Prognosis Of Cancer Patients Research Articles

Micro-computed Tomography in the Evaluation of Eosin-stained Axillary Lymph Node Biopsies of Females Diagnosed with Breast Cancer.

Histopathological investigation of metastasis in core needle axillary lymph node (ALN) biopsies is crucial for the prognosis and treatment planning of breast cancer patients. Biopsies are typically sliced and evaluated as two-dimensional (2D) images. Biopsy sampling errors and the limited view provided by 2D histology are leading factors contributing to false-negative results in the preoperative detection of metastatic lymph nodes and underestimation of metastatic foci.In this proof-of-concept study, we aim to explore the technical feasibility and the potential capacities of tridimensional (3D) X-ray micro-computed tomography imaging to expedite error detection, enhancement of histopathological accuracy, and precise measurement of metastatic lesion on ALN core needle biopsies of two breast cancer patients. Our self-developed micro-CT protocol uses eosin for the first time, a common histological dye, to enhance 3D architecture of ALNs. Performed analysis on the images of the ALN biopsies involves cancer tissue segmentation, swift biopsy evaluation, and measurement of the metastatic longest diameter and deposit volume.The eosin micro-CT protocol shows potential for an improved tumor deposit estimates, offering additional clinical value compared to standard 2D histology, however, further studies for validating this method are needed.

Small but mighty: Platelets as multifunctional architects of tumor metastasis and immune regulation

AbstractPlatelets play an irreplaceable role in hemostasis and wound healing. However, beyond these classical roles, as the smallest anucleate cells in the blood stream, they are crucial for immune response which have inflammatory functions through specialized receptors and different signaling pathways, influencing both innate and adaptive immune response. Furthermore, many research have proved that platelets significantly contribute to tumor metastasis and are associated with poor prognoses in cancer patients through its coagulability and supporting an immunosuppressive tumor microenvironment. When tumor cells detach from the primary tumor mass and enter the bloodstream, they rapidly initiate the direct activation and adhesion of platelets, forming a protective microenvironment. This environment shields circulating tumor cells (CTCs) from the mechanical shear forces of blood flow and immune surveillance. Here we delve into the interaction between platelets and immunomodulation and explore the multifaceted roles and underlying mechanisms by which platelets influence tumor cell metastasis and tumor growth. Furthermore, we also discussed the diagnostic role of platelets in cancer occurrence and progression, as well as the feasibility and prospects of targeting platelets for antitumor immunotherapy. This review provides a multidimensional perspective and reference for platelet‐related cancer treatment strategies and diagnosis.

Integration of Machine Learning and Experimental Validation to Identify Anoikis-Related Prognostic Signature for Predicting the Breast Cancer Tumor Microenvironment and Treatment Response

Background/Objectives: Anoikis-related genes (ANRGs) are crucial in the invasion and metastasis of breast cancer (BC). The underlying role of ANRGs in the prognosis of breast cancer patients warrants further study. Methods: The anoikis-related prognostic signature (ANRS) was generated using a variety of machine learning methods, and the correlation between the ANRS and the tumor microenvironment (TME), drug sensitivity, and immunotherapy was investigated. Moreover, single-cell analysis and spatial transcriptome studies were conducted to investigate the expression of prognostic ANRGs across various cell types. Finally, the expression of ANRGs was verified by RT-PCR and Western blot analysis (WB), and the expression level of PLK1 in the blood was measured by the enzyme-linked immunosorbent assay (ELISA). Results: The ANRS, consisting of five ANRGs, was established. BC patients within the high-ANRS group exhibited poorer prognoses, characterized by elevated levels of immune suppression and stromal scores. The low-ANRS group had a better response to chemotherapy and immunotherapy. Single-cell analysis and spatial transcriptomics revealed variations in ANRGs across cells. The results of RT-PCR and WB were consistent with the differential expression analyses from databases. NU.1025 and imatinib were identified as potential inhibitors for SPIB and PLK1, respectively. Additionally, findings from ELISA demonstrated increased expression levels of PLK1 in the blood of BC patients. Conclusions: The ANRS can act as an independent prognostic indicator for BC patients, providing significant guidance for the implementation of chemotherapy and immunotherapy in these patients. Additionally, PLK1 has emerged as a potential blood-based diagnostic marker for breast cancer patients.

TMIC-40. TARGETING GLIOMA TUMOR MICROENVIRONMENT BY SPECIFIC NEUTRALIZATION OF EXTRACELLULAR NICOTINAMIDE PHOSPHORIBOSYLTRANSFERASE (ENAMPT) USING ALT-100, A NOVEL HUMANIZED MONOCLONAL ANTIBODY

Abstract BACKGROUND Intracellular nicotinamide phosphoribosyltransferase (iNAMPT is the rate-limiting enzyme of NAD salvage pathway and is preferentially used by glioma cells for regulating energy metabolism and homeostasis. When secreted, extracellular NAMPT (eNAMPT) exerts cytokine-like functions and is associated with poor prognosis in cancer patients. We have previously reported an essential role of iNAMPT for glioma cell proliferation and survival. Here, we examined whether eNAMPT influences glioma biology and tumor microenvironment by neutralizing eNAMPT using ALT-100, a novel humanized monoclonal antibody. METHODS Native levels of eNAMPT in blood samples of patients with primary/recurrent gliomas were determined using ELISA under an IRB approved protocol. Next, the effects of ALT-100 on glioma microenvironment were determined by treating viable human glioma tissue slices with ALT-100 and assessing downstream effects on RNA and protein using RNASeq, reverse phase protein array and spatial transcriptomics. Lastly, the in vivo effect of ALT-100-mediated eNAMPT neutralization on survival was determined in a mouse intracranial glioma model. RESULTS Measurable levels of eNAMPT were noted in all patient samples with a range of (3.7-71.2 ng/ml). Preliminary results showed a correlation of eNAMPT levels with grade of tumor. Human organotypic glioma slice cultures treated with ALT-100, showed a profound alteration of gene and protein expression particularly related to key energy metabolism and proliferation pathways and the PD-1/PD-L1 axis. Additionally, results of spatial profiling of ALT-100 treated human organotypic glioma slices will be presented. Survival and response data from ALT-100 treatment in ongoing in vivo experiment will also be reported. CONCLUSIONS This is the first report of ALT-100-mediated eNAMPT neutralization in gliomas and demonstrates profound effects on the tumor and its microenvironment. Given that ALT-100 is in phase 2 trials (NCT05938036) against ARDS, data from our studies can potentially accelerate translating ALT-100-mediated eNAMPT neutralization to treat gliomas.

FABP4-mediated lipid accumulation and lipolysis in tumor-associated macrophages promote breast cancer metastasis.

A high density of tumor-associated macrophages (TAMs) is associated with poorer prognosis and survival in breast cancer patients. Recent studies have shown that lipid accumulation in TAMs can promote tumor growth and metastasis in various models. However, the specific molecular mechanisms that drive lipid accumulation and tumor progression in TAMs remain largely unknown. Herein, we demonstrated that unsaturated fatty acids (FAs), unlike saturated ones, are more likely to form lipid droplets in murine macrophages. Specifically, unsaturated FAs, including linoleic acids (LA), activate the FABP4/CEBPα pathway, leading to triglyceride synthesis and lipid droplet formation. Furthermore, FABP4 enhances lipolysis and FA utilization by breast cancer cell lines, which promotes cancer cell migration in vitro and metastasis in vivo. Notably, a deficiency of FABP4 in murine macrophages significantly reduces LA-induced lipid metabolism. Therefore, our findings suggest FABP4 as a crucial lipid messenger that facilitates unsaturated FA-mediated lipid accumulation and lipolysis in TAMs, thus contributing to the metastasis of breast cancer.

FABP4-mediated lipid accumulation and lipolysis in tumor-associated macrophages promote breast cancer metastasis

A high density of tumor-associated macrophages (TAMs) is associated with poorer prognosis and survival in breast cancer patients. Recent studies have shown that lipid accumulation in TAMs can promote tumor growth and metastasis in various models. However, the specific molecular mechanisms that drive lipid accumulation and tumor progression in TAMs remain largely unknown. Herein, we demonstrated that unsaturated fatty acids (FAs), unlike saturated ones, are more likely to form lipid droplets in murine macrophages. Specifically, unsaturated FAs, including linoleic acids (LA), activate the FABP4/CEBPα pathway, leading to triglyceride synthesis and lipid droplet formation. Furthermore, FABP4 enhances lipolysis and FA utilization by breast cancer cell lines, which promotes cancer cell migration in vitro and metastasis in vivo. Notably, a deficiency of FABP4 in murine macrophages significantly reduces LA-induced lipid metabolism. Therefore, our findings suggest FABP4 as a crucial lipid messenger that facilitates unsaturated FA-mediated lipid accumulation and lipolysis in TAMs, thus contributing to the metastasis of breast cancer.

Nanoparticles and their application in the diagnosis of hepatocellular carcinoma

Abstract Most patients are at advanced stages when they are diagnosed with hepatocellular carcinoma, leading to poor prognosis and a low 5-year survival rate. Serological markers, ultrasound, computed tomography, magnetic resonance imaging, positron emission tomography, and liver biopsy are the common clinical diagnostic techniques for liver cancer. Effective interventions in the early stage will be beneficial to improve the prognosis of liver cancer patients and reduce the global burden. Therefore, it is urgent to develop new diagnostic methods to improve the diagnosis and management of liver cancer. Nanotechnology has become a new frontier subject in medical detection along with the application of nanomaterials in the manufacture of drug carriers, diagnostic tools, and therapeutic devices. Many studies have shown that nanoparticles (NPs) can be applied to the clinical diagnosis of liver cancer in combination with existing technologies, providing a new method for the early diagnosis of liver cancer. In this review, we elaborate on the theoretical basis and characteristics of NPs in the diagnosis of liver cancer, and the research progress and prospects of NPs in the diagnosis of liver cancer are summarized.

Impact of bone metastasis on prognosis in non-small cell lung cancer patients treated with immune checkpoint inhibitors: a systematic review and meta-analysis

Impact of bone metastasis on prognosis in non-small cell lung cancer patients treated with immune checkpoint inhibitors: a systematic review and meta-analysis

CT-based radiomics model for predicting perineural invasion status in gastric cancer.

Perineural invasion (PNI) is an independent risk factor for poor prognosis in gastric cancer (GC) patients. This study aimed to develop and validate predictive models based on CT imaging and clinical features to predict PNI status in GC patients. This retrospective study included 291 GC patients (229 in the training cohort and 62 in the validation cohort) who underwent gastrectomy between January 2020 and August 2022. The clinical data and preoperative abdominal contrast-enhanced computed tomography (CECT) images were collected. Radiomics features were extracted from the venous phase of CECT images. The intraclass correlation coefficient (ICC), Pearson correlation coefficient, and t-test were applied for radiomics feature selection. The random forest algorithm was used to construct a radiomics signature and calculate the radiomics feature score (Rad-score). A hybrid model was built by aggregating the Rad-score and clinical predictors. The area under the receiver operating characteristic curve (ROC) and decision curve analysis (DCA) were used to evaluate the prediction performance of the radiomics, clinical, and hybrid models. A total of 994 radiomics features were extracted from the venous phase images of each patient. Finally, 5 radiomics features were selected and used to construct a radiomics signature. The hybrid model demonstrated strong predictive ability for PNI, with AUCs of 0.833 (95% CI: 0.779-0.887) and 0.806 (95% CI: 0.628-0.983) in the training and validation cohorts, respectively. The DCA showed that the hybrid model had good clinical utility. We established three models, and the hybrid model that combined the Rad-score and clinical predictors had a high potential for predicting PNI in GC patients.

HOXC12 promotes the invasion and migration of gastric cancer cells by upregulating SALL4 and activating Wnt/β-catenin signaling pathway

BackgroundGastric cancer is one of the most common malignant tumors in the world, with a poor prognosis. HOXC is a family of transcription factors that are up-regulated in gastric cancer tissues. However, the relationship between Homeobox C12 (HOXC12) and gastric cancer is still unclear.MethodsTCGA-STAD and HPA data were analyzed to explore HOXC12 level. Kaplan–Meier Plotter was used to analyze the relationship between HOXC12 level and the prognosis of gastric cancer patients. The HOXC12 was knocked down or overexpressed by shRNA or overexpression vector to explore its functions. Cell migration/invasion assays and wound healing assay were used to assess the invasion/migration ability of gastric cancer cells. Western blot and qPCR were used to detect gene expression and the activation of Wnt/β-catenin signaling pathway. Dual-luciferase reporter assay was used to detect the active region bound by HOXC12 in the promoter of Spalt-like transcription factor 4 (SALL4).ResultsHOXC12 was highly expressed in gastric cancer and was positively correlated with the poor prognosis of gastric cancer patients. HOXC12 promotes the invasion and migration of gastric cancer cells via Wnt/β-catenin signaling pathway. HOXC12 upregulated the transcription of SALL4 by binding to its promoter. HOXC12 was negatively correlated with both the levels of CD8+ T cells and T cell cytotoxicity-related genes.ConclusionHOXC12 promotes the invasion/migration of gastric cancer cells via SALL4/Wnt/β-catenin axis, and is negatively correlated with the infiltration of CD8+ T cells, suggesting HOXC12 as a diagnostic marker and a potential therapeutic target for gastric cancer.

Effect of MPP2 and its DNA methylation levels on prognosis of colorectal cancer patients

Colorectal cancer is one of the common malignant tumors with poor prognosis, which is partly due to the lack of an effective biomarker. The purpose of this study is to explore the impact of membrane palmitoylated protein (MPP2) on the prognosis of colorectal cancer patients. We obtained transcriptome data and DNA methylation data of 380 colorectal cancer patients from the Cancer Genome Atlas (TCGA). Then we used a series of bioinformatics analysis methods to reveal the relationship between MPP2 expression, DNA methylation sites, prognosis, immune checkpoint and clinical characteristics of patients. Finally, in vitro experiment and the meta-analysis of thousands of patients further confirmed the impact of MPP2 on the prognosis of colorectal cancer patients and cell migration and proliferation. The expression level of MPP2 is negatively regulated by its DNA methylation sites, which leads to its low expression in colorectal cancer. High expression of MPP2 is an independent prognostic risk factor, which may be a biomarker for colorectal cancer. Moreover, the expression of MPP2 shows a close relationship with immune checkpoint or immune cells infiltration, especially CD4+T cells. In addition, meta-analysis involving 1584 patients from four different data further confirmed that MPP2 was a risk factor for colorectal cancer. Finally, knockdown of MPP2 could significantly inhibit the proliferation of SW480 cells via mTOR signaling pathway. This study was the first to suggest that MPP2 may become a promising biomarker, and has an important role in immune checkpoint or immune cell infiltration in colorectal cancer.

The correlation between multi-mode ultrasonographic features of breast cancer and axillary lymph node metastasis.

This study aimed to explore the correlation between multi-mode ultrasonographic features of breast cancer and axillary lymph node metastasis. A total of 196 patients with surgically confirmed breast cancer between September 2019 and December 2023 were included. Data on preoperative B-mode ultrasound (US), color Doppler, and shear wave elastography (SWE) features of breast cancer masses were collected and analyzed to determine their correlation with axillary lymph node metastasis. The area under the receiver operating characteristic curve (AUC) of B-mode US, color Doppler, SWE, and the multi-mode predictive model for evaluating axillary lymph node metastasis were compared. Among the 196 patients, 70 had positive axillary lymph nodes, while 126 had negative axillary lymph nodes. There was no significant difference in the color features between the negative and positive axillary lymph node groups. Multifocality/multicentricity, architectural distortion, microcalcifications, and the "stiff rim" sign in SWE were identified as independent risk factors to predict axillary lymph node metastasis according to binary logistic regression analysis. The AUC of the predictive model based on these independent risk factors was 0.803 (95% CI: 0.739-0.867), which was significantly higher than that of B-mode US or SWE alone. Multifocality/multicentricity, architectural distortion, microcalcifications, and the "stiff rim" sign in SWE were found to be valuable for predicting axillary lymph node metastasis in patients with breast cancer. The predictive model developed in this study, combining the multi-mode ultrasonographic features of breast cancer masses, could serve as a noninvasive and convenient method to predict axillary lymph node status. This approach could aid in clinical decision-making and individualized treatment to improve the prognosis of breast cancer patients.

Disruption of RNA Splicing Increases Vulnerability of Cells to DNA-PK Inhibitors.

DNA-dependent protein kinase (DNA-PK) is a key effector of non-homologous end joining (NHEJ)-mediated double-strand break (DSB) repair. Since its identification, a substantial body of evidence has demonstrated that DNA-PK is frequently overexpressed in cancer, plays a critical role in tumor development and progression, and is associated with poor prognosis in cancer patients. Recent studies have also uncovered novel functions of DNA-PK, shifting the paradigm of the role of DNA-PK in oncogenesis and renewing interest in targeting DNA-PK for cancer therapy. To gain genetic insight into the cellular pathways requiring DNA-PK activity, we used a CRISPR/Cas9 screen to identify genes in which defects cause hypersensitivity to DNA-PK inhibitors. We identified over one hundred genes involved in DNA replication, cell cycle regulation, and RNA processing that promoted cell survival when DNA-PK kinase activity was suppressed. This gene set will be useful for characterizing novel biological processes that require DNA-PK activity and identifying predictive biomarkers of response to DNA-PK inhibition in the clinic. We also validated several genes from this set and reported previously undescribed genes that modulate the response to DNA-PK inhibitors. In particular, we found that compromising the mRNA splicing pathway led to marked hypersensitivity to DNA-PK inhibition, providing a possible rationale for the combined use of splicing inhibitors and DNA-PK inhibitors for cancer therapy.

The Influence of treatment intervals on prognosis in young breast cancer patients: Insights from the French national cohort

BackgroundSuboptimal treatment delays is known to impact prognosis of patients with cancer but optimal timing in specific subgroups remains poorly studied. This study aimed to analyze treatment delays in young women treated for a breast cancer (BC) on and its impact on their prognosis using French Nationwide Data. MethodsUsing the CAREPAT-YBC Cohort based on the French National Healthcare System Database, we analyzed disease-free survival (DFS) in 22,093 young women (18-45 years) who underwent either surgery-chemotherapy-radiotherapy pathway (adjuvant setting, 15,433 patients) or chemotherapy-surgery-radiotherapy pathway (neoadjuvant setting, 6,660 patients), according to delays between the different pathways. ResultsFor the adjuvant chemotherapy-radiotherapy interval, the best timing was 17-31 days with increased risk above this delay. For the neoadjuvant setting, the optimal neoadjuvant chemotherapy-surgery interval was 17-31 days, while ≤15 days (HR 1.44, 95%CI 1.21-1.71) or ≥62 days (HR 2.07, 95%CI 1.36-3.15) showed poorer prognosis. Combining best timing into an "optimal pathway" was associated with respectively a 1.2-fold decreased risk for recurrence or mortality. ConclusionOptimizing treatment intervals enhance BC survival in younger age.

Clinical and prognostic significance of Hec1 expression in patients with Cervical Cancer.

Hec1 is a component of the Ndc80 kinetochore complex and is frequently upregulated in various cancers. However, the clinical significance of Hec1 in cervical cancer remains largely unknown. This study aimed to investigate the expression patterns of Hec1 in cervical cancer and its relationship with the clinicopathological characteristics of patients diagnosed with the disease. Immunohistochemistry was used to assess the expression of Hec1 in 136 cervical cancer tissue samples and 82 normal cervical tissue samples. The relationship between Hec1 protein expression and the clinicopathological characteristics of cervical cancer patients was analyzed using the Chi-square test. Additionally, the association between Hec1 protein expression and patient survival was examined using Kaplan-Meier survival curves. Independent risk factors affecting the prognosis of cervical cancer patients were analyzed using the Cox proportional hazards regression model. The positive expression rate of Hec1 protein in cervical cancer tissues was 83.82%, significantly higher than the 7.31% in normal cervical tissues. Compared to patients with negative Hec1 expression, those with positive expression exhibited significantly higher FIGO staging, increased lymph node metastasis, greater depth of tumor stromal infiltration, and larger tumor diameter. Multivariable analysis using the Cox proportional hazards regression model indicated that Hec1 positive expression was an independent risk factor for both overall survival (HR = 2.79, 95% CI: 1.65-4.05, p = 0.012) and progression-free survival (HR = 1.81, 95% CI: 1.22-3.18, p = 0.002) in cervical cancer patients. Kaplan-Meier survival curve analysis showed that patients with positive Hec1 expression experienced a lower overall survival (HR: 2.72, 95% CI: 1.15-4.52, p = 0.004) and progression-free survival (HR: 3.12, 95% CI: 1.62-5.03, p = 0.002) when compared to those with negative Hec1 expression. Hec1 is significantly upregulated in cervical cancer tissues and associated with poor prognosis in cervical cancer patients. Therefore, Hec1 could be a novel biomarker, not only for the diagnosis and treatment evaluation of cervical cancer but also as an indicator for predicting the prognosis of cervical cancer patients.

Machine learning algorithms able to predict the prognosis of gastric cancer patients treated with immune checkpoint inhibitors

BACKGROUND Although immune checkpoint inhibitors (ICIs) have demonstrated significant survival benefits in some patients diagnosed with gastric cancer (GC), existing prognostic markers are not universally applicable to all patients with advanced GC. AIM To investigate biomarkers that predict prognosis in GC patients treated with ICIs and develop accurate predictive models. METHODS Data from 273 patients diagnosed with GC and distant metastasis, who un-derwent ≥ 1 cycle(s) of ICIs therapy were included in this study. Patients were randomly divided into training and test sets at a ratio of 7:3. Training set data were used to develop the machine learning models, and the test set was used to validate their predictive ability. Shapley additive explanations were used to provide insights into the best model. RESULTS Among the 273 patients with GC treated with ICIs in this study, 112 died within 1 year, and 129 progressed within the same timeframe. Five features related to overall survival and 4 related to progression-free survival were identified and used to construct eXtreme Gradient Boosting (XGBoost), logistic regression, and decision tree. After comprehensive evaluation, XGBoost demonstrated good accuracy in predicting overall survival and progression-free survival. CONCLUSION The XGBoost model aided in identifying patients with GC who were more likely to benefit from ICIs therapy. Patient nutritional status may, to some extent, reflect prognosis.

Beneficial effect of sodium-glucose cotransporter-2 inhibitors on mortality among patients with cancer and diabetes mellitus.

The work attempts to describe mortality outcomes of sodium-glucose cotransporter-2 inhibitor (SGLT2I) in patients with diabetes mellitus (DM) and cancer. Using Taiwan's National Health Insurance Research Database to analyze the prognosis of cancer patients with coexisting DM, comparing those receiving SGLT2I with those who do not. After index-year and matching (age, sex, some comorbidities and medications), weobtain two groups of 20,339 patients. After further adjustment for age, sex and comorbidities, those with SGLT2I had a lower adjusted hazard ratio of mortality (aHR: 0.64 [95% CI: 0.60-0.68]). We conclude that SGLT2I medication should be considered first choice in patients suffering from DM and cancer.

Evaluation of naples prognostic score to predict long-term mortality in patients with pulmonary embolism

Abstract Background/Introduction APE mortality rates are still not satisfactory despite new diagnosis and treatment methods (1). Thus, risk classification is crucial due to the wide range of clinical presentations. Several risk stratifications have been developed such as simplified Pulmonary Embolism Severity Index (sPESI) (2). Nonetheless, there remains a need for an optimal indicator that can be conveniently measured with a high degree of precision to predict clinical outcomes. Naples prognostic score (NPS) is a newly defined index that is developed to determine the prognosis of cancer patients and reflects the inflammatory and nutritional status of the patients (3). Purpose The aim of our study was to determine the long-term prognostic value of NPS in APE patients. Methods Two hundred ninety-three patients diagnosed with APE between November 2016 and February 2022 were included in the study. NPS consists of 4 parameters: serum albumin, total cholesterol (TC) concentration, neutrophil-to-lymphocyte ratio (NLR) and lymphocyte-to-monocyte ratio (LMR). Naples scores of all patients were calculated and the patients were divided into 2 groups according to their NPS and their long-term mortality was compared. The primary endpoint of the study was long-term mortality. Results The long-term mortality was observed in 38 patients out of 293 patients in the mean follow-up of 24 (16-42) months. In the low-Naples risk group (group 1), there were 215 patients, while the high-Naples risk group (group 2) had 78 patients. Multivariate analysis showed that NPS as a categorical parameter (HR: 3.458, 95%CI:1.734-6.896, p<0.001), NPS as a numerical parameter, (HR:1.651, 95%CI:1.217-2.241, p=0.001) and simplified pulmonary embolism severity index (sPESI) (HR:1.887, 95%CI:1.223-2.911), p=0.004) score were independent predictors of long-term mortality. The receiver operating characteristic curve analysis showed that the model 2 with NPS as continuous had higher discriminative ability than the baseline model for detecting patients with mortality (Area under curve (AUC) values = 0.791 vs. 0.723, respectively, p=0.04) (Figure 1A). The long-term predictive capability of NPS was non-inferior than the sPESI score (Figure 1B). Conclusions The current study highlights that NPS, which reflects systemic inflammation and nutritional status may have potential to predict long-term mortality in APE patients. To our knowledge, this is the first study to show the relationship between long-term mortality and NPS in APE patients.

Impact of Obesity on Gleason Score- Elderly and Very Elderly Patients with Prostate Cancer Indicated for Radical Radiotherapy

Introduction: Prostate cancer is an important public health concern in Brazil, especially among older men, with a significant mortality rate. In addition to advanced age, obesity emerges as a relevant risk factor, associated with a worse prognosis of the disease. Objective: To investigate the relationship between body mass index (BMI) and Gleason score in older and very older patients with prostate cancer indicated for radiotherapy treatment. Methods: Prospective, descriptive, and longitudinal study with 258 patients with prostate cancer, evaluating age, initial PSA, BMI, race, and Gleason Score. Result: Findings revealed an association between a higher BMI and a more aggressive degree of disease, as indicated by higher Gleason scores. Conclusion: Overweight and obese patients have a higher and more evident Gleason score in older patients compared to the very older, being more notable in the older. This study is one of the few studies to examine the link between BMI and poor prognosis in prostate cancer patients

Human Cripto-1 and Cripto-3 Protein Expression in Normal and Malignant Settings That Conflicts with Established Conventions.

Background/Objectives: Cripto-1 (CR1) is a plurifunctional embryonic protein required for implantation and re-expressed in the adult during wound repair, inflammation, and tumorigenesis. CR1 and its predicted CR1 pseudogene product Cripto-3/CR3 are highly homologous proteins, and given this physical attribute, commercially available antibodies cannot discriminate between CR1 and CR3. Methods: A series of mouse monoclonal antibodies [MoAbs] were developed with a high-affinity binding that can differentiate human CR1/CR3 proteins and showed no measurable cross-reactivity. Results: Using these reagents, we confirm that CR3 is a bona fide translated protein found in human tumor tissue, cancer cell lysates, and in normal/cancer patient donor sera. We also reveal that CR1 and CR3 compete for binding to signal transduction protein Nodal, glucose-regulated protein 78Da (GRP78), and activin receptor-like kinase 4 (Alk4). Our discriminatory MoAbs provide new reagents to help clarify current CR1/CR3 protein expression vagaries in the Cripto field of study, challenging established CR1 conventions. In addition, our data validate CR3 involvement in human carcinogenesis and cell signaling pathways, with potential clinical relevance in determining cancer patient prognosis and disease severity.