Spontaneous pneumothorax (SP) is defined by the presence of air in the pleural space arising from neither trauma nor iatrogenic causes. It can develop secondary to various etiologies. The familial clustering observed in some patients with SP supports the view that genetic factors play a role in the pathogenesis of SP. Several recognizable pneumothorax-associated genetic syndromes exist, including Birt-Hogg-Dubé syndrome (BHD), tuberous sclerosis complex-associated lymphangioleiomyomatosis (TSC-LAM), Marfan syndrome (MFS), cystic fibrosis (CF), alpha-1 antitrypsin deficiency (AATD), vascular Ehlers-Danlos syndrome (vEDS), Loeys-Dietz syndrome (LDS), and a few others. Recognition of these syndromes underlying SP facilitates optimal management and counseling regarding prognosis and potential comorbidities. In this review, we systematically summarize several genetic syndromes associated with pneumothorax, in which SP may manifest either as an initial presenting symptom or as a potential complication that adversely affects the prognosis.

Tertiary lymphoid structures (TLS) are organized lymphoid aggregates that form outside lymph nodes within the tumor microenvironment. They are linked to better prognosis and stronger antitumor immune responses. However, the key molecular factors that control TLS maturation in non-small cell lung cancer (NSCLC) are still not clear, and their prognostic value is not fully defined. We analyzed TLS-related genes to identify markers linked to prognosis. We used consensus clustering to define molecular subtypes with different survival outcomes. We then built a TLS risk score signature (TLSRS) using LASSO-Cox regression and tested it in independent meta-GEO cohorts. We also examined the association between DKK1 expression and TLS maturation by multiplex immunofluorescence in a clinical cohort. TLSRS separated patients into high- and low-risk groups in the training cohort (n = 503, P < 0.0001) and in the validation cohorts (n = 681, P < 0.0001). The time-dependent AUC values were 0.762, 0.710, and 0.708 at 1, 3, and 5 years. Multivariable analysis showed that TLSRS was an independent prognostic factor in all cohorts. Patients with low TLSRS showed higher immune cell infiltration and higher CCL19 expression, and they also showed stronger immune-related activity across cohorts. In an independent in-house cohort (n = 119), higher DKK1 expression was linked to worse overall survival. DKK1 expression was negatively correlated with the TLS maturity ratio, but it was not correlated with the number of TLS. We developed a prognostic TLSRS that captures key features of the immune microenvironment in NSCLC. We also found that DKK1 may act as a negative regulator of TLS maturation. These results help explain TLS biology and suggest that DKK1 could be a therapeutic target to improve antitumor immunity in NSCLC.

Structural variants (SVs) are increasingly recognized as important contributors to oncogenesis through their effects on 3D genome folding. Recent advances in whole-genome sequencing have enabled large-scale profiling of SVs across diverse tumors, yet experimental characterization of their individual impact on genome folding remains infeasible. Here, we leveraged a convolutional neural network, Akita, to predict disruptions in genome folding caused by somatic SVs identified in 61 tumor types from the Children's Brain Tumor Network dataset. Our analysis reveals significant variability in SV-induced disruptions across tumor types, with the most disruptive SVs coming from lymphomas and sarcomas, metastatic tumors, and germline cell tumors. Dimensionality reduction of disruption scores identified five recurrently disrupted regions enriched for high-impact SVs across multiple tumors. Some of these regions are highly disrupted despite not being highly mutated, and harbor tumor-associated genes and transcriptional regulators. To further interpret the functional relevance of high-scoring SVs, we integrated epigenetic data and developed a modified Activity-by-Contact scoring approach to prioritize SVs with disrupted genome contacts at active enhancers. This method highlighted highly disruptive SVs near key oncogenes, as well as novel candidate loci potentially implicated in tumorigenesis. These findings highlight the utility of machine learning for identifying novel SVs, loci, and genetic mechanisms contributing to pediatric cancers. This framework provides a foundation for future studies linking SV-driven regulatory changes to cancer pathogenesis.

Lung cancer, being the top cause of global cancer-related mortality, calls for effective treatments. RN7SK (7SK) is a long non-coding RNA (lncRNA) that plays a significant role in the regulation of gene transcription and thereby controls essential cellular activities. Limited evidence supports the anticancer potential of 7SK, and its suppressive effects have not been tested against lung cancer. This study explored the anticancer effects of RN7SK (7SK), a long non-coding RNA known to regulate gene transcription, through exosome-mediated delivery in lung cancer cells. Treatment with exosome-loaded 7SK (Exo-7SK) significantly elevated 7SK levels in non-small-cell lung cancer cells and suppressed key cancer traits. Exo-7SK reduced cell viability and proliferation, promoted apoptosis, and inhibited migration and invasion by shifting gene expression away from epithelial-mesenchymal transition. It also impaired spheroid formation and reduced spheroid dispersion and viability in 3D microfluidic cultures. In conclusion, our findings highlight the cancer-suppressive potential of exosome-mediated 7SK delivery against lung cancer, demonstrating significant efficacy in both 2D and 3D culture models. These observations warrant further confirmation in future studies employing advanced designs and clinically relevant models.

Liquid biopsies offer a promising, noninvasive approach for monitoring and predicting responses to immunotherapy across multiple solid tumors. For the most part these are circulating tumor DNA (ctDNA) based assays. Here, we discuss the biological basis, clinical evidence, and potential applications of different types of ctDNA assays in tracking tumor dynamics, distinguishing pseudoprogression, and assessing minimal residual disease. We explore the current limitations, assay variability, and future directions, including integration with other biomarkers and real-world clinical trials aimed at validating ctDNA as a routine tool in precision immuno-oncology.

Colorectal cancer (CRC) remains a leading cause of cancer‑related morbidity and mortality worldwide. Although the adenoma-carcinoma sequence and its genetic drivers are well described, the earliest cellular and molecular events initiating tumorigenesis within histologically normal colonic epithelium remain poorly defined. This study aims to identify tumor‑initiating cells (TICs), distinguish them from normal stem‑like cells (nSTMs), and delineate early transcriptional and signaling programs using single‑cell RNA sequencing (scRNA‑seq) from paired normal‑appearing and transformed human colonic tissues.

In biomedical studies, testing for differences in covariance may offer scientific insights, especially when differences are driven by complex joint behavior between features. However, when differences in joint behavior are weakly dispersed across many dimensions and arise from differences in low-rank structures within the data, as is often the case in genomics and neuroimaging, existing two-sample covariance testing methods may suffer from power loss. The Ky-Fan(k) norm, defined by the sum of the top k singular values, is a simple and intuitive matrix norm able to capture signals caused by differences in low-rank structures between matrices, but its statistical properties in hypothesis testing have not been studied well. In this paper, we investigate the behavior of the Ky-Fan(k) norm in two-sample covariance testing. Ultimately, we propose a novel methodology, rank-adaptive covariance testing (RACT), which is able to leverage differences in low-rank structures found in the covariance matrices of two groups in order to maximize power. RACT uses permutation for statistical inference, ensuring an exact Type I error control. We validate RACT in simulation studies and evaluate its performance when testing for differences in gene expression networks between two types of lung cancer, as well as testing for covariance heterogeneity in diffusion tensor imaging data taken on two different scanner types.

Quercetin, a plant-derived dietary flavonoid, has multifunctional biological activities, including anticancer action; however, its applications may be restricted due to limited bioavailability. Thus, novel synthetic quercetin derivatives (QDs) with improved properties and/or drug combinations should be designed and tested. In the present study, anticancer activity of fourteen newly synthesized QDs was investigated using four cellular models of melanoma, namely A375, MM370, G-361, and SH-4 cells. Thioquercetins (thioQ, thioQ(OAc)4, and thioQ(OAc)5), when used at low micromolar range, induced apoptotic cell death in melanoma cells compared to normal cells. Thioquercetins also reduced the population of spheroid-forming cells and suppressed the growth of A375 cells in 3D spheroid models. Thioquercetin-mediated antimelanoma action was potentiated upon heat shock protein 90 (HSP90) inhibition. Co-treatment with the HSP90 inhibitor 17-DMAG and thioquercetins augmented oxidative stress (increased superoxide production, decreased levels of antioxidant proteins SOD1, and PRDX1-2), and impaired the aryl hydrocarbon receptor (AhR)/cytochrome P450 1A1 (CYP1A1) signaling pathway-based detoxification of thioquercetins by the inhibition of AhR translocation to the nucleus and AhR-mediated stimulation of CYP1A1 expression leading to enhanced cytotoxic effects against melanoma cells. The senolytic activity of thioQ(OAc)4 with four acetylated hydroxy groups against cisplatin-induced senescent melanoma cells was also revealed in selected experimental settings. We suggest that the use of novel thioquercetin-based derivatives along with HSP90 inhibitors should be further validated in vivo and considered for the design of more effective antimelanoma strategies in the future.

Patients with a DPYD genetic deficiency who receive capecitabine are at increased risk of severe, potentially fatal toxicities due to impaired drug metabolism. Genetic testing for this deficiency allows for proactive dose adjustments to mitigate these risks. We evaluated the cost-effectiveness of DPYD genotyping prior to capecitabine administration, followed by dose modification for patients with metastatic breast cancer.

HCC is a highly vascularized solid tumor that develops rapidly and has a poor prognosis. Previous studies have shown that fibroblasts and angiogenesis in the tumor microenvironment play significant roles in the progression of HCC, and the combined effect of both on HCC is worth exploring. Therefore, we developed the CAF-VEGF prognostic scoring model to assess the prognosis of HCC patients. Single-cell sequencing was done on cancer tissues and nearby normal tissues in the study using data that we downloaded from the GEO database. We used the CellChat and Monocle3 packages to analyze the angiogenesis pathways and differentiation trajectories of fibroblasts. Subsequently, we conducted functional enrichment on fibroblasts. We constructed the CAF-VEGF prognostic model using the COX and LASSO algorithms and evaluated its prognostic value through survival and ROC curves. Based on the prognostic model, we identified key genes through differential expression screening, WGCNA, and PPI network analysis. The conclusions were ultimately validated by expression experiments and functional assays. We found that fibroblasts had a higher infiltration rate in HCC tissues and successfully constructed a CAF-VEGF prognostic model in HCC, proving its effectiveness. Using the CAF-VEGF score, we identified the key molecular markers ESCO2 and WDHD1, both significantly upregulated in HCC cells. Their overexpression may lead to poor prognosis in HCC patients. Additionally, through experiments, we found that both can promote angiogenesis and enhance the proliferation and invasion-migration abilities of HCC cells. This study successfully constructed the CAF-VEGF prognostic model for HCC, and may help improve the prognosis of HCC patients. We also found that the genes WDHD1 and ESCO2 can promote HCC infiltration by regulating angiogenesis, providing insights for future HCC treatment.

Autophagy has a critical involvement in the initiation and progression of various cancers, including colorectal cancer (CRC). The feasibility of using autophagy-related genes (ATGs) as prognostic tools for CRC patients is yet to be determined.

The fusion of data features from different modes, such as pathology images and sequence data, has the potential to predict the overall survival (OS) of patients with cervical cancer. This study aims to develop a novel prediction model for overall survival (OS) that incorporates pathology images, clinical data and molecular data. The model underwent training using comprehensive cervical cancer data from The Cancer Genome Atlas (TCGA), which include 119 patients. To independently validate the model, we used a manually collected dataset from Peking Union Medical College Hospital (PUMCH), comprising 53 patients with cervical cancer. LASSO Cox regression analysis was applied to identify relevant features associated with overall survival (OS), resulting in the identification of 484 genes, including RGR, DBN1 and CALCR, as well as numerous image features. Building upon these findings, a multimodal deep learning model was developed to effectively classify the overall survival (OS) of patients with cervical cancer into two categories: short term (ST: ≤ 3 years) and long term (LT: > 3 years) based on the integration of pathology images and clinical features. The developed model achieved reasonably good prediction accuracy in the independent testing dataset from PUMCH, with an area under the curve (AUC) value of 0.783. In conclusion, the combination of pathology images with clinical and molecular data enables the creation of accurate and reliable prediction models for cervical cancer.

Recent studies have increasingly demonstrated that chemoresistance in ovarian cancer primarily stems from resistance to oxidative stress and ferroptosis. Ferroptosis, a non-apoptotic form of cell death dependent on intracellular iron and marked by the buildup of lipid reactive oxygen species (ROS), has shown enhanced effectiveness in triggering cell death in ovarian cancer cells. Thus, this study aimed to explore the potential of gene knockdown associated with ferroptosis as an innovative therapeutic strategy against ovarian cancer. Up-regulated genes were identified using a gene bank, and their expression levels were validated through Western blotting (WB) and quantitative PCR (qPCR). Levels of MDA, Fe2+, GSH, ROS, SQSTM1, LC3-I and LC3-II in ovarian cancer cells treated with sorafenib and subjected to gene knockout were assessed using specific kits. Expression levels of proteins related to ferroptosis were analyzed by WB. Tumor size, volume, ferroptosis and autophagy in ovarian cancer tumor tissues were also examined. IGF2BP3 was elevated in human ovarian cancer and decreased during ferroptosis induced by sorafenib in human ovarian cancer cells. IGF2BP3 knockdown inhibited ovarian cancer cell function and promoted ferroptosis, in addition to autophagy-mediated EMC2 degradation. IGF2BP3 knockdown increased ovarian cancer sensitivity to sorafenib. This study confirmed that IGF2BP3 knockdown inhibited ovarian cancer cell malignancy, promoted ferroptosis and inhibited autophagy-mediated EMC2 degradation, and verified that IGF2BP3 knockdown increased the sensitivity to sorafenib in ovarian cancer mice.

Hepatocellular carcinoma (HCC) is a prevalent form of primary liver cancer, commonly related to chronic hepatitis B virus (HBV) infection. As an essential enzyme in glycolysis, Enolase-1 (ENO1) is implicated in the progression of multiple types of cancer. The aim of this study was to explore the ENO1's function in HBV-associated HCC. The expression of ENO1 in HBV-HCC was determined with RT-qPCR, immunohistochemistry, and Western blot. ENO1 and HBx overexpression or knockdown was performed through transfection. EdU staining, TUNEL staining, wound healing assay, and Transwell assay were utilized to evaluate the malignant biological behavior of HBV-HCC cells. HBV replication in HBV-HCC cells was assessed by measuring HBV DNA, HBsAg, and HBV cccDNA levels. The interaction of HBx with ENO1 was analyzed by co-IP and Western blot analysis. This study showed the elevated ENO1 expression in HBV-HCC. ENO1 overexpression in HBV-HCC cells markedly enhanced proliferation, migration, invasion, and HBV replication, while significantly inhibiting apoptosis. Conversely, ENO1 silencing produced the opposite effects. HBx was found to upregulate ENO1 expression. By rescue assays, HBx silencing suppressed the malignant behavior of HBV-HCC cells, but was reversed by ENO1 overexpression. Additionally, the enhancement of HBx overexpression on the malignant behavior of HBV-HCC cells was counteracted by ENO1 silencing. HBx facilitates the malignant advancement of HBV-associated HCC by elevating ENO1 expression.

BACKGROUND Lung squamous cell carcinoma (LUSC) is a highly heterogeneous malignancy, with the immune micro-environment playing a critical role in tumor progression and response to therapy. However, stemness, endothelial-to-mesenchymal transition (EMT), and anoikis (a type of apoptosis) are not sufficiently studied in the LUSC immune micro-environment. This research aimed to explore the prognostic value of anoikis-related genes and tumor immune in the treatment of LUSC. MATERIAL AND METHODS Immune-cell fractions in LUSC samples were predicted using 3 computational algorithms: CIBERSORT, quanTseq, and SVR. The immune-cell infiltration patterns, including B cells, NK cells, neutrophils, macrophages, mast cells, and T cells, were analyzed. A prognostic nomogram was constructed using clinical variables and immune markers, and its predictive ability for overall survival at 1, 3, and 5 years was evaluated. Calibration plots, decision curve analysis, and receiver operating characteristic (ROC) curves were used to assess model performance. We used Python and R software to perform the analysis. P<0.05 was considered as statistically significant. RESULTS S100A7, S100A8, and SPP1 were identified from the LUSC tumor micro-environment and were used to construct a nomogram. The immune profiling revealed significant heterogeneity in immune-cell infiltration across LUSC samples, with T cells, macrophages, tregs, and dendritic cells being predominantly associated with immune suppression. The nomogram integrating clinical and immune markers demonstrated moderate predictive accuracy for overall survival. Calibration and decision curve analyses confirmed the clinical utility of the nomogram for survival prediction. CONCLUSIONS Our study presents a prognostic model of the interplay between anoikis resistance and immune-cell infiltration. Personalized immunotherapy strategies, including targeting the identified prognostic markers can improve treatment efficacy and overcome immune evasion mechanisms and can enhance clinical outcomes for LUSC patients.

Epstein-Barr virus (EBV), a ubiquitous human herpesvirus infecting over 90% of the adult population, is causally associated with a distinct molecular subtype of gastric cancer (GC). A key mechanism by which EBV influences tumour biology is the expression of viral microRNAs (miR/miRNA) encoded within the BamHI-A rightward transcript (BART) region, although inter-patient variability in EBV-miRNA expression and its molecular significance remain incompletely defined. In this study, small RNA sequencing was performed on 11 primary gastric tumour samples to characterise EBV-derived miRNA expression, followed by quantitative RT-PCR analysis in an extended cohort of 21 tumours for targeted validation. EBV-miRNAs were detected in a subset of tumours and showed marked inter-tumour heterogeneity in abundance. EBV-miRNA-positive tumours were dominated by a conserved set of BART miRNAs, including miR-BART19-3p, miR-BART1-5p, miR-BART10-3p, miR-BART6-3p, miR-BART13-5p, and miR-BART22. These BART miRNAs displayed correlated expression patterns, characterised by concurrent elevation of multiple viral miRNA species within the same tumour samples. To link viral miRNA expression with host molecular responses, in silico virus-host interaction analysis was conducted using ViRBase to prioritise host genes associated with the detected BART miRNAs. PTEN, BCL2L11, FOXO3, and CDKN1A were identified as high-confidence targets and selected for experimental assessment. RT-qPCR analysis demonstrated differential expression of these host genes across tumours stratified by EBV BART miRNA abundance. Together, these findings identify a consistent BART miRNA pattern within this cohort. This study provides patient-level molecular evidence linking EBV-miRNA regulatory output to host gene expression states in GC.

Background and Objectives: Non-small cell lung cancer (NSCLC) accounts for approximately 85% of all lung cancers and remains a leading cause of cancer-related mortality worldwide. EGFR-targeted tyrosine kinase inhibitors (TKIs) have substantially improved outcomes in EGFR-mutant NSCLC; however, primary and acquired resistance continues to limit their long-term efficacy. HER3 (receptor tyrosine-protein kinase ErbB3), a member of the ErbB receptor family, has been implicated in TKI resistance through heterodimerization with EGFR and HER2, leading to downstream PI3K/AKT pathway activation. Despite its biological plausibility as a resistance mediator, the clinical significance of HER3 expression as a prognostic and predictive biomarker in EGFR-mutant NSCLC has not been thoroughly characterized in real-world cohorts. Materials and Methods: This retrospective, single-center study included 52 patients diagnosed with EGFR-mutant NSCLC who received TKI therapy at Afyonkarahisar Health Sciences University between January 2011 and September 2023. HER3 protein expression was evaluated by immunohistochemistry (IHC) on formalin-fixed, paraffin-embedded tumor tissue sections using the Huabio anti-HER3 antibody (clone PD00-44, 1:2000 dilution). Staining in more than 30% of tumor cells was considered HER3-positive; membranous staining intensity was scored on a 1-3 scale. Progression-free survival (PFS1, PFS2) and overall survival (OS) were analyzed using the Kaplan-Meier method and log-rank test. Statistical significance was set at p < 0.05. Results: Of 52 patients (55.8% female; mean age 64.5 years), 59.6% received chemotherapy and 40.4% received an EGFR TKI as first-line treatment; erlotinib constituted 71.2% of targeted therapies. In the first-line TKI group, HER3-negative patients had a numerically longer median PFS1 compared with HER3-positive patients (14.0 vs. 7.1 months; p = 0.285); however, this difference did not reach statistical significance and should be interpreted with caution given the small sample size. In contrast, among patients receiving first-line chemotherapy, HER3 staining status did not meaningfully affect PFS1 (4.1 vs. 2.5 months; p = 0.063). In second-line treatment, HER3-positive patients who received TKI after prior chemotherapy demonstrated a PFS2 comparable to or slightly exceeding that of HER3-negative patients (21.8 vs. 19.8 months; p = 0.49), suggesting that the sequencing of chemotherapy before TKI may attenuate the adverse effect of HER3 positivity. Median OS was 15.1 months in HER3-negative patients and 12.7 months in HER3-positive patients (p = 0.824); this numerical difference of approximately 3 months did not reach statistical significance and should therefore be interpreted cautiously. Among patients receiving TKI in the first line, HER3-positive patients had a shorter median OS than HER3-negative patients (9.6 vs. 14.2 months), whereas those receiving TKI in the second line showed a trend toward longer OS in HER3-positive patients (20.5 vs. 17.2 months). Conclusions: HER3 expression was associated with reduced first-line TKI efficacy in EGFR-mutant NSCLC, suggesting a possible role for HER3 in primary TKI resistance; however, these findings are exploratory and did not reach statistical significance. The observation that HER3-positive patients who received chemotherapy before TKI demonstrated outcomes comparable to HER3-negative patients raises the hypothesis that treatment sequencing may potentially influence the impact of HER3 positivity, though this requires prospective validation before any clinical conclusions can be drawn. These results suggest that HER3 expression may warrant further investigation as a candidate biomarker for treatment sequencing decisions and as a potential therapeutic target in EGFR-mutant NSCLC. Prospective studies evaluating chemotherapy-TKI sequencing and HER3-directed agents such as patritumab deruxtecan (HER3-DXd) in HER3-positive patients are needed to confirm these preliminary observations.

Background and Objectives: Melanoma is the leading cause of skin cancer-related mortality due to its high propensity for early metastasis, although survival rates have improved with the advent of targeted and immune-based therapies. Accurate detection of targetable mutations and assessment of tumor mutational burden are essential for informed therapeutic decision-making. Mutation profiling is routinely performed using next-generation sequencing (NGS). The Oncomine Focus Assay (OFA) detects common alterations in 52 genes across various tumor entities, whereas MelArray is a melanoma-specific NGS panel covering mutations in 190 melanoma-relevant genes and providing a genome-wide copy number analysis. Moreover, tumor mutational burden is being assessed. Materials and Methods: In this retrospective study, we analyzed the phenotypic characteristics of 100 patients with cutaneous melanoma who underwent NGS testing using either OFA or MelArray. The aims were to compare the diagnostic yield of the two panels and to investigate potential associations between mutational profiles and clinicopathological features of melanoma. Results: Tumor location, ulceration, and Breslow thickness showed significant correlations with the melanoma subtypes. BRAF mutations were the most frequent driver alterations across all cutaneous melanoma subtypes; however, no significant correlation between specific driver mutations and phenotypic characteristics was identified. MelArray detected a notably high number of alterations in the TERT promoter and CDKN2A genes, which were not captured by OFA and are of potential therapeutic relevance. Conclusions: In conclusion, MelArray enables a more comprehensive molecular characterization of cutaneous melanoma compared with a small generic cancer panel and may support more personalized therapeutic decision-making.

Background and Objectives: Reliable tools for evaluating tumor biology and forecasting clinical outcomes in recurrent hepatocellular carcinoma (HCC) remain scarce, and molecular characterization through genetic profiling is equally limited in this setting. This investigation explores whether serum tumor marker expression patterns correlate with genomic mutation profiles, and whether such correlations may facilitate more accurate prediction of tumor biology and patient prognosis in recurrent HCC. Materials and Methods: We analyzed a cohort of 20 patients who underwent curative-intent resection for both primary and recurrent HCC. Tumor specimens collected at the time of each operation were subjected to targeted next-generation sequencing for mutation profiling. Based on pre-operative serum levels of AFP (alpha-fetoprotein) and PIVKA-II (Protein Induced by Vitamin K Absence or Antagonist-II) measured before each surgery, patients were stratified into four biomarker subgroups. Those who maintained the same biomarker subgroup at both operations were designated the 'serum concordant group', whereas those who transitioned between subgroups were classified as the 'serum discordant group'. Clinical characteristics and mutation data were subsequently compared between these two classifications. Results: The interval from primary surgery to disease recurrence was significantly shorter in the serum concordant group relative to the serum discordant group (mean 11.16 ± 1.86 vs. 44.8 ± 9.45 months, p < 0.001). Additionally, disease-free survival following reoperation was significantly inferior in the concordant group compared with the discordant group (p = 0.039). Regarding mutational patterns, the concordant group demonstrated shared gene mutations between primary and recurrent lesions, while the discordant group exhibited divergent mutational landscapes across both timepoints. Conclusions: The concordance or discordance of serum tumor marker profiles between primary and recurrent HCC lesions may serve as a clinically accessible surrogate for underlying tumor biology and prognostic stratification. These results are preliminary and hypothesis-generating. Further studies in larger, independent cohorts are warranted to confirm the observed associations.

Background/Objectives: There is a clear need for more options to control the progression of breast cancer and prevent the occurrence of breast cancer in minority populations that have a higher rate of mortality due to triple-negative breast cancer (TNBC) subtypes. Prevalent nutraceuticals such as Ashwagandha (also known as the Indian Winter Cherry) have anti-inflammatory and apoptotic capabilities, as well as the ability to inhibit cancer growth. The purpose of this study is to analyze the novel combination of withaferin A (derived from the Indian Winter Cherry and known to have histone deacetylase inhibition capabilities) and sodium butyrate (a short-chain fatty acid produced from the gut microbiome and known to have DNA methyltransferase inhibition capabilities) treatment on breast cancer-derived cell lines. There is a scientific gap of possible causality of decreasing breast cancer progression when treated with sodium butyrate and withaferin A. Methods: Two in vitro cell viability assays were utilized consisting of [MTT (4,5 Dimethylthiazol-2-yl)] and the neutral red assay to analyze the impact of treatment of compounds alone and in combination on breast cancer cells for 72 h. The Highest Single Agent (HSA) combination analysis was utilized to derive combination indexes for our breast cancer cell types. Protein and gene expression was investigated for Class 1 histone deacetylases, de novo DNA methyltransferase, the p65 subunit of NF-κB, and NFκB1. Lastly, DNA methyltransferase enzymatic activity was analyzed via the Epigentek DNMT Activity/Inhibition ELISA Easy Kit. Results: Through the cell viability assay [MTT (4,5 Dimethylthiazol-2-yl)], MCF-7, MDA-MB-231, and MDA-MB-157 cells were found to have a decrease in cell viability due to combinatorial treatment with withaferin A and sodium butyrate. Western blot results depicted a decrease in protein expression levels for DNA methyltransferases due to the administration of 2.5 mM sodium butyrate and 0.2 µM withaferin A alone and in combination for breast cancer cell lines MCF-7, MDA-MB-231, and MDA-MB-157. Additionally, the combination of these two components have successfully inhibited the progression of the NFκB1 gene within analysis through the quantitative polymerase chain reaction (qPCR). Conclusions: The novel combination of withaferin A and sodium butyrate have markedly reduced the progression of breast cancer-derived cell lines for cell viability, epigenetic DNMT gene expression, as well as inhibiting NFκB1 signaling on the gene expression level.