This study examines the impact of estrogenic compounds like bisphenol A (BPA), estradiol (E2), and zearalenone (ZEA) on human ovarian cancer, focusing on constructing a risk model, conducting Gene Set Variation Analysis (GSVA), and evaluating immune infiltration. Differential gene expression analysis identified 980 shared differentially expressed genes (DEGs) in human ovarian cells exposed to BPA, E2, and ZEA, indicating disruptions in ribosome biogenesis and RNA processing. Using the Cancer Genome Atlas Ovarian Cancer (TCGA-OV) dataset, a least absolute shrinkage and selection operator (LASSO)-based risk model was developed incorporating prognostic genes 4-Hydroxyphenylpyruvate Dioxygenase Like (HPDL), Thy-1 Cell Surface Antigen (THY1), and Peptidase Inhibitor 3 (PI3). This model effectively stratified ovarian cancer patients into high-risk and low-risk categories, showing significant differences in overall survival, disease-specific survival, and progression-free survival. GSVA analysis linked HPDL expression to pathways related to the cell cycle, DNA damage, and repair, while THY1 and PI3 were associated with apoptosis, hypoxia, and proliferation pathways. Immune infiltration analysis revealed distinct immune cell profiles for high and low expression groups of HPDL, THY1, and PI3, indicating their influence on the tumor microenvironment. The findings demonstrate that estrogenic compounds significantly alter gene expression and oncogenic pathways in ovarian cancer. The risk model integrating HPDL, THY1, and PI3 offers a strong prognostic tool, with GSVA and immune infiltration analyses providing insights into the interplay between these genes and the tumor microenvironment, suggesting potential targets for personalized therapies.

Cholangiocarcinoma (CCA) is a heterogeneous and aggressive malignancy with limited therapeutic options and poor prognosis. The identification of reliable prognostic biomarkers and a deeper understanding of the molecular subtypes are critical for the development of targeted therapies and improvement of patient outcomes. This study aims to uncover oxidative stress-related genes (ORGs) in CCA and develop a prognostic risk model using comprehensive transcriptomic analysis from The Cancer Genome Atlas (TCGA). Through LASSO regression analysis, we identified prognosis-related ORGs and constructed a prognostic signature consisting of six ORGs. This signature demonstrated strong predictive performance in survival analysis and ROC curve assessment. Functional enrichment and GSEA analyses revealed significant enrichment of immune-related pathways among different risk groups. GSVA analysis indicated reduced activity in inflammation and oxidative stress pathways in the high-risk subgroup, and xCell results showed lower immune cell infiltration levels in this group. Additionally, immune checkpoint genes and immune-related pathways were downregulated in the high-risk subgroup. Our research has developed a unique prognostic model focusing on oxidative stress, enabling accurate forecasting of patient outcomes and providing crucial insights and recommendations for the prognosis of individuals with CCA. Future studies should aim to validate these findings in clinical settings and further explore therapeutic targets within oxidative stress pathways.

MDSCs (myeloid-derived suppressor cells) are crucial for immune system evasion in cancer. They accumulate in peripheral blood and tumor microenvironment, suppressing immune cells like T-cells, natural killer cells and dendritic cells. They promote tumor angiogenesis and metastasis by secreting cytokines and growth factors and contribute to a tumor-promoting environment. The accumulation of MDSCs in cancer patients has been linked to poor prognosis and resistance to various cancer therapies. Targeting MDSCs and their immunosuppressive mechanisms may improve treatment outcomes and enhance immune surveillance by developing drugs that inhibit MDSC function, by preventing their accumulation and by disrupting the tumor-promoting environment. This review presents a detailed overview of the MDSC research in cancer with regulation of their development and function. The relevance of MDSC as a prognostic and predictive biomarker in different types of cancers, along with recent advancements on the therapeutic approaches to target MDSCs are discussed in detail.

UNASSIGNED: Advances in targeted therapy development and tumor sequencing technology are reclassifying cancers into smaller biomarker-defined diseases. Randomized controlled trials (RCTs) are often impractical in rare diseases, leading to calls for single-arm studies to be sufficient to inform clinical practice based on a strong biological rationale. However, without RCTs, favorable outcomes are often attributed to therapy but may be due to a more indolent disease course or other biases. When the clinical benefit of targeted therapy in a common cancer is established in RCTs, this benefit may extend to rarer cancers sharing the same biomarker. However, careful consideration of the appropriateness of extending the existing trial evidence beyond specific cancer types is required. A framework for extrapolating evidence for biomarker-targeted therapies to rare cancers is needed to support transparent decision-making.
UNASSIGNED: To construct a framework outlining the breadth of criteria essential for extrapolating evidence for a biomarker-targeted therapy generated from RCTs in common cancers to different rare cancers sharing the same biomarker.
UNASSIGNED: A series of questions articulating essential criteria for extrapolation.
UNASSIGNED: The framework was developed from the core topics for extrapolation identified from a previous scoping review of methodological guidance. Principles for extrapolation outlined in guidance documents from the European Medicines Agency, the US Food and Drug Administration, and Australia\'s Medical Services Advisory Committee were incorporated.
UNASSIGNED: We propose a framework for assessing key assumptions of similarity of the disease and treatment outcomes between the common and rare cancer for five essential components: prognosis of the biomarker-defined cancer, biomarker test analytical validity, biomarker actionability, treatment efficacy, and safety. Knowledge gaps identified can be used to prioritize future studies.
UNASSIGNED: This framework will allow systematic assessment, standardize regulatory, reimbursement and clinical decision-making, and facilitate transparent discussions between key stakeholders in drug assessment for rare biomarker-defined cancers.

Heart failure with preserved ejection fraction (HFpEF) represents a complex clinical syndrome, often very difficult to diagnose using the available tools. As the global burden of this disease is constantly growing, surpassing the prevalence of heart failure with reduced ejection fraction, during the last few years, efforts have focused on optimizing the diagnostic and prognostic pathways using an immense panel of circulating biomarkers. After the paradigm of HFpEF development emerged more than 10 years ago, suggesting the impact of multiple comorbidities on myocardial structure and function, several phenotypes of HFpEF have been characterized, with an attempt to find an ideal biomarker for each distinct pathophysiological pathway. Acknowledging the limitations of natriuretic peptides, hundreds of potential biomarkers have been evaluated, some of them demonstrating encouraging results. Among these, soluble suppression of tumorigenesis-2 reflecting myocardial remodeling, growth differentiation factor 15 as a marker of inflammation and albuminuria as a result of kidney dysfunction or, more recently, several circulating microRNAs have proved their incremental value. As the number of emerging biomarkers in HFpEF is rapidly expanding, in this review, we aim to explore the most promising available biomarkers linked to key pathophysiological mechanisms in HFpEF, outlining their utility for diagnosis, risk stratification and population screening, as well as their limitations.

Oral squamous cell carcinoma (OSCC) has an extremely poor prognosis. Recent studies have suggested that mitophagy-related genes (MRGs) are closely correlated with the development and occurrence of cancer, but the role they play in oral cancer has not yet been explained.We conducted a comprehensive analysis of integrated single-cell and bulk RNA sequencing (RNA-seq) data retrieved from Gene Expression Omnibus (GEO) datasets and The Cancer Genome Atlas (TCGA) database. Multiple methods were combined to provide a comprehensive understanding of the genetic expression patterns and biology of OSCC, such as analysis of pseudotime series, CellChat cell communication, immune infiltration, Gene Ontology (GO), LASSO Cox regression, gene set variation analysis (GSVA), Kyoto Encyclopedia of Genes and Genomes (KEGG), gene set enrichment analysis (GSEA), Tumor Mutation Burden (TMB) and drug sensitivity assessments. The findings of this study demonstrated significantly greater activity of MRGs in NK cells than in other cells in OSCC. A reliable prognostic model was developed using 12 candidate genes strongly associated with mitochondrial autophagy. T stage, N stage and risk score were revealed as independent prognostic factors. Distinctively enriched pathways and immune cells were observed in different risk groups. Notably, low-risk patients were more responsive to chemotherapy. In addition, a nomogram model with excellent predictive ability was established by combining the risk scores and clinical features. The activity of MRGs suggest the potential for the development of new targeted therapies. The construction of a robust prognostic model also provides reference value for individualized prediction and clinical decision-making in patients with OSCC.

UNASSIGNED: With increasing recognition of the value of incorporating prognostic markers into amyotrophic lateral sclerosis (ALS) trial design and analysis plans, there is a pressing need to understand which among the prevailing clinical and biochemical markers have real value, and how they can be optimally used.
UNASSIGNED: A subset of patients with ALS recruited through the multi-center Phenotype-Genotype-Biomarker study (clinicaltrials.gov: NCT02327845) was identified as \"trial-like\" based on meeting common trial eligibility criteria. Clinical phenotyping was performed by evaluators trained in relevant assessments. Serum neurofilament light (NfL) and phosphorylated neurofilament heavy (pNfH), urinary p75ECD, plasma microRNA-181, and an array of biochemical and clinical measures were evaluated for their prognostic value. Associations with functional progression were estimated by random-slopes mixed models of ALS functional rating scale-revised (ALSFRS-R) score. Associations with survival were estimated by log-rank test and Cox proportional hazards regression. Potential sample size savings from adjusting for given biomarkers in a hypothetical trial were estimated.
UNASSIGNED: Baseline serum NfL is a powerful prognostic biomarker, predicting survival and ALSFRS-R rate of decline. Serum NfL <40pg/ml and >100pg/ml correspond to future ALSFRS-R slopes of ~0.5 and 1.5 points/month, respectively. Serum NfL also adds value to the best available clinical predictors, encapsulated by the European Network to Cure ALS (ENCALS) predictor score. In models of functional decline, the addition of NfL yields ~25% sample size saving above those achieved by inclusion of either clinical predictors or ENCALS score alone. The prognostic value of serum pNfH, urinary p75ECD, and plasma miR-181ab is more limited.
UNASSIGNED: Among the multitude of biomarkers considered, only blood NfL adds value to the ENCALS prediction model and should be incorporated into analysis plans for all ongoing and future ALS trials. Defined thresholds of NfL might also be used in trial design, for enrichment or stratified randomisation, to improve trial efficiency.
UNASSIGNED: NIH (U01-NS107027, U54-NS092091). ALSA (16-TACL-242).

Background This study aims to evaluate the prognostic significance of the modified Glasgow Prognostic Score (mGPS) in patients with metastatic colorectal cancer (mCRC). Methodology A retrospective analysis was conducted among 65 patients diagnosed with stage IV colorectal cancer who received treatment and follow-up at the Oncology Department of Elias Emergency University Hospital in Bucharest, Romania, from January 2016 to January 2024. Patient data were collected, including demographic information, tumor characteristics, and laboratory parameters. The mGPS was calculated based on serum albumin and C-reactive protein (CRP) levels. Patients were stratified into the following three mGPS categories: 0 (normal CRP and albumin), 1 (elevated CRP or hypoalbuminemia), and 2 (elevated CRP and hypoalbuminemia). Results Of the 65 patients included, 33 (50.8%) were male and 32 (49.2%) were female, with a mean age of 63.7 years. According to mGPS, 25 (38.5%) patients scored 0, 30 (46.2%) scored 1, and 10 (15.4%) scored 2. The median overall survival (OS) was 53 months (95% confidence interval (CI) = 23.512-82.488), and the median progression-free survival (PFS) was 23 months (95% CI = 19.244-26.756). Although numerical differences in the median PFS and OS were observed between treatment groups, these differences were not statistically significant (PFS: p = 0.292; OS: p = 0.5). Conclusions The mGPS is a useful prognostic tool in mCRC, providing insights into patient survival outcomes. However, further studies with larger sample sizes are needed to validate these findings and clarify the role of mGPS in guiding clinical decision-making for mCRC patients.

BACKGROUND: Gastric cancer is one of the most common malignant tumours of the gastrointestinal tract, which has a significant negative impact on human health.
OBJECTIVE: CCL chemokines play important roles in a variety of tumor microenvironments; nevertheless, gastric cancer has surprisingly limited associations with CCL chemokines.
METHODS: In our study, we comprehensively utilized bioinformatics analysis tools and databases such as cBioPortal, UALCAN, GEPIA, GeneMANIA, STRING, and TRRUST to clarify the clinical significance and biology function of CCL chemokines in gastric cancer.
RESULTS: The mRNA expression levels of CCL1/3/4/5/7/8/14/15/18/20/21/22/26 were up-regulated, while the mRNA expression levels of CCL2/11/13/16/17/19/23/24/25/28 were down-regulated. The chemokine significantly associated with the pathological stage of gastric cancer is CCL2/11/19/21. In gastric cancer, the expression level of CCL chemokines was not associated with disease-free survival, but low expression of CCL14 was significantly associated with longer overall survival. Therein, associated with the regulation of CCL chemokines are only 10 transcription factors (RELA, NFKB1, STAT6, IRF3, REL, SPI1, STAT1, STAT3, JUN and SP1). The major biological process and functional enrichment of CCL chemokines are to induce cell-directed migration.
CONCLUSIONS: These results may indicate that CCL chemokines may be immunotherapeutic targets and promising prognostic biomarkers for gastric cancer.

We assessed the impact of DNA damage response and repair (DDR) biomarker expressions in 222 node-positive early breast cancer (BC) patients from a previous Phase III GOIM 9902 trial of adjuvant taxanes. At a median follow-up of 64 months, the original study showed no disease-free survival (DFS) or overall survival (OS) differences with the addition of docetaxel (D) to epirubicine-cyclophosphamide (EC). Immunohistochemistry was employed to assess the expression of DDR phosphoproteins (pATM, pATR, pCHK1, γH2AX, pRPA32, and pWEE1) in tumor tissue, and their association with clinical outcomes was evaluated through the Cox elastic net model. Over an extended follow-up of 234 months, we confirmed no significant differences in DFS or OS between patients treated with EC and those receiving D → EC. A DDR risk score, inversely driven by ATM and ATR expression, emerged as an independent prognostic factor for both DFS (HR = 0.41, p < 0.0001) and OS (HR = 0.61, p = 0.046). Further validation in a public adjuvant BC cohort was possible only for ATM, confirming its protective role. Overall, our findings confirm the potential role of the DDR pathway in BC prognostication and in shaping treatment strategies advocating for an integrated approach, combining molecular markers with clinical-pathological factors.