Types Of Cancer Research Articles

A common secretomic signature across epithelial cancers metastatic to the pleura supports IL-6 axis therapeutic targeting.

Many cancers metastasize to the pleura, resulting in effusions that cause dyspnea and discomfort. Regardless of the tissue of origin, pleural malignancies are aggressive and uniformly fatal, with no treatment shown to prolong life. The pleural mesothelial monolayer is joined by tight junctions forming a contained bioreactor-like space, concentrating cytokines and chemokines secreted by the mesothelium, tumor, and infiltrating immune cells. This space represents a unique environment that profoundly influences tumor and immune cell behavior. Defining the pleural secretome is an important step in the rational development localized intrapleural immunotherapy. We measured cytokine/chemokine content of 252 malignant pleural effusion (MPE) samples across multiple cancers using a 40-analyte panel and Luminex multiplexing technology. Eleven analytes were consistently present in concentrations ≥ 10.0 pM: CXCL10/IP10 (geometric mean = 672.3 pM), CCL2/MCP1 (562.9 pM), sIL-6Rα (403.1 pM), IL-6 (137.6 pM), CXCL1/GRO (80.3 pM), TGFβ1 (76.8 pM), CCL22/MDC (54.8 pM), CXCL8/IL-8 (29.2 pM), CCL11/Eotaxin (12.6 pM), IL-10 (11.3 pM), and G-CSF (11.0 pM). All are capable of mediating chemotaxis, promotion of epithelial to mesenchymal transition, or immunosuppression, and many of are reportedly downstream of a pro-inflammatory cytokine cascade mediated by cytokine IL-6 and its soluble receptor. The data indicate high concentrations of several cytokines and chemokines across epithelial cancers metastatic to the pleura and support the contention that the pleural environment is the major factor responsible for the clinical course of MPE across cancer types. A sIL-6Rα to IL-6 molar ratio of 2.7 ensures that virtually all epithelial, immune and vascular endothelial cells in the pleural environment are affected by IL-6 signaling. The central role likely played by IL-6 in the pathogenesis of MPE argues in favor of a therapeutic approach targeting the IL-6/IL-6R axis.

Symptom burden and quality of life among patient and family caregiver dyads in advanced cancer.

Symptom management among patients diagnosed with advanced cancer is a high priority in clinical care that often involves the support of a family caregiver. However, limited studies have examined parallel patient and caregiver symptom burden and associations with their own and each other's quality of life (QOL). This study seeks to identify patient and caregiver symptom clusters and investigate associations between identified clusters and demographic, clinical, and psychosocial factors (cognitive appraisals and QOL). This study was a secondary analysis of self-reported baseline survey data collected from a randomized clinical trial of 484 adult advanced cancer patients and their caregivers. Latent class analysis and factor analysis were used to identify symptom clusters. Bivariate statistics tested associations between symptom clusters and demographic, clinical, and psychosocial variables. The most prevalent symptom for patients was energy loss/fatigue and for caregivers, mental distress. Low, moderate, and high symptom burden subgroups were identified at the patient, caregiver, and dyad level. Age, gender, race, income, chronic conditions, cancer type, and treatment type were associated with symptom burden subgroups. Higher symptom burden was associated with more negative appraisals of the cancer and caregiving experience, and poorer QOL (physical, social, emotional, functional, and overall QOL). Dyads whose caregivers had more chronic conditions were more likely to be in the high symptom burden subgroup. Patient and caregiver symptom burden influence their own and each other's QOL. These findings reinforce the need to approach symptom management from a dyadic perspective.

Leveraging hybrid 1D-CNN and RNN approach for classification of brain cancer gene expression

AbstractLeveraging deep learning (DL) approaches in genomics data has led to significant advances in cancer prediction. The continuous availability of gene expression datasets over the preceding years has made them one of the most accessible sources of genome-wide data, advancing cancer bioinformatics research and advanced prediction of cancer genomic data. To contribute to this topic, the proposed work is based on DL prediction in both convolutional neural network (CNN) and recurrent neural network (RNN) for five classes in brain cancer using gene expression data obtained from Curated Microarray Database (CuMiDa). This database is used for cancer classification and is publicly accessible on the official CuMiDa website. This paper implemented DL approaches using a One Dimensional-Convolutional Neural Network (1D-CNN) followed by an RNN classifier with and without Bayesian hyperparameter optimization (BO). The accuracy of this hybrid model combination of (BO + 1D-CNN + RNN) produced the highest classification accuracy of 100% instead of the 95% for the ML model in prior work and 90% for the (1D-CNN + RNN) algorithm considered in the paper. Therefore, the classification of brain cancer gene expression according to the hybrid model (BO + 1D-CNN + RNN) provides more accurate and useful assessments for patients with different types of brain cancers. Thus, gene expression data are used to create a DL classification-based- hybrid model that will hold senior promise in the treatment of brain cancer.

A Mendelian randomization analysis reveals the multifaceted role of the skin microbiota in liver cancer.

Hepatocellular carcinoma (HCC, or hepatic cancer, HC) and cholangiocarcinoma (CCA, or hepatic bile duct cancer, HBDC) are two major types of primary liver cancer (PLC). Previous studies have suggested that microbiota can either act as risk factors or preventive factors in PLC. However, no study has reported the relationship between skin microbiota and PLC. Therefore, we conducted a two-sample Mendelian randomization (MR) study to assess the causality between skin microbiota and PLC. Data from the genome-wide association study (GWAS) on skin microbiota were collected. The GWAS summary data of GCST90018803 (HBDC) and GCST90018858 (HC) were utilized in the discovery and verification phases, respectively. The inverse variance weighted (IVW) method was utilized as the principal method in our MR study. The MR-Egger intercept test, Cochran's Q-test, MR-Pleiotropy RESidual Sum and Outlier (MR-PRESSO), and leave-one-out analysis were conducted to identify the heterogeneity and pleiotropy. The results showed that Veillonella (unc.) plays a protective role in HBDC, while the family Neisseriaceae has a positive association with HBDC risk. The class Betaproteobacteria, Veillonella (unc.), and the phylum Bacillota (Firmicutes) play a protective role in HC. Staphylococcus epidermidis, Corynebacterium (unc.), the family Neisseriaceae, and Pasteurellaceae sp. were associated with an increased risk of HC. This study provided new evidence regarding the association between skin microbiota and PLC, suggesting that skin microbiota plays a role in PLC progression. Skin microbiota could be a novel and effective way for PLC diagnosis and treatment.

Synaptotagmin 13 Could Drive the Progression of Esophageal Squamous Cell Carcinoma Through Upregulating ACRV1.

SYT13 is one of the atypical members of the synaptotagmin (SYT) family whose function has attracted considerable attention in recent years. Although SYT13 has been studied in several types of human cancers, such as lung cancer, its role in esophageal squamous cell carcinoma (ESCC) is still unclear. It was demonstrated that SYT13 is significantly upregulated in ESCC tissues compared with normal ones and correlated with higher degree of malignancy. Knockdown of SYT13 could inhibit ESCC cell proliferation and migration, while promoting cell apoptosis. Meanwhile, ESCC cells with relatively lower SYT13 expression grew slower invivo and finally formed smaller xenografts. Furthermore, acrosomal vesicular protein 1 was identified as a potential downstream target of SYT13, which regulates cell phenotypes of ESCC cells in cooperation with SYT13. All the in vitro and invivo results in this study identified that SYT13 silencing could be an effective strategy to inhibit the development of ESCC, which could be considered as a promising therapeutic target in the treatment of ESCC.

The TALAPRO-3 study design: a plain language summary.

This summary is about the ongoing research study called TALAPRO-3. This study is testing the use of two medicines called talazoparib and enzalutamide. The two medicines are being used together as a treatment for patients with a type of cancer called metastatic castration-sensitive prostate cancer and changes in specific DNA repair genes within their tumors. The study began in May 2021, and includes 599 patients from 27 countries. Metastatic castration-sensitive prostate cancer is known as mCSPC for short. It is cancer that has started in the prostate and spread to other body parts. The prostate is a gland below the bladder and helps make semen (the liquid that contains sperm). Castration-sensitive means that the cancer responds to treatments that lower testosterone in the blood. In this study, some patients will take talazoparib plus enzalutamide while others will take a placebo plus enzalutamide. Talazoparib and enzalutamide are two different cancer medicines. Talazoparib is not currently used to treat patients with mCSPC. Enzalutamide is used to treat patients with prostate cancer. Talazoparib plus enzalutamide is being compared with a placebo plus enzalutamide to see if patients live longer without their cancer getting worse, or them dying, when taking talazoparib plus enzalutamide or when taking a placebo plus enzalutamide. This study aims to find out if treatment with talazoparib plus enzalutamide increases the length of time the patients in the study live without their cancer getting worse, or them dying, compared with treatment with a placebo plus enzalutamide. The study will also measure how long the patients in the study live, the number and types of side effects they have, their general health and quality of life, and whether there are changes in how patients report their pain.Clinical Trial Registration: NCT03395197 (TALAPRO-2) (ClinicalTrials.gov).

A Curated Cell Life Imaging Dataset of Immune-enriched Pancreatic Cancer Organoids with Pre-trained AI Models

Tumor organoids are three-dimensional in vitro models which can recapitulate the complex mutational landscape and tissue architecture observed in cancer patients, providing a realistic model for testing novel therapies, including immunotherapies. A significant challenge in organoid research in oncology lies in developing efficient and reliable methods for segmenting organoid images, quantifying organoid growth, regression and response to treatments, as well as predicting the behavior of organoid systems. Up to now, a curated dataset of organoids co-cultured with immune cells is not available. To address this gap, we present a new public dataset, comprising both phase-contrast images of murine and patient-derived tumor organoids of one of the deadliest cancer types, the Pancreatic Ductal Adenocarcinoma, co-cultured with immune cells, and state-of-the-art algorithms for object detection and segmentation. Our dataset, OrganoIDNetData, encompassing 180 images with 33906 organoids, can be a potential common benchmark for different organoids segmentation protocols, moving beyond the current practice of training and testing these algorithms on isolated datasets.

Construction of pan-cancer regulatory networks based on causal inference

The pan-cancer initiative aims to study the origin patterns of cancer cell, the processes of carcinogenesis, and the signaling pathways from a perspective that spans across different types of cancer. The construction of the pan-cancer related gene regulatory network is helpful to excavate the commonalities in regulatory relationships among different types of cancers. It also aids in understanding the mechanisms behind cancer occurrence and development, which is of great scientific significance for cancer prevention and treatment. In light of the high dimension and large sample size of pan-cancer omics data, a causal pan-cancer gene regulation network inference algorithm based on stochastic complexity is proposed. With the network construction strategy of local first and then global, the stochastic complexity is used in the conditional independence test and causal direction inference for the candidate adjacent node set of the target nodes. This approach aims to decrease the time complexity and error rate of causal network learning. By applying this algorithm to the sample data of seven types of cancers in the TCGA database, including breast cancer, lung adenocarcinoma, and so on, the pan-cancer related causal regulatory networks are constructed, and their biological significance is verified. The experimental results show that this algorithm can eliminate the redundant regulatory relationships effectively and infer the pan-cancer regulatory network more accurately (https://github.com/LindeEugen/CNI-SC).

The evaluation of melatonin and EGF interaction on breast cancer metastasis.

Metastasis in breast cancer is the first cause of death in patients. The epidermal growth factor (EGF) increases cancer cells' invasion, and migration. Melatonin's inhibitory effects on various types of cancer were confirmed. This study aimed to investigate whether melatonin could apply its impact through the EGF-related pathways or not. First, MDA-MB-231 and MCF7 cells were cultured, and then melatonin effects on cell viability were determined by MTT assay. Transwell invasion assay was applied to identify the invasiveness of these breast cancer cell lines under treatment of EGF and melatonin. Real-time RT-PCR then investigated the expression of MMP9 and MMP2 in determined groups. Cell proliferation was also assayed under EGF and melatonin treatment using Ki67 assessment by flow cytometry. The rate of invasion and migration of EGF-treated cells increased in both groups, in which melatonin caused increased invasion by EGF just in MCF7 cells. MMP9 and MMP2 expression increased significantly in both cell lines under EGF treatment, and melatonin increased these genes' expression in both cell lines (p<0.05). EGF increased the MMP9 and MMP2 gene expression, and melatonin increased EGF-induced expression (p<0.05). The EGF reduced the expression of the Ki67 protein in the MCF7 cell line, which was negatively affected by melatonin and EGF. In contrast, along with melatonin, EGF did not affect the proliferation of the MDA-MB-231 cell line. The results of this study show that melatonin in the presence of EGF does not show the anti-cancer properties previously described for this substance.

DNA methylation-mediated suppression of TUSC1 expression regulates the malignant progression of esophagogastric junction cancer

BackgroundEsophagogastric junction cancer (EJC) refers to malignant tumors that develop at the junction between the stomach and the esophagus. TUSC1 is a recently identified tumor suppressor gene known for its involvement in various types of cancer. The objective of this investigation was to elucidate the regulatory influence of DNA methylation on TUSC1 expression and its role in the progression of EJC.MethodsBioinformatics software was utilized to analyze the expression of TUSC1, enriched pathways, and highly methylated sites in the promoter region. TUSC1 expression in EJC was assessed using quantitative reverse transcription polymerase chain reaction (qRT-PCR), western blot (WB), and immunohistochemistry. Methylation-specific PCR was employed to detect the methylation level of TUSC1. To analyze the effects of TUSC1 and 5-AZA-2 on tumor cell proliferation, migration, invasion, cell cycle, and apoptosis, several assays including CCK-8, colony formation, transwell, and flow cytometry were conducted. The expression of MDM2 was assessed using qRT-PCR and WB. WB detected the expression of p53, and p-p53, markers for EJC cell proliferation, epithelial-mesenchymal transition, and apoptosis. The role of TUSC1 in tumor occurrence in vivo was examined using a xenograft mouse model.ResultsTUSC1 expression was significantly downregulated in EJC. Overexpression of TUSC1 and treatment with 5-AZA-2 inhibited the malignant progression of EJC cells. In EJC, low methylation levels promoted the expression of TUSC1. Upregulation of TUSC1 suppressed the expression of MDM2 and activated the p53 signaling pathway. Inactivation of this pathway attenuated the inhibitory effect of TUSC1 overexpression on EJC cell proliferation, migration, invasion, and other behaviors. Animal experiments demonstrated that TUSC1 overexpression inhibited EJC tumor growth and metastasis in vivo.ConclusionTUSC1 was commonly downregulated in EJC and regulated by methylation. It repressed the malignant progression of EJC tumors by mediating the p53 pathway, suggesting its potential as a diagnostic and therapeutic target for EJC.

Scinderin is a potential prognostic biomarker and correlated with immunological regulation: from pan-cancer analysis to liver hepatocellular carcinoma.

This study aimed to systematically dissect the role of Scinderin (SCIN) in tumorigenesis. Bioinformatics techniques were employed based on cancer data from TCGA, ENCORI, HPA, GEPIA2, UALCAN, Kaplan-Meier plotter, TIMER, TISIDB, cBioPortal, HCCDB, GeneMANIA and LinkedOmics database. Experiments in vitro and in vivo were conducted to dissect the role of SCIN in liver hepatocellular carcinoma (LIHC). Significantly differential expression of SCIN was found in nine types of cancers, including LIHC. Through pan-cancer analysis, the correlations between SCIN expression with prognosis and immune cell infiltration were proven, especially in LIHC, ovarian serous cystadenocarcinoma and lung adenocarcinoma. The highest frequency of alteration in SCIN (6.81%) was seen in patients with uterine corpus endometrial carcinoma, in which "mutation" was the predominant type, with a frequency of about 5.29%; meanwhile, S673F and S381Y were the two most frequent mutation sites. Furthermore, the abnormal expression of SCIN exhibited a strong relationship with immune cell subtypes, immune checkpoint genes, tumor mutation burden, microsatellite instability, neoantigen, molecular subtypes, mismatch repair signatures and DNA methyl-transferase in different cancer types. Through comparative analysis, we discovered that SCIN was dramatically up-regulated in LIHC, and associated with poor survival. Experiments in vitro and in vivo suggested the knockdown of SCIN could suppress tumor cell proliferation and improve the survival rate partly in animal models. This study reveals SCIN may be a promising biomarker for prognosis and treatment in certain cancers, especially in LIHC.

Inhibition of human epidermal growth factor receptor-2 protein by some alkaloid inhibitors

BackgroundHuman Epidermal Growth Factor Receptor-2 (HER2), a transmembrane tyrosine kinase receptor, has been associated with several types of cancer, including breast, lung, ovarian, etc. Therefore, this receptor is targeted by a variety of therapeutic approaches for cancer treatments. The alkaloid and lead compounds are among the selective and potent HER2 inhibitors that have been reported so far. MethodsThe present work involves molecular docking, molecular dynamics (MD) simulations, and density functional theory (DFT) calculations on alkaloid and lead compounds as HER2 inhibitors. Significant findingsThe docking results expressed that the alkaloids mainly interacted with Cys805, Val734, and Ala751 residues of HER2 protein. The MD simulation outcomes represented that all the complexes have adequate dynamic stability and flexibility based on the root mean square deviation, root mean square fluctuation, and radius of gyration. Furthermore, it is found that the strongest HER2 − ligand interaction belongs to the nocamycin I (NOI, ΔGbind = -12.84 kcal mol−1) molecule. The DFT calculations showed that electron density and the second − order perturbation stabilization energy values for HER2 − NOI interactions are higher than the other complexes. The molecular docking, MD simulation, and DFT calculation results are all in agreement and complementary. It is expected that the results obtained here can present very helpful information for the design of efficacious inhibitors for the treatment of HER2 − related cancer disease.

Extracellular vesicles in tumor-adipose tissue crosstalk: key drivers and therapeutic targets in cancer cachexia

Cancer cachexia is a complex metabolic syndrome characterized by unintentional loss of skeletal muscle and body fat. This syndrome is frequently associated with different types of cancer and negatively affects the prognosis and outcome of these patients. It involves a dynamic interplay between tumor cells and adipose tissue, where tumor-derived extracellular vesicles (EVs) play a crucial role in mediating intercellular communication. Tumor cells release EVs containing bioactive molecules such as hormones (adrenomedullin, PTHrP), pro-inflammatory cytokines (IL-6), and miRNAs (miR-1304-3p, miR-204-5p, miR-155, miR-425-3p, miR-146b-5p, miR-92a-3p), which can trigger lipolysis and induce the browning of white adipocytes contributing to a cancer cachexia phenotype. On the other hand, adipocyte-derived EVs can reprogram the metabolism of tumor cells by transporting fatty acids and enzymes involved in fatty acid oxidation, resulting in tumor growth and progression. These vesicles also carry leptin and key miRNAs (miR-155-5p, miR-10a-3p, miR-30a-3p, miR-32a/b, miR-21), thereby supporting tumor cell proliferation, metastasis formation, and therapy resistance. Understanding the intricate network underlying EV-mediated communication between tumor cells and adipocytes can provide critical insights into the mechanisms driving cancer cachexia. This review consolidates current knowledge on the crosstalk between tumor cells and adipose tissue mediated by EVs and offers valuable insights for future research. It also addresses controversial topics in the field and possible therapeutic approaches to manage cancer cachexia and ultimately improve patient outcomes and quality of life.

CTHRC1 is associated with BRAF(V600E) mutation and correlates with prognosis, immune cell infiltration, and drug resistance in colon cancer, thyroid cancer, and melanoma.

Colon cancer, thyroid cancer, and melanoma are common malignant tumors that seriously threaten human health globally. The B-Raf proto-oncogene, serine/threonine kinase (BRAF)(V600E) mutation is an important driver gene mutation in these cancer types. In this study, we identified that collagen triple helix repeat containing 1 (CTHRC1) expression was associated with the BRAF(V600E) mutation in colon cancer, thyroid cancer, and melanoma. Based on database analysis and clinical tissue studies, CTHRC1 was verified to correlate with poor prognosis and worse clinicopathological features in colon cancer and thyroid cancer patients, but not in patients with melanoma. Several signaling pathways, immune cell infiltration, and immunotherapy markers were associated with CTHRC1 expression. Additionally, a high level of CTHRC1 was correlated with decreased sensitivity to antitumor drugs (vemurafenib, PLX-4720, dabrafenib, and SB-590885) targeting the BRAF(V600E) mutation. This study provides evidence of a significant correlation between CTHRC1 and the BRAF(V600E) mutation, suggesting its potential utility as a diagnostic and prognostic biomarker in human colon cancer, thyroid cancer, and melanoma.

New nano-complexes targeting protein 3S7S in breast cancer and protein 4OO6 in liver cancer investigated in cell line

Cancer, a lethal ailment, possesses a multitude of therapeutic alternatives to combat its presence, metal complexes have emerged as significant classes of medicinal compounds, exhibiting considerable biological efficacy, especially as anticancer agents. The utilization of cis-platin in the treatment of various cancer types, including breast cancer, has served as inspiration to devise novel nanostructured metal complexes for breast cancer therapy. Notably, homo- and hetero-octahedral bimetallic complexes of an innovative multifunctional ether ligand (comprising Mn(II), Ni(II), Cu(II), Zn(II), Hg(II), and Ag(I) ions) have been synthesized. To ascertain their structural characteristics, elemental and spectral analyses, encompassing IR, UV–Vis, 1H-NMR, mass and electron spin resonance (ESR) spectra, magnetic moments, molar conductance, thermal analysis, and electron microscopy, were employed. The molar conductance of these complexes in DMF demonstrated a non-electrolytic nature. Nanostructured forms of the complexes were identified through electron microscopic data. At ambient temperature, the ESR spectra of the solid complexes exhibited anisotropic and isotropic variants, indicative of covalent bonding. The ligand and several of its metal complexes were subjected to cytotoxicity testing against breast cancer protein 3S7S and liver cancer protein 4OO6, with the Ag(I) complex (7) evincing the most potent effect, followed by the Cu(II) with ligand (complex (2)), Cis-platin, the ligand itself, and the Cu(II)/Zn(II) complex (8). Molecular docking data unveiled the inhibitory order of several complexes.

Clinical impact of a dose-escalation strategy for lenvatinib in differentiated thyroid cancer.

Treatment options for patients with differentiated thyroid cancer (DTC) who experience disease progression on lenvatinib treatment are limited. Although dose escalation of treatment with tyrosine kinase inhibitors at disease progression has been reported across cancer types, clinical significance in patients with DTC has not been investigated. We retrospectively reviewed patients with DTC who experienced disease progression on lenvatinib treatment from September 2011 to June 2022. We compared subjects who received dose-escalation treatment with standard treatment of termination at the time of initial disease progression. The escalated dose was decided by referencing to the previous effective and tolerated dose. Thirty-three patients were identified, 15 with dose escalation and 18 with lenvatinib termination. In both groups, the starting dose of lenvatinib was 24mg/day, and the median dose at initial disease progression was 10mg/day. In the former, the median dose escalation was 6mg/day (range: 4-12). Objective response rate, clinical benefit rate by escalation, and median treatment duration of the dose-escalation phase were 13.3%, 73.3%, and 9.9months (95% confidence interval [CI] 5.71-27.6), respectively. Median overall survival from initial disease progression was significantly longer in the dose-escalation group (median OS: 20.4months [95% CI 7.0-NA] vs. 3.9months [95% CI 1.7-7.9], log-rank p-value; 0.0004, hazard ratio; 0.22 [95% CI 0.09-0.55]). There were no grade 5 adverse events, and one patient discontinued due to a grade 3 lung abscess. The dose-escalation strategy appears to be a safe and effective treatment option after disease progression in patients treated with lenvatinib for DTC.

LINC00518: a key player in tumor progression and clinical outcomes.

Long non-coding RNAs (lncRNAs), defined as RNA molecules exceeding 200 nucleotides in length, have been implicated in the regulation of various biological processes and the progression of tumors. Among them, LINC00518, a recently identified lncRNA encoded by a gene located on chromosome 6p24.3, consists of three exons and is predicted to positively regulate the expression of specific genes. LINC00518 has emerged as a key oncogenic lncRNA in multiple cancer types. It exerts its tumor-promoting effects by modulating the expression of several target genes, primarily through acting as a sponge for microRNAs (miRNAs). Additionally, LINC00518 influences critical signaling pathways, including the Wnt/β-catenin, JAK/STAT, and integrin β3/FAK pathways. Elevated levels of LINC00518 in tumor tissues are associated with increased tumor size, advanced clinical stage, metastasis, and poor survival prognosis. This review provides a comprehensive summary of the genetic characteristics, expression patterns, biological functions, and underlying mechanisms of LINC00518 in human diseases.

Regenerating Chemotherapeutics through Copper-Based Nanomedicine: Disrupting Protein Homeostasis for Enhanced Tumor Therapy.

The bis-(diethyldithiocarbamate)-copper (CuET), the disulfiram (DSF)-Cu complex, has exhibited noteworthy anti-tumor property. However, its efficacy is compromised due to the inadequate oxidative conditions and the limitation of bioavailable copper. Because CuET can inactivate valosin-containing protein (VCP), a bioinformatic pan-cancer analysis of VCP is first conducted in this study to identify CuET as a promising anticancer drug for diverse cancer types. Then, based on the drug action mechanism, a nanocomposite of CuET and copper oxide (CuO) is designed and fabricated utilizing bovine serum albumin (BSA) as the template (denoted as CuET-CuO@BSA, CCB). CCB manifests peroxidase (POD)-mimicking activity to oxidize the tumor endogenous H2O2 to generate reactive oxygen species (ROS), enhancing the chemotherapy effect of CuET. Furthermore, the cupric ions released after enzymatic reaction can regenerate CuET, which markedly perturbs intracellular protein homeostasis and induces apoptosis of tumor cells. Meanwhile, CCB triggers cuproptosis by inducing the aggregation of lipoylated proteins. The multifaceted action of CCB effectively inhibits tumor progression. Therefore, this study presents an innovative CuET therapeutic strategy that creates an oxidative microenvironment in situ and simultaneously self-supply copper source for CuET regeneration through the combination of CuO nanozyme with CuET, which holds promise for application of CuET for effective tumor therapy.

Manipulating the EphB4-ephrinB2 axis to reduce metastasis in HNSCC.

The EphB4-ephrinB2 signaling axis has been heavily implicated in metastasis across numerous cancer types. Our emerging understanding of the dichotomous roles that EphB4 and ephrinB2 play in head and neck squamous cell carcinoma (HNSCC) poses a significant challenge to rational drug design. We find that EphB4 knockdown in cancer cells enhances metastasis in preclinical HNSCC models by augmenting immunosuppressive cells like T regulatory cells (Tregs) within the tumor microenvironment. EphB4 inhibition in cancer cells also amplifies their ability to metastasize through increased expression of genes associated with epithelial mesenchymal transition and hallmark pathways of metastasis. In contrast, vascular ephrinB2 knockout coupled with radiation therapy (RT) enhances anti-tumor immunity, reduces Treg accumulation into the tumor, and decreases metastasis. Notably, targeting the EphB4-ephrinB2 signaling axis with the engineered EphB4 ligands EFNB2-Fc-His and Fc-TNYL-RAW-GS reduces local tumor growth and distant metastasis in a preclinical model of HNSCC. Our data suggest that targeted inhibition of vascular ephrinB2 while avoiding inhibition of EphB4 in cancer cells could be a promising strategy to mitigate HNSCC metastasis.

Symptom impact and health-related quality of life (HRQoL) assessment by cancer stage: a narrative literature review

BackgroundCancer stage at diagnosis is an important prognostic indicator for patient outcomes, with detection at later stages associated with increased mortality and morbidity. The impact of cancer stage on patient-reported outcomes is poorly understood. This research aimed to understand symptom burden and health related quality of life (HRQoL) impact by cancer stage for ten cancer types: 1) ovarian, 2) lung, 3) pancreatic, 4) esophageal, 5) stomach, 6) head and neck, 7) colorectal, 8) anal, 9) cervical, and 10) liver and bile duct.MethodsTen narrative literature reviews were performed to identify and collate published literature on patient burden at different stages of disease progression. Literature searches were conducted using an AI-assisted platform to identify relevant articles published in the last five (2017–2022) or ten years (2012–2022) where articles were limited. Conference abstracts were searched for the last two years (2020–2022). The geographic scope was limited to the United States, Canada, Europe, and global studies, and only journal articles written in English were included.ResultsA total of 26 studies with results stratified by cancer stage at diagnosis (and before treatment) were selected for the cancer types of lung, pancreatic, esophageal, stomach, head and neck, colorectal, anal, and cervical cancers. Two cancer types, ovarian cancer, and liver and bile duct cancer did not return any search results with outcomes stratified by disease stage. A general trend was observed for worse patient-reported outcomes in patients with cancer diagnosed at an advanced stage of disease compared with diagnosis at an earlier stage. Advanced disease stage was associated with greater symptom impact including general physical impairments such as pain, fatigue, and interference with functioning, as well as disease/region-specific symptom burden. Poorer HRQoL was also associated with advanced disease with commonly reported symptoms including anxiety and depression.ConclusionsOverall, the general trend for greater symptom burden and poorer HRQoL seen in late stage versus early-stage disease across the included cancer types supports the importance for early diagnosis and treatment to improve patient survival and decrease negative impacts on disease burden and HRQoL.