Lymph Node Metastasis Status Research Articles

The Short- and Long-Term Surgical Results of Consecutive Hepatopancreaticoduodenectomy for Wide-Spread Biliary Malignancy.

Cancer-free resection (R0) is one of the most important factors for the long-term survival of biliary carcinoma. For some patients with widespread invasive cancer located between the hilar and intrapancreatic bile duct, hepatopancreaticoduodenectomy (HPD) is considered a radical surgery for R0 resection. However, HPD is associated with high morbidity and mortality rates. Furthermore, previous reports have not shown lymph node metastasis (LNM) status, such as the location or number, which could influence the prognosis after HPD. In this study, first, we explored the prognostic factors for survival, and second, we evaluated whether the LNM status (number and location of LNM) would influence the decision on surgical indications in patients with widely spread biliary malignancy. We retrospectively reviewed the medical records of 54 patients who underwent HPD with hepatectomy in ≥2 liver sectors from January 2003 to December 2021 (HPD-G). We also evaluated 54 unresectable perihilar cholangiocarcinoma patients who underwent chemotherapy from January 2010 to December 2021 (CTx-G). R0 resection was performed in 48 patients (89%). The median survival time (MST) and 5-year overall survival rate of the HPD-G and CTx-G groups were 36.9 months and 31.1%, and 19.6 months and 0%, respectively. Univariate and multivariate analyses showed that pathological portal vein involvement was an independent prognostic factor for survival (MST: 18.9 months). Additionally, patients with peripancreatic LNM had worse prognoses (MST: 13.3 months) than CTx-G. Patients with peripancreatic LNM or PV invasion might be advised to be excluded from surgery-first indications for HPD.

The Value of Percutaneous Contrast-Enhanced Ultrasound in Sentinel Lymph Node Identification, Metastatic Status and Burden Diagnosis in Early Breast Cancer.

The aim of this study was to evaluate the value of percutaneous contrast-enhanced ultrasound (PCEUS) in the identification and characterization of sentinel lymph node (SLN). A total of 102 breast cancer patients were collected and underwent preoperative PCEUS, which was used to identify SLN and lymphatic drainage. SLNs were classified into 4 enhancement patterns, including 6 subtypes: homogeneous (I), featured inhomogeneous (II) including inhomogeneous hypoenhancement (IIa) and annular or semi-annular enhancement (IIb), focal filling defect (III) including filling defect area < 50% (IIIa) and filling defect area ≥ 50% (IIIb), and no enhancement (IV). The enhancement patterns of SLNs were compared with the final pathological diagnosis. The identification rate of SLNs using PCEUS was 100% (102/102); the rate of identification of LCs was 100% (102/102), and the coincidence rate was 98.0% (100/102). Four lymphatic drainage patterns (LDPs) including 5 subtypes were found: single LC/single SLN(74.5%), multiple LCs/ single SLN (13.7%) including 2 subtypes:2 LCs/1 SLN and 3 LCs/1 SLN, single LC/multiple SLNs (7.8%), and multiple LCs/multiple SLNs (3.9%). A total of 86.3% (44/51) of patients without axillary metastasis could be safely selected for types I, IIa, and IIb, while the axillary metastasis rates of types III and IV were 74.4%and 87.5%, respectively (P < .001). Compared with grayscale US, the PCEUS significant improvement in diagnosing metastatic SLNs (.794 versus .579, P < .001). For the SLN metastatic burden, Types I, IIa, IIb, and IIIa had ≤2 SLNs metastases, with a pathological coincidence rate of (64/67, 95.5%), and types IIIb and IV had >2 SLNs metastases, with a pathological coincidence rate of (25/35, 71.4%) (P < .001). The AUC of PCEUS for the diagnosis of SLN metastatic status and burden was .794 and .879, respectively (P < .001). PCEUS has a high identification rate for SLN and has good potential for diagnosing SLN metastatic status and burden by enhancement patterns.

High PGAP3 expression is associated with lymph node metastasis and low CD8+T cell in patients with HER2+ breast cancer

BackgroundBreast cancer (BC) stands as the most prevalent malignancy among women and ranks as the second most frequently diagnosed cancer globally among newly identified cases. Post-GPI attachment to proteins factor 3（PGAP3）was reported to involve in lipid remodeling. However, its specific role in breast cancer remains inadequately elucidated. Consequently, the principal objective of this study was to investigate the clinical significance of PGAP3 in breast cancer. MethodsWe conducted an extensive analysis using both public databases and our own sample cohort to assess the role of PGAP3 in breast cancer. Immunohistochemistry was employed to assess PGAP3 expression, immune markers, and the co-expression of PGAP3 with key susceptibility genes. Data analysis was performed using the R programming language. ResultsOur findings revealed that PGAP3 is significantly overexpressed in breast cancer, particularly in human epidermal growth factor 2 positive (HER2 +) breast cancer cases (p < 0.001). Co-expression analyses demonstrated a significant correlation between PGAP3 and susceptibility genes associated with breast cancer, including BRCA1, BRCA2, PALB2, ATM, CHEK2, RAD51C, and RAD51D (p < 0.05). Logistic regression analysis identified PGAP3 as a significant predictor of estrogen receptor (ER), progesterone receptor (PR), HER2, and lymph node metastasis status (p < 0.01). Furthermore, higher PGAP3 expression was associated with decreased infiltration of CD8 + T cells in breast cancer samples. ConclusionOur study sheds light on the clinical significance of PGAP3 in breast cancer. PGAP3 is not only overexpressed in breast cancer but also correlates with key susceptibility genes, lymph node metastasis, and CD8 + T cell infiltration. These findings provide valuable insights into the potential role of PGAP3 as a biomarker in breast cancer and may contribute to our understanding of the disease's pathogenesis.

UTP23 Functions in Breast Cancer Progression and Predicts Poor Prognosis of Luminal a Breast Cancer

BackgroundLuminal A breast cancer is the most common molecular subtype of breast cancer. Exploring biomarkers to identify luminal A breast cancer patients at high risk of recurrence and metastasis has important clinical significance. UTP23 is a component of ribosomal small-subunit processome, which is involved in ribosome synthesis and RNA maturation. The role of UTP23 in breast cancer has not been reported. MethodsTCGA-BRCA data, LinkedOmics, STRING, Metascape and ssGSEA were used to analyze UTP23 expression in breast cancer and evaluate prognosis. Quantitative real-time PCR, western blot and in vitro cell experiment were used to demonstrate the role of UTP23 in breast cancer. ResultsUTP23 showed abnormally high expression in multiple cancers and was associated with poor prognosis. UTP23 was associated with T stage, lymph node metastasis, race, histological type, molecular subtypes and survival status in breast cancer. Importantly, UTP23 was significantly associated with poor OS in luminal A or early breast cancer, not in non-luminal A or advanced breast cancer. UTP23 expression was significantly correlated with immune cells infiltration. Enrichment analysis suggested that UTP23 might regulate cell cycle and cell division. Bioinformatics analysis showed DCAF13 might be downstream factor of UTP23. UTP23 expression promoted MCF-7 cells proliferation, migration and invasion possibly through regulating DCAF13 expression. ConclusionsUTP23 may function in breast cancer progression. The elevated UTP23 may be a potential prognostic biomarker for luminal A or early breast cancer.

The Relationship between Body Mass Index (BMI) and Clinical Pathological Profile of Invasive Breast Carcinoma Patients in the Department of Anatomic Pathology FKUI/RSCM from 2019 to 2022

Background&#x0D; Breast cancer is the most prevalent malignancy among women and is the second largest contributor to cancer-related deaths globally. Women with a high body mass index (BMI) are at a greater risk of developing breast cancer and an increased risk of lymph node metastasis. This retrospective study aimed to determine the relationship between BMI and the clinical pathological profile of invasive breast carcinoma (IBC) patients.&#x0D; Method&#x0D; This study was conducted from 2019 to 2022. Data were collected through the archives of the Department of Anatomic Pathology FKUI/RSCM (Faculty of Medicine, University of Indonesia/Cipto Mangunkusumo Hospital). Clinical pathological data were collected. The histological type, grade, lymphovascular invasion, and lymph node metastasis of the tumors were re-evaluated. The chi-square hypothesis test was used to determine the relationship between BMI and clinical pathological profile. The results were considered statistically significant with a p &lt;0.05.&#x0D; Result&#x0D; A total of 151 cases of IBC with lymph node dissection from 2019 to 2022 were included in this study, all of which were female, with the majority being &gt;50 years old (55%). The most common tumor size and histological type were T2 (39,7%) and invasive ductal carcinoma NST (74,8%), 49% of cases were grade 3 tumors. Most IBC cases had an obese BMI (49%), 63.1% with lymph node metastasis had an overweight-obese BMI. Statistical analysis was performed between BMI and lymph node metastasis status, and p-value=0.025 was obtained. The relationship between tumor size and lymphovascular invasion with lymph node metastasis was also found to be statistically significant, as indicated by a p-value of 0.000.&#x0D; Conclusion&#x0D; Cases with lymph node metastasis had the highest rate of overweight-obesity, and a significant relationship was found between BMI and lymph node metastasis status. A significant relationship was also found between tumor size and lymphovascular invasion with lymph node metastasis.

Survival outcomes of low-risk papillary thyroid carcinoma at different risk levels: a corollary for active surveillance.

This study aims to compare the outcomes of active surveillance (AS) in low-risk papillary thyroid carcinoma (PTC) patients with different tumor sizes and lymph node metastasis status, in order to establish appropriate management strategies. By analyzing these results, this study provides valuable insights for the effective management of such patients, addressing the issues and challenges associated with AS in practical clinical practice. The study utilized the SEER database supported by the National Cancer Institute of the United States, extracting data of PTC diagnosed between 2000 and 2015. Statistical analyses were conducted using inverse probability weighting (IPTW) and propensity score matching (PSM), including Kaplan-Meier survival curves and Cox regression models, to evaluate the impact of different tumor sizes and lymph node metastasis status on thyroid cancer-specific survival (TCSS). A total of 57,000 PTC patients were included, with most covariates having standardized mean differences below 10% after IPTW and PSM adjustments. The TCSS of PTC with a diameter smaller than 13mm is significantly better than that of tumors with a diameter larger than 13mm, regardless of the presence of lymph node metastasis. Among PTC cases with a diameter smaller than 13mm, the TCSS of patients is similar, regardless of the presence of lymph node metastasis. However, in PTC cases with a diameter larger than 13mm, the presence of lateral neck lymph node metastasis (N1b stage) significantly impacts the TCSS, although the absolute impact on TCSS rate is minimal. The treatment strategy of AS is safe for patients with T1a stage papillary thyroid microcarcinoma (PTMC). However, for patients with T1b stage, if the tumor diameter exceeds 13mm or there is lymph node metastasis in the lateral neck region, the TCSS will be significantly affected. Nevertheless, the absolute impact on survival is relatively small.

MRI-based automated machine learning model for preoperative identification of variant histology in muscle-invasive bladder carcinoma.

It is essential yet highly challenging to preoperatively diagnose variant histologies such as urothelial carcinoma with squamous differentiation (UC w/SD) from pure UC in patients with muscle-invasive bladder carcinoma (MIBC), as their treatment strategy varies significantly. We developed a non-invasive automated machine learning (AutoML) model to preoperatively differentiate UC w/SD from pure UC in patients with MIBC. A total of 119 MIBC patients who underwent baseline bladder MRI were enrolled in this study, including 38 patients with UC w/SD and 81 patients with pure UC. These patients were randomly assigned to a training set or a test set (3:1). An AutoML model was built from the training set, using 13 selected radiomic features from T2-weighted imaging, semantic features (ADC values), and clinical features (tumor length, tumor stage, lymph node metastasis status), and subsequent ten-fold cross-validation was performed. A test set was used to validate the proposed model. The AUC of the ROC curve was then calculated for the model. This AutoML model enabled robust differentiation of UC w/SD and pure UC in patients with MIBC in both training set (ten-fold cross-validation AUC = 0.955, 95% confidence interval [CI]: 0.944-0.965) and test set (AUC = 0.932, 95% CI: 0.812-1.000). The presented AutoML model, that incorporates the radiomic, semantic, and clinical features from baseline MRI, could be useful for preoperative differentiation of UC w/SD and pure UC. This MRI-based automated machine learning (AutoML) study provides a non-invasive and low-cost preoperative prediction tool to identify the muscle-invasive bladder cancer patients with variant histology, which may serve as a useful tool for clinical decision-making. •It is important to preoperatively diagnose variant histology from urothelial carcinoma in patients with muscle-invasive bladder carcinoma (MIBC), as their treatment strategy varies significantly. •An automated machine learning (AutoML) model based on baseline bladder MRI can identify the variant histology (squamous differentiation) from urothelial carcinoma preoperatively in patients with MIBC. •The developed AutoML model is a non-invasive and low-cost preoperative prediction tool, which may be useful for clinical decision-making.

Patterns of the lymph node metastasis and the influencing factors in esophagogastric junction cancers.

A retrospective analysis of 214 cases of esophagogastric junction cancers (EGJCs) in Kunming, Yunnan Province, was conducted to investigate the lymph node metastasis (LNM) pattern for EGJCs and its associated risk factors (RFs), as well as the predictive value of common clinical metabolic indicators for it. The clinical data of 214 patients diagnosed with EGJCs by electronic gastroscope and postoperative pathology between 2013 and 2021at the First Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, and the Second Affiliated Hospital of Kunming Medical University were retrospectively examined. Preoperative gastroscopy, imaging, biochemical data, and postoperative pathological findings analysis in EGJCs were statistically analyzed to determine the RFs of LNM. At presentation, 92.5% of EGJCs were progressive malignancies, including 68.2% LNMs, 79.5% abdominal lymph nodes (ALN), 20.1% mediastinal lymph nodes (MLN), and 27.1% distal metastases. The ratio of Siewert subtypes was approximately 2:11:7 (type I to type II to type III). In terms of age, disease duration at initial presentation, history, tumor length, pathological biopsy histology, degree of differentiation, depth of infiltration, LNM status, MLN metastasis, and surgical route, the differences between the three Siewert subgroups were statistically significant (p<0.05). Multifactor analysis revealed that the proportion of patients aged <65at the time of consultation was significantly more significant in Siewert II and Siewert III than in Siewert I. Significantly more patients than in Siewert I had <2 months of disease duration at the time of their first consultation. The proportion of patients with tumors <3 Cm in length was significantly higher than in Siewert I. For the RFs analysis of LNM, Siewert staging (type I and type II), depth of infiltration, and distant metastasis were the independent RFs for LNM. The depth of infiltration and family history of the tumor were the independent RFs for ALN metastasis, and the number of lymph nodes cleared in the abdominal and mediastinal regions was a protective factor for ALN metastasis. Siewert staging(type I and type II), infiltration depth, invasion of the esophagus by the tumor, tumor length, and distant metastasis were independent risk factors for MLN metastasis. Among the metabolic variables evaluated, BMI was an independent RF for LNM, fasting glucose was an independent RF for ALN metastasis, and triacylglycerol was a protective factor for MLN metastasis. EGJCs are frequently advanced at presentation, characterized by minimal differentiation and a high incidence of LNM. The Siewert subtype is concentrated near the stomach. Different Siewert subtypes exhibit distinct clinicopathological characteristics. LNM and MLN metastasis risk are considerably higher in type I tumors compared to types II and III. There is a strong correlation between LNM and MLN metastasis and distant metastasis in EGJCs, so Siewert I is more aggressive and associated with a worse prognosis. EGJCs have numerous RFs associated with LNM, and there are similarities and differences in the RFs affecting their LNM, ALN metastases, and MLN metastases, which are related to their unique anatomical features. There is a close relationship between metabolic factors and EGJCs with some predictive value.

362. AUTOMATED DETECTION OF UPPER MEDIASTINAL LYMPH NODES METASTASIS OF ESOPHAGEAL SQUAMOUS CANCER USING BERT ON COMPUTED TOMOGRAPHY

Abstract Upper mediastinal lymph node (LN) metastasis is the extremely frequent metastasis lymph node site and dissection of this site of lymph node harbors a high risk of recurrent laryngeal nerve injury. Prediction of LN metastasis before dissection is necessary for personalized therapy. We developed a pre-training unsupervised deep learning model based on Bidirectional Encoder Representation from Transformers (BERT) to extract features from pre-operational CT images and detect patients with LN metastasis. A total of 3769 esophageal cancer patients from 2012 to 2020 with complete post-surgical pathology in our institute were included in this study, 823 of which had upper mediastinal LN metastasis. The extracted features of CT images were labeled with the LN metastasis status of the corresponding patients and then divided into training and validation groups (7:3) for training. In order to keep balancing of the positive and negative ratio in the test dataset, 800 patients were randomly selected from the validation group (1:1). The BERT-based pretrained learning model achieved a AUROC of 0.651 on detection of upper mediastinal LN metastasis. The specificity of this model could reach up to 0.732. Our model can be used to improve diagnostic ability of upper mediastinal LN metastasis before surgery.

Nomogram for prognosis of elderly patients with cervical cancer who receive combined radiotherapy

This retrospective study identified prognostic factors to help guide the clinical treatment of elderly patients (≥ 65 years) with cervical cancer who had undergone radiotherapy. A personalized model to predict 3- and 5-years survival was developed. A review was conducted of 367 elderly women with cervical cancer (staged II–III) who had undergone radiotherapy in our hospital between January 2012 and December 2016. The Cox proportional hazards regression model was used for survival analysis that considered age, hemoglobin, squamous cell carcinoma antigen, pathologic type, stage, pelvic lymph node metastasis status, and others. A nomogram was constructed to predict the survival rates. The median follow-up time was 71 months (4–118 months). The 3- (5-) years overall, progression-free, local recurrence-free, and distant metastasis-free survival rates were, respectively, 91.0% (84.4%), 92.3% (85.9%), 99.18% (99.01%), and 99.18% (97.82%). The following were significant independent prognostic factors for overall survival: tumor size, pre-treatment hemoglobin, chemotherapy, and pelvic lymph node metastasis. The C-index of the line chart was 0.699 (95% CI 0.652–0.746). The areas under the receiver operating characteristic curves for 3- and 5-years survival were 0.751 and 0.724. The nomogram was in good concordance with the actual survival rates. The independent prognostic factors for overall survival in elderly patients with cervical cancer after radiotherapy were: tumor size, pre-treatment hemoglobin, chemotherapy, and pelvic lymph node metastasis. The novel prognostic nomogram based on these factors showed good concordance with the actual survival rates and can be used to guide personalized clinical treatment.

Computed Tomography-Based Predictive Model for the Probability of Lymph Node Metastasis in Gastric Cancer: A Meta-analysis.

Whether or not a gastric cancer (GC) patient exhibits lymph node metastasis (LNM) is critical to accurately guiding their treatment and prognostic evaluation, necessitating the ability to reliably predict preoperative LNM status. The present meta-analysis sought to examine the diagnostic value of computed tomography (CT)-based predictive models as a tool to gauge the preoperative LNM status of patients with GC. Relevant articles were identified in the PubMed, Web of Science, and Wanfang databases. These studies were used to conduct pooled analyses examining sensitivity, specificity, positive likelihood ratio (PLR), and negative likelihood ratio (NLR) values, and area under the curve values were computed for summary receiver operating characteristic curves. The final meta-analysis incorporated data from 15 studies, all of which were conducted in China, enrolling 3,817 patients with GC (LNM+: 1790; LNM-: 2027). The developed CT-based predictive model exhibited respective pooled sensitivity, specificity, PLR, and NLR values of 84% (95% confidence interval [CI], 0.79-0.87), 81% (95% CI, 0.76-0.85), 4.39 (95% CI, 3.40-5.67), and 0.20 (95% CI, 0.16-0.26). The identified results were not associated with significant potential for publication bias ( P = 0.071). Similarly, CT-based analyses of LN status exhibited respective pooled sensitivity, specificity, PLR, and NLR values of 62% (95% CI, 0.53-0.70), 77% (95% CI, 0.72-0.81), 2.71 (95% CI, 2.20-3.33), and 0.49 (95% CI, 0.40-0.61), with no significant risk of publication bias ( P = 0.984). Overall, the present meta-analysis revealed that a CT-based predictive model may outperform CT-based analyses alone when assessing the preoperative LNM status of patients with GC, offering superior diagnostic utility.

Predicting Survival of Patients with Nonmetastatic Breast Cancer Based on Fibrinogen-to-Albumin Ratio and Lymphocyte-to-Monocyte Ratio: A Nomogram-Based Assessment

Background: Parameters of systemic inflammation have received attention as prognostic surrogates in various malignant tumors. Fibrinogen-to-albumin ratio (FAR) and lymphocyte-to-monocyte ratio (LMR) correlate with tumor growth and dissemination. We aimed to bring the combination of FAR and LMR (FAR-LMR) together to establish novel nomograms for survival and recurrence in nonmetastatic breast cancer patients. Methods: We retrospectively recruited 461 female patients with nonmetastatic breast cancer from January 2011 to December 2013 in our hospital and randomly assigned them into the training cohort (N = 318) and the validation cohort (N = 143). The potential predictive factors for overall survival (OS), locoregional recurrence-free survival (LRFS), and distant metastasis-free survival (DMFS) were assessed by Cox proportional hazards models and log-rank test. Results: Elevated FAR was associated with poor OS (p < 0.001) and DMFS (p = 0.02), whereas increased LMR was associated with satisfactory OS (p = 0.01) and LRFS (p = 0.01). High FAR combined with low LMR was associated with less favorable OS (p = 0.001), LRFS (p = 0.005), and DMFS (p = 0.003) Based on multivariate analysis, FAR-LMR, tumor size, lymph node metastasis, age, and pathologic status contributed to prognostic nomograms of OS, DMFS, and LRFS. Nomograms presented exceptional performance for 3-, 5-, and 8-year OS, DMFS, and LRFS prediction compared with clinical TNM stage. The C-index was significantly higher than that of TNM stage, either of FAR or LMR (3-year: 0.709 vs. 0.621 vs. 0.544 vs. 0.641, 5-year: 0.761 vs. 0.597 vs. 0.605 vs. 0.677, 8-year: 0.84 vs. 0.62 vs. 0.539 vs. 0.623). Conclusions: We developed and validated a convenient predictive model for the survival outcomes of patients with nonmetastatic breast cancer. The nomograms can be utilized as auxiliary tools to provide prognostic information.

Colorectal cancer-secreted exosomal circ_001422 plays a role in regulating KDR expression and activating mTOR signaling in endothelial cells by targeting miR-195-5p.

As non-coding RNAs, exosomal circular RNAs (circRNAs) regulate colorectal cancer (CRC) progression, although the functional mechanisms by which such molecules affect the tumor microenvironment are still elusive. Herein, we aimed to explore the potential clinical significance of a signature of five serum-derived circRNAs in CRC and investigated the mechanisms underlying endothelial cell angiogenesis mediated by CRC-secreted exosomal circ_001422. The expression of a signature of five serum-derived circRNAs (circ_0004771, circ_0101802, circ_0082333, circ_0072309, and circ_001422) were measured by RT-qPCR, and their associations with tumor staging and lymph node metastasis were further evaluated in CRC patients. In silico analysis was used to show the relationship between circ_001422, miR-195-5p, and KDR, validated by dual-luciferase reporter and Western blotting assays. CRC cell-derived exosomes were isolated and characterized by scanning electron microscopy and Western blotting. Endothelial cell uptake of PKH26-labeled exosomes was demonstrated using a spectral confocal microscope. In vitro genetic strategies were used to exogenously alter the expression level of circ_001422 and miR-195-5p expression. Cell proliferation assay, transwell migration assay, and capillary tube formation assay were conducted to explore the role of CRC-secreted exosomal circ_001422 in endothelial cell function in vitro. The expression levels of serum-derived circ_0004771, circ_0101802, circ_0082333, and circ_001422 were significantly higher in CRC and were positively correlated with the lymph node metastasis status. However, circ_0072309 showed a significant down-regulation in CRC than in healthy individuals. Furthermore, a higher expression level of circ_001422 in both cellular and exosomal fractions was found in HCT-116 CRC cells. We found that HCT-116 exosomes considerably enhanced proliferation and migration of endothelial cells through shuttling of circ_001422. We also observed that exosomes derived from HCT-116 cell, but not non-aggressive Caco-2 CRC cells, increased in vitro tubulogenesis of endothelial cells. Importantly, knockdown of circ_001422 impaired the capability of endothelial cells to form the capillary-like tube structures. CRC-secreted circ_001422 acted as an endogenous miR-195-5p sponge to inhibit miR-195-5p activity, which led to increased KDR expression and mTOR signaling activation in endothelial cells. Importantly, ectopic expression of miR-195-5p mimicked the effect of circ_001422 silencing on KDR/mTOR signaling in endothelial cells. This study attributed a biomarker role for circ_001422 in CRC diagnosis and proposed a novel mechanism whereby circ_001422 up-regulates KDR through sponging miR-195-5p. These interactions may give rise to the activation of mTOR signaling and may be a possible clarification for the pro-angiogenesis effects of CRC-secreted exosomal circ_001422 on endothelial cells.

Association of Cervical Lymph Node Metastasis and Perineural Invasion in Patients with Oral Cavity Squamous Cell Carcinoma

Background: Cervical lymph node metastasis (CLNM) is one of the key prognostic factors in oral squamous cell carcinoma and positive perineural invasion (PNI) is a predictor of cervical lymph node metastasis, recurrence, and decline-free survival. This study determines perineural invasion association with cervical lymph node metastasis in oral cavity squamous cell carcinoma (OCSCC). Method: We analyzed the laboratory data collected from the surgical pathology files of a tertiary care hospital in Karachi. This retrospective study included all diagnosed cases of OCSCC that underwent cervical lymph node dissection during the 10-year period from June 2008 to March 2019. The cases were characterized according to age, gender, perineural invasion, and lymph node metastasis. The data was analyzed using SPSS and Chi-Square test was used to find the association between the cervical lymph node metastatic and PNI status. Results: A total of 527 diagnosed cases of OCSCC with cervical neck dissection were found. It is evident from our study that OCSCC with neck dissection specimens is frequently seen in males, mostly belonging to the middle adult age group followed by young adults. Of the 527 cases, 165 showed PNI (31.3%), and 20% of the PNI cases were positive for cervical lymph node metastasis, while 40% showed benign cervical lymph nodes with negative PNI. Conclusion: This study highlights the single parameter of PNI and its association with cervical lymph node metastasis and showed a significant relationship between perineural invasion and cervical lymph node metastatic status (p &lt; .001).

Overexpression of MRPL19 in predicting poor prognosis and promoting the development of lung adenocarcinoma.

Mitochondrial ribosomal protein L19 (MRPL19) is a member of the mitochondrial ribosomal protein (MRP) family. MRPs have a role in the progression of many cancers. However, the role of MRPL19 in lung adenocarcinoma (LUAD) is yet unknown. The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets, real-time polymerase chain reaction, and immunohistochemistry (IHC) were used to assess MRPL19 expression and clinical relevance. Gene Expression Profiling Interactive Analysis (GEPIA) and the online Kaplan-Meier (KM) Plotter database were used to determine the prognostic significance. Through use of LinkedOmics, genes that were coexpressed with MRPL19 and its regulators were identified. The biological roles of MRPL19 were investigated through R-implemented packages and RNA interference. The Tumor Immune Estimation Resource (TIMER) was employed to assess the connection between MRPL19 expression and infiltrated immune cells in LUAD. MRPL19 expression in LUAD was upregulated and was correlated with lymph node metastasis, differentiation level, and tumor status. MRPL19 was prognostic and associated with poor prognosis. Functional network analysis revealed that MRPL19 may be associated with the cell cycle, cell adhesion molecules, spliceosome, and T-helper cell differentiation and was regulated by several microRNA and the E2F family. The gene set enrichment analysis (GSEA) and protein-protein interaction (PPI) network indicated that MRPL19 was correlated with cancer proliferation signaling pathways. The immune infiltration analysis revealed a correlation between MRPL19 expression and the extent of B cells, CD4+ T cells, and dendritic cells' infiltration in LUAD. Additionally, MRPL19 knockdown in LUAD cells substantially reduced cell growth, migration, and invasion of malignant cells. The poor prognosis and immunological infiltration in LUAD were significantly associated with MRPL19, which may have pro-oncogenic effects on the disease.

CTSL, a prognostic marker of breast cancer, that promotes proliferation, migration, and invasion in cells in triple-negative breast cancer.

In the world, the incidence of breast cancer has surpassed that of lung cancer, and it has become the first malignant tumor among women. Triple-negative breast cancer (TNBC) shows an extremely heterogeneous malignancy toward high recurrence, metastasis, and mortality, but there is a lack of effective targeted therapy. It is urgent to develop novel molecular targets in the occurrence and therapeutics for TNBC, and novel therapeutic strategies to block the recurrence and metastasis of TNBC. In this study, CTSL (cathepsin L) expression in tissues and adjacent tissues of TNBC patients was monitored by immunohistochemistry and western blots. The correlations between CTSL expressions and clinicopathological characteristics in the patient tissues for TNBC were analyzed. Cell proliferation, migration, and invasion assay were also performed when over-expressed or knocked-down CTSL. We found that the level of CTSL in TNBC is significantly higher than that in the matched adjacent tissues, and associated with differentiated degree, TNM Stage, tumor size, and lymph node metastatic status in TNBC patients. The high level of CTSL was correlated with a short RFS (p<0.001), OS (p<0.001), DMFS (p<0.001), PPS (p= 0.0025) in breast cancer from online databases; while in breast cancer with lymph node-positive, high level of CTSL was correlated with a short DMFS (p<0.001) and RFS (p<0.001). Moreover, in vitro experiments showed that CTSL overexpression promotes the abilities for proliferation, migration, and invasion in MCF-7 and MDA-MB-231 cell lines, while knocking-down CTSL decreases its characteristics in MDA-MB-231 cell lines. CTSL might involve into the regulation of the proliferation, invasion, and metastasis of TNBC. Thus, CTSL would be a novel, potential therapeutic, and prognostic target of TNBC.

Exosome-derived ANXA9 functions as an oncogene in breast cancer.

Breast cancer (BCA) is one of the most prevalent cancers among women. Emerging evidence has revealed that Annexin A-9 (ANXA9) plays a crucial function in the development of some cancers. Notably, ANXA9 has been reported to be a new prognostic biomarker for gastric and colorectal cancers. However, its expression and biological function in BCA have not yet been investigated. Using online bioinformatics tools such as TIMER, GEPIA, HPA, and UALCAN, we predicted ANXA9 expression and its correlation with the clinicopathological characteristics of BCA patients. RT-qPCR and western blot were utilized to measure ANXA9 mRNA and ANXA9 protein expression in BCA patient tissues and cells. BCA-derived exosomes were identified by transmission electron microscopy. Functional assays were employed to evaluate the biological role of ANXA9 in BCA cell proliferation, migration, invasion, and apoptosis. A tumor xenograft in vivo model was utilized to assess the role of ANXA9 in tumor growth in mice. Bioinformatics and functional screening analysis revealed that ANXA9 was highly expressed in BCA patient tissues, with median ANXA9 expression 1.5- to 2-fold higher than in normal tissues (p < 0.05). RT-qPCR confirmed that ANXA9 expression in BCA tissues was around 1.5-fold higher than the adjacent normal tissues (p < 0.001). ANXA9 expression in different subtypes of BCA also showed a difference, and ANXA9 was found to be mostly significantly upregulated in luminal BCA relative to normal tissues or other histological subtypes (p < 0.001). Moreover, ANXA9 expression was elevated in different races, ages, clinical stages, node metastasis status, and menopause status groups relative to the normal group (p < 0.001). Furthermore, ANXA9 was found to be secreted by BCA tissue-derived exosomes and its expression was upregulated 1- to 7-fold in BCA cells treated with exosomes (p < 0.001), while its expression in MCF10A cells was not significantly altered by treatment with exosomes (p > 0.05). ANXA9 silencing induced a significant decrease of around 30% in the colony number of BCA cells (p < 0.01). The number of migrated and invaded BCA cells also decreased by around 65 and 68%, respectively, after silencing ANXA9 (p < 0.01). Tumor size was significantly reduced (nearly half) in the LV-sh-ANXA9 group relative to the LV-NC group in the xenograft model (p < 0.01), suggesting that ANXA9 silencing repressed tumor progression in BCA progression in vitro and in vivo. In conclusion, exosome-derived ANXA9 functions as an oncogene that facilitates the proliferation, migration, and invasiveness of BCA cells and enhances tumor growth in BCA development, which may provide a new prognostic and therapeutic biomarker for BCA patients.

Clinicopathological features and surgical treatment of thyroid papillary carcinoma in Hashimoto thyroiditis

Background and Aim: Papillary thyroid carcinoma (PTC) is the most prevalent types of thyroid cancer. The present study aimed to investigate the clinicopathological features and surgical treatment of thyroid papillary carcinoma in Hashimoto thyroiditis. Patients and Methods: A cross-sectional study was carried out on 486 papillary thyroid carcinoma patients in the surgical department of Mardan Medical Complex, Mardan Pakistan from March 2020 to March 2023. All the patients were categorized into two groups: Group-I (papillary thyroid carcinoma with Hashimoto thyroiditis) and Group-II (papillary thyroid carcinoma without Hashimoto thyroiditis). Serum thyroid-stimulating hormone (TSH), age, central compartment lymph node metastasis (CLNM), gender, nodular size, and invasive status were different clinicopathological factors recorded. SPSS version 27 was used for data analysis. Results: The overall mean age was 42.84±10.8 years. Out of 486 patients, Group-I had 76 (15.6%) patients whereas Group-II had 410 (84.4%) patients. There were 52 (10.7%) male and 434 (89.3%) females. The incidence of final diagnosis of benign thyroid nodule and PTC was 53.9% (n=262) and 46.1% (n=224) respectively. The prevalence of PT in Group-I was significantly higher 56.8% 57.9% (n=44) than in Group-II 43.4% (n=178).

Predicting Lymph Node Metastasis Status from Primary Muscle-Invasive Bladder Cancer Histology Slides Using Deep Learning: A Retrospective Multicenter Study.

Accurate prediction of lymph node metastasis (LNM) status in patients with muscle-invasive bladder cancer (MIBC) before radical cystectomy can guide the use of neoadjuvant chemotherapy and the extent of pelvic lymph node dissection. We aimed to develop and validate a weakly-supervised deep learning model to predict LNM status from digitized histopathological slides in MIBC. We trained a multiple instance learning model with an attention mechanism (namely SBLNP) from a cohort of 323 patients in the TCGA cohort. In parallel, we collected corresponding clinical information to construct a logistic regression model. Subsequently, the score predicted by the SBLNP was incorporated into the logistic regression model. In total, 417 WSIs from 139 patients in the RHWU cohort and 230 WSIs from 78 patients in the PHHC cohort were used as independent external validation sets. In the TCGA cohort, the SBLNP achieved an AUROC of 0.811 (95% confidence interval [CI], 0.771-0.855), the clinical classifier achieved an AUROC of 0.697 (95% CI, 0.661-0.728) and the combined classifier yielded an improvement to 0.864 (95% CI, 0.827-0.906). Encouragingly, the SBLNP still maintained high performance in the RHWU cohort and PHHC cohort, with an AUROC of 0.762 (95% CI, 0.725-0.801) and 0.746 (95% CI, 0.687-0.799), respectively. Moreover, the interpretability of SBLNP identified stroma with lymphocytic inflammation as a key feature of predicting LNM presence. Our proposed weakly-supervised deep learning model can predict the LNM status of MIBC patients from routine WSIs, demonstrating decent generalization performance and holding promise for clinical implementation.

Effect of HER2 expression status on the prognosis of patients with HR+/HER2‑ advanced breast cancer undergoing advanced first‑line endocrine therapy.

The present study aimed to retrospectively assess the effects of human epidermal growth factor receptor 2 (HER2) expression on the diagnosis of patients with hormone receptor (HR)+/HER2- late-stage breast cancer undergoing advanced first-line endocrine-based treatment. A total of 72 late-stage breast tumor cases from June 2017 to June 2019 were selected from the Department of Surgical Oncology, Shaanxi Provincial People's Hospital (Xi'an, China) and included in the present study. The expression of estrogen receptor, progesterone receptor and HER2 was detected by immunohistochemistry. The subjects were divided into two groups: the HER2-negative (0) cohort (n=31) and the HER2 low expression cohort (n=41). The age, BMI, Karnofsky Performance Status (KPS) score, tumor size, lymph node metastasis, pathological type, Ki-67 expression and menopausal status of the patients were obtained through the electronic medical record system of Shaanxi Provincial People's Hospital. Progression-free survival (PFS) and overall survival (OS) were evaluated for all patients. The median PFS and OS of the HER2(0) cohort were longer than those of the HER2 low expression cohort (all P<0.05). It was shown that age (hazard ratio, 6.000 and 5.465), KPS score (hazard ratio, 4.000 and 3.865), lymph node metastasis (hazard ratio, 3.143; 2.983) and HER2 status (hazard ratio, 3.167 and 2.996) were independent influencing factors of the prognosis of patients with HR+/HER2- advanced breast cancer (ABC) (all P<0.05). Three models (model 1, no parameters adjusted; model 2, BMI, tumor size, pathological type, Ki-67 and menopausal status adjusted; and model 3, age, KPS functional status score and lymph node metastasis adjusted based on model 2) were established within the HER2(0) cohort as the reference for statistical analysis using the multivariate Cox's regression test. In models 2 and 3, the risk of poor prognosis of ABC within the HER2 low expression cohort was significantly higher compared with that in the HER2(0) cohort (hazard ratio, 3.558 and 4.477; 95% CI, 1.349-9.996 and 1.933-11.586; P=0.003 and P<0.001). The HER2 expression status of patients with HR+/HER2- ABC receiving advanced first-line endocrine therapy may affect PFS and OS.