Structural Basis for Allosteric Ligand Recognition in the Human CC Chemokine Receptor 7.

The CC chemokine receptor 7 (CCR7) balances immunity and tolerance by homeostatic trafficking of immune cells. In cancer, CCR7-mediated trafficking leads to lymph node metastasis, suggesting the receptor as a promising therapeutic target. Here, we present the crystal structure of human CCR7 fused to the protein Sialidase NanA by using data up to 2.1 Å resolution. The structure shows the ligand Cmp2105 bound to an intracellular allosteric binding pocket. A sulfonamide group, characteristic for various chemokine receptor ligands, binds to a patch of conserved residues in the Gi protein binding region between transmembrane helix 7 and helix 8. We demonstrate how structural data can be used in combination with a compound repository and automated thermal stability screening to identify and modulate allosteric chemokine receptor antagonists. We detect both novel (CS-1 and CS-2) and clinically relevant (CXCR1-CXCR2 phase-II antagonist Navarixin) CCR7 modulators with implications for multi-target strategies against cancer.

Comprehensive Glycoprofiling of Oral Tumors Associates N-Glycosylation With Lymph Node Metastasis and Patient Survival.

While altered protein glycosylation is regarded a trait of oral squamous cell carcinoma (OSCC), the heterogeneous and dynamic glycoproteome of tumor tissues from OSCC patients remain unmapped. To this end, we here employ an integrated multi-omics approach comprising unbiased and quantitative glycomics and glycoproteomics applied to a cohort of resected primary tumor tissues from OSCC patients with (n = 19) and without (n = 12) lymph node metastasis. While all tumor tissues displayed relatively uniform N-glycome profiles suggesting overall stable global N-glycosylation during disease progression, altered expression of six sialylated N-glycans was found to correlate with lymph node metastasis. Notably, glycoproteomics and advanced statistical analyses uncovered altered site-specific N-glycosylation revealing previously unknown associations with several clinicopathological features. Importantly, the glycomics and glycoproteomics data unveiled that comparatively high abundance of two core-fucosylated and sialylated N-glycans (Glycan 40a and Glycan 46a) and one N-glycopeptide from fibronectin were associated with low patient survival, while a relatively low abundance of N-glycopeptides from both afamin and CD59 were also associated with poor survival. This study provides insight into the complex OSCC tissue N-glycoproteome, thereby forming an important resource to further explore the underpinning disease mechanisms and uncover new prognostic glycomarkers for OSCC.

Expression of SOX4 Significantly Predicts the Risk of Lymph Node Metastasis for Patients With Early-Stage Esophageal Squamous Cell Carcinoma.

Esophageal squamous cell carcinoma stands as a notably aggressive malignancy within the digestive system. In cases of early esophageal cancer without lymph node metastasis, endoscopic surgical resection offers a viable alternative, often resulting in improved patient quality of life. However, the paucity of methods to preoperatively ascertain lymph node involvement complicates surgical planning. SOX4 gene was previously found to be highly associated with invasive metastasis in our work through single-cell RNA sequencing on 5 paired tumor/peritumor tissues. This research included the collection of 124 tissue samples from 106 patients (106 tumor and 18 lymph node specimens). Samples were methodically arranged into a tissue microarray and treated with immunohistochemical staining. Statistical analysis was conducted to assess the relationship between them. In the univariate analysis, 3 factors were identified as statistically significant in relation to lymph node metastasis: T category (P = .014), vascular invasion (P < .001), and SOX4 intensity (P = .001). Additionally, when evaluating SOX4 intensity alongside other clinical indicators, SOX4 was shown to independently influence lymph node metastasis. Further, the multivariate analysis revealed that vascular invasion (P < .001) and SOX4 intensity (P = .003) were significantly associated with lymph node metastasis, exhibiting hazard ratios of 10.174 and 7.142, respectively. The results of our study indicate that both SOX4 expression and vascular invasion serve as predictors of lymph node metastasis in patients diagnosed with category T1 esophageal squamous cell carcinoma, underscoring the potential utility of SOX4 in prognostic evaluations.

Extrachromosomal circular DNA landscape of breast cancer with lymph node metastasis.

Breast cancer (BC) is a complex disease with diverse manifestations, often resulting in lymph node metastasis (LNM) and impacting patient prognosis. Extrachromosomal circular DNA (eccDNA) has emerged as a key player in tumorigenesis, yet its contribution to BC LNM remains elusive. Here, we examined primary tumors and matched LNM tissues from 19 BC patients using the Circle-Seq method. We identified a median count of 44,682 eccDNA in primary tumor tissues and 38,057 in their paired LNM tissues. Furthermore, a ladder-like size distribution is observed in both primary tumor and LNM tissues. Meanwhile, similar repeat sequence distribution and GC content are identified from both primary tissue and LNM tissues. Finally, we found that eccDNA from both groups are flanked with palindromic trinucleotide motifs. These observations indicate that eccDNA of primary tumor and LNM tissues are from similar chromosomal origins. However, a subset of miRNA-associated eccDNA displayed selective enrichment in metastatic lesions, such as miR-6730 and miR-548AA1 genes. This observation implicates the function of miRNA-related eccDNA in the metastatic cascade. Our study uncovers the potential significance of these unique eccDNA molecules, shedding light on their role in cancer metastasis.

Tumor thickness as a novel risk factor for lymph node metastasis by superficial squamous cell carcinoma of head and neck.

Narrow-band imaging combined with magnified endoscopy has enabled the detection of superficial squamous cell carcinoma of the head and neck (SSCCHN) that has been resected with minimally invasive treatment, preserving vocalization and swallowing functions. However, risk factors of lymph node metastasis (LNM) must be identified, as some patients with LNM have a poor prognosis. From an initial 599 patients with 700 lesions who underwent trans-oral surgery in 27 Japanese hospitals (a nationwide registration survey), we enrolled 541 patients with 633 SSCCHNs, as indicated by central pathological diagnoses. All pathological specimens for each patient were examined using 20 pathological factors that are thought to affect the LNM of SSCCHN. In all, 24 (4.4%) of the 568 SSCCHNs exhibited LNM, and all 24 had at least one solitary nest of epithelial neoplastic cells present in the stroma, clearly separated from the intraepithelial carcinoma. Multivariate analysis also showed that tumor thickness (p = 0.0132, RR: 7.85, 95% confidence interval [CI]: 1.54-40.02), and an INFc pattern classified as infiltrating growth (INF) with unclear boundaries between tumor and non-tumor tissues (p = 0.0003, RR: 14.47, 3.46-60.46), and tumor budding (p = 0.0019, RR: 4.35, CI: 1.72-11.01) were significantly associated with LNM. Solitary nests may be indicative of LNM. In addition, tumor thickness was revealed to be a risk factor for LNM in SSCCHNs using pT factors that do not include an invasion depth element because of the anatomical absence of the muscularis mucosae.

Dysfunction of CD8+ T cells around tumor cells leads to occult lymph node metastasis in NSCLC patients.

Occult lymph node metastasis (OLNM) is one of the main causes of regional recurrence in inoperable N0 non-small cell lung cancer (NSCLC) patients following stereotactic ablation body radiotherapy (SABR) treatment. The integration of immunotherapy and SABR (I-SABR) has shown preliminary efficiency in mitigating this recurrence. Therefore, it is necessary to explore the functional dynamics of critical immune effectors, particularly CD8+ T cells in the development of OLNM. In this study, tissue microarrays (TMAs) and multiplex immunofluorescence (mIF) were used to identify CD8+ T cells and functional subsets (cytotoxic CD8+ T cells/predysfunctional CD8+ T cells (CD8+ Tpredys)/dysfunctional CD8+ T cells (CD8+ Tdys)/other CD8+ T cells) among the no lymph node metastasis, OLNM, and clinically evident lymph node metastasis (CLNM) groups. As the degree of lymph node metastasis escalated, the density of total CD8+ T cells and CD8+ Tdys cells, as well as their proximity to tumor cells, increased progressively and remarkably in the invasive margin (IM). In the tumor center (TC), both the density and proximity of CD8+ Tpredys cells to tumor cells notably decreased in the OLNM group compared with the group without metastasis. Furthermore, positive correlations were found between the dysfunction of CD8+ T cells and HIF-1α+CD8 and cancer microvessels (CMVs). In conclusion, the deterioration in CD8+ T cell function and interactive dynamics between CD8+ T cells and tumor cells play a vital role in the development of OLNM in NSCLC. Strategies aimed at improving hypoxia or targeting CMVs could potentially enhance the efficacy of I-SABR.

Head and Neck Squamous Cell Carcinoma of Unknown Primary: A Diagnostic Work-Up.

The current work-up of the primary tumor site of a head and neck squamous cell carcinoma of unknown primary is not standardized and results in several time-consuming procedures that delay treatment initiation. This article seeks to consolidate contemporary strategies used to identify the primary tumor site of an unknown primary head and neck squamous cell carcinoma and offer recommendations based on current literature review.

Enhanced stiffness in peri-cancerous tissue: a marker of poor prognosis in papillary thyroid carcinoma with lymph node metastasis.

BACKGROUND: The prognostic significance of lymph node metastasis (LNM) in papillary thyroid carcinoma (PTC) remains controversial. Notably, there is evidence suggesting an association between tissue stiffness and the aggressiveness of the disease. We therefore aimed to explore the effect of tissue stiffness on LNM-related invasiveness in PTC patients. METHOD: A total of 2492 PTC patients from 3 hospitals were divided into an LNM group and a non-LNM group based on their pathological results. The effects of interior lesion stiffness (E) and peri-cancerous tissue stiffness (Eshell) on the LNM-related recurrence rate and mortality in each patient with PTC subgroup were analyzed. The activation of cancer-associated fibroblasts (CAFs) and extracellular matrix component type 1 collagen (COL-I) in the lesion were compared and analyzed across different subgroups. The underlying biological basis of differences in each subgroup was identified using RNA sequencing (RNA-seq) data. RESULTS: The Eshell value and Eshell/E in the LNM group were significantly higher than those in the non-LNM group of patients with PTC (Eshell: 72.72 ±â€…5.63 vs 66.05 ±â€…4.46; Eshell/E: 1.20 ±â€…1.72 vs 1.09 ±â€…1.10, P < .001). When Eshell/E > 1.412 and LNM were both present, the recurrence rate and mortality were significantly increased compared to those of group of patients with LNM (91.67% and 7.29%, respectively). The CAF activation and COL-I content in the Eshell/E+ group were significantly higher than those in the Eshell/E- group (all P < .001), and the RNA-seq results revealed significant extracellular matrix (ECM) remodeling in the LNM-Eshell/E+ group. CONCLUSIONS: Stiff peri-cancerous tissue induced CAF activation, COL-I deposition, and ECM remodeling, resulting in a poor prognosis for PTC patients with LNM.

Interaction of BANCR in the relationship between Hashimoto's thyroiditis and papillary thyroid carcinoma expression patterns and possible molecular mechanisms.

BACKGROUND: Previous studies have established a connection between Hashimoto's thyroiditis (HT) and an increased risk of papillary thyroid carcinoma (PTC). However, the molecular mechanisms driving this association are not well understood. The long non-coding RNA (lncRNA) BRAF-activated non-coding RNA (BANCR) has been implicated in various cancers, suggesting a potential role in the HT-PTC linkage. METHODS: This study investigated the expression levels of BANCR in PTC and HT samples, compared to control tissues. We also examined the association between BANCR expression and clinicopathological features, including lymph node metastasis. Furthermore, we explored the molecular mechanisms of BANCR in PTC pathogenesis and its potential as a therapeutic target. RESULTS: BANCR expression was significantly lower in PTC samples than in controls, while it was moderately increased in HT samples. In PTC cases with concurrent HT, BANCR expression was markedly reduced compared to normal tissues. Our analysis revealed BANCR's role as an oncogene in PTC, influencing various cancer-related signaling pathways. Interestingly, no significant correlation was found between BANCR expression and lymph node metastasis. CONCLUSION: Our findings underscore the involvement of BANCR in the connection between HT and PTC. The distinct expression patterns of BANCR in PTC and HT, especially in PTC with concurrent HT, provide new insights into the molecular interplay between these conditions. This study opens avenues for the development of innovative diagnostic and therapeutic strategies targeting BANCR in PTC and HT.

PRF1 as a prognostic gene for lymphatic metastasis in skin melanoma.

BACKGROUND: Melanoma is a highly aggressive tumor, predominantly found in the skin, recognized as skin cutaneous melanoma (SKCM). Lymph node metastasis is commonly used as the route of metastasis in SKCM, necessitating the discovery of prognostic genes associated with this process for improved prognosis. METHODS: The prognostic significance of lymph node metastasis in SKCM was assessed through Kaplan-Meier analysis in SEER and TCGA-SKCM datasets. Prognostic genes were identified and a prognostic risk model was constructed Enrichment analysis and immune cell infiltration analysis were also carried out.Moreover, a validation in vitro and in vivo were conducted by CCK8,flow cytometry, transwell and animal study. RESULTS: The Kaplan-Meier survival curve revealed that patients with lymph node metastasis had a worse prognosis compared to those without. FCGR3B and PRF1 were screened by TCGA analysis.Additionally, significant differences in nine immune cell types were observed between the two risk groups. Notably, a strong positive association with CD8 T cells and a negative relationship with M2 macrophages were exhibited by PRF1. The validation of our nomogram were conducted in vitro and in vivo, and the results showed the correlations between CD8+ T cell and PRF1. CONCLUSION: In summary, two prognostic genes (FCGR3B and PRF1) were identified, and a prognostic risk model was developed for SKCM. These findings provide a novel approach for the diagnosis and treatment of SKCM.

Intraoperative spectroscopic evaluation of sentinel lymph nodes in breast cancer surgery.

BACKGROUND AND OBJECTIVES: Sentinel lymph node (SLN) biopsy is a standard procedure for patients with breast cancer and normal axilla on imaging. Positive SLNs on histological examination can lead to a subsequent surgery for axillary lymph node clearance (ALNC). Here we report a non-destructive technique based on autofluorescence (AF) imaging and Raman spectroscopy for intra-operative assessment of SLNs excised in breast cancer surgery. METHODS: A microscope integrating AF imaging and Raman spectroscopy modules was built to allow scanning of lymph node biopsy samples. During AF-Raman measurements, AF imaging determined optimal sampling locations for Raman spectroscopy measurements. After optimisation of the AF image analysis and training of classification models based on data from 85 samples, the AF-Raman technique was tested on an independent set of 81 lymph nodes comprising 58 fixed and 23 fresh specimens. The sensitivity and specificity of AF-Raman were calculated using post-operative histology as a standard of reference. RESULTS: The independent test set contained 66 negative lymph nodes and 15 positive lymph nodes according to the reference standard, collected from 78 patients. For this set of specimens, the area under the receiver operating characteristic (ROC) curve for the AF-Raman technique was 0.93 [0.83-0.98]. AF-Raman was then operated in a regime that maximised detection specificity, producing a 94% detection accuracy: 80% sensitivity and 97% specificity. The main confounders for SLN metastasis were areas rich in histiocytes clusters, for which only few Raman spectra had been included in the training dataset. DISCUSSION: This preliminary study indicates that with further development and extension of the training dataset by inclusion of additional Raman spectra of histiocytes clusters and capsule, the AF-Raman may become a promising technique for intra-operative assessment of SLNs. Intra-operative detection of positive biopsies could avoid second surgery for axillary clearance.

Characteristics and risk factors of axillary lymph node metastasis of microinvasive breast cancer.

PURPOSE: To select patients who would benefit most from sentinel lymph node biopsy (SLNB) by investigating the characteristics and risk factors of axillary lymph node metastasis (ALNM) in microinvasive breast cancer (MIBC). METHODS: This retrospective study included 1688 patients with MIBC who underwent breast surgery with axillary staging at the Asan Medical Center from 1995 to 2020. RESULTS: Most patients underwent SLNB alone (83.5%). Seventy (4.1%) patients were node-positive, and the majority had positive lymph nodes < 10 mm, with micro-metastases occurring frequently (n = 37; 55%). Node-positive patients underwent total mastectomy and axillary lymph node dissection (ALND) more than breast-conserving surgery (BCS) and SLNB compared with node-negative patients (p < 0.001). In the multivariate analysis, independent predictors of ALNM included young age [odds ratio (OR) 0.959; 95% confidence interval (CI) 0.927-0.993; p = 0.019], ALND (OR 11.486; 95% CI 5.767-22.877; p < 0.001), number of lymph nodes harvested (≥ 5) (OR 3.184; 95% CI 1.555-6.522; p < 0.001), lymphovascular invasion (OR 6.831; 95% CI 2.386-19.557; p < 0.001), presence of multiple microinvasion foci (OR 2.771; 95% CI 1.329-5.779; p = 0.007), prominent lymph nodes in preoperative imaging (OR 2.675; 95% CI 1.362-5.253; p = 0.004), and hormone receptor positivity (OR 2.491; 95% CI 1.230-5.046; p = 0.011). CONCLUSION: Low ALNM rate (4.1%) suggests that routine SLNB for patients with MIBC is unnecessary but can be valuable for patients with specific risk factors. Ongoing trials for omitting SLNB in early breast cancer, and further subanalyses focusing on rare populations with MIBC are necessary.

The impact of the COVID-19 pandemic in the clinical assistance to breast cancer patients.

PURPOSE: We aimed to disclose the impact of the pandemic on breast cancer patients in a specialized breast cancer center (BCC). METHODS: A total of 501 breast cancer patients with a first appointment in the BCC from April 1st, 2019 to March 31st, 2021 were divided into four consecutive periods of 6 months. Data from the homologous semesters was compared. Patients with an appointment in the BCC during the study period were eligible for the secondary aim of our study (BCC workload). RESULTS: After the pandemic declaration (period 3), we found a decrease in the referral by screening programs (p = 0.002) and a reduction in the waiting time between the primary care referral and the first BCC appointment (p < 0.001). There were higher rates of palpable axillary nodes (p = 0.001), an increase in N stage 2 and 3 (p = 0.050), and a trend for primary endocrine therapy as the first treatment (p = 0.021) associated with higher rates of complete axillary node dissection (p = 0.030). In period 4, there were more outward diagnoses (p = 0.003) and a higher rate of surgery as the first treatment (p = 0.013). CONCLUSION: COVID-19 pandemic implied a more advanced nodal stage, which may be related to the delay in breast cancer screening.

Association of the pathomics-collagen signature with lymph node metastasis in colorectal cancer: a retrospective multicenter study.

BACKGROUND: Lymph node metastasis (LNM) is a prognostic biomarker and affects therapeutic selection in colorectal cancer (CRC). Current evaluation methods are not adequate for estimating LNM in CRC. H&E images contain much pathological information, and collagen also affects the biological behavior of tumor cells. Hence, the objective of the study is to investigate whether a fully quantitative pathomics-collagen signature (PCS) in the tumor microenvironment can be used to predict LNM. METHODS: Patients with histologically confirmed stage I-III CRC who underwent radical surgery were included in the training cohort (n = 329), the internal validation cohort (n = 329), and the external validation cohort (n = 315). Fully quantitative pathomics features and collagen features were extracted from digital H&E images and multiphoton images of specimens, respectively. LASSO regression was utilized to develop the PCS. Then, a PCS-nomogram was constructed incorporating the PCS and clinicopathological predictors for estimating LNM in the training cohort. The performance of the PCS-nomogram was evaluated via calibration, discrimination, and clinical usefulness. Furthermore, the PCS-nomogram was tested in internal and external validation cohorts. RESULTS: By LASSO regression, the PCS was developed based on 11 pathomics and 9 collagen features. A significant association was found between the PCS and LNM in the three cohorts (P < 0.001). Then, the PCS-nomogram based on PCS, preoperative CEA level, lymphadenectasis on CT, venous emboli and/or lymphatic invasion and/or perineural invasion (VELIPI), and pT stage achieved AUROCs of 0.939, 0.895, and 0.893 in the three cohorts. The calibration curves identified good agreement between the nomogram-predicted and actual outcomes. Decision curve analysis indicated that the PCS-nomogram was clinically useful. Moreover, the PCS was still an independent predictor of LNM at station Nos. 1, 2, and 3. The PCS nomogram displayed AUROCs of 0.849-0.939 for the training cohort, 0.837-0.902 for the internal validation cohort, and 0.851-0.895 for the external validation cohorts in the three nodal stations. CONCLUSIONS: This study proposed that PCS integrating pathomics and collagen features was significantly associated with LNM, and the PCS-nomogram has the potential to be a useful tool for predicting individual LNM in CRC patients.

Deep learning-based pathological prediction of lymph node metastasis for patient with renal cell carcinoma from primary whole slide images.

BACKGROUND: Metastasis renal cell carcinoma (RCC) patients have extremely high mortality rate. A predictive model for RCC micrometastasis based on pathomics could be beneficial for clinicians to make treatment decisions. METHODS: A total of 895 formalin-fixed and paraffin-embedded whole slide images (WSIs) derived from three cohorts, including Shanghai General Hospital (SGH), Clinical Proteomic Tumor Analysis Consortium (CPTAC) and Cancer Genome Atlas (TCGA) cohorts, and another 588 frozen section WSIs from TCGA dataset were involved in the study. The deep learning-based strategy for predicting lymphatic metastasis was developed based on WSIs through clustering-constrained-attention multiple-instance learning method and verified among the three cohorts. The performance of the model was further verified in frozen-pathological sections. In addition, the model was also tested the prognosis prediction of patients with RCC in multi-source patient cohorts. RESULTS: The AUC of the lymphatic metastasis prediction performance was 0.836, 0.865 and 0.812 in TCGA, SGH and CPTAC cohorts, respectively. The performance on frozen section WSIs was with the AUC of 0.801. Patients with high deep learning-based prediction of lymph node metastasis values showed worse prognosis. CONCLUSIONS: In this study, we developed and verified a deep learning-based strategy for predicting lymphatic metastasis from primary RCC WSIs, which could be applied in frozen-pathological sections and act as a prognostic factor for RCC to distinguished patients with worse survival outcomes.

Implications of ZNF334 gene in lymph node metastasis of lung SCC: potential bypassing of cellular senescence.

BACKGROUND: The primary goal of this work is to identify biomarkers associated with lung squamous cell carcinoma and assess their potential for early detection of lymph node metastasis. METHODS: This study investigated gene expression in lymph node metastasis of lung squamous cell carcinoma using data from the Cancer Genome Atlas and R software. Protein-protein interaction networks, hub genes, and enriched pathways were analyzed. ZNF334 and TINAGL1, two less explored genes, were further examined through in vitro, ex vivo, and in vivo experiments to validate the findings from bioinformatics analyses. The role of ZNF334 and TINAGL1 in senescence induction was assessed after H2O2 and UV induced senescence phenotype determined using ß-galactosidase activity and cell cycle status assay. RESULTS: We identified a total of 611 up- and 339 down-regulated lung squamous cell carcinoma lymph node metastasis-associated genes (FDR < 0.05). Pathway enrichment analysis highlighted the central respiratory pathway within mitochondria for the subnet genes and the nuclear DNA-directed RNA polymerases for the hub genes. Significantly down regulation of ZNF334 gene was associated with malignancy lymph node progression and senescence induction has significantly altered ZNF334 expression (with consistency in bioinformatics, in vitro, ex vivo, and in vivo results). Deregulation of TINAGL1 expression with inconsistency in bioinformatics, in vitro (different types of lung squamous cancer cell lines), ex vivo, and in vivo results, was also associated with malignancy lymph node progression and altered in senescence phenotype. CONCLUSIONS: ZNF334 is a highly generalizable gene to lymph node metastasis of lung squamous cell carcinoma and its expression alter certainly under senescence conditions.

Risk Factor Analysis of Lymph Node Metastasis for Rectal Neuroendocrine Tumors: Who Needs a Radical Resection in Rectal Neuroendocrine Tumors Sized 1-2 cm?

BACKGROUND: Rectal neuroendocrine tumors (NETs) have malignant potential, and lymph node (LN) or distant metastases can occur; however, treatment of NETs 1-2 cm in size is controversial. OBJECTIVE: This study aimed to identify predictive factors for LN metastasis and prognostic factors for recurrence of rectal NETs, especially tumors 1‒2 cm in size. METHODS: Between October 2004 and November 2020, 453 patients underwent endoscopic or surgical treatment for rectal NETs in Seoul National University Hospital. The data on these patients were prospectively collected in our database and reviewed retrospectively. In cases of local excision, we evaluated LN metastasis with radiologic imaging, including computed tomography or magnetic resonance imaging before treatment and during the follow-up periods. RESULTS: LN metastasis was observed in 40 patients (8.8%). A higher rate of LN metastasis was observed in larger-sized tumors, advanced T stage, lymphovascular invasion (LVI), perineural invasion (PNI), and high tumor grade. In multivariable analysis, the significant risk factors for LN metastasis were tumor size (1 ≤ size < 2 cm: hazard ratio [HR] 64.07; size ≥2 cm: HR 102.37, p < 0.001) and tumor grade (G2: HR 3.63, p = 0.034; G3: HR 5.09, p = 0.044). In multivariable analysis for tumors 1-2 cm in size, the risk factor for LN metastasis was tumor grade (G2: HR 6.34, p = 0.013). CONCLUSIONS: Tumor grade and size are important predictive factors for LN metastasis. In NETs 2 cm in size, tumor grade is also important for LN metastasis, and radical resection should be considered.

Accuracy and Prognostic Impact of Nodal Status on Preoperative Imaging for Management of Pancreatic Neuroendocrine Tumors: A Multi-Institutional Study.

BACKGROUND: We sought to define the accuracy of preoperative imaging to detect lymph node metastasis (LNM) among patients with pancreatic neuroendocrine tumors (pNETs), as well as characterize the impact of preoperative imaging nodal status on survival. METHODS: Patients who underwent curative-intent resection for pNETs between 2000 and 2020 were identified from eight centers. Sensitivity and specificity of computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET)-CT, and OctreoScan for LNM were evaluated. The impact of preoperative lymph node status on lymphadenectomy (LND), as well as overall and recurrence-free survival was defined. RESULTS: Among 852 patients, 235 (27.6%) individuals had LNM on final histologic examination (hN1). The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were 12.4%, 98.1%, 71.8%, and 74.4% for CT, 6.3%, 100%, 100%, and 80.1% for MRI, 9.5%, 100%, 100%, and 58.7% for PET, 11.3%, 97.5%, 66.7%, and 70.8% for OctreoScan, respectively. Among patients with any combination of these imaging modalities, overall sensitivity, specificity, PPV, and NPV was 14.9%, 97.9%, 72.9%, and 75.1%, respectively. Preoperative N1 on imaging (iN1) was associated with a higher number of LND (iN1 13 vs. iN0 9, p = 0.003) and a higher frequency of final hN1 versus preoperative iN0 (iN1 72.9% vs. iN0 24.9%, p < 0.001). Preoperative iN1 was associated with a higher risk of recurrence versus preoperative iN0 (median recurrence-free survival, iN1→hN1 47.5 vs. iN0→hN1 92.7 months, p = 0.05). CONCLUSIONS: Only 4% of patients with LNM on final pathologic examine had preoperative imaging that was suspicious for LNM. Traditional imaging modalities had low sensitivity to determine nodal status among patients with pNETs.

Significance of Surgery for Resectable M1 Lymph Node Metastases Without Organ Metastasis in Esophageal Carcinoma in the Era of Neoadjuvant Treatment.

BACKGROUND: M1 esophageal carcinoma goes beyond localized disease and requires treatment with systemic therapy. M1 status is primarily divided into two categories: M1 lymph node metastasis and distant organ metastasis. Oligometastasis is defined as a state of limited metastatic disease, and surgery for oligometastasis of distant organs is reported to be beneficial in limited conditions. The aim of this study was to investigate resected cases of M1 lymph node metastases as the only metastatic site in stage IVB esophageal carcinoma. PATIENTS AND METHODS: This study was a single-center retrospective cohort study. Patients with esophageal carcinoma who underwent esophagectomy with curative intent between April 2017 and December 2021 were examined. Neoadjuvant chemotherapy was our standard therapy and administered in almost all cases. We hypothesized that four sites of metastatic M1LN (supraclavicular (no. 104), pretracheal (no. 106pre), posterior thoracic para-aortic (no. 112aoP), and abdominal para-aortic (no. 16a2lat) LNs) were potentially resectable M1LN (rM1LN) metastases with curative intent and compared the prognosis of patients with and without rM1LN metastasis. RESULTS: Six hundred eight-two patients were included in the study. Among these patients, 80 had rM1LN metastasis and received surgery for curative intent. Short-term safety outcomes were equivalent between patients with and without rM1LN metastases. After propensity score matching, there were no significant differences in overall survival between patients with and without rM1LN metastasis. Multivariate analyses revealed that the only independent prognostic factor was ypN status. CONCLUSION: The present study suggests the feasibility and favorable OS in the patients with resection of rM1LN metastasis.

Dual-Region Computed Tomography Radiomics-Based Machine Learning Predicts Subcarinal Lymph Node Metastasis in Patients with Non-small Cell Lung Cancer.

BACKGROUND: Noninvasively and accurately predicting subcarinal lymph node metastasis (SLNM) for patients with non-small cell lung cancer (NSCLC) remains challenging. This study was designed to develop and validate a tumor and subcarinal lymph nodes (tumor-SLNs) dual-region computed tomography (CT) radiomics model for predicting SLNM in NSCLC. METHODS: This retrospective study included NSCLC patients who underwent lung resection and SLNs dissection between January 2017 and December 2020. The radiomic features of the tumor and SLNs were extracted from preoperative CT, respectively. Ninety machine learning (ML) models were developed based on tumor region, SLNs region, and tumor-SLNs dual-region. The model performance was assessed by the area under the curve (AUC) and validated internally by fivefold cross-validation. RESULTS: In total, 202 patients were included in this study. ML models based on dual-region radiomics showed good performance for SLNM prediction, with a median AUC of 0.794 (range, 0.686-0.880), which was superior to those of models based on tumor region (median AUC, 0.746; range, 0.630-0.811) and SLNs region (median AUC, 0.700; range, 0.610-0.842). The ML model, which is developed by using the naive Bayes algorithm and dual-region features, had the highest AUC of 0.880 (range of cross-validation, 0.825-0.937) among all ML models. The optimal logistic regression model was inferior to the optimal ML model for predicting SLNM, with an AUC of 0.727. CONCLUSIONS: The CT radiomics showed the potential for accurately predicting SLNM in NSCLC patients. The ML model with dual-region radiomic features has better performance than the logistic regression or single-region models.