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Through their involvement in cancer metabolism, alanine aminotransferase (ALAT), aspartate aminotransferase (ASAT), γ-glutamyltransferase (GGT) and lactate dehydrogenase (LDH) reflect the tumor burden and thus could have a prognostic potential for patients treated with immune checkpoint inhibitors (CPI). Therefore, this study investigated the prognostic potential of these parameters in a real-world cohort of patients with metastatic renal cell cancer (mRCC) under first-line CPI-based therapy. The retrospective study cohort included 82 mRCC patients treated with CPI-based first-line therapy between 2019 and 2023. Progression-free survival (PFS), overall survival (OS) and response rates were evaluated according to baseline levels and early dynamic changes of ALAT, ASAT, GGT and LDH. Multivariate Cox proportional hazard regression models were generated to identify independent prognosticators for PFS and OS. High baseline levels and non-normalized kinetics of ALAT, ASAT, GGT and LDH were significantly associated with shorter PFS and OS (p < 0.05), which was also reflected by lower response rates. Combining the four parameters at baseline into a 4-Risk-Score resulted in an enhanced prognostic power, as indicated by a higher C-index of 0.693 for OS compared to the individual parameters (≤ 0.663). Patients with all four risk factors present showed the worst PFS and OS. Overall, baseline levels and early kinetics of the four parameters as well as the 4-Risk-Score were identified as independent prognosticators for PFS and OS by multivariate analysis. As standard laboratory parameters, ALAT, ASAT, GGT and LDH are cost-effective and could be easily used either alone or in combination for therapy monitoring of CPI-treated mRCC patients. [ABSTRACT FROM AUTHOR]

Introduction: Pancreatic ductal adenocarcinoma (PDAC) is a lethal cancer with a poor survival outcome. Predicting patient survival allows physicians to tailor treatments to specific individuals. Thus, a simple and cost-effective prognosis model is sorely needed. Methods: This retrospective study assesses the prognostic value of blood biomarkers in advanced and metastatic PDAC patients (n=96) from Spain. Cut-off points for hematological parameters were calculated and correlated with overall survival (OS) using Kaplan-Meier, log-rank test, robust Cox proportional hazards and logistic regressions. Results: In univariate analysis, individuals with low levels of GGT, LDH, ALP, leukocyte-, neutrophil- and monocyte counts showed significantly longer survival than patients with higher levels. In multivariate analysis, lower levels of GGT (HR (95%CI), 2.734 (1.223-6.111); p=0.014), LDH (HR (95%CI), 1.876 (1.035-3.400); p=0.038) and monocyte count (HR (95%CI), 1.657 (1.095-2.506); p = 0.017) remained significantly beneficial. In consequence, we propose a prognostic model based on logistic regression (AUC=0.741) of these three biomarkers as a pioneer tool to estimate OS in PDAC. Conclusion: This study has demonstrated that the joint use of GGT (<92.00), LDH (<220.00) and monocyte count (<800) are independent positive prognostic factors in PDAC that can predict one-year survival in a novel prognostic logistic model. [ABSTRACT FROM AUTHOR]

Sodium is crucial for maintaining cardiovascular health, especially in relation to heart failure. The impact of baseline serum sodium concentrations on the outcomes of newly diagnosed coronary heart disease (CHD) without heart failure remains unclear. This prospective cohort study included 681 patients who were newly diagnosed with CHD. Cox proportional hazards models and restricted cubic spline (RCS) analysis were used to assess the relationship between serum sodium concentrations and major adverse cardiovascular events. The improvement in traditional prediction models by the addition of serum sodium concentrations was assessed using changes in the C-statistic, net reclassification improvement (NRI), and integrated discrimination improvement (IDI). During a median follow-up of 51.04 months (IQR: 40.88–53.80 months), 131 events were recorded. Multivariate Cox proportional hazards models showed that the L2 group (136–138.9 mmol/L) had the highest MACE risk. Compared to L2, the hazard ratios (HRs) and 95% confidence intervals (CIs) for the L1 (130–135.9 mmol/L), L3 (139–140.9 mmol/L), L4 (141–142.9 mmol/L), and L5 (143–147.0 mmol/L) groups were 0.31 (0.14–0.70, P = 0.005), 0.48 (030–0.78, P = 0.003), 0.56 (0.34–0.92, P = 0.022), and 0.37 (0.22–0.64, P < 0.001), respectively. Including serum sodium concentrations in the prediction model significantly improved the C-statistic from 0.647 to 0.679 (P = 0.022), with an NRI of 0.338 (P < 0.001) and an IDI of 0.026 (P < 0.001). RCS analysis showed a nonlinear relationship: within the 130–138 mmol/L sodium range, MACE risk gradually increased with higher sodium levels (HR 1.39, 95% CI 1.09–1.76, P = 0.008); whereas within the 138–147 mmol/L range, the risk gradually decreased (HR 0.88, 95% CI 0.80–0.98, P = 0.014). Baseline serum sodium concentrations are significantly associated with long-term cardiovascular risk in newly diagnosed CHD patients, showing an inverted U-shaped relationship, whereas low serum sodium may be specifically linked to higher risks of death and nonfatal myocardial infarction. Further research is needed to explore the impact of long-term changes in serum sodium concentrations on disease prognosis. [ABSTRACT FROM AUTHOR]

Aims Methods Results Conclusion Loss of heterozygosity in chromosome 9p21, common in urothelial carcinoma (UC), typically involves deletion of CDKN2A and MTAP genes. MTAP loss is emerging as a promising therapeutic target and predictive biomarker in UC. This single‐centrre retrospective study examined the incidence of CDKN2A deletions and MTAP loss in muscle‐invasive bladder cancer (MIBC) and metastatic urothelial carcinoma (mUC), investigating their correlations with clinical, pathological, and genomic features, as well as patient outcomes.Fluorescence in situ hybridization (FISH) and immunohistochemistry (IHC) were performed on 302 MIBC specimens and 63 biopsy‐proven metachronous urothelial metastases to assess CDKN2A deletions and MTAP protein expression.CDKN2A homozygous deletion (HD), identified in 30.3% of MIBCs, and MTAP loss, found in 28.8% of MIBCs, were both significantly associated with the luminal‐URO subtype, FGFR3 mutations, and normal/wildtype p53 IHC (P < 0.05). Loss of MTAP expression was significantly correlated with CDKN2A HD, with 84.0% sensitivity, 92.3% negative predictive value (NPV), 96.3% specificity, and 91.9% positive predictive value (PPV). MTAP expression was 100% concordant between primary tumours and nodal metastases. Patients with MTAP loss had a higher incidence of visceral metastases (50%) compared to bone/soft tissue (35.7%) and nodes (14.3%). Mean progression‐free survival and overall survival were shorter for patients with MTAP loss, although not statistically significant.Our findings highlight CDKN2A HD and MTAP loss as prevalent genetic alterations in MIBC and mUC, particularly within the luminal‐URO subtype and FGFR3‐mutated, p53‐normal/wildtype tumours. MTAP IHC can serve as a surrogate marker for 9p21.3 HD, highlighting its clinical relevance and potential as a therapeutic target and predictive biomarker in MIBC. [ABSTRACT FROM AUTHOR]

Objectives: Lung adenocarcinoma (LUAD) continues to pose a significant global health challenge. This research investigates cuproptosis and its association with LUAD progression. Employing various bioinformatics techniques, the study explores the heterogeneity of LUAD cells, identifies prognostic cuproptosis-related genes (CRGs), examines cell-to-cell communication networks, and assesses their functional roles. Methods: We downloaded single-cell RNA sequencing data from TISCH2 and bulk RNA sequencing data from TCGA for exploring LUAD cell heterogeneity. Subsequently, "CellChat" package was employed for intercellular communication network analysis, while weighted correlation network analysis was applied for identification of hub CRGs. Further, A cuproptosis related prognostic signature was constructed via LASSO regression, validated through survival analysis, nomogram development, and ROC curves. We assessed immune infiltration, gene mutations, and GSEA of prognostic CRGs. Finally, in vitro experiments were applied to validate CDC25C's role in LUAD. Results: We identified 15 clusters and nine cell type in LUAD. Malignant cells showed active communication and pathway enrichment in "oxidative phosphorylation" and "glycolysis". Meanwhile, prognostic hub CRGs including PFKP, CDC25C, F12, SIGLEC6, and NLRP7 were identified, with a robust prognostic signature. Immune infiltration, gene mutations, and functional enrichment correlated with prognostic CRGs. In vitro cell experiments have shown that CDC25C-deficient LUAD cell lines exhibited reduced activity. Conclusion: This research reveals the heterogeneity of LUAD cells, identifies key prognostic CRGs, and maps intercellular communication networks, providing insights into LUAD pathogenesis. These findings pave the way for developing targeted therapies and precision medicine approaches. [ABSTRACT FROM AUTHOR]

Background: There has been a rise in endometrial cancer (EC) incidence leading to increased mortality. To counter this trend, improving the stratification of post-surgery recurrence risk and anticipating disease relapse and treatment resistance is essential. Liquid biopsy analyses offer a promising tool for these clinical challenges, though the best strategy for applying them in EC must be defined. This study was designed to determine the value of cfDNA/ctDNA monitoring in improving the clinical management of patients with localized and recurrent disease. Methods: Plasma samples and uterine aspirates (UA) from 198 EC patients were collected at surgery and over time. The genetic landscape of UAs was characterized using targeted sequencing. Total cfDNA was analyzed for ctDNA presence based on the UA mutational profile. Results: High cfDNA levels and detectable ctDNA at baseline correlated with poor prognosis for DFS (p-value < 0.0001; HR = 9.25) and DSS (p-value < 0.0001; HR = 11.20). This remained clinically significant when stratifying tumors by histopathological risk factors. Of note, cfDNA/ctDNA analyses discriminated patients with early post-surgery relapse and the ctDNA kinetics served to identify patients undergoing relapse before any clinical evidence emerged. Conclusions: This is the most comprehensive study on cfDNA/ctDNA characterization in EC, demonstrating its value in improving risk stratification and anticipating disease relapse in patients with localized disease. CtDNA kinetics assessment complements current strategies to monitor the disease evolution and the treatment response. Therefore, implementing cfDNA/ctDNA monitoring in clinical routines offers a unique opportunity to improve EC management. Translational relevance: The study demonstrates that high levels of cfDNA and detectable ctDNA at baseline are strong indicators of poor prognosis. This enables more accurate risk stratification beyond traditional histopathological factors, allowing clinicians to identify high-risk patients who may benefit from more aggressive treatment and closer monitoring. Moreover, longitudinal analysis of cfDNA/ctDNA can detect disease recurrence months before clinical symptoms or imaging evidence appear. This early warning system offers a significant advantage in clinical practice, providing a window of opportunity for early intervention and potentially improving patient outcomes. [ABSTRACT FROM AUTHOR]

Background: In the era of tyrosine kinase inhibitor (TKI) treatment, the progression of chronic myeloid leukemia (CML) remains a significant clinical challenge, and genetic biomarkers for the early identification of CML patients at risk for progression are limited. This study explored whether essential circular RNAs (circRNAs) can be used as biomarkers for diagnosing and monitoring CML disease progression and assessing CML prognosis. Methods: Peripheral blood (PB) samples were collected from 173 CML patients (138 patients with chronic phase CML [CML-CP] and 35 patients with accelerated phase/blast phase CML [CML-AP/BP]) and 63 healthy controls (HCs). High-throughput RNA sequencing (RNA-Seq) was used to screen dysregulated candidate circRNAs for a circRNA signature associated with CML disease progression. Quantitative real-time PCR (qRT-PCR) was used for preliminary verification and screening of candidate dysregulated genes, as well as subsequent exploration of clinical applications. Receiver operating characteristic (ROC) curve analysis, Spearman's rho correlation test, and the Kaplan-Meier method were used for statistical analysis. Results: The aberrant expression of hsa_circ_0006010 and hsa_circ_0002903 during CML progression could serve as valuable biomarkers for differentiating CML-AP/BP patients from CMP-CP patients or HCs. In addition, the expression levels of hsa_circ_0006010 and hsa_circ_0002903 were significantly associated with the clinical features of CML patients but were not directly related to the four scoring systems. Furthermore, survival analysis revealed that high hsa_circ_0006010 expression and low hsa_circ_0002903 expression indicated poor progression-free survival (PFS) in CML patients. Finally, PB hsa_circ_0006010 and hsa_circ_0002903 expression at diagnosis may also serve as disease progression surveillance markers for CML patients but were not correlated with PB BCR-ABL1/ABL1IS. Conclusions: Our study demonstrated that PB levels of hsa_circ_0006010 and hsa_circ_0002903 may serve as novel diagnostic, surveillance, and prognostic biomarkers for CML disease progression and may contribute to assisting in the diagnosis of CML patients at risk for progression and accurate management of advanced CML patients. [ABSTRACT FROM AUTHOR]

Extracellular adenosine is extensively involved in regulating the tumor microenvironment. Given the disappointing results of adenosine-targeted therapy trials, personalized treatment might be necessary, tailored to the microenvironment status of individual patients. Here, we introduce the adenosine signaling score (ADO-score) model using non-negative matrix fraction identified patient subtypes using publicly available melanoma dataset, which aimed to profile adenosine signaling-related genes and construct a model to predict prognosis. We analyzed 580 malignant melanoma samples and demonstrated its robust value for prognosis. Further investigation in immune checkpoint inhibitor dataset suggests its potential as a stratified factor of immune checkpoint inhibitor efficacy. We validated the power of the ADO-score at the protein level immunofluorescence in a melanoma cohort from Xiangya Hospital. More importantly, single-cell and spatial transcriptomic data highlighted the cell-specific expression patterns of adenosine signaling-related genes and the existence of adenosine signaling-mediated crosstalk between tumor cells and immune cells in melanoma. Our study reveals a robust connection between adenosine signaling and clinical benefits in melanoma patients and proposes a universally applicable adenosine signaling model, the ADO-score, in gene expression profiles and histological sections. This model enables us to more precisely and conveniently select patients who are likely to benefit from immunotherapy. [ABSTRACT FROM AUTHOR]

AbstractThis 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: 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. Objectives: 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. Design: A series of questions articulating essential criteria for extrapolation. Methods: 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. Results: 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. Conclusion: 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. [ABSTRACT FROM AUTHOR]

Simple Summary: Non-small cell lung cancer (NSCLC) remains the leading cause of cancer-related mortality. This study investigates the clinical interest of whole exome sequencing for analyzing somatic mutational signatures in patients with advanced or metastatic NSCLC treated with the current standard of care. Investigating somatic mutational signatures as well as structural variations, we evaluated the association between genomic features and patient outcomes in a cohort of 132 patients. This study identified specific signatures associated with poor response to immune checkpoint inhibitor (ICI) therapy and chemotherapy, potentially aiding treatment selection and identifying patients unlikely to benefit from these approaches. Background: Non-small cell lung cancer (NSCLC) remains the leading cause of cancer-related mortality. This study investigates the clinical interest of whole exome sequencing (WES) for analyzing somatic mutational signatures in patients with advanced or metastatic NSCLC treated with the current standard of care. Methods: Exome sequencing data and clinical characteristics from 132 patients with advanced or metastatic NSCLC were analyzed. Somatic mutational signatures including single base substitutions (SBSs), double base substitutions (DBSs), and copy number signatures were evaluated. Structural variations including tumor mutational burden (TMB), the number of neoantigens, TCR clonality, homologous recombination deficiency (HRD), copy number alterations (CNAs), and microsatellite instability (MSI) score were determined. The association between these genomic features, NSCLC subtypes, and patient outcomes (progression-free and overall survival) was evaluated. Conclusions: Exome sequencing offers valuable insights into somatic mutational signatures in NSCLC. This study identified specific signatures associated with a poor response to immune checkpoint inhibitor (ICI) therapy and chemotherapy, potentially aiding treatment selection and identifying patients unlikely to benefit from these approaches. [ABSTRACT FROM AUTHOR]

BACKGROUND Sepsis is a severe, life-threatening condition characterized by systemic inflammation and multiorgan dysfunction. Identifying reliable biomarkers for early diagnosis and prognosis is crucial for improving patient outcomes. The Blood Urea Nitrogen to Albumin Ratio (BUN/Alb) has emerged as a potential indicator of sepsis severity. This study aims to evaluate the BUN/Alb ratio's utility in predicting outcomes in septic patients in Bengaluru, India. METHODS We conducted a retrospective study involving 200 sepsis patients admitted to a tertiary care hospital in Bengaluru between January 2023 and December 2023. Data were collected from electronic medical records, including BUN, albumin levels, and clinical outcomes. Statistical analyses were performed to assess the correlation between BUN/Alb ratios and patient outcomes, including mortality and length of hospital stay. RESULTS The average BUN/Alb ratio in the study population was found to be significantly higher in patients with severe sepsis compared to those with mild to moderate sepsis. A higher BUN/Alb ratio was associated with increased mortality and longer hospital stays. The ratio demonstrated predictive value for adverse outcomes, with an area under the ROC curve of 0.9. CONCLUSION The BUN/Alb ratio is a promising biomarker for assessing the severity of sepsis and predicting patient outcomes. This study supports its utility in clinical practice, especially in resource-limited settings where sophisticated diagnostic tools may not be available. Further prospective studies are recommended to validate these findings and explore the ratio's potential for guiding treatment decisions. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Purpose: Quantification of Ki67 in breast cancer is a well-established prognostic and predictive marker, but inter-laboratory variability has hampered its clinical usefulness. This study compares the prognostic value and reproducibility of Ki67 scoring using four automated, digital image analysis (DIA) methods and two manual methods. Methods: The study cohort consisted of 367 patients diagnosed between 1990 and 2004, with hormone receptor positive, HER2 negative, lymph node negative breast cancer. Manual scoring of Ki67 was performed using predefined criteria. DIA Ki67 scoring was performed using QuPath and Visiopharm® platforms. Reproducibility was assessed by the intraclass correlation coefficient (ICC). ROC curve survival analysis identified optimal cutoff values in addition to recommendations by the International Ki67 Working Group and Norwegian Guidelines. Kaplan–Meier curves, log-rank test and Cox regression analysis assessed the association between Ki67 scoring and distant metastasis (DM) free survival. Results: The manual hotspot and global scoring methods showed good agreement when compared to their counterpart DIA methods (ICC > 0.780), and good to excellent agreement between different DIA hotspot scoring platforms (ICC 0.781–0.906). Different Ki67 cutoffs demonstrate significant DM-free survival (p < 0.05). DIA scoring had greater prognostic value for DM-free survival using a 14% cutoff (HR 3.054–4.077) than manual scoring (HR 2.012–2.056). The use of a single cutoff for all scoring methods affected the distribution of prediction outcomes (e.g. false positives and negatives). Conclusion: This study demonstrates that DIA scoring of Ki67 is superior to manual methods, but further study is required to standardize automated, DIA scoring and definition of a clinical cut-off. [ABSTRACT FROM AUTHOR]

Aims: Soluble fms‐like tyrosine kinase‐1 (sFlt‐1) and placental growth factor (PlGF), components of the vascular endothelial growth factor (VEGF) system, play key roles in angiogenesis. Reports of elevated plasma levels of sFlt‐1 and PlGF in coronary heart disease and heart failure (HF) led us to investigate their utility, and VEGF system gene single nucleotide polymorphisms (SNPs), as prognostic biomarkers in HF. Methods and results: ELISA assays for sFlt‐1, PlGF and N‐terminal pro‐B‐type natriuretic peptide (NT‐proBNP) were performed on baseline plasma samples from the PEOPLE cohort (n = 890), a study of outcomes among patients after an episode of acute decompensated HF. Eight SNPs potentially associated with sFlt‐1 or PlGF levels were genotyped. sFlt‐1 and PlGF were assayed in 201 subjects from the Canterbury Healthy Volunteers Study (CHVS) matched to PEOPLE participants. All‐cause death was the major endpoint for clinical outcome considered. In PEOPLE participants, mean plasma levels for both sFlt‐1 (125 ± 2.01 pg/ml) and PlGF (17.5 ± 0.21 pg/ml) were higher (both p < 0.044) than in the CHVS cohort (81.2 ± 1.31 pg/ml and 15.5 ± 0.32 pg/ml, respectively). sFlt‐1 was higher in HF with reduced ejection fraction compared to HF with preserved ejection fraction (p = 0.005). The PGF gene SNP rs2268616 was univariately associated with death (p = 0.016), and was also associated with PlGF levels, as was rs2268614 genotype. Cox proportional hazards modelling (n = 695, 246 deaths) showed plasma sFlt‐1, but not PlGF, predicted survival (hazard ratio 6.44, 95% confidence interval 2.57–16.1; p < 0.001) in PEOPLE, independent of age, NT‐proBNP, ischaemic aetiology, diabetic status and beta‐blocker therapy. Conclusions: Plasma sFlt‐1 concentrations have potential as an independent predictor of survival and may be complementary to established prognostic biomarkers in HF. [ABSTRACT FROM AUTHOR]

Simple Summary: This study evaluates DDR biomarkers in 222 node-positive early breast cancer patients from a Phase III trial on adjuvant taxanes. Over a 234-month follow-up period, no differences in DFS or OS were observed between treatment groups. However, a DDR risk score, influenced by ATM and ATR expression, proved to be an independent prognostic factor for both DFS and OS. Validation in a public cohort confirmed ATM's protective role. These findings highlight the importance of DDR pathways in breast cancer prognostication and support, integrating molecular markers with clinical–pathological factors to inform treatment strategies. 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. [ABSTRACT FROM AUTHOR]

Laminin is an extracellular matrix molecule that is the major component of the basement membrane and plays a key role in regulating various processes. However, the association between the laminin gene family and the prognosis of pancreatic carcinoma has not been systematically investigated. The role of the laminin gene family in pancreatic cancer was evaluated using data from the TCGA database. The effects of different expressions of members of the laminin gene family on pancreatic cancer survival were compared, and their primary cellular roles were examined. The effects of different expressions of positive family genes on proliferation, metastasis, and invasion, as well as EMT and ferroptosis in pancreatic cancer, were also examined. Based on univariate and multifactorial analysis of pancreatic cancer patients, LAMA3 was identified as an independent prognostic factor for overall survival in pancreatic cancer. LAMA3 was found to be enriched in the actin cytoskeleton, P53 signaling pathway, adhesion molecule junctions, pentose phosphate pathway, and regulatory differences in the cell cycle and focal adhesion. Additionally, high expression of LAMA3 was found to promote cancer proliferation, invasion, and metastasis, facilitate the EMT process, and inhibit ferroptosis. Our results identified LAMA3 was associated with the prognosis of patients with pancreatic cancer and may serve as a prognostic biomarker for pancreatic cancer. [ABSTRACT FROM AUTHOR]

Abstract Through their involvement in cancer metabolism, alanine aminotransferase (ALAT), aspartate aminotransferase (ASAT), γ-glutamyltransferase (GGT) and lactate dehydrogenase (LDH) reflect the tumor burden and thus could have a prognostic potential for patients treated with immune checkpoint inhibitors (CPI). Therefore, this study investigated the prognostic potential of these parameters in a real-world cohort of patients with metastatic renal cell cancer (mRCC) under first-line CPI-based therapy. The retrospective study cohort included 82 mRCC patients treated with CPI-based first-line therapy between 2019 and 2023. Progression-free survival (PFS), overall survival (OS) and response rates were evaluated according to baseline levels and early dynamic changes of ALAT, ASAT, GGT and LDH. Multivariate Cox proportional hazard regression models were generated to identify independent prognosticators for PFS and OS. High baseline levels and non-normalized kinetics of ALAT, ASAT, GGT and LDH were significantly associated with shorter PFS and OS (p

Abstract Extracellular adenosine is extensively involved in regulating the tumor microenvironment. Given the disappointing results of adenosine-targeted therapy trials, personalized treatment might be necessary, tailored to the microenvironment status of individual patients. Here, we introduce the adenosine signaling score (ADO-score) model using non-negative matrix fraction identified patient subtypes using publicly available melanoma dataset, which aimed to profile adenosine signaling-related genes and construct a model to predict prognosis. We analyzed 580 malignant melanoma samples and demonstrated its robust value for prognosis. Further investigation in immune checkpoint inhibitor dataset suggests its potential as a stratified factor of immune checkpoint inhibitor efficacy. We validated the power of the ADO-score at the protein level immunofluorescence in a melanoma cohort from Xiangya Hospital. More importantly, single-cell and spatial transcriptomic data highlighted the cell-specific expression patterns of adenosine signaling-related genes and the existence of adenosine signaling-mediated crosstalk between tumor cells and immune cells in melanoma. Our study reveals a robust connection between adenosine signaling and clinical benefits in melanoma patients and proposes a universally applicable adenosine signaling model, the ADO-score, in gene expression profiles and histological sections. This model enables us to more precisely and conveniently select patients who are likely to benefit from immunotherapy.

Abstract Background There has been a rise in endometrial cancer (EC) incidence leading to increased mortality. To counter this trend, improving the stratification of post-surgery recurrence risk and anticipating disease relapse and treatment resistance is essential. Liquid biopsy analyses offer a promising tool for these clinical challenges, though the best strategy for applying them in EC must be defined. This study was designed to determine the value of cfDNA/ctDNA monitoring in improving the clinical management of patients with localized and recurrent disease. Methods Plasma samples and uterine aspirates (UA) from 198 EC patients were collected at surgery and over time. The genetic landscape of UAs was characterized using targeted sequencing. Total cfDNA was analyzed for ctDNA presence based on the UA mutational profile. Results High cfDNA levels and detectable ctDNA at baseline correlated with poor prognosis for DFS (p-value

Abstract Objectives Lung adenocarcinoma (LUAD) continues to pose a significant global health challenge. This research investigates cuproptosis and its association with LUAD progression. Employing various bioinformatics techniques, the study explores the heterogeneity of LUAD cells, identifies prognostic cuproptosis-related genes (CRGs), examines cell-to-cell communication networks, and assesses their functional roles. Methods We downloaded single-cell RNA sequencing data from TISCH2 and bulk RNA sequencing data from TCGA for exploring LUAD cell heterogeneity. Subsequently, “CellChat” package was employed for intercellular communication network analysis, while weighted correlation network analysis was applied for identification of hub CRGs. Further, A cuproptosis related prognostic signature was constructed via LASSO regression, validated through survival analysis, nomogram development, and ROC curves. We assessed immune infiltration, gene mutations, and GSEA of prognostic CRGs. Finally, in vitro experiments were applied to validate CDC25C’s role in LUAD. Results We identified 15 clusters and nine cell type in LUAD. Malignant cells showed active communication and pathway enrichment in “oxidative phosphorylation” and “glycolysis”. Meanwhile, prognostic hub CRGs including PFKP, CDC25C, F12, SIGLEC6, and NLRP7 were identified, with a robust prognostic signature. Immune infiltration, gene mutations, and functional enrichment correlated with prognostic CRGs. In vitro cell experiments have shown that CDC25C-deficient LUAD cell lines exhibited reduced activity. Conclusion This research reveals the heterogeneity of LUAD cells, identifies key prognostic CRGs, and maps intercellular communication networks, providing insights into LUAD pathogenesis. These findings pave the way for developing targeted therapies and precision medicine approaches.

Abstract 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.

Abstract Sodium is crucial for maintaining cardiovascular health, especially in relation to heart failure. The impact of baseline serum sodium concentrations on the outcomes of newly diagnosed coronary heart disease (CHD) without heart failure remains unclear. This prospective cohort study included 681 patients who were newly diagnosed with CHD. Cox proportional hazards models and restricted cubic spline (RCS) analysis were used to assess the relationship between serum sodium concentrations and major adverse cardiovascular events. The improvement in traditional prediction models by the addition of serum sodium concentrations was assessed using changes in the C-statistic, net reclassification improvement (NRI), and integrated discrimination improvement (IDI). During a median follow-up of 51.04 months (IQR: 40.88–53.80 months), 131 events were recorded. Multivariate Cox proportional hazards models showed that the L2 group (136–138.9 mmol/L) had the highest MACE risk. Compared to L2, the hazard ratios (HRs) and 95% confidence intervals (CIs) for the L1 (130–135.9 mmol/L), L3 (139–140.9 mmol/L), L4 (141–142.9 mmol/L), and L5 (143–147.0 mmol/L) groups were 0.31 (0.14–0.70, P = 0.005), 0.48 (030–0.78, P = 0.003), 0.56 (0.34–0.92, P = 0.022), and 0.37 (0.22–0.64, P

Abstract Most TRIM family members characterized by the E3-ubiquitin ligases, participate in ubiquitination and tumorigenesis. While there is a dearth of a comprehensive investigation for the entire family in gastric cancer (GC). By combining the TCGA and GEO databases, common TRIM family members (TRIMs) were obtained to investigate gene expression, gene mutations, and clinical prognosis. On the basis of TRIMs, a consensus clustering analysis was conducted, and a risk assessment system and prognostic model were developed. Particularly, TRIM31 with clinical prognostic and diagnostic value was chosen for single-gene bioinformatics analysis, in vitro experimental validation, and immunohistochemical analysis of clinical tissue microarrays. The combined dataset consisted of 66 TRIMs, of which 52 were differentially expressed and 43 were differentially prognostic. Significant survival differences existed between the gene clusters obtained by consensus clustering analysis. Using 4 differentially expressed genes identified by multivariate Cox regression and LASSO regression, a risk scoring system was developed. Higher risk scores were associated with a poorer prognosis, suppressive immune cell infiltration, and drug resistance. Transcriptomic data and clinical sample tissue microarrays confirmed that TRIM31 was highly expressed in GC and associated with a poor prognosis. Pathway enrichment analysis, cell migration and colony formation assay, EdU assay, reactive oxygen species (ROS) assay, and mitochondrial membrane potential assay revealed that TRIM31 may be implicated in cell cycle regulation and oxidative stress-related pathways, contribute to gastric carcinogenesis. This study investigated the whole functional and expression profile and a risk score system based on the TRIM family in GC. Further investigation centered around TRIM31 offers insight into the underlying mechanisms of action exhibited by other members of its family in the context of GC.

Abstract Prolyl 4-hydroxylases (P4Hs) are a family of key modifying enzymes in collagen synthesis. P4Hs have been confirmed to be closely associated with tumor occurrence and development. However, the expression of P4Hs in head and neck cancer (HNSC) as well as its relationship with prognosis and tumor immunity infiltration has not yet been analyzed. We investigated the transcriptional expression, survival data, and immune infiltration of P4Hs in patients with HNSC from multiple databases. P4H1-3 expression was significantly higher in HNSC tumor tissues than in normal tissues. Moreover, P4HA1 and P4HA2 were associated with tumor stage, patient prognosis, and immune cell infiltration. P4HA3 was related to patient prognosis and immune cell infiltration. Correlation experiments confirmed that P4HA1 may serve as a prognosis biomarker and plays a role in the progression of nasopharyngeal carcinoma. These findings suggest that P4HA1-3 may be a novel biomarker for the prognosis and treatment of HNSC, which is expected to support the development of new therapies for patients with head and neck tumors and improve patient outcomes.

Most TRIM family members characterized by the E3-ubiquitin ligases, participate in ubiquitination and tumorigenesis. While there is a dearth of a comprehensive investigation for the entire family in gastric cancer (GC). By combining the TCGA and GEO databases, common TRIM family members (TRIMs) were obtained to investigate gene expression, gene mutations, and clinical prognosis. On the basis of TRIMs, a consensus clustering analysis was conducted, and a risk assessment system and prognostic model were developed. Particularly, TRIM31 with clinical prognostic and diagnostic value was chosen for single-gene bioinformatics analysis, in vitro experimental validation, and immunohistochemical analysis of clinical tissue microarrays. The combined dataset consisted of 66 TRIMs, of which 52 were differentially expressed and 43 were differentially prognostic. Significant survival differences existed between the gene clusters obtained by consensus clustering analysis. Using 4 differentially expressed genes identified by multivariate Cox regression and LASSO regression, a risk scoring system was developed. Higher risk scores were associated with a poorer prognosis, suppressive immune cell infiltration, and drug resistance. Transcriptomic data and clinical sample tissue microarrays confirmed that TRIM31 was highly expressed in GC and associated with a poor prognosis. Pathway enrichment analysis, cell migration and colony formation assay, EdU assay, reactive oxygen species (ROS) assay, and mitochondrial membrane potential assay revealed that TRIM31 may be implicated in cell cycle regulation and oxidative stress-related pathways, contribute to gastric carcinogenesis. This study investigated the whole functional and expression profile and a risk score system based on the TRIM family in GC. Further investigation centered around TRIM31 offers insight into the underlying mechanisms of action exhibited by other members of its family in the context of GC. [ABSTRACT FROM AUTHOR]

Bladder cancer prognosis remains a pressing clinical challenge, necessitating the identification of novel biomarkers for precise survival prediction and improved quality of life outcomes. This study proposes a comprehensive strategy to uncover key prognostic biomarkers in bladder cancer using DNA methylation analysis and extreme survival pattern observations in matched pairs of cancer and adjacent normal cells. Unlike traditional approaches that overlook cancer heterogeneity by analyzing entire samples, our methodology leverages patient-matched samples to account for this variability. Specifically, DNA methylation profiles from adjacent normal bladder tissue and bladder cancer tissue collected from the same individuals were analyzed to pinpoint critical methylation changes specific to cancer cells while mitigating confounding effects from individual genetic differences. Utilizing differential threshold settings for methylation levels within cancer-associated pathways enabled the identification of biomarkers that significantly impact patient survival. Our analysis identified distinct survival patterns associated with specific CpG sites, underscoring these sites' pivotal roles in bladder cancer outcomes. By hypothesizing and testing the influence of methylation levels on survival, we pinpointed CpG biomarkers that profoundly affect the prognosis. Notably, CpG markers, such as cg16269144 (PRKCZ), cg16624272 (PTK2), cg11304234, and cg26534425 (IL18), exhibited critical methylation thresholds that correlate with patient mortality. This study emphasizes the importance of tailored approaches to enhancing prognostic accuracy and refining therapeutic strategies for bladder cancer patients. The identified biomarkers pave the way for personalized prognostication and targeted interventions, promising advancements in bladder cancer management and patient care. [ABSTRACT FROM AUTHOR]

Objective: Immune checkpoint inhibitors (ICIs), specifically targeting the programmed cell death protein-1 or its ligand (PD-1/PD-L1), have been extensively used in the treatment of a spectrum of malignancies, although the predictive biomarkers remain to be elucidated. This study aims to investigate the association between baseline circulating levels of cytokines and the creatinine/cystatin C ratio (CCR) with the treatment outcomes of ICIs in patients with advanced cancer. Methods: The pre-treatment circulating levels of 10 cytokines (PD-L1, CTLA4, CXCL10, LAG3, HGF, CCL2, MIG, GRANB, IL-18, and IL-6) were measured via automated capillary-based immunoassay platform in the serum of 65 advanced cancer patients treated with anti-PD-1/PD-L1-based systemic therapy and 10 healthy volunteers. The levels of cytokines and CCR were quantified and categorized into high and low groups based on the median value. The associations of serum cytokines and CCR with response to treatment, survival, and immune-related adverse events were assessed. Results: Elevated circulating levels of 6 cytokines (PD-L1, CXCL10, HGF, CCL2, MIG, and IL-6) were observed in cancer patients compared with that in healthy volunteers. The correlation coefficients between cytokines, CCR and nutritional risk index were also calculated. In the cancer cohort (N = 65), low circulating HGF (P = 0.023, P = 0.029), low IL-6 (P = 0.002, P < 0.001), and high CCR (P = 0.031, P = 0.008) were associated with significantly improved progression-free survival (PFS) and overall survival (OS). Multi-variable COX analyses adjusted for clinicopathological factors revealed that low HGF, low IL-6, and high CCR were independent favorable prognostic factors for PFS (P = 0.028, P = 0.010, and P = 0.015, respectively) and OS (P = 0.043, P = 0.003, and P = 0.026, respectively). Grade 2 irAEs occurred more frequently in patients with low levels of circulating CCL2 and LAG3. Conclusions: Pre-treatment circulating levels of serum IL-6, HGF, and CCR may serve as independent predictive and prognostic biomarkers in advanced cancer patients treated with ICIs-based systemic therapy. These findings might help to identify potential patients who would benefit from these therapies. [ABSTRACT FROM AUTHOR]

Introduction: Cross‐talk among biological pathways is essential for normal biological function and plays a significant role in cancer progression. Through integrated network analysis, this study explores the significance of pathway cross‐talk in colorectal cancer (CRC) development at both the pathway and gene levels. Methods: In this study, we integrated the gene expression data with domain knowledge to construct state‐dependent pathway cross‐talk networks. The significance of the genes involved in pathway cross‐talk was assessed by analyzing their association with cancer hallmarks, disease‐gene relation, genetic alterations, and survival analysis. We also analyzed the gene regulatory network to identify the dysregulated genes and their role in CRC progression. Results: Cross‐talk was observed between immune‐related pathways and pathways associated with cell communication and signaling. The PTPRC gene was identified as a mediator, facilitating interactions within the immune system and other signaling pathways. The rewired interactions of ITGA7 were identified as influential in the epithelial‐mesenchymal transition in CRC. This study also highlighted the crucial link between cell communication and vascular smooth muscle contraction pathway in CRC progression. The survival analysis of identified gene clusters showed their significant prognostic value in distinguishing high‐risk from low‐risk CRC groups, and L1000CDS2 revealed seven potential drug molecules in CRC. Nine dysregulated genes (CTNNB1, EP300, JUN, MYC, NFKB1, RELA, SP1, STAT1, and TP53) emerge as transcription factors acting as common regulators across various pathways. Conclusions: This study highlights the crucial role of pathway cross‐talk in CRC progression and identified the potential prognostic biomarkers and potential drug molecules. [ABSTRACT FROM AUTHOR]

Immunotherapy represents a significant and essential component of renal carcinoma therapy (RCC), but the selection of an optimal regimen for an individual patient remains unclear. Despite significant improvements in therapeutic options for RCC, predictive biomarkers for immunotherapeutic agents remain elusive. Neopterin is a biomarker of cell-mediated immune response, with concentrations increased in different disorders, including cancer. High neopterin levels herald, in general, a poor prognosis. This review briefly overviews the contemporary clinical data on biomarkers in metastatic RCC therapy, focusing on neopterin. Elevated neopterin levels have been observed in tumors of different primary locations. Research indicates that neopterin may serve as a potential biomarker for assessing the inflammatory status associated with certain cancers. However, it is necessary to interpret neopterin levels in the context of a comprehensive clinical evaluation, as elevated neopterin alone is not specific to cancer and can be influenced by other factors, including comorbid conditions. Neopterin has also been identified as a prognostic biomarker. An increasing neopterin level in serum and urine is associated with advanced cancer, but the role as a potential predictor of response to immunotherapy has yet to be established. A reliable biomarker for optimal therapy selection in metastatic RCC is still putative. [ABSTRACT FROM AUTHOR]

Prolyl 4-hydroxylases (P4Hs) are a family of key modifying enzymes in collagen synthesis. P4Hs have been confirmed to be closely associated with tumor occurrence and development. However, the expression of P4Hs in head and neck cancer (HNSC) as well as its relationship with prognosis and tumor immunity infiltration has not yet been analyzed. We investigated the transcriptional expression, survival data, and immune infiltration of P4Hs in patients with HNSC from multiple databases. P4H1-3 expression was significantly higher in HNSC tumor tissues than in normal tissues. Moreover, P4HA1 and P4HA2 were associated with tumor stage, patient prognosis, and immune cell infiltration. P4HA3 was related to patient prognosis and immune cell infiltration. Correlation experiments confirmed that P4HA1 may serve as a prognosis biomarker and plays a role in the progression of nasopharyngeal carcinoma. These findings suggest that P4HA1-3 may be a novel biomarker for the prognosis and treatment of HNSC, which is expected to support the development of new therapies for patients with head and neck tumors and improve patient outcomes. [ABSTRACT FROM AUTHOR]

Objective: This research was aimed to comprehensively investigate the expression levels, diagnostic and prognostic implications, and the relationship with immune infiltration of G2 and S phase‐expressed‐1 (GTSE1) across 33 tumor types, including lung adenocarcinoma (LUAD), through gene expression profiling. Methods: GTSE1 mRNA expression data together with clinical information were acquired from Xena database of The Cancer Genome Atlas (TCGA), ArrayExpress, and Gene Expression Omnibus (GEO) database for this study. The Wilcoxon rank‐sum test was used to detect differences in GTSE1 expression between groups. The ability of GTSE1 to accurately predict cancer status was evaluated by calculating the area under the curve (AUC) value for the receiver operating characteristic curve. Additionally, we investigated the predictive value of GTSE1 in individuals diagnosed with neoplasms using univariate Cox regression analysis as well as Kaplan–Meier curves. Furthermore, the correlation between GTSE1 expression and levels of immune infiltration was assessed by utilizing the Tumor Immune Estimate Resource (TIMER) database to calculate the Spearman rank correlation coefficient. Finally, the pan‐cancer analysis findings were validated by examining the association between GTSE1 expression and prognosis among patients with LUAD. Results: GTSE1 exhibited significantly increased expression levels in a wide range of tumor tissues in contrast with normal tissues (p < 0.05). The expression of GTSE1 in various tumors was associated with clinical features, overall survival, and disease‐specific survival (p < 0.05). In immune infiltration analyses, a strong correlation of the level of immune infiltration with the expression of GTSE1 was observed. Furthermore, GTSE1 demonstrated good discriminative and diagnostic value for most tumors. Additional experiments confirmed the relationship between elevated GTSE1 expression and unfavorable prognosis in individuals diagnosed with LUAD. These findings indicated the crucial role of GTSE1 expression level in influencing the development and immune infiltration of different types of tumors. Conclusions: GTSE1 might be a potential biomarker for the prognosis of pan‐cancer. Meanwhile, it represented a promising target for immunotherapy. [ABSTRACT FROM AUTHOR]

Introduction. Adjuvant durvalumab has become a standard treatment protocol for patients with locally advanced non-small cell lung cancer (LA-NSCLC). However, there is still limited knowledge about prognostic factors in a real-world setting across this specific patient group. Materials and methods. In our single-center retrospective study, we evaluated 45 patients to identify predictors of overall survival (OS) in LA-NSCLC. We utilized the univariable Cox proportional hazards models, and we developed multivariable Cox models after adjusting for the known clinical predictors. Results. In univariable analysis nodal status, the percentage of basophils in peripheral blood before treatment and D-dimers were associated with OS. Multivariable analysis, adjusted for age, sex, T characteristics, and nodal status revealed that the percentage of basophils is a significant predictor of OS. A higher percentage of basophils was associated with improved OS (HR = 0.077, 95% CI: 0.007-0.853, p = 0.037). Conclusions. Our study indicates that a lower serum percentage of basophils may be associated with better OS in patients with LA-NSCLC. These findings should be validated in larger cohorts. [ABSTRACT FROM AUTHOR]

Simple Summary: This review summarizes the pivotal role of tumor-infiltrating immune cells (TIICs) within the tumor microenvironment (TME) and their impact on cancer prognosis and treatment response. By analyzing TIICs alongside tumor mutation burden (TMB) and immune checkpoint inhibitor (ICI) scores, this study reveals insights into cancer's immune landscapes. Understanding TIICs' influence enables tailored cancer treatments, aiding postoperative care, therapy decisions, and personalized medicine choices. We effectively examined the predictive and prognostic value of TIICs alongside TMB and ICI scores in identifying the diverse immunological environments of cancer. Several approaches discussed in this review provide more accurate predictions of patient outcomes and treatment responses. These models can help identify individuals who may derive greater benefit from adjuvant or neoadjuvant treatment. In summary, we believe that the major contribution of TIICs in cancer will have a substantial positive impact on postoperative follow-up, therapy, interventions, and the ability to make educated decisions regarding personalized cancer treatments. This comprehensive study underscores the significant role of TIICs in combating tumor-mediated immunosuppression and fostering antitumor immune responses, promising improved cancer prognosis and therapeutic outcomes. TIICs are critical components of the TME and are used to estimate prognostic and treatment responses in many malignancies. TIICs in the tumor microenvironment are assessed and quantified by categorizing immune cells into three subtypes: CD66b+ tumor-associated neutrophils (TANs), FoxP3+ regulatory T cells (Tregs), and CD163+ tumor-associated macrophages (TAMs). In addition, many cancers have tumor-infiltrating M1 and M2 macrophages, neutrophils (Neu), CD4+ T cells (T-helper), CD8+ T cells (T-cytotoxic), eosinophils, and mast cells. A variety of clinical treatments have linked tumor immune cell infiltration (ICI) to immunotherapy receptivity and prognosis. To improve the therapeutic effectiveness of immune-modulating drugs in a wider cancer patient population, immune cells and their interactions in the TME must be better understood. This study examines the clinicopathological effects of TIICs in overcoming tumor-mediated immunosuppression to boost antitumor immune responses and improve cancer prognosis. We successfully analyzed the predictive and prognostic usefulness of TIICs alongside TMB and ICI scores to identify cancer's varied immune landscapes. Traditionally, immune cell infiltration was quantified using flow cytometry, immunohistochemistry, gene set enrichment analysis (GSEA), CIBERSORT, ESTIMATE, and other platforms that use integrated immune gene sets from previously published studies. We have also thoroughly examined traditional limitations and newly created unsupervised clustering and deconvolution techniques (SpatialVizScore and ProTICS). These methods predict patient outcomes and treatment responses better. These models may also identify individuals who may benefit more from adjuvant or neoadjuvant treatment. Overall, we think that the significant contribution of TIICs in cancer will greatly benefit postoperative follow-up, therapy, interventions, and informed choices on customized cancer medicines. [ABSTRACT FROM AUTHOR]

Osteosarcoma, the primary bone cancer in adolescents and young adults, is notorious for its aggressive growth and metastatic potential. Our study delved into the prognostic impact of inflammasome‐related gene signatures in osteosarcoma patients, employing comprehensive genetic profiling to uncover signatures linked with patient outcomes. We identified three patient subgroups through consensus clustering, with one showing worse survival rates correlated with high FGFR3 and RARB expressions. Immune profiling revealed significant immune cell infiltration differences among these subgroups, affecting survival. Utilising advanced machine learning, including StepCox and gradient boosting machine algorithms, we developed a prognostic model with a notable c‐index of 0.706, highlighting CD36 and MYD88 as key genes. Higher inflammasome risk scores from our model were associated with poorer survival, corroborated across datasets. In vitro experiments validated CD36 and MYD88's roles in promoting osteosarcoma cell proliferation, invasion and migration, emphasising their therapeutic potential. This research offers new insights into inflammasomes' role in osteosarcoma, introducing novel biomarkers for risk assessment and potential therapeutic targets. Our findings suggest a pathway towards personalised treatment strategies, potentially improving patient outcomes in osteosarcoma. [ABSTRACT FROM AUTHOR]

Gastric adenocarcinoma (STAD) is characterized by high heterogeneity and aggressiveness, leading to poor prognostic outcomes worldwide. This study explored the prognostic significance of lactylation-related gene sets and mitochondrial functions in STAD by integrating large-scale genomic datasets, including TCGA and several GEO datasets. We utilized Spatial transcriptomics and single-cell RNA sequencing to delineate the tumor microenvironment and assess the heterogeneity of cellular responses within the tumor. Additionally, the study identified distinct molecular subtypes within STAD that correspond with unique survival outcomes and immune profiles, enhancing the molecular classification beyond current paradigms. Prognostic models incorporating these molecular markers demonstrated superior predictive capabilities over existing models across multiple validation datasets. Furthermore, our analysis of immune landscapes revealed that variations in lactylation could influence immune cell infiltration and responsiveness, pointing towards novel avenues for tailored immunotherapy approaches. These comprehensive insights provide a foundation for targeted therapeutic strategies and underscore the potential of metabolic and immune modulation in improving STAD treatment outcomes.

Summary: Background: 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. Methods: 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. Findings: Baseline serum NfL is a powerful prognostic biomarker, predicting survival and ALSFRS-R rate of decline. Serum NfL 100 pg/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. Interpretation: 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. Funding: NIH (U01-NS107027, U54-NS092091). ALSA (16-TACL-242).

IntroductionPancreatic ductal adenocarcinoma (PDAC) is a lethal cancer with a poor survival outcome. Predicting patient survival allows physicians to tailor treatments to specific individuals. Thus, a simple and cost-effective prognosis model is sorely needed.MethodsThis retrospective study assesses the prognostic value of blood biomarkers in advanced and metastatic PDAC patients (n=96) from Spain. Cut-off points for hematological parameters were calculated and correlated with overall survival (OS) using Kaplan-Meier, log-rank test, robust Cox proportional hazards and logistic regressions.ResultsIn univariate analysis, individuals with low levels of GGT, LDH, ALP, leukocyte-, neutrophil- and monocyte counts showed significantly longer survival than patients with higher levels. In multivariate analysis, lower levels of GGT (HR (95%CI), 2.734 (1.223-6.111); p=0.014), LDH (HR (95%CI), 1.876 (1.035-3.400); p=0.038) and monocyte count (HR (95%CI), 1.657 (1.095-2.506); p = 0.017) remained significantly beneficial. In consequence, we propose a prognostic model based on logistic regression (AUC=0.741) of these three biomarkers as a pioneer tool to estimate OS in PDAC.ConclusionThis study has demonstrated that the joint use of GGT (

The high mortality rate due to chemoresistance in patients with high-grade ovarian cancer (HGSOC) emphasizes the urgent need to determine optimal treatment strategies for advanced and recurrent cases. Our study investigates the interplay between estrogens and chemoresistance in HGSOC and shows clear differences between platinum-sensitive and -resistant tumors. Through comprehensive transcriptome analyzes, we uncover differences in the expression of genes of estrogen biosynthesis, metabolism, transport and action underlying platinum resistance in different tissues of HGSOC subtypes and in six HGSOC cell lines. Furthermore, we identify genes involved in estrogen biosynthesis and metabolism as prognostic biomarkers for HGSOC. Additionally, our study elucidates different patterns of estrogen formation/metabolism and their effects on cell proliferation between six HGSOC cell lines with different platinum sensitivity. These results emphasize the dynamic interplay between estrogens and HGSOC chemoresistance. In particular, targeting the activity of steroid sulfatase (STS) proves to be a promising therapeutic approach with potential efficacy in limiting estrogen-driven cell proliferation. Our study reveals potential prognostic markers as well as identifies novel therapeutic targets that show promise for overcoming resistance and improving treatment outcomes in HGSOC.

Pancreatic cancer is a type of gastrointestinal tumor with a growing incidence and mortality worldwide. Pancreatic ductal adenocarcinoma (PDAC) constitutes 90% of cases, and late-stage diagnosis is common, leading to a 5-year survival rate of less than 10% in high-income countries. The use of biomarkers has different proven translational applications, facilitating early diagnosis, accurate prognosis and identification of potential therapeutic targets. Several studies have shown a correlation between the tissue expression levels of various molecules, measured through immunohistochemistry (IHC), and survival rates in PDAC. Following the hallmarks of cancer, epigenetic and metabolic reprogramming, together with immune evasion and tumor-promoted inflammation, plays a critical role in cancer initiation and development. In this study, we aim to explore via IHC and Kaplan–Meier analyses the prognostic value of various epigenetic-related markers (histones 3 and 4 (H3/H4), histone acetyl transferase 1 (HAT-1), Anti-Silencing Function 1 protein (ASF1), Nuclear Autoantigenic Sperm Protein (NASP), Retinol Binding Protein 7 (RBBP7), importin 4 (IPO4) and IPO5), metabolic regulators (Phosphoglycerate mutase (PGAM)) and inflammatory mediators (allograft inflammatory factor 1 (AIF-1), interleukin 10 (IL-10), IL-12A and IL-18) in patients with PDAC. Also, through a correlation analysis, we have explored the possible interconnections in the expression levels of these molecules. Our results show that higher expression levels of these molecules are directly associated with poorer survival rates in PDAC patients, except in the case of IL-10, which shows an inverse association with mortality. HAT1 was the molecule more clearly associated with mortality, with a hazard risk of 21.74. The correlogram demonstrates an important correlation between almost all molecules studied (except in the case of IL-18), highlighting potential interactions between these molecules. Overall, our study demonstrates the relevance of including different markers from IHC techniques in order to identify unexplored molecules to develop more accurate prognosis methods and possible targeted therapies. Additionally, our correlation analysis reveals potential interactions among these markers, offering insights into PDAC’s pathogenesis and paving the way for targeted therapies tailored to individual patient profiles. Future studies should be conducted to confirm the prognostic value of these components in PDAC in a broader sample size, as well as to evaluate the possible biological networks connecting them.

Background: Prostate cancer, the second most prevalent malignancy among men, poses a significant threat to affected patients’ well-being due to its poor prognosis. Novel biomarkers are required to enhance clinical outcomes and tailor personalized treatments. Herein, we describe our research to explore the prognostic value of long non-coding RNAs (lncRNAs) deregulated by copy number variations (CNVs) in prostate cancer. Methods: The study employed an integrative multi-omics data analysis of the prostate cancer transcriptomic, CNV and methylation datasets to identify prognosis-related subtypes. Subtype-specific expression profiles of protein-coding genes (PCGs) and lncRNAs were determined. We analysed CNV patterns of lncRNAs across the genome to identify subtype-specific lncRNAs with CNV changes. LncRNAs exhibiting significant amplification or deletion and a positive correlation were designated CNV-deregulated lncRNAs. A prognostic risk score model was subsequently developed using these CNV-driven lncRNAs. Results: Six molecular subtypes of prostate cancer were identified, demonstrating significant differences in prognosis (P = 0.034). The CNV profiles of subtype-specific lncRNAs were examined, revealing their correlation with CNV amplification or deletion. Six lncRNAs (CCAT2, LINC01593, LINC00276, GACAT2, LINC00457, LINC01343) were selected based on significant CNV amplifications or deletions using a rigorous univariate Cox proportional risk regression model. A robust risk score model was developed, stratifying patients into high-risk and low-risk categories. Notably, our prognostic model based on these six lncRNAs exhibited exceptional predictive capabilities for recurrence-free survival (RFS) in prostate cancer patients (P = 0.024). Conclusions: Our study successfully identified a prognostic risk score model comprising six CNV-driven lncRNAs that could potentially be prognostic biomarkers for prostate cancer. These lncRNA signatures are closely associated with RFS, providing promising prospects for improved patient prognostication and personalized therapeutic strategies for novel prostate cancer treatment.

Abstract Background Shugoshin-1 (SGOL1) is a mammalian ortholog of Shugoshin in yeast and is essential for precise chromosome segregation during mitosis and meiosis. Aberrant SGOL1 expression was reported to be closely correlated with the malignant progression of various tumors. However, the expression pattern and biological function of SGOL1 in clear cell renal cell carcinoma (ccRCC) are unclear. Methods The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases provide mRNA expression data and outcome information for ccRCC patients. Immunohistochemistry (IHC) of ccRCC tissue chips verified SGOL1 protein expression in ccRCC patients. Data processing and visualization were performed with the UALCAN, TISIDB, TIMER, GSCA, LinkedOmics, and starBase databases. Gene Ontology (GO) annotation and gene set enrichment analysis (GSEA) were used to identify SGOL1-related biological functions and signaling pathways. Immune infiltration analysis was performed using the TISIDB database, ssGSEA algorithm, and TCGA-KIRC cohort. The biological role of SGOL1 in ccRCC was investigated using a series of in vitro cytological assays, including the MTT assay, EdU staining assay, flow cytometry analysis, Transwell assay, and wound healing assay. Results SGOL1 was highly expressed in ccRCC and linked to adverse clinicopathological parameters and unfavorable prognosis. Multivariate logistic regression and nomogram calibration suggested that SGOL1 might serve as an independent and reliable prognostic predictor of ccRCC. Functional enrichment analysis indicated that SGOL1 may be involved in the cell cycle, the p53 pathway, DNA replication, and T-cell activation. Furthermore, tumor microenvironment (TME) analysis suggested that SGOL1 was positively associated with Treg infiltration and immune checkpoint upregulation. In addition, we identified a potential SNHG17/PVT1/ZMIZ1-AS1-miR-23b-3p-SGOL1 axis correlated with ccRCC carcinogenesis and progression. Finally, we demonstrated that SGOL1 promoted ccRCC cell proliferation, migratory capacity, and invasion in vitro. Conclusions SGOL1 potentially functions as an oncogene in ccRCC progression and might contribute to the immunosuppressive TME by increasing Treg infiltration and checkpoint expression, suggesting that targeting SGOL1 could be a novel therapeutic strategy for the treatment of ccRCC patients.

Lei Feng,1,&ast; Ning Zhang,1,&ast; Lan Luo,1,&ast; Jie Liu,1,&ast; Yong Yao,1,&ast; Ming-Sheng Gao,1,&ast; Jin Pan,1,&ast; Cai He2 1The Division of Gastroenterology and Hepatology, Suining Central Hospital, Suining City, Sichuan Province, People’s Republic of China; 2The Division of Gastroenterology and Hepatology, Yibin Second People’s Hospital, Yibin City, Sichuan Province, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Lei Feng, The Division of Gastroenterology and Hepatology, Suining Central Hospital, Suining City, Sichuan Province, People’s Republic of China, Tel +8618008258982, Email fenglei822@163.comBackground: Several studies suggest that Proteasome 26S Subunit, ATPase (PSMC) family genes are of great importance in tumor progression and spreading, but the study for systematic evaluation of the function of PSMC genes in hepatocellular carcinoma (HCC) is currently lacking.Methods: The functions of PSMC genes in HCC were analyzed using multiple online databases, including the TCGA database, GEO database, HPA database, cBioPortal database, DAVID, and KEGG pathway. Experiments were later conducted to verify PSMC expression.Results: High levels of PSMC gene expression were detected in HCC tissues and PSMCs exhibited potentially powerful abilities in diagnosing HCC patients. All PSMC proteins are expressed to varying degrees in HCC tissues and high expression of the PSMC genes lead to poor prognosis in patients with HCC. Moreover, DNA methylation involves the regulation of the expression of PSMC2 and PSMC5 in HCC, and the levels of methylation of PSMC2 or PSMC5 correlate positively with patient overall survival in HCC patients. The copy number alteration and mutation of PSMC genes were observed and related to the expression of PSMCs in HCC. Functional enrichment analysis showed that many highly co-expressed genes of PSMCs had a potential role in tumor progression and metastasis, which merited further in-depth study. Functional network analysis also suggests that the primary biological function of PSMC genes is the regulation of protein homeostasis and energy metabolism in HCC. Moreover, the expression levels of PSMCs are related to immune cell infiltrates and immunomodulatory factors in HCC.Conclusion: Our study indicates that PSMC genes are the potential target for precision immunotherapy and novel prognostic biomarkers for HCC.Keywords: Proteasome 26s Subunit, ATPase, PSMC, hepatocellular carcinoma, prognostic biomarkers, therapeutic targets

Colorectal cancer (CRC) raises considerable clinical challenges, including a high mortality rate once the tumor spreads to distant sites. At this advanced stage, more accurate prediction of prognosis and treatment outcome is urgently needed. The role of cancer immunity in metastatic CRC (mCRC) is poorly understood. Here, we explore cellular immune cell status in patients with multi-organ mCRC. We analyzed T cell infiltration in primary tumor sections, surveyed the lymphocytic landscape of liver metastases, and assessed circulating mononuclear immune cells. Besides asking whether immune cells are associated with survival at this stage of the disease, we investigated correlations between the different tissue types; as this could indicate a dominant immune phenotype. Taken together, our analyses corroborate previous observations that higher levels of CD8+ T lymphocytes link to better survival outcomes. Our findings therefore extend evidence from earlier stages of CRC to indicate an important role for cancer immunity in disease control even after metastatic spreading to multiple organs. This finding may help to improve predicting outcome of patients with mCRC and suggests a future role for immunotherapeutic strategies.

Background: R‐CHOP (rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone) is a standard first‐line treatment for diffuse large B‐cell lymphoma (DLBCL). However, 20%–40% of patients survive less than 5 years. Novel prognostic biomarkers remain in demand. Methods: Baseline plasma autoantibodies (AAbs) were assessed in 336 DLBCLs. In the discovery phase (n = 20), a high‐density antigen microarray (∼21,000 proteins) was used to expound AAb profiles. In the verification phase (n = 181), with a DLBCL‐focused microarray, comparative results based on event‐free survival at 24 months (EFS24) and lasso Cox regression models of progression‐free survival (PFS) and overall survival (OS) were integrated to identify potential biomarkers. They were further validated by enzyme‐linked immunosorbent assay in validation phase 1 (n = 135) and a dynamic cohort (n = 12). In validation phase 2, a two‐AAb‐based risk score was established. They were further validated in an immunohistochemistry cohort (n = 55) and four independent Gene Expression Omnibus datasets (n = 1598). Results: Four AAbs (CREB1, N4BP1, UBAP2, and DEAF1) were identified that showed associations with EFS24 status (p <.05) and superior PFS and OS (p <.05). A novel risk score model based on CREB1 and N4BP1 AAbs was developed to predict PFS with areas under the curve of 0.72, 0.71, 0.76, and 0.82 at 1, 3, 5, and 7 years, respectively, in DLBCL treated with R‐CHOP independent of the International Prognostic Index (IPI) and provided significant additional recurrence risk discrimination (p <.05) for the IPI. CREB1 and N4BP1 proteins and messenger RNAs were also associated with better PFS and OS (p <.05). Conclusions: This study identified a novel prognostic panel of CREB1, N4BP1, DEAF1, and UBAP2 AAbs that is independent of the IPI in DLBCL. Autoantibodies (AAbs) have the potential for personalized monitoring of tumor recurrence. Serological AAbs against N4BP1, CREB1, DEAF1, and UBAP2 were independent of International Prognostic Index traditional risk factors for diffuse large B‐cell lymphoma (DLBCL) treated with rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone. Notably, two of these biomarkers, CREB1 and N4BP1, exhibited prognostic significance at multiple levels, including messenger RNA, protein, and AAb. These findings suggest that monitoring AAb levels during treatment may be a useful tool for predicting prognosis and guiding personalized treatment strategies for patients with DLBCL. [ABSTRACT FROM AUTHOR]

Simple Summary: Epidemiologic evidence and previous research have established obesity, diabetes and the metabolic syndrome as risk factors for pancreatic cancer in humans, while the precise mechanisms remain incompletely characterized. The concept that these metabolic diseases may be driven by diet implies that many cancers could be prevented or delayed through lifestyle modifications. By design, genetically engineered mouse models expressing oncogenic mutants of KRAS protein within the epithelial cells of the pancreas closely recapitulate the human disease. Research on diet-induced obesity in such mice implies the involvement of diverse factors including elevated insulin/insulin-like growth factors, inflammation, and genetic/epigenetic alterations and has revealed dramatic acceleration of cancer incidence that was more marked in males than females. The present research uses proteomic and phosphoproteomic analysis as a foundation to assess differentially expressed proteins and associated signal transduction pathways, yielding further novel mechanistic insights into the influence of tumor microenvironment on diet-induced obesity-associated pancreatic cancer. Diet-induced obesity (DIO) promotes pancreatic ductal adenocarcinoma (PDAC) in mice expressing KRasG12D in the pancreas (KC mice), but the precise mechanisms remain unclear. Here, we performed multiplex quantitative proteomic and phosphoproteomic analysis by liquid chromatography–tandem mass spectrometry and further bioinformatic and spatial analysis of pancreas tissues from control-fed versus DIO KC mice after 3, 6, and 9 months. Normal pancreatic parenchyma and associated proteins were steadily eliminated and the novel proteins, phosphoproteins, and signaling pathways associated with PDAC tumorigenesis increased until 6 months, when most males exhibited cancer, but females did not. Differentially expressed proteins and phosphoproteins induced by DIO revealed the crucial functional role of matrisomal proteins, which implies the roles of upstream regulation by TGFβ, extracellular matrix-receptor signaling to downstream PI3K-Akt-mTOR-, MAPK-, and Yap/Taz activation, and crucial effects in the tumor microenvironment such as metabolic alterations and signaling crosstalk between immune cells, cancer-associated fibroblasts (CAFs), and tumor cells. Staining tissues from KC mice localized the expression of several prognostic PDAC biomarkers and elucidated tumorigenic features, such as robust macrophage infiltration, acinar–ductal metaplasia, mucinous PanIN, distinct nonmucinous atypical flat lesions (AFLs) surrounded by smooth muscle actin-positive CAFs, invasive tumors with epithelial–mesenchymal transition arising close to AFLs, and expanding deserted areas by 9 months. We next used Nanostring GeoMX to characterize the early spatial distribution of specific immune cell subtypes in distinct normal, stromal, and PanIN areas. Taken together, these data richly contextualize DIO promotion of Kras-driven PDAC tumorigenesis and provide many novel insights into the signaling pathways and processes involved. [ABSTRACT FROM AUTHOR]