Types Of Cancer Research Articles

Decoding long non‑coding RNAs: Friends and foes in cancer development (Review).

Cancer remains a formidable adversary, challenging medical advancements with its dismal prognosis, low cure rates and high mortality rates. Within this intricate landscape, long non‑coding RNAs (lncRNAs) emerge as pivotal players, orchestrating proliferation and migration of cancer cells. Harnessing the potential of lncRNAs as therapeutic targets and prognostic markers holds immense promise. The present comprehensive review delved into the molecular mechanisms underlying the involvement of lncRNAs in the onset and progression of the top five types of cancer. By meticulously examining lncRNAs across diverse types of cancer, it also uncovered their distinctive roles, highlighting their exclusive oncogenic effects or tumor suppressor properties. Notably, certain lncRNAs demonstrate diverse functions across different cancers, confounding the conventional understanding of their roles. Furthermore, the present study identified lncRNAs exhibiting aberrant expression patterns in numerous types of cancer, presenting them as potential indicators for cancer screening and diagnosis. Conversely, a subset of lncRNAs manifests tissue‑specific expression, hinting at their specialized nature and untapped significance in diagnosing and treating specific types of cancer. The present comprehensive review not only shed light on the intricate network of lncRNAs but also paved the way for further research and clinical applications. The unraveled molecular mechanisms offer a promising avenue for targeted therapeutics and personalized medicine, combating cancer proliferation, invasion and metastasis.

Cancer survival in sub-Saharan Africa (SURVCAN-3): a population-based study

The Cancer Survival in Africa, Asia, and South America project (SURVCAN-3) of the International Agency for Research on Cancer aims to fill gaps in the availability of population-level cancer survival estimates from countries in these regions. Here, we analysed survival for 18 cancers using data from member registries of the African Cancer Registry Network across 11 countries in sub-Saharan Africa. We included data on patients diagnosed with 18 cancer types between Jan 1, 2005, and Dec 31, 2014, from 13 population-based cancer registries in Cotonou (Benin), Abidjan (CÔte d'Ivoire), Addis Ababa (Ethiopia), Eldoret and Nairobi (Kenya), Bamako (Mali), Mauritius, Namibia, Seychelles, Eastern Cape (South Africa), Kampala (Uganda), and Bulawayo and Harare (Zimbabwe). Patients were followed up until Dec 31, 2018. Patient-level data including cancer topography and morphology, age and date at diagnosis, vital status, and date of death (if applicable) were collected. The follow-up (survival) time was measured from the date of incidence until the date of last contact, the date of death, or until the end of the study, whichever occurred first. We estimated the 1-year, 3-year, and 5-year survival (observed, net, and age-standardised net survival) by sex, cancer type, registry, country, and human development index (HDI). 1-year and 3-year survival data were available for all registries and all cancer sites, whereas availability of 5-year survival data was slightly more variable; thus to provide medium-term survival prospects, we have focused on 3-year survival in the Results section. 10 500 individuals from 13 population-based cancer registries in 11 countries were included in the survival analyses. 9177 (87·4%) of 10 500 cases were morphologically verified. Survival from cancers with a high burden and amenable to prevention was poor: the 3-year age-standardised net survival was 52·3% (95% CI 49·4-55·0) for cervical cancer, 18·1% (11·5-25·9) for liver cancer, and 32·4% (27·5-37·3) for lung cancer. Less than half of the included patients were alive 3 years after a cancer diagnosis for eight cancer types (oral cavity, oesophagus, stomach, larynx, lung, liver, non-Hodgkin lymphoma, and leukaemia). There were differences in survival for some cancers by sex: survival was longer for females with stomach or lung cancer than males with stomach or lung cancer, and longer for males with non-Hodgkin lymphomas than females with non-Hodgkin lymphomas. Survival did not differ by country-level HDI for cancers of the oral cavity, oesophagus, liver, thyroid, and for Hodgkin lymphoma. For cancers for which population-level prevention strategies exist, and with relatively poor prognosis, these estimates highlight the urgent need to upscale population-level prevention activities in sub-Saharan Africa. These data are vital for providing the knowledge base for advocacy to improve access to prevention, diagnosis, and care for patients with cancers in sub-Saharan Africa. Vital Strategies, the Martin-Luther-University Halle-Wittenberg, and the International Agency for Research on Cancer. For the French and Portuguese translations of the abstract see Supplementary Materials section.

Unveiling myricetin's pharmacological potency: A comprehensive exploration of the molecular pathways with special focus on PI3K/AKT and Nrf2 signaling.

Myricetin can be found in the traditional Chinese medicinal plant, Myrica rubra. Myricetin is a flavonoid that is present in many vegetables, fruits, and plants and is considered to have strong antioxidant properties as well as a wide range of therapeutic applications. Growing interest has been piqued by its classification as a polyphenolic molecule because of its potential therapeutic benefits in both the prevention and management of numerous medical conditions. To clarify myricetin's traditional medical uses, modern research has investigated various pharmacological effects such as antioxidant, anticancer, anti-inflammation, antiviral, antidiabetic, immunomodulation, and antineurodegenerative effects. Myricetin shows promise as a nutritional flavonol that could be beneficial in the prevention and mitigation of prevalent health conditions like diabetes, cognitive decline, and various types of cancer in humans. The findings included in this study indicate that myricetin has a great deal of promise for application in the formulation of medicinal products and nutritional supplements since it affects several enzyme activities and alters inflammatory markers. However, comprehensive preclinical studies and research studies are necessary to lay the groundwork for assessing myricetin's possible effectiveness in treating these long-term ailments. This review summarizes both in vivo and in vitro studies investigating myricetin's possible interactions through the nuclear factor-E2-related factor 2 (Nrf2) as well as PI3K (phosphatidylinositol 3-kinase)/AKT(protein kinase B) signaling pathways in an attempt to clarify the compound's possible clinical applicability across a range of disorders.

A retrospective study on the delay in three different timescales of CT simulation among patients with pediatric cancer in a tertiary hospital.

Patients with pediatric cancer receive radiotherapy to cure several types of cancer, requiring computed tomography simulation (CT sim) for precise treatment. However, there is currently no suitable framework to reduce the inherent delays in CT sim. The present study aimed to identify the underlying causes of the delays in CT sim regarding three different time periods (duration of patient admission to CT sim, diagnosis to treatment and CT sim to treatment) among patients with pediatric cancer. A total of 58 patients with pediatric cancer who received radiation therapy under anesthesia at King Abdulaziz University Hospital (Jeddah, Saudi Arabia) between 2016 and 2021 (60 months) were included in the current study. The underlying cause of delays regarding three separate time periods was determined according to patient type, diagnosis, therapy type and year of diagnosis. The CT sim processing time averaged 73 days and was received by patients after 28.96±28.5 days. The major delays in terms of frequency and length of duration between different time points such as patient admission and CT sim, interval between diagnosis and treatment, and duration between CT sim and therapy were (mean±SD) 37.13±29.9, 58.08±24.9 and 28.15±7.9 days, respectively. Machine availability, instability of the patients' medical condition and intensity-modulated radiation therapy (IMRT) caused 66.6% of the delays. In conclusion, outpatients may experience CT sim delays. Machine availability, conditions of patients and IMRT treatment were the major reasons to cause the delay in CT sim. Strategies should be employed to prevent CT sim delays and improve patient experience.

Improving the performance for automated brain tumor classification on magnetic resonance imaging deep learningbased

<p>Brain tumor is an uncontrolled growth of abnormal cell in the brain. Early diagnosis of brain tumor has a crucial step in this type of cancer, which is fatal. Magnetic resonance imaging (MRI) is one of the examination tools to examine brain anatomy in clinical practice. The high resolution and clear separation of the tissue enable medical experts to identify brain tumor. The earlier of brain tumor is detected, the wider of treatment options. However, manually analysed of brain anatomy on MRI images are time-consuming. Computer-aided diagnosis with automated way is helpful solution to help management with unreliable degrees of automation to trace various tissue boundaries. This study proposes convolutional neural network (CNN) with its excellences to automated features extraction in convolution layer. The popular architectures of CNN, i.e., visual geometry group16 (VGG16), residual network-50 (resNet-50), inceptionV3, mobileNet, and efficientNetB7 in medical image processing are compared to brain tumor classification task. As the results, VGG16 outperformed other architectures of CNN in this study. VGG16 yields 100% accuracy, precision, sensitivity, specificity, and F1-score for testing set data. The results show the excellent performance in classifying brain tumor and no tumor from MRI images that demonstrate the efficiency of system suggested.</p>

Trends in cause-specific mortality among people with type 2 and type 1 diabetes from 2002 to 2019: a Danish population-based study

BackgroundDespite advances in primary and secondary prevention of cardiovascular disease, excess mortality persists within the diabetes population. This study explores the components of this excess mortality and their interaction with sex. MethodsUsing Danish registries (2002-2019), we identified residents aged 18-99 years, their diabetes status, and recorded causes of death. Applying Lexis-based methods, we computed age-standardized mortality rates (asMRs), mortality relative risks (asMRRs), and log-linear trends for cause-specific mortality. FindingsFrom 2002-2019, 958,278 individuals died in Denmark (T2D: 148,620; T1D: 7,830) during 84.4M person-years. During the study period, overall asMRs declined, driven by reducing cardiovascular mortality, notably in men with T2D. Conversely, cancer mortality remained high, making cancer the leading cause of death in individuals with T2D. Individuals with T2D faced an elevated mortality risk from nearly all cancer types, ranging from 9% to 257% compared to their non-diabetic counterparts. Notably, obesity-related cancers exhibited the highest relative risks: liver cancer (Men: asMRR 3·58(3·28;3·91); Women: asMRR 2·49(2·14;2·89)), pancreatic cancer (Men: asMRR 3·50(3·25;3·77); Women: asMRR 3·57(3·31;3·85)), and kidney cancer (Men: asMRR 2·10(1·84;2·40); Women: asMRR 2·31(1·92;2·79)). In men with type 2 diabetes, excess mortality remained stable, except for dementia. In women, diabetes-related excess mortality increased by 6-17% per decade across all causes of death, except cardiovascular disease. InterpretationIn the last decade, cancer has emerged as the leading cause of death among individuals with T2D in Denmark, emphasizing the need for diabetes management strategies incorporating cancer prevention. A sex-specific approach is crucial to address persistently higher relative mortality in women with diabetes. FundingSupported by Steno Diabetes Center Aarhus, which is partially funded by an unrestricted donation from the Novo Nordisk Foundation, and by The Danish Diabetes Academy.

Thiazole, isatin and phthalimide derivatives tested in vivo against cancer models: a literature review of the last six years.

Cancer is a disease characterized by the abnormal multiplication of cells and is the second leading cause of death in the world. The search for new effective and safe anticancer compounds is ongoing due to factors such as low selectivity, high toxicity, and multidrug resistance. Thus, heterocyclic compounds derived from isatin, thiazole and phthalimide that have achieved promising in vitro anticancer activity have been tested in vivo and in clinical trials. This review focused on the compilation of promising data from thiazole, isatin, and phthalimide derivatives, reported in the literature between 2015 and 2022, with in vivo anticancer activity and clinical trials. A bibliographic search was carried out in the PUBMED, MEDLINE, ELSEVIER, and CAPES PERIODIC databases, selecting relevant works for each pharmacophoric group with in vivo antitumor activity in the last 6 years. In our study, 68 articles that fit the scope were selected and critically analyzed. These articles were organized considering the type of antitumor activity and their year of publication. Some compounds reported here demonstrated potent antitumor activity against several tumor types. This review allowed us to highlight works that reported promising structures for the treatment of various cancer types and also demonstrated that the privileged structures thiazole, isatin and phthalimide are important in the design of new syntheses and molecular optimization of compounds with antitumor activity.

Ethnopharmacological Survey of Medicinal Plants Used by Local Herbalists and Traditional Healers for the Treatment of Cancer in Jordan

Background: As many Jordanians include herbs in their treatment, an ethnopharmacological survey was conducted to identify the most prescribed plants for the treatment of cancer by local herbalists and traditional healers in Jordan, aiming to encourage the prescription that is based on scientific evidence, to tackle some important practices in traditional healing, and to provide candidates for the isolation of new anticancer agents. Methods: Thirty-two Jordanian herbalists and traditional healers were interviewed. Both the use value and frequency of citation were implemented as quantitative methods to demonstrate the relative importance of a chosen species for the treatment of cancer. Furthermore, literature was screened for evidences that supported or opposed the use of the plants of interest Results: It was revealed that 31 plants are currently used in Jordan for the treatment of cancer, with Curcuma longa and Ephedra foeminea being the most used ones. Conclusions: It was noticed that the use of many prescribed plants could be rationalised by in vitro and/or in vivo studies. However, more attention should be paid by practitioners to some important aspects, such as the method of use and preparation of plants, their interaction with chemotherapeutic agents and the differences in their efficacy against different cancer types.

1,3-Diaryl Triazenes Incorporating Disulfonamides Show Both Antiproliferative Activity and Effective Inhibition of Tumor-associated Carbonic Anhydrases IX and XII.

The aim of this study was to synthesize a library of novel di-sulfa drugs containing 1,3- diaryltriazene derivatives TS (1-13) by conjugation of diazonium salts of primary sulfonamides with sulfa drugs to investigate the cytotoxic effect of these new compounds in different cancer types and to determine their inhibitory activity against tumor-associated carbonic anhydrases IX and XII. A carbonic anhydrase inhibitory activity of the obtained compounds was evaluated against four selected human carbonic anhydrase isoforms (hCA I, hCA II, hCA IX and hCA XII) by a stoppedflow CO2 hydrase assay. In addition, in vitro, cytotoxicity studies were applied by using A549 (lung cancer), BEAS-2B (normal lung), MCF-7 (breast cancer), MDA-MB-231 (breast cancer), CRL-4010 (normal breast epithelium), HT-29 (colon cancer), and HCT -116 (colon cancer) cell lines. As a result of the inhibition data, the 4-aminobenzenesulfonamide derivatives were more active than their 3-aminobenzenesulfonamide counterparts. More specifically, compounds TS-1 and TS-2, both of which have primary sulfonamides on both sides of the triazene linker, showed the best inhibitory activity against hCA IX with Ki values of 19.5 and 13.7 nM and also against hCA XII with Ki values of 6.6 and 8.3 nM, respectively. In addition, in vitro cytotoxic activity on the human breast cancer cell line MCF-7 showed that some derivatives of di-sulfa triazenes, such as TS-5 and TS-13, were more active than SLC-0111. With the aim of developing more potent and isoform-selective CA inhibitors, these novel hybrid molecules containing sulfa drugs, triazene linkers, and the classical primary sulfonamide chemotype may be considered an interesting example of effective enzyme inhibitors and important anticancer agents.

Review on Paclitaxel Derivatization: Enhanced Anticancer Action

Background: The United States Food and Drug Administration (FDA) has authorized paclitaxel for the treatment of numerous types of cancer, including breast, lung, ovarian, and Kaposi's sarcoma. It possesses all the characteristics of BCS class IV medications, including low bioavailability, low water solubility, poor permeability, unpredictable and poor absorption, and inter- and intrasubject variability. Objective: The purpose of this research was to evaluate previous efforts done to derivatize paclitaxel for greater effectiveness. Methods: A systematic literature review was conducted from a variety of sources, including published research, review articles, and patents, that mainly focus on the derivatization of paclitaxel that has been done in the last 10 years to enhance its solubility, permeability, and bioavailability. Different forms of derivatization were done in order to improve the drug's ability to be absorbed by the body, as well as its solubility and bioavailability. Results: This article explores the current and future strategies for increasing the anti-cancer efficacy of paclitaxel by enhancing its bioavailability, solubility, and penetration efficacy. Some examples are lipidbased delivery systems, polymer-based nanocarriers, crystal engineering (nanocrystals and co-crystals), liquidsolid technologies, and self-emulsifying solid dispersions. Other strategies are also discussed in this article. Conclusion: It is quite likely that this review article will contain perfect fragments of evidence for building a new model for the application of paclitaxel in the treatment of cancer.

The epidemiological profile of cancer in Beni Mellal: a cross-sectional descriptive study

In Morocco, where cancer is a major public health problem, the characteristics of cancer in the Beni Mellal-Khenifra region of Morocco are unknown. Our objective was to establish the epidemiological profile of cancer in this region and the main risk factors influencing cancer. We conducted a cross-sectional study, including all types of cancer, with a sample of 100 patients at the Beni Mellal regional oncology center. Data collected in June and July 2021 using a questionnaire, pre-tested, and analyzed using SPSS and Excel. The questionnaire included sections on cancer-related clinical characteristics and other items related to cancer risk exposures. Gyneco-mammary cancers occupied the first position (49%). The most common localization of cancer in women was breast cancer, with a proportion of 63% of cases recorded during the period studied. In men, lung cancer was the most frequent location at 17%. We found some possible risk factors for cancer: tobacco and alcohol use, dietary habits, use of hormonal contraceptive methods, low income, pollution, sun radiation, exposure to asbestos, family history of cancer, and diseases associated with cancer. Women’s cancers are very common in the region. Several factors are responsible for this frequency. These results suggest several avenues for further research.

An Updated Review on Molecular Biomarkers in Diagnosis and Therapy of Colorectal Cancer.

Colorectal cancer is one of the most common cancer types worldwide. Since colorectal cancer takes time to develop, its incidence and mortality can be treated effectively if it is detected in its early stages. As a result, non-invasive or invasive biomarkers play an essential role in the early diagnosis of colorectal cancer. Many experimental studies have been carried out to assess genetic, epigenetic, or protein markers in feces, serum, and tissue. It may be possible to find biomarkers that will help with the diagnosis of colorectal cancer by identifying the genes, RNAs, and/or proteins indicative of cancer growth. Recent advancements in the molecular subtypes of colorectal cancer, DNA methylation, microRNAs, long noncoding RNAs, exosomes, and their involvement in colorectal cancer have led to the discovery of numerous new colorectal cancer biomarkers. In small-scale investigations, most biomarkers appear promising. However, large-scale clinical trials are required to validate their effectiveness before routine clinical implementation. Hence, this review focuses on small-scale investigations and results of big data analysis that may provide an overview of the biomarkers for the diagnosis, therapy, and prognosis of colorectal cancer.

Emergency Department Visits Before Cancer Diagnosis Among Women at Mayo Clinic

ObjectiveTo determine associations of incident cancer diagnoses in women with recent emergency department (ED) care. Patients and MethodsA retrospective cohort study analyzing biological females aged 18 years and older, who were diagnosed with an incident primary cancer (12 cancer types studied) from January 1, 2015, to December 31, 2021, from electronic health records. The primary outcome was a cancer diagnosis within 6 months of a preceding ED visit. Secondary outcomes included patient factors associated with a preceding ED visit. ResultsOf 25,736 patients (median age of 62 years, range 18-101) diagnosed with an incident primary cancer, 1938 (7.5%) had an ED visit ≤6 months before a diagnosis. The ED-associated cancer cases were highest in lung cancer (n=514, 14.7%) followed by acute lymphoblastic leukemia (n=22, 13.3%). Patient factors increasing the likelihood of ED evaluation before diagnosis included 18-50 years of age (OR=1.32; 95% CI, 1.09-1.61), Elixhauser score (measure of comorbidities) >4 (OR=17.90; 95% CI, 14.21-22.76), use of Medicaid or other government insurance (OR=2.10; 95% CI, 1.63-2.69), residence within the institutional catchment areas (OR=3.18; 95% CI, 2.78-3.66), non-Hispanic Black race/ethnicity (OR=1.41; 95% CI, 1.04-1.88), and established primary care provider at Mayo Clinic (OR=1.45; 95% CI, 1.28-1.65). The ED visits were more likely in those who died within 6 months of diagnosis (n=327, 37.8%) than those who did not die (n=1611, 6.5%). ConclusionPatient characteristics identified in this study offer opportunities to provide cancer risk assessment and health navigation, particularly among individuals with comorbidities and limited health care access.

Psychological outcomes in patients with rare cancers: a systematic review and meta-analysis

Rare cancers are those that exhibit an incidence of less than six per 100,000 in a year. On average, the five-year relative survival for patients with rare cancers is worse than those with common cancers. The traumatic experience of cancer can be further intensified in patients with rare cancers due to the limited clinical evidence and the lack of empirical evidence for informed decision-making. With rare cancers cumulatively accounting for up to 25% of all cancers, coupled with the rising burden of rare cancers on societies globally, it is necessary to determine the psychological outcomes of patients with rare cancers. This PRISMA-adherent systematic review (PROSPERO: CRD42023475748) involved a systematic search of PubMed, Embase, Cochrane and PsycINFO for all peer-reviewed English language studies published since 2000 to 30th January 2024 that evaluated the prevalence, incidence and risk of depression, anxiety, suicide, and post-traumatic stress disorder (PTSD) in patients with rare cancers. Two independent reviewers appraised and extracted the summary data from published studies. Random effects meta-analyses and meta-regression were used for primary analysis. We included 32 studies with 57,470 patients with rare cancers. Meta-analyses indicated a statistically significant increased risk-ratio (RR) of depression (RR=2.61, 95% CI: 1.43-4.77, I2=97%) and anxiety (RR=2.66, 95% CI: 1.27-5.55, I2=92%) in patients with rare cancers compared to healthy controls. We identified a high suicide incidence (315 per 100,000 person-years, 95% CI: 162-609, I2=95%), prevalence of depression (17%, 95% CI: 14-22, I2=88%), anxiety (20%, 95% CI: 15-25, I2=96%) and PTSD (18%, 95% CI: 9-32, I2=25%). When compared to patients with common cancer types, suicide incidence, and PTSD prevalence were significantly higher in patients with rare cancers. Systematic review found that having advanced disease, chemotherapy treatment, lower income, and social status were risk factors for negative psychological outcomes. We highlight the need for early identification of psychological maladjustment in patients with rare cancers. Additionally, studies to identify effective interventions are imperative. This study was supported by the National Medical Research Council Transition Award, SingHealth Duke-NUS Oncology Academic Clinical Programme, the Khoo Pilot Collaborative Award, the National Medical Research Council Clinician Scientist-Individual Research Grant-New Investigator Grant, the Terry Fox Grant and the Khoo Bridge Funding Award.

Prediction of Abnormal Growth of Breast Cancer Cell Using Support Vector Machine

Abstract: Breast cancer is a serious health concern that affects millions of women worldwide. Early detection of breast cancer is crucial for effective treatment and improved survival rates. Artificial intelligence (AI) has shown great promise in the field of medical imaging and has been increasingly used for breast cancer detection. Cancer is one of the most dangerous diseases to humans, and yet no permanent cure has been developed for it. Breast cancer is one of the most common cancer types. According to the National Breast Cancer foundation, in 2020 alone, more than 276,000 new cases of invasive breast cancer and more than 48,000 non-invasive cases were diagnosed in the US. To put these figures in perspective, 64% of these cases are diagnosed early in the disease’s cycle, giving patients a 99% chance of survival. In this paper we develop a system for diagnosis, prognosis and prediction of breast cancer using AI. This will assist the doctors in diagnosis of the disease. In this research work, we systematically reviewed previous work done on detection and treatment of breast cancer using genetic sequencing or histopathological imaging with the help of deep learning and machine learning We use of AI for breast cancer detection, including studies that have used mammography, ultrasound, and magnetic resonance imaging (MRI) as imaging modalities. AI can also improve the accuracy and efficiency of breast cancer screening and diagnosis, as well as the challenges that must be addressed to ensure the successful integration of AI into clinical practice. However, further research and development are needed to optimize AI algorithms and ensure their safety and effectiveness in clinical practice. Breast cancer detection has emerged as a critical area of research, leveraging the power of Artificial Intelligence (AI) to enhance diagnostic accuracy and efficiency. Utilizing AI technologies, particularly deep learning, enables the development of robust and precise models for early breast cancer detection. These models analyze mammographic images, identifying subtle patterns indicative of malignancies that may escape human eye detection. Transfer learning, employing pre-trained neural network architectures, has demonstrated significant success in leveraging existing knowledge for improved performance. The integration of convolutional neural networks (CNNs) and image processing techniques empowers AI models to discern subtle abnormalities, aiding in the timely identification of potential breast tumors. Additionally, AI-driven diagnostic tools can streamline radiologists' workflow, providing rapid and reliable assessments, ultimately contributing to early intervention and improved patient outcomes. As these technologies continue to evolve, the synergy between AI and breast cancer detection promises to revolutionize screening methods, fostering a paradigm shift towards more accurate, efficient, and accessible diagnostic practices in the realm of breast health.

Exploring the neutrophil-to-lymphocyte ratio as a prognostic biomarker in triple-negative breast cancer

Triple-negative breast cancer is a subtype characterized by the absence of estrogen receptor, progesterone Receptor, and Human Epidermal Growth Factor Receptor 2 receptors, limiting treatment options primarily to chemotherapy due to lack of targeted therapies typically used for other breast cancer types, hence necessitating research for improved therapeutic strategies and outcomes. The neutrophil and lymphocyte percentages, absolute counts, and the ratio of neutrophils to lymphocytes were evaluated in peripheral blood of 81 patients with triple-negative breast cancer (TNBC) and 25 healthy controls. This study observed trend of high neutrophil percentage was observed in patients with positive lymph node status as compared to negative lymph node status. Significant high absolute neutrophil count was observed in patients with positive LN status, High BR score and presence of metastasis. A trend of high neutrophil to lymphocyte ratio was observed in patients with presence of perineural invasion, presence of necrosis, and patients with presence of metastasis.

Pleiotropic Regulation of PGC-1α in Tumor Initiation and Progression.

Mitochondria are recognized as a central metabolic hub with bioenergetic, biosynthetic, and signaling functions that tightly control key cellular processes. As a crucial component of mitochondrial biogenesis, peroxisome proliferator-activated receptor gamma coactivator 1α (PGC-1α) is involved in regulating various metabolic pathways, including energy metabolism and ROS homeostasis. Recent studies have highlighted the significant role of PGC-1α in tumorigenesis, cancer progression, and treatment resistance. However, PGC-1α exhibits pleiotropic effects in different cancer types, necessitating a more comprehensive and thorough understanding. In this review, we discuss the structure and regulatory mechanisms of PGC-1α, analyze its cellular and metabolic functions, explore its impact on tumorigenesis, and propose potential strategies for targeting PGC-1α. The targeted adjustment of PGC-1α based on the metabolic preferences of different cancer types could offer a hopeful therapeutic approach for both preventing and treating tumors.

Hepatocellular carcinoma-the role of the underlying liver disease in clinical practice

Hepatocellular carcinoma (HCC) is one of the most common causes of cancer-related mortality. This particular type of cancer has the distinctive characteristic of mostly happening in individuals with an underlying liver disease. This makes the management of patients more challenging, since physicians must take into consideration two different conditions, the chronic liver disease and the tumor. The underlying liver disease has several implications in clinical practice, because different kinds of chronic liver disease can lead to varying degrees of risk of developing HCC, obstacles in surveillance, and differences in the efficacy of the treatment against HCC. A shift in the prevalence of liver diseases has been evident over the last few years, with viral hepatitis gradually losing the leading position as cause of HCC and metabolic dysfunction-associated steatotic liver disease gaining importance. Therefore, in an era of personalized medicine, it is imperative that physicians are aware of the underlying liver disease of individuals with HCC and its impact in the management of their tumors.

Targeting Epidermal Growth Factor Receptor with Ficus virens Metabolites to Manage Cancer Progression: Molecular Docking and ADME Study

Abstract Introduction: Targeting epidermal growth factor receptor (EGFR) has been used in the treatment of several cancer types where EGFR has a notable involvement in signalling pathways. Medicinal plants are the oldest and healthiest source of medication used in modern pharmacological therapy. Previous research indicates that the compounds found in Ficus virens stem bark have significant therapeutic properties against a range of illnesses, including cancer. Therefore, in this study, molecular docking research was conducted to determine the binding interactions and affinity of secondary metabolites predicted in F. virens methanolic extract with the target protein, EGFR. Methodology: Three-dimensional (3D) conformers of the secondary metabolism products and adenosine triphosphate (ATP) were collected from PubChem on 5 January 2024. The 3D structure of EGFR and its inhibitor was retrieved from the Protein Data Bank (PDB) databank and ligands and proteins were converted to AutoDock-compatible format and then the energy minimisation was performed by the Open Babel in PyRx. Finally, using PyRx-Python 0.8, molecular docking was done, and using Discovery Studio, visualisation was done as well. The grid box dimensions were specified at 30 Å ×30 Å ×25 Å, and the physiochemical property evaluation was done by the SwissADME online server. Results: In this study, molecular docking assessed 14 compounds, including phytochemicals and ATP, for their binding with EGFR (PDB Id: 1XKK). Redocking of lapatinib validated the results. Natural chemicals showed binding energies from −4.0 to −7.8 Kcal/mol, with oleic acid and iso-caryophyllene demonstrating promising interactions, sourced from F. virens. Despite some limitations, these compounds exhibit potential for EGFR-targeted drug development, despite one Lipinski’s rule violation. Conclusions: EGFR inhibitory activities of iso-caryophyllene and oleic acid, which were identified in the F. virens methanol extract, were remarkable and higher than that of the substrate; their potential opens up exciting new possibilities for moving forward with cancer treatment. It is encouraged to further investigate the in vivo effectiveness of iso-caryophyllene, by means of animal models and cell lines.

Immunotherapy for esophageal cancer: Where are we now and where can we go

Immune checkpoint inhibitor therapy has dramatically improved patient prognosis, and thereby transformed the treatment in various cancer types including esophageal squamous cell carcinoma (ESCC) in the past decade. Monoclonal antibodies that selectively inhibit programmed cell death-1 (PD-1) activity has now become standard of care in the treatment of ESCC in metastatic settings, and has a high expectation to provide clinical benefit during perioperative period. Further, anti-cytotoxic T-lymphocyte–associated protein 4 (CTLA-4) monoclonal antibody has also been approved in the treatment of recurrent/metastatic ESCC in combination with anti-PD-1 antibody. Well understanding of the existing evidence of immune-based treatments for ESCC, as well as recent clinical trials on various combinations with chemotherapy for different clinical settings including neoadjuvant, adjuvant, and metastatic diseases, may provide future prospects of ESCC treatment for better patient outcomes.