Predictive and Prognostic Relevance of Tumor-Infiltrating Immune Cells: Tailoring Personalized Treatments against Different Cancer Types.

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.

Inflammasome-related gene signatures as prognostic biomarkers in osteosarcoma.

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.

GTSE1: A potential prognostic and diagnostic biomarker in various tumors including lung adenocarcinoma.

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.

Evaluation of cleaved caspase-3 and Ki-67 index on diagnostic biopsy in response to neoadjuvant chemotherapy in the context of post-treatment tumour ypT stage, ypN stage, grade, and molecular subtype.

Introduction: Breast carcinoma is a heterogeneous disease, characterised by diverse clinical behaviour. The aim of this study was to assess how cleaved caspase-3 and Ki-67 index, evaluated on diagnostic biopsy, are related to response to neoadjuvant chemotherapy in the context of molecular subtype, post-treatment tumour, N category, and grade. Material and methods: A retrospective analysis was carried out among 110 breast cancer patients. Ki-67 levels and caspase-3 expression on diagnostic biopsy were explored regarding their relation to tumour grade and molecular subtype, ypT, ypN categories, and T and N categories according to Sataloff tumour response evaluation. Results: A statistically significant relationship was found between Ki-67 levels and tumour grade K-W = 24.2932, p < 0.0001; molecular subtype K-W = 28.5439, p < 0.00000967538; size and invasion of the primary tumour after neoadjuvant chemotherapy K-W = 11.7944, p < 0.0377169; caspase-3 expression after neoadjuvant therapy, evaluated according to the Sataloff classification χ2 = 5.97, df = 1, p = 0.0145. Discussion: No significant difference was found between Ki-67 expression in patients with pathological complete response, compared to those with partial and no response, a statistically significant difference in cases with different molecular subtype, histology grade, and tumour stage after neoadjuvant therapy. Cleaved caspase-3-positive breast cancer cases are often better responders to neoadjuvant therapy, but with no significant correlation to molecular subtype, high-grade categories, or tumour stage. Conclusions: The caspase-3 and Ki-67 index on diagnostic biopsy are related to post-neoadjuvant treatment prognostic factors (ypT stage, grade), proving them useful for prediction of treatment response to neoadjuvant therapy and further patient management.

The Clinicopathological Significance of the Cyclin D1/E1-Cyclin-Dependent Kinase (CDK2/4/6)-Retinoblastoma (RB1/pRB1) Pathway in Epithelial Ovarian Cancers.

Cyclin-dependent kinases (CDK2, CDK4, CDK6), cyclin D1, cyclin E1 and phosphorylated retinoblastoma (pRB1) are key regulators of the G1/S cell cycle checkpoint and may influence platinum response in ovarian cancers. CDK2/4/6 inhibitors are emerging targets in ovarian cancer therapeutics. In the current study, we evaluated the prognostic and predictive significance of the CDK2/4/6-cyclin D1/E1-pRB1 axis in clinical ovarian cancers (OC). The CDK2/4/6, cyclin D1/E1 and RB1/pRB1 protein expression were investigated in 300 ovarian cancers and correlated with clinicopathological parameters and patient outcomes. CDK2/4/6, cyclin D1/E1 and RB1 mRNA expression were evaluated in the publicly available ovarian TCGA dataset. We observed nuclear and cytoplasmic staining for CDK2/4/6, cyclins D1/E1 and RB1/pRB1 in OCs with varying percentages. Increased nuclear CDK2 and nuclear cyclin E1 expression was linked with poor progression-free survival (PFS) and a shorter overall survival (OS). Nuclear CDK6 was associated with poor OS. The cytoplasmic expression of CDK4, cyclin D1 and cyclin E1 also has predictive and/or prognostic significance in OCs. In the multivariate analysis, nuclear cyclin E1 was an independent predictor of poor PFS. Tumours with high nuclear cyclin E1/high nuclear CDK2 have a worse PFS and OS. Detailed bioinformatics in the TCGA cohort showed a positive correlation between cyclin E1 and CDK2. We also showed that cyclin-E1-overexpressing tumours are enriched for genes involved in insulin signalling and release. Our data not only identified the prognostic/predictive significance of these key cell cycle regulators but also demonstrate the importance of sub-cellular localisation. CDK2 targeting in cyclin-E1-amplified OCs could be a rational approach.

Bioinformatics-driven identification of prognostic biomarkers in kidney renal clear cell carcinoma.

Renal cell carcinoma (RCC), particularly the clear cell subtype (ccRCC), poses a significant global health concern due to its increasing prevalence and resistance to conventional therapies. Early detection of ccRCC remains challenging, resulting in poor patient survival rates. In this study, we employed a bioinformatic approach to identify potential prognostic biomarkers for kidney renal clear cell carcinoma (KIRC). By analyzing RNA sequencing data from the TCGA-KIRC project, differentially expressed genes (DEGs) associated with ccRCC were identified. Pathway analysis utilizing the Qiagen Ingenuity Pathway Analysis (IPA) tool elucidated key pathways and genes involved in ccRCC dysregulation. Prognostic value assessment was conducted through survival analysis, including Cox univariate proportional hazards (PH) modeling and Kaplan-Meier plotting. This analysis unveiled several promising biomarkers, such as MMP9, PIK3R6, IFNG, and PGF, exhibiting significant associations with overall survival and relapse-free survival in ccRCC patients. Cox multivariate PH analysis, considering gene expression and age at diagnosis, further confirmed the prognostic potential of MMP9, IFNG, and PGF genes. These findings enhance our understanding of ccRCC and provide valuable insights into potential prognostic biomarkers that can aid healthcare professionals in risk stratification and treatment decision-making. The study also establishes a foundation for future research, validation, and clinical translation of the identified prognostic biomarkers, paving the way for personalized approaches in the management of KIRC.

Deciphering the prognostic landscape of osteosarcoma: Integrating the roles of hippo pathway genes, programmed cell death, and the tumor immune microenvironment.

Osteosarcoma is a highly aggressive cancer prevalent among adolescents and young adults, notorious for its tendency to metastasize to the lungs. This research delves into the molecular foundations of osteosarcoma by examining the role of the Hippo signaling pathway and its interaction with the tumor immune microenvironment (TME). Through analysis of transcriptomic data from the TARGET-OS dataset and control samples from GTEx, we identified a set of 131 genes that link high expression profiles in osteosarcoma with the Hippo pathway. A focused examination through univariate Cox regression analysis revealed eight key genes (DLG5, WNT11, TGFB2, DLG4, WNT16, ID2, WNT10B, and WNT10A) with a significant correlation to patient outcomes. Hierarchical clustering of these genes delineated two distinct patient groups with significantly different survival rates, a finding supported by Kaplan-Meier survival analysis. Further investigation into immune cell infiltration and expression profiles of immunoregulatory factors uncovered a notable pattern of immune evasion in the group with poorer prognosis, marked by reduced effector immune cell activity and lower levels of immunostimulatory factors. Single-cell sequencing highlighted the cellular diversity within osteosarcoma samples and identified markers differentiating malignant from nonmalignant cells, correlating these markers with prognostic risk scores. Our results emphasize the critical prognostic value of Hippo pathway genes and the TME in osteosarcoma, shedding light on new avenues for therapeutic intervention and patient-specific treatment strategies.

Comprehensive analysis of lung adenocarcinoma: Unveiling differential gene expression, survival-linked genes, subtype stratification, and immune landscape implications.

This study offers a detailed exploration of lung adenocarcinoma (LUAD), addressing its heterogeneity and treatment challenges through a multi-faceted analysis that includes gene expression, genetic subtyping, pathway analysis, immune assessment, and drug sensitivity. It identifies 165 genes with significant expression differences and 46 genes associated with survival, revealing insights into oxidative stress and autophagy. LUAD samples were divided into three subtypes using consensus clustering on these 46 genes, with distinct survival outcomes. Gene Set Enrichment Analysis (GSEA) on HALLMARK gene sets indicated pathway variations with survival implications. The immune landscape, analyzed using the CIBERSORT algorithm, showed different immune cell distributions across subtypes, with the first subtype exhibiting a better immune environment and survival prospects. Advanced machine learning techniques developed a risk model from a set of four genes, effectively categorizing patients into high and low-risk groups, validated through external datasets and analyses. This model linked lower risk scores to better clinical stages, with a higher mutation rate and potential immunotherapy benefits observed in the high-risk group. Drug sensitivity assessments highlighted varied treatment responses between risk groups, suggesting avenues for personalized therapy. This comprehensive analysis enhances the understanding of LUAD's molecular and clinical nuances, offering valuable insights for tailored treatment approaches.

Neopterin as a potential prognostic and predictive biomarker in metastatic renal cell carcinoma treated with immune checkpoint inhibitors.

INTRODUCTION: 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. AREAS COVERED: This review briefly overviews the contemporary clinical data on biomarkers in metastatic RCC therapy, focusing on neopterin. EXPERT OPINION: 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.

Programmed Death 1 and Cytotoxic T-Lymphocyte-Associated Protein 4 Gene Expression in Peripheral Blood Mononuclear Cells Can Serve as Prognostic Biomarkers for Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is a highly aggressive form of liver cancer with poor prognosis. The lack of reliable biomarkers for early detection and accurate diagnosis and prognosis poses a significant challenge to its effective clinical management. In this study, we investigated the diagnostic and prognostic potential of programmed cell death protein 1 (PD-1) and cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) expression in peripheral blood mononuclear cells (PBMCs) in HCC. PD-1 and CTLA-4 gene expression was analyzed comparatively using PBMCs collected from HCC patients and healthy individuals. The results revealed higher PD-1 gene expression levels in patients with multifocal tumors, lymphatic invasion, or distant metastasis than those in their control counterparts. However, conventional serum biomarkers of liver function do not exhibit similar correlations. In conclusion, PD-1 gene expression is associated with OS and PFS and CTLA-4 gene expression is associated with OS, whereas the serum biomarkers analyzed in this study show no significant correlation with survival in HCC. Hence, PD-1 and CTLA-4 expressed in PBMCs are considered potential prognostic biomarkers for patients with HCC that can facilitate prediction of malignancy, response to currently available HCC treatments, and overall survival.

Upregulated Matrisomal Proteins and Extracellular Matrix Mechanosignaling Underlie Obesity-Associated Promotion of Pancreatic Ductal Adenocarcinoma.

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 TGFß, 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.

Prognostic and predictive biomarkers with therapeutic targets in nonsmall-cell lung cancer: A 2023 update on current development, evidence, and recommendation.

BACKGROUND: Since the publication of the original work in 2014, significant progress has been made in the characterization of genomic alterations that drive oncogenic addiction of nonsmall cell lung cancer (NSCLC) and how the immune system can leverage non-oncogenic pathways to modulate therapeutic outcomes. This update evaluates and validates the recent and emerging data for prognostic and predictive biomarkers with therapeutic targets in NSCLC. DATA SOURCES: We performed a literature search from January 2015 to October 2023 using the keywords non-small cell lung cancer, clinical practice guidelines, gene mutations, genomic assay, immune cancer therapy, circulating tumor DNA, predictive and prognostic biomarkers, and targeted therapies. STUDY SELECTION AND DATA EXTRACTION: We identified, reviewed, and evaluated relevant clinical trials, meta-analyses, seminal articles, and published clinical practice guidelines in the English language. DATA SYNTHESIS: Regulatory-approved targeted therapies include those somatic gene alterations of EGFR ("classic" mutations, exon 20 insertion, and rare EGFR mutations), ALK, ROS1, BRAF V600, RET, MET, NTRK, HER2, and KRAS G12C. Data for immunotherapy and circulating tumor DNA in next-generation sequencing are considered emerging, whereas the predictive role for PIK3CA gene mutation is insufficient. CONCLUSIONS: Advances in sequencing and other genomic technologies have led to identifying novel oncogenic drivers, novel resistance mechanisms, and co-occurring mutations that characterize NSCLC, creating further therapeutic opportunities. The benefits associated with immunotherapy in the perioperative setting hold initial promise, with their long-term results awaiting.

microRNAs, oxidative stress, and genotoxicity as the main inducers in the pathobiology of cancer development.

Cancer is one of the most serious leading causes of death in the world. Many eclectic factors are involved in cancer progression including genetic and epigenetic alongside environmental ones. In this account, the performance and fluctuations of microRNAs are significant in cancer diagnosis and treatment, particularly as diagnostic biomarkers in oncology. So, microRNAs manage and control the gene expression after transcription by mRNA degradation, or also they can inhibit their translation. Conspicuously, these molecular structures take part in controlling the cellular, physiological and pathological functions, which many of them can accomplish as tumor inhibitors or oncogenes. Relatively, Oxidative stress is defined as the inequality between the creation of reactive oxygen species (ROS) and the body's ability to detoxify the reactive mediators or repair the resulting injury. ROS and microRNAs have been recognized as main cancer promoters and possible treatment targets. Importantly, genotoxicity has been established as the primary reason for many diseases as well as several malignancies. The procedures have no obvious link with mutagenicity and influence the organization, accuracy of the information, or fragmentation of DNA. Conclusively, mutations in these patterns can lead to carcinogenesis. In this review article, we report the impressive and practical roles of microRNAs, oxidative stress, and genotoxicity in the pathobiology of cancer development in conjunction with their importance as reliable cancer biomarkers and their association with circulating miRNA, exosomes and exosomal miRNAs, RNA remodeling, DNA methylation, and other molecular elements in oncology.

Prognostic value of histopathologic traits independent of stromal tumor-infiltrating lymphocyte levels in chemotherapy-naïve patients with triple-negative breast cancer.

BACKGROUND: In the absence of prognostic biomarkers, most patients with early-stage triple-negative breast cancer (eTNBC) are treated with combination chemotherapy. The identification of biomarkers to select patients for whom treatment de-escalation or escalation could be considered remains an unmet need. We evaluated the prognostic value of histopathologic traits in a unique cohort of young, (neo)adjuvant chemotherapy-naïve patients with early-stage (stage I or II), node-negative TNBC and long-term follow-up, in relation to stromal tumor-infiltrating lymphocytes (sTILs) for which the prognostic value was recently reported. MATERIALS AND METHODS: We studied all 485 patients with node-negative eTNBC from the population-based PARADIGM cohort which selected women aged <40 years diagnosed between 1989 and 2000. None of the patients had received (neo)adjuvant chemotherapy according to standard practice at the time. Associations between histopathologic traits and breast cancer-specific survival (BCSS) were analyzed with Cox proportional hazard models. RESULTS: With a median follow-up of 20.0 years, an independent prognostic value for BCSS was observed for lymphovascular invasion (LVI) [adjusted (adj.) hazard ratio (HR) 2.35, 95% confidence interval (CI) 1.49-3.69], fibrotic focus (adj. HR 1.61, 95% CI 1.09-2.37) and sTILs (per 10% increment adj. HR 0.75, 95% CI 0.69-0.82). In the sTILs <30% subgroup, the presence of LVI resulted in a higher cumulative incidence of breast cancer death (at 20 years, 58%; 95% CI 41% to 72%) compared with when LVI was absent (at 20 years, 32%; 95% CI 26% to 39%). In the ≥75% sTILs subgroup, the presence of LVI might be associated with poor survival (HR 11.45, 95% CI 0.71-182.36, two deaths). We confirm the lack of prognostic value of androgen receptor expression and human epidermal growth factor receptor 2 -low status. CONCLUSIONS: sTILs, LVI and fibrotic focus provide independent prognostic information in young women with node-negative eTNBC. Our results are of importance for the selection of patients for de-escalation and escalation trials.

Predictive and Prognostic Biomarkers in Patients With Mycosis Fungoides and Sézary Syndrome (BIO-MUSE): Protocol for a Translational Study.

BACKGROUND: Cutaneous T-cell lymphoma (CTCL) is a rare group of lymphomas that primarily affects the skin. Mycosis fungoides (MF) is the most common form of CTCL and Sézary syndrome (SS) is more infrequent. Early stages (IA-IIA) have a favorable prognosis, while advanced stages (IIB-IVB) have a worse prognosis. Around 25% of patients with early stages of the disease will progress to advanced stages. Malignant skin-infiltrating T-cells in CTCL are accompanied by infiltrates of nonmalignant T-cells and other immune cells that produce cytokines that modulate the inflammation. Skin infection, often with Staphylococcus aureus, is frequent in advanced stages and can lead to sepsis and death. S. aureus has also been reported to contribute to the progression of the disease. Previous reports indicate a shift from Th1 to Th2 cytokine production and dysfunction of the skin barrier in CTCL. Treatment response is highly variable and often unpredictable, and there is a need for new predictive and prognostic biomarkers. OBJECTIVE: This prospective translational study aims to identify prognostic biomarkers in the blood and skin of patients with MF and SS. METHODS: The Predictive and Prognostic Biomarkers in Patients With MF and SS (BIO-MUSE) study aims to recruit 120 adult patients with MF or SS and a control group of 20 healthy volunteers. The treatments will be given according to clinical routine. The sampling of each patient will be performed every 3 months for 3 years. The blood samples will be analyzed for lactate dehydrogenase, immunoglobulin E, interleukins, thymus and activation-regulated chemokine, and lymphocyte subpopulations. The lymphoma microenvironment will be investigated through digital spatial profiling and single-cell RNA sequencing. Microbiological sampling and analysis of skin barrier function will be performed. The life quality parameters will be evaluated. The results will be evaluated by the stage of the disease. RESULTS: Patient inclusion started in 2021 and is still ongoing in 2023, with 18 patients and 20 healthy controls enrolled. The publication of selected translational findings before the publication of the main results of the trial is accepted. CONCLUSIONS: This study aims to investigate blood and skin with a focus on immune cells and the microbiological environment to identify potential new prognostic biomarkers in MF and SS. TRIAL REGISTRATION: ClinicalTrials.gov NCT04904146; https://www.clinicaltrials.gov/study/NCT04904146. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/55723.

Unveiling Prognostic RNA Biomarkers through a Multi-Cohort Study in Colorectal Cancer.

Because cancer is a leading cause of death and is thought to be caused by genetic errors or genomic instability in many circumstances, there have been studies exploring cancer's genetic basis using microarray and RNA-seq methods, linking gene expression data to patient survival. This research introduces a methodological framework, combining heterogeneous gene expression data, random forest selection, and pathway analysis, alongside clinical information and Cox regression analysis, to discover prognostic biomarkers. Heterogeneous gene expression data for colorectal cancer were collected from TCGA-COAD (RNA-seq), and GSE17536 and GSE39582 (microarray), and were integrated with Entrez Gene IDs. Using Cox regression analysis and random forest, genes with consistent hazard ratios and significantly affecting patient survivability were chosen. Predictive accuracy was evaluated using ROC curves. Pathway analysis identified potential RNA biomarkers. The authors identified 28 RNA biomarkers. Pathway analysis revealed enrichment in cancer-related pathways, notably EGFR downstream signaling and IGF1R signaling. Three RNA biomarkers (ZEB1-AS1, PI4K2A, and ITGB8-AS1) and two clinical biomarkers (stage and age) were chosen for a prognostic model, improving predictive performance compared to using clinical biomarkers alone. Despite biomarker identification challenges, this study underscores integration of heterogenous gene expression data for discovery.

A 14-gene B-cell immune signature in early-stage triple-negative breast cancer (TNBC): a pooled analysis of seven studies.

BACKGROUND: Early-stage triple-negative breast cancer (TNBC) displays clinical and biological diversity. From a biological standpoint, immune infiltration plays a crucial role in TNBC prognosis. Currently, there is a lack of genomic tools aiding in treatment decisions for TNBC. This study aims to assess the effectiveness of a B-cell/immunoglobulin signature (IGG) alone, or in combination with tumor burden, in predicting prognosis and treatment response in patients with TNBC. METHODS: Genomic and clinical data were retrieved from 7 cohorts: SCAN-B (N = 874), BrighTNess (n = 482), CALGB-40603 (n = 389), METABRIC (n = 267), TCGA (n = 118), GSE58812 (n = 107), GSE21653 (n = 67). IGG and a risk score integrating IGG with tumor/nodal staging (IGG-Clin) were assessed for event-free survival (EFS) and overall survival (OS) in each cohort. Random effects model was used to derive pooled effect sizes. Association of IGG with pathological complete response (pCR) was assessed in CALGB-40603 and BrighTNess. Immune significance of IGG was estimated through CIBERSORTx and EcoTyper. FINDINGS: IGG was associated with improved EFS (pooled HR = 0.77, [95% CI = 0.70-0.85], I2 = 18%) and OS (pooled HR = 0.79, [0.73-0.85], I2 = 0%) across cohorts, and was predictive of pCR in CALGB-40603 (OR 1.25, [1.10-1.50]) and BrighTNess (OR 1.57 [1.25-1.98]). IGG-Clin was predictive of recurrence (pooled HR = 2.11, [1.75-2.55], I2 = 0%) and death (pooled HR = 1.99, 95% [0.84-4.73], I2 = 79%) across cohorts. IGG was associated with adaptive immune response at CIBERSORTx and EcoTyper analysis. INTERPRETATION: IGG is linked to improved prognosis and pCR in early-stage TNBC. The integration of IGG alongside tumor and nodal staging holds promise as an approach to identify patients benefitting from intensified or de-intensified treatments. FUNDING: This study received funding from: Associació Beca Marta Santamaria, European Union's Horizon 2020 research and innovation and Marie Sklodowska-Curie Actions programs, Fundación FERO, Fundación CRIS contra el cáncer, Agència de Gestó d'Ajuts Universitaris i de Recerca, Instituto de Salud Carlos III, Fundación Contigo, Asociación Cáncer de Mama Metastásico IV, Breast Cancer Research Foundation, RESCUER, Fundación científica AECC and FSEOM.

Exploring the Role and Prognostic Value of TMEM208 in Head and Neck Squamous Cell Carcinoma.

OBJECTIVE: Head and neck squamous cell carcinoma (HNSCC) is one of the world's eight most common malignancies and a severe hazard to human health. Transmembrane protein 208 (TMEM208) has been reported to be associated with autophagy,which is strongly tied to the onset and development of numerous illnesses, including cancer. For this reason, we investigated the expression and prognostic significance of TMEM208 in HNSCC. METHODS: To explore the role and molecular mechanism of this gene in HNSCC, we performed a comprehensive analysis of the TMEM208 gene, including gene expression analysis, prognostic analysis, and immune infiltration analysis using the UALCAN, HPA, CVCDAP, DAVID, TIMER, CIBERSORTx, TISIDB, and cBioPortal online databases. It was further validated by in vitro cell culture. RESULTS: Analysis of TCGA data showed that TMEM208 was highly expressed in HNSCC (P < 0.01) and significantly correlated with several clinicopathologic features, and in vitro cellular assays demonstrated that TMEM208 was highly expressed in multiple squamous carcinoma cell lines. Survival analysis showed that high expression of TMEM208 decreased OS (P=0.0088), PFI (P=0.0062), and DSS (P=0.0036) in HNSCC patients. cox regression analysis indicated that high expression of TMEM208 was an independent risk factor for OS in HNSCC patients (P<0.05). In addition, functional enrichment analysis showed that TMEM208 was closely associated with translation, ribosomal and mitochondrial functions, and GSVA analysis showed that TMEM208 was negatively correlated with a variety of immune cell differentiation in HNSCC, with a statistically significant difference. Immunocorrelation analysis showed that TMEM208 could affect immune cell infiltration in HNSCC; in addition, TMEM208 correlated with CD24, CD276, LAG3, and HVEM. CONCLUSION: In conclusion, TMEM208 holds promise as a prognostic indicator for HNSCC and is closely related to ICI treatment.

Phospholipase A2 enzymes PLA2G2A and PLA2G12B as potential diagnostic and prognostic biomarkers in cholangiocarcinoma.

BACKGROUND: Phospholipase A2 (PLA2) enzymes are pivotal in various biological processes, such as lipid mediator production, membrane remodeling, bioenergetics, and maintaining the body surface barrier. Notably, these enzymes play a significant role in the development of diverse tumors. AIM: To systematically and comprehensively explore the expression of the PLA2 family genes and their potential implications in cholangiocarcinoma (CCA). METHODS: We conducted an analysis of five CCA datasets from The Cancer Genome Atlas and the Gene Expression Omnibus. The study identified differentially expressed genes between tumor tissues and adjacent normal tissues, with a focus on PLA2G2A and PLA2G12B. Gene Set Enrichment Analysis was utilized to pinpoint associated pathways. Moreover, relevant hub genes and microRNAs for PLA2G2A and PLA2G12B were predicted, and their correlation with the prognosis of CCA was evaluated. RESULTS: PLA2G2A and PLA2G12B were discerned as differentially expressed in CCA, manifesting significant variations in expression levels in urine and serum between CCA patients and healthy individuals. Elevated expression of PLA2G2A was correlated with poorer overall survival in CCA patients. Additionally, the study delineated pathways and miRNAs associated with these genes. CONCLUSION: Our findings suggest that PLA2G2A and PLA2G12B may serve as novel potential diagnostic and prognostic markers for CCA. The increased levels of these genes in biological fluids could be employed as non-invasive markers for CCA, and their expression levels are indicative of prognosis, underscoring their potential utility in clinical settings.