Analysis of Body Mass Index and Clinicopathological Factors in Patients with Papillary Thyroid Carcinoma.

Objective: To analyze the correlation between body mass index (BMI) and clinicopathological factors of papillary thyroid cancer (PTC). Methods: The clinical data of patients with PCT who were hospitalized in the Department of Thyroid Surgery of the Affiliated Hospital of Guizhou Medical University from March 2023 to September 2023 were retrospectively collected, including age, gender, height, weight, BMI, v-raf murine sarcoma viral oncogene homolog B (BRAF) gene mutation, tumor size, multifocus, Hashimoto's thyroiditis, lymph node metastasis and other clinicopathological factors. According to the World Health Organization (WHO) definition for Asian population, BMI≥25kg/m2 was obese group, 23≤BMI≤24.9kg/m2 was overweight group, 18.5≤BMI≤22.9kg/m2 was normal weight group, and BMI≤18.5kg/m2 was low weight group. The clinicopathological factors of overweight and obese patients with PTC were analyzed. Results: A total of 164 PTC patients were included, with an average BMI of (24.44±3.57) kg/m2. Age of overweight and obese PTC patients (Z=1.978, p=0.083); Gender of overweight and obese PTC patients (χ2 value: 11.570, p=0.004); Tumor size in overweight and obese PTC patients (Z=0.894, p=0.411); BRAF gene mutation in overweight and obese PTC patients (χ2 value: 1.452, p =0.623); Multifocal lesions were found in overweight and obese patients (χ2 value: 1.653, p =0.201). Hashimoto's thyroiditis was found in overweight and obese PTC patients (χ2 value: 1.147, p=0.298). Overweight and obese patients with PTC had lymph node metastasis (χ2 value: 1.690, p =0.251). Conclusion: Overweight and obesity in PTC patients are correlated with male, but not with age, tumor size, BRAF mutation, multifocality, Hashimoto's thyroiditis and lymph node metastasis.

Overall Survival and Prognostic Factors in Metastatic Triple-Negative Breast Cancer: A National Cancer Database Analysis.

BACKGROUND: Metastatic triple-negative breast cancer (TNBC) is aggressive with poor median overall survival (OS) ranging from 8 to 13 months. There exists considerable heterogeneity in survival at the individual patient level. To better understand the survival heterogeneity and improve risk stratification, our study aims to identify the factors influencing survival, utilizing a large patient sample from the National Cancer Database (NCDB). METHODS: Women diagnosed with metastatic TNBC from 2010 to 2020 in the NCDB were included. Demographic, clinicopathological, and treatment data and overall survival (OS) outcomes were collected. Kaplan-Meier curves were used to estimate OS. The log-rank test was used to identify OS differences between groups for each variable in the univariate analysis. For the multivariate analysis, the Cox proportional hazard model with backward elimination was used to identify factors affecting OS. Adjusted hazard ratios and 95% confidence intervals are presented. RESULTS: In this sample, 2273 women had a median overall survival of 13.6 months. Factors associated with statistically significantly worse OS included older age, higher comorbidity scores, specific histologies, higher number of metastatic sites, presence of liver or other site metastases in those with only one metastatic site (excluding brain metastases), presence of cranial and extra-cranial metastases, lack of chemotherapy, lack of immunotherapy, lack of surgery to distant sites, lack of radiation to distant sites, and receipt of palliative treatment to alleviate symptoms. In the multivariate analysis, comorbidity score, histology, number of metastatic sites, immunotherapy, and chemotherapy had a statistically significant effect on OS. CONCLUSIONS: Through NCDB analysis, we have identified prognostic factors for metastatic TNBC. These findings will help individualize prognostication at diagnosis, optimize treatment strategies, and facilitate patient stratification in future clinical trials.

Machine learning for predicting colon cancer recurrence.

INTRODUCTION: Colorectal cancer (CRC) is a global public health concern, ranking among the most commonly diagnosed malignancies worldwide. Despite advancements in treatment modalities, the specter of CRC recurrence remains a significant challenge, demanding innovative solutions for early detection and intervention. The integration of machine learning into oncology offers a promising avenue to address this issue, providing data-driven insights and personalized care. METHODS: This retrospective study analyzed data from 396 patients who underwent surgical procedures for colon cancer (CC) between 2010 and 2021. Machine learning algorithms were employed to predict CC recurrence, with a focus on demographic, clinicopathological, and laboratory characteristics. A range of evaluation metrics, including AUC (Area Under the Receiver Operating Characteristic), accuracy, recall, precision, and F1 scores, assessed the performance of machine learning algorithms. RESULTS: Significant risk factors for CC recurrence were identified, including sex, carcinoembryonic antigen (CEA) levels, tumor location, depth, lymphatic and venous invasion, and lymph node involvement. The CatBoost Classifier demonstrated exceptional performance, achieving an AUC of 0.92 and an accuracy of 88 % on the test dataset. Feature importance analysis highlighted the significance of CEA levels, albumin levels, N stage, weight, platelet count, height, neutrophil count, lymphocyte count, and gender in determining recurrence risk. DISCUSSION: The integration of machine learning into healthcare, exemplified by this study's findings, offers a pathway to personalized patient risk stratification and enhanced clinical decision-making. Early identification of individuals at risk of CC recurrence holds the potential for more effective therapeutic interventions and improved patient outcomes. CONCLUSION: Machine learning has the potential to revolutionize our approach to CC recurrence prediction, emphasizing the synergy between medical expertise and cutting-edge technology in the fight against cancer. This study represents a vital step toward precision medicine in CC management, showcasing the transformative power of data-driven insights in oncology.

Predicting lymph node metastasis in colorectal cancer: An analysis of influencing factors to develop a risk model.

BACKGROUND: Colorectal cancer (CRC) is a significant global health issue, and lymph node metastasis (LNM) is a crucial prognostic factor. Accurate prediction of LNM is essential for developing individualized treatment strategies for patients with CRC. However, the prediction of LNM is challenging and depends on various factors such as tumor histology, clinicopathological features, and molecular characteristics. The most reliable method to detect LNM is the histopathological examination of surgically resected specimens; however, this method is invasive, time-consuming, and subject to sampling errors and interobserver variability. AIM: To analyze influencing factors and develop and validate a risk prediction model for LNM in CRC based on a large patient queue. METHODS: This study retrospectively analyzed 300 patients who underwent CRC surgery at two Peking University Shenzhen hospitals between January and December 2021. A deep learning approach was used to extract features potentially associated with LNM from primary tumor histological images while a logistic regression model was employed to predict LNM in CRC using machine-learning-derived features and clinicopathological variables as predictors. RESULTS: The prediction model constructed for LNM in CRC was based on a logistic regression framework that incorporated machine learning-extracted features and clinicopathological variables. The model achieved high accuracy (0.86), sensitivity (0.81), specificity (0.87), positive predictive value (0.66), negative predictive value (0.94), area under the curve for the receiver operating characteristic (0.91), and a low Brier score (0.10). The model showed good agreement between the observed and predicted probabilities of LNM across a range of risk thresholds, indicating good calibration and clinical utility. CONCLUSION: The present study successfully developed and validated a potent and effective risk-prediction model for LNM in patients with CRC. This model utilizes machine-learning-derived features extracted from primary tumor histology and clinicopathological variables, demonstrating superior performance and clinical applicability compared to existing models. The study provides new insights into the potential of deep learning to extract valuable information from tumor histology, in turn, improving the prediction of LNM in CRC and facilitate risk stratification and decision-making in clinical practice.

N-Myc Downstream Regulated Gene-1 May Play an Important Role in the Prognosis of Ovarian Cancer, in Its Association with Beta-Catenin.

NDRG1 is a nickel- and calcium-inducible gene that plays important roles in the primary growth of malignant tumors, as well as in invasion and metastasis. This study investigated the associations of NDRG1 expression with cell adhesion and other clinicopathological factors in ovarian cancer. The clinical records of 123 women who underwent surgery for ovarian cancer in our institute were reviewed retrospectively. The expression of NDRG1, E-cadherin, and beta-catenin in surgical specimens were evaluated immunohistochemically. The NDRG1 expression level was significantly associated with beta-catenin expression, peritoneal metastasis outside the pelvic cavity, lymph node metastasis, and FIGO stages. The Kaplan-Meier analysis showed a significant association between the NDRG1 expression level and progression-free survival: high NDRG1 expression was related to poor survival. Our results suggest that the increased expression of NDRG1 is associated with cell adhesion and may be a poor prognostic indicator in women with ovarian cancer.

Clinicopathological Predisposing Factors for Gastric Stump Cancer and Its Management: A Single-Center Analytical Study.

Background The incidence of gastric stump carcinoma (GSC) is not declining because of the long latency period. The survival rate of treated gastric cancer patients has increased due to early detection and improvements in surgical techniques and chemotherapy. Increased survival rates and improved surveillance following gastric surgery have increased the incidence of GSC. Aim The study aims to investigate the clinicopathological factors affecting the interval between index gastric surgery and the occurrence of GSC, and our experience in the management of GSC is presented. Methods A retrospective review of patients diagnosed with GSC in our institution was completed. Patient characteristics and clinicopathological outcomes were analyzed. Results A total of 28 patients were included in this cohort with 17 (60.71%) males and 11 (39.28%) females. The mean interval from index surgery to the incidence of GSC was 24.42 years for benign etiology and six years for malignant etiology. Index surgeries were truncal vagotomy with 14 gastrojejunostomies (50%) and 14 subtotal gastrectomies (50%). The interval between index surgery and the incidence of GSC is not statistically significant concerning the type of surgery (p: 0.661), pathological TNM (tumor, nodes, metastases) stage (p: 0.520), pathological differentiation (p: 0.828), lymphovascular invasion (p: 0.252), perineural invasion (p: 0.672), and adjuvant therapy (p: -0.655). Survival was significantly higher in those patients who received curative resection in comparison to a palliative procedure (p: 0.041). Conclusion Strict surveillance for at least 10 years after initial gastric surgery is of utmost importance as half of the patients fated to develop GSC will do so within this time. In those patients with early diagnosis, no evidence of metastasis, and good performance status, curative surgery is feasible with acceptable morbidity.

Clinical Significance of Nodal DCsign Expression in Non-small-cell Lung Cancer Patients.

BACKGROUND/AIM: Dendritic cells (DCs) are difficult to evaluate in lung regional lymph nodes because of region-specific structures, such as abundant trabeculae connecting the medullary and subcapsular sinuses, the latter of which contains few anthracotic macrophages. Therefore, DC-specific intercellular adhesion molecule-3-grabbing non-integrin (DCsign)-positive DCs and CD68-positive macrophages are unlikely to show a typical distribution. The present study therefore explored quantitative factors connecting the nodal DC morphology to the patient outcome. MATERIALS AND METHODS: Lymph nodes from 34 non-small-cell lung cancer patients who underwent complete resection were used for immunohistochemical assessments of DCsign and CD68 and terminal deoxynucleotidyl transferase dUTP nick-end labeling. Preoperative patient blood samples were used for the quantitative evaluation of monocytes. RESULTS: The nodal DCs showed a complementary distribution with macrophages, thus few DCs were seen in clusters of macrophages. DCs often presented as a mesh-like rosette that was solitary or connected to a DC cluster. DCs disappeared, and some macrophages were apoptotic when surrounded by cancer cells that have metastasized to lymph nodes. The proportional area of a DC cluster was significantly associated with the histological differentiation of cancer (p=0.013), with a higher ratio tending to lead to a better overall survival (p=0.059), and significantly so in adenocarcinoma (p=0.007). The rosette number was significantly correlated with the smoking index and blood monocyte number (p=0.013 and p=0.005, respectively). CONCLUSION: The nodal DC morphology appears useful as a prognostic factor and may lead to a new phase of clinicopathological studies of solid cancers.

Human epidermal growth factor receptor-2 gene expression positivity determined by silver in situ hybridization/immunohistochemistry methods and associated factors in a cohort of Sri Lankan patients with gastric adenocarcinoma: a prospective study.

OBJECTIVE: Positive human epidermal growth factor 2 (HER2) expression and its predictive clinicopathological features remain unclear in Sri Lankan gastric cancer (GC) patients. Here, we aimed to determine GC HER2 status predictors by analyzing associations between clinicopathological features and HER2 expression using immunohistochemistry (IHC) and silver in situ hybridization (SISH). METHODS: During this 4-year prospective study, clinicopathological data were collected from participants in the National Hospital of Sri Lanka. HER2 IHC and SISH were performed using commercial reagents. Using chi-square tests, associations of HER2-IHC/SISH with clinicopathological features were analyzed. RESULTS: Overall, 145 GC patients were included, 69 had gastrectomies and 76 had biopsies. Positive HER2 expression by IHC was associated with age <60 years, high T stage (assessed pathologically in resections and radiologically in biopsies), high nuclear grade, tumor necrosis, mitosis >5/high-power field, with additional perineural invasion and lymphovascular invasion in resections. These features, excluding lymphovascular invasion but including male sex, were associated with HER2 expression by SISH. CONCLUSIONS: Age <60 years, high nuclear grade, tumor necrosis, and perineural invasion are associated factors of HER2 status. These could be used to triage GC patients for HER2 status testing in limited resource settings where IHC/SISH analysis is costly.

MTA1 as negative prognostic marker in vulvar carcinoma.

PURPOSE: Vulvar cancer is the fourth most common malignancy of the female genital tract after endometrial, ovarian, and cervical carcinoma and affects mainly elderly women. In 2020 there were registered more than 17,000 deaths worldwide related to vulvar carcinoma. Data about target-based therapies and predictive biomarkers for vulva carcinomas are rare so far. The metastasis-associated gene MTA1 is a transcriptional repressor with a potential effect on cancer. Expression of MTA1 was found to be significantly enhanced in gynecological malignancies as breast or ovarian cancer tissues with advanced cancer stages and higher FIGO grading, indicating an important role of MTA1 in the progression of those tumor entities. Due to the lack of information around MTA1 and its significance regarding vulvar carcinoma, this study focuses on the expression of MTA1 in vulvar carcinoma and its correlation to clinicopathological characteristics and prognosis. METHODS: A total of 157 paraffin-embedded vulvar cancer tissues were immunohistochemically stained and examined for MTA1 expression by using the immunoreactive score. Subsequently, the values were correlated with clinicopathological parameters. RESULTS: MTA1 was found to be expressed in 94% of the patients in the cytoplasm and 91% in the nucleus. Cytoplasmatic expression of MTA1 was significantly increased in non-keratinizing squamous cell carcinoma and in vulvar carcinoma of the condylomatous type, compared to keratinizing squamous cell carcinoma and vulvar carcinoma of the verrucous type. High MTA1 expression in the nucleus was associated with advanced tumor size as well as higher FIGO grading. In addition, p16 negative vulvar carcinomas showed a higher nuclear expression of MTA1 compared to p16 positive vulvar carcinomas. Suprisingly, Kaplan-Meier analysis showed a significantly lower disease-free survival in tumor samples without a nuclear expression of MTA1. CONCLUSIONS: MTA1 was identified as a negative prognostic marker for vulvar carcinoma associated with advanced tumor stage and FIGO grading. A possible explanation could be that the antibody used for this study does not bind to a possible mutation in the C terminal region of MTA leading to negative immunohistochemical staining and this can be correlated with early recurrence in patients with vulvar carcinoma.

Clinicopathological Characteristics and Prognosis of 91 Patients with Seromucinous and Mucinous Borderline Ovarian Tumors: a Comparative Study.

To explore the differences in clinicopathological characteristics and prognosis between seromucinous borderline ovarian tumors (SMBOTs) and mucinous borderline ovarian tumors (MBOTs). Ninety-one patients with SMBOTs and MBOTs who underwent surgery at the Obstetrics and Gynecology Hospital of Fudan University from July 2006 to January 2015 were included. The median onset age of patients with SMBOTs (29 years, 20-77) was younger than that of patients with MBOTs (37 years, 16-71). SMBOTs were more likely to be exogenous and show bilateral ovarian involvement and had a smaller average tumor size of 10.63 cm, while MBOTs were more prone to endogenous growth and show unilateral involvement and had a larger average tumor size of 18.55 cm (p < 0.05). Compared with MBOTs, SMBOTs were characterized by the expression of Mullerian differentiation markers (p < 0.05). Recurrence occurred in 15.8% patients with SMBOT and 9.1% patients with MBOT. One case of SMBOT (2.6%) and one case of MBOT (2.3%) progressed to malignancy during follow-up, but no disease-related death was observed. Age less than 40 years was a risk factor for recurrence, while the effect of fertility-sparing surgery (FSS) on recurrence requires a larger sample size to be validated. The clinical characteristics of SMBOTs and MBOTs are similar but also quite different. High expression of Mullerian differentiation markers in SMBOT may indicate a better response to hormone therapy. Repeated FSS should be performed with caution and fully informed because of the risk of recurrence and progression to malignancy.

The expression of miR-181b, CYLD, CBX-7, BCL2, and p53 in osteosarcoma patients and correlation with clinicopathological factors.

Osteosarcoma is a common human malignancy with a high mortality rate worldwide. Recent studies have been focused on understanding the involvement of microRNA (miRNAs) in the pathogenesis of osteosarcoma. Therefore, the present study aimed to measure the expression levels of miR-181a, cylindromatosis (CYLD), chromo box homolog 7 (CBX7), B-cell lymphoma 2 (BCL2), and tumor protein p53 in tumor tissue and adjacent normal tissues in patients with osteosarcoma and its relationship with clinicopathological factors. The expression levels of miR-181a, CYLD, CBX7, BCL2, and p53 were measured in 60 patients with osteosarcoma using quantitative real-time polymerase chain reaction. Finally, we compared the relationship between these gene levels and clinicopathological factors in tumor and healthy tissues. Our results showed that the expression levels of miR-181a, BCL2, and p53 were significantly higher in osteosarcoma tissue in comparison with normal tissues (p < .05). On the contrary, CYLD and CBX7 were downregulated in osteosarcoma tumor tissues compared to adjacent healthy tissues (p < .05). In addition, the expression levels of miR-181a in tumor tissues were strongly correlated with patients' age, tumor size, clinical stage, cancer grade, and lymph node metastasis (p < .05). Our findings highlight new insights into understanding the role of miR-181a in the pathogenesis of osteosarcoma. However, further studies are needed to elucidate miRNA as therapeutic targets for osteosarcoma.

Study of PD-L1 Expression with Association of Pathological Factors and Molecular Subtypes in Breast Carcinoma.

Background Programmed death ligand 1 (PD-L1), expressed on cancer cells, shows varied results in the prognosis of breast cancer. This study was conducted to study the expression of PD-L1 in breast carcinoma and to correlate it with pathological, molecular classification and prognostic factors. Materials and Methods PD-L1 expression was correlated with tumor size, histopathological grade, necrosis, lymphovascular, perineurial invasion, lymph node metastasis, molecular classification, and survival in breast carcinoma cases. Results Fifty cases were included which showed statistically significant difference of PD-L1 with mean age, tumor size, histopathological grade, lymphovascular emboli, and lymph node metastasis ( p < 0.05). Estrogen receptor was strongly positive in 46%, progesterone receptor in 42%, and PD-L1 in 6% of cases. No statistically significant difference between pathological tumor-node-metastasis (TNM) staging and PD-L1 expression ( p = 0.354) was observed. Receptor operating characteristic curve analysis showed that at the cutoff of PD-L1 greater than 120, specificity was 56.1%, sensitivity 66.7%, negative predictive value 88.5%, and positive predictive value 25% for predicting living status. Conclusion PD-L1 is associated with poor prognostic factors including tumor size, histopathological grade, lymphovascular emboli, and lymph node metastasis in breast carcinoma. However, no significant association was observed between PD-L1 and pathological TNM stage or molecular subtypes of breast carcinoma. It is suggested that immunohistochemical reporting of PD-L1 should be standardized so that it is reproducible and reliable for the evaluation of breast carcinoma. Further, larger studies with extended follow-ups are recommended so that the exact role of PD-L1 as a prognostic marker in breast carcinoma could be ascertained.

Risk Stratification of Pancreatic Neuroendocrine Neoplasms Based on Clinical, Pathological, and Molecular Characteristics.

Pancreatic neuroendocrine neoplasms consist of heterogeneous diseases. Depending on the novel features detected by various modern technologies, their classification and related prognosis predictions continue to change and develop. The role of traditional clinicopathological prognostic factors, including classification systems, is also being refined, and several attempts have been made to predict a more accurate prognosis through novel serum biomarkers, genetic factors, and epigenetic factors that have been identified through various state-of-the-art molecular techniques with multiomics sequencing. In this review article, the latest research results including the traditional approach to prognostic factors and recent advanced strategies for risk stratification of pancreatic neuroendocrine neoplasms based on clinical, pathological, and molecular characteristics are summarized. Predicting prognosis through multi-factorial assessments seems to be more efficacious, and prognostic factors through noninvasive methods are expected to develop further advances in liquid biopsy in the future.

Alternations of gene expression in PI3K and AR pathways and DNA methylation features contribute to metastasis of prostate cancer.

OBJECTIVE: The molecular heterogeneity of prostate cancer (PCa) gives rise to distinct tumor subclasses based on epigenetic modification and gene expression signatures. Identification of clinically actionable molecular subtypes of PCa is key to improving patient outcome, and the balance between specific pathways may influence PCa outcome. It is also urgent to identify progression-related markers through cytosine-guanine (CpG) methylation in predicting metastasis for patients with PCa. METHODS: We performed bioinformatics analysis of transcriptomic, and clinical data in an integrated cohort of 551 prostate samples. The datasets included retrospective The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) cohorts. Two algorithms, Least Absolute Shrinkage and Selector Operation and Support Vector Machine-Recursive Feature Elimination, were used to select significant CpGs. RESULTS: We found that PCa progression is more likely to occur after the third year through conditional survival (CS) analysis, and prostate-specific antigen (PSA) was a better predictor of Progression-free survival (PFS) than Gleason score (GS). Our study first demonstrated that PCa tumors have distinct expression profiles based on the expression of genes involved in androgen receptor (AR) and PI3K-AKT, which influence disease outcome. Our results also indicated that there are multiple phenotypes relevant to the AR-PI3K axis in PCa, where tumors with mixed phenotype may be more aggressive or have worse outcome than quiescent phenotype. In terms of epigenetics, we obtained CpG sites and their corresponding genes which have a good predictive value of PFS. However, various evidences showed that the predictive value of CpGs corresponding genes was much lower than GpG sites in Overall survival (OS) and PFS. CONCLUSIONS: PCa classification specific to AR and PI3K pathways provides novel biological insight into previously established PCa subtypes and may help develop personalized therapies. Our results support the potential clinical utility of DNA methylation signatures to distinguish tumor metastasis and to predict prognosis and outcomes.

Clinicopathological factors associated with progression of oral submucous fibrosis: A population-based retrospective study.

Oral submucosal fibrosis was one of the oral potentially malignant disorders, which has become a global epidemic disease. This study aimed to investigate the clinicopathological features associated with the disease progression of oral submucosal fibrosis. We recruited 700 cases of oral submucosal fibrosis in the Department of oral pathology, Xiangya Stomatological Hospital, Central South University from July 1996 to July 2019, and analyzed the association among staging of oral submucosal fibrosis and age, sex, sites, duration of areca nut chewing. The age of the patients ranged from 14 to 63 years, with a median age of 32 years. The average age of oral submucosal fibrosis in the early stage (35.89 ± 9.97) was different from the average age in the middle stage (32.74 ± 8.83) and advanced stage (31.43 ± 7.57, P < 0.05). The risk of staging progression of oral submucosal fibrosis decreased with age (OR = 0.965, 95%CI: 0.945-0.986, P = 0.001).

The Association of Intra-Tumoral and Stromal Vitamin D Receptor (VDR) Expressions with Molecular Subtypes and Clinicopathological Factors in Breast Carcinoma.

OBJECTIVE: This study aimed to investigate the association between intra-tumoral and stromal VDR expressions with molecular subtypes and clinicopathological factors. METHODS: A total of 75 formalin-fixed paraffin embedded tissue samples were stained using immunohistochemical methods. The VDR expressions were measured by counting brown-stained nuclei in intra-tumoral and stromal areas. The association of VDR expression with molecular subtypes and clinopathological factors was examined. Statistical analysis was performed by chi square tests. RESULTS: High intra-tumoral VDR expression was found in carcinomas with luminal molecular subtypes (p=0.039) and low histological degrees (p=0.035). High VDR expression in the stroma was found in breast carcinomas with large tumor sizes. CONCLUSIONS: High intra-tumoral VDR expression is found in breast carcinomas with luminal subtypes and low histological grade (I/II). Both factors are known to have a good prognosis. These findings further strengthen the function of VDR as anti-tumorigenesis.

Controversies and Opportunities in the Clinical Daily Use of the 21-Gene Assay for Prognostication and Prediction of Chemotherapy Benefit in HR+/HER2- Early Breast Cancer.

Several multigene assays have been developed to help clinicians in defining adjuvant treatment for patients with hormone-receptor-positive (HR+), human epidermal growth factor receptor-2 (HER2)-negative early breast cancer. Despite the 21-gene assay having been available for decades, it has only recently been included in the healthcare systems of several countries. Clinical optimisation of the test remains of critical interest to achieve a greater impact of genomic information in HR+/HER2- early breast cancer. Although current guidelines recommend the use of the 21-gene assay in early breast cancer at intermediate risk of relapse, the implication of the Recurrence Score (RS) in some grey areas still remains uncertain. Our aim is to critically discuss the role of RS in peculiar circumstances. In particular, we focus on the complex integration of genomic data with clinicopathological factors; the potential clinical impact of RS in node-positive premenopausal women and in the neoadjuvant setting; the significance of RS in special histologies and in male patients; and the management and time-optimisation of test ordering. In the absence of robust evidence in these areas, we provide perspectives for improving the use of the 21-gene assay in the decision-making process and guide adjuvant treatment decisions even in challenging cases.

Expression of TSP50, SERCA2 and IL-8 in Colorectal Adenoma and Carcinoma: Correlation to Clinicopathological Factors.

Background: Colorectal cancer (CRC) is the third most common type of cancer, it is considered a genetically heterogeneous disease with different molecular pathways being involved in its initiation and progression. Testes-specific protease 50 (TSP50) gene is a member of cancer/testis antigens that encodes for threonine protease enzyme. Overexpression of TSP50 was found to enhance the progression and invasion of breast cancer and other malignant tumors. SERCA2 is widely expressed in several body tissues; its aberrant expression has been involved in many cancers. IL-8 is an inflammatory cytokine. Alongside its role in inflammation, its expression was reported to induce the migration of tumor cells. Aim: Study the expression of TSP50, SERCA2 and IL-8 in colorectal adenoma (CRA), CRC and normal colonic tissues to compare the expression of these biomarkers in relation to clinicopathological parameters and prognostic factors. Results: TSP50, SERCA2 and IL-8 expression varied between normal colonic tissues, CRA and CRC. Significant statistical association was detected between the three biomarkers' overexpression and degree of dysplasia in CRA. Also, significant statistical relation was found between the three biomarkers' overexpression and presence of lympho-vascular invasion, advanced TNM staging and high intra-tumoral inflammatory infiltrate. Multivariable analysis showed that the overexpression of the three biomarkers is significantly associated with worse prognosis. Conclusion: The expression of TSP50, SERCA2 and IL-8 was different between the normal tissue and neoplastic colorectal tissue on one hand and between CRA and CRC on the other. Increased expression of these biomarkers in neoplastic epithelial cells of colorectal carcinoma is associated with adverse prognostic factors and could be considered as independent prognostic factors.

Nomogram to predict survival of patients with advanced and metastatic pancreatic Cancer.

BACKGROUND: Nomograms are rarely employed to estimate the survival of patients with advanced and metastatic pancreatic cancer (PC). Herein, we developed a comprehensive approach to using a nomogram to predict survival probability in patients with advanced and metastatic PC. METHODS: A total of 323 patients with advanced and metastatic PC were identified from the Chinese People's Liberation Army (PLA) General Hospital. A baseline nomogram was constructed using baseline variables of 323 patients. Additionally, 233 patients, whose tumors showed initial responses to first-line chemotherapy, were enrolled in the chemotherapy response-based model. 128 patients and 108 patients with advanced and metastatic PC from January 2019 to April 2021 were selected for external validating baseline model and chemotherapy response-based model. The 1-year and 2-year survival probability was evaluated using multivariate COX regression models. The discrimination and calibration capacity of the nomograms were assessed using C-statistic and calibration plots. The predictive accuracy and net benefit of the nomograms were evaluated using ROC curve and DCA, respectively. RESULTS: In the baseline model, six variables (gender, KPS, baseline TB, baseline N, baseline WBC and baseline CA19-9) were used in the final model. In the chemotherapy response-based model, nine variables (KPS, gender, ascites, baseline N, baseline CA 19-9, baseline CEA, change in CA 19-9 level at week, change in CEA level at week and initial response to chemotherapy) were included in the final model. The C-statistics of the baseline nomogram and the chemotherapy response-based nomogram were 0.67 (95% CI, 0.62-0.71) and 0.74 (95% CI, 0.69-0.77), respectively. CONCLUSION: These nomograms were constructed to predict the survival probability of patients of advanced and metastatic PC. The baseline model and chemotherapy response-based model performed well in survival prediction.

SYDE1 Acts as an Oncogene in Glioma and has Diagnostic and Prognostic Values.

Objectives: Gliomas remain one of serious public health problems worldwide which demand further and deeper investigation. The aim of this study was to explore the association between synapse defective protein 1 homolog 1 (SYDE1) and gliomas via public database analysis and in vitro validation to determine the potential diagnostic and prognostic values. Methods and Results: Compared with healthy brain tissues, there was a significant increase in SYDE1 expression in glioma tissues. Additionally, SYDE1 exhibited higher expression levels in glioma patients with unfavorable clinicopathological factors. In vitro knockdown of SYDE1 in glioma cell lines A172 inhibited their migrative and invasive ability but not the proliferative ability. GO and KEGG pathway analysis of the top 100 genes coexpressed with SYDE1 showed enrichments of tumor-associated terms. Further bioinformatic analysis revealed that the SNHG16/hsa-miR-520e/SYDE1 axis might be involved in glioma development. Conclusions: SYDE1 is expressed at higher levels in gliomas than in healthy brains, and can promote metastasis and invasion but not proliferation of gliomas. Furthermore, SYDE1 has values in the diagnosis and prognosis prediction of gliomas.