OBJECTIVE: To analyze the presentation and outcomes of eyelid and periocular sebaceous gland carcinoma (SGC) based on prognostic stage of the 8th edition of American Joint Committee on Cancer (AJCC) classification.
METHODS: Retrospective clinical cohort study METHODS: • Setting: Quaternary referral center • Study population: 500 eyes of 499 patients with SGC • Intervention: Excisional biopsy, chemotherapy, Orbital exenteration • Main outcome measures: Tumor recurrence, lymph node metastasis, systemic metastasis, and death based on AJCC prognostic staging RESULTS: The mean age at presentation with SGC was 57 years (55 years; range, 26 to 82 years). Based on the 8th edition of AJCC classification, tumors belonged to Stage 0 (n=13, 3%), I (n=158, 32%), II (n=269, 54%), III (n=48, 9%), and IV (n=12, 2%). At a mean follow-up of 26 months (median, 10 months; range, <1 to 192 months), tumor recurrence, lymph node metastasis, systemic metastasis, and disease-related death were seen in 39 (10%), 65 (16%), 33 (8%), and 33 (8%) patients respectively. Tumor recurrence rates did not differ significantly between the stages (p=0.472). The 5-year Kaplan-Meier estimates of regional lymph node metastasis, systemic metastasis, and metastasis-related death were higher for stage II (12%, 11%, and 12%, respectively), III (69%, 25%, and 42%, respectively) and IV (70%, 100%, and 100%, respectively) compared to stage I (0%, 6%, and 6%, respectively). Cox proportional analysis revealed a greater hazard ratio (HR) for lymph node metastasis in stage II (HR, 3.498; 95% CI, 0.200 to 10.200; p<0.022), III (HR, 95% CI, 24.836; 8.733 to 70.631; p<0.001), and IV (HR, 53.731; 95% CI, 15.418 to 187.253; p<0.001), systemic metastasis in stage III (HR. 13.895; 95% CI, 3.871 to 49.874; p<0.001) and IV (HR, 81.465; 95% CI, 22.267 to 298.051; p<0.001) and for disease-related death in stage III (HR, 9.182; 95% CI, 2.743 to 30.728; p<0.001) and IV (HR, 85.237; 95% CI, 25.331 to 287.422; p<0.001), compared to stage I.
CONCLUSIONS: The prognostic staging of the 8th edition AJCC classification predicts the prognosis of patients with eyelid and periocular SGC, which worsens with the advancing stage. The high incidence of lymph node and systemic metastasis accounts for mortality in these patients.

BACKGROUND: The eighth edition of lung cancer N staging assignment includes the location of lymph node metastasis, but does not include single-N and multiple-N descriptors.
OBJECTIVE: Do the single-N and multiple-N statuses stratify the prognosis of patients with non-small cell lung cancer (NSCLC)?
METHODS: Using the National Cancer Database, we analyzed patients with pathologically staged N1 and N2 NSCLC. N descriptors were classified into pathological single N1 (pSingle-N1), pathological multiple N1 (pMulti-N1), pathological single N2 (pSingle-N2), and pathological multiple N2 (pMulti-N2). Survival analysis was performed using the Kaplan-Meier method and multivariable Cox regression models.
RESULTS: In the general analysis cohort, 24,531, 22,256, 8,528, and 21,949 patients with NSCLC demonstrated pSingle-N1, pMulti-N1, pSingle-N2, and pMulti-N2 disease, respectively. Patients with pMulti-N1 and pMulti-N2 disease showed a shorter survival than those with pSingle-N1 and pSingle-N2 disease, respectively (hazard ratio [HR], 1.22 [P < .0001] for N1 and 1.39 [P < .0001] for N2). After adjusting age, sex, and histologic findings, the HR for pSingle-N2 compared with pMulti-N1 disease was 1.05 (P = .0031). Patients with pN1 disease were categorized by metastatic lymph node count (1, 2, 3, ≥ 4), showing significant prognostic differences among groups (P < .0001). In the sensitivity analysis cohort (limited to R0 resection, lobectomy, or more; survival ≥ 30 days; ≥ 10 examined lymph nodes; and without neoadjuvant therapy; n = 34,904) and the external validation cohort (n = 708), analyses supported these results.
CONCLUSIONS: Patients with NSCLC with one metastatic lymph node, whether in N1 or N2 stations, showed better survival than those with more than one lymph node involved. Patients with NSCLC with a single-skip N2 lymph node metastasis showed survival similar to patients with multiple N1 lymph nodes, and the number of lymph nodes involved in N1 resections up to four or more was sequentially prognostic.

OBJECTIVE: Examining the distribution of breast cancer (BC) stage and molecular subtype among women aged below (< 45 years), within (45-65 years), and above (> 65 years) the recommended screening age range helps to understand the screening program\'s characteristics and contributes to enhancing the effectiveness of BC screening programs.
METHODS: In this retrospective study, female patients with newly diagnosed BC from 2010 to 2020 were identified. The distribution of cases in terms of TNM stages, severity classes, and subtypes was analysed according to age groups.
RESULTS: A total of 3282 women diagnosed with BC were included in the analysis. Among these cases 51.4% were detected outside the screening age group, and these were characterized by a higher TNM stage compared to those diagnosed within the screening age band. We observed significantly higher relative frequency of advanced BC in the older age group compared to both the screening age population and women younger than 45 years (14.9% vs. 8.7% and 7.7%, P < 0.001). HR-/HER2- and HER+ tumours were relatively more frequent among women under age 45 years (HR-/HER2-: 23.6%, HER2+: 20.5%) compared to those within the screening age range (HR-/HER2-: 13.4%, HER2+: 13.9%) and the older age group (HR-/HER2-: 10.4%, HER2+: 11.5%).
CONCLUSIONS: The findings of our study shed light on potential areas for the improvement of BC screening programs (e.g., extending screening age group, adjusting screening frequency based on molecular subtype risk status) in Hungary and internationally, as well.

OBJECTIVE: This study aims to develop a novel prediction model and risk stratification system that could accurately predict progression-free survival (PFS) in patients with nasopharyngeal carcinoma (NPC).
METHODS: Herein, we included 106 individuals diagnosed with NPC, who underwent 18F-FDG PET/CT scanning before treatment. They were divided into training (n = 76) and validation (n = 30) sets. The prediction model was constructed based on multivariate Cox regression analysis results and its predictive performance was evaluated. Risk factor stratification was performed based on the nomogram scores of each case, and Kaplan-Meier curves were used to evaluate the model\'s discriminative ability for high- and low-risk groups.
RESULTS: Multivariate Cox regression analysis showed that N stage, M stage, SUVmax, MTV, HI, and SIRI were independent factors affecting the prognosis of patients with NPC. In the training set, the model considerably outperformed the TNM stage in predicting PFS (AUCs of 0.931 vs. 0.841, 0.892 vs. 0.785, and 0.892 vs. 0.804 at 1-3 years, respectively). The calibration plots showed good agreement between actual observations and model predictions. The DCA curves further justified the effectiveness of the model in clinical practice. Between high- and low-risk group, 3-year PFS rates were significantly different (high- vs. low-risk group: 62.8% vs. 9.8%, p < 0.001). Adjuvant chemotherapy was also effective for prolonging survival in high-risk patients (p = 0.009).
CONCLUSIONS: Herein, a novel prediction model was successfully developed and validated to improve the accuracy of prognostic prediction for patients with NPC, with the aim of facilitating personalized treatment.

BACKGROUND: The first COVID-19 wave in 2020 necessitated temporary suspension of non-essential medical services including organized cancer screening programs in Belgium. This study assessed the impact of the pandemic on breast cancer (BC) incidence, stage at diagnosis, and management in Belgium in 2020.
METHODS: All Belgian residents diagnosed with in situ or invasive BC in 2015-2020 in the nationwide, population-based cancer registry database were included. Incidence trends for 2015-2019 were extrapolated to predict incidence and stage distribution for 2020 and compared with the observed values. National healthcare reimbursement data were used to examine treatment strategies. Exact tumor diameter and nodal involvement, extracted from pathology reports, were analyzed for 2019 and 2020.
RESULTS: 74,975 tumors were selected for analysis of incidence and clinical stage. Invasive BC incidence declined by -5.0% in 2020, with a drop during the first COVID-19 wave (Mar-Jun; -23%) followed by a rebound (Jul-Dec; +7%). Predicted and observed incidence (in situ + invasive) was not different in patients < 50 years. In the 50-69 and 70 + age groups, significant declines of -4.1% and - 8.4% respectively were found. Excess declines were seen in clinical stage 0 and I in Mar-Jun, without excess increases in clinical stage II-IV tumors in Jul-Dec. There was no increase in average tumor diameter or nodal involvement in 2020. Patients diagnosed in Mar-Jun received significantly more neoadjuvant therapy, particularly neoadjuvant hormonal therapy for patients with clinical stage I-II BC.
CONCLUSIONS: BC incidence decline in 2020 in Belgium was largely restricted to very early-stage BC and patients aged 50 and over. Delayed diagnosis did not result in an overall progression to higher stage at diagnosis in 2020. Observed treatment adaptations in Belgium were successful in prioritizing patients for surgery while preventing tumor progression in those with surgical delay. Continuation of monitoring BC incidence and stage in the future is crucial.

This study aims to decipher crucial biomarkers regulated by p73 for the early detection of colorectal cancer (CRC) by employing a combination of integrative bioinformatics and expression profiling techniques. The transcriptome profile of HCT116 cell line p53 - / - p73 + / + and p53 - / - p73 knockdown was performed to identify differentially expressed genes (DEGs). This was corroborated with three CRC tissue expression datasets available in Gene Expression Omnibus. Further analysis involved KEGG and Gene ontology to elucidate the functional roles of DEGs. The protein-protein interaction (PPI) network was constructed using Cytoscape to identify hub genes. Kaplan-Meier (KM) plots along with GEPIA and UALCAN database analysis provided the insights into the prognostic and diagnostic significance of these hub genes. Machine/deep learning algorithms were employed to perform TNM-stage classification. Transcriptome profiling revealed 1289 upregulated and 1897 downregulated genes. When intersected with employed CRC datasets, 284 DEGs were obtained. Comprehensive analysis using gene ontology and KEGG revealed enrichment of the DEGs in metabolic process, fatty acid biosynthesis, etc. The PPI network constructed using these 284 genes assisted in identifying 20 hub genes. Kaplan-Meier, GEPIA, and UALCAN analyses uncovered the clinicopathological relevance of these hub genes. Conclusively, the deep learning model achieved TNM-stage classification accuracy of 0.78 and 0.75 using 284 DEGs and 20 hub genes, respectively. The study represents a pioneer endeavor amalgamating transcriptomics, publicly available tissue datasets, and machine learning to unveil key CRC-associated genes. These genes are found relevant regarding the patients\' prognosis and diagnosis. The unveiled biomarkers exhibit robustness in TNM-stage prediction, thereby laying the foundation for future clinical applications and therapeutic interventions in CRC management.

Activation of the acute-phase cascade (APC) has been correlated with outcomes in various cancers, including head and neck squamous cell carcinoma (HNSCC). Primary drivers of the APC are the cytokines within the interleukin-6 (IL-6) and IL-1 families. Plasma levels of IL-6 family cytokines/soluble receptors (IL-6, IL-27, IL-31, OSM, CNTF, soluble (s-)gp130, s-IL-6Rα) and IL-1 family members (IL-1RA, s-IL-33Rα) were determined at diagnosis for 87 human papillomavirus (HPV)-negative (-) HNSCC patients. We then studied the 5-year Disease-Specific Survival (DSS) and Overall Survival (OS). Increased plasma levels of IL-6 (p < 0.001/p < 0.001) (DSS/OS), IL-31 (p = 0.044/p = 0.07), IL-1RA (p = 0.004/p = 0.035), soluble (s)-IL-6Rα p = 0.022/p = 0.035), and s-gp130 (p = 0.007/p = 0.003) at diagnosis were predictors of both OS and DSS from HPV(-) HNSCC patients. The cytokine DSS/OS predictions were associated with TNM stage and smoking history, whereas the soluble receptors IL-6Rα, gp130, and IL33Rα more uniquely predicted DSS/OS. Clinically, IL-6 levels above 2.5 pg/mL yielded 75% specificity and 70% sensitivity for DSS. In conclusion, high plasma levels of IL-6, IL-31, and IL-1RA, as well as the soluble receptors IL-6Rα, gp130, and IL33Rα, predicted clinical outcome. This shows their potential as candidates for both general therapy and immune therapy stratification, as well as being future platforms for the development of new immunotherapy.

BACKGROUND: The aim of this study was to explore the correlation between biomarkers of lipid metabolism and gastric cancer.
METHODS: 1120 gastric cancer patients and 1134 health examiners enrolled in this study. The clinic data and serum lipid level, including Total cholesterol (TC), Triglyceride (TG), Low-density lipoprotein cholesterol (LDL-C) and High-density lipoprotein cholesterol (HDL-C), were collected.
RESULTS: Serum TG and LDL-C levels in patients with gastric cancer were higher than those in the control group. HDL-C levels were lower than the control group (P < 0.05). HDL-C and LDL-C were significantly correlated with the risk of gastric cancer. Concentrating on clinicopathological features, increased TG was more frequently in male patients with distal gastric cancer, N0 stage and early TNM stage. Increased TC was more frequently in early T, N and TNM stage. Decreased HDL-C was more common in distal location and low-undifferentiated gastric cancer. LDL-C elevation was more common in distal gastric cancer and early T stage.
CONCLUSIONS: The serum lipid level of gastric cancer patients was higher than healthy controls. HDL-C and LDL-C abnormal correlated with gastric cancer risk. However, as the progresses of gastric cancer, poor patient intake, increased tumor consumption, and continuous declining in nutritional status, the levels of TC and TG gradually decreased in advanced gastric cancer.

Background Breast carcinoma has been the most prevalent cancer in women, with research-based evidence showing a significant rise in the incidence of cancer and related morbidity and mortality in the Indian subcontinent. The predictive value of plasmatic lactate dehydrogenase (LDH) levels has been studied in breast cancer. Numerous studies have connected high LDH values to a poor prognosis, increased risk of incidence, recurrence, and associated mortality in patients with breast carcinoma. This study aimed to assess the clinical profile of breast carcinoma and determine the correlation of serum lactate dehydrogenase levels with the stage of the disease and assessment of high-risk features using histopathology and immunohistochemistry. Methods A total of 75 patients with carcinoma breast were enrolled for this study and classified into two groups: upfront surgery and post-adjuvant therapy. Serum LDH levels were estimated a day before the surgery (baseline) and on postoperative days 1, 7, 14, and 30. The clinical tumor, node, metastasis (cTNM) staging was correlated with pathological tumor, node, metastasis TNM (pTNM) staging and immunohistochemistry findings. Results The clinical characteristics of breast cancer, serum LDH levels, and stage of the disease were collected and analyzed. A significant decreasing trend was noted in LDH values post-op days, and statistically significant higher LDH values were noted in the triple-negative group, positive lymph nodes, and positive lymphovascular invasion patients. Conclusion Regularly elevated levels or an unanticipated rise in serum LDH might indicate poor outcomes. Hence, this non-specific enzyme marker can be suggested to be used routinely to assess disease outcomes.

BACKGROUND: Colorectal cancer (CRC) ranks third in cancer incidence globally and is the second leading cause of cancer-related mortality. The nucleoside diphosphate kinase 1 (NME1) and netrin 1 receptor (DCC) genes have been associated with resistance against tumorigenesis and tumor metastasis. This study investigates the potential association between NME1 (rs34214448 G > T and rs2302254 C > T) and DCC (rs2229080 G > C and rs714 A > G) variants and susceptibility to colorectal cancer development.
METHODS: Samples from 232 colorectal cancer patients and 232 healthy blood donors underwent analysis. Variants were identified using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) methodology. Associations were assessed using odds ratios (OR), and the p values were adjusted with Bonferroni test.
RESULTS: Individuals carrying the G/T and T/T genotypes for the NME1 rs34214448 variant exhibited a higher susceptibility for develop colorectal cancer (OR = 2.68, 95% CI: 1.76-4.09, P = 0.001 and OR = 2.47, 95% CI: 1.37-4.47, P = 0.001, respectively). These genotypes showed significant associations in patients over 50 years (OR = 2.87, 95% CI: 1.81-4.54, P = 0.001 and OR = 2.99, 95% CI: 1.54-5.79, P = 0.001 respectively) and with early Tumor-Nodule-Metastasis (TNM) stage (P = 0.001), and tumor location in the rectum (P = 0.001). Furthermore, the DCC rs2229080 variant revealed that carriers of the G/C genotype had an increased risk for develop colorectal cancer (OR = 2.00, 95% CI: 1.28-3.11, P = 0.002) and were associated with age over 50 years, sex, and advanced TNM stages (P = 0.001).
CONCLUSIONS: These findings suggest that the NME1 rs34214448 and DCC rs2229080 variants play a significant role in colorectal cancer development.