Purpose: Cell-free DNA (cfDNA) analysis is a powerful tool for noninvasively predicting patient outcomes. We analyzed the size distribution of cfDNA and assessed its prognostic and diagnostic values in an osteosarcoma cohort. Experimental Design: The fragment size distribution and level of cfDNA were analyzed in 15 healthy donors and 50 patients with osteosarcoma using automated capillary electrophoresis. The prognostic performance of cfDNA size analysis was assessed using univariate and multivariable analyses. By performing whole-genome sequencing of matched cfDNA and osteosarcoma tissue samples, we investigated the correlation between the size and mutation profiles of cfDNA and the mutation concordance between cfDNA and paired tissue tumors. Results: The size of cfDNA fragments in patients with osteosarcoma was significantly shorter than in healthy donors, with the integrative analysis of size distribution and level of cfDNA achieving a high specificity and sensitivity of 100%. The short cfDNA fragment (150-bp cut-off) was an independent prognostic predictor in this osteosarcoma cohort [HR, 9.03; 95% confidence interval (CI), 1.13–72.20; P = 0.038]. Shortened cfDNA fragments were found to be a major source of mutations. Enrichment of cfDNA fragments with less than or equal to 150 bp by in silico size selection remarkedly improved the detection of copy-number variation signals up to 2.3-fold when compared with total cfDNA, with a higher concordance rate with matched osteosarcoma tissue. Conclusions: This finding demonstrated the potential of cfDNA size profiling in the stratification of poor prognostic patients with osteosarcoma. The short fragments of cfDNA are a promising source for boosting the detection of significant mutations in osteosarcoma. See related commentary by Weiser et al., p. 2017

Identification of novel photosynthetic proteins is important for understanding and improving photosynthetic efficiency. Synergistically, genome neighborhood can provide additional useful information to identify photosynthetic proteins. We, therefore, expected that applying a computational approach, particularly machine learning (ML) with the genome neighborhood-based feature should facilitate the photosynthetic function assignment. Our results revealed a functional relationship between photosynthetic genes and their conserved neighboring genes observed by ‘Phylo score’, indicating their functions could be inferred from the genome neighborhood profile. Therefore, we created a new method for extracting patterns based on the genome neighborhood network (GNN) and applied them for the photosynthetic protein classification using ML algorithms. Random forest (RF) classifier using genome neighborhood-based features achieved the highest accuracy up to 87% in the classification of photosynthetic proteins and also showed better performance (Mathew’s correlation coefficient = 0.718) than other available tools including the sequence similarity search (0.447) and ML-based method (0.361). Furthermore, we demonstrated the ability of our model to identify novel photosynthetic proteins compared to the other methods. Our classifier is available at http://bicep2.kmutt.ac.th/photomod_standalone, https://bit.ly/2S0I2Ox and DockerHub: https://hub.docker.com/r/asangphukieo/photomod.

The Khmuic-speaking populations are believed to be the descendants of one of the earliest groups to settle in Mainland Southeast Asia. In Thailand, there are two agricultural Khmuic-speaking ethnic groups, the Khamu and Lua (Htin). These peoples primarily reside in scattered locations along the mountainous Thailand–Laos border in Nan province. In this study, we conducted genome-wide SNP analysis on 81 individuals from three Khamu and two Lua villages in northern Thailand. Our findings revealed that both the Khamu and Lua groups possess genetic structures that are distinct from other ethnicities in Southeast Asia, indicating a unique history of migration and settlement. Within the Khmuic group, the Khamu populations living in different locations exhibited similar genetic structures and displayed genetic affinities only with some hill-tribes and Tai-Kadai (Kra-Dai)-speaking groups in Thailand, suggesting potential intermixing or cultural exchange. Furthermore, the Lua people displayed a distinctive population structure, which could be attributed to the founder effect and endogamous marriage practices. Additionally, we discovered a relationship between the Khmuic-speaking populations in Thailand and a Neolithic ancient sample obtained from the Tham Pha Ling archaeological site in Laos. This study provides new insight into genetic substructure within the Khmuic-speaking people and their potential relationship to the indigenous inhabitants of Mainland Southeast Asia.

High-grade osteosarcoma (HGOS) is the most common primary malignant bone tumor in children and adolescents. Poor response to chemotherapy is linked to worse prognosis and increased risk of recurrence and metastasis. However, current assessment methods, such as tumor necrosis evaluation, are time-consuming and delay treatment decisions. Thus, identifying molecular pathways and predictive biomarkers is essential for guiding early therapeutic strategies. In this study, RNA-seq analysis of HGOS tissues revealed enrichment of cholesterol biosynthesis and mitotic pathways in poor responders. Additionally, high HMGCR expression, as analyzed from TCGA data, was associated with poor prognosis in sarcoma. Functional validation using SaOS-2 cells, which exhibited poor drug sensitivity and elevated HMGCR levels, demonstrated that simvastatin enhanced the efficacy of cisplatin and doxorubicin by inducing mitochondrial-mediated apoptosis and downregulating anti-apoptotic proteins. Simvastatin also reduced cell migration and invasion by suppressing epithelial–mesenchymal transition and extracellular matrix degradation. Mechanistically, simvastatin disrupted Ras prenylation and inhibited downstream oncogenic signaling pathways, including Akt/mTOR and Akt/GSK3, which regulate survival and metastasis-associated gene expression. These findings suggest that the cholesterol biosynthesis pathway particularly plays a critical role in chemoresistance and metastasis in HGOS and may serve as a promising predictive molecular target for guiding early therapeutic strategies.

Background/Objectives: The global SARS-CoV-2 outbreak has escalated into a critical public health emergency, with the spike glycoprotein S1 subunit of SARS-CoV-2 (spike-S1) linked to inflammation in lung tissue and immune cells. Luteolin, a flavone with anti-inflammatory properties, shows promise, but research on its effectiveness against long-COVID-related inflammation and spike protein-induced responses remains limited. This study aims to elucidate the underlying mechanisms of inflammation in THP-1 cells induced by the spike-S1. Additionally, it seeks to assess the potential of luteolin in mitigating inflammatory responses induced by the spike-S1 in a THP-1 macrophage model. Methods: The gene expression profiles of spike-S1 in THP-1 cells were analyzed by transcriptome sequencing. The inhibitory effect of luteolin on ER stress and inflammation in spike-S1-induced THP-1 cells was investigated using Western blotting, RT-PCR, and ELISA. Results: The candidate genes (CAMK2A, SIGLEC7, PPARGC1B, SEC22B, USP28, IER2, and TIRAP) were upregulated in the spike-S1-induced THP-1 group compared to the control group. Among these, calcium/calmodulin-dependent protein kinase II alpha (CAMK2A) was identified as the most promising molecule in spike-S1-induced THP-1 cells. Our results indicate that the spike S1 significantly increased the expression of ER-stress markers at both gene and protein levels. Luteolin significantly reduced ER stress by decreasing the expression of ER-stress marker genes and ER-stress marker proteins (p < 0.01). Additionally, luteolin exhibited anti-inflammatory properties upon spike S1-induction in THP-1 cells by significantly suppressing IL-6, IL-8, and IL-1β cytokine secretion in a dose-dependent manner (p < 0.05). Furthermore, our results revealed that luteolin exhibited the downregulation of the MAPK pathway, as evidenced by modulating the phosphorylation of p-ERK1/2, p-JNK and p-p38 proteins (p < 0.05). Conclusions: The results from this study elucidate the mechanisms by which the spike S1 induces inflammation in THP-1 cells and supports the use of naturally occurring bioactive compounds, like luteolin, against inflammation-related SARS-CoV-2 infection.

Background: The role of lipid-perturbing medications in cancer risk is unclear. Methods: We employed cis-Mendelian randomization and colocalization to evaluate the role of 5 lipid-perturbing drug targets (ANGPTL3, ANGPTL4, APOC3, CETP, and PCSK9) in risk of 5 cancers (breast, colorectal, head and neck, ovarian, and prostate). We triangulated findings using pre-diagnostic protein measures in prospective analyses in EPIC (977 colorectal cancer cases, 4080 sub-cohort members) and the UK Biobank (860 colorectal cancer cases, 50 177 controls). To gain mechanistic insight into the role of ANGPTL4 in carcinogenesis, we examined the impact of the ANGPTL4 p. E40K loss-of-function variant on differential gene expression in normal colon tissue in BarcUVa-Seq. Finally, we evaluated the association of colon tumor ANGPTL4 expression with cancer-specific mortality in TCGA. Results: In analysis of 78 473 cases and 107 143 controls, genetically proxied circulating ANGPTL4 inhibition was associated with reduced colorectal cancer risk (ORSD decrease = 0.76, 95% confidence interval [CI] = 0.66 to 0.89, P = 5.52 × 10−4, PPcolocalization = 0.83). This association was replicated using pre-diagnostic circulating ANGPTL4 concentrations in EPIC (hazard ratio [HR]log10 decrease = 0.91, 95% CI = 0.84 to 0.98, P = .01) and the UK Biobank (HRSD decrease = 0.93, 95% CI = 0.86 to 0.99, P = .03). In gene-set enrichment analysis of differential gene expression in 445 colon tissue samples, ANGPTL4 loss-of-function down-regulated several cancer-related biological pathways (PFDR < .05), including those involved in cellular proliferation, epithelial-to-mesenchymal transition, and bile acid metabolism. In analysis of 465 colon cancer patients, lower ANGPTL4 tumor expression was associated with reduced colorectal cancer-specific mortality risk (HRlog2 decrease = 0.66, 95% CI = 0.50 to 0.87, P = 2.92 × 10−3). Conclusions: Our integrative proteogenomic and observational analyses suggest a potential protective role of lower circulating ANGPTL4 concentrations in colorectal cancer risk. These findings support further evaluation of ANGPTL4 as a therapeutic target for colorectal cancer prevention.