Survival Rate Of Cancer Patients Research Articles

Analyzing the Long-Term Survival of Colon and Rectal Cancer Patients Using Non-Mixture Cure Rate Model

Introduction: Colorectal cancer is the most common cause of cancer mortality in Iran. There are differences in the etiology, clinical behavior and pathological features in cancer of the colon versus the rectum. The aim of this study was to evaluate the factors related to survival and cure probability of patients with colon and rectal cancer using a semi-parametric non-mixture cure rate model.
 Methods: This retrospective cohort study was conducted on 311 patients, with colorectal cancer. Data of all patients with colon and rectum malignances who underwent the first treatment in Omid Hospital, Mashhad, between 2006 and 2011 were gathered through medical records. Patients were followed-up for 9 years until September 2020. Semi-parametric non-mixture cure model was implemented using miCoPTCM package in the R software.
 Results: The mean survival time was 2973.94 days (95% confidence interval [CI]: (2694.96, 3252.93). The 5-year survival rates for colon and rectal cancer patients were 0.54 (%95 CI:(0.45, 0.61)) and 0.57 (%95 CI:(0.48,0.65)), respectively. The proportion of cured colon cancer patients was 44.0%, while it was 40.0% for the ones with rectal cancer. Age and stage of the disease were determined as the common related factors of survival and cure fraction for both colon and rectal cancers. Ethnicity and type of first treatment were distinguished as factors related to survival and cure fraction of rectal cancer. Whereas the history of drug abuse increased the hazard of death in colon cancer patients; Also, overweight played a protective role in the survival and cure fraction of rectal cancer patients.
 Conclusion: Because the factors associated with colorectal cancer are not necessarily equal to the risk factors for colon and rectal cancer, it is recommended to obtain more accurate and valid results in the survival analysis of colorectal cancer patients, the colon and rectum should be considered separately. It is also appropriate to use cure rate models when there is a cure fraction in the data.

Revising the Landscape of Cytokine-Induced Killer Cell Therapy in Lung Cancer: Focus on Immune Checkpoint Inhibitors.

Undeniably, immunotherapy has markedly improved the survival rate of cancer patients. The scenario is no different in lung cancer, where multiple treatment options are now available and the inclusion of immunotherapy yields better clinical benefits than previously used chemotherapeutic strategies. Of interest, cytokine-induced killer (CIK) cell immunotherapy has also taken a central role in clinical trials for the treatment of lung cancer. Herein, we describe the relative success of CIK cell therapy (alone and combined with dendritic cells as DC/CIKs) in lung cancer clinical trials and discuss its combination with known immune checkpoint inhibitors (anti-CTLA-4 and anti-PD-1/PD-L1). Additionally, we provide insights into the findings of several preclinical in vitro/in vivo studies linked to lung cancer. In our opinion, CIK cell therapy, which recently completed 30 years and has been approved in many countries, including Germany, offers tremendous potential for lung cancer. Foremost, when it is optimized on a patient-by-patient basis with special attention to the patient-specific genomic signature.

Inhalable GSH-Triggered Nanoparticles to Treat Commensal Bacterial Infection in In Situ Lung Tumors.

Bacterial infection has been considered one of the primary reasons for low survival rate of lung cancer patients. Herein, we demonstrated that a kind of mesoporous silica nanoparticles loaded with anticancer drug doxorubicin (DOX) and antimicrobial peptide HHC36 (AMP) (MSN@DOX-AMP) can kill both commensal bacteria and tumor cells under GSH-triggering, modulating the immunosuppressive tumor microenvironment, significantly treating commensal bacterial infection, and eliminating in situ lung tumors in a commensal model. Meanwhile, MSN@DOX-AMP encapsulated DOX and AMP highly efficiently via a combined strategy of physical adsorption and click chemistry and exhibited excellent hemocompatibility and biocompatibility. Importantly, MSN@DOX-AMP could be inhaled and accumulate in lung by a needle-free nebulization, achieving a better therapeutic effect. This system is expected to serve as a straightforward platform to treat commensal bacterial infections in tumors and promote the translation of such inhaled GSH-triggered MSN@DOX-AMP to clinical treatments of lung cancer.

Numerical Simulation of Nonlinear Dynamics of Breast Cancer Models Using Continuous Block Implicit Hybrid Methods

In the search for causes and cures of cancer diseases, many mathematical models developed have resulted in systems of nonlinear stiff ordinary differential equations. With these models, many numerical estimates of biological knowledge of the parameters have been obtained, a number of phenomena interpreted, and predictions were made in order to gain further knowledge of cancer development and possible treatment. In this study, numerical simulations of the models were performed using continuous block implicit hybrid methods and the results obtained support the theoretical and clinical findings. We analyzed the interactions among the various tumor cell populations and present the results graphically. From the graphical representation of results, one can clearly see the effects of all the tumor cell populations involved in the competition, as well as the effects of some treatments by the applications of some therapeutic agents which have been heavily used in the clinical treatments of breast cancer. The treatments in the past were mostly conventional chemotherapies, which were used either singly (alone) or in combination with each other or other therapies, and all played vital roles, except for the side effects that these therapies incur in normal tissues and organs. Thus, from recent research works, it is now clear that in many cases they do not represent a complete cure. Therefore, the need to address not only the preventative measures of breast cancer, but also more successful treatment, is clear, and can be successfully achieved to increase the survival rate of breast cancer patients.

Key Members of the CmPn as Biomarkers Distinguish Histological and Immune Subtypes of Hepatic Cancers

Liver cancer, comprising hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA), is a leading cause of cancer-related deaths worldwide. The liver is a primary metabolic organ for progesterone (PRG) and PRG exerts its effects through classic nuclear PRG receptors (nPRs) and non-classic membrane PRG receptors (mPRs) or a combination of both. Previous studies have shown that the CCM signaling complex (CSC) couples both nPRs and mPRs to form the CmPn (CSC-mPR-PRG-nPR) signaling network, which is involved in multiple cellular signaling pathways, including tumorigenesis of various cancers. Despite advances in treatment, 5-year survival rates for liver cancer patients remain low, largely due to the chemoresistant nature of HCCs. The lack of sensitive and specific biomarkers for liver cancer diagnosis and prognosis emphasizes the need for identifying new potential biomarkers. We propose the potential use of CmPn members' expression data as prognostic biomarkers or biomarker signatures for the major types of hepatic cancer, including HCCs and CCAs, as well as rare subtypes such as undifferentiated pleomorphic sarcoma (UPS) and hepatic angiosarcoma (HAS). In this study, we investigated the CmPn network through RNAseq data and immunofluorescence techniques to measure alterations to key cancer pathways during liver tumorigenesis. Our findings reveal significant differential expression of multiple CmPn members, including CCM1, PAQR7, PGRMC1, and nPRs, in both HCCs and CCAs, highlighting the crucial roles of mPRs, nPRs, and CSC signaling during liver tumorigenesis. These key members of the CmPn network may serve as potential biomarkers for the diagnosis and prognosis of liver cancer subtypes, including rare subtypes.

Estimation of Risk Factors Affecting Screening Outcomes of Prostate Cancer Using the Bayesian Ordinal Logistic Model

Prostate cancer occurs when cells in the prostate gland grow out of control. Almost all prostate cancers are adenocarcinomas. The survival rate for prostate cancer patients depends on the screening outcome, which can be either no prostate cancer, early detection, and late detection or advanced stage detection. The main objective of this study was to estimate the risk factors affecting the screening outcome of prostate cancer. With ordinal outcomes, a generalized Bayesian ordinal logistic model was considered in the analysis. The generalized Bayesian ordinal logistic model helped in estimation of coefficient parameters of the risk factors affecting each level of prostate cancer-screening outcomes. In the study, positive coefficients, that is, β k > 0 , indicated that the higher values on the explanatory variable increased the chances of the respondent being in a higher category of the dependent variable than the current one, while the negative coefficients, that is, β k < 0 , signified that the higher values on the explanatory variable increased the likelihood of being in the current or lower category of prostate cancer. For instance, from the analysis, positive or negative outcomes of prostate cancer showed that an increase in weight lowered the chances of an individual having the disease.

Development and external validation of multivariate prediction models for erectile dysfunction in men with localized prostate cancer.

While the 10-year survival rate for localized prostate cancer patients is very good (>98%), side effects of treatment may limit quality of life significantly. Erectile dysfunction (ED) is a common burden associated with increasing age as well as prostate cancer treatment. Although many studies have investigated the factors affecting erectile dysfunction (ED) after prostate cancer treatment, only limited studies have investigated whether ED can be predicted before the start of treatment. The advent of machine learning (ML) based prediction tools in oncology offers a promising approach to improve the accuracy of prediction and quality of care. Predicting ED may help aid shared decision-making by making the advantages and disadvantages of certain treatments clear, so that a tailored treatment for an individual patient can be chosen. This study aimed to predict ED at 1-year and 2-year post-diagnosis based on patient demographics, clinical data and patient-reported outcomes (PROMs) measured at diagnosis. We used a subset of the ProZIB dataset collected by the Netherlands Comprehensive Cancer Organization (Integraal Kankercentrum Nederland; IKNL) that contained information on 964 localized prostate cancer cases from 69 Dutch hospitals for model training and external validation. Two models were generated using a logistic regression algorithm coupled with Recursive Feature Elimination (RFE). The first predicted ED 1 year post-diagnosis and required 10 pre-treatment variables; the second predicted ED 2 years post-diagnosis with 9 pre-treatment variables. The validation AUCs were 0.84 and 0.81 for 1 year and 2 years post-diagnosis respectively. To immediately allow patients and clinicians to use these models in the clinical decision-making process, nomograms were generated. In conclusion, we successfully developed and validated two models that predicted ED in patients with localized prostate cancer. These models will allow physicians and patients alike to make informed evidence-based decisions about the most suitable treatment with quality of life in mind.

Anlotinib Enhances the Therapeutic Effect of Bladder Cancer with GSDMB Expression: Analyzed from TCGA Bladder Cancer Database & Mouse Bladder Cancer Cell Line.

The mitogen-activated protein kinase (MAPK) pathway is inhibited by the pan-target inhibitor Anlotinib, which induces tumor cell death. In addition to the common apoptosis and necrosis, there is also a pyroptosis mode of cancer cell death in recent years, which is mainly manifested by the cleavage of gasdermin proteins (GSDMs). Gasdermin B (GSDMB) participates in the progression and outcome of bladder cancer. The efficacy and mechanism of Anlotinib in the treatment of GSDMB-positive bladder tumors have not been studied to date. The relationship between GSDMB expression and tumor stage, overall survival rate, immunotherapy response, tumor recurrence and progression rate was analyzed from the TCGA bladder cancer database. Anlotinib was used to treat GSDMB-positive bladder cancer in mice followed by flow analysis of the secretion of inflammatory factors related to pyroptosis and the level of anti-tumor factors. Western blot analysis detected which MAPK and MEK signal transduction pathways. TCGA data analysis showed that the overall survival rate of bladder cancer patients with high GSDMB expression was better than that of patients with low GSDMB expression. In vivo experiments showed that Anlotinib was more effective in the treatment of GSDMB-positive bladder cancer than GSDMB-negative bladder cancer. Anlotinib can increase the secretion of antitumor-related factors in GSDMB-positive bladder cancer such as TNF-a and CD107a. In addition, Anlotinib also induced an increase in GSDMB protein expression. Anlotinib treatment of GSDMB-positive bladder cancer decreased AKT and MEK protein expression, which were involved in Anlotinib signal transduction pathway. Anlotinib has a strong antitumor effect on GSDMB-positive bladder tumors. This effect is mainly achieved by anlotinib stimulating the secretion of relevant antitumor factors by lymphocytes. The PI3K/AKT and MEK signal transduction pathways were inhibited by Anlotinib in bladder cancer expressing GSDMB protein.

Abstract P5-07-01: Outcomes of multidisciplinary team approach and intensive patient education in young women with breast cancer to improve the rate of fertility preservation

Abstract Background Young breast cancer patients of childbearing age often had to give up their opportunity as women or mothers for cancer treatment. As the survival rate of young breast cancer patients increases with advances in early detection and treatment of breast cancer, interest in issues such as fertility preservation, which have not been satisfied so far, is increasing. This study aims to report the experience of improvement of the fertility preservation rate through a multidisciplinary team approach and systematic patient education for young breast cancer patients. Methods Patients treated with multidisciplinary team approach including surgical, medical oncologist and fertility specialist were included for analysis. Patient were divided into two periods: before and after intensive patient education. Patient education included in-person counseling, hand-out materials, and audiovisual education about ovarian dysfunctions related to cancer treatment and fertility preservation methods. We compared the rate of fertility counseling, preservation between two periods. Also, effect of hormonal receptor status on fertility outcome with pregnancy and birth were analyzed. Results The rates of fertility counseling (39.4% to 58.1%), ovarian function preservation with gonadotropin releasing hormone antagonists (37.8% to 49.7%), and either embryo (0.9% to 5.6%) or oocyte preservation (0 to 7.5%) were significantly increased (all, p< 0.001) after intensive patient education. Pregnancy (9.5% vs 14.2%, p=0.034) and birth rate (7.7% vs 12.2%, p=0.043) were significantly higher with women with negative hormone receptor status. In hormone receptor positive patients, similar pregnancy rates were observed (13.3 ~ 15.4%) in patients who complete 5yearsd of endocrine therapy, stopped endocrine therapy due to side effects, and received no endocrine therapy. Patients with any type of recurrence were not pregnant during follow up period. Patients who stopped endocrine therapy for child plan showed highest rate of pregnancy (56.0%). Multivariable analysis revealed intensive education were highly associated with improved fertility outcomes (OR 3.843 95% CI 2.781–5.311, p=< 0.001) after adjusted for different stage and treatment modality. Conclusion Multidisciplinary team approach with intensive patient education of fertility preservation in young women breast cancer significantly improved fertility preservation attempt. Hormonal receptor status and recurrence were associated with impaired fertility outcomes Citation Format: Young Joo Lee, Hayan Han, Hee Jeong Kim. Outcomes of multidisciplinary team approach and intensive patient education in young women with breast cancer to improve the rate of fertility preservation [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P5-07-01.

Abstract P6-04-11: Improved quantitative fibrosis indices reveal diverse survivals of triple negative breast cancer patients

Abstract Background: The ability of cancer cells to metastasise influences the mortality rate of patients with cancer. Extracellular matrix (ECM) from stromal organization is associated with tumorigenesis and metastasis in breast cancer. It is proposed that morphological features of collagen, based on second harmonic generation (SHG) microscopy, within the tumour environment can be a quantitative image-based biomarker for to predict the survival rate of triple-negative breast cancer (TNBC) patients. To this, we have developed quantitative fibrosis indices by combining multiple collagen features in breast tumour to reveal the diverse survivals of TNBC patients. Method: The patients (n = 216) in this study were diagnosed with TNBC in Singapore from 2003 to 2015. Disease-free survival (DFS) and overall survival (OS) were defined as time from the point of diagnosis to recurrence or to death/the date of the last follow-up, respectively. The constructed tissue microarrays (TMA) of breast tumours were scanned by the SHG microscope (Genesis, HistoIndex Pte. Ltd., Singapore). 33 collagen parameters were quantified from each sample. These collagen parameters were used to build disease free survival (DFS) index, overall survival (OS) index for prediction of early recurrence (DFS< 1 year) and early death (OS< 4 years), respectively. Kaplan-Meier survival analysis was further performed to assess long-term survival of TNBC patients with high and low risk as stratified by the indices, tumour grade and tumour size. The indices were validated using leave-one-out method. Results: Both DFS-index and OS-index were created using 10 collagen parameters chosen by sequential selection methods. Due to insufficient follow-up time, 12 patients and 81 patients were excluded from the early recurrence analysis and early death analysis, respectively. The DFS-index could differentiate low-risk patients with DFS≥1 year (n=179) and high-risk patients with DFS< 1 year(n=25) (training p< 0.001; validation p=0.157) with a cut-off value DFS-index=0.880. The OS-index could differentiate the low-risk patients with OS≥4 years (n=101) and high-risk patients with OS< 4 years (n=34) (training p< 0.001; validation p=0.011) with a cut-off value OS-index=0.703. The log-rank test showed DFS-index (training p = 0.001; validation p=0.025) and OS-index (training p < 0.001; validation p=0.011) could be used for the prediction of disease-free survival and overall survival. Kaplan-Meier survival analysis revealed tumour size>20mm (DFS, p=0.605; OS, p=0.136) and tumour grade=3 (DFS, p=0.328; OS, p=0.768) had poor predictive value in this study. Conclusion: Quantitative assessment of fibrosis in breast cancer correlates with long-term survival of TNBC patients. This study used DFS-index and OS-index combined complex morphological collagen features and obtained better prediction results than tumour size and tumour grade. Table. The difference between low and high risk groups differentiated by developed indices, tumour size and tumour grade. Low-risk group has a longer DFS and OS months based on DFS-index and OS-index. Citation Format: Yayun Ren, Dean Tai, Ying Zhao, Puay Hoon Tan. Improved quantitative fibrosis indices reveal diverse survivals of triple negative breast cancer patients [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P6-04-11.

A Study to Assess the Knowledge Regarding Self-Breast Examination on Prevention of Breast Cancer Among Women Attending OPD in Sree Balaji Medical and College And Hospital

Self-examination of the breasts is less expensive than mammography. Breast cancer can be discovered sooner, and women's survival rates can be raised. Rural residents have limited access to medical treatment and have a poorer educational position. As a result, it is critical that they be educated about breast cancer prevention and early diagnosis by systematic breast self-examination. Breast cancer risk begins to climb in a woman's early thirties and reaches an all-time high by the time she reaches her sixth decade. Because women between the ages of 30 and 60 are at high risk, an educational programme for them would be quite useful. Because the perceived threat of breast cancer should inspire children to practise breast self-examination on a regular basis, improved knowledge about breast cancer and competence to do breast self-examination at this age would be useful. According to a study, the five-year survival rate of breast cancer patients is 75 percent, and it is suggested that 50 percent of all breast cancer patients worldwide could have their lives extended by increasing public awareness through early detection and effective treatment at the community level.

Study on Breast Cancer in Kazakhstan Using the Functional Time Series.

In Kazakhstan and Central Asia, breast cancer (BC) is the most common malignancy among women. However, no large-scale study on breast cancer using the functional time series approach has been carried out in Kazakhstan. A functional assessment of the age-period-cohort model (APC) and the survival rate (period 2017-2021) was used in the retrospective study. Clinical and demographic information on patients was analysed, including age, gender, region of residence, kind and stage of tumour, occupation, socioeconomic standing, nationality, and specifics of treatment and its outcomes. Additionally, the relationship between nationality, stage, and residency region and the survival rate of breast cancer patients was investigated too. The data of n=22,736 breast cancer patients were analysed. The highest number of breast cancer cases reported was 4,945 (21.7%), in 2019. In 2021, n =4,939 (21.7%) cases were detected, while in 2020, n=4,222 (18.6%) cases were observed. The patients with breast cancer in stages I and Ia were recognized in 6,585 (29% of cases), while those in stages Ib and Ic were confirmed in 8687 (38.2% of cases). In n=10,147 (44.6%) cases, a malignant tumour of the upper outer quadrant of the breast (C50.4) was predominant. Kazakhs made up the majority (n=10,939, 48.1%) of patients with a primary validated diagnosis of breast cancer, followed by Russians (n=7527, 33.1%). Germans had the lowest survival rate overall (11.4 ± 1.7 months) (p ≤ 0.05) (95% CI: 8.0-14.7 months). Uzbeks showed relatively high survival rates of 18.3 ± 1.6 months (95% CI: 15.1-21.5 months) (p ≤ 0.05). The Aktobe region had the lowest breast cancer survival rates, measuring 12.1±0.9 months (95% CI: 10.3-13.9 months) (p ≤ 0.05). The highest survival rates, 18.0±1.3 months (95% CI: 15.5-20.5 months) and 17.9±1.4 months (95% CI: 15.3-20.7 months), were seen in Shymkent and Zhambyl regions (p ≤ 0.05), respectively. The prevalence of breast cancer increases after 37.5 years, according to the results of the APC analysis, with an indicator of 0.572 (95% CI: -0.41 - 1.56), maintaining a steady upward trend in the age range from 42.5 years to 62.5 years. Despite a slight drop in the disease's frequency, the incidence of breast cancer in women 37.5 years and older has been stable over the past five years. Additionally, it was shown that the country's northern regions had a higher incidence of breast cancer cases than the southern and western regions. Our results show the significance of demographic characteristics such as age and location for the development of preventive measures and effective treatment.

Clinical factors affecting the long-term survival of breast cancer patients.

The average 5-year survival rate of breast cancer (BC) patients has been significantly prolonged with new therapeutic methods. However, their effects on BC patient long-term survival rates are unclear. Therefore, this study aimed to analyze the specific clinical factors that can affect BC long-term survival. Here, we conducted a retrospective study and analyzed long-term survival using data of 3,240 BC patients from 1977 to 2005 from the Genotype-Tissue Expression (GTEx) database using the Kaplan-Meier method. Breast tumor size and stage were negatively correlated with long-term survival, but age showed no significant correlation. Estrogen receptor (ER) and progesterone receptor (PR) expression were each positively correlated with patient survival time, while ERBB2 receptor (HER2) expression was negatively correlated with survival time. Patients with high Nottingham prognostic index (NPI) values did not benefit from available therapies. Furthermore, breast-conserving surgery is more conducive to BC patient long-term survival than mastectomy. Early detection and breast-conserving surgery may support long-term survival for BC patients. Elevated expression of ER and PR were both associated with longer patient survival time, while positive expression of HER2 showed the opposite trend. The long-term survival rates of patients with high NPI values can potentially be increased.

Microneedles for Efficient and Precise Drug Delivery in Cancer Therapy.

Cancer is the leading cause of death, acting as a global burden, severely impacting the patients' quality of life and affecting the world economy despite the expansion of cumulative advances in oncology. The current conventional therapies for cancer which involve long treatment duration and systemic exposure of drugs leads to premature degradation of drugs, a massive amount of pain, side effects, as well as the recurrence of the condition. There is also an urgent demand for personalized and precision-based medicine, especially after the recent pandemic, to avoid future delays in diagnosis or treatments for cancer patients as they are very essential in reducing the global mortality rate. Recently, microneedles which consist of a patch with tiny, micron-sized needles attached to it have been quite a sensation as an emerging technology for transdermal application to diagnose or treat various illnesses. The application of microneedles in cancer therapies is also being extensively studied as they offer a myriad of benefits, especially since microneedle patches offer a better treatment approach through self administration, painless treatment, and being an economically and environmentally friendly approach in comparison with other conventional methods. The painless gains from microneedles significantly improves the survival rate of cancer patients. The emergence of versatile and innovative transdermal drug delivery systems presents a prime breakthrough opportunity for safer and more effective therapies, which could meet the demands of cancer diagnosis and treatment through different application scenarios. This review highlights the types of microneedles, fabrication methods and materials, along with the recent advances and opportunities. In addition, this review also addresses the challenges and limitations of microneedles in cancer therapy with solutions through current studies and future works to facilitate the clinical translation of microneedles in cancer therapies.

LUNG CANCER DETECTION USING MORPHOLOGICAL WATERSHED OPERATIONS

Cancer is one of the most serious and widespread disease across the world accounting for a large number of deaths every year. Lung cancer is the leading cause of cancer deaths in the world, having high mortality rate. The main problem in lung cancer is that most of these cases are diagnosed at the later stages of cancer, making treatments more problematic and reducing the survival chances. The survival rate of Cancer patients’ increment from 14-49% if the illness is recognized in time. Early discovery of lung cancer can expand the possibility of survival among individuals. A CT scan is more likely to show lung tumors than routine chest x-rays as it can show the size, shape, and position of any lung tumor and can help find enlarged lymph nodes that might contain cancer that has spread. Visual interpretation of CT scan can be difficult and error prone. Hence image processing techniques are used to detect the cancer nodules at an early stage. This paper deals with an automated approach for early detection of lung cancer. This algorithm is proposed using methods such as Median Filtering for Image Smoothing, Contrast Adjustment for enhancing the image, Segmentation using Morphological Watershed Operations and Otsu’s Thresholding. Key Words: CT, Median Filtering, Contrast Adjustment, Morphological Watershed Operations, Otsu Thresholding.

How do we trade off benefits and harms of anticancer drugs for advanced cancer patients?

Background: The overall survival rate of advanced cancer patients has improved thanks to the development of modern medical treatments, particularly new and innovative chemotherapeutic agents such as targeted therapies and immune checkpoint inhibitors.Current Concepts: Chemotherapy is administered in neoadjuvant, adjuvant, and palliative settings, and its ultimate goal is to improve overall survival. Chemotherapy has several proven and valuable clinical benefits, but also many side effects that cannot be ignored, especially in patients with poor European Cancer Oncology Group performance status. Therefore, we must carefully weigh and trade off the benefits and harms from many chemotherapy agents. In fact, it can be difficult to determine whether advanced cancer patients really benefit from chemotherapy, which is why a number of value measurement tools such as the American Society Clinical Oncology-Value Framework and the European Society for Medical Oncology-Magnitude of Clinical Benefit Scale have been developed.Discussion and Conclusion: We need to include individual cancer patients in decision-making processes and use appropriate shared decision-making to decide whether or not to administer chemotherapy. Furthermore, we should perform rational trade-offs in consideration of limited health resources.

3D multi-view squeeze-and-excitation convolutional neural network for lung nodule classification.

Early screening is crucial to improve the survival rate and recovery rate of lung cancer patients. Computer-aided diagnosis system (CAD) is a powerful tool to assist clinicians in early diagnosis. Lung nodules are characterized by spatial heterogeneity. However, many attempts use the two-dimensional multi-view (MV) framework to learn and simply integrate multiple view features. These methods suffer from the problems of not capturing the spatial characteristics effectively and ignoring the variability of multiple views. In this paper, we propose a three-dimensional MV convolutional neural network (3D MVCNN) framework and embed the squeeze-and-excitation (SE) module in it to further address the variability of each view in the MV framework. First, the 3D multiple view samples of lung nodules are extracted by the spatial sampling method, and a 3D CNN is established to extract 3D abstract features. Second, build a 3D MVCNN framework according to the 3D multiple view samples and 3D CNN. This framework can learn more features of different views of lung nodules, taking into account the characteristics of spatial heterogeneity of lung nodules. Finally, to further address the variability of each view in the MV framework, a 3D MVSECNN model is constructed by introducing a SE module in the feature fusion stage. For training and testing purposes we used independent subsets of the public LIDC-IDRI dataset. For the LIDC-IDRI dataset, this study achieved 96.04% accuracy and 98.59% sensitivity in the binary classification, and 87.76% accuracy in the ternary classification, which was higher than other state-of-the-art studies. The consistency score of 0.948 between the model predictions and pathological diagnosis was significantly higher than that between the clinician's annotations and pathological diagnosis. The results show that our proposed method can effectively learn the spatial heterogeneity of nodules and solve the problem of multiple view variability. Moreover, the consistency analysis indicates that our method can provide clinicians with more accurate results of benign-malignant lung nodule classification for auxiliary diagnosis, which is important for assisting clinicians in clinical diagnosis.

Multimerin 1 aids in the progression of ovarian cancer possibly via modulation of DNA damage response and repair pathways.

Ovarian cancer is one of the leading causes of deaths among women. Despite advances in the treatment regimes, a high rate of diagnosis in the advanced stage makes it almost an incurable malignancy. Thus, more research efforts are required to identify potential molecular markers for early detection of the disease and therapeutic targets to augment the survival rate of ovarian cancer patients. Previously, in this context, we identified dysregulated expression of multimerin 1 (MMRN1) in ovarian cancer. To elucidate the relationship between MMRN1 expression and ovarian cancer progression, siRNA-based MMRN1 knockdown was employed and various cell assays were performed to study its effect on ovarian cancer cells. In addition, network of dysregulated proteins was identified by quantitative proteomics and associated pathways were explored by bioinformatics analysis. MMRN1 silencing showed a significant reduction in cell viability, adhesion, migration, and invasion and a high frequency of cell apoptosis. Label-free quantitative proteomics and in-depth statistical analysis identified 448 dysregulated proteins, majority of which were overexpressed in MMRN1 knockdown cells. The pathways overrepresented in ovarian cancer were DNA replication, mismatch repair, nucleotide excision repair, and cell cycle regulation. Conclusively, the findings of this study suggest that MMRN1 aids in the progression of ovarian cancer via modulation of DNA damage response and repair pathways.

P21 Genetic Modification as a Tumor-Suppressor Gene: A Future Target in Lung Cancer Therapy?

Lung cancer is one of the most common cancers and the leading cause of cancer death worldwide. Although early diagnosis/screening methods and treatment strategies have developed, lung cancer patient survival rates remain low. However, resistance to chemotherapy and radiotherapy causes tumor recurrence and worsening of the disease, thus being the lead cause of treatment failure. In the growth cycle of lung cancer cells, the highest p21WAF1/CIP1 gene expression was found in early-stage lung cancer and decreased in advanced lung cancer. In addition, the association between CDK inhibitors and patient survival showed that inactivation of the p21WAF1/CIP1 and p16INK4a genes was associated with lower overall survival and poor prognosis. In this review, we will focus on the role of genetic modification in lincRNA-p21 in lung cancer therapy and the importance of a combination therapeutic approach.

Two Hawks with One Arrow: A Review on Bifunctional Scaffolds for Photothermal Therapy and Bone Regeneration.

Despite the significant improvement in the survival rate of cancer patients, the total cure of bone cancer is still a knotty clinical challenge. Traditional surgical resectionof bone tumors is less than satisfactory, which inevitably results in bone defects and the inevitable residual tumor cells. For the purpose of realizing minimal invasiveness and local curative effects, photothermal therapy (PTT) under the irradiation of near-infrared light has made extensive progress in ablating tumors, and various photothermal therapeutic agents (PTAs) for the treatment of bone tumors have thus been reported in the past few years, has and have tended to focus on osteogenic bio-scaffolds modified with PTAs in order to break through the limitation that PTT lacks, osteogenic capacity. These so-called bifunctional scaffolds simultaneously ablate bone tumors and generate new tissues at the bone defects. This review summarizes the recent application progress of various bifunctional scaffolds and puts forward some practical constraints and future perspectives on bifunctional scaffolds for tumor therapy and bone regeneration: two hawks with one arrow.