Cancer Samples Research Articles

FNDC5 affects invasion and migration of oral cancer by inhibiting PI3K/Akt/Snail signaling pathway.

This study first investigated how FNDC5 affected the development of oral cancer and revealed the role of FNDC5 in the migration and invasion of oral cancer. The present work evaluated differential FNDC5 expression within oral cancer samples versus matched non-carcinoma samples based on GEO database analysis and immunohistochemistry. We then generated oral cancer cell lines with FNDC5 overexpression and knockdown to determine the role of altered FNDC5 expression in the migration and invasion of oral cancer. PI3K inhibitor was used for investigating the possible mechanism underlying FNDC5 during EMT of oral cancer. Finally, these in-vitro results were validated using the lung metastatic nude mouse model. According to our results, FNDC5 level markedly decreased within oral cancer compared with adjacent samples and FNDC5 overexpression inhibited migration, invasion as well as EMT of oral cancer, while FNDC5 knockdown promoted oral cancer cell EMT. In addition, PI3K inhibitors blocked the induction of oral cancer cells EMT by FNDC5 knockdown. In vivo experiments further demonstrated the above results. This work is the first to illustrate the impact of FNDC5 on inhibiting migration and invasion of oral cancer, and our results suggest that FNDC5 affects EMT of oral cancer via the inhibition of PI3K/Akt/Snail pathway.

A Comparative Study of Methyl-BEAMing and Droplet Digital PCR for MGMT Gene Promoter Hypermethylation Detection

Background: O-6-methylguanine-DNA methyltransferase is responsible for the direct repair of O6-methylguanine lesions induced by alkylating agents, including temozolomide. O-6-methylguanine-DNA methyltransferase promoter hypermethylation is a well-established biomarker for temozolomide response in glioblastoma patients, also correlated with therapeutic response in colorectal cancer. Objectives: The ARETHUSA clinical trial aims to stratify colorectal cancer patients based on their mismatch repair status. Mismatch repair-deficient patients are eligible for treatment with immune checkpoint inhibitors (anti-PDL-1), whereas mismatch repair-proficient samples are screened for O-6-methylguanine-DNA methyltransferase promoter methylation to identify those suitable for temozolomide treatment. Methods: In this context, a subset of ARETHUSA metastatic colorectal cancer samples was used to compare two different techniques for assessing O-6-methylguanine-DNA methyltransferase hypermethylation: Methyl-BEAMing, a highly sensitive digital PCR approach that combines emulsion PCR and flow cytometry, and droplet digital PCR, a more automated procedure that enables the rapid, operator-independent analysis of a large number of samples. Results: Our study clearly demonstrates that the results obtained using Methyl-BEAMing and droplet digital PCR are comparable, with both techniques showing similar accuracy, sensitivity, and reproducibility. Conclusions: Digital droplet PCR proved to be an efficient method for detecting gene promoter methylation. However, the Methyl-BEAMing method has proved more sensitive for detecting low quantities of DNA.

SIGMAR1 Knockdown Enhances Oral Cancer Cell Chemosensitivity to Cisplatin via Decreased PD-L1 Expression

Emerging evidence suggests that aberrant expression levels of Sigma1 (SIGMAR1, also known as sigma-1 receptor) have been implicated in the progression of various diseases, including cancer. However, its significance in oral cancer (OC) has not been thoroughly explored. To advance in this field, the present study aimed to investigate the impact of SIGMAR1 knockdown in oral cancer cells. To do so, we included in this study our cohort of human OC samples and OC cell lines, which were utilized for experimental verification through several in vitro assays. Our findings revealed that SIGMAR1 overexpression was associated with poor survival rates and positively correlated with PD-L1 overexpression in human oral cancer samples. Furthermore, SIGMAR1 inhibition led to a decrease in PD-L1 expression and sensitized oral cancer cells to cisplatin treatment by enhancing apoptosis. These results suggest that SIGMAR1 knockdown may present a promising strategy worthy of further exploration in the management of oral cancer.

Glucocorticoid Receptor Isoforms in Breast Cancer Raise Implications for Personalised Supportive Therapies

Glucocorticoid receptor (GR) activation may promote metastasis in oestrogen receptor-negative and triple-negative breast cancer (TNBC). However, the role of the GRβ isoform, which has opposing effects to the main isoform, has not been studied in clinical samples. We aimed to analyse the intracellular localisation of total GR and GRβ in vitro using plasmid constructs and fluorescent immunocytochemistry. Additionally, our goal was to perform immunostaining for total GR and GRβ on two cohorts: (i) on 194 clinical breast cancer samples to compare the expression in different molecular subtypes, and (ii) on 161 TNBC samples to analyse the association of GR with survival. We supplemented our analysis with RNA data from 1097 TNBC cases. We found that in the absence of the ligand, GR resided in the cytoplasm of breast cancer cells, while upon ligand activation, it translocated to the nucleus. A negative correlation was found between cytoplasmic GRtotal and Ki67 in luminal A tumours, while the opposite trend was observed in TNBC samples. Tumours with strong lymphoid infiltration showed higher cytoplasmic GRtotal staining compared to those with weaker infiltration. Patients with high nuclear GRtotal staining had shorter progression-free survival in univariate analysis. High cytoplasmic GRβ was a marker for better overall survival in multivariate analysis (10-year overall survival HR [95% CI]: 0.46 [0.22–0.95], p = 0.036). As a conclusions, this study is the first to investigate GRβ expression in breast tumours. Different expression and cellular localisation of GRtotal and GRβ were observed in the context of molecular subtypes, underscoring the complex role of GR in breast cancer. An inverse association between cytoplasmic GRtotal and the Ki67 proliferation index was observed in luminal A and TNBC. Regarding the impact of GR on outcomes in TNBC patients, while cytoplasmic GRβ was associated with a better prognosis, patients with nuclear GRtotal staining may be at a higher risk of disease progression, as it negatively affects survival. Caution should be exercised when using glucocorticoids in patients with nuclear GR staining, as it may negatively impact survival.

SIRT2 deacetylates and decreases the expression of FOXM1 in colon cancer.

New FOXM1-specific inhibitors with the potential to be used for therapeutic purposes are under extensive research. We hypothesized that deacetylation of FOXM1 would decrease protein expression, thus providing novel therapeutic management of colon cancers. Immunostaining was used to determine FOXM1 and SIRT2 expressions in human colon cancer tissue microarrays (n = 90) from Stage I to Stage IV. SIRT2-FOXM1 interaction was evaluated in colon cancer cells using immunoprecipitation. Deacetylation of FOXM1 via SIRT2 was determined using in vitro deacetylation assays. FOXM1 could be hyper-acetylated when p300 and pCAF histone acetyltransferases were administered alongside deacetylase inhibitors. We detected that SIRT2 and FOXM1 physically interacted, and SIRT2 deacetylated FOXM1 in vitro. SIRT2 overexpression led to a significant decrease while knockdown of SIRT2 increased the FOXM1 expression in HCT116 human colon carcinoma cells. In the analysis of 90 human colorectal cancer samples, high SIRT2 expression was observed in about 49% of colorectal cancer, intermediate in 29%, and low or no staining in 22%. Strong SIRT2 expression was found to be negatively associated with the FOXM1 staining in our clinical cohort. This study reveals a molecular interaction and association between SIRT2 and FOXM1 expression in colon cancer cell lines and human colon cancer samples, and suggests that targeting SIRT2 activity using small molecule modulators may be a promising therapeutic approach for colorectal cancer.

Association of high-grade serous ovarian cancer sample clonality with clinical outcomes

Association of high-grade serous ovarian cancer sample clonality with clinical outcomes

Genomic and transcriptomic profiling of inflammatory breast cancer reveals distinct molecular characteristics to non-inflammatory breast cancers.

Inflammatory breast cancer (IBC), a rare and highly aggressive form of breast cancer, accounts for 10% of breast cancer-related deaths. Previous omics studies of IBC have focused solely on one of genomics or transcriptomics and did not discover common differences that could distinguish IBC from non-IBC. Seventeen IBC patients and five non-IBC patients as well as additional thirty-three Asian breast cancer samples from TCGA-BRCA were included for the study. We performed whole-exon sequencing (WES) to investigate different somatic genomic alterations, copy number variants, and large structural variants between IBC and non-IBC. Bulk RNA sequencing (RNA-seq) was performed to examine the differentially expressed genes, pathway enrichment, and gene fusions. WES and RNA-seq data were further investigated in combination to discover genes that were dysregulated in both genomics and transcriptomics. Copy number variation analysis identified 10 cytobands that showed higher frequency in IBC. Structural variation analysis showed more frequent deletions in IBC. Pathway enrichment and immune infiltration analysis indicated increased immune activation in IBC samples. Gene fusions including CTSC-RAB38 were found to be more common in IBC. We demonstrated more commonly dysregulated RAS pathway in IBC according to both WES and RNA-seq. Inhibitors targeting RAS signaling and its downstream pathways were predicted to possess promising effects in IBC treatment. We discovered differences unique in Asian women that could potentially explain IBC etiology and presented RAS signaling pathway as a potential therapeutic target in IBC treatment.

Elucidating the roles of SOD3 correlated genes and reactive oxygen species in rare human diseases using a bioinformatic-ontology approach.

Superoxide Dismutase 3 (SOD3) scavenges extracellular superoxide giving a hydrogen peroxide metabolite. Both Reactive Oxygen Species diffuse through aquaporins causing oxidative stress and biomolecular damage. SOD3 is differentially expressed in cancer and this research utilises Gene Expression Omnibus data series GSE2109 with 2,158 cancer samples. Genome-wide expression correlation analysis was conducted with SOD3 as the seed gene. Categorical SOD3 Pearson Correlation gene lists incrementing in correlation strength by 0.01 from ρ≥|0.34| to ρ≥|0.41| were extracted from the data. Positively and negatively SOD3 correlated genes were separated for each list and checked for significance against disease overlapping genes in the ClinVar and Orphanet databases via Enrichr. Disease causal genes were added to the relevant gene list and checked against Gene Ontology, Phenotype Ontology, and Elsevier Pathways via Enrichr before the significant ontologies containing causal and non-overlapping genes were reviewed with a literature search for possible disease and oxidative stress associations. 12 significant individually discriminated disorders were identified: Autosomal Dominant Cutis Laxa (p = 6.05x10-7), Renal Tubular Dysgenesis of Genetic Origin (p = 6.05x10-7), Lethal Arteriopathy Syndrome due to Fibulin-4 Deficiency (p = 6.54x10-9), EMILIN-1-related Connective Tissue Disease (p = 6.54x10-9), Holt-Oram Syndrome (p = 7.72x10-10), Multisystemic Smooth Muscle Dysfunction Syndrome (p = 9.95x10-15), Distal Hereditary Motor Neuropathy type 2 (p = 4.48x10-7), Congenital Glaucoma (p = 5.24x210-9), Megacystis-Microcolon-Intestinal Hypoperistalsis Syndrome (p = 3.77x10-16), Classical-like Ehlers-Danlos Syndrome type 1 (p = 3.77x10-16), Retinoblastoma (p = 1.9x10-8), and Lynch Syndrome (p = 5.04x10-9). 35 novel (21 unique) genes across 12 disorders were identified: ADNP, AOC3, CDC42EP2, CHTOP, CNN1, DES, FOXF1, FXR1, HLTF, KCNMB1, MTF2, MYH11, PLN, PNPLA2, REST, SGCA, SORBS1, SYNPO2, TAGLN, WAPL, and ZMYM4. These genes are proffered as potential biomarkers or therapeutic targets for the corresponding rare diseases discussed.

GD2 in Breast Cancer: A Potential Biomarker and Therapeutic Target.

Expression of disialoganglioside GD2 in normal tissues is primarily limited to the central nervous system, peripheral sensory nerve fibers, dermal melanocytes, lymphocytes, and mesenchymal stem cells. Its widespread overexpression in various cancer types allows it to be classified as a tumor-associated antigen with potential diagnostic and therapeutic implications. This article reviews the synthesis pathways of GD2 and its role in cancer cell adhesion, proliferation, and metastasis with a focus on breast cancer. GD2 appears to be overexpressed on the outer membrane of most breast cancer cells and breast cancer stem cells (BCSCs) and is closely linked to epithelial-mesenchymal transition (EMT). GD3 synthase (GD3S) is considered to be the rate-determining step in GD2 synthesis. Clinical studies indicate that GD2 expression is increased in 35-70% of breast cancer samples, with higher levels in triple-negative breast cancer (TNBC). This overexpression correlates with more aggressive tumor features and worse prognosis. Therapeutic targeting of GD2 with monoclonal antibodies (moABs) like dinutuximab and naxitamab has demonstrated anti-cancer activity in preclinical cancer models and human clinical trials against high-risk neuroblastoma reducing tumor growth and enhancing survival. GD2-specific chimeric antigen receptor (CAR) T-cell therapy and GD3S inhibition present other promising therapeutic strategies to improve clinical outcomes. Furthermore, GD2-targeted vaccines are currently being investigated in cancer therapy. This narrative review article underscores the critical role of GD2 in breast cancer pathogenesis and highlights the promising therapeutic opportunities it offers. It advocates for the initiation of clinical trials to further explore the potential of GD2-targeted treatment in combination with standard breast cancer therapies.

Exploring tumor endothelial cells heterogeneity in hepatocellular carcinoma: insights from single-cell sequencing and pseudotime analysis.

This study aimed to explore the heterogeneity of tumor endothelial cells (TECs) in hepatocellular carcinoma (HCC) and their role in tumor progression, with the goal of identifying new therapeutic targets and strategies to improve patient prognosis. Single-cell RNA sequencing data from nine primary liver cancer samples were analyzed, obtained from the Gene Expression Omnibus (GEO) database. Data preprocessing, normalization, dimensionality reduction, and batch effect correction were performed based on the Seurat package. HCC cell types were identified using uniform manifold approximation and projection (UMAP) and cluster analysis, and the different cell types were annotated using the CellMarker database. Pseudotime trajectory analysis was conducted with Monocle to explore the differentiation trajectory of TECs. MAPK signaling pathway activity and copy number variations (CNV) in TECs were analyzed in conjunction with data from The Cancer Genome Atlas (TCGA), the trans-well and wound healing assay was used for cell invasion and migration activity assessment. Two subgroups of TECs (TECs 1 and TECs 2) were identified, exhibiting distinct functional activities and signaling pathways. Specifically, TECs 1 may be involved in tumor cell proliferation and inflammatory responses, whereas TECs 2 is not only involved in cell proliferation pathways, but also enriched in pathways such as metabolic synthesis. Pseudotime analysis revealed dynamic changes in TECs subgroups during HCC progression, correlating specific gene expressions (such as PDGFRB, PGF, JUN, and NR4A1). Subsequently, the JUN gene was predicted by performing binding sites and was shown to act as a transcription factor that may regulate the expression of the PGF gene. CNV analysis highlighted key genes and pathways in TECs that might influence HCC progression, and the PGF as key regulatory factor mediated cell proliferation and migration. The study revealed the heterogeneity of TECs in HCC and their potential roles in tumor progression, offering new perspectives and potential therapeutic targets for HCC molecular mechanisms. The findings emphasize the importance of further exploring TECs heterogeneity for understanding HCC pathogenesis and developing personalized treatment strategies.

NAT10 functions as a pivotal regulator in gastric cancer metastasis and tumor immunity.

Gastric cancer (GC) presents a significant global health burden, with metastasis being the leading cause of treatment failure and mortality. NAT10, a regulatory protein involved in mRNA acetylation, has been implicated in various cancers. However, its role in GC, especially concerning metastasis and immune interactions, remains unclear. Utilizing multi-omics data from gastric cancer samples, we conducted comprehensive analyses to investigate NAT10 expression, its correlation with clinical parameters and immune relevance. Bioinformatics analysis and digital image processing were employed for this purpose. Furthermore, in vitro and in vivo experiments were conducted to elucidate the functional role of NAT10 in gastric cancer progression, aiming to provide deeper biological insights. Our findings reveal a significant association between NAT10 expression and various aspects of transcriptional, protein, as well as tumor immunity in GC patients. Additionally, we demonstrated that NAT10 promotes gastric cancer cell proliferation and migration, both in cellular models and in animal studies, suggesting its involvement in early tumor microvascular metastasis. NAT10 emerges as a promising molecular target, offering potential avenues for further research into molecular mechanisms and therapeutic strategies for GC.

Profiling Breast Tumor Heterogeneity and Identifying Breast Cancer Subtypes Through Tumor-Associated Immune Cell Signatures and Immuno Nano Sensors.

Breast cancer is a complex and heterogeneous disease with varying cellular, genetic, epigenetic, and molecular expressions.The detection of intratumor heterogeneity in breast cancer poses significant challenges due to its complex multifaceted characteristics, yet its identification is crucial for guiding effective treatment decisions and understanding the diseaseprogression. Currently, there exists no method capable of capturing the full extent of breast tumor heterogeneity. In this study, the aim is to identify and characterize metabolic heterogeneity in breast tumors using immune cells and an ultrafast laser-fabricated Immuno Nano Sensor.Combining spectral markers from both Natural Killer (NK)and T cells, a machine-learning approach is implemented to distinguish cancer from healthy samples, identify primary versus metastatic tumors, and determine estrogen receptor (ER)/progesterone receptor (PR) status at the single-cell level. The platform successfully distinguished heterogeneous breast cancer samples fromhealthy individuals, achieving97.8%sensitivity and92.2%specificity, andaccurately identifiedprimary tumors from metastatic tumors. Characteristic spectral signatures allow for discrimination between ER/PR-positive andnegative tumors with 97.5% sensitivity.This study demonstrates the potential of immune cell-based metabolic profiling in providing a comprehensive assessment of breast tumor heterogeneity and paving the way for minimally invasive liquid biopsy approaches in breast cancer diagnosis and management.

3D cultivation of non-small-cell lung cancer cell lines using four different methods

PurposeThe aim of this study was to set up reliable and reproducible culture conditions for 3D tumoroids derived from non-small cell lung cancer (NSCLC) cell lines to enable greater opportunity for successful cultivation of patient-derived samples.MethodsFour NSCLC cell lines, two adenocarcinomas (A549, NCI-H1975) and two squamous cell carcinomas (HCC-95, HCC-1588), were first cultured in traditional 2D settings. Their expected expression profiles concerning TTF-1, CK7, CK5, and p40 status were confirmed by immunohistochemistry (IHC) before the generation of 3D cultures. Tumoroids were established in the hydrogel GrowDex®-T, Nunclon™ Sphera™ flasks, BIOFLOAT™ plates, and Corning® Elplasia® plates. Western blot was used to verify antigen protein expression. Hematoxylin-eosin staining was used to evaluate the cell morphology in the 2D and 3D cultures. Mutational analysis of KRAS and EGFR by PCR on extracted DNA from 3D tumoroids generated from cells with known mutations (A549; KRAS G12S mutation, NCI-H1975; EGFR L858R/T790M mutations).ResultsWe successfully established 3D cultures from A549, NCI-H1975, HCC-95, and HCC-1588 with all four used cultivation methods. The adenocarcinomas (A549, NCI-H1975) maintained their original IHC features in the tumoroids, while the squamous cell carcinomas (HCC-95, HCC-1588) lost their unique markers in the cultures. PCR analysis confirmed persistent genetic changes where expected.ConclusionThe establishment of tumoroids from lung cancer cell lines is feasible with various methodologies, which is promising for future tumoroid growth from clinical lung cancer samples. However, analysis of relevant markers is a prerequisite and may need to be validated for each model and cell type.

Statistical properties of items and summary scores from the Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE®) in a diverse cancer sample.

The Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE®) was developed to capture symptomatic adverse events from the patient perspective. We aim to describe statistical properties of PRO-CTCAE items and summary scores and to provide evidence for recommendations regarding PRO-CTCAE administration and reporting. Using data from the PRO-CTCAE validation study (NCT02158637), prevalence, means, and standard deviations of PRO-CTCAE items, composite scores, and mean and maximum scores across attributes (frequency, severity, and/or interference) of symptomatic adverse events were calculated. For each adverse event, correlations and agreement between attributes, correlations between attributes and composite scores, and correlations between composite, mean, and maximum scores were estimated. PRO-CTCAE items were completed by 899 patients with various cancer types. Most patients reported experiencing one or more adverse events, with the most prevalent being fatigue (87.7%), sad/unhappy feelings (66.0%), anxiety (63.6%), pain (63.2%), insomnia (61.8%), and dry mouth (60.0%). Attributes were moderately to strongly correlated within an adverse event (r = 0.53 to 0.77, all p < 0.001) but not fully concordant (κweighted = 0.26 to 0.60, all p < 0.001), with interference demonstrating lowest mean scores and prevalence among attributes of the same adverse event. Attributes were moderately to strongly correlated with composite scores (r = 0.67 to 0.97, all p < 0.001). Composite scores were moderately to strongly correlated with mean and maximum scores for the same adverse event (r = 0.69 to 0.94, all p < 0.001). Correlations between composite scores of different adverse events varied widely (r = 0.04 to 0.68) but were moderate to strong for conceptually related adverse events. Results provide evidence for PRO-CTCAE administration and reporting recommendations that the full complement of attributes be administered for each adverse event, and that attributes as well as summary scores be reported.

A Low Transformed Tubal Rank Tensor Model Using a Spatial-Tubal Constraint for Sample Clustering with Cancer Multi-omics Data

Background: Since each dimension of a tensor can store different types of genomics data, compared to matrix methods, utilizing tensor structure can provide a deeper understanding of multi-dimensional data while also facilitating the discovery of more useful information related to cancer. However, in reality, there are issues such as insufficient utilization of prior knowledge in multi-omics data and limitations in the recovery of low-tubal-rank tensors. Therefore, the method proposed in this article was developed. Objective: In this paper, we proposed a low transformed tubal rank tensor model (LTTRT) using a spatial-tubal constraint to accurately partition different types of cancer samples and provide reliable theoretical support for the identification, diagnosis, and treatment of cancer. Method: In the LTTRT method, the transformed tensor nuclear norm based on the transformed tensor singular value decomposition is characterized by the low-rank tensor, which can explore the global low-rank property of the tensor, resolving the challenge of the tensor nuclear norm-based method not achieving the lowest tubal rank. Additionally, the introduction of weighted total variation regularization is conducive to extracting more information from sequencing data in both spatial and tubal dimensions, exploring cross-correlation features of multiple genomic data, and addressing the problem of overlooking prior knowledge from various perspectives. In addition, the L1-norm is used to improve sparsity. A symmetric Gauss‒Seidel-based alternating direction method of multipliers (sGS-ADMM) is used to update the LTTRT model iteratively. Results: The experiments of sample clustering on multiple integrated cancer multi-omics datasets show that the proposed LTTRT method is better than existing methods. Experimental results validate the effectiveness of LTTRT in accurately partitioning different types of cancer samples. result: The experiments of sample clustering on multiple integrated cancer multi-omics datasets show that the proposed LTTRT method is better than existing methods. Experimental results validate the effectiveness of LTTRT in accurately partitioning different types of cancer samples. Conclusion: The LTTRT method achieves precise segmentation of different types of cancer samples.

Senescence-related genes as prognostic indicators in breast cancer survival.

Breast cancer is a leading cause of cancer-related mortality among women worldwide, particularly affecting those in their later years. As the incidence of breast cancer increases with age, understanding the biological mechanisms that link aging and cancer becomes crucial. Cellular senescence, a hallmark of aging, plays a dual role in cancer by inhibiting tumorigenesis while also contributing to tumor progression through the senescence-associated secretory phenotype (SASP). This study aims to investigate the prognostic significance of senescence-related genes in breast cancer. We utilized the SenMayo gene list, a comprehensive set of senescence-related genes, to analyze gene expression data from a large cohort of breast cancer samples. The data was sourced from the Kaplan-Meier plotter, an integrated database that compiles gene expression information from multiple independent cohorts. Cox proportional hazards regression and false discovery rate (FDR) corrections were employed to evaluate the correlation between gene expression and survival outcomes, aiming to establish a prognostic signature. Our findings demonstrate that higher expression levels of senescence-related genes are significantly associated with improved survival, while lower expression levels correlate with shorter survival outcomes. These results suggest that senescence-related pathways play a protective role in breast cancer, potentially serving as valuable prognostic indicators. The identification of a prognostic signature based on senescence-related genes underscores the importance of cellular senescence in breast cancer progression and survival. Our study highlights the potential of senescence-related biomarkers in enhancing patient stratification and informing treatment strategies, contributing to the growing body of literature on the intersection of aging and cancer.

Validity, test-retest reliability, and responsiveness of the Indonesian version of FACIT-COST measure for subjective financial toxicity.

Financial toxicity describes the impairment of financial wellbeing in patients due to the burden of cancer diagnosis and care. The COST: A Functional Assessment of Chronic Illness Therapy Measure of Financial Toxicity (FACIT-COST) is the most widely used cancer-specific measure of subjective financial toxicity, having been validated in multiple languages, but not in Indonesian. This study aimed to validate the Indonesian version of FACIT-COST in a breast cancer sample. A single-center prospective cohort study was performed in Indonesia. Female breast cancer patients aged ≥ 18 undergoing treatment at baseline were invited to participate and followed for up to six months. The survey included the official Indonesian version of FACIT-COST (v2) which was administered to the patients by interviewers. Clinical information (e.g., metastasis status, disease duration) was provided based on medical records. The following measurement properties of FACIT-COST were tested: distributional characteristics, structural validity (principal component [PCA] and confirmatory factor analyses [CFA]), internal consistency reliability (Cronbach's alpha and McDonald's omega), known-groups validity (Mann-Whitney U or Kruskal-Wallis H test), test-retest reliability, and responsiveness to change. Overall, 300 female patients participated at baseline. No patients reported the best or worst possible FACIT-COST total scores. The PCA proposed a two-factor model structure for the instrument, which was confirmed by the CFA (RMSEA = 0.042, SRMR = 0.049, CFI = 0.99, TLI = 0.99). The internal consistency reliability of the two factors was considered adequate (Cronbach's alpha = 0.774-0.882, McDonald's omega = 0.786-0.888). The FACIT-COST total score significantly discriminated across the following known-groups: age, education, residential setting, income, employment, metastasis status, number of symptoms, and financial coping strategies. The FACIT-COST demonstrated excellent test-retest reliability (intraclass correlation coefficient = 0.96) and satisfactory responsiveness to change (standardized response mean and effect size ranges=|0.39| to |0.92|). This is the first study to validate the FACIT-COST in patients with breast cancer and to present the measurement properties of the Indonesian version of FACIT-COST. The Indonesian FACIT-COST demonstrates acceptable psychometric performance and shows potential as a valid measure of subjective financial toxicity. The instrument may serve as a valuable tool for informing health policies that focus on providing resource support to improve cancer care in Indonesia.

Dual-view jointly learning improves personalized drug synergy prediction.

Accurate and robust estimation of the synergistic drug combination is important for medicine precision. Although some computational methods have been developed, some predictions are still unreliable especially for the cross-dataset predictions, due to the complex mechanism of drug combinations and heterogeneity of cancer samples. We have proposed JointSyn that utilizes dual-view jointly learning to predict sample-specific effects of drug combination from drug and cell features. JointSyn outperforms existing state-of-the-art methods in predictive accuracy and robustness across various benchmarks. Each view of JointSyn captures drug synergy-related characteristics and make complementary contributes to the final prediction of drug combination. Moreover, JointSyn with fine-tuning improves its generalization ability to predict a novel drug combination or cancer sample using a small number of experimental measurements. We also used JointSyn to generate an estimated atlas of drug synergy for pan-cancer and explored the differential pattern among cancers. These results demonstrate the potential of JointSyn to predict drug synergy, supporting the development of personalized combinatorial therapies. Source code and data are available at https://github.com/LiHongCSBLab/JointSyn. Supplementary data are available at Bioinformatics online.

Combined spatially resolved metabolomics and spatial transcriptomics reveal the mechanism of RACK1-mediated fatty acid synthesis.

Lipid metabolism is altered in rapidly proliferating cancer cells, where fatty acids (FAs) are utilized in the synthesis of sphingolipids and glycerophospholipids to produce cell membranes and signaling molecules. Receptor for activated C-kinase 1 (RACK1; also known as small ribosomal subunit protein) is an intracellular scaffolding protein involved in signaling pathways. Whether such lipid metabolism is regulated by RACK1 is unknown. Here, integrated spatially resolved metabolomics and spatial transcriptomics revealed that accumulation of lipids in cervical cancer (CC) samples correlated with overexpression of RACK1, and RACK1 promoted lipid synthesis in CC cells. Chromatin immunoprecipitation verified binding of sterol regulatory element-binding protein 1 (SREBP1) to acetyl-CoA carboxylase (ACC) and fatty acid synthase (FASN) promoters. RACK1 enhanced de novo FA synthesis by upregulating expression of sterol regulatory element binding transcription factor 1 (SREBP1) and lipogenic genes FASN and ACC1. Co-immunoprecipitation and western blotting revealed that RACK1 interacted with protein kinase B (AKT) to activate the AKT/mammalian target of rapamycin (mTOR)/SREBP1 signaling pathway to promote FA synthesis. Cell proliferation and apoptosis experiments suggested that RACK1-regulated FA synthesis is key in the progression of CC. Thus, RACK1 enhanced lipid synthesis through the AKT/mTOR/SREBP1 signaling pathway to promote the growth of CC cells. RACK1 may become a therapeutic target for CC.

Construction and multiple validations of a robust ferroptosis-related prognostic model in bladder cancer: A comprehensive study.

Ferroptosis is iron-dependent programmed cell death that inhibits tumor growth, particularly in traditional treatment-resistant tumors. Prognostic models constructed from ferroptosis-related genes are lacking; prognostic biomarkers remain insufficient. We acquired gene expression data and corresponding clinical information for bladder cancer (BC) samples from public databases. Ferroptosis-related genes from the ferroptosis database were screened for clinical predictive value. We validated gene expression differences between tumors and normal tissues through polymerase chain reaction and western blotting. Gene ontology and Kyoto encyclopedia of genes and genomes enrichment analyses were conducted to explore signaling pathways affecting the overall survival of patients with BC. CIBERSORT was used to quantify the infiltration of 22 immune cell types. We identified 6 genes (EGFR, FADS1, ISCU, PGRMC1, PTPN6, and TRIM26) to construct the prognostic risk model. The high-risk group had a poorer overall survival than the low-risk group. Receiver operating characteristic curves demonstrated excellent predictive accuracy. The validation cohort and 3 independent datasets confirmed the models' general applicability and stability. BC tissues had elevated FADS1, PTPN6, and TRIM26 mRNA and protein levels and decreased ISCU levels. Enrichment analysis indicated that neurosecretory activity might be the main pathway affecting the overall survival. High- and low-risk groups had significantly different immune cell infiltration. Specific ferroptosis-related gene expression was associated with immune cell infiltration levels. The risk score was significantly correlated with patients' clinical characteristics. A novel, widely applicable risk model with independent predictive value for the prognosis of patients with BC was established; candidate molecules for future BC research were identified.