Application of machine learning for predicting lymph node metastasis in T1 colorectal cancer: a systematic review and meta-analysis.

BACKGROUND: We review and analyze research on the application of machine learning (ML) and deep learning (DL) models to lymph node metastasis (LNM) prediction in patients with T1 colorectal cancer (CRC). Predicting LNM before radical surgery is important in patients with T1 CRC. However, current surgical treatment guidelines are limited. LNM prediction using ML or DL may improve predictive accuracy. The diagnostic accuracy of LNM prediction using ML- and DL-based models for patients with CRC was assessed. METHODS: We performed a comprehensive search of the PubMed, Embase, and Cochrane databases (inception to April 30th of 2022) for studies that applied ML or DL to LNM prediction in T1 CRC patients specifically to compare with histopathological findings and not related to radiological aspects. RESULTS: 33,199 T1 CRC patients enrolled across seven studies with a retrospective design were included. LNM was observed in 3,173 (9.6%) patients. Overall, the ML- and DL-based model exhibited a sensitivity of 0.944 and specificity of 0.877 for the prediction of LNM in patients with T1 CRC. Six different types of ML and DL models were used across the studies included in this meta-analysis. Therefore, a high degree of heterogeneity was observed. CONCLUSIONS: The ML and DL models provided high sensitivity and specificity for predicting LNM in patients with T1 CRC, and the heterogeneity between studies was significant. These results suggest the potential of ML or DL as diagnostic tools. However, more reliable algorithms should be developed for predicting LNM before surgery in patients with T1 CRC.

[Risk factors analysis and prediction model establishment of contralateral central lymph node metastasis in intermediate-to-high risk unilateral papillary thyroid carcinoma].

Objective: To explore the risk factors of contralateral central lymph nodes (Cont-CLNs) metastasis in intermediate-to-high risk unilateral papillary thyroid carcinoma and establish a prediction model. Methods: The clinical data of 206 patients receiving thyroid cancer surgery at Nantong University Affiliated Hospital between January 2021 and June 2023 were retrospectively analyzed, including 50 males and 156 females, with an age of [M(Q1, Q3)] 49.0(33.8, 57.0) years old. The risk factors of Cont-CLNs metastasis were screened by univariate analysis and multivariate logistic regression analysis. A nomogram was constructed for predicting Cont-CLNs metastasis in intermediate-to-high risk uPTC. The area under the receiver operating characteristic (ROC) curve(AUC), calibration curve, and decision curve analysis (DCA) were used to evaluate the model's predictive ability, accuracy, and clinical applicability, respectively. R language was used to randomly select 70% of the patients to establish a validation group for internal validation of the model. Results: Patients were divided into a metastasis group (n=56) and a non-metastasis group (n=150) based on the occurrence of Cont-CLNs metastasis. The ages of the two groups were 39.0 (28.0, 56.8) years and 51.0 (38.8, 57.0) years, respectively. There were statistically significant differences in gender, maximum tumor diameter (>1 cm), ipsilateral central lymph nodes (Ipsi-CLNs) metastasis, number of Ipsi-CLNs metastases (≥4), and lateral lymph node metastasis and Cont-CLNs metastasis between the two groups (all P<0.05). The results of multivariate logistic regression analyses showed that males(OR=2.926, 95%CI: 1.063-8.051), maximum tumor diameter>1 cm(OR=4.471, 95%CI: 1.344-14.877), and number of Ipsi-CLNs metastases≥4 (OR=5.011, 95%CI: 1.815-13.834) were risk factors for Cont-CLNs metastasis (all P<0.05). The AUC of the ROC curve, sensitivity, and specificity for predicting Cont-CLNs metastasis in intermediate-to-high risk uPTC by the prediction model in the modeling group were 0.821 (95%CI: 0.744-0.898), 82.5%, and 63.4%, respectively. In the internal validation group, the AUC of the ROC curve, sensitivity, and specificity for predicting Cont-CLNs metastasis in intermediate-to-high risk uPTC by the prediction model were 0.810 (95%CI: 0.717-0.902), 63.3%, and 83.7%, respectively. The calibration curves of the modeling group and the validation group showed that the model had good calibration ability. The DCA curves of the modeling group and the validation group indicated that the prediction model had good clinical adaptability. Conclusions: The prediction model constructed in this study has good predictive performance for Cont-CLNs metastasis in intermediate-to-high uPTC. When patient with intermediate-to-high risk uPTC is male, with maximum tumor diameter>1 cm, and the number of Ipsi-CLNs metastases≥4 should be alert to Cont-CLNs metastasis, and bilateral central lymph node dissection may be considered.

Single-cell exome sequencing reveals polyclonal seeding and TRPS1 mutations in colon cancer metastasis.

Liver metastasis remains the primary cause of mortality in patients with colon cancer. Identifying specific driver gene mutations that contribute to metastasis may offer viable therapeutic targets. To explore clonal evolution and genetic heterogeneity within the metastasis, we conducted single-cell exome sequencing on 150 single cells isolated from the primary tumor, liver metastasis, and lymphatic metastasis from a stage IV colon cancer patient. The genetic landscape of the tumor samples revealed that both lymphatic and liver metastases originated from the same region of the primary tumor. Notably, the liver metastasis was derived directly from the primary tumor, bypassing the lymph nodes. Comparative analysis of the sequencing data for individual cell pairs within different tumors demonstrated that the genetic heterogeneity of both liver and lymphatic metastases was also greater than that of the primary tumor. This finding indicates that liver and lymphatic metastases arose from clusters of circulating tumor cell (CTC) of a polyclonal origin, rather than from a single cell from the primary tumor. Single-cell transcriptome analysis suggested that higher EMT score and CNV scores were associated with more polyclonal metastasis. Additionally, a mutation in the TRPS1 (Transcriptional repressor GATA binding 1) gene, TRPS1 R544Q, was enriched in the single cells from the liver metastasis. The mutation significantly increased CRC invasion and migration both in vitro and in vivo through the TRPS1R544Q/ZEB1 axis. Further TRPS1 mutations were detected in additional colon cancer cases, correlating with advanced-stage disease and inferior prognosis. These results reveal polyclonal seeding and TRPS1 mutation as potential mechanisms driving the development of liver metastases in colon cancer.

Expression and diagnostic value of serum free light chain in lung cancer. / è¡€æ¸ æ¸¸ç¦»è½»é“¾åœ¨è‚ºç™Œä¸­çš„è¡¨è¾¾åŠè¯Šæ–­ä»·å€¼.

OBJECTIVES: The expression of serum free light chain (FLC) is abnormal in various diseases, but its role in lung cancer remains unclear. This study aims to investigate the expression and diagnostic value of serum FLC in lung cancer. METHODS: A total of 80 lung cancer patients treated at Xiangdong Hospital, Hunan Normal University from January to December 2021 were selected as the lung cancer group. Another 80 healthy individuals undergoing routine physical examinations during the same period were chosen as the control group. General information and serum κFLC and λFLC levels were collected for all subjects. Clinical indicators such as serum carcinoembryonic antigen (CEA), cytokeratin fragment antigen 21-1 (CYFRA21-1) levels, tumor diameter, histological type, TNM stage, and lymph node metastasis status were recorded for lung cancer patients. The expression levels of serum FLC [κFLC, λFLC, and FLC (κ+λ)] were compared between the lung cancer group and the control group. Lung cancer patients were grouped based on gender, age, smoking history, tumor diameter, TNM stage, histological type, and lymph node metastasis to compare differences in serum κFLC and λFLC levels. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic value of serum FLC alone and in combination with other indicators in lung cancer. RESULTS: The expression levels of serum FLC (κ+λ) and κFLC were significantly higher in the lung cancer group than those in the control group (both P<0.001), while there was no significant difference in serum λFLC levels between the 2 groups (P>0.05). There were no significant differences in serum κFLC levels among lung cancer patients with different tumor diameters, histological types, or TNM stages (all P>0.05); however, serum κFLC levels were higher in lung cancer patients with lymph node metastasis than in those without, with statistical significance (P=0.033). There were no significant differences in serum λFLC levels based on tumor diameter or histological type (both P>0.05), but serum λFLC levels were higher in stage III+IV and lymph node metastatic lung cancer patients compared to stage I+II and non-metastatic patients, with statistical significance (P=0.033 and P=0.019, respectively). The area under the curve (AUC) for κFLC and CEA in diagnosing lung cancer showed no significant difference (P=0.333). The combination of κFLC+CYFRA21-1 had the highest diagnostic efficacy (AUC=0.875) and sensitivity (71.3%). The AUC for the combined diagnosis of κFLC+λFLC+CEA+CYFRA21-1 was 0.915 (95% CI 0.860 to 0.953, P<0.001). CONCLUSIONS: Serum FLC is highly expressed in lung cancer and is associated with its invasion and metastasis. Serum FLC, particularly κFLC, has diagnostic value for lung cancer, and the combined detection of FLC, CEA, and CYFRA21-1 offers the best diagnostic efficacy.

Cross-sectional investigation of the distribution characteristics and prognostic significance of lateral lymph nodes in patients with rectal cancer.

BACKGROUND: Information about the distribution characteristics and prognostic significance of lateral lymph nodes (LLNs) on primary computed tomography (CT) scan in rectal cancer patients is lacking. METHODS: Between January 2013 and December 2016, patients with pathologically proved rectal cancer and pretreatment abdominal enhanced CT in our department were screened. We firstly redivided LLNs into seven categories based on their locations. Then, the number and distribution of all measurable LLNs and the characteristics of the largest LLN in each lateral compartment were recorded. Furthermore, we investigated the long-term outcomes in patients with different LLN characteristics and LLN risk scoring. RESULTS: A total of 572 patients were enrolled in this study. About 80% of patients had measurable LLNs, and most patients developed measurable LLNs in the obturator cranial compartment. Lateral local recurrence (LLR) was observed in 20 patients, which accounted for 83.3% of the local recurrence (LR). Patients with the largest LLN short-axis diameter >10 mm had a poor prognosis, which was similar to that in patients with simultaneous distant metastasis (SDM). Patients with LLN risk scoring ≥2 had a worse prognosis than those with LLN risk scoring <2, while better than those with SDM. CONCLUSION: This study suggests that LLR is the main locoregional recurrence pattern. Most rectal cancer patients have measurable LLNs on primary CT scan. However, patients with enlarged LLNs <10 mm or LLN risk scoring <2 still have a significantly better prognosis than patients with SDM, which indicated the potential value of locoregional treatment for these LLNs.

Prophylactic para-aortic lymph node dissection in Colo-rectal cancer; pilot study.

BACKGROUND: Colorectal cancer is the 3rd most common cancer worldwide, representing 10% of all cancer types, and is considered the 2nd leading cause of cancer-related deaths. It usually metastasizes to the liver or lung. Para-aortic lymph node metastasis is considered a metastatic disease (stage 4) according to the AJCC and is considered a regional disease (stage 3) according to the JSCCR. Para-aortic lymph node metastases occur in about 1% of cases. Neoadjuvant CTH, followed by PALN, is the best option for metastatic para-aortic LNs in colorectal cancer patients. This study addresses the value of prophylactic para-aortic LN dissection among colon-rectal cancer patients (overtreatment protocol). METHODOLOGY: This is a prospective study that included patients attending NCI, Cairo University, from December 2020 to December 2023 who were complaining of left colonic cancer or recto-sigmoid cancer and underwent left hemicolectomy, sigmoid colectomy, or LAR. All patients underwent formal mesenteric LN dissection and prophylactic para-aortic LN dissection. RESULTS: Among 60 patients who underwent colorectal surgery with prophylactic para-aortic LN dissection, 21 cases (35%) were in the descending colon, 22 cases (36.7%) were in the sigmoid colon, 11 cases (18.3%) were in the recto-sigmoid, and 6 cases (10%) were in the upper rectum. 55 cases (91.7%) were in grade 2, and 5 cases (8.3%) were in grade 3. Neoadjuvant CTH was given in 3 cases (5%) while neoadjuvant RTH was given in 6 cases (10%). Regarding reported postoperative complications, lymphorrhea was reported in 2 patients (3.3%) and wound infection occurred in 6 patients (10%). A recurrence was reported among 8 cases (13.4%). CONCLUSIONS: We aimed in this study to highlight the value of prophylactic para-aortic lymph node dissection among colorectal cancer patients (over-treatment protocol) and report its reflection on predicting the behavior of the disease and subsequently selecting the patients who will be suitable to do this procedure.

Disease extent according to baseline [18F]fluorodeoxyglucose PET/CT and molecular subtype: prediction of axillary treatment response after neoadjuvant systemic therapy for breast cancer.

BACKGROUND: Axillary disease extent according to baseline [18F]fluorodeoxyglucose PET/CT combined with pathological axillary treatment response has been proposed to guide de-escalation of axillary treatment for clinically node-positive breast cancer patients treated with neoadjuvant systemic therapy. The aim of this study was to assess whether axillary disease extent according to baseline [18F]fluorodeoxyglucose PET/CT and breast cancer molecular subtype are predictors of axillary pCR. METHODS: This study included clinically node-positive patients treated with neoadjuvant systemic therapy in the prospective Radioactive Iodine Seed placement in the Axilla with Sentinel lymph node biopsy ('RISAS') trial (NCT02800317) with baseline [18F]fluorodeoxyglucose PET/CT imaging available. The predictive value of axillary disease extent according to baseline [18F]fluorodeoxyglucose PET/CT and breast cancer molecular subtype to estimate axillary pCR was evaluated using logistic regression analysis. Discriminative ability is expressed using ORs with 95% confidence intervals. RESULTS: Overall, 185 patients were included, with an axillary pCR rate of 29.7%. The axillary pCR rate for patients with limited versus advanced baseline axillary disease according to [18F]fluorodeoxyglucose PET/CT was 31.9% versus 26.1% respectively. Axillary disease extent was not a significant predictor of axillary pCR (OR 0.75 (95% c.i. 0.38 to 1.46) (P = 0.404)). There were significant differences in axillary pCR rates between breast cancer molecular subtypes. The lowest probability (7%) was found for hormone receptor+/human epidermal growth factor receptor 2- tumours. Using this category as a reference group, significantly increased ORs of 14.82 for hormone receptor+/human epidermal growth factor receptor 2+ tumours, 40 for hormone receptor-/human epidermal growth factor receptor 2+ tumours, and 6.91 for triple-negative tumours were found (P < 0.001). CONCLUSION: Molecular subtype is a significant predictor of axillary pCR after neoadjuvant systemic therapy, whereas axillary disease extent according to baseline [18F]fluorodeoxyglucose PET/CT is not.

Preoperative dual-energy computed tomography and positron-emission tomography evaluation of lymph node metastasis in esophageal squamous cell carcinoma.

PURPOSE: To investigate the detectability of lymph node metastasis in patients with esophageal squamous cell carcinoma using a combination of dual-energy computed tomography (CT) and positron-emission tomography (PET) parameters. METHODS: We analyzed dual-energy CT and PET preoperative data in 27 consecutive patients with esophageal squamous cell carcinoma (23 men, 4 women; mean age, 73.7 years). We selected lymph nodes with a short-axis diameter of ≥5 mm and measured CT values, iodine concentrations, fat fractions, long- and short-axis diameters, and ratio of long- and short-axis diameters. We performed visual assessment of lymph node characteristics based on dual-energy CT and determined the maximum standardized uptake value via PET. The measured values were postoperatively compared between pathologically confirmed metastatic and nonmetastatic lymph nodes. Stepwise logistic regression analysis was performed to determine factors associated with lymph node metastasis. Diagnostic accuracy was assessed via receiver operating characteristic curve analysis. RESULTS: Overall, 18 metastatic and 37 nonmetastatic lymph nodes were detected. CT values, iodine concentrations, fat fractions, and the maximum standardized uptake values differed significantly between metastatic and nonmetastatic lymph nodes (p < 0.05). Stepwise logistic regression showed that iodine concentration and the maximum standardized uptake value were significant predictors of metastatic lymph nodes. The areas under the curve of iodine concentrations and maximum standardized uptake values were 0.809 and 0.833, respectively. The area under the curve of the combined parameters was 0.884, with 83.3% sensitivity and 86.5% specificity. CONCLUSION: Combined dual-energy CT and PET parameters improved the diagnosis of lymph node metastasis in patients with esophageal cancer.

Single-center external validation and reconstruction of multiple predictive models for skip lateral lymph node metastasis in papillary thyroid carcinoma.

Objective: The unique metastatic pattern of skip lateral lymph node metastasis (SLLNM) in PTC patients may lead to missed diagnosis of lateral cervical metastatic lymph nodes. Therefore, many different SLLNM prediction models were constructed. In this study, partially eligible models (Hu 2020, Wang 2020, and Zhao 2023 nomograms) were selected for external validation, and then new variables were incorporated for model reconstruction to extend clinical applicability. Methods: 576 PTC patients from our center were selected to evaluate the performance of the three nomograms using the receiver operating characteristic curve (ROC), calibration curves, and decision curve analyses (DCA). Three new variables were added to calibrate the model, including assessment of LN status on ultrasound (US-SLLNM), the distance from the tumor to the capsule (Capsular distance), and the number of central lymph node dissections (CLND number). Univariate and multivariate logistic regression analyses were used to screen independent predictors to reconstruct the model, and 1000 Bootstrap internal validations were performed. Results: SLLNM were present in 69/576 patients (12.0%). In external validation, the area under the ROC curves (AUCs) for Hu 2020, Wang 2020, and Zhao 2023 nomograms were 0.695 (95% CI:0.633-0.766), 0.792 (95% CI=0.73-0.845), and 0.769 (95% CI:0.713-0.824), respectively. The calibration curves for the three models were overall poorly fitted; DCA showed some net clinical benefit. Model differentiation and net clinical benefit improved by adding three new variables. Based on multivariate analysis, female, age, and maximum tumor diameter ≤ 10 mm, located at the upper pole, Capsular distance < 0mm, US-SLLNM, CLND number ≤ 5 were identified as independent predictors of SLLNM and were used to construct the new model. After 1000 Bootstrap internal validations, the mean AUC of the model was 0.870 (95% CI:0.839-0.901), the calibration curve was close to the ideal curve, and the net clinical benefit was significant. Conclusion: Overall, these nomograms were well differentiated and provided some net clinical benefit, but with varying degrees of underestimation or overestimation of the actual risk and high false-negative rates. New dynamic nomogram was constructed based on the addition of new variables and larger samples, showing better performance.

RATIO OF METASTATIC LYMPH NODES VS. RESECTED LYMPH NODES (N-RATIO) HAS PROGNOSTIC IMPLICATIONS IN GASTRIC CANCER.

BACKGROUND: Lymph node status is vital for gastric cancer (GC) prognosis, but the conventional pN stage may be limited by variations in lymphadenectomy and stage migration. The N-Ratio, which assesses the ratio of metastatic to resected lymph nodes, emerges as a promising prognostic tool. AIMS: To assess N-Ratios prognostic value in GC, particularly in patients with <25 resected lymph nodes. METHODS: Patients who underwent gastrectomy with curative intent for GC were retrospectively evaluated. The N-Ratio categories were determined using the ROC curve method, and the area under the curve (AUC) was used as a measure of performance in predicting recurrence/death. RESULTS: A total of 561 GC patients were included in the study, 57% had pN+ status, and 17.5% had <25 resected lymph nodes. N-Ratio, with a mean of 0.12, predicted survival with 74% accuracy (AUC=0.74; 95%CI 0.70-0.78, p<0.001). N-Ratio categories included: N-Ratio 0 (43%); N-Ratio 1 (12.3%); N-Ratio 2 (31.6%); and N-Ratio 3 (13.2%). Disease-free survival (DFS) varied among all N-Ratio groups, with N-Ratio 3 showing worse survival than pN3 cases (DFS=21.8 vs. 11 months, p=0.022, p<0.05). In cases with <25 resected lymph nodes, DFS was not significantly worse in N-Ratio 0 (68.8 vs. 81.9%, p=0.061, p>0.05) and N-Ratio 1 (66.2 vs. 50%, p=0.504, p>0.05) groups. The DFS of N-Ratio-0 cases with <25 lymph nodes was similar to N-Ratio 1 cases. CONCLUSIONS: N-Ratio influenced survival in GC patients, especially in advanced lymph node disease (N-Ratio 3). Considering that N-Ratio does not impact pN0 cases, individualized prognosis assessment is essential for patients with <25 resected lymph nodes.

Liver metastases from a recurrent invasive ductal carcinoma via a lymphatic route.

Breast cancer usually metastasizes by haematogenous spread. This is a case report of a woman with unusual liver metastases from a recurrent invasive ductal carcinoma via a lymphatic route draining the outer part of the breast to the liver running parallelly with the right rectus abdominis muscle, depicted by preoperative sentinel node lymphoscintigraphy. Realizing this route of metastasis can impact survival, as it has a favourable prognosis compared with haematogenous metastasis, we want to draw attention to this.

Prediction of pathological response and lymph node metastasis after neoadjuvant therapy in rectal cancer through tumor and mesorectal MRI radiomic features.

Establishing predictive models for the pathological response and lymph node metastasis in locally advanced rectal cancer (LARC) treated with neoadjuvant chemoradiotherapy (nCRT) based on MRI radiomic features derived from the tumor and mesorectal compartment (MC). This study included 209 patients with LARC who underwent rectal MRI both before and after nCRT. The patients were divided into a training set (n = 146) and a test set (n = 63). Regions of interest (ROIs) for the tumor and MC were delineated on both pre- and post-nCRT MRI images. Radiomic features were extracted, and delta radiomic features were computed. The predictive endpoints were pathological complete response (pCR), pathological good response (pGR), and lymph node metastasis (LNM). Feature selection for various models involved sequentially removing features with a correlation coefficient > 0.9, and features with P-values ≥ 0.05 in univariate analysis, followed by LASSO regression on the remaining features. Logistic regression models were developed, and their performance was evaluated using the area under the receiver operating characteristic curve (AUC). Among the 209 LARC patients, the number of patients achieving pCR, pGR, and LNM were 44, 118, and 40, respectively. The optimal model for predicting each endpoint is the combined model that incorporates pre- and delta-radiomics features for both the tumor and MC. These models exhibited superior performance with AUC values of 0.874 (for pCR), 0.801 (for pGR), and 0.826 (for LNM), outperforming the MRI tumor regression grade (mrTRG) which yielded AUC values of 0.800, 0.715, and 0.603, respectively. The results demonstrate the potential utility of the tumor and MC radiomics features, in predicting treatment efficacy among LARC patients undergoing nCRT.

Multimodal MRI-based radiomics models for the preoperative prediction of lymphovascular space invasion of endometrial carcinoma.

PURPOSE: To evaluate the predictive capabilities of MRI-based radiomics for detecting lymphovascular space invasion (LVSI) in patients diagnosed with endometrial carcinoma (EC). MATERIALS AND METHODS: A retrospective analysis was conducted on 160 female patients diagnosed with EC. The radiomics model including T2-weighted and dynamic contrast-enhanced MRI (DCE-MRI) images was established. Additionally, a conventional MRI model, which incorporated MRI-reported FIGO stage, deep myometrial infiltration (DMI), adnexal involvement, and vaginal/parametrial involvement, was established. Finally, a combined model was created by integrating the radiomics signature and conventional MRI characteristics. The predictive performance was validated by the area under the curve (AUC) of the receiver operating characteristic (ROC) curves. A stratified analysis was conducted to compare the differences between the three models by Delong test. RESULTS: In predicting LVSI, the radiomics model outperformed the clinical model in the training cohort (AUC: 0.899 vs. 0.8862) but not in the test cohort (AUC: 0.812 vs. 0.8758). The combined model demonstrated superior performance in both the training and test cohorts (training cohort: AUC = 0.934, 95% CI: 0.8807-0.9873; testing cohort: AUC = 0.905, 95% CI: 0.7679-1). CONCLUSIONS: The combined model exhibited utility in preoperatively predicting LVSI in patients with EC, offering potential benefits for clinical decision-making.

Clinical significance of intensity-modulated radiotherapy (IMRT) to the distant metastatic lymph nodes for metastatic cervical cancer.

OBJECTIVE: To retrospectively explore the clinical significance of radiotherapy to the distant metastatic lymph nodes (cervical/ clavicular/ mediastinal et al.) in metastatic cervical cancer. Hereinto, these cervicothoracic lymph nodes were metastasized from IB1-IVA (initial stage at first treatment), and IVB initially had metastatic disease in these areas at diagnosis. METHODS: Metastatic cervical cancer only with the distant cervicothoracic metastatic lymph nodes (cervical/ clavicular/ mediastinal et al.), without distant parenchymal organs metastasis such as lung, liver, bone, and peritoneum, were enrolled in the analysis. These patients were classified into IB1-IVA and IVB based on their initial stage of first treatment. All patients received IMRT for the distant metastatic lymph nodes. The progression-free survival (PFS) and overall survival (OS) were analyzed using the Kaplan-Meier method. RESULTS: Overall, the median PFS was 9 months, and the median OS was 27 months. The subgroup analysis showed that for IB1-IVA, the median PFS was 11 months, and the median OS was 30.5 months. For IVB, the median PFS was 8 months, and the median OS was 16 months. CONCLUSION: Radiotherapy is beneficial to the distant metastatic lymph nodes (cervical/ clavicular/ mediastinal et al.), and could effectively bring the longer PFS and OS for metastatic cervical cancer.

Revelation of comprehensive cell profiling of primary and metastatic tumour ecosystems in oral squamous cell carcinoma by single-cell transcriptomic analysis.

Background: The analysis of single-cell transcriptome profiling of tumour tissue isolates helps to identify heterogeneous tumour cells, neighbouring stromal cells and immune cells. Local metastasis of lymph nodes is the most dominant and influential biological behaviors of oral squamous cell carcinoma (OSCC) in terms of treatment prognosis. Understanding metastasis initiation and progression is important for the discovery of new treatments for OSCC and prediction of clinical responses to immunotherapy. However, the identity of metastasis-initiating cells in human OSCC remains elusive, and whether metastases are hierarchically organized is unknown. Therefore, this study was conducted to understand the cellular origins and gene expression signature of OSCC at the single-cell level. Methods: Single-cell RNA sequencing (scRNA-seq) was used to analyze cells from tissue of para-carcinoma (PCA: adjacent normal tissue not less than 2 cm from the tumour), carcinoma (CA), lymph node metastasis (LNM) from patients with OSCC and PCA and CA tissue from patients with second primary OSCC (SPOSCC) after radiotherapy of nasopharyngeal carcinoma (NPC). The cell types and their underlying functions were classified. The comparisons were then conducted between the homology and heterogeneity from cell types and both conservative and heterogeneous aspects of evolution were identified. Immunohistochemistry was performed to verify the makers of cell clusters and the expression level of novel genes. Results: A single-cell transcriptomic map of OSCC was created, including 16 clusters of PCA cells, 17 clusters of CA cells, 14 clusters of left LNM cells, and 14 clusters of right LNM cells. We also discovered two novel types of cells including CD1C-CD141-dendritic cells and CD1C+_B dendritic cells. Most of the non-cancer cells are immune cells, with two distinct clusters of T lymphocytes, B lymphocytes, CD1C-CD141-dendritic cells+ and CD1C+_B dendritic cells. We also classified cells into 15 clusters for SPOSCC after radiotherapy of NPC. Determining the upregulated expression levels of IL1RN and C15orf48 as novel markers using immunohistochemistry facilitated the correct classification of OSCC including SPOSCC after radiotherapy of NPC and the prediction of their prognosis. Conclusions: The findings provided an unprecedented and valuable view of the functional states and heterogeneity of cell populations in LNM of OSCC and SPOSCC after radiotherapy of NPC at single-cell genomic resolution. Moreover, this transcriptomic map discovered new cell types in mouth, and novel tumour cell-specific markers/oncogene.

A metabolic-inflammatory-nutritional score (MINS) is associated with lymph node metastasis and prognostic stratification for endometrial cancer patients.

Objective: This study aims to propose a personalized cancer prediction model based on the metabolic-inflammatory-nutritional score (MINS) for predicting lymph node metastasis (LNM) in endometrial cancer (EC) and validated prediction of survival probability in patients with a family history of Lynch syndrome-associated cancers (LSAC). Methods: A total of 676 patients diagnosed with EC were enrolled in this study. We calculated the optimal cutoff value using restricted cubic splines (RCS) analysis or the mean value. Our feature selection process for constructing the MINS involved using the LASSO regression model. MINS were evaluated for LNM using logistic regression analysis. To assess the prognostic value of the MINS, we generated survival curves using the Kaplan-Meier method with a log-rank test. Furthermore, we constructed a nomogram to validate the prognostic significance of the MINS. The predictive accuracy of nomogram was evaluated using the concordance index (C-index) and calibration plot. Results: LNM risk was associated with family history of LSAC and MINS group (all adjusted p<0.05). Patients in the high-risk MINS group or patients with a family history of LSAC exhibited poorer overall survival (p=0.038, p=0.001, respectively). Additionally, a nomogram was demonstrated effective predictive performance with a C-index of 0.778 (95% CI: 0.725-0.832). Conclusion: Preoperative MINS has been determined to be associated with the risk of LNM in EC patients. Utilizing MINS as a basis, the development of a prognostic nomogram holds promise as an effective tool for risk stratification in clinical settings among EC patients with a family history of LSAC.

Model for detecting metastatic deposits in lymph nodes of colorectal carcinoma on digital/ non-WSI images.

INTRODUCTION: Colorectal cancer (CRC) constitutes around 10% of global cancer diagnoses and death due to cancer. Treatment involves the surgical resection of the tumor and regional lymph nodes. Assessment of multiple lymph node demands meticulous examination by skilled pathologists, which can be arduous, prompting consideration for an artificial intelligence (AI)-supported workflow due to the growing number of slides to be examined, demanding heightened precision and the global shortage of pathologists. METHOD: This was a retrospective cross-sectional study including digital images of glass slides containing sections of positive and negative lymph nodes obtained from radical resection of primary CRC. Lymph nodes from 165 previously diagnosed cases were selected from Agha Khan University Hospital, from Jan 2021 to Jan 2022. The images were prepared at 10X and uploaded into an open source software, Q path and deep learning model Ensemble was applied for the identification of tumor deposits in lymph node. RESULTS: Out of the 87 positive lymph nodes detected by AI, 73(84%) were true positive and 14(16%) were false positive. The total number of negative lymph nodes detected by AI was 78. Out of these, 69(88.5%) were true negative and 9 (11.5%) were false negative. The sensitivity was 89% and specificity 83.1%. The odds ratio was 40 with a confidence interval of 16.26-98.3. P-value was < 0.05 (< 0.0001). CONCLUSION: Though it was a small study but its results were really appreciating and we encourage more such studies with big sample data in future.

Lateral pelvic lymph node positivity (LPLNP) score: predictive clinic-radiological model of lateral pelvic lymph node involvement in rectal cancer patients.

PURPOSE: The population in Western countries differs significantly from that in Eastern countries, and the prevalence of lateral pelvic lymph node (LPLN) involvement in Western populations remains largely unknown due to the limited application of LPLN dissection (LPLND). This discrepancy is primarily attributed to the higher body mass index commonly observed in Western populations, which increases the risk of intraoperative complications. Consequently, the aim of this study is to describe a specific Western clinico-radiological selection tool for LPLND, namely, the lateral pelvic lymph node positivity (LPLNP) score. METHODS: This retrospective single center study was designed to elaborate the LPLNP score, which was further tested on a prospective cohort of patients. Clinical and MRI factors associated with LPLN involvement were identified, and logistic regression was used to establish the LPLNP score. RESULTS: In the retrospective series, 120 patients underwent lateral pelvic lymph node dissection. After stepwise logistic regression, five parameters were ultimately included in the LPLNP score. When tested on 66 prospectively selected patients, 40 with an LPLNP score > 0.23 (corresponding to the highest sensitivity and specificity) underwent LPLND: 22 patients (55%) had pathologically confirmed positive LPLN. The negative predictive value of the LPLNP score was 96%, with a sensitivity of 95.7% and a specificity of 58.1%. CONCLUSION: The LPLNP score was developed based on the largest group of Western patients with locally advanced rectal cancer. This scoring system demonstrated high sensitivity and specificity during validation on the prospective series, correctly identifying LPLN involvement in 55% of cases.

Value of surgical lymph node assessment for patients with vulvar melanoma.

OBJECTIVE: Investigate the utilization and outcomes of lymphadenectomy/ sampling (LND) for patients with vulvar melanoma. MATERIALS AND METHODS: Patients diagnosed between 2004-2015 with vulvar melanoma with known depth of tumor invasion and no distant metastases were identified in the National Cancer Database. Based on pathology report patients who underwent inguinal lymph node sampling/dissection were identified. Clinico-pathological characteristics and overall survival were compared between the two groups. RESULTS: A total of 1286 patients were identified; 62.8 % (n = 808) underwent lymphadenectomy/ sampling. Patients who underwent lymphadenectomy/ sampling were younger (median 66 vs 76 years, p < 0.001), more likely to have private insurance (42.9 % vs 27.8 %, p < 0.001), present with tumor ulceration (65.9 % vs 58.6 %, p = 0.01), have deeper tumor invasion (p < 0.001) and undergo radical vulvectomy (26.4 % vs 12.1 %, p < 0.001). Patients who underwent lymphadenectomy/ sampling had better overall survival compared to those who did not (median 49.08 vs 35.91 months respectively, p < 0.001). After controlling for patient age, race, insurance status, comorbidities, presence of tumor ulceration and Breslow depth of invasion performance of lymphadenectomy/ sampling was associated with better survival (hazard ratio: 0.78, 95 % confidence intervals: 0.67, 0.92). CONCLUSION: For patients with vulvar melanoma with at least 1 mm invasion lymphadenectomy/ sampling was associated with better overall survival likely secondary to stage migration.