavage fluid (BALF) is a potential liquid biopsy medium that is rich in a variety of bioactive substances and cell components. BALF contains information on the key characteristics of tumors, including the tumor subtype, gene mutation type, and tumor environment, thus BALF may be used as a diagnostic supplement to lung biopsy. In this review, the current research on BALF in the diagnosis, treatment, and prognosis of lung cancer is summarized. The advantages and disadvantages of different components of BALF, including cells, cell-free DNA, extracellular vesicles, and microRNA are introduced. In particular, the great potential of extracellular vesicles in precision diagnosis and detection of drug-resistant for lung cancer is highlighted. In addition, the performance of liquid biopsies with different body fluid sources in lung cancer detection are compared to facilitate more selective studies involving BALF, thereby promoting the application of BALF for precision medicine in lung cancer patients in the future.

Preoperative Neutrophil–Lymphocyte Ratio and Serum Carcinoembryonic Antigen as Predictive Factors of Colorectal Cancer Survival

Introduction. Colorectal cancer is the second leading cause of death worldwide, with a high mortality rate. This study investigates the predictive value of the neutrophil–lymphocyte ratio (NLR) and carcinoembryonic antigen (CEA) in predicting the survival rates of colorectal cancer patients in Indonesia. Method. This retrospective cohort study enrolled the colorectal cancer stage I–IV patients treated at Cipto Mangunkusumo General Hospital (CMGH). The independent variables are NLR and CEA, while the dependent variable is the five–year survival of colorectal cancer. The log rank test proceeded to find a correlation between NLR and CEA with 5–year survival, and the Cox proportional hazard regression proceeded to analyze the predictive value. Results. Of the ninety–six subjects who met the inclusion and exclusion criteria who were enrolled, 6.25% had high NLR, and 66.6% had high CEA levels. The overall five–year survival rate was 35.4%. However, the proportion of subjects with normal NLR had a higher five–year survival rate compared to those with high NLR, and the same pattern was observed for CEA levels. Subgroup analysis based on the cancer stage showed a significant association between high NLR and increased risk of mortality in TNM stages I–II. Still, no significant difference in survival based on NLR was observed in stages III–IV. Conclusion. The preoperative NLR ratio and preoperative CEA did not show a predictive role in colorectal cancer survival. However, when stratifying by cancer stage, there was a significant difference in preoperative NLR levels between the deceased and non–deceased groups in patients with stage I–II colorectal cancer.

Assessing Clinical Relevance of Gastric Cancer Cell Lines as Tumor Models by Identifying Key Genes and miRNAs involved in EMT Metastasis Pathway

Cancer cell lines are in-vitro cancer cell models that continue to divide and proliferate under controlled laboratory conditions. They are used in medical research to study tumor pathology and for testing therapeutics efficacy. Despite their extensive application, significant differences in genetic and transcriptomic expression exist between cell lines and tumor cells. The purpose of this study was to identify the relevance of gastric cancer cell lines as suitable models for gastric tumor research. Using a two-tiered bioinformatics approach- a comparison between the gastric tumor and the gastric cancer cell line was performed using functional genomics data available in the literature to identify the common Differentially Expressed Genes (DEGs). The study revealed differential expression of a total 380 genes common in both gastric cancer cell lines and tumor samples. Interestingly, four of these genes were identified as the Epithelial Mesenchymal Transition (EMT) markers, involved in the accelerated metastasis, of which two genes with discrete over-expression patterns, namely- ITGB1 and TGFB1 were selected for further analysis. Their survival analysis revealed their key role in gastric cancer severity, evident by the regressed survival rate of gastric cancer patients upon their overexpression. A total of nine tumor-suppressor miRNAs relevant to ITGB1 and TGFB1 were also identified. In conclusion, our findings indicate that inspite of various genetic and transcriptomic deviations, the tumor and cell line exhibit comparable expression patterns. The data obtained would be useful to implore the druggability of these targets with a goal of improved translational rates.

Pan-cancer analysis portrays NVL2 as a novel diagnostic and prognostic biomarker

Nuclear VCP Like 2 or NVL2, an ATPases Associated with diverse cellular Activities (AAA+) family protein, has recently been linked with various cancers. By systematic bioinformatics analyses, here we predict the prospect of NVL2 as a cancer biomarker. Our pan-cancer analyses reveal that NVL2 is overexpressed in cancers [GEPIA2, OncoDB, and UALCAN (TCGA) databases] and the top five cancers with elevated expression (more than two fold) of NVL2 are Breast Invasive Carcinoma, Testicular Germ Cell Tumors, Cholangiocarcinoma, Diffuse large B cell lymphoma, and Thymoma. NVL2 is also highly expressed in all stages of most cancers. Additionally, this high expression was found to be associated with the reduced survival rate of cancer patients (Kaplan-Meier Plotter, GEPIA2, and OncoDB databases). Since genetic alteration is one of the major causes of cancer, we investigated the mutation and copy number amplification status (cBioPortal and COSMIC databases) of NVL2 across the cancers. Many potential mutation sites were predicted (cBioPortal and COSMIC databases) and most strikingly, a total of fourteen mutation sites were observed at the ATPase domain of NVL2. This signifies that these are the mutations that might have a role in carcinogenesis. The copy number amplification study also revealed the high amplification percentage of NVL2 across different cancers. We further focused on the functional characteristics of the protein NVL2 across the cancers. The protein-protein interaction analyses found the proteins like SKIV2L2, WDR12, WDR74, UTP18, NAT10, TERT, DKC1, GTPBP4, BOP1, TEP1 directly interact with NVL2. The top canonical pathways indicated that NVL2 has crucial functions in oncogenesis (DAVID). We, therefore, surmise that NVL2 could be considered as a potential prognostic and diagnostic biomarker and a promising target for multiple cancers.

The anti-breast cancer therapeutic potential of 1,2,3-triazole-containing hybrids.

Breast cancer, as one of the most common invasive malignancies and the leading cause of cancer-related deaths in women globally, poses a significant challenge in the world health system. Substantial advances in diagnosis and treatment have significantly improved the survival rate of breast cancer patients, but the number of incidences and deaths of breast cancer are projected to increase by 40% and 50%, respectively, by 2040. Chemotherapy is one of the principal treatments for breast cancer therapy, but multidrug resistance and severe side effects remain the major obstacles to the success of treatment. Hence, there is a vital need to develop novel chemotherapeutic agents to combat this deadly disease. 1,2,3-Triazole, which can be effectively constructed by click chemistry, not only can serve as a linker to connect different anti-breast cancer pharmacophores but also is a valuable pharmacophore with anti-breast cancer potential and favorable properties such as hydrogen bonding, moderate dipole moment, and enhanced water solubility. Particularly, 1,2,3-triazole-containing hybrids have demonstrated promising in vitro and in vivo anti-breast cancer potential against both drug-sensitive and drug-resistant forms and possessed excellent selectivity by targeting different biological pathways associated with breast cancer, representing privileged scaffolds for the discovery of novel anti-breast cancer candidates. This review concentrates on the latest advancements of 1,2,3-triazole-containing hybrids with anti-breast cancer potential, including work published between 2020 and the present. The structure-activity relationships (SARs) and mechanisms of action are also reviewed to shed light on the development of more effective and multitargeted candidates.

The Impact of Neighborhood Deprivation on the Survival Rates of Patients with Cancer in Korea.

The objective of this study is to investigate the correlation between the neighborhood deprivation index and survival rates of cancer patients in Korea. In this study, 5-year age-standardized survival rates of patients with cancer were determined using the National Cancer Cohort from 2014 to 2018 in Korea. The primary cancer sites were the stomach, colorectum, liver, lung, breast, cervix, prostate, and thyroid. Disparities were measured, and their impact on the overall survival rates was assessed using the Korean version of the Neighborhood Deprivation Index. Pearson's correlation coefficient was calculated to determine the strength of the correlation. The study cohort comprised 726,665 patients with cancer, of whom 50.7% were male. The predominant primary cancer sites were the stomach (n = 138,462), colorectum (n = 125,156), and thyroid gland (n = 120,886). Urban residents showed better survival outcomes than those situated in rural areas. The most deprived quartile had the lowest survival rate, while the least deprived quartile had the highest (p < 0.001). Most cancer types revealed significant correlations between neighborhood deprivation and 5-year age-standardized overall survival, with lung cancer showing the most substantial negative correlation (r = -0.510), followed by prostate cancer (r = -0.438). However, thyroid cancer showed only a marginal correlation (p = 0.069). The results of this study suggested that neighborhood deprivation is closely linked to disparities in overall survival across various types of cancer. A substantial negative correlation between the neighborhood deprivation index and all-cause mortality for lung and prostate cancer, as compared to breast and cervical cancers covered by the National Cancer Screening Program, may reinforce the need to address healthcare access and improve the early detection of cancer in socioeconomically deprived neighborhoods.

Factors influencing the 5-year survival rate of oral cancer patients in the Mongolian population: a retrospective cohort study.

The high mortality rate of head and neck cancers, particularly oral cancer, poses a significant health challenge in developing nations such as Mongolia. This retrospective survival analysis study was conducted to identify factors influencing the 5-year survival rate of oral squamous cell carcinoma patients. The study analyzed data from 173 patients diagnosed with oral squamous cell carcinoma, including multiple variables such as age, gender, residence, education, tobacco and alcohol consumption, oral health indicators, family history, precancerous conditions, cancer characteristics, treatment, rehabilitation, cancer recurrence, and 5-year survival. Survival analysis was conducted using the Kaplan-Meier method, and STATA was used for statistical analysis. The study revealed a 5-year survival rate of 50.3% for oral cancer patients, with a survival rate of 38% for tongue cancer patients. Age, residence, cancer stage, and cancer recurrence were identified as significant survival predictors. Compared to those aged 60 or younger, the hazard ratio (HR) for patients aged 61 or older was 1.52. Survival was associated with female gender (HR = 0.47, CI = 0.29-0.77). Urban residence was associated with decreased survival (HR = 1.92, CI = 1.22-3.05). Significantly worse survival was associated with the presence of cancer recurrence (HR = 1.99, CI = 1.15-3.04). Oral cancer patients in stage IV had a fourfold higher risk of mortality compared to those in stage I (HR = 4.08, CI = 1.2-13.84). This research highlights the influence of age, urban habitation, and cancer recurrence on oral cancer survival. Age, urban residence, and cancer recurrence were all associated with decreased survival, whereas cancer at stage IV substantially increased the risk of death. The significance of early detection, treatment, and active surveillance to identify oral cancer at an early stage is highlighted by these findings. Compared to industrialized nations, Mongolia's lower oral cancer survival rates emphasize the need to increase public awareness and education. A comprehensive approach is required to improve oral cancer patient survival rates and quality of life, including emphasizing early detection through active surveillance, implementing preventive measures, and advancing cancer education initiatives.

Amino acids and their roles in tumor immunotherapy of breast cancer.

Breast cancer is the most commonly diagnosed cancer among women. The primary treatment options include surgery, radiotherapy, chemotherapy, targeted therapy and hormone therapy. The effectiveness of breast cancer therapy varies depending on the stage and aggressiveness of the cancer, as well as individual factors. Advances in early detection and improved treatments have significantly increased survival rates for breast cancer patients. Nevertheless, specific subtypes of breast cancer, particularly triple-negative breast cancer, still lack effective treatment strategies. Thus, novel and effective therapeutic targets for breast cancer need to be explored. As substrates of protein synthesis, amino acids are important sources of energy and nutrition, only secondly to glucose. The rich supply of amino acids enables the tumor to maintain its proliferative competence through participation in energy generation, nucleoside synthesis and maintenance of cellular redox balance. Amino acids also play an important role in immune-suppressive microenvironment formation. Thus, the biological effects of amino acids may change unexpectedly in tumor-specific or oncogene-dependent manners. In recent years, there has been significant progress in the study of amino acid metabolism, particularly in their potential application as therapeutic targets in breast cancer. In this review, we provide an update on amino acid metabolism and discuss the therapeutic implications of amino acids in breast cancer.

The mechanism and application of traditional Chinese medicine extracts in the treatment of lung cancer and other lung-related diseases.

Lung cancer stands as one of the most prevalent malignancies worldwide, bearing the highest morbidity and mortality rates among all malignant tumors. The treatment of lung cancer primarily encompasses surgical procedures, radiotherapy, and chemotherapy, which are fraught with significant side effects, unfavorable prognoses, and a heightened risk of metastasis and relapse. Although targeted therapy and immunotherapy have gradually gained prominence in lung cancer treatment, diversifying the array of available methods, the overall recovery and survival rates for lung cancer patients remain suboptimal. Presently, with a holistic approach and a focus on syndrome differentiation and treatment, Traditional Chinese Medicine (TCM) has emerged as a pivotal player in the prognosis of cancer patients. TCM possesses characteristics such as targeting multiple aspects, addressing a wide range of concerns, and minimizing toxic side effects. Research demonstrates that Traditional Chinese Medicine can significantly contribute to the treatment or serve as an adjunct to chemotherapy for lung cancer and other lung-related diseases. This is achieved through mechanisms like inhibiting tumor cell proliferation, inducing tumor cell apoptosis, suppressing tumor angiogenesis, influencing the cellular microenvironment, regulating immune system function, impacting signal transduction pathways, and reversing multidrug resistance in tumor cells. In this article, we offer an overview of the advancements in research concerning Traditional Chinese Medicine extracts for the treatment or adjunctive chemotherapy of lung cancer and other lung-related conditions. Furthermore, we delve into the challenges that Traditional Chinese Medicine extracts face in lung cancer treatment, laying the foundation for the development of diagnostic, prognostic, and therapeutic targets.