Non-metastatic Nodes Research Articles

Diagnostic Value of Multimodal Magnetic Resonance Imaging in Discriminating Between Metastatic and Non-Metastatic Pelvic Lymph Nodes in Cervical Cancer.

BackgroundThe status of pelvic lymph node (PLN) metastasis affects treatment and prognosis plans in patients with cervical cancer. However, it is hard to be diagnosed in clinical practice.PurposeThe present study aimed to evaluate the diagnostic value of multimodal magnetic resonance imaging (MRI) in discriminating between metastatic and non-metastatic pelvic lymph nodes (PLNs) in cervical cancer.MethodsThis retrospective study analyzed MRIs of 209 PLNs in 25 women with pathologically proven cervical cancer. All PLNs had been assessed by pre-treatment multimodal MRIs, and their status was finally confirmed by histopathology. In conventional MRI, lymph node characteristics were compared between metastatic and non-metastatic PLNs. Signal intensity, time–intensity curve (TIC) patterns minimal and mean apparent diffusion coefficients (ADC) were compared between them in DWI. In DCE-MRI, quantitative (Ktrans, Kep and Ve) analyses were performed on DCE-MRI sequences, and their predictive values were analyzed by ROC curves.ResultsOf 209 PLNs, 22 (10.53%) were metastases and 187 (89.47%) were non-metastases at histopathologic examination. Considering a comparison of lymph node characteristics, the short axis size, the long axis size, and the boundary differed significantly between the two groups (P<0.05).The differences in ADCmin, TIC types, Ktrans and Ve between metastatic and non-metastatic PLNs were significant as well (P<0.05). The good diagnostic performance of multimodal MRI was shown in discriminating between metastatic and non-metastatic PLNs, with the sensitivity of 85.0% (17/20), specificity of 97.3% (184/189), and accuracy of 96.2% (201/209). ROC analyses showed that the diagnostic accuracy of ADCmin, Ktrans and Ve for discriminating between metastatic and non-metastatic PLNs in cervical cancer was 83.7%, 91.4%, and 92.4% with the cut-off values of 0.72 × 10−3mm2/s, 0.52 min−1, and 0.53 min−1, respectively.ConclusionMultimodal MRI showed good diagnostic performance in determining PLN status in cervical cancer.

Computed DWI MRI Results in Superior Capability for N-Stage Assessment of Non-Small Cell Lung Cancer Than That of Actual DWI, STIR Imaging, and FDG-PET/CT.

Computed diffusion-weighted imaging (cDWI) is a mathematical computation technique that generates DWIs for any b-value by using actual DWI (aDWI) data with at least two different b-values and may improve differentiation of metastatic from nonmetastatic lymph nodes. To determine the appropriate b-value for cDWI to achieve a better diagnostic capability for lymph node staging (N-staging) in non-small cell lung cancer (NSCLC) patients compared to aDWI, short inversion time (TI) inversion recovery (STIR) imaging, or positron emission tomography with 2-[fluorine-18] fluoro-2-deoxy-d-glucose combined with computed tomography (FDG-PET/CT). Prospective. A total of 245 (127 males and 118 females; mean age 72 years) consecutive histopathologically confirmed NSCLC patients. A 3 T, half-Fourier single-shot turbo spin-echo sequence, electrocardiogram (ECG)-triggered STIR fast advanced spin-echo (FASE) sequence with black blood and STIR acquisition and DWI obtained by FASE with b-values of 0 and 1000 sec/mm2 . From aDWIs with b-values of 0 and 1000 (aDWI1000 ) sec/mm2 , cDWI using 400 (cDWI400 ), 600 (cDWI600 ), 800 (cDWI800 ), and 2000 (cDWI2000 ) sec/mm2 were generated. Then, 114 metastatic and 114 nonmetastatic nodes (mediastinal and hilar lymph nodes) were selected and evaluated with a contrast ratio (CR) for each cDWI and aDWI, apparent diffusion coefficient (ADC), lymph node-to-muscle ratio (LMR) on STIR, and maximum standard uptake value (SUVmax ). Receiver operating characteristic curve (ROC) analysis, Youden index, and McNemar's test. Area under the curve (AUC) of CR600 was significantlylargerthan the CR400 , CR800 , CR2000 , aCR1000 , and SUVmax . Comparison of N-staging accuracy showed that CR600 was significantly higher than CR400 , CR2000 , ADC, aCR1000 , and SUVmax , although there were no significant differences with CR800 (P=0.99) and LMR (P=0.99). cDWI with b-value at 600 sec/mm2 may have potential to improve N-staging accuracy as compared with aDWI, STIR, and PET/CT. 2 TECHNICAL EFFICACY: Stage 2.

Morphological characteristics of lateral pelvic lymph nodes in locally advanced lower rectal cancer: A retrospective study.

This study aimed to investigate the potential of the size and aspect ratio of metastatic and non-metastatic lateral pelvic lymph nodes (LPLNs) as low-risk markers for locally advanced lower rectal cancer, without treatment by neoadjuvant chemoradiation therapy or LPLN dissection. This single-center, retrospective cohort study evaluated 310 consecutive patients diagnosed with lower rectal cancer (T: T3/T4, N: any, and M: M0) who underwent curative surgery without neoadjuvant therapies between 2010 and 2018. The harvested LPLNs were categorized into groups A (metastasis-positive lymph nodes), B (metastasis-negative lymph nodes in the area bearing metastasis-positive lymph nodes), C (metastasis-negative lymph nodes in a metastasis-negative area in metastasis-positive patients), and D (lymph nodes in non-metastatic patients). The main outcome measure was the relationship among lymph node size, aspect ratio, and metastasis in the LPLNs. Overall, 3962 LPLNs were harvested. The long and short axes and the aspect ratio were significantly longer and higher, respectively, in group A than in the other groups (P < .001). The aspect ratio in group B was significantly higher than that in groups C and D (P < .001). The aspect ratio in group C was significantly higher than that in group D (P < .001). Furthermore, no metastasis-positive lymph nodes had an aspect ratio of less than 0.4. Metastasis-positive LPLNs tended to be larger and rounder than their metastasis-negative counterparts. Metastatic LPLNs in patients with lower rectal cancer are significantly larger and have a higher aspect ratio. Lymph nodes with aspect ratios of <0.4 were metastasis negative.

Primary Malignant Melanoma of the Cervix: An Integrated Analysis of Case Reports and Series.

Melanoma, also known as malignant melanoma, is a type of malignant tumour that originates from melanocytes in the basal layer of the epidermis. Primary malignant melanomas of the female genital tract are rare. Similarly, primary malignant melanoma of cervix, which originates from cervical melanocytes, is an extremely rare disease and the second most common type of female melanoma in women aged between 15 to 44 years worldwide. To date, primary malignant melanoma of the cervix is characterized by poor patient prognosis and little consensus exists regarding the best treatment therapy. The situation is worsened by lack of clinical studies with large samples. Notably, surgery remains the preferred treatment option for patients with primary malignant melanomas of the cervix. Current treatments are based on Federation International of Gynecology and Obstetrics(2018) staging with reference to National Comprehensive Cancer Network guidelines. This study is in order to find a more suitable treatment modality for primary malignant melanoma of cervix. Therefore, we first conducted an integrated analysis of case reports and series to assess the impact of various factors on the prognosis of such patients. In summary, this is the first pooled analysis including 149 cases of primary cervical melanoma. We found that patients who underwent radical hysterectomy-based surgery, those with non-metastatic lymph nodes and those who underwent lymphadenectomy had significantly higher survival rates. In patients who had RH-based surgery, survival rates at the 24m time point of those who did not add other treatments was higher than those who did, but for those who had total hysterectomy-based surgery, the addition of other treatments to prolong median survival may be considered. In the overall analysis, age and lymphadenectomy were associated with increased and reduced risk of death in these patients, respectively. Although there is no statistical difference, stage III&IV, TAH, lymphatic metastases increase the risk of death; whereas radical hysterectomy was associated with reduced risk of death. In the subgroup analysis, for patients who have undergone radical hysterectomy-based surgery, lymphadenectomy reduces the risk of death, while lymphatic metastases and complementary other treatments increase the risk of death. For patients who have undergone total hysterectomy-based surgery, complementary treatment reduces the risk of death. In conclusion, via summarizing previous reports, the recommended treatment procedure for PMMC are radical hysterectomy and lymphadenectomy. The addition of other treatment options for patients who undergoing RH-based surgery need further study.

Value of dual-layer spectral detector CT in preoperative prediction of lymph node metastasis of gastric cancer

Objective: To investigate the value of dual-layer spectral detector CT(SDCT) in preoperative prediction of lymph node (LN) metastasis of gastric cancer. Methods: From January 2019 to January 2021, the clinical and imaging data of 130 gastric cancer patients(93 males and 37 females, aged from 37 to 84 years)confirmed by pathology in the Zhongshan hospital of Xiamen University were retrospectively collected. According to the status of lymph node metastasis, those patients were divided into metastatic LNs group (n=104) and nonmetastatic LNs group (n=26). The maximum diameter of gastric cancer on spectral CT images, CT Values of lesions in 40, 50, 60, 70. KeV monoenergetic image of arterial and Venous phase (CT40 keV, CT50 keV, CT60 keV, CT70 keV), iodine concentration (IC) and effective atomic number (Zeff) were measured, then the normalized IC(NIC) and spectral curve(K(40-70)) value were calculated. The differences of each parameter derived from spectral CT between the two groups were compared, and a logistic regression model was constructed. The ROC curves and area under the curve (AUC) were conducted to evaluate the diagnostic performance of each parameter and Delong test was used to compare the difference of each AUC. Results: Compared to nonmetastatic LNs group, metastatic LNs group had higher maximum diameter of tumor, CT40 keV, CT50 keV, CT60 keV, CT70 keV, IC, NIC, Zeff, and K(40-70) values on venous phase (the representative parameter is Zeff: 8.4 (8.2, 8.5) vs 8.2 (8.1, 8.3)) (all P<0.05). The proportion of patients with lower histology differentiated degree, higher T grade and positive carcino embryonic antigen (CEA)were higher than that in nonmetastatic LNs (the representative parameter was CEA: 34.6%(36/104) vs 7.7%(2/26) (all P<0.05). The regression model constructed by CEA and Zeff had the highest predictive value in predicting metastatic LNs, with an AUC of 0.835(0.759-0.894), sensitivity and specificity of 83.65% and 73.08%, respectively. Conclusion: SDCT quantitative parameters on venous phase and CEA facilitate the accurate prediction of metastatic LNs in patients with gastric cancer, and the multi-parameter regression model has the highest diagnostic performance.

Extracellular Volume Fraction Derived From Dual-Layer Spectral Detector Computed Tomography for Diagnosing Cervical Lymph Nodes Metastasis in Patients With Papillary Thyroid Cancer: A Preliminary Study.

ObjectivesThe current study evaluates the performance of dual-energy computed tomography (DECT) derived extracellular volume (ECV) fraction based on dual-layer spectral detector CT for diagnosing cervical lymph nodes (LNs) metastasis from papillary thyroid cancer (PTC) and compares it with the value of ECV derived from conventional single-energy CT (SECT).MethodsOne hundred and fifty-seven cervical LNs (81 non-metastatic and 76 metastatic) were recruited. Among them, 59 cervical LNs (27 non-metastatic and 32 metastatic) were affected by cervical root artifact on the contrast-enhanced CT images in the arterial phase. Both the SECT-derived ECV fraction (ECVS) and the DECT-derived ECV fraction (ECVD) were calculated. A Pearson correlation coefficient and a Bland–Altman analysis were performed to evaluate the correlations between ECVD and ECVS. Receiver operator characteristic curves analysis and the Delong method were performed to assess and compare the diagnostic performance.ResultsECVD correlated significantly with ECVS (r = 0.925; p <0.001) with a small bias (−0.6). Metastatic LNs showed significantly higher ECVD (42.41% vs 22.53%, p <0.001) and ECVS (39.18% vs 25.45%, p <0.001) than non-metastatic LNs. By setting an ECVD of 36.45% as the cut-off value, optimal diagnostic performance could be achieved (AUC = 0.813), which was comparable with that of ECVS (cut-off value = 34.99%; AUC = 0.793) (p = 0.265). For LNs affected by cervical root artifact, ECVD also showed favorable efficiency (AUC = 0.756), which was also comparable with that of ECVS (AUC = 0.716) (p = 0.244).ConclusionsECVD showed a significant correlation with ECVS. Compared with ECVS, ECVD showed comparable performance in diagnosing metastatic cervical LNs in PTC patients, even though the LNs were affected by cervical root artifacts on arterial phase CT.

Near-Infrared Fluorescence Axillary Reverse Mapping (ARM) Procedure in Invasive Breast Cancer: Relationship between Fluorescence Signal in ARM Lymph Nodes and Clinical Outcomes

Simple SummaryNear-infrared fluorescence axillary reverse mapping (ARM) is a promising procedure for identification and preservation of arm lymphatic drainage during axillary lymph node dissection (ALND). We included 109 patients to analyze the indocyanine green fluorescence signal in ARM lymph nodes after resection. The fluorescence signal from ARM lymph nodes were compared with clinical findings to determine the importance of this criterion on the potential management of patients with ALND. ARM lymph nodes were identified in 94.5% of cases. The mean normalized fluorescence signal intensity value was 0.47 with no significant signal difference between metastatic and non-metastatic ARM lymph nodes. Only the preoperative diagnosis of metastasis in the axillary nodes of patients was significantly associated with a higher ARM node fluorescence signal intensity. Although preliminary results did not show that fluorescence signal intensity is a reliable diagnostic tool, the NIR fluorescence ARM procedure may be useful for ARM lymph node identification.The near-infrared (NIR) fluorescence axillary reverse mapping (ARM) procedure is a promising tool to identify and preserve arm lymphatic drainage during axillary lymph node dissection (ALND). The ARMONIC clinical trial was conducted to validate the technique on a large cohort of patients and to analyze the predictive clinical factors for ARM lymph node metastasis. For the first time, the fluorescence signal intensity from the ARM lymph nodes was measured and correlated with clinical findings. A total of 109 patients with invasive breast cancer and indications of mastectomy and ALND underwent the NIR fluorescence ARM procedure. Indocyanine green was administered by intradermal injection followed by intraoperative identification and resection of the ARM lymph nodes with NIR fluorescence camera guidance. The fluorescence signal intensity and signal distribution were then measured ex vivo and compared with clinical outcomes. ARM lymph nodes were successfully identified by fluorescence in 94.5% of cases. The mean normalized fluorescence signal intensity value was 0.47 with no significant signal difference between metastatic and non-metastatic ARM lymph nodes (p = 0.3728). At the microscopic level, the fluorescence signal distribution was focally intense in lymphoid tissue areas. Only the preoperative diagnosis of metastasis in the axillary nodes of patients was significantly associated with a higher ARM node fluorescence signal intensity (p = 0.0253), though it was not significantly associated with the pathological nodal (pN) status (p = 0.8081). Based on an optimal cut-off fluorescence value, the final sensitivity and specificity of the NIR fluorescence ARM procedure for ARM lymph node metastatic involvement were 64.7% and 47.3%, respectively. Although our preliminary results did not show that fluorescence signal intensity is a reliable diagnostic tool, the NIR fluorescence ARM procedure may be useful for ARM lymph node identification. Clinical trial registration: NCT02994225.

Lymphocytes in tumor-draining lymph nodes co-cultured with autologous tumor cells for adoptive cell therapy

BackgroundTumor-draining lymph nodes (TDLNs) are primary sites, where anti-tumor lymphocytes are primed to tumor-specific antigens and play pivotal roles in immune responses against tumors. Although adoptive cell therapy (ACT) using lymphocytes isolated from TDLNs were reported, characterization of immune activity of lymphocytes in TDLNs to tumor cells was not comprehensively performed. Here, we demonstrate TDLNs to have very high potential as cell sources for immunotherapy.MethodsLymphocytes from TDLNs resected during surgical operation were cultured with autologous-tumor cells for 2 weeks and evaluated tumor-reactivity by IFNγ ELISPOT assay. We investigated the commonality of T cell receptor (TCR) clonotypes expanded by the co-culture with tumor cells with those of tumor infiltrating lymphocytes (TILs).ResultsWe found that that TCR clonotypes of PD-1-expressing CD8+ T cells in lymph nodes commonly shared with those of TILs in primary tumors and lymphocytes having tumor-reactivity and TCR clonotypes shared with TILs could be induced from non-metastatic lymph nodes when they were co-cultured with autologous tumor cells.ConclusionOur results imply that tumor-reactive effector T cells were present even in pathologically non-metastatic lymph nodes and could be expanded in vitro in the presence of autologous tumor cells and possibly be applied for ACT.

ITRAQ proteomics of sentinel lymph nodes for identification of extracellular matrix proteins to flag metastasis in early breast cancer

Patients with early breast cancer are affected by metastasis to axillary lymph nodes. Metastasis to these nodes is crucial for staging and quality of surgery. Sentinel Lymph Node Biopsy that is currently used to assess lymph node metastasis is not effective. This necessitates identification of biomarkers that can flag metastasis. Early stage breast cancer patients were recruited. Surgical resection of breast was followed by identification of sentinel lymph nodes. Fresh frozen section biopsy was used to assign metastatic and non-metastatic sentinel lymph nodes. Discovery phase included iTRAQ proteomics coupled with mass spectrometric analysis to identify differentially expressed proteins. Data is available via ProteomeXchange with identifier PXD027668. Validation was done by bioinformatic analysis and ELISA. There were 2398 unique protein groups and 109 differentially expressed proteins comparing metastatic and non-metastatic lymph nodes. Forty nine proteins were up-regulated, and sixty proteins that were down regulated in metastatic group. Bioinformatic analysis showed ECM-receptor interaction pathways to be implicated in lymph node metastasis. ELISA confirmed up-regulation of ECM proteins in metastatic lymph nodes. ECM proteins have requisite parameters to be developed as a diagnostic tool to assess status of sentinel lymph nodes to guide surgical intervention in early breast cancer.

Periostin in lymph node pre-metastatic niches governs lymphatic endothelial cell functions and metastatic colonization

Although lymph node (LN) metastasis is an important prognostic parameter in cervical cancer, the tissue remodeling at a pre-metastatic state is poorly documented in LNs. We here identified periostin (POSTN) as a component of non-metastatic LNs by applying proteomic analyses and computerized image quantifications on LNs of patients with cervical cancer. We provide evidence for remarkable modifications of POSTN and lymphatic vessel distributions and densities in non-metastatic sentinel and metastatic human LNs, when compared to distant non-metastatic LNs. POSTN deposition at a pre-metastatic stage was demonstrated in a pre-clinical murine model (the ear sponge assay). Its expression by fibroblastic LN cells was assessed by in situ hybridization and in vitro cultures. In vitro, POSTN promoted lymphatic endothelial cell functions and tumor cell proliferation. Accordingly, the in vivo injection of recombinant POSTN together with VEGF-C boosted the lymphangiogenic response, while the metastatic potential of tumor cells was drastically reduced using a POSTN blocking antibody. This translational study also supports the existence of an unprecedented dialog “in cascade”, between the primary tumor and the first pelvic nodal relay in early cervical cancer, and subsequently from pelvic LN to para-aortic LNs in locally advanced cervical cancers. Collectively, this work highlights the association of POSTN deposition with lymphangiogenesis in LNs, and provides evidence for a key contribution of POSTN in promoting VEGF-C driven lymphangiogenesis and the seeding of metastatic cells.

Higher accuracy of [68Ga]Ga-DOTA-FAPI-04 PET/CT comparing with 2-[18F]FDG PET/CT in clinical staging of NSCLC.

This study aimed to explore the clinical staging performance of [68Ga]Ga-DOTA-FAPI-04 PET/CT compared with that of 2-[18F]FDG PET/CT in non-small cell lung cancer (NSCLC) patients lesion by lesion. A total of 134 diagnosed or suspected NSCLC patients were enrolled in the prospective study (ChiCTR2000038080); they received paired 2-[18F]FDG PET/CT and [68Ga]Ga-DOTA-FAPI-04 PET/CT. Of these patients, the retrospective analysis of 74 NSCLC patients with pathological results was conducted from primary tumor (T) diagnosis, lymph node (N), and metastatic lesion (M) staging. The imaging characteristics of the lung nodules and suspected metastases were obtained and analyzed, and the staging performance of 2-[18F]FDG PET/CT and [68Ga]Ga-DOTA-FAPI-04 PET/CT was compared. For T diagnosis, [68Ga]Ga-DOTA-FAPI-04 showed better diagnostic performance than 2-[18F]FDG in 79 lung nodules of 72 patients, especially for nonsolid and small-dimension adenocarcinoma nodules. For N staging, 98 lymph nodes (LNs) with pathological results in 37 patients were analyzed. The SUVmax of [68Ga]Ga-DOTA-FAPI-04 in the nonmetastatic LNs was significantly lower than that in the metastatic LNs. Regarding metastatic LN identification, the calculated optimum cut-off value of [68Ga]Ga-DOTA-FAPI-04 SUVmax was 5.5, and the diagnostic accuracy using [68Ga]Ga-DOTA-FAPI-04 and 2-[18F]FDG criteria was 94% and 30%, respectively (P < 0.001). For M staging, [68Ga]Ga-DOTA-FAPI-04 identified more lesions than 2-[18F]FDG (257 vs. 139 lesions) in 14 patients with multiple metastases. Overall, the staging accuracy of [68Ga]Ga-DOTA-FAPI-04 was better than that of 2-[18F]FDG in 52 patients with different pathological stages [43/52 (82.7%) vs. 27/52 (51.9%), P = 0.001]. Compared with 2-[18F]FDG PET/CT, [68Ga]Ga-DOTA-FAPI-04 PET/CT demonstrated better staging performance in NSCLC patients with different pathological stages, especially those with localized disease.

Effector Memory T Cells and CD45RO+ Regulatory T Cells in Metastatic vs. Non-Metastatic Lymph Nodes in Lung Cancer Patients.

Lymphocytes play a leading role in regulation of the immune system in lung cancer patients. The recognition of T cells profile may help in prediction of effectiveness of anticancer immunotherapy. The aim of the study was to determine the dominant subpopulation of CD4+ and CD8+ lymphocytes in metastatic and non-metastatic lymph nodes (LNs) of lung cancer patients. LNs aspirates were obtained during EBUS/TBNA procedure and cells were analyzed by flow cytometry. We showed a higher percentage of CD4+ and CD8+ effector memory T cells in the metastatic than in the non-metastatic LNs (28.6 vs. 15.3% and 28.6 vs. 14.0%, p< 0.05). The proportion of CD45RO+ T regulatory cells (CD45RO+ Tregs) was higher in the metastatic LNs than in the non-metastatic ones (65.6 vs. 31%, p< 0.05). We reported the significant differences in T cell subsets depending on the lung cancer metastatic process. We observed that the effector memory T cells were predominant subpopulations in metastatic LNs. Lymphocyte profile in LNs is easy to evaluate by flow cytometry of EBUS/TBNA samples and may reflect the immune status in lung cancer.

ITRAQ proteomics of sentinel lymph nodes for the identification of extra cellular matrix protein signatures that can flag metastasis in early breast cancer

BackgroundBreast cancer patients who present in the early stage of disease are affected by metastasis to the axillary group of lymph nodes. The first among this group that is affected is called as sentinel lymph node, and metastasis to this lymph node is crucial for the staging of cancer and the quality of surgical intervention. Sentinel Lymph Node Biopsy (SLNB) that is currently used to assess lymph node metastasis is neither sensitive, nor specific, is time‐consuming, thereby necessitating the identification of novel biomarkers that can flag sentinel lymph node metastasis.MethodsThis study was conducted after approval was obtained from the Institute Ethics Committee (Ref. No. IECPG‐ 27/23.01.2019, RT‐03/28.02.2019). Breast cancer patients were screened, and those with early stage were recruited in the study. Surgical resection of the breast was followed by identification of sentinel lymph nodes by methylene fluorescent technique. Histo‐pathology of fresh frozen section biopsy was used as the gold standard to assign the clinical phenotypes of metastatic (SLNM+) and non‐metastatic sentinel lymph nodes (SLNM‐). Discovery phase of the experiment included isobaric Tags for Relative and Absolute Quantitation (iTRAQ) technique comprising of six comparative experiments coupled with mass spectrometric analysis to identify differentially expressed proteins. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD027668. Validation was done by ELISA and protein concentrations were used to estimate the ROC for computing diagnostic parameters. Pathway analysis and gene ontology analysis was done to understand the relevance of the differentially expressed proteins in this study.ResultsBased on MS/MS spectra there were 7510 differentially expressed proteins comparing SLNB + and SLNB ‐. Nineteen proteins up‐regulated, and eight proteins that were down regulated in SLNB+ as compared to SLNB‐. ELISA confirmed the up‐regulation of caveolin 1, collagen α‐1, desmin, fibrillin‐1, and microfibrillar associated glycoprotein 4 in metastatic, as compared to non‐metastatic lymph nodes. These proteins are known to be integral in tumorogenesis, cell proliferation, invasion, cell survival and anti‐apoptosis. These proteins have 80%‐100%, of sensitivity and specificity to differentiate the two clinical phenotypes.ConclusionIdentified protein biomarkers have requisite diagnostic parameters to be developed as a translational tool to assess the status of sentinel lymph nodes during mastectomy procedure to guide surgical therapy of axillary lymph nodes in early breast oncology.

Similar distribution of pelvic sentinel lymph nodes and nodal metastases in cervical and endometrial cancer. A prospective study based on lymphatic anatomy

ObjectiveComparing the anatomical distribution of metastatic and non-metastatic pelvic sentinel lymph nodes (SLN) in cervical and endometrial cancer. MethodsDetailed SLN mapping results were prospectively retrieved in cervical (n = 145) or high-risk endometrial cancer (n = 201) patients undergoing a robotic staging procedure. Cervically injected Indocyanine Green (ICG), allowing for reinjection in case of inadequate mapping, was used as tracer. An anatomically based definition of SLNs was adhered to evaluating the upper (UPP) and lower (LPP) paracervical lymphatic pathways. The positions of SLNs were intraoperatively depicted on an anatomical chart. A completory pelvic lymphadenectomy was performed. Mapping rates and anatomical distribution of SLNs and the location of pelvic nodal metastases were compared between groups. ResultsThe bilateral mapping rate was 97.9% and 95.0% for cervical and endometrial cancer respectively (p = .16). The proportion of typically positioned (interiliac and proximal obturator fossa) SLNs along the UPP was similar between groups (78.1% vs 82.1%, p = .09), and the rate of metastatic SLNs in the obturator fossa was 54.1% and 48.6% respectively (p = .45). All pelvic node positive women (cervical cancer n = 19, endometrial cancer n = 37) had at least one metastatic SLN. Anatomically typical positions could not be defined along the LPP. ConclusionThe anatomical location of SLNs and SLN metastases are similar in cervical and endometrial cancer suggesting that sensitivity results for an SLN concept in endometrial cancer and cervical cancer can be accumulated.

129P Regulatory dendritic cells correlate with an altered T cell distribution and regulatory T cell phenotype in metastatic lymph nodes of NSCLC patients

Dendritic cells (DCs) are considered to be the most important professional population of antigen-presenting cells and play a crucial role in the activation of the immune system. However, the proper function of DCs is altered by the tumor microenvironment (TME). Despite the progress in anticancer immunotherapy, there are still many unresolved issues. Among them, the immunomodulatory properties of DCs in lung cancer are of interest. The aim of the study was to analyze the PD-1+ PD-L1+ CD80- DCs subset, described as regulatory dendritic cells (DCregs), and to investigate correlations between the presence of DCregs and changes in T cell frequencies and immunomodulatory molecules in metastatic and non-metastatic lymph nodes (LNs) aspirates of NSCLC patients. LNs aspirates were obtained during the diagnostic EBUS TBNA procedure of 30 NSCLC patients. DCregs and T cell characteristics were determined by multiparameter flow cytometry. We noticed a higher percentage of DCregs in the metastatic than in the non-metastatic LNs (22.5% vs. 3.1%). DCs cells show increased expression of PD-1 and PD-L1. Additionally, metastatic LNs contained a lower percentage of CD4 T cells, whereas the percentage of CD8 T cells and Tregs was increased as compared to non-metastatic LNs. Surprisingly, the percentage of DCregs positively correlated with the percentage of PD-1+ T cells, Tregs and CD45RO+ Tregs. Our results confirm the utility of flow cytometric analysis of EBUS/TBNA samples to assess the interaction between immune cells in TME. DCregs strongly associates with an altered T cell distribution and immunosuppressive phenotype in metastatic LNs of NSCLC patients. It can be assumed that DCregs are involved in the suppression of anti-tumor response, which could be of importance for the response upon immunotherapy.

In-House Validated Map of Lymph Node Stations in a Prospective Cohort of Colorectal Cancer: A Tool for a Better Preoperative Staging.

Preoperative staging of colorectal cancer (CRC) based on imaging techniques such as computed tomography (CT) or magnetic resonance imaging (MRI) is crucial for identification and then removal of the positive lymph nodes (LNs). The aim of this study was to evaluate the correlation between preoperatively seen morphologic criteria (number, size, shape, structure, borders, or enhancement patterns) and histopathological features of LNs using an in-house validated map of nodal stations. A total of 112 patients with CRC that underwent surgery were preoperatively evaluated by CT scans. The locoregional, intermediate, and central LNs were CT-mapped and then removed during open laparotomy and examined under microscope. The analysis of correlations was interpreted using the suspicious-to-positive ratio (SPR) parameter. The greatest correlation was found in tumors located in the sigmoid colon, descending colon and middle rectum; SPR value was 1.12, 1.18, and 1.26, respectively. SPR proved to be 0.59 for cases of the transverse colon. Regarding the enhancement type, the dotted pattern was mostly correlated with metastatic LNs (OR: 7.84; p < 0.0001), while the homogenous pattern proved a reliable indicator of nonmetastatic LNs (OR: 1.99; p < 0.05). A total of 1809 LNs were harvested, with a median value of 15 ± 1.34 LNs/case. Transdisciplinary approach of CRC focused on pre-, intra-, and postoperatively mapping of LNs might increase the accuracy of detecting metastasized nodes for tumors of the distal colon and middle rectum but not for those of the transverse colon. In addition to morphologic criteria, the enhancement pattern of LNs can be used as a predictor of nodal involvement improving the CT-based preoperative staging.

Radiomics Metrics Combined with Clinical Data in the Surgical Management of Early-Stage (cT1-T2 N0) Tongue Squamous Cell Carcinomas: A Preliminary Study.

Simple SummaryThe purpose of this study is to predict the risk of metastatic lymph nodes related to oral tongue squamous cell carcinoma (OTSCC) and tumor grading through the combination of clinical data with radiomics metrics extracted from computed tomography (CT) images. We aimed to develop a supportive approach in the management of lymphatic cervical areas, with particular attention given to the early stages (T1−T2). Specifically, we evaluated the effectiveness of the radiomics and clinical features in the study of OTSCC and in the prediction of occult laterocervical metastatic lymph nodes. We concluded that radiomics features and clinical parameters have an important role in identifying tumor grading and metastatic lymph nodes. Machine learning approaches can be used as an easy-to-use tool to stratify patients with early-stage OTSCC, based on the identification of metastatic and non-metastatic lymph nodesObjective: To predict the risk of metastatic lymph nodes and the tumor grading related to oral tongue squamous cell carcinoma (OTSCC) through the combination of clinical data with radiomics metrics by computed tomography, and to develop a supportive approach in the management of the lymphatic cervical areas, with particular attention to the early stages (T1−T2). Between March 2016 and February 2020, patients with histologically confirmed OTSCC, treated by partial glossectomy and ipsilateral laterocervical lymphadenectomy and subjected to computed tomography (CT) before surgery, were identified by two centers: 81 patients (49 female and 32 male) with 58 years as the median age (range 19–86 years). Univariate analysis with non-parametric tests and multivariate analysis with machine learning approaches were used. Clinical, hematological parameters and radiological features extracted by CT were considered individually and in combination. All clinical parameters showed statistically significant differences (p < 0.05) for the Kruskal−Wallis test when discriminating both the tumor grading and the metastatic lymph nodes. DOI, PLR, SII, and SIRI showed an accuracy of 0.70 (ROC analysis) when identifying the tumor grading, while an accuracy ≥ 0.78 was shown by DOI, NLR, PLR, SII, and SIRI when discriminating metastatic lymph nodes. In the context of the analysis of radiomics metrics, the original_glszm_HighGrayLevelZoneEmphasis feature was selected for identifying the tumor grading (accuracy of 0.70), while the wavelet_HHH_glrlm_LowGrayLevelRunEmphasis predictor was selected for determining metastatic lymph nodes (accuracy of 0.96). Remarkable findings were also obtained when classifying patients with a machine learning approach. Radiomics features alone can predict tumor grading with an accuracy of 0.76 using a logistic regression model, while an accuracy of 0.82 can be obtained by running a CART algorithm through a combination of three clinical parameters (SIRI, DOI, and PLR) with a radiomics feature (wavelet_LLL_glszm_SizeZoneNonUniformityNormalized). In the context of predicting metastatic lymph nodes, an accuracy of 0.94 was obtained using 15 radiomics features in a logistic regression model, while both CART and CIDT achieved an asymptotic accuracy value of 1.00 using only one radiomics feature. Radiomics features and clinical parameters have an important role in identifying tumor grading and metastatic lymph nodes. Machine learning approaches can be used as an easy-to-use tool to stratify patients with early-stage OTSCC, based on the identification of metastatic and non-metastatic lymph nodes.

Immunosuppressive properties of human PD-1 + , PDL-1 + and CD80 + dendritic cells from lymph nodes aspirates of lung cancer patients.

Dendritic cells (DCs) play a pivotal role in the homeostasis of the immune system. The tumor microenvironment impairs the proper function of DCs. The immunomodulatory properties of DCs in lung cancer are of interest. In the present study, we analysed DCs subsets and immune cells with the expression of immunomodulatory molecules: PD-1 and PD-L1 and co-stimulatory molecule CD80 in metastatic, non-metastatic lymph nodes (LNs) and peripheral blood (PB). LNs aspirates were obtained during the EBUS/TBNA procedure of 29 patients with primary lung cancer. The cells were analyzed by flow cytometry. We reported a higher percentage of DCs in the metastatic than in the non-metastatic LNs and the PB (0.709% vs. 0.166% vs. 0.043%, p < 0.0001). The proportions of PD-1 + , PD-L1 + and CD80 + DCs were higher in the metastatic LNs than in the non-metastatic ones. A higher proportion of regulatory DCs (DCregs) was found in the metastatic ones than in the non-metastatic LNs (22.5% vs. 3.1%, p = 0.0189). We report that DCs cells show increased expression of PD-1, PD-L1 and CD80 molecules that can interact with T lymphocytes. It can be assumed that mature DCs infiltrating metastatic LNs can develop into DCregs, which are involved in the suppression of anti-tumor response.

Segmentation of metastatic cervical lymph nodes from CT images of oral cancers using deep-learning technology.

The purpose of this study was to establish a deep-learning model for segmenting the cervical lymph nodes of oral cancer patients and diagnosing metastatic or non-metastatic lymph nodes from contrast-enhanced computed tomography (CT) images. CT images of 158 metastatic and 514 non-metastatic lymph nodes were prepared. CT images were assigned to training, validation, and test datasets. The colored images with lymph nodes were prepared together with the original images for the training and validation datasets. Learning was performed for 200 epochs using the neural network U-net. Performance in segmenting lymph nodes and diagnosing metastasis were obtained. Performance in segmenting metastatic lymph nodes showed recall of 0.742, precision of 0.942, and F1 score of 0.831. The recall of metastatic lymph nodes at level II was 0.875, which was the highest value. The diagnostic performance of identifying metastasis showed an area under the curve (AUC) of 0.950, which was significantly higher than that of radiologists (0.896). A deep-learning model was created to automatically segment the cervical lymph nodes of oral squamous cell carcinomas. Segmentation performances should still be improved, but the segmented lymph nodes were more accurately diagnosed for metastases compared with evaluation by humans.

Shear wave elastography of lymph nodes in dogs with head and neck cancer: A pilot study.

Shear wave elastography (SWE) is a novel ultrasound imaging technique, used in human medicine to differentiate metastatic from non-metastatic lymph nodes (LNs) based on higher tissue stiffness. The objective of this pilot study was to evaluate whether canine metastatic LNs were stiffer compared to non-metastatic LNs. SWE of sentinel or regional LNs in dogs with head and neck cancer was performed. Ten elastograms of each LN were acquired. In each elastogram, mean, median, and maximum shear wave velocities (SWVs) were calculated in the most elastic region, the stiffest region, and the entire LN. The means of those SWVs for each region of each LN were subsequently calculated. Furthermore, a stepwise subsampling was performed to assess the effect of the number of acquired elastograms on the consistency of the classification of a LN as metastatic or not. Twenty-four LNs in 15 dogs with head and neck cancer were included, of which 10 LNs were metastatic. Metastatic medial retropharyngeal and mandibular LNs were successfully distinguished from non-metastatic LNs based on higher mean and median SWVs in the stiffest region and higher maximum SWVs in entire LNs. Furthermore, maximum SWVs in the stiffest region of mandibular LNs were higher in metastatic LNs compared to non-metastatic LNs. Downstream analyses demonstrated that at least eight elastograms were necessary to perform reliable analyses. This pilot trial demonstrated that SWE has potential to discriminate metastatic from non-metastatic LNs; however, LN status should be based on at least eight elastograms in future clinical trials.